Prenatal and early life exposure to air pollution and the risk of severe lower respiratory tract infections during early childhood: the Espoo Cohort Study

BACKGROUND

There is inconsistent evidence of the effects of exposure to ambient air pollution on the occurrence of lower respiratory tract infections (LRTIs) in early childhood. We assessed the effects of individual-level prenatal and early life exposure to air pollutants on the risk of LRTIs in early life.

METHODS

We studied 2568 members of the population-based Espoo Cohort Study born between 1984 and 1990 and living in 1991 in the City of Espoo, Finland. Exposure assessment was based on dispersion modelling and land-use regression for lifetime residential addresses. The outcome was a LRTI based on data from hospital registers. We applied Poisson regression to estimate the incidence rate ratio (IRR) of LTRIs, contrasting incidence rates in the exposure quartiles to the incidence rates in the first quartile. We used weighted quantile sum (WQS) regression to estimate the joint effect of the studied air pollutants.

RESULTS

The risk of LRTIs during the first 2 years of life was significantly related to exposure to individual and multiple air pollutants, measured with the Multipollutant Index (MPI), including primarily sulphur dioxide (SO2), particulate matter with a dry diameter of up to 2.5 µm (PM2.5) and nitrogen dioxide (NO2) exposures in the first year of life, with an adjusted IRR of 1.72 per unit increase in MPI (95% CI 1.20 to 2.47). LRTIs were not related to prenatal exposure.

CONCLUSIONS

We provide evidence that ambient air pollution exposure during the first year of life increases the risk of LRTIs during the first 2 years of life. SO2, PM2.5 and NO2 were found to contribute the highest weights on health effects.

Effect of cold winters on the risk of new asthma: a case-crossover study in Finland

BACKGROUND

Cold weather increases respiratory symptoms and provokes exacerbations of asthma, but there are no previous studies on its role in the aetiology of asthma.

OBJECTIVE

We tested the hypothesis that a cold winter increases the risk of developing asthma during the following 1 to 2 years.

METHODS

We conducted a case-crossover study of 315 newly diagnosed cases of asthma from the population-based Espoo Cohort Study from birth to the age of 27 years. The hazard period constituted 3 winter months preceding the onset of asthma and bidirectional reference periods of 1 year before hazard period and 1 year after onset of asthma. Exposure constituted average ambient temperature during the winter months of December, January and February. The outcome of interest was new doctor-diagnosed asthma. The measure of effect was OR of asthma estimated by conditional logistic regression analysis.

RESULTS

The average winter temperature for the study period from winter 1983 to 2010 was -4.4°C (range -10.7 to 0.4). A 1°C decrease in the average winter temperature predicted a 7% increase in the risk of new asthma (OR=1.07, 95% CI 1.02 to 1.13). A cold winter with an average temperature below the climate normal value (-4.5°C; period 1981-2010) increased the risk of new asthma by 41% during the following year (OR: 1.41; 95% CI 1.04 to 1.90).

CONCLUSIONS

This case-crossover study provides original evidence that a cold winter with below normal average temperatures increases the risk of developing new asthma during the following 1 to 2 years.

An operational urban air quality model ENFUSER, based on dispersion modelling and data assimilation

An operational urban air quality modelling system ENFUSER is presented with an evaluation against measured data. ENFUSER combines several dispersion modelling approaches, uses data assimilation, and continuously extracts information from online, global open-access sources. The modelling area is described with a combination of geographic datasets. These GIS datasets are globally available with open access, and therefore the model can be applied worldwide. Urban scale dispersion is addressed with a combination of Gaussian puff and Gaussian plume modelling, and long-range transport of pollutants is accounted for via a separate regional model. The presented data assimilation method, which supports the use of AQ sensors and incorporates a longer-term learning mechanism, adjusts emission factors and the regional background values on an hourly basis. The model can be used with reasonable accuracy also in urban areas, for which detailed emissions inventories would not be available, due to the data assimilation capabilities.

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 (PM_2.5) 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 PM_2.5 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 PM_2.5 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 PM_2.5. 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 global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission conditions

This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015-2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM_2.5, PM₁₀, PMC (coarse fraction of PM), NO₂, SO₂, NOx, CO, O₃ and the total gaseous oxidant (OX = NO₂ + O₃) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015-2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO₂ and NOx concentrations and peoples' mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO₂ and between 30% and 40% in mean PM_2.5 concentrations over 2020 full lockdown compared to the same period in 2015-2019. However, PM_2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO₂/CO ratio). Some Chinese cities showed similar increases in PM_2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O₃ concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of ~70%. The SO₂ anomalies were negative for 2020 compared to 2015-2019 (between ~25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to ~40%. The NO₂/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO₂ decrease due to the general reduction in mobility (ratio of ~60%). Analysis of the total oxidant (OX = NO₂ + O₃) showed that primary NO₂ emissions at urban locations were greater than the O₃ production, whereas at background sites, OX was mostly driven by the regional contributions rather than local NO₂ and O₃ concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM_2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.

Evaluation of Methane Emissions Originating from LNG Ships Based on the Measurements at a Remote Marine Station

We analyzed pollution plumes originating from ships using liquefied natural gas (LNG) as a fuel. Measurements were performed at a station located on the Utö island in the Baltic Sea during 2015-2021 when vessels passed the station along an adjacent shipping lane and the wind direction allowed the measurements. The ratio of the measured concentration peaks ΔCH₄/ΔCO₂ ranged from 1% to 9% and from 0.1% to 0.5% for low and high pressure dual fuel engines, respectively. The ratio of the measured concentration peaks of ΔNO_x/ΔCO₂ varied between 0.5‰ and 8.7‰, which was not explained by engine type. The results were consistent with previously measured on-board or test-bed values for the corresponding ratios of emissions. While the methane emissions from high pressure dual fuel engines were found to fulfill the goal of reducing the climatic impacts of shipping, the emissions originating from low pressure dual fuel engines were found to be substantially high, with a potential for increased climatic impacts compared with using traditional marine fuels. Taking only the global warming potential into account, we can suggest a limit value for the methane emissions; the ratio of the emissions ΔCH₄/ΔCO₂ originating from LNG powered ships should not exceed 1.4%.

Long-term exposure to ambient fine particulate matter originating from traffic and residential wood combustion and the prevalence of depression

Introduction

Air pollution has been suggested to be associated with depression. However, current evidence is conflicting, and no study has considered different sources of ambient particulate matter with an aerodynamic diameter below 2.5 µm (PM_2.5). We evaluated the associations of long-term exposure to PM_2.5 from road traffic and residential wood combustion with the prevalence of depression in the Helsinki region, Finland.

Methods

We conducted a cross-sectional analysis based on the Helsinki Capital Region Environmental Health Survey 2015–2016 (N=5895). Modelled long-term outdoor concentrations of PM_2.5 were evaluated using high-resolution emission and dispersion modelling on an urban scale and linked to the home addresses of study participants. The outcome was self-reported doctor-diagnosed or treated depression. We applied logistic regression and calculated the OR for 1 μg/m³ increase in PM_2.5, with 95% CI. Models were adjusted for potential confounders, including traffic noise and urban green space.

