18 research outputs found

    Air quality in the mid-21st century for the city of Paris under two climate scenarios; from the regional to local scale

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    Ozone and PM<sub>2.5</sub> 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 projection 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 developed 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<sub>2.5</sub> is underestimated by 20% over the urban area mainly due to a large wet bias in wintertime precipitation. A significant increase of maximum ozone relative to present-day levels over Paris is modeled under the "business-as-usual" scenario (+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 under 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<sub>x</sub>-sensitive conditions. This explains why the sharp NO<sub>x</sub> reductions implemented in the future scenarios have a different effect on ozone projections at different scales. In rural areas, projections 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<sub>2.5</sub> concentrations 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 reductions of road transport and residential emissions resulting in the smoothing of the large urban increment modeled in the control simulation

    Can we use atmospheric CO<sub>2</sub> measurements to verify emission trends reported by cities? Lessons from a 6-year atmospheric inversion over Paris

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    Existing CO2 emissions reported by city inventories usually lag in real-time by a year or more and are prone to large uncertainties. This study responds to the growing need for timely and precise estimation of urban CO2 emissions to support present and future mitigation measures and policies. We focus on the Paris metropolitan area, the largest urban region in the European Union and the city with the densest atmospheric CO2 observation network in Europe. We performed long-term atmospheric inversions to quantify the citywide CO2 emissions, i.e., fossil fuel as well as biogenic sources and sinks, over 6 years (2016–2021) using a Bayesian inverse modeling system. Our inversion framework benefits from a novel near-real-time hourly fossil fuel CO2 emission inventory (Origins.earth) at 1 km spatial resolution. In addition to the mid-afternoon observations, we attempt to assimilate morning CO2 concentrations based on the ability of the Weather Research and Forecasting model with Chemistry (WRF-Chem) transport model to simulate atmospheric boundary layer dynamics constrained by observed layer heights. Our results show a long-term decreasing trend of around 2 % ± 0.6 % per year in annual CO2 emissions over the Paris region. The impact of the COVID-19 pandemic led to a 13 % ± 1 % reduction in annual fossil fuel CO2 emissions in 2020 with respect to 2019. Subsequently, annual emissions increased by 5.2 % ± 14.2 % from 32.6 ± 2.2 Mt CO2 in 2020 to 34.3 ± 2.3 Mt CO2 in 2021. Based on a combination of up-to-date inventories, high-resolution atmospheric modeling and high-precision observations, our current capacity can deliver near-real-time CO2 emission estimates at the city scale in less than a month, and the results agree within 10 % with independent estimates from multiple city-scale inventories.</p

    Climate-forced air-quality modeling at the urban scale: sensitivity to model resolution, emissions and meteorology

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    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 ÎŒg m&minus;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

    Spatial and temporal variability of BTEX in Paris megacity: Two-wheelers as a major driver

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    Besides their impacts on health, BTEX play an important role in the formation of secondary organic aerosols and ozone for which limit values are regularly exceeded in Paris megacity and Ile de France region. An enrichment by a factor of 3 in the C7C9 aromatic fraction in the Paris atmosphere compared to other northern mid-latitude cities was shown in 2013. Here, we combined different approaches to investigate the role of transport-related sources in such enrichment (gasoline composition and vehicle fleet composition): a statistical analysis of a large BTEX dataset including multi-year and multi-site measurements (traffic, background, tunnel) and a coupled experimental and modelling analysis of liquid and headspace composition of representative fuels distributed in Ile de France region (SP95, SP95 E10, and SP98). For the latter the experimental set-up was designed to analyze the composition of 87 VOCs from C2 to C17 in both liquid and headspace phases. The model is able to predict the headspace composition at ± 15% and with an R2 > 0.9. First a strong positive spatial gradient in BTEX composition at traffic stations is observed, with higher TEX-to-benzene ratio in Paris center compared to the suburbs and outskirts up to a factor of 2. This gradient reflects differences in fleet composition especially gasoline powered vehicles in Paris with a larger proportion of two-wheelers (15% in 2012). This gradient is also consistent with the inter-annual increase of TEX-to-benzene ratios along with the doubling of two-wheelers use and the decrease in the number of passenger cars. The gasoline evaporation model cannot solely explain the observed spatial variability. Finally, we investigated the potential contribution of two-wheelers to the aromatic enrichment in IdF region by introducing an additional unburned gasoline term to the model. The results support the suggestion that two-wheelers are a potential contributor to this enrichment. Considering the high use of two-wheelers in other European cities such as London or Barcelona if Europe is to decrease transport-related air pollution and inner city traffic, policy makers should consider finding alternatives to the conventionally-powered two-wheelers and supporting electric two-wheelers for example. Keywords: Urban air quality, Megacity, VOC, BTEX, Fuel composition, Two-wheelers, Emission ratio

    An attempt at estimating Paris area CO<sub>2</sub> emissions from atmospheric concentration measurements

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    International audienceAtmospheric concentration measurements are used to adjust the daily to monthly budget of fossil fuel CO 2 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 CO 2 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 CO 2 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 CO 2 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 CO 2 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 CO 2 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 CO 2 emissions against independent data

    CO, NOx and 13CO2 as tracers for fossil fuel CO2: results from a pilot study in Paris during winter 2010

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    International audienceMeasurements 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
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