scholarly journals Validation of the Swiss methane emission inventory by atmospheric observations and inverse modelling

2016 ◽  
Vol 16 (6) ◽  
pp. 3683-3710 ◽  
Author(s):  
Stephan Henne ◽  
Dominik Brunner ◽  
Brian Oney ◽  
Markus Leuenberger ◽  
Werner Eugster ◽  
...  
Keyword(s):  
Natural Gas ◽  
Greenhouse Gas ◽  
Urban Areas ◽  
Large Scale ◽  
Transport Model ◽  
Regional Scale ◽  
Inverse Modelling ◽  
Gas Distribution ◽  
Bottom Up ◽  
Ch4 Emissions

Abstract. Atmospheric inverse modelling has the potential to provide observation-based estimates of greenhouse gas emissions at the country scale, thereby allowing for an independent validation of national emission inventories. Here, we present a regional-scale inverse modelling study to quantify the emissions of methane (CH4) from Switzerland, making use of the newly established CarboCount-CH measurement network and a high-resolution Lagrangian transport model. In our reference inversion, prior emissions were taken from the "bottom-up" Swiss Greenhouse Gas Inventory (SGHGI) as published by the Swiss Federal Office for the Environment in 2014 for the year 2012. Overall we estimate national CH4 emissions to be 196 ± 18 Gg yr−1 for the year 2013 (1σ uncertainty). This result is in close agreement with the recently revised SGHGI estimate of 206 ± 33 Gg yr−1 as reported in 2015 for the year 2012. Results from sensitivity inversions using alternative prior emissions, uncertainty covariance settings, large-scale background mole fractions, two different inverse algorithms (Bayesian and extended Kalman filter), and two different transport models confirm the robustness and independent character of our estimate. According to the latest SGHGI estimate the main CH4 source categories in Switzerland are agriculture (78 %), waste handling (15 %) and natural gas distribution and combustion (6 %). The spatial distribution and seasonal variability of our posterior emissions suggest an overestimation of agricultural CH4 emissions by 10 to 20 % in the most recent SGHGI, which is likely due to an overestimation of emissions from manure handling. Urban areas do not appear as emission hotspots in our posterior results, suggesting that leakages from natural gas distribution are only a minor source of CH4 in Switzerland. This is consistent with rather low emissions of 8.4 Gg yr−1 reported by the SGHGI but inconsistent with the much higher value of 32 Gg yr−1 implied by the EDGARv4.2 inventory for this sector. Increased CH4 emissions (up to 30 % compared to the prior) were deduced for the north-eastern parts of Switzerland. This feature was common to most sensitivity inversions, which is a strong indicator that it is a real feature and not an artefact of the transport model and the inversion system. However, it was not possible to assign an unambiguous source process to the region. The observations of the CarboCount-CH network provided invaluable and independent information for the validation of the national bottom-up inventory. Similar systems need to be sustained to provide independent monitoring of future climate agreements.

scholarly journals Validation of the Swiss methane emission inventory by atmospheric observations and inverse modelling

2015 ◽  
Vol 15 (24) ◽  
pp. 35417-35484
Author(s):  
S. Henne ◽  
D. Brunner ◽  
B. Oney ◽  
M. Leuenberger ◽  
W. Eugster ◽  
...  
Keyword(s):  
Natural Gas ◽  
Greenhouse Gas ◽  
Urban Areas ◽  
Transport Model ◽  
Regional Scale ◽  
Inverse Modelling ◽  
Bottom Up ◽  
Climate Agreements ◽  
Ch4 Emissions ◽  
The North

