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Zhang Z, Li M, Zhang L, Zhou Y, Zhu S, Lv C, Zheng Y, Cai B, Wang J. Expanding carbon neutrality strategies: Incorporating out-of-boundary emissions in city-level frameworks. Environ Sci Ecotechnol 2024; 20:100354. [PMID: 38204761 PMCID: PMC10776445 DOI: 10.1016/j.ese.2023.100354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 11/16/2023] [Accepted: 11/23/2023] [Indexed: 01/12/2024]
Abstract
Cities are increasingly vital in global carbon mitigation efforts, yet few have specifically tailored carbon neutrality pathways. Furthermore, out-of-boundary indirect greenhouse gas (GHG) emissions, aside from those related to electricity and heat imports, are often overlooked in existing pathways, despite their significance in comprehensive carbon mitigation strategies. Addressing this gap, here we introduce an integrated analysis framework focusing on both production and consumption-related GHG emissions. Applied to Wuyishan, a service-oriented city in Southern China, this framework provides a holistic view of a city's carbon neutrality pathway, from a full-scope GHG emission perspective. The findings reveal the equal importance of carbon reduction within and outside the city's boundaries, with out-of-boundary emissions accounting for 42% of Wuyishan's present total GHG emissions. This insight highlights the necessity of including these external factors in GHG accounting and mitigation strategy development. This framework serves as a practical tool for cities, particularly in developing countries, to craft effective carbon neutrality roadmaps that encompass the full spectrum of GHG emissions.
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Affiliation(s)
- Zhe Zhang
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100043, China
| | - Mingyu Li
- School of Environment, Tsinghua University, Beijing, 100084, China
| | - Li Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Yunfeng Zhou
- R&D and International Cooperation Office, Chinese Academy of Environmental Planning, Beijing, 100043, China
| | - Shuying Zhu
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100043, China
- School of Economics and Management, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Chen Lv
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100043, China
| | - Yixuan Zheng
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing, 100043, China
| | - Bofeng Cai
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100043, China
| | - Jinnan Wang
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100043, China
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Zhang Z, Shan Y, Zhao D, Tillotson MR, Cai B, Li X, Zheng H, Zhao C, Guan D, Liu J, Hao Y. City level water withdrawal and scarcity accounts of China. Sci Data 2024; 11:449. [PMID: 38702307 PMCID: PMC11068761 DOI: 10.1038/s41597-024-03115-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 03/04/2024] [Indexed: 05/06/2024] Open
Abstract
In the context of China's freshwater crisis high-resolution data are critical for sustainable water management and economic growth. Yet there is a dearth of data on water withdrawal and scarcity regardless of whether total or subsector amount, for prefectural cities. In administrative and territorial scope, we accounted for water withdrawal of all 63 economic-socio-environmental sectors for all 343 prefectural cities in China, based on a general framework and 2015 data. Spatial and economic-sector resolution is improved compared with previous studies by partitioning general sectors into industrial and agricultural sub-sectors. Construction of these datasets was based on selection of 16 driving forces. We connected a size indicator with corresponding water-withdrawal efficiency. We further accounted for total blue-water withdrawal and quantitative water scarcity status. Then we compared different scopes and methods of official accounts and statistics from various water datasets. These disaggregated and complete data could be used in input-output models for municipal design and governmental planning to help gain in-depth insights into subsector water-saving priorities from local economic activities.
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Affiliation(s)
- Zongyong Zhang
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
- Water Security Research Centre, School of International Development, University of East Anglia, Norwich, NR4 7TJ, UK
| | - Yuli Shan
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Dandan Zhao
- Water & Development Research Group, Department of Built Environment, Aalto University, Espoo, 00076, Finland
| | - Martin R Tillotson
- School of Civil Engineering, University of Leeds, Woodhouse Lane, Leeds, LS2 9JT, UK
| | - Bofeng Cai
- Centre for Climate and Environmental Policy, Chinese Academy for Environmental Planning, Beijing, 100012, China
| | - Xian Li
- Water Security Research Centre, School of International Development, University of East Anglia, Norwich, NR4 7TJ, UK
- Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Heran Zheng
- The Bartlett School of Sustainable Construction, University College London, London, WC1H 0QB, UK
| | - Cunxue Zhao
- Business School, Hohai University, Nanjing, 211100, China
| | - Dabo Guan
- Department of Earth System Science, Tsinghua University, Beijing, 100084, China.
- The Bartlett School of Construction and Project Management, University College London, London, WC1E 7HB, UK.
| | - Junguo Liu
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China.
| | - Yu Hao
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China.
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China.
- Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing, 314001, China.
- Sustainable Development Research Institute for Economy and Society of Beijing, Beijing, 100081, China.
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Lei Y, Yin Z, Lu X, Zhang Q, Gong J, Cai B, Cai C, Chai Q, Chen H, Chen R, Chen S, Chen W, Cheng J, Chi X, Dai H, Feng X, Geng G, Hu J, Hu S, Huang C, Li T, Li W, Li X, Liu J, Liu X, Liu Z, Ma J, Qin Y, Tong D, Wang X, Wang X, Wu R, Xiao Q, Xie Y, Xu X, Xue T, Yu H, Zhang D, Zhang N, Zhang S, Zhang S, Zhang X, Zhang X, Zhang Z, Zheng B, Zheng Y, Zhou J, Zhu T, Wang J, He K. The 2022 report of synergetic roadmap on carbon neutrality and clean air for China: Accelerating transition in key sectors. Environ Sci Ecotechnol 2024; 19:100335. [PMID: 37965046 PMCID: PMC10641488 DOI: 10.1016/j.ese.2023.100335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 10/19/2023] [Accepted: 10/19/2023] [Indexed: 11/16/2023]
Abstract
China is now confronting the intertwined challenges of air pollution and climate change. Given the high synergies between air pollution abatement and climate change mitigation, the Chinese government is actively promoting synergetic control of these two issues. The Synergetic Roadmap project was launched in 2021 to track and analyze the progress of synergetic control in China by developing and monitoring key indicators. The Synergetic Roadmap 2022 report is the first annual update, featuring 20 indicators across five aspects: synergetic governance system and practices, progress in structural transition, air pollution and associated weather-climate interactions, sources, sinks, and mitigation pathway of atmospheric composition, and health impacts and benefits of coordinated control. Compared to the comprehensive review presented in the 2021 report, the Synergetic Roadmap 2022 report places particular emphasis on progress in 2021 with highlights on actions in key sectors and the relevant milestones. These milestones include the proportion of non-fossil power generation capacity surpassing coal-fired capacity for the first time, a decline in the production of crude steel and cement after years of growth, and the surging penetration of electric vehicles. Additionally, in 2022, China issued the first national policy that synergizes abatements of pollution and carbon emissions, marking a new era for China's pollution-carbon co-control. These changes highlight China's efforts to reshape its energy, economic, and transportation structures to meet the demand for synergetic control and sustainable development. Consequently, the country has witnessed a slowdown in carbon emission growth, improved air quality, and increased health benefits in recent years.
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Affiliation(s)
- Yu Lei
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing, 100041, China
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100041, China
| | - Zhicong Yin
- Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Xi Lu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
- Institute for Carbon Neutrality, Tsinghua University, Beijing, 100084, China
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Jicheng Gong
- State Key Joint Laboratory for Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering and Center for Environment and Health, Peking University, Beijing, 100871, China
| | - Bofeng Cai
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100041, China
| | - Cilan Cai
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Qimin Chai
- National Center for Climate Change, Strategy and International Cooperation, Beijing, 100035, China
| | - Huopo Chen
- Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and Key Lab of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai, 200032, China
| | - Shi Chen
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Wenhui Chen
- School of Economics and Management, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Jing Cheng
- Department of Earth System Science, University of California, Irvine, CA, 92697, USA
| | - Xiyuan Chi
- National Meteorological Center, China Meteorological Administration, Beijing, 100081, China
| | - Hancheng Dai
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Xiangzhao Feng
- Policy Research Center for Environment and Economy, Ministry of Ecology and Environment of the People's Republic of China, Beijing, 100029, China
| | - Guannan Geng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Jianlin Hu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Shan Hu
- Building Energy Research Center, School of Architecture, Tsinghua University, Beijing, 100084, China
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, 100084, China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Wei Li
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Xiaomei Li
- National Center for Climate Change, Strategy and International Cooperation, Beijing, 100035, China
| | - Jun Liu
- Department of Environmental Engineering, School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China
| | - Xin Liu
- Energy Foundation China, Beijing, 100004, China
| | - Zhu Liu
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Jinghui Ma
- Shanghai Typhoon Institute, Shanghai Meteorological Service, Shanghai, 200030, China
| | - Yue Qin
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Dan Tong
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Xuhui Wang
- College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Xuying Wang
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing, 100041, China
| | - Rui Wu
- Transport Planning and Research Institute (TPRI) of the Ministry of Transport, Beijing, 100028, China
| | - Qingyang Xiao
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Yang Xie
- School of Economics and Management, Beihang University, Beijing, 100191, China
| | - Xiaolong Xu
- China Association of Building Energy Efficiency, Beijing, 100029, China
| | - Tao Xue
- Institute of Reproductive and Child Health/Ministry of Health Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100080, China
| | - Haipeng Yu
- Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
| | - Da Zhang
- Institute of Energy, Environment, and Economy, Tsinghua University, Beijing, 100084, China
| | - Ning Zhang
- Department of Electrical Engineering, Tsinghua University, Beijing, 100084, China
| | - Shaohui Zhang
- School of Economics and Management, Beihang University, Beijing, 100191, China
| | - Shaojun Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Xian Zhang
- The Administrative Centre for China's Agenda 21 (ACCA21), Ministry of Science and Technology (MOST), Beijing, 100038, China
| | - Xin Zhang
- National Center for Climate Change, Strategy and International Cooperation, Beijing, 100035, China
| | - Zengkai Zhang
- State Key Laboratory of Marine Environmental Science, College of the Environment and Ecology, Xiamen University, Xiamen, 361102, China
| | - Bo Zheng
- Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China
| | - Yixuan Zheng
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing, 100041, China
| | - Jian Zhou
- Institute of Energy, Environment, and Economy, Tsinghua University, Beijing, 100084, China
| | - Tong Zhu
- State Key Joint Laboratory for Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering and Center for Environment and Health, Peking University, Beijing, 100871, China
| | - Jinnan Wang
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing, 100041, China
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100041, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
- Institute for Carbon Neutrality, Tsinghua University, Beijing, 100084, China
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Wan R, Qian S, Ruan J, Zhang L, Zhang Z, Zhu S, Jia M, Cai B, Li L, Wu J, Tang L. Modelling monthly-gridded carbon emissions based on nighttime light data. J Environ Manage 2024; 354:120391. [PMID: 38364545 DOI: 10.1016/j.jenvman.2024.120391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 01/25/2024] [Accepted: 02/10/2024] [Indexed: 02/18/2024]
Abstract
Timely and accurate implementation of carbon emissions (CE) analysis and evaluation is necessary for policymaking and management. However, previous inventories, most of which are yearly, provincial or city, and incomplete, have failed to reflect the spatial variations and monthly trends of CE. Based on nighttime light (NTL) data, statistical data, and land use data, in this study, a high-resolution (1 km × 1 km) monthly inventory of CE was developed using back propagation neural network, and the spatiotemporal variations and impact factors of CE at multiple administrative levels was evaluated using spatial autocorrelation model and spatial econometric model. As a large province in terms of both economy and population, Guangdong is facing the severe emission reduction challenges. Therefore, in this study, Guangdong was taken as a case study to explain the method. The results revealed that CE increased unsteadily in Guangdong from 2013 to 2022. Spatially, the high CE areas were distributed in the Pearl River Delta region such as Guangzhou, Shenzhen, and Dongguan, while the low CE areas were distributed in West and East Guangdong. The Global Moran's I decreased from 2013 to 2022 at the city and county levels, suggesting that the inequality of CE in Guangdong steadily decreased at these two administrative levels. Specifically, at the city level, the Global Moran's I gradually decreased from 0.4067 in 2013 to 0.3531 in 2022. In comparison, at the county level, the trend exhibited a slower decline, from 0.3647 in 2013 to 0.3454 in 2022. Furthermore, the analysis of the impact factors revealed that the relationship between CE and gross domestic product was an inverted U-shaped, suggesting the existence of the inverted U-shaped Environmental Kuznets Curve for CE in Guangdong. In addition, the industrial structure had larger positive impact on CE at the different levels. The method developed in this study provides a perspective for establishing high spatiotemporal resolution CE evaluation through NTL data, and the improved inventory of CE could help understand the spatial-temporal variations of CE and formulate regional-monthly-specific emission reduction policies.
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Affiliation(s)
- Ruxing Wan
- School of Economics and Management, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Shuangyue Qian
- School of Economics and Management, University of Chinese Academy of Sciences, Beijing, 100190, China
| | - Jianhui Ruan
- School of Economics and Management, University of Chinese Academy of Sciences, Beijing, 100190, China
| | - Li Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China.
| | - Zhe Zhang
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100043, China
| | - Shuying Zhu
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100043, China
| | - Min Jia
- School of Economics and Management, Beihang University, Beijing, 100191, China
| | - Bofeng Cai
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100043, China.
| | - Ling Li
- International School of Economics and Management, Capital University of Economics and Business, Beijing, 100070, China
| | - Jun Wu
- School of Economics and Management, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Ling Tang
- School of Economics and Management, University of Chinese Academy of Sciences, Beijing, 100190, China
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Luan L, Liu N, Zheng BF, Zhang ZY, Song YF, Li L, Gan M, Cao L, Huang ZY, Ye JK, Zhang ZN, Liu XX, Chen JL, Wang CS, Cai B, Yu WZ. [Thoughts and suggestions on digital services to enhance the level of vaccination management]. Zhonghua Yu Fang Yi Xue Za Zhi 2024; 58:159-165. [PMID: 38387944 DOI: 10.3760/cma.j.cn112150-20231012-00262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/24/2024]
Abstract
With the development of information technology and the increasing demand for vaccination services among the people, it is a definite trend to enhance the quality of vaccination services through digitization. This article starts with a clear concept of digital services for vaccination, introduces the current development status in China and abroad, analyzes the advantages and disadvantages of existing models in leading regions, takes a glean from the summation, and proposes targeted solutions. This study suggests establishing a departmental coordination mechanism for data interconnection and sharing, formulating data standards and functional specifications, enhancing the functionalities of the immunization planning information system, strengthening data collection and analytical usage, and intensifying appointment management and science and health education to provide expert guidance for the construction of digital vaccination services across the country in the future.
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Affiliation(s)
- L Luan
- Department of Immunization Program, Suzhou Center for Disease Control and Prevention, Suzhou 215004, China
| | - N Liu
- Department of Immunization Program, Suzhou Center for Disease Control and Prevention, Suzhou 215004, China
| | - B F Zheng
- Department of Immunization Program, Suzhou Center for Disease Control and Prevention, Suzhou 215004, China
| | - Z Y Zhang
- School of Public Health, Nanjing Medical University, Nanjing 211112, China
| | - Y F Song
- National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - L Li
- National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - M Gan
- Institute of Immunization Program, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning 530028, China
| | - L Cao
- National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Z Y Huang
- Institute of Immunization Program, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - J K Ye
- National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Z N Zhang
- National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - X X Liu
- Institute of Immunization Program, Jinan Center for Disease Control and Prevention, Jinan 250021, China
| | - J L Chen
- Institute of Immunization Program, Fujian Provincial Center for Disease Control and Prevention, Fuzhou 350012, China
| | - C S Wang
- Institute of Immunization Program, Henan Provincial Center for Disease Control and Prevention, Zhengzhou 450016, China
| | - B Cai
- Institute of Immunization Program, Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China
| | - W Z Yu
- National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing 100050, China
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Liang S, Zhang J, Cai B, Wang K, Zhang S, Li Y. How to perceive and map the synergy between CO 2 and air pollutants: Observation, measurement, and validation from a case study of China. J Environ Manage 2024; 351:119825. [PMID: 38169253 DOI: 10.1016/j.jenvman.2023.119825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Revised: 11/02/2023] [Accepted: 11/30/2023] [Indexed: 01/05/2024]
Abstract
Cities occupy a central position in addressing climate change and promoting sustainable regional development. Synergistic control of urban gas emissions at the city level is one of the main issues typically explored. The confounding effect and the interactions between the urban indicators of population and area have been ignored in previous studies. In this study, we examined the spatial distribution characteristics and synergy between greenhouse gases (CO2) and air pollutants (SO2 and NOX) using spatial population and gas emission data. By upgrading the city clustering algorithm (CCA), we established a method for defining active areas of gas emissions (spatial element-coupled clustering, SECC) and identified active areas of gas emissions in China. In this study, we created a research framework that can simultaneously consider the effects of population and area, as well as the possible interactions between these indicators in active areas. The superlinear scaling relationship between the above three gases was revealed at the active zone level, and the existence of synergy between the emission patterns of the three gases was confirmed. Via further model application, we measured the synergistic efficiency of the three gases. It was found that for every 1% increase in SO2 and NOX in an active zone, CO2 increases by 0.86%. In this study, we explored a new perspective and approach to explain the synergy between greenhouse gases and air pollutants. This is essential to promote national competition among cities to achieve synergistic control of CO2 and local air pollutants.
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Affiliation(s)
- Sen Liang
- School of Land Science and Technology, China University of Geosciences, 29, Xueyuan Road, Haidian District, Beijing, 100083, China.
| | - Jianjun Zhang
- School of Land Science and Technology, China University of Geosciences, 29, Xueyuan Road, Haidian District, Beijing, 100083, China; Key Laboratory of Land Consolidation and Rehabilitation, Ministry of Natural Resources, Beijing, 100083, China.
| | - Bofeng Cai
- Center for Climate Change and Environmental Policy, Chinese Academy for Environmental Planning, Beijing, 100012, China.
| | - Ke Wang
- State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Shouguo Zhang
- School of Land Science and Technology, China University of Geosciences, 29, Xueyuan Road, Haidian District, Beijing, 100083, China.
| | - Yue Li
- School of Water Resources and Environment, China University of Geosciences, 29, Xueyuan Road, Haidian District, Beijing, 100083, China.
