大气细颗粒物有机质组成的变化规律及其在源解析中的应用
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摘要
随着我国城市化进程的快速发展,城市大气污染表现为燃煤型污染与光化学污染共存的复合型大气污染,主要特征是大气细颗粒物(PM2.5)污染日趋严重,已成为我国大中城市的首要大气污染物,有机物已占到PM2.5质量的1/3-1/2,成为最重要的化学组成,对人体健康、空气质量和辐射强迫造成重大影响。颗粒有机物种类繁多,其中许多特征化合物可以反映源排放的化学特征,常被选作颗粒物源解析的示踪物。因此,大气颗粒有机物研究成为当前揭示细粒子化学特征及其环境影响和开展颗粒物源解析的关键领域之一。
本研究通过24h样品来研究大气细颗粒物中可溶性有机质组成的季节变化以及市区与工业区有机质组成的差异,通过日时段样品来研究大气细颗粒物中可溶性有机质组成的日变化特征。同时,本研究不仅应用同系物比值法、CPI判别法等方法对不同季节、同一采样日不同时段有机质组分的来源进行研究,而且通过PCA、PMF等统计学方法对于上海市大气细颗粒物有机质的来源进行了解析。本研究还通过各有机组分浓度与不同气象参数的统计分析,研究了不同气象参数与不同污染物的内在相关关系。最后,我们应用上述方法对台州大气细颗粒物中可溶性有机质组成的变化特征进行了研究。
上海大气PM2.5中有机质污染水平在国内大中城市处于较低的水平,但是与欧美发达地区仍存在差距。上海市大气中PM2.5中烷烃、多环芳烃、脂肪酸和左旋葡聚糖浓度具有明显的季节变化,即冬季>春季>夏季;而PM2.5中酞酸酯在不同季节的浓度水平相当,夏季略高于春季和冬季。总体来说,上海大气中PM2.5的污染水平受不同季节气象条件和排放源变化的影响呈现不同的季节特征,冬季PM2.5污染水平最高。
宝山采样点(工业区)的正构烷烃、霍烷、多环芳烃浓度在不同季节都比徐家汇高,反映了宝山地区大气PM2.5污染比市区更严重。上海大气PM2.5中不同类型有机质的组成在不同季节呈现不同的分布特征,其中烷烃、多环芳烃的季节分布差异最为显著。
大气细颗粒物中正构烷烃的日变化特征在不同时期表现出不同的特征,大致可以分为三种情况:第一种情况,风速较低,且变化规律,有明显的静风期,则污染物浓度较高,且夜晚及清晨污染物明显高于其他时间;第二种,风速稍高,但风速有较明显的日变化,夜晚风速通常较小而白天风速较高,则夜晚及清晨污染物浓度比白天高,但差别幅度较小;第三种,风速较高,且风速变化较小,则污染物浓度的变化反映着污染排放强度的变化,即白天的污染物浓度大于夜晚。
多环芳烃浓度也呈现明显的日变化。在同一天多环芳烃的最高浓度是最低浓度的5-6.5倍。对于多环芳烃浓度日变化很小的采样日期,风速都较高而且在一天中不同时段风速变化不大;而风速变化较大且晚上和早晨交通高峰期具有明显静风期的日期多环芳烃浓度具有显著的日变化。多环芳烃浓度从清晨时段到早晨一般都存在显著的上升。对于秋季和冬季的采样日,多环芳烃最高的浓度值都出现在早晨交通高峰时段(6:30AM-10:00AM)。总体而言,多环芳烃的日变化特征与正构烷烃相似。
脂肪酸与烷烃的日变化规律基本相同,明显受排放源和气象条件的变化影响;而左旋葡聚糖的日变化具有随机性,变化规律不明显;春夏两季酞酸酯浓度有较明显的变化规律,与温度的变化趋势一致,但冬季酞酸酯浓度的日变化规律不明显。
PM2.5中有机组分浓度与气象参数之间存在不同程度的相关关系。烷烃、多环芳烃、脂肪酸与温度和风速都呈现不同程度的负相关,说明烷烃、多环芳烃和脂肪酸浓度的高低与温度和风速的高低有很大关系。烷烃与相对湿度呈现弱的正相关关系,而多环芳烃和脂肪酸与相对湿度则呈现不同程度的负相关关系。酞酸酯与温度有弱的正相关,与风速有弱的负相关,与相对湿度几乎无相关性。
对于日时段变化样品的分析结果表明,多环芳烃浓度与温度和风速都呈现负相关关系,这与对于24小时样品的分析结果一致。而多环芳烃浓度与相对湿度则呈现正相关关系,这与对于季节变化的研究结果不同,说明气象条件对于多环芳烃浓度日变化的影响与其对于多环芳烃浓度季节变化的影响存在一定的差异。研究结果表明风速可能是影响多环芳烃日变化的最重要因素,而温度可能是影响多环芳烃季节变化的最重要因素。
