Against the backdrop of increasing coastal risks driven by climate change, sea-level rise and intensifying anthropogenic pressures, understanding the performance and limitations of shoreline-protection systems has become a major scientific and policy concern. This review examines the evolution, effectiveness and management challenges of coastal-protection strategies, with particular attention to West Africa and the Gulf of Guinea. A structured literature search covering 2000–2025 was conducted using Scopus, Web of Science Core Collection, ScienceDirect, African Journals Online, Google Scholar and supplementary citation tracking. After screening, 64 publications were retained for comparative critical narrative synthesis. The evidence shows that coastal erosion results from interacting natural and anthropogenic drivers, including wave and sea-level variability, dam-induced sediment deficits, port development, sand mining, rapid urbanisation and shoreline armouring. Hard-engineering structures remain the dominant response in West Africa and can provide short-term local stabilisation; however, their long-term performance is often constrained by downdrift erosion, sediment-budget disruption, ecological degradation, maintenance requirements and impacts on coastal livelihoods. Socio-economic consequences include infrastructure damage, livelihood disruption, population displacement and limited community participation. Although nature-based, hybrid and adaptive approaches are increasingly recognised internationally, their implementation and long-term evaluation remain limited in the region. The literature is also geographically concentrated and methodologically heterogeneous, with insufficient integration of physical, socio-economic and governance evidence. Future research should prioritise harmonised long-term monitoring, regional sediment-budget modelling, life-cycle assessment of protection systems and stronger coordination between science, planning and governance. Multifunctional coastal systems incorporating renewable-energy functions remain an emerging option requiring cautious, site-specific evaluation.
The building sector exerts significant pressure on planetary systems and must align with environmental limits. Although life cycle assessment (LCA) supports eco-design, it mainly enables relative comparisons and does not determine whether a building is sustainable in absolute terms. Absolute environmental sustainability assessment (AESA) addresses this limitation, but its application to energy-positive buildings remains methodologically challenging. This study proposes a consistent AESA methodology for buildings that export renewable electricity, combining attributional LCA with a system-expansion approach applied to both impacts and carrying capacities. A dwelling per occupant carrying capacity is defined and extended to account for energy export. The framework is demonstrated through a residential case study in France. The case study shows that the dwelling’s ability to comply with the planetary-boundary carrying capacity depends on its positive energy balance and the use of bio-based materials. The approach supports the practical integration of AESA into building eco-design and encourages maximising the energy production capacity of residential buildings.
By 2050, India’s residential housing demand is likely to reach 576 million units. The constructed floor area and per capita floor space consumption needed to service this demand will result in increasing demand for building materials and CO _2 emissions. While some progress has been made on reducing CO _2 emissions from the operation stage, technological advancements and implementation to reduce buildings’ ‘embodied’ carbon emissions are still lacking momentum. This study evaluates mitigation potential and decarbonisation strategies through scenario assessment for cement and steel from residential buildings. The City of Ahmedabad is taken as a case study to assess strategies for decarbonising embodied-carbon impacts of future residential buildings to be built by 2050. Based on the Intergovernmental panel on climate change sixth assessment report (IPCC AR6) framework, four decarbonisation strategies to quantify CO _2 emissions from cement and steel have been adopted for the study. Asia-Pacific Integrated Model (AIM)/ End-use model, has been used for the study to understand and forecast the potential GHG emission reduction. Results from the study show that the energy efficiency and clean technology (EECTS) can achieve 46% CO _2 emission reductions from the cement sector compared to the Reference scenario, while circular economy and sufficiency scenario (CESS) can deliver 34% can be achieved. For steel, 60.2% emission reduction from the EECTS and 48.8% from the CESS scenario can be achieved. The study concludes that attaining deep decarbonisation is feasible, but it would still necessitate higher and earlier levels of material efficiency, a scaling up of carbon capture storage (CCS) capacity, and the adoption of green hydrogen, ambitious grid decarbonisation and major advances in urban and building regulations. Furthermore, as technology alone be sufficient to decarbonise the residential building industry, the concept of sufficiency should be advanced and put into practice through knowledge and policies.
