scholarly journals Air quality modelling in the Berlin-Brandenburg region using WRF-Chem v3.7.1: sensitivity to resolution of model grid and input data

2016 ◽  
Author(s):  
Friderike Kuik ◽  
Axel Lauer ◽  
Galina Churkina ◽  
Hugo A. C. Denier van der Gon ◽  
Daniel Fenner ◽  
...  
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Input Data ◽  
Mixing Layer ◽  
Urban Canopy ◽  
Horizontal Resolution ◽  
Level Of Detail ◽  
Input Parameters ◽  
Mixing Layer Height ◽  
Canopy Model

Abstract. Air pollution is the number one environmental cause of premature deaths in Europe. Despite extensive regulations, air pollution remains a challenge, especially in urban areas. For studying summertime air quality in the Berlin-Brandenburg region of Germany, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) is set up and evaluated against meteorological and air quality observations from monitoring stations as well as from a field campaign conducted in 2014. The objective is to assess which resolution and level of detail in the input data is needed for simulating urban background air pollutant concentrations and their spatial distribution in the Berlin-Brandenburg area. The model setup includes three nested domains with horizontal resolutions of 15 km, 3 km, and 1 km and anthropogenic emissions from the TNO-MACC III inventory. We use RADM2 chemistry and the MADE/SORGAM aerosol scheme. Three sensitivity simulations are conducted updating input parameters to the single-layer urban canopy model based on structural data for Berlin, specifying land use classes on a sub-grid scale (mosaic option) and downscaling the original emissions to a resolution of ca. 1 km × 1 km for Berlin based on proxy data including traffic density and population density. The results show that the model simulates meteorology well, though urban 2 m temperature and urban wind speeds are biased high and nighttime mixing layer height is biased low in the base run. We show that the simulation of urban meteorology can be improved when specifying the input parameters to the urban model, and to a lesser extent when using the mosaic option. On average, ozone is simulated reasonably well, but maximum daily eight hour mean concentrations are underestimated, which is consistent with the results from previous modelling studies using the RADM2 chemical mechanism. Particulate matter is underestimated, which is partly due to an underestimation of secondary organic aerosols. NOx (= NO + NO2) concentrations are simulated reasonably well on average, but nighttime concentrations are overestimated due to the model's underestimation of the mixing layer height, and urban daytime concentrations are underestimated. The daytime underestimation is improved when using downscaled, and thus locally higher emissions, suggesting that part of this bias is due to deficiencies in the emission input data and their resolution. The results further demonstrate that a horizontal resolution of 3 km improves the results and spatial representativeness of the model compared to a horizontal resolution of 15 km. With the input data (land use classes, emissions) at the level of detail of the base run of this study we find that a horizontal resolution of 1 km does not improve the results compared to a resolution of 3 km. However, our results suggest that a 1 km horizontal model resolution could enable a detailed simulation of local pollution patterns in the Berlin-Brandenburg region if the urban land use classes together with the respective input parameters to the urban canopy model are specified with a higher level of detail and if urban emissions of higher spatial resolution are used.

scholarly journals Air quality modelling in the Berlin–Brandenburg region using WRF-Chem v3.7.1: sensitivity to resolution of model grid and input data

2016 ◽  
Vol 9 (12) ◽  
pp. 4339-4363 ◽  
Author(s):  
Friderike Kuik ◽  
Axel Lauer ◽  
Galina Churkina ◽  
Hugo A. C. Denier van der Gon ◽  
Daniel Fenner ◽  
...  
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Input Data ◽  
Mixing Layer ◽  
Urban Canopy ◽  
Horizontal Resolution ◽  
Level Of Detail ◽  
Input Parameters ◽  
Mixing Layer Height ◽  
Canopy Model

