Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling factors.In this study,the data generated by an urban climate model were used to investigate the spat...Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling factors.In this study,the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers.A total of 355 urban clusters were used.We performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its formation.The results show that the midday AUHI is negatively correlated with climate wetness(humid:0.34 K;semi-humid:0.50 K;semi-arid:0.73 K).The annual mean midnight AUHI does not show discernible spatial patterns,but is generally stronger than the midday AUHI.The urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid(0.32±0.09 K)and the semi-arid(0.36±0.11 K)climate zones.The release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate zones.The rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations.A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land.展开更多
本文主要目的是利用卫星图像资料分析南京信息工程大学(Nanjing University of Information Science and Technology,NUIST)建校之初至今校园的变化特征.共分析了1964年11月至1970年12月之间的5幅无云的美国侦察卫星图像(1995年解密),...本文主要目的是利用卫星图像资料分析南京信息工程大学(Nanjing University of Information Science and Technology,NUIST)建校之初至今校园的变化特征.共分析了1964年11月至1970年12月之间的5幅无云的美国侦察卫星图像(1995年解密),地理配准后图像的位置精度为4.8至7.8 m,图像中的建筑物、道路和水体都清晰可见.通过对比这些黑白的侦察卫星图像与2006—2018年的Google Earth彩色图像,发现现在校园面积远远大于旧校园;旧图像里中苑老操场跑道长度为298 m,2006年Google Earth图像中为406.5 m,操场中心点向东移动了9 m,向南移动了47 m.侦察卫星图像和Google Earth图像都是以统一坐标系做地理位置校正,相关图像见附件.展开更多
Methane （CH4） emissions estimated with the Intergovernmental Panel on Climate Change （IPCC） inventory method at the city and regional scale are subject to large uncertainties.In this study,we determined the CH4：C...Methane （CH4） emissions estimated with the Intergovernmental Panel on Climate Change （IPCC） inventory method at the city and regional scale are subject to large uncertainties.In this study,we determined the CH4：CO2 emissions ratio for both Nanjing and the Yangtze River Delta （YRD）,using the atmospheric CH4 and CO2 concentrations measured at a suburban site in Nanjing in the winter.The atmospheric estimate of the CH4：CO2 emissions ratio was in reasonable agreement with that calculated using the IPCC method for the YRD （within 20％）,but was 200％ greater for the municipality of Nanjing.The most likely reason for the discrepancy is that emissions from unmanaged landfills are omitted from the official statistics on garbage production.展开更多
Developed regions of the world represent a major atmospheric methane(CH_4) source,but these regional emissions remain poorly constrained.The Yangtze River Delta(YRD) region of China is densely populated(about 16% of C...Developed regions of the world represent a major atmospheric methane(CH_4) source,but these regional emissions remain poorly constrained.The Yangtze River Delta(YRD) region of China is densely populated(about 16% of China's total population) and consists of large anthropogenic and natural CH_4 sources.Here,atmospheric CH_4 concentrations measured at a 70-m tall tower in the YRD are combined with a scale factor Bayesian inverse(SFBI) modeling approach to constrain seasonal variations in CH_4 emissions.Results indicate that in 2018 agricultural soils(AGS,rice production) were the main driver of seasonal variability in atmospheric CH_4 concentration.There was an underestimation of emissions from AGS in the a priori inventories(EDGAR—Emissions Database for Global Atmospheric Research v432 or v50),especially during the growing seasons.Posteriori CH_4 emissions from AGS accounted for 39%(4.58 Tg,EDGAR v432) to 47%(5.21 Tg,EDGAR v50) of the total CH_4 emissions.The posteriori natural emissions(including wetlands and water bodies) were1.21 Tg and 1.06 Tg,accounting for 10.1%(EDGAR v432) and 9.5%(EDGAR v50) of total emissions in the YRD in2018.Results show that the dominant factor for seasonal variations in atmospheric concentration in the YRD was AGS,followed by natural sources.In summer,AGS contributed 42%(EDGAR v432) to 64%(EDGAR v50) of the CH_4 concentration enhancement while natural sources only contributed about 10%(EDGAR v50) to 15%(EDGAR v432).In addition,the newer version of the EDGAR product(EDGAR v50) provided more reasonable seasonal distribution of CH_4 emissions from rice cultivation than the old version(EDGAR v432).展开更多
Lakes emit large amounts of carbon dioxide(CO_(2))into the atmosphere with 0.81 Pg C a^(-1)[1],which offsets approximately24%of global land carbon sink.However,there is considerable uncertainty in the estimate due to ...Lakes emit large amounts of carbon dioxide(CO_(2))into the atmosphere with 0.81 Pg C a^(-1)[1],which offsets approximately24%of global land carbon sink.However,there is considerable uncertainty in the estimate due to limited data and the effects of human activity and climate change.In China,lakes exhibit substantial variability in CO_(2)exchange,resulting in uncertainties in national and regional land carbon sink assessments.展开更多
