Spatial-temporal variation characteristics of air pollution and apportionment of contributions by different sources in Shanxi province of China

Bai, Xiaoxuan; Tian, Hanqin; Li, Xiangyang; Wu, Bobo; Liu, Shuhan; Hao, Yan; Luo, Lining; Liu, Wei; Zhao, Shuang; Lin, Shu‐Min; Hao, Jiming; Guo, Zhihui; Lv, Yaping

doi:10.1016/j.atmosenv.2020.117926

Cited by 29 publications

(17 citation statements)

References 44 publications

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“…Another concern is emissions from residential properties. A recent study found that the contribution of homes to PM2.5 in the region during the winter months is 19.1% (Bai et al, 2021). Residential are the main activity location for most citizens at night.…”

Section: Exposure Surface In Non-heating and Heating Seasonsmentioning

confidence: 99%

Potential for developing independent daytime/nighttime LUR models based on short-term mobile monitoring to improve model performance

Qin

Yang

et al. 2021

Environmental Pollution

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Land use regression model (LUR) is a widespread method for predicting air pollution exposure. Few studies have explored the performance of independently developed daytime/nighttime LUR models. In this study, fine particulate matter (PM 2.5 ), inhalable particulate matter (PM 10 ), and nitrogen dioxide (NO 2 ) concentrations were measured by mobile monitoring during non-heating and heating seasons in Taiyuan. Pollutant concentrations were higher in the nighttime than the daytime, and higher in the heating season than the non-heating season. Daytime/nighttime and full-day LUR models were developed and validated for each pollutant to examine variations in model performance. Adjusted coefficients of determination (adjusted R 2 ) for the LUR models ranged from 0.53e0.87 (PM 2.5 ), 0.53e0.85 (PM 10 ), and 0.33e0.67 (NO 2 ). The performance of the daytime/nighttime LUR models for PM 2.5 and PM 10 was better than that of the full-day models according to the results of model adjusted R 2 and validation R 2 . Consistent results were confirmed in the non-heating and heating seasons. Effectiveness of developing independent daytime/nighttime models for NO 2 to improve performance was limited. Surfaces based on the daytime/nighttime models revealed variations in concentrations and spatial distribution. In conclusion, the independent development of daytime/nighttime LUR models for PM 2.5 /PM 10 has the potential to replace full-day models for better model performance. The modeling strategy is consistent with the residential activity patterns and contributes to achieving reliable exposure predictions for PM 2.5 and PM 10 . Nighttime could be a critical exposure period, due to high pollutant concentrations.

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Section: Exposure Surface In Non-heating and Heating Seasonsmentioning

confidence: 99%

Potential for developing independent daytime/nighttime LUR models based on short-term mobile monitoring to improve model performance

Qin

Yang

et al. 2021

Environmental Pollution

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“…Linfen is located in Shanxi Province and represents one of the most polluted cities in China ( Bai et al, 2021 ; Li et al, 2020a ). A prior study in Linfen suggested that coal combustion and traffic emissions were the dominant sources of non-cancer risk and cancer risk, respectively, during haze episodes ( Lin et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Potential health risks of inhaled toxic elements and risk sources during different COVID-19 lockdown stages in Linfen, China

Wang

Liu

Zhang

et al. 2021

Environmental Pollution

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Levels of toxic elements in ambient PM 2.5 were measured from 29 October 2019 to 30 March 2020 in Linfen, China, to assess the health risks they posed and to identify critical risk sources during different periods of the COVID-19 lockdown and haze episodes using positive matrix factorization (PMF) and a health-risk assessment model. The mean PM 2.5 concentration during the study period was 145 μg/m 3 , and the 10 investigated toxic elements accounted for 0.31% of the PM 2.5 mass. The total non-cancer risk (HI) and total cancer risk (TCR) of the selected toxic elements exceed the US EPA limits for children and adults. The HI for children was 2.3 times that for adults for all periods, which is likely due to the high inhalation rate per unit body weight for children. While the TCR for adults was 1.7 times that of children, which is mainly attributed to potential longer exposure duration for adults. The HI and TCR of the toxic elements during full lockdown were reduced by 66% and 58%, respectively, compared to their pre-lockdown levels. The HI and TCR were primarily attributable to Mn and As, respectively. Health risks during haze episodes were significantly higher than the average levels during COVID-19 lockdowns, though the HI and TCR of the selected toxic elements during full-lockdown haze episodes were 68% and 17% lower, respectively, than were the levels during pre-lockdown haze episodes. During the study period, fugitive dust and steel-related smelting were the highest contributors to HI and TCR, respectively, and decreased in these emission sources contributed the most to the lower health risks observed during the full lockdown. There, the control of these sources is critical to effectively reduce public health risks.