对于气象参数与多环芳烃组成的关系来说,高分子多环芳烃组分的贡献率和风速之间有较好的负相关关系,高分子组分比率最高的时段平均风速也最小。由于局地污染物的累积而造成的排放源的变化是影响高分子量多环芳烃贡献率日变化的一个主要原因。
分子指标及因子分析结果表明,宝山、徐家汇和闸北三个地区不同季节多环芳烃都以煤燃烧和机动车尾气排放的混合源为主。对于工业区(宝山),冬季燃煤排放特征更明显,而对于城区(闸北和徐家汇),夏季机动车排放更明显。PM2.5有机质中低分子量正构烷烃(≦C26)主要来源于石油燃料燃烧,而C29和C31主要来源于植物蜡的排放。
对上海大气PM2.5中有机质的正定矩阵因子分解(PMF)分析共解析出8个PM2.5来源,分别为煤燃烧、机动车排放、二次硝酸盐、生物质燃烧、植物蜡排放、塑料燃烧、工业排放和肉类烹饪,这8中排放源对于PM2.5质量浓度的贡献率分别为30%、10%、20%、10%、12%、10%、6%和2%。
我们的研究表明台州电子垃圾拆解工业区有机质污染水平明显高于路桥市区,对于人体健康存在较高的风险,应引起足够重视。除了制定更严格的管理电子垃圾拆解工业的措施外,对于工业区交通、餐饮等相关行业的合理规范也需要重视。
台州市区与工业区大气PM2.5多环芳烃主要来自于机动车排放与煤/生物质燃烧的混合源。间四联苯在市区和电子垃圾拆解工业区的分布存在明显的差异,在工业区间四联苯与其它多环芳烃具有较为一致的来源,说明间四联苯可以作为电子垃圾排放的一个指示性物质。
The seasonal and diurnal viriations of organic matter in 24h PM2.5 samples and time interval PM2.5 samples in Shanghai were studied in this research. The differences between urban and industrial area in Shanghai was also analyzed. Simultaneously, ratios of homologous compound, CPI and some statistical methods such as PCA、PMF were also applied for source apportionment of organic matter in PM2.5 of Shanghai. We also carried out the statistical analysis of the concentrations of organic matter in PM2.5 and the meteorological parameters. And these methods were applied to the analysis of the organic matter in PM2.5 samples collected in Taizhou, a city with e-waste industry in Zhejiang province in China.
Though relatively lower compared with other Chinese cities, the concentration of organic matter in PM2.5 of Shanghai was obviously higher than that of the developed areas in the world such as the US. Alkanes, PAHs, fatty acids and levoglucosan showed obvious seasonal variations of winter>spring>summer. As for Phthalates, the concentration in summer was slightly higher than those in spring and winter. Overall, organic matter in PM2.5 had different seasonal characteristics caused by meteorologic conditions and the seasonal change of emission sources.
