By Nidhi DhullReviewed by Susha Cheriyedath, M.Sc.Jul 16 2024A recent article published in Sustainability proposed a binary statistical method for highway construction, quantifying CO2 emissions for formulating a carbon reduction strategy. Considering the case of an expressway in central China, CO2 emissions from different construction activities were estimated.
Study: Quantifying CO2 Emissions in Highway Construction. Image Credit: MVolodymyr/Shutterstock.com
Background
CO2 is one of the main contributors to global climate change. Road infrastructure construction processes, including raw material production and transportation, road construction, maintenance, and recycling, are highly carbon-intensive and energy-demanding. Emissions from these activities contribute 5-25% of total CO2 emissions from the transport sector.
To comprehend the overall carbon emissions across the life-cycle of highway infrastructure, CO2 emissions from each process related to highway construction should be considered.
However, these are generally estimated based on engineering experience or the budgetary quota without accounting for other factors in actual projects such as the contractor, regional geology, construction plan, and engineering methods. CO2 emissions based on actual data are barely analyzed.
Thus, this study proposed a theoretical framework and statistical method to determine CO2 emissions from an entire highway construction process. It aimed to bridge the gap between real-world data statistics and improve carbon estimation accuracy for highway construction projects.
Methods
A highway construction system boundary was constrained to raw material production and on-site construction phases based on the life cycle assessment (LCA) theory. Additionally, per kilometer per lane (km-1·lane-1) was defined as the functional unit to compare different projects.
The proposed binary statistical method considered energy and material consumption from different engineering types (bridge, tunnel, subgrade, and pavement) to evaluate CO2 emissions from highway construction activities. The data were mainly derived from the project cost control and construction management systems for the whole building period.
CO2 emissions during highway construction (Q) were defined as the sum of those in material production (Q1) and on-site construction (Q2) phases. The former covered the entire material production process, including mining, processing, and manufacturing.
This data was derived from local studies conducted during similar years, considering appropriate factors such as source, technique, process, time, and location.
The on-site construction phase is comprised of CO2 generated from energy consumption by construction machinery/equipment. Thus, the data regarding CO2 emissions for different types of energy was based on the 2006 guidelines issued by the United Nations Intergovernmental Panel on Climate Change (IPCC).
A four-lane expressway in central China was selected as the case study to verify the applicability and data accuracy of the proposed binary statistical method for CO2 emission estimation. This project (total length: 121.714 km) was completed from 2011 to 2015.
Results and Discussion
The total CO2 emissions from the studied expressway were estimated at 10,605.2 tons km-1·lane-1, with material production accounting for the major component (95.2%) and the on-site construction phase having a minor component (4.8%).
In the raw material production phase, steel and cement production accounted for more than 99% of CO2 emissions. Thus, saving and recycling measures must be adopted when using steel and cement in highway construction. Accordingly, LCA should be implemented in design, waste materials recycled during construction, and traditional materials replaced with low-carbon materials.
Furthermore, bridges and tunnels exhibited higher emission values (97.7% and 94.3%, respectively) than subgrade (81.6%), pavement (80.2%), and ancillary facilities (88.5%). This was attributed to the extensive engineering required for constructing bridges and tunnels, which consume huge quantities of concrete and steel compared to other structures.
In the on-site construction phase, diesel and electricity energy consumption accounted for 90% of CO2 emissions, mainly during earthwork, subgrade protection, foundations, bridge engineering, superstructures, substructures, tunnel excavation, and pavement surfacing. Thus, adopting energy-saving measures can help further lower CO2 emissions.
These findings can enhance transportation agencies' understanding of road construction's impacts on climate change and provide useful inputs for policy-making by identifying carbon reduction opportunities. Overall, CO2 emission reduction efforts should be directed toward using recycled and low-carbon materials and enhancing work efficiency, machinery performance, and construction technology.
Conclusion and Future Prospects
The researchers comprehensively investigated the CO2 emissions from an entire highway infrastructure using the binary statistical framework based on LCA theory. The estimations made using real-world data regarding material and energy consumption validated the efficacy of the proposed theoretical framework.
Overall, the CO2 emissions for the entire expressway reached 10,605.2 tons km−1·lane−1, with the raw material production and on-site construction phases accounting for 95.2% and 4.8%, respectively.
The estimations made for each phase and component of the structure can help determine the exact emission contributions from different sources and identify the primary contributors.
This study focused only on expressways in central China. However, road construction conditions vary in different regions.
Thus, the authors suggest expanding the method to other case studies to elucidate their emission characteristics. Potential technological advancements or changes in construction practices to reduce CO2 emissions should be evaluated in the future.
Journal Reference
Gao, S., Liu, X., Lu, C., Zhang, H., Wang, X., & Kong, Y. (2024). Quantitative Analysis of Carbon Emissions from Highway Construction Based on Life Cycle Assessment. Sustainability, 16(14), 5897. doi: 10.3390/su16145897, https://www.mdpi.com/2071-1050/16/14/5897
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