Abstract. Air pollution is the number one environmental cause of premature deaths in Europe. Despite extensive regulations, air pollution remains a challenge, especially in urban areas. For studying summertime air quality in the Berlin–Brandenburg region of Germany, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) is set up and evaluated against meteorological and air quality observations from monitoring stations as well as from a field campaign conducted in 2014. The objective is to assess which resolution and level of detail in the input data is needed for simulating urban background air pollutant concentrations and their spatial distribution in the Berlin–Brandenburg area. The model setup includes three nested domains with horizontal resolutions of 15, 3 and 1 km and anthropogenic emissions from the TNO-MACC III inventory. We use RADM2 chemistry and the MADE/SORGAM aerosol scheme. Three sensitivity simulations are conducted updating input parameters to the single-layer urban canopy model based on structural data for Berlin, specifying land use classes on a sub-grid scale (mosaic option) and downscaling the original emissions to a resolution of ca. 1 km × 1 km for Berlin based on proxy data including traffic density and population density. The results show that the model simulates meteorology well, though urban 2 m temperature and urban wind speeds are biased high and nighttime mixing layer height is biased low in the base run with the settings described above. We show that the simulation of urban meteorology can be improved when specifying the input parameters to the urban model, and to a lesser extent when using the mosaic option. On average, ozone is simulated reasonably well, but maximum daily 8 h mean concentrations are underestimated, which is consistent with the results from previous modelling studies using the RADM2 chemical mechanism. Particulate matter is underestimated, which is partly due to an underestimation of secondary organic aerosols. NOx (NO + NO2) concentrations are simulated reasonably well on average, but nighttime concentrations are overestimated due to the model's underestimation of the mixing layer height, and urban daytime concentrations are underestimated. The daytime underestimation is improved when using downscaled, and thus locally higher emissions, suggesting that part of this bias is due to deficiencies in the emission input data and their resolution. The results further demonstrate that a horizontal resolution of 3 km improves the results and spatial representativeness of the model compared to a horizontal resolution of 15 km. With the input data (land use classes, emissions) at the level of detail of the base run of this study, we find that a horizontal resolution of 1 km does not improve the results compared to a resolution of 3 km. However, our results suggest that a 1 km horizontal model resolution could enable a detailed simulation of local pollution patterns in the Berlin–Brandenburg region if the urban land use classes, together with the respective input parameters to the urban canopy model, are specified with a higher level of detail and if urban emissions of higher spatial resolution are used.

Application of continuous remote sensing of mixing layer height for assessment of airport air quality

2010 ◽  
Author(s):  
Klaus Schäfer ◽  
Costas Helmis ◽  
Stefan Emeis ◽  
George Sgouros ◽  
Ralf Kurtenbach ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Air Quality ◽  
Mixing Layer ◽  
Layer Height ◽  
Mixing Layer Height

scholarly journals Impact of Physics Parameterizations on High-Resolution Air Quality Simulations over the Paris Region

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 618 ◽  
Author(s):  
Lei Jiang ◽  
Bertrand Bessagnet ◽  
Frederik Meleux ◽  
Frederic Tognet ◽  
Florian Couvidat
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Urban Canopy ◽  
Urban Region ◽  
Pollution Episode ◽  
Sensitivity Tests ◽  
Physics Parameterizations ◽  
Paris Region ◽  
The Impact ◽  
Canopy Model

