title: Air pollution characteristics and their relation to meteorological conditions during 2014-2015 in major Chinese cities.
abstract: In January 2013, the real-time hourly average concentrations of six pollutants (CO, NO2, O3, PM10, PM2.5and SO2) based on data from air quality monitoring stations in major Chinese cities were released to the public. That report provided a good opportunity to publicise nationwide temporal and spatial pollution characteristics. Although several studies systematically investigated the temporal and spatial trends of pollutant concentrations, the relation between air pollution and multi-scale meteorological conditions and their spatial variations on a nationwide scale remain unclear. This study analysed the air pollution characteristics and their relation to multi-scale meteorological conditions during 2014-2015 in 31 provincial capital cities in China. The annual average concentrations of six pollutants for 31 provincial capital cities were 1.2 mg m-3, 42.4 μg m-3, 49.0 μg m-3, 109.8 μg m-3, 63.7 μg m-3, and 32.6 μg m-3in 2014. The annual average concentrations decreased 5.3%, 4.9%, 11.4%, 12.0% and 21.5% for CO, NO2, PM10, PM2.5and SO2, respectively, but increased 7.4% for O3in 2015. The highest rate of a major pollutant over China was PM2.5followed by PM10, O3, NO2, SO2and CO. Meteorological conditions were the primary factor determining day-to-day variations in pollutant concentrations, explaining more than 70% of the variance of daily average pollutant concentrations over China. Meteorological conditions in 2015 were more adverse for pollutant dispersion than in 2014, indicating that the improvement in air quality was caused by emission controls.
authors.affiliation: State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China; The College of Environmental Science & Engineering, Nankai University, Tianjin 300071, China. Electronic address: hejianjun@camscma.cn.
authors.forename: Jianjun
authors.initials: J
authors.lastname: He
authors.affiliation: State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
authors.forename: Sunling
authors.initials: S
authors.lastname: Gong
authors.affiliation: Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China.
authors.forename: Ye
authors.initials: Y
authors.lastname: Yu
authors.affiliation: Jinan Meteorological Bureau, Jinan 250002, China.
authors.forename: Lijuan
authors.initials: L
authors.lastname: Yu
authors.affiliation: The College of Environmental Science & Engineering, Nankai University, Tianjin 300071, China.
authors.forename: Lin
authors.initials: L
authors.lastname: Wu
authors.affiliation: The College of Environmental Science & Engineering, Nankai University, Tianjin 300071, China.
authors.forename: Hongjun
authors.initials: H
authors.lastname: Mao
authors.affiliation: The College of Environmental Science & Engineering, Nankai University, Tianjin 300071, China.
authors.forename: Congbo
authors.initials: C
authors.lastname: Song
authors.affiliation: Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China.
authors.forename: Suping
authors.initials: S
authors.lastname: Zhao
authors.affiliation: State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
authors.forename: Hongli
authors.initials: H
authors.lastname: Liu
authors.affiliation: The College of Environmental Science & Engineering, Nankai University, Tianjin 300071, China.
authors.forename: Xiaoyu
authors.initials: X
authors.lastname: Li
authors.affiliation: The College of Environmental Science & Engineering, Nankai University, Tianjin 300071, China.
authors.forename: Ruipeng
authors.initials: R
authors.lastname: Li
mesh_terms: D000393:Air Pollutants / Q000032:analysis; D000397:Air Pollution / Q000032:analysis; D002681:China; D002947:Cities; D004784:Environmental Monitoring; D052638:Particulate Matter / Q000032:analysis; D014887:Weather
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter
keywords: Air pollution; Artificial neural network; Emission control; Meteorological conditions