Differential impact of government lockdown policies on reducing air pollution levels and related mortality in Europe.

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.

Fine Particulate Matter Related to Multiple Sclerosis Relapse in Young Patients.

Objective: Particulate matter (PM) of aerodynamic diameter smaller than 10 µm (PM10) has been associated with multiple sclerosis (MS) relapse. However, the impact of smaller PM with a greater ability to penetrate human organism has never been assessed. We evaluated the impact of PM smaller than 2.5 µm (PM2.5) on the risk of MS relapse. Material and Methods: In a case-crossover study, we included 2,109 consecutive hospitalizations likely due to MS relapse in day hospital in 5 MS centers in the Paris area from January 2009 to December 2013. For each hospitalization, the natural logarithm of the average weekly PM2.5 concentrations (µg/m3) at the patient's residence address during each of the 6 weeks (week[0] to week[-5]) preceding admission was compared with the concentration during the previous week, using a conditional logistic regression adjusted on temperature, flu-like syndrome rate, pollen count, and holiday period. Results: PM2.5 average concentration during week[-3] was significantly associated with the risk of hospitalization for MS relapse [OR = 1.21 (CI 1.01;1.46)]. The association was stronger in patients younger than 30 years [OR=1.77 (CI 1.10; 2.83)]. Conclusion: Our study demonstrates an association between exposure to PM2.5 and MS relapse, particularly in young people.

Data fusion for air quality mapping using low-cost sensor observations: Feasibility and added-value.

In Nantes, low-cost sensors were installed in the city center and deployed on driving school cars, ambulances and service vehicles to measure PM10 concentrations. This work aims to use the large amount of observations provided by the sensors for air quality mapping at the urban scale in order to show the potential added-value with respect to the dispersion model (ADMS-Urban) calculations. A preprocessing is applied to the raw sensor dataset to remove the unreliable observations based on an outlier detection technique and to compensate for the measurement drift by adjusting the estimated daily variation of the underlying background PM10 concentrations with the reference stations. Then, data fusion is performed by combining the preprocessed fixed and mobile low-cost sensor observations and the 2016 annual average of the ADMS-Urban outputs. The measurement uncertainty related to the low-cost sensors and the dispersion of the data are considered in data fusion as the Variance of Measurement Error (VME). The spatial interpolation is achieved at hourly resolution and results are presented for November 29th, 2018 from 7 am to 7 pm. Hourly fused maps show disparate responses to data fusion mainly depending on the variability of the sensor data and the correlation between the sensor observations and the drift. The data fusion performance has been investigated by comparing the daily average of the estimated concentrations, the reference observations and the hourly model outputs at each station of the Air Pays de la Loire network. Results show that considering the model alone implies 8% bias whereas including the LCS observations reduces the bias to 2.5%. However, the concentration distributions related to the data fusion are characterized by a lower dispersion than the reference observations and the model estimation. Thus, the fusion smooths the PM10 peaks. In addition, the effect of the measurement uncertainty has been investigated by doubling it or reducing it to the reference station measurement uncertainty. The sensitivity study demonstrates that the performance is increasing by reducing the uncertainty. This highlights the importance to estimate accurately the measurement uncertainty of the devices to ensure relevant air quality mapping. The method efficiency is also quite limited by the low correlation between the sensor observations and the model used as external drift in the kriging that may be explained by the remaining bias on LCS data. Efforts on this issue might increase the performance of the spatial interpolation.

Modelling black carbon absorption of solar radiation: combining external and internal mixing assumptions.

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 1 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 post-processing 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 (ω 0,440) 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 ω 0,440 by ~ 14 %. The combination of external and core-shell configurations (partial internal mixing), parameterized using a simplified function of air mass aging, reduces the ω 0,440 bias to -1/-3 %. The black carbon absorption enhancement (E abs) 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 E abs to values more consistent with this limit. However, the spectral dependence of the absorption is not well reproduced, and the absorption Ångström exponent AAE 675 440 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.

Modeled deposition of nitrogen and sulfur in Europe estimated by 14 air quality model systems: evaluation, effects of changes in emissions and implications for habitat protection.

