Two new rhizomorph-forming species within the family Omphalotaceae , Gymnopus fuscostipes sp. nov . and Pseudomarasmius brunneodiscus sp. nov ., are proposed based on morpho-molecular evidence. Both species are characterized by marasmioid basidiomata, brownish pileus, and black rhizomorphs. Detailed morphological descriptions, color photos, and illustrations are presented herein, as well as comparisons with closely related species.

Since the Industrial Revolution, anthropogenic activities, primarily fossil fuel combustion, have driven a sharp increase in ${\mathrm{CO}}_2$ emissions, making them the principal driver of global climate change. Precise monitoring and quantification of ${\mathrm{CO}}_2$ emissions are essential for effective greenhouse gas mitigation. Traditional “bottom-up” inventories often suffer from limited timeliness, low spatial resolution, and significant uncertainties. Satellite remote sensing offers an alternative “top-down” approach for emission estimation. Compared to existing ${\mathrm{CO}}_2$ sensors, ${\mathrm{NO}}_2$ observation satellites provide higher spatiotemporal resolution. Given that ${\mathrm{NO}}_2$ and ${\mathrm{CO}}_2$ are co-emitted during combustion with a stable relationship, ${\mathrm{NO}}_2$ can serve as an effective proxy to indirectly derive ${\mathrm{CO}}_2$ emissions. In this study, an exploratory framework for city-scale ${\mathrm{CO}}_2$ estimation was developed using TROPOMI ${\mathrm{NO}}_2$ column concentrations, MERRA-2 wind fields, EDGAR inventory and the ODIAC inventory. The analysis focused on seven major cities in Shandong Province, China, from April to September 2022. By integrating a wind-rotation technique with a line density model and the differential evolution (DE) algorithm, we derived ${\mathrm{NO}}_2$ emissions and atmospheric lifetimes. The ${\mathrm{NO}}_2{\mathrm{-to-CO}}_2$ relationship was established based on sector-weighted inventory data to quantify fossil-fuel ${\mathrm{CO}}_2$ fluxes. The results identify Qingdao, Jinan, and Linyi as emission hotspots, followed by Rizhao, with lower emissions observed in Yantai, Liaocheng, and Jining. Comparison with the ODIAC inventory illustrates that this framework provides a top-down constraint for identifying localized emission characteristics and potential discrepancies in bottom-up datasets. This study offers a complementary tool for near-real-time urban carbon monitoring during the non-heating season.