Search

Because China has emerged as the largest greenhouse gas (GHG) emitter in total annual emissions, to accelerate the pace of GHG emission reduction in China is important to the success of global efforts in addressing climate change. Carbon trading is a market mechanism and key instrument in the mitigation of climate change. This paper explores the policy process and development state to date of China׳s carbon-trade market to understand the emergence and development of that market and to understand what barriers are hampering China׳s carbon-trade market development. To achieve this goal, this paper introduces and analyzes China׳s status in the international market, examines the factors driving carbon-market launching by the Chinese government, and traces the development of mandatory carbon-emission trading and voluntary emission trading. It is argued that China׳s carbon-trading market is confronted with challenges such as the absence of a functional carbon-trading market, inaccuracy of the quota allocation, an imperfect trading mechanism, and lagging legislation. At the present stage, shortcomings such as having no real-time carbon price and dominated spot transactions differentiate China׳s trade market substantially from a functional system. A quick market integration of China׳s carbon market appears remote. It is suggested that specific measures be taken to promote the development of the Chinese carbon-trading market. [ABSTRACT FROM AUTHOR]

Latent heat thermal energy storage technologies based on phase change materials (PCMs) are found to be significantly efficient and viable methods for thermal energy storage. These energy storage techniques have been proved to be with positive effects on buildings energy efficiency. The integration of appropriate thermal energy storage system and selection of suitable PCMs plays a very dominating role in the upgrading of energy efficiency. Short and long term storage helps in the reduction of energy demand or shifting peak load for both heating and cooling. However, a comprehensive study for the application of these technologies adopting Chinese built environment is lacking which can relate to climate, energy storage and energy efficiency. The goal of this paper is to provide coherent picture of current status on PCM-based techniques that have been studied with the focus of application in China and analyse the selection and suitability of PCMs and techniques in Chinese regions. The results show that many PCMs and techniques are promising to be used in China however studies can be conducted with the consideration of changing climate rather than winter/summer only. [ABSTRACT FROM AUTHOR]

This paper systematically presents a survey of the empirical literature studying the embodied CO 2 emissions in China’s foreign trade (ECCT). Based on the bibliometric method and the online version of Science Citation Index-Expanded (SCI-E) and Social Sciences Citation Index (SSCI), this study summarizes the latest publications regarding ECCT in peer-reviewed journals in terms of quantities, most productive countries, institutions, authors, citations, and disciplines. By using synthetic analysis of keyword frequency, this study reveals the most popular methodologies applied in measuring ECCT, discusses the variation of numerical results in the literature, and reasons and countermeasures for the results uncertainties. Continuous investigation of the literature releases the methodology employed for measuring ECCT becoming more reasonable and the results more critical. However, the numerical results of ECCT are of great discrepancies within given year by different considerations on methodology specification, accounting principles, and data sources and processing. For instance, the estimates of CO 2 embodied in China’s exports changed from 478 Mt to over 3000 Mt and those of in China’s imports ranged from 140 Mt to over 1700 Mt in 2007. Therefore, overcoming data inherent limitations and reducing discrepancies among available databases should be urgently considered. The results imply that the prospective research tendencies on ECCT are to (1) improve China’s regional input-output data and energy intensity data to more precise estimates under global perspective; (2) estimate China’s carbon emission at firm level by different firm ownerships in production and consumption worldwide; (3) assess China’s carbon emission from processing or non-processing trade by compiling more detailed multi-regional input-output table; (4) evaluate city level carbon mitigation capacity in China under global MRIO model; (5) explore new carbon management experience in China’s carbon trading market and new trade expansion policy of ‘ one belt and one road’ in her new growth era. [ABSTRACT FROM AUTHOR]

In order to mitigate global climate change and air pollution, the Chinese government has assigned high priority to expanding low-carbon power generation in China. Recent studies have shown that wind power is one of the most promising renewable energy option in China. Although many studies have estimated the generation potential of onshore wind power, their results vary widely from 1783 TWh to 39,000 TWh. Therefore, we examine the different assumptions in these papers and identify three main factors influencing the results. The three influencing factors are: weather data set, land utilisation factor, and wind turbine configuration. For our model-based analysis, we define a reference scenario which is used to compare the results. Our analysis shows using a different weather data set increases the generation potential to roughly 35,000 TWh. This is 54% higher than the generation potential of the reference scenario. The land utilisation factor also has a large influence, ranging between −10% and −51%. The studies' assumptions and data should be subjected to careful scrutiny, as the calculated wind power potentials are widely used to develop decarbonisation strategies for the energy system. • Study results on wind power potentials in China vary from 1783 TWh to 39,000 TWh • Influencing factors: weather data set, land utilisation, and wind turbine configuration. • Model-based sensitivity analysis with nine scenario settings. • Chosen weather data set has the highest impact on the calculated results with a variation of 54%. [ABSTRACT FROM AUTHOR]