Results

Of the participants, 377 reported to have been diagnosed or treated for depression by a doctor. Long-term exposure to PM_2.5 from road traffic (OR=1.23, 95% CI 0.86 to 1.73; n=5895) or residential wood combustion (OR=0.78, 95% CI 0.43 to 1.41; n=5895) was not associated with the prevalence of depression. The estimates for PM_2.5 from road traffic were elevated, but statistically non-significant, for non-smokers (OR=1.38, 95% CI 0.94 to 2.01; n=4716).

Conclusions

We found no convincing evidence of an effect of long-term exposure to PM_2.5 from road traffic or residential wood combustion on depression.

Short-term prenatal exposure to ambient air pollution and risk of preterm birth - A population-based cohort study in Finland

BACKGROUND

Previous studies have provided evidence that prenatal exposure to low-level air pollution increases the risk of preterm birth (PTB), but the findings of the effects of short-term exposure have been inconclusive. Moreover, there is little knowledge on potential synergistic effects of different combinations of air pollutants.

OBJECTIVES

To assess independent and joint effects of prenatal exposure to air pollutants during the week prior to the delivery on the risk of PTB.

METHODS

The study population included 2568 members of the Espoo Cohort Study, living in the City of Espoo, Finland, born between 1984 and 1990. We assessed individual-level prenatal exposure to ambient air pollutants of interest based on maternal residential addresses, while taking into account their residential mobility. We used both regional-to-city-scale dispersion modelling and land-use regression-based method to estimates the pollutant concentrations. We contrasted the risk of PTB in the highest quartile (Q₄) of exposure to the lower exposure quartiles (Q₁-Q₃) during the specific periods of pregnancy. We applied Poisson regression analysis to estimate the adjusted risk ratios (RRs) with their 95% confidence intervals (CI), adjusting for season of birth, maternal age, sex of the baby, family's socioeconomic status, maternal smoking, and exposure to environmental tobacco smoke during pregnancy, single parenthood, and exposure to other air pollutants (this in multi-pollutant models).

RESULTS

The risk of PTB was related to exposures to PM_2.5, PM₁₀ and NO₂ during the week prior to the delivery with adjusted RRs of 1.67 (95%CI: 1.14, 2.46), 1.60 (95% CI: 1.09, 2.34) and 1.65 (95% CI: 1.14, 2.37), from three-pollutant models respectively. There were no significant joint effects for these different air pollutants (during the week prior to the delivery).

CONCLUSION

Our results provide evidence that exposure to fairly low-level air pollution may trigger PTB, but synergistic effects of different pollutants are not likely.

An approach to predict population exposure to ambient air PM2.5 concentrations and its dependence on population activity for the megacity London

A comprehensive modelling approach has been developed to predict population exposure to the ambient air PM_2.5 concentrations in different microenvironments in London. The modelling approach integrates air pollution dispersion and exposure assessment, including treatment of the locations and time activity of the population in three microenvironments, namely, residential, work and transport, based on national demographic information. The approach also includes differences between urban centre and suburban areas of London by taking account of the population movements and the infiltration of PM_2.5 from outdoor to indoor. The approach is tested comprehensively by modelling ambient air concentrations of PM_2.5 at street scale for the year 2008, including both regional and urban contributions. Model analysis of the exposure in the three microenvironments shows that most of the total exposure, 85%, occurred at home and work microenvironments and 15% in the transport microenvironment. However, the annual population weighted mean (PWM) concentrations of PM_2.5 for London in transport microenvironments were almost twice as high (corresponding to 13-20 μg/m³) as those for home and work environments (7-12 μg/m³). Analysis has shown that the PWM PM_2.5 concentrations in central London were almost 20% higher than in the surrounding suburban areas. Moreover, the population exposure in the central London per unit area was almost three times higher than that in suburban regions. The exposure resulting from all activities, including outdoor to indoor infiltration, was about 20% higher, when compared with the corresponding value obtained assuming inside home exposure for all times. The exposure assessment methodology used in this study predicted approximately over one quarter (-28%) lower population exposure, compared with using simply outdoor concentrations at residential locations. An important implication of this study is that for estimating population exposure, one needs to consider the population movements, and the infiltration of pollution from outdoors to indoors.

Synergistic effects of prenatal exposure to fine particulate matter (PM2.5) and ozone (O3) on the risk of preterm birth: A population-based cohort study

BACKGROUND

There is some evidence that prenatal exposure to low-level air pollution increases the risk of preterm birth (PTB), but little is known about synergistic effects of different pollutants.

OBJECTIVES

We assessed the independent and joint effects of prenatal exposure to air pollution during the entire duration of pregnancy.

METHODS

The study population consisted of the 2568 members of the Espoo Cohort Study, born between 1984 and 1990, and living in the City of Espoo, Finland. We assessed individual-level prenatal exposure to ambient air pollutants of interest at all the residential addresses from conception to birth. The pollutant concentrations were estimated both by using regional-to-city-scale dispersion modelling and land-use regression-based method. We applied Poisson regression analysis to estimate the adjusted risk ratios (RRs) with their 95% confidence intervals (CI) by comparing the risk of PTB among babies with the highest quartile (Q₄) of exposure during the entire duration of pregnancy with those with the lower exposure quartiles (Q₁-Q₃). We adjusted for season of birth, maternal age, sex of the baby, family's socioeconomic status, maternal smoking during pregnancy, maternal exposure to environmental tobacco smoke during pregnancy, single parenthood, and exposure to other air pollutants (only in multi-pollutant models) in the analysis.

RESULTS

In a multi-pollutant model estimating the effects of exposure during entire pregnancy, the adjusted RR was 1.37 (95% CI: 0.85, 2.23) for PM_2.5 and 1.64 (95% CI: 1.15, 2.35) for O₃. The joint effect of PM_2.5 and O₃ was substantially higher, an adjusted RR of 3.63 (95% CI: 2.16, 6.10), than what would have been expected from their independent effects (0.99 for PM_2.5 and 1.34 for O₃). The relative risk due to interaction (RERI) was 2.30 (95% CI: 0.95, 4.57).

DISCUSSION

Our results strengthen the evidence that exposure to fairly low-level air pollution during pregnancy increases the risk of PTB. We provide novel observations indicating that individual air pollutants such as PM_2.5 and O₃ may act synergistically potentiating each other's adverse effects.

Residential Wood Combustion in Finland: PM2.5 Emissions and Health Impacts with and without Abatement Measures

Exposure to fine particles in ambient air has been estimated to be one of the leading environmental health risks in Finland. Residential wood combustion is the largest domestic source of fine particles, and there is increasing political interest in finding feasible measures to reduce those emissions. In this paper, we present the PM_2.5 emissions from residential wood combustion in Finland, as well as the resulting concentrations. We used population-weighed concentrations in a 250 x 250 m grid as population exposure estimates, with which we calculated the disease burden of the emissions. Compared to a projected baseline scenario, we studied the effect of chosen reduction measures in several abatement scenarios. In 2015, the resulting annual average concentrations were between 0.5 and 2 µg/m³ in the proximity of most cities, and disease burden attributable to residential wood combustion was estimated to be 3400 disability-adjusted life years (DALY) and 200 deaths. Disease burden decreased by 8% in the 2030 baseline scenario and by an additional 63% in the maximum feasible reduction scenario. Informational campaigns and improvement of the sauna stove stock were assessed to be the most feasible abatement measures to be implemented in national air quality policies.

