0000000001315572
AUTHOR
Sini Isokääntä
Modeling atmospheric aging of small-scale wood combustion emissions: distinguishing causal effects from non-causal associations
Small-scale wood combustion is a significant source of particulate emissions. Atmospheric transformation of wood combustion emissions is a complex process involving multiple compounds interacting simultaneously. Thus, an advanced methodology is needed to study the process in order to gain a deeper understanding of the emissions. In this study, we are introducing a methodology for simplifying this complex process by detecting dependencies of observed compounds based on a measured dataset. A statistical model was fitted to describe the evolution of combustion emissions with a system of differential equations derived from the measured data. The performance of the model was evaluated using simu…
Atmospheric aging of small-scale wood combustion emissions (model MECHA 1.0) – is it possible to distinguish causal effects from non-causal associations?
Abstract. Primary emissions of wood combustion are complex mixtures of hundreds or even over a thousand compounds, which pass through a series of chemical reactions and physical transformation processes in the atmosphere (aging). This aging process depends on atmospheric conditions, such as concentration of atmospheric oxidizing agents (OH radical, ozone and nitrate radicals), humidity and solar radiation, and is known to strongly affect the characteristics of atmospheric aerosols. However, there are only few models that are able to represent the aging of emissions during its lifetime in the atmosphere. In this work, we implemented a model (Model for aging of Emissions in environmental CHAm…
Codes and datasets related to https://doi.org/10.5194/gmd-2020-13
Codes and datasets related to https://doi.org/10.5194/gmd-2020-13, discussion paper.