In our recent Delve article, EPA’s Proposed Fenceline Monitoring Requirements for Synthetic Organic Chemical Manufacturing Industry (SOCMI) and Group I and II Polymers and Resins Industries, we explored the upcoming proposed changes in EPA's NSPS and NESHAP regulations, shedding light on the fenceline monitoring requirements for specific pollutants across the SOCMI and Polymer and Resins source categories Group I and II Polymers and Resins Industries. 

As the final rule is expected any day now, let's dive into the challenges that facilities commonly encounter in fenceline monitoring data collection and management.

1. Facilitating Data Exchange from Multiple Sources: Managing diverse data sources, including field measurements, meteorological data, laboratory analyses, and instrument logs, poses a significant challenge in ensuring seamless integration and accuracy throughout the fenceline monitoring process.

2. Inefficient Field Data Collection: The susceptibility to entry and transcription errors in manual processes for collecting field data, such as tube IDs, quality control (QC) samples, dates, times, locations, and comments, highlights a critical inefficiency compromising data accuracy and reliability.

3. Missing Meteorological Data: Laboratories need timely and accurate temperatures to calculate concentration-based results. Manual capture and communication of meteorological data (from on-site or airport stations) can be slow and subject to errors, delaying response time and reporting. 

4. Capturing Maintenance Activities: Properly documenting and correlating site activities with fenceline results can be difficult. However, incomplete information limits the ability to identify activities associated with elevated readings and respond accordingly.

5. Manual Data Analysis:  Without automation and visualization tools, reviewing and interpreting lab results, integrating them with weather data, and understanding patterns can be a time-consuming and resource-intensive manual process, especially on a biweekly basis.

6. Real-Time Data Integration and Near-Field Correction: While continuous real-time contaminant monitoring can pinpoint problem areas when they occur, integrating their data seamlessly with other fenceline monitoring systems can be challenging. Additionally, using real-time data for correcting reported concentrations can become extremely complex and requires robust data management infrastructure and expertise to reduce human error.

7. Data Validation: Inadequate data validation procedures can result in misinterpretations of high readings or errors in calculated results. Implementing comprehensive data validation protocols is crucial for data integrity and reliable decision-making.

8. Manual Quarterly Reporting: Gathering and compiling data points from various sources, ensuring accuracy and completeness, and manually preparing quarterly reports according to the EPA template can be monumental and time-consuming.

9. Tight Deadlines and Complicated Schedules: The new HON rule intensifies pressure on fenceline monitoring with multifaceted sampling requirements, making it challenging to adhere to unique schedules and QC protocols.

The Way Forward

Addressing these challenges and implementing strategic solutions can transform data into a powerful tool for informed decision-making and compliance. Streamlining collection, automating processes, and providing clear insights through data management solutions can significantly improve efficiency and accuracy.

Building upon our extensive experience since the implementation of the 2018 Refinery Sector Rule, Trihydro developed Fenceline Pro^TM. The software was designed to help facilities manage, analyze, and report fenceline monitoring data in compliance with EPA Clean Air Act regulations. With Fenceline Pro, air compliance teams can improve field data accuracy, track trends, identify contributing factors, and create an easily auditable process. 

Want to learn more about Fenceline Pro or talk to one of our air compliance specialists?