Chemistry transport models (CTMs) are an indispensable tool for studying and predicting atmospheric and climate effects associated with carbonaceous aerosol from open biomass burning (BB); this type ...of aerosol is known to contribute significantly to both global radiative forcing and to episodes of air pollution in regions affected by wildfires. Improving model performance requires systematic comparison of simulation results with measurements of BB aerosol and elucidation of possible reasons for discrepancies between them, which, by default, are frequently attributed in the literature to uncertainties in emission data. Based on published laboratory data on the atmospheric evolution of BB aerosol and using the volatility basis set (VBS) framework for organic aerosol modeling, we examined the importance of taking gas-particle partitioning and oxidation of semi-volatile organic compounds (SVOCs) into account in simulations of the mesoscale evolution of smoke plumes from intense wildfires that occurred in western Russia in 2010. Biomass burning emissions of primary aerosol components were constrained with PM10 and CO data from the air pollution monitoring network in the Moscow region. The results of the simulations performed with the CHIMERE CTM were evaluated by considering, in particular, the ratio of smoke-related enhancements in PM10 and CO concentrations (ΔPM10 and ΔCO) measured in Finland (in the city of Kuopio), nearly 1000 km downstream of the fire emission sources. It is found that while the simulations based on a "conventional" approach to BB aerosol modeling (disregarding oxidation of SVOCs and assuming organic aerosol material to be non-volatile) strongly underestimated values of ΔPM10/ΔCO observed in Kuopio (by a factor of 2), employing the "advanced" representation of atmospheric processing of organic aerosol material resulted in bringing the simulations to a much closer agreement with the ground measurements. Furthermore, taking gas-particle partitioning and oxidation of SVOCs into account is found to result in a major improvement of the agreement of simulations and satellite measurements of aerosol optical depth, as well as in considerable changes in predicted aerosol composition and top-down BB aerosol emission estimates derived from AOD measurements.
Simulations with the chemistry transport model CHIMERE are compared to measurements performed during the MEGAPOLI (Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate ...effects, and Integrated tools for assessment and mitigation) summer campaign in the Greater Paris region in July 2009. The volatility-basis-set approach (VBS) is implemented into this model, taking into account the volatility of primary organic aerosol (POA) and the chemical aging of semi-volatile organic species. Organic aerosol is the main focus and is simulated with three different configurations with a modified treatment of POA volatility and modified secondary organic aerosol (SOA) formation schemes. In addition, two types of emission inventories are used as model input in order to test the uncertainty related to the emissions. Predictions of basic meteorological parameters and primary and secondary pollutant concentrations are evaluated, and four pollution regimes are defined according to the air mass origin. Primary pollutants are generally overestimated, while ozone is consistent with observations. Sulfate is generally overestimated, while ammonium and nitrate levels are well simulated with the refined emission data set. As expected, the simulation with non-volatile POA and a single-step SOA formation mechanism largely overestimates POA and underestimates SOA. Simulation of organic aerosol with the VBS approach taking into account the aging of semi-volatile organic compounds (SVOC) shows the best correlation with measurements. High-concentration events observed mostly after long-range transport are well reproduced by the model. Depending on the emission inventory used, simulated POA levels are either reasonable or underestimated, while SOA levels tend to be overestimated. Several uncertainties related to the VBS scheme (POA volatility, SOA yields, the aging parameterization), to emission input data, and to simulated OH levels can be responsible for this behavior. Despite these uncertainties, the implementation of the VBS scheme into the CHIMERE model allowed for much more realistic organic aerosol simulations for Paris during summertime. The advection of SOA from outside Paris is mostly responsible for the highest OA concentration levels. During advection of polluted air masses from northeast (Benelux and Central Europe), simulations indicate high levels of both anthropogenic and biogenic SOA fractions, while biogenic SOA dominates during periods with advection from Southern France and Spain.
