| 苏南五市秋冬季PM2.5化学组成特征和空间差异 |
| 摘要点击 1722 全文点击 136 投稿时间：2023-05-23 修订日期：2023-07-03 |
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| 中文关键词 苏南城市 PM2.5 化学组分 空间分布 二次形成 |
| 英文关键词 city of southern Jiangsu PM2.5 chemical component spatial distribution secondary formation |
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| 中文摘要 |
| 于2020年9月至2021年2月在苏南五市（南京、苏州、无锡、常州和镇江）收集PM2.5滤膜样品,分析了各样品中的水溶性无机离子和碳质组分.结果表明,苏南五市PM2.5各组分中ρ（NO3-）均为最高[（9.54 ± 10.1）~（12.1 ± 11.3）μg·m-3],比其它目标组分高约2倍以上.由于受更多道路扬尘和燃煤源的影响,常州市PM2.5中Ca2+、Cl-、OC和EC的浓度平均值高于其它4个城市.将所有目标组分浓度相加得到重构PM2.5（rPM2.5）浓度,发现各城市rPM2.5浓度均由二次无机离子（NH4+、NO3-和SO42-,SNA）主导,占比高达（59.2%± 11.1%）~（70.8%± 9.72%）,且rPM2.5浓度平均值在不同城市间无显著性差异（P>0.05）.苏南五市ρ（rPM2.5）日均值>35 μg·m-3的情形主要发生在冬季,且出现的日期相同,此期间rPM2.5中NO3-占比[（35.5%± 6.64%）~（43.3%± 6.48%）]远高于其它时间[（23.7%± 9.87%）~（28.5 ± 10.4%）].各目标组分在不同城市间的相关系数和离散系数计算结果表明,受二次源主导化学组分的浓度在时间变化趋势和数值大小上均具有高度的空间相似性.因此,减少PM2.5二次组分前体物的排放和加强区域间的联防联控是进一步改善苏南城市地区PM2.5污染的重要途径. |
| 英文摘要 |
| PM2.5 filter samples were collected from the five cities of northern Jiangsu（Nanjing,Suzhou,Wuxi,Changzhou,and Zhenjiang）and analyzed for water-soluble ions and carbonaceous components. The results showed that NO3- was the most abundant component in PM2.5 of the five cities in southern Jiangsu [（9.54 ± 10.1）-（12.1 ± 11.3）μg·m-3],approximately more than two times higher than the other target components. Due to the influences of dust and combustion sources,the average concentrations of Ca2+,Cl-,organic carbon,and elemental carbon in Changzhou were higher than those in the other four cities. The reconstructed PM2.5（rPM2.5）was calculated as the sum of all measured species concentrations, and we found that its concentrations were dominated by secondary inorganic ions（SO42-,NO3-,and NH4+,SNA）,which accounted for（59.2% ± 11.1%）-（70.8% ± 9.72%）of the rPM2.5. The average concentrations of rPM2.5 exhibited no significant differences（P > 0.05）between all city pairs. The situations in which the average daily concentrations of rPM2.5 in the five cities of southern Jiangsu > 35 μg·m-3 occurred mainly in winter and at the same time. During these periods,the proportions of NO3- in rPM2.5 [（35.5% ± 6.64%）-（43.3% ± 6.48%）] were much higher than those in other periods [（23.7% ± 9.87%）-（28.5 ± 10.4%）]. The correlation coefficients and coefficients of divergence between different cities for individual species were calculated, and the results indicated that the concentrations of the components dominated by secondary sources had high spatial homogeneity in the temporal patterns and magnitude of the numerical values. Therefore, reducing precursor emissions of secondary PM2.5 components and strengthening joint prevention and control between regions are important ways to alleviate PM2.5 pollution in urban areas of southern Jiangsu. |
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