The world is set to miss the 2030 sustainable development goals (SDGs) targets especially the ones related to infrastructure access. Existing service gaps will be further aggravated by the adverse impact of climate change in years to come. The next generation of SDGs will therefore need to consider how to best address existing gaps in infrastructure services such as water, energy and transport across different SDGs in the light of increasing climate uncertainties. This paper sets out how the value of breaking down silos and leveraging interdependencies between water, transportation and energy SDG targets can help to achieve the SDGs. It argues for a new generation of cross-sectoral interdependent SDG targets with climate resilience at the centre stage as well as setting a standalone SDG for transport to leverage its wide-ranging interdependencies with other sectors. Besides reforming the SDGs agenda through a nexus approach for climate-resilient infrastructure, we argue that there are three guiding principles to unlock potential benefits. The principles include holistic policy making, sustained climate financing and planning, and delivery of climate-resilient infrastructure at scale. The aim is to promote a sustainable, interconnected approach for resilient communities and economies in the era of climate uncertainty. The paper contributes to the discourse on strategic infrastructure development in the face of global environmental change and ongoing discussions on the future of SDGs.
Different perspectives of risk and approaches to risk assessment exist, which complicate communication, methodological advances and management across disciplines. To help building bridges, we have developed, tested and applied a generalized mathematical framework for risk assessment in a unique community effort, involving researchers from various fields. We present the derivation of the risk equation, which is tailored to civil and environmental engineering risk assessment of spatially-distributed and dynamic systems. We start off with a general framing and then refine individual parts of the equation as much as needed. The individual terms of the unified risk equation explicitly relate to concepts of frequency, intensity, duration, exposure, vulnerability and asset worth. Our approach takes a new perspective on facilitating communication across disciplines by exploiting mathematical formalism: filling our equation with life enforces a clear definition of the relevant terms and thereby helps in ‘translating’ between different terminology in the involved disciplines. For the sake of clarity and accessibility, we keep the framework simple in terms of additive effects and neglect failure cascades or nonlinear multi-hazard impact functions. Hence, while the framework is not designed to provide a one-fits-all-mathematical solution, it can help carve out the specific properties of a system that potentially violate these assumptions, and this is very valuable when talking risk assessment across disciplines. We demonstrate the utility of our proposed framework with ten selected examples from various domains, ranging from groundwater protection through seismic risk assessment to reliability analysis of critical infrastructure. The structured discussion between all involved researchers has greatly improved mutual understanding, which makes us confident that the proposed framework can serve as a catalyst for interdisciplinary advances in communicating and treating risk.
Achieving a net-zero emissions energy system requires accelerating renewable electricity deployment while addressing associated infrastructural and governance challenges. This study explores how local energy communities (LECs) in sparsely populated mountains could contribute to this transition by establishing microgrids with renewable electricity generation, storage, and grid assets, as well as with increased electrification of heating and transport. Using the case of 719 municipalities in the Swiss Alps, we model at high spatial and temporal resolution optimal technology portfolios and grid reinforcements under eight scenarios of policy frameworks that vary in grid ownership, export penalties, and transformer capacity limits. We find that when LECs co-invest in renewable generation and grid infrastructure expansion—forming community-owned microgrids—total optimal installed capacity of renewable generation increases by up to 50% as compared to current policy frameworks, including more alpine and agri-PV in addition to building-mounted solar PV, wind power, and biomass. Priority for grid reinforcement shifts from more urban to remote regions in the Alps, reflecting the spatial distribution of most productive solar resources. Although storage deployment is higher with higher imbalance penalties, grid co-investment remains more cost-effective. Overall, grid ownership by LECs leads to higher cumulative revenues and consumer benefits, meaning public support yields net welfare gains. Carbon dioxide emissions savings are also the highest with grid ownership by LECs due to higher self-consumption of renewable generation. The results demonstrate that community co-investment in grid assets in mountainous regions can enhance renewable electricity integration, economic viability, and decarbonization.
