Analysis of PM2.5 concentrations in Heilongjiang Province associated with forest cover and other factors

• Published in: Journal of forestry research Vol. 30; no. 1; pp. 269 - 276
• Main Authors: Zheng, Yu, Li, San, Zou, Chuanshan, Ma, Xiaojian, Zhang, Guocai
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 15.02.2019; Springer; Springer Nature B.V; College of Science, Northeast Forestry University, Harbin 150040, People's Republic of China%School of Forestry, Northeast Forestry University, Harbin 150040, People's Republic of China
• Subjects: Air pollution; Air quality; Analysis; Biomedical and Life Sciences; Cardiology; Cardiovascular diseases; Cities; Coronary artery disease; Deforestation; Forestry; Forests; Heart diseases; Heating; Life Sciences; Lung diseases; Nitrogen dioxide; Original Paper; Particulate emissions; Particulate matter; Pollutants; Pollution; Sulfur dioxide; Weather; PM2.5 concentrations; Forest cover; Random forest; Influencing factor; Heilongjiang Province
• ISSN: 1007-662X; 1993-0607
• DOI: 10.1007/s11676-018-0640-7

Atmospheric particulate matter (PM2.5) seriously influences air quality. It is considered one of the main environmental triggers for lung and heart diseases. Air pollutants can be adsorbed by forest. In this study we investigated the effect of forest cover on urban PM2.5 concentrations in 12 cities in Heilongjiang Province, China. The forest cover in each city was constant throughout the study period. The average daily concentration of PM2.5 in 12 cities was below 75 μg/m 3 during the non-heating period but exceeded this level during heating period. Furthermore, there were more moderate pollution days in six cities. This indicated that forests had the ability to reduce the concentration of PM2.5 but the main cause of air pollution was excessive human interference and artificial heating in winter. We classified the 12 cities according to the average PM2.5 concentrations. The relationship between PM2.5 concentrations and forest cover was obtained by integrating forest cover, land area, heated areas and number of vehicles in cities. Finally, considering the complexity of PM2.5 formation and based on the theory of random forestry, we selected six cities and analyzed their meteorological and air pollutant data. The main factors affecting PM2.5 concentrations were PM10, NO 2 , CO and SO 2 in air pollutants while meteorological factors were secondary.