Estimating and comparing greenhouse gas emissions with their uncertainties using different methods: A case study for an energy supply utility

Abstract

Energy supply utilities release significant amounts of greenhouse gases (GHGs) into the atmosphere. It is essential to accurately estimate GHG emissions with their uncertainties, for reducing GHG emissions and mitigating climate change. GHG emissions can be calculated by an activity-based method (i.e., fuel consumption) and continuous emission measurement (CEM). In this study, GHG emissions such as CO 2 , CH 4 , and N 2 O are estimated for a heat generation utility, which uses bituminous coal as fuel, by applying both the activity-based method and CEM. CO 2 emissions by the activity-based method are 12-19% less than that by the CEM, while N 2 O and CH 4 emissions by the activity-based method are two orders of magnitude and 60% less than those by the CEM, respectively. Comparing GHG emissions (as CO 2 equivalent) from both methods, total GHG emissions by the activity-based methods are 12-27% lower than that by the CEM, as CO 2 and N 2 O emissions are lower than those by the CEM. Results from uncertainty estimation show that uncertainties in the GHG emissions by the activity-based methods range from 3.4% to about 20%, from 67% to 900%, and from about 70% to about 200% for CO 2 , N 2 O, and CH 4 , respectively, while uncertainties in the GHG emissions by the CEM range from 4% to 4.5%. For the activity-based methods, an uncertainty in the Intergovernmental Panel on Climate Change (IPCC) default net calorific value (NCV) is the major uncertainty contributor to CO 2 emissions, while an uncertainty in the IPCC default emission factor is the major uncertainty contributor to CH 4 and N 2 O emissions. For the CEM, an uncertainty in volumetric flow measurement, especially for the distribution of the volumetric flow rate in a stack, is the major uncertainty contributor to all GHG emissions, while uncertainties in concentration measurements contribute a little to uncertainties in the GHG emissions. Implications: Energy supply utilities contribute a significant portion of the global greenhouse gas (GHG) emissions. It is important to accurately estimate GHG emissions with their uncertainties for reducing GHG emissions and mitigating climate change. GHG emissions can be estimated by an activity-based method and by continuous emission measurement (CEM), yet little study has been done to calculate GHG emissions with uncertainty analysis. This study estimates GHG emissions and their uncertainties, and also identifies major uncertainty contributors for each method.

Uncertainty analysis of stack gas flow measurements with an S-type Pitot tube for estimating greenhouse gas emissions using a continuous emission monitoring system

“…Human activities are responsible for nearly all of the increase in the level of anthropogenic greenhouse gas (GHG) in the atmosphere over the last 150 years [1]. In particular, the increasing rate of GHG emissions from the combustion of fossil fuels, such as carbon dioxide (CO 2 ), methane (CH 4 ) and nitrous oxide (N 2 O), has been linked to climate change by assessments of the average global temperature rise [2][3][4]. Under the United Nations Framework Convention on Climate Change (UNFCCC) with the recent Paris Agreement, international efforts to mitigate climate change are being conducted in countries with a high proportion of GHG emissions arising from their energy and industrial fields, such as heavy industries, the petrochemical industry, and power plants [5][6][7].…”

“…CEMS directly measures GHG emissions by measuring the GHG concentrations and volumetric flow rates of flue gases in smokestacks. Recent studies have examined the accuracy levels of the two estimating methods to support GHG emissions reduction strategies [3,[8][9][10][11]. Comparisons of the methods in an effort to match the energy and industrial sources showed large discrepancies mainly stemming from the level of uncertainty in CEMS measurements [8,9].…”

Abnormal Data Screening Method of Thermal Power Based on BP Neural Network Algorithm

“…In addition to the emission factor method, in developed countries such as U.S. CO2 form coal-fired plants can be calculated from flue gas composition and volume measurements made by Continuous Emission Monitoring Systems (CEMS), which is named as CEMS method [3][4][5] . It has been proved that the CO2 emissions measured by CEMS method are more accurate than those calculated by emission factor method [5][6][7] .…”

Customized Approach to Greenhouse Gas Emissions Calculations in Railway Freight Transport

“…Supply chain logistic pooling consists of several independent companies sharing logistic activities and can be initiated for environmental reasons to optimize transportation and reduce the companies' GHG emissions [37,38]. Lee et al [39] stated that it is important to accurately estimate GHG emissions with their uncertainties to reduce GHG emissions and mitigate climate change. GHG emission calculators are useful tools for estimating GHG emissions and for providing information that can help to develop behavioral and policy change [40,41].…”