Dispersion Model Evaluation of SO2 Emission From Stack in Oil Refinery Plant Using AERMOD 8.9.0

2020 ◽  
Vol 12 (2) ◽  
Author(s):  
Mohsen Jamshidi Angas ◽  
Seyed Ali Jozi ◽  
Rokhshad Hejazi ◽  
Sahar Rezaian
Keyword(s):  
Air Quality ◽  
Dispersion Model ◽  
Model Performance ◽  
Point Sources ◽  
Air Pollutant ◽  
Oil Refinery ◽  
Dispersion Modeling ◽  
So2 Emission ◽  
Oil Refineries ◽  
Aermod Model

Background: In the operation of oil refineries, one of the main pollutants in stack emission is SO2. Dispersion modeling is a necessary tool for simulation of air pollutant concentration, which is the main part of urban air quality management. Objectives: The ability of air quality models is well established where sufficient input data are available. The present study is performed to assess the SO2 emission from the Tehran oil refinery. Methods: The release pattern of SO2 was simulated by the AERMOD model in the desired zone, with an area of 25 × 25 km2. Modeling was run in the 1, 3, 8, and 24 average times for two warm and cold seasons. Predicted and observed pollutant concentrations were compared for validation of the results by the EPA statistical index. Four receptors were selected to compare the predicted and observed values. Results: Correlation coefficient values for SO2 were 0.92 and 0.95 for the warm and cold seasons, respectively. The maximum concentration of SO2 was on the local scale of 25 × 25 km2. Conclusions: The results showed that modeling is appropriate for conducting point sources in the oil refinery. 1 and 24 h averaging time from the model for SO2 concentrations were lower than standard levels; therefore, in the study area, the AERMOD model performance for prediction of SO2 concentrations was acceptable. Although most of the measurements were lower than standard values, due to the possibility of air pollution transmission to the urban area, their control should be considered.

scholarly journals Mobile atmospheric measurements and local-scale inverse estimation of the location and rates of brief CH<sub>4</sub> and CO<sub>2</sub> releases from point sources

2021 ◽  
Vol 14 (9) ◽  
pp. 5987-6003
Author(s):  
Pramod Kumar ◽  
Grégoire Broquet ◽  
Camille Yver-Kwok ◽  
Olivier Laurent ◽  
Susan Gichuki ◽  
...  
Keyword(s):  
Mole Fraction ◽  
Cross Sections ◽  
Dispersion Model ◽  
Local Scale ◽  
Point Sources ◽  
Mitigation Strategies ◽  
Dispersion Modeling ◽  
Plume Dispersion ◽  
Atmospheric Measurements ◽  
Wide Range

Abstract. We present a local-scale atmospheric inversion framework to estimate the location and rate of methane (CH4) and carbon dioxide (CO2) releases from point sources. It relies on mobile near-ground atmospheric CH4 and CO2 mole fraction measurements across the corresponding atmospheric plumes downwind of these sources, on high-frequency meteorological measurements, and on a Gaussian plume dispersion model. The framework exploits the scatter of the positions of the individual plume cross sections, the integrals of the gas mole fractions above the background within these plume cross sections, and the variations of these integrals from one cross section to the other to infer the position and rate of the releases. It has been developed and applied to provide estimates of brief controlled CH4 and CO2 point source releases during a 1-week campaign in October 2018 at the TOTAL experimental platform TADI in Lacq, France. These releases typically lasted 4 to 8 min and covered a wide range of rates (0.3 to 200 g CH4/s and 0.2 to 150 g CO2/s) to test the capability of atmospheric monitoring systems to react fast to emergency situations in industrial facilities. It also allowed testing of their capability to provide precise emission estimates for the application of climate change mitigation strategies. However, the low and highly varying wind conditions during the releases added difficulties to the challenge of characterizing the atmospheric transport over the very short duration of the releases. We present our series of CH4 and CO2 mole fraction measurements using instruments on board a car that drove along roads ∼50 to 150 m downwind of the 40 m × 60 m area for controlled releases along with the estimates of the release locations and rates. The comparisons of these results to the actual position and rate of the controlled releases indicate ∼10 %–40 % average errors (depending on the inversion configuration or on the series of tests) in the estimates of the release rates and ∼30–40 m errors in the estimates of the release locations. These results are shown to be promising, especially since better results could be expected for longer releases and under meteorological conditions more favorable to local-scale dispersion modeling. However, the analysis also highlights the need for methodological improvements to increase the skill for estimating the source locations.

