| Issue |
E3S Web of Conf.
Volume 379, 2023
2023 13th International Conference on Future Environment and Energy (ICFEE 2023)
|
|
|---|---|---|
| Article Number | 01001 | |
| Number of page(s) | 7 | |
| Section | Air Pollution Monitoring and Assessment | |
| DOI | https://doi.org/10.1051/e3sconf/202337901001 | |
| Published online | 06 April 2023 | |
Investigating the spatio-temporal pattern of PM2.5 concentrations in Jiangsu Province, China
1 Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, China
2 School of Geography, Nanjing Normal University, Nanjing 210023, China
3 Jiangsu Center for Collaborative Innovation in Geographical Information, Resource Development and Application, Nanjing 210023, China
4 Department of Chemistry, COMSATS University Islamabad, Pakistan
5 School of Information and Communication Engineering, Hainan University, Haikou, China
* Corresponding author: shengyehua@njnu.edu.cn
PM2.5 is a typical air pollutant which has harmful health effects worldwide, particularly in the developing countries such as China due to significant air pollution. The objectives of this study were to investigate the spatio-temporal pattern of PM2.5 concentration in Jiangsu Province, China. The data were collected from 72 monitoring stations between 2018-21 and the HYSPLIT model was used to study the transport pathways of air masses. According to the obtained results, the concentration of PM2.5 was obvious during the study duration. The results show that the concentration of PM2.5 was constantly decreased from 2018 to 2021, while the level of PM2.5 was higher in winter and lower in summer in Jiangsu. The backward trajectory analysis revealed that the trajectories were originated from the Siberia, Russia and passed thorough Mongolia and northwestern parts of China then reached at the study spot. These air masses played a significant role in aerosol pathway and affect the air quality of Jiangsu.
Key words: Spatio-temporal / PM2.5 / HYSPLIT model / Jiangsu province / China
© The Authors, published by EDP Sciences, 2023
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