scholarly journals How realistic are air quality hindcasts driven by forcings from climate model simulations?

2012 ◽  
Vol 5 (6) ◽  
pp. 1565-1587 ◽  
Author(s):  
G. Lacressonnière ◽  
V.-H. Peuch ◽  
J. Arteta ◽  
B. Josse ◽  
M. Joly ◽  
...  
Keyword(s):  
Air Quality ◽  
Climate Models ◽  
Climate Model ◽  
Transport Model ◽  
Air Quality Model ◽  
Quality Model ◽  
Future Evolution ◽  
Deposition Velocities ◽  
Set Up ◽  
Horizontal And Vertical Distributions

Abstract. Predicting how European air quality could evolve over the next decades in the context of changing climate requires the use of climate models to produce results that can be averaged in a climatologically and statistically sound manner. This is a very different approach from the one that is generally used for air quality hindcasts for the present period; analysed meteorological fields are used to represent specifically each date and hour. Differences arise both from the fact that a climate model run results in a pure model output, with no influence from observations (which are useful to correct for a range of errors), and that in a "climate" set-up, simulations on a given day, month or even season cannot be related to any specific period of time (but can just be interpreted in a climatological sense). Hence, although an air quality model can be thoroughly validated in a "realistic" set-up using analysed meteorological fields, the question remains of how far its outputs can be interpreted in a "climate" set-up. For this purpose, we focus on Europe and on the current decade using three 5-yr simulations performed with the multiscale chemistry-transport model MOCAGE and use meteorological forcings either from operational meteorological analyses or from climate simulations. We investigate how statistical skill indicators compare in the different simulations, discriminating also the effects of meteorology on atmospheric fields (winds, temperature, humidity, pressure, etc.) and on the dependent emissions and deposition processes (volatile organic compound emissions, deposition velocities, etc.). Our results show in particular how differing boundary layer heights and deposition velocities affect horizontal and vertical distributions of species. When the model is driven by operational analyses, the simulation accurately reproduces the observed values of O3, NOx, SO2 and, with some bias that can be explained by the set-up, PM10. We study how the simulations driven by climate forcings differ, both due to the realism of the forcings (lack of data assimilated and lower resolution) and due to the lack of representation of the actual chronology of events. We conclude that the indicators such as mean bias, mean normalized bias, RMSE and deviation standards can be used to interpret the results with some confidence as well as the health-related indicators such as the number of days of exceedance of regulatory thresholds. These metrics are thus considered to be suitable for the interpretation of simulations of the future evolution of European air quality.

scholarly journals How realistic are air quality hindcasts driven by forcings from climate model simulations?

2012 ◽  
Vol 5 (3) ◽  
pp. 2083-2138
Author(s):  
G. Lacressonnière ◽  
V.-H. Peuch ◽  
J. Arteta ◽  
B. Josse ◽  
M. Joly ◽  
...  
Keyword(s):  
Air Quality ◽  
Climate Models ◽  
Climate Model ◽  
Transport Model ◽  
Air Quality Model ◽  
Quality Model ◽  
Future Evolution ◽  
Deposition Velocities ◽  
Set Up ◽  
Horizontal And Vertical Distributions

