Accounting for and Comparison of Greenhouse Gas (GHG) Emissions between Crop and Livestock Sectors in China
Article
Han, Jinyu, Qu, Jiansheng, Wang, Dai and Maraseni, Tek Narayan. 2023. "Accounting for and Comparison of Greenhouse Gas (GHG) Emissions between Crop and Livestock Sectors in China." Land. 12 (9). https://doi.org/10.3390/land12091787
| Article Title | Accounting for and Comparison of Greenhouse Gas (GHG) Emissions between Crop and Livestock Sectors in China |
|---|---|
| ERA Journal ID | 201217 |
| Article Category | Article |
| Authors | Han, Jinyu, Qu, Jiansheng, Wang, Dai and Maraseni, Tek Narayan |
| Journal Title | Land |
| Journal Citation | 12 (9) |
| Article Number | 1787 |
| Number of Pages | 18 |
| Year | 2023 |
| Publisher | MDPI AG |
| Place of Publication | Switzerland |
| ISSN | 2073-445X |
| Digital Object Identifier (DOI) | https://doi.org/10.3390/land12091787 |
| Web Address (URL) | https://www.mdpi.com/2073-445X/12/9/1787 |
| Abstract | The synergistic greenhouse gas (GHG) emission reduction of the crop production (CP) and livestock farming (LF) sectors is of great significance for food security and low-carbon development, especially for China, the world leader in agricultural production. In this paper, the GHG emissions from the CP and LF sectors are accounted for and compared, and the spatial econometric model is adopted for comparative study based on the panel data from 1997 to 2021. The results show that: (1) The total amount and intensity of GHG emissions from both sectors showed obvious spatial heterogeneity and spatial dependence, and the spatial distribution pattern was relatively stable. (2) The influence of each factor on the GHG intensity and spatial characteristics of CP and LF varies widely. For the CP sector, economic development (local effect ?0.29, adjacent effect +1.13), increased urbanization rate (?0.24, +0.16), agricultural structure (?0.29, +0.05), and urban-rural disparity (?0.03, +0.17) all reduce the GHG intensity of local region, while increasing the GHG intensity of its adjacent areas, signifying leakage. The economic structure (+0.06, +0.16), agricultural finance support (+0.02, +0.26), mechanization level (+0.05, +0.03), and land occupancy rate (+0.54, +0.44) all play a role in increasing the GHG intensity of CP in the local region and its adjacent areas. The disaster degree (?0.03, ?0.03) also reduced the GHG intensity of CP. For the LF sector, economic structure (+0.08, +0.11), urban-rural disparity (+0.11, +0.21), agricultural development level (+0.03, +0.50), and increased land occupancy rate (+0.05, +0.01) can improve the GHG intensity of the one region and adjacent areas. Economic development (+0.03, ?0.15), urbanization rate (+0.04, ?0.30), agricultural structure (+0.09, ?0.03), and disaster degree (+0.02, ?0.06) can increase the GHG intensity of the local region while reducing the GHG intensity of adjacent areas. Based on the results, under the background of carbon peaking and carbon neutralization(dual-carbon) goals, this study first puts forward collaborative emission reduction measures for CP and LF, respectively, then further rises to sector synergy and regional synergy, and constructs the countermeasure system framework of collaborative emission reduction from three levels, to provide guidance and reference for the realization of dual goals of agricultural GHG reduction and food security. |
| Keywords | crop production GHG emission; livestock farming GHG emission; spatial dependence; influencing factors; spatial Durbin model; synergetic measures |
| Contains Sensitive Content | Does not contain sensitive content |
| ANZSRC Field of Research 2020 | 300202. Agricultural land management |
| 300499. Crop and pasture production not elsewhere classified | |
| 410406. Natural resource management | |
| Byline Affiliations | Chinese Academy of Sciences, China |
| Lanzhou University, China | |
| Centre for Sustainable Agricultural Systems (Operations) |
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