我国极端天气气候事件直接和间接经济损失的评估及归因

doi:10.12006/j.issn.1673-1719.2024.305

摘要/Abstract

摘要：

气候变化增加了极端天气气候事件发生的范围、频率和强度，带来巨大的经济损失。尽管现有归因研究量化了人类活动导致的气候变化对极端事件发生概率的贡献，但气候变化对极端事件经济损失的贡献尚不明确，难以有效支撑适应政策的制定。文中基于极端事件归因研究的最新进展及多区域投入产出模型，全面核算了我国各省极端事件的直接和间接经济损失，对损失进行归因分析，并识别了重点适应部门和地区。研究发现，在中国极端事件造成的直接经济损失中，约有27%（约798亿元）可归因于人类活动导致的气候变化。这部分归因损失经由经济系统传导和放大，进一步造成了约911亿元的间接经济损失。其中，制造业和农业是最主要的承灾部门，未受直接影响的金融房地产、批发零售以及商务服务业也受到较大损失。

关键词: 极端天气气候事件, 损失与损害, 损失归因, 气候变化适应, 多区域投入产出模型

Abstract:

Climate change has amplified the range, frequency, and intensity of extreme weather events, leading to substantial economic losses. While existing attribution studies have quantified the role of anthropogenic climate change in increasing the probability of such events, its contribution to the resulting economic losses remains poorly understood. This knowledge gap hinders the development of effective adaptation policies. Based on the latest advances in extreme event attribution research, a multi-regional input-output model was employed to evaluate both direct and indirect economic losses from extreme events across China’s provinces. The portion of these losses attributable to climate change was quantified and key adaptation priorities were identified by sector and region. Findings indicate that extreme events attributed to anthropogenic climate change result in average annual direct and indirect losses of approximately CNY 80 billion and CNY 91 billion yuan, respectively, accounting for around 27% of disaster-related losses. The manufacturing and agriculture sectors are identified as the most affected, while industries such as finance, real estate, wholesale and retail, and business services, though not directly impacted, also incur significant losses.

Key words: Extreme weather and climate events, Loss and damage, Impact attribution, Climate change adaptation, Multi-regional input-output model

王博文, 贺一, 滕飞. 我国极端天气气候事件直接和间接经济损失的评估及归因[J]. 气候变化研究进展, 2025, 21(4): 502-518.

WANG Bo-Wen, HE Yi, TENG Fei. Attribution and assessment of direct and indirect economic losses from extreme weather events in China[J]. Climate Change Research, 2025, 21(4): 502-518.

图/表 10

表1 更新后的中国归因研究文献清单摘要

Table 1 Summary of the updated attribution study list in China

图1 基于风险的极端事件归因方法示意

Fig. 1 Illustration of a risk-based approach to attributing extreme events

表2 各灾种的直接受灾行业及资料来源

Table 2 Directly affected sectors of different disaster types and references

图2 直接经济损失部门分解及利用投入产出模型测算间接经济损失的方法

Fig. 2 Sectoral decomposition of direct economic losses and the use of input-output modelling to estimate indirect economic losses

图3 各省极端事件的年均直接经济损失(a)和全国不同类型极端事件直接经济损失占比(b)

Fig. 3 Annual average direct economic losses of extreme events by province (a) and proportion of direct economic losses from different types of extreme events across the country (b)

图4 各类极端事件年均损失的可归因情况(a)和乘数效应(b) 注：“乘数效应”为极端事件的可归因总损失与可归因直接损失之比，用来反映投入产出关系导致的损失放大效应。

Fig. 4 Attributable losses (a) and multiplier effect of attributable losses (b) of extreme events

图5 可归因直接损失(a)和总损失(b)的部门分布

Fig. 5 Sector distribution of attributable direct losses (a) and attributable total losses (b)

图6 各省可归因直接和间接损失

Fig. 6 Attributable direct and indirect losses of provinces

图7 地区人均生产总值与可归因直接损失(a)和总损失(b)占GDP比重间的关系

Fig. 7 Relationship between regional GDP per capita and attributable losses as a share of GDP

图8 重点适应省份/灾种/部门排序

Fig. 8 Key province/disaster/sector with high avoidable losses

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