The Hyperspectral Infrared Atmospheric Sounder-II(HIRAS-II)onboard China’s FungYun(FY)-3F meteorological satellite was launched in August 2023.This study presents the first attempt to retrieve the global carbon monox...The Hyperspectral Infrared Atmospheric Sounder-II(HIRAS-II)onboard China’s FungYun(FY)-3F meteorological satellite was launched in August 2023.This study presents the first attempt to retrieve the global carbon monoxide(CO)column from HIRAS-II/FY-3F spectra based on a newly established full-physics algorithm.The CO global columns derived from the HIRAS-II/FY-3F satellite are compared to measurements from the Infrared Atmospheric Sounding Interferometer(IASI)onboard Europe’s MetopB satellite,as both satellites have the same spectral range with a similar overpass time.The correlation coefficient between the IASI/Metop-B and HIRAS-II/FY-3F CO retrievals is about 0.8.The HIRAS-II/FY-3F satellite can capture well the regions with high CO values,e.g.,Africa,North America,and East Asia.The relative difference in the CO global column between HIRAS-II and IASI is 1.2±13.7(1)%,which is within their combined retrieval uncertainty.The CO plumes from the fire emissions in North America between 18 and 23 July 2024 were observed by the HIRAS-II/FY-3F satellite and consistent with the CAMS(Copernicus Atmosphere Monitoring Service)model simulations.Our results show that the HIRAS-II/FY-3F spectra are of good enough quality to provide quantitative observations of global CO column remote sensing observations.展开更多
Methane(CH4)is one of the most important greenhouse gases in the atmosphere,making it worthwhile to study its temporal and vertical distributions in source areas,e.g.,North China.For this purpose,a ground-based high-r...Methane(CH4)is one of the most important greenhouse gases in the atmosphere,making it worthwhile to study its temporal and vertical distributions in source areas,e.g.,North China.For this purpose,a ground-based high-resolution Fourier transform infrared spectrometer(FTIR),the Bruker IFS 125 HR,along with an in-situ instrument,the Picarro G2301,were deployed in Xianghe County(39.8°N,117.0°E),Hebei Province,China.Data have been recorded since June2018.For the FTIR measurements,we used two observation modes to retrieve the mole fraction of CH4:the Total Carbon Column Observing Network(TCCON)method(retrieval algorithm:GGG2014),and the Network for the Detection of Atmospheric Composition Change(NDACC)method(retrieval algorithm:SFIT4).Combining FTIR with in-situ measurements,we found the temporal and vertical distributions of atmospheric CH4 within three vertical layers(near the ground,in the troposphere,and in the stratosphere),and throughout the whole atmosphere.Regarding the diurnal variation of CH4 near the ground,the concentration at night was higher than during the daytime.Regarding the seasonal variation,CH4 was low in spring and high in summer,for all three vertical layers.In addition,there was a peak of CH4 in winter near the ground,both in the troposphere and the whole atmosphere.We found that variation of CH4 in the tropospheric column was close to that of the in-situ measurements near the ground.Furthermore,the variations of CH4 in the stratospheric column could be influenced by vertical motions,since it was higher in summer and lower in winter.展开更多
Measurements of carbon dioxide(CO_(2)),methane(CH_(4)),and carbon monoxide(CO)are of great importance in the Qinghai-Tibetan region,as it is the highest and largest plateau in the world affecting global weather and cl...Measurements of carbon dioxide(CO_(2)),methane(CH_(4)),and carbon monoxide(CO)are of great importance in the Qinghai-Tibetan region,as it is the highest and largest plateau in the world affecting global weather and climate systems.In this study,for the first time,we present CO_(2),CH_(4),and CO column measurements carried out by a Bruker EM27/SUN Fourier-transform infrared spectrometer(FTIR)at Golmud(36.42°E,94.91°N,2808 m)in August 2021.The mean and standard deviation of the column-average dry-air mixing ratio of CO_(2),CH_(4),and CO(XCO_(2),XCH_(4),and XCO)are 409.3±0.4 ppm,1905.5±19.4 ppb,and 103.1±7.7 ppb,respectively.The differences between the FTIR co-located TROPOMI/S5P satellite measurements at Golmud are 0.68±0.64%(13.1±12.2 ppb)for XCH_(4)and 9.81±3.48%(–10.7±3.8 ppb)for XCO,which are within their retrieval uncertainties.High correlations for both XCH_(4)and XCO are observed between the FTIR and S5P satellite measurements.Using the FLEXPART model and satellite measurements,we find that enhanced CH_(4)and CO columns in Golmud are affected by anthropogenic emissions transported from North India.This study provides an insight into the variations of the CO_(2),CH_(4),and CO columns in the Qinghai-Tibetan Plateau.展开更多
