Assessing CO2 emissions in China’s iron and steel industry: A dynamic vector autoregression model

Energy saving and carbon dioxide emission reduction in China is attracting increasing attention worldwide. At present, China is in the phase of rapid urbanization and industrialization, which is characterized by rapid growth of energy consumption and carbon dioxide (CO2) emissions. China’s steel industry is highly energy-consuming and pollution-intensive. Between 1980 and 2013, the carbon dioxide emissions in China’s steel industry increased approximately 11 times, with an average annual growth rate of 8%. Identifying the drivers of carbon dioxide emissions in the iron and steel industry is vital for developing effective environmental policies. This study uses Vector Autoregressive model to analyzetheinfluencingfactors of the changes in carbon dioxide emissions in the industry. The results show that energy efficiency plays a dominant role in reducing carbon dioxide emissions.Urbanization also has significant effect on CO2 emissions because of mass urban infrastructure and real estate construction. Economic growthhas more impact on emission reduction than industrialization due to the massive fixed asset investment and industrial energy optimization. These findings are important for the relevant authorities in China in developingappropriateenergy policy and planning for the iron and steel industry.

[1]  Xiongfeng Pan,et al.  Spatial club convergence of regional energy efficiency in China , 2015 .

[2]  Tao Zou,et al.  Impact analysis of coal-electricity pricing linkage scheme in China based on stochastic frontier cost function , 2015 .

[3]  D. F. Stewart,et al.  Technical efficiency and productivity change of China's iron and steel industry , 2002 .

[4]  Madhumita Bhattacharya,et al.  The role of technology on the dynamics of coal consumption–economic growth: New evidence from China , 2015 .

[5]  Boqiang Lin,et al.  How does administrative pricing affect energy consumption and CO2 emissions in China , 2015 .

[6]  Sungwoo Moon,et al.  Stochastic Forecast of Construction Cost Index Using a Cointegrated Vector Autoregression Model , 2013 .

[7]  Chuanglin Fang,et al.  Urbanisation, energy consumption, and carbon dioxide emissions in China: A panel data analysis of China’s provinces , 2014 .

[8]  Boqiang Lin,et al.  China's energy demand and its characteristics in the industrialization and urbanization process , 2012 .

[9]  Iakovos Michailidis,et al.  Model-based and model-free “plug-and-play” building energy efficient control , 2015 .

[10]  Bing Yu,et al.  Low-carbon transition of iron and steel industry in China: carbon intensity, economic growth and policy intervention. , 2015, Journal of environmental sciences.

[11]  Tsuyoshi Fujita,et al.  Pursuing air pollutant co-benefits of CO 2 mitigation in China: A provincial leveled analysis , 2015 .

[12]  Weiqian Zhang,et al.  A quantitative analysis of municipal solid waste disposal charges in China , 2015, Environmental Monitoring and Assessment.

[13]  Dimitris Margaritis,et al.  Market-driven coal prices and state-administered electricity prices in China , 2013 .

[14]  Hai-long Ma,et al.  Exploring the relationship between urbanization and the eco-environment-A case study of Beijing-Tianjin-Hebei region , 2014 .

[15]  Florens Flues,et al.  An analysis of the economic determinants of energy efficiency in the European iron and steel industry , 2015 .

[16]  Ernst Worrell,et al.  Energy efficiency and carbon dioxide emissions reduction opportunities in the US iron and steel sector , 2001 .

[17]  B. W. Ang,et al.  Multiplicative decomposition of aggregate carbon intensity change using input–output analysis , 2015 .

[18]  Siriluk Chiarakorn,et al.  Energy and carbon dioxide intensity of Thailand's steel industry and greenhouse gas emission projection toward the year 2050 , 2014 .

[19]  Li Zhang,et al.  Evaluation of electricity saving potential in China's chemical industry based on cointegration , 2012 .

[20]  Shuang Gao,et al.  Position and orientation error analysis and its compensation for a wheeled train uncoupling robot with four degrees-of-freedom , 2015 .

[21]  N. Pardo,et al.  Prospective scenarios on energy efficiency and CO2 emissions in the European Iron & Steel industry , 2013 .

[22]  Tengfang Xu,et al.  A bottom-up model to estimate the energy efficiency improvement and CO2 emission reduction potentials in the Chinese iron and steel industry , 2013 .

[23]  Li Zhang,et al.  Estimates of the potential for energy conservation in the Chinese steel industry , 2011 .

[24]  C. Sims.  MACROECONOMICS AND REALITY , 1977 .

[25]  Bruno Larue,et al.  The market efficiency hypothesis: The case of coffee and cocoa futures , 1997 .