Concentrations of Alkanes, Hopanes and PAHs in PM2.5 samples from industrial area of Shanghai were obviously higher than those in urban area, indicating more serious atmospheric pollution caused by industrial activities.
The diurnal viriations of n-alkanes in different seasons can be roughly divided into three types: the first case, high concentrations of alkanes can be found at night and in the morning caused by low wind speed and obvious stagnant atmospheric condition, and the diurnal variation of pollutant concentrations was huge. The second case occurred when the speed of wind was higher and had obvious diurnal variation with higher wind speed during the day than at night. Then concentrations of alkanes at night and in the morning were higher than those during daytime but the difference was relatively small. Thirdly, the wind speed was high and showed small diurnal variation, then concentrations of alkanes during daytime were usually higher than those at night, reflecting the diurnal changes of emissions intensity.
Concentrations of PAHs in PM2.5 also showed obvious diurnal viaiations. The highest PAHs concentration was 5-6.5 times of the lowest concentration in the same sampling day. Generally speaking, the characteristics of the diurnal variation of PAHs was similar with that of n-alkanes. PAHs concentration rose distinctly from early morning (0:00AM-6:20AM) to morning (6:30AM-10:00AM) in all sampling days. In the late autumn and winter sampling days, the highest PAHs levels all occurred in the morning rush hours (6:30AM-10:00AM), indicating the contribution of traffic emissions.
The diurnal variation of fatty acids was also mainly controlled by meteorological conditions and similar to that of alkanes. As for levoglucosan, the diurnal variation was not distinct. The diurnal variation of phthalates in spring and summer was consistent with the variation of ambient temperature, but the diurnal variation of phthalates in winter not obvious.
Correlation of organic compounds in PM2.5 and meteorological parameters were found. Alkanes, PAHs and fatty acids had negative correlation with temperature and wind speed, and had significant positive correlation with atmospheric pressure, indicating that the concentrations of alkanes and PAHs were controlled to a large extent by temperature and wind speed. A weak positive correlation was found between alkanes concentration and relative humility, while negative correlation between concentrations of PAHs and fatty acids. The correlation between phthalates and meteorological factors was very weak.
The results of regression analysis of daily time interval samples showed similar relationship between PAH concentrations and temperature and wind speed as that from daily integrated samples, but moderate positive correlations with relative humidity, which was different from the trend of seasonal variation. Our results suggested that wind speed was the most important factor controlling the diurnal variation of concentrations of PAHs and alkanes, while ambient temperature for the seasonal variations. More significant negative correlations between concentration of PAHs and wind speed (higher R value) were found in days with lower ambient temperature such as winter, late autumn and early spring.
The percentage of low molecular weight (LMW) PAHs in total PAHs showed good correlation with wind speed, the lowest contribution of LMW PAHs occurred at the same time interval when the wind speed was the lowest. The variation of emission sources caused by the accumulation of local emitted pollutants should be the major reason for the observed diurnal variations of the LMW and high molecular weight (HMW) PAHs
Judged from the diagnostic PAH ratios, PAHs in PM2.5 samples of Zhabei、Xujiahui and Baoshan in different seasons were all from a mixed sources of coal combustion and tail gas from vehicles. As for industrial area, Baoshan, emission characteristics of PAHs from coal combustion was more obvious in winter, while for the urban areas, Zhabei and Xujiahui, mobile emission of PAHs was more important in summer.
Positive matrix factorization (PMF) was performed to apportion sources of PM2.5 in Shanghai, and eight factors were identified and they can be assigned to coal combustion (30%), vehicles emissions (10%), secondary nitrates (20%), biomass burning (10%), plant wax emissions (12%), industry (6%), cooking meat(2%), and plastic/waste burning(10%).
Our analysis on the organic matter in PM2.5 samples collected in Taizhou showed that the pollution level of airborne organic pollutants was much higher at the e-waste dismantling area than the comparing urban site, indicating severe air pollution caused by the e-waste recycling activities. To achieve better air quality at the e-waste dismantling area, more effort should be put to control the emissions from transportation and kitchen besides regulating the e-waste recycling activities.