Atmospheric ammonia(NH_(3)) is a chemically active trace gas that plays an important role in the atmospheric environment and climate change. Satellite remote sensing is a powerful technique to monitor NH_(3) concentra...Atmospheric ammonia(NH_(3)) is a chemically active trace gas that plays an important role in the atmospheric environment and climate change. Satellite remote sensing is a powerful technique to monitor NH_(3) concentration based on the absorption lines of NH_(3) in the thermal infrared region. In this study, we establish a retrieval algorithm to derive the NH_(3)column from the Hyperspectral Infrared Atmospheric Sounder(HIRAS) onboard the Chinese Feng Yun(FY)-3D satellite and present the first atmospheric NH_(3) column global map observed by the HIRAS instrument. The HIRAS observations can well capture NH_(3) hotspots around the world, e.g., India, West Africa, and East China, where large NH_(3) emissions exist. The HIRAS NH_(3) columns are also compared to the space-based Infrared Atmospheric Sounding Interferometer(IASI)measurements, and we find that the two instruments observe a consistent NH_(3) global distribution, with correlation coefficient(R) values of 0.28–0.73. Finally, some remaining issues about the HIRAS NH_(3) retrieval are discussed.展开更多
Coal-fired power plants are a major carbon source in China. In order to assess the evaluation of China's carbon reduction progress with the promise made on the Paris Agreement, it is crucial to monitor the carbon ...Coal-fired power plants are a major carbon source in China. In order to assess the evaluation of China's carbon reduction progress with the promise made on the Paris Agreement, it is crucial to monitor the carbon flux intensity from coal-fired power plants. Previous studies have calculated CO_(2) emissions from point sources based on Orbiting Carbon Observatory-2 and-3(OCO-2 and OCO-3) satellite measurements, but the factors affecting CO_(2) flux estimations are uncertain. In this study, we employ a Gaussian Plume Model to estimate CO_(2) emissions from three power plants in China based on OCO-3 XCO_(2) measurements. Moreover, flux uncertainties resulting from wind information, background values,satellite CO_(2) measurements, and atmospheric stability are discussed. This study highlights the CO_(2) flux uncertainty derived from the satellite measurements. Finally, satellite-based CO_(2) emission estimates are compared to bottom-up inventories.The satellite-based CO_(2) emission estimates at the Tuoketuo and Nongliushi power plants are ~30 and ~10 kt d^(-1) smaller than the Open-Data Inventory for Anthropogenic Carbon dioxide(ODIAC) respectively, but ~10 kt d^(-1) larger than the ODIAC at Baotou.展开更多
“Diurnal variation of CH4 at the surface from spring to winter.The time units are in local time(+8 h UTC).The error bar is 1σfor all the observed hourly mean data within that season at that local time.”in the capti...“Diurnal variation of CH4 at the surface from spring to winter.The time units are in local time(+8 h UTC).The error bar is 1σfor all the observed hourly mean data within that season at that local time.”in the caption of Fig.8 on Page 604 should be“Diurnal variation of CH4 at the surface from spring to winter.The time units are in UTC.The error bar is 1σfor all the observed hourly mean data within that season at that local time.”展开更多
Accurate estimate of the size of land carbon sink is essential for guiding climate mitigation actions to fulfill China's net-zero ambitions before 2060.The atmospheric inversion is an effective approach to provide...Accurate estimate of the size of land carbon sink is essential for guiding climate mitigation actions to fulfill China's net-zero ambitions before 2060.The atmospheric inversion is an effective approach to provide spatially explicit estimate of surface CO_(2)fluxes that are optimally consistent with atmospheric CO_(2)measurements.But atmospheric inversion of China's land carbon sink has enormous uncertainties,with one major source arising from the poor coverage of CO_(2)observation stations.Here we use a regional atmospheric inversion framework to design an observation network that could minimize uncertainties in inverted estimate of China's land carbon sink.Compared with the large spread of inverted sink(~1 Pg C a~(-1))from state-of-the-art inversions using existing CO_(2)observations,the uncertainty is constrained within 0.3 Pg C a~(-1)when a total of 30 stations were deployed,and is further reduced to approximately 0.2 Pg C a~(-1)when 60 stations were deployed.The proposed stations are mostly distributed over areas with high biosphere productivity during the growing season,such as Southeast China,Northeast China,North China,and the Tibetan Plateau.Moreover,the proposed stations can cover areas where existing satellites have limited coverage due to cloud shadowing in the monsoon season or over complex topography.Such ground-based observation network will be a critical component in the future integrated observing system for monitoring China's land carbon fluxes.展开更多
