1
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Chen ZH, Li BW, Li B, Peng ZR, Huang HC, Wu JQ, He HD. Identification of particle distribution pattern in vertical profile via unmanned aerial vehicles observation. Environ Pollut 2024; 348:123893. [PMID: 38556146 DOI: 10.1016/j.envpol.2024.123893] [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: 12/30/2023] [Revised: 03/03/2024] [Accepted: 03/27/2024] [Indexed: 04/02/2024]
Abstract
Below the boundary layer, the air pollutants have been confirmed to present the decreasing trend with the height in most situaitons. However, the disperiosn rate of air pollutants in the vertical profile is rarely investigated in detail, especially through in-situ measurement. With this consideration, we employed an unmanned aerial vehicle equipped with portable monitoring equipments to scrutinize the vertical distribution of PM2.5. Based on the original data, we found that PM2.5 concentration decreases gradually with altitude below the boundary layer and demonstrated an obvious linear correlation. Therefore, the vertical distribution of PM2.5 was quantified by representing the distribution of PM2.5 with the slope of PM2.5 vertical distribution. We used backward trajectories to reveal the causes of outliers (PM2.5 increasing with altitude), and found that PM2.5 in the high altitude came from the southwest. Besides, the relationship between the vertical distribution of PM2.5 and various meteorological factors was investigated using stepwise regression analysis. The results show that the four meteorological factors most strongly correlated with the slope values are: (a) the difference in relative humidity between the ground and the air; (b) the difference in temperature between the ground and the air; (c) the height of the boundary layer; and (d) the wind speed. The slope values increase with increasing the difference in relative humidity between ground and air and the difference in temperature between the ground and the air, and decrease with increasing boundary layer height and wind speed. According to the Random Forest calculations, the ground-to-air relative humidity difference is the most important at 0.718; the wind speed is the least important at 0.053; and the ground-to-air temperature difference and boundary layer height are 0.140 and 0.088, respectively.
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Affiliation(s)
- Zhi-Heng Chen
- Center for ITS and UAV Applications Research, School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China; Data-Driven Management Decision Making Lab, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Bo-Wen Li
- Center for ITS and UAV Applications Research, School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Bai Li
- Department of Civil & Environmental Engineering, University of South Florida, Tampa, FL, 33620, USA
| | - Zhong-Ren Peng
- International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, PO Box 115706, Gainesville, FL, 32611-5706, USA; Healthy Building Research Center, Ajman University, Ajman, United Arab Emirates
| | - Hai-Chao Huang
- Center for ITS and UAV Applications Research, School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Jun-Qi Wu
- Student Innovation Center, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hong-Di He
- Center for ITS and UAV Applications Research, School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
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2
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Jin MY, Zhang LY, Peng ZR, He HD, Kumar P, Gallagher J. The impact of dynamic traffic and wind conditions on green infrastructure performance to improve local air quality. Sci Total Environ 2024; 917:170211. [PMID: 38278279 DOI: 10.1016/j.scitotenv.2024.170211] [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: 11/06/2023] [Revised: 01/03/2024] [Accepted: 01/14/2024] [Indexed: 01/28/2024]
Abstract
Road traffic represents the dominant source of air pollution in urban street canyons. Local wind conditions greatly impacts the dispersion of these pollutants, yet street trees complicate ventilation in such settings. This case study adopts a novel modelling framework to account for dynamic traffic and wind conditions to identify the optimal street tree configuration that prevents a deterioration in air quality. Measurement data from a shallow to moderately deep street canyon (average 0.5 H/W aspect ratio and four lanes of 1-way traffic) in Dublin, Ireland was used for model calibration. The computational fluid dynamics (CFD) models were used to examine scenarios of dynamic traffic flows within each traffic lane with respect to its impact on local PM2.5 concentrations on adjacent footpaths, segmenting air quality monitoring results based on different wind conditions for model calibration. The monitoring campaign identified higher PM2.5 concentrations on the leeward (north) footpath, with average differences of 14.1 % (2.15 μg/m3) for early evening peaks. The modelling results demonstrated how street trees negatively impacted air quality on the windward footpath in parallel wind conditions regardless of leaf area density (LAD) or tree spacing, with mixed results observed on the leeward footpath in varying traffic flows and wind speeds. Perpendicular wind direction models and high wind speed exacerbated poor air quality on the windward footpath for all tree spacing models, while improving the air quality on the leeward footpath. The findings advise against planting high-LAD trees in this type of street, with a minimum of 20 m spacing for low-LAD trees to balance reducing local air pollution and ventilation capacity in the street. This study highlights the complexities of those in key decision-marking roles and demonstrates the need to adopt a transparent framework to ensure adequate modelling evidence can inform tree planting in city streets.
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Affiliation(s)
- Meng-Yi Jin
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; Department of Civil, Structural & Environmental Engineering, Trinity College Dublin, the University of Dublin, Ireland
| | - Le-Ying Zhang
- Department of Civil, Structural & Environmental Engineering, Trinity College Dublin, the University of Dublin, Ireland
| | - Zhong-Ren Peng
- iAdapt: International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, FL 32611-5706, USA; Healthy Building Research Center, Ajman University, Ajman, United Arab Emirates
| | - Hong-Di He
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Prashant Kumar
- Department of Civil, Structural & Environmental Engineering, Trinity College Dublin, the University of Dublin, Ireland; Global Centre for Clean Air Research (GCARE), School of Sustainability, Civil and Environmental Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, United Kingdom
| | - John Gallagher
- Department of Civil, Structural & Environmental Engineering, Trinity College Dublin, the University of Dublin, Ireland.
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Wang Z, Cao R, Li B, Cai M, Peng ZR, Zhang G, Lu Q, He HD, Zhang J, Shi K, Liu Y, Zhang H, Hu X. Characterizing nighttime vertical profiles of atmospheric particulate matter and ozone in a megacity of south China using unmanned aerial vehicle measurements. Environ Res 2023; 236:116854. [PMID: 37562735 DOI: 10.1016/j.envres.2023.116854] [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: 05/26/2023] [Revised: 07/29/2023] [Accepted: 08/07/2023] [Indexed: 08/12/2023]
Abstract
Daytime atmospheric pollution has received wide attention, while the vertical structures of atmospheric pollutants at night play a crucial role in the photochemical process on the following day, which is still less reported. Focusing on Guangzhou, a megacity of South China, we established an unmanned aerial vehicle (UAV) equipped with micro detectors to collect consecutive high-resolution samples of fine particle (PM2.5), submicron particle (PM1.0), black carbon (BC) and ozone (O3) concentrations in the atmosphere, as well as the air temperature (AT) and relative humidity (RH) within a 500 m altitude during nighttime from Oct. 24th to Nov. 6th, 2018. The measurements showed that PM2.5, PM1.0, and BC decreased with altitude and were influenced by the nighttime shallow planetary boundary layer (PBL) where BC was more accumulated and fluctuated. In contrast, O3 was positively correlated with altitude. Backward trajectory clustering and Pasquill stability classification showed that advection and convection significantly influenced the vertical distribution of all pollutants, particularly particulate matter. External air masses carrying high concentrations of pollutants increased PM1.0 and PM2.5 levels by 145% and 455%, respectively, compared to unaffected periods. The ratio of BC to PM2.5 indicated that local emissions had a minor role in nighttime particulate matter. Vertical transport caused by atmospheric instability reduced the differences in pollutant concentrations at various heights. Geodetector and generalized additive model showed that RH and BC accumulation in the PBL were significant factors influencing vertical changes of the secondary aerosol intensity as indicated by the ratio of PM1.0 to PM2.5. The joint explanation of RH and atmospheric stability with other variables such as BC is essential to understand the generation of secondary aerosols. These findings provide insights into regional and local measures to prevent and control night-time particulate matter pollution.
