基于LEAP的京津冀地区能源结构调整战略居民健康收益评价
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摘要
在控制大气污染和保障居民健康的要求下,京津冀地区能源消费面临着总量控制和结构优化的巨大压力。本研究基于京津冀地区的社会经济发展目标并结合相关节能减排和环保要求,针对2014-2030年间的能源消费分别设计了基准情景(BAU)和能源结构调整情景(ESA),基于LEAP模型模拟预测了地区未来的能源消费及主要风险因子PM2.5的排放强度。分别采用综合暴露-反应关系IER模型和修正人力资本法评估了区域内居民在PM2.5暴露下的健康风险和经济损失,最后得出能源结构调整战略的居民健康收益。结果显示,至2030年,相比于基准情景,进行能源结构调整约可减少能源消费2.32亿吨,避免死亡14592例,获得经济收益约3297721万元。京津冀地区应加快实施能源消费总量控制、清洁能源替代等的强化节能措施,并针对北京、天津、保定等高风险的重点地区率先实行更严格的管控政策,以期更有效地降低区域整体风险,获得最大化的能源结构调整带来的健康收益。
To control the air pollution and protect the residents' health, the energy consumption is facing the pressure of total control and structural optimization in Beijing-Tianjin-Hebei region. Based on the socio-economic development objectives of Beijing-Tianjin-Hebei region and the related energy-saving and environmental protection requirements, this study designed the baseline scenario(BAU) and energy structure adjustment scenario(ESA) respectively for the energy consumption in 2014-2030. The long-range energy alternatives planning( LEAP) model is employed to predict total energy consumptions and the emission intensity of the major risk factor PM2.5. The comprehensive exposure-response relationship IER model and modified human capital method were used to evaluate the health risk and economic loss of residents in the area under PM2.5exposure. Finally, we evaluate the residents' health benefits obtained from the energy structure adjustment strategy. The results show that by 2030, compared to the baseline scenario, the energy structure adjustment can reduce energy consumption by 232 million tons, to avoid the death of 14592 cases, the economic benefits of about 32977 million yuan. Beijing-Tianjin-Hebei region should adopt more strict energy saving and emission reduction policies such as coal consumption control. And for Beijing, Tianjin, Baoding and other key areas, it is necessary to take the lead in the implementation of those policies, which can be more effectively to reduce the regional risk.
To control the air pollution and protect the residents' health, the energy consumption is facing the pressure of total control and structural optimization in Beijing-Tianjin-Hebei region. Based on the socio-economic development objectives of Beijing-Tianjin-Hebei region and the related energy-saving and environmental protection requirements, this study designed the baseline scenario(BAU) and energy structure adjustment scenario(ESA) respectively for the energy consumption in 2014-2030. The long-range energy alternatives planning( LEAP) model is employed to predict total energy consumptions and the emission intensity of the major risk factor PM2.5. The comprehensive exposure-response relationship IER model and modified human capital method were used to evaluate the health risk and economic loss of residents in the area under PM2.5exposure. Finally, we evaluate the residents' health benefits obtained from the energy structure adjustment strategy. The results show that by 2030, compared to the baseline scenario, the energy structure adjustment can reduce energy consumption by 232 million tons, to avoid the death of 14592 cases, the economic benefits of about 32977 million yuan. Beijing-Tianjin-Hebei region should adopt more strict energy saving and emission reduction policies such as coal consumption control. And for Beijing, Tianjin, Baoding and other key areas, it is necessary to take the lead in the implementation of those policies, which can be more effectively to reduce the regional risk.
引文
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[22]陈秉衡,阚海东.城市大气污染健康危险度评价的方法第二讲主要大气污染物的危害认定(续一)[J].环境与健康杂志,2004,21(3):181-182.
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[26]赵晓丽,范春阳,王予希.基于修正人力资本法的北京市空气污染物健康损失评价[J].中国人口资源与环境,2014,24(3):169-176.
[27]赵越.大气污染对城市居民的健康效应及经济损失研究[D].中国地质大学(北京),2007.
[28]刘帅,宋国君.城市PM2.5健康损害评估研究[J].环境科学学报,2016,36(4):1468-1476.
[2]缪育聪,郑亦佳,王姝,刘树华.京津冀地区霾成因机制研究进展与展望[J].气候与环境研究,2015,(03):356-368.
[3]黄蕊珠,陈焕盛,葛宝珠,姚石泉,王哲,杨文夷,陈学舜,朱莉莉,黄思,王自发.京津冀重霾期间PM_(2.5)来源数值模拟研究[J].环境科学学报,2015,(09):2670-2680.
