Diagnostic Ratios and Isotopic Fingerprints of Vehicular Ammonia Across Emission Standards via Dynamometer Chassis Experiments
Diagnostic ratio and isotopic fingerprint hold exceptional promise for improving emission estimates and source attribution of fugitive and complex ammonia (NH<sub>3</sub>) emissions in urban atmospheres. However, systematic research linking these markers specifically to vehicular NH<sub>3</sub> tailpipe emissions across evolving emission standards remains elusive. Here, 12 light-duty gasoline vehicles spanning Euro-3 to Euro-6 emission standards were tested under both cold- and hot-start conditions using a dynamometer chassis. Instantaneous emissions of NH<sub>3</sub>, and coemitted pollutants were comprehensively measured to explore potential diagnostic ratios, while concurrently collecting tailpipe NH<sub>3</sub> for isotopic analysis (<i>δ</i><sup>15</sup>N-NH<sub>3</sub>). We found that both NH<sub>3</sub>/CO<sub>2</sub> diagnostic ratios and δ<sup>15</sup>N-NH<sub>3</sub> values are highly dependent on the emission standard. NH<sub>3</sub>/CO<sub>2</sub> diagnostic ratios varied significantly from 0.07 (Euro 6) to 0.54 ppbv/ppmv (Euro 5), while <i>δ</i><sup>15</sup>N-NH<sub>3</sub> values remained relatively stable for Euro-3 (-1.5 ± 9.2‰), Euro-4 (-1.0 ± 13.3‰), and Euro-5 vehicles (-5.8 ± 7.3‰), but showed significant <sup>15</sup>N depletion (-13.7 ± 7.0‰) Euro 6 vehicles with ultralow emissions. These findings demonstrate that static assumptions for these markers are inadequate for accurately modeling emissions from modern, evolving vehicle fleets. We thus propose a dynamic framework that utilizes these emission-standard-specific fingerprints to enable precise quantification of city-specific and technology-based vehicular NH<sub>3</sub> emissions and their contribution to the urban NH<sub>3</sub> budget.
Authors
- Jun Kun Lu (ORCID: https://orcid.org/0000-0001-9759-0227)
- Cheng Huang (ORCID: https://orcid.org/0000-0001-9518-3628)
- Haifeng Yu (ORCID: https://orcid.org/0009-0009-2716-1051)
- Qingyao Hu (ORCID: https://orcid.org/0000-0003-4579-445X)
- Lin Cheng (ORCID: https://orcid.org/0000-0002-6868-1493)
- Yunhua Chang (ORCID: https://orcid.org/0000-0002-1622-5330)
- Hongli Wang (ORCID: https://orcid.org/0000-0003-0655-3389)
- Yuanjian Yang (ORCID: https://orcid.org/0000-0003-3486-6286)
Institutions
- Nanjing University of Information Science and Technology (CN)
- Prediction Systems (United States) (US)
- Shanghai Academy of Environmental Sciences (CN)
Publication Details
- Journal
- Environmental Science & Technology
- Published
- 2025-10-20
- DOI
- https://doi.org/10.1021/acs.est.5c11609
- Citations
- 1
- Primary Topic
- Vehicle emissions and performance
- Type
- article
- Field-Weighted Citation Impact
- 0.68