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Hao J, Chen Y, Zhang L. Modeling trace elements over Athabasca oil sands region in Alberta, Canada using WRF-Chem. THE SCIENCE OF THE TOTAL ENVIRONMENT 2025; 974:179144. [PMID: 40140263 DOI: 10.1016/j.scitotenv.2025.179144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2024] [Revised: 02/28/2025] [Accepted: 03/12/2025] [Indexed: 03/28/2025]
Abstract
The Athabasca Oil Sands Region (AOSR) in northern Alberta, Canada is a significant source of particulate elements, which may cause negative effects on human and ecosystem health. This study simulates the transport and deposition of eight elements (Al, Ca, Fe, K, Mn, Si, Ti, and Zn) in the AOSR during 2016-2017 using WRF-Chem with a recently developed regional-scale emission database of elements as model input. Point and area emissions of the elements were gridded in the model domain, with stack emissions also considering the plume rise. The model-measurement differences in annual concentrations of the sum of the eight elements were 23 % at AMS1, 25 % at AMS17, and - 56 % at AMS18. Modeled annual average concentrations and atmospheric deposition of individual elements ranged from 0.016 to 2.67 μg m-3 (the sum total of 5.98 μg m-3) and from 2.62 to 385 mg m-2 yr-1 (862 mg m-2 yr-1), respectively, in the central industrial area of the AOSR. The concentration and deposition decreased rapidly with distance from the center industrial area, e.g., by three orders of magnitude in areas 150 km away. Adding the three sites together, modeled total concentrations of the eight elements were 110 % higher during the cold season and 29 % lower during the warm season than the measured values, noting that constant emission rates were used throughout the years of 2016-2017. Two model sensitivity tests were conducted, with the first one using seasonally varying emissions and the second one replacing the default dry and wet deposition schemes in WRF-Chem with different ones found in literature, to demonstrate the magnitudes of the uncertainties in the model simulated ambient concentrations and atmospheric deposition of particulate elements and major causing factors of the uncertainties.
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Affiliation(s)
- Jingliang Hao
- Department of Earth and Space Science & Engineering, York University, 4700 Keele Street, Toronto, Ontario M3J 1P3, Canada
| | - Yongsheng Chen
- Department of Earth and Space Science & Engineering, York University, 4700 Keele Street, Toronto, Ontario M3J 1P3, Canada
| | - Leiming Zhang
- Air Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Toronto, Ontario M3H 5T4, Canada.
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2
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Kraisitnitikul P, Thepnuan D, Chansuebsri S, Yabueng N, Wiriya W, Saksakulkrai S, Shi Z, Chantara S. Contrasting compositions of PM 2.5 in Northern Thailand during La Niña (2017) and El Niño (2019) years. J Environ Sci (China) 2024; 135:585-599. [PMID: 37778829 DOI: 10.1016/j.jes.2022.09.026] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 09/02/2022] [Accepted: 09/17/2022] [Indexed: 10/03/2023]
Abstract
There have been a very limited number of systematic studies on PM2.5 compositions and their source contribution in Southeast Asia. This study aims to explore the characteristics of PM2.5 composition collected in Chiang Mai (Thailand) during La Niña and El Niño years and to apportion their sources during smoke haze and non-haze periods. The average PM2.5 concentration of smoke haze episode in 2019 (El Niño) was much higher than in 2017 (La Niña). The ratios of organic carbon (OC) to elemental carbon (EC), as well as K (biomass burning (BB) tracer) to PM2.5, were higher during smoke haze episodes in 2019 than in 2017 indicating a significant influence from BB. The ratios of secondary organic carbon (SOC) levels to primary organic carbon (POC) levels during smoke haze episodes were higher than those in non-haze period, which indicated greater SOC contributions or more photo-oxidation of precursors in haze episodes with high ambient temperatures. However, the ratios of soil markers (Ca and Mg) during non-haze period were high implying that soil source contributed more to PM2.5 concentrations when there less BB occurred. The positive Matrix Factorization (PMF) model revealed that the source of BB, characterized by high K fractions, was the largest contributor during smoke haze episodes accounting for 50% (2017) and 79% (2019). Climate conditions influence meteorological patterns, particularly during incidences of extreme weather such as droughts, which affect the scale and frequency of open burning and thus air pollution levels.
