Parameter and model uncertainty in a life-table model for fine particles (PM2.5): a statistical modeling study.

BACKGROUND: The estimation of health impacts involves often uncertain input variables and assumptions which have to be incorporated into the model structure. These uncertainties may have significant effects on the results obtained with model, and, thus, on decision making. Fine particles (PM2.5) are believed to cause major health impacts, and, consequently, uncertainties in their health impact assessment have clear relevance to policy-making. We studied the effects of various uncertain input variables by building a life-table model for fine particles. METHODS: Life-expectancy of the Helsinki metropolitan area population and the change in life-expectancy due to fine particle exposures were predicted using a life-table model. A number of parameter and model uncertainties were estimated. Sensitivity analysis for input variables was performed by calculating rank-order correlations between input and output variables. The studied model uncertainties were (i) plausibility of mortality outcomes and (ii) lag, and parameter uncertainties (iii) exposure-response coefficients for different mortality outcomes, and (iv) exposure estimates for different age groups. The monetary value of the years-of-life-lost and the relative importance of the uncertainties related to monetary valuation were predicted to compare the relative importance of the monetary valuation on the health effect uncertainties. RESULTS: The magnitude of the health effects costs depended mostly on discount rate, exposure-response coefficient, and plausibility of the cardiopulmonary mortality. Other mortality outcomes (lung cancer, other non-accidental and infant mortality) and lag had only minor impact on the output. The results highlight the importance of the uncertainties associated with cardiopulmonary mortality in the fine particle impact assessment when compared with other uncertainties. CONCLUSION: When estimating life-expectancy, the estimates used for cardiopulmonary exposure-response coefficient, discount rate, and plausibility require careful assessment, while complicated lag estimates can be omitted without this having any major effect on the results.

Source-specific fine particles in urban air and respiratory function among adult asthmatics.

Fine and ultrafine particles in ambient air are more consistently associated with severe adverse health effects than coarse particles. We assessed whether the effects of PM(2.5) on peak expiratory flow (PEF) and respiratory symptoms in asthma patients differ by the source or the chemical properties of particles. A panel of 57 adult asthmatics was followed for 181 days from November 1996 to April 1997 with 3 daily PEF measurements and diaries. Air quality, including elemental analyses of PM(2.5) filters every 2 days (n= 83), was monitored at a central site. Daily concentrations of PM(2.5) from different sources were estimated using principal component analysis and multiple linear regression. Associations of PM(2.5) from different sources with respiratory endpoints were examined using a generalized least squares autoregressive model after adjustment for covariates. PM(2.5) attributable to local combustion was consistently negatively associated with all measurements of PEF. One interquartile increase (1.3 microg/m(3)) in 5-day average concentrations of PM(2.5) attributable to local combustion was associated with an average 1.14 L/min decline in evening PEF (95% CI: -1.95 to -0.33 L/min). We also observed that PM(2.5) attributable to long-range transport was positively, and soil-derived PM(2.5) negatively, associated with PEF. No consistent associations were observed between source-specific PM(2.5) and respiratory symptoms or between individual chemical elements and any respiratory endpoints. Our results suggest that the negative effects of PM(2.5) on PEF in adult asthmatics are mainly mediated by particles related to local combustion sources.

Structure-based classification of active and inactive estrogenic compounds by decision tree, LVQ and kNN methods.

The performance of decision tree (DT), learning vector quantization (LVQ), and k-nearest neighbour (kNN) methods classifying active and inactive estrogenic compounds in terms of their structure activity relationship (SAR) was evaluated. A set of 311 compounds was used for construction of the models, the predictive power of which was verified with separate training and test sets. Principal components derived from molecular descriptors calculated with DRAGON software were used as variables representing the structures of the compounds. Broadly, kNN had the best classification ability and DT the weakest, although the performance of each method was dependent on the group of compounds used for modelling. The best performance was obtained with kNN for the calf estrogen receptor data, averaging 98.3% of correctly classified compounds in the external tests. Overall, the results indicate that all the methods tested are suitable for the SAR classification of estrogenic compounds, producing models with a predictive power ranging from adequate to excellent.

Thermophilic aeration of cattle slurry with whey and/or jam wastes.

