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
Investing in projects that support environmental benefits,such as tree harvesting,has the potential to reduce air pollution levels in the atmosphere in the future.However,this kind of investment may increase the curre...Investing in projects that support environmental benefits,such as tree harvesting,has the potential to reduce air pollution levels in the atmosphere in the future.However,this kind of investment may increase the current level of emissions.Therefore,it is necessary to estimate how much the policy affects the current level of CO_(2) emissions.This makes sure the policy doesn’t increase the level of CO_(2) emis-sions.This study aims to analyze the effect of the One Bil-lion Trees program on CO_(2) emissions in New Zealand by employing the 2020 input–output table analysis.This inves-tigation examines the direct and indirect effects of policy on both the demand and supply sides across six regions of New Zealand.The results of this study for the first year of plantation suggest that the policy increases the level of CO_(2) emissions in all regions,especially in the Waikato region.The direct and indirect impact of the policy leads to 64 kt of CO_(2) emissions on the demand side and 270 kt of CO_(2) emis-sions on the supply side.These lead to 0.19 and 0.74%of total CO_(2) emissions being attributed to investment shocks.Continuing the policy is recommended,as it has a low effect on CO_(2) emissions.However,it is crucial to prioritize the use of low-carbon machinery that uses fossil fuels during the plantation process.展开更多
China’s first carbon dioxide(CO_(2))measurement satellite mission,TanSat,was launched in December 2016.This paper introduces the first attempt to detect anthropogenic CO_(2) emission signatures using CO_(2) observati...China’s first carbon dioxide(CO_(2))measurement satellite mission,TanSat,was launched in December 2016.This paper introduces the first attempt to detect anthropogenic CO_(2) emission signatures using CO_(2) observations from TanSat and NO_(2) measurements from the TROPOspheric Monitoring Instrument(TROPOMI)onboard the Copernicus Sentinel-5 Precursor(S5P)satellite.We focus our analysis on two selected cases in Tangshan,China and Tokyo,Japan.We found that the TanSat XCO_(2) measurements have the capability to capture the anthropogenic variations in the plume and have spatial patterns similar to that of the TROPOMI NO_(2) observations.The linear fit between TanSat XCO_(2) and TROPOMI NO_(2) indicates the CO_(2)-to-NO_(2) ratio of 0.8×10^(-16) ppm(molec cm^(-2))^(-1) in Tangshan and 2.3×10^(-16) ppm(molec cm^(-2))^(-1) in Tokyo.Our results align with the CO_(2)-to-NOx emission ratios obtained from the EDGAR v6 emission inventory.展开更多
全球变暖已经成为不争的事实,陆地生态系统碳循环的研究受到了各界广泛关注,是当前全球变化研究中的重点。土壤CO_(2)排放是陆地生态系统与大气间二氧化碳交换的最大通量之一,当前陆地生态系统中土壤CO_(2)排放如何响应全球气候变暖及...全球变暖已经成为不争的事实,陆地生态系统碳循环的研究受到了各界广泛关注,是当前全球变化研究中的重点。土壤CO_(2)排放是陆地生态系统与大气间二氧化碳交换的最大通量之一,当前陆地生态系统中土壤CO_(2)排放如何响应全球气候变暖及其影响因素仍不清楚,限制了对土壤碳循环过程及影响机制的深入认识。旨在明确全球变暖背景下陆地生态系统中土壤CO_(2)排放格局及影响因素。基于Web of Science、PubMed和中国知网等中英文期刊数据库,充分收集全球范围内的相关野外试验文献81篇,提取出65个研究位置和213组相关研究数据,采用Meta分析方法探讨陆地生态系统土壤CO_(2)排放对增温的响应特征,分析其与海拔、气候、土壤含水量、容重(BD)、pH、全氮(TN)和土壤有机碳(SOC)的相关关系。结果表明:陆地生态系统中土壤CO_(2)排放对增温整体有显著的正向响应,在农、林、草生态系统中,增温使土壤CO_(2)排放分别显著增加13.1%、18.0%、5.9%(P<0.05),森林生态系统对增温响应的正效应最强烈;增温能在短时期内促进土壤呼吸,但随着增温持续时间增加,土壤呼吸对温度的敏感性会降低,对温度变化产生适应性,从而使其对增温的响应能力减弱;响应特征受到环境因子、土壤特性以及其他试验条件等的影响,绝大多数条件下对增温表现出显著的正响应特征,不同影响因子之间共同作用、相互影响。增温通常能够改变植物生物量、土壤养分含量及微生物数量和活性,从而影响到植被根际呼吸和土壤呼吸速率。相关分析表明,海拔对土壤CO_(2)排放有显著负向影响,而年均气温、年均降水量、土壤含水量和仪器嵌入土壤深度则对土壤CO_(2)排放产生显著正向影响。这些结果对于理解全球土壤CO_(2)排放的时空变化格局有重要意义,也为准确评价全球变暖背景下土壤碳汇功能及其持续性提供理论依据。展开更多
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Investing in projects that support environmental benefits,such as tree harvesting,has the potential to reduce air pollution levels in the atmosphere in the future.However,this kind of investment may increase the current level of emissions.Therefore,it is necessary to estimate how much the policy affects the current level of CO_(2) emissions.This makes sure the policy doesn’t increase the level of CO_(2) emis-sions.This study aims to analyze the effect of the One Bil-lion Trees program on CO_(2) emissions in New Zealand by employing the 2020 input–output table analysis.This inves-tigation examines the direct and indirect effects of policy on both the demand and supply sides across six regions of New Zealand.The results of this study for the first year of plantation suggest that the policy increases the level of CO_(2) emissions in all regions,especially in the Waikato region.The direct and indirect impact of the policy leads to 64 kt of CO_(2) emissions on the demand side and 270 kt of CO_(2) emis-sions on the supply side.These lead to 0.19 and 0.74%of total CO_(2) emissions being attributed to investment shocks.Continuing the policy is recommended,as it has a low effect on CO_(2) emissions.However,it is crucial to prioritize the use of low-carbon machinery that uses fossil fuels during the plantation process.
