Evolution model and risk analysis of urban haze disaster chain are carried out on the basis of disaster system theory and the complex network theory in this paper. Through the information gathering and analysis of the causes and harm of urban haze disaster, the disaster chain mechanism of urban haze is analyzed, as well as the types and characteristics of disaster chain, according to the characteristics of disaster-causing factors, hazard-formative environment and hazard-affected bodies. By building the urban haze disaster chain evolution network model, qualitative risk analysis is made based on the out-in degrees and number of nodes in its subnets, the shortest path and average path, and the number of branched chains. Finally, the key steps are found and the solutions on disconnecting chains are presented. The results of risk analysis show that in the urban haze disaster chain evolution system, the haze event closely relates to the other crisis events. Through several times of transition, the harm effect might spread to the entire network, and the key links are the decline in atmospheric visibility, the decline in air quality or air pollution, traffic jams or paralysis, traffic accidents, resulting in urban atmospheric acid rain, urban greening, economic losses and endanger human health.
[1] Samet J M, Zeger S L, Dominici F, et al. The National morbidi-ty, mortality, and air pollution study, part Ⅱ:Morbidity and mortality from air pollution in the United States[J]. Research Report (Health Effect Institute), 2000, 94(2):65-70.
[2] Nehzat Mtalebi. Winter time PM2.5 and PM10, source apportion-ment at sacramento, caledonia[J]. Air & Waste Management, 1999, 12(9):25-29.
[3] Quinn P K, Bates T S. North American, Asian and Indian haze similar regional impacts on climate[J]. Geophysical Research Letters, 2003, 30(11):1555-1559.
[4] Pilla F, Broderick B. A GlS model for personal exposure to PM10 for Dublin commuters[J]. Sustainable Cities and Society, 2015(15):1-10.
[5] 史军, 崔林丽, 贺千山, 等. 华东雾和霾日数的变化特征及成因分析[J]. 地理学报, 2010, 65(5):533-542. Shi Jun, Cui Linli, He Qianshan, et al. The changes and causes of fog and haze days in eastern China[J]. Journal of Geography, 2010, 65(5):533-542.
[6] 潘本锋, 汪巍, 李亮, 等. 我国大中型城市秋冬季节雾霾天气污染特征与成因分析[J]. 环境与可持续发展, 2013, (1):33-36. Pan Benfeng, Wang Wei, Li Liang, et al. Analysis of the reason of formation key and the characteristic of pollution about fog or haze at key cities in autumn and winterin China[J]. Environment and Sustainable Development, 2013(1):33-36.
[7] 程婷, 魏晓弈, 翟伶俐, 等. 近50年南京雾霾的气候特征及影响因素分析[J]. 环境科学与技术, 2014, 37(6N):54-61. Cheng Ting, Wei Xiaoyi, Zhai Linli, et al. An analysis of climatic characteristics and influence factors of fog and haze in Nanjing in recent 50 years[J]. Environmental Science and Technology, 2014, 37(6N):54-61.
[8] 茹少峰, 雷振宇. 我国城市雾霾天气治理中的经济发展方式转变[J]. 西北大学学报(哲学社会科学版), 2014, 44(2):90-93. Ru Shaofeng, Lei Zhanyu. The governance of fog and haze in cities and the transformation of the mode of economic development[J]. Journal of Northwestern University(Philosophy and Social Sciences Edition), 2014, 44(2):90-93.
[9] 吴伟强, 王欣. 基于故障树模型的城市雾霾风险分析[J]. 广州大学学报(自然科学版), 2015, 14(5):76-82. Wu Weiqiang, Wang Xin. The risk analysis of urban fog-haze based on Fault Tree[J]. Journal of Guangzhou University(Natural Science Edition), 2015, 14(5):76-82.
[10] Yang T, Gbaguidi A, Yan P Z, et al. Model elucidating the sources and formation mechanisms of severe haze pollution over Northeast mega-city cluster in China[J]. Environmental Pollution, 2017, 230:692-700.
