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Qu K, Yan Y, Wang X, Jin X, Vrekoussis M, Kanakidou M, Brasseur GP, Lin T, Xiao T, Cai X, Zeng L, Zhang Y. The effect of cross-regional transport on ozone and particulate matter pollution in China: A review of methodology and current knowledge. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 947:174196. [PMID: 38942314 DOI: 10.1016/j.scitotenv.2024.174196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Revised: 05/29/2024] [Accepted: 06/20/2024] [Indexed: 06/30/2024]
Abstract
China is currently one of the countries impacted by severe atmospheric ozone (O3) and particulate matter (PM) pollution. Due to their moderately long lifetimes, O3 and PM can be transported over long distances, cross the boundaries of source regions and contribute to air pollution in other regions. The reported contributions of cross-regional transport (CRT) to O3 and fine PM (PM2.5) concentrations often exceed those of local emissions in the major regions of China, highlighting the important role of CRT in regional air pollution. Therefore, further improvement of air quality in China requires more joint efforts among regions to ensure a proper reduction in emissions while accounting for the influence of CRT. This review summarizes the methodologies employed to assess the influence of CRT on O3 and PM pollution as well as current knowledge of CRT influence in China. Quantifying CRT contributions in proportion to O3 and PM levels and studying detailed CRT processes of O3, PM and precursors can be both based on targeted observations and/or model simulations. Reported publications indicate that CRT contributes by 40-80 % to O3 and by 10-70 % to PM2.5 in various regions of China. These contributions exhibit notable spatiotemporal variations, with differences in meteorological conditions and/or emissions often serving as main drivers of such variations. Based on trajectory-based methods, transport pathways contributing to O3 and PM pollution in major regions of China have been revealed. Recent studies also highlighted the important role of horizontal transport in the middle/high atmospheric boundary layer or low free troposphere, of vertical exchange and mixing as well as of interactions between CRT, local meteorology and chemistry in the detailed CRT processes. Drawing on the current knowledge on the influence of CRT, this paper provides recommendations for future studies that aim at supporting ongoing air pollution mitigation strategies in China.
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Affiliation(s)
- Kun Qu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China; Laboratory for Modeling and Observation of the Earth System (LAMOS), Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
| | - Yu Yan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China; Sichuan Academy of Environmental Policy and Planning, Chengdu 610041, China
| | - Xuesong Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China.
| | - Xipeng Jin
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Mihalis Vrekoussis
- Laboratory for Modeling and Observation of the Earth System (LAMOS), Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany; Center of Marine Environmental Sciences (MARUM), University of Bremen, Bremen, Germany; Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Nicosia, Cyprus
| | - Maria Kanakidou
- Laboratory for Modeling and Observation of the Earth System (LAMOS), Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany; Environmental Chemical Processes Laboratory, Department of Chemistry, University of Crete, Heraklion, Greece; Center of Studies of Air quality and Climate Change, Institute for Chemical Engineering Sciences, Foundation for Research and Technology Hellas, Patras, Greece
| | - Guy P Brasseur
- Max Planck Institute for Meteorology, Hamburg, Germany; National Center for Atmospheric Research, Boulder, CO, USA
| | - Tingkun Lin
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China
| | - Teng Xiao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China
| | - Xuhui Cai
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China
| | - Limin Zeng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China
| | - Yuanhang Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China; Beijing Innovation Center for Engineering Science and Advanced Technology, Peking University, Beijing 100871, China; CAS Center for Excellence in Regional Atmospheric Environment, Chinese Academy of Sciences, Xiamen 361021, China.
