GIS-Based Approach to Spatio-Temporal Interpolation of Atmospheric CO2 Concentrations in Limited Monitoring Dataset

Understanding the magnitude and distribution of mixes near-ground carbon dioxide (CO2) components spatially (related to surface characteristics) temporally (over seasonal timescales) is critical evaluating present future climate impacts. Thus, application in situ measurement approaches, combined with spatial interpolation methods, will help explore variations source contribution total CO2 mixing ratios urban atmosphere. This study presents characteristic temporal trend atmospheric levels observed within city Wroclaw, Poland for July 2017–August 2018 period. The variability around was directly measured at selected sites using flask sampling a Picarro G2201-I Cavity Ring-Down Spectroscopy (CRDS) technique. current work aimed determining accuracy techniques adjusting parameters estimating time series/seasonal terms limited observations during vegetation non-vegetation periods. objective evaluate how different methods affect assessment air pollutant environment identify optimal strategy. discusses schemes optimization results that may be adopted areas where no are available, which based on kriging error predictions an appropriate density locations. Finally, were extended regarding average prediction bias by exploring additional experimental configurations introducing limitation strategy representation area.