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O. Perrussel

Bio: O. Perrussel is an academic researcher. The author has contributed to research in topics: Emission inventory & Air pollution. The author has an hindex of 5, co-authored 6 publications receiving 254 citations.

Papers
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Journal ArticleDOI
TL;DR: In this article, atmospheric inversion is used to adjust the daily to monthly budget of fossil fuel CO2 emissions of the Paris urban area from the prior estimates established by the Airparif local air quality agency.
Abstract: . Atmospheric concentration measurements are used to adjust the daily to monthly budget of fossil fuel CO2 emissions of the Paris urban area from the prior estimates established by the Airparif local air quality agency. Five atmospheric monitoring sites are available, including one at the top of the Eiffel Tower. The atmospheric inversion is based on a Bayesian approach, and relies on an atmospheric transport model with a spatial resolution of 2 km with boundary conditions from a global coarse grid transport model. The inversion adjusts prior knowledge about the anthropogenic and biogenic CO2 fluxes from the Airparif inventory and an ecosystem model, respectively, with corrections at a temporal resolution of 6 h, while keeping the spatial distribution from the emission inventory. These corrections are based on assumptions regarding the temporal autocorrelation of prior emissions uncertainties within the daily cycle, and from day to day. The comparison of the measurements against the atmospheric transport simulation driven by the a priori CO2 surface fluxes shows significant differences upwind of the Paris urban area, which suggests a large and uncertain contribution from distant sources and sinks to the CO2 concentration variability. This contribution advocates that the inversion should aim at minimising model–data misfits in upwind–downwind gradients rather than misfits in mole fractions at individual sites. Another conclusion of the direct model–measurement comparison is that the CO2 variability at the top of the Eiffel Tower is large and poorly represented by the model for most wind speeds and directions. The model's inability to reproduce the CO2 variability at the heart of the city makes such measurements ill-suited for the inversion. This and the need to constrain the budgets for the whole city suggests the assimilation of upwind–downwind mole fraction gradients between sites at the edge of the urban area only. The inversion significantly improves the agreement between measured and modelled concentration gradients. Realistic emissions are retrieved for two 30-day periods and suggest a significant overestimate by the AirParif inventory. Similar inversions over longer periods are necessary for a proper evaluation of the optimised CO2 emissions against independent data.

160 citations

Journal ArticleDOI
TL;DR: In this paper, measurements of the mole fraction of the CO2 and its isotopes were performed in Paris during the MEGAPOLI winter campaign (January-February 2010) to identify the relative contributions of 77% CO2 from fossil fuel consumption and 23% from biospheric CO2 (CO2 from the use of bio fuels and from human and plant respiration: CO2bio).
Abstract: . Measurements of the mole fraction of the CO2 and its isotopes were performed in Paris during the MEGAPOLI winter campaign (January–February 2010). Radiocarbon (14CO2) measurements were used to identify the relative contributions of 77% CO2 from fossil fuel consumption (CO2ff from liquid and gas combustion) and 23% from biospheric CO2 (CO2 from the use of biofuels and from human and plant respiration: CO2bio). These percentages correspond to average mole fractions of 26.4 ppm and 8.2 ppm for CO2ff and CO2bio, respectively. The 13CO2 analysis indicated that gas and liquid fuel contributed 70% and 30%, respectively, of the CO2 emission from fossil fuel use. Continuous measurements of CO and NOx and the ratios CO/CO2ff and NOx/CO2ff derived from radiocarbon measurements during four days make it possible to estimate the fossil fuel CO2 contribution over the entire campaign. The ratios CO/CO2ff and NOx/CO2ff are functions of air mass origin and exhibited daily ranges of 7.9 to 14.5 ppb ppm−1 and 1.1 to 4.3 ppb ppm−1, respectively. These ratios are consistent with different emission inventories given the uncertainties of the different approaches. By using both tracers to derive the fossil fuel CO2, we observed similar diurnal cycles with two maxima during rush hour traffic.