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Affiliation(s)
- Pavidarin Kraisitnitikul
- Environmental Science Research Center, Faculty of Science, Chiang Mai University, Chiang Mai, 50200, Thailand
| | - Duangduean Thepnuan
- Department of Chemistry, Faculty of Science and Technology, Chiang Mai Rajabhat University, Chiang Mai, 50300, Thailand.
| | - Sarana Chansuebsri
- Environmental Science Research Center, Faculty of Science, Chiang Mai University, Chiang Mai, 50200, Thailand
| | - Nuttipon Yabueng
- Environmental Science Research Center, Faculty of Science, Chiang Mai University, Chiang Mai, 50200, Thailand
| | - Wan Wiriya
- Environmental Science Research Center, Faculty of Science, Chiang Mai University, Chiang Mai, 50200, Thailand; Chemistry Department, Faculty of Science, Chiang Mai University, Chiang Mai, 50200, Thailand
| | - Supattarachai Saksakulkrai
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Zongbo Shi
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Somporn Chantara
- Environmental Science Research Center, Faculty of Science, Chiang Mai University, Chiang Mai, 50200, Thailand; Chemistry Department, Faculty of Science, Chiang Mai University, Chiang Mai, 50200, Thailand.
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Tehrani MW, Fortner EC, Robinson ES, Chiger AA, Sheu R, Werden BS, Gigot C, Yacovitch T, Van Bramer S, Burke T, Koehler K, Nachman KE, Rule AM, DeCarlo PF. Characterizing metals in particulate pollution in communities at the fenceline of heavy industry: combining mobile monitoring and size-resolved filter measurements. ENVIRONMENTAL SCIENCE. PROCESSES & IMPACTS 2023; 25:1491-1504. [PMID: 37584085 PMCID: PMC10510330 DOI: 10.1039/d3em00142c] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 08/09/2023] [Indexed: 08/17/2023]
Abstract
Exposures to metals from industrial emissions can pose important health risks. The Chester-Trainer-Marcus Hook area of southeastern Pennsylvania is home to multiple petrochemical plants, a refinery, and a waste incinerator, most abutting socio-economically disadvantaged residential communities. Existing information on fenceline community exposures is based on monitoring data with low temporal and spatial resolution and EPA models that incorporate industry self-reporting. During a 3 week sampling campaign in September 2021, size-resolved particulate matter (PM) metals concentrations were obtained at a fixed site in Chester and on-line mobile aerosol measurements were conducted around Chester-Trainer-Marcus Hook. Fixed-site arsenic, lead, antimony, cobalt, and manganese concentrations in total PM were higher (p < 0.001) than EPA model estimates, and arsenic, lead, and cadmium were predominantly observed in fine PM (<2.5 μm), the PM fraction which can penetrate deeply into the lungs. Hazard index analysis suggests adverse effects are not expected from exposures at the observed levels; however, additional chemical exposures, PM size fraction, and non-chemical stressors should be considered in future studies for accurate assessment of risk. Fixed-site MOUDI and nearby mobile aerosol measurements were moderately correlated (r ≥ 0.5) for aluminum, potassium and selenium. Source apportionment analyses suggested the presence of four major emissions sources (sea salt, mineral dust, general combustion, and non-exhaust vehicle emissions) in the study area. Elevated levels of combustion-related elements of health concern (e.g., arsenic, cadmium, antimony, and vanadium) were observed near the waste incinerator and other industrial facilities by mobile monitoring, as well as in residential-zoned areas in Chester. These results suggest potential co-exposures to harmful atmospheric metal/metalloids in communities surrounding the Chester-Trainer-Marcus Hook industrial area at levels that may exceed previous estimates from EPA modeling.