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7
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Ren JG, Cai B, Wang H, Wang XL, Cai DS. Effect of methoxymine on prevention and treatment of myocardial injury and cardiac function in elderly patients with hypotension during intraspinal anesthesia. Eur Rev Med Pharmacol Sci 2023; 27:11755-11763. [PMID: 38164838 DOI: 10.26355/eurrev_202312_34773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
OBJECTIVE We aimed to investigate the effects of methoxamine to prevent hypotension in the elderly with intraspinal anesthesia (IA) on myocardial injury and cardiac function. PATIENTS AND METHODS A retrospective study was conducted by enrolling sixty elderly patients who underwent femoral head replacement (FHR) under IA in our hospital from August 2019 to August 2020. The patients were divided into two groups according to the random number table method. In the control group (CG) (30 patients), 5 mg of ephedrine was administered sedately when patients developed hypotension (20% below basal blood pressure). In the research group (RG) (30 cases), 2 μg/(kg·h) of methoxamine hydrochloride was given as a constant-rate pump before anesthesia, and 1 mg of methoxamine hydrochloride was administered intraoperatively if hypotension occurred. The hemodynamic [systolic blood pressure (SBP), diastolic blood pressure (DBP), heart rate (HR)], myocardial injury indexes [cardiac troponin I (cTnI), creatine kinase isoenzyme MB (CK-MB), fatty acid binding protein (FABP), plasma amino-terminal brain natriuretic peptide precursor (NT-proBNP)], cardiac function indexes [systemic vascular resistance (SVR), stroke volume (SV), net percentage ejection time (ET)] were observed before anesthesia (T1), at the end of surgery (T2), and 6 h after surgery (T3) in both groups. The Bruggemann Comfort Score (BCS) and Visual Analog Scale (VAS) scores at T3, 12 h postoperatively (T4) and 24 h postoperatively (T5) in both groups were observed, and the incidence of adverse reactions to intralesional anesthesia in both groups was counted. RESULTS SBP, DBP and HR at T2 were lower than those at T1 in both groups, and SBP, DBP and HR at T3 were higher than those at T2, and SBP, DBP and HR at T2 and T3 in the RG were higher than those in the CG (p<0.05). In both groups, cTnⅠ, CK-MB and FABP were higher at T2 and T3 than at T1, higher at T3 than at T2, and NT-proBNP was higher at T2 than at T1 and T3, and lower in the RG than in the CG (p<0.05). In both groups, SVR and SV at time point T2 were lower than at time point T1 and ET was higher than at time point T1, SVR and SV at time point T3 were higher than at time point T2 and ET was lower than at time point T2, SVR and SV in the RG were higher than in the CG and ET was lower than in the CG (p<0.05). VAS scores were higher in both groups at T4 and T5 than at T3, and lower in the RG than in the CG (p<0.05). CONCLUSIONS Methoxamine can effectively reduce the risk of hypotension in geriatric endotracheal anesthesia, which can reduce myocardial injury and stabilize cardiac function in patients.
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Affiliation(s)
- J-G Ren
- Department of Anesthesiology and Surgery, Danzhou People's Hospital, Danzhou, China.
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Duman Z, Mao X, Cai B, Zhang Q, Chen Y, Gao Y, Guo Z. Exploring the spatiotemporal pattern evolution of carbon emissions and air pollution in Chinese cities. J Environ Manage 2023; 345:118870. [PMID: 37678024 DOI: 10.1016/j.jenvman.2023.118870] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 08/04/2023] [Accepted: 08/26/2023] [Indexed: 09/09/2023]
Abstract
Based on data from 335 cities in China, this study employs the standard deviation ellipse method to portray unbalanced and differential spatiotemporal evolution patterns of environmental emissions and socioeconomic elements. A logarithmic mean Divisia index analysis and in-depth discussion are carried out to disclose the main driving factors and underlying reasons for the differences. Decoupling trends exist among carbon emissions, gross domestic product (GDP) and population in terms of their gravity center migrations. The standard deviation ellipse direction of carbon emissions gradually changed from 'northeast‒southwest' to 'northwest‒southeast', and the standard deviation ellipse areas of carbon emissions and air pollution continuously expanded over time; at the same time, that of GDP contracted. Economic growth has always been the main driver of carbon emissions and air pollution nationally, but its role has weakened. Moreover, decreases in the energy intensity and carbon and pollution intensities are the main factors contributing to emissions reductions. Differentiated spatiotemporal economic structure evolution, regional heterogeneities in the energy intensity and efficiency, and cross-region power energy transmissions are identified as the underlying reasons for the unbalanced spatiotemporal patterns of the environmental emissions and socioeconomic elements. Based on these findings, policy suggestions can be made to address the imbalances and promote carbon mitigation, air quality improvement and high-quality social-economic development at the city level.
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Affiliation(s)
- Zaenhaer Duman
- School of Environment, Beijing Normal University, Beijing, 100875, PR China; Center for Global Environmental Policy, Beijing Normal University, Beijing, 100875, PR China
| | - Xianqiang Mao
- School of Environment, Beijing Normal University, Beijing, 100875, PR China; Center for Global Environmental Policy, Beijing Normal University, Beijing, 100875, PR China.
| | - Bofeng Cai
- Chinese Academy of Environmental Planning, Beijing, 100012, China.
| | - Qingyong Zhang
- School of Environment, Beijing Normal University, Beijing, 100875, PR China; Center for Global Environmental Policy, Beijing Normal University, Beijing, 100875, PR China
| | - Yongpeng Chen
- School of Environment, Beijing Normal University, Beijing, 100875, PR China; Center for Global Environmental Policy, Beijing Normal University, Beijing, 100875, PR China
| | - Yubing Gao
- School of Environment, Beijing Normal University, Beijing, 100875, PR China; Center for Global Environmental Policy, Beijing Normal University, Beijing, 100875, PR China
| | - Zhi Guo
- School of Environment, Beijing Normal University, Beijing, 100875, PR China; Center for Global Environmental Policy, Beijing Normal University, Beijing, 100875, PR China
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9
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Lyu J, Liu T, Cai B, Qi Y, Zhang X. Heterogeneous effects of China's low-carbon city pilots policy. J Environ Manage 2023; 344:118329. [PMID: 37379627 DOI: 10.1016/j.jenvman.2023.118329] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 05/25/2023] [Accepted: 06/04/2023] [Indexed: 06/30/2023]
Abstract
Global south countries, including China, have faced a challenging dilemma of reducing carbon emissions while maintaining rapid economic growth. The low-carbon city pilots (LCCPs) policy in China is a demonstration of how state power intervenes and commands national low-carbon development through voluntary policy tools. Our study, based on panel data of 331 cities from 2005 to 2019, evaluates the policy effect of all three batches of LCCPs and presents an analysis of time-varying effects through batch decomposition and synthetic difference-in-difference models. The study found that implementing low-carbon policies can significantly reduce total carbon emissions and carbon emissions per capita. However, the reduction in carbon emissions per unit of GDP is insignificant, and the policy effect varies according to the batches and their characteristics. The reduction effects in the first and second batches, as well as the insignificance or even increasing effects of the third batch, may be due to carbon leakage between different batches of LCCPs. Overall, this research provides novel and quantitative evidence on low-carbon development in China, making theoretical and empirical contributions to the field, and expanding econometric assessment methods to evaluate the effectiveness of environmental and climate change policies.
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Affiliation(s)
- Jing Lyu
- Interdisciplinary Programs, Hong Kong University of Science and Technology, Kowloon, Hong Kong, China; Jiangmen Laboratory of Carbon Science and Technology, Hong Kong University of Science and Technology, Jiangmen, 529000, China.
| | - Tianle Liu
- Jiangmen Laboratory of Carbon Science and Technology, Hong Kong University of Science and Technology, Jiangmen, 529000, China; School of Humanities and Social Sciences, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, China.
| | - Bofeng Cai
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100012, China.
| | - Ye Qi
- Jiangmen Laboratory of Carbon Science and Technology, Hong Kong University of Science and Technology, Jiangmen, 529000, China; Carbon Neutrality and Climate Change Thrust, Hong Kong University of Science and Technology (Guangzhou), Guangzhou, 511453, China; School of Public Policy and Management, Tsinghua University, Beijing, 100084, China.
| | - Xiaoling Zhang
- Department of Policy and International Affairs, City University of Hong Kong, Kowloon, Hong Kong, China; Shenzhen Research Institute, City University of Hong Kong, Shenzhen, PRC; School of Energy and Environment, City University of Hong Kong, China.
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10
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Montalvo SK, Arbab M, Gonzalez Y, Lin MH, Parsons DDM, Zhuang T, Cai B, Pompos A, Hannan R, Westover KD, Zhang Y, Timmerman RD, Iyengar P. Predictive Factors for Response to Adaptive Therapy in Thoracic Stereotactic Ablative Radiotherapy. Int J Radiat Oncol Biol Phys 2023; 117:e43. [PMID: 37785405 DOI: 10.1016/j.ijrobp.2023.06.742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Online adaptive radiotherapy (ART) has been increasingly adopted for clinical use. However, ART for thoracic malignancies has lagged beyond its implementation for other primary cancers. Efforts are needed to identify optimal patients for ART by finding trends for changes in tumor position, shape, or proximity to OARs are needed. We hypothesized tumor size, histology, pre-RT SUV value, and intrathoracic location could influence how tumors change during cone beam computed tomography (CBCT)-based ART Stereotactic Ablative Radiotherapy (SAbR) for thoracic disease. MATERIALS/METHODS Data was collected from a prospective registry of patients who received CBCT-ART and SAbR for primary and secondary lung tumors. Dosimetry data was obtained from the simulation planning and the daily adaptive workflow. Central lung tumors were defined as those located within 2 cm of the bronchial tree. Plans were either delivered as per simulation or through the online adaptive workflow delivery (AD). Change in planning tumor volumes (PTV) were calculated between initial and final fractions (ΔPTV). RESULTS A total of 42 patients with a median age of 67 (range 17-90) and median 8.3 months follow up, treated between June 2021 and December 2022 were included. Most patients had NSCLC or presumed NSCLC (73.85%, 31/42), and most lesions were peripheral (61.9%, 26/42) versus central (31%, 13/42) or apical (7.1%, 3/42). Mean dose and median fractions were 52.5 Gy (SD 8.07) and 5 (range 3-5) while median initial (i) PTV was 31.75 cm3 (IQR 42.3 cm3). On average, ΔPTV decreased by 4.9% (SD 21) and volume shrunk by 5 cm3 (SD 14.5). AD improved per fraction PTV coverage and conformality while esophageal, cardiac, and spinal cord dose were significantly decreased (all p < 0.05), and most fractions were delivered with AD (73.4%, 138/188). AD was aborted most often for small iPTVs. ΔPTV grew >10% for two lesions though their iPTV were < 10 cm3. 12/42 ΔPTV were >10% smaller by the end of RT and corresponded to larger iPTVs. Age, lung primary, metastatic disease, smoking status, and tumor location were not predictive for >10% decrease in ΔPTV. Among 24 biopsy-proven NSCLC ΔPTV was >10% smaller in 6/12 patients (50%) with adenocarcinoma and only in 2/12 (16.7%) with SCC, although this was not significant on χ2 testing (p = 0.08). There were no differences in local, regional, distant failure or death comparing those with a ΔPTV of >10% vs <10% (all p > 0.1). Comparing pre-treatment PET SUV and tumor response, lower SUVs appear to be associated with more PTV shrinkage, with no significant PTV change plateauing at SUV 20. However, this analysis was limited by the number of patients with high SUV values. CONCLUSION CBCT-ART SAbR is associated with improved PTV coverage, target conformality, and reduced OAR dose. Large iPTV and adenocarcinomas were more likely to decrease >10%. High metabolic activity appeared predictive for a lack of significant ΔPTV. Further clinical and radiographic features should be explored to predict response to ART.
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Affiliation(s)
- S K Montalvo
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - M Arbab
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - Y Gonzalez
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - M H Lin
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - D D M Parsons
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - T Zhuang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - B Cai
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - A Pompos
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - R Hannan
- University of Texas Southwestern Medical Center, Dallas, TX
| | - K D Westover
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Y Zhang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - R D Timmerman
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - P Iyengar
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
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11
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Gibbard G, Aguilera TA, Dan T, Zhuang T, Lin MH, Peng H, Jiang SB, Da Silva A, Kuduvalli G, Iyengar P, Sher DJ, Timmerman RD, Garant A, Cai B. Towards Biology-Guided Radiotherapy Planning and Delivery on a Novel O-Ring PET-Linac Platform: Extended Beyond Bone and Lung Lesions. Int J Radiat Oncol Biol Phys 2023; 117:e647. [PMID: 37785924 DOI: 10.1016/j.ijrobp.2023.06.2064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Biology-guided radiotherapy (BgRT) with FDG signal collected via an on-board positron emission tomography (PET) system integrated in an O-ring gantry Linac was recently cleared by the FDA for lung and bone lesions. This study aims to determine if BgRT plans, guided via PET signal, are clinically acceptable for FDG-avid lesions in disease sites beyond bone and lung. MATERIALS/METHODS Ten patients previously treated for lesions in the liver, head and neck (HN), pancreas, renal and pelvic-abdominal lymph nodes were identified. Diagnostic PET/CT images of these treatment sites were first collected and processed/converted to mimic PET images that are acquired on PET-Linac and would be used to guide the delivery. For BgRT planning, the PTV was generated with 5 mm margin from GTV and a Biology Tracking Zone was generated including the anticipated full range of target motion. BgRT plans, guided by the emulated PET signal, were generated with 46Gy in 3 fractions for liver and 40Gy in 5 fractions for all other sites. BgRT plan deliverability was first assessed by evaluating the Activity Concentration (AC) and Normalized Target Signals (NTS) on converted PET images with the goal to meet NTS >2 (hard constraint) and AC >5kBq/ml (goal). BgRT plan quality was then evaluated with institutional guidelines on PTV coverage, OAR doses, conformity index (CI) and Heterogeneity index (HI). RESULTS BgRT plans were successfully generated for 11 target lesions among ten patients. The average diagnostic PET SUV, derived NTS and AC on converted PET images were 12.62, 9.33 and 12.10 kBq/ml, respectively. All images met the NTS constraints, and 8/11 plans met the AC goal for deliverability. All plans met the OAR hard constraints such as max dose on duodenum, small bowel, large bowel and spinal cord. Five of 11 plans had a limiting GI structure that resulted in an expected reduction in PTV coverage with an average PTV V100% = 77.9%, CI of 1.4, HI of 1.36 and max dose of 133.8%. The other 6 of 11 cases met the PTV V100% = 95%, had an average CI of 1.1, HI of 1.28 and Dmax of 127.67%. The estimated average time for BgRT delivery was 17 mins 25 secs. Although these plan parameters are deemed to be clinically acceptable, heterogeneity was detected inside the target region and suboptimal dose fall off was observed in some cases that may be caused by current implementation. CONCLUSION This preliminary study showed that BgRT plans were generated successfully with emulated PET images on 11 treatment sites covering HN, abdominal and pelvic regions. All plans met NTS constraints and 8 out of 11 met AC goals for deliverability. The plan quality of all BgRT plans were clinically acceptable based on institutional constraints. Further investigations are required to test more patients/sites for BgRT plan feasibility. Dosimetric benefit from margin reduction of BgRT target should also be investigated in future study.
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Affiliation(s)
- G Gibbard
- University of Texas Southwestern Medical Center, Dallas, TX
| | - T A Aguilera
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - T Dan
- Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX
| | - T Zhuang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - M H Lin
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - H Peng
- University of Texas Southwestern Medical Center, Dallas, TX
| | - S B Jiang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | | | | | - P Iyengar
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - D J Sher
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - R D Timmerman
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - A Garant
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - B Cai
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
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12
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Zhang Q, Yin Z, Lu X, Gong J, Lei Y, Cai B, Cai C, Chai Q, Chen H, Dai H, Dong Z, Geng G, Guan D, Hu J, Huang C, Kang J, Li T, Li W, Lin Y, Liu J, Liu X, Liu Z, Ma J, Shen G, Tong D, Wang X, Wang X, Wang Z, Xie Y, Xu H, Xue T, Zhang B, Zhang D, Zhang S, Zhang S, Zhang X, Zheng B, Zheng Y, Zhu T, Wang J, He K. Synergetic roadmap of carbon neutrality and clean air for China. Environ Sci Ecotechnol 2023; 16:100280. [PMID: 37273886 PMCID: PMC10236195 DOI: 10.1016/j.ese.2023.100280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 04/05/2023] [Accepted: 04/06/2023] [Indexed: 06/06/2023]
Abstract
It is well recognized that carbon dioxide and air pollutants share similar emission sources so that synergetic policies on climate change mitigation and air pollution control can lead to remarkable co-benefits on greenhouse gas reduction, air quality improvement, and improved health. In the context of carbon peak, carbon neutrality, and clean air policies, this perspective tracks and analyzes the process of the synergetic governance of air pollution and climate change in China by developing and monitoring 18 indicators. The 18 indicators cover the following five aspects: air pollution and associated weather-climate conditions, progress in structural transition, sources, inks, and mitigation pathway of atmospheric composition, health impacts and benefits of coordinated control, and synergetic governance system and practices. By tracking the progress in each indicator, this perspective presents the major accomplishment of coordinated control, identifies the emerging challenges toward the synergetic governance, and provides policy recommendations for designing a synergetic roadmap of Carbon Neutrality and Clean Air for China.