67 citations

Journal ArticleDOI
TL;DR: In this article, a 10-year model simulation over the greater Paris (France) area at 4 km resolution and anthropogenic emissions from a 1 km resolution bottom-up inventory was used to estimate the sensitivity of modeled ozone and PM2.5 concentrations to different potentially influential factors with a particular interest over the urban areas.
Abstract: . While previous research helped to identify and prioritize the sources of error in air-quality modeling due to anthropogenic emissions and spatial scale effects, our knowledge is limited on how these uncertainties affect climate-forced air-quality assessments. Using as reference a 10-year model simulation over the greater Paris (France) area at 4 km resolution and anthropogenic emissions from a 1 km resolution bottom-up inventory, through several tests we estimate the sensitivity of modeled ozone and PM2.5 concentrations to different potentially influential factors with a particular interest over the urban areas. These factors include the model horizontal and vertical resolution, the meteorological input from a climate model and its resolution, the use of a top-down emission inventory, the resolution of the emissions input and the post-processing coefficients used to derive the temporal, vertical and chemical split of emissions. We show that urban ozone displays moderate sensitivity to the resolution of emissions (~ 8 %), the post-processing method (6.5 %) and the horizontal resolution of the air-quality model (~ 5 %), while annual PM2.5 levels are particularly sensitive to changes in their primary emissions (~ 32 %) and the resolution of the emission inventory (~ 24 %). The air-quality model horizontal and vertical resolution have little effect on model predictions for the specific study domain. In the case of modeled ozone concentrations, the implementation of refined input data results in a consistent decrease (from 2.5 up to 8.3 %), mainly due to inhibition of the titration rate by nitrogen oxides. Such consistency is not observed for PM2.5. In contrast this consistency is not observed for PM2.5. In addition we use the results of these sensitivities to explain and quantify the discrepancy between a coarse (~ 50 km) and a fine (4 km) resolution simulation over the urban area. We show that the ozone bias of the coarse run (+9 ppb) is reduced by ~ 40 % by adopting a higher resolution emission inventory, by 25 % by using a post-processing technique based on the local inventory (same improvement is obtained by increasing model horizontal resolution) and by 10 % by adopting the annual emission totals of the local inventory. The bias of PM2.5 concentrations follows a more complex pattern, with the positive values associated with the coarse run (+3.6 μg m−3), increasing or decreasing depending on the type of the refinement. We conclude that in the case of fine particles, the coarse simulation cannot selectively incorporate local-scale features in order to reduce its error.

36 citations

Journal ArticleDOI
TL;DR: In this paper, the CHIMERE air quality model was used to model ozone and PM 2.5 concentrations over the city of Paris. But the results showed that ozone formation over Paris at the current urban-scale study is driven by volatile organic compound (VOC)-limited chemistry, whereas at the regional-scale ozone formation occurs under NO x -sensitive conditions.
Abstract: Ozone and PM 2.5 concentrations over the city of Paris are modeled with the CHIMERE air-quality model at 4 km × 4 km horizontal resolution for two future emission scenarios. A high-resolution (1 km × 1 km) emission projec-tion until 2020 for the greater Paris region is developed by local experts (AIRPARIF) and is further extended to year 2050 based on regional-scale emission projections devel-oped by the Global Energy Assessment. Model evaluation is performed based on a 10-year control simulation. Ozone is in very good agreement with measurements while PM 2.5 is underestimated by 20 % over the urban area mainly due to a large wet bias in wintertime precipitation. A signifi-cant increase of maximum ozone relative to present-day lev-els over Paris is modeled under the "business-as-usual" sce-nario (+7 ppb) while a more optimistic "mitigation" scenario leads to a moderate ozone decrease (−3.5 ppb) in year 2050. These results are substantially different to previous regional-scale projections where 2050 ozone is found to decrease un-der both future scenarios. A sensitivity analysis showed that this difference is due to the fact that ozone formation over Paris at the current urban-scale study is driven by volatile organic compound (VOC)-limited chemistry, whereas at the regional-scale ozone formation occurs under NO x -sensitive conditions. This explains why the sharp NO x reductions im-plemented in the future scenarios have a different effect on ozone projections at different scales. In rural areas, projec-tions at both scales yield similar results showing that the longer timescale processes of emission transport and ozone formation are less sensitive to model resolution. PM 2.5 con-centrations decrease by 78 % and 89 % under business-as-usual and mitigation scenarios, respectively, compared to the present-day period. The reduction is much more prominent over the urban part of the domain due to the effective reduc-tions of road transport and residential emissions resulting in the smoothing of the large urban increment modeled in the control simulation.

29 citations

Journal ArticleDOI
TL;DR: In this article, an approach based on airborne measurements across the Paris, France, plume was developed in order to evaluate BC and NO x emissions at the scale of a whole agglomeration.
Abstract: 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 NO x 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 NO x emissions, as well as for the BC / NO x emission ratio in TNO-MP. The benefit of the airborne approach is discussed through a comparison with the BC / NO x ratio at a ground site in Paris, which additionally suggests a spatially heterogeneous error in BC emissions over the agglomeration. © Author(s) 2015.

18 citations


Cited by
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01 Jan 1989
TL;DR: In this article, a two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea.
Abstract: Abstract A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea. The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are: Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil componen...

3,813 citations

Journal ArticleDOI
TL;DR: In this article, the authors illustrate some approaches to answering questions about the role of human factors, and the relative role of different natural factors, for six specific extreme weather or climate events of 2011.
Abstract: Attribution of extreme events shortly after their occurrence stretches the current state-of-theart of climate change assessment. To help foster the growth of this science, this article illustrates some approaches to answering questions about the role of human factors, and the relative role of different natural factors, for six specific extreme weather or climate events of 2011. Not every event is linked to climate change. The rainfall associated with the devastating Thailand floods can be explained by climate variability. But long-term warming played a part in the others. While La Nina contributed to the failure of the rains in the Horn of Africa, an increased frequency of such droughts there was linked to warming in the Western Pacific– Indian Ocean warm pool. Europe's record warm temperatures would probably not have been as unusual if the high temperatures had been caused only by the atmospheric flow regime without any long-term warming. Calculating how the odds of a particular extreme event have change...

