Evaluation and Comparison of Data Sources for Determining Industrial Fuel End Use: Mecs Vs. EPA GHG Reporting Program

Informed policy, business, and regulatory decisions related to energy efficiency and GHG mitigation require deep understanding of the energy consumption of industry. The US Department of Energy’s Manufacturing Energy Consumption Survey (MECS) data are frequently used as a reference since, to date, they are the most consistent and comprehensive source of data in the public domain on the energy consumption characteristics of US industry. However, the MECS data are based on surveys and are therefore subject to sampling and reporting errors.  The implication of these inherent errors is that many studies and projections of US industrial energy use and emissions are by nature uncertain.  Quantifying these uncertainties has been impossible to date since no separate independent database on industrial fuel use and emissions of similar depth and breadth to MECS has existed for comparison and calibration.  The situation has changed with the recent release of the US EPA’s Greenhouse Gas Reporting Program (GHGRP) database, which contains detailed fuel use and emissions data for all US industrial plants with annual CO2-equivalent emissions exceeding 25 kilotons.  In this presentation, we present the results of a study that quantifies the differences between these two databases, discuss the implications of these differences on our understanding of US industrial emissions and abatement potentials, and offer recommendations that can help substantially improve industrial fuel use and emissions data quality moving forward. 

In 2008, the US Congress issued a mandate for GHG emissions reporting.  As a result, in 2012 the US EPA first released the GHGRP data for reporting year 2010. Mandatory reporting gives the GHGRP an advantage over MECS because its data are based on measurements and engineering methods whereas data in MECS are often simply estimated by plant personnel.  Though the purpose of the GHGRP is to record and report GHG emissions, more detailed information in the database, such as fuel type and combustion unit capacity, allows for converting reported emissions into fuel use. We present here our structured method for converting reported emissions into fuel use data at the level of industrial end use technologies (e.g., boiler systems and process heating systems).  Our method involves the use of heuristics, engineering estimates, and independent data sources (such as the US EPA’s boiler MACT database and individual plant Title V air permits) to construct a picture of fuel end uses at each plant in the GHGRP database.  We then compare these end use data to those reported in the MECS data in order to quantify the differences and potential errors associated with MECS.  These results are useful for quantifying the uncertainties associated with previous studies and models that rely solely on MECS for industrial energy and emissions projections, including the US DOE’s Annual Energy Outlook, National Energy Modeling System (NEMS), the GCAM model (the main US model for climate change mitigation analysis), and many different industrial GHG emissions potentials studies. 

Our results for the US food industry will be shown as an example, which suggest differences of 20% (or more) between the end use data in MECS and the end use data derived from the GHGRP database.  Such differences have major implications for the accuracy of food industry energy analyses and projections.  We discuss the major differences between these data sources, which came to light via our structured approach.  We also offer recommendations for improving data collection and sharing within and between US government agencies to significantly improve the accuracy of industrial fuel use and GHG emissions data moving forward.  More accurate data will lead to better informed decisions and policies for industrial GHG emissions mitigation.