Air Pollution 4 Essay Research Paper Damage — страница 3

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airborne residuals is in the agricultural sector. To appropriately deal with this issue requires looking at background information over time. This will allow a person to make their best guess for a model to illustrate what is taking place. The model requires air quality modeling which will help show what is happening to convert emissions into ambient concentrations. This is influenced by factors such as time, temperature, moisture, and wind direction. Emissions from both point and mobile sources should be viewed to relate ambient concentrations to agricultural losses, thereby formulating damage functions. However it is often difficult to accept them because the results aren’t certain. Many are uncomfortable in establishing a schedule dealing with crop loss to ambient

concentration, however they can give their best guess. A study dealing with agricultural losses from airborne residuals in the Ohio River Basin looked at producers of corn, soybeans, and wheat between 1976 and 2000 in regards to concentrations of SO2 and 03. The purpose of the study was to find estimates of damage functions and recognize monetary losses attributed to them. This required looking at utility related damages versus other sources, and to what extent they are related to nominal and peak load emissions. Three scenarios where devised to represent possible cases. The first scenario assumes that business is conducted as usual. This means that plants comply with performance standards, which requires replacing SIP units with new source performance ones. These new standards

require a different physical capital stock to be applied to the plants. Compliance must be done in order to accurately judge air pollution and how effective pollution control is. This also includes looking at annual projected emissions and a schedule of bringing plants online. The second scenario is the same as the first except there is no compliance with the SIP’s. This is referred to as the dirty air scenario. The third scenario indicates a high growth in electric demand. Utility life of the SIP’s was upwards of 45 years. It is hard to determine which variable caused a change in the outcome. The way to begin this study was to look at what output was versus what output could have been. Declining productivity, for example, can be viewed in bushels per acre. This will give the

physical damages, which then can be converted into monetary losses. Considering the size of the region being studied, the best that could be done was to be given a damage coefficient, which represented a number indicating the percent reduction in activity. The damage coefficient is probable, not a precise value. The observed production in any year is a point estimate of dirty air production. From this a weighted average price was calculated. This in turn will help determine the change in producer surplus. This change is distinguished by the shift in the supply curves, which reveals a number considered to be a legitimate number of the loss experienced. To arrive at this number first requires determining dirty air and clean air output. Dirty air is found when the damage coefficient

is subtracted from clean air output, then multiplied by clean air output. Clean air output is found by dividing dirty air output by one minus the damage coefficient. These values now show the location and magnitude of the supply curves. The next problem in deriving this calculation deals with the time value of money. Dollar values change over the years and in order to use an appropriate value in the calculation, future losses must be discounted to a present value in time. The discount rate picked for this must be in the area of what a relatively informed person can earn over the time horizon. Choosing a low discount rate will have losses maximized in the future while a high discount rate will have losses minimized in the future. In this study, a discount rate of 10 percent was

chosen. The results of the study indicate that monetary losses were 12 percent of the present discounted value of clean air production. Looking at scenario one, the total region losses constituted roughly 10.3 percent of the discounted value of pollution free output. These losses were during peak load emissions and half the losses, 4.3 percent, are utility related from coal-fired activity. The rest of the losses are from point and mobile sources. Looking at the second scenario the results are almost identical showing a total regional loss of 10.4 percent and utility related losses at 4.3 percent. This indicates that compliance or noncompliance with the SIP’s did not significantly influence the losses experienced in the region. The third scenario showed similar results except