CO2 Emission Reduction Potential in China's Electricity Sector: Scenario Analysis Based on LMDI Decomposition

AbstractThe CO2 emission reduction from China's electricity sector will matter not only for China but impact the result of the global action on climate change. This paper firstly analyzed the main factors that affect the CO2 emission in accordance with the LMDI decomposition model. Then three scenarios were assumed based on the main factors to explore the CO2 reduction potential. Furthermore, LMDI method was used again to measure the contribution of each factor to CO2 emission reduction potential in the future. The results showed that the CO2 emission will continue to grow in the three scenarios from 2010 to 2020, with an annual growth rate of 10.7%, 6.5% and 4.5%, respectively. The active low carbon policies taken on the driving factors will contribute to 2701Mt - 3688Mt CO2 emission reduction. The share of low-carbon power generation and thermal power generation efficiency are most important factors for emission reduction. However, in the long run, low-carbon power generation will contribute more. Terminal electricity consumption is always the most important factor driving CO2 emission up. Finally, policies for low-carbon development of China's electricity sector are proposed based on the analysis results

Study on China's Regional Carbon Emission Factors: The case of Chongqing City

AbstractLow-carbon development has become a hot issue concerned by the whole world. Governments respectively introduced the country's low-carbon strategy and action. China has put forward a series of obligatory targets and has issued a provincial area “twelfth five-year” carbon intensity reduction target. How to coordinate the contradiction between economic growth and environmental constraints, and formulating corresponding low-carbon development path and the supporting measures, has become one of the problems to be solved. Considering the regional resource endowment, stage of economic development, energy structure, industrial structure, technical development level and other factors, this article constructs the model of regional carbon emission factors, the paper takes Chongqing of China as an example. The research results show that: The major contribution of elements, in turn, is the improvement of technology energy efficiency, the optimization of energy structure, and the adjustment of industrial structure. Based on this, this paper puts forward the corresponding low-carbon development policies according to the results of analysis, from the aspects such as energy structure, industrial structure, and technological progress and so on

Flood risk assessment using the CV-TOPSIS method for the Belt and Road Initiative: an empirical study of Southeast Asia

Instruction The countries along the Belt and Road Initiative remain high exposure and vulnerability to climate extremes. Southeast Asia, a significant part of the Belt and Road Initiative, suffers a lot from flood disasters. This study assessed the flood disaster risk from 1990–2015 in all 11 Southeast Asian countries. A model integrating the coefficient of variation approach and the Technique for Order Preference by Similarity to Ideal Solution method was introduced to analyze the flood disaster data. Considering that populations living in areas where elevation is below 5 m and land area where elevation is below 5 m have reached 11.86% and 3.54% (2015), respectively, the two indicators were opted for to propose new metrics for flood disaster risk assessment.Outcomes: Our findings show that the flood disaster risk in Southeast Asia appeared very high during most of the study period. Indonesia had an extremely high flood disaster risk, followed by Vietnam, whereas Laos, Malaysia, Brunei, and Timor Leste had lower flood risks. The model introduced in this paper is quite simple and easy to understand, providing accessible flood risk information for decision makers.Conclusion: The results we obtained have practical implications for land use and investment activities in Southeast Asia

Scenario Analysis of Urban Road Transportation Energy Demand and GHG Emissions in China—A Case Study for Chongqing

This study, using Chongqing City of China as an example, predicts the future motor vehicle population using the Gompertz Model and the motorcycle population using the piecewise regression model, and predicts and analyzes fuel consumption and greenhouse gas (GHG) emissions of motor vehicles from 2016 to 2035 based on the bottom-up method under different scenarios of improving the fuel economy of conventional vehicles, promoting alternative fuel vehicles, and the mixed policy of the above two policy options. The results indicate that the total population of motor vehicles in Chongqing will increase from 4.61 million in 2015 to 10.15 million in 2035. In the business-as-usual scenario, the road-transportation energy demand in Chongqing will keep increasing from 2015 and will peak in 2030, before it begins to decline by 2035. The trends for the tank to wheel (TTW) and well to wheel (WTW) GHG emissions are similar to that of energy demand. The WTW GHG emissions will increase from 24.9 Mt CO2e in 2016 to 50.5 Mt CO2e in 2030 and will then gradually decline to 48.9 Mt CO2e in 2035. Under the policy scenarios of improving fuel economy of conventional fuel passenger cars, promoting alternative fuel vehicles, and their mixed policy, direct energy consumption and TTW and WTW GHG emissions from 2016 to 2035 will be reduced to different levels. It is also found that the two types of policies have a hedging effect on the direct energy-consumption saving, TTW, and WTW GHG emission reductions. Sensitivity analysis of key parameters and policy settings is conducted to investigate the impact of their changes on the vehicle population projection, direct energy demand, and WTW GHG emissions. Some policy implications are suggested to provide reference for the formulation and adjustment of Chongqing’s, or even China’s, low-carbon road transportation policies in the future based on the analysis results