Among several influential factors, the geographical position and depth of a lake determine its thermal structure. In temperate zones, shallow lakes show significant differences in thermal stratification compared to de...Among several influential factors, the geographical position and depth of a lake determine its thermal structure. In temperate zones, shallow lakes show significant differences in thermal stratification compared to deep lakes. Here,the variation in thermal stratification in Lake Taihu, a shallow fresh water lake, is studied systematically. Lake Taihu is a warm polymictic lake whose thermal stratification varies in short cycles of one day to a few days. The thermal stratification in Lake Taihu has shallow depths in the upper region and a large amplitude in the temperature gradient,the maximum of which exceeds 5°C m–1. The water temperature in the entire layer changes in a relatively consistent manner. Therefore, compared to a deep lake at similar latitude, the thermal stratification in Lake Taihu exhibits small seasonal differences, but the wide variation in the short term becomes important. Shallow polymictic lakes share the characteristic of diurnal mixing. Prominent differences on the duration and frequency of long-lasting thermal stratification are found in these lakes, which may result from the differences of local climate, lake depth, and fetch. A prominent response of thermal stratification to weather conditions is found, being controlled by the stratifying effect of solar radiation and the mixing effect of wind disturbance. Other than the diurnal stratification and convection, the representative responses of thermal stratification to these two factors with contrary effects are also discussed. When solar radiation increases, stronger wind is required to prevent the lake from becoming stratified. A daily average wind speed greater than 6 m s–1 can maintain the mixed state in Lake Taihu. Moreover, wind-induced convection is detected during thermal stratification. Due to lack of solar radiation, convection occurs more easily in nighttime than in daytime. Convection occurs frequently in fall and winter, whereas long-lasting and stable stratification causes less convection in summer.展开更多
The kinetic fractionation of open-water evaporation against the stable water isotope H_2 ^(18)O is an important mechanism underlying many hydrologic studies that use ^(18)O as an isotopic tracer. A recent in-situ meas...The kinetic fractionation of open-water evaporation against the stable water isotope H_2 ^(18)O is an important mechanism underlying many hydrologic studies that use ^(18)O as an isotopic tracer. A recent in-situ measurement of the isotopic water vapor flux over a lake indicates that the kinetic effect is much weaker(kinetic factor 6.2‰) than assumed previously(kinetic factor14.2‰) by lake isotopic budget studies. This study investigates the implications of the weak kinetic effect for studies of deuterium excess-humidity relationships, regional moisture recycling, and global evapotranspiration partitioning. The results indicate that the low kinetic factor is consistent with the deuterium excess-humidity relationships observed over open oceans.The moisture recycling rate in the Great Lakes region derived from the isotopic tracer method with the low kinetic factor is a much better agreement with those from atmospheric modeling studies than if the default kinetic factor of 14.2‰ is used. The ratio of transpiration to evapotranspiration at global scale decreases from 84±9%(with the default kinetic factor) to 76±19%(with the low kinetic factor), the latter of which is in slightly better agreement with other non-isotopic partitioning results.展开更多
基金supported by the National Key R&D Program of China (Grant No.2019YFA0607202)the National Natural Science Foundation of China (Grant Nos. 42021004 and 42005143)+2 种基金support by the Postgraduate Research&Practice Innovation Program of Jiangsu Province (Grant No. KYCX21_0978)support by the Open Research Fund Program of the Key Laboratory of Urban Meteorology,China Meteorological Administration (Grant No. LUM-2023-12)the 333 Project of Jiangsu Province (Grant No. BRA2022023)
文摘Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling factors.In this study,the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers.A total of 355 urban clusters were used.We performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its formation.The results show that the midday AUHI is negatively correlated with climate wetness(humid:0.34 K;semi-humid:0.50 K;semi-arid:0.73 K).The annual mean midnight AUHI does not show discernible spatial patterns,but is generally stronger than the midday AUHI.The urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid(0.32±0.09 K)and the semi-arid(0.36±0.11 K)climate zones.The release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate zones.The rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations.A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land.
