Should the US clean air act include CO2 emission control?: Examination by data envelopment analysis

This study proposes a new use of Data Envelopment Analysis (DEA) to measure the operational, environmental and both-unified efficiency measures of US coal-fired power plants. The power plants produce not only desirable outputs (e.g., electricity) but also undesirable outputs (e.g., CO2 and NOx) as a result of their plant operations. A Range-Adjusted Measure (RAM) is used as an original non-radial DEA model. Then, it is reformulated for handling undesirable (bad) outputs. The proposed use of DEA models measures the environmental and unified performance of power plants under two variable alternatives (with and without CO2 emission control) in order to examine both the influence of US Clean Air Act (CAA) on the acid rain causing gases (NOx and SO2) and its extension to the CO2 regulation. This study finds that the acid rain program under the CAA has been effective on the emission control of SO2 and NOx produced at US coal-fired power plants. Moreover, additional regulation on CO2 may enhance their environmental and unified performance. Thus, it is recommended that the US federal and state governments need to expand the legal scope of CAA to the emission control on CO2 because the gas is considered as a main source of global warming and climate change.

[1]  Barnali Nag,et al.  Estimation of carbon baselines for power generation in India: the supply side approach , 2006 .

[2]  Douglas A. Wolfe,et al.  Nonparametric Statistical Methods , 1973 .

[3]  Peng Zhou,et al.  A survey of data envelopment analysis in energy and environmental studies , 2008, Eur. J. Oper. Res..

[4]  Kazuyuki Sekitani,et al.  An occurrence of multiple projections in DEA-based measurement of technical efficiency: Theoretical comparison among DEA models from desirable properties , 2009, Eur. J. Oper. Res..

[5]  Rolf Färe,et al.  Environmental Performance : an Index Number Approach , 2004 .

[6]  Ali Emrouznejad,et al.  Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years , 2008 .

[7]  Toshiyuki Sueyoshi,et al.  Performance analysis of US coal-fired power plants by measuring three DEA efficiencies , 2010 .

[8]  A. Charnes,et al.  Cost Horizons and Certainty Equivalents: An Approach to Stochastic Programming of Heating Oil , 1958 .

[9]  Rodrigo Taborda,et al.  Perfomance and Efficiency in Colombia's Power Distribution Sistem: Effects of the 1994 Reform , 2006 .

[10]  Toshiyuki Sueyoshi,et al.  Can environmental investment and expenditure enhance financial performance of US electric utility firms under the clean air act amendment of 1990 , 2009 .

[11]  M. Abbott,et al.  The productivity and efficiency of the Australian electricity supply industry , 2006 .

[12]  Alice Shiu,et al.  A data envelopment analysis of the efficiency of China’s thermal power generation , 2001 .

[13]  Alexander Vaninsky,et al.  Efficiency of electric power generation in the United States: Analysis and forecast based on data envelopment analysis , 2006 .

[14]  Rob Alexander,et al.  Does regulation stimulate productivity? The effect of air quality policies on the efficiency of US power plants , 2009 .

[15]  David E. Dismukes,et al.  A data envelopment analysis of the levels and determinants of coal-fired electric power generation performance , 2000 .

[16]  Toshiyuki Sueyoshi,et al.  Core business concentration vs. corporate diversification in the US electric utility industry: Synergy and deregulation effects , 2009 .

[17]  Sabuj Kumar Mandal,et al.  Environmental efficiency of the Indian cement industry: An interstate analysis , 2010 .

[18]  W. Cooper,et al.  RAM: A Range Adjusted Measure of Inefficiency for Use with Additive Models, and Relations to Other Models and Measures in DEA , 1999 .

[19]  H. Rudnick,et al.  DEA efficiency for the determination of the electric power distribution added value , 2004, IEEE Transactions on Power Systems.

[20]  Carlos Pestana Barros,et al.  Technical efficiency of thermoelectric power plants , 2008 .

[21]  Tooraj Jamasb,et al.  International benchmarking and regulation: an application to European electricity distribution utilities , 2003 .

[22]  Ali Azadeh,et al.  An integrated DEA–COLS–SFA algorithm for optimization and policy making of electricity distribution units , 2009 .

[23]  H. B. Mann,et al.  On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other , 1947 .

[24]  W. Cooper,et al.  Survey of mathematical programming models in air pollution management , 1997 .

[25]  Kemal Sarica,et al.  Efficiency assessment of Turkish power plants using data envelopment analysis , 2007 .

[26]  Per Joakim Agrell,et al.  Economic and environmental efficiency of district heating plants , 2005 .

[27]  Pekka J. Korhonen,et al.  Evaluation of Cost Efficiency in Finnish Electricity Distribution , 2003, Ann. Oper. Res..

[28]  Katsuya Tanaka,et al.  Efficiency analysis of Chinese industry : A directional distance function approach , 2007 .

[29]  A. Charnes,et al.  BLENDING AVIATION GASOLINES-A STUDY IN PROGRAMMING INTERDEPENDENT ACTIVITIES IN AN INTEGRATED OIL COMPANY' , 1952 .

[30]  Fred W. Glover,et al.  Contributions of Professor William W. Cooper in Operations Research and Management Science , 2009, Eur. J. Oper. Res..

[31]  William L. Weber,et al.  Characteristics of a Polluting Technology: Theory and Practice , 2002 .