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.

A model for evaluating physico-chemical substance properties required by consequence analysis models.

Modeling systems for analyzing the consequences of chemical emergencies require as input values a number of physico-chemical substance properties, commonly as a function of temperature at atmospheric pressure. This paper presents a mathematical model "CHEMIC", which can be used for evaluating such substance properties, assuming that six basic constant quantities are available (molecular weight, freezing or melting point, normal boiling point, critical temperature, critical pressure and critical volume). The model has been designed to yield reasonably accurate numerical predictions, while at the same time keeping the amount of input data to a minimum. The model is based on molecular theory or thermodynamics, together with empirical corrections. Mostly, model equations are based on the so-called law of corresponding states. The model evaluates substance properties as a function of temperature at atmospheric pressure. These include seven properties commonly required by consequence analysis and heavy gas dispersion modeling systems: vapor pressure, vapor and liquid densities, heat of vaporization, vapor and liquid viscosities and binary diffusion coefficient. The model predictions for vapor pressure, vapor and liquid densities and heat of vaporization have been evaluated by using the Clausius-Clapeyron equation. We have also compared the predictions of the CHEMIC model with those of the DATABANK database (developed by the AEA Technology, UK), which includes detailed semi-empirical correlations. The computer program CHEMIC could be easily introduced into consequence analysis modeling systems in order to extend their performance to address a wider selection of substances.