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This study aims to estimate the mortality risk associated with air pollution in a Swedish cohort with relatively low exposure. Air pollution models were used to estimate annual mean concentrations of particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5), primary emitted carbonaceous particles (BC/pOC), sea salt, chemically formed particles grouped as secondary inorganic and organic aerosols (SIA and SOA) as well as ozone (O3) and nitrogen dioxide (NO2). The exposure, as a moving average was calculated based on home address for the time windows 1 year (lag 1), 1–5 years (lag 1–5) and 1–10 years (lag 1–10) preceding the death. During the study period, 1151 cases of natural mortality, 253 cases of cardiovascular disease (CVD) mortality and 113 cases of respiratory and lung cancer mortality were observed during 369,394 person-years of follow-up. Increased natural mortality was observed in association with NO2 (3% [95% CI −8–14%] per IQR) and PM2.5 (2% [95% CI −5–9%] for an IQR increase) and its components, except for SOA where a decreased risk was observed. Higher risk increases were observed for CVD mortality (e.g., 18% [95% CI 1–39%] per IQR for NO2). These findings at low exposure levels are relevant for future decisions concerning air quality policies.

An accurate simulation of the absorption properties is key for assessing the radiative effects of aerosol on meteorology and climate. The representation of how chemical species are mixed inside the particles (the mixing state) is one of the major uncertainty factors in the assessment of these effects. Here we compare aerosol optical properties simulations over Europe and North America, coordinated in the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII), to one year of AERONET sunphotometer retrievals, in an attempt to identify a mixing state representation that better reproduces the observed single scattering albedo and its spectral variation. We use a single postprocessing tool (FlexAOD) to derive aerosol optical properties from simulated aerosol speciation profiles, and focus on the absorption enhancement of black carbon when it is internally mixed with more scattering material, discarding from the analysis scenes dominated by dust. We found that the single scattering albedo at 440 nm (ω0,440) is on average overestimated (underestimated) by 3-5% when external (core-shell internal) mixing of particles is assumed, a bias comparable in magnitude with the typical variability of the quantity. The (unphysical) homogeneous internal mixing assumption underestimates ω0,440 by ~14%. The combination of external and core-shell configurations (partial internal mixing), parameterized using a simplified function of air mass aging, reduces the ω0,440 bias to -1/-3%. The black carbon absorption enhancement (Eabs) in core-shell with respect to the externally mixed state is in the range 1.8-2.5, which is above the currently most accepted upper limit of ~1.5. The partial internal mixing reduces Eabs to values more consistent with this limit. However, the spectral dependence of the absorption is not well reproduced, and the absorption Angostrom exponent 𝐴𝐴𝐸675- 440 is overestimated by 70-120%. Further testing against more comprehensive campaign data, including a full characterization of the aerosol profile in terms of chemical speciation, mixing state, and related optical properties, would help in putting a better constraint on these calculations.

Background Road traffic noise has been linked to increased risk of ischemic heart disease, yet evidence on stroke shows mixed results. We examine the association between long-term exposure to road traffic noise and incidence of stroke, overall and by subtype (ischemic or hemorrhagic), after adjustment for air pollution. Methods Twenty-five thousand six hundred and sixty female nurses from the Danish Nurse Cohort recruited in 1993 or 1999 were followed for stroke-related first-ever hospital contact until December 31st, 2014. Full residential address histories since 1970 were obtained and annual means of road traffic noise (L den [dB]) and air pollutants (particulate matter with diameter < 2.5 μm and < 10 μm [PM 2.5 and PM 10 ], nitrogen dioxide [NO 2 ], nitrogen oxides [NOx]) were determined using validated models. Time-varying Cox regression models were used to estimate hazard ratios (HR) (95% confidence intervals [CI]) for the associations of one-, three-, and 23-year running means of L den preceding stroke (all, ischemic or hemorrhagic), adjusting for stroke risk factors and air pollutants. The World Health Organization and the Danish government’s maximum exposure recommendations of 53 and 58 dB, respectively, were explored as potential L den thresholds. Results Of 25,660 nurses, 1237 developed their first stroke (1089 ischemic, 148 hemorrhagic) during 16 years mean follow-up. For associations between a 1-year mean of L den and overall stroke incidence, the estimated HR (95% CI) in the fully adjusted model was 1.06 (0.98–1.14) per 10 dB, which attenuated to 1.01 (0.93–1.09) and 1.00 (0.91–1.09) in models further adjusted for PM 2.5 or NO 2 , respectively. Associations for other exposure periods or separately for ischemic or hemorrhagic stroke were similar. There was no evidence of a threshold association between L den and stroke. Conclusions Long-term exposure to road traffic noise was suggestively positively associated with the risk of overall stroke, although not after adjusting for air pollution.

