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2015
2010
Assessing the impacts of citizen-led policies on emissions, air quality and health
Air pollution is a global challenge, and especially urban areas are particularly affected by acute episodes. Traditional approaches used to mitigate air pollution primarily consider the technical aspects of the problem but not the role of citizen behaviour and day-to-day practices. ClairCity, a Horizon 2020 funded project, created an impact assessment framework considering the role of citizen behaviour to create future scenarios, aiming to improve urban environments and the wellbeing and health of its inhabitants. This framework was applied to six pilot cases: Bristol, Amsterdam, Ljubljana, Sosnowiec, Aveiro Region and Liguria Region, considering three-time horizons: 2025, 2035 and 2050. The scenarios approach includes the Business As Usual (BAU) scenario and a Final Unified Policy Scenarios (FUPS) established by citizens, decision-makers, local planners and stakeholders based on data collected through a citizen and stakeholder co-creation process. Therefore, this paper aims to present the ClairCity outcomes, analysing the quantified impacts of selected measures in terms of emissions, air quality, population exposure, and health. Each case study has established a particular set of measures with different levels of ambition, therefore different levels of success were achieved towards the control and mitigation of their specific air pollution problems. The transport sector was the most addressed by the measures showing substantial improvements for NO2, already with the BAU scenarios, and overall, even better results when applying the citizen-led FUPS scenarios. In some cases, due to a lack of ambition for the residential and commercial sector, the results were not sufficient to fulfil the WHO guidelines. Overall, it was found in all cities that the co-created scenarios would lead to environmental improvements in terms of air quality and citizens’ health compared to the baseline year of 2015. However, in some cases, the health impacts were lower than air quality due to the implementation of the measures not affecting the most densely populated areas. Benefits from the FUPS comparing to the BAU scenario were found to be highest in Amsterdam and Bristol, with further NO2 and PM10 emission reductions around 10%–16% by 2025 and 19%–28% by 2050, compared to BAU.
2021
2014
2014
2019
Assessing the environmental burden of disease related to air pollution in Europe in 2023
This report evaluates the environmental burden of disease (EBD) linked to long-term exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) across 41 European countries in 2023. Using the key health indicators—attributable deaths, years of life lost, years lived with disability, and disability-adjusted life years—the analysis quantifies the health impacts of air pollution above concentrations defined as the World Health Organisation’s air quality guideline levels. Approximately 206,000 deaths are attributable to PM2.5, while about 56,000 and 71,000 deaths area attributable to NO2 and O3, respectively. The disease burden from PM2.5 was highest due to its association with multiple health outcomes, with high baseline prevalence and mortality. Results highlight strong regional disparities, with South-Eastern Europe most affected by health effects from PM2.5 and NO2, and Southern Europe by those from O3. Findings underscore the need for targeted policies to reduce pollutant-specific health impacts in Europe.
European Topic Centre on Human Health and the Environment (ETC HE)
2025
Assessing the environmental burden of disease related to air pollution in Europe in 2022
This report evaluates the health burden due to long-term exposure to PM2.5, NO2, and O3 across Europe in 2022. By analysing all-cause and cause-specific mortality and morbidity, it estimates disease burden using four indicators: Attributable Deaths (AD), Years of Life Lost, Years Lived with Disability, and Disability-Adjusted Life Years (DALY). However, the main results only consider the impact of exposure to levels of pollutants exceeding the current WHO air quality guidelines. The results indicate that PM2.5 contributes the most significant health impact (linked to six diseases), resulting in over 2.7 million DALY across 40 countries, and resulting in 269 000 AD, with mortality rates peaking in Eastern Europe. The report introduces methodological advancements, assessing the long-term impacts of O3 for the first time. Findings underscore the critical need for targeted air quality interventions, as pollution continues to drive significant health losses across the continent, particularly among vulnerable populations.
ETC/HE
2024
2025
2015
2008
Long-term Arctic air monitoring of per- and polyfluoroalkyl substances (PFASs) is essential in assessing their long-range transport and for evaluating the effectiveness of chemical control initiatives. We report for the first time temporal trends of neutral and ionic PFASs in air from three arctic stations: Alert (Canada, 2006–2014); Zeppelin (Svalbard, Norway, 2006–2014) and Andøya (Norway, 2010–2014). The most abundant PFASs were the perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), perfluorobutanoic acid (PFBA), and fluorotelomer alcohols (FTOHs). All of these chemicals exhibited increasing trends at Alert with doubling times (t2) of 3.7 years (y) for PFOA, 2.9 y for PFOS, 2.5 y for PFBA, 5.0 y for 8:2 FTOH and 7.0 y for 10:2 FTOH. In contrast, declining or non-changing trends, were observed for PFOA and PFOS at Zeppelin (PFOA, half-life, t1/2 = 7.2 y; PFOS t1/2 = 67 y), and Andøya (PFOA t1/2 = 1.9 y; PFOS t1/2 = 11 y). The differences in air concentrations and in time trends between the three sites may reflect the differences in regional regulations and source regions. We investigate the source region for particle associated compounds using the Lagrangian particle dispersion model FLEXPART. Model results showed that PFOA and PFOS are impacted by air masses originating from the ocean or land. For instance, PFOA at Alert and PFOS at Zeppelin were dominated by oceanic air masses whereas, PFOS at Alert and PFOA at Zeppelin were influenced by air masses transported from land.
