School of Resources and Environment, Northeast Agricultural University, Harbin, Heilongjiang, China.
Joint Laboratory of Agriculture coping with Climate Change of China Meteorological Administration (CMA) and China Agricultural University (CAU), Beijing, China.
PeerJ. 2024 Aug 12;12:e17856. doi: 10.7717/peerj.17856. eCollection 2024.
As a key agricultural region in China, Heilongjiang Province has experienced significant carbon emissions over the past few decades. To understand the underlying factors and future trends in these emissions, a comprehensive analysis was conducted from 1993 to 2030.
The agricultural carbon emissions from 1993 to 2020 were estimated using the emission factor method. To analyze the influencing factors and future trends of these emissions, the study employed the Logarithmic Mean Divisia Index (LMDI) and integrated it with the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model.
Results showed that (1) the agricultural carbon emissions in Heilongjiang were primarily driven by rice cultivation, followed by fertilizer production and irrigation electricity. (2) The economic and labor structure effects were the main driving factors of agricultural carbon emissions, while the population, demographic, and intensity effects were the main inhibitors. (3) Agricultural carbon emissions in Heilongjiang Province peaked in 2016 with 69.6 Mt CO-eq and could subsequently decline by -3.92% to -4.52% between 2020 and 2030 in different scenario simulations. In the future, Heilongjiang Province should prioritize the reduction of agricultural carbon emissions from rice production. Adjusting the planting structure, managing the layout of rice paddies, and promoting the cultivation of dry rice varieties would significantly contribute to mitigating agricultural carbon emissions.
黑龙江省作为中国的主要农业区之一,在过去几十年中经历了显著的碳排放。为了了解这些排放的潜在因素和未来趋势,我们对 1993 年至 2030 年期间的农业碳排放进行了全面分析。
使用排放因子法估算了 1993 年至 2020 年的农业碳排放。为了分析这些排放的影响因素和未来趋势,我们采用了对数平均迪氏分解指数(LMDI)并将其与人口、富裕程度和技术的随机影响回归(STIRPAT)模型相结合。
结果表明:(1)黑龙江省的农业碳排放主要受水稻种植驱动,其次是化肥生产和灌溉用电。(2)经济和劳动力结构效应是农业碳排放的主要驱动因素,而人口、人口结构和强度效应是主要的抑制因素。(3)黑龙江省的农业碳排放于 2016 年达到峰值,为 6960 万吨二氧化碳当量,在不同情景模拟下,2020 年至 2030 年期间可能会下降-3.92%至-4.52%。未来,黑龙江省应优先考虑减少水稻生产的农业碳排放。调整种植结构、管理稻田布局和推广旱地水稻品种将对减少农业碳排放产生重大影响。