Ground‐based and airborne volatile organic compound (VOC) measurements in Los Angeles, California, and Paris, France, during the Research at the Nexus of Air Quality and Climate Change (CalNex) and ...Megacities: Emissions, Urban, Regional and Global Atmospheric Pollution and Climate Effects, and Integrated Tools for Assessment and Mitigation (MEGAPOLI) campaigns, respectively, are used to examine the spatial variability of the composition of anthropogenic VOC urban emissions and to evaluate regional emission inventories. Two independent methods that take into account the effect of chemistry were used to determine the emission ratios of anthropogenic VOCs (including anthropogenic isoprene and oxygenated VOCs) over carbon monoxide (CO) and acetylene. Emission ratios from both methods agree within ±20%, showing the reliability of our approach. Emission ratios for alkenes, alkanes, and benzene are fairly similar between Los Angeles and Paris, whereas the emission ratios for C7–C9 aromatics in Paris are higher than in Los Angeles and other French and European Union urban areas by a factor of 2–3. The results suggest that the emissions of gasoline‐powered vehicles still dominate the hydrocarbon distribution in northern mid‐latitude urban areas, which disagrees with emission inventories. However, regional characteristics like the gasoline composition could affect the composition of hydrocarbon emissions. The observed emission ratios show large discrepancies by a factor of 2–4 (alkanes and oxygenated VOC) with the ones derived from four reference emission databases. A bias in CO emissions was also evident for both megacities. Nevertheless, the difference between measurements and inventory in terms of the overall OH reactivity is, in general, lower than 40%, and the potential to form secondary organic aerosols (SOA) agrees within 30% when considering volatile organic emissions as the main SOA precursors.
Key PointsUrban VOC emission ratios are compared in two modern megacitiesGasoline‐powered vehicles emissions are still the dominant VOC urban sourceObservations/inventory differences are <40% in terms of OH‐reactvity and SOAP
We compare tropospheric column densities (vertically integrated concentrations) of NO2 from three data sets for the metropolitan area of Paris during two extensive measurement campaigns (25 days in ...summer 2009 and 29 days in winter 2010) within the European research project MEGAPOLI. The selected data sets comprise a regional chemical transport model (CHIMERE) as well as two observational data sets: ground-based mobile Multi-AXis-Differential Optical Absorption Spectroscopy (car-MAX-DOAS) measurements and satellite measurements from the Ozone Monitoring Instrument (OMI). On most days, car-MAX-DOAS measurements were carried out along large circles (diameter ∼ 35 km) around Paris. The car-MAX-DOAS results are compared to coincident data from CHIMERE and OMI. All three data sets have their specific strengths and weaknesses, especially with respect to their spatiotemporal resolution and coverage as well as their uncertainties. Thus we compare them in two different ways: first, we simply consider the original data sets. Second, we compare modified versions making synergistic use of the complementary information from different data sets. For example, profile information from the regional model is used to improve the satellite data, observations of the horizontal trace gas distribution are used to adjust the respective spatial patterns of the model simulations, or the model is used as a transfer tool to bridge the spatial scales between car-MAX-DOAS and satellite observations. Using the modified versions of the data sets, the comparison results substantially improve compared to the original versions. In general, good agreement between the data sets is found outside the emission plume, but inside the emission plumes the tropospheric NO2 vertical column densities (VCDs). are systematically underestimated by the CHIMERE model and the satellite observations (compared to the car-MAX-DOAS observations). One major result from our study is that for satellite validation close to strong emission sources (like power plants or megacities), detailed information about the intra-pixel heterogeneity is essential. Such information may be gained from simultaneous car-MAX-DOAS measurements using multiple instruments or by combining (car-) MAX-DOAS measurements with results from regional model simulations.
High uncertainties affect black carbon (BC) emissions, and, despite its important impact on air pollution and climate, very few BC emissions evaluations are found in the literature. This paper ...presents a novel approach, based on airborne measurements across the Paris, France, plume, developed in order to evaluate BC and NOx emissions at the scale of a whole agglomeration. The methodology consists in integrating, for each transect, across the plume observed and simulated concentrations above background. This allows for several error sources (e.g., representativeness, chemistry, plume lateral dispersion) to be minimized in the model used. The procedure is applied with the CHIMERE chemistry-transport model to three inventories - the EMEP inventory and the so-called TNO and TNO-MP inventories - over the month of July 2009. Various systematic uncertainty sources both in the model (e.g., boundary layer height, vertical mixing, deposition) and in observations (e.g., BC nature) are discussed and quantified, notably through sensitivity tests. Large uncertainty values are determined in our results, which limits the usefulness of the method to rather strongly erroneous emission inventories. A statistically significant (but moderate) overestimation is obtained for the TNO BC emissions and the EMEP and TNO-MP NOx emissions, as well as for the BC / NOx emission ratio in TNO-MP. The benefit of the airborne approach is discussed through a comparison with the BC / NOx ratio at a ground site in Paris, which additionally suggests a spatially heterogeneous error in BC emissions over the agglomeration.
