Health impact assessment of transportation noise in two Estonian cities.

Transportation noise is a growing public health concern worldwide, especially in urban areas, causing annoyance, sleep disturbance, cardiovascular diseases and other health effects. Recently, European Commission (EC) has developed a mutual methodology for assessing health impacts of transportation noise in European Union using strategic noise mapping. Applying this methodology, our aim was to quantify the health effects of road, rail and aircraft noise in two Estonian cities, Tallinn and Tartu. We also aimed to assess sensitivity of this methodology, while implementing lower threshold values and employing additional health outcomes. The proportion of highly annoyed residents due to road traffic noise was 11.6% in Tallinn, and 9.2% in Tartu; around 2.5% residents in both cities could have high sleeping disturbances. As exposure to railway and aircraft noise was relatively low in both cities, people with high annoyance and high sleep disturbance caused by railway and aircraft noise was below 1%. Ischemic heart disease (IHD) cases attributable to road traffic noise was estimated to be 122.6 in Tallinn and 21.5 in Tartu. Altogether transportation noise was estimated to cause 1807 disability adjusted life years (DALYs) in Tallinn and 370 DALYs in Tartu. The health costs were calculated as €126.5 and €25.9 million annually, respectively in the two cities. When we included higher number of health outcomes (stroke incidence, IHD deaths) and lowered exposure threshold by 5 dB, the annual burden of disease was doubled. As the latest epidemiological studies showed transportation noise having larger number of effects on lower noise levels, the results with the currently applied European Commission health impact assessment (HIA) methodology were rather conservative. Despite of uncertainties associated to applied methodology, transportation noise, especially road traffic noise, is an important environmental risk factor, that leads to considerable loss of healthy life years and causes large health costs in urban areas.

Health impacts of PM2.5 originating from residential wood combustion in four nordic cities.

BACKGROUND: Residential wood combustion (RWC) is one of the largest sources of fine particles (PM2.5) in the Nordic cities. The current study aims to calculate the related health effects in four studied city areas in Sweden, Finland, Norway, and Denmark. METHODS: Health impact assessment (HIA) was employed as the methodology to quantify the health burden. Firstly, the RWC induced annual average PM2.5 concentrations from local sources were estimated with air pollution dispersion modelling. Secondly, the baseline mortality rates were retrieved from the national health registers. Thirdly, the concentration-response function from a previous epidemiological study was applied. For the health impact calculations, the WHO-developed tool AirQ + was used. RESULTS: Amongst the studied city areas, the local RWC induced PM2.5 concentration was lowest in the Helsinki Metropolitan Area (population-weighted annual average concentration 0.46 µg m- 3) and highest in Oslo (2.77 µg m- 3). Each year, particulate matter attributed to RWC caused around 19 premature deaths in Umeå (95% CI: 8-29), 85 in the Helsinki Metropolitan Area (95% CI: 35-129), 78 in Copenhagen (95% CI: 33-118), and 232 premature deaths in Oslo (95% CI: 97-346). The average loss of life years per premature death case was approximately ten years; however, in the whole population, this reflects on average a decrease in life expectancy by 0.25 (0.10-0.36) years. In terms of the relative contributions in cities, life expectancy will be decreased by 0.10 (95% CI: 0.05-0.16), 0.18 (95% CI: 0.07-0.28), 0.22 (95% CI: 0.09-0.33) and 0.63 (95% CI: 0.26-0.96) years in the Helsinki Metropolitan Area, Umeå, Copenhagen and Oslo respectively. The number of years of life lost was lowest in Umeå (172, 95% CI: 71-260) and highest in Oslo (2458, 95% CI: 1033-3669). CONCLUSIONS: All four Nordic city areas have a substantial amount of domestic heating, and RWC is one of the most significant sources of PM2.5. This implicates a substantial predicted impact on public health in terms of premature mortality. Thus, several public health measures are needed to reduce the RWC emissions.

Perinatal Health Inequalities in the Industrial Region of Estonia: A Birth Registry-Based Study.

