Abstract
Abstract Air pollution is one of the most serious environmental problems faced by mankind. It is regional and highly complex, and it is more prominent in China. With the development of air quality management in China, the research on cross-regional transmission of air pollutants is particularly important. This paper reports on pollution characteristics, transport path, and distribution of pollution sources of major contaminants in Shenyang. For this purpose, pollution-monitoring data were gathered from November 2017 to March 2018. Data were analyzed using the HYSPLIT back trajectory model, the potential source contribution function (PSCF), and the concentration weighted trajectory (CWT) model. Results indicated that PM2.5 was the main pollutant in Shenyang during the study period. Air pollution was mainly affected by coal combustion, traffic emissions, and long-distance transmission. Among the 11 monitoring points, the pollution of Shenliaoxilu was relatively serious. Mongolia, eastern Inner Mongolia, northwestern Jilin, and most of Liaoning were the main potential sources of PM2.5 in Shenyang during the winter.
Highlights
Air pollution has become a global challenge; it has harmful effects on health, ecology, and people’s lives [1]
When the concentration is higher than the standard value determined by the user, the obtained potential source contribution function (PSCF) value can be regarded as a conditional probability associated with the trajectory of the air mass having the PSCF value reaching the research site through the mesh unit
The time series of CO, O3, SO2, and NO2 particulate matter with aerodynamic diameters of
Summary
Air pollution has become a global challenge; it has harmful effects on health, ecology, and people’s lives [1]. In January 2018, the monthly average maximum concentration of PM2.5, PM10, SO2, and NO2 in 74 major cities in China were 141, 191, 69, and 76 μg/m3, respectively [6]. Hourly PM2.5, PM10, SO2, NO2, O3, and CO concentrations were obtained from the national air quality-monitoring network in 11 different stations in Shenyang. This information was combined with meteorological data so as to analyze the spatial and temporal distribution characteristics of air pollutants in Shenyang. It is possible to identify potential sources of environmental pollutants This will assist decision-makers in designing effective strategies for air pollution control.
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