Data fusion of modelled and-measured deposition in the U.S. and Canada, part I: Description of methodology and validation of wet deposition of sulfur and nitrogen

Abstract

This study constitutes Part I of the ADAGIO project (Atmospheric Deposition Analysis Generated by Integrating Observations into model), initiated by Environment and Climate Change Canada (ECCC) to improve the accuracy of sulfur (S), nitrogen (N), and ozone deposition estimates across Canada and the United States. Using deterministic data fusion, it combines numerical models and ground-level observations to generate seasonal objective analyses (OAs) for twelve chemical species, including gases, particulates, and precipitation species, over multiple years (2010, 2013, 2014, 2015, 2016, 2019). OAs are computed seasonally to enable high-resolution estimates of annual total deposition, validate air quality models, assess model errors, and evaluate ecosystem impacts, such as acidification and eutrophication. ADAGIO employs Optimal Interpolation, optimized through sensitivity tests, to integrate measurements with archived outputs from ECCC’s GEM-MACH regional air quality model. The ADAGIO project spans three papers, addressing wet deposition (pollutants in precipitation), dry deposition (gas and particles deposited onto surfaces), and total annual deposition (wet and dry combined). Objectives of ADAGIO include deriving total annual N and S deposition over North America and comparing seasonal OAs with model outputs to identify biases and errors. Part I, presented here, focuses on wet deposition and represents the first application of optimal interpolation for fusing wet deposition estimates with observational data over a continental scale. This innovative approach using OI marks a significant advancement in deposition data fusion methodologies over North America