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.
We describe a computational technology for studying the effects of the aerosol-radiation interaction and calculating regional estimates of the direct (DRE) and semidirect radiative effects (SDRE) of ...biomass burning (BB) aerosol based on simulations with the CHIMERE chemistry transport model coupled with the WRF meteorological model. The technology was applied to numerical studying the radiative effects of Siberian biomass burning aerosol in the eastern Arctic in the period of July 16–31, 2016. The model simulations show that Siberian smokes, on the whole, had a significant cooling effect on the atmosphere in the eastern Arctic in that period due to the DRE, the value of which at top of the atmosphere was, on average, −6.0 W m
−2
, being minimal over the snow-ice cover of the ocean (−1.2 W m
−2
). At the same time, the contribution of the Siberian BB aerosol DRE to the radiative balance of the Arctic atmosphere is found to be offset to a certain extent by the SDRE, which is positive (2.0 W m
−2
), on average. The SDRE is formed as a result of the multihour aerosol effect on meteorological processes and plays the most important role over the snow-ice Arctic covers, where it exceeds the DRE in absolute value. It has been shown that the SDRE of Siberian BBA in our numerical experiments is mainly due to scattering (rather than absorption) of radiation by aerosol particles.
The approach of Bayesian Monte Carlo analysis has been used for evaluating model uncertainty in ozone production and its sensitivity to emission changes. This approach has been applied to the ozone ...fields calculated by the CHIMERE regional model in the Ile‐de‐France area during the 1998 and 1999 summer seasons. The AIRPARIF network measurements of urban NO and O3 concentrations and rural O3 over the Ile‐de‐France region have been used for constraining the Monte Carlo simulations. Our results yield the following major conclusions: (1) The simulated formation of O3 plumes are mainly located in southwestern to southeastern directions downwind the Paris area. (2) Uncertainties on simulated ozone concentrations and several derived quantities are evaluated and reduced using the BMC approach; simulated urban and plume ozone concentrations are enhanced through the observational constraint as compared to those obtained from the unconstrained model. (3) The chemical regime over the urban area of Paris and within plumes is clearly VOC sensitive on the average over two summers. This statement is robust with respect to the BMC uncertainty analysis.
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.
An ensemble Kalman filter (EnKF) has been coupled to the CHIMERE chemical transport model in order to assimilate ozone ground-based measurements on a regional scale. The number of ensembles is ...reduced to 20, which allows for future operational use of the system for air quality analysis and forecast. Observation sites of the European ozone monitoring network have been classified using criteria on ozone temporal variability, based on previous work by Flemming et al. (2005). This leads to the choice of specific subsets of suburban, rural and remote sites for data assimilation and for evaluation of the reference run and the assimilation system. For a 10-day experiment during an ozone pollution event over Western Europe, data assimilation allows for a significant improvement in ozone fields: the RMSE is reduced by about a third with respect to the reference run, and the hourly correlation coefficient is increased from 0.75 to 0.87. Several sensitivity tests focus on an a posteriori diagnostic estimation of errors associated with the background estimate and with the spatial representativeness of observations. A strong diurnal cycle of both these errors with an amplitude up to a factor of 2 is made evident. Therefore, the hourly ozone background error and the observation error variances are corrected online in separate assimilation experiments. These adjusted background and observational error variances provide a better uncertainty estimate, as verified by using statistics based on the reduced centered random variable. Over the studied 10-day period the overall EnKF performance over evaluation stations is found relatively unaffected by different formulations of observation and simulation errors, probably due to the large density of observation sites. From these sensitivity tests, an optimal configuration was chosen for an assimilation experiment extended over a three-month summer period. It shows a similarly good performance as the 10-day experiment.
The ozone–NOy photochemistry is explored in contrasting polluted plumes sampled with the Safire ATR 42 research aircraft during three summer field international campaigns in the megacity Paris, the ...North West Mediterranean basin (WMB) and southern West Africa (SWA). Various metrics derived from the photostationary steady state (PSS) and the ozone production efficiency (OPE) are calculated from airborne observations. A new metric, the oxidant production rate normalized to carbon monoxide (PROx), is introduced and quantified as a function of the processing time of the plume. In most of the polluted plumes, it is found that the Leighton ratio (F) characterizing the equilibrium between O3 and NOx is, on average, within the PSS range (1 0.32) or greater. The positive dependence of Ox to NO usually indicates a VOC-sensitive regime inside the plumes with some exceptions. In Paris, under oceanic westerly winds, and during DACCIWA, the plumes show a rural-like chemistry behaviour at moderate NOx levels (NOx-sensitive). Intense and frequent rapid changes in J(NO2), NO and NO2 explain the deviations from the PSS. The OPE for Paris plume suggests that the VOC-sensitive regime extends far beyond the urban plume. The mean ozone production is higher downwind of Paris (30 ppb h1 on average) compared to SWA (20 ppb h-1) and WMB (6 ppb h1). PROx values vary between 0 (no oxidantproduction) and 0.27 ppbOx ppbCO1 h1. The determined uncertainty on the Leighton ratio value could affect the differences in the estimation of the photochemical oxidant production by PO3 and PROx. The emissions of CO along the flight path and the presence of vegetation and high humidity levels might shape the oxidant production depending on the explored environment. While limited in number, PROx values set a benchmark for future photochemical studies to compare with: Paris as representative of an anthropogenic urban plume and WMB as representative of a biogenic continental plume.
The purpose of this article is inverse modeling of emissions at regional scale for photochemical applications. The study is performed for the Ile‐de‐France region over a two summers (1998 and 1999) ...period. This area represents an ideal framework since concentrated anthropogenic emissions in the Paris region frequently lead to the formation of urban plumes. The inversion method is based on Bayesian Monte Carlo analysis applied to a regional‐scale chemistry transport model, CHIMERE. This method consists in performing a large number of successive simulations with the same model but with a distinct set of model input parameters at each time. Then a posteriori weights are attributed to individual Monte Carlo simulations by comparing them with observations from the AIRPARIF network: urban NO and O3 concentrations and rural O3 concentrations around the Paris area. For both NO and O3 measurements, observations used for constraining Monte Carlo simulations are additionally averaged over the time period considered for analysis. The observational constraints strongly reduce the a priori uncertainties in anthropogenic NOx and volatile organic compounds (VOC) emissions: (1) The a posteriori probability density function (pdf) for NOx emissions is not modified in its average, but the standard deviation is decreased to around 20% (40% for the a priori one). (2) VOC emissions are enhanced (+16%) in the a posteriori pdf's with a standard deviation around 30% (40% for the a priori one). Uncertainties in the simulated urban NO, urban O3, and O3 production within the plume are reduced by a factor of 3.2, 2.4, and 1.7, respectively.
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