Conjunctive Use of Models to Design Cost-Effective Ozone Control Strategies

Author:

Fu Joshua S.1,Brill Downey E.2,Ranjithan Ranji S.2

Affiliation:

1. a Department of Civil and Environmental Engineering , University of Tennessee , Knoxville , TN , USA

2. b Department of Civil Engineering , North Carolina State University , Raleigh , NC , USA

Publisher

Informa UK Limited

Subject

Management, Monitoring, Policy and Law,Waste Management and Disposal

Reference10 articles.

1. Kohn, R.E. Optimal Air Quality Standards;Econometrica1971,39, 983-995.

2. Mcbride, S.J.; Oravetz, M.A.; Russell, A.G. Cost-Benefit and Uncertainty Issues in Using Organic Reactivity to Regulate Urban Ozone.Environ. Sci. Technol.1997,31, 238A–244A.

3. Sich, B.; Baugh, J.W. Linear Regression Approach to Optimization of Tropospheric Ozone Control Strategies. North Carolina State University Civil Engineering Department Undergraduate Research: Raleigh, NC, 1995.

4. Goldberg, D.E.Genetic Algorithms in Search, Optimization, and Machine Learning; Addison-Wesley: Reading, MA, 1989.

5. Biscoff, C.; Carle, A.; Khademi, P.; Mauer, A. The ADIFOR 2.0 System for the Automatic Differentiation of Fortran 77 Programs;IEEE Computational Science and Engineering,1996,3, pp 1-32.

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