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Of all the construction waste, the building interior decoration and renovation waste (D&R waste) is difficult to dispose of and recycle due to its complex components and varied producers. The goal of this study is to reveal the current situation of D&R waste disposal through case studies and put forward the correlation proposal to improve standards of D&R waste recycling. This study investigated the various stages of the D&R waste management process, including generation, collection, transportation, sorting, recycling, and landfilling. Detailed studies were conducted for (i) the composition of D&R waste and (ii) the material flow analysis (MFA) of D&R waste recycling in different cases with different sorting technology. The results show that (i) concrete, stone, and other hard inorganic materials accounted for about 35–55% of the total. Soft inorganic materials such as aerated concrete and gypsum made up 5–25%, slag 15–20%, timber 5–10%, combustible matter such as plastic, rubber, and paper 9–12%, and glass and metal 1–5%, and (ii) artificial intelligence (AI) sorting offers better sorting performance and economic advantages over manual sorting, promoting the application of artificial AI sorting equipment as important solutions to face the key challenges of D&R waste recycling.

Carbon emissions from buildings account for a large proportion of total social carbon emissions. Prefabricated buildings can effectively reduce carbon emissions in the construction materialization phase. The existing building carbon emission calculation method for prefabricated buildings seems too complicated due to the large amounts of data that need to be consulted in the production, transportation, construction, and demolition phases of each building. Meanwhile, the traditional building carbon emission calculation method must be carried out after the completion of construction drawings, because the consumption of labor, materials, and machinery must be calculated according to these drawings. This paper proposes a building carbon emission calculation method for prefabricated buildings based on the component design method. A case study proved that our method can calculate carbon emissions in the materialization phase of construction more quickly than the traditional quota carbon emission calculation method, and the results of the two methods differ by less than 10%. This method significantly improves the prediction of carbon emissions in the building materialization phase.

Abstract Biosensors are powerful tools for detecting, real-time imaging, and quantifying molecules, but rapidly constructing diverse genetically encoded biosensors remains challenging. Here, we report a method to rapidly convert enzymes into genetically encoded circularly permuted fluorescent protein-based indicators to detect organic acids (GECFINDER). ANL superfamily enzymes undergo hinge-mediated ligand-coupling domain movement during catalysis. We introduce a circularly permuted fluorescent protein into enzymes hinges, converting ligand-induced conformational changes into significant fluorescence signal changes. We obtain 11 GECFINDERs for detecting phenylalanine, glutamic acid and other acids. GECFINDER-Phe3 and GECFINDER-Glu can efficiently and accurately quantify target molecules in biological samples in vitro. This method simplifies amino acid quantification without requiring complex equipment, potentially serving as point-of-care testing tools for clinical applications in low-resource environments. We also develop a GECFINDER-enabled droplet-based microfluidic high-throughput screening method for obtaining high-yield industrial strains. Our method provides a foundation for using enzymes as untapped blueprint resources for biosensor design, creation, and application.

Construction contributes significantly to gas emissions, such as Greenhouse Gases (GHGs) and Criteria Air Pollutants (CAPs). To mitigate negative environmental effects, diverse efforts have been undertaken in construction; however, currently there is no effective tool available for small-scale (e.g., project-based), reliable emission estimation in construction. A new approach to simulating emissions, Discrete-Event Simulation (DES), offers accurate representations of construction operations over time (e.g., equipment utilization rates and duration of use). This approach allows the comparison of emissions from different operational scenarios and can therefore be used in diverse decision-making processes. In this paper, we present a DES-based simulation template created using Simphony, a special purpose simulation environment developed at the University of Alberta. This template permits inexperienced simulators to build simulation models that can estimate emissions of a construction project. A case study of typical aggregate operations in road construction is presented to showcase the model development process. Through its scenario comparisons, daily emissions forecast, and other output analysis, this case study also demonstrates how this simulation-based method can provide valuable information for practitioners to make better decisions on sustainable construction processes. [ABSTRACT FROM AUTHOR]