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Because China's statistical system differs from other countries, the reported energy data of its transport sector cannot be used for worldwide comparison, representing an obstacle for scientific research and policy making. A practical methodology to evaluate internationally consistent energy data for China's transport sector is presented in this paper. A calibration process was used to combine the results from top-down and bottom-up methods. The results indicate that the total energy consumption related to all transport activities is about one-third higher than the officially reported data. Gasoline and diesel used by non-operating vehicles in the road sector represent the greatest difference. Total energy demand in China's transport sector was 327 million tons of coal equivalent (Mtce) in 2010, 411 Mtce in 2013, and 452 Mtce in 2015. After adjustment, the transport sector accounted for 13% of the total final energy demand in 2010 and 2013, 14% in 2015, and 10% of national CO 2 emissions in 2015. During 2010–2013 and 2013–2015, total energy demand in China's transport sector increased by 84 Mtce and 41 Mtce, respectively, and 88% and 85% of the growth came from the road sector. Without calibration, bottom-up methods often resulted in an overestimation of energy consumption for gasoline and diesel, sometimes exceeding the total national consumption level. The proposed method and estimated results not only support the development of energy consumption and CO 2 emission inventories for China but also lay the foundation for further research on low-carbon strategies for China's transport sector and associated policies. Uncertainties in the estimations and suggestions for improvement are also discussed. • Official data underestimated the energy demand in China's transport sector. • A methodology to evaluate energy data for China's transport sector was introduced. • Energy demand and CO 2 emissions in transport in 2010, 2013 and 2015 were evaluated. • Total energy demand of transport sector was one-third higher than official data. • The reliability of evaluation result was substantially improved by this method. [ABSTRACT FROM AUTHOR]

Sanitary ware industry consumes vast amounts of energy and materials; however, little is known about the environmental impacts and economic costs associated with the production of sanitary ware. Selecting a factory of a leading Chinese sanitary ware company, Huida Co. Ltd., this paper employs a combined "cradle-to-gate" life cycle assessment (LCA) and life cycle costing (LCC) methodology to evaluate the environmental impacts and economic costs related to the production of one tonne of sanitary ware. The LCA results indicate firing and drying are the processes with the greatest environmental impacts, attributing to the combustion of coke oven gas. The LCC results show that casting, body preparation and firing are the greatest contributors to the total equipment, material and energy costs, respectively. The results of sensitivity analysis confirm that increasing fuel efficiency, natural gas usage and recycling rates can reduce the overall environmental impacts, but the total costs would be increased by 13.8% if coke oven gas is fully replaced by natural gas, even considering carbon tax. Based on the findings, recommendations such as using green materials and improving energy efficiency, are provided to promote both the environmental and economic sustainability of sanitary ware production. Image 1 • Environmental impacts and economic costs of sanitary ware production are evaluated. • Firing and drying have the greatest environmental impacts due to fuel consumption. • Casting and body preparation contribute most to the equipment and material costs. • Using natural gas as fuel reduces environmental impacts while rises costs. • Recommendations are provided to foster the sustainable production of sanitary ware. [ABSTRACT FROM AUTHOR]

On the basis of literature review and current situation analysis, models were established to carryout scientific measurement for carbon emissions and its intensity in China in this paper. With full consideration to the actual situation of energy consumption growth and carbon emission intensity controlling of energy consumption in new-type urbanization construction, the Kaya model was revised. With population intensity of GDP production, urbanization rate, employment rate of urban population, per capita energy consumption of urban employed population and carbon emission density of energy consumption selected as independent variables, test models of multivariate linear correlation were established for new-type urbanization construction, energy consumption growth and carbon emission intensity controlling of energy consumption, and the empirical equilibrium equation and error correction equation were determined through stability test, lag order test and co-integration test. The results are shown as follows: the urban employment rate (UER) has the greatest impact on carbon emission intensity, the per capita urban employment energy consumption (PEC) has the least impact on carbon emission intensity, and the degree of other factors in proper order is: urbanization rate (UR), population intensity of GDP production (PG) and carbon emission density (CD). Image 10106 • Energy consumption is the main source of China's carbon emissions and environmental pollution. • China's urbanization has contributed to the reduction of energy consumption and carbon emission intensity. • The change law of energy consumption carbon emission intensity in China's urbanization construction is analyzed. • Kaya model was adopted to study the influencing factors of carbon emission intensity control. [ABSTRACT FROM AUTHOR]

