大气能见度下降影响因素、来源解析及灰霾评估指标体系研究
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摘要
我国一些城市大气颗粒物污染形势严峻，PM_(2.5)污染严重，远高于国家新环境空气质量标准GB3095-2012中规定的标准限值。城市大气污染类型已由最初的煤烟型污染发展到复合型污染，大气氧化性增强，细粒子浓度升高，导致能见度下降，灰霾天数增加。因此，研究灰霾天气的影响因素，建立灰霾评估体系并对灰霾天气下大气能见度下降的来源进行解析，是灰霾污染进行防治的客观需要。
颗粒物浓度、相对湿度和能见度之间存在着复杂的非线性关系，能见度受相对湿度、细颗粒物浓度的共同影响，二者对能见度的影响不是相互独立的，并且存在明显的地域差异。针对以上这些问题，本文提出能见度变化敏感性综合评价模型，用以研究细颗粒物浓度、相对湿度对能见度变化的影响敏感性及程度，区分大气能见度变化的不同控制区（细颗粒物浓度控制区、相对湿度控制区、二者影响作用相当区）及阈值，为建立灰霾定量判别方法提供依据。
根据细颗粒物浓度、相对湿度影响能见度变化的阈值研究结果，本文对灰霾进行了定义，并对灰霾表征的因子进行了筛选，同时结合环境质量监测与气象观测体系以及环境质量管理的需求，建立了科学合理、便于操作的灰霾污染评估指标体系、分级标准及评估方法。
对灰霾天气下能见度下降的来源进行解析是灰霾污染防治的重要基础。现有方法可解析灰霾天气下细颗粒物的化学组分对大气消光的贡献，但不能定量解析各类颗粒物排放源对能见度下降的贡献。针对上述问题，本研究建立基于颗粒物来源解析模型和颗粒物消光模型的耦合模型，定量解析大气能见度下降的细颗粒物来源及其贡献，为灰霾污染防治提供更有针对性的依据。
基于上述模型及方法，本论文对天津市灰霾表征、评估及来源解析进行了应用研究，分析了PM_(2.5)浓度、相对湿度影响能见度变化的不同控制区及阈值，建立了天津市灰霾天气的评估指标体系，并对天津市秋季灰霾天气下大气能见度下降的来源进行了解析，结果如下：
1.当能见度＜2km时，PM_(2.5)≥350μg/m~3，能见度的变化主要受PM_(2.5)浓度的影响，为PM_(2.5)浓度控制区；相对湿度≥85%时，能见度的变化主要受相对湿度的影响，为相对湿度控制区；同理，当2km≤能见度＜5km时，以PM_(2.5)≥220μg/m~3为PM_(2.5)浓度控制区，相对湿度≥80%为相对湿度控制区；当5km≤能见度＜10km时，以PM_(2.5)≥130μg/m~3为PM_(2.5)浓度控制区，相对湿度≥85%为相对湿度控制区；当10km≤能见度＜15km时，以PM_(2.5)≥80μg/m~3为PM_(2.5)浓度控制区，相对湿度≥80%为相对湿度控制区；当能见度≥15km时时，以PM_(2.5)≥10μg/m~3为PM_(2.5)浓度控制区，相对湿度则不存在明显的控制区。
2.天津市灰霾天气是指在相对湿度小于80%的情况下，由PM_(2.5)浓度控制区所造成的能见度低于10km的现象。当能见度≥10km，界定为无灰霾天气，PM_(2.5)的浓度限值为80μg/m~3，灰霾等级为0；当5km≤能见度＜10km，界定为轻度灰霾天气，PM_(2.5)的浓度限值为130μg/m~3，灰霾等级为1；当2km≤能见度＜5km，界定为中度灰霾天气，PM_(2.5)的浓度限值为220μg/m~3，灰霾等级为2；当能见度＜2km时，界定为重度灰霾天气，PM_(2.5)的浓度限值为350μg/m~3，灰霾等级为3。
3.研究期间，对于秋季灰霾天气下，二次硝酸盐是对能见度下降贡献最大的源类，其次为二次硫酸盐、机动车尾气尘，三者对能见度下降的分担率达70%以上，城市扬尘、燃煤尘对能见度下降的分担率分别为13.57%、7.05%，二次有机碳对能见度的下降的分担率为6.68%，六种源类对能见度下降的分担率达98%以上，是能见度下降的主要源类。
PM_(2.5)(particulate matter with a diameter less than2.5μm) pollution is stillsevere in some cities of China, and concentrations of PM_(2.5)were significantly higherthan the new ambient air quality standard (GB3095-2012) of annual secondarystandard limit. The type of urban air pollution has been changed from soot pollutionto complex pollution, which resulted in enhancing of atmospheric oxidation,increasing of fine particle concentration, degrading of atmospheric visibility, anddramatically increasing number of haze days. Therefore, studying influencing factorsof haze, establishing haze assessment system, and making source apportionment ofvisibility degradation were very necessary to prevent and control haze pollution.
