南昌市大气PM_（10）、PM_（2.5）的污染特征及来源解析
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摘要
大气颗粒物是大气环境中危害较大的污染物之一,对气候变化、能见度降低、环境危害(如酸雨、烟雾)及健康危害等具有重要影响。本研究以南昌市不同功能区、不同季节的大气颗粒物为主要研究对象,于2007年7月-8月、2007年11月-12月及2008年4月-7月同步采集PM_(10)、PM_(2.5)样品,对比分析了夏、冬季大气PM_(10)、PM_(2.5)中无机组分和多环芳烃的分布特征、时空变化规律;采用多种方法对颗粒物来源进行解析;研究了室内外PM_(2.5)中多环芳烃的分布特征;在此基础上,得出以下结论:
南昌市夏季PM_(10)日均浓度为149.09μg/m~3,为国家二级标准的0.99倍,PM_(2.5)日均浓度为88.03μg/m~3,为美国PM_(2.5)标准的1.35倍,冬季PM_(10)日均浓度为170.73μg/m~3,为国家二级标准的1.14倍,PM_(2.5)日均浓度为110.16μg/m~3,为美国PM_(2.5)标准的1.69倍,PM_(10)、PM_(2.5)质量平均浓度均呈现出夏低冬高的特征,空间分布上,夏、冬季PM_(10)和PM_(2.5)的污染情况为交通干线>工业区>商业区>居住区>郊区。PM_(10)和PM_(2.5)之间存在显著的线性关系,大气中细颗粒物(PM_(2.5))在PM_(10)中的比重大于粗颗粒物,约占63%。
不同功能区的元素浓度存在较明显的空间分布特征:市内元素浓度值高于郊区元素浓度值,交通干线和工业区的元素浓度值比商业区和居民区高。冬季PM_(10)中Al、Ca、Mg、Fe、Mn、Pb、Zn、Ti、Ni元素平均浓度高于夏季,与质量浓度变化趋势一致,As、Cu、Cr元素平均浓度未表现出明显的季节变化,S元素夏季平均浓度高于冬季。冬季PM_(2.5)中Al、Ca、Mg、Fe、S、Mn、Pb、Zn、Ni元素平均浓度高于夏季,与质量浓度变化趋势一致,As、Cu、Cr、Ti元素平均浓度未表现出明显的季节变化。
源解析结果表明,土壤尘、燃煤尘、建筑尘、机动车尾气尘、冶金尘是南昌市环境空气中PM_(10)和PM_(2.5)的主要排放源类,对PM_(10)贡献大的源类,对PM_(2.5)贡献基本也大。土壤尘、煤烟尘和建筑尘是决定PM_(10)和PM_(2.5)是否超标的主要源类,是污染防治的重点。用BP网络进行源解析与CMB源解析法求出的污染源贡献率大小排序上夏、冬季完全一致,仅数值大小存在着差异,取得了较好的效果,因此BP网络模型应用于大气颗粒物的源解析是可行的。
建立了二极管阵列检测器和荧光检测器串联的高效液相色谱分析方法,优化得到对应高效色谱仪及特定色谱柱测定多环芳烃化合物的色谱条件,确定荧光检测器发射波长在390nm处各多环芳烃组分有很好的响应,在标样未完全分离的情况下,采用双激发波长有效地改善了色谱分离条件。
南昌市大气PM_(10)和PM_(2.5)中PAHs污染情况为交通干线>工业区>商业区>居民区>郊区,PM_(10)和PM_(2.5)中PAHs单体以4环和5环为主,6环次之,3环最少,2环基本未检出。毒性风险从大到小排列为八一广场>罗家集区>南昌二中老校区>荣昌小区>下罗村。南昌市的主要污染源车辆排放源、燃煤污染源、高温加热源和焦化污染源对大气PM_(10)中多环芳烃的贡献率分别为33.7%、18.8%、13.0%和18.0%。各污染源对南昌市大气PM_(2.5)中多环芳烃的贡献率分别为31.0%、21.1%、14.6%和25.8%。因子分析/多元线性逐步回归法分析的结果与南昌市区能源结构基本吻合。
罗家集区室内外PAHs的浓度总量水平高于八一广场、南昌二中老校区、荣昌小区、梨园小区室内外,八一广场、南昌二中老校区、荣昌小区、梨园小区四个室内外采样点室内PAHs与室外PAHs是相关的,而罗家集区室内外采样点存在室内源对颗粒物中PAHs的贡献,相对于3-4环的PAHs而言,5-6环的PAHs更易富集在室内的可吸入颗粒物中。
The atmospheric particles are one of the hazardous pollutants in atmospheric environment which significantly impact climate changes, visibility decline, environmental damage(eg. acid rain, smog) and health hazard. This research focuses on the atmospheric particles of different functional areas and different seasons in Nanchang city. PM_(10) and PM_(2.5) were synchronous sampled in Jul-Aug 2007, Nov-Dec 2007 and Apr-Jul 2008, and the inorganic components and PAHs of PM_(10) and PM_(2.5) collected in summer and winter were comparatively analyzed to investigate the distribution characteristics and the rules of space-time changes. Source apportionment and the distribution characteristics of PAHs in PM_(2.5) indoors and outdoors were also studied in this paper.
