Estimating domestic wood burning emissions of particulate matter in two Nordic cities by combining ambient air observations with receptor and dispersion models

Abstract

The major emission source of primary PM2.5 in many Nordic countries is wood burning for domestic heating. Though direct measurements of wood burning emissions are possible under controlled conditions, emission inventories for urban scale domestic heating are difficult to calculate and remain uncertain. As an alternative method for estimating these emissions, this paper makes use of ambient air measurements, chemical analysis of filter samples, receptor models, dispersion models, and simple inverse modelling methods to infer the emission strengths. A comparison of dispersion models with receptor models indicates that the dispersion models tend to overestimate the contribution from wood burning. The inverse modelling results are found to agree with those from the receptor modelling. Though both the receptor and inverse modelling point to an overestimation of the wood burning emissions of PM2.5, it is not possible to assign this solely to errors in the emissions inventory as a dispersion model error can be significant. It is recommended to improve plume rise and urban canopy meteorological descriptions in the dispersion models before these models are of sufficient quality to allow quantitative assessments of emission inventories.

Keywords

• particulate matter
• urban air quality
• receptor modeling
• dispersion modeling
• inverse modeling
• wood burning.