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Affiliation(s)
- Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Zhicong Yin
- Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Xi Lu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
- Institute for Carbon Neutrality, Tsinghua University, Beijing, 100084, China
| | - Jicheng Gong
- State Key Joint Laboratory for Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering and Center for Environment and Health, Peking University, Beijing, 100871, China
| | - Yu Lei
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing, 100012, China
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100012, China
| | - Bofeng Cai
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100012, China
| | - Cilan Cai
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Qimin Chai
- National Center for Climate Change, Strategy and International Cooperation, Beijing, 100035, China
| | - Huopo Chen
- Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Hancheng Dai
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Zhanfeng Dong
- Institute of Environmental Policy Management, Chinese Academy of Environmental Planning, Beijing, 100012, China
| | - Guannan Geng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Dabo Guan
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Jianlin Hu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, 100084, China
| | - Jianing Kang
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Wei Li
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Yongsheng Lin
- School of Economics and Resource Management, Beijing Normal University, Beijing, 100875, China
| | - Jun Liu
- Department of Environmental Engineering, School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China
| | - Xin Liu
- Energy Foundation China, Beijing, 100004, China
| | - Zhu Liu
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Jinghui Ma
- Shanghai Typhoon Institute, Shanghai Meteorological Service, Shanghai, 200030, China
| | - Guofeng Shen
- College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Dan Tong
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Xuhui Wang
- College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Xuying Wang
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing, 100012, China
| | - Zhili Wang
- State Key Laboratory of Severe Weather and Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
| | - Yang Xie
- School of Economics and Management, Beihang University, Beijing, 100191, China
| | - Honglei Xu
- Laboratory of Transport Pollution Control and Monitoring Technology, Transport Planning and Research Institute, Ministry of Transport of the People's Republic of China, Beijing, 100028, China
| | - Tao Xue
- Institute of Reproductive and Child Health/Ministry of Health Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100080, China
| | - Bing Zhang
- State Key Laboratory of Pollution Control & Resource Reuse School of Environment, Nanjing University, Nanjing, 210008, China
| | - Da Zhang
- Institute of Energy, Environment, and Economy, Tsinghua University, Beijing, 100084, China
| | - Shaohui Zhang
- School of Economics and Management, Beihang University, Beijing, 100191, China
| | - Shaojun Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Xian Zhang
- The Administrative Centre for China's Agenda 21 (ACCA21), Ministry of Science and Technology (MOST), Beijing, 100038, China
| | - Bo Zheng
- Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China
| | - Yixuan Zheng
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing, 100012, China
| | - Tong Zhu
- State Key Joint Laboratory for Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering and Center for Environment and Health, Peking University, Beijing, 100871, China
| | - Jinnan Wang
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing, 100012, China
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100012, China
- Institute of Environmental Policy Management, Chinese Academy of Environmental Planning, Beijing, 100012, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
- Institute for Carbon Neutrality, Tsinghua University, Beijing, 100084, China
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13
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Li R, Montalvo SK, Zhuang T, Parsons DDM, Zhong X, Chen L, Iqbal Z, Kim H, Hrycushko BA, Westover KD, Zhang Y, Cai B, Lin MH, Iyengar P. Dosimetric Analysis of CBCT-Based Weekly Online Adaptive Radiotherapy for Locally Advanced Non-Small Cell Lung Cancer. Int J Radiat Oncol Biol Phys 2023; 117:e36-e37. [PMID: 37785239 DOI: 10.1016/j.ijrobp.2023.06.728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Anatomic and geometric changes are common during a radiotherapy course amongst patients receiving conventional fractionated radiotherapy for locally advanced non-small cell lung cancer (LA-NSCLC). These changes may cause significant deviation from initial reference plan resulting in over-treatment of normal tissue or under-coverage of the target. Cone-beam computed tomography (CBCT)-based online adaptive radiotherapy (ART) platforms allow for response to these changes and is being increasingly used in the clinic though less so for intrathoracic disease. We hypothesized weekly CBCT-ART would improve target coverage and decrease dose to organs at risk (OAR) in patients with LA-NSCLC. MATERIALS/METHODS Data was collected from a prospective registry of 23 LA-NSCLC patients treated to 60 Gy in 30 fractions with CBCT-ART between June 2021 and December 2022. For weekly ART (Wk-ART), online plan adaptation started on week two. The adapted plan was then used to treat patients with image guidance until the next ART. For comparison, doses were recalculated with the initial reference plan on the SCT with updated contours to derive non-adapted (non-ART) dosimetry for each week. The final dosimetric parameters were obtained by averaging weekly coverage (ITV, PTV) and critical OAR (Lung, esophagus, heart, spinal cord) doses for non-ART and weekly ART treatments respectively for each patient. Paired student t-test was performed to compare the dosimetric parameters between non-ART and Wk-ART. RESULTS We observed an average 29% ± 19% (median: 26%) reduction in ITV volume through the radiotherapy course, with 48% (11/23) of patients showing >30% reduction. Most significant volume reductions (16%) were observed between the third and fourth adaptation. Weekly ART showed significant (p<1×10-3) improvements in ITV and PTV coverage, and showed improved clinically relevant lung, esophageal, cardiac, and lung dosimetry (Table 1), especially in the later stages of treatment when the tumor showed significant shrinkage. The average time from contour review to quality assurance completed is 8.5±1.2 min. CONCLUSION CBCT-ART provides robust ART plan quality and efficient workflow. There are significant improvements in target coverage and OAR sparing in LA-NSCLC treated with weekly CBCT-ART and these are driven by the significant volume reduction of the ITV throughout treatment course.
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Affiliation(s)
- R Li
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - S K Montalvo
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - T Zhuang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - D D M Parsons
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - X Zhong
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - L Chen
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Z Iqbal
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - H Kim
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - B A Hrycushko
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - K D Westover
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Y Zhang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - B Cai
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - M H Lin
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - P Iyengar
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
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14
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Keilty D, Visak J, Wang S, Chen L, Kim DN, Arbab M, Alluri PG, Zhong X, Iqbal Z, Zhuang T, Cai B, Kim H, Timmerman RD, Lin MH, Parsons DDM, Rahimi AS. Predicted Cardiac Toxicity in Daily Cone-Beam CT-Based Online Adaptive Stereotactic Partial Breast Irradiation with Decreased PTV Margins. Int J Radiat Oncol Biol Phys 2023; 117:e184-e185. [PMID: 37784811 DOI: 10.1016/j.ijrobp.2023.06.1041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Partial breast irradiation (PBI) targets a smaller volume over less time compared to whole breast radiation, but the organ-at-risk (OAR) sparing allowed by its large (up to 1 cm) PTV can be improved. The heart is sensitive to low doses with conventional fractionation and NTCP models have been created for heart substructures. We hypothesized that daily online adaptive stereotactic PBI (A-SPBI) IMRT with 3-mm PTV improves dosimetry and predicted cardiac toxicity risk. MATERIALS/METHODS Patients treated with daily CBCT-based online A-SPBI IMRT were excluded if the minimum heart dose was <1 Gy. IMRT radiation plans with 3-mm PTV margins were recreated with 1-cm margins per the Florence APBI IMRT trial planning guideline. Dose statistics were converted to the equivalent doses in 2-Gy fractions (EQD2) using α/β = 3 for use in NTCP models and for comparison using paired t tests, with differences considered significant if p≤0.05. RESULTS The table details heart, left anterior descending artery (LAD), and left (LV) and right ventricle (RV) EQD2 statistics for 4 left-sided and 4 right-sided 3-mm PTV plans and their 1-cm PTV replans. For 2 patients with non-zero LV V5, 9-year excess cumulative risk of acute coronary event was <0.001% for both margin sizes. No plan reached thresholds for increased risk of non-cardiac death, major adverse cardiac event, or >10% decrease in LV ejection fraction. CONCLUSION Given the established relationship between low MHD and cardiac events, the significant decrease in MHD revealed in comparisons of 3-mm and 1-cm PTV A-SPBI plans of our first 8 patients is promising; we expect the forthcoming larger sample size to show significant differences in substructure doses. NTCP models created for non-IMRT breast plans and targets with higher heart exposure did not predict clinically-relevant differences in cardiac risk. NTCP model development for the low heart dose achieved with A-SPBI would define expected benefit in these patients; in their absence, daily adaptation should be considered in patients with unfavorable anatomy or cardiac risk factors.
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Affiliation(s)
- D Keilty
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - J Visak
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - S Wang
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - L Chen
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - D N Kim
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - M Arbab
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - P G Alluri
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - X Zhong
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Z Iqbal
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - T Zhuang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - B Cai
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - H Kim
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - R D Timmerman
- Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX
| | - M H Lin
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - D D M Parsons
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - A S Rahimi
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
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Keilty D, Visak J, Wang S, Chen L, Kim DN, Arbab M, Alluri PG, Zhong X, Iqbal Z, Zhuang T, Cai B, Kim H, Timmerman RD, Lin MH, Parsons DDM, Rahimi AS. Observed and Predicted Toxicity in Daily Cone-Beam CT-Based Online Adaptive Stereotactic Partial Breast Irradiation with Decreased PTV Margins. Int J Radiat Oncol Biol Phys 2023; 117:e184. [PMID: 37784810 DOI: 10.1016/j.ijrobp.2023.06.1040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Accelerated partial breast irradiation (APBI) delivers smaller radiation volumes over less time compared to whole breast irradiation (WBI), but the organ-at-risk (OAR) sparing allowed by its large (up to 1 cm) planning target volume (PTV) can be improved. PTV can be decreased with daily online adaptive planning, which we hypothesized yields low rates of adverse events observed and predicted by normal tissue complication probability (NTCP) models. MATERIALS/METHODS Intensity-modulated (IMRT) cone-beam CT (CBCT)-based daily online adaptive stereotactic PBI (A-SPBI) plans with 3-mm PTV from 8 patients were recreated with 1-cm PTV per the Florence APBI IMRT trial planning guideline. Dose statistics with evidence for association with toxicity were compared. Documented toxicities were collected for patients treated with A-SPBI with a minimum follow-up of 3.5 months and Common Terminology Criteria for Adverse Events (CTCAE) v.5.0 grade was assigned. Using α/β = 3 for breast and lung, dose statistics were converted to equivalent doses in 2-Gy fractions (EQD2) for use in NTCP models and for comparison using paired t tests, with differences considered significant if p≤0.05. RESULTS The table details EQD2 dose statistics for breast, lung, and cosmetic toxicity for A-SPBI plans with 3-mm PTV and their 1-cm PTV re-plans in 8 patients. PTV volume, mean lung dose (MLD), and lung V5, V20, and V30 were significantly lower in 1-cm plans. Acute, subacute (3-6 months), and late toxicities were collected for 30 patients followed for a median of 8 months (range 4-13 months). Radiation dermatitis was the most common acute toxicity (n = 16, 53%), followed by hyperpigmentation (n = 12, 40%), fibrosis (n = 9, 30%), and fatigue (n = 9, 30%). One grade 3 radiation dermatitis was the only grade ≥3 toxicity. Six patients (20%) acutely developed breast or axillary edema: 4 (13.3%) resolved, and 2 (6.7%) developed acutely and persist at last follow-up, >6 months after RT. No patient had a lung V20, V30, or MLD meeting thresholds for radiation-induced lung injury, radiation pneumonitis, or symptomatic or imaging-based pneumonitis models, respectively. The breast V55 model predicted a median risk of unfavorable cosmesis of 33% (range 26-44%) for A-SBPI plans and 35% (range 28-51) for 1-cm PTV plans (p = 0.28). CONCLUSION Observed acute toxicities are tolerable and rarely persist in patients treated with A-SPBI with 3-mm PTV margins with daily CBCT-based online adaptation. NTCP modeling predicts similar cosmetic outcome to 1-cm margins. The significant reduction in ipsilateral lung dose with a 3-mm PTV in our first 8 patients especially supports daily adaptation in low-risk breast cancer patients with smoking history and/or lung comorbidity.
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Affiliation(s)
- D Keilty
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - J Visak
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - S Wang
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - L Chen
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - D N Kim
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - M Arbab
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - P G Alluri
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - X Zhong
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Z Iqbal
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - T Zhuang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - B Cai
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - H Kim
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - R D Timmerman
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - M H Lin
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - D D M Parsons
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - A S Rahimi
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
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Surucu M, Vitzthum L, Chang DT, Gensheimer MF, Kovalchuk N, Han B, Iagaru AH, Da Silva A, Narayanan M, Aksoy D, Feghali K, Shirvani SM, Maniyedath A, Cai B, Pompos A, Dan T, Öz OK, Iyengar P, Timmerman RD, Garant A. Analysis of the Measured FDG Uptake from the First-in-Human Clinical Trial of Biology-Guided Radiotherapy. Int J Radiat Oncol Biol Phys 2023; 117:e61-e62. [PMID: 37785835 DOI: 10.1016/j.ijrobp.2023.06.782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) The RefleXion X1 system is a novel linear accelerator equipped with dual 90° PET arcs incorporated into its architecture to capture emissions from tumors and designed to respond by directing the radiation beam towards target. This study reports on the measured FDG uptake from the first in human multi-institutional clinical trial (BIOGUIDE-X) evaluating the performance and safety of the RefleXion X1 PET-LINAC. MATERIALS/METHODS A total of nine patients treated with stereotactic body radiotherapy (SBRT) for lung (5) and bone (4) tumors were enrolled in the Cohort II of this study after screening their pre-study diagnostic PET/CT, acquired up to 60 days prior to enrollment, to ensure their tumor size between 2 to 5 cm and SUVmax >6. After CT simulation, the tumor and OARs were delineated, and patients had a 4-pass Imaging-only (BgRT Modeling) PET/CT acquisition on the X1 system to generate biology-guided radiotherapy (BgRT) plans. Before the patients' first and last SBRT fractions, they were injected with FDG, and short PET pre-scan (1-pass) was performed on the X1 followed by a long-PET acquisition (4-pass) to emulate the expected BgRT dose distribution without firing beam. Patients were also imaged on a third-party diagnostic PET/CT scanner after the last-fraction X1 scan. This study compares the SUVmax from the screening PET/CT, X1 Imaging-only scan, X1 PET pre-scan and long scan before the first and last-fractions, and final diagnostic PET/CT. RESULTS The median time from injection to PET imaging was 84 ± 15.4 mins for X1 Imaging-only (used for generating BgRT plans), 77 ± 21.6 mins for X1 pre-scan (safety check before treatment start), 108+/- 22 mins for X1 long-PET (used to emulate treatment delivery), and 161 ± 23 mins for final diagnostic PET. For a nominal 10 mCi injection, the mean SUVmax for screening imaging performed on the diagnostic PET/CT was 10.8 ± 4.3. For a 15 mCi nominal injection, the mean SUVmax calculated on the X1 was 5.3 ± 2.6, 5.4 ± 2.0, 5.5 ± 2.6, 5.2 ± 1.8 and 5.4 ± 2.2 for the Imaging-only, first-fraction PET pre-scan, first-fraction long PET scan, last-fraction PET pre-scan, and last-fraction long PET scan, respectively. The overall median SUVmax for all patients across all timepoints and scans with X1 was calculated to be 4.8 with a range of 2.4 to 9.8. The median SUVmax for the diagnostic PET/CT scan after the last fraction X1 scan was 15.8 with a range of 8.5 to 27.7. CONCLUSION The dual PET arcs and limited axial extent of the X1 PET subsystem results in lower system sensitivity in comparison to diagnostic PET scanners equipped with full ring and larger axial extent, as expected. With the same FDG injection, the RefleXion X1 produced SUVmax values that were 30.4 % of the diagnostic PET/CT scanners' values. Nevertheless, the X1 collected sufficient emission data to enable successful completion of emulated BgRT deliveries that met dose accuracy criteria in a clinical setting.
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Affiliation(s)
- M Surucu
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - L Vitzthum
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - D T Chang
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA; Department of Radiation Oncology, Michigan Medicine, Ann Arbor, MI
| | - M F Gensheimer
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - N Kovalchuk
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - B Han
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - A H Iagaru
- Department of Radiology, Stanford University School of Medicine, Palo Alto, CA
| | | | | | - D Aksoy
- RefleXion Medical, Inc., Hayward, CA
| | - K Feghali
- RefleXion Medical, Inc., Hayward, CA
| | | | | | - B Cai
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - A Pompos
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - T Dan
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - O K Öz
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - P Iyengar
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - R D Timmerman
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - A Garant
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
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Garant T, Iyengar P, Dan T, Pompos A, Timmerman RD, Öz OK, Cai B, Shirvani SM, Aksoy D, Al Feghali KA, Maniyedath A, Narayanan M, Da Silva A, Surucu M, Gensheimer MF, Kovalchuk N, Han B, Pham D, Chang DT, Vitzthum L. Imaging Performance of the PET Scan on a Novel Ring Gantry-Based PET/CT Linear Accelerator System in the First-in-Human Study of Biology-Guided Radiotherapy. Int J Radiat Oncol Biol Phys 2023; 117:e665. [PMID: 37785968 DOI: 10.1016/j.ijrobp.2023.06.2105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Biology-guided radiotherapy (BgRT) is a novel tracked dose delivery modality using real-time positron emission tomography (PET) to guide radiotherapy beamlets. The present study was performed with sequential cohorts of participants to evaluate the performance and safety of BgRT. Primary endpoints were previously reported. We hereby report on one of the secondary endpoints assessing a novel treatment planning machine with integrated dual kVCT/PET imaging ("novel device") performance in comparison to a third-party diagnostic PET/CT scan. MATERIALS/METHODS This single-arm, open-label, prospective study included participants with at least 1 FDG-avid targetable primary or metastatic tumor (≥2cm and ≤5cm) in the lung or bone. PET imaging data were collected on the novel device and on a third-party diagnostic PET/CT performed in sequence once at the planning timepoint in Cohort I, and immediately before the last fraction among patients undergoing stereotactic radiotherapy in Cohort II. Three central read radiation oncologists (CRRO) provided an interpretation of the novel device PET scans which were compared to an agreement standard based on 3 central radiologists' review of the paired diagnostic PET/CT scan. Positive percent agreement for localization of the target tumor within the biology-tracking zone (BTZ) was the key metric because it reflects whether advancing patients to subsequent steps in the BgRT workflow based on the novel device's imaging was ultimately appropriate. RESULTS In Cohort 1, 6 image comparisons were performed. The positive (%) agreement for the aggregate radiation oncologist review was 100% (5/5), reflecting that in all 5 cases where the aggregate radiation oncologists deemed the tumor to fall within the BTZ based upon the novel device PET images, the central radiologists came to the same conclusion upon review of the paired diagnostic PET/CT images. The overall (%) agreement for the aggregate radiation oncologist review was 83.3% (5/6): localization was not established on the novel device in 1 case, even though it was established on the diagnostic PET/CT. This would not pose risk in real world practice as BgRT candidacy would be aborted for tumors not visible on the novel device. In Cohort II, among the 7 image comparisons, there was 100% positive percent agreement between the aggregate CRRO and the agreement standard as the localization criteria was met in both scans for all 7 patients. This was concordant with a 100% overall percent agreement. CONCLUSION This investigation demonstrated a 100% positive percent agreement between central review of this novel device images by radiation oncologists and central review of the accompanying third-party PET/CT images by radiologists. There were no cases where a positive localization by the aggregate CRRO was not confirmed by the third-party PET/CT standard, providing evidence against the likelihood of falsely positive localizations on the novel device that would inappropriately advance patients in the workflow.