[26]  Zhancheng Guo,et al.  Reduction Behavior With CO Under Micro-Fluidized Bed Conditions , 2013 .

[27]  Yi-Ming Wei,et al.  An empirical analysis of energy efficiency in China's iron and steel sector , 2007 .

[28]  Ernst Worrell,et al.  International comparison of CO2 emission trends in the iron and steel industry , 2002 .

[29]  Chunping Xie,et al.  Reduction potential of CO2 emissions in China's transport industry , 2014 .

[30]  Yue Zhao,et al.  Impact of environmental regulations on the efficiency and CO2 emissions of power plants in China , 2015 .

[31]  Shaopu Yang,et al.  Dynamical Analysis on Single Degree-of-Freedom Semiactive Control System by Using Fractional-Order Derivative , 2015 .

[32]  Li Wang,et al.  A new coal gas utilization mode in China’s steel industry and its effect on power grid balancing and emission reduction , 2015 .

[33]  C. Granger.  Some recent development in a concept of causality , 1988 .

[34]  Xiang Yin,et al.  A bottom-up analysis of China’s iron and steel industrial energy consumption and CO2 emissions , 2014 .

[35]  Georgios Magkonis,et al.  Exploring the Effects of Financial and Fiscal Vulnerabilities on G7 Economies: Evidence from SVAR Analysis , 2014 .

[36]  Iker García-Garizábal,et al.  Climate change and the water cycle in newly irrigated areas , 2015, Environmental Monitoring and Assessment.

[37]  Krushna Mahapatra.  Energy use and CO2 emission of new residential buildings built under specific requirements – The case of Växjö municipality, Sweden , 2015 .

[38]  Bangzhu Zhu,et al.  Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China , 2013 .

[39]  Ernst Worrell,et al.  Co-benefits of energy efficiency improvement and air pollution abatement in the Chinese iron and steel industry , 2014 .

[40]  Boqiang Lin,et al.  How industrialization and urbanization process impacts on CO2 emissions in China: Evidence from nonparametric additive regression models , 2015 .

[41]  Tengfang Xu,et al.  Undertaking high impact strategies: The role of national efficiency measures in long-term energy and emission reduction in steel making , 2014 .

[42]  Boqiang Lin,et al.  Estimates of inter-fuel substitution possibilities in Chinese chemical industry , 2013 .

[43]  Zongguo Wen,et al.  Estimates of the potential for energy conservation and CO2 emissions mitigation based on Asian-Pacific Integrated Model (AIM): the case of the iron and steel industry in China , 2014 .

[44]  Fredrik N G Andersson,et al.  CO2 emissions and economic activity: Short- and long-run economic determinants of scale, energy intensity and carbon intensity , 2013 .

[45]  Marcelle Chauvet,et al.  Nonlinear Relationship Between Permanent and Transitory Components of Monetary Aggregates and the Economy , 2013 .

[46]  Mats Söderström,et al.  Electricity generation from low-temperature industrial excess heat—an opportunity for the steel industry , 2014 .

[47]  Xiaolei Wang,et al.  Promoting energy conservation in China's iron & steel sector , 2014 .

[48]  S. Johansen,et al.  MAXIMUM LIKELIHOOD ESTIMATION AND INFERENCE ON COINTEGRATION — WITH APPLICATIONS TO THE DEMAND FOR MONEY , 2009 .

[49]  H. Farag,et al.  Study of corrosion behaviour of A106 carbon steel absorber for CO2 removal in amine promoted hot potassium carbonate solution (Benfield solution) , 2014 .

[50]  Chengkang Gao,et al.  Analyzing and forecasting CO2 emission reduction in China’s steel industry , 2015, Frontiers of Earth Science.

[51]  Yuan Li,et al.  Contribution weight of engineering technology on pollutant emission reduction based on IPAT and LMDI methods , 2014, Clean Technologies and Environmental Policy.

[52]  J. Stock,et al.  Efficient Tests for an Autoregressive Unit Root , 1992 .

[53]  Li Ji,et al.  Energy use and carbon dioxide emissions from steel production in China , 2002 .

[54]  Qinghua Zhu,et al.  An analysis of energy-related greenhouse gas emissions in the Chinese iron and steel industry , 2013 .

[55]  Zhanming Chen,et al.  Inflationary effect of coal price change on the Chinese economy , 2014 .

[56]  Uwaoma George Nwaogu,et al.  FDI, Foreign Aid, Remittance and Economic Growth in Developing Countries , 2015 .

