考虑“水—土—能—碳”关联的我国工农业碳排放效率及减排潜力研究

考虑“水—土—能—碳”关联，本文将水土资源要素纳入投入变量，构建了我国工农业碳排放效率投入产出测度指标，运用考虑非期望产出的SBM-undesirable模型计算我国29个省份2004—2017年农业、工业部门碳排放效率，利用乘法逆转法计算碳减排潜力并对影响碳排放的投入产出因素进行分析。结果表明：研究期内我国整体农业、工业碳排放效率均呈波动下降趋势，各年的农业碳排放效率均高于工业碳排放效率，江苏、山东等7省份农业碳排放效率以及北京、天津工业碳排放效率最优；各省份农业、工业减排潜力和规模具有显著差异，山西、甘肃的农业、工业碳减排均具有较大潜力；我国绝大多数省份均存在农业、工业的资源能源投入冗余和非期望产出冗余，土地资源投入过剩是影响农业碳排放效率的最重要因素，水资源投入过剩是影响工业碳排放效率的最重要因素。碳排放效率较低省份应积极开展技术创新，发展低碳技术，提高水土资源和能源利用效率，减少碳排放。

China's Industrial and Agricultural Carbon Emission Efficiency and Reduction Potential Considering the Water-Land-Energy-Carbon Nexus

Considering the interactions of water, land, energy and carbon, the measurement indexes for China''s industrial and agricultural carbon emission efficiency were constructed by taking the factors of water and land resources into the input variables. Carbon emission efficiency of agricultural and industrial sectors in 29 provinces of China from 2004 to 2017 was calculated using the SBM-undesirable model that considering undesired output. Carbon reduction potential was calculated with the use of multiplicative reversal method, and the input-output factors were analyzed that affecting carbon emissions. The results showed that during the study period, China''s overall agricultural and industrial carbon emission efficiency showed a declining trend. The agricultural carbon emission efficiency was higher than the industrial carbon emission efficiency in each year. The agricultural carbon emission efficiency of seven provinces including Jiangsu and Shandong and the industrial carbon emission efficiency of Beijing and Tianjin were the best. There was a significant difference in the potential and scale of agricultural and industrial emission reduction among provinces, and Shanxi and Gansu had great potential of both agriculture and industrial carbon emission reduction. Majority of provinces in China had resource and energy input redundancy and unintended output redundancy in agriculture and industry. Excess land resource input was the most important factor affecting agricultural carbon emission efficiency, while excess water resource input was the most important factor affecting industrial carbon emission efficiency. Provinces with low carbon emission efficiency should actively carry out technological innovation, develop low-carbon technologies, and improve the efficiency of water and land resources and energy to reduce carbon emissions.