Atmospheric chamber study of oil shale fly ash particles from circulating fluidized bed and pulverized firing processes

Oil shale combustion fly ash collected to electric precipitators from pulverized firing (PF) and circulating fluidized bed combustion (CFB) processes was investigated in atmospheric chamber experiments. The aim of the work was to detect differences in the atmospheric behaviour of the fine particles from CFB and PF boilers of the Estonian Power Plant (PP), located close to Narva, Estonia. One series of experiments was performed in a dual outdoor Teflon film smog chamber (270 m3) at the University of North Carolina at Chapel Hill (USA) under normal weather conditions (temperature, humidity, sunlight). Parallel tests were carried out in an outdoor smog chamber (108 m3) at Tuulna, Harju County, Estonia, where the experiment was made under meteorological conditions similar to those at the location of the PP. The size distribution and number concentration of particles in the chamber were monitored during the experiment. The fractional distribution results demonstrate that the CFB aerosol in the chamber air had more fine particles than the PF aerosol. Approximately 2 h after injection the fly ash particles larger than 4 μm had settled out from both samples. The initial fly ash aerosol had a trimodal fractional distribution. Both PF and CFB fly ash formed stable aerosols 1–3 μm in diameter during the 6 h experiment and are therefore prone to long-range transport

Health impact assessment of particulate pollution in Tallinn using fine spatial resolution and modeling techniques

<p>Abstract</p> <p>Background</p> <p>Health impact assessments (HIA) use information on exposure, baseline mortality/morbidity and exposure-response functions from epidemiological studies in order to quantify the health impacts of existing situations and/or alternative scenarios. The aim of this study was to improve HIA methods for air pollution studies in situations where exposures can be estimated using GIS with high spatial resolution and dispersion modeling approaches.</p> <p>Methods</p> <p>Tallinn was divided into 84 sections according to neighborhoods, with a total population of approx. 390 000 persons. Actual baseline rates for total mortality and hospitalization with cardiovascular and respiratory diagnosis were identified. The exposure to fine particles (PM_2.5) from local emissions was defined as the modeled annual levels. The model validation and morbidity assessment were based on 2006 PM₁₀or PM_2.5levels at 3 monitoring stations. The exposure-response coefficients used were for total mortality 6.2% (95% CI 1.6–11%) per 10 μg/m³increase of annual mean PM_2.5concentration and for the assessment of respiratory and cardiovascular hospitalizations 1.14% (95% CI 0.62–1.67%) and 0.73% (95% CI 0.47–0.93%) per 10 μg/m³increase of PM₁₀. The direct costs related to morbidity were calculated according to hospital treatment expenses in 2005 and the cost of premature deaths using the concept of Value of Life Year (VOLY).</p> <p>Results</p> <p>The annual population-weighted-modeled exposure to locally emitted PM_2.5in Tallinn was 11.6 μg/m³. Our analysis showed that it corresponds to 296 (95% CI 76528) premature deaths resulting in 3859 (95% CI 10236636) Years of Life Lost (YLL) per year. The average decrease in life-expectancy at birth per resident of Tallinn was estimated to be 0.64 (95% CI 0.17–1.10) years. While in the polluted city centre this may reach 1.17 years, in the least polluted neighborhoods it remains between 0.1 and 0.3 years. When dividing the YLL by the number of premature deaths, the decrease in life expectancy among the actual cases is around 13 years. As for the morbidity, the short-term effects of air pollution were estimated to result in an additional 71 (95% CI 43–104) respiratory and 204 (95% CI 131–260) cardiovascular hospitalizations per year. The biggest external costs are related to the long-term effects on mortality: this is on average €150 (95% CI 40–260) million annually. In comparison, the costs of short-term air-pollution driven hospitalizations are small €0.3 (95% CI 0.2–0.4) million.</p> <p>Conclusion</p> <p>Sectioning the city for analysis and using GIS systems can help to improve the accuracy of air pollution health impact estimations, especially in study areas with poor air pollution monitoring data but available dispersion models.</p

European aerosol phenomenology - 8 : Harmonised source apportionment of organic aerosol using 22 Year-long ACSM/AMS datasets

