A ground‑based spectrometer network to estimate net carbon dioxide and methane emissions from the City of Edinburgh

Abstract. Progress towards net‑zero targets depends on independent verification of urban greenhouse gas emissions. Cities account for ~75% of energy‑related CO2 emissions, yet their quantification remains challenging due to spatially complex sources, heterogeneous meteorology, and limited observation coverage. We deploy seven EM27/SUN ground‑based Fourier‑transform spectrometers, within weatherproof enclosures, across the City of Edinburgh to measure column‑integrated carbon dioxide, methane and carbon monoxide (XCO2, XCH4, XCO), which are less sensitive than in situ sensors to highly localised surface signals. A comprehensive calibration and quality-control framework leads to inter‑instrument precision of 0.26–0.62 ppb for XCH4 and 0.05–0.07 ppm for XCO2. The influence of the weatherproof enclosure dome on XCO2 and XCH4 retrievals is negligible but introduces a correctable XCO bias. City-wide observations reveal clear seasonal cycles and detectable intra-city gradients, with XCH4 showing consistent upwind-downwind behaviour, while XCO2 and XCO are strongly influenced by background variability and atmospheric transport. Comparison with the ICON-ART mesoscale model (6.5 km resolution) shows that total column variability is dominated by background conditions, with anthropogenic contributions typically < 0.2–0.3 ppm. These signals exceed model minus observation differences in only ~5% of cases, highlighting the challenge of isolating urban emissions from column measurements. Overall, our results demonstrate that dense column networks provide robust, scalable constraints on urban greenhouse gas emission estimates and valuable validation for atmospheric transport models and satellite retrievals, forming a foundation for inverse modelling with the UK-wide network of similar instruments.

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Published
2026-10-27
DOI
https://doi.org/10.5194/egusphere-2026-4832
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
preprint

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preprint

A ground‑based spectrometer network to estimate net carbon dioxide and methane emissions from the City of Edinburgh

Neil Humpage, Robbie Ramsay, Douglas Finch, Paul I. Palmer et al.
Atmospheric and Environmental Gas Dynamics
preprint

A ground‑based spectrometer network to estimate net carbon dioxide and methane emissions from the City of Edinburgh

Neil Humpage, Robbie Ramsay, Douglas Finch, Paul I. Palmer, Jerome Woodwark, Nikolai Ponomarev, William Morrison
preprint en

Abstract

Abstract. Progress towards net‑zero targets depends on independent verification of urban greenhouse gas emissions. Cities account for ~75% of energy‑related CO2 emissions, yet their quantification remains challenging due to spatially complex sources, heterogeneous meteorology, and limited observation coverage. We deploy seven EM27/SUN ground‑based Fourier‑transform spectrometers, within weatherproof enclosures, across the City of Edinburgh to measure column‑integrated carbon dioxide, methane and carbon monoxide (XCO2, XCH4, XCO), which are less sensitive than in situ sensors to highly localised surface signals. A comprehensive calibration and quality-control framework leads to inter‑instrument precision of 0.26–0.62 ppb for XCH4 and 0.05–0.07 ppm for XCO2. The influence of the weatherproof enclosure dome on XCO2 and XCH4 retrievals is negligible but introduces a correctable XCO bias. City-wide observations reveal clear seasonal cycles and detectable intra-city gradients, with XCH4 showing consistent upwind-downwind behaviour, while XCO2 and XCO are strongly influenced by background variability and atmospheric transport. Comparison with the ICON-ART mesoscale model (6.5 km resolution) shows that total column variability is dominated by background conditions, with anthropogenic contributions typically < 0.2–0.3 ppm. These signals exceed model minus observation differences in only ~5% of cases, highlighting the challenge of isolating urban emissions from column measurements. Overall, our results demonstrate that dense column networks provide robust, scalable constraints on urban greenhouse gas emission estimates and valuable validation for atmospheric transport models and satellite retrievals, forming a foundation for inverse modelling with the UK-wide network of similar instruments.

Natural Environment Research Council (GB), University of Leicester (GB), National Centre for Earth Observation (GB), University of Edinburgh (GB)
Queen Margaret University, Àrainneachd Eachdraidheil Alba, University of Edinburgh, College of Science and Engineering, University of Minnesota, National Centre for Earth Observation
Climate action, Sustainable cities and communities
Atmospheric and Environmental Gas Dynamics
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