Energy demand and greenhouse gas emissions during the production of a passenger car in China
Energy demand and greenhouse gas emissions during the production of a passenger car in China
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Environmental implications of fleet electrification highly depend on the adoption and utilization of electric vehicles at the individual level. Past research has been constrained by using aggregated data to assume all vehicles with the same travel pattern as the aggregated average. This neglects the inherent heterogeneity of individual travel behaviors and may lead to unrealistic estimation of environmental impacts of fleet electrification. Using "big data" mining techniques, this research examines real-time vehicle trajectory data for 10,375 taxis in Beijing in one week to characterize the travel patterns of individual taxis. We then evaluate the impact of adopting plug-in hybrid electric vehicles (PHEV) in the taxi fleet on life cycle greenhouse gas emissions based on the characterized individual travel patterns. The results indicate that 1) the largest gasoline displacement (1.1 million gallons per year) can be achieved by adopting PHEVs with modest electric range (approximately 80 miles) with current battery cost, limited public charging infrastructure, and no government subsidy; 2) reducing battery cost has the largest impact on increasing the electrification rate of vehicle mileage traveled (VMT), thus increasing gasoline displacement, followed by diversified charging opportunities; 3) government subsidies can be more effective to increase the VMT electrification rate and gasoline displacement if targeted to PHEVs with modest electric ranges (80 to 120 miles); and 4) while taxi fleet electrification can increase greenhouse gas emissions by up to 115 kiloton CO2-eq per year with the current grid in Beijing, emission reduction of up to 36.5 kiloton CO2-eq per year can be achieved if the fuel cycle emission factor of electricity can be reduced to 168.7 g/km. Although the results are based on a specific public fleet, this study demonstrates the benefit of using large-scale individual-based trajectory data (big data) to better understand environmental implications of fleet electrification and inform better decision making.
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The carbon emissions of new energy vehicles (NEVs)have transited from the use stage to the production stage, indicating that the environmental impact of NEVs in the manufacturing stage cannot be ignored. To reduce carbon emissions and maintain profits, this study proposes a fuzzy multi-objective optimization model to achieve a sustainable production planning scheme for NEVs. The proposed model not only considers the maximum profits of automobile enterprises but also the minimum target of carbon emissions in the production process, to coordinate the optimal production quantity. The results show that the output of NEVs in different price ranges has different proportions. The market share of blade electric vehicles is the highest, accounting for 39% of the NEV market, and the proportion of plug-in hybrid and blade electric vehicles is increasing. The sensitivity analysis further reflects the impact of government subsidy “recession” and body lightweight on the output, carbon emissions, and annual profits of NEVs in China. Accordingly, this paper provides policy implications for achieving a sustainable production planning scheme for NEVs in China.
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The continuous increase in energy consumption by cellular networks requires rethinking their energy efficiency. Current research indicates that one third of operating energy could be saved by reducing the transmission power of base stations. However, this approach requires the introduction of a range of additional equipment containing more embodied energy - consumed by all processes associated with the production of equipment. This problem is addressed first in this article. Furthermore, a new cellular network energy efficiency model with embodied energy is proposed, and optimization between the number of cells and their coverage is investigated. Contrary to previous works, we have found that embodied energy accounts for a significant proportion of total energy consumption and cannot be neglected. The simulation results confirm an important trade-off between operating and embodied energies, which can provide some practical guidelines for designing energy-efficient cellular access networks. The new model considering embodied energy is not limited to just cellular networks, but to other telecommunications, such as wireless local area networks and wired networks.
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자동차 온실가스 저감정책에 따른 이산화탄소 저감 효과 평가
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In this paper, the vehicle cycle environment impacts of a mid-size passenger car in China is performed, with a special focus on the primary energy consumption and greenhouse gas (GHG) emissions. The vehicle cycle analysis results show that the energy consumption and GHG emissions of a passenger car in China are about 91.1 GJ and 11.5 ton per vehicle, respectively. And coal as the main process fuel in China is the key contributor to the high GHG emissions. The material production process is very energy-intensive, and vehicle assembly process is very emission-intensive. The energy consumption and GHG emissions of the remaining stages are small compared to the overall vehicle cycle impacts. There are three means to reduce vehicle cycle environmental impacts: automotive light weighting, adopt low energy-intensive and low emission-intensive materials in vehicle, and substitute environment friendly energy for coal as the main process fuel in China.
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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.
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8
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Municipal solid waste (MSW) management systems play a crucial role in greenhouse gas (GHG) emissions in China. Although the government has implemented many policies to improve the MSW management system, the impact of these improvements on city-level GHG emission reduction remains largely unexplored. This study conducted a comprehensive analysis of both direct and downstream GHG emissions from the MSW sector, encompassing sanitary landfill, dump, incineration, and biological treatment, across 352 Chinese cities from 2001 to 2021 by adopting inventory methods recommended by the Intergovernmental Panel on Climate Change (IPCC). The results reveal that (1) GHG emissions from the MSW sector in China peaked at 70.6 Tg of CO2 equiv in 2018, followed by a significant decline to 47.6 Tg of CO2 equiv in 2021, (2) cities with the highest GHG emission reduction benefits in the MSW sector were historical emission hotspots over the past 2 decades, and (3) with the potential achievement of zero-landfilling policy by 2030, an additional reduction of 203.7 Tg of CO2 equiv is projected, with the emission reduction focus toward cities in South China (21.9%), Northeast China (17.8%), and Southwest China (17.3%). This study highlights that, even without explicit emission reduction targets for the MSW sector, the improvements of this sector have significantly reduced GHG emissions in China.
