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| Carbon emissions from agricultural and animal husbandry in Shanxi Province：temporal and regional aspects, and trend forecast |
| Received:November 22, 2022 Revised:March 09, 2023 |
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| KeyWord:agricultural carbon emission;temporal and spatial variation;STIRPAT model |
| Author Name | Affiliation | E-mail | | WANG Shufen | College of Environment and Resource, Shanxi University, Taiyuan 030006, China | | | GAO Guanlong | College of Environment and Resource, Shanxi University, Taiyuan 030006, China
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Shanxi Laboratory for Yellow River, Taiyuan 030006, China
Academy of Water Resources Conservation Forests in the Qilian Mountains of Gansu Province, Zhangye 734000, China | gaoguanlong@sxu.edu.cn | | LI Wei | College of Environment and Resource, Shanxi University, Taiyuan 030006, China | | | LIU Simin | China National Forestry-Grassland Economics and Development Research Center, Beijing 100714, China | |
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| Abstract: |
| In Shanxi Province, to investigate the temporal and spatial characteristics of agricultural carbon emissions and their future trends, agricultural carbon emissions were estimated using the emission factor method based on 10 carbon sources of planting and animal husbandry during 2000-2020, and agricultural carbon emissions during 2021-2030 were predicted using the STIRPAT model. From 2000 to 2020, agricultural carbon emissions in Shanxi Province tended to rise slowly, followed by a fluctuating decline. Agriculture and animal husbandry carbon emission intensity exhibited a fluctuating trend of decline, with an average annual decline of 4.1%. The planting and animal husbandry contribution rates were 42.2% and 57.8%, respectively. Fertilizer usage is the largest source of planting carbon emissions, accounting for 26.9% annually. Cattle and sheep are the two main sources of carbon emissions from animal husbandry, accounting for 28.4% and 21.9% of total emissions, respectively. The high-value areas of total agricultural carbon emissions were mainly distributed in the north and south. In contrast, the low-value areas were distributed in the central part. Therefore, the distribution characteristics of agricultural carbon emission intensity were high in the north and low in the south. Because the STIRPAT model is accurate in estimating agricultural carbon emissions during 2010-2020, the agricultural carbon emissions during 2021-2030 are predicted. In the baseline scenarios, low-carbon scenario 1 and scenario 2, the projected carbon emissions from agriculture and animal husbandry by 2030 are 2 772 000 tons, 2 685 000 tons, and 2 523 000 tons, respectively. The study demonstrates that agricultural carbon in Shanxi Province has reached its peak. With the further strengthening of low-carbon measures, agricultural carbon emissions will continue to decrease, which will help accelerate the realization of carbon neutrality. |
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