基于行业减排的森林碳汇需求空间测度与分类

  目的   对全国28个省级行政区域和深圳市的森林碳汇需求空间进行分类，就提升各类地区未来的森林碳汇需求空间提出针对性建议，为科学设计碳汇政策以及差异化开发森林碳汇需求空间提供客观依据。   方法   以全国28个省级行政区域和深圳市为样本地区，收集整理2008?2017年《统计年鉴》中工业行业的投入产出数据，运用方向性距离函数模型测算各地区工业行业碳边际减排成本，并采用需求空间模型，对全国28个省级行政区域和深圳市10 a的森林碳汇需求空间进行测度，对求得的需求空间数据进行聚类分析和判别分析。   结果   各样本地区的碳边际减排成本和森林碳汇需求空间数据均存在一定的地区性波动。3类地区碳边际减排成本与森林碳汇需求空间的皮尔逊相关系数为0.999，呈显著正相关。聚类结果发现:1、2、3类地区的碳边际减排成本平均值分别为1.59、1.18、0.51万元·t?1；1、2、3类地区森林碳汇需求空间平均值分别为571.91、374.93、174.15万t·a?1。最终判别方程发现:2011、2014年的需求空间数据对地区分类的影响最为显著。   结论   整体来看，分类结果与中国东中西部地区的经济发展水平大致吻合。政策情景模拟显示:差异化开发森林碳汇需求空间要将超排处罚率作为第1、2类地区的重要切入点，同时优化配额发放模式；第3类地区以鼓励引导为主。表6参16

Spatial measurement and classification of forest carbon sink demand based on industry emission reduction

[Objective]This paper classifies the forest carbon sink demand space of 28 provincial administrative regions and Shenzhen City in China,and puts forward some suggestions for improving the future forest carbon sink demand space of various regions,so as to provide an objective basis for scientific design of carbon sink policy and targeted development of forest carbon sink demand space.[Method]Taking the above29 areas as sample units,the input and output data of the industrial industries in 2008-2017 statistical yearbook were collected.The directional distance function model was used to calculate the carbon marginal emission reduction cost of the industrial industries in each region,and the demand space model was used to measure the forest carbon sink demand space of 29 areas in the past 10 years.Then cluster analysis and discriminant analysis were carried out on the obtained demand space data.[Result]There were some regional fluctuations in the marginal carbon emission reduction cost and the spatial data of forest carbon sink demand in each sample area.The Pearson correlation coefficient between marginal carbon emission reduction cost and forest carbon sink demand space was 0.999,showing a significant positive correlation.The clustering results showed that the average marginal carbon emission reduction cost in regions of Category 1,2 and 3 was 15.9,11.8 and 5.1 thousand yuan·t^-1respectively.The average spatial value of forest carbon sink demand in Category 1,2 and 3 was 5719.1,3749.3 and 1741.5 thousand t·a^-1,respectively.Through the final discriminant equation,it was found that the demand spatial data of 2011 and 2014 had the most significant impact on regional classification.[Conclusion]On the whole,the classification results are roughly consistent with the economic development level of the eastern,central and western regions of China.The policy scenario simulation shows that the penalty rate of over emission should be taken as an important entry point for the regions of Category 1 and 2,and the quota distribution mode should be optimized.The 3 rd category should be encouraged and guided.