While green stormwater infrastructure (GSI) is a promising tactic for combating the effects of urbanization and climate change, its effect on the local climate is still not fully understood. Temperature reduction is commonly cited as a co-benefit due to evapotranspirative cooling from vegetated GSI, particularly by planners and policymakers who are more focused on heat stress adaptation. However, while evapotranspiration does provide cooling, it also increases the atmospheric moisture, potentially altering the local surface hydroclimate. Additionally, cooling performance is not fully understood across background climates and urban form. In this work, we use an Earth system model to examine the relationship between widespread implementation of rain gardens, our representative vegetated GSI technique, and resulting impacts to the urban hydroclimate across cities in the contiguous United States. Our results illustrate that while rain garden implementation does decrease the summer air temperature across most locations, there is typically a corresponding increase in humidity, ultimately leaving the human perception of temperature unchanged in many locations. These results are encouraging from a stormwater management perspective, but may not be an ideal outcome if GSI has been adopted in part for its heat stress adaptation capabilities. We find strong evidence that background climate influences the strength of rain garden impacts on the urban thermal environment, in addition to urban morphology. Suburban areas are more likely to benefit from implementation than their urban core counterparts.
As Australia prepares for the broader deployment of vehicle-to-grid (V2G) technologies, understanding consumer willingness to adopt will be critical to successful implementation. This study investigates the demographic, behavioural, and attitudinal factors associated with willingness to adopt V2G among 1358 members of a national Australian motorists’ association, a subgroup characterised by high rates of EV and solar PV ownership, established home-charging infrastructure, and greater-than-average energy technology engagement, consistent with a likely early-adopter population. An L1-regularised binomial logistic regression with cross-validated penalty selection is applied to a comprehensive set of candidate predictors to identify factors associated with adoption willingness. Behavioural reasoning theory is then applied as a retrospective interpretive lens for understanding reasons for and against V2G adoption and to consider implications for future uptake. The results show that adoption willingness is positively associated with rooftop solar and electric vehicle ownership, familiarity with the V2G concept, energy independence, and perceived financial and environmental benefits. Conversely, safety concerns and the perception of a lack of relevant benefits are associated with a reduced likelihood of adoption. Correlation diagnostics confirm limited multicollinearity among predictors, and regularisation highlights the relative importance of attitudinal factors over certain household characteristics. These findings align with previous qualitative research highlighting the importance of consumer education and trust, while providing new quantitative evidence on those most likely to adopt V2G. Importantly, this study draws on a sample of motorists’ association members who resemble likely early adopters of V2G, providing insights relevant to the initial phase of V2G market development. As the regulatory and technological barriers to V2G diminish, the social and behavioural dimensions will play a decisive role in shaping uptake. The insights from this research can inform targeted consumer awareness raising, product and value proposition design, business model development, and policy interventions aimed at supporting scalable V2G adoption.
Industrial sectors, especially those with significant global CO _2 emissions like the cement and concrete industries, are striving to achieve net-zero emissions by 2050. It is anticipated that carbon dioxide removal will be required to meet these goals. Hydrated cement in concrete can react with atmospheric CO _2 to form carbonate minerals (i.e. carbonation), and in doing so, act as a carbon uptake mechanism. This carbonation process can be accelerated via various engineering interventions, such as crushing concrete after demolition. In this literature review, we examine key parameters, including porosity, exposure conditions, CO _2 concentration, curing methods, coatings, and the use of supplementary cementitious materials, that affect CO _2 uptake in concrete to inform better quantification of life cycle emissions. These findings can inform the feasibility of implementing carbonation as a method for reducing emissions from cement-based materials and identify data limitations that need further study for future modeling efforts. Presently, it has been estimated that 9%–17% of concrete production emissions could be re-adsorbed during use and end of life. However, such estimates of uptake have only considered limited data sets, without fully addressing the comingled effects of the parameters impacting carbonation. Further, some carbon uptake modeling efforts may require input values that are not readily available, or may be challenging to repeat, and do not accurately account for carbon fluxes over the life cycle. Findings from this review highlight the importance of development of systematic approaches to assess cradle-to-grave life cycle assessments using dynamic carbon accounting when measuring concrete carbonation.
