The Conundrums of Sustainability: Carbon Emissions and Electricity Consumption in the Electronics and Petrochemical Industries in Taiwan

The electronics industry plays an essential role in the future of a Taiwan economy based on science, technology, and innovation. At the same time, it is also the most energy-intensive industry. Taiwan is currently driven by high-carbon power generation, and adopts a passive carbon reduction pathway, but unless Taiwan urgently undergoes energy transition, the development of Taiwan’s electronics industry will be impeded. Our analysis found that the petrochemical and electronics industries are the main sources of carbon emissions (27.1%) and electricity consumption (31.6%) in Taiwan, and the existence of the petrochemical industry has constrained the growth of the electronics industry, which has therefore resulted in conundrums to Taiwan’s sustainability strategy. To accommodate the growth of the electronics industry, Taiwan needs to undertake three major transitions: energy transition, industrial transition, and restrain the growth of energy (energy conservation). Under the policy of the nuclear-free homeland, the reduction of coal-fired and thermal power generation, while at the same time increasing the share of renewable energy in power generation, are urgent and important government projects in Taiwan; however, the implementation has been sluggish.

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Driving Factor Analysis of Carbon Emissions in China’s Power Sector for Low-Carbon Economy

Mathematical Problems in Engineering ◽

10.1155/2017/4954217 ◽

2017 ◽

Vol 2017 ◽

pp. 1-10 ◽

Cited By ~ 5

Author(s):

Dan Yan ◽

Yalin Lei ◽

Li Li

Keyword(s):

Power Generation ◽

Carbon Emissions ◽

Electricity Consumption ◽

Least Squares Regression ◽

Low Carbon ◽

Power Sector ◽

Stirpat Model ◽

Coal Consumption ◽

Low Carbon Economy ◽

Generation Structure

The largest percentage of China’s total coal consumption is used for coal-fired power generation, which has resulted in the power sector becoming China’s largest carbon emissions emitter. Most of the previous studies concerning the driving factors of carbon emissions changes lacked considerations of different socioeconomic factors. This study examines the impacts of eight factors from different aspects on carbon emissions within power sector from 1981 to 2013 by using the extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model; in addition, the regression coefficients are effectively determined by a partial least squares regression (PLS) method. The empirical results show that (1) the degree of influence of various factors from strong to weak is urbanization level (UL) > technology level (T1) > population (P) > GDP per capita (A) > line loss (T2) > power generation structure (T3) > energy intensity (T4) > industry structure (IS); (2) economic activity is no longer the most important contributing factor; the strong correlation between electricity consumption and economic growth is weakening; and (3) the coal consumption rate of power generation had the most obvious inhibitory effect, indicating that technological progress is still a vital means of achieving emissions reductions.

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Low-Carbon Innovation, Economic Growth and CO2 Emissions: Evidence From a Dynamic Spatial Panel Approach in China

10.21203/rs.3.rs-999793/v1 ◽

2021 ◽

Author(s):

Caijiang Zhang ◽

Yu Zhou ◽

Zhangwen Li

Keyword(s):

Carbon Emissions ◽

Energy Transition ◽

Spillover Effects ◽

Policy Implications ◽

Kuznets Curve ◽

Low Carbon ◽

Carbon Reduction ◽

Long Run ◽

Short Run ◽

High Emission

Abstract Low-carbon innovation plays an essential role in carbon reduction worldwide. This study investigates how low-carbon innovation affects carbon emissions by the Dynamic Spatial Durbin Model based on 30 Chinese provinces from 2007 to 2017. The empirical results show that: First, there exists provincial agglomeration of carbon emissions. High emission provinces concentrate in major economic zones and energy extraction areas. Second, low-carbon innovation decreases carbon emissions in general. The spillover effects are higher than the direct effects in the short run, but the spillover effects are not significant in the long run. Third, the environmental Kuznets curve (EKC) hypothesis is valid both in the short-run and long-run. Ninety percent of the provinces' GDP is above the inflection point by 2017. The summary of policy implications is as follows. First, targeted incentives for R&D in low-carbon technologies are needed; Second, the externalities of low-carbon innovation require attention; Third, energy transition need to be promoted as soon as possible.

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China's coal use will grow despite energy transition

Emerald Expert Briefings ◽

10.1108/oxan-db227526 ◽

2017 ◽

Keyword(s):

Economic Growth ◽

Power Generation ◽

Natural Gas ◽

Electricity Consumption ◽

Energy Transition ◽

Northern China ◽

Liquefied Natural Gas ◽

Content Type ◽

The North ◽

Chinese Coal

Subject The outlook for China's power generation sector. Significance Electricity consumption in the first ten months of the year rose by 6.7% year-on-year, up from a 5.0% increase in 2016, suggesting that China's electricity consumption will grow at the fastest rate this year since 2013. Impacts Coal-to-gas-switching in northern China introduces a seasonal element of new demand to the global liquefied natural gas (LNG) market. China is likely to build new LNG import capacity in the north or reconsider a second major Russian gas pipeline, the Altai project. Despite the coal-to-gas switching, stronger economic growth will see Chinese coal use and greenhouse gas emissions rise.

