Spatiotemporal patterns of recent PM2.5 concentrations over typical urban agglomerations in China

Shen, Yang; Zhang, Lianpeng; Fang, Xing; Ji, Hanyu; Li, Xing; Zhao, Zhuowen

doi:10.1016/j.scitotenv.2018.11.105

Cited by 126 publications

(63 citation statements)

References 49 publications

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“…3 ). A stable vertical atmospheric structure weakens the atmospheric turbulent exchange and hinders the diffusion of air pollutants in the vertical direction ( Shen et al., 2018 ; Zhang et al., 2013 ). There was no significant difference in wind speed between the two heavy pollution periods in Beijing and Tianjin, while the wind speed increased by 41% during the second episode compared with the first episode ( Fig.…”

Section: Resultsmentioning

confidence: 99%

Air pollution episodes during the COVID-19 outbreak in the Beijing–Tianjin–Hebei region of China: An insight into the transport pathways and source distribution

Zhao

Gang

et al. 2020

Environmental Pollution

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Although anthropogenic emissions decreased, polluted days still occurred in the Beijing–Tianjin–Hebei (BTH) region during the initial outbreak of the coronavirus disease (COVID-19). Analysis of the characteristics and source distribution of large-scale air pollution episodes during the COVID-19 outbreak (from 23 January to April 8, 2020) in the BTH region is helpful for exploring the efficacy of control measures and policy making. The results indicated that the BTH region suffered two large-scale air pollution episodes (23–28 January and 8–13 February), which were characterized by elevated PM 2.5 , SO 2 , NO 2 , and CO concentrations, while the O 3 concentration decreased by 1.5%–33.9% (except in Shijiazhuang, where it increased by 16.6% during the second episode). These large-scale air pollution episodes were dominated by unfavorable meteorological conditions comprising a low wind speed and increased relative humidity. The transport pathways and source distribution were explored using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT), potential source contribution function (PSCF), and concentration weighted trajectory (CWT) models. The air pollution in the BTH region was mainly affected by local emission sources during the first episode, which contributed 51.6%–60.6% of the total trajectories in the BTH region with a PM 2.5 concentration ranging from 146.2 μg/m 3 to 196.7 μg/m 3 . The short-distance air masses from the southern and southwestern areas of the BTH region were the main transport pathways of airflow arriving in the BTH region during the second episode. These contributed 51.9%–57.9% of the total trajectories and originated in Hebei, Henan, central Shanxi, and Shaanxi provinces, which were the areas contributing the most to the PM 2.5 level and exhibited the highest PSCF and CWT values. Therefore, on the basis of local emission reduction, enhancing regional environmental cooperation and implementing a united prevention and control of air pollution are effective mitigation measures for the BTH region.

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Section: Resultsmentioning

confidence: 99%

Air pollution episodes during the COVID-19 outbreak in the Beijing–Tianjin–Hebei region of China: An insight into the transport pathways and source distribution

Zhao

Gang

et al. 2020

Environmental Pollution

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“…The Moran's I of PM 2.5 concentration in CPEZ is about 0.08-0.19, which reveals an autocorrelation of PM 2.5 concentration in the region. However, Moran's I of PM 2.5 concentration in CPEZ is relatively lower compared with the three major economic growth areas (BTH, YRD, and PRD), which is about 0.4 to 0.9 [42][43][44]. There are two possible reasons for this situation.…”

Section: Discussionmentioning

confidence: 94%

Spatial Econometric Analysis of the Impact of Socioeconomic Factors on PM2.5 Concentration in China’s Inland Cities: A Case Study from Chengdu Plain Economic Zone