The electrification of light-duty vehicles (LDVs) is central to California's strategy to reduce greenhouse gas emissions from the transportation sector, which remains the state's largest source of emissions. Our study evaluates the projected electricity demand and associated emissions from statewide LDV electrification. Using adoption forecasts from the U.S. Department of Energy's EVI-Pro Lite tool, hourly grid carbon intensity profiles from the California Independent System Operator, and statewide electricity generation data from the U.S. Energy Information Administration, we assess charging demand and emissions across 75 cities in California. By incorporating demographic trends and driving behaviors, our modeling captures how regional differences in temperature, mileage, and grid carbon intensity affect outcomes for zero-emission vehicles (ZEVs). We reveal a threefold difference in energy demand and CO2 emissions between the best- and worst-case scenarios, underscoring the need for region-specific strategies to reduce emissions. Our results indicate that full LDV electrification would add between 81 and 305 TWh yr-1 of annual charging demand, relative to a modeled baseline of 109 TWh yr-1, approximately 19% lower than the CARB 2045 Scoping Plan projection of 137 TWh yr-1. Associated annual operational emissions average 69 979 metric tons CO2 yr-1 under baseline conditions but vary substantially across scenarios. Under high decarbonization conditions, emissions decline to 44 332 metric tons CO2 yr-1 (-36.7%), whereas under low-decarbonization conditions, emissions increase to 92 652 metric tons CO2 yr-1 (+32.4%). Adjustments to charging timing also strongly influence emissions outcomes. Daytime charging reduces emissions to 61 732 metric tons CO2 yr-1 (-11.8%), while nighttime charging and uniform charging patterns increase emissions to 81 973 metric tons CO2 yr-1 (+17.1%) and 71 852 metric tons CO2 yr-1 (+2.7%), respectively. These findings highlight the critical role of both electricity grid carbon intensity and charging behavior in determining the overall emissions outcomes of large-scale vehicle electrification. These results reaffirm that grid decarbonization remains the dominant structural driver of system-wide emissions, whereas behavioral factors, such as charging timing, serve as important but secondary levers. Although managed charging can yield meaningful near-term reductions by aligning load with renewable generation, long-term emissions trajectories will be shaped more profoundly by grid carbon intensity, travel demand, and improvements in vehicle efficiency. Our findings emphasize the crucial roles of both grid decarbonization and carbon-aware charging strategies in maximizing the climate benefits of electrifying transportation. By incorporating behavioral, demographic, and regional differences into emissions modeling, our study provides practical insights for policymakers and stakeholders seeking to align large-scale ZEV adoption with California's carbon-neutrality objectives.
Accurate and spatially consistent digital representations of the built environment are essential for urban infrastructure analysis, sustainability assessment, and planning, particularly in countries experiencing rapid urbanisation, such as India. GlobalBuildingAtlas (GBA) is a recently released open-access global dataset that provides individual building footprints, building heights, and level of detail-1 (LoD1) three-dimensional building models. However, its suitability for digital urban infrastructure applications across diverse urban contexts remains largely unevaluated. This study presents an independent assessment of GBA at the individual-building scale, focusing on footprint completeness and building height accuracy using independent reference data. Building footprint completeness was evaluated across five gated residential communities using reference building counts derived from automated extraction applied to very high-resolution satellite imagery, while building height accuracy was assessed for representative structures intersected by ICESat-2 laser altimetry ground tracks using photon-based height estimates. Results show that GBA achieves high building footprint completeness in planned low-rise residential developments, with completeness ratios exceeding 99% and minimal count discrepancies, supporting its use as a reliable digital representation of horizontal urban infrastructure. In contrast, building height estimates exhibit a systematic negative bias, with errors increasing for mid-rise and high-rise buildings, consistent with limitations associated with monocular optical imagery-based height inference, the uneven geographic distribution of LiDAR training data, and the geometric abstraction inherent to LoD1 building representations. Overall, the findings indicate that GBA provides a robust foundation for digital urban infrastructure and sustainability-oriented applications in India, while underscoring the need for caution and region-specific validation when its height component is applied in vertically complex urban environments.
