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Background and Aims: We aimed to assess the associations of exposure to air pollutants and standard and advanced lipoprotein measures, in a nationwide sample representative of the adult population of Spain. Methods: We included 4647 adults (>18 years), participants in the national, cross‐sectional, population‐based di@bet.es study, conducted in 2008–2010. Standard lipid measurements were analysed on an Architect C8000 Analyzer (Abbott Laboratories SA). Lipoprotein analysis was made by an advanced 1H‐NMR lipoprotein test (Liposcale®). Participants were assigned air pollution concentrations for particulate matter <10 μm (PM10), <2.5 μm (PM2.5) and nitrogen dioxide (NO2), corresponding to the health examination year, obtained by modelling combined with measurements taken at air quality stations (CHIMERE chemistry‐transport model). Results: In multivariate linear regression models, each IQR increase in PM10, PM2.5 and NO2 was associated with 3.3%, 3.3% and 3% lower levels of HDL‐c and 1.3%, 1.4% and 1.1% lower HDL particle (HDL‐p) concentrations (p <.001 for all associations). In multivariate logistic regression, there was a significant association between PM10, PM2.5 and NO2 concentrations and the odds of presenting low HDL‐c (<40 mg/dL), low HDL‐p (

Exposure to air particulate matter has been linked with hypertension and blood pressure levels. The metabolic risks of air pollution could vary according to the specific characteristics of each area, and has not been sufficiently evaluated in Spain. We analyzed 1103 individuals, participants in a Spanish nationwide population based cohort study (di@bet.es), who were free of hypertension at baseline (2008–2010) and completed a follow-up exam of the cohort (2016–2017). Cohort participants were assigned air pollution concentrations for particulate matter < 10 μm (PM10) and < 2.5 μm (PM2.5) during follow-up (2008–2016) obtained through modeling combined with measurements taken at air quality stations (CHIMERE chemistry-transport model). Mean and SD concentrations of PM10 and PM2.5 were 20.17 ± 3.91 μg/m3 and 10.83 ± 2.08 μg/m3 respectively. During follow-up 282 cases of incident hypertension were recorded. In the fully adjusted model, compared with the lowest quartile of PM10, the multivariate weighted ORs (95% CIs) for developing hypertension with increasing PM10 exposures were 0.82 (0.59–1.14), 1.28 (0.93–1.78) and 1.45 (1.05–2.01) in quartile 2, 3 and 4 respectively (p for a trend of 0.003). The corresponding weighted ORs according to PM2.5 exposures were 0.80 (0.57–1.13), 1.11 (0.80–1.53) and 1.48 (1.09–2.00) (p for trend 0.004). For each 5-μg/m3 increment in PM10 and PM2.5 concentrations, the odds for incident hypertension increased 1.22 (1.06–1.41) p = 0.007 and 1.39 (1.07–1.81) p = 0.02 respectively. In conclusion, our study contributes to assessing the impact of particulate pollution on the incidence of hypertension in Spain, reinforcing the need for improving air quality as much as possible in order to decrease the risk of cardiometabolic disease in the population. [ABSTRACT FROM AUTHOR]

Current European legislation aims to reduce the air pollutants emitted by European countries in the coming years. In this context, this article studies the effects on air quality of the measures considered for 2030 in the Spanish National Air Pollution Control Programme (NAPCP). Three different emission scenarios are investigated: a scenario with the emissions in 2016 and two other scenarios, one with existing measures in the current legislation (WEM2030) and another one considering the additional measures of NAPCP (WAM2030). Previous studies have addressed this issue at a national level, but this study assesses the impact at the street scale in three neighborhoods in Madrid, Spain. NO2 concentrations are modelled at high spatial resolution by means of a methodology based on computational fluid dynamic (CFD) simulations driven by mesoscale meteorological and air quality modelling. Spatial averages of annual mean NO2 concentrations are only estimated to be below 40 µg/m3 in all three neighborhoods for the WAM2030 emission scenarios. However, for two of the three neighborhoods, there are still zones (4–12% of the study areas) where the annual concentration is higher than 40 µg/m3. This highlights the importance of considering microscale simulations to assess the impacts of emission reduction measures on urban air quality. [ABSTRACT FROM AUTHOR]