Abstract. Predicting how European air quality could evolve over the next decades in the context of changing climate requires the use of climate models to produce results that can be averaged in a climatologically and statistically sound manner. This is a very different approach from the one that is generally used for air quality hindcasts for the present period: analysed meteorological fields are used to represent specifically each date and hour. Differences arise both from the fact that a climate model run is a pure model output, with no influence from observations (which are useful to correct for a range of errors), and that in a "climate" set-up, simulations on a given day, month or even season cannot be related to any specific period of time (but can just be interpreted in a climatological sense). Hence, although an air quality model can be thoroughly validated in a "realistic" set-up using analysed meteorological fields, the question remains of how far its outputs can be interpreted in a "climate" set-up. For this purpose, we focus on Europe and on the current decade using three 6-yr simulations performed with the multiscale chemistry-transport model MOCAGE and use meteorological forcings either from operational meteorological analyses or from climate simulations. We investigate how statistical skill indicators compare in the different simulations, discriminating also the effects of meteorology on atmospheric fields (winds, temperature, humidity, pressure \\ldots) and on the dependent emissions and deposition processes (volatile organic compound emissions, deposition velocities . . .). Our results show in particular how differing boundary layer heights and deposition velocities affect horizontal and vertical distributions of species. When the model is driven by operational analyses, the simulation accurately reproduces the observed values of O3, NOx, SO2 and, with some bias that can be explained by the set-up, PM10. We study how the simulations driven by climate forcings differ, both due to the realism of the forcings (lack of data assimilated and lower resolution) and due to the lack of representation of the actual chronology of events. We conclude that the indicators such as mean bias, mean normalized bias, RMSE and deviation standards can be used to interpret the results with some confidence as well as the health-related indicators such as SOMO35 and the number of days of exceedance of regulatory thresholds. These metrics are thus considered to be suitable for the interpretation of simulations of the future evolution of European air quality.

scholarly journals High Resolution Air Quality Forecasting over Prague within the URBI PRAGENSI Project: Model Performance during the Winter Period and the Effect of Urban Parameterization on PM

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 625 ◽  
Author(s):  
Jana Ďoubalová ◽  
Peter Huszár ◽  
Kryštof Eben ◽  
Nina Benešová ◽  
Michal Belda ◽  
...  
Keyword(s):  
Air Quality ◽  
Model Performance ◽  
Urban Canopy ◽  
Urban Environments ◽  
Winter Period ◽  
Air Quality Model ◽  
Quality Model ◽  
Boundary Layer Height ◽  
Project Model ◽  
Set Up

The overall impact of urban environments on the atmosphere is the result of many different nonlinear processes, and their reproduction requires complex modeling approaches. The parameterization of these processes in the models can have large impacts on the model outputs. In this study, the evaluation of a WRF/Comprehensive Air Quality Model with Extensions (CAMx) forecast modeling system set up for Prague, the Czech Republic, within the project URBI PRAGENSI is presented. To assess the impacts of urban parameterization in WRF, in this case with the BEP+BEM (Building Environment Parameterization linked to Building Energy Model) urban canopy scheme, on Particulate Matter (PM) simulations, a simulation was performed for a winter pollution episode and compared to a non-urbanized run with BULK treatment. The urbanized scheme led to an average increase in temperature at 2 m by 2 ∘ C, a decrease in wind speed by 0.5 m s − 1 , a decrease in relative humidity by 5%, and an increase in planetary boundary layer height by 100 m. Based on the evaluation against observations, the overall model error was reduced. These impacts were propagated to the modeled PM concentrations, reducing them on average by 15–30 μ g m − 3 and 10–15 μ g m − 3 for PM 10 and PM 2.5 , respectively. In general, the urban parameterization led to a larger underestimation of the PM values, but yielded a better representation of the diurnal variations.

scholarly journals A description and evaluation of an air quality model nested within global and regional composition-climate models using MetUM

2017 ◽  
Author(s):  
Lucy S. Neal ◽  
Mohit Dalvi ◽  
Gerd Folberth ◽  
Rachel N. McInnes ◽  
Paul Agnew ◽  
...  
Keyword(s):  
Air Quality ◽  
Spatial Resolution ◽  
Climate Models ◽  
Climate Model ◽  
Air Quality Model ◽  
Nested Models ◽  
Modelling Framework ◽  
Resolution Model ◽  
The Uk ◽  
The Impact