Perioperative platelet rich plasma (PRP) in total hip arthroplasty through the Hardinge approach: protocol to study the effectiveness for gluteus medius healing

Background

Platelet-rich plasma (PRP) has been used to support tendon regeneration mainly in sports medicine. PRP is a concentrate of platelet-rich plasma proteins derived from whole blood by centrifugation to remove erythrocytes and leukocytes. PRP has high amounts of platelets which may promote healing tendons affected by degenerative conditions. These platelets contain growth factors and are known to facilitate the regeneration of injured tendon structures. Total hip arthroplasty (THA) through the Hardinge approach may leave the patient with impaired gait and poor regeneration of the gluteus medius tendon if the tendon is not reattached properly after closure of the surgical wound.

Methods

The study will be a multicenter, double-blinded and randomized study enrolling 90 patients based on power calculations. The efficacy of perioperative PRP treatment will be assessed by subjective and objective outcome variables. The participants will be randomized (sealed envelope) into either a placebo (saline) or a PRP group (1:1). For subjective outcomes, the Oxford Hip Score (OHS) will be collected before surgery and 3 and 12 months after surgery. The objective measures are findings at magnetic resonance imaging and plain radiographs and recorded values of measured strength.

Discussion

We present the perioperative use and the ways to measure the clinical efficacy of PRP. As PRP may have benefits regarding degenerative tendon regeneration, studies on the use of PRP in hip arthroplasty are warranted to facilitate postoperative recovery.

Trial registration

This study has been approved by the ethics committee of the Hospital District of Southwest Finland and approved by the local institutional research board. The study has been registered in ClinicalTrials.gov (NCT02607462).

Health Impacts of Ambient Air Pollution in Finland

Air pollution has been estimated to be one of the leading environmental health risks in Finland. National health impact estimates existing to date have focused on particles (PM) and ozone (O₃). In this work, we quantify the impacts of particles, ozone, and nitrogen dioxide (NO₂) in 2015, and analyze the related uncertainties. The exposures were estimated with a high spatial resolution chemical transport model, and adjusted to observed concentrations. We calculated the health impacts according to Word Health Organization (WHO) working group recommendations. According to our results, ambient air pollution caused a burden of 34,800 disability-adjusted life years (DALY). Fine particles were the main contributor (74%) to the disease burden, which is in line with the earlier studies. The attributable burden was dominated by mortality (32,900 years of life lost (YLL); 95%). Impacts differed between population age groups. The burden was clearly higher in the adult population over 30 years (98%), due to the dominant role of mortality impacts. Uncertainties due to the concentration-response functions were larger than those related to exposures.

Mortality due to Vegetation Fire-Originated PM2.5 Exposure in Europe-Assessment for the Years 2005 and 2008

BACKGROUND

Vegetation fires can release substantial quantities of fine particles (PM2.5), which are harmful to health. The fire smoke may be transported over long distances and can cause adverse health effects over wide areas.

OBJECTIVE

We aimed to assess annual mortality attributable to short-term exposures to vegetation fire-originated PM2.5 in different regions of Europe.

METHODS

PM2.5 emissions from vegetation fires in Europe in 2005 and 2008 were evaluated based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data on fire radiative power. Atmospheric transport of the emissions was modeled using the System for Integrated modeLling of Atmospheric coMposition (SILAM) chemical transport model. Mortality impacts were estimated for 27 European countries based on a) modeled daily PM2.5 concentrations and b) population data, both presented in a 50 × 50 km2 spatial grid; c) an exposure-response function for short-term PM2.5 exposure and daily nonaccidental mortality; and d) country-level data for background mortality risk.

RESULTS

In the 27 countries overall, an estimated 1,483 and 1,080 premature deaths were attributable to the vegetation fire-originated PM2.5 in 2005 and 2008, respectively. Estimated impacts were highest in southern and eastern Europe. However, all countries were affected by fire-originated PM2.5, and even the lower concentrations in western and northern Europe contributed substantially (~ 30%) to the overall estimate of attributable mortality.

CONCLUSIONS

Our assessment suggests that air pollution caused by PM2.5 released from vegetation fires is a notable risk factor for public health in Europe. Moreover, the risk can be expected to increase in the future as climate change proceeds. This factor should be taken into consideration when evaluating the overall health and socioeconomic impacts of these fires. Citation: Kollanus V, Prank M, Gens A, Soares J, Vira J, Kukkonen J, Sofiev M, Salonen RO, Lanki T. 2017. Mortality due to vegetation fire-originated PM2.5 exposure in Europe-assessment for the years 2005 and 2008. Environ Health Perspect 125:30-37; http://dx.doi.org/10.1289/EHP194.

Fine-Scale Exposure to Allergenic Pollen in the Urban Environment: Evaluation of Land Use Regression Approach

BACKGROUND

Despite the recent developments in physically and chemically based analysis of atmospheric particles, no models exist for resolving the spatial variability of pollen concentration at urban scale.

OBJECTIVES

We developed a land use regression (LUR) approach for predicting spatial fine-scale allergenic pollen concentrations in the Helsinki metropolitan area, Finland, and evaluated the performance of the models against available empirical data.

METHODS

We used grass pollen data monitored at 16 sites in an urban area during the peak pollen season and geospatial environmental data. The main statistical method was generalized linear model (GLM).

RESULTS

GLM-based LURs explained 79% of the spatial variation in the grass pollen data based on all samples, and 47% of the variation when samples from two sites with very high concentrations were excluded. In model evaluation, prediction errors ranged from 6% to 26% of the observed range of grass pollen concentrations. Our findings support the use of geospatial data-based statistical models to predict the spatial variation of allergenic grass pollen concentrations at intra-urban scales. A remote sensing-based vegetation index was the strongest predictor of pollen concentrations for exposure assessments at local scales.

CONCLUSIONS

The LUR approach provides new opportunities to estimate the relations between environmental determinants and allergenic pollen concentration in human-modified environments at fine spatial scales. This approach could potentially be applied to estimate retrospectively pollen concentrations to be used for long-term exposure assessments.

CITATION

Hjort J, Hugg TT, Antikainen H, Rusanen J, Sofiev M, Kukkonen J, Jaakkola MS, Jaakkola JJ. 2016. Fine-scale exposure to allergenic pollen in the urban environment: evaluation of land use regression approach. Environ Health Perspect 124:619-626; http://dx.doi.org/10.1289/ehp.1509761.

Particulate matter air pollution components and risk for lung cancer

BACKGROUND

Particulate matter (PM) air pollution is a human lung carcinogen; however, the components responsible have not been identified. We assessed the associations between PM components and lung cancer incidence.

METHODS

We used data from 14 cohort studies in eight European countries. We geocoded baseline addresses and assessed air pollution with land-use regression models for eight elements (Cu, Fe, K, Ni, S, Si, V and Zn) in size fractions of PM2.5 and PM10. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effect models for meta-analysis.