[11] 盛小星, 叶春明. 基于集对分析法的长三角雾霾风险评估[J]. 资源开发与市场, 2017, 33(3):334-337, 359. Sheng Xiaoxing, Ye Chunming. Haze risk assessment based on set pair analysis in Changjiang river delta[J]. Resource Development and Marketing, 2017, 33(3):334-337, 359.
[12] 韩琭. 雾霾灾害风险指数的构建与测度[J]. 统计与决策, 2017(2):28-32. Han Lu. Construction and measurement of haze-fog disaster risk index[J]. Statistics and Decision, 2017(2):28-32.
[13] 史培军. 四论灾害系统研究的理论与实践[J]. 自然灾害学报, 2005, 14(6):1-7. Shi Peijun. Theory and practice on disaster system research in a fourth tine[J]. Journal of Natural Disasters, 2005, 14(6):1-7.
[14] Yang T R, Liu X G, Qu Y, et al. Formation mechanism of con-tinuous extreme haze episodes in the mega city Beijing, Chi-na, in January 2013[J]. Atmospheric Research. 2015, 155:192-203
[15] 孟晓艳, 余予, 张志富, 等. 2013年1月京津冀地区强雾霾频发成因初探[J]. 环境科学与技术, 2014, 37(1):190-194. Meng Xiaoyan, Yu Yu, Zhang Zhifu, et al. Preliminary study of the dense fog and haze events' formation over BeijingTianjin-and-Hebei region in January of 2013[J]. Environmental Science and Technology, 2014, 37(1):190-194.
[16] 孙亮. 灰霾天气成因危害及控制治理[J]. 环境科学与管理, 2012, 37(10):71-75. Sun Liang. Hazard and Treatment of Haze Weather[J]. Environmental Science and Management, 2012, 37(10):71-75.
[17] 余瀚, 王静爱, 柴玫等. 灾害链灾情累积放大研究方法进展[J]. 地理科学进展, 2014, 33(11):1498-1511. Yu Han, Wang Jingai, Chai Mei, et al. Review on research methods of disaster loss accumulation and amplification of disaster chains[J]. Progress in Geography, 2014, 33(11):1498-1511.
[18] 陈建均. 地铁灾害链风险评估研究[D]. 北京:北京交通大学, 2017. Chen Jianjun. Research on risk assessment of the metro disaster chain[D]. Beijing:Beijing Jiaotong University, 2017.
[19] 郭增建, 秦保燕. 灾害物理学简论[J]. 灾害学, 1987(2):9-17. Guo Zengjian, Qin Baoyan. Brief discussion on disaster physics[J]. Journal of Catastrophology, 1987(2):9-17.
[20] 李智. 基于复杂网络的灾害事件演化与控制模型研究[D]. 长沙:中南大学, 2010. Li Zhi. Research on evolution and control model of disaster events based on complex network[D]. Changsha:Central South University, 2010.
[21] 刘爱华. 城市灾害链动力学演变模型与灾害链风险评估方法的研究[D]. 长沙:中南大学, 2013. Liu Aihua. Research on the dynamics evolution model of urban disaster chain and the risk assessment method of disaster chain[D]. Changsha:Central South University, 2013.
[22] 刘涛, 陈忠, 陈晓荣. 复杂网络理论及其应用研究概述[J]. 系统工程, 2005, 23(6):1-7. Liu Tao, Chen Zhong, Chen Xiaorong. A brief review of complex networks and its application[J]. Systems Engineering, 2005, 23(6):1-7.
[23] 陈长坤, 纪道溪. 基于复杂网络的台风灾害演化系统风险分析与控制研究[J]. 灾害学, 2012, 27(1):1-4. Chen Changkun, Ji Daoxi. Risk analysis and control for the evolution disaster system of typhoon based on complex network[J]. Disaster Science, 2012, 27(1):1-4.