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Multi-Footprint Constrained Energy Sector Planning

Energies ◽

10.3390/en12122329 ◽

2019 ◽

Vol 12 (12) ◽

pp. 2329 ◽

Cited By ~ 3

Author(s):

Jui-Yuan Lee ◽

Han-Fu Lin

Keyword(s):

Power Generation ◽

Carbon Emissions ◽

Carbon Capture ◽

Environmental Control ◽

Programming Model ◽

Thermal Power ◽

International Energy Agency ◽

Energy Sector ◽

Recent Analysis ◽

Trade Offs

Fossil fuels have been heavily exploited since the Industrial Revolution. The resulting carbon emissions are widely regarded as being the main cause of global warming and climate change. Key mitigation technologies for reducing carbon emissions include carbon capture and storage (CCS) and renewables. According to recent analysis of the International Energy Agency, renewables and CCS will contribute more than 50% of the cumulative emissions reductions by 2050. This paper presents a new mathematical programming model for multi-footprint energy sector planning with CCS and renewables deployment. The model is generic and considers a variety of carbon capture (CC) options for the retrofit of individual thermal power generation units. For comprehensive planning, the Integrated Environmental Control Model is employed in this work to assess the performance and costs of different types of power generation units before and after CC retrofits. A case study of Taiwan’s energy sector is presented to demonstrate the use of the proposed model for complex decision-making and cost trade-offs in the deployment of CC technologies and additional low-carbon energy sources. Different scenarios are analysed, and the results are compared to identify the optimal strategy for the energy mix to satisfy the electricity demand and the various planning constraints.

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Energy Cost Performance of Thermal Power Industry in China Considering Regional Heterogeneity: A Meta-Frontier Cost Malmquist Productivity Decomposition Approach

Sustainability ◽

10.3390/su13126823 ◽

2021 ◽

Vol 13 (12) ◽

pp. 6823

Author(s):

Zhigang Zhu ◽

Xuping Zhang ◽

Yujia Wang ◽

Xiang Chen

Keyword(s):

Power Generation ◽

Carbon Emissions ◽

Energy Cost ◽

Thermal Power ◽

Power Industry ◽

Economic Benefits ◽

Eastern Region ◽

Regional Heterogeneity ◽

Decomposition Approach ◽

Thermal Power Generation

Since thermal power generation is still one of the main sources of carbon emissions in China, the economic benefits and productivity of the thermal power generation industry have been seriously affected in recent years with the increasingly strict environmental regulations and restrictions on carbon emissions, as well as by the sharp fluctuations of coal prices. Therefore, it has been an important issue to improve the productivity performance of the thermal power industry. Due to the regional heterogeneity among different regions of China, we introduced a meta-frontier framework into the energy cost productivity model to develop a meta-energy cost productivity model. The energy cost gap between the group-specific and meta-frontiers was also utilized to assess the convergence rate of the group-specific frontier to the meta-frontier. The estimated results present that the energy cost efficiency of the eastern region outperformed that of the other two regions, and the cost Malmquist (CM) productivity of these three regions all showed positive growth, in which the progress of allocative efficiency and price effect were the main driving factors. Additionally, the central and western regions displayed the convergence of group-specific CM productivity towards the meta-frontier.

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Research on carbon emission potential of electric vehicles and fuel vehicles

E3S Web of Conferences ◽

10.1051/e3sconf/202123601025 ◽

2021 ◽

Vol 236 ◽

pp. 01025

Author(s):

Qiang Zhou ◽

Wanfu Liu ◽

Wuqin Qi

Keyword(s):

Power Generation ◽

Electric Vehicles ◽

Carbon Emissions ◽

Emission Reduction ◽

Carbon Emission ◽

Reduction Potential ◽

Energy Structure ◽

Carbon Reduction ◽

Generation Structure ◽

Coal Power

Electric vehicles are considered as a effective tool for energy conservation and emission reduction, Because of its zero direct carbon emissions. However, thermal power generation accounts for a large proportion in China's power generation structure, so the indirect carbon emissions of electric vehicles must be considered. In order to further study the carbon emission potential of electric vehicles compared with traditional fuel vehicles, the direct carbon emission of fuel vehicles and the indirect carbon emission of battery electric vehicles were calculated. The results show that the carbon reduction effect of electric vehicles is obvious, and the coal power technology and the energy structure of power generation have great influence on the carbon reduction potential of electric vehicles. Based on this, suggestions are put forward to promote electric vehicles and fully release their emission reduction potential from the aspects of enhancing consumers' perception of social value, improving energy structure and improving coal power technology.

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Matrix-Based Model of the Carbon Footprint Analysis for Thermal Power Generation in China

Materials Science Forum ◽

10.4028/www.scientific.net/msf.685.230 ◽

2011 ◽

Vol 685 ◽

pp. 230-238 ◽

Cited By ~ 3

Author(s):

Bo Xue Sun ◽

Xian Zheng Gong ◽

Yu Liu ◽

Wen Juan Chen ◽

Zhi Hong Wang

Keyword(s):

Power Generation ◽

Carbon Footprint ◽

Carbon Emissions ◽

Interaction Effect ◽

Electricity Generation ◽

Thermal Power ◽

Calculation Model ◽

Major Work ◽

Footprint Analysis ◽

Thermal Power Generation

With the increasing seriousness of climate change problem, carbon footprint has become a very useful method to measure carbon emissions and has been widely accepted. In modern industry, electricity is almost consumed in all industry processes, and electricity is the first "footprint" of most products. As carbon emissions is always measured by theoretical estimation from input inventory but not experimental data, the input inventory of electricity generation becomes very important in carbon footprint analysis. Electricity generation is a very complex process, where all input items inter-dependant on each other and the whole system is an infinite cycle net. But in the traditional calculation model of input inventory, the interaction effect of production system is usually neglected. The major work of this study is to make clear the carbon emissions of provision 1kWh thermal power generation to consumers in China in 2006, since thermal power generation takes the most proportion of Chinese electricity. This study used a matrix-based model which includes interaction effect of the system to calculate the input inventory of electricity generation, and then the carbon emissions of thermal electricity generation in China in 2006 can be calculated. The final result of this paper can be used in carbon footprint, Life Cycle Assessment or some other related fields.

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