398 citations

Journal Article
TL;DR: In this paper, the authors investigated the association between hospital admission for cardiovascular disease (CVD) and respiratory disease and the chemical components of PM2.5 in the United States.
Abstract: Background Population-based studies have estimated health risks of short-term exposure to fine particles using mass of PM2.5 (particulate matter ≤ 2.5 μm in aerodynamic diameter) as the indicator. Evidence regarding the toxicity of the chemical components of the PM2.5 mixture is limited. Objective In this study we investigated the association between hospital admission for cardiovascular disease (CVD) and respiratory disease and the chemical components of PM2.5 in the United States. Methods We used a national database comprising daily data for 2000–2006 on emergency hospital admissions for cardiovascular and respiratory outcomes, ambient levels of major PM2.5 chemical components [sulfate, nitrate, silicon, elemental carbon (EC), organic carbon matter (OCM), and sodium and ammonium ions], and weather. Using Bayesian hierarchical statistical models, we estimated the associations between daily levels of PM2.5 components and risk of hospital admissions in 119 U.S. urban communities for 12 million Medicare enrollees (≥ 65 years of age). Results In multiple-pollutant models that adjust for the levels of other pollutants, an interquartile range (IQR) increase in EC was associated with a 0.80% [95% posterior interval (PI), 0.34–1.27%] increase in risk of same-day cardiovascular admissions, and an IQR increase in OCM was associated with a 1.01% (95% PI, 0.04–1.98%) increase in risk of respiratory admissions on the same day. Other components were not associated with cardiovascular or respiratory hospital admissions in multiple-pollutant models. Conclusions Ambient levels of EC and OCM, which are generated primarily from vehicle emissions, diesel, and wood burning, were associated with the largest risks of emergency hospitalization across the major chemical constituents of PM2.5.

394 citations

01 Jan 2010
TL;DR: In this paper, the authors compare the performance of different types of absorption photometers for real-time application and find that the response to absorbing aerosol particles is a function of the total particle load on the filter.
Abstract: Abstract. Absorption photometers for real time application have been available since the 1980s, but the use of filter-based instruments to derive information on aerosol properties (absorption coefficient and black carbon, BC) is still a matter of debate. Several workshops have been conducted to investigate the performance of individual instruments over the intervening years. Two workshops with large sets of aerosol absorption photometers were conducted in 2005 and 2007. The data from these instruments were corrected using existing methods before further analysis. The inter-comparison shows a large variation between the responses to absorbing aerosol particles for different types of instruments. The unit to unit variability between instruments can be up to 30% for Particle Soot Absorption Photometers (PSAPs) and Aethalometers. Multi Angle Absorption Photometers (MAAPs) showed a variability of less than 5%. Reasons for the high variability were identified to be variations in sample flow and spot size. It was observed that different flow rates influence system performance with respect to response to absorption and instrumental noise. Measurements with non absorbing particles showed that the current corrections of a cross sensitivity to particle scattering are not sufficient. Remaining cross sensitivities were found to be a function of the total particle load on the filter. The large variation between the response to absorbing aerosol particles for different types of instruments indicates that current correction functions for absorption photometers are not adequate.

238 citations

Journal ArticleDOI
TL;DR: In this paper, the authors developed the first comprehensive monitoring system of CO2 emissions at high resolution over the city of Indianapolis using a uniquely dense network of surface towers measuring continuously the atmospheric concentrations of greenhouse gases (GHGs).
Abstract: Based on a uniquely dense network of surface towers measuring continuously the atmospheric concentrations of greenhouse gases (GHGs), we developed the first comprehensive monitoring systems of CO2 emissions at high resolution over the city of Indianapolis. The urban inversion evaluated over the 2012-2013 dormant season showed a statistically significant increase of about 20% (from 4.5 to 5.7 MtC ± 0.23 MtC) compared to the Hestia CO2 emission estimate, a state-of-the-art building-level emission product. Spatial structures in prior emission errors, mostly undetermined, appeared to affect the spatial pattern in the inverse solution and the total carbon budget over the entire area by up to 15%, while the inverse solution remains fairly insensitive to the CO2 boundary inflow and to the different prior emissions (i.e., ODIAC). Preceding the surface emission optimization, we improved the atmospheric simulations using a meteorological data assimilation system also informing our Bayesian inversion system through updated observations error variances. Finally, we estimated the uncertainties associated with undetermined parameters using an ensemble of inversions. The total CO2 emissions based on the ensemble mean and quartiles (5.26-5.91 MtC) were statistically different compared to the prior total emissions (4.1 to 4.5 MtC). Considering the relatively small sensitivity to the different parameters, we conclude that atmospheric inversions are potentially able to constrain the carbon budget of the city, assuming sufficient data to measure the inflow of GHG over the city, but additional information on prior emission error structures are required to determine the spatial structures of urban emissions at high resolution.

205 citations