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Affiliation(s)
- Mina W Tehrani
- Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA
| | | | - Ellis S Robinson
- Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Andrea A Chiger
- Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA
- Risk Sciences and Public Policy Institute, Johns Hopkins University, Baltimore, MD, USA
| | - Roger Sheu
- Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA
| | | | - Carolyn Gigot
- Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA
| | | | | | - Thomas Burke
- Risk Sciences and Public Policy Institute, Johns Hopkins University, Baltimore, MD, USA
- Department of Health Policy and Management, Johns Hopkins University, Baltimore, MD, USA
| | - Kirsten Koehler
- Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Keeve E Nachman
- Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA
- Risk Sciences and Public Policy Institute, Johns Hopkins University, Baltimore, MD, USA
| | - Ana M Rule
- Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Peter F DeCarlo
- Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA
- Risk Sciences and Public Policy Institute, Johns Hopkins University, Baltimore, MD, USA
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Yang F, Cheng I, Xiao R, Qiu X, Zhang L. Emissions database development and dispersion model predictions of airborne particulate elements in the Canadian Athabasca oil sands region. ENVIRONMENTAL RESEARCH 2023; 220:115223. [PMID: 36608763 DOI: 10.1016/j.envres.2023.115223] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 12/28/2022] [Accepted: 01/02/2023] [Indexed: 06/17/2023]
Abstract
This study developed an emission inventory for 29 elements in PM2.5 and PM2.5-10 covering an area of approximately 300 by 420 km2 in the Athabasca Oil Sands Region in northern Alberta, Canada. Emission sources were aggregated into nine categories, of which the Oil Sands (OS) Sources emitted the most, followed by the Non-OS Dust sources for both fine and coarse elements over the study area. The top six fine particulate elements include Si, Ca, Al, Fe, S, and K (933, 442, 323, 269, 116, and 103 tonnes/year, respectively), the sum of which accounted for 20.5% of the total PM2.5 emissions. The top five coarse elements include Si, Ca, Al, Fe, and K (3713, 1815, 1198, 1073, and 404 tonnes/year), and their sum accounted for 29% of the total PM2.5-10 emissions. Using this emission inventory as input, the CALPUFF dispersion model simulated reasonable element concentrations in both PM2.5 and PM2.5-10 when compared to measurements collected at three sites during 2016-2017. Modeled PM10 concentrations of all elements were very close to the measurements at an industrial site with the highest ambient concentration, overestimated by 65% at another industrial site with moderate ambient concentration, and underestimated by 27% at a remote site with very low ambient concentration. Model-measurement differences of annual average concentrations were within 20% for Si, Ca, Al, Fe, Ti, Mn, and Cu in PM2.5, and were 20-50% for K, S, and Zn in PM2.5 at two sites located within the OS surface mineable area. Model-measurement differences were larger, but still within a factor of two for elements in PM2.5-10 at these two sites and for elements in both PM2.5 and PM2.5-10 at a background site.
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Affiliation(s)
- Fuquan Yang
- Air Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Toronto, Ontario, M3H 5T4 Canada; SLR Consulting (Canada) Ltd, 100 Stone Road West, Suite 201, Guelph, Ontario, N1G 5L3 Canada
| | - Irene Cheng
- Air Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Toronto, Ontario, M3H 5T4 Canada
| | - Richard Xiao
- SLR Consulting (Canada) Ltd, 100 Stone Road West, Suite 201, Guelph, Ontario, N1G 5L3 Canada
| | - Xin Qiu
- SLR Consulting (Canada) Ltd, 100 Stone Road West, Suite 201, Guelph, Ontario, N1G 5L3 Canada.
| | - Leiming Zhang
- Air Quality Research Division, Science and Technology Branch, Environment and Climate Change Canada, Toronto, Ontario, M3H 5T4 Canada.
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Bai X, Tian H, Zhu C, Luo L, Hao Y, Liu S, Guo Z, Lv Y, Chen D, Chu B, Wang S, Hao J. Present Knowledge and Future Perspectives of Atmospheric Emission Inventories of Toxic Trace Elements: A Critical Review. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:1551-1567. [PMID: 36661479 DOI: 10.1021/acs.est.2c07147] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Toxic trace elements (TEs) can pose serious risks to ecosystems and human health. However, a comprehensive understanding of atmospheric emission inventories for several concerning TEs has not yet been developed. In this study, we systematically reviewed the status and progress of existing research in developing atmospheric emission inventories of TEs focusing on global, regional, and sectoral scales. Multiple studies have strengthened our understanding of the global emission of TEs, despite attention being mainly focused on Hg and source classification in different studies showing large discrepancies. In contrast to those of developed countries and regions, the officially published emission inventory is still lacking in developing countries, despite the fact that studies on evaluating the emissions of TEs on a national scale or one specific source category have been numerous in recent years. Additionally, emissions of TEs emitted from waste incineration and traffic-related sources have produced growing concern with worldwide rapid urbanization. Although several studies attempt to estimate the emissions of TEs based on PM emissions and its source-specific chemical profiles, the emission factor approach is still the universal method. We call for more extensive and in-depth studies to establish a precise localization national emission inventory of TEs based on adequate field measurements and comprehensive investigation to reduce uncertainty.
