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

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 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_2.5 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_x-sensitive conditions. This explains why the sharp NO_x 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_2.5 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 CO₂ measurements to verify emission trends reported by cities? Lessons from a 6-year atmospheric inversion over Paris

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

Mangrove and saltmarsh surface elevation dynamics in relation to environmental variables in Southeastern Australia|

Research has demonstrated that at many sites in Southeastern Australia, there have been changes in the extent of mangrove and saltmarsh communities over the past five decades. In particular, this has been characterised by encroachment of saltmarsh by mangrove. Changes in the relationship between marsh elevation and water levels, facilitated either by altered tidal regimes, eustatic sea-level rise or marsh subsidence/autocompaction, have been hypothesised as the driver of these community-scale changes. In addition, the evidence for future sea-level rise is compelling and abundant. However, our understanding of marsh sedimentary and elevation dynamics in relation to sea-level and the impacts of sea-level rise on mangrove and saltmarsh in Southeastern Australia is limited. The aim of this study was to examine marsh elevation trajectories in relation to sea-level change, establish the contribution of sedimentation to these changes and determine the vulnerability of mangrove and saltmarsh to submergence from sea-level rise. This research has been carried out over approximately 1 500 km of coastline and at wide range of sites in Southeastern Australia, including the Tweed River, Hunter River, Hawkesbury River, Parramatta River, Minnamurra River, Jervis Bay and Western Port Bay. Photogrammetric mapping of mangrove and saltmarsh extent was compiled for each study site and tidal inundation models were developed to determine the vertical and horizontal change in mangrove and saltmarsh extent since the commencement of aerial photography. A network of Surface Elevation Tables was established to examine marsh elevation trajectories in relation to sea-level changes and determine the environmental variables influencing marsh elevation. Feldspar marker horizons were established in mangrove and saltmarsh to examine contemporary sediment accretion trajectories and determine the contribution of sedimentation to marsh elevation. Sediment cores from saltmarshes in Western Port Bay were 210Pb dated to establish historic sedimentation rates and make comparisons with sea-level changes. To ascertain whether mangrove and saltmarsh distribution changes were related to sea-level rise, sedimentation and/or subsidence, comparisons were made between changes in vegetation extent, sedimentation, marsh elevation changes and sea-level changes. Contemporary rates of sediment accretion varied greatly, but generally agreed with historic rates of sedimentation determined for the past 100 years at Western Port Bay. Inundation frequency, tidal range and geomorphology were all shown to influence sediment accretion at study sites. Surface elevation changes were strongly correlated to El Niño intensity (Southern Oscillation Index) and rainfall. Mean sedimentation contributed to approximately 67% of surface elevation change in saltmarsh settings and 51% in mangrove settings. A consistent relationship between sediment accretion and surface elevation changes was not observed. At most study sites sediment accretion exceeded surface elevation changes due to subsurface processes causing subsidence/autocompaction. The bulk of subsidence was attributed to reduced rainfall in association with the 2002 to 2004 El Niño related drought, which was shown to cause groundwater reserves to be depleted. Surface elevation exceeded sediment accretion in the saltmarsh at three study sites and this was attributed to ponding of surface water causing sediments to swell due to porewater storage increases, and increased primary productivity and associated belowground root development that displaced the marsh surface. Rates of sediment accretion generally kept pace with or exceeded sea-level changes, However, since subsurface processes of subsidence/autocompaction and uplift influenced marsh elevations, it was more appropriate to determine mangrove and saltmarsh vulnerability to sea-level rise on the basis of an elevation deficit, defined as the difference between rates of marsh elevation change and sea-level change over the same study period. Elevation deficits indicated that the vulnerability of mangrove and saltmarsh in Southeastern Australia to submergence was low. Submergence may not be the only possible impact of sea-level rise on mangrove and saltmarsh communities. No relationship was found between mangrove increase and sedimentation or saltmarsh decline and sedimentation. However, a significant relationship was established between rates of surface elevation change in the saltmarsh and rates of mangrove area increase. By determining the vertical gradient over which mangrove had increased extent and relative sea-level rise, which incorporates mangrove surface elevation changes and eustatic sea-level rise, a significant correlation was found between relative sea-level rise and the vertical component of landward mangrove encroachment. Observed changes to mangrove and saltmarsh extent in Southeastern Australia over the past 50 years were attributed to subsidence and sea-level rise. Several sedimentation and surface elevation trends in Southeastern Australia were typical of marshes within the international SET network. Sedimentation was equivalent to surface elevation change at few sites and marsh elevations were typically influenced by subsidence. Mangrove sediment accretion may also be globally predicted on the basis of tide range and long-term sea-level rise at study sites. However, marsh surface dynamics in Southeastern Australia differ from global trends due to the upper intertidal location of saltmarshes, the strong influence of drought on marsh elevations and generally lower rates of sea-level rise. The results of this study have important implications for current estuary management practices. For example, interference with natural sediment movements within estuaries by trapping sediments and associated nutrients upstream may actually reduce sediment availability to mangrove and saltmarsh communities and increase their vulnerability to the impacts of sea-level rise. Also, the finding that groundwater plays an important role in maintaining marsh surface elevation has implications on the management of groundwater resources and the role of climate change on the longterm survival of mangrove and saltmarsh communities

Automated Synthesis of Mechanisms

Mechanism Design aims to design a game so that a desirable outcome is reached regardless of agents' self-interests. In this paper, we show how this problem can be rephrased as a synthesis problem, where mechanisms are automatically synthesized from a partial or complete specification in a high-level logical language. We show that Quantitative Strategy Logic is a perfect candidate for specifying mechanisms as it can express complex strategic and quantitative properties. We solve automated mechanism design in two cases: when the number of actions is bounded, and when agents play in turn

Strategic Reasoning in Automated Mechanism Design

Mechanism Design aims at defining mechanisms that satisfy a predefined set of properties, and Auction Mechanisms are of foremost importance. Core properties of mechanisms, such as strategy-proofness or budget-balance, involve: (i) complex strategic concepts such as Nash equilibria, (ii) quantitative aspects such as utilities, and often (iii) imperfect information, with agents' private valuations. We demonstrate that Strategy Logic provides a formal framework fit to model mechanisms, express such properties, and verify them. To do so, we consider a quantitative and epistemic variant of Strategy Logic. We first show how to express the implementation of social choice functions. Second, we show how fundamental mechanism properties can be expressed as logical formulas, and thus evaluated by model checking. Finally, we prove that model checking for this particular variant of Strategy Logic can be done in polynomial space

Synthesis of Mechanisms with Strategy Logic (Short Paper)

Mechanism Design aims to design a game so that a desirable outcome is reached regardless of agents' self-interests. In this paper, we show how this problem can be rephrased as a synthesis problem, where mechanisms are automatically synthesized from a partial or complete specification in a high-level logical language. We show that Quantitative Strategy Logic is a perfect candidate for specifying mechanisms as it can express complex strategic and quantitative properties

Influence des différences individuelles sur l'utilisation des composantes verbales et spatiales de la mémoire de travail lors de l'encodage d'itinéraires virtuels

International audienceno abstrac

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

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&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

The role of working memory components and visuospatial abilities in route learning within a virtual environment

International audienceno abstrac