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Affiliation(s)
- T Garant
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - P Iyengar
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - T Dan
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - A Pompos
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - R D Timmerman
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - O K Öz
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - B Cai
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | | | - D Aksoy
- RefleXion Medical, Inc., Hayward, CA
| | | | | | | | | | - M Surucu
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - M F Gensheimer
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - N Kovalchuk
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - B Han
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - D Pham
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - D T Chang
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - L Vitzthum
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
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18
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Gonzalez Y, Chen L, Lee H, Kim N, Arbab M, Alluri PG, Zhang Y, Chiu TD, Iqbal Z, Zhuang T, Cai B, Kim H, Pompos A, Jiang SB, Godley AR, Timmerman RD, Lin MH, Rahimi AS, Parsons DDM. Dosimetric Comparison of Adaptive Radiotherapy Modalities for Stereotactic Partial Breast Irradiation. Int J Radiat Oncol Biol Phys 2023; 117:S163-S164. [PMID: 37784408 DOI: 10.1016/j.ijrobp.2023.06.260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) An increase in the availability of adaptive radiotherapy (ART) platforms have proven to be effective in the treatment of a variety of sites. In this study, we aim to evaluate the effectiveness of non-adaptive RT and 3 different ART platforms: (1) CBCT-based, (2) CT-based, and (3) MRI-based for stereotactic partial breast irradiation (SPBI). MATERIALS/METHODS Data were collected from 32 patients (16 left and 16 right breast) treated at a single institution. 16 patients (8 left and 8 right) treated using the non-ART platform were re-planned onto two different ART platforms, CBCT- and MRI-based. The remaining 16 patients treated using CT-based adaptive platform were not re-planned due to the prone patient treatment position (others systems supine). All cases were planned to 30 Gy in 5 fractions. Plan quality was evaluated based on pre-defined planning goals to the OARS: ipsilateral and contralateral lungs (Dmean, Dmax, V20 Gy, V9 Gy), ipsilateral (V15 Gy, V30 Gy) and contralateral breasts (Dmax), heart (Dmean, Dmax, V3 Gy, V1.5 Gy), skin (Dmax, V36.5 Gy), and rib (Dmax, V30 Gy). Target goals were defined by Dmax, Dmin, gradient index, and paddock conformality index. Re-planned cases were compared within the cohort using a paired t-test and a 2-sided t-test was used comparing to the CT-based platform. RESULTS Comparing the left and right breast cohort across all platforms, the CT-based ART system showed a signification dose reduction in Dmean (p<0.001 for all platforms), Dmax (p<0.001 for left breast, p<0.03 for right breast) and V9 Gy (p<0.004 for left breast, p<0.001 for right breast) to the ipsilateral lung, V15 Gy (p<0.004 for left breast cohort) to the ipsilateral breast, and Dmax to the contralateral breast (p<0.001) and ribs (p = 0.01, p<0.001, p = 0.01 for CBCT-ART, MRI-ART, and non-ART for left breast cohort only). On average, the MR-Linac platform showed the least degree of OAR sparing across nearly all dosimetric parameters evaluated when compared to all modalities, especially for contralateral lung Dmean and Dmax (p<0.05 for all dosimetric parameters for all platforms) and contralateral breast Dmax (p<0.003 for all platforms). The CBCT-based platform showed superior dose reduction in contralateral lung mean (p<0.03 for all platforms) and heart Dmean (p = 0.065, p<0.001, p = 0.045 for non-adaptive, MRI-ART, and CT-ART for left breast and p<0.008 for right breast). PTV coverage was comparable across all platforms, averaging at approximately 95%. The CT-based ART platform showed a significantly reduced gradient index relative to the CBCT- and MRI-based platforms (p<0.001). CONCLUSION For SPBI treatments, the CT-based ART platforms displayed a higher degree of OAR sparing for many of the dosimetric parameters recorded relative to the other ART and non-ART platforms presented. The MRI-based system typically showed less reduced OAR sparing; however, the advantage of the system is shown if soft tissue contrast is needed. PTV coverage remained comparable across all platforms.
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Affiliation(s)
- Y Gonzalez
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - L Chen
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - H Lee
- Washington University School of Medicine in St. Louis, St. Louis, MO
| | - N Kim
- Vanderbilt University Department of Radiation Oncology, Nashville, TN
| | - M Arbab
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - P G Alluri
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - Y Zhang
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - T D Chiu
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Z Iqbal
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - T Zhuang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - B Cai
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - H Kim
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - A Pompos
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - S B Jiang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - A R Godley
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - R D Timmerman
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - M H Lin
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - A S Rahimi
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - D D M Parsons
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
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Surucu M, Vitzthum L, Chang DT, Gensheimer MF, Kovalchuk N, Han B, Pham D, Da Silva A, Narayanan M, Aksoy D, Feghali K, Shirvani SM, Maniyedath A, Cai B, Pompos A, Dan T, Öz OK, Iyengar P, Timmerman RD, Garant A. Workflow Considerations for Biology-Guided Radiotherapy (BgRT) Implementation. Int J Radiat Oncol Biol Phys 2023; 117:e441. [PMID: 37785431 DOI: 10.1016/j.ijrobp.2023.06.1618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Biology-guided radiotherapy (BgRT) is a novel platform that combines real-time PET imaging with a 6MV Linac to target tumors. The performance and safety of BgRT was assessed in the BIOGUIDE-X clinical trial. This study aims to report on the BgRT workflow steps and assess the time required for each step of the BgRT process during this trial. MATERIALS/METHODS A total of nine patients were enrolled in the second Cohort of the BIOGUIDE-X study which included patients treated with stereotactic body radiotherapy (SBRT) for lung tumors (5) and bone tumors (4). The pre-treatment BgRT workflow includes CT simulation, contouring, imaging-only (BgRT Modeling) PET acquisition, BgRT planning, patient specific QA and plan approval. The imaging-only PET acquisition on the X1 collects a representative PET volumetric 3D image and is an input to develop the BgRT treatment plan. The steps during the BgRT delivery session are kVCT localization, PET pre-scan, PET evaluation and BgRT delivery. The PET PreScan is a 1-pass short-duration PET acquisition that is used to confirm that the PET biodistribution on the day of treatment is consistent with that of the imaging-only PET. During BIOGUIDE-X, the BgRT delivery step was replaced by a 4-pass long-PET acquisition that was used to emulate the expected BgRT dose distribution without turning the beam on. To assess BgRT workflow, times from 18F-FDG injection to image-only PET acquisition, 18F-FDG injection to PET pre-scan, Pre-scan to PET evaluation, and PET evaluation to BgRT delivery (long PET acquisition) were recorded. RESULTS Time between the 18F-FDG injection and the X1 imaging-only PET scan was 84 ± 19 minutes which includes time for 18F-FDG update. Average time to perform imaging-only PET scan was 26 ± 4 minutes. During the BgRT 'delivery' session, the mean time between the kVCT acquisition and PET pre-scan acquisition was 7 ± 3 minutes. The mean time to acquire a 1-pass PET pre-scan was 6 ± 1 then followed by 6 ± 1 minutes for the PET pre-scan dose calculation to estimate the BgRT doses that it would have delivered for this fraction. On average, the PET reconstruction, the PET signal localization verification and the evaluation of safety metrics took 11 ± 4 minutes. The mean time for BgRT 'delivery' was 27 ± 5 minutes based on the 4-pass long PET acquisition. Time from the start of the BgRT session to the end of the BgRT 'delivery' with this version of the investigative product release was 65 ± 9 minutes. CONCLUSION The new processes introduced by the BgRT technology were evaluated and found clinically feasible. Improvements are being undertaken to shorten the time required for each step and to increase patient comfort ahead of BgRT clinical implementation.
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Affiliation(s)
- M Surucu
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - L Vitzthum
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - D T Chang
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA; Department of Radiation Oncology, Michigan Medicine, Ann Arbor, MI
| | - M F Gensheimer
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - N Kovalchuk
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - B Han
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | - D Pham
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA
| | | | | | - D Aksoy
- RefleXion Medical, Inc., Hayward, CA
| | - K Feghali
- RefleXion Medical, Inc., Hayward, CA
| | | | | | - B Cai
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - A Pompos
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - T Dan
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - O K Öz
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - P Iyengar
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
| | - R D Timmerman
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
| | - A Garant
- University of Texas Southwestern Department of Radiation Oncology, Dallas, TX
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20
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Zhang D, Wang Q, Song S, Chen S, Li M, Shen L, Zheng S, Cai B, Wang S, Zheng H. Machine learning approaches reveal highly heterogeneous air quality co-benefits of the energy transition. iScience 2023; 26:107652. [PMID: 37680462 PMCID: PMC10480617 DOI: 10.1016/j.isci.2023.107652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 01/18/2023] [Accepted: 08/14/2023] [Indexed: 09/09/2023] Open
Abstract
Estimating health benefits of reducing fossil fuel use from improved air quality provides important rationales for carbon emissions abatement. Simulating pollution concentration is a crucial step of the estimation, but traditional approaches often rely on complicated chemical transport models that require extensive expertise and computational resources. In this study, we develop a machine learning framework that is able to provide precise and robust annual average fine particle (PM2.5) concentration estimations directly from a high-resolution fossil energy use dataset. Applications of the framework with Chinese data reveal highly heterogeneous health benefits of avoiding premature mortality by reducing fossil fuel use in different sectors and regions in China with a mean of $19/tCO2 and a standard deviation of $38/tCO2. Reducing rural and residential coal use offers the highest co-benefits with a mean of $151/tCO2. Our findings prompt careful policy designs to maximize cost-effectiveness in the transition toward a carbon-neutral energy system.
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Affiliation(s)
- Da Zhang
- Institute of Energy, Economy, and Environment, Tsinghua University, Beijing, China
- Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Qingyi Wang
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Shaojie Song
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
- CMA-NKU Cooperative Laboratory for Atmospheric Environment Health Research, Tianjin 300350, China
- Harvard-China on Energy, Economy, and Environment, Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Simiao Chen
- Heidelberg Institute of Global Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Mingwei Li
- Institute of Energy, Economy, and Environment, Tsinghua University, Beijing, China
- Center for Policy Research on Energy and the Environment, Princeton University, Princeton, NJ, USA
| | - Lu Shen
- Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, China
| | - Siqi Zheng
- Department of Urban Studies and Planning, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Bofeng Cai
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, China
| | - Shenhao Wang
- Department of Urban Studies and Planning, Massachusetts Institute of Technology, Cambridge, MA, USA
- Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Haotian Zheng
- CMA-NKU Cooperative Laboratory for Atmospheric Environment Health Research, Tianjin 300350, China
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, China
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21
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Dong J, Cai B, Zhang S, Wang J, Yue H, Wang C, Mao X, Cong J, Guo F. Closing the Gap between Carbon Neutrality Targets and Action: Technology Solutions for China's Key Energy-Intensive Sectors. Environ Sci Technol 2023; 57:4396-4405. [PMID: 36942443 DOI: 10.1021/acs.est.2c08171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Facing significant carbon emissions annually, China requires a clear decarbonization strategy to meet its climate targets. This study presents a MESSAGEix-CAEP model to explore Chinese decarbonization pathways and their cost-benefit under two mitigation scenarios by establishing connections between five energy-intensive sectors based on energy and material flows. The results indicated the following: 1) Interaction and feedback between sectors should not be disregarded. The electrification process of the other four sectors was projected to increase electricity production by 206%, resulting in a higher power demand than current forecasts. 2) The marginal abatement cost to achieve carbon neutrality across all five sectors was 2189 CNY/tCO2, notably higher than current Chinese carbon emission trading prices. 3) The cost-benefit analysis indicates that a more ambitious abatement strategy would decrease the marginal abatement cost and result in a higher net carbon abatement benefit. The cumulative net benefit of carbon reduction was 7.8 trillion CNY under ambitious mitigation scenario, 1.3 trillion CNY higher than that under current Chinese mitigation scenario. These findings suggest that policy-makers should focus on the interaction effects of decarbonization pathways between sectors and strengthen their decarbonization efforts to motivate early carbon reduction.
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Affiliation(s)
- Jinchi Dong
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Bofeng Cai
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Shaohui Zhang
- School of Economics and Management, Beihang University, Beijing 100191, China
- International Institute for Applied Systems Analysis, Schlossplatz 1, A-2361 Laxenburg, Austria
| | - Jinnan Wang
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, Jiangsu 210023, China
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Hui Yue
- Center for Energy, Environment & Economy Research, School of Management, Zhengzhou University, Zhengzhou 450001, China
- Copernicus Institute of Sustainable Development, Utrecht University, Princetonlaan 8a, 3584 CB Utrecht, Netherlands
| | - Can Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 100084, China
| | - Xianqiang Mao
- School of Environment, Beijing Normal University, Beijing 100875, China
| | - Jianhui Cong
- School of Economics and Management, Shanxi University, Taiyuan 030000, China
| | - Fei Guo
- International Institute for Applied Systems Analysis, Schlossplatz 1, A-2361 Laxenburg, Austria
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22
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Wu Q, Han L, Li S, Wang S, Cong Y, Liu K, Lei Y, Zheng H, Li G, Cai B, Hao J. Facility-Level Emissions and Synergistic Control of Energy-Related Air Pollutants and Carbon Dioxide in China. Environ Sci Technol 2023; 57:4504-4512. [PMID: 36877596 DOI: 10.1021/acs.est.2c07704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Boilers involve ∼60% of primary energy consumption in China and emit more air pollutants and CO2 than any other infrastructures. Here, we established a nationwide, facility-level emission data set considering over 185,000 active boilers in China by fusing multiple data sources and jointly using various technical means. The emission uncertainties and spatial allocations were significantly improved. We found that coal-fired power plant boilers were not the most emission-intensive boilers with regard to SO2, NOx, PM, and mercury but emitted the highest CO2. However, biomass- and municipal waste-fired combustion, regarded as zero-carbon technologies, emitted a large fraction of SO2, NOx, and PM. Future biomass or municipal waste mixing in coal-fired power plant boilers can make full use of the advantages of zero-carbon fuel and the pollution control devices of coal-fired power plants. We identified small-size boilers, medium-size boilers using circulating fluidized bed boilers, and large-size boilers located in China's coal mine bases as the main high emitters. Future focuses on high-emitter control can substantially mitigate the emissions of SO2 by 66%, NOx by 49%, PM by 90%, mercury by 51%, and CO2 by 46% at the most. Our study sheds light on other countries wishing to reduce their energy-related emissions and thus the related impacts on humans, ecosystems, and climates.