The evaluation and intercomparison of air quality models is key to reducing model errors and uncertainty. The projects AQMEII3 and EURODELTA-Trends, in the framework of the Task Force on Hemispheric Transport of Air Pollutants and the Task Force on Measurements and Modelling, respectively (both task forces under the UNECE Convention on the Long Range Transport of Air Pollution, LTRAP), have brought together various regional air quality models to analyze their performance in terms of air concentrations and wet deposition, as well as to address other specific objectives. This paper jointly examines the results from both project communities by intercomparing and evaluating the deposition estimates of reduced and oxidized nitrogen (N) and sulfur (S) in Europe simulated by 14 air quality model systems for the year 2010. An accurate estimate of deposition is key to an accurate simulation of atmospheric concentrations. In addition, deposition fluxes are increasingly being used to estimate ecological impacts. It is therefore important to know by how much model results differ and how well they agree with observed values, at least when comparison with observations is possible, such as in the case of wet deposition. This study reveals a large variability between the wet deposition estimates of the models, with some performing acceptably (according to previously defined criteria) and others underestimating wet deposition rates. For dry deposition, there are also considerable differences between the model estimates. An ensemble of the models with the best performance for N wet deposition was made and used to explore the implications of N deposition in the conservation of protected European habitats. Exceedances of empirical critical loads were calculated for the most common habitats at a resolution of 100 × 100 m2 within the Natura 2000 network, and the habitats with the largest areas showing exceedances are determined. Moreover, simulations with reduced emissions in selected source areas indicated a fairly linear relationship between reductions in emissions and changes in the deposition rates of N and S. An approximate 20 % reduction in N and S deposition in Europe is found when emissions at a global scale are reduced by the same amount. European emissions are by far the main contributor to deposition in Europe, whereas the reduction in deposition due to a decrease in emissions in North America is very small and confined to the western part of the domain. Reductions in European emissions led to substantial decreases in the protected habitat areas with critical load exceedances (halving the exceeded area for certain habitats), whereas no change was found, on average, when reducing North American emissions in terms of average values per habitat.

Influence of anthropogenic emissions and boundary conditions on multi-model simulations of major air pollutants over Europe and North America in the framework of AQMEII3.

In the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3), and as contribution to the second phase of the Hemispheric Transport of Air Pollution (HTAP2) activities for Europe and North America, the impacts of a 20 % decrease of global and regional anthropogenic emissions on surface air pollutant levels in 2010 are simulated by an international community of regional-scale air quality modeling groups, using different state-of-the-art chemistry and transport models (CTMs). The emission perturbations at the global level, as well as over the HTAP2-defined regions of Europe, North America and East Asia, are first simulated by the global Composition Integrated Forecasting System (C-IFS) model from European Centre for Medium-Range Weather Forecasts (ECMWF), which provides boundary conditions to the various regional CTMs participating in AQMEII3. On top of the perturbed boundary conditions, the regional CTMs used the same set of perturbed emissions within the regional domain for the different perturbation scenarios that introduce a 20 % reduction of anthropogenic emissions globally as well as over the HTAP2-defined regions of Europe, North America and East Asia. Results show that the largest impacts over both domains are simulated in response to the global emission perturbation, mainly due to the impact of domestic emission reductions. The responses of NO2, SO2 and PM concentrations to a 20 % anthropogenic emission reduction are almost linear (~ 20 % decrease) within the global perturbation scenario with, however, large differences in the geographical distribution of the effect. NO2, CO and SO2 levels are strongly affected over the emission hot spots. O3 levels generally decrease in all scenarios by up to ~ 1 % over Europe, with increases over the hot spot regions, in particular in the Benelux region, by an increase up to ~ 6 % due to the reduced effect of NOx titration. O3 daily maximum of 8 h running average decreases in all scenarios over Europe, by up to ~ 1 %. Over the North American domain, the central-to-eastern part and the western coast of the US experience the largest response to emission perturbations. Similar but slightly smaller responses are found when domestic emissions are reduced. The impact of intercontinental transport is relatively small over both domains, however, still noticeable particularly close to the boundaries. The impact is noticeable up to a few percent, for the western parts of the North American domain in response to the emission reductions over East Asia. O3 daily maximum of 8 h running average decreases in all scenarios over north Europe by up to ~ 5 %. Much larger reductions are calculated over North America compared to Europe. In addition, values of the Response to Extra-Regional Emission Reductions (RERER) metric have been calculated in order to quantify the differences in the strengths of nonlocal source contributions to different species among the different models. We found large RERER values for O3 (~ 0.8) over both Europe and North America, indicating a large contribution from non-local sources, while for other pollutants including particles, low RERER values reflect a predominant control by local sources. A distinct seasonal variation in the local vs. non-local contributions has been found for both O3 and PM2.5, particularly reflecting the springtime long-range transport to both continents.

Assessment and economic valuation of air pollution impacts on human health over Europe and the United States as calculated by a multi-model ensemble in the framework of AQMEII3.

