中国七大地区“气候变化—作物产量—经济影响”综合评价

doi:10.12006/j.issn.1673-1719.2020.222

气候变化研究进展 ›› 2021, Vol. 17 ›› Issue (4): 455-465.doi: 10.12006/j.issn.1673-1719.2020.222

中国七大地区“气候变化—作物产量—经济影响”综合评价

刘远¹^,², 王芳¹^,², 张正涛¹^,²(), 黄承芳¹^,², 陈曦¹^,², 李宁¹^,²

1 北京师范大学地理科学学部环境演变与自然灾害教育部重点实验室,北京 100875
2 北京师范大学应急管理部-教育部减灾与应急管理研究院,北京 100875

收稿日期:2020-09-22 修回日期:2020-10-23 出版日期:2021-07-30 发布日期:2021-08-11
通讯作者: 张正涛
作者简介:刘远,男,博士研究生
基金资助:
国家自然科学基金青年项目(41907395);中国博士后科学基金资助项目(2021M690425);中国博士后科学基金资助项目(2020T130647);中国博士后科学基金资助项目(2019M650828);国家重点研发计划重点专项课题(2016YFA0602403);国家自然科学基金(41775103)

Comprehensive assessment of “climate change-crop yield-economic impact” in seven sub-regions of China

LIU Yuan¹^,², WANG Fang¹^,², ZHANG Zheng-Tao¹^,²(), HUANG Cheng-Fang¹^,², CHEN Xi¹^,², LI Ning¹^,²

1 Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China
2 Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management and Ministry of Education & Beijing Normal University, Beijing 100875, China

Received:2020-09-22 Revised:2020-10-23 Online:2021-07-30 Published:2021-08-11
Contact: ZHANG Zheng-Tao

摘要/Abstract

摘要：

农业作为响应气候变化最敏感的领域之一,未来作物产量可能受到深刻影响。量化气候变化冲击作物产量导致的最终经济影响,需要综合“气候变化—作物产量—经济影响”开展链式研究。文中采用系统回顾和Meta回归分析方法整合了55篇文献的667项研究结果,推导出我国七大地区主要作物（水稻、玉米、小麦）产量与地区内未来温度和降水变化的定量关系,并将其作为农业部门的损失量代入改进的多区域投入产出模型,量化七大地区内与地区间遭受的经济波及影响（ERE)。结果显示：(1)气候变化对我国作物产量的影响主要体现在温度升高上,每升温1℃减产2.6%~12.7%,东北和西北地区作物受升温影响最显著;(2) 气候变化导致的作物减产将对经济产生更严重的波及影响,GDP因作物减产每下降1%将额外产生17.8%的波及影响;(3) 21世纪末,若不考虑CO₂肥效作用,作物减产导致的ERE将占GDP的-0.1%~13.6%（负值表示收益),最悲观情况下ERE与当前我国农业总产值相当（2012年为基准年);(4)不同地区受ERE影响程度的差异较大,因各区之间产业结构、贸易联系及经济发展程度存在差异,西南地区遭受本区及来自其他地区的ERE比华东地区高2.8~8.5倍。

关键词: 气候变化, 经济波及影响（ERE）, 作物产量, 系统回顾, Meta回归分析, 投入产出分析

Abstract:

Agriculture is one of the most sensitive areas in response to climate change, and future crop yields may be profoundly affected. To quantitatively assess the final economic impact of climate change on crop yields, it is necessary to conduct a chain study on the comprehensive “climate change-crop yield-economic impact”. In this study systematic assessment and Meta regression methods were used to integrate 667 research results from 55 literatures, deriving the quantitative relationship between the main crop yields (rice, corn, wheat) in the seven sub-regions of China and future temperature and precipitation changes in the local area. Subsequently, the crop yields data were input to the improved multi-regional input-output model as the loss of the agricultural sector to evaluate the economic ripple effects (ERE) in and between the seven sub-regions. Results are as follows. (1) The impact of climate change on crop yields was mainly reflected in temperature increases, with an average yield loss of 2.6%-12.7% per℃, and with crop yields being more vulnerable in Northeast China and Northwest China than in other sub-regions. (2) Crop failure caused by climate change is estimated to have a more serious impact on China’s economy, each 1% drop in GDP due to crop failure will have an additional 17.8% ripple effects. (3) At the end of the 21st century, the ERE is -0.1% - 13.6% of GDP (negative values indicate economic gains) without considering CO₂ fertilization effect, of which the ERE in the most pessimistic pathway is equivalent to the total agricultural output in China in 2012. (4) Sub-regional-level results show an uneven distribution of economic impact in China, which is related to the regional economic development. Southwest China experiences 2.8-8.5 times more ERE than East China.

Key words: Climate change, Economic ripple effects (ERE), Crop yield, Systematic assessment, Meta regression analysis, Input-output analysis

刘远, 王芳, 张正涛, 黄承芳, 陈曦, 李宁. 中国七大地区“气候变化—作物产量—经济影响”综合评价[J]. 气候变化研究进展, 2021, 17(4): 455-465.

LIU Yuan, WANG Fang, ZHANG Zheng-Tao, HUANG Cheng-Fang, CHEN Xi, LI Ning. Comprehensive assessment of “climate change-crop yield-economic impact” in seven sub-regions of China[J]. Climate Change Research, 2021, 17(4): 455-465.

图/表 6

表1 本文选取的19个GCMs的基本概况

Table 1 A basic overview of 19 GCMs in this paper

图1 我国七大地区温度变化和降水变化率与作物产量变化率的关系注：直线表示回归方程,虚线表示通过95%信度检验区间。

Fig. 1 The relationship between temperature change and precipitation change rate and crop yield change rate in seven sub-regions of China (The curves represent 95% confidence levels)

图2 RCP8.5情景下我国不同地区农作物单产的变化趋势注：阴影部分表示通过95%的信度区间。

Fig. 2 The trend of crop yield change in different sub-regions of China under RCP8.5 (The curves represent 95% confidence levels)

图3 2020—2099年气候变化冲击我国作物生产造成的ERE预估值注：阴影部分表示通过95%的信度区间。

Fig. 3 The estimation of economic ripple effects (ERE) caused by the impact of climate change on crop production in China from 2020 to 2099 (The shaded areas represent the 95% confidence levels)

表2 ERE作为DED函数的条件分布

Table 2 The distribution of ERE as a direct economic damage (DED) function

图4 2020—2099年气候变化冲击我国不同地区作物生产造成的ERE预估值

Fig. 4 The estimation of ERE caused by the impact of climate change on grain production in different sub-regions of China from 2020 to 2099

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中国七大地区“气候变化—作物产量—经济影响”综合评价

Comprehensive assessment of “climate change-crop yield-economic impact” in seven sub-regions of China

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