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Objective To evaluate the short term associations between nitrogen dioxide (NO2) and total, cardiovascular, and respiratory mortality across multiple countries/regions worldwide, using a uniform analytical protocol. Design Two stage, time series approach, with overdispersed generalised linear models and multilevel meta-analysis. Setting 398 cities in 22 low to high income countries/regions. Main outcome measures Daily deaths from total (62.8 million), cardiovascular (19.7 million), and respiratory (5.5 million) causes between 1973 and 2018. Results On average, a 10 μg/m3 increase in NO2 concentration on lag 1 day (previous day) was associated with 0.46% (95% confidence interval 0.36% to 0.57%), 0.37% (0.22% to 0.51%), and 0.47% (0.21% to 0.72%) increases in total, cardiovascular, and respiratory mortality, respectively. These associations remained robust after adjusting for co-pollutants (particulate matter with aerodynamic diameter ≤10 μm or ≤2.5 μm (PM10 and PM2.5, respectively), ozone, sulfur dioxide, and carbon monoxide). The pooled concentration-response curves for all three causes were almost linear without discernible thresholds. The proportion of deaths attributable to NO2 concentration above the counterfactual zero level was 1.23% (95% confidence interval 0.96% to 1.51%) across the 398 cities. Conclusions This multilocation study provides key evidence on the independent and linear associations between short term exposure to NO2 and increased risk of total, cardiovascular, and respiratory mortality, suggesting that health benefits would be achieved by tightening the guidelines and regulatory limits of NO2., HaK was supported by the National Natural Science Foundation of China (92043301, 82030103, and 91843302) and China Medical Board Collaborating Program (16-250). AG and FS were supported by the Medical Research Council, UK (MR/M022625/1), the Natural Environment Research Council, UK (NE/R009384/1), and the European Union’s Horizon 2020 Project Exhaustion (820655). VH was supported by the Spanish Ministry of Science and Innovation (PCIN-2017-046), and the German Federal Ministry of Education and Research (01LS1201A2). YH and MH were supported by the Environment Research and Technology Development Fund (JPMEERF15S11412) of the Environmental Restoration and Conservation Agency, Japan. JK and AU were supported by the Czech Science Foundation (18-22125S). ST was supported by the Shanghai Municipal Science and Technology Commission (18411951600). Y-LLG was supported by a Career Development Fellowship of the Australian National Health and Medical Research Council (APP1163693). SL was supported by an Early Career Fellowship of the Australian National Health and Medical Research Council (APP1109193). JJKJJ and NR were supported by the Academy of Finland (310372). The funders had no role in considering the study design or in the collection, analysis, interpretation of data, writing of the report, or decision to submit the article for publication.

Summary Background Many regions of the world are now facing more frequent and unprecedentedly large wildfires. However, the association between wildfire-related PM2·5 and mortality has not been well characterised. We aimed to comprehensively assess the association between short-term exposure to wildfire-related PM2·5 and mortality across various regions of the world. Methods For this time series study, data on daily counts of deaths for all causes, cardiovascular causes, and respiratory causes were collected from 749 cities in 43 countries and regions during 2000–16. Daily concentrations of wildfire-related PM2·5 were estimated using the three-dimensional chemical transport model GEOS-Chem at a 0·25° × 0·25° resolution. The association between wildfire-related PM2·5 exposure and mortality was examined using a quasi-Poisson time series model in each city considering both the current-day and lag effects, and the effect estimates were then pooled using a random-effects meta-analysis. Based on these pooled effect estimates, the population attributable fraction and relative risk (RR) of annual mortality due to acute wildfire-related PM2·5 exposure was calculated. Findings 65·6 million all-cause deaths, 15·1 million cardiovascular deaths, and 6·8 million respiratory deaths were included in our analyses. The pooled RRs of mortality associated with each 10 μg/m3 increase in the 3-day moving average (lag 0–2 days) of wildfire-related PM2·5 exposure were 1·019 (95% CI 1·016–1·022) for all-cause mortality, 1·017 (1·012–1·021) for cardiovascular mortality, and 1·019 (1·013–1·025) for respiratory mortality. Overall, 0·62% (95% CI 0·48–0·75) of all-cause deaths, 0·55% (0·43–0·67) of cardiovascular deaths, and 0·64% (0·50–0·78) of respiratory deaths were annually attributable to the acute impacts of wildfire-related PM2·5 exposure during the study period., Australian Research Council, Australian National Health & Medical Research Council.

