Simulation model as a tool for assessing air quality in cities and further urban planning: Quantifying PM emissions in Russian industrial city - Kemerovo
Zinoveva, Oksana (2023)
2023
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2023060220658
https://urn.fi/URN:NBN:fi:amk-2023060220658
Tiivistelmä
Poor air quality is a recognized major issue in urban areas, and effective urban planning is vital to mitigate this problem. However, not all decisions are equally effective, and it is crucial to consider a comprehensive structure of the city that takes into account the sources of pollution and the characteristics of urban change.
This study aimed to develop a simulation model of the Russian industrial city of Kemerovo to assess and predict changes in particulate matter (PM) emissions. Urban planning scenarios were utilized to evaluate the effectiveness of possible changes in mitigating PM emissions and preserving green zones.
To consider a comprehensive structure, the study used an approach of dynamic modelling consisting of six sectors: population, transport, agriculture, households, industries, and green zones. While the sectors showed a high level of effectiveness in the validation test, the industrial sector required a more detailed approach as a discrete-event method.
The adopted scenarios did not show a significant reduction in emissions, as the industrial city required a primary focus on reducing emissions from its industrial sector. However, the scenarios could decrease deforestation, which had a positive ecological impact overall. The simulation modelling results were directly useful for emissions assessment and urban planning.
This study aimed to develop a simulation model of the Russian industrial city of Kemerovo to assess and predict changes in particulate matter (PM) emissions. Urban planning scenarios were utilized to evaluate the effectiveness of possible changes in mitigating PM emissions and preserving green zones.
To consider a comprehensive structure, the study used an approach of dynamic modelling consisting of six sectors: population, transport, agriculture, households, industries, and green zones. While the sectors showed a high level of effectiveness in the validation test, the industrial sector required a more detailed approach as a discrete-event method.
The adopted scenarios did not show a significant reduction in emissions, as the industrial city required a primary focus on reducing emissions from its industrial sector. However, the scenarios could decrease deforestation, which had a positive ecological impact overall. The simulation modelling results were directly useful for emissions assessment and urban planning.