天津市“十三五”期间O3污染特征和驱动因子

为了解“十三五”期间天津市O₃污染特征和驱动因素,基于2016～2020年高时空分辨率的在线监测数据,利用空间自相关、空间热点分析和STIRPAT模型分析了O₃污染空间分布、聚集特征和驱动因子.结果表明,2016～2020年天津市O₃浓度变化特征呈现污染发生时间点提前和污染范围扩大的趋势.6～10月O₃污染分布具有显著聚集性,高值-高值聚集区主要为市内六区、北辰区、津南区和静海区,O₃浓度在西南部地区形成高值热点聚集区,在东北部地区形成低值冷点聚集区.气温、小风百分率和日照时数等气象因子与NO_x排放量、 VOCs排放量和机动车保有量等社会因子对O₃浓度有显著性影响,综合驱动STIRPAT模型的回归拟合效果比单一气象因子或社会因子模型更好.为科学高效地开展“十四五”期间O₃污染的防治,在关注气象条件基础上,在“双碳”目标的约束下,天津市应进一步提升钢铁、石化、火电和建材等行业全过程排放的绩效水平,引导企业清洁化提升...

Characteristics and Driving Factors of O3 Pollution During 13th Five-Year Period in Tianjin

The spatial distribution, accumulation features, and driving factors of O₃ pollution were analyzed using spatial autocorrelation and hotspot analysis and the STIRPAT model based on the high spatiotemporal resolution online monitoring data from 2016 to 2020 in Tianjin. The results showed that the variation characteristics of O₃ concentration in Tianjin from 2016 to 2020 had the trend of pollution occurring in advance and the scope of the pollution expanding. The distribution of O₃ pollution showed significant aggregation from June to October. High-high value clustering areas included six urban districts, Beichen District, Jinnan District, and Jinghai District. O₃ concentration formed high value hot spots in the southwest and low value cold spots in the northeast. Meteorological factors such as temperature, breeze percentage, and sunshine duration, as well as social factors such as NO_x emission, VOCs emission, and motor vehicle ownership had significant effects on O₃ concentration. The regression fitting effect of the integrated drive STIRPAT model was better than that of the single meteorological factor or social factor models. In order to promote scientific and efficient prevention and control of ozone pollution during the 14^th Five-Year Plan period, meteorological conditions require attention; under the goal of "peaking carbon dioxide emissions and achieving carbon neutrality," it is necessary for Tianjin to further improve the emission performance of steel, petrochemicals, thermal power, building materials, and other industries, Additionally, clean upgrading, transformation, and green development should be guided for enterprises to reduce VOCs and NO_x emissions. At same time, the increase in fuel vehicle numbers should be controlled, and new energy vehicles should be vigorously promoted to reduce vehicle emissions.