2018
2024
2012
2016
BACKGROUND: In order to use in situ measurements to constrain urban anthropogenic emissions of carbon dioxide (CO2), we use a Lagrangian methodology based on diffusive backward trajectory tracer reconstructions and Bayesian inversion. The observations of atmospheric CO2 were collected within the Tokyo Bay Area during the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) flights, from the Tsukuba tall tower of the Meteorological Research Institute (MRI) of the Japan Meteorological Agency and at two surface sites (Dodaira and Kisai) from the World Data Center for Greenhouse Gases (WDCGG).
RESULTS: We produce gridded estimates of the CO2 emissions and calculate the averages for different areas within the Kanto plain where Tokyo is located. Using these inversions as reference we investigate the impact of perturbing different elements in the inversion system. We modified the observations amount and location (surface only sparse vs. including aircraft CO2 observations), the background representation, the wind data used to drive the transport model, the prior emissions magnitude and time resolution and error parameters of the inverse model.
CONCLUSIONS: Optimized fluxes were consistent with other estimates for the unperturbed simulations. Inclusion of CONTRAIL measurements resulted in significant differences in the magnitude of the retrieved fluxes, 13% on average for the whole domain and of up to 21% for the spatiotemporal cells with the highest fluxes. Changes in the background yielded differences in the retrieved fluxes of up to 50% and more. Simulated biases in the modelled transport cause differences in the retrieved fluxes of up to 30% similar to those obtained using different meteorological winds to advect the Lagrangian trajectories. Perturbations to the prior inventory can impact the fluxes by ~ 10% or more depending on the assumptions on the error covariances. All of these factors can cause significant differences in the estimated flux, and highlight the challenges in estimating regional CO2 fluxes from atmospheric observations.
2019
2011
2026
Climate change is expected to intensify the frequency and severity of droughts across Europe,
posing significant risks to agricultural production and the food systems that depend on it. As drought
severity can range widely within one country, estimates of supply chains with higher spatial
resolution are needed to characterize drought risk exposure. This study develops an inter-regional
(NUTS-2) version of the Food and Agriculture Biomass Input Output (FABIO)[1] model to quantify
the exposure of European food trade to drought risk under current and future climate conditions.
Drought exposure is quantified by linking regional agricultural trade flows to Copernicus
satellite-based soil moisture anomaly data.
Input output (IO) analysis has been widely used to study supply-chain dependencies, resource
use, and environmental pressures embedded in production and trade. The development of
multi-regional input output (MRIO) databases, which combine national IO tables into a single
balanced global framework, has enabled such analyses at the global scale. Prominent examples
include EXIOBASE[2], Eora[3], and FIGARO[4], which have been applied to assess environmental
impacts embodied in trade. However, while these databases provide global coverage, their
national-level resolution limits their ability to capture spatially heterogeneous climate risks such as
droughts, which often vary substantially within countries. Subnational or interregional IO tables are
rarely published due to data and resource constraints, creating a critical gap for climate risk
assessments that require finer spatial detail.
This study extends FABIO[1], an established physical MRIO framework for food, feed, and biomass
flows, into an interregional European model. The interregional FABIO disaggregates national food
trade into NUTS2-level trade using regional crop and livestock production, regional demand, and
reported trade flows. The FABIO database is regionalized following two main steps, similarly to
Ouyang et al[5]. First, international trade is estimated using reported subnational trade data where
available, subject to the constraints that regional exports and imports do not exceed supply and
demand, and that national totals remain consistent with the original FABIO data. Second, domestic
interregional flows are estimated using the CHARM approach in combination with a gravity model[6].
The model distinguishes 67 sectors and 332 NUTS 2 regions.
Using this framework, drought exposure is assessed by linking regional agricultural trade with
satellite-based drought intensity metrics, considering both historical events and projected future
conditions. The results show that accounting for trade significantly increases estimated drought
exposure of food consumption in Northern Europe compared with production-based assessments.
Exposure varies strongly across food categories; non-essential commodities are generally more
exposed than staple foods. Trade can both amplify and buffer drought impacts, depending on the
geographic extent of the drought and the availability of alternative sourcing regions.
Overall, this study demonstrates the value of combining interregional input output modeling with
satellite-based climate indicators to assess the vulnerability of European food trade to droughts. The
results reveal the exposure to drought risk in regions and support the design of diversification and
resilience strategies in agricultural supply chains. The annual resolution of the model, consistent
with input output tables and available trade data, cannot capture dynamics such as monthly stock
variations that can be critical for drought impacts, and merits further research. Beyond drought risk
assessment, the interregional FABIO framework can be applied to other spatially explicit
environmental questions, including consumption-based analyses of nitrogen emissions, land use,
and other local pressures.
2026
2024
2025
2018