Urban NO2 Atlas

The Atlas shows, for selected cities, the likely effects of the implementation of “Traffic Policies” intended to reduce urban NO2 concentrations. As NO2 pollution in urban areas is mainly caused by traffic, the analysis focuses on assessing the relative contribution to the NO2 concentration in ambient air from different types of vehicles. The results, obtained for a selected number of cities in Europe show that, depending on the size of the selected “Inner Area” (by this name, we mean the area over which traffic measures are applied), one could reduce on average up to 40% the NO2 urban background concentrations. Of this average reduction, roughly 15% is linked to passenger diesel cars, 13% to trucks and 6% to vans (mostly diesel); while the remaining share is associated to other type of vehicles (buses, gasoline cars, etc…). This Atlas provides a first indication of the relative effectiveness of mobility policies aimed at reducing urban NO2 pollution concentrations in European cities. However, considering the specific assumptions in the applied approach, as on traffic flows, fleet composition, emission factors, size of the “Inner Area”, etc…, the results may not be as accurate as they would be when using detailed local data. The SHERPA-City methodology and tool applied in this Atlas can be used by local authorities to assess a broad range of air quality measures, including technological (e.g. fleet renewal, new technologies) and soft measures (i.e. promotion of walking and cycling). Such measures can be assessed alone or in combination.JRC.C.5-Air and Climat

Assessment of the sensitivity of model responses to urban emission changes in support of emission reduction strategies

© 2023 The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/The sensitivity of air quality model responses to modifications in input data (e.g. emissions, meteorology and boundary conditions) or model configurations is recognized as an important issue for air quality modelling applications in support of air quality plans. In the framework of FAIRMODE (Forum of Air Quality Modelling in Europe, https://fairmode.jrc.ec.europa.eu/) a dedicated air quality modelling exercise has been designed to address this issue. The main goal was to evaluate the magnitude and variability of air quality model responses when studying emission scenarios/projections by assessing the changes of model output in response to emission changes. This work is based on several air quality models that are used to support model users and developers, and, consequently, policy makers. We present the FAIRMODE exercise and the participating models, and provide an analysis of the variability of O3 and PM concentrations due to emission reduction scenarios. The key novel feature, in comparison with other exercises, is that emission reduction strategies in the present work are applied and evaluated at urban scale over a large number of cities using new indicators such as the absolute potential, the relative potential and the absolute potency. The results show that there is a larger variability of concentration changes between models, when the emission reduction scenarios are applied, than for their respective baseline absolute concentrations. For ozone, the variability between models of absolute baseline concentrations is below 10%, while the variability of concentration changes (when emissions are similarly perturbed) exceeds, in some instances 100% or higher during episodes. Combined emission reductions are usually more efficient than the sum of single precursor emission reductions both for O3 and PM. In particular for ozone, model responses, in terms of linearity and additivity, show a clear impact of non-linear chemistry processes. This analysis gives an insight into the impact of model’ sensitivity to emission reductions that may be considered when designing air quality plans and paves the way of more in-depth analysis to disentangle the role of emissions from model formulation for present and future air quality assessments.Peer reviewe

Assessing the Impact of Local Policies on PM2.5 Concentration Levels: Application to 10 European Cities

In this paper, we propose a methodology to evaluate the effectiveness of local emission reduction policies on PM2.5 concentration levels. In particular, we look at the impact of emission reduction policies at different scales (from urban to EU scale) on different PM2.5 baseline concentration levels. The methodology, based on a post-processing of air quality model simulations, is applied to 10 cities in Europe to understand on which sources local actions are effective to improve air quality, and over which concentration ranges. The results show that local actions are effective on low-level concentrations in some cities (e.g., Rome), whereas in other cases, policies are more effective on high-level concentrations (e.g., Krakow). This means that, in specific geographical areas, a coordinated approach (among cities or even at different administration levels) would be needed to significantly improve air quality. At last, we show that the effectiveness of local actions on urban air pollution is highly city-dependent

Assessing the Impact of Local Policies on PM2.5 Concentration Levels: Application to 10 European Cities

In this paper, we propose a methodology to evaluate the effectiveness of local emission reduction policies on PM2.5 concentration levels. In particular, we look at the impact of emission reduction policies at different scales (from urban to EU scale) on different PM2.5 baseline concentration levels. The methodology, based on a post-processing of air quality model simulations, is applied to 10 cities in Europe to understand on which sources local actions are effective to improve air quality, and over which concentration ranges. The results show that local actions are effective on low-level concentrations in some cities (e.g., Rome), whereas in other cases, policies are more effective on high-level concentrations (e.g., Krakow). This means that, in specific geographical areas, a coordinated approach (among cities or even at different administration levels) would be needed to significantly improve air quality. At last, we show that the effectiveness of local actions on urban air pollution is highly city-dependent