基金supported by the National Key Research And Development Plan (2019YFE0127500)International Partnership Program of the Chinese Academy of Sciences (060GJHZ2022070MI)+2 种基金the Key Research Program of the Chinese Academy of Sciences (ZDRWZS-2019-1)the Finland-China mobility cooperation project funded by the Academy of Finland (No. 348596)Financial support for the Academy of Finland (No. 336798)
文摘China’s first carbon dioxide(CO_(2))measurement satellite mission,TanSat,was launched in December 2016.This paper introduces the first attempt to detect anthropogenic CO_(2) emission signatures using CO_(2) observations from TanSat and NO_(2) measurements from the TROPOspheric Monitoring Instrument(TROPOMI)onboard the Copernicus Sentinel-5 Precursor(S5P)satellite.We focus our analysis on two selected cases in Tangshan,China and Tokyo,Japan.We found that the TanSat XCO_(2) measurements have the capability to capture the anthropogenic variations in the plume and have spatial patterns similar to that of the TROPOMI NO_(2) observations.The linear fit between TanSat XCO_(2) and TROPOMI NO_(2) indicates the CO_(2)-to-NO_(2) ratio of 0.8×10^(-16) ppm(molec cm^(-2))^(-1) in Tangshan and 2.3×10^(-16) ppm(molec cm^(-2))^(-1) in Tokyo.Our results align with the CO_(2)-to-NOx emission ratios obtained from the EDGAR v6 emission inventory.
文摘全球变暖已经成为不争的事实,陆地生态系统碳循环的研究受到了各界广泛关注,是当前全球变化研究中的重点。土壤CO_(2)排放是陆地生态系统与大气间二氧化碳交换的最大通量之一,当前陆地生态系统中土壤CO_(2)排放如何响应全球气候变暖及其影响因素仍不清楚,限制了对土壤碳循环过程及影响机制的深入认识。旨在明确全球变暖背景下陆地生态系统中土壤CO_(2)排放格局及影响因素。基于Web of Science、PubMed和中国知网等中英文期刊数据库,充分收集全球范围内的相关野外试验文献81篇,提取出65个研究位置和213组相关研究数据,采用Meta分析方法探讨陆地生态系统土壤CO_(2)排放对增温的响应特征,分析其与海拔、气候、土壤含水量、容重(BD)、pH、全氮(TN)和土壤有机碳(SOC)的相关关系。结果表明:陆地生态系统中土壤CO_(2)排放对增温整体有显著的正向响应,在农、林、草生态系统中,增温使土壤CO_(2)排放分别显著增加13.1%、18.0%、5.9%(P<0.05),森林生态系统对增温响应的正效应最强烈;增温能在短时期内促进土壤呼吸,但随着增温持续时间增加,土壤呼吸对温度的敏感性会降低,对温度变化产生适应性,从而使其对增温的响应能力减弱;响应特征受到环境因子、土壤特性以及其他试验条件等的影响,绝大多数条件下对增温表现出显著的正响应特征,不同影响因子之间共同作用、相互影响。增温通常能够改变植物生物量、土壤养分含量及微生物数量和活性,从而影响到植被根际呼吸和土壤呼吸速率。相关分析表明,海拔对土壤CO_(2)排放有显著负向影响,而年均气温、年均降水量、土壤含水量和仪器嵌入土壤深度则对土壤CO_(2)排放产生显著正向影响。这些结果对于理解全球土壤CO_(2)排放的时空变化格局有重要意义,也为准确评价全球变暖背景下土壤碳汇功能及其持续性提供理论依据。
