Turbulence permitting air pollution simulation for the Stuttgart metropolitan area - A winter case study

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

<p>Currently a strong discussion is ongoing in Germany and Europe whether to ban vehicles from downtown areas in order to lower particle concentrations of e.g. PM<sub>10</sub> and NO<sub>2</sub>. As often only few measurements exist inside city centers, little to nothing is known about the horizontal and vertical distributions of air pollutants. Within the EU demonstration project Open Forecast (https://open-forecast.eu/), we applied the WRF-Chem model system version 4.0.3 in order to close this knowledge gap. We zoom in the urban area of Stuttgart, a hot spot of air pollution in Germany. The outermost domain with convection-permitting resolution of 1.25 km encompasses parts of Central Europe in order to provide boundary conditions for the inner two domains.</p><p>The model system was improved in many ways, e.g., with respect to the representation of land cover, urban canopy, and soil properties, which turned out to be key for an acceptable performance. Furthermore, we developed a sophisticated infrastructure to ingest the required high-resolution emission data, which turned out to be very challenging.</p><p>We show that this model approach is likely the best means to understand and to predict air pollution, as the distribution of their constituents depends strongly and simultaneously on the vertical mixing by turbulence, the mesoscale circulation in the complex urban environment, and orographic environment.</p><p>The model system was operated and investigated for a case study of January 21, 2019 during which an alert with respect to the exceedance of PM<sub>10</sub> was issued. We present the simulations of meteorological variables as well as PM<sub>10</sub> and NO<sub>2</sub> and show the complexity of their distribution in the nighttime stable and daytime shallow boundary layer in dependence of the temporal variability of the traffic in the Stuttgart metropolitan area.</p><p>To the best of our knowledge, the results reveal for the first time the complex dynamics of air pollution in complex urban space of Stuttgart at a very high spatial and temporal resolution that cannot currently be achieved with measurements.</p>

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Md. Shohel Reza Amin ◽  
Umma Tamima ◽  
Luis Amador Jimenez

This study demonstrates through a case study that detailed analyses, even after the construction of a project, are feasible using current technologies and available data. A case study of highway 25 is used to illustrate the method and verify the levels of air contaminants from additionally induced traffic during and after the construction of highway. Natural traffic growth was removed from the effect of observed gas emissions by comparing observed levels on other further locations in the same metropolitan area. This study estimates air pollution from the additional traffic during and after the construction of A-25 extension project. NO2 levels were spatially interpolated during peak and off-peak hour traffic and traffic density simulated on the road network for four scenarios. Comparing the four scenarios, it was found that levels of NO2 concentrations were reduced at neighbor areas due to less traffic during the construction period. Levels of NO2 after the construction were higher than those in 2008. The simulated traffic density for four scenarios revealed that traffic density was significantly increased on both arterial and access roads within the close vicinity of the extension project during and after its construction.


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.


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.


Author(s):  
William Ng ◽  
Kevin Weaver ◽  
Zachary Gemmill ◽  
Herve Deslandes ◽  
Rudolf Schlangen

Abstract This paper demonstrates the use of a real time lock-in thermography (LIT) system to non-destructively characterize thermal events prior to the failing of an integrated circuit (IC) device. A case study using a packaged IC mounted on printed circuit board (PCB) is presented. The result validated the failing model by observing the thermal signature on the package. Subsequent analysis from the backside of the IC identified a hot spot in internal circuitry sensitive to varying value of external discrete component (inductor) on PCB.


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