Four essays on environmental policy under uncertainty with applications to water quality and carbon sequestration

In this thesis, I present four essays that deal with several diverse issues in environmental economics, ranging from soil carbon sequestration, to a design of a pollution permit trading program, to proposing watershed-scale solutions to water quality problems, both on state and regional scale.;The first essay is titled "Environmental policy under benefit and cost uncertainty: application to soil carbon offsets". I characterize an optimal spatial allocation of land parcels to specific environmental practices explicitly dealing with uncertainty in both the benefits and program costs. The results provide a magnitude of uncertainty discount for soil carbon offsets and the margin of safety necessary in the budget to ensure at the planning stage that the program's costs will not exceed the planned expenditures.;The second essay is titled "Optimal design of permit markets with an ex ante pollution target". In this essay, the design of permit trading programs when the objective is to minimize the cost of achieving an ex ante pollution target; that is, one that is defined in expectation rather than an ex post deterministic value, is examined. I demonstrate that to minimize expected abatement costs regulators must use information on the joint distribution of firms' abatement costs, as well as the pollution delivery coefficients. As a result, the optimal trading ratio is a function of the delivery coefficient, as well as the moments of abatement costs, and the total permit allocation deviates from the pollution goal. These findings differ from a typical permit market design, where no cost information is needed to achieve cost-efficiency, the trading ratio is set to the ratio of pollution delivery coefficients, and the permit allocation exactly equals the pollution goal.;The third and the fourth chapters of the thesis build a simulation-optimization modeling framework for the analysis of efficient nonpoint source pollution reduction strategies. These essays integrate modern multi-objective optimization tools with a realistic water quality model to provide decision-makers with sets of cost-efficient pollution reduction solutions.;In the third essay, titled "Efficient reductions in local and state-level nonpoint source nutrient pollution: an application to the state of Iowa," I incorporate a water quality model, SWAT, in conjunction with detailed information on conservation practices, into an evolutionary search algorithm to find allocations of conservation practices that minimize the costs of achieving given water quality targets for all the major watersheds in the state of Iowa.;In the final essay, titled "Searching for efficiency: least cost nonpoint source pollution control with multiple pollutants, practices, and targets", I examine the policy implications of efficient control of nonpoint source pollution using a spatially explicit model of a large and critically important agricultural region: the Upper Mississippi River Basin in the central U.S. I derive the conservation production possibility frontier that explicitly incorporates the tradeoffs between pollution control costs and water quality benefits, between different pollutants, or between different control targets. The regional scale of the modeling framework facilitates the investigation of relevant policy analyses related to the growing "dead zone" in the Gulf of Mexico.