ArticleACS ES&T air2026
Insights from the Convolution of Emission Inventories with Flux Footprints from Tall Eddy Covariance Towers at Three European Cities.
Article in ACS ES&T air, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Climate change is primarily driven by anthropogenic emissions of greenhouse gases. Reducing these emissions globally requires a massive effort at the individual, city, and national scales. Urban areas are hotspots of anthropogenic emissions, given the high density of human-based activities, and clarity on the variations of emissions in these areas will enable effective targeted reduction plans. However, efforts to do so are hampered by a lack of direct measurements of temporal and spatial trends of the emissions. This study combines emission inventories with flux observations and footprint modeling in three pilot sites for urban emission studies (Zurich, Munich, and Paris) with a focus on carbon dioxide (CO
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