Ambient ammonia (NH3) measurements were performed with a mobile platform in three European cities: Zurich (Switzerland), Tartu (Estonia) and Tallinn (Estonia) deploying an NH3 analyzer based on cavity ring-down spectroscopy. A heated inlet line along with an auxiliary flow was used to minimize NH3 adsorption onto the inlet walls. In addition, a detailed characterization of the response and recovery times of the measurement system was used to deconvolve the true NH3 signal from the remaining adsorption-induced hysteresis. Parallel measurements with an aerosol mass spectrometer were used to correct the observed NH3 for the contribution of ammonium nitrate, which completely evaporated in the heated line at the chosen temperature, in contrast to ammonium sulfate. In this way a quantitative measurement of ambient gaseous NH3 was achieved with sufficient time resolution to enable measurement of NH3 point sources with a mobile sampling platform. The NH3 analyzer and the aerosol mass spectrometer were complemented by an aethalometer and various gas-phase analyzers to enable a complete characterization of the sources of air pollution, including the spatial distributions and the regional background concentrations and urban increments of all measured components. Although at all three locations similar increment levels of organic aerosols were attributed to biomass burning and traffic, traffic emissions clearly dominated the city enhancements of NH3, equivalent black carbon (eBC) and carbon dioxide (CO2). Urban increments of 3.4, 1.8 and 3.0 ppb of NH3 were measured in the traffic areas in Zurich, Tartu and Tallinn, respectively, representing an enhancement of 36.6, 38.3 and 93.8% over the average background concentrations. Measurements in areas strongly influenced by traffic emissions (including tunnel drives) were used to estimate emission factors (EF) for the traffic-related pollutants. The obtained median EFs range between 136.8-415.1 mg kg−1 fuel for NH3, 157.1–734.8 mg kg−1 fuel for eBC and 39.9–324.3 mg kg−1 fuel for HOA. Significant differences were found between the EFs of certain components in the three cities, which were partially linked to an older vehicle fleet in Estonia compared to Switzerland. Using the determined EFs we show that traffic can fully explain the NH3 enhancements in the three cities and also presents a non-negligible fraction of the background concentrations, which are mostly related to agricultural activities. Moreover, the estimated total contribution of traffic to NH3 at all three locations is in good agreement with the available emission inventories.

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.

Background:Traffic and residential heating are the main sources of particulate matter (PM) in Northern Europe. Wood is widely used for residential heating and vehicle numbers are increasing. Besides traffic exhaust, studded tires produce road dust that is the main source of traffic-related PM10. Several studies have associated total PM mass with health symptoms; however there has been little research on the effects of PM from specific sources.Objective:To study the health effects resulting from traffic and local heating PM.Methods:Data on respiratory and cardiac diseases were collected within the framework of RHINE III (2011/2012) in Tartu, Estonia. Respondents’ geocoded home addresses were mapped in ArcGIS and linked with local heating-related PM2.5,traffic-related PM10and total PM2.5concentrations. Association between self-reported health and PM was assessed using multiple logistic regression analysis.Results:The annual mean modelled exposure for local heating PM2.5was 2.3 μg/m3, for traffic PM103.3 μg/m3and for all sources PM2.55.6 μg/m3. We found relationship between traffic induced PM10as well as all sources induced PM2.5with cardiac disease, OR=1.45 (95% CI 1.06−1.93) and 1.42 (95% CI 1.02−1.95), respectively. However, we did not find any significant association between residential heating induced particles and self-reported health symptoms. People with longer and better confirmed exposure period were also significantly associated with traffic induced PM10, all sources induced PM2.5and cardiac diseases.Conclusion:Traffic-related PM10and all sources induced PM2.5associated with cardiac disease; whereas residential heating induced particles did not.

Air pollution is one of the main environmental concerns in urban areas, where anthropogenic emissions strongly affect air quality. This work presents the first spatially resolved detailed characterization of PM2.5 (particulate matter with aerodynamic equivalent diameter daero ≤ 2.5 µm) in two major Estonian cities, Tallinn and Tartu. The measurements were performed in March 2014 using a mobile platform. In both cities, the non-refractory (NR)-PM2.5 was characterized by a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) using a recently developed lens which increases the transmission of super-micron particles. Equivalent black carbon (eBC) and several trace gases including carbon monoxide (CO), carbon dioxide (CO2), and methane (CH4) were also measured. The chemical composition of PM2.5 was found to be very similar in the two cities. Organic aerosol (OA) constituted the largest fraction, explaining on average about 52 to 60 % of the PM2.5 mass. Four sources of OA were identified using positive matrix factorization (PMF): hydrocarbon-like OA (HOA, from traffic emissions), biomass burning OA (BBOA, from biomass combustion), residential influenced OA (RIOA, probably mostly from cooking processes with possible contributions from waste and coal burning), and oxygenated OA (OOA, related to secondary aerosol formation). OOA was the major OA source during nighttime, explaining on average half of the OA mass, while during daytime mobile measurements the OA was affected by point sources and dominated by the primary fraction. A strong increase in the secondary organic and inorganic components was observed during periods with transport of air masses from northern Germany, while the primary local emissions accumulated during periods with temperature inversions. Mobile measurements offered the identification of different source regions within the urban areas and the assessment of the extent to which pollutants concentrations exceeded regional background levels (urban increments). HOA, eBC, CO2, and CO showed stronger enhancements on busy roads during the morning and evening traffic rush hours; BBOA had its maximum enhancement in the residential areas during the evening hours and RIOA was enhanced in both the city center (emissions from restaurants) and in the residential areas (emissions from residential cooking). In contrast, secondary components (OOA, sulfate (SO4), nitrate (NO3), ammonium (NH4), and chloride (Cl)) had very homogeneous distributions in time and space. We were able to determine a total PM2.5 urban increment in Tartu of 6.0 µg m−3 over a regional background concentration of 4.0 µg m−3 (i.e., a factor of 2.5 increase). Traffic exhaust emissions were identified as the most important source of this increase, with eBC and HOA explaining on average 53.3 and 20.5 % of the total increment, respectively.

