【摘要】 基于2016年安徽省空气质量监测站的O₃数据,分析O₃的时空分布特征,运用地理探测器方法,探讨O₃浓度的影响因素。结果表明:①2016年安徽省O₃浓度在季度上呈现春夏高、秋冬低的规律;在月度上5—9月O₃浓度中位值较高,1月、2月、12月O₃浓度中位值较低;O₃浓度日变化总体呈单峰型,最高值出现在下午15:00,最低值出现在7:00。②安徽省O₃浓度空间分布总体为北高南低。③因子探测结果表明,对臭氧浓度影响较大的因子有PM₁₀、CO、相对湿度、气压、降水量、日照时数、风速、PM_2.5、第三产业产值、工业企业个数、工业废气排放量、全社会用电量及公路里程。交互探测分析表明,不同因子间的交互作用,正向强化了各因子的解释力,最大交互因子为相对湿度∩公路里程,降水量∩气温,CO∩常住人口。更多还原

【Abstract】 This study is based on the O₃ data of the 2016 Anhui Air Quality Monitoring Substation,analyzes the temporal and spatial distribution characteristics of O₃,and uses the geo-detector method to explore the influencing factors of O₃ concentration.The results show that:①In 2016,the concentration of O₃ in Anhui Province showed a pattern of high in spring and summer and low in autumn and winter.The median value of O₃ concentration in May-September was higher,and the concentration of O₃ in January,February and December was higher.The median value was lower;the daily variation of O₃ concentration was generally unimodal,with the highest value occurring at 15:00 pm and the lowest value appearing at 7:00.②The spatial distribution of O₃ concentration in Anhui province is generally high in North and South.③Factor detection results show that the factors that have a greater impact on ozone concentration are PM₁₀,CO,relative humidity,air pressure,precipitation,sunshine hours,wind speed,PM_2.5,tertiary industry output value,number of industrial enterprises,industrial exhaust emissions,total social electricity consumption and highway mileage.The interactive detection analysis shows that the interaction between different factors positively enhances the explanatory power of each factor.The maximum interaction factor is relative humidity∩highway mileage,precipitation∩temperature,CO∩resident population.更多还原