Spatial distribution characteristics of gaseous pollutants and particulate matter inside a city in the heating season of Northeast China

Abstract

The aim of this paper is to analyze the distribution characteristics of gaseous pollutants (SO2 and NO2) and particulate matter (PM1.0, PM2.5 and PM10) and to explore the main factors affecting the distribution pattern of air pollutants inside Shenyang urban areas in the heating season of Northeast China. To achieve this goal, the concentration of five air pollutants on two main roads in the Shenyang four-ring area was measured by a vehicle-borne air pollutant monitor. Through analysis of the spatial distribution pattern of these air pollutants, it can be found that the average concentrations of SO2 for the three monitoring events are similar (43.1, 40.6 and 40.3 μg/m3), and the concentrations of NO2, PM1.0, PM2.5 and PM10 are the highest for the 20190304 event, followed by the 20190107 and 20181213 events. Pearson correlation was used to analyze the relationships of the gaseous pollutants and particulate matter based on the data from the three monitoring events. The results indicated that SO2 is negatively correlated with the other pollutants, while there are positive correlations among the other four pollutants. In particular, there is a strong positive correlation among the three classes of particulate matter (correlation coefficients > 0.97, p < 0.01). The relative contributions of environmental factors and landscape pattern factors to the air pollutants were analyzed by the BRT model. It is revealed that the environmental factors have a significant influence (relative contributions> 10 %) on air pollution, and temperature was the main influencing factor (relative contributions > 20 %). The findings obtained through this study can increase the understanding of the distribution pattern of air pollutants and their main influencing factors in the heating season of Northeast China and provide decision makers and urban planners with a scientific basis for the amelioration of air pollution via urban planning and management.