[4]於方,过孝民,张衍燊,等.2004年中国大气污染造成的健康经济损失评估[J].环境与健康杂志,2007,24(12):999-1003.
[5]Chen B H,Kan H D.Air pollution and population health:a global challenge[J].Environmental Health and Preventive,2008,13(2):94-101.
[6]Lim,S.S.,Vos T.,Flaxman A.D.,et al.A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions,1990–2010:a systematic analysis for the Global Burden of Disease Study 2010[J].The lancet,2012,380(9859):2224-2260
[7]谢杨,戴瀚程,花岡達也,増井利彦.PM_(2.5)污染对京津冀地区人群健康影响和经济影响[J].中国人口·资源与环境,2016,(11):19-27.
[8]吕铃钥,李洪远.京津冀地区PM_(10)和PM_(2.5)污染的健康经济学评价[J].南开大学学报(自然科学版),2016,(01):69-77.
[9]黄德生,张世秋.京津冀地区控制PM2.5污染的健康效益评估[J].中国环境科学学,2013,(01):166-174.
[10]Chen L,Shi M,Li S,et al.Quantifying public health benefits of environmental strategy of PM2.5,air quality management in Beijing–Tianjin–Hebei region,China[J].Journal of Environmental Sciences,2016.
[11]董战峰,高晶蕾,郝春旭,葛察忠.《大气污染防治行动计划》实施的人体健康效应评估[J].环境污染与防治,2017,(02):225.
[12]阚海东,陈秉衡,陈长虹.上海市能源提高效率和优化结构对居民健康影响的评价[J].上海环境科学,2002,(09):520-524+579.
[13]Fang B,Liu C F.The assessment of health impact caused by energy use in urban areas of China:an intake fraction-based analysis[J].Natural Hazards,2012,62(1):101-114.
[14]Wang X,Mauzerall D L.Evaluating impacts of air pollution in China on public health:Implications for future air pollution and energy policies[J].Atmospheric Environment,2006,40(9):1706-1721.
[15]周健,崔胜辉,林剑艺,等.厦门市能源消费对环境及公共健康影响研究[J].环境科学学报,2011,31(9):2058-2065.
[16]Kale R V,Pohekar S D.Electricity demand and supply scenarios for Maharashtra(India)for2030:An application of long range energy alternatives planning[J].Energy Policy,2014,72(3):1-13.
[17]Emodi N V,Emodi C C,Murthy G P,et al.Energy policy for low carbon development in Nigeria:A LEAP model application[J].Renewable&Sustainable Energy Reviews,2017,68:247-261.
[18]Huang Y,Bor Y J.The long-term forecast of Taiwan's energy supply and demand:LEAP model application[J].Energy Policy,2011,39(11):6790-6803.
[19]Wang S X,Zhao M,Xing J,et al.Quantifying the air pollutants emission reduction during the 2008 Olympic games in Beijing[J].Environmental Science&Technology,2010,44(7):2490-2496.
[20]Zhao B,Wang P,Ma J Z,et al.A high-resolution emission inventory of primary pollutants for the Huabei region,China[J].Atmospheric Chemistry and Physics,2012,12(1):481-501
[21]谢元博,李巍.基于能源-环境情景模拟的北京市大气污染对居民健康风险评价研究[J].环境科学学报,2013,33(6):1763-1770.
[22]陈秉衡,阚海东.城市大气污染健康危险度评价的方法第二讲主要大气污染物的危害认定(续一)[J].环境与健康杂志,2004,21(3):181-182.
[23]陈仁杰,陈秉衡,阚海东.我国113个城市大气颗粒物污染的健康经济学评价[J].中国环境科学,2010,30(3):410-415.
[24]Burnett R T,Pope III C A,Ezzati M,et al.An integrated risk function for estimating the global burden of disease attributable to ambient fine particulate matter exposure[J].Environmental Health Perspectives,2014,122(4):397-403.
[25]Institute for Health Metrics and Evaluation.Global Burden of Disease Study2010(GBD 2010)-Ambient Air Pollution Risk Model 1990-2010[EB/OL].USA:Institute for Health Metrics and Evaluation,2014[2014-05-17].http://ghdx.healthdata.org/record/global-burden-disease-study-2010-gbd-2010-ambient-airpollution-risk-model-1990-2010.
[26]赵晓丽,范春阳,王予希.基于修正人力资本法的北京市空气污染物健康损失评价[J].中国人口资源与环境,2014,24(3):169-176.
[27]赵越.大气污染对城市居民的健康效应及经济损失研究[D].中国地质大学(北京),2007.
[28]刘帅,宋国君.城市PM2.5健康损害评估研究[J].环境科学学报,2016,36(4):1468-1476.