Air Pollution in Europe.
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ABSTRACT:
SUBMITTER: Koolen CD
PROVIDER: S-EPMC6391984 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe paper presents an overview of air quality in the 27 member countries of the European Union (EU) and the United Kingdom (previous EU-28), from 2000 to 2017. We reviewed the progress made towards meeting the air quality standards established by the EU Ambient Air Quality Directives (European Council Directive 2008/50/EC) and the World Health Organization (WHO) Air Quality Guidelines by estimating the trends (Mann-Kendal test) in national emissions of main air pollutants, urban population exposure to air pollution, and in mortality related to exposure to ambient fine particles (PM2.5) and tropospheric ozone (O3).ResultsDespite significant reductions of emissions (e.g., sulfur oxides: ~ 80%, nitrogen oxides: ~ 46%, non-methane volatile organic compounds: ~ 44%, particulate matters with a diameter lower than 2.5 µm and 10 µm: ~ 30%), the EU-28 urban population was exposed to PM2.5 and O3 levels widely exceeding the WHO limit values for the protection of human health. Between 2000 and 2017, the annual PM2.5-related number of deaths decreased (- 4.85 per 106 inhabitants) in line with a reduction of PM2.5 levels observed at urban air quality monitoring stations. The rising O3 levels became a major public health issue in the EU-28 cities where the annual O3-related number of premature deaths increased (+ 0.55 deaths per 106 inhabitants).ConclusionsTo achieve the objectives of the Ambient Air Quality Directives and mitigate air pollution impacts, actions need to be urgently taken at all governance levels. In this context, greening and re-naturing cities and the implementation of fresh air corridors can help meet air quality standards, but also answer to social needs, as recently highlighted by the COVID-19 lockdowns.
| S-EPMC7937352 | biostudies-literature
Project description:Air pollutants, especially PM2.5 and NO2, are associated with adverse health impacts, as shown by numerous epidemiological studies. In these studies, the observed health impacts have been correlated with ambient concentrations, mainly taken from air pollution monitoring stations. However, individuals are harmed by the pollutants in the inhaled air at the places where they stay, and thus, the concentration of pollutants in the inhaled air is obviously a better indicator for health impacts than the ambient concentration at a monitoring station. Furthermore, the current method for estimating the occurrence of chronic diseases uses annual average concentrations as indicator. However, according to current hypotheses, chronic diseases, especially chronic mortality, develop through the exposure to pollutants over many years, maybe up to a full lifetime. Thus in this study, a methodology and a computer-aided probabilistic model system are described for calculating the exposure of a person to PM2.5 and NO2 over the whole lifetime where the person is characterized by attributes such as age, gender, place of residence and work as well as socioeconomic status. The model system contains a “life course trajectory model”, which estimates the course of the education and professional development for the past lifetime of a person, whose present socioeconomic status is known. Furthermore, a “time-activity model” estimates at which places (so-called micro-environments) a person with a certain socioeconomic status stayed and how long he stayed there within a certain year. The concentrations of air pollutants in indoor environments are calculated with a “mass-balance model”, the outdoor concentrations with “atmospheric models”. Finally, the results of these models are combined to estimate the annual average exposure for the life years of individuals and population subgroups. The exposure is then used to estimate and monetize health impacts. The exposures and health impacts for a number of population subgroups in Europe are presented. For instance, a European citizen, who was 70 years old in 2015, has been exposed to around 25 μg/m3 of PM2.5 during his lifetime above the age of 30, which is associated with a reduction of life expectancy of 13.4 days per year of exposure above 30.
| S-EPMC9174982 | biostudies-literature
Project description:As our results suggested that metformin acts to limit mitochondrial ROS and calcium-mediated activation of IL-6, we reasoned it would likely affect other processes in alveolar macrophages triggered by exposure to particulate matter (PM). Therefore, we treated mice with metformin in the drinking water for 24 hours before we instilled PM intratracheally. We then flow-sorted alveolar macrophages from whole lung homogenates 24 hours later for transcriptomic analysis (RNA-Seq).
2018-10-05 | GSE98731 | GEO
Project description:AimsAmbient air pollution is a major health risk, leading to respiratory and cardiovascular mortality. A recent Global Exposure Mortality Model, based on an unmatched number of cohort studies in many countries, provides new hazard ratio functions, calling for re-evaluation of the disease burden. Accordingly, we estimated excess cardiovascular mortality attributed to air pollution in Europe.Methods and resultsThe new hazard ratio functions have been combined with ambient air pollution exposure data to estimate the impacts in Europe and the 28 countries of the European Union (EU-28). The annual excess mortality rate from ambient air pollution in Europe is 790 000 [95% confidence interval (95% CI) 645 000-934 000], and 659 000 (95% CI 537 000-775 000) in the EU-28. Between 40% and 80% are due to cardiovascular events, which dominate health outcomes. The upper limit includes events attributed to other non-communicable diseases, which are currently not specified. These estimates exceed recent analyses, such as the Global Burden of Disease for 2015, by more than a factor of two. We estimate that air pollution reduces the mean life expectancy in Europe by about 2.2 years with an annual, attributable per capita mortality rate in Europe of 133/100 000 per year.ConclusionWe provide new data based on novel hazard ratio functions suggesting that the health impacts attributable to ambient air pollution in Europe are substantially higher than previously assumed, though subject to considerable uncertainty. Our results imply that replacing fossil fuels by clean, renewable energy sources could substantially reduce the loss of life expectancy from air pollution.
