Juhani Ruuskanen

Ultrafine particles in urban air and respiratory health among adult asthmatics.

Airborne particles are associated with adverse health effects and contribute to excess mortality in epidemiological studies. A recent hypothesis proposes that the high numbers of ultrafine (<0.1 microm diameter) particles in ambient air might provoke alveolar inflammation and subsequently cause exacerbations in pre-existing cardiopulmonary diseases. To test the hypothesis adult asthmatics were followed with daily peak expiratory flow (PEF) measurements and symptom and medication diaries for six months, while simultaneously monitoring particulate pollution in ambient air. The associations between daily health endpoints of 57 asthmatics and indicators of air pollution were examined by multivariate regression models. Daily mean number concentration of particles, but not particle mass (PM10 (particle mass <10 microm), PM2.5-10, PM2.5, PM1), was negatively associated with daily PEF deviations. The strongest effects were seen for particles in the ultrafine range. However, the effect of ultrafine particles could not definitely be separated from other traffic generated pollutants, namely nitric oxide, nitrogen dioxide and carbon monoxide. No associations were observed with respiratory symptoms or medication use. Particle mass measurements can be strongly influenced by mechanically produced, soil-derived particles, which may not be associated with adverse health effects. Therefore, air quality monitoring should include particle number concentrations, which mainly reflect ultrafine particles.

Neural networks and periodic components used in air quality forecasting

Abstract Forecasting of air quality parameters is one topic of air quality research today due to the health effects caused by airborne pollutants in urban areas. The work presented here aims at comparing two principally different neural network methods that have been considered as potential tools in that area and assessing them in relation to regression with periodic components. Self-organizing maps (SOM) represent a form of competitive learning in which a neural network learns the structure of the data. Multi-layer perceptrons (MLPs) have been shown to be able to learn complex relationships between input and output variables. In addition, the effect of removing periodic components is evaluated with respect to neural networks. The methods were evaluated using hourly time series of NO2 and basic meteorological variables collected in the city of Stockholm in 1994–1998. The estimated values for forecasting were calculated in three ways: using the periodic components alone, applying neural network methods to the residual values after removing the periodic components, and applying only neural networks to the original data. The results showed that the best forecast estimates can be achieved by directly applying a MLP network to the original data, and thus, that a combination of the periodic regression method and neural algorithms does not give any advantage over a direct application of neural algorithms.

Concentrations of ultrafine, fine and PM2.5 particles in three European cities

Total number concentrations, number concentrations of ultrane (0.01}0.1 m) and accumulation (0.1}0.5 m) particles, as well as mass concentration of PM particles and blackness of PM lters, which is related to Black Smoke were simultaneously monitored in three European cities during the winter period for three and a half months. The purpose of the study was to describe the di!erences in concentration levels and daily and diurnal variations in particle number and mass concentrations between European cities. The results show statistically signicant di!erences in the concentrations of PM and the blackness of the PM lters between the cities, but not in the concentrations of ultrane particles. Daily PM levels were found to be poorly correlated with the daily total and ultrane number concentrations but better correlated with the number concentration of accumulation particles. According to the principal component analysis airborne particulate pollutants seem to be divided into two major source categories, one identied with particle number concentrations and the other related to mass-based information. The present results underline the importance of using both particle number and mass concentrations to evaluate urban air quality. 2001 Elsevier Science Ltd. All rights reserved.

Oxidation of gas mixtures containing dimethyl sulfide, hydrogen sulfide, and methanethiol using a two-stage biotrickling filter.

ABSTRACT A biofiltration technique was developed for removing a mixture of hydrogen sulfide (H2S), methanethiol (MeSH), and dimethyl sulfide (Me2S) from waste gases. Since H2S, especially at high concentrations, disturbs the removal of Me2S, two biotrickling filters with different microbes and operating pH levels were connected in series to create a two-stage system. Different loads of these gases were studied in order to determine their impact on the removal capacity of the system. The microbial consortia for these filters were enriched from the sludge of a Finnish refinery with bubbling H2S or Me2S. Acclimation for Me2S took 2 weeks, though no acclimation time was needed for the other gases. The first filter, at a pH of 2, removed most of the H2S and some of the MeSH and Me2S. The second filter, at a pH of ~6.5, removed the rest of the MeSH and most of the Me2S. The total maximum loads of the whole two-stage biotrickling filter were 1150 g/m3/day for H2S-S (suffix S indicates the results are counted as sulfur amounts), 879 g/m3/day for Me2S-S, and 66 g/m3/day for MeSH-S treated in a gas mixture. The average removal efficiencies for all gases tested were 99% or higher.

Removal of ammonia from air by a peat biofilter

Peat was studied as a filter material for removing ammonia from air. Since the peat itself contained no nitrifiers and had no nitrification potential, it was inoculated with nitrifying bacteria from nitrifying activated sludge. To achieve good nitrifying activity, the acid filter material had to be neutralized by Ca(OH)2. The addition of nutrients (P, K, Mg+ and micronutrients) increased the capacity of the filter to oxidize ammonia to nitrate. The removal of ammonia was effective (mean removal rate 95 %) when initial concentrations were less than 14 mg NH3 m−3 (1.8 g NH3 m−3 peat per hour). The biofilter became overloaded at a concentration of 45 mg NH3 m−3 (7.9 g NH3 m−3 peat per hour), which caused an accumulation of ammonium and nitrite, as the ammonium inhibited oxidation of the nitrite. The biofilter operated properly down to a temperature of 5°C, and the amounts of bacteria and fungi released from biofilter into the filtered air were low.