Centralized wastewater treatment systems can improve wastewater management in urbanizing tropical ecotourism communities. The urban center of Monteverde, Costa Rica, faces numerous challenges in handling increasing wastewater loads resulting from population growth and tourism, which can overwhelm existing septic systems. Additionally, Monteverde stakeholders desire to integrate the recovery of energy, nutrients, and water during the treatment process. The overall goal of this study was to identify a suitable wastewater treatment scenario that reduces environmental, economic, and social impacts. Three centralized wastewater treatment scenarios were investigated: an upflow anaerobic sludge blanket (UASB) reactor with an activated sludge system, a UASB reactor with a constructed wetland (UASB-CW), and a UASB reactor with a trickling filter system (UASB-TF). Life cycle assessment and life cycle cost analysis were used to assess the environmental and economic impacts, respectively, of each scenario. Additionally, the social and technical aspects were investigated to achieve a holistic assessment approach using a modified version of the social, environmental, economic wastewater decision support system tool. The UASB-TF was identified as the most sustainable option because of its low capital costs, carbon footprint, eutrophication potential, and social and technical impacts. The UASB-CW was considered the least preferred option due to its high carbon footprint, high capital cost, and large land area requirements. This SEE tool can be used in other urbanizing tropical ecotourism communities for identifying sustainable wastewater treatment alternatives.
Background. Infrastructure systems are threatened by extreme weather events, such as river flooding. Climate change increases the frequency and severity of flooding, resulting in more repairs and operational disruptions. While this explains a clear need to adapt to changing hazards, it is often difficult to compare all adaptation options that infrastructure can benefit from in a coherent way. Objective. The aim of this paper is to propose a four-level framework for infrastructure adaptation, from asset- to system-level, and demonstrate its application in a case study of railway adaptation to flooding. Method. We apply a framework to appraise adaptation options against flooding at hazard-, asset-, network-, and system-levels in the case of a railway line in Rhineland-Palatinate, Germany. Results. Baseline flood risk for railways in Rhineland-Palatinate is & euro;102 million yr-1 (mean), with indirect losses accounting for 53% of total risk. Climate change could increase this risk by up to 310% by 2120. About 38% of the rail network length can be partly flooded, compared to a 17% Germany-wide average. None of the adaptation options were economically efficient under all scenarios (BCR > 1), but efficiency varied by location: floodwalls (L1) reached benefit-to-cost ratio (BCR) 0.88 in one area, while new network connections (L3) reached BCR 1.08 in another. Conclusion. Accounting for both flood damages and losses arising from network disruptions is essential for appraising flood adaptation options for railways. Adaptation effectiveness and economic efficiency are highly location-specific. Measures that reduce indirect losses, such as network redundancies, can outperform asset-level measures in some contexts. No single option is robust across all scenarios, highlighting the value of multi-level strategies and location-tailored planning.
Optimal design of timber roof truss topology, geometry, and cross-sections is limited in practice due to the absence of integrated, code-aware design tools. This paper presents a Grasshopper 3D-based optimisation plug-in. The plug-in combines site-specific action generation with Eurocode 1, finite element analysis in Karamba3D, Eurocode 5 member checks in Python and genetic algorithm (GA)-based topology and geometry search within a single parametric workflow. Considering three truss types Fink, Pratt, and Howe cross-section sizing is performed against a discrete library of solid timber sections. Optimised models export to Industry Foundation Class format, supporting interoperability with building information modelling based coordination tools. The plug-in is applied across six Norwegian locations, as well as four inventory scenarios consisting of one new and three reclaimed component stocks. This results in location-specific, minimum mass roof configurations that satisfy Eurocode ultimate limit states. Cross-section optimisation with Eurocode 5 compliance checks executes in under 20 s on a standard office computer. The overall computational cost is dominated by the GA, with total runtimes varying according to truss type and stock composition, ranging from a minimum of 1 h 15 min to a maximum of 5 h 54 min. The applicability of the plug-in is constrained by predefined geometric limits, including a roof pitch between 20 degrees and 35 degrees, bay spacing from 1.55 m to 2.8 m, and web member spacing between 0.7 m and 1.25 m. Cost and embodied carbon (EC) assessments show that minimising mass alone is an insufficient objective when connection contributions are included. Plug-in extensions to broader geometry, more locations, direct cost and EC optimisation, and reliability-based design for reclaimed stock are identified as priorities for future work.
