In the context of the era of carbon peaking and carbon neutrality,clarifying the emission patterns of non-CO_(2)Greenhouse Gas(GHG)from agricultural sources is of practical significance to China’s implementation of g...In the context of the era of carbon peaking and carbon neutrality,clarifying the emission patterns of non-CO_(2)Greenhouse Gas(GHG)from agricultural sources is of practical significance to China’s implementation of greenhouse gas emission reduction policies.The Intergovernmental Panel on Climate Change(IPCC)coefficient method was used to calculate non-CO_(2)GHG emissions from agricultural sources in 122 counties in Hunan Province,China,from 2010 to 2020,and the spatiotemporal evolution characteristics of emission intensity were analyzed.The Stochastic Impacts by Regression on Population,Affluence,and Technology(STRIPAT)model forecasted the prospective evolution of non-CO_(2)GHG emissions from agricultural sources at the county level under various scenarios from 2030 to 2050.The results demonstrated a general decline in non-CO_(2)GHG emissions from agricultural sources within the study area,with 75.41%of counties exhibiting a reduction in emissions.Geographically,emissions were higher in the Dongting Lake area and central Hengyang.The emission intensity per unit of agricultural added value and the intensity per unit of agricultural land area showed an overall downward trend.Spatially,the emission intensity per unit of farmland area in a few counties(cities,districts)in southern Hunan was still relatively high.By forecasting the non-CO_(2)GHG emissions from agricultural sources,the majority of counties(cities and districts)demonstrated a gradual decline in emissions,suggesting that agricultural production had the potential to reduce emissions in the future,while also facing certain pressure to reduce emissions.It is recommended that Hunan Province formulate agricultural carbon emission reduction policies that take regional development differences into account.This would provide a reference for future agricultural carbon emission reduction research in the whole country.展开更多
我国已宣布力争2030年前二氧化碳排放达到峰值,为确保河北省能够保质保量完成碳达峰目标,采用联合国政府间气候变化专门委员会(Intergovernmental Panel on Climate Change, IPCC)排放因子法测算河北省2005-2021年化石能源消费碳排放量...我国已宣布力争2030年前二氧化碳排放达到峰值,为确保河北省能够保质保量完成碳达峰目标,采用联合国政府间气候变化专门委员会(Intergovernmental Panel on Climate Change, IPCC)排放因子法测算河北省2005-2021年化石能源消费碳排放量,选取人口、人均GDP、城镇化率、产业结构、能源强度和能源结构6个因素,构建了河北省碳排放人口、财富和技术影响(stochastic impacts by regression on population, affluence, and technology, STIRPAT)预测模型,通过构建河北省碳排放情景,对河北2022-2040年碳排放量进行了预测。结果表明在基准情景和经济发展情景下,河北省碳排放趋势是持续上升的,未出现达峰点;产业转型、绿色发展和目标导向情景下出现了峰值点,其中目标导向情景在2029年达峰,绿色发展情景在2030年达峰,碳达峰量分别为81 626.658万吨二氧化碳和86 018.255万吨二氧化碳,产业转型情景在2035年达峰,碳达峰量为85 214.349万吨二氧化碳。按照目前情景发展下河北省难以在2030年实现碳达峰,为保质保量完成达峰目标,需要以能源绿色低碳发展为关键手段,同时以科技和制度创新为动力,调整优化产业结构和能源结构。展开更多
基金Under the auspices of the National Natural Science Foundation of China(No.42471241,41971219,41571168)Hunan Provincial Natural Science Foundation(No.2020JJ4372)。
文摘In the context of the era of carbon peaking and carbon neutrality,clarifying the emission patterns of non-CO_(2)Greenhouse Gas(GHG)from agricultural sources is of practical significance to China’s implementation of greenhouse gas emission reduction policies.The Intergovernmental Panel on Climate Change(IPCC)coefficient method was used to calculate non-CO_(2)GHG emissions from agricultural sources in 122 counties in Hunan Province,China,from 2010 to 2020,and the spatiotemporal evolution characteristics of emission intensity were analyzed.The Stochastic Impacts by Regression on Population,Affluence,and Technology(STRIPAT)model forecasted the prospective evolution of non-CO_(2)GHG emissions from agricultural sources at the county level under various scenarios from 2030 to 2050.The results demonstrated a general decline in non-CO_(2)GHG emissions from agricultural sources within the study area,with 75.41%of counties exhibiting a reduction in emissions.Geographically,emissions were higher in the Dongting Lake area and central Hengyang.The emission intensity per unit of agricultural added value and the intensity per unit of agricultural land area showed an overall downward trend.Spatially,the emission intensity per unit of farmland area in a few counties(cities,districts)in southern Hunan was still relatively high.By forecasting the non-CO_(2)GHG emissions from agricultural sources,the majority of counties(cities and districts)demonstrated a gradual decline in emissions,suggesting that agricultural production had the potential to reduce emissions in the future,while also facing certain pressure to reduce emissions.It is recommended that Hunan Province formulate agricultural carbon emission reduction policies that take regional development differences into account.This would provide a reference for future agricultural carbon emission reduction research in the whole country.
文摘我国已宣布力争2030年前二氧化碳排放达到峰值,为确保河北省能够保质保量完成碳达峰目标,采用联合国政府间气候变化专门委员会(Intergovernmental Panel on Climate Change, IPCC)排放因子法测算河北省2005-2021年化石能源消费碳排放量,选取人口、人均GDP、城镇化率、产业结构、能源强度和能源结构6个因素,构建了河北省碳排放人口、财富和技术影响(stochastic impacts by regression on population, affluence, and technology, STIRPAT)预测模型,通过构建河北省碳排放情景,对河北2022-2040年碳排放量进行了预测。结果表明在基准情景和经济发展情景下,河北省碳排放趋势是持续上升的,未出现达峰点;产业转型、绿色发展和目标导向情景下出现了峰值点,其中目标导向情景在2029年达峰,绿色发展情景在2030年达峰,碳达峰量分别为81 626.658万吨二氧化碳和86 018.255万吨二氧化碳,产业转型情景在2035年达峰,碳达峰量为85 214.349万吨二氧化碳。按照目前情景发展下河北省难以在2030年实现碳达峰,为保质保量完成达峰目标,需要以能源绿色低碳发展为关键手段,同时以科技和制度创新为动力,调整优化产业结构和能源结构。
