Biomedical subjects

Jaakko Kukkonen

Publications and source records attributed to Jaakko Kukkonen.

2 recordsLinked to original sources

PubMed2004

Statistical model for assessing the portion of fine particulate matter transported regionally and long range to urban air.

OBJECTIVES: This study attempted to develop a simple statistical model for assessing the contribution of aerosols transported regionally and those transported long range to the concentrations of fine particulate matter (PM2.5) in urban air in Helsinki. METHODS: The construction and testing of the linear regression model was based on PM2.5 measurement data from two locations in the City of Helsinki (Vallila & Kallio) and on ion concentration data obtained from the three nearest monitoring stations of The Co-operative Programme for Monitoring and Evaluating of the Long-range Transmission of Air Pollutants in Europe (EMEP). The "ion sum" was calculated on the basis of the following daily measured EMEP parameters in 1998--2000: (i) sulfate (SO4(2-)), (ii) the sum of nitrate (NO3-) and nitrogen acid (HNO3), and (iii) the sum of ammonium (NH4+) and ammonia (NH3). The ion sum was compared with sulfate as the proxy variable for PM2.5 transported long range. RESULTS: The correlation of the daily average PM2.5 concentration with the ion sum (R2=0.59-0.61) was higher than that with sulfate (R2 = 0.48-0.50). The regression estimates showed relatively small year-to-year variation. The contribution of long-range transport to the measured PM2.5 concentration in urban air in Helsinki was estimated to be 64-76%. CONCLUSIONS: The results showed a strong association between the ion sum interpolated from the EMEP data and the PM2.5 concentration measured at urban sites in Helsinki. This association can be utilized in local dispersion modeling of the PM2.5 concentration in urban air.

Air Pollutants↗

PubMed2002

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.

Atmospheric Pressure↗