The Temporal And Spatial Variations Of PM_2.5 And PM₁₀ In Suzhou And Their Driving Factors

In nearly a decade, with the rapid development of economic construction and urbanization, the high level of Particulate Matter (PM) concentration events happens frequently in China, especially in the developed Yangtze River Delta economically. It not only affected seriously the air quality, urban ecological environment and economic development, and also harms the health of the residents. So improving air quality has become the most urgent problem for the society and government.Suzhou as a representative city of Yangtze River Delta, researching the spatial and temporal distribution of PM2.5and PM10in Suzhou has the vital significance.This study will be of great practical guidance to improve urban planning, and can provide a scientific basis for emission reduction measures.In this paper, we present detailed analyses on the observational data of air pollutants such as PM2.5, PM10, NO, NO2, SO2, CO, and O3, and meteorological variables such as the temperature, wind speed, and wind direction, relative humidity at Suzhou, Kunshan, Taicang in2012. Using these data, we analyze the temporal-spatial variations in PM2.5and PM10; we use the BP neural network (Back Propagation Neural Network) model, to quantify the relative impact of meteorological and chemical factors on PM2.5and PM10concentrations; we present a detailed analysis to examine impacts of adifferent meteorological conditions on a typically high concentration of PM2.5events. The results show:(1) Typical diurnal and seasonal variations are identified in PM2.5and PM10in Suzhou and its surrounding regions. The peak value of PM2.5was observed around8-9LST (local standard time) coinciding with traffic hours. This indicates that anthropogenic emissions such as mobile sources dominate PM2.5concentrations. The maximum monthly mean PM2.5appeared in Spring whereas the minimum monthly mean PM2.5in summer. This implies that meteorological conditions govern the seasonal variations of PM2.5. The annual average PM2.5(42.5μ/m3) and PM10(88.5μg/m3) in Suzhou were much lower than those in surrounding regions (62.0μg/m3for PM2.5and111.5μ/m3for PM10).; In addition, the minimum ratio of PM2.5to PM10is observed in April and the maximumin June, implying the relative contribution of primary and secondary particulate matter to PM2.5and PM10in different seasons.(2) The calculations with BP neural network model show that different meteorological factors impose different impacts on PM2.5and PM10-Wind speed is the key factor of PM2.5concentration, and followed by temperature, precipitation in Suzhou and Kunshan. Precipitation exerts the most important impact PM10, followed by wind speed and temperature. NO and SO2are the two most important chemical factors to PM2.5at Suzhou and Kunshan. NOx has the greatest influence on PM10concentrations.(3) By analyzing the meteorological characteristics during high PM concentrations pollution process, the four characteristics of the atmosphere were found followed as the atmosphere gas was stable; the temperature rose gradually; wind speed was small in the boundary layer; Air relative humidity decreased. These unfavorable factors caused the accumulation of the pollutants and not easy to spread. But with the advent of the cold air, atmospheric circulation situation changed; boundary layer appeared unstable stratification; relative humidity increased. Rainfall and strong wind could very well play the role of clearing and diluting pollutants. In the end, pollutant concentration quickly reduced to normal levels.