Search

Abstract The emergence of Shanghai as an international city necessitate that the industrial sector should be less polluting as much as possible because pollution will alienate businesses, professionals and the relocation or setting up of corporate offices that enhances green economic growth. To ensure that policy targeting industrial emissions are achieved, standard mean based models underperforms, so exploring a quantile framework, varying effects of economic development, energy structure, energy efficiency, industrial structure and urbanization across the levels of carbon dioxide emissions were analyzed for the industrial sector of Shanghai where estimates both described the distribution of carbon dioxide emissions and their marginal effects on different quantiles. Explanatory variables were emission friendly and did not exert same effects on the acceleration of carbon emissions. Averagely, the coefficient of GDP, ENS, ENE, IND, and URB at Q(0.50) = 0.06306, 0.39285, 0.07375, 0.52193 and 0.48357 respectively, implying that a unit increase in these economic indicators will increase carbon dioxide emissions by 6.3, 39.3, 7.3, 52.2 and 48.4 percent approximately and the model goodness of fit was 87.8 percent. Urbanization had the greatest impact on carbon dioxide emissions across all quantiles, showing that it is a major driving force that increase carbon emissions, followed by energy structure, industrial structure, economic growth and energy efficiency. An optimized energy efficiency will be the best mitigating variable that could curb carbon dioxide emissions, then followed by energy structure. Favorable economic policies from the government have contributed enormously to the development of the industrial sector, however, additional policies are needed to steer the city from an investment and export growth model to consumption (services). [ABSTRACT FROM AUTHOR]

China is at the stage of industrialization and urbanization and because the energy demand and consumption for this process is rigid, coupled with emissions and global warming awareness, China is on a path to cut back emissions as she focuses on alternative and sustainable way to green the economy. This research investigates determining factors in measuring the dynamic changes in green development growth index (GDGI) over a given time frame. By adopting a non-radial directional distance function (NDDF), where more pollutants are added like sulphur dioxide emissions, solid wastes, waste water, and carbon dioxide emissions instead of using only one pollutant in measurement and using a global distance envelop analysis (DEA) to model green performance by considering both desirable and undesirable outputs, the model was decomposed into efficiency change (EC) index, best practice gap change (BPC) index, and technology gap change (TCG) index and these three indexes were employed to measure the green development performance in thirty provinces across china from 2000 to 2012. Results showed that provinces in the eastern region of China are greener than the central and western regions. Analyzing all three calculated dependent variables from a quantile perspective revealed that effects of EC, BPC, and TGC varied across different quantiles of GDGI. The coefficients of BPC were more significant than EC across quantiles, and TGC coefficients only became significant from Q(0.35), and continued on this path until the last observed quantile Q(0.95) however it was less than EC in terms of significance. The values of pseudo R 2 also continued to increase from Q(0.20) until the last observed quantile with 86% accuracy in prediction recorded at Q(0.95). Analyzing the 80th percentile revealed that the coefficient of BPC was highest in this percentile which implies that a unit increase in best practice gap change, will influence green development growth by 102.3 percent, and a unit increase in efficiency change, will accelerate green development growth by 99.41 percent while a unit increase in technical gap ratio change will produce 99.38 percent increase in green development growth of China. [ABSTRACT FROM AUTHOR]

This research examines the impact of GDP per capita (gross domestic product), energy intensity (EI), carbon intensity (CI), and total population on carbon dioxide emissions in China's transport industry using quantile analysis from 1980 to 2010. Obviously the study on carbon dioxide has garnered attention globally due to climate change and its relation to green house gas emissions and several other factors, and considering the alarming pace of industrialization and urbanization in China which has led to rapid economic growth and high energy consumption. Also, the percentage of oil consumption to total oil demand in the transport industry of China was 38.2% for the year 2010 which has significantly raised the emission level of carbon dioxide. In this study, having confirmed stationarity and that there exist a long term relationship among our variables (carbon emission, gross domestic product, energy intensity, carbon intensity, and urbanization), we checked which variable(s) has a greater impact on carbon emission on different quantiles. Our quantile estimates showed how the effects of the independent variables (gross domestic product, energy intensity, carbon intensity, and urbanization) varies across the levels of the dependent variable (carbon emission), the results showed that these effect are not constant across the spectrum of the dependent variable. Unlike the gross domestic product, energy intensity, carbon intensity, and urbanization had an inconsistent effects across the spectrum of carbon emissions. All variables were statistically significant in all the spectrum of carbon emissions except for urbanization, which was only significant at the tail ends of the distribution (urbanization was only significant at 10th percentile and 90th percentile respectively). The results therefore shows clearly that GDP, energy intensity, carbon intensity has a greater impact on carbon emission than urbanization, this makes sense to an extent in real life comparing the fact that China is still in the process of urbanization, so not all cities are urban for now. However, this shows that where urbanization exist, it can influence carbon emissions alongside other factors immensely. [ABSTRACT FROM AUTHOR]