文摘本文主要目的是利用卫星图像资料分析南京信息工程大学(Nanjing University of Information Science and Technology,NUIST)建校之初至今校园的变化特征.共分析了1964年11月至1970年12月之间的5幅无云的美国侦察卫星图像(1995年解密),地理配准后图像的位置精度为4.8至7.8 m,图像中的建筑物、道路和水体都清晰可见.通过对比这些黑白的侦察卫星图像与2006—2018年的Google Earth彩色图像,发现现在校园面积远远大于旧校园;旧图像里中苑老操场跑道长度为298 m,2006年Google Earth图像中为406.5 m,操场中心点向东移动了9 m,向南移动了47 m.侦察卫星图像和Google Earth图像都是以统一坐标系做地理位置校正,相关图像见附件.
基金supported by the Ministry of Education of China (Grant PCSIRT)the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)+2 种基金the National Natural Science Foundation of China (Grant No.31100359)the Natural Science Foundation of Jiangsu Province (Grant No.BK2011830)the Ningbo Planning Project of Science and Technology (Grant No.2012C50044)
文摘Methane （CH4） emissions estimated with the Intergovernmental Panel on Climate Change （IPCC） inventory method at the city and regional scale are subject to large uncertainties.In this study,we determined the CH4：CO2 emissions ratio for both Nanjing and the Yangtze River Delta （YRD）,using the atmospheric CH4 and CO2 concentrations measured at a suburban site in Nanjing in the winter.The atmospheric estimate of the CH4：CO2 emissions ratio was in reasonable agreement with that calculated using the IPCC method for the YRD （within 20％）,but was 200％ greater for the municipality of Nanjing.The most likely reason for the discrepancy is that emissions from unmanaged landfills are omitted from the official statistics on garbage production.
基金supported by the National Key R&D Program of China (Grant Nos.2020YFA0607501 and 2019YFA0607202 to WX)the Natural Science Foundation of Jiangsu Province (Grant No.BK20200802 to CH)the Key Laboratory of Meteorology and Ecological Environment of Hebei Province (Grant No.Z201901H to WX)。
文摘Developed regions of the world represent a major atmospheric methane(CH_4) source,but these regional emissions remain poorly constrained.The Yangtze River Delta(YRD) region of China is densely populated(about 16% of China's total population) and consists of large anthropogenic and natural CH_4 sources.Here,atmospheric CH_4 concentrations measured at a 70-m tall tower in the YRD are combined with a scale factor Bayesian inverse(SFBI) modeling approach to constrain seasonal variations in CH_4 emissions.Results indicate that in 2018 agricultural soils(AGS,rice production) were the main driver of seasonal variability in atmospheric CH_4 concentration.There was an underestimation of emissions from AGS in the a priori inventories(EDGAR—Emissions Database for Global Atmospheric Research v432 or v50),especially during the growing seasons.Posteriori CH_4 emissions from AGS accounted for 39%(4.58 Tg,EDGAR v432) to 47%(5.21 Tg,EDGAR v50) of the total CH_4 emissions.The posteriori natural emissions(including wetlands and water bodies) were1.21 Tg and 1.06 Tg,accounting for 10.1%(EDGAR v432) and 9.5%(EDGAR v50) of total emissions in the YRD in2018.Results show that the dominant factor for seasonal variations in atmospheric concentration in the YRD was AGS,followed by natural sources.In summer,AGS contributed 42%(EDGAR v432) to 64%(EDGAR v50) of the CH_4 concentration enhancement while natural sources only contributed about 10%(EDGAR v50) to 15%(EDGAR v432).In addition,the newer version of the EDGAR product(EDGAR v50) provided more reasonable seasonal distribution of CH_4 emissions from rice cultivation than the old version(EDGAR v432).