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Affiliation(s)
- Qingru Wu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Licong Han
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Shengyue Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Yan Cong
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Kaiyun Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Yu Lei
- Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Haotian Zheng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Guoliang Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Bofeng Cai
- Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Jiming Hao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
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23
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Cai B, Wilson A. A205 EVALUATING THE ASSOCIATION BETWEEN PERIPHERAL BLOOD EOSINOPHILS AND DRUG RESPONSE IN CROHN'S DISEASE: CONTINUING ANALYSIS. J Can Assoc Gastroenterol 2023. [PMCID: PMC9991192 DOI: 10.1093/jcag/gwac036.205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/09/2023] Open
Abstract
Background Th2 cytokines, IL-5 and IL-13 enhance peripheral and mucosal eosinophil survival, recruitment and degranulation, facilitating inflammation in Crohn's Disease. In a preliminary analysis, peripheral eosinophilia (PBE) is seen to have an association with rates of steroid response and anti-TNF response in CD patients. Participants with high PBE (> 200 cells/μL) appear to be more steroid-responsive but less responsive to Th1-targeting anti-TNF therapies. We hypothesize the pattern of PBE at CD diagnosis can help identify distinct subsets within a larger CD population and correlate with response to treatments such as prednisone or anti-TNFs. Purpose We aim to evaluate the pattern of PBE of CD patients at time of diagnosis (prior to drug exposure) and with each subsequent treatment; and if baseline PBE or any changes seen with drug exposures are predictive of treatment response. Method A retrospective cohort study is ongoing with CD patients exposed to glucocorticoids and an anti-TNF seen at 3 hospitals affiliated with University of Western Ontario. Patients were identified using administrative databases and reviewed for biochemical data (complete blood count) and disease activity (Harvey Bradshaw Index) at baseline, before and after each drug exposure. Participants were classified as having high PBE (eosinophils>200 cells/μL) versus low PBE (eosinophils <200 cells/μL). To date, 350 patients have been screened. Subgroup analyses of PBE > 300 cells/μL, and differences between female and male patients will be carried out. Result(s) 46 of 200 CD patients are included in the continuing analysis with a mean age of 45 years. 26 had PBE >200 cells/μL at baseline and 20 did not. The median number therapies used was 4 (IQR=0.75). All received glucocorticoids followed by an anti-TNF. There was no difference in the occurrence of hospitalization or surgery between the two groups. Overall 50% participants with high PBE >200 and >300 cells/μL had clinical response to glucocorticoid exposure, seen as a 3-point decrease in HBI compared to 45%, 47% in the low PBE cohort (n=13/26 vs. n=9/20 p=0.77; n=6/12 vs. n=16/34 p=1.0 respectively). With subsequent anti-TNF exposure, PBE rebounded in 7 participants. 36% patients in the high PBE group required anti-TNF dose escalation versus 24% in the low PBE group (n=9/25 vs. n=5/21, p=0.52). The proportion of patients with anti-TNF discontinuation was similar in both groups (high PBE 19.2%, n=5/26 vs. low PBE 15%, n=3/20, p=1.0). Men had higher steroid response rates compared to women in both high and low PBE groups (n=6/8 vs. n=8/18 p=0.21; n=4/9 vs. 4/11 p=1.0 respectively). Conclusion(s) Peripheral eosinophilia is seen in varying degrees in CD patients. Participants with high PBE are more steroid-responsive. High PBE patients overall were less responsive to anti-TNF therapies, requiring more dose-escalation and discontinued anti-TNF treatment. Completion of this study will help clarify the association between PBE in CD and treatment response. Please acknowledge all funding agencies by checking the applicable boxes below None Disclosure of Interest None Declared
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Affiliation(s)
- B Cai
- Gastroenterology, Western University, London, Canada
| | - A Wilson
- Gastroenterology, Western University, London, Canada
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24
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Cai B, Arnold Egloff S, Goyal R, Cai B, Caro N, Frost M, Mahmud S, Ansquer V, Davis K, Brisbin L, Lisi M, McKenzie A, Paulson S. PP01.63 Real-World Assessment of Clinical Outcomes Associated with Immunotherapy (IO) and chemotherapy in Non–Small Cell Lung Cancer (NSCLC) Patients with Brain Metastases and METexon14 Skipping Mutations Treated in US Community Centers. J Thorac Oncol 2023. [DOI: 10.1016/j.jtho.2022.09.089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
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25
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Zhang L, Niu M, Zhang Z, Huang J, Pang L, Wu P, Lv C, Liang S, Du M, Li M, Cao L, Lei Y, Cai B, Zhu Y. A new method of hotspot analysis on the management of CO 2 and air pollutants, a case study in Guangzhou city, China. Sci Total Environ 2023; 856:159040. [PMID: 36174686 DOI: 10.1016/j.scitotenv.2022.159040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 09/05/2022] [Accepted: 09/22/2022] [Indexed: 06/16/2023]
Abstract
Emission inventory plays an important role in designing effective emission control strategies. Currently, there is unbalanced development of CO2 and air pollutant emission inventories in China and the spatial information of both cannot be obtained simultaneously, which prevents a collaborative control strategy. In this study, we developed a unified emission inventory including both CO2 and air pollutants, then utilized spatial mapping methods to identify the co-hotspots of both CO2 and air pollutants at a high spatial resolution (1 × 1 km2). We applied Guangzhou city as a case study to illustrate the method. The results showed that CO2 and air pollutants were mainly emitted from the stationary combustion sector and the transportation sector. These two sectors contributed 95 %, 67 %, and 93 % to total CO2, SO2, and NOx emissions, respectively. Up to 86 %, 86 %, 66 %, and 72 % of total CO2, SO2, NOx, and PM2.5 emissions were attributed to the top 10 % emission grids with 1 × 1 km2 resolution. However, our results showed high emission grids were not surrounded by other high emissions grids for all types of emissions analyzed in this study. The co-hotspot analysis enables accurate identification of high-emission grids, which helps environment managers to prioritize resource allocation when designing control strategies. Our study underscores the importance of managing CO2 and air pollutants simultaneously at the city level.
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Affiliation(s)
- Li Zhang
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China; Institute of Environment and Sustainability, University of California Los Angeles, Los Angeles, CA 90095, United States
| | - Muchuan Niu
- Department of Environmental Health Sciences, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA 90095, United States
| | - Zhe Zhang
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Jizhang Huang
- Guangzhou Research Institute of Environmental Protection, Guangzhou, Guangdong 510620, China
| | - Lingyun Pang
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Pengcheng Wu
- School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Cheng Lv
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Sen Liang
- School of Land Science and Technology, China University of Geosciences, Beijing 100083, China
| | - Mengbing Du
- Department of Public Policy, City University of Hong Kong, Kowloon Tong, Hong Kong 999077, China
| | - Mingyu Li
- School of Environment, Tsinghua University, Beijing 100084, China
| | - Libin Cao
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Yu Lei
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China.
| | - Bofeng Cai
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China.
| | - Yifang Zhu
- Institute of Environment and Sustainability, University of California Los Angeles, Los Angeles, CA 90095, United States; Department of Environmental Health Sciences, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA 90095, United States.
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26
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Li F, Li F, Cai B, Lv C. Mapping carbon emissions of China's domestic air passenger transport: From individual cities to intercity networks. Sci Total Environ 2022; 851:158199. [PMID: 36028026 DOI: 10.1016/j.scitotenv.2022.158199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 07/15/2022] [Accepted: 08/18/2022] [Indexed: 06/15/2023]
Abstract
As a significant carbon emission source with high growth potential, the air transport sector plays a crucial role in China's decarbonisation efforts. However, the spatial pattern and evolutionary dynamics of aviation carbon emissions in China have not been thoroughly studied. This study proposed a framework to reveal the spatial characteristics and influencing factors of aviation carbon emissions at the city level. Using data from 2019 to construct the aviation carbon emissions network of China (ACENC), the novelty of the study lies in the subdivision of carbon emissions of air passenger transport into cities and intercity lines in China, which helps to reveal the spatial characteristics of individual cities in the intercity network. Beijing, Shanghai, Shenzhen, Chengdu, and Guangzhou were the cities with the highest carbon emissions, and the routes between these cities caused a significant amount of carbon emissions. >80 % of the total carbon emissions can be attributed to two communities in the network, owing to their large size and strong connections. Correlation analysis indicates that a city's carbon emissions are significantly related to its demographic and economic attributes as well as its connection with other cities, while a city's carbon emission intensity may be influenced by its centrality in the whole network and the structure of the community to which it belongs. Overall, the presented results provide directions for stakeholders and policymakers to regulate carbon emissions from air transportation.
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Affiliation(s)
- Fangyi Li
- School of Management, Hefei University of Technology, Hefei 230009, China; Key Laboratory of Process Optimization and Intelligent Decision-making, Hefei University of Technology, Ministry of Education, Hefei 230009, China.
| | - Fei Li
- School of Management, Hefei University of Technology, Hefei 230009, China; Key Laboratory of Process Optimization and Intelligent Decision-making, Hefei University of Technology, Ministry of Education, Hefei 230009, China
| | - Bofeng Cai
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China.
| | - Chen Lv
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China.
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27
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Fan ZX, Wang CB, Fang LL, Cai B, Yuan P, Niu TT, Ma L, Yuan GB, Liu GZ. [Clinical features, risk factors and prognosis of idiopathic dilated cardiomyopathy complicated by ischemic stroke]. Zhonghua Yi Xue Za Zhi 2022; 102:3592-3597. [PMID: 36480862 DOI: 10.3760/cma.j.cn112137-20220427-00949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Objective: To analyze the clinical features, risk factors and prognosis of idiopathic dilated cardiomyopathy (DCM) complicated with ischemic stroke (IS) (DCM-IS). Methods: The clinical data of patients with idiopathic DCM (n=613) in Beijing Anzhen Hospital, Liangxiang Hospital and Fuxing Hospital from January 2016 to December 2020 were retrospectively collected, and among them, 123 cases were DCM-IS. Clinical features of patients with DCM-IS were summarized and multivariate logistic regression model was utilized to analyze the independent risk factors of DCM-IS. Furthermore, 1-year follow-up was conducted and Kaplan-Meier curve was adopted to analyze the prognosis of DCM, using all-cause death and heart transplantation as adverse outcomes. Results: Among the 70 patients with DCM-IS, 6 patients (8.6%, 6/70) were in accordance with the subtype of large artery atherosclerosis, and 47 patients (67.1%, 47/70) were in line with the subtype of cardiogenic embolism, and small artery occlusion subtype (ie, lacunar infarction) were detected in 17 cases (24.3%, 17/70). Hypertension [odds ratio (OR)=1.617, 95% confidence interval (CI): 1.049-2.491, P=0.029], hyperlipidemia (OR=1.918, 95%CI: 1.198-3.073, P=0.007), atrial fibrillation (AF) (OR=1.617, 95%CI: 1.016-2.572, P=0.043), lower estimated glomerular filtration rate (eGFR) (OR=0.986, 95%CI: 0.977-0.996, P=0.005) and a higher incidence of intracardiac thrombus (OR=6.127, 95%CI: 3.174-11.827, P<0.001) were risk factors for DCM-IS. The overall 1-year survival rate was lower in DCM-IS patients (70.7%) than DCM patients without stroke (83.6%, P=0.004), and the main causes of death included obstinate heart failure (3 cases of DCM-IS, and 5 cases of non-DCM-IS) and malignant arrhythmia (DCM-IS) (22 cases of DCM-IS, and 18 cases of non-DCM-IS). Conclusions: Among IS patients with idiopathic DCM, cardioembolism is the most common, followed by lacunar infarction, and the large-artery atherosclerotic subtype is the least common.Hypertension, hyperlipidemia, AF, lower eGFR value and higher incidence of intracardiac thrombus are risk factors for DCM-IS. DCM patients complicated with IS have poor short-term prognosis, and obstinate heart failure and malignant arrhythmia are their main causes of death.
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Affiliation(s)
- Z X Fan
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China
| | - C B Wang
- Department of Neurology, Liangxiang Hospital, Fangshan District, Beijing, Beijing 102400, China
| | - L L Fang
- Department of Neurology, Fuxing Hospital, Capital Medical University, Beijing 100045, China
| | - B Cai
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China
| | - P Yuan
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China
| | - T T Niu
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China
| | - L Ma
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China
| | - G B Yuan
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China
| | - G Z Liu
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China
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28
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Zhang Z, Cao L, Dong H, Cai B, Geng Y, Pang L, Tang Y. Allocating China's 2025 CO 2 emission burden shares to 340 prefecture cities: methods and findings. Environ Sci Pollut Res Int 2022; 29:90671-90685. [PMID: 35871202 DOI: 10.1007/s11356-022-22052-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 07/12/2022] [Indexed: 06/15/2023]
Abstract
Peak emission is an important policy/scheme for all the countries to respond greenhouse gas mitigation. The key is how to distribute the emission burden shares to its sub-regions. This study aims to develop a prefecture city leveled CO2 emission allocation model by integrating multi-indicators method and benchmark method so that China's 2025 (end year of 14th Five-Year Plan, FYP) CO2 emission burdens can be allocated to its prefecture cities and provinces. Results show that China's total CO2 emission will reach 12 billion tons in 2025. The majority of such emission will occur in the east China due to its more developed economy and dense population. Cities with high emissions are usually allocated more emission quotas, such as Shanghai, Tianjin, Chongqing, Tangshan, Yulin, Suzhou, and Ningbo. The top five provinces with higher CO2 emission quotas are traditionally high-emission and energy-intensive provinces, including Shandong, Jiangsu, Inner Mongolia, Henan, and Hebei. The national CO2 emission intensity will decrease by 69.35% in 2025 compared to the 2005 level. The CO2 emission intensity reduction rates among the 340 Chinese cities is found to be fluctuating significantly from 16 to 74% during the 14th FYP. Finally, policy recommendations are raised for mitigating city level CO2 emissions by considering the local realities.
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Affiliation(s)
- Zhe Zhang
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100012, China
- China-UK Low Carbon College, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Libin Cao
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100012, China
| | - Huijuan Dong
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
- Shanghai Engineering Research Center of Solid Waste Treatment and Resource Recovery, Shanghai Jiao Tong University, Shanghai, 200240, China.
| | - Bofeng Cai
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100012, China
| | - Yong Geng
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
- Shanghai Engineering Research Center of Solid Waste Treatment and Resource Recovery, Shanghai Jiao Tong University, Shanghai, 200240, China
- School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai, 200030, China
| | - Lingyun Pang
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100012, China
| | - Yiqi Tang
- School of Public Affairs, Zhejiang University, Hangzhou, 310058, China
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29
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Gao Y, Zhang L, Huang A, Kou W, Bo X, Cai B, Qu J. Unveiling the spatial and sectoral characteristics of a high-resolution emission inventory of CO 2 and air pollutants in China. Sci Total Environ 2022; 847:157623. [PMID: 35901902 DOI: 10.1016/j.scitotenv.2022.157623] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Revised: 07/18/2022] [Accepted: 07/21/2022] [Indexed: 06/15/2023]
Abstract
Under the target of carbon neutrality as well as stringent air quality guideline, understanding the spatial characteristics of both greenhouse gases and air pollutants emissions, in particular of their mutual sources, is crucial for assessing the feasibility of achieving their concomitant emission control, which, nevertheless, remains to be unclear yet. To this end, we construct a high-resolution (10 km × 10 km) emission inventory including both CO2 and air pollutants in China, which fosters us an opportunity to examine their spatial and sectoral characteristics. The primary sources for both CO2 and air pollutant emissions are power and industry. Among different subsectors in industry, detailed information indicates cement, iron and steel are the major subsectors for both CO2 and majority of air pollutants. Analysis of the high-resolution spatial distribution indicates that for CO2, 5 % of the grids account for 90 % of the total CO2 emissions, indicative of the existence of spatial heterogeneity. These grids are the major locations with air pollutant emissions as well, i.e., 73 % for SO2 emissions, and more than 50 % for volatile organic compounds (VOCs), CO, NOx, PM10 and PM2.5, stressing the spatial consistency between greenhouse gases and air pollutant emissions. A large portion of emissions concentrate in a relatively small number of grids further implies the possibility to achieve the mutual control of both greenhouse gas emissions and air pollutant emissions, which is useful for future policy in particular of achieving the carbon neutrality and air quality improvement.
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Affiliation(s)
- Yang Gao
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266100, China
| | - Lei Zhang
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266100, China
| | - Aishi Huang
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266100, China
| | - Wenbin Kou
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, Key Laboratory of Marine Environment and Ecology, Ministry of Education, Ocean University of China, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266100, China
| | - Xin Bo
- Department of Environmental Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China; BUCT Institute for Carbon-Neutrality of Chinese Industries, Beijing 100029, China.
| | - Bofeng Cai
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China.
| | - Jiabao Qu
- Appraisal Center for Environment and Engineering, Ministry of Ecology and Environment, Beijing 100012, China
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Meng B, Dohopolski M, Bai T, Jiang S, Cai B, Lin M. Quantifying AI Assisted Auto-Segmentations Performance for a Clinical Online Adaptive Radiotherapy System in Multiple Treatment Sites. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.2280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Montalvo S, Kim D, Nwachukwu C, Alluri P, Parsons D, Lin M, Cai B, Zhuang T, Hrycushko B, Chen L, Timmerman R, Rahimi A. Real-Time Online Adaptation for Accelerated Partial Breast Irradiation Significantly Improves Target Coverage without Compromising Organs at Risk. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.2281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
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Gonzalez Y, Meng B, Parsons D, Hrycushko B, Zhuang T, Cai B, Zhang Y, Westover K, Lin M, Iyengar P. Initial Clinical Experience of CBCT-Based Adaptive Online Radiotherapy for SAbR of Thoracic Malignancies. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.2276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
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Zhao H, Meng B, Dohopolski M, Choi B, Liang X, Bai T, Nguyen D, Cai B, Lin M, Jiang S. Segmentation of Targets and Organs at Risk for CBCT-Based Online Adaptive Radiotherapy Using Recurrent Neural Networks: A Clinical Evaluation. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.2197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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34
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Wang K, Morgan H, Yan Y, Desai N, Hannan R, Chambers E, Dohopolski M, Cai B, Lin M, Sher D, Wang J, Wang A, Jiang S, Timmerman R, Park J, Garant A. Time Dependence of Coverage of the Prostatic Fossa: Implications for Daily Adaptive Radiotherapy. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.2296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
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Li K, Cai B, Wang Z. Accessing the Climate Change Impacts in China through a Literature Mapping. Int J Environ Res Public Health 2022; 19:13411. [PMID: 36293988 PMCID: PMC9603466 DOI: 10.3390/ijerph192013411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 10/12/2022] [Accepted: 10/14/2022] [Indexed: 06/16/2023]
Abstract
In the 21st century, carbon dioxide emissions have led to adverse climate changes; meanwhile, the impact of climate change has imposed challenges worldwide, particularly in developing countries, and China is one of the most affected countries. Assessing the impact of climate change requires handling a large amount of data in the literature comprehensively. In this study, a text-based classification method and literature mapping were used to process the massive literature and map it according to its location. A total of 39,339 Chinese academic studies and 36,584 Chinese master's and doctoral theses, from 2000 to 2022, with evidence of the impact of climate change were extracted from the China National Knowledge Infrastructure database. Our results show that the literature on climate change impacts has exploded during the last decades. This indicates that increasing attention to the intensified impact of climate change in China has been paid. More importantly, by mapping the geolocation of the literature into spatial grid data, our results show that over 36.09% of the land area shows clear evidence of climate change. Those areas contribute to 89.29% of the gross domestic product (GDP) and comprise 85.06% of the population in China. Furthermore, the studies we collected on the climate change impacts showed a huge spatial heterogeneity. The hotspot areas of research were generally located in developed regions, such as the BTH urban agglomeration and Yangtze River Economic Zone, major agricultural production areas such as Shandong and Henan, and ecologically fragile regions including Yunnan, Xinjiang, and Inner Mongolia. Considering the imbalance spatially of the evidence of climate change can help in a better understanding of the challenges in China imposed by climate change. Appraising the evidence of climate change is of great significance for adapting to climate change, which is closely related to the natural ecosystem services and human health. This study will provide policy implications for coping with climatic events and guide future research.