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“…However, it is still necessary to analyze the emission reduction causes of gaseous pollutants in this complex scenario so as to determine the main contributor of gaseous pollutants in the region, namely, the focus of pollution control. As for source analyses of atmospheric pollutants, the research methods mainly focus on component analysis (Garbariene et al 2020) and model analysis (Bai et al 2021). In addition, through the induction and analysis of social development data in the research area (e.g., relevant data of economy, road traffic transportation, and industrial production) and comparative analysis of the changes in the pollutant mass concentration, the causes of pollutant emission reduction can also be explored.…”

Section: Analysis Of Spatial Distribution Changes Of No 2 and So 2 In Different Phasesmentioning

confidence: 99%

Spatial and temporal variation characteristics of atmospheric NO2 and SO2 in the Beijing-Tianjin-Hebei region before and after the COVID-19 outbreak

Shen

Zhao

Zhou

et al. 2021

Air Qual Atmos Health

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Emergency response mechanisms were activated throughout China during the COVID-19 outbreak. It is different from the temporary, partial, and limited pollution control measures taken to ensure the regional environmental quality during several important events such as the 2008 Beijing Olympic Games and the 2014 Asia-Pacific Economic Cooperation (APEC). During the COVID-19 epidemic period, extensive movement of people and almost all unnecessary industrial production (necessary industrial production refers to the production of food, epidemic prevention materials, etc.) have been severely restricted, so transportation and industrial production have been greatly reduced. This is a rare extreme emission reduction scenario that presents a unique opportunity for atmospheric research. In this study, based on hourly mass concentration data of NO 2 and SO 2 from atmospheric monitoring sites in the Beijing-Tianjin-Hebei (BTH) region during the COVID-19 epidemic period, the changes in transportation and industrial production in the region, data statistics, and spatial analysis were used to analyze the pollution changes and their causes. The results indicate that the NO 2 and SO 2 concentrations in the BTH region decreased significantly during the epidemic period. The spatial distribution pattern of NO 2 pollution in the BTH region was "high in the southeast and low in the northwest," and SO 2 pollution in the BTH region was high in the southern and eastern parts of Hebei. The initiation of emergency response level 1 had an obvious effect on reducing NO 2 and SO 2 pollution in the region, while the impact of emergency response level 2 and below was limited. Compared with the single traffic control, the comprehensive control, similar to the emergency response, had a better effect on reducing NO 2 pollution in the region. The control of major large cities in the region also had a certain effect on alleviating NO 2 and SO 2 pollution in the entire region. Moreover, for activities under short-term control, it is particularly important to guard against the "retaliatory growth" after the control is lifted. By reducing and controlling some polluting industries in industrial production, the degree of NO 2 and SO 2 pollution in the region can be effectively reduced. The manufacturing industry of chemical raw materials and the chemical products and non-metallic mineral products industry made a great contribution to the change in industrial source pollution emissions in the BTH region during the COVID-19 epidemic. Road traffic emissions remained an important source of NO 2 emissions in the BTH region during this period. NO 2 emission reduction can be effectively achieved by controlling road traffic and transportation.

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Spatial-temporal variation characteristics of air pollution and apportionment of contributions by different sources in Shanxi province of China

Cited by 29 publications

References 44 publications

Potential for developing independent daytime/nighttime LUR models based on short-term mobile monitoring to improve model performance

Potential for developing independent daytime/nighttime LUR models based on short-term mobile monitoring to improve model performance

Potential health risks of inhaled toxic elements and risk sources during different COVID-19 lockdown stages in Linfen, China

Spatial and temporal variation characteristics of atmospheric NO2 and SO2 in the Beijing-Tianjin-Hebei region before and after the COVID-19 outbreak

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