Background Inconclusive evidence has suggested a possible link between air pollution and central nervous system (CNS) tumors. We investigated a range of air pollutants in relation to types of CNS tumors. Methods We identified all ( n  = 21,057) intracranial tumors in brain, meninges and cranial nerves diagnosed in Denmark between 1989 and 2014 and matched controls on age, sex and year of birth. We established personal 10-year mean residential outdoor exposure to particulate matter < 2.5 μm (PM 2.5 ), nitrous oxides (NO X ), primary emitted black carbon (BC) and ozone. We used conditional logistic regression to calculate odds ratios (OR) linearly (per interquartile range (IQR)) and categorically. We accounted for personal income, employment, marital status, use of medication as well as socio-demographic conditions at area level. Results Malignant tumors of the intracranial CNS was associated with BC (OR: 1.034, 95%CI: 1.005–1.065 per IQR. For NO x the OR per IQR was 1.026 (95%CI: 0.998–1.056). For malignant non-glioma tumors of the brain we found associations with PM 2.5 (OR: 1.267, 95%CI: 1.053–1.524 per IQR), BC (OR: 1.049, 95%CI: 0.996–1.106) and NO x (OR: 1.051, 95% CI: 0.996–1.110). Conclusion Our results suggest that air pollution is associated with malignant intracranial CNS tumors and malignant non-glioma of the brain. However, additional studies are needed.

High-resolution air quality data are critical for exposure assessment, regulatory compliance, and urban planning. In this study, we present modelled annual mean concentrations of NO2, PM2.5, PM10, Black Carbon (BC), and particle number concentration (PNC) for all ~2.5 million Danish addresses in 2019 using the Air Quality at Your Street 2.0 system. The modelling framework combines coupled chemistry–transport models (DEHM/UBM/OSPM) with input from the Green Mobility Model and GPS-based vehicle speed data. Model outputs were evaluated against observations from the Danish Air Quality Monitoring Programme, showing strong agreement for NO2, PM2.5, PM10, and BC, but notable overestimation of PNC background levels and underestimation of street contributions. Indicative exceedances of NO2 EU limit values decreased markedly from 2012 to 2019, while exceedances of updated EU and WHO guidelines persist, especially for particulate matter. This work identifies key sources of model uncertainty and supports high-resolution national-scale assessment and citizen access via an interactive map.

A tighter integration of modeling frameworks for climate and air quality is urgently needed to assess the impacts of clean air policies on future Arctic and global climate. We combined a new model emulator and comprehensive emissions scenarios for air pollutants and greenhouse gases to assess climate and human health co-benefits of emissions reductions. Fossil fuel use is projected to rapidly decline in an increasingly sustainable world, resulting in far-reaching air quality benefits. Despite human health benefits, reductions in sulfur emissions in a more sustainable world could enhance Arctic warming by 0.8 °C in 2050 relative to the 1995–2014, thereby offsetting climate benefits of greenhouse gas reductions. Targeted and technically feasible emissions reduction opportunities exist for achieving simultaneous climate and human health co-benefits. It would be particularly beneficial to unlock a newly identified mitigation potential for carbon particulate matter, yielding Arctic climate benefits equivalent to those from carbon dioxide reductions by 2050.

Ozone air pollution is identified as one of the main threats bearing upon human health and ecosystems, with 25 000 deaths in 2005 attributed to surface ozone in Europe (IIASA 2013 TSAP Report #10). In addition, there is a concern that climate change could negate ozone pollution mitigation strategies, making them insufficient over the long run and jeopardising chances to meet the long term objective set by the European Union Directive of 2008 (Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008) (60 ppbv, daily maximum). This effect has been termed the ozone climate penalty. One way of assessing this climate penalty is by driving chemistry-transport models with future climate projections while holding the ozone precursor emissions constant (although the climate penalty may also be influenced by changes in emission of precursors). Here we present an analysis of the robustness of the climate penalty in Europe across time periods and scenarios by analysing the databases underlying 11 articles published on the topic since 2007, i.e. a total of 25 model projections. This substantial body of literature has never been explored to assess the uncertainty and robustness of the climate ozone penalty because of the use of different scenarios, time periods and ozone metrics. Despite the variability of model design and setup in this database of 25 model projection, the present meta-analysis demonstrates the significance and robustness of the impact of climate change on European surface ozone with a latitudinal gradient from a penalty bearing upon large parts of continental Europe and a benefit over the North Atlantic region of the domain. Future climate scenarios present a penalty for summertime (JJA) surface ozone by the end of the century (2071-2100) of at most 5 ppbv. Over European land surfaces, the 95% confidence interval of JJA ozone change is [0.44; 0.64] and [0.99; 1.50] ppbv for the 2041-2070 and 2071-2100 time windows, respectively.

