Data Quality and Sample Planning to Develop Credible Emissions Estimates

Companies and governments worldwide are facing mounting pressure to reduce emissions from methane, a potent climate pollutant. Yet, the landscape of methane emissions monitoring is rapidly evolving, unveiling numerous innovative technologies — from satellites to handheld sensors. These tools hold the promise of developing more accurate estimates of actual emissions, shifting away from conventional inventory calculations toward measurement-based inventories. As the energy industry embraces these transformative monitoring technologies, a flood of measurement data is being amassed at an unprecedented pace. Amidst this wealth of information, an important question arises: Is more data necessarily better or more meaningful than quality data?

While direct measurements are necessary for creating measurement-based inventories, they are not sufficient to develop credible measurement-based inventories. Unlocking insights from new technologies depends on the deployment method, quality control, and approach to analysis. A thoughtful and systematic approach that includes data quality and sample planning is essential for developing reliable, accurate inventory estimates from monitoring and measurement data.

Data Quality is the Foundation for Credible Estimation and Decision Making

Data quality extends beyond mere measurement accuracy and technological capabilities. It entails holistic thinking that considers the intended applications of measurement campaign results and data analysis. Data quality encompasses the quality and quantity of measurements and other data sources required to support and improve the resulting estimates.

High-quality data is paramount to enabling comparisons of emissions estimates over time, and serves as a critical tool in verifying companies’ and governments’ achievements in meeting ESG goals. Such data can identify unknown emissions and evaluate emissions trends, inform repairs, and support optimal emissions mitigation strategies.

That said, obtaining high-quality data can present its fair share of challenges. Factors that come into play encompass the capabilities of emissions monitoring technology, including detection, localization, and quantification. Additionally, considerations such as cost, deployment feasibility, and the extent of spatial and temporal coverage further contribute to its complexity.

Data Quality Objectives and Sample Planning

The good news is that achieving high-quality data and accurate emissions estimates is possible through the implementation of data quality objectives, which are a sample planning tool developed by the U.S. Environmental Protection Agency to determine the “type, quantity, and quality of data needed to reach defensible decisions or make credible estimates.” By defining data quality objectives, purposeful measurements can be taken to support the goals of the sampling campaign, ensuring that the collected data are representative and reliable.

Sample planning using data quality objectives involves a series of steps — identifying the study’s goals, evaluating measurement needs and sampling methods, specifying analytical approaches, and establishing sampling protocols. These steps ensure that the survey collects an appropriate number of samples, attains representative asset coverage, and provides a tolerable level of estimation uncertainty. Employing standardized sampling protocols fosters consistency and standardization across measurements and the ability to compare estimates over time and across locations, ultimately enhancing the overall reliability and quality of the data.

GTI Energy’s Expertise in Developing Credible Emissions Estimates

At GTI Energy, we assist operators and others looking to reduce emissions to create credible and actionable methane emissions inventories through data quality objectives and sample planning. For example, the Veritas protocols are a sample planning tool designed to aid operators in estimating their methane emissions intensity. When paired with data quality objectives, the Veritas framework furnishes operators with resource-effective guidance to develop accurate and actionable methane emissions estimates. GTI Energy also takes a leading or collaborative role in four U.S. Department of Energy awards to estimate methane emissions, develop an integrated methane monitoring platform, and expand a surface-based monitoring network. These efforts expand beyond methane to encompass hydrogen emissions as well.

As the world continues to navigate the pathway to credible, measurement-based emissions inventories, GTI Energy’s team of experts and resources stand ready to lend their support.