High-Resolution Emissions From Wood Burning in Norway - The Effect of Cabin Emissions

Abstract

Emissions from wood burning for heating in secondary homes or cabins is an important aspect for the development of high-resolution emission inventories in specific areas. Norway is used as case study as the national wood consumption for heating in cabins is around 20% of the total. Our study shows first a method to estimate emissions from cabins based on traffic data to derive cabin occupancy, which combined with heating need allows for the spatial and temporal distribution of emissions. The combination of residential (RWC) and cabin wood combustion (CWC) emissions shows large spatial and temporal differences, and a temporally “cabin population” can in areas be orders of magnitude larger than the registered population. While RWC emissions have been steadily reduced, CWC have kept relatively constant or even increased, which results on an increase in the cabin share to total heating emissions up to 25-35%. When comparing with regional emissions inventories, our study shows that the gradient between rural and urban areas is not well represented in regional emissions inventories, which resembles a population-based distribution and does not allocate emissions in cabin municipalities. At last, our study shows that CWC emissions may become an increasing environmental concern as higher densification trends in mountain areas are observed.

Air pollution emission inventory using national high-resolution spatial parameters for the Nordic countries and analysis of PM2.5 spatial distribution for road transport and machinery and off-road sectors

“…These can help with creating separate proxies for exhaust and dust (resuspension) emissions. The proxy can also be based on bottom-up emission calculation (Andersson et al, 2019;Grythe et al, 2022); i.e. the emissions are calculated on street or even single vehicle level and then aggregated to a grid.…”

“…However, for some other types of machinery, for example, the ones used in construction, it is more difficult, as the locations of construction sites change regularly, and GIS data of such activities might not be easily available in consistent forms. A proxy that would represent the activity over several years is hard to develop and would require detailed information on the construction activity over time and data that define the energy used associated with the different phases of the construction project (Lopez-Aparicio and Grythe, 2022).…”