Table · dataset · 2026
Breaking the “Measure-Model-Optimize” Bottleneck: A High-Resolution Spatial Framework for Reliable Wastewater Greenhouse Gas Management
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Non-CO<sub>2</sub> greenhouse gas (GHG) emissions from urban wastewater resource recovery facilities (WRRFs) are spatially heterogeneous at the meter scale, introducing large uncertainties in national inventories and process-level control.
Description
We establish SMART-GHG (Spatially explicit Monitoring, Assessment, and Reduction Technology for Greenhouse Gas management), combining unmanned-aerial-vehicle (UAV) concentration mapping with floating-chamber flux measurements to reconstruct continuous CH<sub>4</sub> and N<sub>2</sub>O emission fields.
The framework quantifies sampling requirements and validates an activated-sludge model as a facility-specific digital twin. At a full-scale anaerobic/anoxic/oxic WRRF (300,000 m<sup>3</sup> d<sup>–1</sup>), seasonal surveys of the monitored basin in one of four parallel treatment trains yielded CH<sub>4</sub> emissions of 3.15–13.08 kg d<sup>–1</sup>, dominated by influent stripping, and N<sub>2</sub>O emissions of 4.74–28.64 kg d<sup>–1</sup>, with mid-train peaks corresponding to aeration transitions.
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Numerical sub-sampling indicated that stable emission estimates required approximately 30 measurement points per lane (5 m spacing) in this basin; sparser sampling induced errors up to ±30%. Validation against longitudinal dissolved-oxygen and nitrogen profiles yielded mean absolute percentage errors of 3.6–17.5%. Model-guided optimization of zoned dissolved-oxygen set points predicted approximately 12% lower N<sub>2</sub>O emissions and 9% lower aeration energy use than a simulated conventional-aeration baseline, while maintaining effluent compliance in the model.
SMART-GHG supports spatially explicit emission inventories and model-based aeration optimization in WRRFs.
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Where it is published
- DOI doi.org/10.1021/acs.est.6c09219.s001 ↗
DOI / persistent id · from zivahub uct ac za
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from zivahub uct ac za
Topics
- From keywords
- Astronomy & Astrophysics · Chemistry · Earth & Environmental Science · Ecology · Life Sciences · Medicine & Health · Plant biology
- Inferred from text
- Longitudinal study 65%
Provenance · 1 source records, 13 field assertions
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|---|---|---|---|
| ZivaHub | oai:figshare.com:article/34022531 | 12 d ago | JSON v1 |
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| license | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/rights |
| publication_date | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| title | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/title |