A very high-resolution assessment and modelling of urban air quality

Abstract

Abstract. Urban air quality is one of the most prominent environmental concerns for modern city residents and authorities. Accurate monitoring of air quality is difficult due to intrinsic urban landscape heterogeneity and superposition of multiple polluting sources. Existing approaches often do not provide the necessary spatial details and peak concentrations of pollutants, especially at larger distances from monitoring stations. A more advanced integrated approach is needed. This study presents a very high-resolution air quality assessment with the Parallelized Large-Eddy Simulation Model (PALM), capitalising on local measurements. This fully three-dimensional primitive-equation hydrodynamical model resolves both structural details of the complex urban surface and turbulent eddies larger than 10 m in size. We ran a set of 27 meteorological weather scenarios in order to assess the dispersion of pollutants in Bergen, a middle-sized Norwegian city embedded in a coastal valley. This set of scenarios represents typically observed weather conditions with high air pollution from nitrogen dioxide (NO2) and particulate matter (PM2.5). The modelling methodology helped to identify pathways and patterns of air pollution caused by the three main local air pollution sources in the city. These are road vehicle traffic, domestic house heating with wood-burning fireplaces and ships docked in the harbour area next to the city centre. The study produced vulnerability maps, highlighting the most impacted districts for each weather and emission scenario. Overall, the largest contribution to air pollution over inhabited areas in Bergen was caused by road traffic emissions for NO2 and wood-burning fireplaces for PM2.5 pollution. The effect of emission from ships in the port was mostly restricted to the areas close to the harbour and moderate in comparison. However, the results have contributed to implementation of measures to reduce emissions from ships in Bergen harbour, including provision of shore power.

Dispersion of particulate matter (PM<sub>2.5</sub>) from wood combustion for residential heating: Optimisation of mitigation actions based on large-eddy simulations

“…As many Nordic cities, Bergen has clean air brought to the city with westerlies from the Atlantic Ocean. The main local permanent PM2.5 sources are ships in the harbor and road traffic (Wolf et al, 2020). In winter months, however, households actively use wood-burning stoves as a secondary heating source.…”

“…CC BY 4.0 License. et al, 2017;Wolf et al, 2020). A large fraction of PM2.5 emission comes out from household wood-burning stoves installed before 1998, hereafter referred to as older stoves.…”

“…With our turbulence-resolving model, we aim to understand contributions from the dynamical component of turbulent diffusion and transport in spatial variability of the observable PM2.5 concentrations. In realistic urban domains such as, e.g., in Bergen, Norway, concentrations are patchy and follow intricate pattern of local wind convergence and stagnation zones (Wolf et al, 2020). Such microscale climate information must be considered in air quality impact studies (Chandler, 1976), (Bai, 2018).…”

“…In this configuration, the modeling results could be used in policy scenario evaluation and decision-making processes. We use the Parallelize Atmospheric Large-eddy simulation Model (PALM) described by Maronga et al (Maronga et al, 2015, 2019b with minor own modifications as described by Wolf et al (Wolf-Grosse et al, 2017a;Wolf et al, 2020). Furthermore, we investigate a set of plausible mitigation policy scenarios, which were proposed to reduce emissions from the residential wood combustion sourcesthe household stoves.…”

An urban large-eddy-based dispersion model for marginal grid resolutions: CAIRDIO v1.0

“…CC BY 4.0 License. the limiting factor as they restrict ULES applications to research purposes or to areas encompassing city parts only (Wolf et al, 2020). Further depending on the degree of physical detail (e.g.…”