Comparing Standardized and Real-World Oil Combustion Emission Measurements | AIChE

Comparing Standardized and Real-World Oil Combustion Emission Measurements

One of the main focuses of the Energy Conversion Group at Brookhaven National
Laboratory is understanding and measuring emissions produced by heating and cooling
technologies, such as residential boilers. These appliances produce pollution such as carbon
dioxide and particulate matter, which are harmful to the environment. Residential boilers using
oil as fuel are common in the Northeastern United States, including New York, but the emission
rates for these appliances are outdated and need to be updated. To make these necessary updates,
we need to measure the pollutant emissions from such devices. To this end, a Dunkirk Empire II
boiler was operated using No.2 oil under two different circumstances. The first circumstance was
operating the boiler at constant high heat output (CHHO) the entire test. The second
circumstance was operating the boiler while it changes to different heat output levels by
adjusting the flowrate of the cooling water through the boiler. This second circumstance is called
cyclic operation and is more realistic than the standardized high output testing method. While the
boiler is operating it produces particulate emissions, we measure these particles using the Magee
Scientific Aethalometer® Model AE33, the TSI Optical Particle Sizer Model 3330, and the
California Analytical Instruments ZRE Gas Analyzer instruments, in order to characterize their
composition and size. From the measurements recorded by these instruments we concluded that
during cyclic operation, as the heat output decreased, the particulate matter and methane
emissions increased while the carbon dioxide emissions decreased from high output to
approximately 50% and 20% output. A trend was not necessarily concluded with the black
carbon emissions. As a result of my work, I furthered my confidence in a lab setting as I helped
operate the setup to collect emission data and learned Python coding to analyze the data to
deduct conclusions.