Household-scale decision support for climate-resilient urban greening informed by monitoring and modelling

UK homes are increasingly exposed to summertime overheating and traffic-related air pollution, alongside growing risks from intense rainfall, biodiversity decline, and unequal access to health-supportive green space. However, evidence on the effectiveness of greening at the household boundary, where residents can implement rapid and affordable interventions in front gardens, back gardens and balconies, remains fragmented and difficult to translate into actionable guidance. This study addresses that gap by producing integrated, decision-ready evidence on the environmental and socio-ecological performance of household-scale green-blue-grey infrastructure across five outcome domains: air quality, overheating, flooding, biodiversity, and health and well-being. This study combines real-world monitoring, process-based microclimate modelling, and decision support development. A living lab network is established, comprising two front gardens, three back gardens, and one balcony, selected to represent common UK residential configurations and contrasting degrees of enclosure, surface cover, and greening potential. Multi-season monitoring captures exposure-relevant conditions, including air temperature and relative humidity, for overheating-related metrics, as well as particulate indicators such as PM2.5 and PM10, for near-boundary air quality. Complementary site surveys document features that mediate performance and enable transferability, including garden and balcony geometry, boundary permeability, surface materials and permeability, vegetation structure, and practical constraints on installation and upkeep. These datasets are used to parameterise and evaluate site-specific ENVI met models capable of reproducing observed microclimate and near-boundary air quality patterns. The validated models then support the systematic testing of alternative intervention configurations, placements, and intensities under current conditions and future climate stress test scenarios. Simulation ensembles quantify how intervention design and meteorological variability influence multi-benefit performance, while explicitly considering trade-offs, such as cooling gains from shading and evapotranspiration versus potential reductions in ventilation, or boundary sheltering effects that may alter pollutant dispersion patterns. The study provides a decision support tool that integrates environmental outcomes and DIY feasibility to guide household action. The tool links simple user inputs, including space type, exposure, and constraints, to ranked intervention options with indicative co-benefit ranges across the five environmental domains, alongside DIY factors such as cost, required expertise, space availability, maintenance burden, and an indicative cost-benefit perspective. A suite of DIY cards complements the tool by translating monitoring and modelling insights into step-by-step guidance on what to install, where to place it, and expected outcomes across air quality, overheating, flooding, biodiversity, and health and wellbeing, as well as typical installation and maintenance considerations. Together, these outputs support informed resident decision-making and provide local authorities and community partners with a scalable and consistent evidence base for promoting household-level climate adaptation.