@article{36f79a7a16bd4098877b22b907b1a8a9,
title = "Evaluating environmental risks using safety-first constraints",
abstract = "This article incorporates an upper partial moment concept into a linear programming model to impose safety-first environmental constraints. The model is linear and deterministic, treats a discrete sample as an empirical distribution, and optimizes over the column space. It allows a decision maker to specify the objectives and the compliance probabilities with the objectives when making decisions, and endogenously determines the risk levels. Even though it is presented in the context of environmental management, the model is general enough to be extended to other situations where the probability of a variable exceeding some target or standard is restricted.",
keywords = "And nitrogen runoff, Chance constrained programming, Environmental risk, Safety-first, Sedimentation, Target MOTAD, Upper partial moment",
author = "Zeyuan Qiu and Tony Prato and Francis McCamley",
note = "Funding Information: The authors are research assistant professor, professor, and associate professor in the Department of Agricultural Economics, University of Missouri, Columbia, Missouri, respectively. The funding support from the U.S. Department of Agriculture through the Agricultural Systems for Environmental Quality project is acknowledged. The authors are grateful to Peter Berck and two anonymous reviewers for their helpful comments. Funding Information: The model is applied to evaluate the economic impacts of enforcing safety-first environmental constraints in the Goodwater Creek watershed, Missouri. The 19,132-acre watershed is located in north-central Missouri and has been the study site for the Missouri Agricultural Systems for Environmental Quality (ASEQ) project and its predecessor the Missouri Management Systems Evaluation Areas (MSEA) project funded by the U.S. Department of Agriculture since 1990. The watershed is located in the Central Claypan Soils Major Land Resource Area (MLRA 113), an area of about 10 million acres in the Midwestern United States. Crop production is the primary agricultural activity in the watershed. One aspect of those projects is to deal with uncertain environmental impacts of farming systems affected by stochastic weather conditions. Sedimentation and nitrogen runoff are two primary water quality problems caused by crop production. The data set contains annual average net returns for six farming systems, and simulated sediment yield and nitrogen concentration in runoff with these farming systems for sixteen states of nature in the Goodwater Creek watershed. The data set was originally developed by Wu and was used in several empirical risk-based economic and policy analyses of nonpoint source pollution (Xu, Prato, and Zhu; Qiu, Prato, and Kaylen). The data set is briefly described below and more details can be found in Wu.",
year = "2001",
month = may,
doi = "10.1111/0002-9092.00165",
language = "English (US)",
volume = "83",
pages = "402--413",
journal = "American Journal of Agricultural Economics",
issn = "0002-9092",
publisher = "Oxford University Press",
number = "2",
}