According to above analysis, the DAC (daily average concentration) of PM_(10) in summer was 149.09μg/m~3, 0.99 times the concentration of National Secondary Standard; PM_(2.5) in summer was 88.03μg/m~3, 1.35 times as much as American PM_(2.5) Standard; the DAC of PM_(10) in winter was 170.73μg/m~3, 1.14 times of National Secondary Standard; and PM_(2.5) in winter 110.16μg/m~3,1.69 times of American PM_(2.5) Standard. The DAC of PM_(10) and PM_(2.5) in summer were lower than that in winter. In different areas the pollution severity order of PM_(10) and PM_(2.5) was traffic roads (worse than), industrial zone, commercial mixing zone, residential zone and suburbs. The amount of PM_(2.5) was remarkably linear correlated with the amount of PM_(10), and a larger proportion than coarse particles in PM_(10), about 63%.
Distinct space-time distribution characteristics of EAC (element average concentration) were shown in different functional areas. The EAC of urban areas was higher than that of the suburbs, while the EAC of the traffic roads and industrial zone was higher than that of the commercial mixing zone and residential zone. In PM_(10), the EAC of Al, Ca, Mg, Fe, Mn, Pb, Zn, Ti and Ni in winter were higher than those in summer, which was consistent with the tendency of DAC, and the EAC of S in summer was higher than that in winter, but no evident EAC changes of As, Cu and Cr with seasons were observed. In PM_(2.5), the EAC of Al, Ca, Mg, Fe, S, Mn, Pb, Zn and Ni in winter was higher than those in summer as the tendency of DAC; whereas no obvious EAC changes of As, Cu, Cr and Ti with seasons were found.
The results of source apportionment illustrated that soil dust, burnt dust, building dust, vehicle dust and metallurgical dust were the dominant emission sources of PM_(10) and PM_(2.5) in atmospheric environment of Nanchang. The sources which made more contribution to PM_(10) also contributed more to PM_(2.5). Whether the concentrations of PM_(10) and PM_(2.5) reached the standard depends on soil dust, burnt dust and building dust, which become the emphasis of pollution control. The rank of pollution sources contribution ratio in the Summer and Winter simulated by BP network was the same as that simulated by CMB method, only varies in ratio numerical value. The preferable results proved feasibility of BP network in source apportionment.
The HPLC method with diode array and fluorescence series detectors was established and corresponding chromatographic conditions determining PAHs of specific chromatographic column were optimized. The optimal emission wavelength was selected in 390 nm, and dual wavelength excitation was applied without complete separation of standard sample. The components of PAHs were separated efficiently in chromatographic column.
The severity order of PAHs pollution in PM_(10) and PM_(2.5) was traffic roads (worse than), industrial zone, commercial mixing zone, residential zone and suburbs. The primary monomers of PAHs were 4-ring and 5-ring aromatics, 6-ring came next, 3-ring was least and 2-ring was hardly detected. The toxic risk rank was Bayi Square (more serious than), Luojiaji district, Old Campus of Nanchang No.2 Middle School, Rongchang district, and Xialuo Village. The contribution ratios of vehicle emission, coal burning, high-temperature heating and coking pollution to PAHs in PM_(10) were 33.7%, 18.8%, 13.0% and 18.0% respectively; the contribution ratios of various sources to PAHs in PM_(2.5) were 31.0%, 21.1%, 14.6% and 25.8% respectively. The results of factor analysis/multiple linear stepwise analysis conform to the energy structure of Nanchang city.
