The Concentration and Variation Characteristics of Airborne Particulate Matters in Heavy and Light Pollution Areas of Hohhot

Objectives  To assess the concentration of particulate matters in heavy and light pollution areas of Hohhot and their variation tendencies.

Methods  The Future City Community in Huimin District of Hohhot was selected as the monitoring point of heavy pollution area, and the Wulanchabu East Road Community in Saihan District was selected as the monitoring point of light pollution area. The TH-150c intelligent medium flow sampler was used at two monitoring points to measure the concentrations of PM₁₀ and PM_2.5 of air particles for 24 h every day from 2014 to 2017. The annual average concentration was calculated by measuring the concentrations of daily particles. At the same time, the quarterly average concentration with the latest year's (2017) data for specific analysis was calculated. Chi-square test was used to compare and analyze the variation trend of air particle concentrations in the two monitoring points over the years.

Results  The PM₁₀ concentration differences in different years in Saihan District, a light pollution area in Hohhot, were statistically significant (H=110.661, P < 0.001). The highest was in 2014, decreased year by year from 2014 to 2016, and then picked up in 2017. The PM_2.5 concentration differences were statistically significant (H=33.178, P < 0.001). The highest was in 2014, decreased year by year from 2014 to 2016, and increased in 2017. The difference of PM₁₀ concentrations in the heavily polluted Huimin area was statistically significant in different years (H=33.475, P < 0.001). It was highest in 2014, declining year by year from 2014 to 2016, and picked up in 2017. The difference in PM_2.5 concentrations was statistically significant (H=57.582, P < 0.001), which was the highest in 2014, and increased year by year from 2015 to 2017. The PM₁₀ annual average concentration of Huimin district was higher than that of Saihan District, and the difference was statistically significant (Z=segregation 10.644, P < 0.001). The annual average concentration of PM_2.5 in Huimin district was higher than that in Saihan district, and the difference was statistically significant (Z=way10.189, P < 0.001). From 2014 to 2017, the number of days with excessive PM₁₀ and PM_2.5 in Huimin District was higher than that in Saihan.

Conclusions  The annual average concentration of PM₁₀ and PM_2.5 in Huimin was higher than that in Saihan, and high concentrations of high airborne particulate matter mainly appeared in winter. From 2014 to 2017, the concentrations of air particulate matters PM₁₀ and PM_2.5 in the two regions showed an overall downward trend.