RESULTS

The 245,782 cohort members contributed 3,229,220 person-years at risk. During follow-up (mean, 13.1 years), 1878 incident cases of lung cancer were diagnosed. In the meta-analyses, elevated hazard ratios (HRs) for lung cancer were associated with all elements except V; none was statistically significant. In analyses restricted to participants who did not change residence during follow-up, statistically significant associations were found for PM2.5 Cu (HR, 1.25; 95% CI, 1.01-1.53 per 5 ng/m(3)), PM10 Zn (1.28; 1.02-1.59 per 20 ng/m(3)), PM10 S (1.58; 1.03-2.44 per 200 ng/m(3)), PM10 Ni (1.59; 1.12-2.26 per 2 ng/m(3)) and PM10 K (1.17; 1.02-1.33 per 100 ng/m(3)). In two-pollutant models, associations between PM10 and PM2.5 and lung cancer were largely explained by PM2.5 S.

CONCLUSIONS

This study indicates that the association between PM in air pollution and lung cancer can be attributed to various PM components and sources. PM containing S and Ni might be particularly important.

Elemental Constituents of Particulate Matter and Newborn's Size in Eight European Cohorts

BACKGROUND

The health effects of suspended particulate matter (PM) may depend on its chemical composition. Associations between maternal exposure to chemical constituents of PM and newborn's size have been little examined.

OBJECTIVE

We aimed to investigate the associations of exposure to elemental constituents of PM with term low birth weight (LBW; weight < 2,500 g among births after 37 weeks of gestation), mean birth weight, and head circumference, relying on standardized fine-scale exposure assessment and with extensive control for potential confounders.

METHODS

We pooled data from eight European cohorts comprising 34,923 singleton births in 1994-2008. Annual average concentrations of elemental constituents of PM ≤ 2.5 and ≤ 10 μm (PM2.5 and PM10) at maternal home addresses during pregnancy were estimated using land-use regression models. Adjusted associations between each birth measurement and concentrations of eight elements (copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc) were calculated using random-effects regression on pooled data.

RESULTS

A 200-ng/m3 increase in sulfur in PM2.5 was associated with an increased risk of LBW (adjusted odds ratio = 1.36; 95% confidence interval: 1.17, 1.58). Increased nickel and zinc in PM2.5 concentrations were also associated with an increased risk of LBW. Head circumference was reduced at higher exposure to all elements except potassium. All associations with sulfur were most robust to adjustment for PM2.5 mass concentration. All results were similar for PM10.

CONCLUSION

Sulfur, reflecting secondary combustion particles in this study, may adversely affect LBW and head circumference, independently of particle mass.

CITATION

Pedersen M, Gehring U, Beelen R, Wang M, Giorgis-Allemand L, Andersen AM, Basagaña X, Bernard C, Cirach M, Forastiere F, de Hoogh K, Gražulevičienė R, Gruzieva O, Hoek G, Jedynska A, Klümper C, Kooter IM, Krämer U, Kukkonen J, Porta D, Postma DS, Raaschou-Nielsen O, van Rossem L, Sunyer J, Sørensen M, Tsai MY, Vrijkotte TG, Wilhelm M, Nieuwenhuijsen MJ, Pershagen G, Brunekreef B, Kogevinas M, Slama R. 2016. Elemental constituents of particulate matter and newborn's size in eight European cohorts. Environ Health Perspect 124:141-150; http://dx.doi.org/10.1289/ehp.1409546.

Natural-cause mortality and long-term exposure to particle components: an analysis of 19 European cohorts within the multi-center ESCAPE project

BACKGROUND

Studies have shown associations between mortality and long-term exposure to particulate matter air pollution. Few cohort studies have estimated the effects of the elemental composition of particulate matter on mortality.

OBJECTIVES

Our aim was to study the association between natural-cause mortality and long-term exposure to elemental components of particulate matter.

METHODS

Mortality and confounder data from 19 European cohort studies were used. Residential exposure to eight a priori-selected components of particulate matter (PM) was characterized following a strictly standardized protocol. Annual average concentrations of copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc within PM size fractions ≤ 2.5 μm (PM2.5) and ≤ 10 μm (PM10) were estimated using land-use regression models. Cohort-specific statistical analyses of the associations between mortality and air pollution were conducted using Cox proportional hazards models using a common protocol followed by meta-analysis.

RESULTS

The total study population consisted of 291,816 participants, of whom 25,466 died from a natural cause during follow-up (average time of follow-up, 14.3 years). Hazard ratios were positive for almost all elements and statistically significant for PM2.5 sulfur (1.14; 95% CI: 1.06, 1.23 per 200 ng/m3). In a two-pollutant model, the association with PM2.5 sulfur was robust to adjustment for PM2.5 mass, whereas the association with PM2.5 mass was reduced.

CONCLUSIONS

Long-term exposure to PM2.5 sulfur was associated with natural-cause mortality. This association was robust to adjustment for other pollutants and PM2.5.

Comparing land use regression and dispersion modelling to assess residential exposure to ambient air pollution for epidemiological studies

BACKGROUND

Land-use regression (LUR) and dispersion models (DM) are commonly used for estimating individual air pollution exposure in population studies. Few comparisons have however been made of the performance of these methods.

OBJECTIVES

Within the European Study of Cohorts for Air Pollution Effects (ESCAPE) we explored the differences between LUR and DM estimates for NO2, PM10 and PM2.5.

METHODS

The ESCAPE study developed LUR models for outdoor air pollution levels based on a harmonised monitoring campaign. In thirteen ESCAPE study areas we further applied dispersion models. We compared LUR and DM estimates at the residential addresses of participants in 13 cohorts for NO2; 7 for PM10 and 4 for PM2.5. Additionally, we compared the DM estimates with measured concentrations at the 20-40 ESCAPE monitoring sites in each area.

RESULTS

The median Pearson R (range) correlation coefficients between LUR and DM estimates for the annual average concentrations of NO2, PM10 and PM2.5 were 0.75 (0.19-0.89), 0.39 (0.23-0.66) and 0.29 (0.22-0.81) for 112,971 (13 study areas), 69,591 (7) and 28,519 (4) addresses respectively. The median Pearson R correlation coefficients (range) between DM estimates and ESCAPE measurements were of 0.74 (0.09-0.86) for NO2; 0.58 (0.36-0.88) for PM10 and 0.58 (0.39-0.66) for PM2.5.

CONCLUSIONS

LUR and dispersion model estimates correlated on average well for NO2 but only moderately for PM10 and PM2.5, with large variability across areas. DM predicted a moderate to large proportion of the measured variation for NO2 but less for PM10 and PM2.5.

Long-term exposure to elemental constituents of particulate matter and cardiovascular mortality in 19 European cohorts: results from the ESCAPE and TRANSPHORM projects

BACKGROUND

Associations between long-term exposure to ambient particulate matter (PM) and cardiovascular (CVD) mortality have been widely recognized. However, health effects of long-term exposure to constituents of PM on total CVD mortality have been explored in a single study only.

