极端洪灾情景下上海汽车制造业经济损失与波及效应评估

doi:10.11821/dlyj201709015

摘要/Abstract

摘要：

随着全球气候变暖和全球极端气象、水文事件日益多发,沿海低地地区的产业系统面临着极端洪水等灾害的严重威胁。开展极端洪灾情景下沿海特大城市的产业经济损失评估,分析产业网络的波及效应,识别出产业空间损失最为严重的地带,可为沿海城市的气候变化适应和灾害风险管理提供新的思路与方法。以上海黄浦江极端洪灾模拟结果为灾害情景,基于2013年上海汽车制造业第三次经济普查微观数据,评估了上海汽车制造业受灾后的直接经济损失、停产损失,并结合投入—产出模型评估了上海汽车制造企业停产引发波及效应造成的产业关联损失。分析结果表明,在极端洪灾情景下：① 上海市共有451家汽车制造企业受到灾害影响,占上海汽车制造企业总数的23.1%。② 上海汽车制造业厂房建筑、生产设备、整车存货直接经济损失分别为3.1亿元、196.1亿元、9.7亿元。汽车整车制造企业、零部件及配件制造企业的停产损失分别为209.1亿元、69亿元,对相关产业分别造成了1037.6亿元、144.7亿元产业关联损失。受到相关产业停产、减产影响后,汽车整车制造、零部件及配件产业关联损失分别为120.9亿元、247.1亿元。产业关联损失明显大于停产损失和直接经济损失。③ 浦东新区生产设备直接经济损失和停产损失较为严重,分别为93.4亿元、221.7亿元,分别占全市的47.6%、79.7%。上海通用整车厂所在的浦东新区金桥镇停产损失为184.1亿元。④ 由于2.5~3.0 m洪水水深区间分布有两家大型整车厂,因此停产损失最为严重,高达255.2亿元。上海市各级政府需要进一步加强黄浦江、苏州河流域的防汛工程以及工业园区的防洪设施建设;相关企业需要制定周密的业务连续性规划,降低企业停产后波及效应衍生的系统性风险。

关键词: 极端洪灾情景, 汽车制造业, 波及效应, 直接经济损失, 停产损失, 产业关联损失, 上海

Abstract:

Coastal lowland areas such as Shanghai are increasingly facing the threats from flood and other environmental hazards. Therefore, identifying areas and sectors that are susceptible to flood risk is of great importance for hazards and disaster management for low-lying cities. In this study, we assess the impact of floods on automobile firms and related industries in Shanghai under extreme flood scenarios of the Huangpu River. Information about the automobile industry in Shanghai is obtained from Shanghai's 'Third Economic Census Database'. Our analytical framework is implemented in a GIS environment with the support of input-output models. Our approach can estimate the direct economic losses, economic losses due to disrupted production, as well as the cascading and ripple effects on related industries. More specifically, our analysis suggests that under extreme flood scenarios, (1) 451 or 23.1% of the automobile firms will be susceptible to flood risk. (2) Direct economic losses due to damaged building, equipments, and stocks are estimated to be around 0.31, 20.05, and 0.97 billion yuan, respectively. Disrupted production will also cost 20.91 and 6.9 billion yuan in the manufacturing and supplier firms, respectively. Ripple effects on related industries will significantly exceed economic losses caused by damaged buildings and equipments as well as disrupted production. (3) The Pudong New Area will be hit particularly hard under extreme flood scenarios, accounting for 46% of the equipment damages and close to 80% of the economic losses due to disrupted production. (4) Because there are two large whole-vehicle manufacturers, if the inundated depth is between 2.5 and 3 meters, there will be an economic loss of 25.52 billion yuan. Our study concludes with policy recommendations. For example, the Shanghai municipal government should strengthen the flood control capacity along the Huangpu River and Suzhou River. Relevant firms also need to carefully develop 'Business Continuity Planning' in order to be resilient under floods and other natural disasters. In particular, these firms need to pay special attention to the ripple effects and systemic risks caused by disrupted production.

