Spatial surrogate for domestic combustion’s air emissions: A case study from Silesian Metropolis, Poland

ABSTRACT

The aim of this study is improving currently applied methodology for spatial disaggregation, as well as mapping air emission inventories by taking into account the auxiliary spatial data on population density. District heating infrastructure occurring in more populated areas changes distinctly the spatial distribution of estimated air emission; however, it does not change the initial estimate. That means the total, disaggregated value is constant. Considered sources of domestic combustion are located in the central part of the Silesian Metropolis, in the southern part of Poland. A large part of this area is strongly urbanized and supplied with heat (hot water) from the district heating system. Data on population density help to determine the area within which the dwellers use heat energy and hot water supplied by the heating infrastructure, apart from heating with small domestic boilers and stoves. This causes the domestic combustion’s emission impact within the distinguished area to be significantly lower in comparison to the official guidelines on air emission inventories. The important differences in spatial air emissions distributions calculated using a top-down approach are found for strongly urbanized areas supplied partly with heat and hot water from the district heating network. This fact should be taken into account when preparing detailed, high-resolution emission inventories for air regional and local quality modeling.

Implications: The spatial issues connected with elaboration of the high-resolution emission inventories are presented for the example of the populated area of the Silesian Metropolis (Poland). Spatial distribution of the population density is used to determine the area supplied with heat and hot water from the district heating system. It changes distinctly the spatial distribution of the air emission from small residential combustion sources.

Funding

The authors thank the China Section of the Air & Waste Management Association for the generous scholarship they received to cover the cost of page charges and make the publication of this paper possible.

Additional information

Funding

The authors thank the China Section of the Air & Waste Management Association for the generous scholarship they received to cover the cost of page charges and make the publication of this paper possible.

Notes on contributors

Damian Zasina

Damian Zasina works in the Institute of Environmental Protection–National Research Institute, Warsaw, Poland. He is also a PhD student and teaching assistant in the Faculty of Building Services, Hydro and Environmental Engineering, at the Warsaw University of Technology. His research interests focus on using of geospatial methods for disaggregation and uncertainty analysis in air emission inventories.

Jaroslaw Zawadzki

Jaroslaw Zawadzki is a professor of statistics and geostatistics in the Faculty of Building Services, Hydro and Environmental Engineering, at the Warsaw University of Technology. He specializes in environmental studies and production engineering. His research interests focus on environmental risk assessment, environmetrics, geostatistics, remote sensing, and environmental

physics.