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Affiliation(s)
- Keke Li
- College of Resource and Environment, Huazhong Agricultural University, Wuhan 430070, China
| | - Bofeng Cai
- Center for Climate Change and Environmental Policy, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Zhen Wang
- College of Resource and Environment, Huazhong Agricultural University, Wuhan 430070, China
- Interdisciplinary Research Center for Territorial Spatial Governance and Green Development, Huazhong Agricultural University, Wuhan 430070, China
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Zhang L, Wu P, Niu M, Zheng Y, Wang J, Dong G, Zhang Z, Xie Z, Du M, Jiang H, Liu H, Cao L, Pang L, Lv C, Lei Y, Cai B, Zhu Y. A systematic assessment of city-level climate change mitigation and air quality improvement in China. Sci Total Environ 2022; 839:156274. [PMID: 35644391 DOI: 10.1016/j.scitotenv.2022.156274] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Revised: 05/04/2022] [Accepted: 05/23/2022] [Indexed: 06/15/2023]
Abstract
China is facing dual challenges of air pollution and climate change. By using city-level data, we comprehensively assessed air quality and CO2 emission changes from 2015 to 2019 for 335 Chinese cities. We selected important regions for air pollution control and categorized all cities into different classes according to their development levels. Our novel approach revealed new insights on different patterns of changes of PM2.5, O3, and CO2 by region and city class. We found that PM2.5 concentrations decreased remarkably due to mandatory city-level reduction targets, especially in the Beijing-Tianjin-Hebei (-27%) region. Nonetheless, O3 concentrations and CO2 emissions increased in 91% and 69% of Chinese cities, respectively. Observed CO2 emission reductions in more developed cities were mainly due to prominent energy intensity reduction and energy structure improvement. Our study indicates a lack of synergy in air pollution control and CO2 mitigation under current policies in China. To address both challenges holistically, we suggest setting mandatory city-level CO2 emission reduction targets and reinforcing clean energy and energy efficiency measures.
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Affiliation(s)
- Li Zhang
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China; Institute of Environment and Sustainability, University of California Los Angeles, Los Angeles, CA 90095, United States
| | - Pengcheng Wu
- School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Muchuan Niu
- Department of Environmental Health Sciences, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA 90095, United States
| | - Yixuan Zheng
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Junxia Wang
- State Environmental Protection Key Laboratory of Quality Control in Environmental Monitoring, China National Environmental Monitoring Centre, Beijing 100012, China
| | - Guangxia Dong
- State Environmental Protection Key Laboratory of Quality Control in Environmental Monitoring, China National Environmental Monitoring Centre, Beijing 100012, China
| | - Zhe Zhang
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Zixuan Xie
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States
| | - Mengbing Du
- Department of Public Policy, City University of Hong Kong, Kowloon Tong, Hong Kong 999077, China
| | - Hanying Jiang
- School of Environment, Tsinghua University, Beijing 100084, China
| | - Hui Liu
- School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China
| | - Libin Cao
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Lingyun Pang
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Chen Lv
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Yu Lei
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China; Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing 100012, China.
| | - Bofeng Cai
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China.
| | - Yifang Zhu
- Institute of Environment and Sustainability, University of California Los Angeles, Los Angeles, CA 90095, United States; Department of Environmental Health Sciences, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA 90095, United States.
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Liu Y, Cheng Z, Chen AJ, Geng Y, Zhang K, Zhu N, Skitmore M, Cai B, Zhang X, Lou Z. Big disparities in CH4 emission patterns from landfills between the United States and China and their behind driving forces. Fundamental Research 2022. [DOI: 10.1016/j.fmre.2022.08.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
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38
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Meng Y, Cai B, Lan Q, Niu F, Zhang X, Yang Y. Synthesis and Structural Characterization of a Di-nuclear Uranyl Complex with Quinoline-6-carboxylate. CRYSTALLOGR REP+ 2022. [DOI: 10.1134/s1063774522020092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Yang L, Hong S, He C, Huang J, Ye Z, Cai B, Yu S, Wang Y, Wang Z. Spatio-Temporal Heterogeneity of the Relationships Between PM 2.5 and Its Determinants: A Case Study of Chinese Cities in Winter of 2020. Front Public Health 2022; 10:810098. [PMID: 35480572 PMCID: PMC9035510 DOI: 10.3389/fpubh.2022.810098] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 03/21/2022] [Indexed: 11/17/2022] Open
Abstract
Fine particulate matter (PM2.5) poses threat to human health in China, particularly in winter. The pandemic of coronavirus disease 2019 (COVID-19) led to a series of strict control measures in Chinese cities, resulting in a short-term significant improvement in air quality. This is a perfect case to explore driving factors affecting the PM2.5 distributions in Chinese cities, thus helping form better policies for future PM2.5 mitigation. Based on panel data of 332 cities, we analyzed the function of natural and anthropogenic factors to PM2.5 pollution by applying the geographically and temporally weighted regression (GTWR) model. We found that the PM2.5 concentration of 84.3% of cities decreased after lockdown. Spatially, in the winter of 2020, cities with high PM2.5 concentrations were mainly distributed in Northeast China, the North China Plain and the Tarim Basin. Higher temperature, wind speed and relative humidity were easier to promote haze pollution in northwest of the country, where enhanced surface pressure decreased PM2.5 concentrations. Furthermore, the intensity of trip activities (ITAs) had a significant positive effect on PM2.5 pollution in Northwest and Central China. The number of daily pollutant operating vents of key polluting enterprises in the industrial sector (VOI) in northern cities was positively correlated with the PM2.5 concentration; inversely, the number of daily pollutant operating vents of key polluting enterprises in the power sector (VOP) imposed a negative effect on the PM2.5 concentration in these regions. This work provides some implications for regional air quality improvement policies of Chinese cities in wintertime.
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Affiliation(s)
- Lu Yang
- School of Resource and Environment Science, Wuhan University, Wuhan, China
| | - Song Hong
- School of Resource and Environment Science, Wuhan University, Wuhan, China
| | - Chao He
- College of Resources and Environment, Yangtze University, Wuhan, China
| | - Jiayi Huang
- Business School, The University of Sydney, Sydney, NSW, Australia
| | - Zhixiang Ye
- School of Resource and Environment Science, Wuhan University, Wuhan, China
| | - Bofeng Cai
- Center for Climate Change and Environmental Policy, Chinese Academy of Environmental Planning, Beijing, China
| | - Shuxia Yu
- College of Resource and Environment, Huazhong Agricultural University, Wuhan, China
| | - Yanwen Wang
- Economics and Management College, China University of Geosciences, Wuhan, China
| | - Zhen Wang
- College of Resource and Environment, Huazhong Agricultural University, Wuhan, China
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Cai B, Wilson A. A163 EVALUATING THE ASSOCIATION BETWEEN PERIPHERAL BLOOD EOSINOPHILS AND DRUG RESPONSE IN CROHN’S DISEASE: A PRELIMINARY REPORT. J Can Assoc Gastroenterol 2022. [PMCID: PMC8859199 DOI: 10.1093/jcag/gwab049.162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Background Th1, Th2, and Th17 immune pathways are variably activated in inflammatory bowel disease (IBD). The degree to which pathway having a more dominant role in propagating Crohn’s disease (CD) is not considered when selecting a treatment strategy. Th2 cytokines, IL-5 and IL-13 enhance eosinophil survival, recruitment and degranulation, facilitating inflammation. Mucosal eosinophilia has been documented in CD and its presence is a surrogate marker of Th2 pathway activation. Peripheral eosinophilia has an established role in asthma to help prognosticate treatment response to Th2-cytokine-specific therapies. We hypothesize the pattern of peripheral blood eosinophils (PBE) at CD diagnosis will identify distinct subsets within a larger CD population and correlate with response to treatments such as prednisone or anti-TNFs. Aims We aim to evaluate the pattern of PBE of CD patients at time of diagnosis (prior to drug exposure) and with each subsequent treatment; and if baseline PBE or any changes seen with drug exposures are predictive of treatment response. Methods A retrospective cohort study is ongoing with CD patients exposed to glucocorticoids and an anti-TNF seen at one of 3 hospitals affiliated with University of Western Ontario. Patients were identified using administrative databases and reviewed for biochemical data (complete blood count) and disease activity (Harvey Bradshaw Index) at baseline as well as before and after each drug exposure. Participants were classified as having high PBE (eosinophils >200 cells/μl) versus low PBE (eosinophils <200 cells/μl). Results To date,10 of 200 CD patients are included in the preliminary analyses with a mean age of 47. 8 had PBE >200 cells/μL at baseline, while 2 did not. The median number therapies used was 4 (IQR=0.75). All received glucocorticoids followed by an anti-TNF. There was no difference in the occurrence of hospitalization or surgery between the two cohorts. Overall 75% (n=6/8) participants with high PBE had clinical response to glucocorticoid exposure, seen as a 3-point decrease in HBI compared to 0% (n=0/2, p=0.5) in the low PBE cohort. With subsequent anti-TNF exposure, PBE rebounded in 6 participants. More patients in the high PBE group required anti-TNF dose escalation versus the low PBE group (63%, n=5/8 versus 50%, n=1/2, p=0.99). The proportion of patients with anti-TNF discontinuation was similar in both groups (high PBE, 50%, n=4/8 versus low PBE, 50%, n=1/2, p=1.00). Conclusions Peripheral eosinophilia is seen in varying degrees in CD patients. Participants with high PBE appear to be more steroid-responsive which is typical for Th2-mediated pathways. They were less responsive to Th1-targeting anti-TNF therapies, requiring more dose-escalation and discontinued anti-TNF treatment. Completion of this study will help clarify the association between PBE in CD and treatment response. Funding Agencies None
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Affiliation(s)
- B Cai
- Gastroenterology, Western University, London, ON, Canada
| | - A Wilson
- Gastroenterology, Western University, London, ON, Canada
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41
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Adhikari P, Ajaj R, Auty D, Bina C, Bonivento W, Boulay M, Cadeddu M, Cai B, Cárdenas-Montes M, Cavuoti S, Chen Y, Cleveland B, Corning J, Daugherty S, DelGobbo P, Di Stefano P, Doria L, Dunford M, Erlandson A, Farahani S, Fatemighomi N, Fiorillo G, Gallacher D, Garcés E, García Abia P, Garg S, Giampa P, Goeldi D, Gorel P, Graham K, Grobov A, Hallin A, Hamstra M, Hugues T, Ilyasov A, Joy A, Jigmeddorj B, Jillings C, Kamaev O, Kaur G, Kemp A, Kochanek I, Kuźniak M, Lai M, Langrock S, Lehnert B, Levashko N, Li X, Litvinov O, Lock J, Longo G, Machulin I, McDonald A, McElroy T, McLaughlin J, Mielnichuk C, Monroe J, Oliviéro G, Pal S, Peeters S, Pesudo V, Piro MC, Pollmann T, Rand E, Rethmeier C, Retière F, Rodríguez-García I, Roszkowski L, Sanchez García E, Sánchez-Pastor T, Santorelli R, Sinclair D, Skensved P, Smith B, Smith N, Sonley T, Stainforth R, Stringer M, Sur B, Vázquez-Jáuregui E, Viel S, Vincent A, Walding J, Waqar M, Ward M, Westerdale S, Willis J, Zuñiga-Reyes A. Erratum: Constraints on dark matter-nucleon effective couplings in the presence of kinematically distinct halo substructures using the DEAP-3600 detector [Phys. Rev. D
102
, 082001 (2020)]. Int J Clin Exp Med 2022. [DOI: 10.1103/physrevd.105.029901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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42
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Adhikari P, Ajaj R, Alpízar-Venegas M, Auty DJ, Benmansour H, Bina CE, Bonivento W, Boulay MG, Cadeddu M, Cai B, Cárdenas-Montes M, Cavuoti S, Chen Y, Cleveland BT, Corning JM, Daugherty S, DelGobbo P, Di Stefano P, Doria L, Dunford M, Ellingwood E, Erlandson A, Farahani SS, Fatemighomi N, Fiorillo G, Gallacher D, García Abia P, Garg S, Giampa P, Goeldi D, Gorel P, Graham K, Grobov A, Hallin AL, Hamstra M, Hugues T, Ilyasov A, Joy A, Jigmeddorj B, Jillings CJ, Kamaev O, Kaur G, Kemp A, Kochanek I, Kuźniak M, Lai M, Langrock S, Lehnert B, Leonhardt A, Levashko N, Li X, Lissia M, Litvinov O, Lock J, Longo G, Machulin I, McDonald AB, McElroy T, McLaughlin JB, Mielnichuk C, Mirasola L, Monroe J, Oliviéro G, Pal S, Peeters SJM, Perry M, Pesudo V, Picciau E, Piro MC, Pollmann TR, Raj N, Rand ET, Rethmeier C, Retière F, Rodríguez-García I, Roszkowski L, Ruhland JB, Sanchez García E, Sánchez-Pastor T, Santorelli R, Seth S, Sinclair D, Skensved P, Smith B, Smith NJT, Sonley T, Stainforth R, Stringer M, Sur B, Vázquez-Jáuregui E, Viel S, Walding J, Waqar M, Ward M, Westerdale S, Willis J, Zuñiga-Reyes A. First Direct Detection Constraints on Planck-Scale Mass Dark Matter with Multiple-Scatter Signatures Using the DEAP-3600 Detector. Phys Rev Lett 2022; 128:011801. [PMID: 35061499 DOI: 10.1103/physrevlett.128.011801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 10/15/2021] [Accepted: 11/16/2021] [Indexed: 06/14/2023]
Abstract
Dark matter with Planck-scale mass (≃10^{19} GeV/c^{2}) arises in well-motivated theories and could be produced by several cosmological mechanisms. A search for multiscatter signals from supermassive dark matter was performed with a blind analysis of data collected over a 813 d live time with DEAP-3600, a 3.3 t single-phase liquid argon-based detector at SNOLAB. No candidate signals were observed, leading to the first direct detection constraints on Planck-scale mass dark matter. Leading limits constrain dark matter masses between 8.3×10^{6} and 1.2×10^{19} GeV/c^{2}, and ^{40}Ar-scattering cross sections between 1.0×10^{-23} and 2.4×10^{-18} cm^{2}. These results are interpreted as constraints on composite dark matter models with two different nucleon-to-nuclear cross section scalings.