The Sensitivity of the CHIMERE Model to Emissions Reduction Scenarios on Air Quality in Northern Italy

The sensitivity of the CHIMERE model to emission reduction scenarios on particulate matter PM2.5 and ozone (O3) in Northern Italy is studied. The emissions of NOx, PM2.5 SO2, VOC or NH3 were reduced by 50% for different source sectors for the Lombardy region, together with 5 additional scenarios to estimate the effect of local measures on improving the air quality for the Po valley area. Firstly, we evaluate the model performance by comparing calculated surface aerosol concentrations for the standard case (no emission reductions) with observations for January and June 2005. Calculated monthly mean PM10 concentrations are in general underestimated by a factor of 1.4 for January, while NO3- and NH4+ calculated monthly mean values are in good correspondence with observations. However, SO4= is underestimated by a factor of 2.4 and the sum of elemental carbon, organic material and anthropogenic dust (PPM) is underestimated by a factor of 3.8 when compared to measurements for January 2005. For June, modelled PM10 concentrations slightly overestimate the measurements by a factor of 1.2 and calculated monthly mean SO4=, NO3-, NH4+ concentrations are in good agreement with the observations. PPM is a factor 2 underestimated. Monthly mean calculated ozone concentrations are in general 12% overestimated when compared to the observations for June 2005. Secondly, the model sensitivity of emission reduction scenarios on PM2.5 and O3 calculated concentrations for the Po valley area is evaluated. The most effective 1 scenarios to abate PM2.5 concentration are based on the SNAP2 (non-industrial combustion plants) and SNAP 7 (road traffic) sectors, for which the NOx and PM2.5 emissions are reduced by 50%. These scenarios reduce the monthly calculated PM2.5 concentrations for January for the Po valley area on average by 4-10µg/m3 and 3-8µg/m3 respectively, with maximum reductions of 13.4µg/m3 and 14µg/m3 respectively, compared to the standard case. The number of days that the 2015 PM2.5 limit value of 25µg/m3 in Milan is exceeded by reducing primary PM2.5 and NOx emissions for SNAP 2 and 7 by 50%, does not change in January when compared to the standard case for the Milan area. From the additional scenarios carried out to investigate the impact of local versus regional air pollution, it appears that 60% of the PM2.5 concentration in the greater Milan area is caused by the emissions from the Lombardy region, while 40% of the PM2.5 concentration over the Milan area is due to the emissions surrounding the Lombardy region and from the model boundary conditions. This study also showed that a more effective pollutant reduction (emissions) per tonne of pollutant reduced (concentrations) for the greater Milan area is obtained by reducing the primary PM2.5 emissions for SNAP 7 by 50%. This scenario is almost four times more efficient than reducing the PM2.5 emissions of SNAP 2 by 50%. Reducing the precursor NOx emissions by 50% is the most effective for SNAP 2 on the decrease of PM2.5 concentrations. The most effective scenario on PM2.5 decrease for which the precursor SO2 emissions are reduced is achieved by SNAP 7. Our study showed that during summer time, the largest reductions in O3 concentrations are achieved for SNAP 7 emission reductions (up to 12 ppb over a larger area around Milan), when volatile organic compounds (VOCs) are reduced by 50%JRC.H.4-Transport and air qualit

A simple and fast method to downscale chemistry transport model output fields from the regional to the urban/district scale

International audienceFor policy applications, the need to improve the resolution of environmental variables is crucial. Air pollution assessment indeed requires the use of air pollutant concentration fields at a high resolution, to better evaluate the exposure of citizens. In this paper, we propose a fast proxy-based downscaling strategy, to downscale air quality modelling results using the fraction of the pollutant concentration influenced by precursor emissions in a given cell. The approach combines in an additive way (i) a classically interpolated background pollutant fraction, with (ii) a proxy-based concentration derived from the emissions. The proxy-based pollutant fraction is spread over the high resolution mesh into the surrounding cells with a Gaussian approach to account for diffusion effects. The evaluation of our approach against observations shows its relevance to create reliable air pollution concentration fields at a higher resolution, starting from a coarse resolution modelling results

Sensitivity of air quality model responses to emission changes: comparison of results based on four EU inventories through FAIRMODE benchmarking methodology.