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Affiliation(s)
- Xiaoxuan Bai
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Hezhong Tian
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Chuanyong Zhu
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
| | - Lining Luo
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Yan Hao
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Shuhan Liu
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Zhihui Guo
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Yunqian Lv
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Dongxue Chen
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Biwu Chu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100875, China
| | - Jiming Hao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100875, China
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Wu H, Wang J, Guo J, Hu X, Bao H, Chen J. Record of heavy metals in Huguangyan Maar Lake sediments: Response to anthropogenic atmospheric pollution in Southern China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 831:154829. [PMID: 35346700 DOI: 10.1016/j.scitotenv.2022.154829] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 03/18/2022] [Accepted: 03/22/2022] [Indexed: 05/16/2023]
Abstract
The historical atmospheric heavy metal pollution of southern China over the past 200 years was explored by analyzing radiometric dating, heavy metals, and Pb isotopes from a sediment core in Huguangyan Maar Lake. Zn, Cd, Sb, Tl, and Pb in the lake are closely related to anthropogenic activities, while Cr and Ni are mainly derived from the weathering of basalt surrounding the lake. Atmospheric Zn, Cd, Sb, and Tl increased rapidly after 1980, consistent with the local industrial development. The increase of atmospheric Pb in southern China occurred earlier than in other regions of China, with the increase after 1850. War and the use of leaded gasoline were the main causes for the rapid increase in atmospheric Pb during 1910-1950. From 1950 to 2000, the input of Pb from anthropogenic activities decreased gradually due to the stable social environment. After 2000, atmospheric Pb continued to rise due to continued industrial development. The three-end-member model of Pb isotopes indicates that coal combustion is the main source of current atmospheric Pb. The proportion of Pb derived from vehicle exhaust emissions reached a peak in the 1960s, then gradually decreased and further reduced with the ban on leaded gasoline after 2000. These results are important in identifying the sources of atmospheric heavy metal pollution and in formulating pollution control strategies.
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Affiliation(s)
- Hongchen Wu
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Jingfu Wang
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China.
| | - Jianyang Guo
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Xinping Hu
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Hongyun Bao
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Jingan Chen
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China.
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Yan Q, Kong S, Yan Y, Liu X, Zheng S, Qin S, Wu F, Niu Z, Zheng H, Cheng Y, Zeng X, Wu J, Yao L, Liu D, Shen G, Shen Z, Qi S. Emission and spatialized health risks for trace elements from domestic coal burning in China. ENVIRONMENT INTERNATIONAL 2022; 158:107001. [PMID: 34991261 DOI: 10.1016/j.envint.2021.107001] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 11/08/2021] [Accepted: 11/22/2021] [Indexed: 06/14/2023]
Abstract
Residential coal combustion (RCC) emission exhibited obvious daily variation, while no real-time estimation of air pollutants from RCC has been reported, as the shortages of corresponding activity dataset and emission factors with high time resolution. A real-time monitoring platform for RCC emission was established. Hourly emission factors of 18 typed of TEs from eleven kinds of chunk coals and nine kinds of honeycomb coals burning in China were obtained. The monthly and hourly coal consumption amounts were calculated with reference and our field survey. Then the hourly TEs emission inventories from RCC were established in China. GEOS-Chem and Risk Quotients Models were utilized to map the spatialized health risks of hazardous elements, including the gridded hazard index and carcinogenic risk. The result indicated that the EFs of TEs would be underestimated if the tests only consider flaming conditions. Cu, K, Ca, Zn, and Co were the top five elements from RCC, with corresponding emission amounts as 1397.7, 1054.0, 676.0, 623.5 and 420 tons in 2017, respectively. K, Ti, Fe, Sn, and Sb showed hourly peak values under flaming dominated periods, accounting for 48.2%, 45.9%, 31.8%, 42.8%, and 33.8% of their daily emissions. Other elements (e.g., V, Co, As, Hg and Pb) exhibited higher emissions under smoldering dominated period in nighttime, accounting for 22.2%, 32.9%, 27.6%, 34.7%, and 28.4% of their daily emissions. TEs emission from RCC closely follows the habits of human daily cooking and heating activity. The national HI were lower than the acceptable level (HI ≤ 1) except Sichuan Province (up to 1.2). Higher carcinogenic risks (≥1 × 10-6) occurred in parts of Sichuan, Shanxi, Hunan and Hubei, which were up to 2.0 × 10-5. The high-resolution TEs emission inventories could be useful for future modeling works on the formation and evolution of air pollution and are helpful for human exposure assessment.
