極端洪災(zāi)情景下上海汽車制造業(yè)經(jīng)濟損失與波及效應(yīng)評估
發(fā)布時間:2018-04-21 17:51
本文選題:極端洪災(zāi)情景 + 汽車制造業(yè)。 參考:《地理研究》2017年09期
【摘要】:隨著全球氣候變暖和全球極端氣象、水文事件日益多發(fā),沿海低地地區(qū)的產(chǎn)業(yè)系統(tǒng)面臨著極端洪水等災(zāi)害的嚴(yán)重威脅。開展極端洪災(zāi)情景下沿海特大城市的產(chǎn)業(yè)經(jīng)濟損失評估,分析產(chǎn)業(yè)網(wǎng)絡(luò)的波及效應(yīng),識別出產(chǎn)業(yè)空間損失最為嚴(yán)重的地帶,可為沿海城市的氣候變化適應(yīng)和災(zāi)害風(fēng)險管理提供新的思路與方法。以上海黃浦江極端洪災(zāi)模擬結(jié)果為災(zāi)害情景,基于2013年上海汽車制造業(yè)第三次經(jīng)濟普查微觀數(shù)據(jù),評估了上海汽車制造業(yè)受災(zāi)后的直接經(jīng)濟損失、停產(chǎn)損失,并結(jié)合投入—產(chǎn)出模型評估了上海汽車制造企業(yè)停產(chǎn)引發(fā)波及效應(yīng)造成的產(chǎn)業(yè)關(guān)聯(lián)損失。分析結(jié)果表明,在極端洪災(zāi)情景下:(1)上海市共有451家汽車制造企業(yè)受到災(zāi)害影響,占上海汽車制造企業(yè)總數(shù)的23.1%。(2)上海汽車制造業(yè)廠房建筑、生產(chǎn)設(shè)備、整車存貨直接經(jīng)濟損失分別為3.1億元、196.1億元、9.7億元。汽車整車制造企業(yè)、零部件及配件制造企業(yè)的停產(chǎn)損失分別為209.1億元、69億元,對相關(guān)產(chǎn)業(yè)分別造成了1037.6億元、144.7億元產(chǎn)業(yè)關(guān)聯(lián)損失。受到相關(guān)產(chǎn)業(yè)停產(chǎn)、減產(chǎn)影響后,汽車整車制造、零部件及配件產(chǎn)業(yè)關(guān)聯(lián)損失分別為120.9億元、247.1億元。產(chǎn)業(yè)關(guān)聯(lián)損失明顯大于停產(chǎn)損失和直接經(jīng)濟損失。(3)浦東新區(qū)生產(chǎn)設(shè)備直接經(jīng)濟損失和停產(chǎn)損失較為嚴(yán)重,分別為93.4億元、221.7億元,分別占全市的47.6%、79.7%。上海通用整車廠所在的浦東新區(qū)金橋鎮(zhèn)停產(chǎn)損失為184.1億元。(4)由于2.5~3.0 m洪水水深區(qū)間分布有兩家大型整車廠,因此停產(chǎn)損失最為嚴(yán)重,高達(dá)255.2億元。上海市各級政府需要進(jìn)一步加強黃浦江、蘇州河流域的防汛工程以及工業(yè)園區(qū)的防洪設(shè)施建設(shè);相關(guān)企業(yè)需要制定周密的業(yè)務(wù)連續(xù)性規(guī)劃,降低企業(yè)停產(chǎn)后波及效應(yīng)衍生的系統(tǒng)性風(fēng)險。
[Abstract]:With the global climate warming and extreme weather, hydrological events are more and more frequent, and the industrial system of coastal low-lying areas is facing the serious threat of extreme floods and other disasters. To carry out an assessment of industrial economic losses in coastal mega-cities under extreme flood scenarios, analyze the spillover effects of industrial networks, and identify the areas where industrial space losses are the most serious. It can provide new ideas and methods for climate change adaptation and disaster risk management in coastal cities. Based on the results of the Shanghai Huangpu River extreme Flood disaster simulation, and based on the microcosmic data of the third Shanghai Automobile Manufacturing Economic Census in 2013, the direct economic losses and shutdown losses of the Shanghai auto manufacturing industry were evaluated. Combined with the input-output model, the industrial association losses caused by the spillover effect caused by the shutdown of Shanghai automobile manufacturing enterprises are evaluated. The results show that, under the extreme flood scenario, there are 451 auto manufacturing enterprises in Shanghai affected by the disaster, accounting for 23.1.1% of the total number of auto manufacturing enterprises in Shanghai. The direct economic loss of vehicle inventory was 310 million yuan, 19.61 billion yuan, 970 million yuan respectively. The shutdown losses of automobile manufacturing enterprises, parts and accessories manufacturers were 20.91 billion yuan and 6.9 billion yuan respectively, which caused 103.76 billion yuan and 14.47 billion yuan related losses to related industries, respectively. Affected by the shutdown of related industries, the related losses of automobile manufacturing, parts and accessories industry were 12.09 billion yuan and 24.71 billion yuan respectively. The direct economic loss and shutdown loss of production equipment in Pudong New area are more serious, which are 9.34 billion yuan and 22.17 billion yuan respectively, accounting for 47.6% and 79.7% of the whole city respectively. The shutdown loss of Jinqiao Town in Pudong New area is 18.41 billion yuan. Because there are two large vehicle plants in the range of 2.5 ~ 3.0m flood depth, the loss of shutdown is the most serious, as high as 25.52 billion yuan. Shanghai governments at all levels need to further strengthen flood control projects in the Huangpu River and Suzhou River basins and flood control facilities in industrial parks, and relevant enterprises need to formulate careful business continuity planning, Reduce the systemic risk derived from the ripple effect after the shutdown of the enterprise.
【作者單位】: 上海師范大學(xué)地理系;
【基金】:國家自然科學(xué)基金項目(41301168,71603168,41401603)
【分類號】:F426.471
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