Estimated Damage Caused by the Phenomenon of Dust on People Health in Iran (Case Study Provinces of Khuzestan, Kermanshah and Kurdistan)

Inrtoduction
Developing countries and newly industrialized countries face the twin challenges of protecting the environment while also strengthening their economies. Over the past few decades, the intensified process of urbanization and industrialization undertaken by these countries, coupled with rapid population growth, has resulted in the degradation of the environmental quality. Particularly, the emission of harmful pollutants such as particulate matter has contributed considerably to a rapid drop in the air quality in the cities.
Recent studies on the effects of chronic exposure to air pollution have identified PM10 as the pollutant most responsible for the life-shortening effect of dirty air. The major concerns for human health include effects on breathing and respiratory symptoms, aggravation of existing respiratory and cardiovascular disease, alterations in the body’s defense systems against foreign materials, damage to lung tissue, carcinogenesis and premature death. Particulate exposure might increase susceptibility to bacterial or viral respiratory infections, leading to an increased incidence of pneumonia in vulnerable members of the population. It might also aggravate the severity of underlying chronic lung disease, causing more frequent or severe exacerbation of airway disease or more rapid loss of lung function. Besides its adverse impact on human health, particulate matter can also result in visibility degradation.
 
Matherial&Methods
this paper attempts to provide more insights into the epidemiological and valuation relationships of particulate air pollution which is apparently lacking in Iran. If cost of particulate air pollution were substantial, it would highlight the importance of not ignoring the environment in pursuing economic progresses. Given the available epidemiological data, PM10 may be regarded as an important and useful indicator for the health risk of air pollution. We use PM10 as the main indicator for air pollution and its impact on health as the proxy for the estimation of the economic cost of particulate air pollution. The most troubling finding from many recent scientific health studies in the air pollution epidemiological literature is that increase in ambient concentrations of particulate matter under 10 mg (PM10) is associated with increase in the risk of premature mortality.
 
The most troubling finding from many recent scientific health studies in the air pollution epidemiological literature is that increase in ambient concentrations of particulate matter under 10 mg (PM10) is associated with increase in the risk of premature mortality.
Once the links between emissions to human health effect have been established, the next stage requires the assignment of economic (monetary) value to the predicted health effects. In the case of health effects, the monetarization approach should determine values according to individual stated preferences (willingness to pay). It has been argued that E. Quah, T.L. Boon / Journal of Asian Economics 14 (2003) 73–90 75 if people’s preferences are a valid basis upon which to make judgments concerning changes in human well being, then it follows that changes in human mortality and morbidity should also be valued according to what individuals are willing to pay or willing to accept as compensation to forgo the change in health status.  The value of a statistical life (VOSL) is the value of a small change in the risks associated with an unnamed member of a large group dying. COI measures the total cost of illness that is imposed on the society. These costs include value of the lost productivity (loss in earnings) due to illness, medical costs such as hospital care, home health care, medicine, services of the doctors and nurses; and other related out-of-pocket expenditures.
 
We adopt the DRFs developed by Ostro (1994) and Rowe, (1995). The estimated health impact can be calculated by the following relationship:
 =                                                                                                 
where, dHij is the change in population’s risk of health impact i due to pollutant j; aij, slope from the dose response curve for health impact i due to pollutant j; POPi, population at risk of health effect i and dAj is the change in ambient concentration of air pollutant j.
DRFs relate information on changes in ambient air quality for different pollutants to different health outcomes. The principle is that changes in ambient air pollution levels for certain pollutants can be statistically related to observed changes in morbidity and mortality in a population .  Since there are great variations in the coefficients estimated by the various studies, three alternative assumptions about health effects are presented with the central estimate being given the most weight. The high (low) end estimates are calculated by increasing (decreasing) the coefficient by one estimated standard deviation. Ostro (1994) suggests to use 0.062, 0.096 and 0.13 as the lower, central and upper coefficient, respectively for the estimation of percentage change in mortality.
Following the DRF in following formula , the number of cases of premature mortality due to PM10 can then be expressed as:
 Mortality = b      0.01  Crude Mortality Rate  POP                                     
where b is the mortality coefficient (0.062, 0.096 and 0.13 for lower, central and higher estimate, respectively) and POP is the population exposed to risk.
A similar approach is also used to estimate the effects of changes in air quality on air pollution-related illnesses. The increase in number of morbidity cases in terms of respiratory health admission (RHA), emergency room visits (ERV), restricted activity days (RAD), lower respiratory illness in children (LRI), asthma attacks, respiratory symptoms and chronic bronchitis can be estimated using the following formula:
 Morbidity =    POP                                                                               
where ci is the morbidity coefficients for each discrete measure of morbidity effect  and POP is the population exposed to risk.
 
