保定市PM2.5和臭氧污染特征分析

PM2.5 and O3 Pollution Characteristics in Baoding City

    摘要
  • 摘要: 为深入了解保定市空气质量状况，揭示PM2.5与臭氧(O3)的变化特征及相互关系，利用小波分析法对保定市2013—2020年每年4—9月AQI、PM2.5、O3-8 h (O3日最大8 h滑动平均值)和NO2浓度的逐日数据进行分析. 结果表明：①2013—2018年保定市O3污染呈逐年加重趋势，最大日浓度达到347 μg/m3；随着治理措施的颁布与实施，PM2.5超标天数由2013年的97 d减至2020年的1 d，PM2.5超标情况逐年改善. ②O3超标天数由2013年的3 d增至2018年的95 d，2020年减至61 d；O3超标天数占PM2.5和O3超标总天数的比例从2013年的3%增至2020年的98%，说明O3逐渐成为影响保定市空气质量的主要污染物. ③2013年保定市O3-8 h浓度低于“2+26”城市均值，2014—2020年O3-8 h浓度高于或接近“2+26”城市均值，说明近年来保定市O3-8 h浓度的升幅已超过“2+26”城市的平均水平. ④小波分析发现，2013—2020年(除2015年和2018年外)AQI与PM2.5污染序列的第1主周期相近，从2017年开始，AQI与O3-8 h污染序列的第1主周期和第2主周期均一致，说明近年来保定市空气污染逐渐由PM2.5污染转为PM2.5与O3复合污染. ⑤在同一时间尺度范围内，PM2.5与O3-8 h污染序列的震荡频率基本一致，说明二者存在较明显的正相关关系；2015—2019年，NO2与O3-8 h污染序列的震荡频率趋于一致，说明保定市O3-8 h浓度受前体物NO2影响较大，2020年震荡频率有较大差异，这可能与新冠肺炎疫情复工后生产规模尚未完全恢复，致使NO2、PM2.5等污染物排放强度同比降低有关. 因此，减少NO2排放，协同控制多污染物是实现保定市空气质量改善的主要途径.

     

    Abstract: In order to comprehensively understand the air quality in Baoding and reveal the changing characteristics and relationship between PM2.5 and O3, this study used wavelet analysis to analyze the daily data of AQI, PM2.5, O3-8 h (the maximum 8-hour moving average of O3) and NO2 from April to September in Baoding City from 2013 to 2020. The results show that: (1) From 2013 to 2018, O3 concentration showed an increasing trend, and the maximum daily concentration reached 347 μg/m3. The O3 concentrations began to decline since 2019. There were more days when the PM2.5 concentrations exceeded the secondary limit of the National Ambient Air Quality Standard (GB 3095-2012) (NAAQS) in 2013 than in other years. With the promulgation and implementation of governance measures, the situation of high PM2.5 pollution has improved. (2) The number of days when PM2.5 concentrations exceeded the NAAQS secondary limit was reduced from 97 days in 2013 to 1 day in 2020. The number of days of O3-8 h exceeding the NAAQS secondary limit increased from 3 days in 2013 to 95 days in 2018, and then decreased to 61 days in 2020. The proportion of O3-8 h exceeding-limit days in the total number of days in which the two pollutants exceeded the limit increased from 3% in 2013 to 98% in 2020, indicating that O3 has become a major pollutant affecting air quality in Baoding. (3) In 2013, the concentration of O3-8 h in Baoding City was lower than the average value of ‘2+26’ cities, and the concentration was higher than or close to the average value of ‘2+26’ cities during 2014-2020, indicating that the increase in O3-8 h concentration in Baoding City exceeded the average level of ‘2+26’ cities in recent years. (4) Wavelet analysis found that the AQI was similar to the first major cycle of PM2.5 from 2013 to 2020 (except for 2015 and 2018). Since 2017, the AQI and O3-8 h's first and second major cycles were consistent with each other. It shows that the air pollution in Baoding City changed from PM2.5 pollution to PM2.5 and O3 pollution. (5) Within the same time scale, the oscillation frequencies of PM2.5 and O3-8 h were basically the same, indicating that there was a clear positive correlation between PM2.5 and O3-8 h. From 2015 to 2019, the oscillation frequencies of NO2 and O3-8 h tended to be the same, indicating that the concentration of O3-8 h in Baoding City was greatly affected by the precursor NO2. The large difference in the frequency of oscillations in 2020 may be due to the fact that the production scale was not fully recovered after the resumption from the epidemic, which led the reduction of emission intensity of pollutants such as NO2 and PM2.5 during the epidemic period. Therefore, reducing NO2 emissions and coordinated control of multi-pollutants are the main ways to improve air quality in Baoding City.

     

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