Abstract. There is a clear need for the development of modelling frameworks for both climate change and air quality to help inform policies for addressing these issues. This paper presents an initial attempt to develop a single modelling framework, by introducing a greater degree of consistency in the modelling framework by using a two-step, one-way nested configuration of models, from a global composition-climate model (GCCM) (140 km resolution) to a regional composition-climate model covering Europe (RCCM) (50 km resolution) and finally to a high (12 km) resolution model over the UK (AQUM). The latter model is used to produce routine air quality forecasts for the UK. All three models are based on the Met Office's Unified Model (MetUM). In order to better understand the impact of resolution on the downscaling of projections of future climate and air quality, we have used this nest of models to simulate a five year period using present-day emissions and under present-day climate conditions. We also consider the impact of running the higher resolution model with higher spatial resolution emissions, rather than simply regridding emissions from the RCCM. We present an evaluation of the models compared to in situ air quality observations over the UK, plus a comparison against an independent 1 km resolution gridded dataset, derived from a combination of modelling and observations. We show that using a high resolution model over the UK has some benefits in improving air quality modelling, but that the use of higher spatial resolution emissions is important to capture local variations in concentrations, particularly for primary pollutants such as nitrogen dioxide and sulphur dioxide. For secondary pollutants such as ozone and the secondary component of PM10, the benefits of a higher resolution nested model are more limited and reasons for this are discussed. This study confirms that the resolution of models is not the only factor in determining model performance - consistency between nested models is also important.

scholarly journals The impact of differences in large-scale circulation output from climate models on the regional modeling of ozone and PM

2012 ◽  
Vol 12 (20) ◽  
pp. 9441-9458 ◽  
Author(s):  
A. M. M. Manders ◽  
E. van Meijgaard ◽  
A. C. Mues ◽  
R. Kranenburg ◽  
L. H. van Ulft ◽  
...  
Keyword(s):  
Air Quality ◽  
Climate Models ◽  
Climate Model ◽  
Transport Model ◽  
Global Climate Model ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Climate Simulations ◽  
The Impact

Abstract. Climate change may have an impact on air quality (ozone, particulate matter) due to the strong dependency of air quality on meteorology. The effect is often studied using a global climate model (GCM) to produce meteorological fields that are subsequently used by chemical transport models. However, climate models themselves are subject to large uncertainties and fail to reproduce the present-day climate adequately. The present study illustrates the impact of these uncertainties on air quality. To this end, output from the SRES-A1B constraint transient runs with two GCMs, i.e. ECHAM5 and MIROC-hires, has been dynamically downscaled with the regional climate model RACMO2 and used to force a constant emission run with the chemistry transport model LOTOS-EUROS in a one-way coupled run covering the period 1970–2060. Results from the two climate simulations have been compared with a RACMO2-LOTOS-EUROS (RLE) simulation forced by the ERA-Interim reanalysis for the period 1989–2009. Both RLE_ECHAM and RLE_MIROC showed considerable deviations from RLE_ERA for daily maximum temperature, precipitation and wind speed. Moreover, sign and magnitude of these deviations depended on the region. The differences in average present-day concentrations between the simulations were equal to (RLE_MIROC) or even larger than (RLE_ECHAM) the differences in concentrations between present-day and future climate (2041–2060). The climate simulations agreed on a future increase in average summer ozone daily maximum concentrations of 5–10 μg m−3 in parts of Southern Europe and a smaller increase in Western and Central Europe. Annual average PM10 concentrations increased 0.5–1.0 μg m−3 in North-West Europe and the Po Valley, but these numbers are rather uncertain: overall, changes for PM10 were small, both positive and negative changes were found, and for many locations the two climate runs did not agree on the sign of the change. This illustrates that results from individual climate runs can at best indicate tendencies and should therefore be interpreted with great care.

scholarly journals Comparisons of ground-based tropospheric NO<sub>2</sub> MAX-DOAS measurements to satellite observations with the aid of an air quality model over the Thessaloniki area, Greece