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Affiliation(s)
- P Adhikari
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - R Ajaj
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen's University, Kingston ON K7L 3N6,Canada
| | - M Alpízar-Venegas
- Instituto de Física, Universidad Nacional Autónoma de México, A.P. 20-364, México D.F. 01000, México
| | - D J Auty
- Department of Physics, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada
| | - H Benmansour
- Department of Physics, Engineering Physics, and Astronomy, Queen's University, Kingston, Ontario, K7L 3N6, Canada
| | - C E Bina
- Department of Physics, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen's University, Kingston ON K7L 3N6,Canada
| | | | - M G Boulay
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - M Cadeddu
- Physics Department, Università degli Studi di Cagliari, Cagliari 09042, Italy
- INFN Cagliari, Cagliari 09042, Italy
| | - B Cai
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen's University, Kingston ON K7L 3N6,Canada
| | - M Cárdenas-Montes
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Madrid 28040, Spain
| | - S Cavuoti
- Physics Department, Università degli Studi "Federico II" di Napoli, Napoli 80126, Italy
- Astronomical Observatory of Capodimonte, Salita Moiariello 16, I-80131 Napoli, Italy
- INFN Napoli, Napoli 80126, Italy
| | - Y Chen
- Department of Physics, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada
| | - B T Cleveland
- Department of Physics and Astronomy, Laurentian University, Sudbury, Ontario, P3E 2C6, Canada
- SNOLAB, Lively, Ontario, P3Y 1N2, Canada
| | - J M Corning
- Department of Physics, Engineering Physics, and Astronomy, Queen's University, Kingston, Ontario, K7L 3N6, Canada
| | - S Daugherty
- Department of Physics and Astronomy, Laurentian University, Sudbury, Ontario, P3E 2C6, Canada
| | - P DelGobbo
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen's University, Kingston ON K7L 3N6,Canada
| | - P Di Stefano
- Department of Physics, Engineering Physics, and Astronomy, Queen's University, Kingston, Ontario, K7L 3N6, Canada
| | - L Doria
- PRISMA+, Cluster of Excellence and Institut für Kernphysik, Johannes Gutenberg-Universität Mainz, 55128 Mainz, Germany
| | - M Dunford
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - E Ellingwood
- Department of Physics, Engineering Physics, and Astronomy, Queen's University, Kingston, Ontario, K7L 3N6, Canada
| | - A Erlandson
- Canadian Nuclear Laboratories, Chalk River, Ontario, K0J 1J0, Canada
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - S S Farahani
- Department of Physics, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada
| | - N Fatemighomi
- Royal Holloway University London, Egham Hill, Egham, Surrey TW20 0EX, United Kingdom
- SNOLAB, Lively, Ontario, P3Y 1N2, Canada
| | - G Fiorillo
- Physics Department, Università degli Studi "Federico II" di Napoli, Napoli 80126, Italy
- INFN Napoli, Napoli 80126, Italy
| | - D Gallacher
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - P García Abia
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Madrid 28040, Spain
| | - S Garg
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - P Giampa
- TRIUMF, Vancouver, British Columbia, V6T 2A3, Canada
| | - D Goeldi
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen's University, Kingston ON K7L 3N6,Canada
| | - P Gorel
- Department of Physics and Astronomy, Laurentian University, Sudbury, Ontario, P3E 2C6, Canada
- SNOLAB, Lively, Ontario, P3Y 1N2, Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen's University, Kingston ON K7L 3N6,Canada
| | - K Graham
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - A Grobov
- National Research Centre Kurchatov Institute, Moscow 123182, Russia
- National Research Nuclear University MEPhI, Moscow 115409, Russia
| | - A L Hallin
- Department of Physics, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada
| | - M Hamstra
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - T Hugues
- AstroCeNT, Nicolaus Copernicus Astronomical Center, Polish Academy of Sciences, Rektorska 4, 00-614 Warsaw, Poland
| | - A Ilyasov
- National Research Centre Kurchatov Institute, Moscow 123182, Russia
- National Research Nuclear University MEPhI, Moscow 115409, Russia
| | - A Joy
- Department of Physics, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen's University, Kingston ON K7L 3N6,Canada
| | - B Jigmeddorj
- Canadian Nuclear Laboratories, Chalk River, Ontario, K0J 1J0, Canada
| | - C J Jillings
- Department of Physics and Astronomy, Laurentian University, Sudbury, Ontario, P3E 2C6, Canada
- SNOLAB, Lively, Ontario, P3Y 1N2, Canada
| | - O Kamaev
- Canadian Nuclear Laboratories, Chalk River, Ontario, K0J 1J0, Canada
| | - G Kaur
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - A Kemp
- Department of Physics, Engineering Physics, and Astronomy, Queen's University, Kingston, Ontario, K7L 3N6, Canada
- Royal Holloway University London, Egham Hill, Egham, Surrey TW20 0EX, United Kingdom
| | - I Kochanek
- INFN Laboratori Nazionali del Gran Sasso, Assergi (AQ) 67100, Italy
| | - M Kuźniak
- AstroCeNT, Nicolaus Copernicus Astronomical Center, Polish Academy of Sciences, Rektorska 4, 00-614 Warsaw, Poland
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen's University, Kingston ON K7L 3N6,Canada
| | - M Lai
- Physics Department, Università degli Studi di Cagliari, Cagliari 09042, Italy
- INFN Cagliari, Cagliari 09042, Italy
| | - S Langrock
- Department of Physics and Astronomy, Laurentian University, Sudbury, Ontario, P3E 2C6, Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen's University, Kingston ON K7L 3N6,Canada
| | - B Lehnert
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - A Leonhardt
- Department of Physics, Technische Universität München, 80333 Munich, Germany
| | - N Levashko
- National Research Centre Kurchatov Institute, Moscow 123182, Russia
- National Research Nuclear University MEPhI, Moscow 115409, Russia
| | - X Li
- Physics Department, Princeton University, Princeton, New Jersey 08544, USA
| | - M Lissia
- INFN Cagliari, Cagliari 09042, Italy
| | - O Litvinov
- TRIUMF, Vancouver, British Columbia, V6T 2A3, Canada
| | - J Lock
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - G Longo
- Physics Department, Università degli Studi "Federico II" di Napoli, Napoli 80126, Italy
- INFN Napoli, Napoli 80126, Italy
| | - I Machulin
- National Research Centre Kurchatov Institute, Moscow 123182, Russia
- National Research Nuclear University MEPhI, Moscow 115409, Russia
| | - A B McDonald
- Department of Physics, Engineering Physics, and Astronomy, Queen's University, Kingston, Ontario, K7L 3N6, Canada
| | - T McElroy
- Department of Physics, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada
| | - J B McLaughlin
- Royal Holloway University London, Egham Hill, Egham, Surrey TW20 0EX, United Kingdom
- TRIUMF, Vancouver, British Columbia, V6T 2A3, Canada
| | - C Mielnichuk
- Department of Physics, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada
| | - L Mirasola
- Physics Department, Università degli Studi di Cagliari, Cagliari 09042, Italy
| | - J Monroe
- Royal Holloway University London, Egham Hill, Egham, Surrey TW20 0EX, United Kingdom
| | - G Oliviéro
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen's University, Kingston ON K7L 3N6,Canada
| | - S Pal
- Department of Physics, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen's University, Kingston ON K7L 3N6,Canada
| | - S J M Peeters
- University of Sussex, Sussex House, Brighton, East Sussex BN1 9RH, United Kingdom
| | - M Perry
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - V Pesudo
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Madrid 28040, Spain
| | - E Picciau
- Physics Department, Università degli Studi di Cagliari, Cagliari 09042, Italy
- INFN Cagliari, Cagliari 09042, Italy
| | - M-C Piro
- Department of Physics, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen's University, Kingston ON K7L 3N6,Canada
| | - T R Pollmann
- Department of Physics, Technische Universität München, 80333 Munich, Germany
| | - N Raj
- TRIUMF, Vancouver, British Columbia, V6T 2A3, Canada
| | - E T Rand
- Canadian Nuclear Laboratories, Chalk River, Ontario, K0J 1J0, Canada
| | - C Rethmeier
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - F Retière
- TRIUMF, Vancouver, British Columbia, V6T 2A3, Canada
| | - I Rodríguez-García
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Madrid 28040, Spain
| | - L Roszkowski
- AstroCeNT, Nicolaus Copernicus Astronomical Center, Polish Academy of Sciences, Rektorska 4, 00-614 Warsaw, Poland
- BP2, National Centre for Nuclear Research, ul. Pasteura 7, 02-093 Warsaw, Poland
| | - J B Ruhland
- Department of Physics, Technische Universität München, 80333 Munich, Germany
| | - E Sanchez García
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Madrid 28040, Spain
| | - T Sánchez-Pastor
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Madrid 28040, Spain
| | - R Santorelli
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, Madrid 28040, Spain
| | - S Seth
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen's University, Kingston ON K7L 3N6,Canada
| | - D Sinclair
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - P Skensved
- Department of Physics, Engineering Physics, and Astronomy, Queen's University, Kingston, Ontario, K7L 3N6, Canada
| | - B Smith
- TRIUMF, Vancouver, British Columbia, V6T 2A3, Canada
| | - N J T Smith
- Department of Physics and Astronomy, Laurentian University, Sudbury, Ontario, P3E 2C6, Canada
- SNOLAB, Lively, Ontario, P3Y 1N2, Canada
| | - T Sonley
- SNOLAB, Lively, Ontario, P3Y 1N2, Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen's University, Kingston ON K7L 3N6,Canada
| | - R Stainforth
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
| | - M Stringer
- Department of Physics, Engineering Physics, and Astronomy, Queen's University, Kingston, Ontario, K7L 3N6, Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen's University, Kingston ON K7L 3N6,Canada
| | - B Sur
- Canadian Nuclear Laboratories, Chalk River, Ontario, K0J 1J0, Canada
| | - E Vázquez-Jáuregui
- Department of Physics and Astronomy, Laurentian University, Sudbury, Ontario, P3E 2C6, Canada
- Instituto de Física, Universidad Nacional Autónoma de México, A.P. 20-364, México D.F. 01000, México
| | - S Viel
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen's University, Kingston ON K7L 3N6,Canada
| | - J Walding
- Royal Holloway University London, Egham Hill, Egham, Surrey TW20 0EX, United Kingdom
| | - M Waqar
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen's University, Kingston ON K7L 3N6,Canada
| | - M Ward
- Department of Physics, Engineering Physics, and Astronomy, Queen's University, Kingston, Ontario, K7L 3N6, Canada
- SNOLAB, Lively, Ontario, P3Y 1N2, Canada
| | - S Westerdale
- Department of Physics, Carleton University, Ottawa, Ontario, K1S 5B6, Canada
- INFN Cagliari, Cagliari 09042, Italy
| | - J Willis
- Department of Physics, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada
| | - A Zuñiga-Reyes
- Instituto de Física, Universidad Nacional Autónoma de México, A.P. 20-364, México D.F. 01000, México
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Shi X, Zheng Y, Lei Y, Xue W, Yan G, Liu X, Cai B, Tong D, Wang J. Air quality benefits of achieving carbon neutrality in China. Sci Total Environ 2021; 795:148784. [PMID: 34246132 DOI: 10.1016/j.scitotenv.2021.148784] [Citation(s) in RCA: 71] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 06/22/2021] [Accepted: 06/27/2021] [Indexed: 05/10/2023]
Abstract
Achieving carbon neutrality before 2060 newly announced in China are expected to substantially affect air quality. Here we project the pollutants emissions in China based on a carbon neutrality roadmap and clean air policies evolution; national and regional PM2.5 and O3 concentrations in 2030 (the target year of carbon peak), 2035 (the target year of "Beautiful China 2035" launched by the Chinese government to fundamentally improve air quality) and 2060 (the target year of carbon neutrality) are then simulated using an air quality model. Results showed that compared with 2019, emissions of SO2, NOx, primary PM2.5, and VOCs are projected to reduce by 42%, 42%, 44%, and 28% in 2030, by 57%, 58%, 60%, and 42% in 2035, by 93%, 93%, 90% and 61% in 2060 respectively. Consequently, in 2030, 2035, and 2060, the national annual mean PM2.5 will be 27, 23, and 11 μg m-3; and the 90th percentile of daily 8-h maxima of O3 (O3-8h 90th) will be 129, 123, and 93 μg m-3; 82%, 94%, and 100% of 337 municipal cities will reach the current national air quality standard, respectively. It's expected that the "Beautiful China 2035" target is very likely to be achieved, and about half of the 337 cities will meet the current WHO air quality guideline in 2060. In the near future, strict environmental policies driven by "Beautiful China 2035" are needed due to their substantial contribution to emission reductions. By 2060, the low-carbon policies driven by the carbon neutrality target are expected to contribute to larger than 80% of reductions in PM2.5 and O3-8h 90th concentrations relative to the 2020 levels, implying that more attention could be paid to low-carbon policies after 2035. Our research would provide implications for future co-governance of air pollution and climate change mitigation in China and other developing countries.
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Affiliation(s)
- Xurong Shi
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, 100012 Beijing, China
| | - Yixuan Zheng
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, 100012 Beijing, China
| | - Yu Lei
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, 100012 Beijing, China
| | - Wenbo Xue
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, 100012 Beijing, China; State Environmental Protection Key Laboratory of Environmental Planning and Policy Simulation, Chinese Academy of Environmental Planning, 100012 Beijing, China.
| | - Gang Yan
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, 100012 Beijing, China
| | - Xin Liu
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, 100012 Beijing, China
| | - Bofeng Cai
- Center for Climate Change and Environmental Policy, Chinese Academy of Environmental Planning, 100012 Beijing, China
| | - Dan Tong
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, 100084 Beijing, China
| | - Jinnan Wang
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, 100012 Beijing, China; State Environmental Protection Key Laboratory of Environmental Planning and Policy Simulation, Chinese Academy of Environmental Planning, 100012 Beijing, China.
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44
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Adhikari P, Ajaj R, Alpízar-Venegas M, Amaudruz PA, Auty DJ, Batygov M, Beltran B, Benmansour H, Bina CE, Bonatt J, Bonivento W, Boulay MG, Broerman B, Bueno JF, Burghardt PM, Butcher A, Cadeddu M, Cai B, Cárdenas-Montes M, Cavuoti S, Chen M, Chen Y, Cleveland BT, Corning JM, Cranshaw D, Daugherty S, DelGobbo P, Dering K, DiGioseffo J, Di Stefano P, Doria L, Duncan FA, Dunford M, Ellingwood E, Erlandson A, Farahani SS, Fatemighomi N, Fiorillo G, Florian S, Flower T, Ford RJ, Gagnon R, Gallacher D, García Abia P, Garg S, Giampa P, Goeldi D, Golovko V, Gorel P, Graham K, Grant DR, Grobov A, Hallin AL, Hamstra M, Harvey PJ, Hearns C, Hugues T, Ilyasov A, Joy A, Jigmeddorj B, Jillings CJ, Kamaev O, Kaur G, Kemp A, Kochanek I, Kuźniak M, Lai M, Langrock S, Lehnert B, Leonhardt A, Levashko N, Li X, Lidgard J, Lindner T, Lissia M, Lock J, Longo G, Machulin I, McDonald AB, McElroy T, McGinn T, McLaughlin JB, Mehdiyev R, Mielnichuk C, Monroe J, Nadeau P, Nantais C, Ng C, Noble AJ, O’Dwyer E, Oliviéro G, Ouellet C, Pal S, Pasuthip P, Peeters SJM, Perry M, Pesudo V, Picciau E, Piro MC, Pollmann TR, Rand ET, Rethmeier C, Retière F, Rodríguez-García I, Roszkowski L, Ruhland JB, Sánchez-García E, Santorelli R, Sinclair D, Skensved P, Smith B, Smith NJT, Sonley T, Soukup J, Stainforth R, Stone C, Strickland V, Stringer M, Sur B, Tang J, Vázquez-Jáuregui E, Viel S, Walding J, Waqar M, Ward M, Westerdale S, Willis J, Zuñiga-Reyes A. Pulse-shape discrimination against low-energy Ar-39 beta decays in liquid argon with 4.5 tonne-years of DEAP-3600 data. Eur Phys J C Part Fields 2021; 81:823. [PMID: 34720726 PMCID: PMC8550104 DOI: 10.1140/epjc/s10052-021-09514-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 07/30/2021] [Indexed: 06/13/2023]
Abstract
The DEAP-3600 detector searches for the scintillation signal from dark matter particles scattering on a 3.3 tonne liquid argon target. The largest background comes from 39 Ar beta decays and is suppressed using pulse-shape discrimination (PSD). We use two types of PSD estimator: the prompt-fraction, which considers the fraction of the scintillation signal in a narrow and a wide time window around the event peak, and the log-likelihood-ratio, which compares the observed photon arrival times to a signal and a background model. We furthermore use two algorithms to determine the number of photons detected at a given time: (1) simply dividing the charge of each PMT pulse by the mean single-photoelectron charge, and (2) a likelihood analysis that considers the probability to detect a certain number of photons at a given time, based on a model for the scintillation pulse shape and for afterpulsing in the light detectors. The prompt-fraction performs approximately as well as the log-likelihood-ratio PSD algorithm if the photon detection times are not biased by detector effects. We explain this result using a model for the information carried by scintillation photons as a function of the time when they are detected.
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Affiliation(s)
- P. Adhikari
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - R. Ajaj
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - M. Alpízar-Venegas
- Instituto de Física, Universidad Nacional Autónoma de México, A. P. 20-364, 01000 Mexico, D.F. Mexico
| | | | - D. J. Auty
- Department of Physics, University of Alberta, Edmonton, AB T6G 2R3 Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - M. Batygov
- Department of Physics and Astronomy, Laurentian University, Sudbury, ON P3E 2C6 Canada
| | - B. Beltran
- Department of Physics, University of Alberta, Edmonton, AB T6G 2R3 Canada
| | - H. Benmansour
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - C. E. Bina
- Department of Physics, University of Alberta, Edmonton, AB T6G 2R3 Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - J. Bonatt
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | | | - M. G. Boulay
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - B. Broerman
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - J. F. Bueno
- Department of Physics, University of Alberta, Edmonton, AB T6G 2R3 Canada
| | - P. M. Burghardt
- Department of Physics, Technische Universität München, 80333 Munich, Germany
| | - A. Butcher
- Royal Holloway University London, Egham Hill, Egham, Surrey TW20 0EX UK
| | | | - B. Cai
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - M. Cárdenas-Montes
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, 28040 Madrid, Spain
| | - S. Cavuoti
- Physics Department, Università degli Studi “Federico II” di Napoli, 80126 Naples, Italy
- INFN Napoli, 80126 Naples, Italy
- INAF-Astronomical Observatory of Capodimonte, Salita Moiariello 16, 80131 Naples, Italy
| | - M. Chen
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - Y. Chen
- Department of Physics, University of Alberta, Edmonton, AB T6G 2R3 Canada
| | - B. T. Cleveland
- Department of Physics and Astronomy, Laurentian University, Sudbury, ON P3E 2C6 Canada
- SNOLAB, Lively, ON P3Y 1M3 Canada
| | - J. M. Corning
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - D. Cranshaw
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - S. Daugherty
- Department of Physics and Astronomy, Laurentian University, Sudbury, ON P3E 2C6 Canada
| | - P. DelGobbo
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - K. Dering
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - J. DiGioseffo
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - P. Di Stefano
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - L. Doria
- PRISMA+ Cluster of Excellence and Institut für Kernphysik, Johannes Gutenberg-Universität Mainz, 55128 Mainz, Germany
| | | | - M. Dunford
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - E. Ellingwood
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - A. Erlandson
- Canadian Nuclear Laboratories Ltd, Chalk River, ON K0J 1J0 Canada
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - S. S. Farahani
- Department of Physics, University of Alberta, Edmonton, AB T6G 2R3 Canada
| | | | - G. Fiorillo
- Physics Department, Università degli Studi “Federico II” di Napoli, 80126 Naples, Italy
- INFN Napoli, 80126 Naples, Italy
| | - S. Florian
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - T. Flower
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - R. J. Ford
- Department of Physics and Astronomy, Laurentian University, Sudbury, ON P3E 2C6 Canada
- SNOLAB, Lively, ON P3Y 1M3 Canada
| | - R. Gagnon
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - D. Gallacher
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - P. García Abia
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, 28040 Madrid, Spain
| | - S. Garg
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - P. Giampa
- TRIUMF, Vancouver, BC V6T 2A3 Canada
| | - D. Goeldi
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - V. Golovko
- Canadian Nuclear Laboratories Ltd, Chalk River, ON K0J 1J0 Canada
| | - P. Gorel
- Department of Physics and Astronomy, Laurentian University, Sudbury, ON P3E 2C6 Canada
- SNOLAB, Lively, ON P3Y 1M3 Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - K. Graham
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - D. R. Grant
- Department of Physics, University of Alberta, Edmonton, AB T6G 2R3 Canada
| | - A. Grobov
- National Research Centre Kurchatov Institute, Moscow, 123182 Russia
- National Research Nuclear University MEPhI, Moscow, 115409 Russia
| | - A. L. Hallin
- Department of Physics, University of Alberta, Edmonton, AB T6G 2R3 Canada
| | - M. Hamstra
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - P. J. Harvey
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - C. Hearns
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - T. Hugues
- AstroCeNT, Nicolaus Copernicus Astronomical Center, Polish Academy of Sciences, Rektorska 4, 00-614 Warsaw, Poland
| | - A. Ilyasov
- National Research Centre Kurchatov Institute, Moscow, 123182 Russia
- National Research Nuclear University MEPhI, Moscow, 115409 Russia
| | - A. Joy
