Estimation of inter-seasonal differences in NO2 concentrations using a dispersion ADMS-Urban model and measurements

Dėdelė, Audrius; Miškinytė, Auksė

doi:10.1007/s11869-014-0272-9

Cited by 11 publications

(3 citation statements)

References 28 publications

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“…Another study was performed to check the reliability of the numerical model results, focusing on the estimation of average annual NO 2 concentration near heavy traffic streets in the city of Kaunas in Lithuania. The modelled results have obtained a plausible correlation of 75% with the observed concentration in summer and winter [12].…”

Section: Introductionsupporting

confidence: 55%

Application of the Urban Climate Model PALM-4U to Investigate the Effects of the Diesel Traffic Ban on Air Quality in Stuttgart

Samad,

Caballero Arciénega,

Alabdallah

et al. 2024

Atmosphere

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The air pollution situation in the German city of Stuttgart is very important, as high pollutant concentrations are measured here compared to other German cities. This is mainly due to Stuttgart’s geographical location as it is in a basin covered by hills on three sides. This leads to reduced wind speeds that inhibit pollutant dispersion. One of the main contributors to the pollutant concentrations in Stuttgart is local traffic. To improve the air quality in Stuttgart, a diesel traffic ban was introduced on 1 January 2019, and is ongoing. In this study, the urban climate model PALM-4U was applied to obtain the pollutant distribution along the federal highways B14 and B27 of Stuttgart to evaluate the impact of the diesel traffic ban on air quality. The simulations were carried out in two areas of the city, namely the city center and Kaltental Valley, with domain sizes of 3.2 km × 2 km and 3.2 km × 1.6 km, respectively, and with a grid size of 10 m for each domain. The influence of traffic emissions on the air quality of Stuttgart was studied for a typical summer day. The results showed that air pollutant concentrations were highest near federal highways B14 and B27 (e.g., NO2 concentration peaks of around 200 µg/m3). Also, a significant reduction of around four times in air pollutant concentrations was observed in the study area after the diesel traffic ban was introduced.

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Section: Introductionsupporting

confidence: 55%

Application of the Urban Climate Model PALM-4U to Investigate the Effects of the Diesel Traffic Ban on Air Quality in Stuttgart

Samad,

Caballero Arciénega,

Alabdallah

et al. 2024

Atmosphere

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“…The results showed that the model underestimated NO x and NO 2 concentrations but that R 2 equaled 0.88. Dėdelė and Miškinytė ( 37 ) used ADMS-Urban to model NO 2 concentrations in Kaunas city and validated the modeled concentration against measurements from 41 Ogawa passives samplers operated as part of ESCAPE. Differently from the other studies, the vehicle fleet was assigned an age of 14 years to calculate emissions.…”

Section: Discussionmentioning

confidence: 99%

The Impact of Different Validation Datasets on Air Quality Modeling Performance

Khreis

Hoogh

Zietsman

et al. 2018

Transportation Research Record: Journal of the Transportation R

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Many studies rely on air pollution modeling such as land use regression (LUR) or atmospheric dispersion (AD) modeling in epidemiological and health impact assessments. Generally, these models are only validated using one validation dataset and their estimates at select receptor points are generalized to larger areas. The primary objective of this paper was to explore the effect of different validation datasets on the validation of air quality models. The secondary objective was to explore the effect of the model estimates’ spatial resolution on the models’ validity at different locations. Annual NOx and NO2 were generated using a LUR and an AD model. These estimates were validated against four measurement datasets, once when estimates were made at the exact locations of the validation points and once when estimates were made at the centroid of the 100m×100m grid in which the validation point fell. The validation results varied substantially based on the model and validation dataset used. The LUR models’ R2 ranged between 21% and 58%, based on the validation dataset. The AD models’ R2 ranged between 13% and 56% based on the validation dataset and the use of constant or varying background NOx. The validation results based on model estimates at the exact validation site locations were much better than those based on a 100m×100m grid. This paper demonstrated the value of validating modeled air quality against various datasets and suggested that the spatial resolution of the models’ estimates has a significant influence on the validity at the application point.

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“…It considers the processes of gravity settlement, building topography and chemical reactions, then simulates multiple traffic pollution sources with different spatial distributions and finally obtains a higher-resolution pollutant concentration map to analyze the impact of different pollution sources on the prediction results [ 22 ]. It can accurately simulate not only the diffusion of pollutants emitted by various pollution sources in the atmosphere, including point, line and surface sources, but also their impact on the environment [ 23 , 24 , 25 , 26 ].…”

Section: Methodsmentioning

confidence: 99%

Emission Variations of Primary Air Pollutants from Highway Vehicles and Implications during the COVID-19 Pandemic in Beijing, China

Cao

Tian

Shen

et al. 2021

IJERPH

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According to the traffic flow variation from January 2019 to August 2020, emissions of primary air pollutants from highway vehicles were calculated based on the emission factor method, which integrated the actual structure of on-road vehicles. The characteristics of on-highway traffic flow and pollution emissions were compared during various progression stages of coronavirus disease (COVID-19). The results showed that the average daily traffic volume decreased by 38.2% in 2020, with a decrease of 62% during the strict lockdown due to the impact of COVID-19. The daily emissions of primary atmospheric pollutants decreased by 29.2% in 2020 compared to the same period in 2019. As for the structure of on-highway vehicle types, the small and medium-sized passenger vehicles predominated, which accounted for 76.3% of traffic, while trucks and large passenger vehicles accounted for 19.7% and 4.0%, but contributed 58.4% and 33.9% of nitrogen oxide (NOx) emissions, respectively. According to the simulation results of the ADMS model, the average concentrations of NOx were reduced by 12.0 µg/m3 compared with the same period in 2019. As for the implication for future pollution control, it is necessary to further optimize the structure of on-highway and the road traffic vehicle types and increase the proportions of new-energy vehicles and vehicles with high emission standards.

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Estimation of inter-seasonal differences in NO2 concentrations using a dispersion ADMS-Urban model and measurements

Cited by 11 publications

References 28 publications

Application of the Urban Climate Model PALM-4U to Investigate the Effects of the Diesel Traffic Ban on Air Quality in Stuttgart

Application of the Urban Climate Model PALM-4U to Investigate the Effects of the Diesel Traffic Ban on Air Quality in Stuttgart

The Impact of Different Validation Datasets on Air Quality Modeling Performance

Emission Variations of Primary Air Pollutants from Highway Vehicles and Implications during the COVID-19 Pandemic in Beijing, China

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