Correlations between the visibility and the concentrations of fine particulatematter (FPM) and relative humidity (RH) were very complicated. There werenon-linear, non-mutual independence as well as the obvious geographical differencesbetween visibility and FPM concentration and RH. Based on reasons mentionedabove, a new model, named as visibility variation sensitivity hybid model, wasestablished to study sensitivity degree of visibility variation depending on theconcentration of FPM and RH, to discern the different control areas of visibilityvariation (such as the control areas of FPM concentration, control areas of RH, FPMand RH together control areas), to determine threshold values of FPM concentrationand RH, which can provide scientific basis for haze judgment.
According to the threshold values of FPM concentration studied above, the hazyweather was defined, at the same time, taking convenience of environmental qualitymonitor, meteorological observation and environmental management into account,the key factors which can characterize the hazy weather were selected, hazy weathergrade standards and haze assessment index system were established.
Source apportionment of visibility degradation is very important to prevent andcontrol haze pollution. However, research methods of visibility degradation attributedto the corresponding sources were lacked, in view of this situation, a new coupled model developed from the chemical mass balance （CMB） and Mie model wasintroduced to apportion sources of visibility degradation in hazy weather.
Based on the methods mentioned above, the city of Tianjing was selected as acase for study: threshold values of PM_(2.5)concentration and RH which impacted onthe degradtion of visibility were analyzed; hazy weather grade standards and hazeassessment index system were established; and source apportionment of visibilitydegradation was also studied. Results were as follows:
1.As visibility<2km, when PM_(2.5)≥350μg/m~3, visibility variation was mainlydetermined by concentration of PM_(2.5), When RH≥85%, visibility variation wasmainly determined by RH; As2km≤visibility<5km, when PM_(2.5)≥220μg/m~3,visibility variation was mainly determined by concentration of PM_(2.5); When RH≥80%,visibility variation was mainly determined by RH; As5km≤visibility<10km, whenPM_(2.5)≥130μg/m~3, visibility variation was mainly determined by concentration ofPM_(2.5), When RH≥85%, visibility variation was mainly determined by RH; As10km≤visibility<15km, when PM_(2.5)≥80μg/m~3, visibility variation was mainly determinedby concentration of PM_(2.5); When RH≥80%, visibility variation was mainlydetermined by RH; As visibility≥15km, PM_(2.5)concentration which impactedvisibility degradation was10μg/m~3, and there was no obvious threshold value of RH.
2.Hazy weather of Tianjin was when RH<80%, visibility degradation caused byPM_(2.5)concentration and visual range lower than10km. hazy weather grade standardsand haze assessment index system were established as follows: when visibility≥10km, type of hazy weather was non-haze, concentration limit of PM_(2.5)was80μg/m~3,haze grade was0; when5km≤visibility<10km, type of hazy weather was light haze,concentration limit of PM_(2.5)was130μg/m~3, haze grade was1; when2km≤visibility＜5km, type of hazy weather was moderate haze, concentration limit of PM_(2.5)was220μg/m~3, haze grade was2; when visibility<2km, type of hazy weather was severehaze, concentration limit of PM_(2.5)was350μg/m~3, haze grade was3.
