Decision Making Process in a Nonpoint Pollution Control Model

A nonpoint pollution control approach is suggested when: (i) there is no one-to-one correspondence between emission and ambient levels of the pollutant because of the effect of random variables, and (ii) the emissions of several polluters may affect the ambient levels and it is not possible to separate their contributions. The approach is relevant for all dispersed pollution problems where monitoring difficulties and uncertainty are present. The model offered in this paper is based on the premise that government can influence but not fully control the response of economic agents, who behave according to their own criteria when given policy signals set by the government. Their responses, however, may or may not be desirable outcomes for the policy makers. Therefore, any attempt to model policy implications must consider two inter-connected objectives: those of the policy maker and those of the economic agents influenced by policy. Thus, a policy based on a tax/subsidy scheme will indirectly lead the polluting firm(s) to the point of optimal abatement, fulfilling both the regulatorʹs and firmʹs objectives. The regulatorʹs policy instruments are considered to be exogenous variables by polluting firms, while polluting firms» objectives and related sets of constaints are considered to be behavioral constraints by the regulator. Multi-level mathematical programming is the methodology suggested for practical studies. The structure of the nonpoint pollution control model and multi-level programming are built on similar premises. A well-established microeconomics theory lies behind this model, and its obvious link to multi-level programming methodology, which has been proven in applied work in some other scientific areas, and promises good results in future at a practical level.