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Wood DA. Trend-attribute forecasting of hourly PM2.5 trends in fifteen cities of Central England applying optimized machine learning feature selection. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 356:120561. [PMID: 38479290 DOI: 10.1016/j.jenvman.2024.120561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 02/18/2024] [Accepted: 03/05/2024] [Indexed: 04/07/2024]
Abstract
Recorded particulate matter (PM2.5) hourly trends are compared for fifteen urban recording sites distributed across central England for the period 2018 to 2022. They include 10 urban-background and five urban-traffic (roadside) sites with some located within the same urban area. The sites all show consistent background and peak distributions with mean annual values and standard deviations higher for 2018 and 2019 than for 2020 to 2022. The objective of this study is to demonstrate that trend attributes extracted from hourly recorded univariate PM2.5 trends at these sites can be used to provide reliable short-term hourly predictions and provide valuable insight into the regional variations in the recorded trends. Fifteen trend attributes extracted from the prior 12 h (t-1 to t-12) of recorded PM2.5 data were compiled and used as input to four supervised machine learning models (SML) to forecast PM2.5 concentrations up to 13 h ahead (t0 to t+12). All recording sites delivered forecasts with similar ranges of error levels for specific hours ahead which are consistent with their PM2.5 recorded ranges. Forecasting results for four representative sites are presented in detail using models trained and cross-validated with 2020 and 2021 hourly data to forecast 2021 and 2022 hourly data, respectively. A novel optimized feature selection procedure using a suite of five optimizers is used to improve the efficiency of the forecasting models. The LASSO and support vector regression models generate the best and most generalizable hourly PM2.5 forecasts from trained and validated SML models with mean average error (MAE) of between ∼1 and ∼3 μg/m3 for t0 to t+3 h ahead. A novel overfitting indicator, exploiting the cross-validation mean values, demonstrates that these two models are not affected by overfitting. Forecasts for t+6 to t+12 h forward generate higher MAE values between ∼3 and ∼4 μg/m3 due to their tendency to underestimate some of the extreme PM2.5 peaks. These findings indicate that further model refinements are required to generate more reliable short-term predictions for the t+6 to t+24 h ahead.
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Sun X, Zhao T, Hu J, Bai Y, Meng L, Yang Q, Zhou Y, Fu W. Inverse effects of aerosol radiative forcing on heavy PM 2.5 pollution of local accumulation and regional transport over Central China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 917:170319. [PMID: 38278241 DOI: 10.1016/j.scitotenv.2024.170319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 01/17/2024] [Accepted: 01/18/2024] [Indexed: 01/28/2024]
Abstract
Regional transport of air pollutants is a crucial factor influencing atmospheric environment, and aerosol radiative forcing (ARF) feedback to atmospheric boundary layer (ABL) structure and ambient air pollution is yet to be comprehensively understood over the receptor region of regional transport. By simulating meteorology and air pollutants during a heavy PM2.5 pollution event with WRF-Chem model, we quantitatively investigated the ARF and ABL interaction for PM2.5 pollution over the Twain-Hu Basin (THB), a key receptor region of regional transport over central China. Driven by northerly winds, PM2.5 was transported from upstream north China to downstream THB accompanied by high PM2.5 levels in the free troposphere. The ARF exacerbated local PM2.5 accumulation by up to 20 μg m-3 and inhibited the impact of regional transport on PM2.5 levels in the ABL with reducing near-surface PM2.5 concentrations of 5 μg m-3 over the THB. The ARF-intensified air temperature inversion at the top of ABL was unfavorable for the transported air pollutants crossing the ABL top to the near-surface layer, thus weakening the impact of regional PM2.5 transport on air quality in the receptor region. Meanwhile, the ARF of transported PM2.5 induced updrafts in the free troposphere, promoting vertical mixing of air pollutants with positive feedback on increasing secondary PM2.5 concentrations in the free troposphere. The ARF induced more and less secondary PM2.5 formations respectively in the free troposphere and the near-surface layer during the regional transport period of air pollution. These results enhance our comprehension of aerosol-meteorology feedback in regional changes of atmospheric environment with inverse effects of ARF on PM2.5 pollution of local accumulation and regional transport.
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Affiliation(s)
- Xiaoyun Sun
- Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing 210044, China; Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Anhui Institute of Meteorological Sciences, Hefei 230031, China
| | - Tianliang Zhao
- Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing 210044, China.
