High Energy-intensive Industries Research Articles

A dataset of high energy-consuming industrial products in the ASEAN during 2012–2021

The uneven energy distribution and economic development levels of the countries in the ASEAN region have led to the uncoordinated distribution of high-energy-consuming industries in the region. It is extremely important to timely obtain the spatial distribution pattern of high energy-intensive industries. In this paper, on the basis of the 375m high spatial and temporal resolution NPP-VIIRS active fire point data and vector data density segmentation algorithms, we produced a dataset of high energy-consuming industrial products in the ASEAN during 2012–2021. This dataset covers valuable information, such as latitude and longitude of industrial heat sources data, administrative region to which they belong, and the year of operation start and end, etc. It can provide scientific data support for energy distribution and economic development in the region, as well as decision-making support for its cooperation with China for further development.

Potential integration of Chinese and European emissions trading market: welfare distribution analysis

Central to the aims of the Paris Agreement, an integrated carbon market could potentially be a practical bottom-up option for effective and efficient mitigation. This paper quantifies the welfare effects of integration of Emission Trading Scheme (ETS) between the European Union (EU) and China. Using the European version of the computable general equilibrium model GEMINI-E3, our assessment reveals that integrating trading markets benefits both regions through the decrease welfare costs from abatements. China’s welfare improves through net gain of selling the allowance, while the EU experiences lower deadweight loss. This effect is stronger to some notable countries in the EU, with high energy-intensive industries such as Poland and the Czech Republic. While a few others, such as Netherlands and Ireland, face higher welfare costs from negative trade gain. Limiting the trade quotas to 40% captures most of the EU welfare gain coming from CO2 trading. Further analysis at the sectoral level reveals that market integration significantly minimizes the loss of competitiveness of European energy-intensive industries and reduces international leakage. Our finding thus confirms the potential of the emissions trading market as an effective instrument to facilitate multilateral coordination in global mitigation.

Energy policy and corporate financial performance: Evidence from China's 11th five-year plan

Abstract The implementation of energy policies inevitably affects the micro-level behavior of enterprises, in turn affecting their financial performance. However, the relationship between China's energy policy and corporate financial performance remains to be verified. Combining of time, provincial difference in applying the binding energy-saving target in the 11th Five-Year Plan, and industry energy intensive variations, we employ a difference-in-difference-in-difference model to estimate the impact of energy policy on corporate financial performance. We find that in the high energy-intensive industries, stricter energy policy reduces corporate financial performance, as manifested by higher financial expense ratio, lower inventory turnover rate, and lower accounts receivables turnover ratio. In the eastern region, high energy-intensive enterprises within stricter energy policy provinces have higher financial expense ratio and lower inventory turnover ratio compared with similar enterprises in the central and western regions. Also, the energy policy has significant negative effect on the financial performance of large-scale enterprises and non-state-owned enterprises. Grasping this relationship is important for understanding the economic consequences of energy policy and helping the decisions-making of the Chinese government and regulated enterprises.

How does carbon tax affect social welfare and emission reduction in Finland?

Environmental concerns related to fossil fuels utilization has developed different energy/environmental policy tools that Carbon tax is one of the important ones. There are huge debates among different political parties related to the positive and negative effects of the carbon tax on the energy and environmental policies of the countries. However, carbon tax not only can have effects on the utilization and consumption of energy sources portfolios, but it may also have negative or positive effects on the economy, industry, and social welfare of the countries that should be identified and analyzed, in particular for countries with high energy-intensive industries such as Finland. The purpose of this research is to answer the question: “How does Carbon Tax affect social welfare and emission reduction in Finland?” We use the computable general equilibrium model to analyze the impact of the carbon tax on social welfare and the rate of emission reduction. Considering the fact that Finland has several years of carbon tax policy application background, evaluation of the impact of this policy on Finland’s social-environmental structure is very valuable for other countries, especially newcomers. Our results show that despite carbon tax policy in Finland has been successful in the reduction of carbon dioxide emissions, however, it has negative effects on the social welfare of Finns. Therefore, an optimum level of the carbon price is recommended for future policy revision

Exploring regional differences in the impact of high energy-intensive industries on CO2 emissions: Evidence from a panel analysis in China.

