Distributional dynamic and trend evolution of China’s agricultural carbon emissions – an analysis on panel data of 31 provinces from 2002 to 2011

Yuan, Tian; Zhang, Junbiao; Qiqi, Chen

doi:10.1080/10042857.2015.1057439

Cited by 22 publications

(14 citation statements)

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“…It has been widely used to simulate CH 4 emissions from paddy fields all over the world over the past 20 years. Numerous studies have shown that DNDC can be used to estimate CH 4 emissions from paddy fields at a regional scale [ 38 , 39 , 40 , 41 ]. The model also has a good simulation performance in the study area and near latitudes [ 22 , 40 , 42 ].…”

Section: Methodsmentioning

confidence: 99%

Characterizing Spatiotemporal Dynamics of CH4 Fluxes from Rice Paddies of Cold Region in Heilongjiang Province under Climate Change

Nie

Zhang

et al. 2019

IJERPH

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Paddy fields have become a major global anthropogenic CH4 emission source, and climate change affects CH4 emissions from paddy ecosystems by changing crop growth and the soil environment. It has been recognized that Heilongjiang Province has become an important source of CH4 emission due to its dramatically increased rice planting area, while less attention has been paid to characterize the effects of climate change on the spatiotemporal dynamics of CH4 fluxes. In this study, we used the calibrated and validated Long Ashton Research Station Weather Generator (LARS-WG) model and DeNitrification-DeComposition (DNDC) model to simulate historical and future CH4 fluxes under RCP 4.5 and RCP 8.5 of four global climate models (GCMs) in Heilongjiang Province. During 1960–2015, the average CH4 fluxes and climatic tendencies were 145.56 kg C/ha and 11.88 kg C/ha/(10a), respectively. Spatially, the CH4 fluxes showed a decreasing trend from west to east, and the climatic tendencies in the northern and western parts were higher. During 2021–2080, the annual average CH4 fluxes under RCP 4.5 and RCP 8.5 were predicted to be 213.46 kg C/ha and 252.19 kg C/ha, respectively, and their spatial distributions were similar to the historical distribution. The average climatic tendencies were 13.40 kg C/ha/(10a) and 29.86 kg C/ha/(10a), respectively, which decreased from west to east. The simulation scenario analysis showed that atmospheric CO2 concentration and temperature affected CH4 fluxes by changing soil organic carbon (SOC) content and plant biomass. This study indicated that a paddy ecosystem in a cold region is an important part of China’s greenhouse gas emission inventory in future scenarios.

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Section: Methodsmentioning

confidence: 99%

Characterizing Spatiotemporal Dynamics of CH4 Fluxes from Rice Paddies of Cold Region in Heilongjiang Province under Climate Change

Nie

Zhang

et al. 2019

IJERPH

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“…Wang et al [26] calculated the carbon emissions of China's transportation infrastructure industry and found that more than 80% of the carbon emissions of expressway projects came from the production of raw materials, while site construction and material transportation only accounted for 10% and 3% of the total carbon emissions respectively. Tian et al [27] found that the spatial distribution of agricultural carbon emissions in China is unbalanced, and this spatial disequilibrium feature shows an increasing trend. Yan et al [28] analyzed the variation characteristics of agricultural carbon emission intensity in China, and the results has shown that agricultural carbon emission intensity showed a trend of steady decline.…”

Section: The Carbon Emissions On the Energy Demand-sidementioning

confidence: 99%

Energy carbon emission structure and reduction potential focused on the supply-side and demand-side

Jijun

2020

PLoS ONE

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In recent years, the environmental problems caused by excessive carbon emissions from energy sources have become increasingly serious, which not only aggravates the climate change caused by the greenhouse effect but also seriously restricts the sustainable development of Chinese economy. An attempt is made in this paper to use energy consumption method and input-output method to study the carbon emission structure of China's energy system and industry in 2015 from two perspectives, namely China's energy supply side and energy demand side, by taking into account the two factors of energy invest in gross capital formation and export. The results show that neglecting these two factors will lead to underestimation of intermediate use carbon emissions and overestimation of final use carbon emissions. On energy supply side, the carbon emission structure of China's energy system is still dominated by high-carbon energy (raw coal, coke, diesel, and fuel oil, etc.), accounting for more than 70% of total energy carbon emissions; on the contrary, the natural gas such as clean energy accounts for only 3.45% of total energy carbon emissions, indicating that the energy consumption structure optimization and emission reduction gap of China's energy supply side are still substantial. On energy demand side, the final use (direct consumption by residents and government) produces less carbon emissions, while the intermediate use (production by enterprises) produces more than 90% of the total energy carbon emissions. Fossil energy, power sector, heavy industry, chemical industry, and transportation belong to industries with larger carbon emissions and lower carbon emission efficiency, while agriculture, construction, light industry, and service belong to industries with fewer carbon emissions and higher carbon emission efficiency. This means that the optimization of industrial structure is conducive to slowing down the growth of energy carbon emissions on the demand side.

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“…Agricultural carbon emissions can be affected by the method of land use. It has been proven that agricultural carbon emissions can be effectively reduced by afforestation and the Grain for Green Program [34]. Carbon emissions from construction land are the highest, compared with those from urban land, rural residential land, land for transportation, and agricultural land [35].…”

Section: Introductionmentioning

confidence: 99%

Research on Agricultural Carbon Emissions and Regional Carbon Emissions Reduction Strategies in China

2020

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Carbon emissions and strategies for reducing them have become hot topics in recent years. This study firstly measured the total amount and the intensity of agricultural carbon emissions (i.e., agricultural carbon emission per capital) in China. The results show that China’s total carbon emission in 2016 was 272.022 million tons, which is 26.67% more than that in 2000, with an average annual increase of 1.67%. It then compared the regional differences of agricultural carbon emissions in China using the method of coefficient of variation and the Theil index. Following this, this paper finally provides scientific and technological support for the reduction of agricultural carbon emissions in China based on a matrix of carbon emission reduction strategies.

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Distributional dynamic and trend evolution of China’s agricultural carbon emissions – an analysis on panel data of 31 provinces from 2002 to 2011

Cited by 22 publications

References 0 publications

Characterizing Spatiotemporal Dynamics of CH4 Fluxes from Rice Paddies of Cold Region in Heilongjiang Province under Climate Change

Characterizing Spatiotemporal Dynamics of CH4 Fluxes from Rice Paddies of Cold Region in Heilongjiang Province under Climate Change

Energy carbon emission structure and reduction potential focused on the supply-side and demand-side

Research on Agricultural Carbon Emissions and Regional Carbon Emissions Reduction Strategies in China

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