Explore the vast range of titles available.

Girder design for suspension bridges has remained largely unchanged for the past 60 years. However, for future super-long bridges, aiming at record-breaking spans beyond 3 km, the girder weight is a limiting factor. Here we report on a design concept, inspired by computational morphogenesis procedures, demonstrating possible weight savings in excess of 28 percent while maintaining manufacturability. Although morphogenesis procedures are rarely used in civil engineering, often due to complicated designs, we demonstrate that even a crude extraction of the main features of the optimized design, followed by a simple parametric optimization, results in hitherto unseen weight reductions. We expect that further studies of the proposed design, as well as applications to other structures, will lead to even greater weight savings and reductions in carbon footprint in a construction industry, currently responsible for 39 percent of the world’s CO 2 emissions. Girder design for suspension bridges has remained largely unchanged for the past 60 years. Here, the authors present a design resulting in weight savings in excess of 28% while maintaining manufacturability, thus closing the gap towards super-long suspension bridges.

Building renovation is urgently required to reduce the environmental impact associated with the building stock. Typically, building renovation is performed by envelope insulation and/or changing the fossil-based heating system. The goal of this paper is to provide strategies for robust renovation considering uncertainties on the future evolution of climate, energy grid, and user behaviors, amongst others by applying life cycle assessment and life cycle cost analysis. The study includes identifying optimal renovation options for the envelope and heating systems for building representatives from all construction periods that are currently in need of renovation in Switzerland. The findings emphasize the paramount importance of heating system replacements across all construction periods. Notably, when incorporating bio-based insulation materials, a balance emerges between environmental impact reduction and low energy operation costs. This facilitates robust, equitable, and low-carbon transformations in Switzerland and similar Northern European contexts while avoiding a carbon spike due to the embodied carbon of the renovation. Building renovation is an urgent requirement to reduce the environmental impact associated with the building stock. In this paper, authors identify strategies for robust renovation considering uncertainties on the future and provide recommendations for the residential buildings in Switzerland.

Restoration is becoming a vital tool to counteract coastal ecosystem degradation. Modifying transplant designs of habitat-forming organisms from dispersed to clumped can amplify coastal restoration yields as it generates self-facilitation from emergent traits, i.e. traits not expressed by individuals or small clones, but that emerge in clumped individuals or large clones. Here, we advance restoration science by mimicking key emergent traits that locally suppress physical stress using biodegradable establishment structures. Experiments across (sub)tropical and temperate seagrass and salt marsh systems demonstrate greatly enhanced yields when individuals are transplanted within structures mimicking emergent traits that suppress waves or sediment mobility. Specifically, belowground mimics of dense root mats most facilitate seagrasses via sediment stabilization, while mimics of aboveground plant structures most facilitate marsh grasses by reducing stem movement. Mimicking key emergent traits may allow upscaling of restoration in many ecosystems that depend on self-facilitation for persistence, by constraining biological material requirements and implementation costs. Coastal restoration tends to be failure-prone and expensive. Temmink and colleagues improve seagrass and cordgrass transplant survival in field experiments using biodegradable structures which temporarily mimic self-facilitation occurring in mature vegetation stands, and combine onsite and laboratory measurements on sediment stability and stem movement to test the biophysical mechanisms.

Well-intended climate actions are confounding each other. Cities must take a strategic and integrated approach to lock into a climate-resilient and low-emission future.

The thermal comfort standards developed in the 1960s were based on the average male. Altering these standards to account for female metabolic rates could save energy and reduce greenhouse-gas emissions from buildings. Energy consumption of residential buildings and offices adds up to about 30% of total carbon dioxide emissions; and occupant behaviour contributes to 80% of the variation in energy consumption 1 . Indoor climate regulations are based on an empirical thermal comfort model that was developed in the 1960s (ref.  2 ). Standard values for one of its primary variables—metabolic rate—are based on an average male, and may overestimate female metabolic rate by up to 35% (ref.  3 ). This may cause buildings to be intrinsically non-energy-efficient in providing comfort to females. Therefore, we make a case to use actual metabolic rates. Moreover, with a biophysical analysis we illustrate the effect of miscalculating metabolic rate on female thermal demand. The approach is fundamentally different from current empirical thermal comfort models and builds up predictions from the physical and physiological constraints, rather than statistical association to thermal comfort. It provides a substantiation of the thermal comfort standard on the population level and adds flexibility to predict thermal demand of subpopulations and individuals. Ultimately, an accurate representation of thermal demand of all occupants leads to actual energy consumption predictions and real energy savings of buildings that are designed and operated by the buildings services community.

Current infrastructure management frameworks typically involve replacing bridges at the end of their intended service duration or when significant structural deficiencies arise, resulting in high costs and environmental impacts. Novel structural-strengthening methods using ultra-high-performance fiber-reinforced cementitious composite (UHPFRC) have allowed the preservation of hundreds of bridges in several countries. Their service duration has been extended, and their performance has been improved to match that of a new structure. Examining the Swiss federal network (3903 bridges), it is found that interventions using the UHPFRC method are feasible on more than 99.7% of structures, demonstrating that the structural intervention can be technically applied to most bridges in this network. On the given case study, systematically applying the UHPFRC method would lead to savings of up to 7.7 MtCO 2eq , and 18.5 billion CHF over the next 80 years compared to current engineering practice. This study highlights the significant potential of systematically implementing the UHPFRC method for sustainable and cost-effective infrastructure management. The study evaluates using ultra-high-performance fiber-reinforced cementitious composite (UHPFRC) for bridge maintenance in Switzerland, finding it feasible for 99.7% of bridges, potentially saving 7.7 million tons of CO 2 equivalent and 18.5 billion Swiss francs over 80 years compared to traditional methods.