<p>Source code to "Sensitivity of air quality indicators to emission inventories (EDGAR, EMEP-GNFR, CAMS-REG) in Europe through FAIRMODE benchmarking methodology."</p&gt

Why is the city's responsibility for its air pollution often underestimated? A focus on PM2.5

While the burden caused by air pollution in urban areas is well documented, the origin of this pollution and therefore the responsibility of the urban areas in generating this pollution are still a subject of scientific discussion. Source apportionment represents a useful technique to quantify the city's responsibility, but the approaches and applications are not harmonized and therefore not comparable, resulting in confusing and sometimes contradicting interpretations. In this work, we analyse how different source apportionment approaches apply to the urban scale and how their building elements and parameters are defined and set. We discuss in particular the options available in terms of indicator, receptor, source, and methodology. We show that different choices for these options lead to very large differences in terms of outcome. For the 150 large EU cities selected in our study, different choices made for the indicator, the receptor, and the source each lead to an average difference of a factor of 2 in terms of city contribution. We also show that temporal- and spatial-averaging processes applied to the air quality indicator, especially when diverging source apportionments are aggregated into a single number, lead to the favouring of strategies that target background sources while occulting actions that would be efficient in the city centre. We stress that methodological choices and assumptions most often lead to a systematic and important underestimation of the city's responsibility, with important implications. Indeed, if cities are seen as a minor actor, plans will target the background as a priority at the expense of potentially effective local actions

The Sensitivity of Aerosol in Europe to two Different Emission Inventories and Temporal Distribution of Emissions

The sensitivity to two different emission inventories, injection altitude and temporal variations of anthropogenic emissions in aerosol modelling is studied, using the two way nested global transport chemistry model TM5 focussing on Europe in June and December 2000. The simulations of gas and aerosol concentrations and aerosol optical depth (AOD) with the EMEP and AEROCOM emission inventories are compared with EMEP gas and aerosol surface based measurements, AERONET sun photometers retrievals and MODIS satellite data. For the aerosol precursor gasses NOx and SO2 in both months the model results calculated with the EMEP inventory agree better with the EMEP measurements than the simulation with the AEROCOM inventory. In June, with the AEROCOM inventory, SO2 and NOx concentrations are overestimated by a factor of 2.4 and 1.9, respectively. In contrast, the EMEP inventory only slightly overestimates the measured concentrations with a factor 1.3 for both SO2 and NOx. Besides the differences in total emissions between the two inventories, an important role is also played by the vertical distribution of SO2 and NOx emissions in understanding the differences between the EMEP and AEROCOM inventories. In December NOx and SO2 from both simulations agree within 50 % with observations. In June SO4= evaluated with the EMEP emission inventory agrees slightly better with surface observations than the AEROCOM simulation, whereas in December the use of both inventories results in an underestimate of SO4 with a factor 2. Nitrate aerosol measured in summer is not reliable, however in December nitrate aerosol calculations with the EMEP and AEROCOM agree with 30%, and 60 %, respectively with the filter measurements. Differences are caused by the total emissions and the temporal distribution of the aerosol precursor gasses NOx and NH3. Despite these differences, we show that the column integrated AOD is less sensitive to the underlying emission inventories. Calculated AOD values with both emission inventories underestimate the observed AERONET AOD values by 20 - 30%, whereas a case study using MODIS data shows a high spatial agreement. Our evaluation of the role of temporal distribution of anthropogenic emissions on aerosol calculations shows that the daily and weekly temporal distributions of the emissions are only important for NOx, NH3 and aerosol nitrate. For the aerosols species SO4=, NH4+, POM, BC, as well as for AOD, the weekly and daily temporal variation appear not to be important. However, the seasonal temporal variations used in the emission inventory are important for all species under consideration. Our study shows the value of including at least seasonal information on anthropogenic emissions, although from a comparison with a range of measurements it is often difficult to firmly identify the superiority of specific emission inventories, since other modelling uncertainties, e.g. related to transport, aerosol removal, water uptake, and model resolution, play a dominant role.JRC.H.4-Transport and air qualit

Caudal lumbar spinal cysts in two French Bulldogs

BACKGROUND: Spinal cysts are rare findings in veterinary medicine, but they are increasingly recognized due to the availability of advanced imaging techniques. Extradural meningeal cysts in French Bulldogs have not been reported previously and arachnoid cysts (diverticula) have not been reported at the caudal lumbar (L6-L7) region in dogs. CASE PRESENTATION: Two French Bulldogs, aged 5 and 8 years, were referred for evaluation of lower back pain and bilateral hind limb neurological deficits. Neurologic examination revealed ataxia and postural deficits in both dogs. Magnetic resonance imaging (MRI) showed cauda equina compression due to a cyst-like lesion at the level of L6-L7 in both cases. The dogs underwent dorsal laminectomy and the meningeal cyst was completely removed in one dog and in the other dog the spinal arachnoid diverticula was marsupialized. In Case 1, histopathology of the cysts was performed and MRI was repeated. Both dogs were pain free during follow-up evaluations. CONCLUSIONS: Based on radiological, intra-operative and histopathological findings, the first case was diagnosed as a meningocele connected by a pedicle to the caudal tip of the dural sac forming a dural diverticulum categorized as an extradural spinal cyst type Ib, and Case 2 as a type III intradural arachnoid diverticula. It is concluded that spinal cysts should be included in the differential diagnosis of cauda equina syndrome and lower back pain in French Bulldogs. Results of these cases may be useful for diagnostic and treatment management