scholarly journals Mobile atmospheric measurements and local-scale inverse estimation of the location and rates of brief CH<sub>4</sub> and CO<sub>2</sub> releases from point sources

2020 ◽  
Author(s):  
Pramod Kumar ◽  
Grégoire Broquet ◽  
Camille Yver-Kwok ◽  
Olivier Laurent ◽  
Susan Gichuki ◽  
...  
Keyword(s):  
Cross Sections ◽  
Dispersion Model ◽  
Local Scale ◽  
Point Sources ◽  
Mitigation Strategies ◽  
Average Error ◽  
Dispersion Modeling ◽  
Plume Dispersion ◽  
Atmospheric Measurements ◽  
Wide Range

Abstract. We present a local-scale atmospheric inversion framework to estimate the location and rate of methane (CH4) and carbon dioxide (CO2) releases from point sources. It relies on mobile near-ground atmospheric CH4 and CO2 mole fraction measurements across the corresponding atmospheric plumes downwind the sources, on high-frequency meteorological measurements, and a Gaussian plume dispersion model. It exploits the spread of the positions of individual plume cross-sections and the integrals of the gas mole fractions above the background within these plume cross-sections to infer the position and rate of the releases. It has been developed and applied to provide estimates of brief controlled CH4 and CO2 point source releases during a one-week campaign in October 2018 at the TOTAL's experimental platform TADI in Lacq, France. These releases lasted typically 4 to 8 minutes and covered a wide range of rates (0.3 to 200 gCH4/s and 0.2 to 150 gCO2/s) to test the capability of atmospheric monitoring systems to react fast to emergency situations in industrial facilities. It also allowed testing their capability to provide precise emission estimates for the application of climate change mitigation strategies. However, the low and highly varying wind conditions during the releases added difficulties to the challenge of characterizing the atmospheric transport over the very short duration of the releases. We present our series of measurements of CH4 and CO2 mole fractions using instruments onboard a car that drives along the roads ~50 to 150 m downwind the 40 m × 60 m area of controlled releases for each of the releases and the results from the inversions of the release locations and rates. The comparisons of these results to the actual position and rate of the controlled release indicate a 20 %–30 % average error on the release rates and a ~30–40 m errors in the estimates of the release locations. These results are shown to be promising especially since better results could be expected for longer releases and under meteorological conditions more favorable to local scale dispersion modeling.

scholarly journals GEOSTATISTICS FOR AIR QUALITY MAPPING: CASE OF BAGUIO CITY, PHILIPPINES

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 353-359
Author(s):  
R. V. Ramos ◽  
A. C. Blanco
Keyword(s):  
Air Quality ◽  
Dispersion Model ◽  
Atmospheric Dispersion ◽  
Spatial Variations ◽  
Dispersion Modeling ◽  
Dispersion Models ◽  
Night Time ◽  
Smoothing Factor ◽  
Pollutant Concentrations ◽  
Atmospheric Dispersion Models

