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Chufu Mou

Bio: Chufu Mou is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Clinker (cement) & Climate change. The author has an hindex of 3, co-authored 5 publications receiving 50 citations.

Papers
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Journal ArticleDOI
TL;DR: In this article, the authors explored the differences of the integrated value of shale gas development between the US and China and analyzed the reasons for these differences, including market demand, cost and price, technologies, gas content, water contamination/supply, and policy.
Abstract: This paper is to explore the differences of the integrated value of shale gas development between the US and China. On the basis of an extensive literature survey and 17 in-depth personal interviewswith domestic experts, a fuzzy-AHP model is exploited herein to evaluate the development of shale gas in the US and China. The fuzzy-AHP model encompasses 21 indicators, which can be further categorized into 4 critical factors: (1) market prospects, (2) environmental impacts, (3) conditions of resource & occurrence, and (4) general conditions of extraction & utilization. Among the 21 indicators, market demand, cost and price, technologies, gas content, water contamination/supply, and policy contribute significantly to the integrated value of the model. According to the integrated value of the shale gas development in the US and China, the comparative analysis suggests that there is a large gap between these two countries. Furthermore, differences in shale gas development between the US and China are identified and reasons for these differences are analyzed. The US-China comparative analysis and the experience from US suggest that government policies will be crucial to determine the future development of shale gas in China and other countries.

35 citations

Journal ArticleDOI
TL;DR: In this article, a bottom-up spatial-integration system was proposed to estimate the CO2 emissions from clinker and cement production at factory level, and a discrepancy was identified between the clinker emission factors relevant to the two main production processes (i.e., the new suspension preheating and pre-calcining kiln and the vertical shaft kiln).
Abstract: Much attention is being given to estimating cement-related CO2 emissions in China. However, scant explicit and systematical exploration is being done on regional and national CO2 emission volumes. The aim of this work is therefore to provide an improved bottom-up spatial-integration system, relevant to CO2 emissions at factory level, to allow a more accurate estimation of the CO2 emissions from cement production. Based on this system, the sampling data of cement production lines were integrated as regional- and national-level information. The integration results showed that each ton of clinker produced 883 kg CO2, of which the process, fuel, and electricity emissions accounted for 58.70%, 35.97%, and 5.33%, respectively. The volume of CO2 emissions from clinker and cement production reached 1202 Mt and 1284 Mt, respectively, in 2013. A discrepancy was identified between the clinker emission factors relevant to the two main production processes (i.e., the new suspension preheating and pre-calcining kiln (NSP) and the vertical shaft kiln (VSK)), probably relevant to the energy efficiency of the two technologies. An analysis of the spatial characteristics indicated that the spatial distribution of the clinker emission factors mainly corresponded to that of the NSP process. The discrepancy of spatial pattern largely complied with the economic and population distribution pattern of China. The study could fill the knowledge gaps and provide role players with a useful spatial integration system that should facilitate the accurate estimation of carbon and corresponding regional mitigation strategies in China.

17 citations

Journal ArticleDOI
15 Mar 2017-Energies
TL;DR: In this paper, the authors analyzed the key determinant factors on energy-related CO2 emissions growth rates around the world and in eight types of regions, including the Middle East, Africa, Europe, Asia and the Americas.
Abstract: Understanding the spatial heterogeneity and driving force identification of energy-related CO2 emissions (ECEs) can help build consensus for mitigating CO2 emissions and designing appropriate policies. However, previous studies on ECEs that focus on both the global-regional scale and the interaction of factors have been seldom conducted. In this paper, ECE data from 143 countries from 1990 to 2014 were selected to analyze regional differences in ECE growth rates by using the coefficient of variation. Then a geographical detector was used to analyze the key determinant factors on ECE growth rates around the world and in eight types of regions. The results show that: (1) the ECE growth rate in the Organization for Economic Cooperation and Development (OECD) region is low and tended to decrease, while in the non-OECD region it is high and tended to increase; (2) the coefficient of variation and detection factor of ECE growth rates at a regional scale are higher than those at a global scale; (3) in terms of the key determinant factors, population growth rate, growth rate of per capita GDP, and energy intensity growth rate are the three key determinant factors of ECE growth rates in the OECD region and most of the non-OECD regions such as non-OECD European and Eurasian (NO-EE), Asia (NO-AS), non-OECD Americas (NO-AM). The key determinant factors in the African (NO-AF) region are population growth rates and natural gas carbon intensity growth rates. The key determinant factors of the Middle East (NO-ME) are population growth rate, coal carbon intensity growth rate and per capita GDP growth rate; (4) the determinant power of the detection factor, the population growth rate at the global scale and regional scale is the strongest, showing a significant spatial consistency. The determinant power of per capita GDP growth rate and energy intensity growth rate in the OECD region, respectively, rank second and third, also showing a spatial consistency. However, the carbon intensity growth rates of the three fossil fuels contribute little to the growth rate of ECEs, and their spatial coherence is weak; (5) from the perspective of the interaction of detection factors, six detection factors showed bilinear or non-linear enhancement at a global and a regional scale, and the determinant power of the interaction of factors was significantly enhanced; and (6) from the perspective of ecological detection, the growth rate of carbon intensity and the growth rate of natural gas carbon intensity at the global scale and NO-ME region are significantly stronger than other factors, with a significant difference in the spatial distribution of its incidence. Therefore, the OECD region should continue to reduce the growth of energy intensity, and develop alternative energy resources in the future, while those that are plagued by carbon emissions in non-OECD regions should pay more attention to the positive influence of lower population growth rates on reducing the growth rate of energy-related CO2 emissions. Reducing energy intensity growth rates and reducing, fossil energy consumption carbon intensity.