| | - Jun Hu
- Fujian Provincial Key Laboratory of Environmental Engineering, Fujian Academy of Environmental Sciences, Fuzhou 350011, China
| | - Yongqing Bai
- Institute of Heavy Rain, China Meteorological Administration, Wuhan 430205, China
| | - Lu Meng
- Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China
| | - Qingjian Yang
- Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Yue Zhou
- Institute of Heavy Rain, China Meteorological Administration, Wuhan 430205, China
| | - Weikang Fu
- Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing 210044, China
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Zhang H, Wang X, Lv L, Li G, Liu X, Li X, Yao Z. Insights into quantitative evaluation technology of PM 2.5 transport at multi-perspective and multi-spatial and temporal scales in the north China plain. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 338:122693. [PMID: 37802287 DOI: 10.1016/j.envpol.2023.122693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 09/14/2023] [Accepted: 10/03/2023] [Indexed: 10/08/2023]
Abstract
Cross-border transport is a crucial factor affecting air quality, while how to quantify the transport contribution through different technologies at multi-perspective and multi-scale have not been fully understood. This study established three quantification techniques, and conducted a systematic assessment of PM2.5 transport over the North China Plain (NCP) based on numerical simulations and vertical observations. Results suggested that the annual local emissions, inter-urban and outer-regional transport contributed 44.5%-64.6%, 15.2%-27.9% and 18.0%-28.2% of total surface PM2.5 concentrations, respectively, with transport intensity stronger in July and April, yet weaker in January and October. The southwest-northeast, northeast-southwest, and southeast-northwest were three prevailing transport directions near the surface. By comparison, the annual PM2.5 transport contribution below the atmospheric boundary layer height increased by 16.8%-24.5% in Beijing, Tianjin and Shijiazhuang, with inter-urban and outer-regional contribution of 29.8%-32.1% and 18.5%-23.1%. Furthermore, observed fluxes from fixed-point and vehicle-based mobile lidar were in good agreement with the simulated flux. PM2.5 net flux intensity varied with height, with generally larger at the middle- and high-altitude layer than that of low-altitude layer. In the early, during and late period of haze peak formation (Stage Ⅰ, Ⅱ, Ⅲ, respectively), the largest absolute flux intensity on average was Stage Ⅱ (566.7 t/d), followed by Stage Ⅲ (307.0 t/d) and Ⅰ (191.4 t/d). Besides, external transport may dominate the second concentration peak, while local emissions may play a more vital role in the first and third peaks. It has been noted that joint prevention and control measures should be proposed 1-2 days before reaching PM2.5 extremes. These findings could improve our understanding of transport influence mechanism of PM2.5 and propose effective emission reduction measures in the NCP region.
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Affiliation(s)
- Hanyu Zhang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Xuejun Wang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Longyue Lv
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Guohao Li
- Beijing Municipal Research Institute of Environmental Protection, Beijing Key Laboratory of Urban Atmospheric Volatile Organic Compounds Pollution Control and Application, National Urban Environmental Pollution Control Engineering Research Center, Beijing, 100037, China
| | - Xiaoyu Liu
- Beijing Municipal Research Institute of Environmental Protection, Beijing Key Laboratory of Urban Atmospheric Volatile Organic Compounds Pollution Control and Application, National Urban Environmental Pollution Control Engineering Research Center, Beijing, 100037, China
| | - Xin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China; State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing, 100048, China.
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Yuan Z, Pei CL, Li HX, Lin L, Hou R, Liu S, Zhang K, Cai MG, Xu XR. Vertical distribution and transport of microplastics in the urban atmosphere: New insights from field observations. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 895:165190. [PMID: 37385506 DOI: 10.1016/j.scitotenv.2023.165190] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 06/19/2023] [Accepted: 06/26/2023] [Indexed: 07/01/2023]
Abstract
The distribution and transport of atmospheric microplastics (AMPs) have raised concerns regarding their potential effects on the environment and human health. Although previous studies have reported the presence of AMPs at ground level, there is a lack of comprehensive understanding of their vertical distribution in urban environments. To gain insight into the vertical profile of AMPs, field observations were conducted at four different heights (ground level, 118 m, 168 m and 488 m) of the Canton Tower in Guangzhou, China. Results showed that the profiles of AMPs and other air pollutants had similar layer distribution patterns, although their concentrations differed. The majority of AMPs were composed of polyethylene terephthalate and rayon fibers ranging from 30 to 50 μm. As a result of atmospheric thermodynamics, AMPs generated at ground level were only partially transported upward, leading to a decrease in their abundance with increasing altitude. The study found that the stable atmospheric stability and lower wind speed between 118 m and 168 m resulted in the formation of a fine layer where AMPs tended to accumulate instead of being transported upward. This study for the first time delineated the vertical profile of AMPs within the atmospheric boundary layer, providing valuable data for understanding the environmental fate of AMPs.
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Affiliation(s)
- Zhen Yuan
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Cheng-Lei Pei
- Guangzhou Sub-branch of Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510006, China
| | - Heng-Xiang Li
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; Sanya Institute of Ocean Eco-Environmental Engineering, Sanya 572100, China
| | - Lang Lin
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; Sanya Institute of Ocean Eco-Environmental Engineering, Sanya 572100, China
| | - Rui Hou
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; Sanya Institute of Ocean Eco-Environmental Engineering, Sanya 572100, China
| | - Shan Liu
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; Sanya Institute of Ocean Eco-Environmental Engineering, Sanya 572100, China
| | - Kai Zhang
- National Observation and Research Station of Coastal Ecological Environments in Macao, Macao Environmental Research Institute, Macau University of Science and Technology, Macao SAR, China
| | - Ming-Gang Cai
- State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen 361102, China
| | - Xiang-Rong Xu
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; Sanya Institute of Ocean Eco-Environmental Engineering, Sanya 572100, China.