AIMS

The aim of this study was to examine the association of PM composition with cardiovascular mortality.

METHODS

We used data from 19 European ongoing cohorts within the framework of the ESCAPE (European Study of Cohorts for Air Pollution Effects) and TRANSPHORM (Transport related Air Pollution and Health impacts--Integrated Methodologies for Assessing Particulate Matter) projects. Residential annual average exposure to elemental constituents within particle matter smaller than 2.5 and 10 μm (PM2.5 and PM10) was estimated using Land Use Regression models. Eight elements representing major sources were selected a priori (copper, iron, potassium, nickel, sulfur, silicon, vanadium and zinc). Cohort-specific analyses were conducted using Cox proportional hazards models with a standardized protocol. Random-effects meta-analysis was used to calculate combined effect estimates.

RESULTS

The total population consisted of 322,291 participants, with 9545 CVD deaths. We found no statistically significant associations between any of the elemental constituents in PM2.5 or PM10 and CVD mortality in the pooled analysis. Most of the hazard ratios (HRs) were close to unity, e.g. for PM10 Fe the combined HR was 0.96 (0.84-1.09). Elevated combined HRs were found for PM2.5 Si (1.17, 95% CI: 0.93-1.47), and S in PM2.5 (1.08, 95% CI: 0.95-1.22) and PM10 (1.09, 95% CI: 0.90-1.32).

CONCLUSION

In a joint analysis of 19 European cohorts, we found no statistically significant association between long-term exposure to 8 elemental constituents of particles and total cardiovascular mortality.

PM2.5 concentrations in London for 2008--a modeling analysis of contributions from road traffic

We report on the analysis of contributions from road traffic emissions to fine particulate matter (PM2.5) concentrations within London for 2008 with the OSCAR Air Quality Assessment System. A spatiotemporal evaluation of the OSCAR system has been conducted with measurements from the London air quality network (LAQN). For the predicted and measured hourly time series of concentrations at 18 sites in London, the medians of correlation, mean absolute error, index of agreement, and factor of two (FAC2) of all stations were 0.80, 4.1 microg/m3, 0.86, and 74%, respectively. Spatial evaluation of modeled and observed annual mean concentrations also showed a fairly good agreement, with all the values falling within the FAC2 range. According to model predictions, the urban increment (including the contributions from urban traffic and other urban sources) was evaluated to be on the average 18%, 33%, 39%, and 43% of the total PM2.5 in suburban environments, in the urban background, near roads, and near busy roads, respectively. However, the highest values of the urban traffic increment can be around 50% of the total PM2.5 concentrations near motorways and major roads. The total concentrations (including regional background, and the contributions from urban traffic and other urban sources) can therefore be almost three times the regional background. The total urban increment close to busy roads was around 7-8 microg/m3, in which the estimated traffic contribution is more than 2 microg/m3. On the average, urban traffic contributes approximately 1 microg/m3 of PM2.5 to the urban background across London. According to modeling, approximately two-thirds of the traffic increment originated from exhaust emissions and most of the rest was due to brake and tire wear.

IMPLICATIONS

The urban increment and traffic contribution to the total PM2.5 are significant and spatially heterogeneous across London. The highly heterogeneous distribution of PM2.5 hence requires detailed modeling studies to be carried out at high spatial resolution, which can be particularly important for exposure and health impact assessment. This type of information can be used to quantify health impacts resulting from specific sources of PM2.5 such as traffic emissions, to aid city and national decision makers when formulating pollution control strategies.

A comprehensive inventory of the ship traffic exhaust emissions in the Baltic Sea from 2006 to 2009

This study addresses the exhaust emissions of CO₂, NO(x), SO(x), CO, and PM(2.5) originated from Baltic Sea shipping in 2006-2009. Numerical results have been computed using the Ship Traffic Emissions Assessment Model. This model is based on the messages of the automatic identification system (AIS), which enable the positioning of ships with a high spatial resolution. The NO(x) emissions in 2009 were approximately 7 % higher than in 2006, despite the economic recession. However, the SO(x) emissions in 2009 were approximately 14 % lower, when compared to those in 2006, mainly caused by the fuel requirements of the SO(x) emission control area (SECA) which became effective in May 2006, but affected also by changes in ship activity. Results are presented on the differential geographic distribution of shipping emissions before (Jan-April 2006) and after (Jan-April 2009) the SECA regulations. The predicted NO(x) emissions in 2009 substantially exceeded the emissions in 2006 along major ship routes and at numerous harbors, mostly due to the continuous increase in the number of small vessels that use AIS transmitters. Although the SO(x) emissions have been reduced in 2009 in most major ship routes, these have increased in the vicinity of some harbors and on some densely trafficked routes. A seasonal variation of emissions is also presented, as well as the distribution of emissions in terms of vessel flag state, type, and weight.

Treatment of non-traumatic rotator cuff tears: A randomised controlled trial with one-year clinical results

We have compared three different methods of treating symptomatic non-traumatic tears of the supraspinatus tendon in patients above 55 years of age. A total of 180 shoulders (173 patients) with supraspinatus tendon tears were randomly allocated into one of three groups (each of 60 shoulders); physiotherapy (group 1), acromioplasty and physiotherapy (group 2) and rotator cuff repair, acromioplasty and physiotherapy (group 3). The Constant score was assessed and followed up by an independent observer pre-operatively and at three, six and twelve months after the intervention. Of these, 167 shoulders were available for assessment at one year (follow-up rate of 92.8%). There were 55 shoulders in group 1 (24 in males and 31 in females, mean age 65 years (55 to 79)), 57 in group 2 (29 male and 28 female, mean age 65 years (55 to 79)) and 55 shoulders in group 3 (26 male and 29 female, mean age 65 years (55 to 81)). There were no between-group differences in the Constant score at final follow-up: 74.1 (sd 14.2), 77.2 (sd 13.0) and 77.9 (sd 12.1) in groups 1, 2 and 3, respectively (p = 0.34). The mean change in the Constant score was 17.0, 17.5, and 19.8, respectively (p = 0.34). These results suggest that at one-year follow-up, operative treatment is no better than conservative treatment with regard to non-traumatic supraspinatus tears, and that conservative treatment should be considered as the primary method of treatment for this condition.

A numerical model of birch pollen emission and dispersion in the atmosphere. Model evaluation and sensitivity analysis

An evaluation of performance of the System for Integrated modeLling of Atmospheric coMposition (SILAM) in application to birch pollen dispersion is presented. The system is described in a companion paper whereas the current study evaluates the model sensitivity to details of the pollen emission module parameterisation and to the meteorological input data. The most important parameters are highlighted. The reference year considered for the analysis is 2006. It is shown that the model is capable of predicting about two-thirds of allergenic alerts, with the odds ratio exceeding 12 for the best setup. Several other statistics corroborate with these estimations. Low-pollen concentration days are also predicted correctly in more than two-thirds of cases. The model experiences certain difficulties only with intermediate pollen concentrations. It is demonstrated that the most important input parameter is the near-surface temperature, the bias of which can easily jeopardise the results. The model sensitivity to random fluctuations of temperature is much lower. Other parameters important at various stages of pollen development, release, and dispersion are precipitation and ambient humidity, as well as wind direction.