The PAHs amount of Luojia district indoors and outdoors was higher than that of Bayi Square, Old Campus of Nanchang No.2 Middle School, Rongchang district and Liyuan district. The indoor PAHs of Bayi Square, Old Campus of Nanchang No.2 Middle School, Rongchang district and Liyuan district was correlated with outdoor PAHs, except that the indoor source in Luojia district contributes to PAHs as well. Compared with 3-ring and 4-ring PAHs, 5-ring and 6-ring PAHs were easilier accumulating in inhaled particles.
南昌市夏季PM_(10)日均浓度为149.09μg/m~3,为国家二级标准的0.99倍,PM_(2.5)日均浓度为88.03μg/m~3,为美国PM_(2.5)标准的1.35倍,冬季PM_(10)日均浓度为170.73μg/m~3,为国家二级标准的1.14倍,PM_(2.5)日均浓度为110.16μg/m~3,为美国PM_(2.5)标准的1.69倍,PM_(10)、PM_(2.5)质量平均浓度均呈现出夏低冬高的特征,空间分布上,夏、冬季PM_(10)和PM_(2.5)的污染情况为交通干线>工业区>商业区>居住区>郊区。PM_(10)和PM_(2.5)之间存在显著的线性关系,大气中细颗粒物(PM_(2.5))在PM_(10)中的比重大于粗颗粒物,约占63%。
不同功能区的元素浓度存在较明显的空间分布特征:市内元素浓度值高于郊区元素浓度值,交通干线和工业区的元素浓度值比商业区和居民区高。冬季PM_(10)中Al、Ca、Mg、Fe、Mn、Pb、Zn、Ti、Ni元素平均浓度高于夏季,与质量浓度变化趋势一致,As、Cu、Cr元素平均浓度未表现出明显的季节变化,S元素夏季平均浓度高于冬季。冬季PM_(2.5)中Al、Ca、Mg、Fe、S、Mn、Pb、Zn、Ni元素平均浓度高于夏季,与质量浓度变化趋势一致,As、Cu、Cr、Ti元素平均浓度未表现出明显的季节变化。
源解析结果表明,土壤尘、燃煤尘、建筑尘、机动车尾气尘、冶金尘是南昌市环境空气中PM_(10)和PM_(2.5)的主要排放源类,对PM_(10)贡献大的源类,对PM_(2.5)贡献基本也大。土壤尘、煤烟尘和建筑尘是决定PM_(10)和PM_(2.5)是否超标的主要源类,是污染防治的重点。用BP网络进行源解析与CMB源解析法求出的污染源贡献率大小排序上夏、冬季完全一致,仅数值大小存在着差异,取得了较好的效果,因此BP网络模型应用于大气颗粒物的源解析是可行的。
建立了二极管阵列检测器和荧光检测器串联的高效液相色谱分析方法,优化得到对应高效色谱仪及特定色谱柱测定多环芳烃化合物的色谱条件,确定荧光检测器发射波长在390nm处各多环芳烃组分有很好的响应,在标样未完全分离的情况下,采用双激发波长有效地改善了色谱分离条件。
南昌市大气PM_(10)和PM_(2.5)中PAHs污染情况为交通干线>工业区>商业区>居民区>郊区,PM_(10)和PM_(2.5)中PAHs单体以4环和5环为主,6环次之,3环最少,2环基本未检出。毒性风险从大到小排列为八一广场>罗家集区>南昌二中老校区>荣昌小区>下罗村。南昌市的主要污染源车辆排放源、燃煤污染源、高温加热源和焦化污染源对大气PM_(10)中多环芳烃的贡献率分别为33.7%、18.8%、13.0%和18.0%。各污染源对南昌市大气PM_(2.5)中多环芳烃的贡献率分别为31.0%、21.1%、14.6%和25.8%。因子分析/多元线性逐步回归法分析的结果与南昌市区能源结构基本吻合。
罗家集区室内外PAHs的浓度总量水平高于八一广场、南昌二中老校区、荣昌小区、梨园小区室内外,八一广场、南昌二中老校区、荣昌小区、梨园小区四个室内外采样点室内PAHs与室外PAHs是相关的,而罗家集区室内外采样点存在室内源对颗粒物中PAHs的贡献,相对于3-4环的PAHs而言,5-6环的PAHs更易富集在室内的可吸入颗粒物中。
The atmospheric particles are one of the hazardous pollutants in atmospheric environment which significantly impact climate changes, visibility decline, environmental damage(eg. acid rain, smog) and health hazard. This research focuses on the atmospheric particles of different functional areas and different seasons in Nanchang city. PM_(10) and PM_(2.5) were synchronous sampled in Jul-Aug 2007, Nov-Dec 2007 and Apr-Jul 2008, and the inorganic components and PAHs of PM_(10) and PM_(2.5) collected in summer and winter were comparatively analyzed to investigate the distribution characteristics and the rules of space-time changes. Source apportionment and the distribution characteristics of PAHs in PM_(2.5) indoors and outdoors were also studied in this paper.