Aerosol simulations in chemistry transport models (CTMs) still suffer from numerous uncertainties, and diagnostic evaluations are required to point out major error sources. This paper presents an ...original approach to evaluate CTMs based on local and imported contributions in a large megacity rather than urban background concentrations. The study is applied to the CHIMERE model in the Paris region (France) and considers the fine particulate matter (PM2.5) and its main chemical constituents (elemental and organic carbon, nitrate, sulfate and ammonium), for which daily measurements are available during a whole year at various stations (PARTICULES project). Back-trajectory data are used to locate the upwind station, from which the concentration is identified as the import, the local production being deduced from the urban concentration by subtraction. Uncertainties on these contributions are quantified. Small biases in urban background PM2.5 simulations (bias of +16%) hide significant error compensations between local and advected contributions, as well as in PM2.5 chemical compounds. In particular, winter time organic matter (OM) imports appear strongly underestimated while local OM and elemental carbon (EC) production is overestimated all along the year. Erroneous continental wood burning emissions and missing secondary organic aerosol (SOA) pathways may explain errors on advected OM, while the carbonaceous compounds is likely to be related to errors in emissions and dynamics. A statistically significant local formation of nitrate is also highlighted from observations, but missed by the model. Together with the overestimation of nitrate imports, it leads to a bias of +51% on the local PM2.5 contribution. Such an evaluation finally gives more detailed insights on major gaps in current CTMs on which future efforts are needed.
The spread of the new coronavirus SARS-CoV-2 that causes COVID-19 forced the Spanish Government to implement extensive lockdown measures to reduce the number of hospital admissions, starting on 14 ...March 2020. Over the following days and weeks, strong reductions in nitrogen dioxide (NO2) pollution were reported in many regions of Spain. A substantial part of these reductions was obviously due to decreased local and regional anthropogenic emissions. Yet, the confounding effect of meteorological variability hinders a reliable quantification of the lockdown's impact upon the observed pollution levels. Our study uses machine-learning (ML) models fed by meteorological data along with other time features to estimate the “business-as-usual” NO2 mixing ratios that would have been observed in the absence of the lockdown. We then quantify the so-called meteorology-normalized NO2 reductions induced by the lockdown measures by comparing the estimated business-as-usual values with the observed NO2 mixing ratios. We applied this analysis for a selection of urban background and traffic stations covering the more than 50 Spanish provinces and islands.The ML predictive models were found to perform remarkably well in most locations, with an overall bias, root mean square error and correlation of +4 %, 29 % and 0.86, respectively. During the period of study, from the enforcement of the state of alarm in Spain on 14 March to 23 April, we found the lockdown measures to be responsible for a 50 % reduction in NO2 levels on average over all provinces and islands. The lockdown in Spain has gone through several phases with different levels of severity with respect to mobility restrictions. As expected, the meteorology-normalized change in NO2 was found to be stronger during phase II (the most stringent phase) and phase III of the lockdown than during phase I. In the largest agglomerations, where both urban background and traffic stations were available, a stronger meteorology-normalized NO2 change is highlighted at traffic stations compared with urban background sites. Our results are consistent with foreseen (although still uncertain) changes in anthropogenic emissions induced by the lockdown. We also show the importance of taking the meteorological variability into account for accurately assessing the impact of the lockdown on NO2 levels, in particular at fine spatial and temporal scales.Meteorology-normalized estimates such as those presented here are crucial to reliably quantify the health implications of the lockdown due to reduced air pollution.
