This study focuses on the relationship between the complexity of pore structure and capillary water absorption of concrete, as well as the connection behavior of concrete in specific directions. In this paper, the water absorption of concrete with different binders was tested during the curing process, and the pore structure of concrete was investigated by mercury intrusion porosimetry (MIP). The results show that the water absorption of concrete with mineral admixtures is lower, mainly due to the existence of reasonable pore structure. The effect of slag on concrete modification is more remarkable comparing with fly ash. In addition, the analysis shows that the pore with different diameters has different fractal characteristics. The connectivity probability and water absorption of unidirectional chaotic pore are linearly correlated with the pore diameter of 50–550 nm, and the correlation coefficient reaches a very significant level, and detailed analysis was undertaken to interpret these results based on fractal theory.

In this study, we explore a new method based on color variation data to derive the kinetics of the entire process of the hydration of alkali-activated slag (AAS). Using this image analysis technique, we can monitor the induction period that cannot be observed using conventional microcalorimetry techniques. Color variation was recorded across a sequence of 9999 images, which were processed via MATLAB software package. Further, an average pixel value (APV) was determined to represent the color in each image. Reaction parameters, such as color variation velocity v(t), reaction speed ε(t), and hydration degree α(t), that govern the entire hydration process were determined. On the basis of the reaction parameters and a Krstulovic–Dabic kinetic model, integral and differential equations were derived to simulate the three basic processes of AAS hydration. Equations describing the reaction kinetics of AAS with solutions of three different concentrations of NaOH were extracted using this method.

Amidst the global energy structure transition and intensification of climate warming, the temperature control targets of the Paris Agreement and China’s “dual carbon” goals have driven the rapid development of building-integrated photovoltaics (BIPVs). However, solar cells in BIPV systems may produce exhaust gases that affect local urban air quality if exposed to extreme environmental conditions such as high temperatures during operation. In this study, eight air quality monitoring points were established around the BIPV system at Shenyang Jianzhu University as the experimental group, along with one additional air quality monitoring point serving as a control group. The concentrations of four air pollutant indicators (PM_2.5, PM₁₀, SO₂, and NO₂) were monitored continuously for 14 days. The weight of each indicator was calculated using the principle of information entropy, and the air quality evaluation grades were determined by combining the homomorphic inverse correlation function. The Entropy-Weighted Set Pair Analysis model was applied to evaluate the air quality of the BIPV system at Shenyang Jianzhu University. The results indicated that due to the high concentrations of SO₂ and NO₂, the Air Quality Index (AQI) grade at Shenyang Jianzhu University was classified as “light pollution.” Corresponding recommendations were proposed to promote the sustainable development of urban BIPV. Simultaneously, the evaluation results of the Entropy-Weighted Set Pair Analysis model were similar to those obtained using other methods, demonstrating the feasibility of this evaluation model for assessing the impact on air quality.