Abstract. Atmospheric inverse modelling has the potential to provide observation-based estimates of greenhouse gas emissions at the country scale, thereby allowing for an independent validation of national emission inventories. Here, we present a regional scale inverse modelling study to quantify the emissions of methane (CH4) from Switzerland, making use of the newly established CarboCount-CH measurement network and a high resolution Lagrangian transport model. Overall we estimate national CH4 emissions to be 196 ± 18 Gg yr−1 for the year 2013 (1σ uncertainty). This result is in close agreement with the recently revised "bottom-up" estimate of 206 ± 33 Gg yr−1 published by the Swiss Federal Office for the Environment as part of the Swiss Greenhouse Gas Inventory (SGHGI). Results from sensitivity inversions using alternative prior emissions, covariance settings, baseline treatments, two different inverse algorithms (Bayesian and extended Kalman Filter), and two different transport models confirms the robustness and independent character of our estimate. According to the latest "bottom-up" inventory the main CH4 source categories in Switzerland are agriculture (78 %), waste handling (15 %) and natural gas distribution and combustion (6 %). The spatial distribution and seasonal variability of our posterior emissions suggest an overestimation of agricultural CH4 emissions by 10 to 20 % in the most recent national inventory, which is likely due to an overestimation of emissions from manure handling. Urban areas do not appear as emission hotspots in our posterior results suggesting that leakages from natural gas disribution are only a minor source of CH4 in Switzerland. This is consistent with rather low emissions of 8.4 Gg yr−1 reported by the SGHGI but inconsistent with the much higher value of 32 Gg yr−1 implied by the EDGARv4.2 inventory for this sector. Increased CH4 emissions (up to 30 % compared to the prior) were deduced for the north-eastern parts of Switzerland. This feature was common to most sensitivity inversions, which rules out an artefact of the transport model and the inversion system. However, it was not possible to assign an unambiguous source process to the region. The observations of the CarboCount-CH network provided invaluable and independent information for the validation of the national bottom-up inventory. Similar systems need to be sustained to provide independent monitoring of future climate agreements.

scholarly journals Assessing Urban Methane Emissions using Column Observing Portable FTIR Spectrometers and a Novel Bayesian Inversion Framework

2021 ◽  
Author(s):  
Taylor S. Jones ◽  
Jonathan E. Franklin ◽  
Jia Chen ◽  
Florian Dietrich ◽  
Kristian D. Hajny ◽  
...  
Keyword(s):  
Natural Gas ◽  
Urban Areas ◽  
Transport Model ◽  
Methane Emissions ◽  
Surface Fluxes ◽  
Bayesian Inversion ◽  
Inversion Method ◽  
Bottom Up ◽  
The City ◽  
Total Column

Abstract. Cities represent a large and concentrated portion of global greenhouse gas emissions, including methane. Quantifying methane emissions from urban areas is difficult, and inventories made using bottom-up accounting methods often differ greatly from top-down estimates generated from atmospheric observations. Emissions from leaks in natural gas infrastructure are difficult to predict, and are therefore poorly constrained in bottom-up inventories. Natural gas infrastructure leaks and emissions from end uses can be spread throughout the city, and this diffuse source can represent a significant fraction of a city's total emissions. We investigated diffuse methane emissions of the city of Indianapolis, USA during a field campaign in May of 2016. A network of five portable solar-tracking Fourier transform infrared (FTIR) spectrometers was deployed throughout the city. These instruments measure the mole fraction of methane in a total column of air, giving them sensitivity to larger areas of the city than in situ sensors at the surface. We present an innovative inversion method to link these total column concentrations to surface fluxes. This method combines a Lagrangian transport model with a Bayesian inversion framework to estimate surface emissions and their uncertainties, together with determining the concentrations of methane in the air flowing into the city. Variations exceeding 10 ppb were observed in the inflowing air on a typical day, somewhat larger than the enhancements due to urban emissions (

Coupling bottom-up process modeling to atmospheric inversions to constrain the Siberian methane budget

2020 ◽  
Author(s):  
Mathias Goeckede ◽  
Philipp de Vrese ◽  
Victor Brovkin ◽  
Frank-Thomas Koch ◽  
Christian Roedenbeck
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Global Climate ◽  
Regional Scale ◽  
Atmospheric Methane ◽  
Max Planck ◽  
Bottom Up ◽  
High Northern Latitude ◽  
Ch4 Emissions ◽  
The Impact

