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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]

Promoting the coupled development of water, energy, and food (WEF) subsystems is a critical step to enhance synergies and increase efficiencies in the WEF nexus. However, the evolution and obstacles of coupled development are largely ignored. This study developed a framework dividing links in the nexus to select indicators and integrated models for the degree of coordination and obstacle diagnosis to explore the coupled development of the WEF nexus from 2000 to 2020 in the water-scarce megacities of Beijing and Tianjin. The results show that the average coordination degree of the WEF nexus in Beijing (0.315) and Tianjin (0.317) is at a low level, indicating a limited interaction between the WEF subsystems, while the coordinated development degree of the WEF nexus is increasing. The order degree of the WEF subsystems shows a two-level hierarchical structure, indicating that both similarities and differences are included in place-specific characteristics. Furthermore, obstacle factors are identified from water and energy subsystems, in which environmental water use (W3) and the energy consumption per gross domestic production unit (E4) played the most significant roles and require a higher priority in policy response. The results in this paper complement obstacle factor analysis in WEF nexus practice, and provide operational indicators for nexus governance. [Display omitted] • Linkages are divided into one-, two-, and three-resource scales. • The number of related official documents is used to define the weight of subsystems. • The water subsystem dominated the coupled development of the water-energy-food nexus. • The order degree of subsystems show a two-level hierarchical structure. • Key obstacle factors are identified from water and energy subsystems. [ABSTRACT FROM AUTHOR]

The ever-increasing electricity price and energy consumption in high-speed railway industry push railway companies to seek a promising way to realize their sustainable developments. Making full use of the solar resource along with high-speed railways can be a potential solution to cut the electricity bill, bring more profit to railway companies and realize the decarbonization of high-speed railway industry. This paper studies the optimal planning of distributed photovoltaic generation (DPVG) and energy storage system (ESS) for the traction power supply system (TPSS) of high-speed railway. A quantitative method is proposed to study the time and space characteristics of photovoltaic generation and electricity demand of high-speed trains. An integrated cost-benefit analysis framework is developed to evaluate the effect of DPVG and ESS on the economy of TPSS. To derive the optimal planning scheme and energy management strategy of DPVG and ESS, a mathematical programming model with the objective of minimizing the total cost is proposed to seek the most economical solution. A hybrid global optimal solution approach is developed to solve the model. A real-world case of Beijing-Baoding high-speed railway in China is used to illustrate the capability and characteristics of the proposed model. The computational results show that DPVG is able to supply 32.5 % electricity demand of high-speed trains. The integration of DPVG and ESS can help railway company save 4.2 million CNY each year in Beijing-Baoding high-speed railway. This paper demonstrates the potential and applicability of DPVG and ESS in high-speed railway industry. • A novel distributed photovoltaic generation model is proposed for the traction power supply system of high-speed railway. • A global optimal algorithm is provided to derive the most economical planning scheme and energy-management strategy. • Photovoltaic generation can help Beijing-Baoding high-speed railway save 4.2 million China Yuan each year. • Solar energy is able to supply 32.5% electricity demand of Beijing-Baoding high-speed railway. [ABSTRACT FROM AUTHOR]

With the rapid growth of urbanisation and associated vehicle numbers in China, urban transportation has become responsible for a large increase in the country's energy consumption and, consequently, its air pollution levels. Beijing has been making significant efforts to reduce transportation sector energy consumption and pollution. However, owing to the existence of a large number of private cars, the implementation of effective energy consumption and emission reduction measures has been difficult to achieve. This paper reviews the policies and regulations that have so far been developed to tackle Beijing's transportation sector issues. Perspective and analysis are given on the specific policies and regulations that have been employed, focusing on the overarching regulation mechanism, public transportation infrastructure, vehicle technology-related measures, vehicle activity-related measures and eco-driving -related measures, relevant experiences and lessons are summarised. A key finding concludes that the implementation of driving restriction policy can restrain pollutants emissions significantly, it shows energy consumption and emission reduction should not only be applied to public transportation, but the effective control of emissions from private cars should also attract more attention. To better control energy consumption of urban transport, various measures and solutions are proposed and discussed, including the further popularizing of eco-driving and the widespread application of e-mobility. Specific proposals for developing urban transportation policy are also discussed. [ABSTRACT FROM AUTHOR]

