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| 1 |
ID:
116955
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2012.
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| Summary/Abstract |
China is the largest coke producer in the world, accounting for over 60% of the world coke production, which makes the coke industry in China a significant coal consumer and air pollutant emitter. Recently, China has taken a series of measures to improve energy efficiency and reduce emissions from the coke industry, including eliminating old and low energy-efficiency coking technologies, promoting advanced technologies, and strengthening energy and environmental requirements on coking processes. As a consequence, China's coke industry is experiencing an unprecedented technology shift, which was characterized by the elimination of old, inefficient, and polluting indigenous ovens and small machinery ones within 10 years. This study examines the policies and the prompt technology shift in China's coke industry, as well as the associated energy and environmental effects, and discusses the implications with respect to the development of the coke industry in China towards a more efficient and clean future. As China sets stricter requirements on energy efficiency and the ambient environment, a more significant change focusing on technologies of energy saving and emission reduction is urgently needed at present. Those mature technologies, including coke dry quenching, coke oven gas recycle, fine particle removal, etc., should be enforced in the near future.
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| 2 |
ID:
110394
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2011.
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| Summary/Abstract |
Recently, China has implemented many policy measures to control the oil demand of on-road vehicles. In 2010, China started to report the fuel consumption rates of light-duty vehicles tested in laboratory and to require new vehicles to show the rates on window labels. In this study, we examined the differences between the test and real-world fuel consumption of Chinese passenger cars by using the data reported by real-world drivers on the internet voluntarily. The sales-weighted average fuel consumption of new cars in China in 2009 was 7.80 L/100 km in laboratory and 9.02 L/100 km in real-world, representing a difference of 15.5%. For the 153 individual car models examined, the real-world fuel consumption rates were -8 to 60% different from the test values. The simulation results of the International Vehicle Emission model show that the real-world driving cycles in 22 selected Chinese cities could result in -8 to 34% of changes in fuel consumption compared to the laboratory driving cycle. Further government effort on fuel consumption estimates adjustment, local driving cycle development, and real-world data accumulation through communication with the public is needed to improve the accuracy of the labeling policy.
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| 3 |
ID:
109602
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2011.
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| Summary/Abstract |
Products other than biofuels are produced in biofuel plants. For example, corn ethanol plants produce distillers' grains and solubles. Soybean crushing plants produce soy meal and soy oil, which is used for biodiesel production. Electricity is generated in sugarcane ethanol plants both for internal consumption and export to the electric grid. Future cellulosic ethanol plants could be designed to co-produce electricity with ethanol. It is important to take co-products into account in the life-cycle analysis of biofuels and several methods are available to do so. Although the International Standard Organization's ISO 14040 advocates the system boundary expansion method (also known as the "displacement method" or the "substitution method") for life-cycle analyses, application of the method has been limited because of the difficulty in identifying and quantifying potential products to be displaced by biofuel co-products. As a result, some LCA studies and policy-making processes have considered alternative methods. In this paper, we examine the available methods to deal with biofuel co-products, explore the strengths and weaknesses of each method, and present biofuel LCA results with different co-product methods within the U.S. context.
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| 4 |
ID:
112231
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2012.
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| Summary/Abstract |
This article presents an updated and upgraded methodology, the Fuel Economy and Environmental Impacts (FEEI) model (http://www.feeimodel.org/), to project vehicle sales and stock in China on the basis of our previous studies. The methodology presented has the following major improvements: it simulates private car ownership on an income-level basis, takes into account car purchase prices, separates sales into purchases for fleet growth and for replacements of scrapped vehicles, and examines various possible vehicle scrappage patterns for China. The results show that the sales of private light-duty passenger vehicles in China could reach 23-42 million by 2050, with the share of new-growth purchases representing 16-28%. The total vehicle stock may be 530-623 million by 2050. We compare this study to other publicly available studies in terms of both projection methodology and results. A sensitivity analysis shows that vehicle sales are more affected than levels of vehicle stock by the model parameters, which makes projecting sales more difficult owing to the lack of reliable input data for key model parameters. Because it considers key factors in detail, the sales and stock projection module of the FEEI model offers many advantages over previous models and is capable of simulating various policy scenarios.
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| 5 |
ID:
125547
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2013.
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| Summary/Abstract |
China is experiencing rapid motorization and each city has a unique motorization pathway owing to its different characteristics and development progress. The temporal and spatial variation trend in on-road energy use and CO2 emissions need to be better understood in order to project the future growth and to support policy-making at both local and national levels. This study simulates the on-road energy use and CO2 emissions of all of China's prefectural-level cities (and above) from 1978 through 2008, on the basis of the collected vehicle data from hundreds of national and local statistical yearbooks. The results show that China's on-road energy use and CO2 emissions were 119 million metric tons (MMT) and 377 MMT in 2008, respectively-20 times the levels in 1978. The economically developed cities and heavy industrial cities had the highest on-road energy use and CO2 emissions before the year 2000, but recently the spatial distribution has varied significantly as the uptake of motorization increases successively in these cities. Now and in the near future, the most important driving force of the on-road energy and CO2 growth in China is the great number of average cities that have just started or will soon start the motorization.
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| 6 |
ID:
112232
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| Publication |
2012.
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| Summary/Abstract |
One of the principal ways to reduce transport-related energy use is to reduce fuel-consumption rates of motor vehicles (usually measured in liters of fuel per 100 km). Since 2004, China has implemented policies to improve vehicle technologies and lower the fuel-consumption rates of individual vehicles. Policy evaluation requires accurate and adequate information on vehicle fuel-consumption rates. However, such information, especially for Chinese vehicles under real-world operating conditions, is rarely available from official sources in China. For each vehicle type we first review the vehicle technologies and fuel-economy policies currently in place in China and their impacts. We then derive real-world (or on-road) fuel-consumption rates on the basis of information collected from various sources. We estimate that the real-world fuel-consumption rates of vehicles in China sold in 2009 are 9 L/100 km for light-duty passenger vehicles, 11.4 L/100 km for light-duty trucks, 22 L/100 km for inter-city transport buses, 40 L/100 km for urban transit buses, and 24.9 L/100 km for heavy-duty trucks. These results aid in understanding the levels of fuel consumption of existing Chinese vehicle fleets and the effectiveness of policies in reducing on-road fuel consumption, which can help in designing and evaluating future vehicle energy-efficiency policies.
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| 7 |
ID:
112230
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| Publication |
2012.
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| Summary/Abstract |
Vehicle-use intensity (kilometers traveled per vehicle per year or VKT) is important because it directly affects simulation results for vehicle fuel use and emissions, but the poor understanding of VKT in China could significantly affect the accuracy of estimation of total fuel use and CO2 emissions, and thus impair precise evaluation of the effects of associated energy and environmental policies. As an important component of our work on the Fuel Economy and Environmental Impacts (FEEI) model, we collected VKT survey data in China from available sources and conducted additional surveys during 2004 and 2010, from which we derived VKT values and VKT-age functions by vehicle type for China. We also projected the future VKT for China by examining the relationship of vehicle use to per-capita GDP in 20 other countries worldwide. The purpose of this work is to achieve a better understanding of vehicle-use intensity in China and to generate reliable VKT input (current and future VKT levels) for the FEEI model. The VKT results obtained from this work could also benefit other work in the field associated with vehicle energy use and emissions.
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