Earthquakes represent a significant but often overlooked environmental burden in the construction sector, driven by post-disaster repairs and reconstruction that generate substantial carbon emissions. Here, we unveil the environmental toll of earthquakes in Europe by presenting a seismic risk map of embodied carbon associated with earthquake damage across residential, commercial, and industrial buildings. We develop a harmonised database of material quantities and carbon factors covering diverse construction materials and building types, which we integrate into a continental-scale probabilistic seismic risk model. Our analysis reveals that Europe’s building stock embodies nearly 14 billion tonnes of CO₂e, with seismic damage, based on over three million earthquake scenarios, contributing an average of 6.6 million tonnes annually. These values are comparable to the yearly emissions of millions of cars or tens of thousands of transatlantic flights. Our models and datasets offer a scalable, transferable tool to incorporate sustainability into disaster risk reduction and advance climate-resilient development. Earthquakes generate substantial carbon emissions from building damage repair and reconstruction. The study maps Europe’s seismic carbon risk, showing annual losses of 6.6 Mt CO 2 e and providing tools for sustainable disaster planning.

The frequent occurrences of bridge fires and the substantial disruptions and direct/indirect economic losses resulting from these events highlight the immediate need for effective fire-safety-oriented design of new bridges and retrofit approaches for vulnerable existing bridges. In this Perspective, we discuss why a holistic engineering approach integrating innovative fire analysis methods and structural design/retrofit strategies into multi-hazard and future-oriented risk modeling frameworks represents the way forward to more sustainable and resilient infrastructure in an uncertain and rapidly changing built environment. Bridge fires cause significant disruptions and economic losses in modern society, yet fire hazards are still often ignored or oversimplified in bridge design. This Perspective emphasizes the need for more holistic and comprehensive fire-safety design when retrofitting or designing new bridges.

The study of geographical systems as graphs, and networks has gained significant momentum in the academic literature as these systems possess measurable and relevant network properties. Crowd-based sources of data such as OpenStreetMaps (OSM) have created a wealth of worldwide geographic information including on transportation systems (e.g., road networks). In this work, we offer a Geographic Information Systems (GIS) protocol to transfer polyline data into a workable network format in the form of; a node layer, an edge layer, and a list of nodes/edges with relevant geographic information (e.g., length). Moreover, we have developed an ArcGIS tool to perform this protocol on OSM data, which we have applied to 80 urban areas in the world and made the results freely available. The tool accounts for crossover roads such as ramps and bridges. A separate tool is also made available for planar data and can be applied to any line features in ArcGIS. Design Type(s) data integration objective • observation design Measurement Type(s) network graph construction Technology Type(s) digital curation Factor Type(s) Sample Characteristic(s) Tokyo • Jakarta • Seoul • Delhi • Shanghai Proper • City of Manila • Karachi • New York City • Sao Paulo • Beijng Proper • Mumbai • Guangzhou City Prefecture • Moscow Federal City • City of Los Angeles • Kolkata • Dhaka • Buenos Aires • Istanbul • Rio de Janeiro • Shenzhen City Prefecture • Commune of Paris • Lima • City of Chicago • Tianjin Proper • Chennai • Bogota • Bangalore • London • Taipei City • Ho Chi Minh City • Dongguan City Prefecture • Hyderabad • Chengdu City Prefecture • Lahore • Johannesburg • Tehran • Bangkok • Wuhan • Ahmedabad • Chongqing Proper • Baghdad • Hangzhou City Prefecture • Province of Santiago de Chile • City of Fort Worth • City of San Francisco • Quanzhou City Prefecture • City of Miami • Shenyang City Prefecture • Belo Horizonte • City of Philadelphia • Nanjing City Prefecture • Madrid • City of Houston • Xianyang City Prefecture • Milan • Pune • Saint Petersburg • City of Atlanta • Surat • City of Washington • Bandung • Municipality of Surabaya • Harbin City Prefecture • City of Boston • Zhengzhou City Prefecture • Qingdao City Prefecture • Abidjan • Barcelona • Ankara • Suzhou City Prefecture • City of Phoenix • Salvador • Municipality of Porto Alegre • Roma • Recife • Province of Naples • City of Detroit • Dalian City Prefecture • Fuzhou City Prefecture • Medellin Metropolitan Area • city Machine-accessible metadata file describing the reported data (ISA-Tab format)

Identifying workers’ activities is crucial for ensuring the safety and productivity of the human workforce on construction sites. Many studies implement vision-based or inertial-based sensors to construct 3D human skeletons for automated postures and activity recognition. Researchers have developed enormous and heterogeneous datasets for generic motion and artificially intelligent models based on these datasets. However, the construction-related motion dataset and labels should be specifically designed, as construction workers are often exposed to awkward postures and intensive physical tasks. This study developed a small construction-related activity dataset with an in-lab experiment and implemented the datasets to manually label a large-scale construction motion data library (CML) for activity recognition. The developed CML dataset contains 225 types of activities and 146,480 samples; among them, 60 types of activities and 61,275 samples are highly related to construction activities. To verify the dataset, five widely applied deep learning algorithms were adopted to examine the dataset, and the usability, quality, and sufficiency were reported. The average accuracy of models without tunning can reach 74.62% to 83.92%. Measurement(s) motion of construction workers Technology Type(s) wearable motion sensing system Factor Type(s) skeleton joints position Sample Characteristic - Organism construction workers Sample Characteristic - Environment construction site