Risk Assessment Study Of fire Following An Earthquake: A .
Natural Hazardsand Earth SystemSciencesOpen AccessNat. Hazards Earth Syst. Sci., 14, 891–900, /doi:10.5194/nhess-14-891-2014 Author(s) 2014. CC Attribution 3.0 License.Risk assessment study of fire following an earthquake: a case studyof petrochemical enterprises in ChinaJ. Li1,2 , Y. Wang1,2 , H. Chen1,2 , and L. Lin1,21 KeyLaboratory of Environmental Change and Natural Disaster of MOE, Beijing Normal University, No.19,XinJieKouWai St., HaiDian District, 100875, Beijing, China2 Academy of Disaster Reduction and Emergency Management, Beijing Normal University, No.19, XinJieKouWai St.,HaiDian District, 100875, Beijing, ChinaCorrespondence to: Y. Wang (wy@bnu.edu.cn)Received: 13 January 2013 – Published in Nat. Hazards Earth Syst. Sci. Discuss.: 29 April 2013Revised: 6 November 2013 – Accepted: 11 November 2013 – Published: 16 April 2014Abstract. After an earthquake, the fire risk of petrochemical enterprises is higher than that of other enterprises as itinvolves production processes with inflammable and explosive characteristics. Using Chinese petrochemical enterprisesas the research object, this paper uses a literature reviewand case summaries to study, amongst others, the classification of petrochemical enterprises, the proportion of dailyfires, and fire loss ratio. This paper builds a fire followingan earthquake risk assessment model of petrochemical enterprises based on a previous earthquake fire hazard model,and the earthquake loss prediction assessment method, calculates the expected loss of the fire following an earthquake in various counties and draws a risk map. Moreover,this research identifies high-risk areas, concentrating on theBeijing–Tianjin–Tangshan region, and Shandong, Jiangsu,and Zhejiang provinces. Differences in enterprise type produce different levels and distribution of petrochemical enterprise earthquake fire risk. Furthermore, areas at high risk ofpost-earthquake fires and with low levels of seismic fortification require extra attention to ensure appropriate mechanismsare in place.1IntroductionPetrochemical enterprises produce products under complexprocess conditions and can be described as having the following characteristics: airtight environments, high temperatures,high pressure, deep cooling and pipelining in most cases,and involve raw materials and products that are inflammable,explosive, toxic, and corrosive. Further, such processes areprone to catch fire in daily production because of a numberof factors including operation errors and equipment failure.After a destructive earthquake strikes, fires are likelyto occur in petrochemical enterprises with the leakage ofinflammable and explosive substances, ignited by frictionsparks or open flames as a result of earthquake damageto workshops, equipment, containers, and other structures.For example, during the Tangshan earthquake in China in1976, a fire occurred in a synthetic fat factory in Tianjin,which totally destroyed the workshop after the sudden explosion of the synthetic tower resulting from a rise in temperature and pressure due to a power failure after workshopframes collapsed. A fire also broke out in a chemical plantin Hangu because of the spontaneous combustion of silicon dichloride following pipeline equipment damage withthe collapse of buildings. Furthermore, a fire started in a factory in Hangu when a violent shake threw glycerin into astrong oxidant potassium permanganate and caused a chemical reaction (Business Community, 2008). During Japan’s2011 earthquake, numerous fires started in refineries in citiessuch as Sendai and Chiba, leading to a significant interruption of factory production (Sohu News, 2011a, b). Therefore,post-earthquake fires (secondary fires) constitute the greatest threat and harm to petrochemical enterprises (Hui andJiang, 2002). In 1976, fires in petrochemical enterprises accounted for 24 % of the total post-earthquake fires in Tianjinas a result of the Tangshan earthquake in China (BusinessCommunity, 2008).Published by Copernicus Publications on behalf of the European Geosciences Union.
892J. Li et al.: Risk assessment study of fire following an earthquakeThe total output value of the Chinese petrochemical industry makes up more than 12 % of the gross industrial outputvalue (China Petroleum and Chemical Industry Association,2009). However, in terms of site selection, petrochemical enterprises’ main concern is given to raw materials, producttransport, and industrial basis, with little or no considerationfor earthquakes. For example, a great many petrochemicalenterprises, such as the Jianfeng enterprise, Youxin chemical plant, Hongda chemical plant, and Huafeng phosphoruschemical plant, are located along the Longmenshan Mountain fault belt where the Wenchuan earthquake occurred in2008. Furthermore, the layout of most petrochemical enterprises significantly increases post-earthquake fire hazards.From the perspective of the post-earthquake fire-causingmechanism of petrochemical enterprises, by summarizingthe regular pattern of general fire occurrence in differenttypes of enterprises, this paper can build a petrochemicalenterprise post-earthquake fire risk assessment model basedon the post-earthquake fire risk model put forward by ZhaoZhendong (Yu et al., 2003; Zhao et al., 2003) and earthquakeloss prediction assessment methods. A macroanalysis willfollow, with comments on the post-earthquake fire risk ofChinese petrochemical enterprises, and thus this paper canprovide a scientific basis for regional economic developmentand industrial planning.2Previous researchCurrently, the most common analysis model to determine therate of post-earthquake fires is the empirical statistics regression model. Its aim is to find the expression between the postearthquake fire rate and post-earthquake fire factors using aregression analysis method based on statistics regarding historical earthquake damage.Kobayashi (1984) performed a statistical regression analysis with historical earthquake secondary fire data and obtained expressions between the earthquake secondary fire incidence rate and house collapse rate. The expressions are regression models built in linear, logarithmic, and index formswith the number of post-earthquake fires per square meter of building as dependent variables and building collapserates as independent variables. Scawthorn put forward a regression model (Scawthorn, 1986, 1996; Scawthorn et al.,1981), looking for a relationship between post-earthquakefire rates and earthquake intensity on the basis of collectingand analyzing data on 20th century post-earthquake fires inthe United States. His results have been applied to the software package HAZUS developed by the Federal EmergencyManagement Agency (FEMA) to assess loss under the effect of multiple disasters, and to predict the number of postearthquake secondary fires in the United States.In studying the fire after the Northridge earthquake in California, Trifunac and Todorovska (1997, 1998) found thatfire ignition rate models correlated with site intensity, peakNat. Hazards Earth Syst. Sci., 14, 891–900, 2014horizontal ground velocity, the number of red-tagged buildings, and breaks in water pipes. Based on the Monte Carlosimulation and physics-based fire-spread/evacuation simulation, Nishino et al. (2012) considered a number of factors(number and location of fire outbreaks, firefighting at the initial stages, weather, earthquake-related structural damage tobuildings, initial evacuee locations, and the obstruction ofroads) to simulate the burn-down risk and fire-fatality riskafter an earthquake. Zhao (2010) built an integrated software system for the dynamic simulation of fires followingan earthquake based on GIS; fire ignition, fire spread, andfire suppression were also considered in this system.Tanaka (2012) studied the characteristics and problemsof fires following the Great East Japan Earthquake inMarch 2011, and he classified post-earthquake fires into threetypes: conventional types
Fire ignition rates should be doc-umented to determine the relative occurrence of gas, electri-cal, chemical and other types of fires (Trifunac and Todor-ovska, 1997). The DOW Fire and Explosion Index method and the ICI MOND method, which was developed from the DOW Fire & Explosion Index by personnel at the Imperial Chemical In-
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