Thermophilic aeration of cattle slurry and food industrial by-products was studied with the aim to improve hygienic qualities of the slurry so that it could be used as a safe fertiliser for berries to be eaten raw. We also wanted to study if the process would be energetically favourable in an arctic climate. Cattle slurry alone or with whey and/or jam waste was treated. The tests were done in a well heat-insulated reactor with a 10 m(3) volume. Temperature increases up to over 70 degrees C could be recorded in 19 days even though some processes were carried out in winter time when the ambient air temperature was less than 0 degrees C. The heat energy formed was higher than the electrical energy needed to carry out the aeration. The hygienic qualities of the aerated product were good with only minor nitrogen losses. The end product could be useful as a fertiliser and soil improving compound to increase the organic matter content of agricultural soil. Cattle slurry alone was well suited as the raw material if attaining a high temperature was the main goal. A part of slurry could be replaced with food-industrial side products. Whey waste suited better for co-composting than jam waste but the mixture of whey, jam waste, and slurry was optimal for composting.

Photometrically measured continuous personal PM(2.5) exposure: levels and correlation to a gravimetric method.

There is evidence that hourly variations in exposure to airborne particulate matter (PM) may be associated with adverse health effects. Still there are only few published data on short-term levels of personal exposure to PM in community settings. The objectives of the study were to assess hourly and shorter-term variations in personal PM(2.5) exposure in Helsinki, Finland, and to compare results from portable photometers to simultaneously measured gravimetric concentrations. The effect of relative humidity on the photometric results was also evaluated. Personal PM(2.5) exposures of elderly persons were assessed for 24 h every second week, resulting in 308 successful measurements from 47 different subjects. Large changes in concentrations in minutes after cooking or changing microenvironment were seen. The median of daily 1-h maxima was over twice the median of 24-h averages. There was a strong significant association between the two means, which was not linear. Median (95th percentile) of the photometric 24-h concentrations was 12.1 (37.7) and of the 24-h gravimetric concentrations 9.2 (21.3) microg/m3. The correlation between the photometric and the gravimetric method was quite good (R2=0.86). Participants spent 94.1% of their time indoors or in a vehicle, where relative humidity is usually low and thus not likely to cause significant effects on photometric results. Even outdoors, the relative humidity had only modest effect on concentrations. Photometers are a promising method to explore the health effects of short-term variation in personal PM(2.5) exposure.

Resuspended dust episodes as an urban air-quality problem in subarctic regions.

OBJECTIVES: This paper describes the resuspension of road dust in an urban subarctic environment and focuses especially on the effect of wind speed on the formation of resuspended dust episodes. METHODS: The study was conducted in Kuopio, Finland, in the spring of 1995. There were 36 daily measurements of mass concentrations of fine particulate matter (PM2.5), thoracic particulate matter (PM10), total suspended particulate matter, black carbon and carbon monoxide; size-segregated number concentrations of particles (diameter range 0.01-10 microm); and meteorological parameters. Total elemental compositions of PM2.5 and PM10 samples were analyzed with inductively coupled plasma mass spectrometry. RESULTS: The mass and number concentrations of particles in all the size ranges and the concentrations of soil-derived (iron) and combustion-derived (vanadium and lead) elements in the PM2.5 and PM10 increased during the dust episodes. The daily average wind speed dually affected the episodes. The pollutant concentrations increased at wind speeds of <4 m/s and >5 m/s. The former was related to inversion-type conditions characterized by low wind speeds, while the latter was likely to be due to wind-blown resuspended dust. Resuspended lead accounted for an average of 27% of the total lead, and resuspended vanadium for 46% of the total vanadium in PM2.5. CONCLUSIONS: Resuspended dust episodes were related to both low and high wind speeds, and the relationship suggests that factors other than wind speed, such as turbulence induced by traffic, affect the emergence of such episodes. The contribution of elevated levels of crustal material and toxic metals in resuspended PM2.5 to human adverse health effects should be investigated.

Sources of fine particulate matter in personal exposures and residential indoor, residential outdoor and workplace microenvironments in the Helsinki phase of the EXPOLIS study.

