Effects of Nature-based Solution Configurations on Indoor Energy and Outdoor Comfort in Rowhouse Neighborhoods: An Integrated Microclimate-Energy Simulation Approach

With climate change amplifying heat island effects in cities, using Nature-based Solutions (NbS) for climate adaptation becomes essential, especially in areas where buildings are tightly packed. In rowhouse neighborhoods, where open space is scarce and air conditioning is often limited, NbS in the form of urban vegetation serve as a main way to adjust to the heat island effect. However, the integration of NbS into these constrained environments presents complex challenges regarding spatial scales and ecosystem service trade-offs. Though trees can lower air temperature through moisture release and shading, poor layout might slow wind movement or trap heat at ground level. This work aims to examine how planting decisions may affect the targets of maximizing indoor energy conservation and optimizing outdoor thermal comfort.

A combined simulation framework was created by linking a detailed microclimate model (ENVI-met) with a building energy simulation model (EnergyPlus) for considering indoor energy efficiency and outdoor thermal comfort. Applied in a rowhouse block in Baltimore, Maryland (USA), the simulation framework was validated against on-site sensor data. To examine the planting patterns' effect on both thermal comfort and energy efficiency, we created a pipeline to systematically generate tree configurations at the block scale, and we utilize morphological indices, including the aggregation index, nearest neighbor distance, and centripetal index, to categorize distinct vegetation patterns. The effects of spatial characteristics on simulated microclimatic and building performance will be determined by statistical analysis. 

The microclimate model demonstrates high predictive accuracy, yielding a R-squared of 0.95 and a root mean square error (RMSE) of 0.831°C on air temperature in the reference day. Preliminary assessments suggest that the efficacy of NbS in this context is highly sensitive to the spatial arrangement of individual trees. Following the conducted simulation, further analysis aims to clarify the relationships between vegetation spatial heterogeneity, microclimatic variance, and building energy demand. The findings will provide practical, data-backed advice for decision-makers and community leaders to implement resilient, multi-purpose NbS planning strategies tailored to the specific layout of rowhouse neighborhoods.