The impact of air pollution on human health and the associated external costs in Europe and the United States (US) for the year 2010 are modeled by a multi-model ensemble of regional models in the frame of the third phase of the Air Quality Modelling Evaluation International Initiative (AQMEII3). The modeled surface concentrations of O3, CO, SO2 and PM2.5 are used as input to the Economic Valuation of Air Pollution (EVA) system to calculate the resulting health impacts and the associated external costs from each individual model. Along with a base case simulation, additional runs were performed introducing 20 % anthropogenic emission reductions both globally and regionally in Europe, North America and east Asia, as defined by the second phase of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP2). Health impacts estimated by using concentration inputs from different chemistry-transport models (CTMs) to the EVA system can vary up to a factor of 3 in Europe (12 models) and the United States (3 models). In Europe, the multi-model mean total number of premature deaths (acute and chronic) is calculated to be 414 000, while in the US, it is estimated to be 160 000, in agreement with previous global and regional studies. The economic valuation of these health impacts is calculated to be EUR 300 billion and 145 billion in Europe and the US, respectively. A subset of models that produce the smallest error compared to the surface observations at each time step against an all-model mean ensemble results in increase of health impacts by up to 30 % in Europe, while in the US, the optimal ensemble mean led to a decrease in the calculated health impacts by ~ 11 %. A total of 54 000 and 27 500 premature deaths can be avoided by a 20 % reduction of global anthropogenic emissions in Europe and the US, respectively. A 20 % reduction of North American anthropogenic emissions avoids a total of ~ 1000 premature deaths in Europe and 25 000 total premature deaths in the US. A 20 % decrease of anthropogenic emissions within the European source region avoids a total of 47 000 premature deaths in Europe. Reducing the east Asian anthropogenic emissions by 20 % avoids ~ 2000 total premature deaths in the US. These results show that the domestic anthropogenic emissions make the largest impacts on premature deaths on a continental scale, while foreign sources make a minor contribution to adverse impacts of air pollution.

Two-scale multi-model ensemble: is a hybrid ensemble of opportunity telling us more?

In this study we introduce a hybrid ensemble consisting of air quality models operating at both the global and regional scale. The work is motivated by the fact that these different types of models treat specific portions of the atmospheric spectrum with different levels of detail, and it is hypothesized that their combination can generate an ensemble that performs better than mono-scale ensembles. A detailed analysis of the hybrid ensemble is carried out in the attempt to investigate this hypothesis and determine the real benefit it produces compared to ensembles constructed from only global-scale or only regional-scale models. The study utilizes 13 regional and 7 global models participating in the Hemispheric Transport of Air Pollutants phase 2 (HTAP2)-Air Quality Model Evaluation International Initiative phase 3 (AQMEII3) activity and focuses on surface ozone concentrations over Europe for the year 2010. Observations from 405 monitoring rural stations are used for the evaluation of the ensemble performance. The analysis first compares the modelled and measured power spectra of all models and then assesses the properties of the mono-scale ensembles, particularly their level of redundancy, in order to inform the process of constructing the hybrid ensemble. This study has been conducted in the attempt to identify that the improvements obtained by the hybrid ensemble relative to the mono-scale ensembles can be attributed to its hybrid nature. The improvements are visible in a slight increase of the diversity (4 % for the hourly time series, 10 % for the daily maximum time series) and a smaller improvement of the accuracy compared to diversity. Root mean square error (RMSE) improved by 13-16 % compared to G and by 2-3 % compared to R. Probability of detection (POD) and false-alarm rate (FAR) show a remarkable improvement, with a steep increase in the largest POD values and smallest values of FAR across the concentration ranges. The results show that the optimal set is constructed from an equal number of global and regional models at only 15 % of the stations. This implies that for the majority of the cases the regional-scale set of models governs the ensemble. However given the high degree of redundancy that characterizes the regional-scale models, no further improvement could be expected in the ensemble performance by adding yet more regional models to it. Therefore the improvement obtained with the hybrid set can confidently be attributed to the different nature of the global models. The study strongly reaffirms the importance of an in-depth inspection of any ensemble of opportunity in order to extract the maximum amount of information and to have full control over the data used in the construction of the ensemble.

Advanced error diagnostics of the CMAQ and Chimere modelling systems within the AQMEII3 model evaluation framework.