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Affiliation(s)
- Zhanyong Wang
- College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou, 350108, China.
| | - Ruhui Cao
- College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou, 350108, China
| | - Bai Li
- School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Ming Cai
- School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, 510006, China
| | - Zhong-Ren Peng
- iAdapt: International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, PO Box 115706, Gainesville, FL, 32611-5706, USA; Healthy Building Research Center, Ajman University, Ajman, UAE
| | - Guohua Zhang
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640, China
| | - Qingchang Lu
- Department of Traffic Information and Control Engineering, School of Electronic and Control Engineering, Chang'an University, Xi'an, 710064, China
| | - Hong-di He
- School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Jinpu Zhang
- Guangzhou Sub-branch of Guangdong Ecological and Environmental Monitoring Center, Guangzhou, 510006, Guangdong, China
| | - Kai Shi
- College of Environmental Science and Engineering, China West Normal University, Nanchong, 637009, China
| | - Yonghong Liu
- School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, 510006, China
| | - Hui Zhang
- School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, 510006, China
| | - Xisheng Hu
- College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou, 350108, China
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4
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Lu DN, He HD, Zhao HM, Lu KF, Peng ZR, Li J. Quantifying traffic-related carbon emissions on elevated roads through on-road measurements. Environ Res 2023; 231:116200. [PMID: 37209989 DOI: 10.1016/j.envres.2023.116200] [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: 01/14/2023] [Revised: 04/30/2023] [Accepted: 05/17/2023] [Indexed: 05/22/2023]
Abstract
Vehicles generally move smoothly and with high speeds on elevated roads, thereby producing specific traffic-related carbon emissions in contrast to ground roads. Hence, a portable emission measurement system was adopted to determine traffic-related carbon emissions. The on-road measurement results revealed that the instantaneous emissions of CO2 and CO from elevated vehicles were 17.8% and 21.9% higher than those from ground vehicles, respectively. Based on it, the vehicle specific power was confirmed to exhibit a positive exponential relationship with instantaneous CO2 and CO emissions. In addition to carbon emissions, carbon concentrations on roads were simultaneously measured. The average CO2 and CO emissions on elevated roads in urban areas were 1.2% and 6.9% higher than those on ground roads, individually. Finally, a numerical simulation was performed, and the results verified that elevated roads could deteriorate the air quality on ground roads but improve the air quality above them. What ought to be paid attention to is that the elevated roads present varied traffic behaviour and cause particular carbon emissions, indicating that comprehensive consideration and further balance among the traffic-related carbon emissions are necessary when building elevated roads to alleviate the traffic congestion in urban areas.
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Affiliation(s)
- Dan-Ni Lu
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hong-Di He
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
| | - Hong-Mei Zhao
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Kai-Fa Lu
- International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, PO Box 115706, Gainesville, FL 32611-5706, USA
| | - Zhong-Ren Peng
- International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, PO Box 115706, Gainesville, FL 32611-5706, USA
| | - Jian Li
- Key Laboratory of Road and Traffic Engineering of the Ministry of Education, College of Transportation Engineering, Tongji University, 4800 Cao'an Road, Shanghai 201804, China.
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5
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Zhai W, Fu X, Liu M, Peng ZR. The impact of ethnic segregation on neighbourhood-level social distancing in the United States amid the early outbreak of COVID-19. Urban Stud 2023; 60:1403-1426. [PMID: 37273498 PMCID: PMC10230299 DOI: 10.1177/00420980211050183] [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] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
The COVID-19 pandemic has been argued to be the 'great equaliser', but, in fact, ethnically and racially segregated communities are bearing a disproportionate burden from the disease. Although more people have been infected and died from the disease among these minority communities, still fewer people in these communities are complying with the suggested public health measures like social distancing. The factors contributing to these ramifications remain a long-lasting debate, in part due to the contested theories between ethnic stratification and ethnic community. To offer empirical evidence to this theoretical debate, we tracked public social-distancing behaviours from mobile phone devices across urban census tracts in the United States and employed a difference-in-difference model to examine the impact of racial/ethnic segregation on these behaviours. Specifically, we focussed on non-Hispanic Black and Hispanic communities at the neighbourhood level from three principal dimensions of ethnic segregation, namely, evenness, exposure, and concentration. Our results suggest that (1) the high ethnic diversity index can decrease social-distancing behaviours and (2) the high dissimilarity between ethnic minorities and non-Hispanic Whites can increase social-distancing behavior; (3) the high interaction index can decrease social-distancing behaviours; and (4) the high concentration of ethnic minorities can increase travel distance and non-home time but decrease work behaviours. The findings of this study shed new light on public health behaviours among minority communities and offer empirical knowledge for policymakers to better inform just and evidence-based public health orders.
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Affiliation(s)
- Wei Zhai
- Hong Kong Baptist University, China
| | - Xinyu Fu
- University of Waikato, New Zealand
| | - Mengyang Liu
- Huazhong University of Science and Technology, China
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6
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Fang XR, Zhu XH, Li XZ, Peng ZR, Qingyao H, He HD, Chen AY, Cheng H. Assessing the effects of short-term traffic restriction policies on traffic-related air pollutants. Sci Total Environ 2023; 867:161451. [PMID: 36621495 DOI: 10.1016/j.scitotenv.2023.161451] [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: 09/25/2022] [Revised: 12/28/2022] [Accepted: 01/03/2023] [Indexed: 06/17/2023]
Abstract
The implementation of short-term traffic restriction policies (TRPs) during major events positively influences the traffic emission reduction. However, few studies explore the impact of diesel vehicle emissions on air quality during short-term TRP. In particular, the intertwined influences of short-term TRP and Spring Festival remains unclear. Based on Beijing 2022 Olympic Games, this study analyzed the spatiotemporal changes in urban air quality and diesel vehicle emission during short-term TRP. The results showed that the TRPs and Spring Festival contributed equally to the improvement of air quality and reduction of diesel vehicle emissions. The "interruption-recovery" pattern of short-term TRPs is characterized by a longer duration and a slower decline/recovery rate. Additionally, the individual contribution rate of diesel vehicle emissions to urban air pollutants was 15-20 % higher than that of meteorological factors during short-term TRPs.
