卫生研究

目的了解西安市莲湖区和雁塔区PM_2.5质量浓度的变化特征及其与气象条件的关系。方法 2015—2018年,根据2012年西安市6个主城区全部环保站点的环保监测数据,包括NO₂、SO₂,PM₁₀、PM_2.5、CO和O₃,选择上述污染物浓度相对较高的莲湖区和相对较低的雁塔区分别采集空气样本,按照国家环保部《环境空气PM₁₀和PM_2.5的测定重量法》(HJ 618—2011)开展PM_2.5的质量浓度检测。依据《环境空气质量标准》(GB 3095—2012)中日均二级浓度限值标准(75μg/m³),按照不同年度、区域和季节对检测结果分别开展统计分析和评价。收集同期西安市气象局气象数据资料,包括日平均温度、日平均气压、日均相对湿度、日平均风速、日降水量、最高温度和最低温度,分析PM_2.5质量浓度与气象影响因素的关系。结果共采集分析空气样本660份,PM_2.5质量浓度中位数为71μg/m³,达标356份,样本总达标率为53.94%,4年样本达标率由高到低依次为2017年>2018年>2016年>2015年(P<0.001),全部样品PM_2.5质量浓度平均水平由高到低依次为2015年>2016年>2017年>2018年(P<0.001)。样本达标率和PM_2.5质量浓度在莲湖区、雁塔区间的差异均无统计学意义(P>0.05)。不同季节样品达标率由高到低依次为夏季>春季>秋季>冬季(P<0.05);不同季节PM_2.5质量浓度平均水平由高到低依次为冬季>秋季>春季>夏季(P<0.001)。日均温度、日均气压、日均风速、日均相对湿度、降水量和最低温度同PM_2.5质量浓度显著相关(P<0.001)。莲湖区和雁塔区气象因素多元回归分析的调整后R²分别为0.390和0.373。结论西安市两城区空气质量逐年改善,秋冬季PM_2.5污染较为严重。气象因素影响大气中PM_2.5质量浓度水平。

OBJECTIVE To master the variation characteristics of PM_2.5 mass concentration in Lianhu district and Yanta district of Xi'an City and its relationship with meteorological conditions. METHODS From 2015 to 2018, according to the environmental monitoring data of six main urban areas in Xi'an City in 2012, including NO₂, SO₂, PM₁₀, PM_2.5, CO and O₃, air samples were collected in the relatively heavy polluted Lianhu district and the relatively light Yanta district of Xi'an City. The mass concentration test of PM_2.5 was carried out in accordance with the Ministry of Environmental Protection's "Determination of atmospheric articles PM₁₀ and PM_2.5 in ambient air by gravimetric method "(HJ 618-2011). According to the Ambient air quality standards(GB 3095-2012), the average daily secondary concentration limit(75 μg/m³) was used for statistical analysis and evaluation according to different annual, regional and seasonal test result. Meteorological data of Xi'an City were collected, including daily average temperature, daily average pressure, daily average relative humidity, daily average wind speed, daily precipitation, maximum temperature and minimum temperature, and the relationship between PM_2.5concentration and meteorological factors was analyzed. RESULTS A total of 660 air samples were collected and qualified, the median concentration of PM_2.5 was 71 μg/m³.356 air samples were qualified, and the pass rate was 53.94%.The sample pass rate for each year from high to low was 2017>2018>2016>2015(P<0.001), The average level of PM_2.5 mass concentration from high to low was 2015>2016>2017>2018(P<0.001). There was no significant difference in the sample pass rate and PM_2.5mass concentration between Lianhu district and Yanta district(P>0.05). The qualified rate of samples from high to low in different seasons was summer>spring> autumn>winter(P<0.05). The average concentration of PM_2.5 in different seasons from high to low was winter>autumn>spring>summer(P<0.001). Mean temperature, mean air pressure, average wind speed, average relative humidity, precipitation and lowest temperature were significantly correlated with PM_2.5 mass concentration(P<0.001). The determination coefficients of multiple regression analysis of meteorological factors in Lianhu and Yanta regions were 0.390 and 0.373, respectively. CONCLUSION The air quality in Lianhu district and Yanta district of Xi'an City had improved year by year, and the pollution of PM_2.5 in autumn and winter was more serious. Meteorological conditions affected the concentration level of PM_2.5 in the atmosphere.