Energy-saving technologies in buildings have received great attention from energy efficiency researchers in the construction sector. Traditional research tends to focus on the energy used during building operation and in construction materials production, but it usually neglects the energy consumed in the building construction process. Very few studies have explored the impacts of technological progress on energy efficiency in the construction industry. This paper presents a model of the building construction process based on Cobb-Douglas production function. The model estimates the effects of technological progress on energy efficiency with the objective to examine the role that technological progress plays in energy savings in China's construction industry. The modeling results indicated that technological progress improved energy efficiency by an average of 7.1% per year from 1997 to 2014. Furthermore, three main technological progress factors (the efficiency of machinery and equipment, the proportion change of the energy structure, and research and development investment) were selected to analyze their effects on energy efficiency improvement. These positive effects were verified, and results show the effects of first two factors are significant. Finally, recommendations for promoting energy efficiency in the construction industry are proposed. • Explored energy efficiency of the building production process through analysis of national statistical data. • Technological progress was found to increase energy efficiency by an annual average of 7.1%. • Analyzed the roles of technological progress factors in improving energy efficiency. [ABSTRACT FROM AUTHOR]

This paper builds an input-output model to analyze the energy and economic impacts of the 4.7 trillion-CNY investment projects of the " Three-Year Action Plan for Major Construction Projects of Transportation Infrastructure ", which was launched by the Chinese government in 2016. The results show that, from 2016 to 2018, the investment plan could increase China's GDP by 2.39%, 1.30%, and 1.24%, respectively, and the country's energy consumption by 3.98%, 2.35%, and 2.40%, respectively. The top five production sectors could contribute 55% of the GDP growth induced by the plan, and the top three sectors could contribute 83% of the energy consumption growth, indicating that the impact of the investment plan centers mainly on a limited number of sectors. From the view of supply chains, the 20 paths with the largest GDP contribution cover approximately 47% of the GDP growth induced by the plan, and the 20 paths that consume the most energy cover approximately 32% of the energy consumption growth. In these paths, the construction industry is the dominant demand sector, whereas the industry of nonmetallic mineral products, the industry of production and supply of electricity and steam, and the industry of smelting and pressing of metals are the primary supply sectors. In the future, the Chinese government should pay more attention to indirect energy consumption related to the construction industry, and policymakers will also need to set up more effective energy conservation policies for the upstream sectors of the construction industry, such as the sectors providing cement, glass, and steel. • Estimate the energy and economic impacts of China's three-year investment plan for transportation infrastructure. • Identify critical supply chains for the energy consumption and economic changes induced by the investment plan. • Propose several policy recommendations on reducing energy consumption in the construction industry. [ABSTRACT FROM AUTHOR]

The industrial sector in China is energy-intensive and accounts for more than 60% of the nation's total energy consumption (demand). Narrating the story behind the growth of China's industrial energy consumption could help us understand the past and prepare for the future. This paper aims to investigate the factors affecting China's industrial energy consumption in the 21st century by using an extended production-theoretical decomposition approach (PDA) with considering the technological gap and scale of the economy effects. The new proposed decomposition framework includes four new factors, namely, the energy technological gap, the output technological gap, energy scale efficiency, and output scale efficiency. The results show that in the 21st century, the energy consumption of China's industry increased by more than one billion tons of standard coal. The expansion of the industrial economy is a dominant driver of China's industrial energy consumption, while potential energy intensity, energy technology, and output technology are the three largest energy-saving factors. In addition to the conventional factors, the newly proposed factors also have important effects on China's industrial energy consumption. Specifically, output scale efficiency is an energy-saving factor, while the energy technological gap, output technological gap, and energy scale efficiency are drivers of energy consumption. This suggests that China's industry is at the stage of returns to scale that is beneficial to output performance but harmful to energy performance. Meanwhile, the widening of the industrial technological gaps has negative impacts on China's industrial energy conservation. The proposed decomposition approach can provide information that cannot be obtained from traditional approaches and it can also be applied to many other cases for investigating feasible paths of energy-saving and emissions reduction. • A newly extended decomposition approach was proposed in this study. • The approach can quantify the effects of technological gap and scale economy. • Drivers of China's industrial energy consumption were investigated as a case. • The newly provided factors do have impacts on China's industrial consumptions. • It can provide information that cannot be obtained from traditional approaches. [ABSTRACT FROM AUTHOR]

China's urbanization is rapidly proceeding while bringing marked impact on the energy consumption. This paper contributes to current literature by using an improved spatial econometric model Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) to investigate the effect of urbanization on energy consumption for China's regions. The impact of urbanization is further disaggregated into direct and indirect impacts from the perspective of spatial econometrics. Results show that, if the urbanization level increases by 1.0%, energy consumption levels will correspondingly decrease by 0.089%. The spatial spillover effect on adjacent areas is positive: a 1.0% increase in one specific area's urbanization level leads to a 0.136% increase in an adjacent area's energy consumption. It is suggested that, it is essential to devote major efforts to energy conservation, in the process of improving the new-type urbanization. In particular, disaggregating China's targets for controlling energy consumption into smaller targets for different regions will contribute to controlling the growth of energy consumption. [ABSTRACT FROM AUTHOR]