Manure acidification has been introduced as an abatement to reduce ammonia (NH3) emissions to improve air quality and protect terrestrial and aquatic environments from nitrogen deposition. A successful regulation of NH3 emissions using manure acidification might, however, result in increased nitrogen leaching from fertilized fields with adverse effects on freshwater and marine ecosystems, if the overall fertilizer application rate in the fields is not adjusted according to the increased fertilizer value of the manure. We apply a holistic model framework encapsulating all important environmental compartments to assess the ecological and economic consequences of a specific agricultural practice or a combination of these. The results show that manure acidification combined with air cleaners reduces NH3 emission and atmospheric nitrogen deposition with substantial positive effects on the terrestrial environment. Although manure acidification results in a slight increase in total nitrogen input into freshwater and marine ecosystems, the subsequent increase in chlorophyll a concentration and decrease in water transparency is insignificant. Hence, according to the model results, manure acidification will improve terrestrial nature quality, with no significant adverse effects on the aquatic environments.

Air pollution is negatively associated with cardiovascular health. Impediments to efficient regulation include lack of knowledge about which sources of air pollution contributes most to health burden and few studies on effects of the potentially more potent ultrafine particles (UFP). The authors aimed to investigate myocardial infarction (MI) morbidity and specific types and sources of air pollution. We identified all persons living in Denmark in the period 2005-2017, age y and never diagnosed with MI. We quantified 5-y running time-weighted mean concentrations of air pollution at residencies, both total and apportioned to traffic and nontraffic sources. We evaluated particulate matter (PM) with aerodynamic diameter ( ), (UFP), elemental carbon (EC), and nitrogen dioxide ( ). We used Cox proportional hazards models, with adjustment for time-varying exposures, and personal and area-level demographic and socioeconomic covariates from high-quality administrative registers. In this nationwide cohort of 1,964,702 persons (with person-years of follow-up and 71,285 cases of MI), UFP and were associated with increased risk of MI with hazard ratios (HRs) per interquartile range (IQR) of 1.040 [95% confidence interval (CI): 1.025, 1.055] and 1.053 (95% CI: 1.035, 1.071), respectively. HRs per IQR of UFP and from nontraffic sources were similar to the total (1.034 and 1.051), whereas HRs for UFP and from traffic sources were smaller (1.011 and 1.011). The HR for EC from traffic sources was 1.013 (95% CI: 1.003, 1.023). from nontraffic sources was associated with MI ( ; 95% CI: 1.034, 1.062) but not from traffic sources. In general, nontraffic sources contributed more to total air pollution levels than national traffic sources. and UFP from traffic and nontraffic sources were associated with increased risk of MI, with nontraffic sources being the dominant source of exposure and morbidity. https://doi.org/10.1289/EHP10556.

Coastal seas and estuarine systems are highly variable in both time and space and with their heterogeneity difficult to capture with measurements. Models are useful tools in obtaining a better spatiotemporal coverage or, at least, a better understanding of the impacts such heterogeneity has in driving variability in coastal oceans and estuaries. A model-based sensitivity study is constructed in this study in order to examine the effects of short-term variability in surface water p on the annual air-sea exchange in coastal regions. An atmospheric transport model formed the basis of the modelling framework for the study of the Baltic Sea and the Danish inner waters. Several maps of surface water p were employed in the modelling framework. While a monthly Baltic Sea climatology (BSC) had already been developed, the current study further extended this with the addition of an improved near-coastal climatology for the Danish inner waters. Furthermore, daily surface fields of p were obtained from a mixed layer scheme constrained by surface measurements of p (JENA). Short-term variability in surface water p was assessed by calculating monthly mean diurnal cycles from continuous measurements of surface water p , observed at stationary sites within the Baltic Sea. No apparent diurnal cycle was evident in winter, but diurnal cycles (with amplitudes up to 27  atm) were found from April to October. The present study showed that the temporal resolution of surface water p played an influential role on the annual air-sea exchange for the coastal study region. Hence, annual estimates of exchanges are sensitive to variation on much shorter time scales, and this variability should be included for any model study investigating the exchange of across the air-sea interface. Furthermore, the choice of surface p maps also had a crucial influence on the simulated air-sea exchange.