11 citations

Journal ArticleDOI
TL;DR: In this article, the effects of price changes in the nonferrous metal industry chain on economic development in Yunnan province, China were analyzed using a static computable general equilibrium model with a looping algorithm.

6 citations

Journal ArticleDOI
TL;DR: In this paper, the authors constructed an evaluation model that analyzed the factors of hard power, soft power, and climate change on geopolitical influence, and used factor analysis to calculate the geopolitical influence of 30 countries accounting for the impact of climate change influence.
Abstract: Based on domestic and international research on geopolitical influence, this study constructed an evaluation model that analyzed the factors of hard power, soft power, and climate change on geopolitical influence. After selecting indexes for each of these elements, a Factor Analysis was used to calculate the geopolitical influence of 30 countries, accounting for the impact of climate change influence. The results showed: 1. Climate change has an impact on the shifting landscape of geopolitical influence, but shifts in global power can still be largely related to preexisting factors of influence. 2. There are obvious differences in the degrees of influence among the 30 surveyed countries, and these differences can be divided into four levels. 3. Members in the three climate negotiating groups also have their own hierarchies of influence; for instance, EU countries have three distinct levels, and members in the Umbrella Group vary greatly, as does their stance on climate change. This is even more true for states that are members of the G77 and China group.

3 citations


Cited by
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Journal ArticleDOI
TL;DR: In this paper, a review of the shale gas transport process during shale gas production is presented, and the corresponding multi-scale simulation models that describe the gas multiscale transport mechanisms and accurately predict the amount of shale production are explained.

137 citations

Journal ArticleDOI
TL;DR: In this article, a review of the recent advances of molecular simulation on gas adsorption/desorption and diffusion in the shale matrix is reviewed and further developments of the molecular simulation method in shale gas production are also discussed.
Abstract: Shale gas is becoming an increasingly promising alternative energy resource because of its high efficiency and environment-friendly characteristic. The amount of adsorbed gas on the shale matrix surfaces and dissolved gas in the shale matrix bulk is the dominant factor in the long-term productivity of shale reservoir. Although experimental measurements have been extensively carried out to investigate the gas adsorption and diffusion properties in the shale matrix, they cannot provide the detailed information on the microscopic transport mechanism of shale gas during the gas production process. Molecular simulation can accurately visualize the gas adsorption/desorption and diffusion processes in the shale matrix. In the present study, the recent research advances of molecular simulation on gas adsorption/desorption and diffusion in the shale matrix are reviewed. Firstly, the density functional theory (DFT) for shale gas molecule desorption/adsorption on the surface of the matrix crystal is illustrated. Then, the grand canonical Monte Carlo (GCMC) method predicting the amount of shale gas desorption/adsorption in the shale matrix crystal is introduced. Finally, molecular dynamics simulation (MD) for gas diffusion in the shale matrix is elucidated. Further developments of the molecular simulation method in shale gas production are also discussed.

95 citations

Journal ArticleDOI
TL;DR: Wang et al. as mentioned in this paper developed an interval grey number-based approach to calculate the relative uncertainty and presented a forecast for the Chinese cement industry CO2 emissions using a novel grey prediction model.
Abstract: The cement industry is a significant contributor to anthropogenic CO2. For China, the cement industry is crucial for development, considering the surging urbanization. CO2 emissions from the industry are detrimental to the planet, its ecosystem, and inhabitants. Forecasting of the emissions is a critical step in the emissions' mitigation strategies, and to achieve sustainable development. However, the level of uncertainty accompanying CO2 estimates leads to discrepancies in predictions. The current work aims to study the estimation of cement industry CO2 emissions from an uncertainty-driven technical perspective, and present a forecast for the Chinese cement industry emissions using a novel grey prediction model. By modeling the framework of China's cement industry and the CO2 emissions estimation techniques as grey systems with partially known information, this study develops an interval grey number-based approach to calculate the relative uncertainty. A grey sequence is generated from the whitenization of the interval grey numbers to represent annual emissions from different sources. The proposed approach is more flexible than the conventional midpoint estimate-based approach recommended by JCGM. The proposed model, V-GM(1,N), is found to give the highest accuracy of 97.29% in simulating the actual cement industry CO2 emissions data from 2005 to 2018. Comparative analysis of the proposed model with other forecasting models revealed the superiority of the model. The proposed framework, involving the forecasting model and uncertainty analysis approach, is likely to facilitate the decision-makers in making realistic and reliable forecasts at reasonable computational costs.

83 citations

Journal ArticleDOI
TL;DR: As the typical unconventional reservoir, shale gas is believed to be the most promising alternative for the conventional resources in future energy patterns, attracting more and more attention from the energy industry as discussed by the authors.
Abstract: As the typical unconventional reservoir, shale gas is believed to be the most promising alternative for the conventional resources in future energy patterns, attracting more and more attention thro...

83 citations