An understanding of how storage technologies coordinate with other power resources to deliver value for electricity market participants in compliance with climate policy will be vital as policy makers seek to decarbonize electricity generation in a cost-effective way. This paper adopts a game-theoretic electricity market model to evaluate the interaction between pumped hydro storage, electric vehicles, and climate policy under a range of assumptions regarding market power and ownership of generation and storage assets. Using data from the Chinese electricity market, it shows that climate policy may not incentivize storage utilization especially when firms that hold a dominant position in storage operation own a limited portfolio of generation assets. In addition, electric vehicles may not improve consumers' welfare in the presence of pumped hydro storage when perfect competition exists in the market. These results have significant implications for public policy. • A game-theoretic electricity market model is evaluated for China. • The interaction between storage, electric vehicles, and climate policy is studied. • Climate policy may not incentivize storage use depending on the ownership of assets. • The benefits of electric vehicles decline in the presence of pumped hydro storage. • Perfect competition may not always create the best choices for consumers. [ABSTRACT FROM AUTHOR]

Chinese nonmetallic mineral products industry is one of the largest electricity consumer in China and has a large impact on overall electricity consumption in China. This paper examines the impact of economic variables on the demand for electricity in Chinese nonmetallic mineral products industry where economic growth, sectoral value added per worker, sectoral R&D intensity, and energy price were utilized to analyze sectoral electricity consumption, with an application of quantile model. The paper's estimates unveiled the varying effects of economic variables across the spectrum of sectoral electricity consumption where the coefficient of economic growth was positive and significant across all quantiles, while sectoral value-added per worker had both positive and negative significant coefficients. An increase in income level and sectoral value added per worker will increase the electricity consumed by the industry, however, the latter will also enhance a decreasing trend in few regions across China and did not influence high energy efficiency but rather enhanced the production of additional outputs, while sectoral R&D intensity and energy price will ensure a substantial decrease in sectoral electricity consumption with the latter having a greater impact. Increase in investment for sectoral R&D intensity will boost technological advancement and is recommended as a cornerstone to ensuring decline in sectoral energy consumption that will buttress sectoral value added per worker coupled with a robust energy price. [ABSTRACT FROM AUTHOR]

The metallurgy industry that was crucial in developing Chinese economy also enhanced energy consumption and carbon emissions. This paper examines the impact of economic variables on carbon emissions from the metallurgy industry of China, where energy structure, energy intensity, carbon intensity, industrial structure, and labor productivity were utilized in analyzing carbon dioxide emissions within a quantile models framework. Quantile estimates unveiled varying effects of variables across spectrum of carbon emissions and averagely, a unit increase in the above economic variables will influence carbon emissions by 97.2 percent, 100.3 percent, 118.6 percent, 98.4 percent and 100.2 percent approximately. Across all quantiles, results showed that carbon intensity had the greatest impact on carbon dioxide emissions, then energy intensity, labor productivity, industrial structure, and energy structure, most but not all the industry was plagued by carbon intensity, while industrial scale should be minimized optimally, labor productivity should be improved too. Energy intensity is the most influencing factor, prompting an urgent need for technology advancement The uniqueness of the metallurgy industry must be considered when administering economic policies across the industry in China. The enhancement of clean energy technology and optimizing energy structure are crucial for carbon emissions reduction and a review of energy consumption by the industry to accommodate renewable energy is recommended. [ABSTRACT FROM AUTHOR]