• Environmental and Resource Economics Review
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• 제13권1호
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• pp.49-82
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• 2004

The study aimed to evaluate cancer damage cost due to risk from benzene inhalation. We performed health risk assessment based on US EPA guideline to estimate annual population risk in Ulsan metropolitan city. Also, we estimated a willingness-to-pay amount for reducing a cancer mortality rate to evaluate a value of statistical life. We combined the annual population risk and the value of statistical life to calculate the cancer damage cost. In the health risk assessment, we applied the benzene unit risk ($2.2{\times}10^{-6}{\sim}7.8{\times}10^{-6}$) in the US EPA'S Integrated Risk Information System to assess the annual population risk. Average concentration of benzene in ambient air is $7.88{\mu}g/m^3$(min: 1.16~max: $23.32{\mu}g/m^3$). We targeted an exposure population of 516,641 persons who aged over 30 years old. Using a Monte-Carlo simulation for uncertainty analysis, we evaluated that the population risk of benzene during ten years in Ulsan city is 2.90 persons (5 percentile: 0.32~95 percentile: 9.11persons). And the monthly average WTP for 5/1,000 cancer mortality reduction during ten years is 14,852 Won(95% C.I: 13,135~16,794 Won) and the implied VSL is 36 million Won(95% C.I: 30~40 million Won). Cancer damage cost due to risk from benzene inhalation during 10 years in Ulsan city is about 104 million Won(5 percentile: 13~95 percentile: 328 million Won). Health benefit cost to reduce a cancer mortality risk of benzene is about 50 million Won is Ulsan metropolitann city. But, it is very important that this cost is not for all health damage cost of cancer mortality in some area. We just recommended a model for evaluating a cancer risk reduction, so we must re-evaluate an integrated application of total VOCs damage cost including benzene.

• Korean Journal of Ecology and Environment
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• 제38권2호통권112호
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• pp.225-236
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• 2005

The protection of public health In wastewater reclamation and reuse is one of the most important issues. Monitoring data of Escherichia coli were collected from paddy rice plots in 2003 and 2004 experiments. Five treatments were used and each one was triplicated to evaluate the changes of E. coli: surface water, biofilter effluent (secondary level), UV-disinfected water and pond treatment. Microbial risk was quantified to assess human health risk by exposure to E. coli in paddy rice plots, which were irrigated with reclaimed wastewater. Beta-Poisson model was used to estimate the microbial risk of pathogen ingestion that may occur to farmer and neighbor children. Monte-Carlo analysis (10,000 trials) was used to estimate the risk characterization of uncertainty. In the following analysis, two scenarios were related to the reduction of risk against direct ingestion and exposure times. Scenarios A and B were assumed that the risk was 1,000 and 10,000 times lower than direct ingestion.'Golfers were assumed to be 0.001 L of reclaimed water by contact with balls and their cloths. Opportunity of contact in paddy rice field with pathogens was more frequent than handing golf balls, because of agricultural activity was practiced in ponded water in paddy rice culture. As a result of microbial risk assessment using total data of experimental period, risk value of E. coli in 2003 and 2004 experiment ranged from $10^{-5}$ to $10^{-8}$ and $10^{-4}$ to $10^{-8}$, respectively. The risk values in biofilter effluent irrigation was the highest, which is $10^{-4}$ in 2003 and $10^{-5}$ in 2004 experiments with scenario A. Ranges of $10^{-6}$ to $10^{-8}$ were considered at reasonable levels of risk for communicable disease transmission from environmental exposure and the risk value above $10^{-4}$ was considered to be attributable to the risk of infection. Irrigation with UV-disinfected water in the paddy field during the agricultural Period showed significantly lower microbial risk than others, and their levels of risk value were within the range of actual paddy rice field with surface water.

