Summary Building stock constitutes a huge repository of construction materials in a city and a potential source for replacing primary resources in the future. This article describes the application of a methodological approach for analyzing the material stock (MS) in buildings and its spatial distribution at a city‐wide scale. A young Latin‐American city, the city of Chiclayo in Peru, was analyzed by combining geographical information systems (GIS) data, census information, and data collected from different sources. Application of the methodology yielded specific indicators for the physical size of buildings (i.e., gross floor area and number of stories) and their material composition. The overall MS in buildings, in 2007, was estimated at 24.4 million tonnes (Mt), or 47 tonnes per capita. This mass is primarily composed of mineral materials (97.7%), mainly concrete (14.1 Mt), while organic materials (e.g., 0.15 Mt of wood) and metals (e.g., 0.40 Mt of steel) constitute the remaining share (2.3%). Moreover, historical census data and projections were used to evaluate the changes in the MS from 1981 to 2017; showing a 360% increase of the MS in the last 36 years. This study provides essential supporting information for urban planners, helping to provide a better understanding of the availability of resources in the city and its future potential supply for recycling as well as to develop strategies for the management of construction and demolition waste.

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In our rapidly urbanizing world, many hazard-prone regions face significant challenges regarding risk-informed urban development. This study addresses this issue by investigating evolving spatial interactions between natural hazards, ever-increasing urban areas, and social vulnerability in Kathmandu Valley, Nepal. The methodology considers: (1) the characterization of flood hazard and liquefaction susceptibility using pre-existing global models; (2) the simulation of future urban built-up areas using the cellular-automata SLEUTH model; and (3) the assessment of social vulnerability, using a composite index tailored for the case-study area. Results show that built-up areas in Kathmandu Valley will increase to 352 km2 by 2050, effectively doubling the equivalent 2018 figure. The most socially vulnerable villages will account for 29% of built-up areas in 2050, 11% more than current levels. Built-up areas in the 100-year and 1000-year return period floodplains will respectively increase from 38 km2 and 49 km2 today to 83 km2 and 108 km2 in 2050. Additionally, built-up areas in liquefaction-susceptible zones will expand by 13 km2 to 47 km2. This study illustrates how, where, and to which extent risks from natural hazards can evolve in socially vulnerable regions. Ultimately, it emphasizes an urgent need to implement effective policy measures for reducing tomorrow's natural-hazard risks.

Structural risk-mitigation measures have been shown to significantly reduce earthquake-induced physical damage and casualties in various regions worldwide. However, these benefits remain unknown or inadequately quantified for potential future events in some hazard-prone areas such as Kathmandu Valley, Nepal, which this article addresses. The analysis involves modeling an earthquake scenario similar to the 2015 Gorkha earthquake (moment magnitude 7.8) and using four exposure inventories representing the current (2021) urban system or near-future (2031) development trajectories that Kathmandu Valley could experience. The results predict substantial losses (€8.2 billion in repair/reconstruction costs and 89,199 fatalities) in 2021 if the building stock’s quality is assumed to have remained the same as in 2011 (Scenario A). However, a partial improvement of the building stock’s quality in the present (Scenario B) can decrease financial losses and fatalities by 17% and 44%, respectively. Moreover, under a “no change” pathway for 2031 (Scenario C), where the quality of the expanding building stock remains the same as in 2011, and the number of buildings is larger to reflect population growth, financial losses and fatalities will increase by 20% and 25% respectively over those of Scenario A. In contrast, further upgrades to the building stock’s quality by 2031 (Scenario D) would reduce financial and human losses by 14% and 54% respectively, relative to those of Scenario A. In addition, the largest financial and human losses computed in the four scenarios are consistently associated with the low- and middle-income population. The main findings of this article can be used to inform decision makers about the benefits of investing in forward-looking seismic risk-mitigation efforts.

Abstract. Flood risk is expected to increase in many regions worldwide due to rapid urbanization and climate change if adequate risk-mitigation (or climate-change-adaptation) measures are not implemented. However, the exact benefits of these measures remain unknown or inadequately quantified for potential future events in some flood-prone areas such as Kathmandu Valley, Nepal, which this paper addresses. This study examines the present (2021) and future (2031) flood risk in Kathmandu Valley, considering two flood occurrence cases (with 100-year and 1000-year mean return periods) and using four residential exposure inventories representing the current urban system (Scenario A) or near-future development trajectories (Scenarios B, C, D) that Kathmandu Valley could experience. The findings reveal substantial mean absolute financial losses (EUR 473 million and 775 million in repair and reconstruction costs) and mean loss ratios (2.8 % and 4.5 %) for the respective flood occurrence cases in current times if the building stock's quality is assumed to have remained the same as in 2011 (Scenario A). Under a “no change” pathway for 2031 (Scenario B), where the vulnerability of the expanding building stock remains the same as in 2011, mean absolute financial losses would increase by 14 %–16 % over those of Scenario A. However, a minimum (0.20 m) elevation of existing residential buildings located in the floodplains and the implementation of flood-hazard-informed land-use planning for 2031 (Scenario C) could decrease the mean absolute financial losses of the flooding occurrences by 9 %–13 % and the corresponding mean loss ratios by 23 %–27 %, relative to those of Scenario A. Moreover, an additional improvement of the building stock's vulnerability that accounts for the multi-hazard-prone nature of the valley (by means of structural retrofitting and building code enforcement) for 2031 (Scenario D) could further decrease the mean loss ratios by 24 %–28 % relative to those of Scenario A. The largest mean loss ratios computed in the four scenarios are consistently associated with populations of the highest incomes, which are largely located in the floodplains. In contrast, the most significant benefits of risk mitigation (i.e., largest reduction in mean absolute financial losses or mean loss ratios between scenarios) are experienced by populations of the lowest incomes. This paper's main findings can inform decision makers about the benefits of investing in forward-looking multi-hazard risk-mitigation efforts.