This paper assesses the health impact, in terms of the reduction of premature deaths associated with changes in air pollutant exposure, resulting from double-aim strategies for reducing emissions of greenhouse gases and air pollutants from the transport sector for the year 2030 in Spain. The impact on air quality of selected measures for reducing emissions from the transport sector (increased penetration of biofuel and electric car use) was assessed by air quality modeling. The estimation of population exposure to NO2, particulate matter (PM) and O3 allows for estimation of associated mortality and external costs in comparison with the baseline scenario with no measures. The results show that the penetration of the electric vehicle provided the largest benefits, even when the emissions due to the additional electricity demand were considered. [ABSTRACT FROM AUTHOR]

During the last few decades, European legislation has driven progress in reducing air pollution in Europe through emission mitigation measures. In this paper, we use a chemistry transport model to assess the impact on ambient air quality of the measures considered for 2030 in the for the scenarios with existing (WEM2030) and additional measures (WAM2030). The study estimates a general improvement of air quality for the WAM2030 scenario, with no non-compliant air quality zones for NO2, SO2, and PM indicators. Despite an improvement for O3, the model still estimates non-compliant areas. For this pollutant, the WAM2030 scenario leads to different impacts depending on the indicator considered. Although the model estimates a reduction in maximum hourly O3 concentrations, small increases in O3 concentrations in winter and nighttime in the summer lead to increases in the annual mean in some areas and increases in other indicators (SOMO35 for health impacts and AOT40 for impacts on vegetation) in some urban areas. The results suggest that the lower NOx emissions in the WEM and WAM scenarios lead to less removal of O3 by NO titration, especially background ozone in winter and both background and locally produced ozone in summer, in areas with high NOx emissions. [ABSTRACT FROM AUTHOR]

This paper aims to provide scientific support for decision-making in the field of improving air quality by evaluating pollution reduction measures included in the current Spanish policy framework of the 1st National Air Pollution Control Programme (NAPCP). First, the health impacts of air quality are estimated by using the concentrations estimated by multiscale air quality modeling and the recommended concentration–response functions (CRF), specifically as a result of exposure to particulate matter (PM), nitrogen dioxide (NO2), and ozone (O3). Second, the associated external costs are calculated by monetization techniques. Two scenarios are analyzed: a package including existing measures (WM2030) and a package with additional measures (WAM2030). Compared with the baseline scenario, an improvement was found in the health effects of NO2, PM10, and PM2.5, while for O3 there was a slight worsening, mainly due to the increase in the O3 metric used (SOMO35), which increases over some urban areas. Despite this, the monetary valuation of the total effects on health as a whole shows external benefits due to the adoption of measures (WM2030), compared with the reference scenario (no measures) of more than € 17.5 billion and, when considering the additional measures (WAM2030), benefits of about € 58.1 billion. [ABSTRACT FROM AUTHOR]

For air quality management, while numerical tools are mainly evaluated to assess their performances on absolute concentrations, this study assesses the impact of their settings on the robustness of model responses to emission reduction strategies for the main criteria pollutants. The effect of the spatial resolution and chemistry schemes is investigated. We show that whereas the spatial resolution is not a crucial setting (except for NO 2), the chemistry scheme has more impact, particularly when assessing hourly values of the absolute potential of concentrations. The analysis of model responses under the various configurations triggered an analysis of the impact of using online models, like WRF-chem or WRF-CHIMERE, which accounts for the impact of aerosol concentrations on meteorology. This study informs the air quality modeling community on what extent some model settings can affect the expected model responses to emission changes. We suggest to not activate online effects when analyzing the effect of an emission reduction strategy to avoid any confusion in the interpretation of results even if an online simulation should represent better the reality. [Display omitted] • Even deemed small changes in the model settings can greatly modify model responses to emission changes. • Model delta is, on average, not so sensitive to chemistry scheme but at an hourly scale, differences can be large. • Model horizontal resolution has a small impact on model delta, a 3 km resolution seems sufficient to obtain a robust delta for PM and ozone. • For online models, a change of emissions modifies the meteorology which can affect model responses to emission changes. [ABSTRACT FROM AUTHOR]