昆明城区大气污染物时空分布特征

Temporal and spatial distribution characteristics of atmospheric pollutants in urban area of Kunming City

  • 摘要: 利用2013—2020年昆明城区国控点监测数据,分析大气污染物时空分布特征。结果表明:2013—2020年昆明城区O3年均浓度总体呈上升趋势,其余污染物年均浓度呈下降趋势,O3增幅为4.1%,SO2降幅为67.9%,其余污染物降幅为35.0%~55.0%。超过GB 3095—2012《环境空气质量标准》一级以上标准的首要污染物天数占比显示,O3已经代替PM2.5成为昆明市最主要的大气污染物;O3浓度春季最高,夏季次之,秋季最低;PM10和PM2.5浓度春、冬季高,夏季最低;SO2、NO2、CO浓度冬季最高,夏季最低,但SO2和NO2四季变化幅度较其他污染物小。春、夏季的O3,冬、春季的PM2.5是昆明市大气污染的防治的重点。O3浓度日变化呈单峰型分布,CO、NO2、PM10、PM2.5浓度呈双峰型分布,但PM10、PM2.5浓度峰谷变化不明显;NO2、CO、PM2.5、PM10浓度峰值出现在早高峰时段,O3浓度峰值出现在14:00—15:00,SO2浓度上午高于下午。大气污染物浓度分布具有明显的空间差异性,SO2、PM2.5、NO2、PM10、CO浓度城区西部高于东部,分别高出54.5%、20.0%、17.9%、14.6%和2.4%,O3浓度则相反,城区东部高于西部,高出9.0%;SO2、NO2、O3浓度东部、西部差异呈逐年减小趋势,不排除上风向安宁工业园区污染传输影响变弱的可能性。

     

    Abstract: Based on the monitoring data of national control monitoring stations in the urban area of Kunming in 2013-2020, the temporal and spatial distribution features of atmospheric pollutants were analyzed. The results showed that during the period of 2013-2020, the annually-averaged concentration of O3 in the urban area of Kunming generally showed an upward trend, and the annually-averaged concentrations of other pollutants showed a downward trend. The annually-averaged concentration of O3 increased by 4.1%, while that of SO2 dropped by 67.9% and other pollutants dropped by 35.0%-55.0%. The proportion of days of primary pollutants exceeding Level 1 or above the standard of Ambient Air Quality Standards (GB 3095—2012 ) indicated that O3 instead of PM2.5 had become the primary atmospheric pollutant in Kunming. The highest concentration of O3 appeared in spring, followed by summer, and the lowest in autumn, the concentrations of PM10 and PM2.5 were generally high in spring and winter but low in autumn, and as for SO2, NO2 and CO, the highest concentrations appeared in winter and lowest in summer. But the variation ranges in four seasons of SO2 and NO2 were smaller than that of other pollutants. O3 in spring and summer and PM2.5 in spring and winter were the key points of air pollutants control in Kunming. The daily variation of O3 presented single peak distribution, CO, NO2, PM10 and PM2.5 presented double peaks distribution, but the variation of peak-valley of PM10 and PM2.5 concentrations were not distinct. The peaks of NO2, PM2.5, PM10 and CO were identical to morning rush hours, the peak of O3 usually appeared during 14:00-15:00, and the concentration of SO2 was higher in the morning than in the afternoon. As for spatial distribution patterns, remarkable distinctions existed for different pollutants. The concentrations of SO2, PM2.5, NO2, PM10 and CO of western stations were 54.5%, 20.0%, 17.9%, 14.6% and 2.4%, respectively higher than those of eastern stations. On the contrary, O3 concentrations in eastern stations were 9.0% higher than that of western stations. The difference of SO2, NO2 and O3 concentrations between eastern and western stations had narrowed down year by year, and this might be caused by the weakening of the impact of pollution transmission from Anning Industrial Park.

     

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