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大气颗粒物PM2.5与气候变化、人体健康、生态环境等密切相关[1]. 三亚市(18°18′N,109°31′E)位于海南岛的最南端,地处低纬度,属热带海洋性季风气候区. 随着海南自由贸易港建设进展加快、国际旅游岛对外开放和海南热带气候等区位优势,海南人口激增与经济快速发展,空气质量的压力越来越大[2],三亚市政府和国内外游客也日益重视PM2.5的健康效应.
三亚PM2.5研究报道较少,与之关联的是南海大气化学研究. 前人研究如下:三亚PM2.5中OC和EC [3-4];PM2.5光学特征[5-6];PM2.5的潜在源定性分析[4,7];PMF模型定量源解析[8]. 海口CMB模型源解析[9-10];南海PMF模型源解析[11-12];南海有机气溶胶分子标识物和同位素示踪来源[13-15];上述源解析很少单用微量元素. 受体模型PMF源解析优点在于灵活性(不需源谱)和操作性(模型软件化和源个数“眼球法”),缺点在于共线源问题和源解析结果时空差异大[16]. 基于PMF的优缺点,在实际运用中,呈现两种局面:一方面是接受PMF优点,广泛应用,同时,单用微量元素组分进行源解析,多与PM2.5中重金属健康效应结合 [17-18];另一方面是将受体模型、源清单法和源过程法等方法结合,进行多种源解析,相互验证解决PMF不足 [19]. 本文基于微量元素数据及其健康评价,采用PMF源解析第一情况,其不足在于微量元素标识物的共线源问题,优势在于微量元素相对于有机组分来说,其变化程度小. 三亚市PM2.5微量元素的源解析尚鲜见报道,研究PM2.5中微量元素污染特征及健康评价具有十分重要的意义.
本文通过离线滤膜样品采集得到三亚市PM2.5微量元素数据,结合富集因子分析,表征三亚市PM2.5微量元素的化学特征;使用受体PMF模型进行源解析,定量估算微量元素排放源对三亚市PM2.5的贡献比例;利用暴露评估模型,评价PM2.5中微量元素的健康效应. 此论文为三亚市PM2.5的空气质量监测及防治提供思路及措施.
2019年三亚市PM2.5微量元素的源解析和健康评价
Source analysis and health assessment of PM2.5 trace elements in Sanya City in 2019
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摘要: 本研究通过滤膜采样分析得到三亚市PM2.5微量元素数据,结合富集因子,表征化学特征;使用PMF模型进行源解析,定量估算各排放源的贡献比例,并与南海周边城市源解析比较;根据暴露评估模型评估健康效应. 结果表明,三亚市致癌性重金属Cr(7.70×10-3 μg·m−3)已经超过标准限值(2.50×10−5 μg·m−3),S的富集因子高达825.46,表明三亚PM2.5受S元素污染严重;源排放贡献大小比例分别为:海洋源(24.9%)>生物质燃烧源(20.8%)>工业源(20.5%)>土壤源(19%)>交通源(14.8%),源解析结果比较得知,海盐贡献比例与采样点离岸距离有梯度变化特征;滨海城市的主要人为排放源受制于城市经济发展程度;二次无机气溶胶的贡献与工业源的比例呈反比,取决于SAN SNA标识物的配分;重金属污染对三亚不同人群的影响大小顺序为:成年男子>成年女子>儿童;9种重金属元素对 3 类人群经呼吸途径暴露的健康风险均为Cr>As>Ni>Al>Mn>Pb>Cu>Zn>Se.Abstract: This study used membrane filter sampling to collect PM2.5 trace element data of Sanya, China. Enrichment factor analysis and chemical characterization were used with a positive matrix factorization model to conduct source apportionment. The contribution proportions of each emission source were quantified and compared with the source apportionment results of coastal cities of South China Sea. According to an exposure assessment model, the effects of the elements on health was evaluated. The results revealed that the carcinogenic heavy metal Cr (7.70×10−3 μg·m−3)at Sanya exceeded the threshold of 2.50×10−5 μg·m−3. The enrichment factor of S reached as high as 825.46, implying that the PM2.5 in Sanya was severely polluted by S. The contribution proportions of emission sources ranking from high to low were the ocean (24.9%) > biomass combustion (20.8%) > industry (20.5%) > soil (19%) > traffic (14.8%). The source apportionment results revealed that the contribution proportion of sea salt exhibited gradient changes in relation to the distance of the sampling location to the coast. The main anthropogenic emissions of coastal cities were subject to the level of economic development of individual cities. The contribution proportions of secondary inorganic aerosols were inversely proportional to that of industrial emission sources, depending on the ratios of SNA markers. The level of influence of heavy metal pollution on different populations in Sanya was highest on adult man, followed by adult women and children. The risks of the 3 populations exposed to 9 heavy metals through respiratory tracts were Cr > As > Ni > Al > Mn > Pb > Cu > Zn > Se.
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Key words:
- Sanya /
- PM2.5 /
- trace elements /
- source apportionment /
- health assessment.