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Affiliation(s)
- Xiao-Rui Fang
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
| | - Xing-Hang Zhu
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Xing-Zhou Li
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Zhong-Ren Peng
- International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, Florida 32611-5706, USA.
| | - Hu Qingyao
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China.
| | - Hong-Di He
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Aj Yuan Chen
- University of Southern California (Marshall), Los Angeles, CA 90089, USA
| | - Huang Cheng
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
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7
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Wu CL, He HD, Song RF, Zhu XH, Peng ZR, Fu QY, Pan J. A hybrid deep learning model for regional O 3 and NO 2 concentrations prediction based on spatiotemporal dependencies in air quality monitoring network. Environ Pollut 2023; 320:121075. [PMID: 36641063 DOI: 10.1016/j.envpol.2023.121075] [Citation(s) in RCA: 2] [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: 12/05/2022] [Revised: 01/06/2023] [Accepted: 01/10/2023] [Indexed: 06/17/2023]
Abstract
Short-term prediction of urban air quality is critical to pollution management and public health. However, existing studies have failed to make full use of the spatiotemporal correlations or topological relationships among air quality monitoring networks (AQMN), and hence exhibit low precision in regional prediction tasks. With this consideration, we proposed a novel deep learning-based hybrid model of Res-GCN-BiLSTM combining the residual neural network (ResNet), graph convolutional network (GCN), and bidirectional long short-term memory (BiLSTM), for predicting short-term regional NO2 and O3 concentrations. Auto-correlation analysis and cluster analysis were first utilized to reveal the inherent temporal and spatial properties respectively. They demonstrated that there existed temporal daily periodicity and spatial similarity in AQMN. Then the identified spatiotemporal properties were sufficiently leveraged, and monitoring network topological information, as well as auxiliary pollutants and meteorology were also adaptively integrated into the model. The hourly observed data from 51 air quality monitoring stations and meteorological data in Shanghai were employed to evaluate it. Results show that the Res-GCN-BiLSTM model was better adapted to the pollutant characteristics and improved the prediction accuracy, with nearly 11% and 17% improvements in mean absolute error for NO2 and O3, respectively compared to the best performing baseline model. Among the three types of monitoring stations, traffic monitoring stations performed the best for O3, but the worst for NO2, mainly due to the impacts of intensive traffic emissions and the titration reaction. These findings illustrate that the hybrid architecture is more suitable for regional pollutant concentration.
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Affiliation(s)
- Cui-Lin Wu
- Center for ITS and UAV Applications Research, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hong-di He
- Center for ITS and UAV Applications Research, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
| | - Rui-Feng Song
- Department of Civil and Environmental Engineering, Northeastern University, 360 Huntington Ave., Boston, MA, 02115, USA
| | - Xing-Hang Zhu
- Center for ITS and UAV Applications Research, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Zhong-Ren Peng
- International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, PO Box 115706, Gainesville, FL, 32611-5706, USA
| | - Qing-Yan Fu
- Shanghai Environmental Monitoring Center, Shanghai, 200235, China
| | - Jun Pan
- Shanghai Environmental Monitoring Center, Shanghai, 200235, China
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8
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Lu KF, Peng ZR. Impacts of viaduct and geometry configurations on the distribution of traffic-related particulate matter in urban street canyon. Sci Total Environ 2023; 858:159902. [PMID: 36328259 DOI: 10.1016/j.scitotenv.2022.159902] [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: 08/09/2022] [Revised: 10/15/2022] [Accepted: 10/29/2022] [Indexed: 06/16/2023]
Abstract
Viaduct is a ubiquitous transportation infrastructure in the congested megacities worldwide to improve the accessibility and capacity of urban transportation network. However, there is a lack of understanding of the impacts of the interplay between viaduct-ground emissions and viaduct-canyon configurations on the particle distribution in urban street canyon. To fill the research gap, we conducted vertical measurements of particle number concentrations (PNCs) at different heights of "street canyon along a viaduct" to reveal effect of viaduct on the vertical distribution of PNCs in street canyon. Observation results indicated that the vertical profiles of PNCs exhibited bimodal distribution patterns, which were more significant for coarse particles than fine particles. The one peak appeared at ground level and the other at the viaduct height, indicating the impacts of "double" emission sources (i.e., the emissions on the ground and viaduct) and the hindrance of viaduct to particle diffusion. We further modelled the role of viaduct in street canyon through Computational Fluid Dynamics (CFD) simulations to reveal the vertical distribution of particles under different viaduct-canyon configurations and discern the contributions of viaduct and ground emissions to the particle distribution. Simulation results showed that viaduct changed airflow field and turbulence structure and elevated particle concentrations in street canyon while the optimized viaduct-canyon configurations including higher viaduct height (12 > 10 > 8 m), smaller aspect ratio (0.5 > 0.67 > 1), and shorter centerline distance (0 > 1 > 2 m) between canyon and viaduct could bring better dispersion conditions and lower particle concentrations. Additionally, ground emissions contributed more to the vertical distribution of particles on the leeward side of street canyon than viaduct emissions while the windward side displayed the opposite characteristics to the leeward side. These findings revealed the general patterns of particle diffusion in viaduct-canyon configurations and provided implications into viaduct design and traffic management to alleviate local particulate pollution.
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Affiliation(s)
- Kai-Fa Lu
- iAdapt: International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, PO Box 115706, Gainesville, FL 32611-5706, USA
| | - Zhong-Ren Peng
- iAdapt: International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, PO Box 115706, Gainesville, FL 32611-5706, USA.
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9
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Han Y, Mao L, Chen X, Zhai W, Peng ZR, Mozumder P. Agent-based Modeling to Evaluate Human-Environment Interactions in Community Flood Risk Mitigation. Risk Anal 2022; 42:2041-2061. [PMID: 34773275 DOI: 10.1111/risa.13854] [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: 07/20/2018] [Revised: 02/15/2021] [Accepted: 10/14/2021] [Indexed: 06/13/2023]
Abstract
This article deals with household-level flood risk mitigation. We present an agent-based modeling framework to simulate the mechanism of natural hazard and human interactions, to allow evaluation of community flood risk, and to predict various adaptation outcomes. The framework considers each household as an autonomous, yet socially connected, agent. A Beta-Bernoulli Bayesian learning model is first applied to measure changes of agents' risk perceptions in response to stochastic storm surges. Then the risk appraisal behaviors of agents, as a function of willingness-to-pay for flood insurance, are measured. Using Miami-Dade County, Florida as a case study, we simulated four scenarios to evaluate the outcomes of alternative adaptation strategies. Results show that community damage decreases significantly after a few years when agents become cognizant of flood risks. Compared to insurance policies with pre-Flood Insurance Rate Maps subsidies, risk-based insurance policies are more effective in promoting community resilience, but it will decrease motivations to purchase flood insurance, especially for households outside of high-risk areas. We evaluated vital model parameters using a local sensitivity analysis. Simulation results demonstrate the importance of an integrated adaptation strategy in community flood risk management.
