Sustainable energy systems based on efficiency, low-carbon, and smart technologies are essential for the future energy transition. A new integrated sustainability assessment framework (ISAF) is required to evaluate cross-cutting subjects and future research. Sustainability analysis based on conventional dimensions and complementary categories is needed for a digital energy transition. Industry 4.0 created a new platform and technological portfolio to improve the efficiency and automation of cleaner energy systems (lower environmental and social impacts and high performance). To address these aspects, a new methodology based on bibliometric analysis, systematic literature review, and energy systems thinking was developed. From Scopus and Web of Science databases, 1521 and 959 documents were respectively compiled and merged to select 181 articles related to these research subjects between 2017 and 2021. Out of this total, 62 articles from industrial manufacturing were identified as the most representative energy consumption sub-sector. These articles were analysed from the ISAF using conventional dimensions (environmental, economic, and social) and complementary categories of sustainability (technological innovation, governance and life cycle). The main findings reveal that worldwide studies addressing the nexus between Industry 4.0, Energy and Sustainability have increased significantly in recent years, primaly in high-income countries. These studies have centred on the industrial manufacturing subsector, assessing sustainability unevenly by focusing mainly on technological and environmental issues. Research gaps indicate that a comprehensive assessment of social, governance, and life cycle aspects is still required.

Cities consume most of the energy used worldwide and are the largest emitters of greenhouse gases (GHGs) that cause global warming, mainly from the road transport sector. In megacities, the light vehicle fleet is responsible for most of the emissions in the sector. Among this fleet, light commercial vehicles (CVs), which have grown to support instant delivery services demand, are also responsible for emissions and traffic congestion. Due to the urgency to reduce transport impacts, emission mitigation strategies are required. Aligned with this aim, this article evaluates GHG emissions along the entire process of energy production, called the operating trajectory, and also known as Well-To-Wheel (WTW), in four combinations of transportation modes for last-mile delivery services, using light CVs, such as electric or diesel vans, and electric cargo bikes (E-bikes). The analysis is firstly conducted in a local area of Mexico City and subsequently compared to other countries around the world. In this respect, the main result of this article shows that in the case study conducted in the Metropolitan Zone of the Valley of Mexico, the energy consumption of a given route for an electric van combined with E-bikes generates 24% less GHG emissions than a diesel van combined with E-bikes. Therefore, the achievement of effective mitigation strategies for GHG emissions reduction through vehicle electrification requires WTW emission analysis and quantification, optimal route design, a combination of sustainable transport modes and clean energy generation.

Big cities affected by intense mobility, traffic and pollution are adopting electrification-based solutions for the reduction of the ${\mathrm{CO}}_2$ emissions of combustion engines. An interesting field in which the transition toward electrification can achieve important benefits is the area of instant deliveries. Instant deliveries deal with the mobility related to commercial trades between suppliers and customers. In this respect, optimal solutions can be considered during route planning based on the minimization of several metrics, such as distance, energy and road slope, among others. To this end, this paper presents an optimal solution to the instant deliveries problem in which the result is the optimal route, in the city under study, that minimizes energy consumption based on road slope and total distance traveled, and that gives higher priority to routes that include cycling infrastructure that the city can provide. The paper uses electric bikes since they are easily transportable and are highly versatile for instant deliveries. The results obtained were compared to a previous version of the optimal algorithm already published by the authors which minimizes the Haversine and Euclidian distances only. It was found that the shortest distance travelled between customers does not necessarily imply the least energy consumption. The latter, in combination with an energy consumption estimation approach, represent the original contribution of the work.