Much higher concentrations of quterphenyl was found at the e-waste dismantling area than those at the urban area of Taizhou. Quaterphenyl had strong correlation with other PAHs in the e-waste dismantling area, suggesting that it cab be an indicator for the emisson from e-waste dismantling activities.
本研究通过24h样品来研究大气细颗粒物中可溶性有机质组成的季节变化以及市区与工业区有机质组成的差异,通过日时段样品来研究大气细颗粒物中可溶性有机质组成的日变化特征。同时,本研究不仅应用同系物比值法、CPI判别法等方法对不同季节、同一采样日不同时段有机质组分的来源进行研究,而且通过PCA、PMF等统计学方法对于上海市大气细颗粒物有机质的来源进行了解析。本研究还通过各有机组分浓度与不同气象参数的统计分析,研究了不同气象参数与不同污染物的内在相关关系。最后,我们应用上述方法对台州大气细颗粒物中可溶性有机质组成的变化特征进行了研究。
上海大气PM2.5中有机质污染水平在国内大中城市处于较低的水平,但是与欧美发达地区仍存在差距。上海市大气中PM2.5中烷烃、多环芳烃、脂肪酸和左旋葡聚糖浓度具有明显的季节变化,即冬季>春季>夏季;而PM2.5中酞酸酯在不同季节的浓度水平相当,夏季略高于春季和冬季。总体来说,上海大气中PM2.5的污染水平受不同季节气象条件和排放源变化的影响呈现不同的季节特征,冬季PM2.5污染水平最高。
宝山采样点(工业区)的正构烷烃、霍烷、多环芳烃浓度在不同季节都比徐家汇高,反映了宝山地区大气PM2.5污染比市区更严重。上海大气PM2.5中不同类型有机质的组成在不同季节呈现不同的分布特征,其中烷烃、多环芳烃的季节分布差异最为显著。
大气细颗粒物中正构烷烃的日变化特征在不同时期表现出不同的特征,大致可以分为三种情况:第一种情况,风速较低,且变化规律,有明显的静风期,则污染物浓度较高,且夜晚及清晨污染物明显高于其他时间;第二种,风速稍高,但风速有较明显的日变化,夜晚风速通常较小而白天风速较高,则夜晚及清晨污染物浓度比白天高,但差别幅度较小;第三种,风速较高,且风速变化较小,则污染物浓度的变化反映着污染排放强度的变化,即白天的污染物浓度大于夜晚。
多环芳烃浓度也呈现明显的日变化。在同一天多环芳烃的最高浓度是最低浓度的5-6.5倍。对于多环芳烃浓度日变化很小的采样日期,风速都较高而且在一天中不同时段风速变化不大;而风速变化较大且晚上和早晨交通高峰期具有明显静风期的日期多环芳烃浓度具有显著的日变化。多环芳烃浓度从清晨时段到早晨一般都存在显著的上升。对于秋季和冬季的采样日,多环芳烃最高的浓度值都出现在早晨交通高峰时段(6:30AM-10:00AM)。总体而言,多环芳烃的日变化特征与正构烷烃相似。
脂肪酸与烷烃的日变化规律基本相同,明显受排放源和气象条件的变化影响;而左旋葡聚糖的日变化具有随机性,变化规律不明显;春夏两季酞酸酯浓度有较明显的变化规律,与温度的变化趋势一致,但冬季酞酸酯浓度的日变化规律不明显。
PM2.5中有机组分浓度与气象参数之间存在不同程度的相关关系。烷烃、多环芳烃、脂肪酸与温度和风速都呈现不同程度的负相关,说明烷烃、多环芳烃和脂肪酸浓度的高低与温度和风速的高低有很大关系。烷烃与相对湿度呈现弱的正相关关系,而多环芳烃和脂肪酸与相对湿度则呈现不同程度的负相关关系。酞酸酯与温度有弱的正相关,与风速有弱的负相关,与相对湿度几乎无相关性。
对于日时段变化样品的分析结果表明,多环芳烃浓度与温度和风速都呈现负相关关系,这与对于24小时样品的分析结果一致。而多环芳烃浓度与相对湿度则呈现正相关关系,这与对于季节变化的研究结果不同,说明气象条件对于多环芳烃浓度日变化的影响与其对于多环芳烃浓度季节变化的影响存在一定的差异。研究结果表明风速可能是影响多环芳烃日变化的最重要因素,而温度可能是影响多环芳烃季节变化的最重要因素。
对于气象参数与多环芳烃组成的关系来说,高分子多环芳烃组分的贡献率和风速之间有较好的负相关关系,高分子组分比率最高的时段平均风速也最小。由于局地污染物的累积而造成的排放源的变化是影响高分子量多环芳烃贡献率日变化的一个主要原因。