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Li X, Abdullah LC, Sobri S, Syazarudin Md Said M, Aslina Hussain S, Poh Aun T, Hu J. Long-term spatiotemporal evolution and coordinated control of air pollutants in a typical mega-mountain city of Cheng-Yu region under the "dual carbon" goal. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2023; 73:649-678. [PMID: 37449903 DOI: 10.1080/10962247.2023.2232744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 05/31/2023] [Accepted: 06/20/2023] [Indexed: 07/18/2023]
Abstract
Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for megacities to formulate relevant air pollution prevention and control measures and achieve carbon neutrality goals. Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain-city in China, environmental problems are complex and sensitive. This research aims to investigate the exceeding standard levels and spatio-temporal evolution of criteria pollutants between 2014 and 2020. The results indicated that PM10, PM2.5, CO and SO2 were decreased significantly by 45.91%, 52.86%, 38.89% and 66.67%, respectively. Conversely, the concentration of pollutant O3 present a fluctuating growth and found a "seesaw" phenomenon between it and PM. Furthermore, PM and O3 are highest in winter and summer, respectively. SO2, NO2, CO, and PM showed a "U-shaped", and O3 showed an inverted "U-shaped" seasonal variation. PM and O3 concentrations are still far behind the WHO, 2021AQGs standards. Significant spatial heterogeneity was observed in air pollution distribution. These results are of great significance for Chongqing to achieve "double control and double reduction" of PM2.5 and O3 pollution, and formulate a regional carbon peaking roadmap under climate coordination. Besides, it can provide an important platform for exploring air pollution in typical terrain around the world and provide references for related epidemiological research.Implications: Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain city, environmental problems are complex and sensitive. Under the background of the "14th Five-Year Plan", the construction of the "Cheng-Yu Dual-City Economic Circle" and the "Dual-Carbon" goal, this article comprehensively discussed the annual and seasonal excess levels and spatiotemporal evolution of pollutants under the multiple policy and the newest international standards (WHO,2021AQG) backgrounds from 2014 to 2020 in Chongqing. Furthermore, suggestions and measures related to the collaborative management of pollutants were discussed. Finally, limitations and recommendations were also put forward.Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for cities to formulate relevant air pollution control measures and achieve carbon neutrality goals. This study is of great significance for Chongqing to achieve "double control and double reduction" of PM2.5 and O3 pollution, study and formulate a regional carbon peaking roadmap under climate coordination and an action plan for sustained improvement of air quality.In addition, this research can advanced our understanding of air pollution in complex terrain. Furthermore, it also promote the construction of the China national strategic Cheng-Yu economic circle and build a beautiful west. Moreover, it provides scientific insights for local policymakers to guide smart urban planning, industrial layout, energy structure, and transportation planning to improve air quality throughout the Cheng-Yu region. Finally, this is also conducive to future scientific research in other regions of China, and even megacities with complex terrain in the world.