Abstract. Mapping of air quality are often based on ground measurements using gravimetric and air portable sensors, remote sensing methods and atmospheric dispersion models. In this study, Geographic Information Systems (GIS) and geostatistical techniques are employed to evaluate coarse particulate matter (PM10) concentrations observed in the Central Business District of Baguio City, Philippines. Baguio City has been reported as one of the most polluted cities in the country and several studies have already been conducted in monitoring its air quality. The datasets utilized in this study are based on hourly simulations from a Gaussian-based atmospheric dispersion model that considers the impacts of vehicular emissions. Dispersion modeling results, i.e., PM10 concentrations at 20-meter interval, show that high values range from 135 to 422 μg/mm3. The pollutant concentrations are evident within 40 meters from the roads. Spatial variations and PM10 estimates at unsampled locations are determined using Ordinary Kriging. Geostatistical modeling estimates are evaluated based on recommended values for mean error (ME), root mean square error (RMSE) and standardized errors. Optimal predictors for pollutant concentrations at 5-meter interval include 2 to 5 search neighbors and variable smoothing factor for night-time datasets while 2 to 10 search neighbors and smoothing factors 0.3 to 0.5 were used for daytime datasets. Results from several interpolation tests indicate small ME (0.0003 to 0.0008 μg/m3) and average standardized errors (4.24 to 8.67 μg/m3). RMSE ranged from 2.95 to 5.43 μg/m3, which are approximately 2 to 3% of the maximum pollutant concentrations in the area. The methodology presented in this paper may be integrated with atmospheric dispersion models in refining estimates of pollutant concentrations, in generating surface representations, and in understanding the spatial variations of the outputs from the model simulations.

scholarly journals Ground level concentrations of hydrocarbon emissions from diesel fuelled electric power generators

2015 ◽  
Vol 17 (4) ◽  
pp. 673-681 ◽  
Keyword(s):  
Air Quality ◽  
Dispersion Model ◽  
Ground Level ◽  
Point Sources ◽  
National Standard ◽  
Case Scenario ◽  
Worst Case ◽  
Power Generators ◽  
Worst Case Scenario ◽  
Ground Level Concentration

<div> <p>ISC-Aermod view dispersion model has been used to study the ground level concentration of hydrocarbon (HC). The purpose was to predict the air quality effects from off-grid diesel power generators operated by a textile factory in Lagos, Nigeria on its host airshed. Emissions from 22 point sources in 5 sections of the factory were considered with 6 different scenarios. 4 years of hourly meteorological observations were used for the investigation of dispersion. The model output showed the highest value of maximum ground level concentration at 90 m south east of the factory. The predicted impact using the worst case scenario showed that the ambient HC of the host air shed will change by 0.01-0.05% of Nigeria&rsquo;s Federal Ministry of Environment (FMENV) standard. HC emissions from factory will not significantly affect the host air shed as the maximum concentrations from the worst case scenario were still lower than the national standard. However, since emissions from other factories will also be released into the same host environment, an integrated approach factoring the contributions from other factories should be employed in host air quality management.</p> </div> <p>&nbsp;</p>

scholarly journals The Eulerian urban dispersion model EPISODE. Part II: Extensions to the source dispersion and photochemistry for EPISODE-CityChem v1.2 and its application to the city of Hamburg

2019 ◽  
Author(s):  
Matthias Karl ◽  
Sam-Erik Walker ◽  
Sverre Solberg ◽  
Martin O. P. Ramacher
Keyword(s):  
Air Quality ◽  
Atmospheric Chemistry ◽  
Urban Areas ◽  
Dispersion Model ◽  
Model Performance ◽  
Pollutant Dispersion ◽  
Lower Latitude ◽  
Urban Dispersion ◽  
Grid Model ◽  
The City

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 lower latitude cities with higher insolation than in northern European cities. 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 the dispersion in the proximity of urban emission sources. The WMPP (WORM Meteorological Pre-Processor) is used in the point source sub-grid model to calculate the wind speed at plume height. The simplified street canyon model (SSCM) is used in the line source sub-grid model to calculate pollutant dispersion in street canyons. The EPISODE-CityChem model integrates the CityChem extension in EPISODE, with the capability of simulating 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. EPISODE-CityChem was evaluated with a series of tests and with a first application to the air quality situation in the city of Hamburg, Germany. A performance analysis with the FAIRMODE DELTA Tool for the air quality in Hamburg showed that the model 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. Observed levels of annual mean ozone at the five urban background stations in Hamburg are captured by the model within 15 %. 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.

