Xiaoliang Ma shares his thoughts on the development of an accurate model to evaluate the emissions from construction machinery in different construction operations, in conjunction with the Construction Climate Challenge initiative.
Environmental consequences from construction sites is a topic of increasing concern. In 2015, one of the CCC Initiative pre-studies took a closer look into the subject of emissions evaluation from construction machinery.
According to Xiaoliang Ma, Associate Professor and group leader at System Simulation & Control, Department of Transport Science at KTH Royal Institute of Technology, there is a lack of scientific knowledge in this area. In particular, he believes that the industry needs to make an effort to find effective ways to estimate emissions during construction operations.
“Obviously, more experiments are required and more data is needed to be collected in relation to CO2, fuel efficiency etcetera. It’s not easy to go further,” Xiaoliang says.
But him and his team of researchers did go further. They set about developing an emission model that could be applied to evaluate emissions from construction machines during different operations. In addition to this, they investigated a construction case regarding the emissions from a wheel loader, where they could describe the construction process using computer models.
“We developed a NOx (nitrogen oxide) emission model for the construction machine’s diesel engine using experimental data. In the mean time, case studies were carried out to model the construction operations. A prototype computer model was developed to describe the construction processes,” Xiaoliang explains.
The final stage of the research project was devoted to a discrete-event simulation (DES), which was developed to simulate the construction case. The study provided a basis for future integration of emission models with the DES simulation, so technically it should be possible to assess fuel efficiency and environmental impacts from different construction operations in reality.
R:?Do you think there is enough investigation into how construction machines can reduce the CO2?emissions?
X:?No, the current research still focuses on NOx, known as the main gas emissions from diesel engines that are very harmful to human health. CO2?sensors were not deployed in our experiment, though we collected detailed fuel consumption data, which is highly correlated to CO2.
R:?Was there anything that surprised you with your findings?
X:?The main unexpected result is that we can get so much data that is normally expensive to collect. This is due to the support from our Chinese partners and they have a relevant project funded by Chinese National Science Foundation. The pre-study indeed helps us enhance the collaboration. The research result is quite promising.
R:?What are your thoughts on eco-driving as a way to reduce emissions?
X:?Operational behavior has obviously effects on emissions. We actually collected emissions data produced from different machine operators when operating the same driving cycle.
R:?What would you say the most important findings of your study were?
X:?I think our approach to quantify the emissions during the construction process is an important finding. When we attended and presented our research result in the Transportation Research Board’s (TRB) annual meeting in the US in January, we found that our colleagues in EPA are working in the same direction, which was quite encouraging.
R:?Are you planning on continuing the research?
X:?Even though we finished the report, we are still working on the topics in collaboration with our partners. I feel quite excited to be part of this initiative. There are still lots to do to achieve our goals of reducing emissions and improving energy efficiency for construction operations. However, I believe we are on track.
R:?What do you think is really important for the construction industry right now?
X:?I think all players in the industry should recognize that this is serious and strategic, and it is time that everyone should start acting. Sustainability has to be implemented with emerging technologies.