Organic aerosol (OA) is a key component of total submicron particulate matter (PM1), and comprehensive knowledge of OA sources across Europe is crucial to mitigate PM1 levels. Europe has a well-established air quality research infrastructure from which yearlong datasets using 21 aerosol chemical speciation monitors (ACSMs) and 1 aerosol mass spectrometer (AMS) were gathered during 2013-2019. It includes 9 non-urban and 13 urban sites. This study developed a state-of-the-art source apportionment protocol to analyse long-term OA mass spectrum data by applying the most advanced source apportionment strategies (i.e., rolling PMF, ME-2, and bootstrap). This harmonised protocol was followed strictly for all 22 datasets, making the source apportionment results more comparable. In addition, it enables quantification of the most common OA components such as hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking-like OA (COA), more oxidised-oxygenated OA (MO-OOA), and less oxidised-oxygenated OA (LO-OOA). Other components such as coal combustion OA (CCOA), solid fuel OA (SFOA: mainly mixture of coal and peat combustion), cigarette smoke OA (CSOA), sea salt (mostly inorganic but part of the OA mass spectrum), coffee OA, and ship industry OA could also be separated at a few specific sites. Oxygenated OA (OOA) components make up most of the submicron OA mass (average = 71.1%, range from 43.7 to 100%). Solid fuel combustion-related OA components (i.e., BBOA, CCOA, and SFOA) are still considerable with in total 16.0% yearly contribution to the OA, yet mainly during winter months (21.4%). Overall, this comprehensive protocol works effectively across all sites governed by different sources and generates robust and consistent source apportionment results. Our work presents a comprehensive overview of OA sources in Europe with a unique combination of high time resolution (30-240 min) and long-term data coverage (9-36 months), providing essential information to improve/validate air quality, health impact, and climate models.Peer reviewe

Perinatal Health Inequalities in the Industrial Region of Estonia: A Birth Registry-Based Study

Despite the increasing number of studies on industrially contaminated sites (ICS) and their health effects, there are very few studies on perinatal health outcomes in ICSs. In the present study, we examined the perinatal health inequalities by comparing adverse birth outcomes (ABOs) in the oil shale industry region of Ida-Viru County in Estonia with national-level figures and investigated the effects of maternal environmental and sociodemographic factors. Based on the 208,313 birth records from 2004–2018, Ida-Viru ICS has a birth weight 124.5 g lower than the average of 3544 g in Estonia. A higher prevalence of preterm birth (4.3%) and low birth weight (4.8%) in Ida-Viru ICS is found compared to 3.3% on both indicators at the national level. Multiple logistic regression analysis shows the statistically significant association of ABOs with fine particle (PM2.5) air pollution, mother’s ethnicity, and education throughout Estonia. However, in Ida-Viru ICS, the ABOs odds are remarkably higher in these characteristics except for the mother’s ethnicity. Furthermore, the ABOs are associated with the residential proximity to ICS. Thus, the Ida-Viru ICS has unequally higher odds of adverse perinatal health across the environmental and sociodemographic factors. In addition to reducing the air pollutants, policy actions on social disparities are vital to address the country’s unjustly higher perinatal health inequalities, especially in the Ida-Viru ICS

Basket-ball : l'enseignement de l'arbitrage en sports collectifs dans le cadre scolaire

Peened osakesed välisõhus mõjutavad olulisel määral inimeste tervist. Neid hingatakse sügavale hingamisteedesse ning koos seotud raskmetallide, orgaaniliste ja muude keemiliste ühenditega põhjustavad osakesed erinevate mehhanismide koostoimel eeskätt põletikulisi protsesse. Käesoleva uuringu käigus tehtud tervisemõjude hinnang näitas, et peened osakesed välisõhus põhjustavad viies suuremas Eesti linnas kokku 462 (95% CI 120–815) varajast surma aastas, mis avaldub 6034 (95% CI 1583–10309) kaotatud eluaastana. Keskmine oodatava eluea vähenemine on 0,63 (95% CI 0,16–1,08) aastat, mis enam saastunud kesklinnas on veidi üle aasta ning äärelinnas mõni kuu. Varajastele surmadele lisandub 231 (95% CI 145–306) hingamisteede ja 338 (95% CI 205–454) südame-veresoonkonnakaebusega hospitaliseerimise juhtu aastas. Kõik see tekitab tervishoiu süsteemile olulise kulu, mille suurus jääb 3–5,5 miljardi krooni vahele. Eesti Arst 2010; 89(4):242−25

Development of a versatile source apportionment analysis based on positive matrix factorization: a case study of the seasonal variation of organic aerosol sources in Estonia

