MIT CSHub Releases Research Briefs on Embodied Emission of Concrete

The first research brief, Assessing the impact of overdesign on concrete embodied emissions, illustrates how overdesigning concrete mixtures for strength increases the embodied greenhouse gas (GHG) emissions associated with concrete mixtures. The brief is based on the analysis of 115,000 batch information of 30,000 unique mixtures from 57 plants in the U.S.

Mixtures were developed for specified strength between 3000 and 5000 psi. Excessive overdesign, relative to what is required by ACI 301, is quantified for more than 50% of the mixtures evaluated. The higher average strength of mixtures increases the embodied GHG and identifying and optimizing causes for the significant overdesign can achieve a reduction of greater than 80 kg CO2e / m3, a 25% reduction. These causes can be due to increased variability of strength test records that are impacted by variation in material characteristics, batching accuracy, quality control procedures and testing, and quality control procedures to monitor changes in concrete materials. This research brief can be accessed here.

The second research brief, Impact of compressive strength test variability on concrete embodied emissions, evaluates the impact of variations in strength acceptance testing of concrete on the embodied GHG of mixtures and the relative risk of failing acceptance criteria. The data evaluated are from 824 concrete loads for a specified strength of 4500 psi. Comparing results from different labs relative to testing by an internal lab with a low coefficient of variation of strength test results, external labs had varying levels of testing variation between 6 and 15%. The higher variation due to testing either causes concrete producers to target a higher strength to avoid low strength test results or increases the risk of failing the acceptance criteria.

The brief indicates that reducing the testing variability and reliable acceptance testing can result in a reduction of 40 kg CO2e / m3 of concrete mixtures. Suggestions are provided to reduce variability of acceptance testing. This research brief can be accessed here.