基金supported by the FengYun Application Pioneering Project (Grant No. FY-APP-2022.0502)the National Natural Science Foundation of China (42205140)the State Key Laboratory of Atmospheric Environment end Extreme Meteorology (Grant No. 2024QN04)
文摘The Hyperspectral Infrared Atmospheric Sounder-II(HIRAS-II)onboard China’s FungYun(FY)-3F meteorological satellite was launched in August 2023.This study presents the first attempt to retrieve the global carbon monoxide(CO)column from HIRAS-II/FY-3F spectra based on a newly established full-physics algorithm.The CO global columns derived from the HIRAS-II/FY-3F satellite are compared to measurements from the Infrared Atmospheric Sounding Interferometer(IASI)onboard Europe’s MetopB satellite,as both satellites have the same spectral range with a similar overpass time.The correlation coefficient between the IASI/Metop-B and HIRAS-II/FY-3F CO retrievals is about 0.8.The HIRAS-II/FY-3F satellite can capture well the regions with high CO values,e.g.,Africa,North America,and East Asia.The relative difference in the CO global column between HIRAS-II and IASI is 1.2±13.7(1)%,which is within their combined retrieval uncertainty.The CO plumes from the fire emissions in North America between 18 and 23 July 2024 were observed by the HIRAS-II/FY-3F satellite and consistent with the CAMS(Copernicus Atmosphere Monitoring Service)model simulations.Our results show that the HIRAS-II/FY-3F spectra are of good enough quality to provide quantitative observations of global CO column remote sensing observations.
基金funded by the National Key R&D Program of China(Grant Nos.2017YFB0504000 and 2017YFC1501701)the National Natural Science Foundation of China(Grant No.41975035)。
文摘Methane(CH4)is one of the most important greenhouse gases in the atmosphere,making it worthwhile to study its temporal and vertical distributions in source areas,e.g.,North China.For this purpose,a ground-based high-resolution Fourier transform infrared spectrometer(FTIR),the Bruker IFS 125 HR,along with an in-situ instrument,the Picarro G2301,were deployed in Xianghe County(39.8°N,117.0°E),Hebei Province,China.Data have been recorded since June2018.For the FTIR measurements,we used two observation modes to retrieve the mole fraction of CH4:the Total Carbon Column Observing Network(TCCON)method(retrieval algorithm:GGG2014),and the Network for the Detection of Atmospheric Composition Change(NDACC)method(retrieval algorithm:SFIT4).Combining FTIR with in-situ measurements,we found the temporal and vertical distributions of atmospheric CH4 within three vertical layers(near the ground,in the troposphere,and in the stratosphere),and throughout the whole atmosphere.Regarding the diurnal variation of CH4 near the ground,the concentration at night was higher than during the daytime.Regarding the seasonal variation,CH4 was low in spring and high in summer,for all three vertical layers.In addition,there was a peak of CH4 in winter near the ground,both in the troposphere and the whole atmosphere.We found that variation of CH4 in the tropospheric column was close to that of the in-situ measurements near the ground.Furthermore,the variations of CH4 in the stratospheric column could be influenced by vertical motions,since it was higher in summer and lower in winter.
基金supported by the National Natural Science Foundation of China(Grant No.42205140,41975035)the National Key Research and Development Program of China(2021YFB3901000).
文摘Measurements of carbon dioxide(CO_(2)),methane(CH_(4)),and carbon monoxide(CO)are of great importance in the Qinghai-Tibetan region,as it is the highest and largest plateau in the world affecting global weather and climate systems.In this study,for the first time,we present CO_(2),CH_(4),and CO column measurements carried out by a Bruker EM27/SUN Fourier-transform infrared spectrometer(FTIR)at Golmud(36.42°E,94.91°N,2808 m)in August 2021.The mean and standard deviation of the column-average dry-air mixing ratio of CO_(2),CH_(4),and CO(XCO_(2),XCH_(4),and XCO)are 409.3±0.4 ppm,1905.5±19.4 ppb,and 103.1±7.7 ppb,respectively.The differences between the FTIR co-located TROPOMI/S5P satellite measurements at Golmud are 0.68±0.64%(13.1±12.2 ppb)for XCH_(4)and 9.81±3.48%(–10.7±3.8 ppb)for XCO,which are within their retrieval uncertainties.High correlations for both XCH_(4)and XCO are observed between the FTIR and S5P satellite measurements.Using the FLEXPART model and satellite measurements,we find that enhanced CH_(4)and CO columns in Golmud are affected by anthropogenic emissions transported from North India.This study provides an insight into the variations of the CO_(2),CH_(4),and CO columns in the Qinghai-Tibetan Plateau.