Different jurisdictions across the United States continue to implement Buy Clean policies that mandate infrastructure agencies to benchmark greenhouse gas emissions associated with construction materials. Therefore, understanding how to categorize those materials reliably has become a relevant point of departure to ensure a fair analysis and comparison of their life cycle assessment results. Colorado's Buy Clean legislation specifically requires materials to be assessed on a cradle-to-gate (A1-A3) scope due to the current state of environmental product declaration (EPD) reporting, the production stage emphasis associated with suppliers for threshold setting, and the substantial impact of cradle-to-gate emissions on the overall life cycle of construction materials. This study proposes an assessment of how asphalt plant mobility (stationary versus portable plants) influences the global warming potential (GWP) of asphalt mixtures by analyzing life cycle modules from raw material supply to transportation to the construction site (A1-A4) in Colorado. The scope is expanded beyond the production stage to evaluate the effect of plant placement relative to a construction site (A4). Plant mobility can systematically influence mixture design decisions (A1), transportation distances to a manufacturing plant (A2), and manufacturing emissions (A3), potentially evidenced by notable differences in GWP results. This study summarizes available EPD information for stationary and portable asphalt plants in Colorado, in conjunction with a broader job mix formula information submitted for placement on Colorado Department of Transportation projects. The study concluded that portable and stationary plants should be categorized differently based on statistically significant differences in the currently available data.
As electric vehicle (EV) adoption continues to increase, the strategic siting of EV charging infrastructure (EVCI) is critical to ensuring equitable access to clean transportation. Existing EVCI installations are often concentrated in affluent areas, with substantial disparities in public charging access across regions with different demographic characteristics. Traditional EVCI siting approaches prioritize logistic viability, corridor charging, and existing EV uptake, which can reinforce accessibility gaps. As a result, communities that may benefit most from electrification, such as lower-income populations with higher pollution burdens, are frequently overlooked, while potential health and air quality benefits remain under-considered in siting decisions. This study develops a spatial suitability modeling framework to assess how the inclusion of social and health-based criteria influences EVCI siting outcomes. Using a case study of Merced, California, a city characterized by poor air quality and a predominantly minority population, we integrate indicators such as asthma prevalence, particulate matter exposure, and demographic vulnerability into a multi-criteria decision analysis framework. Sensitivity analyses evaluate the influence of equity and health criteria inclusion, weighting scenarios, and alternative charging density measurements on suitability outcomes. Results demonstrate that both criteria choices and weight scenarios substantially affect spatial siting outcomes, revealing areas that are highly sensitive to modeling assumptions as well as locations that remain robust across scenarios. These findings suggest that while tools such as the geospatial energy mapper provide a valuable foundation for identifying candidate charging locations, equity-focused scenario testing and informed criteria selection are essential for more transparent and just EVCI planning.
Extreme heat is a growing source of health-related risk in cities, and urban greening is widely promoted as a strategy to reduce its adverse consequences. However, urban green space can be measured in very different ways, and it remains unclear whether commonly used metrics are interchangeable when estimating health-relevant cooling benefits. Here we test how green space metric choice affects inferred heat-mortality attenuation in Paris using a harmonised arrondissement-day panel for the 2008-2017 summer seasons, combining daily mortality, 100-meter resolution UrbClim heat fields, and three urban vegetation measurement approaches: street-level green view index (GVI), satellite-derived normalized difference vegetation index (NDVI), and local planimetry-based vegetation cover (IMU). We estimate conditional time-series distributed lag non-linear models across nine heat indicators. Greener arrondissements consistently show lower heat-related mortality risk: across all 45 heat-metric and greenness-metric combinations assessed. Street-level GVI yields the strongest central attenuation estimate, followed closely by NDVI, and finally by IMU. For example, for mean daily wet-bulb globe temperature, the central estimate for the attenuation in heat-related mortality risk is 18.5% with GVI, compared with 16% for NDVI and 14% for planimetry-based vegetation. Despite uncertainty around individual effect sizes, the consistent directional ordering across all three metrics suggests that green-space indicators are not interchangeable in heat-health research. Metric and weighting choices made upstream-in how vegetation is measured and spatially aggregated-can materially alter estimated health burdens and, in some cases, even reverse their sign, with direct consequences for policy recommendations. We treat these findings as hypothesis-generating: more systematic investigation across cities and climate contexts is needed to establish which representations of urban greenness best capture heat-relevant cooling benefits.
