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Composition analysis and formation pathway comparison of PM_1 between two pollution episodes during February 2017 in Beijing, China

机译:2017年2月北京地区两次污染事件之间PM_1的成分分析和形成途径比较

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摘要

SO42-, NO3- and NH4+ (SNA) are the major components of particulate matter in Beijing. In this study, hourly concentrations of SNA in PM1 were measured through an Aerodyne Aerosol Chemical Speciation Monitor (ACSM) at an urban site of Beijing, from February 3rd to 20th of 2017. The analysis of the differences between two pollution cases during the sampling period was further conducted. The results showed that the concentrations of NO3-, SO42- and NH4+ were 38.9 +/- 10.5 mu g/m(3), 41.9 +/- 22.2 mu g/m(3) and 31.3 +/- 10.6 mu g/m(3) respectively in the first case. A negative correlation was reflected between the PM2.5 concentrations and the following two ratios: 1) NO3-/SO42-; 2) [NH4+] to ([NO3-]+2[SO42-]), with a correlation coefficient of -0.92 and -0.76 respectively. In the second case, the PM2.5 concentrations (proportions) were much higher, with values of 49.9 +/- 17.0 mu g/m(3) (22.9 +/- 7.7%), 42.3 +/- 15.8 mu g/m(3) (20.3 +/- 7.2%) and 33.1 +/- 10.1 mu g/m(3) (15.3 +/- 4.3%). In contrast. The two ratios were positively correlated with the PM2.5 concentrations, along with the correlation coefficient of 0.77 and 0.62. Hence, it is palpable that two pollution cases were sulfate and nitrate dominant in respective. The emission characteristics due to the Chinese Spring Festival before P1 might be a major cause. A modeling-monitoring coupled approach was established for the recognition of the secondary conversion of SO42- and NO3-. Results showed that sulfateitrate aged ratio (SAR and NAR) and sulphur oxidation ratio (SOR) in the second case were 0.48 +/- 0.23, 0.22 +/- 0.07 and 0.38 +/- 0.23. They were all higher than those of the first case whose values were 0.32 +/- 0.15, 0.18 +/- 0.05 and 0.22 +/- 0.12, which indicated that secondary conversion of precursors was enhanced in the second case. Although the OH concentrations were of no obvious difference in both cases, the average concentrations of H2O2, NO2 and the relative humidity were much higher in the second case, which provided sufficient conditions and time for the formation of SO42- and NO3-.
机译:SO42-,NO3-和NH4 +(SNA)是北京颗粒物的主要成分。在这项研究中,2017年2月3日至20日,通过北京城市地区的Aerodyne气溶胶化学形态监测器(ACSM)测量了PM1中SNA的每小时浓度。分析采样期间两个污染案例之间的差异进一步进行。结果表明,NO3-,SO42-和NH4 +的浓度分别为38.9 +/- 10.5μg / m(3),41.9 +/- 22.2μg / m(3)和31.3 +/- 10.6μg / m (3)在第一种情况下。 PM2.5浓度与以下两个比率之间呈负相关:1)NO3- / SO42-; 2)[NH4 +]至([NO3-] + 2 [SO42-]),相关系数分别为-0.92和-0.76。在第二种情况下,PM2.5浓度(比例)要高得多,分别为49.9 +/- 17.0μg / m(3)(22.9 +/- 7.7%),42.3 +/- 15.8μg / m (3)(20.3 +/- 7.2%)和33.1 +/- 10.1μg / m(3)(15.3 +/- 4.3%)。相反。这两个比率与PM2.5浓度呈正相关,相关系数分别为0.77和0.62。因此,可以看出两个污染案例分别以硫酸盐和硝酸盐为主。 P1之前的中国春节造成的排放特征可能是主要原因。建立了模型-监测耦合方法来识别SO42-和NO3-的二次转化。结果显示,第二种情况下的硫酸盐/硝酸盐老化率(SAR和NAR)和硫氧化率(SOR)分别为0.48 +/- 0.23、0.22 +/- 0.07和0.38 +/- 0.23。它们均高于第一种情况的值,即值分别为0.32 +/- 0.15、0.18 +/- 0.05和0.22 +/- 0.12,这表明在第二种情况下前体的二次转化得到了增强。尽管两种情况下的OH浓度无明显差异,但第二种情况下H2O2,NO2的平均浓度和相对湿度要高得多,这为形成SO42-和NO3-提供了充足的条件和时间。

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