[57]  Brantley Liddle,et al.  Urban Density and Climate Change: A STIRPAT Analysis Using City-Level Data , 2013 .

[58]  C. Tang,et al.  The dynamic links between CO2 emissions, economic growth and coal consumption in China and India , 2013 .

[59]  Dennis Normile,et al.  China's Living Laboratory in Urbanization , 2008, Science.

[60]  Jan-Olof Dalenbäck,et al.  Energy efficient climate control in office buildings without giving up implementability , 2015 .

[61]  Boqiang Lin,et al.  Carbon emissions from energy intensive industry in China: Evidence from the iron & steel industry , 2015 .

[62]  Wenqiang Sun,et al.  Change in Carbon Dioxide (CO2) Emissions From Energy Use in China’s Iron and Steel Industry , 2011 .

[63]  Nikola Burić,et al.  Relations Between Different Notions of Degrees of Freedom of a Quantum System and Its Classical Model , 2014, 1411.4425.

[64]  Peng Zeng,et al.  The dual and degrees of freedom of linearly constrained generalized lasso , 2015, Comput. Stat. Data Anal..

[65]  Shenggang Ren,et al.  The effects of urbanization, consumption ratio and consumption structure on residential indirect CO2 emissions in China: A regional comparative analysis , 2015 .

[66]  M. Hashem Pesaran,et al.  Working with Microfit 4.0 : interactive econometric analysis , 1997 .

[67]  Jie Shen,et al.  A Cauchy estimator test for autocorrelation , 2015 .

[68]  Jing Huang,et al.  Mitigation paths for Chinese iron and steel industry to tackle global climate change , 2009 .

[69]  Zhaohua Wang,et al.  Indirect carbon emissions in household consumption: evidence from the urban and rural area in China , 2014 .

[70]  Henk Folmer,et al.  What role does the real estate–construction sector play in China’s regional economy? , 2014 .

[71]  Kunwoo Han,et al.  Performance of an ammonia-based CO2 capture pilot facility in iron and steel industry , 2014 .

[72]  P. Jochem,et al.  Including road transport in the EU ETS (European Emissions Trading System): A model-based analysis of the German electricity and transport sector , 2014 .

[73]  Elisabetta Allevi,et al.  The steel industry: A mathematical model under environmental regulations , 2015, Eur. J. Oper. Res..

[74]  Tao Du,et al.  Energy Consumption and Its Influencing Factors of Iron and Steel Enterprise , 2013 .

[75]  Elena Pervukhina,et al.  An optimization technique based on a vector autoregression model with state space representation: application to Ukrainian cargo transport data , 2014 .

[76]  Jesus Maria Blanco,et al.  New investigation on diagnosing steam production systems from multivariate time series applied to thermal power plants , 2013 .

[77]  Stephen J. Perez,et al.  Still puzzling: evaluating the price puzzle in an empirically identified structural vector autoregression , 2014 .

[78]  Boqiang Lin,et al.  Analysis of energy-related CO2 (carbon dioxide) emissions and reduction potential in the Chinese non-metallic mineral products industry , 2014 .

[79]  Nyakundi M. Michieka,et al.  An Empirical Analysis of the Role of China's Exports on CO2 Emissions , 2013 .

[80]  E. Rosa,et al.  Effects of population and affluence on CO2 emissions. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[81]  Pentti Saikkonen,et al.  Forecasting with a Noncausal VAR Model , 2012, Comput. Stat. Data Anal..

[82]  Fanxin Meng,et al.  Using hybrid method to evaluate carbon footprint of Xiamen City, China , 2013 .

[83]  Mark Cummins,et al.  EU ETS market interactions: The case for multiple hypothesis testing approaches , 2013 .

[84]  Feng He,et al.  Energy efficiency and productivity change of China’s iron and steel industry: Accounting for undesirable outputs , 2013 .

[85]  Javier Gomez-Biscarri,et al.  A Residual-Based ADF Test for Stationary Cointegration in I (2) Settings , 2015 .

[86]  Rafat Siddique,et al.  Utilization (recycling) of iron and steel industry by-product (GGBS) in concrete: strength and durability properties , 2014 .

[87]  Semida Silveira,et al.  Capturing energy efficiency in European iron and steel production—comparing specific energy consumption and Malmquist productivity index , 2014 .

[88]  Jin-Hua Xu,et al.  CO2 emissions reduction potential in China’s cement industry compared to IEA’s Cement Technology Roadmap up to 2050 , 2014 .

[89]  Jack Chin Pang Cheng,et al.  Comparison of Greenhouse Gas Emission Accounting Methods for Steel Production in China , 2014 .