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表 1 经呼吸进入人体的暴露参数
Table 1. Exposure parameters of breathing into human body
重金属元素
Heavy metal element性质
Characteristic致癌因子/((kg·d)· μg−1)
SF参考剂量/(μg·(kg·d) −1)
RfDAs 致癌 2.01×10−2 — Cd 致癌 8.40×10−3 — Ni 致癌 1.19×10−3 — Al 非致癌 — 4.00×10−1 Cu 非致癌 — 2.00 Mn 非致癌 — 3.00×10−1 Pb 非致癌 — 4.30×10−1 Se 非致癌 — 1.00 Zn 非致癌 — 1.00×10−2 表 2 重金属经呼吸进人体的剂量-反应参数
Table 2. Dose-response parameters of heavy metals breathing into human body
人群
Crowd呼吸速率/(m3·d−1)
IR体重/kg
BW暴露持续时间/d
ED致癌暴露时间/d
AT-Carcinogenesis非致癌暴露时间/d
AT-Non-carcinogens儿童 8.70 36.00 18.00 70.00 18.00 成年女性 14.17 57.30 30.00 70.00 30.00 成年男性 19.02 66.20 30.00 70.00 30.00 表 3 三亚市PM2.5重金属元素的质量浓度
Table 3. Mass concentration of PM2.5 heavy metal elements in Sanya
元素
Element2019年均值/(μg·m−3)
2019 mean6月均值/(μg·m−3)
June mean10月均值/(μg·m−3)
October mean12月均值/(μg·m−3)
December mean标准限值/(μg·m−3)
Standard limitAs 4.30×10−3 — 4.00×10−4 4.90×10−3 6.00×10−3 Cr 7.70×10−3 7.60×10−3 8.50×10−3 7.40×10−3 2.50×10−5 Ni 3.50×10−3 3.00×10−3 4.00×10−3 3.60×10−3 — Cu 1.74×10−2 1.44×10−2 1.64×10−2 2.04×10−2 — Pb 1.53×10−2 1.19×10−2 1.75×10−2 1.68×10−3 5.00×10−1 Se 1.60×10−3 1.00×10−3 1.80×10−3 2.00×10−3 — Zn 3.23×10−2 2.04×10−2 3.79×10−2 3.92×10−2 — 表 4 南海周边大气颗粒物PM受体模型源解析比较表
Table 4. Comparison of source analysis of PM receptor models around the South China Sea
采样点
Sampling site粒径
Size采样时间
Date模型
Model源解析结果
Source analysis results参考文献
References中国海南省三亚市 PM2.5
(n=34)2012, 1.6 — 2.8;
2013.6.6—7.25PMF 1.生物质燃烧(23.2%);2.机动车(37.9%); 3.燃煤(22.6%); 4.其他(16.3%); [8] PM2.5
(n=90)2019, 6 — 2019,12 PMF 1. 海洋源(24.9%); 2. 生物质燃烧源(20.8%); 3. 工业源(20.5%); 4. 土壤源(19%); 5. 交通源(14.8%) 本研究 中国海南省三沙市 TSP
(n=73)2014.3—2015.2 PMF 1. 海盐(46.6%); 2. 土壤尘(11.9%); 3. 二次无机气溶胶(30.1%); 4. 海洋排放(11%) [11] 中国海南省海口市 PM2.5
(n=38)2011.12.26 — 2012.6.3; 2012.4.17—26 CMB 1. 扬尘(14.9%); 2. 机动车尾气(17.5%);
3. SO42-(9.5%); 4. 海盐(3%);[9] PM10
(n=76)1. 扬尘(23.6%); 2. 机动车尾气(35%);
3. SO42-(15.7%); 4. 海盐(8%);中国台湾省高雄港 PM2.5
(n=28)2018.5— 2019.1 PMF 1. 船舶排放(15.6%);2. 二次无机气溶胶(24%);3. 机动车尾气(12.2%);4. 海盐(20.7%);5. 海盐和生物质燃烧(14.4%);6. 重油, 生物质燃烧(13.2%) [30] 菲律宾马尼拉 PM2.5
(n=28)2018.5— 2019.1 PMF 1. 道路扬尘, 燃煤(17.4%);2. 船舶排放, 机动车(19.1%);3. 工业(17.7%);4. 机动车(12.6%);5. 二次气溶胶,土壤, 生物质燃烧(21.3%);6. 海盐, 生物质燃烧(11.8%) [30] 马来西亚八打灵 PM2.5
(n=247)2017.1.11—2018.2.19 PMF 1. 混合冶炼工业和道路扬尘(5.6);2. 矿物尘(7.2%);3. 海盐(7.4%);4. 冶金工业(5.1%);
5. 农业(19.2%);6. 制造业 (12%);
7. 二次无机气溶胶,交通 (28.5%);8.生物质燃烧(15.2%)[31] 表 5 三亚市大气PM2.5中重金属元素经呼吸途径对人群的年均超额危险度
Table 5. Average annual excess risk of heavy metal elements in atmospheric PM2.5 in Sanya City to the population through respiratory pathway
元素
Elements年均超额危险度R(无量纲)
Annual excess risk R(No unit)儿童
Child成年女性
Adult women成年男性
Adult menAs 7.64×10−8 1.30×10−7 1.51×10−7 Cr 3.85×10−7 6.57×10−7 7.63×10−7 Ni 3.68×10−9 6.27×10−9 7.28×10−9 Al 2.21×10−9 2.26×10−9 2.62×10−9 Cu 3.01×10-11 3.08×10-11 3.58×10-11 Mn 5.46×10-10 5.58×10-10 6.49×10-10 Pb 1.23×10-10 1.26×10-10 1.46×10-10 Se 5.40×10-12 5.52×10-12 6.42×10-12 Zn 1.12×10-11 1.14×10-11 1.33×10-11 -
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