2017 ◽  
Vol 17 (9) ◽  
pp. 5829-5849 ◽  
Author(s):  
Theano Drosoglou ◽  
Alkiviadis F. Bais ◽  
Irene Zyrichidou ◽  
Natalia Kouremeti ◽  
Anastasia Poupkou ◽  
...  
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
Optical Absorption Spectroscopy ◽  
Monitoring Site ◽  
Air Quality Model ◽  
Ozone Monitoring Instrument ◽  
Quality Model ◽  
Meteorological Model ◽  
Tropospheric No2 ◽  
Ozone Monitoring

Abstract. One of the main issues arising from the comparison of ground-based and satellite measurements is the difference in spatial representativeness, which for locations with inhomogeneous spatial distribution of pollutants may lead to significant differences between the two data sets. In order to investigate the spatial variability of tropospheric NO2 within a sub-satellite pixel, a campaign which lasted for about 6 months was held in the greater area of Thessaloniki, Greece. Three multi-axial differential optical absorption spectroscopy (MAX-DOAS) systems performed measurements of tropospheric NO2 columns at different sites representative of urban, suburban and rural conditions. The direct comparison of these ground-based measurements with corresponding products from the Ozone Monitoring Instrument onboard NASA's Aura satellite (OMI/Aura) showed good agreement over the rural and suburban areas, while the comparison with the Global Ozone Monitoring Experiment-2 (GOME-2) onboard EUMETSAT's Meteorological Operational satellites' (MetOp-A and MetOp-B) observations is good only over the rural area. GOME-2A and GOME-2B sensors show an average underestimation of tropospheric NO2 over the urban area of about 10.51 ± 8.32  ×  1015 and 10.21 ± 8.87  × 1015 molecules cm−2, respectively. The mean difference between ground-based and OMI observations is significantly lower (6.60 ± 5.71  ×  1015 molecules cm−2). The differences found in the comparisons of MAX-DOAS data with the different satellite sensors can be attributed to the higher spatial resolution of OMI, as well as the different overpass times and NO2 retrieval algorithms of the satellites. OMI data were adjusted using factors calculated by an air quality modeling tool, consisting of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the Comprehensive Air Quality Model with Extensions (CAMx) multiscale photochemical transport model. This approach resulted in significant improvement of the comparisons over the urban monitoring site. The average difference of OMI observations from MAX-DOAS measurements was reduced to −1.68 ± 5.01  ×  1015 molecules cm−2.

scholarly journals Development of prognostic aerosol–cloud interactions combining a chemistry transport model and a regional climate model

2015 ◽  
Vol 8 (2) ◽  
pp. 897-933
Author(s):  
M. A. Thomas ◽  
M. Kahnert ◽  
C. Andersson ◽  
H. Kokkola ◽  
U. Hansson ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Transport Model ◽  
Regional Climate ◽  
Cloud Droplet ◽  
Microphysical Properties ◽  
Aerosol Effect ◽  
Aerosol Cloud Interactions ◽  
Set Up

Abstract. To reduce uncertainties and hence, to obtain a better estimate of aerosol (direct and indirect) radiative forcing, next generation climate models aim for a tighter coupling between chemistry transport models and regional climate models and a better representation of aerosol–cloud interactions. In this study, this coupling is done by first forcing the Rossby Center regional climate model, RCA4 by ERA-Interim lateral boundaries (LBCs) and SST using the standard CDNC (cloud droplet number concentration) formulation (hereafter, referred to as the "stand-alone RCA4 version" or "CTRL" simulation). In this simulation, the CDNCs are assigned fixed numbers based on if the underlying surface is land or oceanic. The meteorology from this simulation is then used to drive the chemistry transport model, MATCH which is coupled online with the aerosol dynamics model, SALSA. CDNC fields obtained from MATCH-SALSA are then fed back into a new RCA4 simulation. In this new simulation (referred to as "MOD" simulation), all parameters remain the same as in the first run except for the CDNCs provided by MATCH-SALSA. Simulations are carried out with this model set up for the period 2005–2012 over Europe and the differences in cloud microphysical properties and radiative fluxes as a result of local CDNC changes and possible model responses are analyzed. Our study shows substantial improvements in the cloud microphysical properties with the input of the MATCH-SALSA derived 3-D CDNCs compared to the stand-alone RCA4 version. This model set up improves the spatial, seasonal and vertical distribution of CDNCs with higher concentration observed over central Europe during summer half of the year and over Eastern Europe and Russia during the winter half of the year. Realistic cloud droplet radii (CD radii) values have been simulated with the maxima reaching 13 μm whereas in the stand-alone version, the values reached only 5 μm. A substantial improvement in the distribution of cloud liquid water path was observed when compared to the satellite retrievals from MODIS for the boreal summer months. The median and SD values from the "MOD" simulation are closer to observations than those obtained using the stand-alone RCA4 version. These changes resulted in a significant decrease in the total annual mean net fluxes at the top of the atmosphere (TOA) by −5 W m−2 over the domain selected in the study. The TOA net fluxes from the "MOD" simulation show a better agreement with the retrievals from CERES instrument. The aerosol indirect effects are evaluated based on 1900 emissions. Our simulations estimated the domain averaged annual mean total radiative forcing of −0.64 W m−2 with larger contribution from the first indirect aerosol effect than from the second indirect aerosol effect.

