Spatio-temporal patterns of air pollution in China from 2015 to 2018 and implications for health risks

Guo

et al. 2020

IJERPH

The Beijing–Tianjin–Hebei (BTH) air pollution transmission channel and its surrounding areas are of importance to air pollution control in China. Based on daily data of air quality index (AQI) and air pollutants (PM2.5, PM10, SO2, NO2, CO, and O3) from 2015 to 2016, this study analyzed the spatial and temporal characteristics of air pollution and influencing factors in Henan Province, a key region of the BTH air pollution transmission channel. The result showed that non-attainment days and NAQI were slightly improved at the provincial scale during the study period, whereas that in Hebi, Puyang, and Anyang became worse. PM2.5 was the largest contributor to the air pollution in all cities based on the number of non-attainment days, but its mean frequency decreased by 21.62%, with the mean occurrence of O3 doubled. The spatial distribution of NAQI presented a spatial agglomeration pattern, with high-high agglomeration area varying from Jiaozuo, Xinxiang, and Zhengzhou to Anyang and Hebi. In addition, the NAQI was negatively correlated with sunshine duration, temperature, relative humidity, wind speed, and positively to atmospheric pressure and relative humidity in all four clusters, whereas relationships between socioeconomic factors and NAQI differed among them. These findings highlight the need to establish and adjust regional joint prevention and control of air pollution as well as suggest that it is crucially important for implementing effective strategies for O3 pollution control.

Section: Variations Of Naqisupporting

confidence: 89%

“…With rapid economic growth and dramatic increase in energy consumption, China has been experiencing serious environment problems related to air pollution, leading to adverse impacts on human health [1,2] and socioeconomic development [3]. The air pollution issue has attracted increasing attention of all aspects of the society [4,5].…”

Section: Introductionmentioning

confidence: 99%

Spatial Association Pattern of Air Pollution and Influencing Factors in the Beijing–Tianjin–Hebei Air Pollution Transmission Channel: A Case Study in Henan Province

Qin

Guo

et al. 2020

IJERPH

“…The transportation sector was the major factor for the reduction of NO 2 mass concentrations, indicating the control measures greatly reduced the pollution emissions caused by the movement of people. As a major pollutant emitted from the coal heating in winter (Kuerban et al, 2019), the mass concentration of SO 2 decreased the least, suggesting the emissions from coal heating activities were probably little affected by the control measures.…”

Section: Reducing Air Pollutionmentioning

confidence: 99%

“…1). Taken together, the sites can be considered representative of the overall air quality in China (Kuerban et al, 2019;Zhao et al, 2019).…”

Section: Study Area and Periodmentioning

confidence: 99%

“…The data had a time resolution of 1 h (http:// www.cnemc.cn). Previous studies have shown that data from China's National Environmental Monitoring Center are statistically reliable (Kuerban et al, 2019;Zhao et al, 2019). The AQI monitoring values calculated from the six priority pollutants (Bai et al, 2019) and the data for the individual pollutants themselves were averaged for the periods prior to and during the Covid-19 controls.…”

Section: Data Sourcesmentioning

confidence: 99%

See 1 more Smart Citation

Changes in air quality related to the control of coronavirus in China: Implications for traffic and industrial emissions

Yuan

Science of The Total Environment

et al. 2020

255

201

Env Prog and Sustain Energy

Analysis on temporal variation law of ozone pollution and meteorological driving factors in Pudong New Area of Shanghai

Guan

Geng

Yang³

et al. 2023

In order to deeply understand the influence of meteorological drivers on ozone (O3) pollution during the high season and explore O3 pollution control options, we analyzed the temporal variation characteristics of O3 pollution based on the ambient air observation data of Pudong New Area, Shanghai from 2020 to 2021, studied the influence of meteorological drivers on O3 pollution, and explored seasonal emission reduction options based on the results of EKMA (Empirical Kinetics Modeling Approach) curves. The results show that the seasonal O3 concentration variation is spring > summer > autumn > winter; relative humidity, temperature and wind speed are the main meteorological drivers of O3 pollution; the cross‐regional transport of high O3 concentrations and precursors from the south and southwest has a strong influence on the local O3 concentration; Pudong New Area is in the “VOCs control zone” during the O3 pollution period in May. Therefore, it is important to control the production and emission of local VOCs and to strengthen the synergistic control of O3 and its precursors between regions for the control of spring O3 in Pudong New Area.