OBJECTIVES: This study assessed the source contributions to the mass concentrations of fine particles (PM2.5) in personal exposures and in residential indoor, residential outdoor, and workplace indoor microenvironments of the nonsmoking adult population unexposed to environmental tobacco smoke in Helsinki, Finland. METHODS: The elemental composition of 48-hour personal exposure and residential indoor, residential outdoor, and workplace indoor PM2.5 was analyzed by energy-dispersive X-ray fluorescence spectrometry for 76 participants not exposed to environmental tobacco smoke and 102 participating residences with no smoking in Helsinki as a part of the EXPOLIS study. Subsequently, a principal component analysis was used to identify the emission sources of PM2.5-bound elements and black smoke in each microenvironment, and this information was used to identify the corresponding sources in personal exposures. Finally, source reconstruction was done to determine the relative contributions of each source type to the total PM2.5 mass concentrations. RESULTS: Inorganic secondary particles, primary combustion, and soil were the dominant source types for the PM2.5 mass concentration in all the microenvironments and personal exposures. The ratio of the residential indoor-to-outdoor PM2.5 concentration was close to unity, but the corresponding elemental ratios and source contributions varied. Resuspension of soil dust tracked indoors was a much larger contributor to residential and workplace indoor PM2.5 than soil dust to residential outdoor PM2.5. Source contributions to personal PM2.5 exposures were best approximated by data from residential and workplace indoor microenvironments. CONCLUSIONS: Population exposure assessment of PM2.5, based on outdoor fixed-site monitoring, overestimates exposures to outdoor sources like traffic and long-range transport and does not account for the contribution of significant indoor sources.

Theoretical analysis of the influence of aerosol size distribution and physical activity on particle deposition pattern in human lungs.

OBJECTIVES: A theoretical comparison of modeled particle depositions in the human respiratory tract was performed by taking into account different particle number and mass size distributions and physical activity in an urban environment. METHODS: Urban-air data on particulate concentrations in the size range 10 nm-10 microm were used to estimate the hourly average particle number and mass size distribution functions. The functions were then combined with the deposition probability functions obtained from a computerized ICRP 66 deposition model of the International Commission on Radiological Protection to calculate the numbers and masses of particles deposited in five regions of the respiratory tract of a male adult. The man's physical activity and minute ventilation during the day were taken into account in the calculations. RESULTS: Two different mass and number size distributions of aerosol particles with equal (computed) <10 microm particle mass concentrations gave clearly different deposition patterns in the central and peripheral regions of the human respiratory tract. The deposited particle numbers and masses were much higher during the day (0700-1900) than during the night (1900-0700) because an increase in physical activity and ventilation were temporally associated with highly increased traffic-derived particles in urban outdoor air. CONCLUSIONS: In future analyses of the short-term associations between particulate air pollution and health, it would not only be important to take into account the outdoor-to-indoor penetration of different particle sizes and human time-activity patterns, but also actual lung deposition patterns and physical activity in significant microenvironments.

Chemical inhibition of PCDD/F formation in incineration processes.

This review summarises results of our pilot-scale experiments to find suitable inhibitors for preventing the formation of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/F) during waste incineration and to specify the role of the main factors affecting the inhibition process, and is based on doctoral dissertation of Ruokojaärvi (2002). Results of previous experiments reported by other researchers are also presented and compared with ours. The detailed aims of our experiments were (1) to compare the effects of different inhibitors on PCDD/F formation during incineration in a pilot plant, (2) to investigate the role of the particle size distribution of the flue gas on the inhibition of PCDD/Fs, and (3) to find the main parameters affecting PCDD/F inhibition in waste incineration. Prevention of the formation of PCDD/Fs with chemical inhibitors and the effects of different supply points, feed temperatures and process parameters were studied in a pilot scale incinerator (50 kW) using light heating oil and refuse-derived fuel as test fuels. Various concentrations of the gaseous inhibitors (sulfur dioxide, ammonia, dimethylamine and methyl mercaptan) were sprayed into the flue gases after the furnace, in addition to which urea was dissolved in water and injected in at different concentrations. The residence time of the flue gas between the furnace and the PCDD/F sampling point was varied in the tests. In another set of urea tests, urea-water solutions at three concentrations were mixed with the RDF prior to incineration. PCDD/F and chlorophenol concentrations, together with other flue gas parameters (e.g. temperature, O2, CO, CO2 and NO), were analysed in the cooling flue gases. The gaseous and liquid inhibitors both notably reduced PCDD/F concentrations in the flue gas, the reductions achieved with the gaseous inhibitors varying from 50 to 78%, with dimethyl amine the most effective, while that produced with urea was up to 90%. The PCDD/F reductions were greater at increased inhibitor concentrations and with increased residence time of the flue gas between the furnace and the sampling point. PCDD/F concentrations in the particle phase decreased much more markedly than those in the gas phase. The urea inhibitor did not alter the particle size distribution of the PCDD/Fs when the amount of inhibitor was adequate. Chemical inhibitors seem to offer a very promising technique for preventing the formation of PCDD/Fs in waste incineration. The addition of urea to the fuel before combustion proved to be very effective approach and could be a useful technique even in the full-scale incinerators.

