Peter Zemek 7 min read
EPA ICRs and Consent Decrees: Understanding SOF Requirements and Measurement Options
Contributors
Peter Zemek
With over 38 years of experience in environmental, industrial, and process engineering, Dr. Peter Zemek is a recognized leader in emerging contaminant technologies, including PFAS detection and carbon capture. A patent-holding scientist and strategic executive, Peter has led global initiatives in air, soil, and groundwater monitoring, developed cutting-edge spectrometry platforms, and spearheaded regulatory innovations. His work spans technical leadership, M&A strategy, and international client engagement, with successful deployments in over a dozen countries. At RJ Lee Group, he drives innovation in VOC testing, litigation support, and advanced analytical services, helping clients navigate complex compliance landscapes with science-backed solutions.
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Facilities subject to EPA Section 114 Information Collection Requests (ICRs) or Consent Decrees involving air emissions may be asked to deploy Solar Occultation Flux (SOF) monitoring as part of a fenceline measurement strategy.
Before implementing any monitoring approach, it is important to understand what information EPA is seeking, how various measurement technologies generate data, and whether the resulting emissions estimates are scientifically appropriate and fit for regulatory, compliance, and legal purposes.
This is not a question of compliance versus non-compliance—it is about selecting measurement methods that align with regulatory intent, data quality objectives, and long‑term defensibility.

Overview of SOF-Based Fenceline Monitoring
Solar Occultation Flux (SOF) techniques, including open-path FTIR and UV‑DOAS, are designed to estimate emissions by measuring path‑integrated atmospheric concentrations across a facility boundary and combining those measurements with meteorological models.
In certain contexts, SOF approaches can provide screening‑level or comparative insights. However, when applied to ground‑level fenceline monitoring under regulatory frameworks, there are important scientific characteristics to understand.
Key Scientific Considerations with SOF Approaches
When SOF techniques are used to estimate facility emissions, the resulting data are influenced by several underlying assumptions:
- Model-dependent outputs, rather than direct empirical measurements
- Path-integrated column data, not source‑specific emission measurements
- High sensitivity to atmospheric variables, including wind fields, mixing height, and plume dispersion
- Limited ability to distinguish individual equipment or unit-level sources (e.g., tanks, process units, valves)
- Operational constraints, such as reliance on sunlight and favorable atmospheric conditions
As a result, SOF-derived flux values typically represent integrated emissions across an area, rather than quantified emission factors at the source level.
This distinction matters because many EPA regulatory programs, consent decree terms, and enforcement proceedings ultimately rely on source‑specific, method-based emission data.
Regulatory and Data Quality Implications
From a regulatory perspective, the challenge is not whether SOF produces data—but how that data can be used and interpreted. Facilities relying solely on modeled, integrated flux estimates may face challenges related to:
- Reproducibility and uncertainty when results vary with meteorological assumptions
- Attribution, when emissions cannot be definitively linked to specific units or equipment
- Alignment with EPA reference methods and established QA/QC frameworks
- Downstream use of data in enforcement actions, audits, or litigation
Once submitted, emissions data often become part of a permanent regulatory record, making early decisions about measurement strategy especially important.
An Empirical, Source-Resolved Measurement Complement
To support EPA’s core objectives—accurate emissions characterization, transparency, and defensible data—many facilities incorporate empirical, source-resolved measurement techniques alongside or in place of integrated flux monitoring.
RJ Lee Group specializes in direct, empirical air emissions measurement strategies designed to produce:
- Source-specific benzene emission factors
- Equipment- and unit-level resolution (tanks, refinery assets, process units)
- Alignment with EPA reference methods and QA/QC expectations
- Data suitable for regulatory reporting, consent decree compliance, and expert review
These approaches focus on measured data rather than modeled approximations, supporting clearer attribution and higher confidence in reported results.

Why Measurement Strategy Matters
Across regulatory, compliance, and legal settings, decision-makers consistently prioritize:
- Measured values over inferred estimates
- Documented QA/QC over atmospheric assumptions
- Source-resolved attribution over integrated flux values
A measurement strategy that reflects these priorities helps facilities meet regulatory expectations while reducing future uncertainty and risk. Facilities subject to EPA ICRs or consent decree requirements often have flexibility in how measurement objectives are achieved, provided the resulting data are robust, transparent, and scientifically defensible.
RJ Lee Group works with facilities that:
- Need to evaluate monitoring requirements within ICRs or consent decrees
- Want to validate or contextualize SOF-derived flux estimates
- Require high-confidence benzene emission factors
- Are preparing for regulatory discussions, audits, or expert review
Our Environmental Forensics & Advanced Air Measurement expertise includes:
- Empirical flux and source‑level measurement specialists
- PTR‑TOF‑MS and advanced analytical platforms
- Extensive experience supporting regulatory compliance and expert testimony
Take a Proactive, Science‑Aligned Approach
If SOF monitoring has been proposed or required for your facility, understanding the scientific strengths and limitations of each measurement option is essential.
Contact RJ Lee Group to discuss how an empirical, defensible measurement strategy can support compliance objectives—while ensuring the data you generate stands up to technical and regulatory scrutiny.