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Affiliation(s)
- Yu Han
- Department of Landscape Architecture and Urban Planning, College of Architecture, Texas A&M University, TX, USA
| | - Liang Mao
- Department of Geography, University of Florida, Gainesville, FL, USA
| | - Xuqi Chen
- Department of Agricultural and Resource Economics, University of Tennessee, Knoxville, TN, USA
| | - Wei Zhai
- Department of Geography, Hong Kong Baptist University, Hong Kong, SAR, China
| | - Zhong-Ren Peng
- International Center for Adaptation Planning and Design, School of Landscape Architecture and Design, College of Design, Construction, and Planning, University of Florida, P.O. Box 115706, Gainesville, FL, USA
| | - Pallab Mozumder
- Institute of Environment, Department of Earth & Environment and Department of Economics, Florida International University, Miami, FL, USA
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10
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Zhang Z, He HD, Yang JM, Wang HW, Xue Y, Peng ZR. Spatiotemporal evolution of NO 2 diffusion in Beijing in response to COVID-19 lockdown using complex network. Chemosphere 2022; 293:133631. [PMID: 35041819 PMCID: PMC8760926 DOI: 10.1016/j.chemosphere.2022.133631] [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: 12/07/2021] [Revised: 01/10/2022] [Accepted: 01/12/2022] [Indexed: 06/14/2023]
Abstract
The COVID-19 pandemic and the corresponding lockdown measures have been confirmed to reduce the air pollution in major megacities worldwide. Especially at some monitoring hotspots, NO2 has been verified to show a significant decrease. However, the diffusion pattern of these hotspots in responding to COVID-19 is not clearly understood at present stage. Hence, we selected Beijing, a typical megacity with the strictest lockdown measures during COVID-19 period, as the studied city and attempted to discover the NO2 diffusion process through complex network method. The improved metrics derived from the topological structure of the network were adopted to describe the performance of diffusion. Primarily, we found evidences that COVID-19 had significant effects on the spatial diffusion distribution due to combined effect of changed human activities and meteorological conditions. Besides, to further quantify the impacts of disturbance caused by different lockdown measures, we discussed the evolutionary diffusion patterns from lockdown period to recovery period. The results displayed that the difference between normal operation and pandemic operation firstly increased at the cutoff of lockdown measures but then declined after the implement of recovery measures. The source areas had greater vulnerability and lower resilience than receptors areas. Furthermore, based on the conclusion that the diffusion pattern changed during different periods, we explored the key stations on the path of diffusion process to further gain information. These findings could provide references for comprehending spatiotemporal pattern on city scale, which might be help for high-resolution air pollution mapping and prediction.
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Affiliation(s)
- Zhe Zhang
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, No. 800 Dongchuan Road, Minhang District, Shanghai, 200240, China
| | - Hong-Di He
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, No. 800 Dongchuan Road, Minhang District, Shanghai, 200240, China.
| | - Jin-Ming Yang
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, No. 800 Dongchuan Road, Minhang District, Shanghai, 200240, China
| | - Hong-Wei Wang
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, No. 800 Dongchuan Road, Minhang District, Shanghai, 200240, China
| | - Yu Xue
- Institute of Physical Science and Technology, Guangxi University, Nanning, 53004, China
| | - Zhong-Ren Peng
- International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, Gainesville, FL, 32611-5706, USA
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11
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Zhao HM, He HD, Lu KF, Han XL, Ding Y, Peng ZR. Measuring the impact of an exogenous factor: An exponential smoothing model of the response of shipping to COVID-19. Transp Policy (Oxf) 2022; 118:91-100. [PMID: 35125683 PMCID: PMC8805997 DOI: 10.1016/j.tranpol.2022.01.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 01/24/2022] [Indexed: 05/25/2023]
Abstract
Following the outbreak of the COVID-19 pandemic, various lockdown strategies restrained global economic growth bringing a significant decline in maritime transportation. However, the previous studies have not adequately recognized the specific impacts of COVID-19 on maritime transportation. In this study, a series of analyses of the Baltic Dry Index (BDI), the China Coastal Bulk Freight Index (CCBFI) and of container throughputs with and without the impact of COVID-19 were carried out to assess changing trends in dry bulk and container transportation. The results show that global dry bulk transportation was largely affected by lockdown policies in the second month during COVID-19, and BDI presented a year-on-year decrease of approximately 35.5% from 2019 to 2020. The CCBFI showed an upward trend in the second month during COVID-19, one month ahead of the BDI. The container throughputs at Shanghai Port, the Ports of Hong Kong, the Ports of Singapore and the Ports of Los Angeles from 2019 to 2020 presented the largest year-on-year drops of approximately 19.6%, 7.1%, 10.6% and 30.9%, respectively. In addition, the authors developed exponential smoothing models of BDI, CCBFI, and container transportation, and calculated the percentage prediction error between the observed and predicted values to examine the impact of exogenous effects on the shipping industry due to the outbreak of COVID-19. The results are consistent with the conclusions obtained from the comparison of BDI, CCBFI, and container transportation during the same period in 2020 and 2019. Finally, on the basis of the findings, smart shipping and special support policies are proposed to reduce the negative impacts of COVID-19.
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Affiliation(s)
- Hong-Mei Zhao
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
- School of Economics and Management, Shanghai Maritime University, Shanghai, 200135, China
| | - Hong-Di He
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Kai-Fa Lu
- International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, PO Box 115706, Gainesville, FL, 32611-5706, USA
| | - Xiao-Long Han
- Logistics Research Center, Shanghai Maritime University, Shanghai, 200135, China
| | - Yi Ding
- Logistics Research Center, Shanghai Maritime University, Shanghai, 200135, China
| | - Zhong-Ren Peng
- International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, PO Box 115706, Gainesville, FL, 32611-5706, USA
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12
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Cai WJ, Wang HW, Wu CL, Lu KF, Peng ZR, He HD. Characterizing the interruption-recovery patterns of urban air pollution under the COVID-19 lockdown in China. Build Environ 2021; 205:108231. [PMID: 34393324 PMCID: PMC8354860 DOI: 10.1016/j.buildenv.2021.108231] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 07/30/2021] [Accepted: 08/04/2021] [Indexed: 05/28/2023]
Abstract
The COVID-19 pandemic provides an opportunity to study the effects of urban lockdown policies on the variation in pollutant concentrations and to characterize the recovery patterns of urban air pollution under the interruption of COVID-19 lockdown policies. In this paper, interruption-recovery models and regression discontinuity design were developed to characterize air pollution interruption-recovery patterns and analyze environmental impacts of the COVID-19 lockdown, using air pollution data from four Chinese metropolises (i.e., Shanghai, Wuhan, Tianjin, and Guangzhou). The results revealed the air pollutant interruption-recovery curve represented by the three lockdown response periods (Level I, Level II and Level III) during COVID-19. The curve decreased during Level I (A 25.3%-48.8% drop in the concentration of NO2 has been observed in the four metropolises compared with the same period in 2018-2019.), then recovered around reopening, but decreased again during Level III. Moreover, the interruption-recovery curve of the year-on-year air pollution difference suggests a process of first decreasing during Level I and gradually recovering to a new equilibrium during Level III (e.g., the unit cumulative difference of NO2 mass concentrations in Shanghai was 21.7, 22.5, 11.3 (μg/m3) during Level I, II, and III and other metropolises shared similar results). Our findings reveal general trends in the air quality externality of different lockdown policies, hence could provide valuable insights into air pollutant interruption-recovery patterns and clear scientific guides for policymakers to estimate the effect of different lockdown policies on urban air quality.
