明确当地臭氧生成敏感性变化的主控因子是制定有效臭氧污染控制策略的前提。采用卫星观测OMI FNR(Ratio of the tropospheric columns of Formaldehyde to Nitrogen dioxide,HCHO/NO_(2))指示剂将河南省夏季臭氧生成敏感性OFS(Ozone For...明确当地臭氧生成敏感性变化的主控因子是制定有效臭氧污染控制策略的前提。采用卫星观测OMI FNR(Ratio of the tropospheric columns of Formaldehyde to Nitrogen dioxide,HCHO/NO_(2))指示剂将河南省夏季臭氧生成敏感性OFS(Ozone Formation Sensitivity)划分为VOCs控制区、协同控制区和NO_(x)控制区。基于地理探测器,量化气象条件、人为源前体物及其交互作用与OFS的关系。研究揭示:(1)河南省夏季OFS以协同控制区为主,区域内臭氧污染严重,仅次于VOCS控制区。2005年—2015年,FNR值波动下降,OFS向协同控制区转变,主要受NO_(X)减排的影响。2016年之后,FNR值变大,OFS有向NO_(X)控制区转变的趋势。(2)人为源排放是OFS变化的主要驱动因子,平均可解释FNR变化的40.5%(q=0.405)。若CO、PM_(2.5)、NO_(x)和非甲烷挥发性有机物NMVOC(Non-methane Volatile Organic Compounds)的排放量增加,FNR减小,河南省夏季OFS向VOCs控制区转变,对NO_(x)减排的敏感性降低。(3)地表净太阳辐射SSR(q=0.321,Surface net Solar Radiation)和大气柱总水量TCW(q=0.302,Total Column Water)是河南省夏季OFS变化的主要气象驱动因素。SSR增加,FNR减小,使臭氧生成对VOCs更加敏感。TCW对OFS变化的影响较为复杂,当TCW<40 kg/m^(2)时,TCW增加,FNR减小,臭氧生成对VOCs更加敏感;当TCW>40 kg/m^(2)时,TCW增加,FNR增大,臭氧生成对NO_(x)更加敏感。(4)因子间的交互作用对OFS空间分布的驱动大于单一因子的独立作用,人为源前体物和气象因子的交互作用占主导地位。研究结果可加强对臭氧生成光化学过程的认识,为制定合理的污染减排措施提供依据。展开更多
There has been paucity of field campaigns in India in past few decades on the urban heat island intensities (UHI). Remote sensing observations provide useful information on urban heat island intensities and hotspots a...There has been paucity of field campaigns in India in past few decades on the urban heat island intensities (UHI). Remote sensing observations provide useful information on urban heat island intensities and hotspots as supplement or proxy to in-situ surface based measurements. A case study has been undertaken to assess and compare the UHI and hotspots based on in-situ measurements and remote sensing observations as the later method can be used as a proxy in absence of in-situ measurements both spatially and temporally. Capital of India, megacity Delhi has grown by leaps and bounds during past 2 - 3 decades and strongly represents tropical climatic conditions where such studies and field campaigns are practically non-existent. Thus, a field campaign was undertaken during summer, 2008 named DELHI-I (Delhi Experiments to Learn Heat Island Intensity-I) in this megacity. Urban heat island effects were found to be most dominant in areas of dense built up infrastructure and at commercial centers. The heat island intensity (UHI) was observed to be higher in magnitude both during afternoon hours and night hours (maximum up to 8.3?C) similar to some recent studies. The three high ranking urban heat island locations in the city are within commercial and/or densely populated areas. The results of this field campaign when compared with MODIS-Terra data of land surface temperature revealed that UHI hotspots are comparable only during nighttime. During daytime, similar comparison was less satisfactory. Further, available relationship of maximum UHI with population data is applied for the current measurements and discussed in the context of maximum UHI of various other countries.展开更多
文摘明确当地臭氧生成敏感性变化的主控因子是制定有效臭氧污染控制策略的前提。采用卫星观测OMI FNR(Ratio of the tropospheric columns of Formaldehyde to Nitrogen dioxide,HCHO/NO_(2))指示剂将河南省夏季臭氧生成敏感性OFS(Ozone Formation Sensitivity)划分为VOCs控制区、协同控制区和NO_(x)控制区。基于地理探测器,量化气象条件、人为源前体物及其交互作用与OFS的关系。研究揭示:(1)河南省夏季OFS以协同控制区为主,区域内臭氧污染严重,仅次于VOCS控制区。2005年—2015年,FNR值波动下降,OFS向协同控制区转变,主要受NO_(X)减排的影响。2016年之后,FNR值变大,OFS有向NO_(X)控制区转变的趋势。(2)人为源排放是OFS变化的主要驱动因子,平均可解释FNR变化的40.5%(q=0.405)。若CO、PM_(2.5)、NO_(x)和非甲烷挥发性有机物NMVOC(Non-methane Volatile Organic Compounds)的排放量增加,FNR减小,河南省夏季OFS向VOCs控制区转变,对NO_(x)减排的敏感性降低。(3)地表净太阳辐射SSR(q=0.321,Surface net Solar Radiation)和大气柱总水量TCW(q=0.302,Total Column Water)是河南省夏季OFS变化的主要气象驱动因素。SSR增加,FNR减小,使臭氧生成对VOCs更加敏感。TCW对OFS变化的影响较为复杂,当TCW<40 kg/m^(2)时,TCW增加,FNR减小,臭氧生成对VOCs更加敏感;当TCW>40 kg/m^(2)时,TCW增加,FNR增大,臭氧生成对NO_(x)更加敏感。(4)因子间的交互作用对OFS空间分布的驱动大于单一因子的独立作用,人为源前体物和气象因子的交互作用占主导地位。研究结果可加强对臭氧生成光化学过程的认识,为制定合理的污染减排措施提供依据。
文摘There has been paucity of field campaigns in India in past few decades on the urban heat island intensities (UHI). Remote sensing observations provide useful information on urban heat island intensities and hotspots as supplement or proxy to in-situ surface based measurements. A case study has been undertaken to assess and compare the UHI and hotspots based on in-situ measurements and remote sensing observations as the later method can be used as a proxy in absence of in-situ measurements both spatially and temporally. Capital of India, megacity Delhi has grown by leaps and bounds during past 2 - 3 decades and strongly represents tropical climatic conditions where such studies and field campaigns are practically non-existent. Thus, a field campaign was undertaken during summer, 2008 named DELHI-I (Delhi Experiments to Learn Heat Island Intensity-I) in this megacity. Urban heat island effects were found to be most dominant in areas of dense built up infrastructure and at commercial centers. The heat island intensity (UHI) was observed to be higher in magnitude both during afternoon hours and night hours (maximum up to 8.3?C) similar to some recent studies. The three high ranking urban heat island locations in the city are within commercial and/or densely populated areas. The results of this field campaign when compared with MODIS-Terra data of land surface temperature revealed that UHI hotspots are comparable only during nighttime. During daytime, similar comparison was less satisfactory. Further, available relationship of maximum UHI with population data is applied for the current measurements and discussed in the context of maximum UHI of various other countries.