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This report summarizes the findings and recommendations of a three-year study on greenhouse gas (GHG) emissions in China and options for abatement over the coming decades. Macroeconomic modeling results show that the continuation of rapid economic growth in China could result in a threefold increase in GHG emissions between 1990 and the year 2020. Specific measures for limiting GHG emissions are examined in detail, including improvements in energy efficiency, more rapid introduction of non-fossil energy technologies, afforestation for carbon sequestration, and modifications to various GHG-producing agricultural practices. In the short- to medium-term (before 2010), energy efficiency holds the greatest potential for low-cost GHG emission reduction. Over the longer term, however, the only option for China and the world is to switch to non-carbon energy sources. The study concludes that a two-pronged strategy for reducing GHG emissions in China should be adopted, whereby (i) economic reform and policy initiatives are continued for the purpose of improving resource allocation and encouraging energy conservation, and (ii) a set of priority investment and technical assistance programs are undertaken which promote the acceleration of more efficient and low-carbon technologies and which improve the institutional and human resource capacities to implement and sustain these programs.
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7
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Greenhouse gas (GHG) emissions are an important factor in the evaluation of green industrial growth, when low GHG emissions along with high industrial growth are expected. In this paper, the improvement of sustainable development of industry in China (2007–2015) was investigated via analysis of the relationships between the GHG emissions and energy consumption in comparison to European countries. A hierarchical cluster analysis (HCA) was conducted to distinguish industrial growth with GHG emission and energy consumption structures. The results of this research indicated that green industrial growth in Europe had a negative annual rate of GHG emissions. This contributed to the ratio of renewable energy consumption increasing to a maximum of 33% and an average of 16%. In comparison, the GHG emissions in China increased at a rate of 50% to 77% in the main industrial provinces since 2007 with their rapid industrial growth. The rate of GHG emissions decreased after 2012, which was 7% or less than the rate of emissions in the industrial provinces. Contrary to in Europe, the decreasing rate of GHG emissions in China was attributed to the improvement of fossil energy efficiency, as renewable energy consumption was less than 10% in most industrial provinces. Our data analysis identified that the two different energy consumption strategies improved green industrial growth in Europe and China, respectively. Our data analysis identified the two different energy consumption strategies employed by Europe and China, each of which promoted green industrial growth in the corresponding areas. We concluded that China achieved green industrial growth through an increase in energy efficiency through technology updates to decrease GHG emissions, which we call the “China Model.” The “Europe Model” proved to be quite different, having the core characteristic of increasing renewable energy use.
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67
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Structure and impacts of fuel economy standards for passenger cars in China
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293
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The availability of fossil resources is predicted to decrease in the near future: they are a non-renewable source, they cause environmental concerns, and they are subjected to price instability. Utilization of biomass as raw material in a biorefinery is a promising alternative to fossil resources for production of energy carriers and chemicals, as well as for mitigating climate change and enhancing energy security. This paper focuses on a biorefinery concept which produces bioethanol, bioenergy, and biochemicals from switchgrass, a lignocellulosic crop. Results are compared with a fossil reference system producing the same products/services from fossil sources. The biorefinery system is investigated using a Life Cycle Assessment approach, which takes into account all the input and output flows occurring along the production chain. This paper elaborates on methodological key issues like land use change effects and soil N2O emissions, whose influence on final outcomes is weighted in a sensitivity analysis. Since climate change mitigation and energy security are the two most important driving forces for biorefinery development, the assessment has a focus on greenhouse gas (GHG) emissions and cumulative primary energy demand (distinguished into fossil and renewable), but other environmental impact categories (e.g., abiotic depletion, eutrophication, etc.) are assessed as well. The use of switchgrass in a biorefinery offsets GHG emissions and reduces fossil energy demand: GHG emissions are decreased by 79% and about 80% of non-renewable energy is saved. Soil C sequestration is responsible for a large GHG benefit (65 kt CO2-eq/a, for the first 20 years), while switchgrass production is the most important contributor to total GHG emissions of the system. If compared with the fossil reference system, the biorefinery system releases more N2O emissions, while both CO2 and CH4 emissions are reduced. The investigation of the other impact categories revealed that the biorefinery has higher impacts in two categories: acidification and eutrophication. Results are mainly affected by raw material (i.e., switchgrass) production and land use change effects. Steps which mainly influence the production of switchgrass are soil N2O emissions, manufacture of fertilizers (especially those nitrogen-based), processing (i.e., pelletizing and drying), and transport. Even if the biorefinery chain has higher primary energy demand than the fossil reference system, it is mainly based on renewable energy (i.e., the energy content of the feedstock): the provision of biomass with sustainable practices is then a crucial point to ensure a renewable energy supply to biorefineries. This biorefinery system is an effective option for mitigating climate change, reducing dependence on imported fossil fuels, and enhancing cleaner production chains based on local and renewable resources. However, this assessment evidences that determination of the real GHG and energy balance (and all other environmental impacts in general) is complex, and a certain degree of uncertainty is always present in final results. Ranges in final results can be even more widened by applying different combinations of biomass feedstocks, conversion routes, fuels, end-use applications, and methodological assumptions. This study demonstrated that the perennial grass switchgrass enhances carbon sequestration in soils if established on set-aside land, thus, considerably increasing the GHG savings of the system for the first 20 years after crop establishment. Given constraints in land resources and competition with food, feed, and fiber production, high biomass yields are extremely important in achieving high GHG emission savings, although use of chemical fertilizers to enhance plant growth can reduce the savings. Some strategies, aiming at simultaneously maintaining crop yield and reduce N fertilization application through alternative management, can be adopted. However, even if a reduction in GHG emissions is achieved, it should not be disregarded that additional environmental impacts (like acidification and eutrophication) may be caused. This aspect cannot be ignored by policy makers, even if they have climate change mitigation objectives as main goal.
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