基金supported by the National Natural Science Foundation of China(42271114,42271377,U2243205)the Provincial Science and Technology Innovative Program for Carbon Peak and Carbon Neutrality of Jiangsu of China(BK20220041,BE2022422)+1 种基金the Science and Technology Planning Project of NIGLAS(NIGLAS2022TJ12,NIGLAS2022GS09)the Youth Innovation Promotion Association of CAS(2023329)。
文摘Lakes emit large amounts of carbon dioxide(CO_(2))into the atmosphere with 0.81 Pg C a^(-1)[1],which offsets approximately24%of global land carbon sink.However,there is considerable uncertainty in the estimate due to limited data and the effects of human activity and climate change.In China,lakes exhibit substantial variability in CO_(2)exchange,resulting in uncertainties in national and regional land carbon sink assessments.
基金Supported by the National Natural Science Foundation of China(41275024,41575147,41505005,and 41475141)Natural Science Foundation of Jiangsu Province(BK20150900)+2 种基金Startup Funds for Introduced Talents of Nanjing University of Information Science&Technology(2014r046)Ministry of Education of China grant PCSIRTPriority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)
文摘Among several influential factors, the geographical position and depth of a lake determine its thermal structure. In temperate zones, shallow lakes show significant differences in thermal stratification compared to deep lakes. Here,the variation in thermal stratification in Lake Taihu, a shallow fresh water lake, is studied systematically. Lake Taihu is a warm polymictic lake whose thermal stratification varies in short cycles of one day to a few days. The thermal stratification in Lake Taihu has shallow depths in the upper region and a large amplitude in the temperature gradient,the maximum of which exceeds 5°C m–1. The water temperature in the entire layer changes in a relatively consistent manner. Therefore, compared to a deep lake at similar latitude, the thermal stratification in Lake Taihu exhibits small seasonal differences, but the wide variation in the short term becomes important. Shallow polymictic lakes share the characteristic of diurnal mixing. Prominent differences on the duration and frequency of long-lasting thermal stratification are found in these lakes, which may result from the differences of local climate, lake depth, and fetch. A prominent response of thermal stratification to weather conditions is found, being controlled by the stratifying effect of solar radiation and the mixing effect of wind disturbance. Other than the diurnal stratification and convection, the representative responses of thermal stratification to these two factors with contrary effects are also discussed. When solar radiation increases, stronger wind is required to prevent the lake from becoming stratified. A daily average wind speed greater than 6 m s–1 can maintain the mixed state in Lake Taihu. Moreover, wind-induced convection is detected during thermal stratification. Due to lack of solar radiation, convection occurs more easily in nighttime than in daytime. Convection occurs frequently in fall and winter, whereas long-lasting and stable stratification causes less convection in summer.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41475141, 41830860, 41575147 & 41505005)the National Key Research and Development Program of China (Grant No. 2016YFC0500102)+5 种基金the U. S. National Science Foundation (Grant No. 1520684)the Science and Technology Department of Ningxia (Grant No. 2015KJHM34)the China Special Fund for Meteorological Research in the Public Interest (Major projects, Grant No. GYHY201506001-6)the NUIST Scientific Foundation (Grant No. KLME1415)the Priority Academic Program Development of Jiangsu Higher Education Institutions (Grant No. PAPD)the Ministry of Education of the People’s Republic of China (Grant No. PCSIRT)
文摘The kinetic fractionation of open-water evaporation against the stable water isotope H_2 ^(18)O is an important mechanism underlying many hydrologic studies that use ^(18)O as an isotopic tracer. A recent in-situ measurement of the isotopic water vapor flux over a lake indicates that the kinetic effect is much weaker(kinetic factor 6.2‰) than assumed previously(kinetic factor14.2‰) by lake isotopic budget studies. This study investigates the implications of the weak kinetic effect for studies of deuterium excess-humidity relationships, regional moisture recycling, and global evapotranspiration partitioning. The results indicate that the low kinetic factor is consistent with the deuterium excess-humidity relationships observed over open oceans.The moisture recycling rate in the Great Lakes region derived from the isotopic tracer method with the low kinetic factor is a much better agreement with those from atmospheric modeling studies than if the default kinetic factor of 14.2‰ is used. The ratio of transpiration to evapotranspiration at global scale decreases from 84±9%(with the default kinetic factor) to 76±19%(with the low kinetic factor), the latter of which is in slightly better agreement with other non-isotopic partitioning results.