3.Results of source apportionment of visibility degradation in autumn showedthat nitrate was the largest source to visibility degradation, and followed by sulfate,vehicle exhaust, the total contribution of these three sources was above70%,contributions of suspended dust, flying ash from coal combustion to visibility degradation were13.57%,7.05%, respectively, contributions of secondary organiccarbon (SOC) was about6%. Nitrates, sulfate, vehicle exhaust, suspended dust, flyingash from coal combustion and SOC were important sources to visibility degradationin Tianjin autumn.
颗粒物浓度、相对湿度和能见度之间存在着复杂的非线性关系，能见度受相对湿度、细颗粒物浓度的共同影响，二者对能见度的影响不是相互独立的，并且存在明显的地域差异。针对以上这些问题，本文提出能见度变化敏感性综合评价模型，用以研究细颗粒物浓度、相对湿度对能见度变化的影响敏感性及程度，区分大气能见度变化的不同控制区（细颗粒物浓度控制区、相对湿度控制区、二者影响作用相当区）及阈值，为建立灰霾定量判别方法提供依据。
根据细颗粒物浓度、相对湿度影响能见度变化的阈值研究结果，本文对灰霾进行了定义，并对灰霾表征的因子进行了筛选，同时结合环境质量监测与气象观测体系以及环境质量管理的需求，建立了科学合理、便于操作的灰霾污染评估指标体系、分级标准及评估方法。
对灰霾天气下能见度下降的来源进行解析是灰霾污染防治的重要基础。现有方法可解析灰霾天气下细颗粒物的化学组分对大气消光的贡献，但不能定量解析各类颗粒物排放源对能见度下降的贡献。针对上述问题，本研究建立基于颗粒物来源解析模型和颗粒物消光模型的耦合模型，定量解析大气能见度下降的细颗粒物来源及其贡献，为灰霾污染防治提供更有针对性的依据。
基于上述模型及方法，本论文对天津市灰霾表征、评估及来源解析进行了应用研究，分析了PM_(2.5)浓度、相对湿度影响能见度变化的不同控制区及阈值，建立了天津市灰霾天气的评估指标体系，并对天津市秋季灰霾天气下大气能见度下降的来源进行了解析，结果如下：
1.当能见度＜2km时，PM_(2.5)≥350μg/m~3，能见度的变化主要受PM_(2.5)浓度的影响，为PM_(2.5)浓度控制区；相对湿度≥85%时，能见度的变化主要受相对湿度的影响，为相对湿度控制区；同理，当2km≤能见度＜5km时，以PM_(2.5)≥220μg/m~3为PM_(2.5)浓度控制区，相对湿度≥80%为相对湿度控制区；当5km≤能见度＜10km时，以PM_(2.5)≥130μg/m~3为PM_(2.5)浓度控制区，相对湿度≥85%为相对湿度控制区；当10km≤能见度＜15km时，以PM_(2.5)≥80μg/m~3为PM_(2.5)浓度控制区，相对湿度≥80%为相对湿度控制区；当能见度≥15km时时，以PM_(2.5)≥10μg/m~3为PM_(2.5)浓度控制区，相对湿度则不存在明显的控制区。
2.天津市灰霾天气是指在相对湿度小于80%的情况下，由PM_(2.5)浓度控制区所造成的能见度低于10km的现象。当能见度≥10km，界定为无灰霾天气，PM_(2.5)的浓度限值为80μg/m~3，灰霾等级为0；当5km≤能见度＜10km，界定为轻度灰霾天气，PM_(2.5)的浓度限值为130μg/m~3，灰霾等级为1；当2km≤能见度＜5km，界定为中度灰霾天气，PM_(2.5)的浓度限值为220μg/m~3，灰霾等级为2；当能见度＜2km时，界定为重度灰霾天气，PM_(2.5)的浓度限值为350μg/m~3，灰霾等级为3。
3.研究期间，对于秋季灰霾天气下，二次硝酸盐是对能见度下降贡献最大的源类，其次为二次硫酸盐、机动车尾气尘，三者对能见度下降的分担率达70%以上，城市扬尘、燃煤尘对能见度下降的分担率分别为13.57%、7.05%，二次有机碳对能见度的下降的分担率为6.68%，六种源类对能见度下降的分担率达98%以上，是能见度下降的主要源类。
PM_(2.5)(particulate matter with a diameter less than2.5μm) pollution is stillsevere in some cities of China, and concentrations of PM_(2.5)were significantly higherthan the new ambient air quality standard (GB3095-2012) of annual secondarystandard limit. The type of urban air pollution has been changed from soot pollutionto complex pollution, which resulted in enhancing of atmospheric oxidation,increasing of fine particle concentration, degrading of atmospheric visibility, anddramatically increasing number of haze days. Therefore, studying influencing factorsof haze, establishing haze assessment system, and making source apportionment ofvisibility degradation were very necessary to prevent and control haze pollution.