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Affiliation(s)
- Xiaoju Li
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
- Department of Resource and Environment, Xichang University, Xichang City, Sichuan Province, China
| | - Luqman Chuah Abdullah
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
| | - Shafreeza Sobri
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
| | - Mohamad Syazarudin Md Said
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
| | - Siti Aslina Hussain
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
| | - Tan Poh Aun
- SOx NOx Asia Sdn Bhd, Subang Jaya, Selangor, Malaysia
| | - Jinzhao Hu
- Department of Resource and Environment, Xichang University, Xichang City, Sichuan Province, China
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Cai X, Hu H, Liu C, Tan Z, Zheng S, Qiu S. The effect of natural and socioeconomic factors on haze pollution from global and local perspectives in China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:68356-68372. [PMID: 37120500 DOI: 10.1007/s11356-023-27134-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 04/17/2023] [Indexed: 05/27/2023]
Abstract
Analyzing the factors that cause haze and the regional differences in the influence of factors on haze is the premise and critical to precise prevention and control of haze pollution. This paper explores the global effects of haze pollution drivers and the spatial heterogeneity of factors on haze pollution using global and local regression models. The results show that, from a global perspective, a 1 μg/m3 increase in the average PM2.5 concentration of a city's neighbors will increase the city's PM2.5 concentration by 0.965 μg/m3. Temperature, atmospheric pressure, population density, and green coverage of built-up areas are positively associated with haze, while GDP per capita is the opposite. From a local perspective, each factor has different influencing scales on haze pollution. Specifically, technical support is on a global scale, and for every 1 unit increase in technical support level, the PM2.5 concentration will decrease by 0.106-0.102 μg/m3. The influencing scales of other drivers are local. In southern China, the concentration of PM2.5 decreases by 0.001-0.075 μg/m3 for every 1 °C increase in temperature, while in northern China, the concentration of PM2.5 increases by 0.001-0.889 μg/m3. In the region around the Bohai Sea in eastern China, the concentration of PM2.5 will decrease by 0.001-0.889 μg/m3 for every 1 m/s increase in wind speed. Population density positively impacts haze pollution, and the impact intensity gradually increases from 0.097 to 1.140 from south to north. For every 1% increase in the proportion of the secondary industry in southwest China, the PM2.5 concentration will increase by 0.001-0.284 μg/m3. For cities in northeast China, for every 1% increase in the urbanization rate, the PM2.5 concentration will decrease by 0.001-0.203 μg/m3. These findings help policymakers develop targeted joint prevention and control policies for haze pollution, considering regional differences.
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Affiliation(s)
- Xiaomei Cai
- School of Management, China University of Mining and Technology, No. 11 Xueyuan Road, Haidian District, Beijing, 100083, China
| | - Han Hu
- School of Management, China University of Mining and Technology, No. 11 Xueyuan Road, Haidian District, Beijing, 100083, China
| | - Chan Liu
- School of Management, China University of Mining and Technology, No. 11 Xueyuan Road, Haidian District, Beijing, 100083, China.
| | - Zhanglu Tan
- School of Management, China University of Mining and Technology, No. 11 Xueyuan Road, Haidian District, Beijing, 100083, China
| | - Shuxian Zheng
- School of Management, China University of Mining and Technology, No. 11 Xueyuan Road, Haidian District, Beijing, 100083, China
| | - Shuohan Qiu
- China Electronics Standardization Institute, Beijing, 100007, China
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Wang Y, Wang M, Wu Y, Sun G. Exploring the effect of ecological land structure on PM 2.5: A panel data study based on 277 prefecture-level cities in China. ENVIRONMENT INTERNATIONAL 2023; 174:107889. [PMID: 36989762 DOI: 10.1016/j.envint.2023.107889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 03/05/2023] [Accepted: 03/15/2023] [Indexed: 06/19/2023]
Abstract
In the context of serious urban air pollution and limited land resources, it is important to understand the environmental value of ecological land. Previous studies focused mostly on the effectiveness of a particular type of green space or the total amount of ecological land on PM2.5 and have rarely analyzed the association between ecological land structure and PM2.5 systematically and quantitatively. Therefore, we took 277 cities in China as an example, comprehensively compared the results of different models, and selected a spatial Durbin model using time-fixed effects to dissect the degree of influence of ecological land and different land types within it on PM2.5. The urban ecological land use structure was closely related to PM2.5, and the higher the proportion of ecological land use was, the lower the PM2.5. The degree and direction of influence of different types of land functions within ecological land on PM2.5 differed, with forests, shrubs, and grasslands causing a weakening impact on PM2.5, while wetlands and waters did not have a weakening role. The degree of reduction of PM2.5 by a single type of ecological land was significantly smaller than that by a composite type of ecological land. Green space should be comprehensively considered, designed and adjusted in urban planning to continuously optimize the ecological spatial structure, increase landscape diversity and maximize ecological benefits. The findings of this study help with exploring the effects of land use structure under the goal-oriented control of air pollution and provide theoretical reference and decision-making support for formulating precise air pollution control policies and optimizing the spatial development of national land.
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Affiliation(s)
- Yang Wang
- Faculty of Geography, Yunnan Normal University, Kunming 650500, China
| | - Min Wang
- Faculty of Geography, Yunnan Normal University, Kunming 650500, China.
| | - Yingmei Wu
- Faculty of Geography, Yunnan Normal University, Kunming 650500, China
| | - Guiquan Sun
- Faculty of Geography, Yunnan Normal University, Kunming 650500, China
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