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Affiliation(s)
- Qin Yan
- Department of Atmospheric Sciences, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China; Department of Environmental Science and Engineering, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China
| | - Shaofei Kong
- Department of Atmospheric Sciences, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China; Department of Environmental Science and Engineering, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China.
| | - Yingying Yan
- Department of Atmospheric Sciences, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China
| | - Xi Liu
- Department of Environmental Science and Engineering, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China
| | - Shurui Zheng
- Department of Atmospheric Sciences, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China; Department of Environmental Science and Engineering, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China
| | - Si Qin
- Department of Environmental Science and Engineering, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China
| | - Fangqi Wu
- Department of Atmospheric Sciences, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China
| | - Zhenzhen Niu
- Department of Atmospheric Sciences, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China
| | - Huang Zheng
- Department of Atmospheric Sciences, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China; Department of Environmental Science and Engineering, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China
| | - Yi Cheng
- Department of Atmospheric Sciences, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China
| | - Xin Zeng
- Department of Atmospheric Sciences, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China; Department of Environmental Science and Engineering, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China
| | - Jian Wu
- Department of Atmospheric Sciences, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China; Department of Environmental Science and Engineering, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China
| | - Liquan Yao
- Department of Atmospheric Sciences, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China; Department of Environmental Science and Engineering, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China
| | - Dantong Liu
- Department of Atmospheric Sciences, School of Earth Sciences, Zhejiang University, Hangzhou 310058, China
| | - Guofeng Shen
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Zhenxing Shen
- Department of Environmental Science and Engineering, Xi'an Jiaotong University, Xi'an 710049, China
| | - Shihua Qi
- State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan 430074, China
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8
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Weichenthal S, Lavigne E, Traub A, Umbrio D, You H, Pollitt K, Shin T, Kulka R, Stieb DM, Korsiak J, Jessiman B, Brook JR, Hatzopoulou M, Evans G, Burnett RT. Association of Sulfur, Transition Metals, and the Oxidative Potential of Outdoor PM2.5 with Acute Cardiovascular Events: A Case-Crossover Study of Canadian Adults. ENVIRONMENTAL HEALTH PERSPECTIVES 2021; 129:107005. [PMID: 34644144 PMCID: PMC8513754 DOI: 10.1289/ehp9449] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 08/30/2021] [Accepted: 09/28/2021] [Indexed: 05/28/2023]
Abstract
BACKGROUND We do not currently understand how spatiotemporal variations in the composition of fine particulate air pollution [fine particulate matter with aerodynamic diameter ≤2.5μm (PM2.5)] affects population health risks. However, recent evidence suggests that joint concentrations of transition metals and sulfate may influence the oxidative potential (OP) of PM2.5 and associated health impacts. OBJECTIVES The purpose of the study was to evaluate how combinations of transition metals/OP and sulfur content in outdoor PM2.5 influence associations with acute cardiovascular events. METHODS We conducted a national case-crossover study of outdoor PM2.5 and acute cardiovascular events in Canada between 2016 and 2017 (93,344 adult cases). Monthly mean transition metal and sulfur (S) concentrations in PM2.5 were determined prospectively along with estimates of OP using acellular assays for glutathione (OPGSH), ascorbate (OPAA), and dithiothreitol depletion (OPDTT). Conditional logistic regression models were used to estimate odds ratios (OR) [95% confidence intervals (CI)] for PM2.5 across strata of transition metals/OP and sulfur. RESULTS Among men, the magnitudes of observed associations were strongest when both transition metal and sulfur content were elevated. For example, an OR of 1.078 (95% CI: 1.049, 1.108) (per 10μg/m3) was observed for cardiovascular events in men when both copper and S were above the median, whereas a weaker association was observed when both elements were below median values (OR=1.019, 95% CI: 1.007, 1.031). A similar pattern was observed for OP metrics. PM2.5 was not associated with acute cardiovascular events in women. DISCUSSION The combined transition metal and sulfur content of outdoor PM2.5 influences the strength of association with acute cardiovascular events in men. Regions with elevated concentrations of both sulfur and transition metals in PM2.5 should be examined as priority areas for regulatory interventions. https://doi.org/10.1289/EHP9449.