The work here complements the overview analysis of the modelling systems participating in the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3) by focusing on the performance for hourly surface ozone by two modelling systems, Chimere for Europe and CMAQ for North America. The evaluation strategy outlined in the course of the three phases of the AQMEII activity, aimed to build up a diagnostic methodology for model evaluation, is pursued here and novel diagnostic methods are proposed. In addition to evaluating the "base case" simulation in which all model components are configured in their standard mode, the analysis also makes use of sensitivity simulations in which the models have been applied by altering and/or zeroing lateral boundary conditions, emissions of anthropogenic precursors, and ozone dry deposition. To help understand of the causes of model deficiencies, the error components (bias, variance, and covariance) of the base case and of the sensitivity runs are analysed in conjunction with timescale considerations and error modelling using the available error fields of temperature, wind speed, and NO x concentration. The results reveal the effectiveness and diagnostic power of the methods devised (which remains the main scope of this study), allowing the detection of the timescale and the fields that the two models are most sensitive to. The representation of planetary boundary layer (PBL) dynamics is pivotal to both models. In particular, (i) the fluctuations slower than ~ 1.5 days account for 70-85 % of the mean square error of the full (undecomposed) ozone time series; (ii) a recursive, systematic error with daily periodicity is detected, responsible for 10-20 % of the quadratic total error; (iii) errors in representing the timing of the daily transition between stability regimes in the PBL are responsible for a covariance error as large as 9 ppb (as much as the standard deviation of the network-average ozone observations in summer in both Europe and North America); (iv) the CMAQ ozone error has a weak/negligible dependence on the errors in NO2, while the error in NO2 significantly impacts the ozone error produced by Chimere; (v) the response of the models to variations of anthropogenic emissions and boundary conditions show a pronounced spatial heterogeneity, while the seasonal variability of the response is found to be less marked. Only during the winter season does the zeroing of boundary values for North America produce a spatially uniform deterioration of the model accuracy across the majority of the continent.

The impact of climate change on photovoltaic power generation in Europe.

Ambitious climate change mitigation plans call for a significant increase in the use of renewables, which could, however, make the supply system more vulnerable to climate variability and changes. Here we evaluate climate change impacts on solar photovoltaic (PV) power in Europe using the recent EURO-CORDEX ensemble of high-resolution climate projections together with a PV power production model and assuming a well-developed European PV power fleet. Results indicate that the alteration of solar PV supply by the end of this century compared with the estimations made under current climate conditions should be in the range (-14%;+2%), with the largest decreases in Northern countries. Temporal stability of power generation does not appear as strongly affected in future climate scenarios either, even showing a slight positive trend in Southern countries. Therefore, despite small decreases in production expected in some parts of Europe, climate change is unlikely to threaten the European PV sector.

A multi-scale health impact assessment of air pollution over the 21st century.

BACKGROUND: Ozone and PM2.5 are current risk factors for premature death all over the globe. In coming decades, substantial improvements in public health may be achieved by reducing air pollution. To better understand the potential of emissions policies, studies are needed that assess possible future health impacts under alternative assumptions about future emissions and climate across multiple spatial scales. METHOD: We used consistent climate-air-quality-health modeling framework across three geographical scales (World, Europe and Ile-de-France) to assess future (2030-2050) health impacts of ozone and PM2.5 under two emissions scenarios (Current Legislation Emissions, CLE, and Maximum Feasible Reductions, MFR). RESULTS: Consistently across the scales, we found more reductions in deaths under MFR scenario compared to CLE. 1.5 [95% CI: 0.4, 2.4] million CV deaths could be delayed each year in 2030 compared to 2010 under MFR scenario, 84% of which would occur in Asia, especially in China. In Europe, the benefits under MFR scenario (219000 CV deaths) are noticeably larger than those under CLE (109,000 CV deaths). In Ile-de-France, under MFR more than 2830 annual CV deaths associated with PM2.5 changes could be delayed in 2050 compared to 2010. In Paris, ozone-related respiratory mortality should increase under both scenarios. CONCLUSION: Multi-scale HIAs can illustrate the difference in direct consequences of costly mitigation policies and provide results that may help decision-makers choose between different policy alternatives at different scales.

Regional climate model simulations indicate limited climatic impacts by operational and planned European wind farms.

The rapid development of wind energy has raised concerns about environmental impacts. Temperature changes are found in the vicinity of wind farms and previous simulations have suggested that large-scale wind farms could alter regional climate. However, assessments of the effects of realistic wind power development scenarios at the scale of a continent are missing. Here we simulate the impacts of current and near-future wind energy production according to European Union energy and climate policies. We use a regional climate model describing the interactions between turbines and the atmosphere, and find limited impacts. A statistically significant signal is only found in winter, with changes within ±0.3 °C and within 0-5% for precipitation. It results from the combination of local wind farm effects and changes due to a weak, but robust, anticyclonic-induced circulation over Europe. However, the impacts remain much weaker than the natural climate interannual variability and changes expected from greenhouse gas emissions.