分子指标及因子分析结果表明,宝山、徐家汇和闸北三个地区不同季节多环芳烃都以煤燃烧和机动车尾气排放的混合源为主。对于工业区(宝山),冬季燃煤排放特征更明显,而对于城区(闸北和徐家汇),夏季机动车排放更明显。PM2.5有机质中低分子量正构烷烃(≦C26)主要来源于石油燃料燃烧,而C29和C31主要来源于植物蜡的排放。
对上海大气PM2.5中有机质的正定矩阵因子分解(PMF)分析共解析出8个PM2.5来源,分别为煤燃烧、机动车排放、二次硝酸盐、生物质燃烧、植物蜡排放、塑料燃烧、工业排放和肉类烹饪,这8中排放源对于PM2.5质量浓度的贡献率分别为30%、10%、20%、10%、12%、10%、6%和2%。
我们的研究表明台州电子垃圾拆解工业区有机质污染水平明显高于路桥市区,对于人体健康存在较高的风险,应引起足够重视。除了制定更严格的管理电子垃圾拆解工业的措施外,对于工业区交通、餐饮等相关行业的合理规范也需要重视。
台州市区与工业区大气PM2.5多环芳烃主要来自于机动车排放与煤/生物质燃烧的混合源。间四联苯在市区和电子垃圾拆解工业区的分布存在明显的差异,在工业区间四联苯与其它多环芳烃具有较为一致的来源,说明间四联苯可以作为电子垃圾排放的一个指示性物质。
The seasonal and diurnal viriations of organic matter in 24h PM2.5 samples and time interval PM2.5 samples in Shanghai were studied in this research. The differences between urban and industrial area in Shanghai was also analyzed. Simultaneously, ratios of homologous compound, CPI and some statistical methods such as PCA、PMF were also applied for source apportionment of organic matter in PM2.5 of Shanghai. We also carried out the statistical analysis of the concentrations of organic matter in PM2.5 and the meteorological parameters. And these methods were applied to the analysis of the organic matter in PM2.5 samples collected in Taizhou, a city with e-waste industry in Zhejiang province in China.
Though relatively lower compared with other Chinese cities, the concentration of organic matter in PM2.5 of Shanghai was obviously higher than that of the developed areas in the world such as the US. Alkanes, PAHs, fatty acids and levoglucosan showed obvious seasonal variations of winter>spring>summer. As for Phthalates, the concentration in summer was slightly higher than those in spring and winter. Overall, organic matter in PM2.5 had different seasonal characteristics caused by meteorologic conditions and the seasonal change of emission sources.
Concentrations of Alkanes, Hopanes and PAHs in PM2.5 samples from industrial area of Shanghai were obviously higher than those in urban area, indicating more serious atmospheric pollution caused by industrial activities.