scholarly journals The impact of differences in large-scale circulation output from climate models on the regional modeling of ozone and PM

2012 ◽  
Vol 12 (5) ◽  
pp. 12245-12285 ◽  
Author(s):  
A. M. M. Manders ◽  
E. van Meijgaard ◽  
A. C. Mues ◽  
R. Kranenburg ◽  
L. H. van Ulft ◽  
...  
Keyword(s):  
Air Quality ◽  
Climate Models ◽  
Climate Model ◽  
Transport Model ◽  
Global Climate Model ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Climate Simulations ◽  
The Impact

Abstract. Climate change may have an impact on air quality (ozone, particulate matter) due to the strong dependency of air quality on meteorology. The effect is often studied using a global climate model (GCM) to produce meteorological fields that are subsequently used by chemical transport models. However, climate models themselves are subject to large uncertainties and fail to adequately reproduce the present-day climate. The present study illustrates the impact of this uncertainty on air quality. To this end, output from the SRES-A1B constraint transient runs with two GCMs, i.e. ECHAM5 and MIROC-hires, has been dynamically downscaled with the regional climate model RACMO2 and used to force a constant emission run with the chemistry transport model LOTOS-EUROS in a one-way coupled run covering the period 1970–2060. Results from the two climate simulations have been compared with a RACMO2-LOTOS-EUROS (RLE) simulation forced by the ERA-Interim reanalysis for the period 1989–2009. Both RLE_ECHAM and RLE_MIROC showed considerable deviations from RLE_ERA in daily maximum temperature, precipitation and wind speed. Moreover, sign and magnitude of these deviations depended on the region. Differences in average concentrations for the present-day simulations were found of equal to (RLE_MIROC) or even larger than (RLE_ECHAM) the differences in concentration between present-day and future climate (2041–2060). The climate simulations agreed on a future increase in average summer ozone daily maximum concentrations (5–10 μg m−3) in parts of Southern Europe and a smaller increase in Western and Central Europe. Annual average PM10 concentrations increased (0.5–1.0 μg m−3) in North-West Europe and the Po Valley, but these numbers are rather uncertain. Overall, changes for PM10 were small, both positive and negative changes were found, and for many locations the two runs did not agree on the sign of the change. The approach taken here illustrates that results from individual climate runs can at best indicate tendencies and should therefore be interpreted with great care.

scholarly journals Estimating NH<sub>3</sub> emissions from agricultural fertilizer application in China using the bi-directional CMAQ model coupled to an agro-ecosystem model

