济南市大气污染物时空变化及预测分析

大气污染影响生产生活和人体健康，了解大气污染物时空分布特征及污染源是大气污染治理的基础和前提。基于济南市2014-2018年空气质量实时监测数据，主要污染物浓度数据和气象要素数据，运用相关分析法和BP神经网络预测模型，分析了济南市大气污染物时空分布特征及污染物来源，并对济南市6种主要污染物进行预测。结果表明:在时间维度上，空气质量呈逐年好转趋势，季节上则表现出冬季污染最严重，夏季最轻，采暖期污染物浓度远远高于非采暖期的特点；从日变化看，上下班高峰段是污染最严重时段。在空间维度上，城市外围污染较为严重，市区污染相对较轻。在污染物成分上，PM₁₀逐渐成为颗粒物污染的主体。通过济南市污染物浓度预测结果，分析未来3年内污染物浓度变化情况，进一步提出合理优化的污染治理方案来改善济南市大气污染状况。

ANALYSIS ON TEMPO-SPATIAL VARIATION AND PREDICTION OF AIR POLLUTANTS IN JINAN

Air pollution seriously affects people's production, life and health. Analysis on tempo-spatial distribution of air pollutants and their sources is the basis and prerequisite for air pollution control. Based on the real-time air quality monitoring data, the main pollutant concentration data and meteorological elements data of Jinan from 2014 to 2018, this paper analyzed the spatial and temporal distribution characteristics and sources of air pollutants in Jinan by using correlation analysis method and BP neural network prediction model, and forecasted 6 major pollutants in Jinan.The results showed that the air quality revealed an improving trend year by year. The concentration of the majority pollutants in winter was higher than that in summer, and air quality in non-heating period was better than that in heating period. From the perspective of diurnal variation, the peak period of commuting was the most serious pollution period. Spatially, the pollution of urban periphery was more serious than that of urban. PM₁₀ was becoming the most serious pollutant, and the pollution caused by vehicle exhaust emission was increasing significantly. Strengthening the control of air pollution in suburbs and rural areas, especially the monitoring and control of large particulate matters, and reducing vehicle exhaust pollution by means of vehicle restriction were the main ways to further improve the air quality of Jinan.By prediction result of pollutants concentration, and its analysis for the next three years, we further put forward the pollution control optimization scheme to improve atmospheric pollution in Jinan.