Comparison of TROPOMI/Sentinel-5 Precursor NO2 product with ground-based observations in Helsinki and first societal applications

2020 ◽  
Author(s):  
Iolanda Ialongo ◽  
Henrik Virta ◽  
Henk Eskes ◽  
Jari Hovila ◽  
John Douros
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
A Priori ◽  
Urban Air Quality ◽  
Oil Refinery ◽  
Urban Air ◽  
Chemical Transport Model ◽  
Weekly Cycle ◽  
Oil Refineries

&lt;p&gt;We evaluate the satellite-based TROPOMI (TROPOspheric Monitoring Instrument) NO2 products against ground-based observations in Helsinki (Finland). TROPOMI NO2 total (summed) columns are compared with the measurements performed by the Pandora spectrometer during April&amp;#8211;September 2018. The mean relative and absolute bias between the TROPOMI and Pandora NO2 total columns is about 10 % and 0.12 &amp;#215; 10&lt;sup&gt;15&lt;/sup&gt; molec. cm&lt;sup&gt;-2&lt;/sup&gt; respectively.&lt;span&gt;&amp;#160;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;We find high correlation (r = 0.68) between satellite- and ground-based data, but also that TROPOMI total columns underestimate ground-based observations for relatively large Pandora NO2 total columns, corresponding to episodes of relatively elevated pollution. This is expected because of the relatively large size of the TROPOMI ground pixel (3.5 &amp;#215; 7 km) and the a priori used in the retrieval compared to the relatively small field-of-view of the Pandora instrument. On the other hand, TROPOMI slightly overestimates relatively small NO2 total columns. Replacing the coarse a priori NO2 profiles with high-resolution profiles from the CAMS chemical transport model improves the agreement between TROPOMI and Pandora total columns for episodes of NO2 enhancement.&lt;span&gt;&amp;#160;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;In order to evaluate the capability of TROPOMI observation for monitoring urban air quality, we also analyse the consistency between satellite-based data and NO2 surface concentrations from the local air quality station. We find similar day-to-day variability between TROPOMI and in situ measurements, with NO2 enhancements observed during the same days. Both satellite- and ground-based data show a similar weekly cycle, with lower NO2 levels during the weekend compared to the weekdays as a result of reduced emissions from traffic and industrial activities (as expected in urban sites). The TROPOMI NO2 maps reveal also spatial features, such as the main traffic ways, the airport and other industrial areas, as well as the effect of the prevailing south-west wind patterns.&lt;span&gt;&amp;#160;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;These first results confirm that TROPOMI NO2 products are valuable to complement the traditional ground-based in situ data for monitoring urban air quality and are already tested by local and national authorities as well as private companies to monitor pollution sources in the Helsinki region (e.g., emissions from traffic, energy production or oil refineries). For example, TROPOMI NO2 products are already used by the oil refinery company NESTE in their sustainability report and by the Finnish Ministry of Environment to map the air pollution levels in Finland.&lt;/p&gt;&lt;p&gt;Ialongo, I., Virta, H., Eskes, H., Hovila, J., and Douros, J.: Comparison of TROPOMI/Sentinel 5 Precursor NO2 observations with ground-based measurements in Helsinki, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-329, accepted for publication, 2020.&lt;/p&gt;

scholarly journals A high-resolution emission inventory of primary pollutants for the Huabei region, China

2012 ◽  
Vol 12 (1) ◽  
pp. 481-501 ◽  
Author(s):  
B. Zhao ◽  
P. Wang ◽  
J. Z. Ma ◽  
S. Zhu ◽  
A. Pozzer ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Air Quality ◽  
Emission Inventory ◽  
Emission Factors ◽  
Cloud Microphysics ◽  
Point Sources ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Environmental Research ◽  
Straw Burning