This paper investigates whether the China ETS policy has achieved carbon emission reduction at the expense of economic development. Moreover, we are interested in unmasking the role of the institutional factors adopted by the ETS pilots in their ETS effects. Using the province-level panel data during the 2008–2016 period. we employ the DID model to compare carbon emissions and economic development between the ETS and non-ETS regions and between the pre- and post-ETS periods. Some novel empirical findings emerge. First, compared with the non-ETS areas, the ETS policy has significantly reduced carbon emission in the ETS areas. This emission reduction has not come at the cost of economic development. Second, the ETS policy leads to a decline in carbon intensity and fossil fuel energy consumption relative to all energy types. Lastly, some heterogeneity across markets arise. The Beijing carbon market performs the best among all pilots in terms of achieving targets of carbon reductions, followed by the Hubei carbon market. [ABSTRACT FROM AUTHOR]

Along with rapid urbanization and economic development, urban household consumption has experienced a remarkable change, leading to a corresponding increase in direct and indirect carbon emissions. A systematic accounting of household carbon footprints (HCFs) in Beijing during 2002, 2007, and 2012 using a nested input-output model is presented in this paper. The results indicate that the per capita carbon footprint from urban household consumption in Beijing increased from 3054.05 kg in 2002–4611.12 kg in 2012, of which the indirect emissions were the majority. In terms of consumption structure, food, housing, transportation and communication, and education and entertainment were the four dominant sources contributing to the indirect urban HCFs in Beijing. With respect to the source, local Beijing was the largest contributor for itself materials and service provisions in 2002 and 2007, while the domestic source became the largest contributor in 2012, accounting for 55.08% of the total indirect household carbon emissions. Moreover, we also discovered that families with high income level had much higher HCFs compared to those with low income level. Given these considerations, transitions towards low-carbon household consumption are needed so as to provide equality and sustainability. • Nested input-output model is adopted to calculate household carbon footprints (HCFs). • Per capita HCFs in Beijing increased from 3054.05 kg in 2002–4611.12 kg in 2012. • Indirect emission constituted the majority of HCFs, accounting for 63.69% in 2012. • Income level has great impacts on HCFs due to energy intensive consumption pattern. [ABSTRACT FROM AUTHOR]

Carbon emissions and energy consumption have serious impacts on humans and ecosystems. This paper investigates the effects of industrial reconstructuring on energy conservation and emission reduction. A multi-objective optimization model was established. The model classifies industrial sectors into four groups according to their carbon emission levels and contributions to economic growth, then non dominated sorting genetic algorithm is applied to solve the model and the Pareto frontier is obtained. The best solution is selected from the Pareto frontier by using a super data envelopment analysis model which measures the degree of coordination between economy and environment. The model is used to analyze the effects of industrial reconstructuring in Beijing during 2018–2020. The results show that industrial reconstructuring enabled economic growth to reach the government's planned rate while the carbon intensity and energy intensity surpassed the goal of the 13th Five-Year Plan. This case can provide decision-making basis for the sustainable development of ecology and economy in other regions. Fig. 6. Pareto front in Beijing region in 2020 The optimal Pareto solution for carbon emissions, energy consumptions and GDP targets after industrial structure reconstructuring. Image 1 • Classifying industrial sectors into four groups according to carbon emission levels and economic growth contributions. • A multi-objective optimization model was established and solved by the genetic algorithm. • A super DEA model evaluates the final plan which reflects the coordination of the economy and environment. • The analysis of each group can help achieving maximum benefits of economic and environment. [ABSTRACT FROM AUTHOR]