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Affiliation(s)
- Wan-Jin Cai
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hong-Wei Wang
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Cui-Lin Wu
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Kai-Fa Lu
- International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, PO Box 115706, Gainesville, FL, 32611-5706, USA
| | - Zhong-Ren Peng
- International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, PO Box 115706, Gainesville, FL, 32611-5706, USA
| | - Hong-Di He
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
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13
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Zheng T, Jia YP, Zhang S, Li XB, Wu Y, Wu CL, He HD, Peng ZR. Impacts of vegetation on particle concentrations in roadside environments. Environ Pollut 2021; 282:117067. [PMID: 33838442 DOI: 10.1016/j.envpol.2021.117067] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [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: 11/27/2020] [Revised: 03/11/2021] [Accepted: 03/30/2021] [Indexed: 06/12/2023]
Abstract
In roadside environments, commuters are exposed to a high level of traffic-related pollution. Despite vegetation is often used to mitigate air pollution in road environments, its air quality impacts are complex and could be both positive or negative depending on specific conditions. This study conducted field measurements to assess the air quality impacts of roadside vegetation. Three common street vegetation configurations (dense vegetation, porous vegetation, and clearing) were selected and the concentrations of size-resolved particles and black carbon were measured. Results show that dense vegetation formed an accumulation area of particle pollutants on the sidewalk and bikeway, which was attributable to the increased deposition of pollutants. Compared with porous vegetation, the increase in particle concentrations before dense vegetation was 0-35% on the sidewalk (closer to vegetation) and 0-6% on the bikeway. Due to high homogeneity, fine particles (0.3-1 μm) showed low variability among different sample points, while coarse particles (>1 μm) showed high variability and presented a significant increase in concentration before dense vegetation. Porous vegetation showed weak interception effects on pollutants, and the particle concentrations before porous vegetation were close to those in the clearing. The horizontal decay of particle concentrations in porous and dense vegetation showed that particle pollutants were difficult to penetrate dense vegetation, which concentrations of particles presented a pronounced increase in the front part (0-5 m) of dense vegetation but also showed a large drop across it. These results suggest that vegetation serves as a good filter to clean the air and could improve the air quality away from the vegetation but could also worsen the air quality close to the vegetation. This study provides an insight into the environmental impacts of roadside vegetation, which could have practical implications in air pollution abatement.
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Affiliation(s)
- Tie Zheng
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Yue-Ping Jia
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Shaojun Zhang
- School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing, 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, 100084, China
| | - Xiao-Bing Li
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, 510632, China
| | - Ye Wu
- School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing, 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, 100084, China
| | - Cui-Lin Wu
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hong-Di He
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State-Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Zhong-Ren Peng
- International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, PO Box 115706, Gainesville, FL, 32611-5706, USA.
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14
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Wu CL, Wang HW, Cai WJ, He HD, Ni AN, Peng ZR. Impact of the COVID-19 lockdown on roadside traffic-related air pollution in Shanghai, China. Build Environ 2021; 194:107718. [PMID: 33633432 PMCID: PMC7891056 DOI: 10.1016/j.buildenv.2021.107718] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 02/09/2021] [Accepted: 02/13/2021] [Indexed: 05/09/2023]
Abstract
The outbreak of COVID-19 has significantly inhibited global economic growth and impacted the environment. Some evidence suggests that lockdown strategies have significantly reduced traffic-related air pollution (TRAP) in regions across the world. However, the impact of COVID-19 on TRAP on roadside is still not clearly understood. In this study, we assessed the influence of the COVID-19 lockdown on the levels of traffic-related air pollutants in Shanghai. The pollution data from two types of monitoring stations-roadside stations and non-roadside stations were compared and evaluated. The results show that NO2, PM2.5, PM10, and SO2 had reduced by ~30-40% at each station during the COVID-19 pandemic in contrast to 2018-2019. CO showed a moderate decline of 28.8% at roadside stations and 16.4% at non-roadside stations. In contrast, O3 concentrations increased by 30.2% at roadside stations and 5.7% at non-roadside stations. This result could be resulted from the declined NOx emissions from vehicles, which lowered O3 titration. Full lockdown measures resulted in the highest reduction of primary pollutants by 34-48% in roadside stations and 18-50% in non-roadside stations. The increase in O3 levels was also the most significant during full lockdown by 64% in roadside stations and 33% in non-roadside stations due to the largest decrease in NO2 precursors, which promote O3 formation. Additionally, Spearman's rank correlation coefficients between NO2 and other pollutants significantly decreased, while the values between NO2 and O3 increased at roadside stations.
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Affiliation(s)
- Cui-Lin Wu
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hong-Wei Wang
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Wan-Jin Cai
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hong-di He
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - An-Ning Ni
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Zhong-Ren Peng
- International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, PO Box 115706, Gainesville, FL, 32611-5706, USA
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15
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Wang D, Wang HW, Li C, Lu KF, Peng ZR, Zhao J, Fu Q, Pan J. Roadside Air Quality Forecasting in Shanghai with a Novel Sequence-to-Sequence Model. Int J Environ Res Public Health 2020; 17:ijerph17249471. [PMID: 33348819 PMCID: PMC7766230 DOI: 10.3390/ijerph17249471] [Citation(s) in RCA: 4] [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] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2020] [Revised: 12/12/2020] [Accepted: 12/15/2020] [Indexed: 11/16/2022]
Abstract
The establishment of an effective roadside air quality forecasting model provides important information for proper traffic management to mitigate severe pollution, and for alerting resident's outdoor plans to minimize exposure. Current deterministic models rely on numerical simulation and the tuning of parameters, and empirical models present powerful learning ability but have not fully considered the temporal periodicity of air pollutants. In order to take the periodicity of pollutants into empirical air quality forecasting models, this study evaluates the temporal variations of air pollutants and develops a novel sequence to sequence model with weekly periodicity to forecast air quality. Two-year observation data from Shanghai roadside air quality monitoring stations are employed to support analyzing and modeling. The results conclude that the fine particulate matter (PM2.5) and carbon monoxide (CO) concentrations show obvious daily and weekly variations, and the temporal patterns are nearly consistent with the periodicity of traffic flow in Shanghai. Compared with PM2.5, the CO concentrations are more affected by traffic variation. The proposed model outperforms the baseline model in terms of accuracy, and presents a higher linear consistency in PM2.5 prediction and lower errors in CO prediction. This study could assist environmental researchers to further improve the technologies for urban air quality forecasting, and serve as tools for supporting policymakers to implement related traffic management and emission control policies.
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Affiliation(s)
- Dongsheng Wang
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; (D.W.); (C.L.); (K.-F.L.)
| | - Hong-Wei Wang
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; (D.W.); (C.L.); (K.-F.L.)
- Correspondence: (H.-W.W.); (Z.-R.P.); Tel.: +1-352-294-1491 (Z.-R.P.)
| | - Chao Li
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; (D.W.); (C.L.); (K.-F.L.)
| | - Kai-Fa Lu
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; (D.W.); (C.L.); (K.-F.L.)
| | - Zhong-Ren Peng
- International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, P.O. Box 115706, Gainesville, FL 32611-5706, USA
- Correspondence: (H.-W.W.); (Z.-R.P.); Tel.: +1-352-294-1491 (Z.-R.P.)
| | - Juanhao Zhao
- Department of Computer Science, Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089, USA;
| | - Qingyan Fu
- Shanghai Environmental Monitoring Center, Shanghai 200235, China; (Q.F.); (J.P.)
| | - Jun Pan
- Shanghai Environmental Monitoring Center, Shanghai 200235, China; (Q.F.); (J.P.)
