scholarly journals SC on The urban dispersion model EPISODE. Part 1: A Eulerian and subgrid-scale air quality model and its application in Nordic winter conditions.

2019 ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 3357-3399 ◽  
Author(s):  
Matthias Karl ◽  
Sam-Erik Walker ◽  
Sverre Solberg ◽  
Martin O. P. Ramacher

Abstract. This paper describes the CityChem extension of the Eulerian urban dispersion model EPISODE. The development of the CityChem extension was driven by the need to apply the model in largely populated urban areas with highly complex pollution sources of particulate matter and various gaseous pollutants. The CityChem extension offers a more advanced treatment of the photochemistry in urban areas and entails specific developments within the sub-grid components for a more accurate representation of dispersion in proximity to urban emission sources. Photochemistry on the Eulerian grid is computed using a numerical chemistry solver. Photochemistry in the sub-grid components is solved with a compact reaction scheme, replacing the photo-stationary-state assumption. The simplified street canyon model (SSCM) is used in the line source sub-grid model to calculate pollutant dispersion in street canyons. The WMPP (WORM Meteorological Pre-Processor) is used in the point source sub-grid model to calculate the wind speed at plume height. The EPISODE–CityChem model integrates the CityChem extension in EPISODE, with the capability of simulating the photochemistry and dispersion of multiple reactive pollutants within urban areas. The main focus of the model is the simulation of the complex atmospheric chemistry involved in the photochemical production of ozone in urban areas. The ability of EPISODE–CityChem to reproduce the temporal variation of major regulated pollutants at air quality monitoring stations in Hamburg, Germany, was compared to that of the standard EPISODE model and the TAPM (The Air Pollution Model) air quality model using identical meteorological fields and emissions. EPISODE–CityChem performs better than EPISODE and TAPM for the prediction of hourly NO2 concentrations at the traffic stations, which is attributable to the street canyon model. Observed levels of annual mean ozone at the five urban background stations in Hamburg are captured by the model within ±15 %. A performance analysis with the FAIRMODE DELTA tool for air quality in Hamburg showed that EPISODE–CityChem fulfils the model performance objectives for NO2 (hourly), O3 (daily max. of the 8 h running mean) and PM10 (daily mean) set forth in the Air Quality Directive, qualifying the model for use in policy applications. Envisaged applications of the EPISODE–CityChem model are urban air quality studies, emission control scenarios in relation to traffic restrictions and the source attribution of sector-specific emissions to observed levels of air pollutants at urban monitoring stations.


2020 ◽  
Vol 13 (9) ◽  
pp. 4323-4353
Author(s):  
Paul D. Hamer ◽  
Sam-Erik Walker ◽  
Gabriela Sousa-Santos ◽  
Matthias Vogt ◽  
Dam Vo-Thanh ◽  
...  

Abstract. This paper describes the Eulerian urban dispersion model EPISODE. EPISODE was developed to address a need for an urban air quality model in support of policy, planning, and air quality management in the Nordic, specifically Norwegian, setting. It can be used for the calculation of a variety of airborne pollutant concentrations, but we focus here on the implementation and application of the model for NO2 pollution. EPISODE consists of an Eulerian 3D grid model with embedded sub-grid dispersion models (e.g. a Gaussian plume model) for dispersion of pollution from line (i.e. roads) and point sources (e.g. chimney stacks). It considers the atmospheric processes advection, diffusion, and an NO2 photochemistry represented using the photostationary steady-state approximation for NO2. EPISODE calculates hourly air concentrations representative of the grids and at receptor points. The latter allow EPISODE to estimate concentrations representative of the levels experienced by the population and to estimate their exposure. This methodological framework makes it suitable for simulating NO2 concentrations at fine-scale resolution (<100 m) in Nordic environments. The model can be run in an offline nested mode using output concentrations from a global or regional chemical transport model and forced by meteorology from an external numerical weather prediction model; it also can be driven by meteorological observations. We give a full description of the overall model function and its individual components. We then present a case study for six Norwegian cities whereby we simulate NO2 pollution for the entire year of 2015. The model is evaluated against in situ observations for the entire year and for specific episodes of enhanced pollution during winter. We evaluate the model performance using the FAIRMODE DELTA Tool that utilises traditional statistical metrics, e.g. root mean square error (RMSE), Pearson correlation R, and bias, along with some specialised tests for air quality model evaluation. We find that EPISODE attains the DELTA Tool model quality objective in all of the stations we evaluate against. Further, the other statistical evaluations show adequate model performance but that the model scores greatly improved correlations during winter and autumn compared to the summer. We attribute this to the use of the photostationary steady-state scheme for NO2, which should perform best in the absence of local ozone photochemical production. Oslo does not comply with the NO2 annual limit set in the 2008/50/EC directive (AQD). NO2 pollution episodes with the highest NO2 concentrations, which lead to the occurrence of exceedances of the AQD hourly limit for NO2, occur primarily in the winter and autumn in Oslo, so this strongly supports the use of EPISODE for application to these wintertime events. Overall, we conclude that the model is suitable for an assessment of annual mean NO2 concentrations and also for the study of hourly NO2 concentrations in the Nordic winter and autumn environment. Further, in this work we conclude that it is suitable for a range of policy applications specific to NO2 that include pollution episode analysis, evaluation of seasonal statistics, policy and planning support, and air quality management. Lastly, we identify a series of model developments specifically designed to address the limitations of the current model assumptions. Part 2 of this two-part paper discusses the CityChem extension to EPISODE, which includes a number of implementations such as a more comprehensive photochemical scheme suitable for describing more chemical species and a more diverse range of photochemical environments, as well as a more advanced treatment of the sub-grid dispersion.


