The purpose of this study is to determine the mix proportions that can minimize CO₂ emissions while satisfying the target performance of porous vegetation concrete. The target performance of porous vegetation concrete was selected as compressive strength (>15 MPa) and void ratio (>25%). This study considered the use of reinforcing fiber and styrene butadiene (SB) latex to improve the strength of porous vegetation concrete, as well as the use of blast furnace slag aggregate to improve the CO₂ emissions-reducing effect, and analyzed and evaluated the influence of fiber reinforcing, SB latex, and blast furnace slag aggregate on the compressive strength and CO₂ emissions of porous vegetation concrete. The CO₂ emissions of the raw materials were highest for cement, followed by aggregate, SB latex, and fiber. Blast furnace slag aggregate showed a 30% or more CO₂ emissions-reducing effect versus crushed aggregate, and blast furnace slag cement showed a 78% CO₂ emissions-reducing effect versus Portland cement. The CO₂ emissions analyses for each raw material showed that the CO₂ emissions during transportation were highest for the aggregate. Regarding CO₂ emissions in each production stage, the materials stage produced the highest CO₂ emissions, while the proportion of CO₂ emissions in the transportation stage for each raw material, excluding fiber, were below 3% of total emissions. Use of blast furnace slag aggregate in porous vegetation concrete produced CO₂ emissions-reducing effects, but decreased its compressive strength. Use of latex in porous vegetation concrete improved its compressive strength, but also increased CO₂ emissions. Thus, it is appropriate to use latex in porous vegetation concrete to improve its strength and void ratio, and to use a blast furnace slag aggregate replacement ratio of 40% or less.

Condition assessment of concrete bridge decks is critical for ensuring structural integrity and public safety, particularly as infrastructure ages. Traditionally, such assessments are made using destructive techniques, such as coring through concrete to collect samples for analysis. However, these invasive methods create weak points within the structure and risk damaging essential components, such as cutting through rebars. This paper explores the use of three non-destructive testing (NDT) methods—electrical resistivity (ER), impact echo (IE), and infrared thermography (IRT)—to evaluate the structural health of concrete bridge decks and overlays. These techniques are tested individually and in combination through a mock-up experiment to detect defects such as delamination and corrosion. The findings demonstrate that while each NDT method has specific strengths—surface ER with a 46.67% detection rate, IE with 40%, and IRT with 53.33%—the combined detection rate increased to 60%. This combined approach provides a more comprehensive assessment and is expected to help establish better maintenance strategies for aging infrastructure. The study highlights the importance of optimizing NDT methods for real-world applications, addressing current limitations such as environmental sensitivity and scanning speed, to improve the early detection and prevention of structural failures.

In this study, for restoration of ecological systems in buildings, porous vegetation red clay green roof blocks were designed for performance evaluation. Blast furnace slag (BFS; fine aggregates (agg.)), coarse aggregates, polyvinyl alcohol (PVA) fiber (hydrophilic fiber), and red clay (ecofriendly additive material) were applied to the construction of the porous vegetation red clay green roof blocks. A decrease in cement use is one way of reducing carbon emissions. To increase the water retentivity and the efficiency of roof vegetation blocks, blast furnace slag aggregates with excellent water absorptivity and polyvinyl alcohol fiber with a water absorption rate above 20% were added. In particular, the addition of polyvinyl alcohol fiber prevents performance reduction of the green roof vegetation blocks during freezing and melting in winter. Compressive strength, void ratio, and unit-mass tests were conducted to evaluate the performance of the roof vegetation blocks. After their application to roof vegetation, the effect of water purification was evaluated. According to the experimental results, the mix that satisfies the target performance of green roof vegetation blocks (compression strength above 8 MPa, void ratio above 20%, unit mass 2.0 kg/cm³ or below) is: cement = 128.95 kg/m³, BFS = 96.75 kg/m³, red clay = 96.75 kg/m³, water = 81.50 kg/m³, BFS agg. = 1450 kg/m³, PVA fiber = 1.26 kg/m³. The green roof vegetation blocks were designed using the mix that satisfied the target performance. To find the amount of attainable water due to rainfall, a rainfall meter was installed after application of the roof vegetation to measure daily rainfall and calculate the amount of attainable water. The results show that, for 1 mm of rainfall, it is possible to attain about 0.53 L of water per 1 m². In addition, the water quality of effluents after application of roof vegetation was analyzed, and the results satisfied Class 4 of the River-life Environmental Standard for Availability of Agricultural Water.

Portland cement concrete is widely used in road construction due to its durability and minimal maintenance needs. However, its susceptibility to spall highlights the drawbacks of conventional repair methods, including cost inefficiencies, delays, environmental impacts, and safety risks from road closures. To address these challenges, this study evaluated the environmental benefits of a spall detection and repair method employing artificial-intelligence-based computer vision technology. By utilizing machine vision techniques, this approach detects spall damage without road closures and automates the calculation of repair areas and material requirements through a proprietary estimation program. Environmental impact assessments were conducted using life cycle assessment across three frameworks, TRACI, ReCiPe, and ILCD, to compare this method with conventional practices. The results revealed a 79% reduction in the overall environmental impacts, including significant decreases in global warming due to shorter road closures and reduced material waste. Resource usage improved through optimized processes, and air pollution decreased, with lower emissions of smog and particulates. This study highlights the potential of machine-vision-driven repair material quantity takeoff as a more efficient and sustainable alternative. The results of this study will help institutional engineers and practitioners adopt sustainable strategies for green infrastructure repair and integrate them into various infrastructure maintenance practices to contribute to the development of sustainable urban environments.

In this study, the mechanical properties and durability of rainwater penetration and retention pavement concrete blocks incorporating bottom ash fine aggregate were investigated to develop pavement concrete blocks that could reduce the rainwater leakage of impervious concrete structures. Pavement concrete blocks were prepared by replacing 0%, 10%, and 20% of the weight of natural fine aggregate with bottom ash fine aggregate for 410 and 450 kg/m 3 cement contents. Experimental tests were conducted to determine the compressive strength, flexural strength, abrasion resistance, slip resistance, freeze-thaw resistance, and permeability coefficient of the pavement concrete blocks. Pavement concrete blocks produced with a cement content of 450 kg/m 3 and a 10% replacement ratio of bottom ash fine aggregate satisfied the target performance and exhibited the best overall performance. Theseoptimal mix parameters were applied in this study to design and manufacture pavement concrete blocks for rainwater penetration and retention that satisfied the target performance.