<p>Methane (CH4) is one of the most important greenhouse gases, but unexpected changes in atmospheric CH4 budgets over the past decades emphasize that many aspects regarding the role of this gas in the global climate system remain unexplained to date. With emissions and concentrations likely to continue increasing in the future, quantitative and qualitative insights into processes governing CH4 sources and sinks need to be improved in order to better predict feedbacks with a changing climate. Particularly the high northern latitudes have been identified as a potential future hotspot for global CH4 emissions, but the effective impact of rapid climate change on the mobilization of the enormous carbon reservoir currently stored in northern soils remains unclear.</p><p> </p><p>Process-based modelling frameworks are the most promising tool for predicting CH4 emission trajectories under future climate scenarios. In order to improve the insights into CH4 emissions and their controls, the land-surface component of the Max Planck Earth System model, JSBACH, has been upgraded in recent years. In this context, a particular focus has been placed on refining important processes in permafrost landscapes, including freeze-thaw processes, high-resolution vertical gradients in transport and transformation of carbon in soils, and a dynamic coupling between carbon, water and energy cycles. Evaluating the performance of this model, however, remains a challenge because of the limited observational database for high Northern latitude regions.</p><p> </p><p>In the presented study, we couple methane flux fields simulated by JSBACH to an atmospheric inversion scheme to evaluate model performance within the Siberian domain. Optimization of the surface-atmosphere exchange processes against an atmospheric methane mixing-ratio database will allow to identify the large-scale representativeness of JSBACH simulations, including its spatio-temporal variability in the chosen domain. We will test the impact of selected model parameter settings on the agreement between bottom-up and top-down techniques, therefore highlighting how sensitive regional scale methane budgets are to dominant processes and controls within this region.</p>

THE ROLE OF GAS IN ENVIRONMENTAL CONTROL

1973 ◽  
Vol 13 (1) ◽  
pp. 125
Author(s):  
Hanns F. Hartmann
Keyword(s):  
Air Pollution ◽  
Los Angeles ◽  
Natural Gas ◽  
Pollution Control ◽  
Urban Areas ◽  
Large Scale ◽  
Fossil Fuels ◽  
Environmental Control ◽  
Air Pollution Control ◽  
Oxides Of Nitrogen

The gases comprising the atmosphere are in dynamic balance both with the oceans and the dry land of the continents. The mechanisms which operate to keep the atmospheric content of oxygen, nitrogen, carbon and sulphur constant are now well defined. The capacity of the system to absorb excess gaseous impurities is adequate on a global basis with the exception of carbon dioxide.Air pollution is thus a local problem resulting from the overloading of a particular air space with contaminants. The greater part of air pollution is due to the combustion of fossil fuels. Ease of control and virtual freedom from sulphur give natural gas an advantage over liquid and solid fuels as far as air pollution control is concerned. Oxides of nitrogen are produced when natural gas is burned but in smaller quantities than in the combustion of other fuels. In high capacity industrial gas burners where oxides of nitrogen may be generated in large quantities control is easier and can achieve a lower level of oxides of nitrogen than is the case with other fuels.The large scale use of natural gas to solve the air pollution problems of Pittsburgh, Los Angeles and many other cities is proof of the usefulness of gas in this respect. Specialised applications include use in incinerators and industrial after burners. Advances in removal of impurities from fuels and of air pollutants from products of combustion combined with rising gas prices will in time displace gas from its preeminent position in air pollution control. It is, however, likely to retain its advantage in small installations and in dense urban areas. In public and private transport its use will probably remain limited.While technological developments in the distant future may eventually displace fossil fuels, gas will have a large share of the fuel market until that day comes and will contribute effectively to the control of air pollution.

scholarly journals The Canadian atmospheric transport model for simulating greenhouse gas evolution on regional scales: GEM-MACH-GHG v.137-reg

2019 ◽  
Author(s):  
Jinwoong Kim ◽  
Saroja Polavarapu ◽  
Douglas Chan ◽  
Michael Neish
Keyword(s):  
Greenhouse Gas ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Forecast Error ◽  
Regional Scale ◽  
The United States ◽  
Regional Model ◽  
Boreal Summer ◽  
Chemical Transport Model ◽  
Atmospheric Transport Model