• Journal of Preventive Medicine and Public Health
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• 제16권1호
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• pp.135-152
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• 1983

Emergency medical service is an important part of the health care delivery system, and the optimal allocation of resources and their efficient utilization are essentially demanded. Since these conditions are the prerequisite to prompt treatment which, in turn, will be crucial for life saving and in reducing the undesirable sequelae of the event. This study, taking the hyperbaric chamber for carbon monoxide poisoning as an example, is to develop a stochastic approach for solving the problems of optimal allocation of such emergency medical facility in Korea. The hyperbaric chamber, in Korea, is used almost exclusively for the treatment of acute carbon monoxide poisoning, most of which occur at home, since the coal briquette is used as domestic fuel by 69.6 per cent of the Korean population. The annual incidence rate of the comatous and fatal carbon monoxide poisoning is estimated at 45.5 per 10,000 of coal briquette-using population. It offers a serious public health problem and occupies a large portion of the emergency outpatients, especially in the winter season. The requirement of hyperbaric chambers can be calculated by setting the level of the annual queueing rate, which is here defined as the proportion of the annual number of the queued patients among the annual number of the total patients. The rate is determined by the size of the coal briquette-using population which generate a certain number of carbon monoxide poisoning patients in terms of the annual incidence rate, and the number of hyperbaric chambers per hospital to which the patients are sent, assuming that there is no referral of the patients among hospitals. The queueing occurs due to the conflicting events of the 'arrival' of the patients and the 'service' of the hyperbaric chambers. Here, we can assume that the length of the service time of hyperbaric chambers is fixed at sixty minutes, and the service discipline is based on 'first come, first served'. The arrival pattern of the carbon monoxide poisoning is relatively unique, because it usually occurs while the people are in bed. Diurnal variation of the carbon monoxide poisoning can hardly be formulated mathematically, so empirical cumulative distribution of the probability of the hourly arrival of the patients was used for Monte Carlo simulation to calculate the probability of queueing by the number of the patients per day, for the cases of one, two or three hyperbaric chambers assumed to be available per hospital. Incidence of the carbon monoxide poisoning also has strong seasonal variation, because of the four distinctive seasons in Korea. So the number of the patients per day could not be assumed to be distributed according to the Poisson distribution. Testing the fitness of various distributions of rare event, it turned out to be that the daily distribution of the carbon monoxide poisoning fits well to the Polya-Eggenberger distribution. With this model, we could forecast the number of the poisonings per day by the size of the coal-briquette using population. By combining the probability of queueing by the number of patients per day, and the probability of the number of patients per day in a year, we can estimate the number of the queued patients and the number of the patients in a year by the number of hyperbaric chamber per hospital and by the size of coal briquette-using population. Setting 5 per cent as the annual queueing rate, the required number of hyperbaric chambers was calculated for each province and for the whole country, in the cases of 25, 50, 75 and 100 per cent of the treatment rate which stand for the rate of the patients treated by hyperbaric chamber among the patients who are to be treated. Findings of the study were as follows. 1. Probability of the number of patients per day follows Polya-Eggenberger distribution. $$P(X=\gamma)=\frac{\Pi\limits_{k=1}^\gamma[m+(K-1)\times10.86]}{\gamma!}\times11.86^{-{(\frac{m}{10.86}+\gamma)}}$$ when$${\gamma}=1,2,...,n$$$$P(X=0)=11.86^{-(m/10.86)}$$ when $${\gamma}=0$$ Hourly arrival pattern of the patients turned out to be bimodal, the large peak was observed in $7 : 00{\sim}8 : 00$ a.m., and the small peak in $11 : 00{\sim}12 : 00$ p.m. 2. In the cases of only one or two hyperbaric chambers installed per hospital, the annual queueing rate will be at the level of more than 5 per cent. Only in case of three chambers, however, the rate will reach 5 per cent when the average number of the patients per day is 0.481. 3. According to the results above, a hospital equipped with three hyperbaric chambers will be able to serve 166,485, 83,242, 55,495 and 41,620 of population, when the treatmet rate are 25, 50, 75 and 100 per cent. 4. The required number of hyperbaric chambers are estimated at 483, 963, 1,441 and 1,923 when the treatment rate are taken as 25, 50, 75 and 100 per cent. Therefore, the shortage are respectively turned out to be 312, 791. 1,270 and 1,752. The author believes that the methodology developed in this study will also be applicable to the problems of resource allocation for the other kinds of the emergency medical facilities.