NMR and molecular modeling in environmental chemistry: prediction of 13C chemical shifts in selected C10-chloroterpenes employing DFT/GIAO theory.

Accurate predictions of 13C NMR chemical shifts (standard error approximately 1.7 ppm) are achieved for a subset of chlorinated bornanes by empirical scaling of shifts from GIAO calculations with geometries obtained from HF/6-31G* calculations. The optimized molecular geometries were compared with X-ray structures for three of the toxaphene components most frequently detected in environmental samples (Parlar nos. 26, 50 and 62), and the concordance between the experimental and calculated values was found to be satisfactory. Taken overall, the results indicate that theoretical methods hold great promise for rationalizing 13C NMR chemical shifts in organohalogen compounds. However, it appeared that the DFT/GIAO shifts need to be empirically scaled to achieve good numerical agreement with experimental shifts in chlorinated bornanes. Obviously, there is a need to develop new computational methods to describe the large deshielding effects of chlorine atoms properly.

Effects of physical activity on the deposition of traffic-related particles into the human lungs in silico.

Traffic-related particle emissions have been a great concern over a number of years due to their adverse health effects. In this research project, traffic-related particle deposition in the human lungs is studied using lung deposition estimates based on the ICRP 66 model. This study covers four human groups, i.e. adult males, adult females and two groups of children aged 5 and 10 years. The study examines particle deposition in the human lungs in relation to four different physical exercise levels, i.e. sleeping, sitting, light exercise and heavy exercise. To conduct the study, the particle size distributions of diesel and compressed natural gas (CNG) busses were monitored in field laboratory conditions. The study indicates that the total number of diesel particles measured is greater than the total number of CNG particles. The results further display that most of the diesel particles measured are smaller than 0.2 µm, whereas the CNG particles are smaller than 0.05 µm in aerodynamic diameter. The level of physical exercise, as well as the age and gender of a person affects the deposition of particles in the lungs. An increase in the physical activity results in larger amounts of small-size particles penetrating deeper into the respiratory system. The lung deposition of particles in males was substantially different compared to that of females and children. The deposited dose of particles was generally lower for females than for males and further lower for children than for females. This article argues that these groups should be discussed separately when conducting exposure assessments and that the level of physical activity should be taken into account when assessing potential health consequences.

Exposure assessment of particulates of diesel and natural gas fuelled buses in silico.

Lung deposition estimates of particulate emissions of diesel and natural gas (CNG) fuelled vehicles were studied by using in silico methodology. Particulate emissions and particulate number size distributions of two Euro 2 petroleum based diesel buses and one Euro 3 gas bus were measured. One of the petroleum based diesel buses used in the study was equipped with an oxidation catalyst on the vehicle (DI-OC) while the second had a partial-DPF catalyst (DI-pDPF). The third bus used was the gas bus with an oxidation catalyst on the vehicle (CNG-OC). The measurements were done using a transient chassis dynamometer test cycle (Braunschweig cycle) and an Electric Low Pressure Impactor (ELPI) with formed particulates in the size range of 7 nm to 10 microm. The total amounts of the emitted diesel particulates were 88-fold for DI-OC and 57-fold for DI-pDPF compared to the total amount of emitted CNG particulates. Estimates for the deposited particulates were computed with a lung deposition model ICRP 66 using in-house MATLAB scripts. The results were given as particulate numbers and percentages deposited in five different regions of the respiratory system. The percentages of particulates deposited in the respiratory system were 56% for DI-OC, 51% for DI-pDPF and 77% for CNG-OC of all the inhaled particulates. The result shows that under similar conditions the total lung dose of particulates originating from petroleum diesel fuelled engines DI-OC and DI-pDPF was more than 60-fold and 35-fold, respectively, compared to the lung dose of particulates originating from the CNG fuelled engine. The results also indicate that a majority (35-50%) of the inhaled particulates emitted from the tested petroleum diesel and CNG engines penetrate deep into the unciliated regions of the lung where gas-exchange occurs.

