中国省域种植业碳汇量、碳排放量的时空分异及公平性研究

Study on the Temporal and Spatial Differentiation and Equity of Carbon Sink and Carbon Emission of China’s Provincial Planting Industry

2020年9月,中国在联合国大会上向世界宣布力争在2030年前实现碳达峰、2060年前实现碳中和的目标,因此测算种植业碳排放量、碳汇量对政策的制定有重要意义。本文基于2013—2020年中国国家统计局的主要农作物、主要农用物资消耗量的年度数据测算中国31个省份种植业碳排放量、碳汇量,运用灰色预测法GM(1,1)预测中国31个省份未来5年的碳排放量,深入分析其时空分异特征,并采用基尼系数研究中国省域种植业碳汇量、碳排放量的公平性。研究结果表明:(1)山东碳排放总量最高,广西碳汇总量、净碳汇总量最高。(2)从时间序列看,中国种植业碳排放高峰已经过去,并且种植业未来碳排放量有明显下降趋势。不管是到达碳排放高峰的时间点、碳排放总量还是未来碳排放量下降趋势都出现明显的"马太效应",即东部地区优于中部地区,中部地区优于西部地区。另外,新疆、黑龙江和河南部分主要农用物资(农用塑料薄膜、农用化肥和灌溉)碳排放量存在逐年上升的趋势。(3)从空间分布看,河南、山东、安徽以及吉林属于高-高型地区,四川和新疆属于高-低型地区。东部沿海地区、南部沿海地区和东北地区种植业碳排放基尼系数明显高于其他地区,基尼系数大小与地理位置和经济发展水平呈正相关关系,高值基尼系数在地理分布上,明显呈现沿海性的特征。西北地区和西南地区的种植业碳汇量基尼系数显著高于其他地区,基尼系数的大小与其地理位置和经济发展水平有负相关关系。

In September 2020, China announced to the world at the United Nations General Assembly the goals of achieving carbon peak by 2030 and carbon neutralization by 2060.Therefore, it is of great significance to calculate the carbon emissions and carbon sinks of planting industry for policy-making.Based on the annual data of the consumption of main crops and agricultural materials of the National Bureau of Statistics from 2013 to 2020, this paper estimates the carbon sequestration and carbon emissions of the planting industry in 31 provinces, autonomous regions and municipalities in China, and forecasts the carbon emissions of 31 provinces, autonomous regions and municipalities in the next five years by using the motion grey prediction method GM(1,1).The Gini coefficient is used to study the equity of carbon sequestration and carbon emission of China’s provincial planting industry.The results show that:(1)The total carbon emission of Shandong is the highest, and the total carbon sink and net carbon sink of Guangxi are the highest.(2)In terms of time series, the peak of carbon emission of China’s planting industry has passed, and the carbon emission of planting industry has an obvious downward trend in the future.Whether it is the time point of reaching the peak of carbon emission, the total carbon emission or the downward trend of carbon emission in the future, there is an obvious“Matthew effect”, that is, the eastern region is better than the central region, and the central region is better than the western region.In addition, the carbon emissions of some main agricultural materials(agricultural plastic film, agricultural chemical fertilizer and irrigation) in Xinjiang, Heilongjiang and Henan are increasing year by year.(3)In terms of spatial distribution, Henan, Shandong, Anhui and Jilin belong to high high type provinces, while Sichuan and Xinjiang belong to high low type provinces.The Gini coefficient of planting carbon emission in eastern coastal areas, southern coastal areas and Northeast China is significantly higher than that in other areas.The Gini coefficient has a positive correlation with geographical location and economic development level.The geographical distribution of high-value Gini coefficient obviously shows the characteristics of coastal.The Gini coefficient of planting carbon sink in Northwest and Southwest China is significantly higher than that in other regions.The Gini coefficient has a negative correlation with its geographical location and economic development level.