Chen Rui, Sun Jianyun, Wei Qiaozhen, Fan Yufang
Gansu Provincial Center for Disease Control and Prevention, Lanzhou 730000, China.
Wei Sheng Yan Jiu. 2021 Sep;50(5):769-774. doi: 10.19813/j.cnki.weishengyanjiu.2021.05.011.
To study the distribution characteristics of atmospheric pollutants and their correlation with meteorological factors.
The PM_(2.5), PM_(10), NO_2, SO_2, O_(3-1 h), O_(3-8 h) and CO daily average concentration data from 2014 to 2020 were obtained from Lanzhou Environmental Protection Bureau. The interannual changes of pollutants, monthly changes, seasonal changes and trend of spatial distribution were analysed. Spearman correlation analysis was performed on the relationship among pollutants.
The main pollutants exceeding the standard in Lanzhou from 2014 to 2020 were PM_(10), PM_(2.5) and NO_2, average annual concentration of PM_(10), PM_(2.5), NO_2 and CO were decreasing year by year, and O_3 was increasing year by year. The monthly average concentration of PM_(10) was the highest in December, January, March and November were the second highest, and it was higher in February, April and May. The monthly change trends of PM_(2.5), NO_2, SO_2 and CO concentrations were the same, and the monthly change trends of the 1 hour average and daily maximum 8-hour average concentrations of O_3 were the same. The seasonal variation of atmospheric pollutant concentration was obvious, the concentrations of PM_(10), PM_(2.5), SO_2, NO_(2 )and CO were the highest in winter and the lowest in summer. O_3 concentration was the highest in summer and lowest in winter. Average annual concentration of 6 pollutants in different regions had statistically significant differences(H=750.40, 1112.99, 1410.05, 352.04, 360.17, 619.20, 729.52; P<0.001). Among them, the average annual concentration of PM_(10), PM_(2.5), SO_(2 )and O_(3-1 h) in Xigu District were the highest. PM_(10), PM_(2.5), NO_2, SO_2, CO average annual concentration were negatively correlated with temperature and wind speed(r_s=-0.423, -0.561, -0.395, -0.660, -0.569, -0.043, -0.094, -0.130, -0.172, -0.135), the concentration of PM_(10), PM_(2.5), O_3, SO_2 concentration were negatively correlated with humidity(r_s=-0.238, -0.121, -0.110, -0.094), only O_3 was positively correlated with temperature(r_s=0.486).
The primary pollutants in Lanzhou from 2014 to 2020 were PM_(10), PM_(2.5) and NO_2.O_3 had an obvious upward trend year by year. The 6 pollutants had obvious seasonal changes and regional distribution characteristics. Some pollutants had the same homology, and meteorological factors affected each pollution. The concentration of the substance had an important influence. Relevant air pollution control measures should be formulated based on the main excessive pollutants, the monthly change trend of air pollution and the seasonal pollution characteristics, the same emission sources and geographical distribution characteristics should be considered, and the meteorological factors should be combined.
研究大气污染物的分布特征及其与气象因素的相关性。
获取兰州市环境保护局2014年至2020年的PM₂.₅、PM₁₀、NO₂、SO₂、O₃-1h、O₃-8h和CO日平均浓度数据。分析污染物的年际变化、月变化、季节变化及空间分布趋势。对污染物之间的关系进行Spearman相关性分析。
2014年至2020年兰州市超标主要污染物为PM₁₀、PM₂.₅和NO₂，PM₁₀、PM₂.₅、NO₂和CO年均浓度逐年下降，O₃逐年上升。PM₁₀月平均浓度12月最高，1月、3月和11月次之，2月、4月和5月较高。PM₂.₅、NO₂、SO₂和CO浓度月变化趋势相同，O₃ 1小时平均浓度和日最大8小时平均浓度月变化趋势相同。大气污染物浓度季节变化明显，PM₁₀、PM₂.₅、SO₂、NO₂和CO浓度冬季最高，夏季最低。O₃浓度夏季最高，冬季最低。不同区域6种污染物年均浓度有统计学差异（H = 750.40、1112.99、1410.05、352.04、360.17、619.20、729.52；P < 0.001）。其中，西固区PM₁₀、PM₂.₅、SO₂和O₃-1h年均浓度最高。PM₁₀、PM₂.₅、NO₂、SO₂、CO年均浓度与温度和风速呈负相关（rₛ = -0.423、-0.561、-0.395、-0.660、-0.569、-0.043、-0.094、-0.130、-0.172、-0.135），PM₁₀、PM₂.₅、O₃、SO₂浓度与湿度呈负相关（rₛ = -0.238、-0.121、-0.110、-0.094），仅O₃与温度呈正相关（rₛ = 0.486）。
2014年至2020年兰州市主要污染物为PM₁₀、PM₂.₅和NO₂，O₃呈明显逐年上升趋势。6种污染物有明显的季节变化和区域分布特征，部分污染物具有同源性，气象因素对各污染物浓度有重要影响。应根据主要超标污染物、大气污染月变化趋势和季节污染特征制定相关大气污染控制措施，考虑相同排放源和地理分布特征，并结合气象因素。
