Vinayak Kaushal

Aging wastewater networks require sustainable and low-impact rehabilitation strategies. Open-cut pipeline installation (OCPI) is a conventional rehabilitation method associated with significant construction-related disruptions, whereas Cured-in-Place Pipe (CIPP) is a trenchless alternative that minimizes surface disturbance. However, existing studies rarely integrate construction costs (CC), environmental costs (EC), and social costs (SC) within a unified, sustainability-oriented life-cycle cost analysis (LCCA) framework. This study develops supervised machine-learning (ML) models—k-Nearest Neighbors (KNN), Decision Tree Regression (DTR), Gradient Boosting Regression (GBR), and Multiple Linear Regression (MLR)—to predict construction costs for OCPI and CIPP across pipe diameters ranging from 150 to 2,130 mm (6–84 in.). These predictions are integrated into a modular LCCA framework incorporating EC quantified using SimaPro 2024 with the ReCiPe 2016 Midpoint (H) method and SC estimated using established formulations. Under the stated planning-level assumptions and included cost components, integrating CC, EC, and SC demonstrated. A national dataset comprising more than 750 installations was preprocessed using Multiple Imputation by Chained Equations (MICE), five-fold cross-validation, and hyperparameter optimization. Model performance was evaluated using the coefficient of determination (R²), root mean square error (RMSE), mean absolute percentage error (MAPE), and prediction accuracy based on a ± 20% relative error threshold. KNN achieved the highest predictive performance for OCPI, while GBR performed best for CIPP. OCPI generated higher environmental impacts in 16 of the 18 ReCiPe midpoint categories for pipe diameters of 150–525 mm (6–21 in.). Under the assumptions and cost components considered in this planning-level assessment, integrating CC, EC, and SC resulted in CIPP having an average LCC approximately 56% lower than OCPI, with peak savings of 69% for pipe diameters of 150–1,500 mm (6–60 in.). Under these same assumptions, CIPP rehabilitated approximately 2.3 times more pipeline length per dollar than OCPI. The proposed integrated ML–LCCA framework provides a practical decision-support tool for sustainable and resource-efficient sewer infrastructure planning.

Amid accelerating Arctic warming-occurring at nearly four times the global rate-cold-region infrastructure faces escalating risks from permafrost thaw, sea-level rise, and compound climate stressors. This study presents a 25-year (2001-2026) review combining bibliometric analysis with a six-nation comparative synthesis to evaluate infrastructure vulnerability, engineering adaptation strategies, and policy implementation gaps. A dataset of 1,077 Web of Science records is analyzed using VOSviewer to map thematic evolution, while detailed case comparisons across the United States, Canada, Russia, Norway, Greenland (Denmark), and China identify tested engineering practices. The findings reveal a rapidly expanding but unevenly applied knowledge base, with research concentrated on high-elevation permafrost and largely disconnected from Arctic policy and military infrastructure contexts. While multiple nations have developed coherent design philosophies-emphasizing passive cooling, ventilated foundations, geohazard-informed siting, and climate-scenario-based design-the United States remains comparatively reactive, lacking systematic adoption of these approaches. The study concludes that the primary barrier to resilience is not the absence of technical solutions but the gap between knowledge and implementation. These insights underscore the need for integrated, forward-looking design frameworks applicable not only to Arctic infrastructure but also to climate-vulnerable built environments more broadly.

Sustainable construction practices and robust waste management strategies provide a viable pathway to mitigate these challenges. By integrating resource-efficient design, circular economy principles, and environmentally responsible technologies, the industry can significantly reduce its ecological burden. This paper presents a synthesis of environmental impacts from construction and a practical playbook of interventions spanning design, delivery, operations, and end-of-life. The study is organized as a systems guide: mapping life-cycle impact pathways (materials, energy, emissions, runoff, and noise) and pairing each with project-level governance, metrics, and technologies-eco-design, circularity, BIM and LCA, stormwater compliance, and performance-based certification. Recent policy and market updates (EPA’s 2022 Construction General Permit; LEED v4 energy update effective March 1, 2024; global buildings status reports) and introduce four original schematics for implementation. This technical review provides actionable guidance for owners, designers, and constructors to reduce waste, air and water pollution, and noise while improving project outcomes and community well-being.

Urban water infrastructure faces increasing deterioration, necessitating accurate, cost-effective condition assessment. Traditional inspection techniques are intrusive and inefficient, creating demand for scalable machine learning (ML) solutions. This study develops a hybrid ML meta-model to predict underground pipe conditions using a comprehensive dataset of 11,544 records. The objective is to enhance multi-class classification performance while preserving interpretability. A stacked hybrid architecture was employed, integrating Random Forest, LightGBM, and CatBoost models. Following data preprocessing, feature engineering, and correlation analysis, the neural network-based stacking meta-model achieves 96.67% accuracy, surpassing individual base learners while delivering enhanced robustness through model diversity, improved probability calibration, and consistent performance on challenging intermediate condition classes, which are essential for condition prioritization. Age emerged as the most influential feature, followed by length, material type, and diameter. ROC-AUC scores ranged from 0.894 to 0.998 across all models and classes, confirming high discriminative capability. This work demonstrates hybrid architectures for infrastructure diagnostics.

Styrene is an aromatic compound widely used as a reactive monomer in polyester resins, which are among the most utilized resins in cured-in-place pipe (CIPP) technology, the most widely used trenchless pipe renewal method. Given that styrene is classified as a suspected human carcinogen, this study aims to evaluate styrene concentrations emitted into the air during sewer pipe rehabilitation using CIPP. This study included developing a comprehensive methodology to collect data from six different CIPP installations across the U.S. and document styrene emissions before, during, and after the curing process. The air samples were collected and analyzed using the USEPA method TO-15 and TO-17. Measured styrene emissions were then compared with exposure limits established by USEPA, NIOSH, and OSHA to assess potential occupational and worker health impacts. The result confirmed that high styrene concentrations, exceeding the established threshold, can be observed within the CIPP work zone. The result also indicated a considerable reduction in styrene concentration within five feet downwind of the work zone. In conclusion, while the health risk to the public appears to be low, there is a potential for health impact for the CIPP crew. Therefore, implementing real-time air quality monitoring during CIPP installation to mitigate these health risks is recommended. Additionally, the use of appropriate personal protective equipment (PPE) by the crew is essential.

The journal retracts the article titled, “Thermoenergetic Performance of Phase Change Materials in Building Envelopes under Future Climate Scenarios”