- Department of Physics, University of Alberta, Edmonton, AB T6G 2R3 Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - B. Jigmeddorj
- Canadian Nuclear Laboratories Ltd, Chalk River, ON K0J 1J0 Canada
| | - C. J. Jillings
- Department of Physics and Astronomy, Laurentian University, Sudbury, ON P3E 2C6 Canada
- SNOLAB, Lively, ON P3Y 1M3 Canada
| | - O. Kamaev
- Canadian Nuclear Laboratories Ltd, Chalk River, ON K0J 1J0 Canada
| | - G. Kaur
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - A. Kemp
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
- Royal Holloway University London, Egham Hill, Egham, Surrey TW20 0EX UK
| | - I. Kochanek
- INFN Laboratori Nazionali del Gran Sasso, 67100 Assergi, AQ Italy
| | - M. Kuźniak
- AstroCeNT, Nicolaus Copernicus Astronomical Center, Polish Academy of Sciences, Rektorska 4, 00-614 Warsaw, Poland
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - M. Lai
- Physics Department, Università degli Studi di Cagliari, 09042 Cagliari, Italy
- INFN Cagliari, Cagliari, 09042 Italy
| | - S. Langrock
- Department of Physics and Astronomy, Laurentian University, Sudbury, ON P3E 2C6 Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - B. Lehnert
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
- Present Address: Nuclear Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
| | - A. Leonhardt
- Department of Physics, Technische Universität München, 80333 Munich, Germany
| | - N. Levashko
- National Research Centre Kurchatov Institute, Moscow, 123182 Russia
- National Research Nuclear University MEPhI, Moscow, 115409 Russia
| | - X. Li
- Physics Department, Princeton University, Princeton, NJ 08544 USA
| | - J. Lidgard
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | | | - M. Lissia
- INFN Cagliari, Cagliari, 09042 Italy
| | - J. Lock
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - G. Longo
- Physics Department, Università degli Studi “Federico II” di Napoli, 80126 Naples, Italy
- INFN Napoli, 80126 Naples, Italy
| | - I. Machulin
- National Research Centre Kurchatov Institute, Moscow, 123182 Russia
- National Research Nuclear University MEPhI, Moscow, 115409 Russia
| | - A. B. McDonald
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - T. McElroy
- Department of Physics, University of Alberta, Edmonton, AB T6G 2R3 Canada
| | - T. McGinn
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - J. B. McLaughlin
- Royal Holloway University London, Egham Hill, Egham, Surrey TW20 0EX UK
- TRIUMF, Vancouver, BC V6T 2A3 Canada
| | - R. Mehdiyev
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - C. Mielnichuk
- Department of Physics, University of Alberta, Edmonton, AB T6G 2R3 Canada
| | - J. Monroe
- Royal Holloway University London, Egham Hill, Egham, Surrey TW20 0EX UK
| | - P. Nadeau
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - C. Nantais
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - C. Ng
- Department of Physics, University of Alberta, Edmonton, AB T6G 2R3 Canada
| | - A. J. Noble
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - E. O’Dwyer
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - G. Oliviéro
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - C. Ouellet
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - S. Pal
- Department of Physics, University of Alberta, Edmonton, AB T6G 2R3 Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - P. Pasuthip
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - S. J. M. Peeters
- University of Sussex, Sussex House, Brighton, East Sussex BN1 9RH UK
| | - M. Perry
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - V. Pesudo
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, 28040 Madrid, Spain
| | - E. Picciau
- Physics Department, Università degli Studi di Cagliari, 09042 Cagliari, Italy
- INFN Cagliari, Cagliari, 09042 Italy
| | - M.-C. Piro
- Department of Physics, University of Alberta, Edmonton, AB T6G 2R3 Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - T. R. Pollmann
- Department of Physics, Technische Universität München, 80333 Munich, Germany
- Present Address: Nikhef and the University of Amsterdam, Science Park, 1098 XG Amsterdam, The Netherlands
| | - E. T. Rand
- Canadian Nuclear Laboratories Ltd, Chalk River, ON K0J 1J0 Canada
| | - C. Rethmeier
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | | | - I. Rodríguez-García
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, 28040 Madrid, Spain
| | - L. Roszkowski
- AstroCeNT, Nicolaus Copernicus Astronomical Center, Polish Academy of Sciences, Rektorska 4, 00-614 Warsaw, Poland
- BP2, National Centre for Nuclear Research, ul. Pasteura 7, 02-093 Warsaw, Poland
| | - J. B. Ruhland
- Department of Physics, Technische Universität München, 80333 Munich, Germany
| | - E. Sánchez-García
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, 28040 Madrid, Spain
| | - R. Santorelli
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas, 28040 Madrid, Spain
| | - D. Sinclair
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - P. Skensved
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - B. Smith
- TRIUMF, Vancouver, BC V6T 2A3 Canada
| | - N. J. T. Smith
- Department of Physics and Astronomy, Laurentian University, Sudbury, ON P3E 2C6 Canada
- SNOLAB, Lively, ON P3Y 1M3 Canada
| | - T. Sonley
- SNOLAB, Lively, ON P3Y 1M3 Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - J. Soukup
- Department of Physics, University of Alberta, Edmonton, AB T6G 2R3 Canada
| | - R. Stainforth
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - C. Stone
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - V. Strickland
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
| | - M. Stringer
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - B. Sur
- Canadian Nuclear Laboratories Ltd, Chalk River, ON K0J 1J0 Canada
| | - J. Tang
- Department of Physics, University of Alberta, Edmonton, AB T6G 2R3 Canada
| | - E. Vázquez-Jáuregui
- Department of Physics and Astronomy, Laurentian University, Sudbury, ON P3E 2C6 Canada
- Instituto de Física, Universidad Nacional Autónoma de México, A. P. 20-364, 01000 Mexico, D.F. Mexico
| | - S. Viel
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - J. Walding
- Royal Holloway University London, Egham Hill, Egham, Surrey TW20 0EX UK
| | - M. Waqar
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
- Arthur B. McDonald Canadian Astroparticle Physics Research Institute, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - M. Ward
- Department of Physics, Engineering Physics and Astronomy, Queen’s University, Kingston, ON K7L 3N6 Canada
| | - S. Westerdale
- Department of Physics, Carleton University, Ottawa, ON K1S 5B6 Canada
- INFN Cagliari, Cagliari, 09042 Italy
| | - J. Willis
- Department of Physics, University of Alberta, Edmonton, AB T6G 2R3 Canada
| | - A. Zuñiga-Reyes
- Instituto de Física, Universidad Nacional Autónoma de México, A. P. 20-364, 01000 Mexico, D.F. Mexico
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Yao Y, Cai B, Xu LL, Wang JW. [Correlation between neck pressure pain threshold and forward head posture in patients with temporomandibular joint disorders]. Zhonghua Kou Qiang Yi Xue Za Zhi 2021; 56:759-763. [PMID: 34404141 DOI: 10.3760/cma.j.cn112144-20210312-00111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To investigate the association between neck muscles pressure pain thresholds (PPT) and forward head posture (FHP) in patients with temporomandibular disorders (TMD). Methods: A total of 145 TMD patients, including 23 males and 122 females with a median age of 28 years, were enrolled in the Department of Rehabilitation Medicine, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine from December 2019 to April 2020. Informations of FHP and neck muscles PPT were collected for all participants. FHP was characterized by the craniocervical angle (CVA) between C7, the tragus of the ear and the horizontal line. Each of the participants completed a questionaire of the neck disability index (NDI). The patients with CVA≤51 ° were asigned into FHP group, otherwise the patients with CVA>51° were asigned into non-FHP group. PPT were measured at the midpoint of the upper trapezius and 1 cm aside from C5-C6 articular pillars. Nonparametric test and Spearman correlation analysis were conducted for the data analysis. Results: There were 70 patients in the FHP group and 75 patients in the non-FHP group. The trapezius PPT of the FHP group [2.82(0.86) kg] was significantly higher than that of the non-FHP group [2.46(0.80) kg] (P<0.01). No significant differences in PPT and NDI were observed between the two groups (P>0.05). Low correlation was found between trapezius PPT and FHP negatively (r=-0.273, P<0.01) and no correlation was found between C5-C6 PPT and FHP (r=-0.124, P>0.05). PPT in trapezius and C5-C6 was negatively correlated with NDI in moderate (r=-0.301, P<0.01) and low (r=-0.206, P<0.05) levels. Conclusions: The trapezius PPT was correlated with FHP negatively. The more FHP, the more pain tolerant of trapezius muscles. There was no correlation between neck function and FHP directly. The higher threshold was followed by better neck function.
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Affiliation(s)
- Y Yao
- Department of Rehabilitation Medicine, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200001, China
| | - B Cai
- Department of Rehabilitation Medicine, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200001, China
| | - L L Xu
- Department of Rehabilitation Medicine, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200001, China
| | - J W Wang
- Department of Orthopedics, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200001, China
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46
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Cai B. P–797 A novel method for establishing human embryonic stem cells independent of feeder cells. Hum Reprod 2021. [DOI: 10.1093/humrep/deab130.796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Study question
Is there a efficient establishing method of human embryonic stem cells directly from the human blastocysts independent of feeder cells?
Summary answer
We established a novel method of generating human embryonic stem cells directly from human blastocysts independent of feeder layer cells.
What is known already
Establishing embryonic stem cells lines mainly needed to coculture ICM clumps with feeder cells (like mouse or human fibroblasts) ,this brought in potential heterogeneous pollution.Although there had be some reports about generating human ESCs independent of feeder cells,but the efficiency was low and conditioned medium were unstable and also had the biological contamination.
Study design, size, duration
We used ten day5/6 donated human blastocysts from our reproductive center ,most of them were genetically diseased embryos with abnormal PGT diagnosis.After establishing ESCs procedure , all the cell lines were identified with pluripotency and differentiation potential tests.The success rate of system was calculated and compared with the conventional methods.
Participants/materials, setting, methods
In brief, ICM clumps were separated mechanically by using a micromanipulation system,and then transferred to a 30ul mTESR plus culture media drop pretreated with the geltrex (1:100 dilution) matrix and oxygen concentration was 5%. When cells attached and migrated,we also used laser to destroy the remaining trophoblast cells.About 10 days,the typical ES clone can be mechanically passaged and cells can be cultured in normal oxygen concentrations after passage 2. .
Main results and the role of chance
Using this method we had successfully established nine embryonic stem cell lines from donated human blastocysts ,the success rate was 90% (9/10). Each cell lines had passed the evaluation test of embryonic stem cell. When compared with the conventional feeder cells dependent method,our novol methods not only eliminated the pollution from heterogeneous cells,but also had higher success rate (90% vs 25%).
Limitations, reasons for caution
Due to the scarcity of donated human blastocysts, this experiment was a single-center experiment with small samples.
Wider implications of the findings: We speculated that the batch differences of culture dishes, matrix and culture medium might affect the establish efficiency , and how to carry out a high level of quality control work might be the key factor to keep the system stable.
Trial registration number
basic research
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Affiliation(s)
- B Cai
- First Affiliated Hospital of SunYat-sen University, reproductive medicine center, Guangzhou-Guangdong, China
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47
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Cai B. P-797 A novel method for establishing human embryonic stem cells independent of feeder cells. Hum Reprod 2021. [DOI: 10.1093/humrep/deab128.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Study question
Is there a efficient establishing method of human embryonic stem cells directly from the human blastocysts independent of feeder cells?
Summary answer
We established a novel method of generating human embryonic stem cells directly from human blastocysts independent of feeder layer cells.
What is known already
Establishing embryonic stem cells lines mainly needed to coculture ICM clumps with feeder cells (like mouse or human fibroblasts), this brought in potential heterogeneous pollution. Although there had be some reports about generating human ESCs independent of feeder cells, but the efficiency was low and conditioned medium were unstable and also had the biological contamination.
Study design, size, duration
We used ten day5/6 donated human blastocysts from our reproductive center, most of them were genetically diseased embryos with abnormal PGT diagnosis. After establishing ESCs procedure, all the cell lines were identified with pluripotency and differentiation potential tests. The success rate of system was calculated and compared with the conventional methods.
Participants/materials, setting, methods
In brief, ICM clumps were separated mechanically by using a micromanipulation system,and then transferred to a 30ul mTESR plus culture media drop pretreated with the geltrex (1:100 dilution) matrix and oxygen concentration was 5%. When cells attached and migrated,we also used laser to destroy the remaining trophoblast cells. About 10 days,the typical ES clone can be mechanically passaged and cells can be cultured in normal oxygen concentrations after passage 2..
Main results and the role of chance
Using this method we had successfully established nine embryonic stem cell lines from donated human blastocysts, the success rate was 90% (9/10). Each cell lines had passed the evaluation test of embryonic stem cell. When compared with the conventional feeder cells dependent method,our novol methods not only eliminated the pollution from heterogeneous cells,but also had higher success rate (90% vs 25%).
Limitations, reasons for caution
Due to the scarcity of donated human blastocysts, this experiment was a single-center experiment with small samples.
Wider implications of the findings
We speculated that the batch differences of culture dishes, matrix and culture medium might affect the establish efficiency, and how to carry out a high level of quality control work might be the key factor to keep the system stable.
Trial registration number
basic research
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Affiliation(s)
- B Cai
- First Affiliated Hospital of SunYat-sen University, reproductive medicine center, Guangzhou-Guangdong, China
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48
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Cai B, Ma L, Meng L, Mo J, Xu S, Qu B, Liu F. PO-0975 ICT Plus Simultaneous Modulated Accelerated Radiation Therapy in Non-operative SCCH/L. Radiother Oncol 2021. [DOI: 10.1016/s0167-8140(21)07426-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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49
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Wu P, Guo F, Cai B, Wang C, Lv C, Liu H, Huang J, Huang Y, Cao L, Pang L, Gao J. Co-benefits of peaking carbon dioxide emissions on air quality and health, a case of Guangzhou, China. J Environ Manage 2021; 282:111796. [PMID: 33476940 DOI: 10.1016/j.jenvman.2020.111796] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Revised: 10/25/2020] [Accepted: 12/04/2020] [Indexed: 05/22/2023]
Abstract
Cities play a key role in making carbon emission reduction targets achievable and tackling air pollution. Using Guangzhou city as a case, this paper explored the air quality and health co-benefits of peaking carbon dioxide emissions under three scenarios and developed an integrated assessment framework by combining a local air pollutant emission inventory, an atmospheric chemistry transport model, and a health assessment model. The results showed that SO2, PM10, and PM2.5 could achieve larger emission reductions than NH3, VOCs, and NOx among all the scenarios we examined. Under the enhanced peaking scenario with the most stringent mitigation strategies, Guangzhou could meet the local ambient air quality standard for PM2.5 (34 μg/m3), with the most reduction observed in the annual average PM2.5 concentration (28.4%) and related premature deaths (17.08%), compared with the base year 2015. We also identified hotspot grids, which were areas with high concentrations of carbon emissions, high concentrations of air pollution and poor air quality in Guangzhou. Our analysis highlighted the importance of promoting peaking carbon dioxide emission for the improvement of air quality and public health at the city level.
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Affiliation(s)
- Pengcheng Wu
- Center for Climate Change and Environmental Policy, Chinese Academy of Planning, Beijing, 100012, China
| | - Fang Guo
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), and School of Environment, Tsinghua University, Beijing, 100084, China.
| | - Bofeng Cai
- Center for Climate Change and Environmental Policy, Chinese Academy of Planning, Beijing, 100012, China.
| | - Can Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), and School of Environment, Tsinghua University, Beijing, 100084, China
| | - Chen Lv
- Beijing University of Technology, Beijing, 100124, China
| | - Hui Liu
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, 430072, China
| | - Jizhang Huang
- Guangzhou Research Institute of Environmental Protection, Guangzhou, 510620, China
| | - Ying Huang
- Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou, 510640, China
| | - Libin Cao
- Center for Climate Change and Environmental Policy, Chinese Academy of Planning, Beijing, 100012, China
| | - Lingyun Pang
- Center for Climate Change and Environmental Policy, Chinese Academy of Planning, Beijing, 100012, China
| | - Ji Gao
- Environmental Defense Fund, Beijing, 100007, China
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50
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Wei J, Zhang J, Cai B, Wang K, Liang S, Geng Y. Characteristics of carbon dioxide emissions in response to local development: Empirical explanation of Zipf's law in Chinese cities. Sci Total Environ 2021; 757:143912. [PMID: 33321336 DOI: 10.1016/j.scitotenv.2020.143912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 11/12/2020] [Accepted: 11/17/2020] [Indexed: 06/12/2023]
Abstract
Carbon emissions and city development are currently two major areas of interest worldwide. With the continuous development of cities, the problem of carbon emissions has received substantial attention. Analyzing the relationship between carbon emissions and city development is key to building low-carbon cities. This paper selects the revised Zipf's law to explore diverse carbon emission characteristics in different stages of city development and tries to verify the balance of city development and the rationality of key emitting sectors in China, thus filling a gap in this domain. Based on the analysis of different emitting sectors and diverse city categories, several discoveries are made. First, nearly 80% of Chinese cities have reached the ideal state of Zipf's law between carbon dioxide (CO2) emissions and city development. In general, carbon emissions and city development are basically matched at the present stage. Second, in cities, the carbon emissions of the agricultural and industrial processes sectors are relatively balanced and stable with the city development. In addition, only the traffic sector is in the stage of intensive development. Other sectors (industrial energy, rural household, urban household, services, and indirect emissions) need to be further optimized. Third, CO2 emissions in other type of cities are basically matched with the city development. Industrial cities, megalopolises and metropolises are in the stage of intensive development, while cities of other types (service-oriented cities and small-medium cities) need to be further optimized. Fourth, corresponding measures, such as adjusting energy and industrial structure, optimizing resource allocation, and promoting intensive production, need to be taken to optimize carbon emissions in cities of different types and in different emitting sectors. Our study provides a particular theoretical basis and practical value, for China and other countries in similar situations, to coordinate the matching correlation between city development and carbon emissions in the future.
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Affiliation(s)
- Jing Wei
- School of Land Science and Technology, China University of Geosciences (Beijing), 29, Xueyuan Road, Haidian District, Beijing 100083, China
| | - Jianjun Zhang
- School of Land Science and Technology, China University of Geosciences (Beijing), 29, Xueyuan Road, Haidian District, Beijing 100083, China; Key Laboratory of Land Consolidation and Rehabilitation, Ministry of Natural Resources, Beijing 100083, China; Institute of Environment Sciences, Department of Biological Sciences, University of Québec at Montréal, Montréal, QC H3C 3P8, Canada.
| | - Bofeng Cai
- Center for Climate Change and Environmental Policy, Chinese Academy of Environmental Planning, Beijing 100012, China.
| | - Ke Wang
- School of Land Science and Technology, China University of Geosciences (Beijing), 29, Xueyuan Road, Haidian District, Beijing 100083, China
| | - Sen Liang
- School of Land Science and Technology, China University of Geosciences (Beijing), 29, Xueyuan Road, Haidian District, Beijing 100083, China
| | - Yuhuan Geng
- Institute of Environment Sciences, Department of Biological Sciences, University of Québec at Montréal, Montréal, QC H3C 3P8, Canada; Tourism Institute, Beijing Union University, 99, Beisihuan East Road, Chaoyang District, Beijing 100101, China
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