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16
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Cao R, Li B, Wang Z, Peng ZR, Tao S, Lou S. Using a distributed air sensor network to investigate the spatiotemporal patterns of PM 2.5 concentrations. Environ Pollut 2020; 264:114549. [PMID: 32408078 DOI: 10.1016/j.envpol.2020.114549] [Citation(s) in RCA: 12] [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: 06/26/2019] [Revised: 04/04/2020] [Accepted: 04/04/2020] [Indexed: 06/11/2023]
Abstract
Spatiotemporal variations in PM2.5 are a key factor affecting personal pollution exposure levels in urban areas. However, fixed-site monitoring stations are so sparsely distributed that they hardly capture the dynamic and fine-scale variations in PM2.5 in urban areas with complex geographical features and urban forms. Recently, a distributed air sensor network (DASN) was deployed in Dezhou city, China, to monitor fine-scale air pollution information and obtain deep insight into variations in PM2.5. Based on the data collected by the DASN, this paper investigated the spatiotemporal patterns of PM2.5 using the time-series clustering method. The results demonstrated that there were four stages of PM2.5 daily variations, i.e., accumulation, continuous pollution, dispersion, and cleaning. Generally, the stage of dispersion occurred more rapidly than the stage of accumulation, and PM2.5 accumulated easily in warm and humid weather with low wind speeds. However, the stage of dispersion was affected mainly by high wind speeds and precipitation. Additionally, the results suggested that four variation stages did not strictly correspond to seasonal divisions. The spatial distributions of PM2.5 revealed that the main pollution source was located in a southeastern industrial park, which exhibited a significant impact throughout the four stages. Considering both the temporal and spatial characteristics of PM2.5, this study successfully identified pollution hotspots and confirmed the effect of industrial parks. The study demonstrates that the DASN has high prospective applicability for assessing the fine-scale spatial distribution of PM2.5, and the time-series clustering method can also assist environmental researchers in further exploring the spatiotemporal characteristics of urban air pollution.
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Affiliation(s)
- Rong Cao
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Bai Li
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Zhanyong Wang
- College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou, 350108, China.
| | - Zhong-Ren Peng
- International Center for Adaptation Planning and Design (iAdapt), School of Landscape Architecture and Planning, College of Design, Construction, and Planning, University of Florida, P.O. Box 115706, Gainesville, FL, 32611-5706, USA
| | - Shikang Tao
- State Environmental Protection Key Laboratory of the Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, 200233, China
| | - Shengrong Lou
- State Environmental Protection Key Laboratory of the Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, 200233, China
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17
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Song XY, Lu QC, Peng ZR. Spatial Distribution of Fine Particulate Matter in Underground Passageways. Int J Environ Res Public Health 2018; 15:ijerph15081574. [PMID: 30044418 PMCID: PMC6121543 DOI: 10.3390/ijerph15081574] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2018] [Revised: 07/20/2018] [Accepted: 07/23/2018] [Indexed: 11/28/2022]
Abstract
The unfavorable locations of underground infrastructures and poor ventilation facilities can result in the deterioration of enclosed air quality. Some researchers have studied air quality and ventilation measures in different types of underground buildings. However, few studies have investigated the pollution in pedestrian passageways connecting underground structures. Hence, in this paper, we attempted to investigate the spatial distribution of fine particulate matter (PM2.5) in underground passageways. First, measurements were designed and conducted in a pedestrian passageway beneath the Shanghai South Railway Station, Shanghai, China. Second, numerical simulations were performed based on computational fluid dynamic (CFD) technology. Finally, the numerical simulations were extended to examine impacts of the ventilation measures on PM2.5 concentration with different inlet positions and air velocity in underground passageways. The simulation results showed good agreement with the experimental data, and the numerical model was validated to be an effective method to investigate the spatial distribution of PM2.5 in underground passageways. Results suggest that building additional entrances is an advisable method for improving air quality in the underground passageways of the Shanghai South Railway Station, while jet fans are not recommended. Findings of this study offer suggestions for mitigating PM2.5 pollution in underground passageways.
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Affiliation(s)
- Xin-Yi Song
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
| | - Qing-Chang Lu
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
| | - Zhong-Ren Peng
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
- China Institute for Urban Governance, Shanghai Jiao Tong University, Shanghai 200240, China.
- Department of Urban and Regional Planning, University of Florida, Gainesville, FL 32611, USA.
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18
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Liu X, Peng ZR, Zhang LY. Real-time UAV Rerouting for Traffic Monitoring with Decomposition Based Multi-objective Optimization. J INTELL ROBOT SYST 2018. [DOI: 10.1007/s10846-018-0806-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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19
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Wang Z, Wang D, Peng ZR, Cai M, Fu Q, Wang D. Performance assessment of a portable nephelometer for outdoor particle mass measurement. Environ Sci Process Impacts 2018; 20:370-383. [PMID: 29250634 DOI: 10.1039/c7em00336f] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
The availability of portable nephelometers has improved assessment of exposure to atmospheric particles at a high resolution regarding space and time. However, nephelometer performance has seldom been evaluated for outdoor measurements, especially in Chinese cities. During 37 days of measurements at four outdoor sites in Shanghai, we assessed a popular nephelometer called SidePak (TSI Inc., USA) for PM1.0, PM2.5 and PM10 mass measurements and compared them to US federal reference methods (FRMs) based on different measurement principles. The nephelometer showed high measurement precision and stability and was strongly correlated with FRMs, making it superior to the portable light scattering monitors reported in the past and thus indicating the maturity of this principle. The nephelometer measurements overestimated all those of FRMs by a factor of two, which is higher than in evaluations in other international cities. This overestimation showed a descending order for PM1.0 (2.9-fold), PM2.5 (2.2-fold) and PM10 (1.9-fold) relative to the FRMs of tapered element oscillating microbalance or beta attenuation combined with nephelometry, based on whole samples. Sites that are far from direct pollution sources showed very good agreement between the nephelometer and FRMs for PM2.5 mass measurements, while, by comparison, the roadside site showed a lower SidePak/FRM PM2.5 ratio, which is likely due to higher abundance of elemental carbon in roadside particles. Relative humidity (RH) was shown to be a key factor that distorted the measurement of the nephelometer. An empirical formula incorporating an RH adjustment developed to correct the nephelometer could produce a reasonable result, even across the various sites. This study demonstrates the great potential of the nephelometer for outdoor particle mass measurements, but for accurate and comparable data, a site-specific calibration is strongly recommended before using.
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Affiliation(s)
- Zhanyong Wang
- School of Engineering, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Intelligent Transportation System, Guangzhou 510006, China.
