Sub-kilometer dispersion simulation of a CO tracer for an inter-Andean urban valley

Henao, Juan J.; Mejía, John F.; Rendón, Angela M.; Salazar, Juan F.

doi:10.1016/j.apr.2020.02.005

Cited by 19 publications

(31 citation statements)

References 82 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The simulation results without data assimilation (LE) underestimated the observed concentrations in all the validation stations. This was also seen in previous related works [18,35]. The RMSE value reflected a low correspondence between the observed and simulated concentrations when using the model without data assimilation.…”

Section: Evaluation Of Data Assimilation Runssupporting

confidence: 84%

“…Our results displayed low correlation values and a marked tendency to underestimate the observed concentrations by the LOTOS-EUROS model without assimilation. Similar behaviors were observed in previous works [18,35]. In [35] the WRF-Chem model in a sub-kilometer configuration was used to reproduce the CO dynamics in the valley.…”

Section: Discussionsupporting

confidence: 74%

“…Similar behaviors were observed in previous works [18,35]. In [35] the WRF-Chem model in a sub-kilometer configuration was used to reproduce the CO dynamics in the valley. The emission inventory was obtained from the AMVA Official Emission Inventory [26] following a methodology similar to the presented in Section 2.2.2.…”

Section: Discussionsupporting

confidence: 74%

See 2 more Smart Citations

Urban Air Quality Modeling Using Low-Cost Sensor Network and Data Assimilation in the Aburrá Valley, Colombia

et al. 2021

View full text Add to dashboard Cite

The use of low air quality networks has been increasing in recent years to study urban pollution dynamics. Here we show the evaluation of the operational Aburrá Valley’s low-cost network against the official monitoring network. The results show that the PM2.5 low-cost measurements are very close to those observed by the official network. Additionally, the low-cost allows a higher spatial representation of the concentrations across the valley. We integrate low-cost observations with the chemical transport model Long Term Ozone Simulation-European Operational Smog (LOTOS-EUROS) using data assimilation. Two different configurations of the low-cost network were assimilated: using the whole low-cost network (255 sensors), and a high-quality selection using just the sensors with a correlation factor greater than 0.8 with respect to the official network (115 sensors). The official stations were also assimilated to compare the more dense low-cost network’s impact on the model performance. Both simulations assimilating the low-cost model outperform the model without assimilation and assimilating the official network. The capability to issue warnings for pollution events is also improved by assimilating the low-cost network with respect to the other simulations. Finally, the simulation using the high-quality configuration has lower error values than using the complete low-cost network, showing that it is essential to consider the quality and location and not just the total number of sensors. Our results suggest that with the current advance in low-cost sensors, it is possible to improve model performance with low-cost network data assimilation.

show abstract

Section: Evaluation Of Data Assimilation Runssupporting

confidence: 84%

Section: Discussionsupporting

confidence: 74%

See 1 more Smart Citation

Urban Air Quality Modeling Using Low-Cost Sensor Network and Data Assimilation in the Aburrá Valley, Colombia

et al. 2021

View full text Add to dashboard Cite

show abstract

“…The simulation results without data assimilation (LE) underestimated the observed concentrations in all the validation stations. This was also seen in previous related works [24,33]. The RMSE value reflected a low correspondence between the observed and simulated concentrations when using the model without data assimilation.…”

Section: Resultssupporting

confidence: 84%

Data Assimilation as a Tool to Improve Chemical Transport Models Performance in Developing Countries

Restrepo

Botero

Montoya³

et al. 2021

Environmental Sustainability - Preparing for Tomorrow

View full text Add to dashboard Cite

Particulate matter (PM) is one of the most problematic pollutants in urban air. The effects of PM on human health, associated especially with PM of ≤2.5μm in diameter, include asthma, lung cancer and cardiovascular disease. Consequently, major urban centers commonly monitor PM2.5 as part of their air quality management strategies. The Chemical Transport models allow for a permanent monitoring and prediction of pollutant behavior for all the regions of interest, different to the sensor network where the concentration is just available in specific points. In this chapter a data assimilation system for the LOTOS-EUROS chemical transport model has been implemented to improve the simulation and forecast of Particulate Matter in a densely populated urban valley of the tropical Andes. The Aburrá Valley in Colombia was used as a case study, given data availability and current environmental issues related to population expansion. Using different experiments and observations sources, we shown how the Data Assimilation can improve the model representation of pollutants.

show abstract

“…( Figure 11 (a), (c), (e), and (g)), with a slight overestimation of the concentration between 11:00 and 17:00. During the high concentration period (Figure 11 (b), (d), (f), and (h)), pollutants remain trapped in the valley due to the high atmospheric stability, which generates higher concentrations in the afternoon Henao, Mejía, Rendón and Salazar (2020), the reason why LE-AMVA reproduces better this temporal variability (although not in terms of magnitude).…”

Section: Simulated Concentrationsmentioning

confidence: 99%

Spatial Disaggregation of Particulate Matter Emission Inventory in the Metropolitan Area of Aburr\'a Valley for Air Quality Modelling

Restrepo¹,

Botero²,

Pinel³

et al. 2020

Preprint

View full text Add to dashboard Cite

In this paper a local emission inventory for PM 10 and PM 2.5 is presented that has been developed using a top-down spatial disaggregation of the official emission inventory for the Metropolitan Area of the Aburrá Valley in Colombia. The local emission inventory was evaluated using the LOTOS-EUROS Chemical Transport Model in a high-resolution simulation, and compared with the global emission inventory EDGAR. A detailed analysis of the model using the local emission inventory was performed. The results showed a considerable improvement in model performance when the local emission inventory was used in comparison to the global emission inventory.

show abstract

Sub-kilometer dispersion simulation of a CO tracer for an inter-Andean urban valley

Cited by 19 publications

References 82 publications

Urban Air Quality Modeling Using Low-Cost Sensor Network and Data Assimilation in the Aburrá Valley, Colombia

Urban Air Quality Modeling Using Low-Cost Sensor Network and Data Assimilation in the Aburrá Valley, Colombia

Data Assimilation as a Tool to Improve Chemical Transport Models Performance in Developing Countries

Spatial Disaggregation of Particulate Matter Emission Inventory in the Metropolitan Area of Aburr\'a Valley for Air Quality Modelling

Contact Info

Product

Resources

About