Yang

Lan

2019

IJERPH

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Particulate matter with a diameter less than 2.5 µm (PM2.5), one of the main sources of air pollution, has increasingly become a concern of the people and governments in China. Examining the socioeconomic factors influencing on PM2.5 concentration is important for regional prevention and control. Previous studies mainly concentrated on the economically developed eastern coastal cities, but few studies focused on inland cities. This study selected Chengdu Plain Economic Zone (CPEZ), an inland region with heavy smog, and used spatial econometrics methods to identify the spatiotemporal distribution characteristics of PM2.5 concentration and the socioeconomic factors underlying it from 2006 to 2016. Moran’s index indicates that PM2.5 concentration in CPEZ does have spatial aggregation characteristics. In general, the spatial clustering from the fluctuation state to the stable low state decreased by 1% annually on average, from 0.190 (p < 0.05) in 2006 to 0.083 (p < 0.1) in 2016. According to the results of the spatial Durbin model (SDM), socioeconomic factors including population density, energy consumption per unit of output, gross domestic product (GDP), and per capita GDP have a positive effect on PM2.5 concentration, while greening rate and per capita park space have a negative effect. Additionally, those factors have identified spatial spillover effects on PM2.5 concentration. This study could be a reference and support for the formulation of more efficient air pollution control policies in inland cities.

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“…Combined with the results in Figure 2, PM 2.5 and PM 10 were the main factors of the AECC overload in Xinjiang. However, the high PM 2.5 and PM 10 levels in Xinjiang were the result of natural factors, such as drought, low rain amounts, sparse vegetation, the extensive Gobi Desert and more wind [48][49][50], with human activities having a lower impact [51,52]. At the same time, some environmental experts in Xinjiang have pointed out that the monitoring data on PM 2.5 and PM 10 in Xinjiang are too high to truly evaluate the air quality of arid regions [53][54][55].…”

Section: Comparative Analysismentioning

confidence: 99%

Comparative Study of Environmental Assessment Methods in the Evaluation of Resources and Environmental Carrying Capacity—A Case Study in Xinjiang, China

et al. 2019

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Scientifically assessing the environmental carrying capacity (ECC) based on an evaluation of environmental quality standards (EQSs) holds great significance for establishing a long-term monitoring and early warning mechanism for resources and environmental carrying capacity (RECC) and for coordinating the sustainable development of ecological environments and regional economies. However, it remains unclear whether the evaluation of EQSs based on the short board effect is suitable for environmental assessments under different natural environments. In this research, Xinjiang is used as a case study. Based on the evaluation of EQSs, the atmospheric environmental carrying capacity (AECC), water environmental carrying capacity (WECC) and comprehensive environmental carrying capacity (CECC) are assessed using the short board effect and the weighted average. Additionally, the suitability of ECC evaluation in RECC evaluation is discussed. The results show the following: (1) In the atmosphere, the overload of inhalable particles (PM10) and fine particulate matter (PM2.5) is more serious, while in water, the overload of total nitrogen (TN) is more serious. (2) The percentages of the AECC, WECC and CECC in overloaded counties and cities based on the short board effect are 84%, 45%, and 51%, respectively, while the percentages based on the weighted average are 32%, 6% and 7%, respectively. (3) The extreme effects of a single pollutant can be eliminated by the weighted average, which is more suitable for environmental assessments in Xinjiang. (4) In evaluating RECC monitoring and early warning systems, weighted average evaluation is used to assess the elements, and short board effect evaluation is used in the comprehensive integration to prevent the influence of the amplification of a single index. Thus, the interference of non-key factors in the regional system on the final evaluation results is reduced.

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Spatiotemporal patterns of recent PM2.5 concentrations over typical urban agglomerations in China

Cited by 126 publications

References 49 publications

Air pollution episodes during the COVID-19 outbreak in the Beijing–Tianjin–Hebei region of China: An insight into the transport pathways and source distribution

Air pollution episodes during the COVID-19 outbreak in the Beijing–Tianjin–Hebei region of China: An insight into the transport pathways and source distribution

Spatial Econometric Analysis of the Impact of Socioeconomic Factors on PM2.5 Concentration in China’s Inland Cities: A Case Study from Chengdu Plain Economic Zone

Comparative Study of Environmental Assessment Methods in the Evaluation of Resources and Environmental Carrying Capacity—A Case Study in Xinjiang, China

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