Literature DB >> 30640107

Properties of particulate matter and gaseous pollutants in Shandong, China: Daily fluctuation, influencing factors, and spatiotemporal distribution.

Youru Yao1, Cheng He2, Shiyin Li3, Weichun Ma4, Shu Li4, Qi Yu4, Na Mi5, Jia Yu5, Wei Wang5, Li Yin5, Yong Zhang6.   

Abstract

Characteristics of the spatial and temporal distribution of air pollutants may reveal the cause of air pollution, especially for large regions where the anthropogenic pollutant emission is concentrated. This study addresses this issue by focusing on Shandong province, which has the highest air pollutant emissions in China. First, the spatial and temporal variation characteristics of the observed concentrations of conventional pollutants are analyzed in detail. The most prominent indicator of the problem (PM2.5), was selected as the key analytical object. On the spatial scale, the Multivariate Moran model was used to identify factors affecting the spatial distribution of PM2.5. On the time scale, wavelet analysis was used to explore the fluctuation characteristics of PM2.5 at different time periods. Results show that there are significant regional differences in pollutant concentration within Shandong province. The concentration of particulate matter and gaseous pollutants in western and northern Shandong is significantly higher than eastern Shandong. The average concentrations of PM2.5, PM10, SO2 and NO2 were highest in winter and lowest in summer, whereas concentration of O3 peaked in summer. For PM2.5, the annual mean concentration has a significant spatial correlation with SO2 emission, GDP per capita, population density and energy consumption per unit of GDP; in addition, the correlation between different regions and various indices is different. On the time scale, the fluctuation energy of PM2.5 concentrated in Dezhou and Liaocheng is the strongest on December 18 and 19, 2015. The inversion temperature has a strong influence on the daily variation of PM2.5 concentration. The formation and evolution of atmospheric pollution, therefore, can be explored by combining the temporal and spatial distribution of pollutants, providing a comprehensive analytical method for atmospheric pollution in different regions.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Air particulate matter and other pollutants; China; Daily fluctuations; Temporal and spatial distribution

Year:  2019        PMID: 30640107     DOI: 10.1016/j.scitotenv.2019.01.026

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  4 in total

1.  Spatial variation in biodiversity loss across China under multiple environmental stressors.

Authors:  Yonglong Lu; Yifu Yang; Bin Sun; Jingjing Yuan; Minzhao Yu; Nils Chr Stenseth; James M Bullock; Michael Obersteiner
Journal:  Sci Adv       Date:  2020-11-20       Impact factor: 14.136

2.  Study on Air Quality and Its Annual Fluctuation in China Based on Cluster Analysis.

Authors:  Shengyong Zhang; Yunhao Chen; Yudong Li; Xing Yi; Jiansheng Wu
Journal:  Int J Environ Res Public Health       Date:  2022-04-08       Impact factor: 4.614

3.  Evaluation and Treatment Analysis of Air Quality Including Particulate Pollutants: A Case Study of Shandong Province, China.

Authors:  Bowen Jiang; Yuangang Li; Weixin Yang
Journal:  Int J Environ Res Public Health       Date:  2020-12-17       Impact factor: 3.390

4.  Spatiotemporal Variation in Ground Level Ozone and Its Driving Factors: A Comparative Study of Coastal and Inland Cities in Eastern China.

Authors:  Mengge Zhou; Yonghua Li; Fengying Zhang
Journal:  Int J Environ Res Public Health       Date:  2022-08-05       Impact factor: 4.614

  4 in total

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