The construction sector's high carbon footprint has intensified interest in bio-based materials with integrated energy efficiency and carbon storage potential. Insulation materials are one interesting sub-field, where conventional materials are typically either energy-intensive or made of petroleum-based plastics, but where bio-based alternatives exist, and where new materials are emerging. Mycelium-based composites (MBCs) are one such emerging new material as a thermally efficient alternative to high-emission materials; however, strategies for fireproofing and fabrication are still underdeveloped. Here, we investigate how fabrication strategy and additive selection jointly govern the microstructure, mechanical properties, thermal performance, and fireproofing of MBCs grown from Ganoderma lucidum on birch woodchip substrates. Bio-composites were produced via two distinct fabrication routes-block-grown and mold-grown-and modified with sheep wool fibers or silica particles. Several testing methods were applied to evaluate mechanical and thermophysical characteristics, whereas the fabrication method was the primary driver of densification and surface integument formation, with bulk densities ranging from 140 to 200 kg m-3. Block-grown samples developed a continuous mycelial skin and exhibited thermal conductivities of 0.059-0.066 W m & centerdot;K-1, consistent with insulation-grade performance. Compressive strengths reflect the material's porous architecture while meeting requirements for non-load-bearing applications. When exposed to controlled direct flame, fireproofing performance varied notably among formulations, with wool-reinforced composites showing the highest resistance and outperforming control samples significantly. The outcomes from applied route fabrication were then linked by microstructural analysis via scanning electron microscopy (SEM), where distinct hyphal organizations were observed. Wool fibers promoted fiber-hyphae interlocking and network continuity, whereas silica addition disrupted filament connectivity. The results establish a direct relationship between growth confinement, microstructural development, and flame resistance. This study demonstrates that adjusting fabrication strategies and additive use accordingly allows for control over microstructure and fire performance, advancing the development of mycelium- based composites for low- rise building applications.
Cities across Sub Saharan Africa face mounting climate risks, yet many lack financial resources, institutional capacity, and planning tools needed to implement effective and locally relevant resilience strategies. Recent research underscores the critical role of urban NbS in addressing the growing challenges faced by rapidly expanding African cities. To support local decision-making, World Resources Institute developed the Strategic NbS Framework—a practical tool designed to help cities identify, evaluate, and prioritize NbS interventions that align with community needs and climate vulnerabilities. This paper examines the application of the Framework in two pilot cities, Addis Ababa and Kigali, and distills actionable lessons for policymakers, urban planners, and civil society actors working to integrate NbS into urban development and climate resilience planning.
Sustainable and integrated urban mass transit planning not only enhances mobility but also plays a decisive role in mitigating climate change. Light rail transit (LRT) is increasingly being integrated into urban traffic systems and city landscapes, although several integration challenges remain. The Addis Ababa LRT, introduced in 2015 as Sub-Saharan Africa's first light rail system, has since faced varied opinions from the public and academic spheres regarding its efficiency and integration. This study aimed to objectively analyze the spatial integration of the LRT and its effects on urban mobility and sustainability. It examined the structural configuration of the LRT lines, their impact on vehicular and pedestrian traffic, and compatibility with standards. A descriptive research design was adopted, utilizing both primary and secondary data. Primary data were collected through field visits, pedestrian and motorized traffic crossing inventories and mapping, and key informant interviews (KIIs). The study found that the spatial integration and sustainability of the Addis Ababa LRT are low, with significant noncompliance to standards, resulting in poor compatibility with both motorized and pedestrian traffic. The average exceedance score of the motorized crossing is 0.53 (which means 53% incompliance with the standard) for the East-West LRT, and 70% of incompliance for the North-South LRT, indicating very low compatibility and inadequate spatial integration. Exceedance of pedestrian crossing standards is also markedly high: 240% for the East-West and 160% for the North-South LRT, more than a twofold deviation from the standard. The center-periphery analysis provided better compliance in the center of business district compared to the peripheral areas. There is also a notable contrast in incompliance rates between the two lines: 59% and 78% of their respective total lengths. KII results align with the compliance findings and highlight the low spatial integration of the LRT and its implications for sustainability: increased travel, low permeability, and urban segregation, thereby undermining overall sustainability and compromising the LRT's clean transport benefits.