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Affiliation(s)
- Scott Weichenthal
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Canada
- Air Health Science Division, Health Canada, Ottawa, Canada
| | - Eric Lavigne
- Air Health Science Division, Health Canada, Ottawa, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada
| | - Alison Traub
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Canada
| | - Dana Umbrio
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Canada
| | - Hongyu You
- Air Health Science Division, Health Canada, Ottawa, Canada
| | - Krystal Pollitt
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut, USA
| | - Tim Shin
- Air Health Science Division, Health Canada, Ottawa, Canada
| | - Ryan Kulka
- Air Health Science Division, Health Canada, Ottawa, Canada
| | - Dave M. Stieb
- Population Studies Division, Health Canada, Ottawa, Canada
| | - Jill Korsiak
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Canada
| | - Barry Jessiman
- Air Health Science Division, Health Canada, Ottawa, Canada
| | - Jeff R. Brook
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Marianne Hatzopoulou
- Department of Civil and Mineral Engineering, University of Toronto, Toronto, Canada
| | - Greg Evans
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Canada
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Bai X, Luo L, Tian H, Liu S, Hao Y, Zhao S, Lin S, Zhu C, Guo Z, Lv Y. Atmospheric Vanadium Emission Inventory from Both Anthropogenic and Natural Sources in China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:11568-11578. [PMID: 34415166 DOI: 10.1021/acs.est.1c04766] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Vanadium is a strategically important metal in the world, although sustained exposure under high vanadium levels may lead to notable adverse impact on health. Here, we leverage a bottom-up approach to quantitatively evaluate vanadium emissions from both anthropogenic and natural sources during 1949-2017 in China for the first time. The results show that vanadium emissions increased by 86% from 1949 to 2005 to a historical peak value and then gradually decreased to 12.9 kt in 2017. With the effective implementation of air pollution control measures, vanadium emissions from anthropogenic sources decreased sharply after 2011. During 2011-2017, about half of vanadium emissions came from coal and oil combustion. In addition, industrial processes and natural sources also cannot be ignored, with the total contributions of more than 24%. The high levels of vanadium emissions were mainly distributed throughout the North China Plain and the eastern and coastal regions, especially in several urban agglomerations. Furthermore, the comprehensive evaluation by incorporating contrastive analysis, Monte Carlo approach, and GEOS-Chem simulation shows that vanadium emissions estimated in this study were reasonable and acceptable. The findings of our study provide not only a scientific foundation for investigating the health effects of vanadium but also useful information for formulating mitigation strategies.
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Affiliation(s)
- Xiaoxuan Bai
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Lining Luo
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Hezhong Tian
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Shuhan Liu
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Yan Hao
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Shuang Zhao
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Shumin Lin
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Chuanyong Zhu
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
| | - Zhihui Guo
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Yunqian Lv
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
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10
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Xu JW, Martin RV, Evans GJ, Umbrio D, Traub A, Meng J, van Donkelaar A, You H, Kulka R, Burnett RT, Godri Pollitt KJ, Weichenthal S. Predicting Spatial Variations in Multiple Measures of Oxidative Burden for Outdoor Fine Particulate Air Pollution across Canada. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:9750-9760. [PMID: 34241996 DOI: 10.1021/acs.est.1c01210] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Fine particulate air pollution (PM2.5) is a leading contributor to the overall global burden of disease. Traditionally, outdoor PM2.5 has been characterized using mass concentrations which treat all particles as equally harmful. Oxidative potential (OP) (per μg) and oxidative burden (OB) (per m3) are complementary metrics that estimate the ability of PM2.5 to cause oxidative stress, which is an important mechanism in air pollution health effects. Here, we provide the first national estimates of spatial variations in multiple measures (glutathione, ascorbate, and dithiothreitol depletion) of annual median outdoor PM2.5 OB across Canada. To do this, we combined a large database of ground-level OB measurements collected monthly prospectively across Canada for 2 years (2016-2018) with PM2.5 components estimated using a chemical transport model (GEOS-Chem) and satellite aerosol observations. Our predicted ground-level OB values of all three methods were consistent with ground-level observations (cross-validation R2 = 0.63-0.74). We found that forested regions and urban areas had the highest OB, predicted primarily by black carbon and organic carbon from wildfires and transportation sources. Importantly, the dominant components associated with OB were different than those contributing to PM2.5 mass concentrations (secondary inorganic aerosol); thus, OB metrics may better indicate harmful components and sources on health than the bulk PM2.5 mass, reinforcing that OB estimates can complement the existing PM2.5 data in future national-level epidemiological studies.