A numerical model of birch pollen emission and dispersion in the atmosphere. Description of the emission module

A birch pollen emission model is described and its main features are discussed. The development of the model is based on a double-threshold temperature sum model that describes the propagation of the flowering season and naturally links to the thermal time models to predict the onset and duration of flowering. For the flowering season, the emission model considers ambient humidity and precipitation rate, both of which suppress the pollen release, as well as wind speed and turbulence intensity, which promote it. These dependencies are qualitatively evaluated using the aerobiological observations. Reflecting the probabilistic character of the flowering of an individual tree in a population, the model introduces relaxation functions at the start and end of the season. The physical basis of the suggested birch pollen emission model is compared with another comprehensive emission module reported in literature. The emission model has been implemented in the SILAM dispersion modelling system, the results of which are evaluated in a companion paper.

Smoking and operative treatment of rotator cuff tear

This registry study was set up to evaluate the effect of smoking on the pre-operative status, intraoperative findings, and post-operative status after rotator cuff reconstruction. Five hundred seventy-six consecutive shoulders with primarily arthroscopically repaired penetrating rotator cuff tear were followed up. Tobacco consumption was recorded as pack-years. Age-adjusted Constant score was used as an outcome measure. Five hundred sixty-four patients were available for 1-year follow-up (dropout rate 2%). One hundred fourteen (20%) and 450 (80%) patients were pre-operatively recorded to be smokers and non-smokers, respectively. The gender distribution did not differ between the groups (P = 0.286). The mean age of all patients was 55 years in smokers (SD 9.1) and 61 years in non-smokers (SD 9.4) (P < 0.001). There was no statistically significant difference in pre-operative Constant score (P = 0.075) or mean size of intraoperatively measured tendon tear (P = 0.290) between the groups. At final follow-up, there was a statistically significant difference in Constant scores between smokers [71 (SE 1.4)] and non-smokers [75 (SE 0.7)] (P = 0.017). The pack-years of smoking correlated with neither the Constant score (P = 0.815) nor the size of the tear (P = 0.786). We conclude that operatively treated rotator cuff tear patients who smoked were significantly younger than non-smokers, and that smoking was associated with lower post-operative Constant score.

Interactions of physical, chemical, and biological weather calling for an integrated approach to assessment, forecasting, and communication of air quality

This article reviews interactions and health impacts of physical, chemical, and biological weather. Interactions and synergistic effects between the three types of weather call for integrated assessment, forecasting, and communication of air quality. Today's air quality legislation falls short of addressing air quality degradation by biological weather, despite increasing evidence for the feasibility of both mitigation and adaptation policy options. In comparison with the existing capabilities for physical and chemical weather, the monitoring of biological weather is lacking stable operational agreements and resources. Furthermore, integrated effects of physical, chemical, and biological weather suggest a critical review of air quality management practices. Additional research is required to improve the coupled modeling of physical, chemical, and biological weather as well as the assessment and communication of integrated air quality. Findings from several recent COST Actions underline the importance of an increased dialog between scientists from the fields of meteorology, air quality, aerobiology, health, and policy makers.

Evaluation of a multiple regression model for the forecasting of the concentrations of NOx and PM10 in Athens and Helsinki

Forecasting models based on stepwise multiple linear regression (MLR) have been developed for Athens and Helsinki. The predictor variables were the hourly concentrations of pollutants (NO, NO(2), NO(x), CO, O(3), PM(2.5) and PM(10)) and the meteorological variables (ambient temperature, wind speed/direction, and relative humidity) and in case of Helsinki also Monin-Obukhov length and mixing height of the present day. The variables to be forecasted are the maximum hourly concentrations of PM(10) and NO(x), and the daily average PM(10) concentrations of the next day. The meteorological pre-processing model MPP-FMI was used for computing the Monin-Obukhov length and the mixing height. The limitations of such statistical models include the persistence of both the meteorological and air quality situation; the model cannot account for rapid changes (on a temporal scale of hours or less than a day) that are commonly associated, e.g., with meteorological fronts, or episodes of a long-range transport origin. We have selected the input data for the model from one urban background and one urban traffic station both in Athens and Helsinki, in 2005. We have used various statistical evaluation parameters to analyze the performance of the models, and inter-compared the performance of the predictions for both cities. Forecasts from the MLR model were also compared to those from an Artificial Neural Network model (ANN) to investigate, if there are substantial gains that might justify the additional computational effort. The best predictor variables for both cities were the concentrations of NO(x) and PM(10) during the evening hours as well as wind speed, and the Monin-Obukhov length. In Athens, the index of agreement (IA) for NO(x) ranged from 0.77 to 0.84 and from 0.69 to 0.72, in the warm and cold periods of the year. In Helsinki, the corresponding values of IA ranged from 0.32 to 0.82 and from 0.67 to 0.86 for the warm and cold periods. In case of Helsinki the model accuracy was expectedly better on the average, when Monin-Obukhov length and mixing height were included as predictor variables. The models provide better forecasts of the daily average concentration, compared with the maximum hourly concentration for PM(10). The results derived by the ANN model where only slightly better than the ones derived by the MLR methodology. The results therefore suggest that the MLR methodology is a useful and fairly accurate tool for regulatory purposes.

Intercomparison of air quality data using principal component analysis, and forecasting of PM₁₀ and PM₂.₅ concentrations using artificial neural networks, in Thessaloniki and Helsinki

In this paper we propose a methodology consisting of specific computational intelligence methods, i.e. principal component analysis and artificial neural networks, in order to inter-compare air quality and meteorological data, and to forecast the concentration levels for environmental parameters of interest (air pollutants). We demonstrate these methods to data monitored in the urban areas of Thessaloniki and Helsinki in Greece and Finland, respectively. For this purpose, we applied the principal component analysis method in order to inter-compare the patterns of air pollution in the two selected cities. Then, we proceeded with the development of air quality forecasting models for both studied areas. On this basis, we formulated and employed a novel hybrid scheme in the selection process of input variables for the forecasting models, involving a combination of linear regression and artificial neural networks (multi-layer perceptron) models. The latter ones were used for the forecasting of the daily mean concentrations of PM₁₀ and PM₂.₅ for the next day. Results demonstrated an index of agreement between measured and modelled daily averaged PM₁₀ concentrations, between 0.80 and 0.85, while the kappa index for the forecasting of the daily averaged PM₁₀ concentrations reached 60% for both cities. Compared with previous corresponding studies, these statistical parameters indicate an improved performance of air quality parameters forecasting. It was also found that the performance of the models for the forecasting of the daily mean concentrations of PM₁₀ was not substantially different for both cities, despite the major differences of the two urban environments under consideration.

MEGAPOLI: concept of multi-scale modelling of megacity impact on air quality and climate

Abstract. The EU FP7 Project MEGAPOLI: "Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation" (http://megapoli.info) brings together leading European research groups, state-of-the-art scientific tools and key players from non-European countries to investigate the interactions among megacities, air quality and climate. MEGAPOLI bridges the spatial and temporal scales that connect local emissions, air quality and weather with global atmospheric chemistry and climate. The suggested concept of multi-scale integrated modelling of megacity impact on air quality and climate and vice versa is discussed in the paper. It requires considering different spatial and temporal dimensions: time scales from seconds and hours (to understand the interaction mechanisms) up to years and decades (to consider the climate effects); spatial resolutions: with model down- and up-scaling from street- to global-scale; and two-way interactions between meteorological and chemical processes.

