化石能源使用过程中排放的温室气体及大气污染物对气候变化、空气质量和人体健康造成严重影响，而火电行业的化石能源消费量约占全球消费总量的50%左右，因此成为全球温室气体减排和污染控制的最主要目标之一。面对改善空气质量和减缓气候变化的双重压力，亟需建立完善的政策评价体系，对火电厂排放的环境影响及减排效益开展评估，并在此基础上制订针对性的减排政策，实现火电行业的可持续发展。本研究以全球火电厂为研究对象，构建了由高分辨率排放现状及预测模型、大气化学模型、健康效应模型组成的火电行业政策评价体系，剖析了全球现役火电机组排放特征，分析了全球火电厂未来减排路径及不同减排路径对实现INDCs目标的影响，估算了全球火电厂排放对空气质量和健康的影响及未来减排路径下的环境和健康效益。 首先，通过耦合同化多个全球和区域尺度的火电机组基础信息数据库，建立了统一的火电机组排放表征参数化方法，开发出包含7.2万个在役机组的全球火电厂高分辨率排放数据库GPED。基于GPED深入剖析了不同类型机组的排放水平和减排潜力。其次，通过构建机组动态演替函数，建立了全球火电厂未来排放预测模型，实现了对未来火电机组活动水平和排放量的动态连续预测。基于该模型预测了不同情景下2030年全球火电厂排放，发现通过深度调整能源结构可削减2030年全球火电厂CO2及大气污染物排放约22%-25%，通过强化末端控制可削减大气污染物排放约40%-49%，而改变退役模式和发电负荷可避免约2000GW的新建火电厂需求。研究同时发现，若按现有规划布局和建设火电厂，中国和欧洲将存在不能完成INDCs承诺的碳排放目标的风险。最后，通过耦合电厂排放模型、大气化学模型和健康效应模型，评估了全球火电厂排放的环境和健康影响及未来减排效益。评估结果显示，2010年全球火电厂排放导致全球PM2.5暴露水平增加约3.9μg/m3，导致全球每年46.1万人过早死亡。通过深度调整能源结构和强化末端控制，2030年火电厂排放导致的PM2.5暴露水平可较基准情景下降52.7%，从而避免每年33.5万人的过早死亡。
Greenhouse gases and air pollutants in the process of using fossil fuels causes a great impact on the air quality, climate change and human health. About half of global fossil fuel consumed in thermal power sector, which becomes one of the most significant control targets of greenhouse gases and air pollutants. Under the duel pressure of improving air quality and alleviating climate change, we urgently need to build a comprehensive policy assessment system to evaluate the environmental impact of the emissions from power sector and benefits from future emission reductions in order to support the accurate control policies and realize the sustainable development of thermal power plants. Our study establishes a system including the global high-resolution thermal power plant emission database, the emission projection model, atmospheric chemistry model and health exposure model. We further analyze the current emission characteristics, explore the emissions mitigation pathway, evaluate climate effect under INDCs targets of CO2 emissions from future power sector, and analyze air quality and health impact from present global thermal power plants’ emissions, as well as air quality and health benefits from power plants’ emissions mitigation under various emission scenarios.Firstly, a publically available global power plant emission database for CO2 and air pollutants at unit level (GPED) is established, which combines the best available data from national statistics and previous unit-level inventories, and fills data gaps with modeled emissions. GPED database includes more than 72,000 units with accurate locations. We further analyze the energy efficiencies and emission characteristics at region and unit level. Secondly, we construct a fleet turn-over projection model, and the model is designed to simulate power plant fleet turnover by tracking the lifespan of each power generation unit, which can dynamicaly project annual activity rates and emission factors. In this work, we design various future emission scenarios and find that the deep energy structure adjustment can decrease CO2 and air pollutants emissions by 22-25%, and end-of-pipe control measures enhancement can significantly decrease air pollutants emissions by 40-49%. We also find that changing retirement mode and improving the capacity factor of generating units can significantly reduce the demand of the new-built capacity of ~2,000 GW, avoiding the resources waste and reducing CO2 committed emissions. And results show there is a big risk to achieve INDCs targets in European Union and China if we develop new-built plants as proposed. Finally, through coupling emission inventory, atmospheric chemistry model and health exposure model, we assess the air quality and health impact from thermal power plant emissions in 2010 and benefits from future emissions mitigation. Results show that the global thermal power plants emissions in 2010 contribute 3.9μg/m3 population-weighted average PM2.5 concentrations. The global thermal power plants emission further leads to 461,000 premature deaths. Through the analysis of future emission scenarios, we find that energy structure adjustment and end-of-pipe control measures enhancement in power sector could bring 52.7% reductions of population-weighted average PM2.5 concentrations, and avoid 335,000 premature deaths in 2030 compared to the base scenario, respectively.