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Affiliation(s)
- Jun-Wei Xu
- Department of Physics and Atmospheric Science, Dalhousie University, 6310 Coburg Road, Halifax, Nova Scotia B3H 4R2, Canada
| | - Randall V Martin
- Department of Physics and Atmospheric Science, Dalhousie University, 6310 Coburg Road, Halifax, Nova Scotia B3H 4R2, Canada
- Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, 1 Brookings Drive, St. Louis, Missouri 63130, United States
- Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, Massachusetts 02138, United States
| | - Greg J Evans
- Southern Ontario Centre for Atmospheric Aerosol Research, University of Toronto, 200 College Street, Toronto, Ontario M5S 3E5, Canada
- Dalla Lana School of Public Health, University of Toronto, 480 University Avenue, Toronto, Ontario M5G 1V2, Canada
| | - Dana Umbrio
- Southern Ontario Centre for Atmospheric Aerosol Research, University of Toronto, 200 College Street, Toronto, Ontario M5S 3E5, Canada
| | - Alison Traub
- Southern Ontario Centre for Atmospheric Aerosol Research, University of Toronto, 200 College Street, Toronto, Ontario M5S 3E5, Canada
| | - Jun Meng
- Department of Physics and Atmospheric Science, Dalhousie University, 6310 Coburg Road, Halifax, Nova Scotia B3H 4R2, Canada
| | - Aaron van Donkelaar
- Department of Physics and Atmospheric Science, Dalhousie University, 6310 Coburg Road, Halifax, Nova Scotia B3H 4R2, Canada
- Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, 1 Brookings Drive, St. Louis, Missouri 63130, United States
| | - Hongyu You
- Air Health Science Division, Health Canada, 269 Laurier Avenue West, Ottawa, Ontario K1A 0K0, Canada
| | - Ryan Kulka
- Air Health Science Division, Health Canada, 269 Laurier Avenue West, Ottawa, Ontario K1A 0K0, Canada
| | - Richard T Burnett
- Population Studies Division, Health Canada, 101 Tunney's Pasture Dr., Ottawa, Ontario K1A 0K9, Canada
| | - Krystal J Godri Pollitt
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, New Haven, Connecticut 06520, United States
| | - Scott Weichenthal
- Air Health Science Division, Health Canada, 269 Laurier Avenue West, Ottawa, Ontario K1A 0K0, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, 1020 Pine Avenue West, Montreal, Quebec H3A 1A2, Canada
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11
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Hossain M, Karmakar D, Begum SN, Ali SY, Patra PK. Recent trends in the analysis of trace elements in the field of environmental research: A review. Microchem J 2021. [DOI: 10.1016/j.microc.2021.106086] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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12
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Kajino M, Hagino H, Fujitani Y, Morikawa T, Fukui T, Onishi K, Okuda T, Kajikawa T, Igarashi Y. Modeling Transition Metals in East Asia and Japan and Its Emission Sources. GEOHEALTH 2020; 4:e2020GH000259. [PMID: 32999946 PMCID: PMC7507570 DOI: 10.1029/2020gh000259] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 07/23/2020] [Accepted: 07/25/2020] [Indexed: 05/04/2023]
Abstract
Emission inventories of anthropogenic transition metals, which contribute to aerosol oxidative potential (OP), in Asia (Δx = 0.25°, monthly, 2000-2008) and Japan (Δx = 2 km, hourly, mainly 2012) were developed, based on bottom-up inventories of particulate matters and metal profiles in a speciation database for particulate matters. The new inventories are named Transition Metal Inventory (TMI)-Asia v1.0 and TMI-Japan v1.0, respectively. It includes 10 transition metals in PM2.5 and PM10, which contributed to OP based on reagent experiments, namely, Cu, Mn, Co, V, Ni, Pb, Fe, Zn, Cd, and Cr. The contributions of sectors in the transition metals emission in Japan were also investigated. Road brakes and iron-steel industry are primary sources, followed by other metal industry, navigation, incineration, power plants, and railway. In order to validate the emission inventory, eight elements such as Cu, Mn, V, Ni, Pb, Fe, Zn, and Cr in anthropogenic dust and those in mineral dust were simulated over East Asia and Japan with Δx = 30 km and Δx = 5 km domains, respectively, and compared against the nation-wide seasonal observations of PM2.5 elements in Japan and the long-term continuous observations of total suspended particles (TSPs) at Yonago, Japan in 2013. Most of the simulated elements generally agreed with the observations, while Cu and Pb were significantly overestimated. This is the first comprehensive study on the development and evaluation of emission inventory of OP active elements, but further improvement is needed.