The concentration of airborne particulate matter in large scale uninsulated loose housing cowsheds was investigated. Airborne particulate matter can be a potential risk factor for human and animal health. Also investigated were correlations between indoor particulate matter, noxious gas concentrations and other microclimate parameters. Measures of inhalable particulate matter (PMtotal, PM10) and respirable particulate matter (PM2.5 and PM1.0), carbon dioxide (CO 2 ) and ammonia (NH 3 ) concentrations, air temperature, and relative humidity were taken at eight to 13 locations in nine large uninsulated loose housing cowsheds in Estonia from September 2008 to August 2009. The mean recorded concentrations of PMtotal were 205 ± 270 μg m −3 , PM10 65 ± 121 μg m −3 , PM2.5 18 ± 46 μg m −3 and PM1.0 10 ± 11 μg m −3 . The overall mean inside air CO 2 concentration was 553 ± 315 ppm, and that of ammonia 1.2 ± 1.9 ppm. The mean air temperature was 9.6 ± 6.6 °C, and relative humidity 83.2 ± 16.8%. The concentration of particulate matter (all fractions) inside the uninsulated loose housing cowsheds was low compared to pig and poultry housing systems. There was a clear seasonal variation between measurements in summer and winter. The particulate matter (all fractions) and CO 2 concentrations were higher, and ammonia concentrations lower, in the winter. The particulate matter concentration in the atmosphere also had an effect on the internal environment in uninsulated loose housing cowsheds.

Particulate matter (PM) is the major air pollution problem with health impacts in Estonia. The prevailing sources of particles are traffic and local heating. In this study, we quantified the health effects of PM in neighbourhoods of five main cities with a health impact assessment (HIA) approach that uses information on exposure, baseline mortality/morbidity and exposure–response relationships from previous epidemiological studies. The exposure was defined as modelled PM2.5 annual levels and daily averages of PM10 (monitoring data in Tallinn and Kohtla-Jarve and modelled levels in Tartu, Narva and Parnu). The modelled results were validated with data from monitoring stations and additional measuring programmes. The annual average concentration of PM2.5 in the neighbourhoods studied varied from 7.6 to 23.6 μg m−3. The analysis indicated that the exposure above natural background corresponds to 462 [95% confidence interval (CI) 120–815] premature deaths, resulting in 6,034 (95% CI 1,583–10,309) years of life lost per year. The average decrease in life-expectancy at birth per resident of Tallinn was estimated to be 0.63 (95% CI 0.16–1.08) years. In the polluted city centres, this average decrease may reach >1 year and in Parnu, it may reach 0.95 year. However, in the least polluted neighbourhood, the decrease of life expectancy was only 0.17 years. In addition, 231 (95% CI 145–306) respiratory and 338 (95% CI 205–454) cardiovascular hospitalisations per year could be expected. The majority of the external costs are related to the long-term effects on mortality and amount to €270 (95% CI 190–350) million annually. In comparison, the costs of hospitalisations contribute just €1.1 (95% CI 0.6–1.6) million. The main differences in health impacts were mostly driven by differences in the pollution sources, the magnitude of such sources and distribution patterns in the atmosphere. The smallest health effects, with the exception of the green residential areas, were observed in the industrial cities Kohtla-Jarve and Narva (due to the small share contributed by local residential heating and relatively little car traffic). However, it is questionable whether the mass of fine particles is the best indicator of air pollution risk in such areas.

We aimed to explore the effect of ambient air pollution on individual persons' levels of subjective well-being. Our research question was: to what extent is an individual's life satisfaction shaped by exposure to PM10?We used regression models to analyse data on subjective well-being indicators from the last two waves of the European social survey (ESS) and detailed information on local levels of the air pollutant PM10.An increase in PM10 annual concentrations by 1 μg/m(3) was associated with a significant reduction in life satisfaction of .017 points on the ESS 10-point life satisfaction scale.Our findings suggest that even in cases of relatively low levels of PM10 air pollution (mean annual concentration of 8.3 ± 3.9 μg/m(3)), in addition to the effects on physical health, exposure negatively affects subjective assessments of well-being.