Enhancing Formaldehyde (HCHO) Characterization over Michigan by Merging High-Resolution TEMPO Retrievals with Ground-Based Measurements

This study presents a novel methodology for merging high-resolution TEMPO (Tropospheric Emissions: Monitoring of Pollution) satellite formaldehyde (HCHO) retrievals with EPA ground-based measurements to create an enhanced HCHO dataset over Southeast Michigan. We utilize data from six EPA monitoring sites across four counties: Kalamazoo, Kent, Macomb, and Wayne, leveraging the strengths of both satellite and ground-based observations to provide a comprehensive characterization of HCHO distributions and temporal evolution in the region.

Our approach combines TEMPO's Level 3 gridded HCHO product (0.02° x 0.02° resolution) with EPA 24-hour formaldehyde measurements collected using DNPH cartridge sampling with ozone scrubbing, followed by high-performance liquid chromatography (HPLC) with ultraviolet detection. We employ spatial matching techniques to extract TEMPO HCHO values at grid cells containing EPA monitoring sites. Temporal merging is achieved by distributing daily EPA values at higher frequencies using TEMPO's sub-hourly sampling, creating diurnal profiles that capture fine-scale temporal variations.

To generate continuous HCHO surfaces, we apply the Inverse Distance Weighting (IDW) interpolation technique, adapting the method used by Al-Hamdan et al. (2009) for PM2.5 estimation. This allows us to create spatially continuous HCHO maps that integrate both satellite and ground-based observations across the study area.

Our merged product incorporates auxiliary meteorological data to investigate the relationships between HCHO concentrations and environmental factors at different temporal scales. Additionally, we conduct a comprehensive uncertainty analysis, propagating errors from both TEMPO retrievals and EPA measurements to assess the robustness of our merged dataset.

Preliminary results demonstrate the potential of this merged product to provide accurate and spatially continuous HCHO characterization over Southeast Michigan. This approach offers new insights into the temporal patterns and drivers of HCHO variability, contributing to a better understanding of HCHO dynamics and informing air quality management strategies in the region.