Elucidating the Chemical Compositions and Source Apportionment of Multi-Size Atmospheric Particulate (PM<sub>10</sub>, PM<sub>2.5</sub> and PM<sub>1</sub>) in 2019–2020 Winter in Xinxiang, North China
Huanjia Liu,
Mengke Jia,
Ke You,
Jingjing Wang,
Jie Tao,
Hengzhi Liu,
Ruiqin Zhang,
Lanqing Li,
Mengyuan Xu,
Yan Ren,
Yijie Zhao,
Yongli Liu,
Ke Cheng,
Yujuan Fan,
Juexiu Li
Affiliations
Huanjia Liu
Key Laboratory of Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang 453007, China
Mengke Jia
Key Laboratory of Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang 453007, China
Ke You
Henan Environment Monitoring Center, Zhengzhou 450001, China
Jingjing Wang
Zhengzhou Ecological and Environmental Monitoring Center of Henan Province, Zhengzhou 450001, China
Jie Tao
Zhengzhou Ecological and Environmental Monitoring Center of Henan Province, Zhengzhou 450001, China
Hengzhi Liu
Key Laboratory of Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang 453007, China
Ruiqin Zhang
School of Ecology & Environment, Zhengzhou University, Zhengzhou 450001, China
Lanqing Li
Key Laboratory of Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang 453007, China
Mengyuan Xu
Key Laboratory of Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang 453007, China
Yan Ren
Key Laboratory of Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang 453007, China
Yijie Zhao
Key Laboratory of Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang 453007, China
Yongli Liu
Key Laboratory of Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang 453007, China
Ke Cheng
Key Laboratory of Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang 453007, China
Yujuan Fan
Key Laboratory of Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang 453007, China
Juexiu Li
School of Ecology & Environment, Zhengzhou University, Zhengzhou 450001, China
The pollution characteristics of multi-size atmospheric particulates in Xinxiang, which was one of the most polluted cities across China, are still unclear even through air quality in Xinxiang has been improved in recent years. PM10, PM2.5, and PM1 samples were synchronously collected from 21 December 2019 to 17 January 2020 to explore pollution levels and reveal sources of PM in Xinxiang. The average mass concentrations of PM10, PM2.5, and PM1 were as high as 155.53 μg m−3, 120.07 μg m−3, and 85.64 μg m−3 during the observation period, respectively. Almost all of the chemical compositions in PM10, PM2.5 and PM1 increased continuously and obviously with the aggravation of the pollution level. Compared with the clean period, the enhancement of sulfate (23–27%) in PM was obvious higher than nitrate (19–22%) during the pollution period, which demonstrated that sulfate was the main contributor to the high concentration of PM in this study. Similar source distributions for PM10, PM2.5, and PM1 were also found, including traffic source, combustion source, secondary aerosols, industrial source, and fugitive dust, by using the positive matrix factorization (PMF) model. Furthermore, the contributions of the combustion source and secondary aerosol were found to be higher in smaller particles (PM2.5 and PM1), while the contribution of fugitive dust was higher in PM10. Moreover, dust and sand were entrained by air masses from the northwest that increased the contribution of dust in PM at the observation site. The potential source contribution function (PSCF) analysis illustrated that regional emission sources in northern and eastern Xinxiang might be important potential contributors to PM pollution in Xinxiang.
