The control efficiency and mechanism of heavy metals by permeable pavement system in runoff based on enhanced infiltration materials

Evaluating the influence of Nano-GO concrete pavement mechanical properties on road performance and traffic safety using ANN-GA and PSO techniques

The burgeoning demand for durable and eco-friendly road infrastructure necessitates the exploration of innovative materials and methodologies. This study investigates the potential of Graphene Oxide (GO), a nano-material known for its exceptional dispersibility and mechanical reinforcement capabilities, to enhance the sustainability and durability of concrete pavements. Leveraging the synergy between advanced artificial intelligence techniques-Artificial Neural Networks (ANN), Genetic Algorithms (GA), and Particle Swarm Optimization (PSO)-it is aimed to delve into the intricate effects of Nano-GO on concrete's mechanical properties. The empirical analysis, underpinned by a comparative evaluation of ANN-GA and ANN-PSO models, reveals that the ANN-GA model excels with a minimal forecast error of 2.73%, underscoring its efficacy in capturing the nuanced interactions between GO and cementitious materials. An optimal concentration is identified through meticulous experimentation across varied Nano-GO dosages that amplify concrete's compressive, flexural, and tensile strengths without compromising workability. This optimal dosage enhances the initial strength significantly, and positions GO as a cornerstone for next-generation premium-grade pavement concretes. The findings advocate for the further exploration and eventual integration of GO in road construction projects, aiming to bolster ecological sustainability and propel the adoption of a circular economy in infrastructure development.

Understanding the removal of heavy metals from stormwater runoff in permeable pavement system

Understanding the removal of heavy metals (HMs) in permeable pavement systems is of great significance for controlling urban runoff pollution and optimizing structural design. However, few studies have systematically investigated the mechanism of permeable pavement systems in removing HMs from stormwater runoff. In this study, we adopted a hierarchical strategy to understand the efficiency of individual structural layers on HMs removal in a permeable interlocking concrete pavement (PICP) system. Experimental results illuminated that the surface layer exhibited the highest uptakes of HMs, which can remove up to 64 % of Pb2+, 50 % of Cu2+, 28 % of Cd2+ and 13 % of Zn2+. Meanwhile, as the rainfall return period increased, the removal rates of HMs in PICP was gradually decreased. In addition, batch experiments were conducted and the adsorption results were in accordance with the rainfall filtration experiments. More importantly, X-ray Photoelectron Spectroscopy (XPS) and leaching results were investigated to understand the HMs removal mechanism, which found that the ion exchange is the main mechanism in the surface layer to remove HMs, whereas the chemical adsorption play a crucial role in the base and sub-base layers. Overall, these findings provided new insights into the transport patterns of HMs in the internal structural layers of the PICP.

Distribution of microplastics in rainfall and their control by a permeable pavement in low-impact development facility

Microplastics (MPs) released from plastic products in daily life are present in the air and could be transported to freshwater environments along with rain. Recently, low-impact development (LID) facilities, such as permeable pavements, have been used to treat non-point source pollutants, including rainfall runoff. While runoff is treated by LID facilities, the periodic monitoring of MPs in rainfall and the efficiency of removal of MPs through LID facilities have rarely been investigated. Therefore, this case study focused on monitoring MPs in rainwater runoff and permeate from a permeable pavement in Busan, South Korea, thus evaluating the removal efficiency of MPs by a LID system. The initial rainfall runoff and permeate through the LID system were sampled, and the amounts, types, sizes, and shapes of MPs in the samples were analyzed using micro-Fourier Transform Infrared (FTIR) spectroscopy. The results showed that the distribution of MPs in the initial rainfall was affected by population in tested area. Polyethylene was the most common type of MPs in all the samples. Polyamide was only found in the LID samples because of the pollution caused by water flows and pavement materials. Fragment type MPs was most commonly observed and consisted of relatively small-sized (under 100 μm) particles. LID facilities were able to capture approximately 98% of MPs in the rainfall through a filtration process in the permeable pavement.

The investigation of the binding ability between sodium dodecyl sulfate and Cu (II) in urban stormwater runoff

The simultaneous presence of heavy metals and surfactants in runoff induces complexation and ecological harm during migration. However, interactions between these pollutants are often overlooked in past studies. Thus, investigating heavy metal-surfactant complexes in runoff is imperative. In this work, Cu (II) and sodium dodecyl sulfate (SDS) were selected to investigate the interaction between heavy metals and surfactants due to the higher detected frequency in runoff. Through 1H NMR and FTIR observation of hydrogen atom nuclear displacement and functional group displacement of SDS, the change of SDS and Cu (II) complexation was obtained, and then the complexation form of Cu (II) and SDS was verified. The results showed that solution pH values and ionic strength had significant effects on the complexation of Cu (II). When the pH values increase from 3.0 to 6.0, the complexation efficiency of SDS with Cu (II) increased by 12.12% at low concentration of SDS, which may be attributed to the excessive protonation in the aqueous solution at acidic condition. The increase of ionic strength would inhibit the complexation reaction efficiency by 19.57% and finally reached the platform with concentration of NaNO3 was 0.10 mmol/L, which was mainly due to the competitive relationship between Na (I) and Cu (II). As a general filtering material in stormwater treatment measures, natural zeolite could affect the interaction between SDS and Cu (II) greatly. After the addition of SDS, the content of free Cu (II) in the zeolite-SDS-Cu (II) three-phase mixed system was significantly reduced, indicating that SDS had a positive effect on the removal of Cu (II) from runoff. This study is of great significance for investigating the migration and transformation mechanism of SDS and Cu (II) in the future and studying the control technology of storm runoff pollution.