Applications: Emission event reconstruction, state implementation plans, etc.

TRACER modeling produces ambient concentration predictions with high spatial, temporal, and chemical specificity. This allows for detailed comparisons with ambient measurements to conduct source attribution or identify large, non-routine emission events unidentified by the emissions model. High specificality also allows for granular impact assessments (e.g., “what if” scenarios relevant to state implementation plans).

Reference: Source Attribution of Elevated Ethane Concentrations Detected by Regional Monitors in Oil and Gas Production Regions

Figure reproduced from Graves, et al. (2025) licensed under CC-BY-NC-ND.

The TRACER framework is modular and can accommodate a variety of modeling approaches, enabling the use of methods that are fit-for-purpose in many applications. TRACER methods have been used to develop inventories for dispersion and chemical transport models and, using the predictions from these models, to evaluate local and regional source impacts on ambient concentrations. These predictions have been used to evaluate potential sources of seasonal emission patterns observed in the oil and gas supply chain.

Reference: Source attribution of seasonal variations in light alkane emissions from oil and gas operations in the Permian Basin

Figure reproduced from Chen, et al. (2026) under Creative Commons license CC BY

Applications: health-effects studies, demonstrating attainment for National Ambient Air Quality Standards (NAAQS)

TRACER predictions can be downscaled to various spatial and temporal resolutions for studies interested in longer-term averages or spatially variable impacts

Applications: demonstrating attainment for National Ambient Air Quality Standards (NAAQS), environmental justice studies, evaluating emissions inventories

Coarse emissions datasets can be combined with operational information to upscale emissions estimates in space and time. These distributions can be combined with chemical transport models to evaluate the impact of aggregating emissions at various spatial and temporal scales on predicted distributions of secondary pollutant (e.g. ozone) concentrations.

Reference: Fine Scale Spatial and Temporal Allocation of NOx Emissions from Unconventional Oil and Gas Development Can Result in Increased Predicted Regional Ozone Formation

Figure reproduced from Modi, et al. (2024) licensed under CC-BY-NC-ND.