Once the tide recedes and leaves a significant amount of stranded seaweed on the coast, marine macroalgae pose a serious threat to the surrounding area. Through this work, we considered a large-scale application of stranded macroalgae in building construction. For the first time we studied the impact of incorporating Sargassum mitucum seaweed fiber in replacement of flax fiber used for a standard structural cob. Thus, cob specimens were elaborated and analyzed to evaluate their compressive and hygrothermal performances. It was found that the compressive strength and water vapor resistance factors of cob decreased with the algae content. Additionally, the obtained results showed that a cob made with Sargassum muticum algae presented better thermal (insulation and inertia) and hygroscopic properties than those of a cob made with a flax fiber. Indeed, the replacement of flax straw by algae lead to a reduction in the thermal conductivity by 38% when compared to the standard cob with 2.5% of flax straw fiber. Consequently, numerical simulation showed a reduction in the energy needs in buildings made with an algae-based cob when compared to those made with a flax-based cob. This study can contribute to a global environmental and economic issue, i.e., the valorization of brown algae on a large scale. Indeed, the worldwide knows the largest sea of sargassum algae extent measures over 8850 km². This huge mass of brownish algae is expanding every year, which now covers an area from Africa to the Caribbean. It weighs more than 20 million tons and extends from the Gulf of Mexico to the west coast of Africa. We show that stranded algae, which are considered as wastes, have the ability to improve the mechanical and hygrothermal performance of cob-based material.

The French gravel industry produces approximatively 6.5 million tons of gravel wash mud each year. This material offers very promising properties which require an in-depth characterization study before its use as a construction material, otherwise it is removed from value cycles by disposal in landfills. We examined the suitability of gravel wash mud and seashells, with fly ash as a binder, as an unfired earth construction material. Thermal and mechanical characterizations of the smart mixture composed of gravel wash mud, Crepidula fornicata shells and fly ash are performed. The new specimens exhibit high compressive strengths compared to usual earth construction materials, which appears as a good opportunity for a reduction in the thickness of walls. The use of fly ash and Crepidula shells in addition to gravel wash mud provides high silica and calcium contents, which both react with clay, leading to the formation of tobermorite and Al-tobermorite as a result of a pozzolanic reaction. Considering the reduction in porosity and improvements in strength, these new materials are good candidates to contribute significantly to the Sustainable Development Goals (SDGs) and reduce carbon emissions.

The adverse environmental impacts of building materials can be achieved by reducing the amount of cement in cementitious composites, specifically when incorporating wastes as partial replacement for Portland cement. In this work, we substitute cement with shell by-products while keeping useful specific properties. Scallop shells are good candidates to replace part of the Portland cement as they contain calcium and are available in abundance. We present an experimental and numerical study on the mechanics, hygrothermal behavior, and life cycle analysis of scallop shell concrete. In the fresh state, the replacement of cement by up to 10 wt.% of scallop shells does not significantly affect mortar properties. The results indicate that including 10% shells represents a decrease of up to 40% in the environmental impact, depending on the category of impact considered. Furthermore, the addition of Scallop shells makes the material more porous, leading to the facilitation of moisture transfer.

This study investigates the use of Brewers’ Spent Grains (BSGs) as a sustainable biocomposite building materials, using cornstarch as a biopolymer binder. BSG aggregates are compared with hemp shives, a conventional aggregate known for its thermal properties. Starch is employed as a natural binder in three different formulations to further reduce the carbon footprint of the building material. Considering aggregates, the first formulation contains only BSGs, the second consists of half BSGs and half hemp shives, and the third uses only hemp shives. In addition, morphological analysis using Scanning Electron Microscopy (SEM) is conducted to examine the microstructure and porosity of the raw BSG and hemp shives. Hygrothermal properties are measured using Heat Flow Meter (HFM) and Dynamic Vapor Sorption (DVS) techniques, while mechanical properties are also assessed. Results indicate that the thermal conductivity of the BSG formulation (0.131 W/(m·K)) is double that of the hemp shives formulation (0.067 W/(m·K)), whereas the mixed BSG/hemp shives formulation exhibits a thermal conductivity of 0.106 W/(m·K). However, DVS measurements reveal better hygrothermal properties for the BSG formulation compared to the hemp shives formulation. Lastly, mechanical properties are found to be nearly equivalent across the three formulations. These findings suggest that BSG waste has potential as a viable material for use in construction. Further work on formulation optimization and durability is necessary to fully realize the potential of this waste in promoting a circular economy within the building materials industry.

This paper investigates the in situ hygrothermal behavior of a cob prototype building equipped with multiple sensors for measuring temperature, relative humidity inside the building, and water content within its walls. The experimental results show that the earth-based prototype building presents interesting thermal insulation performance. Without any heating system, the indoor temperature was found to remain stable, near 20 °C, despite large fluctuations in the outdoor temperature. This study also illustrated the ability of cob to absorb and regulate indoor relative humidity. The use of a neural network model for predicting the hygrothermal behavior of the cob prototype building was an additional objective of this work. This latter was centered on investigating the indoor ambience and moisture content within the walls. In this sense, a long short-term memory model (LSTM) was developed and trained. The validation results revealed an excellent agreement between the model predictions and experimental data, with R² values of 0.994 for the indoor air temperature, 0.960 for the relative humidity, and 0.973, 0.925, and 0.938 for the moisture content at three different depths in the building’s walls. These results indicate that the LSTM model is a promising approach for predicting the indoor ambience of an earth-based building, with potential applications in building automation and energy management. Finally, an economic discussion of the CobBauge system is presented.

Knowledge of indoor air quality (IAQ) in cob buildings during the first few months following their delivery is of vital importance in preventing occupants’ health problems. The present research focuses on evaluating IAQ in cob buildings through a prototype built in Normandy, France. To achieve this, the prototype was equipped with a set of sensors to monitor various parameters that determine indoor and outdoor air quality. These parameters include relative humidity (RH), carbon dioxide (CO₂), nitrogen dioxide (NO₂), ozone (O₃), particulate matter (PM1 and PM10), and volatile organic compounds (VOCs). The obtained experimental results indicate that, overall, there is good indoor air quality in the prototype building. However, there are some noteworthy findings, including high indoor RH and occasional spikes in CO₂, PM1, PM10, and VOCs concentrations. The high RH is believed to be a result of the ongoing drying process of the cob walls, while the peaks in pollutants are likely to be attributed to human presence and the earthen floor deterioration. To ensure consistent good air quality, this study recommends the use of a properly sized Controlled Mechanical Ventilation system. Additionally, this study explored IAQ in the cob building from a numerical perspective. A Long Short-Term Memory (LSTM) model was developed and trained to predict pollutant concentrations inside the building. A validation test was conducted on the CO₂ concentration data collected on-site, and the results indicated that the LSTM model has accurately predicted the evolution of CO₂ concentration within the prototype building over an extended period.