2015 ◽  
Vol 15 (12) ◽  
pp. 6637-6649 ◽  
Author(s):  
X. Fu ◽  
S. X. Wang ◽  
L. M. Ran ◽  
J. E. Pleim ◽  
E. Cooter ◽  
...  
Keyword(s):  
Air Quality ◽  
Temporal Resolution ◽  
Climate Model ◽  
Ecosystem Model ◽  
Fertilizer Application ◽  
Emission Rates ◽  
Air Quality Model ◽  
Quality Model ◽  
Cropland Area ◽  
Agricultural Fertilizer

Abstract. Atmospheric ammonia (NH3) plays an important role in atmospheric aerosol chemistry. China is one of the largest NH3 emitting countries with the majority of NH3 emissions coming from agricultural practices, such as fertilizer application and livestock production. The current NH3 emission estimates in China are mainly based on pre-defined emission factors that lack temporal or spatial details, which are needed to accurately predict NH3 emissions. This study provides the first online estimate of NH3 emissions from agricultural fertilizer application in China, using an agricultural fertilizer modeling system which couples a regional air quality model (the Community Multi-scale Air Quality model, or CMAQ) and an agro-ecosystem model (the Environmental Policy Integrated Climate model, or EPIC). This method improves the spatial and temporal resolution of NH3 emissions from this sector. We combined the cropland area data of 14 crops from 2710 counties with the Moderate Resolution Imaging Spectroradiometer (MODIS) land use data to determine the crop distribution. The fertilizer application rates and methods for different crops were collected at provincial or agricultural region levels. The EPIC outputs of daily fertilizer application and soil characteristics were input into the CMAQ model and the hourly NH3 emissions were calculated online with CMAQ running. The estimated agricultural fertilizer NH3 emissions in this study were approximately 3 Tg in 2011. The regions with the highest modeled emission rates are located in the North China Plain. Seasonally, peak ammonia emissions occur from April to July. Compared with previous researches, this study considers an increased number of influencing factors, such as meteorological fields, soil and fertilizer application, and provides improved NH3 emissions with higher spatial and temporal resolution.

scholarly journals Comparisons of ground-based tropospheric NO<sub>2</sub> MAX-DOAS measurements to satellite observations with the aid of an air quality model over Thessaloniki area, Greece

2016 ◽  
Author(s):  
Theano Drosoglou ◽  
Alkiviadis F. Bais ◽  
Irene Zyrichidou ◽  
Natalia Kouremeti ◽  
Anastasia Poupkou ◽  
...  
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
Monitoring Site ◽  
Air Quality Model ◽  
Quality Model ◽  
Meteorological Model ◽  
Multi Scale ◽  
Tropospheric No2 ◽  
Urban Monitoring ◽  
The Difference

Abstract. The main issue arising from the comparison of ground-based and satellite measurements is the difference in spatial representativeness, which for locations with inhomogeneous spatial distribution of pollutants may lead to significant differences between the two datasets. In order to investigate the spatial variability of tropospheric NO2 within a sub-satellite pixel, a campaign which was lasted for about six months was held at the greater area of Thessaloniki, Greece. Three DOAS/MAX-DOAS systems performed measurements of tropospheric NO2 columns at different sites representative of urban, sub-urban and rural conditions. The direct comparison of these ground-based measurements with corresponding OMI/Aura and GOME-2/MetOp-A and GOME2/MetOp-B products showed good agreement only over the rural area. GOME2A and GOME2B sensors show an average underestimation of tropospheric NO2 over the urban area of about 9.12 ± 7.33 × 1015 and 9.58 ± 8.21 × 1015 molecules cm−2, respectively. The mean difference between ground-based and OMI observations is significantly lower (6.03 ± 6.04 × 1015 molecules cm−2), mainly due to the higher spatial resolution of OMI. OMI data were adjusted using factors calculated by an air quality modelling tool, consisting of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the Comprehensive Air Quality Model with Extensions (CAMx) multi-scale photochemical transport model. This approach resulted to significant improvement of the comparisons over the urban monitoring site. The average negative difference of OMI observations from Phaethon measurements was reduced to 1.15 ± 6.32 × 1015 molecules cm−2.

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