Chemical composition of fine particles in fresh smoke plumes from boreal wild-land fires in Europe

A series of smoke plumes was detected in Helsinki, Finland, during a one-month-lasting period in August 2006. The smoke plumes originated from wildfires close to Finland, and they were short-term and had a high particulate matter (PM) concentration. Physical and chemical properties of fine particles in those smokes were characterised by a wide range of real-time measurements that enabled the examination of individual plume events. Concurrently PM(1) filter samples were collected and analysed off-line. Satellite observations employing MODIS sensor on board of NASA EOS Terra satellite with the dispersion model SILAM and the Fire Assimilation System were used for evaluation of the emission fluxes from wildfires. The model predicted well the timing of the plumes but the predicted PM concentrations differed from the observed. The measurements showed that the major growth in PM concentration was caused by submicrometer particles consisting mainly of particulate organic matter (POM). POM had not totally oxidised during the transport based on the low WSOC-to-OC ratio. The fresh plumes were compared to another major smoke episode that was observed in Helsinki during April-May 2006. The duration and the source areas of the two episode periods differed. The episode in April-May was a period of nearly constantly upraised level of long-range transported PM and it was composed of aged particles when arriving in Helsinki. The two episodes had differences also in the chemical composition of PM. The mass concentrations of biomass burning tracers (levoglucosan, potassium, and oxalate) increased during both the episodes but different concentration levels of elemental carbon and potassium indicated that the episodes differed in the form of burning as well as in the burning material. In spring dry crop residue and hay from the previous season were burnt whereas in August smokes from smouldering and incomplete burning of fresh vegetation were detected.

COST ES0602: towards a European network on chemical weather forecasting and information systems

Abstract. The COST ES0602 action provides a forum for benchmarking approaches and practices in data exchange and multi-model capabilities for chemical weather forecasting and near real-time information services in Europe. The action includes approximately 30 participants from 19 countries, and its duration is from 2007 to 2011 (http://www.chemicalweather.eu/). Major efforts have been dedicated in other actions and projects to the development of infrastructures for data flow. We have therefore aimed for collaboration with ongoing actions towards developing near real-time exchange of input data for air quality forecasting. We have collected information on the operational air quality forecasting models on a regional and continental scale in a structured form, and inter-compared and evaluated the physical and chemical structure of these models. We have also constructed a European chemical weather forecasting portal that includes links to most of the available chemical weather forecasting systems in Europe. The collaboration also includes the examination of the case studies that have been organized within COST-728, in order to inter-compare and evaluate the models against experimental data. We have also constructed an operational model forecasting ensemble. Data from a representative set of regional background stations have been selected, and the operational forecasts for this set of sites will be inter-compared and evaluated. The Action has investigated, analysed and reviewed existing chemical weather information systems and services, and will provide recommendations on best practices concerning the presentation and dissemination of chemical weather information towards the public and decision makers.

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.

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.

Modelling aerosol processes related to the atmospheric dispersion of sarin

We have developed mathematical models for evaluating the atmospheric dispersion of selected chemical warfare agents (CWA), including the evaporation and settling of contaminant liquid droplets. The models and numerical results presented may be utilised for designing protection and control measures against the conceivable use of CWA's. The model AERCLOUD (AERosol CLOUD) was extended to treat two nerve agents, sarin and VX, and the mustard agent. This model evaluates the thermodynamical evolution of a five-component aerosol mixture, consisting of two-component droplets together with the surrounding three-component gas. We have performed numerical computations with this model on the evaporation and settling of airborne sarin droplets in characteristic dispersal and atmospheric conditions. In particular, we have evaluated the maximum radii (r(M)) of a totally evaporating droplet, in terms of the ambient temperature and contaminant vapour concentration. The radii r(M) range from approximately 15-80 microm for sarin droplets for the selected ambient conditions and initial heights. We have also evaluated deposition fractions in terms of the initial droplet size.

Effects of pulp mill effluents and restricted diet on growth and physiology of rainbow trout (Oncorhynchus mykiss)

Juvenile female rainbow trout was exposed for 4.5 months (June to October) to two dilutions of untreated and activated sludge treated whole mill effluent from a pulp mill producing bleached ECF pulp. Two controls were used, on fed ad libitum and a second receiving 0.5% feed of the body weight. All effluent exposed groups were fed ad libitum. Mean weight of the fish was measured monthly. At the end of the experiment a number of physiological and biochemical parameters were analyzed in order to establish the physiological status of the exposed fish in comparison with unexposed fish that obtained ad libitum or restricted amount of feed. The fish exposed to treated effluent grew significantly more than ad libitum control fish until August, whereupon growth retarded in fish exposed to the lower effluent dilution (400 v/v). The growth of fish exposed to untreated effluent did not deviate significantly from the control fed ad libitum. The results from the hematological analysis clearly showed that fish fed restricted amount of feed deviated significantly in most parameters compared with the control fed ad libitum. Fish exposed to treated effluent showed a response pattern similar to that of the control fed restricted amount of feed, whereas the fish exposed to untreated effluent showed a response pattern that did not deviate from that of the ad libitum control. The metabolic parameters suggested that fish exposed to treated effluent had a higher metabolic demand than ad libitum control and that the energy allocation at the end of the experiment was directed to processes other than growth. The responses on hematology were mainly a consequence of the increased energy demand and were not primary effects. The implications of using feed related parameters at field studies are discussed.

Occurrence of microcystins in raw water sources and treated drinking water of Finnish waterworks

Problems caused by cyanobacteria are common around the world and also in raw water sources of drinking water treatment plants. Strains belonging to genera Microcystis, Anabaena and Planktothrix produce potent hepatotoxins, the microcystins. Laboratory and pilot scale studies have shown that microcystins dissolved in water may pass the conventional surface water treatment processes. In 1998 the World Health Organization proposed a guide value of 1 microgram/L for microcystin-LR (MC-LR) in drinking water. The purpose of this research was to study the occurrence of microcystins in raw water sources of surface waterworks and in bank filtration plants and to evaluate the removal of microcystins in operating waterworks. Four bank filtration plants and nine surface waterworks using different processes for water treatment were monitored. Phytoplankton was identified and quantified, and microcystins analysed with sensitive immunoassay. Microcystin occurrence in selected water samples was verified with HPLC and a protein phosphatase inhibition method. Microcystins were detected sporadically in raw water sources of most of the waterworks. In two raw water supplies toxins were detected for several months. The highest microcystin concentrations in incoming raw water were approximately 10 micrograms/L MC-LR equivalents. In treated drinking water microcystins were detected occasionally but the concentrations were always below the guide value proposed by WHO.

