Air Pollution Costs in Ukraine

Strukova, Elena; Golub, Alexander; Markandya, Anil

doi:10.2139/ssrn.932511

Cited by 16 publications

(17 citation statements)

References 26 publications

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“…This study is similar to the one conducted for Russia [5] and Ukraine [4]. These studies demonstrated how health risk analysis could be adapted and applied in the former Soviet Union, taking into account important factors such as data availability, demographics, and the composition of industrial emissions.…”

Section: Methodssupporting

confidence: 69%

“…Avaliani and Revich [8] proposed a 0.55 conversion coefficient to convert TSP into PM10 for Russia, slightly below the 0.6 conversion coefficient suggested in Larson et al [1] for Russia and in Strukova et al [4] for Ukraine. Many fo rmer Soviet regions have more combustionrelated activities than average, so using a higher coefficient to convert TSP to PM10 than the world average coefficient of 0.5 would be appropriate [5].…”

Section: Conversion Of Tsp To Pm10mentioning

confidence: 99%

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Human Health Cost of Air Pollution in Kazakhstan

Kenessariyev¹,

Golub²,

Brody³

et al. 2013

JEP

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Kazakhstan, like other former Soviet Republics, inherited a number of serious environmental problems. Air pollution is one of these serious problems, leading to significant environmental health effects on the population of Kazakhstan. This study provides a baseline analysis of health damages from air pollution, based on readily available information. Mean estimates of mortality risk attributable to air pollution are about 16,000 cases per year with a 95% confidence level of the risk not exceeding 25,500. Even taking into account all the uncertainties related to the collection and processing of primary data, as well as the application of risk analysis methodology, we conclude that air pollution in Kazakhstan constitutes a significant contribution to the environmental burden of diseases. In relative terms, the impact of air pollution on premature mortality in Kazakhstan is notably higher than in Russia and the Ukraine.

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Section: Methodssupporting

confidence: 69%

Section: Conversion Of Tsp To Pm10mentioning

confidence: 99%

Human Health Cost of Air Pollution in Kazakhstan

Kenessariyev¹,

Golub²,

Brody³

et al. 2013

JEP

Self Cite

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“…Avaliani and Revich [14] proposed a 0.55 conversion coefficient to convert TSP into PM 10 for Russia. This value is slightly below the 0.6 conversion coefficient suggested in Larson et al [15] for Russia and Strukova et al [16] proposed for Ukraine. Because many former Soviet regions have more combustion-related activities than average, a higher conversion coefficient was used than that for the world average 0.5 [17].…”

Section: Resultsmentioning

confidence: 49%

“…A number of studies in the region conducted between 1996 and 2008 have estimated health risks from air pollution in Russia and Ukraine [3,4,6,7,16,26] or Kazakhstan [27] and have generally concluded that there are significant health risks from inhalation of pollutants, particularly particulate matter. Ambient air pollution standards in the former Soviet Union required short-term pollutant estimates for all major pollution sources.…”

Section: Discussionmentioning

confidence: 99%

Risk Assessment Capacity Building Program in Zaporizhzhia Ukraine: Emissions Inventory Construction, Ambient Modeling, and Hazard Results

Caldwell

Serdyuk²,

Turos³

et al. 2013

JEP

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Historically, Ukraine has been a major source of industrial production for the former Soviet Union and the source of pollution associated with an aging industrial infrastructure. The US Environmental Protection Agency (US EPA) and the Ukrainian Ministry of Environment and Natural Resources (MENR) entered into partnership to develop Ukrainian expertise and capacity in risk assessment so that Ukraine could more effectively use its National and Regional Environmental Protection Funds and set priorities for cleanup and regulation. Ukrainian scientists, local officials, and EPA consultants conducted a pilot study in the heavily industrialized Zaporizhzhia Oblast so that the process, analytical tools, and approach for a risk assessment could be developed for and tailored to Ukrainian needs. As a first step, site-specific information was obtained from multiple sources of air pollution and an emissions inventory of air pollution developed. Efforts by local officials were critical for emissions inventory construction. After refinements were made to the inventory, Ukrainian scientists then performed exposure modeling using this information so that ambient concentrations of pollutants could be estimated. 11 industry types (i.e., enterprises) were identified as a major emission source. Results of the modeling effort demonstrated that emissions estimates of particulate matter (as measured by particles of less than 10 micron diameter or "PM 10 ") and a number of carcinogens were consistent with those from other cities with high concentrations of metallurgical industries in former Soviet Union countries, and were above safety standards. Hazard information was gathered from international databases for each of the estimated pollutants. Using such data, prioritization and identification of potential health concerns can be made, but most importantly, the expertise and experience gained from the pilot allowed for continued support of risk assessment capacity building in the Ukraine and support by the World Bank.

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“…To illustrate the implications of the IEVSL for cross-country benefit transfer, we present an example using parameters from a study by Strukova et al (2006) that estimates the mortality costs of air pollution in major Ukrainian cities. The lack of VSL estimates based on Ukrainian data necessitated the benefit transfer.…”

Section: Environmental Protection Agency's (Epa) Recently Revised Guimentioning

confidence: 99%

A Quantile Estimation Approach to Identify Income and Age Variation in the Value of a Statistical Life

Schaur

Evans

2009

SSRN Journal

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Thanks are due to V. Kerry Smith, Thomas Kniesner, W. Kip Viscusi, and J.R. DeShazo for providing helpful comments on this research. 2A quantile estimation approach to indentify income and age variation in the value of a statistical life Abstract:Theory predicts variation in the marginal willingness to pay for a mortality risk reduction with individual characteristics. Two dimensions of heterogeneity, associated with income and age differences, have recently received attention due to their policy relevance. We propose a quantile regression approach to simultaneously explore these two sources of heterogeneity and their interactions within the context of the hedonic wage model, the most common revealed preference approach for obtaining value of statistical life estimates. We illustrate the approach using data from the Health and Retirement Study (HRS). Our results confirm differences in the wage-risk tradeoff with age and across the wage distribution. In addition, we find that the effect of age on the wage-risk tradeoff varies across the wage distribution. Thus, the conventional mean hedonic wage regression, even when the mean effect is allowed to vary with age, masks important hetereogeneity.

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Air Pollution Costs in Ukraine

Cited by 16 publications

References 26 publications

Human Health Cost of Air Pollution in Kazakhstan

Human Health Cost of Air Pollution in Kazakhstan

Risk Assessment Capacity Building Program in Zaporizhzhia Ukraine: Emissions Inventory Construction, Ambient Modeling, and Hazard Results

A Quantile Estimation Approach to Identify Income and Age Variation in the Value of a Statistical Life

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