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20
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Yu H, Jiao J, Houston E, Peng ZR. Evaluating the relationship between rail transit and industrial agglomeration: An observation from the Dallas-fort worth region, TX. J Transp Geogr 2018; 67:33-52. [PMID: 38322039 PMCID: PMC10846886 DOI: 10.1016/j.jtrangeo.2018.01.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2024]
Abstract
Recent studies have suggested that rail transit not only facilitates urban growth but also promotes urban agglomeration. Yet research that links industrial agglomeration with rail transit is scant-what types of industries are likely to cluster near rail stations? To what extent can rail transit access be seen as having an influence on industrial agglomeration? And how do these interactions vary as rail transit proximity increases? To answer these and related questions, we investigate the relationship between industrial agglomeration and rail transit in the Dallas-Fort Worth metropolitan area using the Longitudinal Employer Dynamics (LEHD) employment data from 2014 at the census block level. First, we use the Local Indicator of Spatial Association statistics (LISA) tests to identify industrial agglomeration patterns within the study area. We then use logistics models to reveal the relationship between rail transit proximity and industrial agglomeration. Our study finds that the impacts of rail transit on industrial agglomeration, in terms of magnitudes and signs, are mixed across industries. The varying results suggest that the benefits of rail transit access exhibit considerable demand from certain industry sectors including the manufacturing, knowledge, and services industries, while exerting weaker forces in pulling agglomeration in its immediate environs among other industries (including the retail trade sector). In practice, these results are useful for justifying evidence-based rail transit planning.
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Affiliation(s)
- Haitao Yu
- Department of Urban and Regional Planning, University of Florida, Architecture Building, 1480 Inner Road, Gainesville, FL 32611, United States
| | - Junfeng Jiao
- School of Architecture, The University of Texas at Austin, Sutton Hall, 3.120, The University of Texas at Austin, Austin, TX 78759, United States
| | - Eric Houston
- City of Hallandale Beach, Department of Transportation and Mobility, 400 South Federal Highway, Hallandale Beach, FL 33009, United States
| | - Zhong-Ren Peng
- Department of Urban and Regional Planning, University of Florida, 1480 Inner Road, Gainesville, FL 32611, United States
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21
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Jiang B, Liang S, Peng ZR, Cong H, Levy M, Cheng Q, Wang T, Remais JV. Transport and public health in China: the road to a healthy future. Lancet 2017; 390:1781-1791. [PMID: 29047445 PMCID: PMC5704968 DOI: 10.1016/s0140-6736(17)31958-x] [Citation(s) in RCA: 67] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2017] [Revised: 06/27/2017] [Accepted: 07/05/2017] [Indexed: 01/15/2023]
Abstract
Transportation-related risk factors are a major source of morbidity and mortality in China, where the expansion of road networks and surges in personal vehicle ownership are having profound effects on public health. Road traffic injuries and fatalities have increased alongside increased use of motorised transport in China, and accident injury risk is aggravated by inadequate emergency response systems and trauma care. National air quality standards and emission control technologies are having a positive effect on air quality, but persistent air pollution is increasingly attributable to a growing and outdated vehicle fleet and to famously congested roads. Urban design favours motorised transport, and physical activity and its associated health benefits are hindered by poor urban infrastructure. Transport emissions of greenhouse gases contribute substantially to regional and global climate change, which compound public health risks from multiple factors. Despite these complex challenges, technological advances and innovations in planning and policy stand to make China a leader in sustainable, healthy transportation.
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Affiliation(s)
- Baoguo Jiang
- Department of Traumatology and Orthopedics, Peking University People's Hospital, Beijing, China; Peking University Trauma Medicine Center, Beijing, China
| | - Song Liang
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA; Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
| | - Zhong-Ren Peng
- Department of Urban and Regional Planning, University of Florida, Gainesville, FL, USA; China Institute for Urban Governance, Beijing, China; Center for Intelligent Transportation Systems and Unmanned Aerial System Applications, Shanghai Jiaotong University, Shanghai, China
| | - Haozhe Cong
- Road Traffic Safety Research Center of the Ministry of Public Security, Beijing, China
| | - Morgan Levy
- Environmental Health Sciences, University of California, Berkeley, CA, USA
| | - Qu Cheng
- Department of Earth System Science, Tsinghua University, Beijing, China
| | - Tianbing Wang
- Department of Traumatology and Orthopedics, Peking University People's Hospital, Beijing, China; Peking University Trauma Medicine Center, Beijing, China
| | - Justin V Remais
- Environmental Health Sciences, University of California, Berkeley, CA, USA.
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Li XB, Wang DS, Lu QC, Peng ZR, Lu SJ, Li B, Li C. Three-dimensional investigation of ozone pollution in the lower troposphere using an unmanned aerial vehicle platform. Environ Pollut 2017; 224:107-116. [PMID: 28202268 DOI: 10.1016/j.envpol.2017.01.064] [Citation(s) in RCA: 14] [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: 11/06/2016] [Revised: 01/15/2017] [Accepted: 01/24/2017] [Indexed: 06/06/2023]
Abstract
Potential utilities of instrumented lightweight unmanned aerial vehicles (UAVs) to quickly characterize tropospheric ozone pollution and meteorological factors including air temperature and relative humidity at three-dimensional scales are highlighted in this study. Both vertical and horizontal variations of ozone within the 1000 m lower troposphere at a local area of 4 × 4 km2 are investigated during summer and autumn times. Results from field measurements show that the UAV platform has a sufficient reliability and precision in capturing spatiotemporal variations of ozone and meteorological factors. The results also reveal that ozone vertical variation is mainly linked to the vertical distribution patterns of air temperature and the horizontal transport of air masses from other regions. In addition, significant horizontal variations of ozone are also observed at different levels. Without major exhaust sources, ozone horizontal variation has a strong correlation with the vertical convection intensity of air masses within the lower troposphere. Higher air temperatures are usually related to lower ozone horizontal variations at the localized area, whereas underlying surface diversity has a week influence. Three-dimensional ozone maps are obtained using an interpolation method based on UAV collected samples, which are capable of clearly demonstrating the diurnal evolution processes of ozone within the 1000 m lower troposphere.
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Affiliation(s)
- Xiao-Bing Li
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Dong-Sheng Wang
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Qing-Chang Lu
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
| | - Zhong-Ren Peng
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; China Institute for Urban Governance, Shanghai Jiao Tong University, Shanghai 200240, China; Department of Urban and Regional Planning, University of Florida, PO Box 115706, Gainesville, FL 32611-5706, USA.
| | - Si-Jia Lu
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Bai Li
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Chao Li
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
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Abstract
Internet GIS, serving spatial data and GIS functionality on the web, offers a special and potentially important means to facilitate public participation in the planning and decision-making process. In this paper I discuss a framework for the design of a web-based public participation system (WPPS) that integrates Internet GIS, Internet communications, and scenario-building tools. The design framework is based on a taxonomy that is created to describe the level of services in serving public participation according to the information content, level of user interactivity, and system functionality. The system is designed to enhance public participation in the planning and decision-making process by providing the general public with data, analysis tools, and a forum to explore knowledge, express opinion, and discuss issues. The unique feature of the WPPS using Internet GIS is that it provides users not only the option of evaluating, commenting, and selecting alternatives, but also the capability of forming their own alternatives. I also discuss system components and design issues in the WPPS.
