ALBERT

Description: 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 (

Description: 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, and, 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 a 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 a 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 (

Description: We present here emissions estimated from a newly developed emission model for residential wood combustion (RWC) at high spatial and temporal resolution, which we title the MetVed model. The model estimates hourly emissions resolved on a 250 m grid resolution for several compounds, including particulate matter (PM), black carbon (BC) and polycyclic aromatic hydrocarbons (PAH) in Norway for a 12 year period. The model uses novel input data and calculation methods that combine databases built with an unprecedented high level of detail and near national coverage. The model establishes wood burning potential at the grid based on the dependencies between variables that influence emissions; i.e., outdoor temperature, number of and type and size of dwellings, type of available heating technologies, distribution of wood-based heating installations and their associated emission factors. RWC activity with a 1 hr temporal profile was produced by combining heating degree day, and hourly and weekday activity profiles reported by wood consumer in official statistics. This approach results in an improved characterisation of the spatio-temporal distribution of wood use and subsequently of emissions, required for urban air quality assessments. Whereas most variables are calculated based on bottom up approaches on a 250 m spatial grid, the MetVed model is set up to use official wood consumption at county level, and then distributes consumption to individual grids proportional to the physical traits of the residences within it. MetVed combines consumption with official emission factors that makes the emissions also upward scalable from the 250 m grid to national level. The MetVed spatial distribution obtained was compared at urban scale to other existing emissions at the same scale. The annual urban emissions, developed according to different spatial proxies, were found to have differences up to order of magnitude. The MetVed total annual PM2.5 emissions in the urban domains compare well to emissions adjusted based on concentration measurements. In addition, hourly PM2.5 concentrations estimated by an Eulerian dispersion model using MetVed emissions was compared to measurements at air quality stations. Both hourly daily profiles and the seasonality of PM2.5 show a slight overestimation of PM2.5 levels. However, a comparison with black carbon from biomass burning and benzo(a)pyrene measurements indicates higher emissions during winter than that obtained by MetVed. The accuracy of urban emissions from RWC relies on the accuracy of the wood consumption (activity data), emission factors and the spatio-temporal distribution. While there are still knowledge gaps regarding emissions, MetVed represents a vast improvement in the spatial and temporal distribution of RWC.

Description: We present here emissions estimated from a newly developed emission model for residential wood combustion (RWC) at high spatial and temporal resolution, which we name the MetVed model. The model estimates hourly emissions resolved on a 250 m grid resolution for several compounds, including particulate matter (PM), black carbon (BC) and polycyclic aromatic hydrocarbons (PAHs) in Norway for a 12-year period. The model uses novel input data and calculation methods that combine databases built with an unprecedented high level of detail and near-national coverage. The model establishes wood burning potential at the grid based on the dependencies between variables that influence emissions: i.e. outdoor temperature, number of and type and size of dwellings, type of available heating technologies, distribution of wood-based heating installations and their associated emission factors. RWC activity with a 1 h temporal profile was produced by combining heating degree day and hourly and weekday activity profiles reported by wood consumers in official statistics. This approach results in an improved characterisation of the spatio-temporal distribution of wood use, and subsequently of emissions, required for urban air quality assessments. Whereas most variables are calculated based on bottom-up approaches on a 250 m spatial grid, the MetVed model is set up to use official wood consumption at the county level and then distributes consumption to individual grids proportional to the physical traits of the residences within it. MetVed combines consumption with official emission factors that makes the emissions also upward scalable from the 250 m grid to the national level. The MetVed spatial distribution obtained was compared at the urban scale to other existing emissions at the same scale. The annual urban emissions, developed according to different spatial proxies, were found to have differences up to an order of magnitude. The MetVed total annual PM2.5 emissions in the urban domains compare well to emissions adjusted based on concentration measurements. In addition, hourly PM2.5 concentrations estimated by an Eulerian dispersion model using MetVed emissions were compared to measurements at air quality stations. Both hourly daily profiles and the seasonality of PM2.5 show a slight overestimation of PM2.5 levels. However, a comparison with black carbon from biomass burning and benzo(a)pyrene measurements indicates higher emissions during winter than that obtained by MetVed. The accuracy of urban emissions from RWC relies on the accuracy of the wood consumption (activity data), emission factors and the spatio-temporal distribution. While there are still knowledge gaps regarding emissions, MetVed represents a vast improvement in the spatial and temporal distribution of RWC.