The US Infrastructure Investment and Job Act (IIJA), also commonly referred to as the Bipartisan Infrastructure Bill, passed in 2021, has drawn international attention. It aims to help to rebuild US infrastructure, including transportation networks, broadband, water, power and energy, environmental protection and public works projects. An estimated $1.2 trillion in total funding over ten years will be allocated. The Bipartisan Infrastructure Bill is the largest funding bill for US infrastructure in the recent history of the United States. This review article will specifically discuss funding allocations for roads and bridges, power and grids, broadband, water infrastructure, airports, environmental protection, ports, Western water infrastructure, electric vehicle charging stations and electric school buses in the new spending of the Infrastructure Investment and Job Act and why these investments are urgently necessary. This article will also briefly discuss the views of think tank experts, the public policy perspectives, the impact on domestic and global arenas of the new spending in the IIJA, and the public policy implications.

The Malaysian government's efforts to promote solar photovoltaic (PV) usage among households face a challenge due to its low adoption rate. This study delves into the factors influencing the exponential adoption of solar PV electricity generation among landed residential property owners in Malaysia. The research aims to comprehensively examine the predictors influencing the adoption of solar PV systems among Malaysian households. Hence, the study employs an enhanced Theory of Planned Behavior framework, integrating sustainable energy security dimensions such as availability, affordability, efficiency, acceptability, regulation, and governance. The sample comprised 556 Malaysian residents who owned and resided in the landed properties. The home locations where at least one solar PV installation existed within a residential street. Snowball sampling was employed through referrals, leveraging social and community networks. Collected data was analyzed using the partial least squares structural equation modeling. Attitude, affordability, and acceptability emerged as pivotal factors significantly impacting the intention to use solar PV systems among Malaysian households. This research not only enriches academic discourse but also offers practical implications for policymakers, guiding the formulation of targeted strategies to promote sustainable energy practices and facilitate the widespread adoption of solar PV systems in Malaysia.

Renewable energy is gaining momentum in developing countries as an alternative to non-renewable sources, with rooftop solar power systems emerging as a noteworthy option. These systems have been implemented across various provinces and cities in Vietnam, accompanied by government policies aimed at fostering their adoption. This study, conducted in Ho Chi Minh City, Vietnam investigates the factors influencing the utilization of rooftop solar power systems by 309 individuals. The research findings, analyzed through the Partial least squares structural equation modeling (PLS-SEM) model, reveal that policies encouragement and support, strategic investment costs, product knowledge and experience, perceived benefits assessment, and environmental attitudes collectively serve as predictors for the decision to use rooftop solar power systems. Furthermore, the study delves into mediating and moderating effects between variables within the model. This research not only addresses a knowledge gap but also furnishes policymakers with evidence to chart new directions for encouraging the widespread adoption of solar power systems.

Global energy agencies and commissions report a sharp increase in energy demand based on commercial, industrial, and residential activities. At this point, we need energy-efficient and high-performance systems to maintain a sustainable environment. More than 30% of the generated electricity has been consumed by HVAC-R units, and heat exchangers are the main components affecting the overall performance. This study combines experimental measurements, numerical investigations, and ANN-aided optimization studies to determine the optimal operating conditions of an industrial shell and tube heat exchanger system. The cold/hot stream temperature level is varied between 10 ℃ and 50 ℃ during the experiments and numerical investigations. Furthermore, the flow rates are altered in a range of 50–500 L/h to investigate the thermal and hydraulic performance under laminar and turbulent regime conditions. The experimental and numerical results indicate that U-tube bundles dominantly affect the total pumping power; therefore, the energy consumption experienced at the cold side is about ten times greater the one at the hot side. Once the required data sets are gathered via the experiments and numerical investigations, ANN-aided stochastic optimization algorithms detected the C10H50 scenario as the optimal operating case when the cold and hot stream flow rates are at 100 L/h and 500 L/h, respectively.