2019 ◽  
Author(s):  
Paul D. Hamer ◽  
Sam-Erik Walker ◽  
Gabriela Sousa-Santos ◽  
Matthias Vogt ◽  
Dam Vo-Thanh ◽  
...  

Abstract. This paper describes the Eulerian urban dispersion model EPISODE. EPISODE was developed to address a need for an urban air quality model in support of policy, planning, and air quality management in the Nordic, and, specifically, Norwegian setting. It can be used for the calculation of a variety of airborne pollutant concentrations, but we focus here on the implementation and application of the model for NO2 pollution. EPISODE consists of a Eulerian 3D grid model with embedded sub-grid dispersion models (e.g., a Gaussian plume model) for dispersion of pollution from line (i.e., roads) and point sources (e.g., chimney stacks). It considers the atmospheric processes advection, diffusion, and a NO2 photochemistry represented using the photostationary steady state approximation for NO2. EPISODE calculates hourly air concentrations representative of the grids and at receptor points. The latter allow EPISODE to estimate concentrations representative of the levels experienced by the population and to estimate their exposure. This methodological framework makes it suitable for simulating NO2 concentrations at fine scale resolution (


Author(s):  
Rajmal Jat ◽  
Veerendra Sahu ◽  
Bhola Ram Gurjar

Exposure analysis is the receptor-oriented approach of the pollution-level measurement. In this chapter, a detailed discussion is provided of the fundamentals of exposure analysis, methods of measurement, basics of models used for the prediction of pollution concentration indoors and outdoors, and a brief discussion about the health impact of selected pollutants. A detail of fundamental of indoor air quality (IAQ) models like mass balance and CFD models is discussed. Also, basic structures of community multiscale air quality model (CMAQ) and AIRMOD ambient air dispersion models are described. It is observed that measurement of pollution exposure by direct method requires more time and effort as compared with the integrated exposure and stationary measurement. AIRMODE is steady state model and based upon the Gaussian dispersion model. CMAQ is capable of simulating the pollution level for the range of geographic scale for multiple pollutants.


2020 ◽  
Author(s):  
Claudia Flandorfer ◽  
Marcus Hirtl ◽  
Barbara Scherllin-Pirscher

&lt;p&gt;ZAMG runs two models for air-quality forecasts operationally: ALARO-CAMx and WRF-Chem.&lt;/p&gt;&lt;p&gt;ALARO-CAMx is a combination of the meteorological model ALARO and the photochemical dispersion model CAMx and is operated at ZAMG since 2005. The emphasis of this modeling system is to predict ozone peaks in the north-eastern Austrian flatlands. The outer model grid covers Central Europe with a resolution of 13.8 km, the inner domain is centered over Austria with a resolution of 4.6 km. The model runs twice per day for a period of 48 hours.&lt;/p&gt;&lt;p&gt;The second operational air quality model at ZAMG is the on-line coupled model WRF-Chem. Meteorology is simulated simultaneously with the emission, turbulent mixing, transport, transformation as well as the fate of trace gases and aerosols. Two modeling domains are used for these simulations. The mother domain covers Europe with a resolution of 12 km. The inner, nested domain covers the Alpine region with a horizontal resolution of 4&amp;#160;km. The model runs two times per day for a period of 72 hours and is initialized with ECMWF forecasts.&lt;/p&gt;&lt;p&gt;The evaluation of both models is conducted for the period from January to September 2019 with the focus on ozone. The summer 2019 was the 2&lt;sup&gt;nd&lt;/sup&gt; warmest summer since the beginning of the meteorological measurements in Austria more than 200 years ago. Although this summer had favorable conditions for Ozone production (sunny and hot weather, less rain), only a few air quality stations in Eastern Austria have measured exceedances of the ozone information threshold (180&amp;#160;&amp;#181;g/m&amp;#179;) on overall 5 days. The measurements of the air-quality stations are compared with the area forecasts for every province of Austria. Besides the evaluation, air quality forecasts of ALARO-CAMx and WRF-Chem are compared.&lt;/p&gt;