Abstract. Huabei, located between 32° N and 42° N, is part of eastern China and includes administratively the Beijing and Tianjin Municipalities, Hebei and Shanxi Provinces, and Inner-Mongolia Autonomous Region. Over the past decades, the region has experienced dramatic changes in air quality and climate, and has become a major focus of environmental research in China. Here we present a new inventory of air pollutant emissions in Huabei for the year 2003 developed as part of the project Influence of Pollution on Aerosols and Cloud Microphysics in North China (IPAC-NC). Our estimates are based on data from the statistical yearbooks of the state, provinces and local districts, including major sectors and activities of power generation, industrial energy consumption, industrial processing, civil energy consumption, crop straw burning, oil and solvent evaporation, manure, and motor vehicles. The emission factors are selected from a variety of literature and those from local measurements in China are used whenever available. The estimated total emissions in the Huabei administrative region in 2003 are 4.73 Tg SO2, 2.72 Tg NOx (in equivalent NO2), 1.77 Tg VOC, 24.14 Tg CO, 2.03 Tg NH3, 4.57 Tg PM10, 2.42 Tg PM2.5, 0.21 Tg EC, and 0.46 Tg OC. For model convenience, we consider a larger Huabei region with Shandong, Henan and Liaoning Provinces included in our inventory. The estimated total emissions in the larger Huabei region in 2003 are: 9.55 Tg SO2, 5.27 Tg NOx (in equivalent NO2), 3.82 Tg VOC, 46.59 Tg CO, 5.36 Tg NH3, 10.74 Tg PM10, 5.62 Tg PM2.5, 0.41 Tg EC, and 0.99 Tg OC. The estimated emission rates are projected into grid cells at a horizontal resolution of 0.1° latitude by 0.1° longitude. Our gridded emission inventory consists of area sources, which are classified into industrial, civil, traffic, and straw burning sectors, and large industrial point sources, which include 345 sets of power plants, iron and steel plants, cement plants, and chemical plants. The estimated regional NO2 emissions are about 2–3% (administrative Huabei region) or 5% (larger Huabei region) of the global anthropogenic NO2 emissions. We compare our inventory (IPAC-NC) with the global emission inventory EDGAR-CIRCE and the Asian emission inventory INTEX-B. Except for a factor of 3 lower EC emission rate in comparison with INTEX-B, the biases of the total emissions of most primary air pollutants in Huabei estimated in our inventory, with respect to EDGAR-CIRCE and INTEX-B, generally range from −30% to +40%. Large differences up to a factor of 2–3 for local emissions in some areas (e.g. Beijing and Tianjin) are found. It is recommended that the inventories based on the activity rates and emission factors for each specific year should be applied in future modeling work related to the changes in air quality and atmospheric chemistry over this region.

scholarly journals HERMESv3, a stand-alone multi-scale atmospheric emission modelling framework – Part 2: The bottom–up module

2020 ◽  
Vol 13 (3) ◽  
pp. 873-903
Author(s):  
Marc Guevara ◽  
Carles Tena ◽  
Manuel Porquet ◽  
Oriol Jorba ◽  
Carlos Pérez García-Pando
Keyword(s):  
Atmospheric Chemistry ◽  
Dispersion Model ◽  
Meteorological Data ◽  
Companion Paper ◽  
Point Sources ◽  
Air Pollutant ◽  
Pollutant Emission ◽  
Emission Model ◽  
Bottom Up ◽  
Multi Scale