Key words: extreme flood scenarios, automobile industry, ripple effect, direct economic losses, disrupted production losses, industry-related losses, Shanghai

黄小莉, 李仙德, 温家洪, 李卫江, 杜士强. 极端洪灾情景下上海汽车制造业经济损失与波及效应评估[J]. 地理研究, 2017, 36(9): 1801-1816.

Xiaoli HUANG, Xiande LI, Jiahong WEN, Weijiang LI, Shiqiang DU. Measuring the economic losses and ripple effects of Shanghai automobile firms under extreme flood scenarios[J]. GEOGRAPHICAL RESEARCH, 2017, 36(9): 1801-1816.

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行业	汽车整车	汽车零部件及配件	铁路运输和城市轨道交通设备	…	最终产品	总产出
汽车整车	1781147	0	0	…	31291604	24640742
汽车零部件及配件	8659071	5524539	105	…	10781079	20875657
铁路运输和城市轨道交通设备	0	177	21096	…	3689314	394961
……	…	…	…	…	…	…
总投入	24640742	20875657	394961	…	31291604	24640742

洪水水深(m)	企业数量(家)	企业数量比例(%)	从业人员(人)	从业人员比例(%)	营业收入(亿元)	营业收入比例(%)
0<h≤0.5	122	27.1	2073	3.1	0.7	0.0
0.5<h≤1	138	30.6	2721	4.0	7.0	0.3
1<h≤1.5	67	14.8	3990	5.8	13.7	0.6
1.5<h≤2	50	11.1	6840	10.1	30.9	1.4
2<h≤2.5	50	11.1	16927	24.9	129.6	5.9
2.5<h≤3	24	5.3	35402	52.1	2025	91.8
合计	451	100.0	67953	100.0	2206.9	100.0

行业	汽车整车产业停产后向关联损失（A）	A损失所占比例(%)	汽车零部件及配件产业停产后向关联损失（B）	B损失所占据比例(%)	合计损失（A+B）
汽车整车	287.6	27.7	0.2	0.1	287.8
汽车零部件及配件	138.7	13.4	48.7	33.6	187.4
钢压延产品	54.3	5.2	6.0	4.2	60.4
有色金属及其合金和铸件	38.3	3.7	11.6	8.0	49.9
废弃资源和废旧材料回收加工品	39.6	3.8	7.7	5.3	47.3
批发和零售	42.2	4.1	4.2	2.9	46.4
商务服务	32.6	3.1	3.7	2.5	36.3
电力、热力生产和供应	24.5	2.4	4.6	3.1	29.1
有色金属压延加工品	21.6	2.1	6.4	4.4	28.0
金属制品、机械和设备修理服务	22.6	2.2	4.0	2.8	26.6
精炼石油和核燃料加工品	21.0	2.0	3.3	2.3	24.3
石油和天然气开采产品	20.7	2.0	3.3	2.3	24.0
货币金融和其他金融服务	19.9	1.9	2.6	1.8	22.5
电子元器件	17.0	1.6	4.3	3.0	21.3
其他通用设备	18.2	1.8	1.2	0.8	19.4
黑色金属矿采选产品	12.9	1.2	1.7	1.2	14.6
塑料制品	13.0	1.2	1.4	1.0	14.3
煤炭采选产品	11.4	1.1	1.7	1.2	13.1
基础化学原料	10.1	1.0	1.5	1.1	11.7
道路运输	9.5	0.9	1.3	0.9	10.8
合成材料	8.0	0.8	1.5	1.0	9.5
家具	8.1	0.8	0.4	0.3	8.6
钢、铁及其铸件	6.7	0.6	1.8	1.3	8.6
其他服务	7.8	0.8	0.5	0.3	8.3
有色金属矿采选产品	6.4	0.6	1.7	1.2	8.1
橡胶制品	7.3	0.7	0.6	0.4	8.0
金属制品	6.4	0.6	1.3	0.9	7.6
房地产	6.7	0.6	0.8	0.6	7.6
水上运输	5.7	0.5	0.8	0.6	6.5
铁合金产品	5.5	0.5	0.7	0.5	6.2
合计	924.5	89.1	129.4	89.4	1053.9