基金supported by the Feng Yun Application Pioneering Project (FY-APP-2022.0502)the National Natural Science Foundation of China (Grant No. 42205140)。
文摘Atmospheric ammonia(NH_(3)) is a chemically active trace gas that plays an important role in the atmospheric environment and climate change. Satellite remote sensing is a powerful technique to monitor NH_(3) concentration based on the absorption lines of NH_(3) in the thermal infrared region. In this study, we establish a retrieval algorithm to derive the NH_(3)column from the Hyperspectral Infrared Atmospheric Sounder(HIRAS) onboard the Chinese Feng Yun(FY)-3D satellite and present the first atmospheric NH_(3) column global map observed by the HIRAS instrument. The HIRAS observations can well capture NH_(3) hotspots around the world, e.g., India, West Africa, and East China, where large NH_(3) emissions exist. The HIRAS NH_(3) columns are also compared to the space-based Infrared Atmospheric Sounding Interferometer(IASI)measurements, and we find that the two instruments observe a consistent NH_(3) global distribution, with correlation coefficient(R) values of 0.28–0.73. Finally, some remaining issues about the HIRAS NH_(3) retrieval are discussed.
基金supported by the Shanghai Sailing Program (Grant No. 22YF1442000)the Key Laboratory of Middle Atmosphere and Global Environment Observation(Grant No. LAGEO-2021-07)+1 种基金the National Natural Science Foundation of China (Grant No. 41975035)Jiaxing University (Grant Nos. 00323027AL and CD70522035)。
文摘Coal-fired power plants are a major carbon source in China. In order to assess the evaluation of China's carbon reduction progress with the promise made on the Paris Agreement, it is crucial to monitor the carbon flux intensity from coal-fired power plants. Previous studies have calculated CO_(2) emissions from point sources based on Orbiting Carbon Observatory-2 and-3(OCO-2 and OCO-3) satellite measurements, but the factors affecting CO_(2) flux estimations are uncertain. In this study, we employ a Gaussian Plume Model to estimate CO_(2) emissions from three power plants in China based on OCO-3 XCO_(2) measurements. Moreover, flux uncertainties resulting from wind information, background values,satellite CO_(2) measurements, and atmospheric stability are discussed. This study highlights the CO_(2) flux uncertainty derived from the satellite measurements. Finally, satellite-based CO_(2) emission estimates are compared to bottom-up inventories.The satellite-based CO_(2) emission estimates at the Tuoketuo and Nongliushi power plants are ~30 and ~10 kt d^(-1) smaller than the Open-Data Inventory for Anthropogenic Carbon dioxide(ODIAC) respectively, but ~10 kt d^(-1) larger than the ODIAC at Baotou.
文摘“Diurnal variation of CH4 at the surface from spring to winter.The time units are in local time(+8 h UTC).The error bar is 1σfor all the observed hourly mean data within that season at that local time.”in the caption of Fig.8 on Page 604 should be“Diurnal variation of CH4 at the surface from spring to winter.The time units are in UTC.The error bar is 1σfor all the observed hourly mean data within that season at that local time.”
基金supported by the Second Tibetan Plateau Scientific Expedition and Research Program(2022QZKK0101)the National Natural Science Foundation of China(41988101,42001104,and 41975140)+1 种基金the National Key Scientific and Technological Infrastructure Project“Earth System Science Numerical Simulator Facility”(Earth Lab,201715003471104355)the Innovation Program for Young Scholars of TPESER(TPESER-QNCX2022ZD-01)。
文摘Accurate estimate of the size of land carbon sink is essential for guiding climate mitigation actions to fulfill China's net-zero ambitions before 2060.The atmospheric inversion is an effective approach to provide spatially explicit estimate of surface CO_(2)fluxes that are optimally consistent with atmospheric CO_(2)measurements.But atmospheric inversion of China's land carbon sink has enormous uncertainties,with one major source arising from the poor coverage of CO_(2)observation stations.Here we use a regional atmospheric inversion framework to design an observation network that could minimize uncertainties in inverted estimate of China's land carbon sink.Compared with the large spread of inverted sink(~1 Pg C a~(-1))from state-of-the-art inversions using existing CO_(2)observations,the uncertainty is constrained within 0.3 Pg C a~(-1)when a total of 30 stations were deployed,and is further reduced to approximately 0.2 Pg C a~(-1)when 60 stations were deployed.The proposed stations are mostly distributed over areas with high biosphere productivity during the growing season,such as Southeast China,Northeast China,North China,and the Tibetan Plateau.Moreover,the proposed stations can cover areas where existing satellites have limited coverage due to cloud shadowing in the monsoon season or over complex topography.Such ground-based observation network will be a critical component in the future integrated observing system for monitoring China's land carbon fluxes.