Despite the increasing number of studies on industrially contaminated sites (ICS) and their health effects, there are very few studies on perinatal health outcomes in ICSs. In the present study, we examined the perinatal health inequalities by comparing adverse birth outcomes (ABOs) in the oil shale industry region of Ida-Viru County in Estonia with national-level figures and investigated the effects of maternal environmental and sociodemographic factors. Based on the 208,313 birth records from 2004-2018, Ida-Viru ICS has a birth weight 124.5 g lower than the average of 3544 g in Estonia. A higher prevalence of preterm birth (4.3%) and low birth weight (4.8%) in Ida-Viru ICS is found compared to 3.3% on both indicators at the national level. Multiple logistic regression analysis shows the statistically significant association of ABOs with fine particle (PM2.5) air pollution, mother's ethnicity, and education throughout Estonia. However, in Ida-Viru ICS, the ABOs odds are remarkably higher in these characteristics except for the mother's ethnicity. Furthermore, the ABOs are associated with the residential proximity to ICS. Thus, the Ida-Viru ICS has unequally higher odds of adverse perinatal health across the environmental and sociodemographic factors. In addition to reducing the air pollutants, policy actions on social disparities are vital to address the country's unjustly higher perinatal health inequalities, especially in the Ida-Viru ICS.

Health impact assessment of particulate pollution in Tallinn using fine spatial resolution and modeling techniques.

BACKGROUND: Health impact assessments (HIA) use information on exposure, baseline mortality/morbidity and exposure-response functions from epidemiological studies in order to quantify the health impacts of existing situations and/or alternative scenarios. The aim of this study was to improve HIA methods for air pollution studies in situations where exposures can be estimated using GIS with high spatial resolution and dispersion modeling approaches. METHODS: Tallinn was divided into 84 sections according to neighborhoods, with a total population of approx. 390,000 persons. Actual baseline rates for total mortality and hospitalization with cardiovascular and respiratory diagnosis were identified. The exposure to fine particles (PM2.5) from local emissions was defined as the modeled annual levels. The model validation and morbidity assessment were based on 2006 PM10 or PM2.5 levels at 3 monitoring stations. The exposure-response coefficients used were for total mortality 6.2% (95% CI 1.6-11%) per 10 microg/m3 increase of annual mean PM2.5 concentration and for the assessment of respiratory and cardiovascular hospitalizations 1.14% (95% CI 0.62-1.67%) and 0.73% (95% CI 0.47-0.93%) per 10 microg/m3 increase of PM10. The direct costs related to morbidity were calculated according to hospital treatment expenses in 2005 and the cost of premature deaths using the concept of Value of Life Year (VOLY). RESULTS: The annual population-weighted-modeled exposure to locally emitted PM2.5 in Tallinn was 11.6 microg/m3. Our analysis showed that it corresponds to 296 (95% CI 76528) premature deaths resulting in 3859 (95% CI 10236636) Years of Life Lost (YLL) per year. The average decrease in life-expectancy at birth per resident of Tallinn was estimated to be 0.64 (95% CI 0.17-1.10) years. While in the polluted city centre this may reach 1.17 years, in the least polluted neighborhoods it remains between 0.1 and 0.3 years. When dividing the YLL by the number of premature deaths, the decrease in life expectancy among the actual cases is around 13 years. As for the morbidity, the short-term effects of air pollution were estimated to result in an additional 71 (95% CI 43-104) respiratory and 204 (95% CI 131-260) cardiovascular hospitalizations per year. The biggest external costs are related to the long-term effects on mortality: this is on average euro 150 (95% CI 40-260) million annually. In comparison, the costs of short-term air-pollution driven hospitalizations are small euro 0.3 (95% CI 0.2-0.4) million. CONCLUSION: Sectioning the city for analysis and using GIS systems can help to improve the accuracy of air pollution health impact estimations, especially in study areas with poor air pollution monitoring data but available dispersion models.