引用本文:孙启斌,肖红伟,肖化云,张忠义,等.南昌市大气降水化学特征及来源分析[J].环境科学研究,2017,30(12):1841-1848.
SUN Qibin,XIAO Hongwei,XIAO Huayun,ZHANG Zhongyi,et al.Chemical Characteristics and Source Apportionment of Atmospheric Precipitation in Nanchang City[J].Reserrch of Environmental Science,2017,30(12):1841-1848.]
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南昌市大气降水化学特征及来源分析
孙启斌1,2, 肖红伟1,3, 肖化云1,2,3, 张忠义1,3
1. 东华理工大学, 江西省大气污染成因与控制重点实验室, 江西 南昌 330013;2. 东华理工大学地球科学学院, 江西 南昌 330013;3. 东华理工大学水资源与环境工程学院, 江西 南昌 330013
摘要:
为分析南昌市大气降水离子来源和源区,对南昌市2016年4—9月大气降水样品主要阴阳离子的组成进行了测定分析,并运用PMF(正定矩阵因子分解)模型分析来源和TrajStat软件模拟后向轨迹.结果表明:NH4+和Ca2+是南昌市大气降水中的主要阳离子,加权平均浓度为65.3和23.9 μmol/L,分别占阳离子总量的57%和21%;SO42-和NO3-是主要阴离子,加权平均浓度为60.4和25.3 μmol/L,分别占阴离子总量的56%和23%.c(NH4+)、c(Ca2+)、c(K+)、c(Mg2+)、c(Na+)、c(Cl-)、c(NO3-)之间均存在着较为显著的相关性,说明它们之间可能有相似的来源或形成化合物共同存在.结合PMF模型分析结果表明,Na+、Cl-很明显受到了海盐的影响,也部分受土壤和二次污染影响;K+、Mg2+、Ca2+大部分来自于土壤,海盐、二次污染也贡献了一部分的K+;SO42-、NH4+和NO3-是组成大气二次颗粒物的主要成分,主要由二次污染源贡献;煤燃烧贡献了主要的F-和部分SO42-.后向轨迹模型分析表明,南昌市大气降水主要受局地降雨气团影响,5月、8月、9月受陆源及人为影响较大,海源性离子经过内陆上空时被稀释或沉降,导致6月、7月来自于海洋上空的降雨气团对南昌影响不大.研究显示,SO42-对南昌市大气降水的影响逐渐增大导致降雨类型逐渐由混合型向硫酸型转化,人为影响是造成大气污染的主要原因.
关键词:  南昌  大气降水  化学组成  正定矩阵因子分解模型  后向轨迹
DOI:10.13198/j.issn.1001-6929.2017.03.38
分类号:X517
基金项目:国家自然科学基金项目(41663003);东华理工大学博士启动基金项目(DHBK2015327);核资源与环境重点实验室自主基金项目(Z1609)
Chemical Characteristics and Source Apportionment of Atmospheric Precipitation in Nanchang City
SUN Qibin1,2, XIAO Hongwei1,3, XIAO Huayun1,2,3, ZHANG Zhongyi1,3
1. Jiangxi Province Key Laboratory of the Causes and Control of Atmospheric Pollution, East China University of Technology, Nanchang 330013, China;2. School of Earth Sciences, East China University of Technology, Nanchang 330013, China;3. School of Water Resources and Environmental Engineering, East China University of Technology, Nanchang 330013, China
Abstract:
This research aimed to identify the sources and origins of atmospheric precipitation ions in Nanchang City. Rainwater samples were collected from April 2016 to September 2016, and the chemical characteristics of major ions were analyzed. Additionally, the positive definite matrix factorization (PMF) model was used to distinguish the sources, and TrajStat software was used to simulate the backward trajectories. The results showed that NH4+ and Ca2+ were the main cations. On average, we measured rainfall-weighted concentrations of 65.3 and 23.9 μmol/L, accounting for 57% and 21% of the total cations respectively. SO42- and NO3- were the major anions, of which the average rainfall-weighted concentrations were 60.4 and 25.3 μmol/L, accounting for 56% and 23% of the total anions respectively. Significant correlations among c(NH4+), c(Ca2+), c(K+), c(Mg2+), c(Na+), c(Cl-) and c(NO3-) indicated similar sources or the formation of compounds. The PMF model showed that Na+ and Cl- were obviously affected by sea salt and partly affected by soil and secondary pollution. The major contribution of K+, Mg2+ and Ca2+ was the soil source. Sea salt and secondary pollution also contributed part of the K+. SO42-, NH4+ and NO3- were the main constituents of the atmospheric secondary particles, which were mainly contributed by secondary pollution sources. Almost all of the F- and part of the SO42- came from coal burning. Backward trajectories revealed the atmospheric precipitation of Nanchang City in 2016 was mainly affected by air masses originating from local areas. In May, August and September, the precipitation was more affected by soil and anthropogenic sources. Oceanic ions were diluted or settled when they went inland, meaning that rainfall air masses originating from the ocean in June and July had little impact on Nanchang. The rainfall type in Nanchang City is shifting gradually from mixed type to sulfuric acid type, and the artificial influence is the main cause of air pollution.
Key words:  Nanchang  precipitation  chemical composition  Positive Matrix Factorization model  backward trajectory