Spectroscopic QSAR methods and self-organizing molecular field analysis for relating molecular structure and estrogenic activity.

The performance of three "spectroscopic" quantitative structure-activity relationship (QSAR) methods (eigenvalue (EVA), electronic eigenvalue (EEVA), and comparative spectra analysis (CoSA)) for relating molecular structure and estrogenic activity are critically evaluated. The methods were tested with respect to the relative binding affinities (RBA) of a diverse set of 36 estrogens previously examined in detail by the comparative molecular field analysis method. The CoSA method with (13)C chemical shifts appears to provide a predictive QSAR model for this data set. EEVA (i.e., molecular orbital energy in this context) is a borderline case, whereas the performances of EVA (i.e., vibrational normal mode) and CoSA with (1)H shifts are substandard and only semiquantitative. The CoSA method with (13)C chemical shifts provides an alternative and supplement to conventional 3D QSAR methods for rationalizing and predicting the estrogenic activity of molecules. If CoSA is to be applied to large data sets, however, it is desirable that the chemical shifts are available from common databases or, alternatively, that they can be estimated with sufficient accuracy using fast prediction schemes. Calculations of NMR chemical shifts by quantum mechanical methods, as in this case study, seem to be too time-consuming at this moment, but the situation is changing rapidly. An inherent shortcoming common to all spectroscopic QSAR methods is that they cannot take the chirality of molecules into account, at least as formulated at present. Moreover, the symmetry of molecules may cause additional problems. There are three pairs of enantiomers and nine symmetric (C(2) or C(2)(v)) molecules present in the data set, so that the predictive ability of full 3D QSAR methods is expected to be better than that of spectroscopic methods. This is demonstrated with SOMFA (self-organizing molecular field analysis). In general, the use of external test sets with randomized data is encouraged as a validation tool in QSAR studies.

Perspectives on the formation of polychlorinated dibenzo-p-dioxins and dibenzofurans during municipal solid waste (MSW) incineration and other combustion processes.

The pathways by which polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) are formed and the interactions between their aromatic precursors, in particular chlorophenols (ClPhs), and transition metal catalysts are discussed. A literature survey and data from pilot-scale combustion experiments allow conclusions to be drawn on the relations between ClPhs and PCDD/Fs in municipal waste incineration and other combustion processes. The results suggest that the ClPh pathway is among the most important for the formation of PCDD/Fs.

Consensus kNN QSAR: a versatile method for predicting the estrogenic activity of organic compounds in silico. A comparative study with five estrogen receptors and a large, diverse set of ligands.

Quantitative structure-activity relationships (QSARs) have proved increasingly useful for predicting the biological activities of molecules (e.g., their binding affinities to different receptors) and can be used in environmental chemistry as a preliminary tool for screening the activities of untested molecules, producing valuable information on which compounds should be tested more thoroughly with experimental affinity assays or in animals. The predictive ability of the consensus kNN QSAR method is corroborated here using a diverse set of 245 compounds, which have been assayed for their relative binding affinities to the estrogen receptor of four species: human (ER alpha and ER beta), calf, mouse, and rat. Leave-one-out cross-validation (LOO-CV) and gamma-randomization tests were applied to the QSAR models for internal validation, and separate training and test sets were used for external validation. The internal predictive abilities of the consensus models for all five data sets were convincing, with cross-validated correlation coefficients (LOO-CV q2 values) varying from 0.69 (human ER beta data) to 0.79 (human ER alpha data). The external predictive abilities were also encouraging, as the predictive r2 scores (pr-r2 values) varied from 0.62 (human ER beta data) to 0.77 (calf and mouse data). The results indicate that consensus kNN QSAR is a feasible method for rapid screening of the estrogenic activity of organic compounds.