Comparison of concentrations and size distributions of fungal spores in buildings with and without mould problems

Abstract Concentrations and types of airborne fungal spores and their aerodynamic sizes were studied in nine buildings with mould problems and in matched reference buildings in order to characterize the exposure in buildings with mould problems. Samples were taken with Andersen six-stage impactors in the autumn and winter. In winter, total concentrations of fungal spores in buildings with mould problems were twice those in reference buildings, even though all concentrations were quite small. In the autumn, the differences were less obvious due to the masking effect of outdoor air fungi. Also, the compositions of fungal genera differed in buildings with mould problems from that in reference buildings. The difference was most significant in the size range 2.1-4.7 μm. The size distribution of fungal spores in dwellings with mould problems skewed towards larger particles than in reference dwellings. The observed differences in size distribution indicate differences in airborne behaviour of fungal spores and, consequently, in respiratory exposure.

FILTER AND LEAK PENETRATION CHARACTERISTICS OF A DUST AND MIST FILTERING FACEPIECE

The filtering facepiece, also referred to as a disposable respirator, is an extensively used type of respirator without an officially accepted fit testing method. This study describes an aerosol generator and a sampling train, which have been developed for investigating the aerosol penetration characteristics through the filter element and the face seal. Electrostatic attraction and impaction are the two primary filtration mechanisms for micrometer- and supermicrometer-sized aerosols, respectively. Filtration and flow dynamics were found to affect aerosol penetration in distinct ways that allow for the differentiation of the face seal leakage from the filter penetration. The slope of the aerosol size-dependent penetration curve potentially may differentiate the face seal leakage from filter penetration.

Peat Biofilters in Long-Term Experiments for Removing Odorous Sulphur Compounds

AbstractPeat was employed as a biological filter material for the removal of hydrogen sulphide (H2>nS) dimethyl sulphide (Me2S) and methyl mercaptan (MeSH) from odorous ventilation air. Removal of H2S was possible without the need to inoculate the filter material with oxidizing microbes whereas Me2S required inoculation for degradation. The removal of Me2S was decreased as a result of MeSH addition. Liming of the filter material, i.e., addition of calcium hydroxide, increased removal efficiency and activated the oxidation of H2S without any adaptation period. As a consequence of the poor Me2S removal efficiency of natural peat, a limed and inoculated biofilter was needed to purify mixtures of gases containing sulphur. The highest H2S load tested with limed but otherwise natural peat was 136 g-S m-3 day-1, yielding a 99 % reduction. The maximum Me2S elimination capacity with limed and inoculated peat was 175 g-S m-3day-1, but removal became unstable when the load exceeded 150 g-S m-3day-1. The maximum MeSH load tested was 107 g-S m-3day-1, yielding 98 % removal.

Carbon disulfide and hydrogen sulfide removal with a peat biofilter.

ABSTRACT Simultaneous removal of H2S and CS2 was studied with a peat biofilter inoculated with a Thiobacillus strain that oxidizes both compounds in an acidic environment. Both sulfurous gases at concentrations below 600 mg S/m3 were efficiently removed, and the removal efficiencies were similar, 99%, with an empty bed retention time (EBRT) of more than 60 sec. Concentrations greater than 1300-5000 mg S/m3 caused overloading of the filter material, resulting in high H2SO4 production, accumulation of elemental sulfur, and reduced removal efficiency. The highest sulfur removal rate achieved was 4500 g-S/day/m3 filter material. These results indicate that peat is suitable as a biofilter material for the removal of a mixture of H2S and CS2 when concentrations of gases to be purified are low (less than 600 mg/m3), but it is still odorous and toxic to the environment and humans.

Intercomparison of Aerosol Spectrometers for Ambient Air Monitoring

Three aerosol spectrometers measuring the number concentration distribution of particles in the diameter range 0.01 to 2.5 w m were compared by running them side-by-side for 385 h under ambient air conditions in Erfurt, Germany in October 1997. From the spectral data the measured hourly number concentrations in 3 size fractions, the ultrafine fraction (0.01-0.1 w m), the accumulation fraction (0.1-0.5 w m), and the coarse fraction (0.5-2.5 w m), were analyzed. The systematic component of the difference between the instruments was assessed as the geometric mean of the ratio of the measured concentrations (GMR) and the random component as the geometric standard deviation of this ratio (GSR). Previous statistical methods to compare instruments were developed further. A nonlinear multivariate regression method was used to compare the aerosol distribution consisting of several size fractions. Also, the imprecision of the individual instruments (GSI) was estimated. Comparing the instruments within the ultrafine and accumulation fractions, both the GMRs and GSRs ranged between 1.06 and 1.23 and correlations were above 0.98. In the coarse fraction, the GMR of the number concentrations ranged between 0.25 and 4.19, the GSRs between 1.81 and 2.61, and the correlations between 0.72 and 0.85. The GSIs of the instruments were below 1.2 for all fractions but the coarse fraction. To explore possible differences in the classification of particles into the accumulation and coarse fractions, coarse fractions were regressed with the coarse and the accumulation fractions of the other instruments. Using a conversion based on this regression, the GSRs between instruments were minimized to 1.35 and the GSI to below 1.3. In conclusion, the aerosol spectrometers were in good agreement in the ultrafine and accumulation size fractions. The differences in the measured number concentrations in the coarse fraction were effectively corrected by using a regression method taking into account also the concentration in accumulation fraction, which suggests possible differences in particle sizing at 0.5 w m.