According to above analysis, the DAC (daily average concentration) of PM_(10) in summer was 149.09μg/m~3, 0.99 times the concentration of National Secondary Standard; PM_(2.5) in summer was 88.03μg/m~3, 1.35 times as much as American PM_(2.5) Standard; the DAC of PM_(10) in winter was 170.73μg/m~3, 1.14 times of National Secondary Standard; and PM_(2.5) in winter 110.16μg/m~3,1.69 times of American PM_(2.5) Standard. The DAC of PM_(10) and PM_(2.5) in summer were lower than that in winter. In different areas the pollution severity order of PM_(10) and PM_(2.5) was traffic roads (worse than), industrial zone, commercial mixing zone, residential zone and suburbs. The amount of PM_(2.5) was remarkably linear correlated with the amount of PM_(10), and a larger proportion than coarse particles in PM_(10), about 63%.
Distinct space-time distribution characteristics of EAC (element average concentration) were shown in different functional areas. The EAC of urban areas was higher than that of the suburbs, while the EAC of the traffic roads and industrial zone was higher than that of the commercial mixing zone and residential zone. In PM_(10), the EAC of Al, Ca, Mg, Fe, Mn, Pb, Zn, Ti and Ni in winter were higher than those in summer, which was consistent with the tendency of DAC, and the EAC of S in summer was higher than that in winter, but no evident EAC changes of As, Cu and Cr with seasons were observed. In PM_(2.5), the EAC of Al, Ca, Mg, Fe, S, Mn, Pb, Zn and Ni in winter was higher than those in summer as the tendency of DAC; whereas no obvious EAC changes of As, Cu, Cr and Ti with seasons were found.
The results of source apportionment illustrated that soil dust, burnt dust, building dust, vehicle dust and metallurgical dust were the dominant emission sources of PM_(10) and PM_(2.5) in atmospheric environment of Nanchang. The sources which made more contribution to PM_(10) also contributed more to PM_(2.5). Whether the concentrations of PM_(10) and PM_(2.5) reached the standard depends on soil dust, burnt dust and building dust, which become the emphasis of pollution control. The rank of pollution sources contribution ratio in the Summer and Winter simulated by BP network was the same as that simulated by CMB method, only varies in ratio numerical value. The preferable results proved feasibility of BP network in source apportionment.
The HPLC method with diode array and fluorescence series detectors was established and corresponding chromatographic conditions determining PAHs of specific chromatographic column were optimized. The optimal emission wavelength was selected in 390 nm, and dual wavelength excitation was applied without complete separation of standard sample. The components of PAHs were separated efficiently in chromatographic column.
The severity order of PAHs pollution in PM_(10) and PM_(2.5) was traffic roads (worse than), industrial zone, commercial mixing zone, residential zone and suburbs. The primary monomers of PAHs were 4-ring and 5-ring aromatics, 6-ring came next, 3-ring was least and 2-ring was hardly detected. The toxic risk rank was Bayi Square (more serious than), Luojiaji district, Old Campus of Nanchang No.2 Middle School, Rongchang district, and Xialuo Village. The contribution ratios of vehicle emission, coal burning, high-temperature heating and coking pollution to PAHs in PM_(10) were 33.7%, 18.8%, 13.0% and 18.0% respectively; the contribution ratios of various sources to PAHs in PM_(2.5) were 31.0%, 21.1%, 14.6% and 25.8% respectively. The results of factor analysis/multiple linear stepwise analysis conform to the energy structure of Nanchang city.
The PAHs amount of Luojia district indoors and outdoors was higher than that of Bayi Square, Old Campus of Nanchang No.2 Middle School, Rongchang district and Liyuan district. The indoor PAHs of Bayi Square, Old Campus of Nanchang No.2 Middle School, Rongchang district and Liyuan district was correlated with outdoor PAHs, except that the indoor source in Luojia district contributes to PAHs as well. Compared with 3-ring and 4-ring PAHs, 5-ring and 6-ring PAHs were easilier accumulating in inhaled particles.
引文
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