The accurate simulation of meteorological conditions, especially within the planetary boundary layer (PBL), is of major importance for air quality modeling. In the present work, we have used the Weather Research and Forecast (WRF) model coupled with the chemistry transport model (CTM) CHIMERE to understand the impact of physics parameterizations on air quality simulation during a short-term pollution episode on the Paris region. A lower first model layer with a 4 m surface layer could better reproduce the transport and diffusion of pollutants in a real urban environment. Three canopy models could better reproduce a 2 m temperature (T2) in the daytime but present a positive bias from 1 to 5 °C during the nighttime; the multi-urban canopy scheme “building effect parameterization” (BEP) underestimates the 10 m windspeed (W10) around 1.2 m s−1 for the whole episode, indicating the city cluster plays an important role in the diffusion rate in urban areas. For the simulation of pollutant concentrations, large differences were found between three canopy schemes, but with an overall overestimation during the pollution episode, especially for NO2 simulation, the average mean biases of NO2 prediction during the pollution episode were 40.9, 62.2, and 29.7 µg m−3 for the Bulk, urban canopy model (UCM), and BEP schemes, respectively. Meanwhile, the vertical profile of the diffusion coefficients and pollutants indicated an important impact of the canopy model on the vertical diffusion. The PBL scheme sensitivity tests displayed an underestimation of the height of the PBL when compared with observations issued from the Lidar. The YonSei University scheme YSU and Boulac PBL schemes improved the PBL prediction compared with the Mellor–Yamada–Janjic (MYJ) scheme. All the sensitivity tests, except the Boulac–BEP, could not fairly reproduce the PBL height during the pollution episode. The Boulac–BEP scheme had significantly better performances than the other schemes for the simulation of both the PBL height and pollutants, especially for the NO2 and PM2.5 (particulate matter 2.5 micrometers or less in diameter) simulations. The mean bias of the NO2, PM2.5, and PM10 (particulate matter 10 micrometers or less in diameter) prediction were −5.1, 1.2, and −8.6 µg m−3, respectively, indicating that both the canopy schemes and PBL schemes have a critical effect on air quality prediction in the urban region.

Impact of mixing layer height on air quality in winter

2020 ◽  
Vol 197 ◽  
pp. 105157 ◽  
Author(s):  
B.S. Murthy ◽  
R. Latha ◽  
Arpit Tiwari ◽  
Aditi Rathod ◽  
Siddhartha Singh ◽  
...  
Keyword(s):  
Air Quality ◽  
Mixing Layer ◽  
Layer Height ◽  
Mixing Layer Height

scholarly journals Evaluation of improved land use and canopy representation in BEIS v3.61 with biogenic VOC measurements in California

2015 ◽  
Vol 8 (9) ◽  
pp. 8117-8154 ◽  
Author(s):  
J. O. Bash ◽  
K. R. Baker ◽  
M. R. Beaver
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Air Quality Model ◽  
Quality Model ◽  
Biogenic Emission ◽  
Considerable Uncertainty ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Regulatory Model ◽  
Vegetation Species ◽  
Canopy Model

Abstract. Biogenic volatile organic compounds (BVOC) participate in reactions that can lead to secondarily formed ozone and particulate matter (PM) impacting air quality and climate. BVOC emissions are important inputs to chemical transport models applied on local to global scales but considerable uncertainty remains in the representation of canopy parameterizations and emission algorithms from different vegetation species. The Biogenic Emission Inventory System (BEIS) has been used to support both scientific and regulatory model assessments for ozone and PM. Here we describe a new version of BEIS which includes updated input vegetation data and canopy model formulation for estimating leaf temperature and vegetation data on estimated BVOC. The Biogenic Emission Landuse Database (BELD) was revised to incorporate land use data from the Moderate Resolution Imaging Spectroradiometer (MODIS) land product and 2006 National Land Cover Database (NLCD) land coverage. Vegetation species data is based on the US Forest Service (USFS) Forest Inventory and Analysis (FIA) version 5.1 for years from 2002 to 2013 and US Department of Agriculture (USDA) 2007 census of agriculture data. This update results in generally higher BVOC emissions throughout California compared with the previous version of BEIS. Baseline and updated BVOC emissions estimates are used in Community Multiscale Air Quality Model (CMAQ) simulations with 4 km grid resolution and evaluated with measurements of isoprene and monoterpenes taken during multiple field campaigns in northern California. The updated canopy model coupled with improved land use and vegetation representation resulted in better agreement between CMAQ isoprene and monoterpene estimates compared with these observations.

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