Bootstrap analysis is commonly used to capture the uncertainties of a bilinear receptor model such as the positive matrix factorization (PMF) model. This approach can estimate the factor-related uncertainties and partially assess the rotational ambiguity of the model. The selection of the environmentally plausible solutions, though, can be challenging, and a systematic approach to identify and sort the factors is needed. For this, comparison of the factors between each bootstrap run and the initial PMF output, as well as with externally determined markers, is crucial. As a result, certain solutions that exhibit suboptimal factor separation should be discarded. The retained solutions would then be used to test the robustness of the PMF output. Meanwhile, analysis of filter samples with the Aerodyne aerosol mass spectrometer and the application of PMF and bootstrap analysis on the bulk water-soluble organic aerosol mass spectra have provided insight into the source identification and their uncertainties. Here, we investigated a full yearly cycle of the sources of organic aerosol (OA) at three sites in Estonia: Tallinn (urban), Tartu (suburban) and Kohtla-Järve (KJ; industrial). We identified six OA sources and an inorganic dust factor. The primary OA types included biomass burning, dominant in winter in Tartu and accounting for 73 % ± 21 % of the total OA, primary biological OA which was abundant in Tartu and Tallinn in spring (21 % ± 8 % and 11 % ± 5 %, respectively), and two other primary OA types lower in mass. A sulfur-containing OA was related to road dust and tire abrasion which exhibited a rather stable yearly cycle, and an oil OA was connected to the oil shale industries in KJ prevailing at this site that comprises 36 % ± 14 % of the total OA in spring. The secondary OA sources were separated based on their seasonal behavior: a winter oxygenated OA dominated in winter (36 % ± 14 % for KJ, 25 % ± 9 % for Tallinn and 13 % ± 5 % for Tartu) and was correlated with benzoic and phthalic acid, implying an anthropogenic origin. A summer oxygenated OA was the main source of OA in summer at all sites (26 % ± 5 % in KJ, 41 % ± 7 % in Tallinn and 35 % ± 7 % in Tartu) and exhibited high correlations with oxidation products of a-pinene-like pinic acid and 3-methyl-1, 2, 3-butanetricarboxylic acid (MBTCA), suggesting a biogenic origin.Acknowledgements. This work was funded by the Estonian–Swiss cooperation program “Enforcement of the surveillance network of the Estonian air quality: Determination of origin of fine particles in Estonia”. María Cruz Minguillón acknowledges the Ramón y Ca-jal Fellowship awarded by the Spanish Ministry of Economy, Industry and Competitiveness. The Labex OSUG@2020 (ANR-10-LABX-56) provided the funding for part of the analytical equipment at Institut des Géosciences de l’Environnement (IGE; France). We also acknowledge the contribution of the COST Action CA16109 COLOSSAL.Peer reviewe

MACC regional multi-model ensemble simulations of birch pollen dispersion in Europe

This paper presents the first ensemble modelling experiment in relation to birch pollen in Europe. The seven-model European ensemble of MACC-ENS, tested in trial simulations over the flowering season of 2010, was run through the flowering season of 2013. The simulations have been compared with observations in 11 countries, all members of the European Aeroallergen Network, for both individual models and the ensemble mean and median. It is shown that the models successfully reproduced the timing of the very late season of 2013, generally within a couple of days from the observed start of the season. The end of the season was generally predicted later than observed, by 5 days or more, which is a known feature of the source term used in the study. Absolute pollen concentrations during the season were somewhat underestimated in the southern part of the birch habitat. In the northern part of Europe, a record-low pollen season was strongly overestimated by all models. The median of the multi-model ensemble demonstrated robust performance, successfully eliminating the impact of outliers, which was particularly useful since for most models this was the first experience of pollen forecasting

European aerosol phenomenology − 8: Harmonised source apportionment of organic aerosol using 22 Year-long ACSM/AMS datasets

Organic aerosol (OA) is a key component of total submicron particulate matter (PM1), and comprehensive knowledge of OA sources across Europe is crucial to mitigate PM1 levels. Europe has a well-established air quality research infrastructure from which yearlong datasets using 21 aerosol chemical speciation monitors (ACSMs) and 1 aerosol mass spectrometer (AMS) were gathered during 2013–2019. It includes 9 non-urban and 13 urban sites. This study developed a state-of-the-art source apportionment protocol to analyse long-term OA mass spectrum data by applying the most advanced source apportionment strategies (i.e., rolling PMF, ME-2, and bootstrap). This harmonised protocol was followed strictly for all 22 datasets, making the source apportionment results more comparable. In addition, it enables quantification of the most common OA components such as hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking-like OA (COA), more oxidised-oxygenated OA (MO-OOA), and less oxidised-oxygenated OA (LO-OOA). Other components such as coal combustion OA (CCOA), solid fuel OA (SFOA: mainly mixture of coal and peat combustion), cigarette smoke OA (CSOA), sea salt (mostly inorganic but part of the OA mass spectrum), coffee OA, and ship industry OA could also be separated at a few specific sites. Oxygenated OA (OOA) components make up most of the submicron OA mass (average = 71.1%, range from 43.7 to 100%). Solid fuel combustion-related OA components (i.e., BBOA, CCOA, and SFOA) are still considerable with in total 16.0% yearly contribution to the OA, yet mainly during winter months (21.4%). Overall, this comprehensive protocol works effectively across all sites governed by different sources and generates robust and consistent source apportionment results. Our work presents a comprehensive overview of OA sources in Europe with a unique combination of high time resolution (30–240 min) and long-term data coverage (9–36 months), providing essential information to improve/validate air quality, health impact, and climate models