2019 ◽  
Vol 116 (22) ◽  
pp. 10711-10716 ◽  
Author(s):  
Sourangsu Chowdhury ◽  
Sagnik Dey ◽  
Sarath Guttikunda ◽  
Ajay Pillarisetti ◽  
Kirk R. Smith ◽  
...  

Exposures to ambient and household fine-particulate matter (PM2.5) together are among the largest single causes of premature mortality in India according to the Global Burden of Disease Studies (GBD). Several recent investigations have estimated that household emissions are the largest contributor to ambient PM2.5 exposure in the country. Using satellite-derived district-level PM2.5 exposure and an Eulerian photochemical dispersion model CAMx (Comprehensive Air Quality Model with Extensions), we estimate the benefit in terms of population exposure of mitigating household sources––biomass for cooking, space- and water-heating, and kerosene for lighting. Complete mitigation of emissions from only these household sources would reduce India-wide, population-weighted average annual ambient PM2.5 exposure by 17.5, 11.9, and 1.3%, respectively. Using GBD methods, this translates into reductions in Indian premature mortality of 6.6, 5.5, and 0.6%. If PM2.5 emissions from all household sources are completely mitigated, 103 (of 597) additional districts (187 million people) would meet the Indian annual air-quality standard (40 μg m−3) compared with baseline (2015) when 246 districts (398 million people) met the standard. At 38 μg m−3, after complete mitigation of household sources, compared with 55.1 μg m−3 at baseline, the mean annual national population-based concentration would meet the standard, although highly polluted areas, such as Delhi, would remain out of attainment. Our results support expansion of programs designed to promote clean household fuels and rural electrification to achieve improved air quality at regional scales, which also has substantial additional health benefits from directly reducing household air pollution exposures.


2007 ◽  
Vol 46 (9) ◽  
pp. 1354-1371 ◽  
Author(s):  
Vlad Isakov ◽  
John S. Irwin ◽  
Jason Ching

Abstract Atmospheric processes and the associated transport and dispersion of atmospheric pollutants are known to be highly variable in time and space. Current air-quality models that characterize atmospheric chemistry effects, for example, the Community Multiscale Air Quality model (CMAQ), provide volume-averaged concentration values for each grid cell in the modeling domain given the stated conditions. Given the assumptions made and the limited set of processes included in any model’s implementation, there are many sources of “unresolved” subgrid variability. This raises the question of the importance of the unresolved subgrid variations on exposure assessment results if such models were to be used to assess air toxics exposure. In this study, the Hazardous Air Pollutant Exposure Model (HAPEM) is applied to estimate benzene and formaldehyde inhalation exposure using ambient annually averaged concentrations predicted by CMAQ to investigate how within-grid variability can affect exposure estimates. An urban plume dispersion model was used to estimate the subgrid variability of annually averaged benzene concentration values within CMAQ grid cells for a modeling domain centered on Philadelphia, Pennsylvania. Significant (greater than a factor of 2) increases in maximum exposure impacts were seen in the exposure estimates in comparison with exposure estimates generated using CMAQ grid-averaged concentration values. These results consider only one source of subgrid variability, namely, the discrete location and distribution of emissions, but they do suggest the importance and value of developing improved characterizations of subgrid concentration variability for use in air toxics exposure assessments.


2005 ◽  
Vol 2005 (3) ◽  
pp. 1393-1414
Author(s):  
Kuo-Liang Lai ◽  
Janet Kremer ◽  
Susan Sciarratta ◽  
R. Dwight Atkinson ◽  
Tom Myers

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