EOX and organochlorine compounds in fish and ringed seal samples from Lake Ladoga, Russia

Information about the pollution of Lake Ladoga, the largest lake in Europe, has been controversial. Various effluents and drainage waters affect the quality of the lake water. Wastewaters have caused eutrophication of parts of Lake Ladoga, but concentrations of persistent organic pollutants in the lake's food webs are poorly understood. In this study, concentrations of some organochlorine compounds, chlorophenols (CPs), and extractable organic halogen (EOX) were determined in smelt (Osmerus eperlanus), vendace (Coregonus albula), pikeperch (Lucioperca lucioperca), whitefish (Coregonus lavaretus), and the Ladoga seal (Phoca hispida ladogensis) from the northern part of the lake. The concentrations of organochlorine compounds in fish were low. Concentrations were between 0.07 and 0.15, 0.65 and 1.0, and 0.29 and 0.48 mg/kg lipids for hexachlorobenzene, total polychlorinated biphenyl (PCB) and p,p'-DDE, respectively. The results indicated biomagnification from smelt and vendace to pikeperch and ringed seal. In ringed seals, concentrations of PCB and DDT were 12 and 29 times higher than in fish used by ringed seals as major food sources.

Effects of hypoxia on valve-closure time and bioaccumulation of 2,4,5-trichlorophenol by the freshwater clam Sphaerium corneum [L]

The effects of hypoxia and 2,4,5-trichlorophenol (TCP) on the behavior of the freshwater clam Sphaerium corneum (L.) and the accumulation and elimination rates of 2,4,5-trichlorophenol were studied in the laboratory at 20 degrees C. After an initial high activity period, the shell valves were held closed for significantly longer periods in hypoxia than in normoxia. At the end of the 36-hr exposure period, the number of individuals with closed valves increased under normoxic conditions as well. The accumulation of TCP into clam tissues in normoxia was rapid and an uptake rate constant of 27.97 (+/-6.64) ml/g/hr was measured. An apparent steady state was achieved within 12 to 24 hr and the bioconcentration factors varied between 115 and 139. The depuration rate constant (kd) based on the accumulation data was 0.2717 (+/-0.07) hr-1. However, the much lower kd of 0.0137 (+/-0.0019) hr-1 measured over the depuration period from 24 to 120 hr suggests biphasic depuration kinetics. After a 6-hr exposure to TCP in both hypoxia and normoxia, the highest body burdens were found in clams exposed under normoxic conditions. A significant correlation was found between body burden and length of time the valves were open during the exposure. Results suggest that in short-term experiments, S. corneum can reduce the bioaccumulation of TCP by closing their shell valves.

Characterization of Lake Ladoga sediments. I. Toxicity to Chironomus riparius and Daphnia magna

Toxicity of surficial sediment of Lake Ladoga, Russia, was studied using bioassays with a midge, Chironomus riparius and Daphnia magna. Many Lake Ladoga sediments caused high mortality of midge larvae in 10-d growth and 40-d emergence tests. In most sediments the biomass production of chironomids was also lowered. However, no statistically significant effect on timing of emergence was observed. Sediment elutriate or pore water tests did not exhibit toxicity to Daphnia magna. The adverse effects observed in midge bioassays indicate the presence of toxic chemicals. It cannot be excluded, however, that the variable sediment physico-chemical characteristics could also have had some effect.

The kinetics of cadmium in Daphnia magna as affected by humic substances and water hardness

In order to investigate mechanisms causing enhanced toxicity of cadmium in humic lake waters the kinetics of cadmium in Daphnia magna was studied. The uptake rate of cadmium was two times faster in humic lake water than in the humic-free reference water. On the other hand, the depuration rate was equal in humic and reference waters. Thus the acutely lethal concentration in animal is reached faster in humic than in humic-free water. However, altered kinetics of cadmium in humic lake water was also affected by lower water hardness compared to the reference.

Apparent noncompetitive antagonism of muscarinic receptor mediated Ca2+ mobilization by some muscarinic antagonists

Ca2+ mobilizations in SH-SY5Y and IMR-32 human neuroblastoma cell lines were measured using the fluorescent Ca2+ indicator fura-2. A variety of antagonists (atropine, pirenzepine, 4-DAMP and N-methyl-scopolamine) inhibited carbamyl choline-induced transient Ca2+ mobilization both in a competitive and a noncompetitive manner. The apparent noncompetitive inhibition constants were lower in IMR-32 than in SH-SY5Y cells even when the competitive inhibition constants were similar. This may relate to the previously reported differential expression of muscarinic receptor subtypes in these cell lines.

Muscarinic receptor subtypes in human neuroblastoma cell lines SH-SY5Y and IMR-32 as determined by receptor binding, Ca++ mobilization and northern blotting

Muscarinic receptor subtypes in neuroblastoma cell lines IMR-32 and SH-SY5Y were determined with receptor binding, Ca++ mobilization and Northern blotting. Displacement of [3H]NMS with pirenzepine in IMR-32 cells revealed apparent binding sites with Kd values of 5 (41%) and 237 nM (59%). With 4-diphenylacetoxy-N-metylpiperidine metiodid, a similar proportion of apparent high- and low-affinity binding was obtained: 36 (Kd = 0.26 nM) and 64% (Kd = 6.3 nM), respectively. In SH-SY5Y cells, two different affinities with apparent Kd of 40 (24%) and 460 nM (76%) could be distinguished with pirenzepine, even though the Kd of the apparent high-affinity site varied markedly (variation = 8.7-96.8 nM). Inhibition of carbachol-induced Ca++ mobilization displayed high sensitivity to 4-diphenylacetoxy-N-methylpiperidine metiodid in both cell lines. IMR-32 cells displayed high sensitivity to pirenzepine, whereas the sensitivity varied between different batches of SH-SY5Y cells. DNA fragments (approximately 1000 base pairs) from SH-SY5Y DNA amplified with polymerase chain reaction were used as probes for muscarinic receptor mRNA. Northern blotting with the Hm1-specific probe gave a stronger signal for SH-SY5Y than for IMR-32, whereas the result obtained with the Hm2-probe was the opposite. Also, the Hm3 mRNA was detected in SH-SY5Y cells. The Hm4 and Hm5 transcripts were not detected in either of these cell lines.

Muscarinic receptor-linked elevation of cAMP in SH-SY5Y neuroblastoma cells is mediated by Ca2+ and protein kinase C

The mechanisms of muscarinic receptor-linked increase in cAMP accumulation in SH-SY5Y human neuroblastoma cells has been investigated. The dose-response relations of carbachol-induced cAMP synthesis and carbachol-induced rise in intracellular free Ca2+ were similar. The stimulated cAMP synthesis was inhibited by about 50% when cells were entrapped with the Ca2+ chelator BAPTA or in the presence of the protein kinase C (PKC) inhibitor staurosporine. Production of cAMP could be induced also by the Ca2+ ionophore, ionomycin and by TPA, an activator of PKC. When added together TPA and ionomycin had a synergistic effect. When cAMP synthesis was activated with cholera toxin, PGE1 or PGE1 + pertussis toxin carbachol stimulated cAMP production to the same extent as in control cells. Ca2+ and protein kinase C thus seem to be the mediators of muscarinic-receptor linked cAMP synthesis by a direct action on adenylate cyclase.