Abstract. In this study, we present the development of a regional atmospheric transport model for greenhouse gas (GHG) simulation based on an operational weather forecast model and a chemical transport model at Environment and Climate Change Canada (ECCC), with the goal of improving our understanding of the high spatio-temporal resolution interaction between the atmosphere and surface GHG fluxes over Canada and the United States. The regional model uses 10 km × 10 km horizontal grid spacing and 80 vertical levels spanning the ground to 0.1 hPa. The lateral boundary conditions of meteorology and tracers are provided by the global transport model used for GHG simulation at ECCC. The performance of the regional model and added benefit of the regional model over our lower resolution global models is investigated in terms of modelled CO2 concentration and meteorological forecast quality for multiple seasons in 2015. We find that our regional model has the capability to simulate high spatial (horizontal and vertical) and temporal scales of atmospheric CO2 concentrations, based on comparisons to surface and aircraft observations. In addition, reduced bias and standard deviation of forecast error in boreal summer are obtained by the regional model. Better representation of model topography in the regional model reduces transport and representation errors significantly compared to the global model, especially in regions of complex topography, as revealed by the more precise and detailed structure of the CO2 diurnal cycle produced at observation sites and in model space. The new regional model will form the basis of a flux inversion system that estimates regional scale fluxes of GHGs over Canada.

scholarly journals The Canadian atmospheric transport model for simulating greenhouse gas evolution on regional scales: GEM–MACH–GHG v.137-reg

2020 ◽  
Vol 13 (1) ◽  
pp. 269-295
Author(s):  
Jinwoong Kim ◽  
Saroja M. Polavarapu ◽  
Douglas Chan ◽  
Michael Neish
Keyword(s):  
Greenhouse Gas ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Forecast Error ◽  
Regional Scale ◽  
The United States ◽  
Regional Model ◽  
Boreal Summer ◽  
Spatiotemporal Resolution ◽  
Atmospheric Transport Model

Abstract. In this study, we present the development of a regional atmospheric transport model for greenhouse gas (GHG) simulation based on an operational weather forecast model and a chemical transport model at Environment and Climate Change Canada (ECCC), with the goal of improving our understanding of the high-spatiotemporal-resolution interaction between the atmosphere and surface GHG fluxes over Canada and the United States. The regional model uses 10 km×10 km horizontal grid spacing and 80 vertical levels spanning the ground to 0.1 hPa. The lateral boundary conditions of meteorology and tracers are provided by the global transport model used for GHG simulation at ECCC. The performance of the regional model and added benefit of the regional model over our lower-resolution global models is investigated in terms of modelled CO2 concentration and meteorological forecast quality for multiple seasons in 2015. We find that our regional model has the capability to simulate the high spatial (horizontal and vertical) and temporal scales of atmospheric CO2 concentrations based on comparisons to surface and aircraft observations. In addition, the bias and standard deviation of forecast error in boreal summer are reduced by the regional model. Better representation of model topography in the regional model results in improved simulation of the CO2 diurnal cycle compared to the global model at Walnut Grove, California. The new regional model will form the basis of a flux inversion system that estimates regional-scale fluxes of GHGs over Canada.

Methane Estimates in the Northeastern US using Continuous Measurements from a Regional Tower Network

2020 ◽  
Author(s):  
Kimberly Mueller ◽  
Subhomoy Ghosh ◽  
Anna Karion ◽  
Sharon Gourdji ◽  
Israel Lopez-Coto ◽  
...  
Keyword(s):  
Natural Gas ◽  
Urban Areas ◽  
The United States ◽  
Ch4 Emission ◽  
Urban Centers ◽  
Ch4 Emissions ◽  
The Us ◽  
Spatio Temporal ◽  
Northeast Us

<p>In the past decade, there has been a scientific focus on improving the accuracy and precision of methane (CH4) emission estimates in the United States, with much effort targeting oil and natural gas producing basins. Yet, regional CH4 emissions and their attribution to specific sources continue to have significant associated uncertainties. Recent urban work using aircraft observations have suggested that CH4 emissions are not well characterized in major cities along the U.S. East Coast; discrepancies have been attributed to an under-estimation of fugitive emissions from the distribution of natural gas. However, much of regional and urban research has involved the use of aircraft campaigns that can only provide a spatio-temporal snapshot of the CH4 emission landscape. As such, the annual representation and the seasonal variability of emissions remain largely unknown. To further investigate CH4 emissions, we present preliminary CH4 emissions estimates in the Northeastern US as part of NIST’s Northeast Corridor (NEC) testbed project using a regional inversion framework. This area encompasses over 20% of the US and contains many of the dominant CH4 emissions sources important at both regional and local scales.  The atmospheric inversion can estimate sub-monthly 0.1-degree emissions using observations from a regional network of up to 37 in-situ towers; some towers are in non-urban areas while others are in cities or suburban areas. The inversion uses different emission products to help provide a prior constraint within the inversion including anthropogenic emissions from both the EDGAR v42 for the year 2008 and the US EPA for the year 2012, and natural wetland CH4 emissions from the WetCHARTs ensemble mean for the year 2010. Results include the comparison of synthetic model simulated CH4 concentrations (i.e., convolutions of the emission products with WRF-STILT footprints + background) to mole-fractions measured at the regional in-situ sites. The comparison provides an indication as to how well our prior understanding of emissions and incoming air flow matches the atmospheric signatures due to the underlying CH4 sources.  We also present a preliminary set of CH4 fluxes for a selected number of urban centers and discuss challenges estimating highly-resolved methane emissions using high-frequency in-situ observations for a regional domain (e.g. few constraints, skewness in underlying fluxes, representing incoming background, etc.). Overall, this work provides the basis for a year-long inversion that will yields regional CH4 emissions over the Northeast US with a focus on Eastern urban areas.</p>

