This review provides a comprehensive examination of porosity and permeability as key parameters governing the durability and performance of construction materials, including natural stone, mortar, concrete, and other cementitious composites. It highlights the pivotal role of pore structure in transport phenomena and degradation mechanisms, examining how the variations in pore architecture, encompassing total vs. effective porosity, pore size distribution, and pore connectivity, dictate a material’s response to environmental stressors. A comparative evaluation of advanced pore characterization techniques is presented, including helium pycnometry, mercury intrusion porosimetry (MIP), nitrogen adsorption (BET/BJH), nuclear magnetic resonance (NMR) relaxometry, and imaging methods such as optical microscopy, scanning electron microscopy (SEM), and X-ray micro-computed tomography (micro-CT). Furthermore, it assesses how these porosity and permeability characteristics influence durability-related processes like freeze–thaw cycling, chloride ingress, sulphate attack, and carbonation. Case studies are discussed in which various additives have been employed to refine the pore structure of cement-based materials, and pervious concrete is highlighted as an example where deliberately high porosity and permeability confer functional benefits (e.g., enhanced drainage). Overall, these insights underscore the importance of tailoring porosity and permeability in material design to enhance durability and sustainability in construction engineering.

The importance of understanding the effects of rainfall on different materials over time makes it essential to carry out controlled tests to reduce analysis time. Rainfall simulators have been in use for decades and have been implemented as technology and knowledge of the physical behavior of water advanced. There are two main types of rainfall simulators: gravity simulators and pressure simulators. In the former, the drop velocity is normally smaller than the terminal velocity reached by natural droplets; in the latter, the drop size is too small to be representative and has far more speed than the natural speed for those sizes. To solve this problem, a simulator has been developed where the terminal velocity of the raindrops is reached and the drop size can be varied by different nozzles of variable sizes, adapting it to the conditions of a given region. In this study, conditions similar to the rainfall conditions of the city of León have been achieved. This paper presents the design of a rainfall simulator that recreates different rainfall conditions and rainwater composition and its calibration process.

Acid rain is a problem that despite efforts to reduce atmospheric pollution, continues to impact not only countries where there is a high production of pollutants, but also transboundary areas to which the pollutants are transported. In addition to its effects on human health, there are also the effects on infrastructure and the consequences that this entails. This study on the effect of rain and acid rain on calcareous materials highlights the need for protection of buildings constructed from these materials, many of which are part of the cultural heritage. The effects caused by rain and acid rain were studied using a rain simulator whose features allow the simulation of natural conditions as realistically as possible. In the same way, the effect of a coating synthesized from nanomaterials, which has been shown to serve as protection against the degradation caused by rain, was analyzed. In addition to a long-lasting protection of the stone material, this type of coating avoids the need for the replacement of elements and the recurrent cleaning of degraded parts. It also avoids the accumulation of parts on the ground, the transport of personnel, work materials and raw materials, thereby contributing to the reduction of the carbon footprint and water savings, which in turn reduces the production of pollutants that cause acid rain.

The data obtained from air quality monitoring stations, which are used to carry out studies using data mining techniques, present the problem of missing values. This paper describes a research work on missing data imputation. Among the most common methods, the method that best imputes values to the available data set is analysed. It uses an algorithm that randomly replaces all known values in a dataset once with imputed values and compares them with the actual known values, forming several subsets. Data from seven stations in the Silesian region (Poland) were analyzed for hourly concentrations of four pollutants: nitrogen dioxide (NO₂), nitrogen oxides (NO_x), particles of 10 μm or less (PM₁₀) and sulphur dioxide (SO₂) for five years. Imputations were performed using linear imputation (LI), predictive mean matching (PMM), random forest (RF), k-nearest neighbours (k-NN) and imputation by Kalman smoothing on structural time series (Kalman) methods and performance evaluations were performed. Once the comparison method was validated, it was determine that, in general, Kalman structural smoothing and the linear imputation methods best fitted the imputed values to the data pattern. It was observed that each imputation method behaves in an analogous way for the different stations The variables with the best results are NO₂ and SO₂. The UMI method is the worst imputer for missing values in the data sets.

Concern for the perpetuation of stone monuments is deeply ingrained in humans; however, despite the attempts made in this field, there is still a great deal of effort needed to bring about advancements in the conservation of ornamental stone. Erosive agents, such as rain, extreme temperatures, and chemical and biological agents, threaten our stone heritage and gradually wear away buildings, sculptures, and other monuments found all around the world. Limestone and dolostone have been widely used throughout history, given their ease of extraction and workability. Nevertheless, these properties make them particularly vulnerable to the aforementioned erosive agents, for which the main solution at present is costly and time‐consuming restoration. Given the scarcity of effective and durable agents to prevent the deterioration of ornamental and heritage stones, and as graphene oxide (GO) has recently shown impressive effectiveness for this task, this work will further explore the viability of GO as a protective coating for monumental dolostone. For this purpose, GO is sprayed over dolostone surfaces by water dispersion with no adjuvants. The coating performance is assessed in terms of thermal stress, optical inspection (structured light 3D scanner), colorimetry, leachate analysis, and electron microscopy. The main results show that spray‐coated GO over stone surfaces creates a highly protective and durable barrier without altering their aesthetic qualities.