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Affiliation(s)
- Mizuo Kajino
- Meteorological Research Institute (MRI), Japan Meteorological Agency (JMA)TsukubaJapan
- Faculty of Life and Environmental SciencesUniversity of TsukubaTsukubaJapan
| | | | - Yuji Fujitani
- National Institute for Environmental Studies (NIES)TsukubaJapan
| | | | | | - Kazunari Onishi
- Graduate School of Public HealthSt. Luke's International UniversityTokyoJapan
| | - Tomoaki Okuda
- Faculty of Science and TechnologyKeio UniversityYokohamaJapan
| | - Tomoki Kajikawa
- Graduate School of Creative Science and EngineeringWaseda UniversityTokyoJapan
| | - Yasuhito Igarashi
- Institute for Integrated Radiation and Nuclear Science (KURNS)Kyoto UniversityOsakaJapan
- College of ScienceIbaraki UniversityMitoJapan
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Zhang L, Gao Y, Wu S, Zhang S, Smith KR, Yao X, Gao H. Global impact of atmospheric arsenic on health risk: 2005 to 2015. Proc Natl Acad Sci U S A 2020; 117:13975-13982. [PMID: 32513708 PMCID: PMC7322006 DOI: 10.1073/pnas.2002580117] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Arsenic is a toxic pollutant commonly found in the environment. Most of the previous studies on arsenic pollution have primarily focused on arsenic contamination in groundwater. In this study, we examine the impact on human health from atmospheric arsenic on the global scale. We first develop an improved global atmospheric arsenic emission inventory and connect it to a global model (Goddard Earth Observing System [GEOS]-Chem). Model evaluation using observational data from a variety of sources shows the model successfully reproduces the spatial distribution of atmospheric arsenic around the world. We found that for 2005, the highest airborne arsenic concentrations were found over Chile and eastern China, with mean values of 8.34 and 5.63 ng/m3, respectively. By 2015, the average atmospheric arsenic concentration in India (4.57 ng/m3) surpassed that in eastern China (4.38 ng/m3) due to the fast increase in coal burning in India. Our calculation shows that China has the largest population affected by cancer risk due to atmospheric arsenic inhalation in 2005, which is again surpassed by India in 2015. Based on potential exceedance of health-based limits, we find that the combined effect by including both atmospheric and groundwater arsenic may significantly enhance the risks, due to carcinogenic and noncarcinogenic effects. Therefore, this study clearly implies the necessity in accounting for both atmospheric and groundwater arsenic in future management.
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Affiliation(s)
- Lei Zhang
- Frontiers Science Center for Deep Ocean Multispheres and Earth System/Key Laboratory of Marine Environmental Science and Ecology, Ministry of Education, Ocean University of China, 266100 Qingdao, China
| | - Yang Gao
- Frontiers Science Center for Deep Ocean Multispheres and Earth System/Key Laboratory of Marine Environmental Science and Ecology, Ministry of Education, Ocean University of China, 266100 Qingdao, China;
- Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, 266237 Qingdao, China
| | - Shiliang Wu
- Atmospheric Sciences Program, Michigan Technological University, Houghton, MI 49931;
| | - Shaoqing Zhang
- Key Laboratory of Physical Oceanography, Ministry of Education/Institute for Advanced Ocean Study/Frontiers Science Center for Deep Ocean Multispheres and Earth System, Ocean University of China and Qingdao National Laboratory for Marine Science and Technology, 266100 Qingdao, China
- International Laboratory for High-Resolution Earth System Prediction, 266237 Qingdao, China
- College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Kirk R Smith
- School of Public Health, University of California, Berkeley, CA 94720;
- Collaborative Clean Air Policy Centre, Delhi 110003, India
| | - Xiaohong Yao
- Frontiers Science Center for Deep Ocean Multispheres and Earth System/Key Laboratory of Marine Environmental Science and Ecology, Ministry of Education, Ocean University of China, 266100 Qingdao, China
- Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, 266237 Qingdao, China
| | - Huiwang Gao
- Frontiers Science Center for Deep Ocean Multispheres and Earth System/Key Laboratory of Marine Environmental Science and Ecology, Ministry of Education, Ocean University of China, 266100 Qingdao, China
- Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, 266237 Qingdao, China
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