Correlations between the visibility and the concentrations of fine particulatematter (FPM) and relative humidity (RH) were very complicated. There werenon-linear, non-mutual independence as well as the obvious geographical differencesbetween visibility and FPM concentration and RH. Based on reasons mentionedabove, a new model, named as visibility variation sensitivity hybid model, wasestablished to study sensitivity degree of visibility variation depending on theconcentration of FPM and RH, to discern the different control areas of visibilityvariation (such as the control areas of FPM concentration, control areas of RH, FPMand RH together control areas), to determine threshold values of FPM concentrationand RH, which can provide scientific basis for haze judgment.
According to the threshold values of FPM concentration studied above, the hazyweather was defined, at the same time, taking convenience of environmental qualitymonitor, meteorological observation and environmental management into account,the key factors which can characterize the hazy weather were selected, hazy weathergrade standards and haze assessment index system were established.
Source apportionment of visibility degradation is very important to prevent andcontrol haze pollution. However, research methods of visibility degradation attributedto the corresponding sources were lacked, in view of this situation, a new coupled model developed from the chemical mass balance （CMB） and Mie model wasintroduced to apportion sources of visibility degradation in hazy weather.
Based on the methods mentioned above, the city of Tianjing was selected as acase for study: threshold values of PM_(2.5)concentration and RH which impacted onthe degradtion of visibility were analyzed; hazy weather grade standards and hazeassessment index system were established; and source apportionment of visibilitydegradation was also studied. Results were as follows:
1.As visibility<2km, when PM_(2.5)≥350μg/m~3, visibility variation was mainlydetermined by concentration of PM_(2.5), When RH≥85%, visibility variation wasmainly determined by RH; As2km≤visibility<5km, when PM_(2.5)≥220μg/m~3,visibility variation was mainly determined by concentration of PM_(2.5); When RH≥80%,visibility variation was mainly determined by RH; As5km≤visibility<10km, whenPM_(2.5)≥130μg/m~3, visibility variation was mainly determined by concentration ofPM_(2.5), When RH≥85%, visibility variation was mainly determined by RH; As10km≤visibility<15km, when PM_(2.5)≥80μg/m~3, visibility variation was mainly determinedby concentration of PM_(2.5); When RH≥80%, visibility variation was mainlydetermined by RH; As visibility≥15km, PM_(2.5)concentration which impactedvisibility degradation was10μg/m~3, and there was no obvious threshold value of RH.
2.Hazy weather of Tianjin was when RH<80%, visibility degradation caused byPM_(2.5)concentration and visual range lower than10km. hazy weather grade standardsand haze assessment index system were established as follows: when visibility≥10km, type of hazy weather was non-haze, concentration limit of PM_(2.5)was80μg/m~3,haze grade was0; when5km≤visibility<10km, type of hazy weather was light haze,concentration limit of PM_(2.5)was130μg/m~3, haze grade was1; when2km≤visibility＜5km, type of hazy weather was moderate haze, concentration limit of PM_(2.5)was220μg/m~3, haze grade was2; when visibility<2km, type of hazy weather was severehaze, concentration limit of PM_(2.5)was350μg/m~3, haze grade was3.
3.Results of source apportionment of visibility degradation in autumn showedthat nitrate was the largest source to visibility degradation, and followed by sulfate,vehicle exhaust, the total contribution of these three sources was above70%,contributions of suspended dust, flying ash from coal combustion to visibility degradation were13.57%,7.05%, respectively, contributions of secondary organiccarbon (SOC) was about6%. Nitrates, sulfate, vehicle exhaust, suspended dust, flyingash from coal combustion and SOC were important sources to visibility degradationin Tianjin autumn.
引文
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