Real-time emissions from construction equipment compared with model predictions: Fid-Bau Portal

Real-time emissions from construction equipment compared with model predictions

Heidari, Bardia / Marr, Linsey C.

The construction industry is a large source of greenhouse gases and other air pollutants. Measuring and monitoring real-time emissions will provide practitioners with information to assess environmental impacts and improve the sustainability of construction. We employed a portable emission measurement system (PEMS) for real-time measurement of carbon dioxide (CO₂), nitrogen oxides (NO_x), hydrocarbon, and carbon monoxide (CO) emissions from construction equipment to derive emission rates (mass of pollutant emitted per unit time) and emission factors (mass of pollutant emitted per unit volume of fuel consumed) under real-world operating conditions. Measurements were compared with emissions predicted by methodologies used in three models: NONROAD2008, OFFROAD2011, and a modal statistical model. Measured emission rates agreed with model predictions for some pieces of equipment but were up to 100 times lower for others. Much of the difference was driven by lower fuel consumption rates than predicted. Emission factors during idling and hauling were significantly different from each other and from those of other moving activities, such as digging and dumping. It appears that operating conditions introduce considerable variability in emission factors. Results of this research will aid researchers and practitioners in improving current emission estimation techniques, frameworks, and databases.

Implications: Construction equipment is an important source of air pollutant emissions. There are large uncertainties in estimates of emissions from construction equipment, partly due to the small number of published measurements. The authors have expanded the database by measuring emissions of CO₂, NO_x, hydrocarbons, and CO from construction equipment under actual operating conditions on-site. There were large discrepancies between measured emissions and those predicted by models, including NONROAD and OFFROAD. Emission factors associated with idling and hauling were significantly different from each other and from those of other activities. These results can be used to improve the next generation of emission estimation models.