| S-EPMC6528157 | biostudies-literature
Project description:PURPOSE OF REVIEW:The aim of this review is to identify the key contextual and methodological differences in health impact assessments (HIA) of ambient air pollution performed for Europe. We limited our review to multi-country reviews. An additional aim is to quantify some of these differences by applying them in a HIA template in three European cities. RECENT FINDINGS:Several HIAs of ambient air pollution have been performed for Europe, and their key results have been largely disseminated. Different studies have, however, come up with substantial differences in attributed health effects. It is of importance to review the background contributing to these differences and to quantify their importance for decision makers who will use them. We identified several methodological differences that could explain the discrepancy behind the number of attributable deaths or years of life lost. The main differences are due to the exposure-response functions chosen, the ways of assessing air pollution levels, the air pollution scenarios and the study population. In the quantification part, we found that using risk estimates from the European Study of Cohorts for Air Pollution Effects (ESCAPE) instead of the American Cancer Society (ACS) study could nearly double the attributable burden of ambient air pollution. This study provides some insights into the differential results in previously published HIAs on air pollution in Europe. These results are important for stakeholders in order to make informed decisions.
| S-EPMC5876343 | biostudies-literature
Project description:Air pollution poses the largest environmental health risk in Europe. Particulate matter (PM) concentrations are the most harmful pollutants representing the main air quality indicator in the Sustainable Development Goals (SDGs). The air quality surveillance in Europe is based on a monitoring network that is too coarse for a comprehensive evaluation of the air pollution burden. We link raw pollutant data with remotely sensed products using Bayesian geostatistical models and for the first time estimate pan-European near-surface concentrations of both fine (PM2.5) and coarse (PM10) particles at 1 km2 spatial resolution during 2006-2019. We evaluate the compliance with the air quality thresholds set by the World Health Organization (WHO) and the European Union (EU) and assess country-wise trends. The results show that during the last 14 years, PM10 and PM2.5 concentrations declined by 36.5% (95% credible interval: 30.3, 41.9%) and 39.1% (26.6, 50.5%), respectively. The number of people exposed to PM10 levels above the WHO thresholds decreased from 78.3% (52.6, 91.8%) in 2006 to 28.4% (16.2, 43.7%) in 2019; for PM2.5, the decrease was smaller: from 91.0% (61.3, 99.1%) exposed in 2006 to 53.6% (33.5, 76.3%) in 2019. Although there is a clear improvement in the overall picture, stricter measures are needed to ensure compliance with the WHO guidelines.
| S-EPMC8600664 | biostudies-literature
Project description:Previous studies have reported a decrease in air pollution levels following the enforcement of lockdown measures during the first wave of the COVID-19 pandemic. However, these investigations were mostly based on simple pre-post comparisons using past years as a reference and did not assess the role of different policy interventions. This study contributes to knowledge by quantifying the association between specific lockdown measures and the decrease in NO2, O3, PM2.5, and PM10 levels across 47 European cities. It also estimated the number of avoided deaths during the period. This paper used new modelled data from the Copernicus Atmosphere Monitoring Service (CAMS) to define business-as-usual and lockdown scenarios of daily air pollution trends. This study applies a spatio-temporal Bayesian non-linear mixed effect model to quantify the changes in pollutant concentrations associated with the stringency indices of individual policy measures. The results indicated non-linear associations with a stronger decrease in NO2 compared to PM2.5 and PM10 concentrations at very strict policy levels. Differences across interventions were also identified, specifically the strong effects of actions linked to school/workplace closure, limitations on gatherings, and stay-at-home requirements. Finally, the observed decrease in pollution potentially resulted in hundreds of avoided deaths across Europe.
| S-EPMC8791935 | biostudies-literature
Project description:In this study, we modeled early life air pollution exposure using C57BL/6J male mice on a controlled chow diet, exposed to real-world inhaled concentrated PM2.5 (~10x ambient level/ ~60-120g/m3) or filtered air (FA) over 14 weeks. We investigated PM2.5 effects on phenotype, transcriptome and chromatin accessibility, compared the effects with a prototypical high-fat diet (HFD) stimulus, and examined the effects of cessation of exposure on reversibility of phenotype/genotype.
2020-11-05 | GSE145840 | GEO
Project description:Chronic exposure to ambient particulate matter (PM) increases the risk of cardiovascular disease (CVD). One proposed mechanism linking PM exposure and CVD is the induction of low-grade systemic inflammation that underlies disease progression. However, the intermediaries that relay signals from the proximal sites of inflammation to the periphery remain unknown. We have previously shown that fine PM (PM2.5) alter red blood cell distribution width. Therefore, the overall goal of this study was to elucidate how PM exposure impacts the spleen and splenic macrophages which are primarily responsible for the turnover of aged and damaged red blood cells.
2024-12-02 | GSE262906 | GEO
Project description:Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.
| S-EPMC5923822 | biostudies-other