The influence of transport model resolution on the inverse modelling of synthetic greenhouse gas emissions in Switzerland

2020 ◽  
Author(s):  
Ioannis Katharopoulos ◽  
Dominique Rust ◽  
Martin Vollmer ◽  
Dominik Brunner ◽  
Stefan Reimann ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Transport Model ◽  
Stratospheric Ozone ◽  
Inverse Modelling ◽  
Model Resolution ◽  
Gas Emissions ◽  
Stratospheric Ozone Layer

<p>Climate change is one of the biggest challenges of the modern era. Halocarbons contribute already about 14% to current anthropogenic radiative forcing, and their future impact may become significantly larger due to their long atmospheric lifetimes and continued and increasing usage. In addition to their influence on climate change, chlorine and bromine-containing halocarbons are the main drivers of the destruction of the stratospheric ozone layer. Therefore, observing their atmospheric abundance and quantifying their sources is critical for predicting the related future impact on climate change and on the recovery of the stratospheric ozone layer.</p><p>Regional scale atmospheric inverse modelling can provide observation-based estimates of greenhouse gas emissions at a country scale and, hence, makes valuable information available to policy makers when reviewing emission mitigation strategies and confirming the countries' pledges for emission reduction. Considering that inverse modelling relies on accurate atmospheric transport modelling any advances to the latter are of key importance. The main objective of this work is to characterize and improve the Lagrangian particle dispersion model (LPDM) FLEXPART-COSMO at kilometer-scale resolution and to provide estimates of Swiss halocarbon emissions by integrating newly available halocarbon observations from the Swiss Plateau at the Beromünster tall tower. The transport model is offline coupled with the regional numerical weather prediction model (NWP) COSMO. Previous inverse modelling results for Swiss greenhouse gases are based on a model resolution of 7 km x 7 km. Here, we utilize higher resolution (1 km x 1 km) operational COSMO analysis fields to drive FLEXPART and compare these to the previous results.</p><p>The higher resolution simulations exhibit increased three-dimensional dispersion, leading to a general underestimation of observed tracer concentration at the receptor location and when compared to the coarse model results. The concentration discrepancies due to dispersion between the two model versions cannot be explained by the parameters utilized in FLEPXART’s turbulence parameterization, (Obhukov length, surface momentum and heat fluxes, atmospheric boundary layer heights, and horizontal and vertical wind speeds), since a direct comparison of these parameters between the different model versions showed no significant differences. The latter suggests that the dispersion differences may originate from a duplication of turbulent transport, on the one hand, covered by the high resolution grid of the Eulerian model and, on the other hand, diagnosed by FLEXPART's turbulence scheme. In an attempt to reconcile FLEXPART-COSMO’s turbulence scheme at high resolution, we introduced additional scaling parameters based on analysis of simulated mole fraction deviations depending on stability regime. In addition, we used FLEXPART-COSMO source sensitivities in a Bayesian inversion to obtain optimized emission estimates. Inversions for both the high and low resolution models were carried out in order to quantify the impact of model resolution on posterior emissions and estimate about the uncertainties of these emissions.  </p>

scholarly journals Clouds, photolysis and regional tropospheric ozone budgets

2009 ◽  
Vol 9 (3) ◽  
pp. 13889-13916 ◽  
Author(s):  
A. Voulgarakis ◽  
O. Wild ◽  
N. H. Savage ◽  
G. D. Carver ◽  
J. A. Pyle
Keyword(s):  
Tropospheric Ozone ◽  
Large Scale ◽  
Transport Model ◽  
Regional Scale ◽  
Three Dimensional ◽  
Global Scale ◽  
Chemical Production ◽  
Chemical Transport Model ◽  
Photolysis Rates ◽  
Boundary Layer Ozone