Abstract. We describe the bottom–up module of the High-Elective Resolution Modelling Emission System version 3 (HERMESv3), a Python-based and multi-scale modelling tool intended for the processing and computation of atmospheric emissions for air quality modelling. HERMESv3 is composed of two separate modules: the global_regional module and the bottom_up module. In a companion paper (Part 1, Guevara et al., 2019a) we presented the global_regional module. The bottom_up module described in this contribution is an emission model that estimates anthropogenic emissions at high spatial- (e.g. road link level,) and temporal- (hourly) resolution using state-of-the-art calculation methods that combine local activity and emission factors along with meteorological data. The model computes bottom–up emissions from point sources, road transport, residential and commercial combustion, other mobile sources, and agricultural activities. The computed pollutants include the main criteria pollutants (i.e. NOx, CO, NMVOCs (non-methane volatile organic compounds), SOx, NH3, PM10 and PM2.5) and greenhouse gases (i.e. CO2 and CH4, only related to combustion processes). Specific emission estimation methodologies are provided for each source and are mostly based on (but not limited to) the calculation methodologies reported by the European EMEP/EEA air pollutant emission inventory guidebook. Meteorologically dependent functions are also included to take into account the dynamical component of the emission processes. The model also provides several functionalities for automatically manipulating and performing spatial operations on georeferenced objects (shapefiles and raster files). The model is designed so that it can be applicable to any European country or region where the required input data are available. As in the case of the global_regional module, emissions can be estimated on several user-defined grids, mapped to multiple chemical mechanisms and adapted to the input requirements of different atmospheric chemistry models (CMAQ, WRF-Chem and MONARCH) as well as a street-level dispersion model (R-LINE). Specific emission outputs generated by the model are presented and discussed to illustrate its capabilities.

scholarly journals An integrated assessment of the impacts of PM2.5 and black carbon particles on the air quality of a large Brazilian city

2021 ◽  
Author(s):  
Lars Gidhagen ◽  
Patricia Krecl ◽  
Admir Créso Targino ◽  
Gabriela Polezer ◽  
Ricardo H. M. Godoi ◽  
...  
Keyword(s):  
Air Quality ◽  
Black Carbon ◽  
Dispersion Model ◽  
Open Data ◽  
Integrated Approach ◽  
Biomass Combustion ◽  
Dispersion Modeling ◽  
Urban Background ◽  
In Situ Data ◽  
The City

AbstractData on airborne fine particle (PM2.5) emissions and concentrations in cities are valuable for traffic and air quality managers, urban planners, health practitioners, researchers, and ultimately for legislators and decision makers. Emissions and ambient concentrations of PM2.5 and black carbon (BC) were assessed in the city of Curitiba, southern Brazil. The methodology combined a month-long monitoring campaign with both fixed and mobile instruments, development of emission inventories, and dispersion model simulations on different scales. The mean urban background PM2.5 concentrations during the campaign were 7.3 μg m−3 in Curitiba city center, but three- to fourfold higher (25.3 μg m-3) in a residential area on the city’s outskirts, indicating the presence of local sources, possibly linked to biomass combustion. BC concentrations seemed to be more uniformly distributed over the city, with mean urban background concentrations around 2 μg m−3, half of which due to local traffic emissions. Higher mean BC concentrations (3–5 μg m-3) were found along busy roads. The dispersion modeling also showed high PM2.5 and BC concentrations along the heavily transited ring road. However, the lack of in situ data over these peripheral areas prevented the verification of the model output. The vehicular emission factors for PM2.5 and BC from the literature were found not to be suitable for Curitiba’s fleet and needed to be adjusted. The integrated approach of this study can be implemented in other cities, as long as an open data policy and a close cooperation among regional, municipal authorities and academia can be achieved.

scholarly journals The urban dispersion model EPISODE v10.0 – Part 1: An Eulerian and sub-grid-scale air quality model and its application in Nordic winter conditions

2020 ◽  
Vol 13 (9) ◽  
pp. 4323-4353
Author(s):  
Paul D. Hamer ◽  
Sam-Erik Walker ◽  
Gabriela Sousa-Santos ◽  
Matthias Vogt ◽  
Dam Vo-Thanh ◽  
...  
Keyword(s):  
Steady State ◽  
Air Quality ◽  
Dispersion Model ◽  
Model Performance ◽  
Air Quality Management ◽  
Air Quality Model ◽  
Quality Model ◽  
Urban Dispersion ◽  
Grid Dispersion ◽  
No2 Pollution

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.

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