Impact of different urban canopy models on air quality simulation in Chengdu, southwestern China

2021 ◽  
Vol 267 ◽  
pp. 118775
Author(s):  
Haofan Wang ◽  
Zhihong Liu ◽  
Yang Zhang ◽  
Zhengyang Yu ◽  
Chunrong Chen
2018 ◽  
Vol 635 ◽  
pp. 576-585 ◽  
Author(s):  
Tingting Liao ◽  
Ke Gui ◽  
Wanting Jiang ◽  
Shigong Wang ◽  
Bihan Wang ◽  
...  

2020 ◽  
Author(s):  
Thomas Schwitalla ◽  
Hans-Stefan Bauer ◽  
Kirsten Warrach-Sagi ◽  
Thomas Bönisch ◽  
Volker Wulfmeyer

Abstract. Air pollution is one of the major challenges in urban areas. It can have a major impact on human health and society and is currently a subject of several litigations at European courts. Information on the level of air pollution is based on near surface measurements, which are often irregularly distributed along the main traffic roads and provide almost no information about the residential areas and office districts in the cities. To further enhance the process understanding and give scientific support to decision makers, we developed a prototype for an air quality forecasting system (AQFS) within the EU demonstration project Open Forecast. For AQFS, the Weather Research and Forecasting model together with its coupled chemistry component (WRF-Chem) is applied for the Stuttgart metropolitan area in Germany. Three model domains from 1.25 km down to a turbulence permitting resolution of 50 m were used and a single layer urban canopy model was active in all domains. As demonstration case study the 21 January 2019 was selected which was a heavy polluted day with observed PM10 concentrations exceeding 50 µg m−3. Our results show that the model is capable to reasonably simulate the diurnal cycle of surface fluxes and 2-m temperatures as well as evolution of the stable and shallow boundary layer typically occurring in wintertime in Stuttgart. The simulated fields of particulates with a diameter of less than 10 µm (PM10) and Nitrogen dioxide (NO2) allow a clear statement about the most heavily polluted areas apart from the irregularly distributed measurement sites. Together with information about the vertical distribution of PM10 and NO2 from the model, AQFS will serve as a valuable tool for air quality forecast and has the potential of being applied to other cities around the world.


Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 625 ◽  
Author(s):  
Jana Ďoubalová ◽  
Peter Huszár ◽  
Kryštof Eben ◽  
Nina Benešová ◽  
Michal Belda ◽  
...  

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.


2016 ◽  
Vol 9 (12) ◽  
pp. 4339-4363 ◽  
Author(s):  
Friderike Kuik ◽  
Axel Lauer ◽  
Galina Churkina ◽  
Hugo A. C. Denier van der Gon ◽  
Daniel Fenner ◽  
...  

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.