Assessing CO2 Emissions from Passenger Transport with the Mixed-Use Development Model in Shenzhen International Low-Carbon City

Assessing transport CO2 emissions is important in the development of low-carbon strategies, but studies based on mixed land use are rare. This study assessed CO2 emissions from passenger transport in traffic analysis zones (TAZs) at the community level, based on a combination of the mixed-use development model and the vehicle emission calculation model. Based on mixed land use and transport accessibility, the mixed-use development model was adopted to estimate travel demand, including travel modes and distances. As a leading low-carbon city project of international cooperation in China, Shenzhen International Low-Carbon City Core Area was chosen as a case study. The results clearly illustrate travel demand and CO2 emissions of different travel modes between communities and show that car trips account for the vast majority of emissions in all types of travel modes in each community. Spatial emission differences are prominently associated with inadequately mixed land use layouts and unbalanced transport accessibility. The findings demonstrate the significance of the mixed land use and associated job-housing balance in reducing passenger CO2 emissions from passenger transport, especially in per capita emissions. Policy implications are given based on the results to facilitate sophisticated transport emission control at a finer spatial scale. This new framework can be used for assessing the impacts of urban planning on transport emissions to promote sustainable urbanization in developing countries

An assessment of renewable energy development in Belt and Road Initiative countries: An entropy and TOPSIS approach

The development of renewable energy is a significant global factor in the achievement of a green economic recovery after the epidemic, and to enhance sustainable social development in the future. However, the Belt and Road Initiative (BRI) countries are experiencing regional differences in renewable energy development owing to the different economic and social levels. It is of theoretical and practical significance to assess the situation of renewable energy development in BRI countries, in order to identify the advantages and disadvantages of renewable energy development and to enhance energy cooperation between countries. In this paper, a multidimensional assessment for BRI countries (47 countries/regions across Asia, Europe, Africa, the Americas, and Oceania) was carried out based on empirical data, (including institutional, economic, technological, energy and environmental facets). The Entropy Weight Method and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) were selected to assess the level of renewable energy development in BRI countries during the period 2009–2017. The results demonstrated that BRI countries/regions had a low overall level of renewable energy development during the study period, but a stable and rising development trend was identifiable. For example, certain countries/regions (e.g. Mainland China, Indonesia, Pakistan, Russia, South Africa and New Zealand) experienced significant growth during the period. When analyzed by continents, the Americas and Oceania had the highest level of renewable energy development, followed by Europe, with Asia and Africa ranking lowest. Europe and Oceania’s notable advantages in “institutional and economic facets” were primarily as a result of the enhanced governance capability and superior economic development. The superior maturity of renewable energy technology in the Americas and Oceania contributes to the superior performance in the “technological facet”. The countries with superior development in the “energy and environmental facets” are located in Asia, Oceania and Europe

Assessing CO₂ Emissions from Passenger Transport with the Mixed-Use Development Model in Shenzhen International Low-Carbon City

Assessing transport CO2 emissions is important in the development of low-carbon strategies, but studies based on mixed land use are rare. This study assessed CO2 emissions from passenger transport in traffic analysis zones (TAZs) at the community level, based on a combination of the mixed-use development model and the vehicle emission calculation model. Based on mixed land use and transport accessibility, the mixed-use development model was adopted to estimate travel demand, including travel modes and distances. As a leading low-carbon city project of international cooperation in China, Shenzhen International Low-Carbon City Core Area was chosen as a case study. The results clearly illustrate travel demand and CO2 emissions of different travel modes between communities and show that car trips account for the vast majority of emissions in all types of travel modes in each community. Spatial emission differences are prominently associated with inadequately mixed land use layouts and unbalanced transport accessibility. The findings demonstrate the significance of the mixed land use and associated job-housing balance in reducing passenger CO2 emissions from passenger transport, especially in per capita emissions. Policy implications are given based on the results to facilitate sophisticated transport emission control at a finer spatial scale. This new framework can be used for assessing the impacts of urban planning on transport emissions to promote sustainable urbanization in developing countries