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Affiliation(s)
- Zhong-Ren Peng
- Department of Urban Planning, University of Wisconsin-Milwaukee, PO Box 413, Milwaukee, WI 53201-0413, USA
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Liu C, Henderson BH, Wang D, Yang X, Peng ZR. A land use regression application into assessing spatial variation of intra-urban fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations in City of Shanghai, China. Sci Total Environ 2016; 565:607-615. [PMID: 27203521 DOI: 10.1016/j.scitotenv.2016.03.189] [Citation(s) in RCA: 85] [Impact Index Per Article: 10.6] [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: 02/02/2016] [Revised: 03/25/2016] [Accepted: 03/25/2016] [Indexed: 05/06/2023]
Abstract
Intra-urban assessment of air pollution exposure has become a priority study while international attention was attracted to PM2.5 pollution in China in recent years. Land Use Regression (LUR), which has previously been proved to be a feasible way to describe the relationship between land use and air pollution level in European and American cities, was employed in this paper to explain the correlations and spatial variations in Shanghai, China. PM2.5 and NO2 concentrations at 35-45 monitoring locations were selected as dependent variables, and a total of 44 built environmental factors were extracted as independent variables. Only five factors showed significant explanatory value for both PM2.5 and NO2 models: longitude, distance from monitors to the ocean, highway intensity, waterbody area, and industrial land area for PM2.5 model; residential area, distance to the coast, industrial area, urban district, and highway intensity for NO2 model. Respectively, both PM2.5 and NO2 showed anti-correlation with coastal proximity (an indicator of clean air dilution) and correlation with highway and industrial intensity (source indicators). NO2 also showed significant correlation with local indicators of population density (residential intensity and urban classification), while PM2.5 showed significant correlation with regional dilution (longitude as a indicator of distance from polluted neighbors and local water features). Both adjusted R squared values were strong with PM2.5 (0.88) being higher than NO2 (0.62). The LUR was then used to produce continuous concentration fields for NO2 and PM2.5 to illustrate the features and, potentially, for use by future studies. Comparison to PM2.5 studies in New York and Beijing show that Shanghai PM2.5 pollutant distribution was more sensitive to geographic location and proximity to neighboring regions.
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Affiliation(s)
- Chao Liu
- Department of Urban and Regional Planning, University of Florida, P. O. Box 115706, Gainesville, FL 32601, USA.
| | - Barron H Henderson
- Department of Environmental Engineering Sciences, University of Florida, Gainesville, FL 32611-5706, USA.
| | - Dongfang Wang
- Shanghai Environmental Monitoring Center, No.55, Sanjiang Rd., Shanghai, 200235, China.
| | - Xinyuan Yang
- Department of Urban and Regional Planning, University of Florida, P. O. Box 115706, Gainesville, FL 32601, USA.
| | - Zhong-Ren Peng
- Department of Urban and Regional Planning, University of Florida, P. O. Box 115706, Gainesville, FL 32611-5706, USA; School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, China.
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Sun D, Xu Y, Peng ZR. Timetable optimization for single bus line based on hybrid vehicle size model. Journal of Traffic and Transportation Engineering (English Edition) 2015. [DOI: 10.1016/j.jtte.2015.03.006] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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26
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Yang ZH, Zhou BG, Peng ZR. [Replantation of segmental destructive amputation of multiple fingers]. Zhongguo Xiu Fu Chong Jian Wai Ke Za Zhi 2001; 15:370-2. [PMID: 11762227] [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: 02/23/2023]
Abstract
OBJECTIVE To discuss the indication of replantation of destructive amputation of multiple fingers for improvement of the function of injured fingers. METHODS From February 1996 to August 1999, 23 amputated fingers in 8 cases were shortened and replanted. The crushed digital bones were fixed by Kirschner wires, flexor tendons repaired by Kessler suture technique, and digital extensor tendons repaired by mattress suture. The arteries and veins were anastomosed in each finger at the ratio of 1 to 2 or 2 to 3. The defect of blood vessels was repaired by free graft of autologous veins in 5 fingers. All of the cases were followed up for 10 to 18 months, and clinical evaluation was performed. RESULTS All replanted fingers survived in the 8 cases, with good sensation, two point discrimination of 6 to 12 mm, and satisfied function, such as pinching, grasping and hooking. The fingers were shortened for 2.6 cm in average, ranging from 2.2 cm to 4.0 cm. CONCLUSION Multiple digits replantation by shortening fingers is beneficial to functional restoration of segmental destructive fingers.
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Affiliation(s)
- Z H Yang
- Department of Hand Surgery, Fourth People's Hospital of Wuhan, Wuhan Hubei, P. R. China 430033
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Peng ZR, Zhou BG, Liao SP. [Reconstruction of nail folds by double pulp flap in congenital complete syndactyly release]. Zhongguo Xiu Fu Chong Jian Wai Ke Za Zhi 2001; 15:144-6. [PMID: 11393952] [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: 02/20/2023]
Abstract
OBJECTIVE To introduce a surgical approach for reconstruction of nail folds in congenital complete syndactyly release. METHODS A narrow flap and a broad flap were raised on the common distal phalanx to cover the denuded nail-edge in 30 fingers of 15 cases whose webs were separated. RESULTS All of the flaps were successfully transferred and survived. The reconstructed nail folds had satisfied figure in 21 out of 30 fingers. The nail folds in the other 9 fingers, covered by a broad flap in 2 fingers and by a narrow flap in 7 fingers, were a little smaller than normal. All of the 30 fingers had normal fullness of pulp and no twisty nails. CONCLUSION The reconstruction of nail folds by double pulp flap can be performed with a one-stage technique, and the outcome is satisfactory, which make it as a good surgical approach to reconstruct nail folds in congenital complete syndactyly release.
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Affiliation(s)
- Z R Peng
- Department of Hand Surgery, Fourth Hospital of Wuhan, Wuhan Hubei, P.R. China 430033
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28
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Wang GL, Shen P, Yang L, Peng ZR. [Cloning and expression of tyrosinase gene from Pseudomonas maltophilia in E. coli]. Yi Chuan Xue Bao 1999; 26:274-9. [PMID: 10589169] [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: 02/14/2023]
Abstract
The enzyme tyrosinase, encoded by tyrosinase gene (mel), is responsible for melanin formation. In a shotgun cloning experiment, a SalI-digested DNA fragment coding for tyrosinase was cloned from Pseudomonas maltophilia DNA into plasmid vector (pUC18) to generate the hybrid plasmid (pWSY). The recombinant plasmid imparted the ability of melanin synthesis to an E. coli host (HB101). The foreign DNA fragment (0.7 kb) possessed no recognition sites for BamHI, HindIII, EcoRI or BclI. Hybridization studies confirmed that the small fragment cloned in pWSY was from P. maltophilia DNA. Nucleotide sequence analysis identified an ORF of 504 nt coding tyrosinase. SDS-PAGE analysis also revealed an additional protein of 18 kDa, which was equal to the putative tyrosinase according to the size of mel fragment, was expressed in the E. coli recombinant carrying the plasmid pWSY.
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Affiliation(s)
- G L Wang
- College of Life Sciences Wuhan University
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Pao-Chang M, Xiou-qi X, Hui Z, Zheng L, Peng ZR. Preliminary report on the application of the CO2 laser scalpel for operations on the maxillo-facial bones. Lasers Surg Med 1981; 1:375-84. [PMID: 7334907 DOI: 10.1002/lsm.1900010411] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
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