2020 ◽  
Author(s):  
Vivien Voss ◽  
K. Heinke Schlünzen ◽  
David Grawe

<p>Air pollution is an important topic within urban areas.  Limit values as given in the European Guidelines are introduced to reduce negative effects on humans and vegetation.  Exceedances of the limit values are to be assessed using measurements.  In case of found exceedances of the limit values, the local authorities need to act to reduce pollution levels. Highest values are found for several pollutants (NOx, NO2, particles) within densely build-up urban areas with traffic emissions being the major source and dispersion being very much impacted by the urban structures.  The quality assured measuring network used by the authorities is often too coarse to determine the heterogeneity in the concentration field. Low cost sample devices as employed in several citizen science projects might help to overcome the data sparsity. Volunteers measure the air quality at many sites, contribute to the measurement networks and provide the data on the web. However, the questions arising are: a) Are these data of sufficient high quality to provide results comparable to those of the quality assured networks? b) Is the network density sufficient to determine concentration patterns within the urban canopy layer? <br>One-year data from a citizen science network, which measures particulate matter (PM10, PM2.5) were compared to measurements provided by the local environmental agency, using two hot-spot areas in the city of Hamburg as an example. To determine how well the measurements agree with each other, a regression analyses was performed dependent on seasonal and diurnal cycles. Additionally, model simulations with the microscale obstacle resolving model MITRAS were performed for two characteristic building structures and different meteorological situations. The model results were used to determine local hot spots as well as areas where measurements might represent the concentration of particles for the urban quarter. The low cost sensor measurements show a general agreement to the city’s measurements, however, the values per sensor differ. Moreover, the measurements of the low-cost-sensor show an unrealistic dependence on relative humidity, resulting in over- or underestimations in certain cases. The model results clearly show that only a few sites allow measurements to be representative for a city quarter. The measurements of the citizen science project can provide a good overview about the tendencies of the air quality, but are currently not of sufficient quality to provide measurements calling for legal action.</p><p>The model results were used for the project AtMoDat. AtMoDat is an attempt to create a data standard for obstacle resolving models based on the existing Climate and Forecast (CF) conventions. A web-based survey is developed to get information on the requirements for the data standard. The next step is to extend the collection of model characteristics and eventually to provide a generic scheme.</p><p><strong>Acknowledgements</strong><br>This work contributes to project “AtMoDat” funded by the Federal Ministry of Education and Research under the funding number 16QK02C. Responsibility for the content of this publication lies with the authors.</p>


2021 ◽  
Vol 21 (6) ◽  
pp. 4575-4597
Author(s):  
Thomas Schwitalla ◽  
Hans-Stefan Bauer ◽  
Kirsten Warrach-Sagi ◽  
Thomas Bönisch ◽  
Volker Wulfmeyer

Abstract. Air pollution is one of the major challenges in urban areas. It can have a major impact on human health and society and is currently a subject of several litigations in European courts. Information on the level of air pollution is based on near-surface measurements, which are often irregularly distributed along the main traffic roads and provide almost no information about the residential areas and office districts in the cities. To further enhance the process understanding and give scientific support to decision makers, we developed a prototype for an air quality forecasting system (AQFS) within the EU demonstration project “Open Forecast”. For AQFS, the Weather Research and Forecasting model together with its coupled chemistry component (WRF-Chem) is applied for the Stuttgart metropolitan area in Germany. Three model domains from 1.25 km down to a turbulence-permitting resolution of 50 m were used, and a single-layer urban canopy model was active in all domains. As a demonstration case study, 21 January 2019 was selected, which was a heavily polluted day with observed PM10 concentrations exceeding 50 µg m−3. Our results show that the model is able to reasonably simulate the diurnal cycle of surface fluxes and 2 m temperatures as well as evolution of the stable and shallow boundary layer typically occurring in wintertime in Stuttgart. The simulated fields of particulates with a diameter of less than 10 µm (PM10) and nitrogen dioxide (NO2) allow a clear statement about the most heavily polluted areas apart from the irregularly distributed measurement sites. Together with information about the vertical distribution of PM10 and NO2 from the model, AQFS will serve as a valuable tool for air quality forecasting and has the potential of being applied to other cities around the world.


2021 ◽  
Vol 21 (18) ◽  
pp. 14309-14332
Author(s):  
Peter Huszar ◽  
Jan Karlický ◽  
Jana Marková ◽  
Tereza Nováková ◽  
Marina Liaskoni ◽  
...  