Abstract. We use a three-dimensional chemical transport model to examine the shortwave radiative effects of clouds on the tropospheric ozone budget. In addition to looking at changes in global concentrations as previous studies have done, we examine changes in ozone chemical production and loss caused by clouds and how these vary in different parts of the troposphere. On a global scale, we find that clouds have a modest effect on ozone chemistry, but on a regional scale their role is much more significant, with the size of the response dependent on the region. The largest averaged changes in chemical budgets (±10–14%) are found in the marine troposphere, where cloud optical depths are high. We demonstrate that cloud effects are small on average in the middle troposphere because this is a transition region between reduction and enhancement in photolysis rates. We show that increases in boundary layer ozone due to clouds are driven by large-scale changes in downward ozone transport from higher in the troposphere rather than by decreases in in-situ ozone chemical loss rates. Increases in upper tropospheric ozone are caused by higher production rates due to backscattering of radiation and consequent increases in photolysis rates, mainly J(NO2). The global radiative effect of clouds on isoprene is stronger than on ozone. Tropospheric isoprene lifetime increases by 7% when taking clouds into account. We compare the importance of clouds in contributing to uncertainties in the global ozone budget with the role of other radiatively-important factors. The budget is most sensitive to the overhead ozone column, while surface albedo and clouds have smaller effects. However, uncertainty in representing the spatial distribution of clouds may lead to a large sensitivity on regional scales.

scholarly journals Mid-21st century air quality at the urban scale under the influence of changed climate and emissions: case studies for Paris and Stockholm

2015 ◽  
Vol 15 (19) ◽  
pp. 27041-27085
Author(s):  
K. Markakis ◽  
M. Valari ◽  
M. Engardt ◽  
G. Lacressonnière ◽  
R. Vautard ◽  
...  
Keyword(s):  
Climate Change ◽  
Urban Areas ◽  
Large Scale ◽  
Regional Scale ◽  
Influential Factor ◽  
Daily Average ◽  
Pollutant Concentrations ◽  
Emission Projections ◽  
The Impact ◽  
The City

Abstract. Ozone, PM10 and PM2.5 concentrations over Paris, France and Stockholm, Sweden were modeled at 4 and 1 \\unit{km} horizontal resolutions respectively for the present and 2050 periods employing decade-long simulations. We account for large-scale global climate change (RCP-4.5) and fine resolution bottom-up emission projections developed by local experts and quantify their impact on future pollutant concentrations. Moreover, we identify biases related to the implementation of regional scale emission projections over the study areas by comparing modeled pollutant concentrations between the fine and coarse scale simulations. We show that over urban areas with major regional contribution (e.g., the city of Stockholm) the bias due to coarse emission inventory may be significant and lead to policy misclassification. Our results stress the need to better understand the mechanism of bias propagation across the modeling scales in order to design more successful local-scale strategies. We find that the impact of climate change is spatially homogeneous in both regions, implying strong regional influence. The climate benefit for ozone (daily average and maximum) is up to −5 % for Paris and −2 % for Stockholm city. The joined climate benefit on PM2.5 and PM10 in Paris is between −10 and −5 % while for Stockholm we observe mixed trends up to 3 % depending on season and size class. In Stockholm, emission mitigation leads to concentration reductions up to 15 % for daily average and maximum ozone and 20 % for PM and through a sensitivity analysis we show that this response is entirely due to changes in emissions at the regional scale. On the contrary, over the city of Paris (VOC-limited photochemical regime), local mitigation of NOx emissions increases future ozone concentrations due to ozone titration inhibition. This competing trend between the respective roles of emission and climate change, results in an increase in 2050 daily average ozone by 2.5 % in Paris. Climate and not emission change appears to be the most influential factor for maximum ozone concentration over the city of Paris, which may be particularly interesting in a health impact perspective.

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