Literature DB >> 23050674

Improving NO(x) cap-and-trade system with adjoint-based emission exchange rates.

S Morteza Mesbah1, Amir Hakami, Stephan Schott.   

Abstract

Cap-and-trade programs have proven to be effective instruments for achieving environmental goals while incurring minimum cost. The nature of the pollutant, however, affects the design of these programs. NO(x), an ozone precursor, is a nonuniformly mixed pollutant with a short atmospheric lifetime. NO(x) cap-and-trade programs in the U.S. are successful in reducing total NO(x) emissions but may result in suboptimal environmental performance because location-specific ozone formation potentials are neglected. In this paper, the current NO(x) cap-and-trade system is contrasted to a hypothetical NO(x) trading policy with sensitivity-based exchange rates. Location-specific exchange rates, calculated through adjoint sensitivity analysis, are combined with constrained optimization for prediction of NO(x) emissions trading behavior and post-trade ozone concentrations. The current and proposed policies are examined in a case study for 218 coal-fired power plants that participated in the NO(x) Budget Trading Program in 2007. We find that better environmental performance at negligibly higher system-wide abatement cost can be achieved through inclusion of emission exchange rates. Exposure-based exchange rates result in better environmental performance than those based on concentrations.

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Year:  2012        PMID: 23050674     DOI: 10.1021/es302406y

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  1 in total

1.  A multiphase CMAQ version 5.0 adjoint.

Authors:  Shunliu Zhao; Matthew G Russell; Amir Hakami; Shannon L Capps; Matthew D Turner; Daven K Henze; Peter B Percell; Jaroslav Resler; Huizhong Shen; Armistead G Russell; Athanasios Nenes; Amanda J Pappin; Sergey L Napelenok; Jesse O Bash; Kathleen M Fahey; Gregory R Carmichael; Charles O Stanier; Tianfeng Chai
Journal:  Geosci Model Dev       Date:  2020-07-02       Impact factor: 6.135

  1 in total

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