Abstract. Urban areas are hot spots of intense emissions, and they influence air quality not only locally but on a regional or even global scale. The impact of urban emissions over different scales depends on the dilution and chemical transformation of the urban plumes which are governed by the local- and regional-scale meteorological conditions. These are influenced by the presence of urbanized land surface via the so-called urban canopy meteorological forcing (UCMF). In this study, we investigate for selected central European cities (Berlin, Budapest, Munich, Prague, Vienna and Warsaw) how the urban emission impact (UEI) is modulated by the UCMF for present-day climate conditions (2015–2016) using two regional climate models, the regional climate models RegCM and Weather Research and Forecasting model coupled with Chemistry (WRF-Chem; its meteorological part), and two chemistry transport models, Comprehensive Air Quality Model with Extensions (CAMx) coupled to either RegCM and WRF and the “chemical” component of WRF-Chem. The UCMF was calculated by replacing the urbanized surface by a rural one, while the UEI was estimated by removing all anthropogenic emissions from the selected cities. We analyzed the urban-emission-induced changes in near-surface concentrations of NO2, O3 and PM2.5. We found increases in NO2 and PM2.5 concentrations over cities by 4–6 ppbv and 4–6 µg m−3, respectively, meaning that about 40 %–60 % and 20 %–40 % of urban concentrations of NO2 and PM2.5 are caused by local emissions, and the rest is the result of emissions from the surrounding rural areas. We showed that if UCMF is included, the UEI of these pollutants is about 40 %–60 % smaller, or in other words, the urban emission impact is overestimated if urban canopy effects are not taken into account. In case of ozone, models due to UEI usually predict decreases of around −2 to −4 ppbv (about 10 %–20 %), which is again smaller if UCMF is considered (by about 60 %). We further showed that the impact on extreme (95th percentile) air pollution is much stronger, and the modulation of UEI is also larger for such situations. Finally, we evaluated the contribution of the urbanization-induced modifications of vertical eddy diffusion to the modulation of UEI and found that it alone is able to explain the modeled decrease in the urban emission impact if the effects of UCMF are considered. In summary, our results showed that the meteorological changes resulting from urbanization have to be included in regional model studies if they intend to quantify the regional footprint of urban emissions. Ignoring these meteorological changes can lead to the strong overestimation of UEI.


2021 ◽  
Author(s):  
Peter Huszar ◽  
Jan Karlický ◽  
Jana Marková ◽  
Tereza Nováková ◽  
Marina Liaskoni ◽  
...  

Abstract. Urban areas are hot-spots of intense emissions and they influence air-quality not only locally but on regional or even global scales. The impact of urban emissions over different scales depends on the dilution and chemical transformation of the urban plumes which are governed by the local and regional scale meteorological conditions. These are influenced by the presence of urbanized land-surface via the so called urban canopy meteorological forcing (UCMF). In this study, we investigate for selected central European cities (Berlin, Budapest, Munich, Prague, Vienna and Warsaw), how the urban emission impact (UEI) is modulated by the UCMF for present day climate conditions (2015–2016) using three regional climate-chemistry models: the regional climate models RegCM and WRF-Chem (its meteorological part), the chemistry transport model CAMx coupled to either RegCM and WRF and the “chemical” component of WRF-Chem. The UCMF was calculated by replacing the urbanized surface by rural one while the UEI was estimated by removing all anthropogenic emissions from the selected cities. We analyzed the urban emissions induced changes of near surface concentrations of NO2, O3 and PM2.5. We found increases of NO2 and PM2.5 concentrations over cities by 4–6 ppbv, and 4–6 μgm−3, respectively meaning that about 40–60 % and 20–40 % of urban concentrations of NO2 and PM2.5 are caused by local emissions and the rest is the result of emissions from surrounding rural areas. We showed that if UCMF is included, the UEI of these pollutants is about 40–60 % smaller, or in other words, the urban emission impact is overestimated if urban canopy effects are not taken into account. In case of ozone, models due to UEI usually predict decreases around −2 to −4 ppbv (about 10–20 %), which is again smaller if UCMF is considered (by about 60 %). We further showed that the impact on extreme (95th percentile) air-pollution is much stronger, as well as the modulation of UEI is larger for such situations. Finally, we evaluated the contribution of the urbanization induced modifications of vertical eddy-diffusion to the modulation of UEI, and found that it alone is able to explain the modelled decrease of the urban emission impact if the effects of UCMF are considered. In summary, our results showed that the meteorological changes resulting from urbanization have to be included in regional model studies if they intend to quantify the regional fingerprint of urban emissions. Ignoring these meteorological changes can lead to strong overestimation of UEI.


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