China is currently the largest CO2 emitter in the world. Within China, more than 60% of CO2 emissions originate from high energy-intensive (HEI) industries. Therefore, controlling and reducing CO2 emissions from HEI industries is crucial if China is to achieve its 2030 emission reduction targets. This study aims to investigate regional differences in the impact of HEI industries on CO2 emissions in China. This paper presents an analysis of the impact of HEI industries on CO2 emissions at the national and regional levels using a modified STIRPAT model and provincial panel data from 2000 to 2015 in China. The results show that HEI industries are significant contributors to China's CO2 emissions owing to the growth in industries, coal-based energy structure, low level of technology, and outstanding conduction effects. The impact intensity of HEI industries on CO2 emissions decreases from the western to the central and eastern regions in China because of a huge regional difference in industrial structure, energy structure, R&D investment, and industrial transfer. Our findings have important implications for policymakers in China by indicating that regional policies concerning HEI industries should be differentiated to successfully reduce CO2 emissions and meet national targets.

Effect of Perform-Achieve-Trade Policy on Energy Efficiency of Indian Industries

India adopted a Cap and Trade in energy intensity via a scheme called Perform-Achieve-Trade (PAT) with the objective to improve energy efficiency of the high energy intensive industries through target setting and tradable energy saving certificates. The scheme was announced in 2007 and the first cycle runs from April 2012-March 2015. This is the first market-based instrument adopted in India to achieve environmental protection. Under this scheme, the Bureau of Energy Efficiency identified eight most energy intensive industries, and within each of these industries it identified the most energy intensive plants and assigned them Energy Intensity (EI) targets. Firms exceeding their targets were given ESCerts which could be traded in Indian Energy Exchange and Power Exchange of India. This paper aims to examine effectiveness of the PAT scheme on inducing firms to reduce energy intensity of Cement, Fertilizer, and Pulp and Paper Industries. We use panel data for firms in the three industries with a difference-in-difference model to estimate the average treatment effect of the PAT scheme on firms that were assigned targets. We find that the PAT scheme was effective in improving energy intensity of firms in the cement and fertilizer industry, but not in the pulp & paper industry. Further, the scheme resulted in a decrease of power & fuel expenditure in the two industries, which in turn amounts to reduction of 9.53 million tC and 1.37 million tC for the cement and fertilizer industries respectively. The paper finally examines the market for ESCerts.

A multi-region multi-sector decomposition and attribution analysis of aggregate carbon intensity in China from 2000 to 2015

Index Decomposition Analysis (IDA) has been used to analyze driving forces of aggregate carbon intensity (ACI). However, previous studies mostly explained changes in ACI from either sectoral or regional perspective, but rarely looked into driving forces of ACI from both sectoral and regional perspectives under a unified and consistent framework. To fill the research gap, this study proposed a multi-region multi-sector decomposition and attribution approach to analyze driving forces of ACI from both sectoral and regional perspectives. The empirical results in China show that the ACI declined by 33% from 2000 to 2015. From the sectoral perspective, the decline can be mainly attributed to the significant energy efficiency improvement in six high energy-intensive industries. However, the rapid growth in electricity consumption, especially in chemicals and iron and steel, and the expansion of iron and steel industry during 2000–2005 greatly offset the negative effect from energy efficiency. From the regional perspective, the ACI decline can be primarily due to an extensive improvement in energy efficiency in most regions. On the contrary, the increasing dependency on coal, particularly in Shandong, Inner Mongolia, and Guangdong, and the increased share of carbon-intensive industries in some provinces such as Guangxi and Sichuan, markedly increased ACI. Based on the results, the effectiveness of underlying sectoral and regional level policies and measures implemented for ACI reduction in China were evaluated.

Business model for integrating energy efficiency performance in manufacturing industries: railcar case study

The strong environmental policies, market demand and environmental sustainability has affected industrial firms, and forced them to create sustainable energy solutions. Improving energy efficiency is a key driver for sustainability, especially in high energy intensive industries that includes rail car manufacturing, which calls for implementation of energy efficiency initiatives in managing energy consumption, thus reducing energy costs and environmental pollution. The article proposes a business model that can be used by Energy Service Companies (ESCos) in creating, delivering and capturing value of energy (electricity) using canvas methodology.

