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Energy consumption has promoted a continuous development for economy and society, but it has also brought serious environmental pollution problems which endanger public health. In order to focus on the impact of PM 2.5 emissions from future energy consumption on human health better, this paper estimated PM 2.5 emissions caused by energy consumption in Beijing in 2020,2025 and 2030 by setting the baseline scenario, emission reduction scenario, intensified emission reduction scenario and the data of the base year 2015, which will be 162.6 thousand tons, 195.9 thousand tons and 235.9 thousand tons in the baseline scenario, 143.1 thousand tons, 151.8 thousand tons and 160.9 thousand tons under the emission reduction scenario, and 132.6 thousand tons, 130.2 thousand tons, 127.9 thousand tons under the intensified emission reduction scenario. Finally the paper measured the number of different health effect ends caused by PM 2.5 emissions and the economic loss. The results showed that there was a rapid increase, a mild increase and a moderate decrease in energy consumption and PM 2.5 emissions in Beijing under the three scenarios from 2015 to 2030. Besides, under the same scenario and the same concentration level baseline, the number of the internal medicine (over the age of 15) was the largest, and the economic loss caused by total death rate was the biggest. This article provides suggestions to reduce PM 2.5 emissions and public health effect ends for Beijing in the future. [ABSTRACT FROM AUTHOR]

Even though renewable energy development has gained momentum in China, thermal power generation still accounts for approximately 70% of the county's total power generation serving as the major source of carbon dioxide (CO 2) emissions in China. Facing the challenges of meeting 2030 peak target of CO 2 emission and realizing the coordinated development of thermal power generation in Beijing-Tianjin-Hebei region, this paper applies generalized Divisia Index Method (GDIM) to decompose the dynamics in the relevant CO 2 emission. The effects of five factors including electricity demand, energy consumption, technology, energy efficiency and energy-mix are considered. The decomposition suggests that electricity demand is the primary factor driving the CO 2 emission up, whereas technology effect decreases CO 2 emission the most. Given the significant roles of technology, energy-mix and energy efficiency in CO 2 emissions reduction, seven scenarios are designed to identify the optimal coordinated development pathway for thermal power generation in Beijing-Tianjin-Hebei region. Through upgrading energy structure and/or enhancing energy efficiency, the thermal power generation in Beijing-Tianjin-Hebei region can achieve coordinated development and realize the 2030 peak target under four scenarios. The detailed development pathways for CO 2 emissions and specific policy implications for Beijing, Tianjin and Hebei are provided to further govern CO 2 emissions and maintain sustainable development. • Proposed a five-factor Generalized Divisia Index Model (GDIM) for CO 2 emission analysis. • Analyzed the CO 2 from thermal power generation in China's Beijing-Tianjin-Hebei region. • Electricity demand and technology contributed the most to the positive and negative changes of CO 2 , respectively. • Designed seven thermal generation development scenarios to study the CO 2 change until 2030. • The 2030 CO 2 peak target can be achieved under four scenarios. [ABSTRACT FROM AUTHOR]