We quantify the reductions in primary emissions due to the COVID-19 lockdowns in Europe. Our estimates are provided in the form of a dataset of reduction factors varying per country and day that will ...allow the modelling and identification of the associated impacts upon air quality. The country- and daily-resolved reduction factors are provided for each of the following source categories: energy industry (power plants), manufacturing industry, road traffic and aviation (landing and take-off cycle). We computed the reduction factors based on open-access and near-real-time measured activity data from a wide range of information sources. We also trained a machine
learning model with meteorological data to derive weather-normalized electricity consumption reductions. The time period covered is from 21 February, when the first European localized lockdown was implemented in the region of Lombardy (Italy), until 26 April 2020. This period includes 5 weeks (23 March until 26 April) with the most severe and relatively unchanged restrictions upon mobility and socio-economic activities across Europe. The computed reduction factors were combined with the Copernicus Atmosphere Monitoring Service's European emission inventory using adjusted temporal emission profiles in order to derive time-resolved emission reductions per country and pollutant sector. During the most severe lockdown period, we estimate the average emission reductions to be −33 % for NOx, −8 % for non-methane volatile organic compounds (NMVOCs), −7 % for SOx and −7 % for PM2.5 at the EU-30 level (EU-28 plus Norway and Switzerland). For all pollutants more than 85 % of the total reduction
is attributable to road transport, except SOx. The reductions reached −50 % (NOx), −14 % (NMVOCs), −12 % (SOx) and −15 % (PM2.5) in countries where the lockdown restrictions were more severe such as Italy, France or Spain. To show the potential for air quality modelling, we simulated and evaluated NO2 concentration decreases in rural and urban background regions across Europe (Italy, Spain, France, Germany, United-Kingdom and Sweden). We found the lockdown measures to be responsible for NO2 reductions of up to −58 % at urban background locations (Madrid, Spain) and −44 % at rural background areas (France), with an average contribution of the traffic sector to total reductions of 86 % and 93 %, respectively. A clear improvement of the modelled results was found when considering the emission reduction factors, especially in Madrid, Paris and London where the bias is reduced by more than 90 %. Future updates will include the extension of the COVID-19 lockdown period covered, the addition of other
pollutant sectors potentially affected by the restrictions (commercial and residential combustion and shipping) and the evaluation of other air quality pollutants such as O3 and PM2.5. All the emission reduction factors are provided in the Supplement.
In the framework of the In Service Aircraft for Global Observing System (IAGOS) program, airborne in-situ O3 and CO measurements are performed routinely using in-service aircraft, providing vertical ...profiles from the surface to about 10–12 km. Due to the specificity of IAGOS measurements (measurements around busy international airports), uncertainties exist on their representativeness in the lower troposphere as they may be impacted by emissions related to airport activities and/or other aircraft. In this study, we thus investigate how the IAGOS measurements in the lower troposphere compare with nearby surface stations (from the local Air Quality monitoring network (AQN)) and more distant regional surface stations (from the Global Atmospheric Watch (GAW) network). The study focuses on Frankfurt but some results at other European airports (Vienna, Paris) are also discussed.
Results indicate that the IAGOS observations close to the surface do not appear to be strongly impacted by local emissions related to airport activities. In terms of mixing ratio distribution, seasonal variations and trends, the CO and O3 mixing ratios measured by IAGOS in the first few hundred metres above the surface have similar characteristics to the mixing ratios measured at surrounding urban background stations. Higher in altitude, both the difference with data from the local AQN and the consistency with the GAW regional stations are higher, which indicates a larger representativeness of the IAGOS data. Despite few quantitative differences with Frankfurt, consistent results are obtained in the two other cities Vienna and Paris.
Based on 11 years of data (2002–2012), this study thus demonstrates that IAGOS observations in the lowest troposphere can be used as a complement to surface stations to study the air quality in/around the agglomeration, providing important information on the vertical distribution of pollution.
Abstract
Ozone is generally assumed to have weak diurnal variations in the free troposphere due to lower production rates than in the boundary layer, in addition to a much lower NO titration and the ...absence of dry deposition at the surface. However, this hypothesis has not been proven due to a lack of high frequency observations at multiple times per day. For the first time, we take benefit from the frequent O3 vertical profiles measured above Frankfurt in the framework of the MOZAIC-IAGOS program to investigate the diurnal variations of O3 mixing ratios at multiple pressure levels throughout the troposphere. With about 21,000 aircraft profiles between 1994 and 2012 (98 per month on average), distributed throughout the day, this is the only dataset that can allow such a study. As expected, strong diurnal variations are observed close to the surface, in particular during spring and summer (enhanced photochemistry and surface deposition). Higher in altitude, our observations show a decrease of the diurnal cycle, with no diurnal cycle discernible above 750 hPa, whatever the season. Similar results are observed for the different percentiles of the O3 distribution (5th, 25th, 50th, 75th, 95th). An insight of the changes of the diurnal cycles between 1994–2003 and 2004–2012 is also given. We found higher O3 mixing ratios during the latter period, particularly on the lowest pressure levels, despite lower mixing ratios during summer.
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