The diurnal viriations of n-alkanes in different seasons can be roughly divided into three types: the first case, high concentrations of alkanes can be found at night and in the morning caused by low wind speed and obvious stagnant atmospheric condition, and the diurnal variation of pollutant concentrations was huge. The second case occurred when the speed of wind was higher and had obvious diurnal variation with higher wind speed during the day than at night. Then concentrations of alkanes at night and in the morning were higher than those during daytime but the difference was relatively small. Thirdly, the wind speed was high and showed small diurnal variation, then concentrations of alkanes during daytime were usually higher than those at night, reflecting the diurnal changes of emissions intensity.
Concentrations of PAHs in PM2.5 also showed obvious diurnal viaiations. The highest PAHs concentration was 5-6.5 times of the lowest concentration in the same sampling day. Generally speaking, the characteristics of the diurnal variation of PAHs was similar with that of n-alkanes. PAHs concentration rose distinctly from early morning (0:00AM-6:20AM) to morning (6:30AM-10:00AM) in all sampling days. In the late autumn and winter sampling days, the highest PAHs levels all occurred in the morning rush hours (6:30AM-10:00AM), indicating the contribution of traffic emissions.
The diurnal variation of fatty acids was also mainly controlled by meteorological conditions and similar to that of alkanes. As for levoglucosan, the diurnal variation was not distinct. The diurnal variation of phthalates in spring and summer was consistent with the variation of ambient temperature, but the diurnal variation of phthalates in winter not obvious.
Correlation of organic compounds in PM2.5 and meteorological parameters were found. Alkanes, PAHs and fatty acids had negative correlation with temperature and wind speed, and had significant positive correlation with atmospheric pressure, indicating that the concentrations of alkanes and PAHs were controlled to a large extent by temperature and wind speed. A weak positive correlation was found between alkanes concentration and relative humility, while negative correlation between concentrations of PAHs and fatty acids. The correlation between phthalates and meteorological factors was very weak.
The results of regression analysis of daily time interval samples showed similar relationship between PAH concentrations and temperature and wind speed as that from daily integrated samples, but moderate positive correlations with relative humidity, which was different from the trend of seasonal variation. Our results suggested that wind speed was the most important factor controlling the diurnal variation of concentrations of PAHs and alkanes, while ambient temperature for the seasonal variations. More significant negative correlations between concentration of PAHs and wind speed (higher R value) were found in days with lower ambient temperature such as winter, late autumn and early spring.
The percentage of low molecular weight (LMW) PAHs in total PAHs showed good correlation with wind speed, the lowest contribution of LMW PAHs occurred at the same time interval when the wind speed was the lowest. The variation of emission sources caused by the accumulation of local emitted pollutants should be the major reason for the observed diurnal variations of the LMW and high molecular weight (HMW) PAHs
Judged from the diagnostic PAH ratios, PAHs in PM2.5 samples of Zhabei、Xujiahui and Baoshan in different seasons were all from a mixed sources of coal combustion and tail gas from vehicles. As for industrial area, Baoshan, emission characteristics of PAHs from coal combustion was more obvious in winter, while for the urban areas, Zhabei and Xujiahui, mobile emission of PAHs was more important in summer.
Positive matrix factorization (PMF) was performed to apportion sources of PM2.5 in Shanghai, and eight factors were identified and they can be assigned to coal combustion (30%), vehicles emissions (10%), secondary nitrates (20%), biomass burning (10%), plant wax emissions (12%), industry (6%), cooking meat(2%), and plastic/waste burning(10%).
Our analysis on the organic matter in PM2.5 samples collected in Taizhou showed that the pollution level of airborne organic pollutants was much higher at the e-waste dismantling area than the comparing urban site, indicating severe air pollution caused by the e-waste recycling activities. To achieve better air quality at the e-waste dismantling area, more effort should be put to control the emissions from transportation and kitchen besides regulating the e-waste recycling activities.
Much higher concentrations of quterphenyl was found at the e-waste dismantling area than those at the urban area of Taizhou. Quaterphenyl had strong correlation with other PAHs in the e-waste dismantling area, suggesting that it cab be an indicator for the emisson from e-waste dismantling activities.
引文
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