 
In recent years, environmental economists and policy makers have taken a lot of effort to estimate the value of change in the quality of the environment, and especially in reducing air pollution and its effect on the reduction of mortality in developing countries. One of these efforts is estimating V.S.L. through income elasticity method. This elasticity, which Bowled and Beghin estimate to range from 1.52 to 2.269, can be expressed as part of the following formula:
 =    
Where  and  are the value of statistical life in two countries,  and Y denotes the per capital income in each nation. The e term is the income elasticity of WTP. To provide a check on the validity of our previous V.S.L. estimates, we use this Bowland- Beghin along with our Iranian V.S.L. numbers, to infer the value of a for Iran. Assuming a US value of statistical life of $5 million, PPP-adjusted per capital incomes to estimate the V.S.L. through this method, the simple concept of income elasticity in microeconomics is used. Using this method, it is possible to use the V.S.L. of other countries to determine the V.S.L. for Iran. When the V.S.L. of another country is used to estimate the V.S.L. of Iran, the effect of income should be considered in the estimation and the V.S.L. should be adjusted on that basis. In order to achieve more precision and care, in this study the researchers used three income elasticity of 1, 1.5, and 2. If WTPA is kept constant, the elasticity of 1 will show a higher elasticity compared to 1.5. Similarly, the income elasticity of 1.5 demonstrates a higher elasticity compared to income elasticity of 2 for Iran. Therefore, the income elasticity of 1 is Upper Limit, the income elasticity of 2 is Lower Limit and the income elasticity of 1.5 is mid Limit.
 
In order to estimate the direct medical costs, sufficient number of general hospitals were selected. Then, all the files pertaining to the illnesses caused by air pollution were extracted. the required information were extracted from the files and registered in the prepared forms. This information included the number of the patient’s file, age, sex, the costs of hoteling, cost of drugs, cost of physician, cost of surgery, cost of
physiotherapy, cost of consumed materials, duration of hospitalization, type of insurance, job and the total expenditure. In the end, the mean of the total direct costs of each illness in each and every group of hospitals was estimated.
 
Discussion of Result & Conclusions
A recent dust phenomenon cover in the South West and the West's has adverse effects on human health the most important effects is on Mortality and diseases such as chronic bronchitis, asthma, and Infections respiRatory in children mild. The aim of this study was to estimate the number of premature Mortality and morbidity and economic costs of the effects of particulate matter (pm10) in Khuzestan, Kermanshah and Kurdistan in 1389, which are calculated using the dose response, the value of statistical life and cost of illness methods. The paper adopts a three-step procedure to estimate the cost of particulate air pollution . Firstly, the ambient concentration of the pollutant, PM10, is determined. The second step involves the use of one increasingly accepted methodology—the damage function approach using dose–response relationships—to estimate the health impacts of PM10 pollution. The health impacts considered here are the increase in mortality or morbidity. The last step then assigns economic (monetary) values to the increase in mortality and morbidity.The results show that attributable to air pollution 2783, 752 and 370 of Mortality (central estimate) in the province of Khuzestan, Kermanshah and Kurdistan PM10 in 1389 and is also about 12 361 hospital admissions, 244,157 visits to emergency ,44534793 restricted activity days (days when the N¬ days, some but not all activities are normal-width), 446008 lower respiratory infections in children, 59751598 asthma attacks, and 63,047  chronic bronchitis, in the Selected province outcome dust occurred. The total cost of mortality associated with particulate pollution PM10 is calculated using the statistical value of life method in the province of Khuzestan, Kermanshah and Kurdistan, 3506580000, 947520000 and 466200000 dollars respectively,that is 0.8, 0.2 and 0.1 percent of Iran”s GDP respectively,  and using the money blood is estimated, 100,000, 20,715 and 10,332 dollars respectively. Direct medical costs of disease, asthma, chronic bronchitis and lower respiratory infections in children associated with particulate pollution PM10  is calculated in selected provinces in 1389, 35 645, 37 and 266 billion dollars (central estimate) and the average opportunity cost per patient (during hospital stay) is calculated 85775.
According to increasing importance of air pollution from dust particles and adverse effects on human health And the need to estimate the health damage caused by this phenomenon, this phenomenon has been increasing recognition of the importance and necessity of this phenomenon, And it must be admitted that this requires detailed knowledge and resources that leads to the release of particulate matter have been provided. One of the major problems in this area, prevent and find the causes of increase or decrease air pollution and also are predicted pollution-reducing factors.