A decomposition analysis of energy-related CO2 emissions in Chinese six high-energy intensive industries

Abstract China's six high-energy intensive industries use more energy than any other industrial sectors, consuming almost 90% of manufacturing energy and more than 50% of national energy and contributing over 50% of national energy-related CO2 emissions. Thus, this study is motivated to identify the drivers of energy-related CO2 emissions change of high-energy intensive industries in China based on the Logarithmic Mean Divisia Index (LMDI) method. Results demonstrate that CO2 emissions in China's high-energy intensive industries were on the rise during 1986–2013 with annual growth rate of 7.8%. The expansion of industrial scale, which increased 52.14 billion tons of CO2 emissions in six high-energy intensive industries, was the leading force explaining CO2 emissions change; and the effect of which was most significant in power industry (20.52 billion tons of CO2 emissions increase). Energy intensity was the major contributor to promote the decline in CO2 emissions, and the effect was most significant in chemical industry and non-metallic mineral products industry. Besides, energy structure and industrial structure effects have relatively small impacts on CO2 emissions change due to the relatively stable energy structure and industrial structure during the study period. Policy recommendations are made for future emission reductions in Chinese six high-energy intensive industries.

Electricity Demand Forecasting For High Energy-Intensive Industries of Inner Mongolia in China

Since the development of high energy-consuming industries has an important impact on the total electricity consumption, it is essential to predict the electricity demand of these industries. A procedure based on LS-SVM algorithm and scenario analysis is proposed to forecast the electricity consumption of high energy-intensive industries in Inner Mongolia, which takes three affecting factors into consideration, including the output value, the proportion of output accounting for GDP, and electricity consumption intensity. The prediction results show that the prediction accuracy of LS-SVM is rather high with an average error rate of 2.03%. The electricity demand of energy-intensive industries in Inner Mongolia will reach 2136.9~2175.1 million kWh in 2015, and reach 2514.4 ~ 2966.9 million kWh in 2020. Meanwhile, the annual growth rate among 2013 to 2020 will be 5.18%~7.48%. In addition, 377.5 million kWh will be saved in 2015, and 791.8 million kWh will be saved in 2020.

Emergy-based comparative analysis of energy intensity in different industrial systems.

With the rapid economic development, energy consumption of China has been the second place in the world next to the USA. Usually, measuring energy consumption intensity or efficiency applies heat unit which is joule per gross domestic production (GDP) or coal equivalent per GDP. However, this measuring approach is only oriented by the conversion coefficient of heat combustion which does not match the real value of the materials during their formation in the ecological system. This study applied emergy analysis to evaluate the energy consumption intensity to fill this gap. Emergy analysis is considered as a bridge between ecological system and economic system, which can evaluate the contribution of ecological products and services as well as the load placed on environmental systems. In this study, emergy indicator for performing energy consumption intensity of primary energy was proposed. Industrial production is assumed as the main contributor of energy consumption compared to primary and tertiary industries. Therefore, this study validated this method by investigating the two industrial case studies which were Dalian Economic Development Area (DEDA) and Fuzhou economic and technological area (FETA), to comparatively study on their energy consumption intensity between the different kinds of industrial systems and investigate the reasons behind the differences. The results show that primary energy consumption (PEC) of DEDA was much higher than that of FETA during 2006 to 2010 and its primary energy consumption ratio (PECR) to total emergy involvement had a dramatically decline from year 2006 to 2010. In the same time, nonrenewable energy of PEC in DEDA was also much higher than that in FETA. The reason was that industrial structure of DEDA was mainly formed by heavy industries like petro-chemistry industry, manufacturing industries, and high energy-intensive industries. However, FETA was formed by electronic business, food industry, and light industries. Although the GDP of DEDA was much higher than that of FETA, its energy intensity was higher as well. Through the 5-year development, energy consumption intensity in DEDA made a significant reduction from 3.90E+16 seJ/$ to 1.84E+16 seJ/$, which was attributed by the improvement of industrial structure, construction of eco-industrial park and circular economic industrial park. The proposed emergy indicator for demonstrating energy consumption intensity overcame the weakness that the indicator was only transformed from the heat burning. Therefore, this study shows an optional way to measure energy consumption intensity from the perspective of material ecological contribution.