Impact of Building Structure on Heat Storage Flux Estimation: An Observational Case Study in Beijing

The urban heat storage flux, <inline-formula> <tex-math notation="LaTeX">$Q_{\mathrm {S}}$ </tex-math></inline-formula>, is one of the main drivers of the nocturnal urban heat island effect. However, the complex 3-D building structure makes observations and simulations of <inline-formula> <tex-math notation="LaTeX">$Q_{\mathrm {S }}$ </tex-math></inline-formula> difficult. This study observes the 3-D surface radiant temperature (<inline-formula> <tex-math notation="LaTeX">$T_{\mathrm {s}}$ </tex-math></inline-formula>) of a building in Beijing, China. The element surface temperature method (ESTM) and the half-order (HO) method are compared for <inline-formula> <tex-math notation="LaTeX">$Q_{\mathrm {S}}$ </tex-math></inline-formula> simulation using <inline-formula> <tex-math notation="LaTeX">$T_{\mathrm {s}}$ </tex-math></inline-formula> observations. The impact of building structure on <inline-formula> <tex-math notation="LaTeX">$Q_{\mathrm {S}}$ </tex-math></inline-formula> and urban heat island intensity (UHII) are also studied. Results show the following. First, <inline-formula> <tex-math notation="LaTeX">$Q_{\mathrm {S}}$ </tex-math></inline-formula>’s simulated by ESTM and HO are nearly the same for walls. However, the HO method only needs one-layer exterior surface temperature, which has great potential for regional <inline-formula> <tex-math notation="LaTeX">$\Delta Q_{\mathrm {S}}$ </tex-math></inline-formula> simulation by satellite remote sensing data. Second, during the daytime, <inline-formula> <tex-math notation="LaTeX">$Q_{\mathrm {S}}$ </tex-math></inline-formula>’s of each facet are significantly different from each other. The maximum observed difference of <inline-formula> <tex-math notation="LaTeX">$Q_{\mathrm {S}}$ </tex-math></inline-formula> is up to 452 W/m<sup>2</sup> between the roof and north wall in May 2019. Third, complete <inline-formula> <tex-math notation="LaTeX">$Q_{\mathrm {S}}$ </tex-math></inline-formula> (<inline-formula> <tex-math notation="LaTeX">$Q_{\mathrm {S, c}}$ </tex-math></inline-formula>) is calculated by each facet <inline-formula> <tex-math notation="LaTeX">$Q_{\mathrm {S}}$ </tex-math></inline-formula> and area fraction. The relationships between UHII and both 2-D <inline-formula> <tex-math notation="LaTeX">$Q_{\mathrm {S}}$ </tex-math></inline-formula>(roof <inline-formula> <tex-math notation="LaTeX">$Q_{\mathrm {S}}$ </tex-math></inline-formula>) and 3-D <inline-formula> <tex-math notation="LaTeX">$Q_{\mathrm {S }}(Q_{\mathrm {S, c}})$ </tex-math></inline-formula> are studied. <inline-formula> <tex-math notation="LaTeX">$Q_{\mathrm {S}}$ </tex-math></inline-formula> is positively correlated with nocturnal UHII, and 3-D <inline-formula> <tex-math notation="LaTeX">$Q_{\mathrm {S}}$ </tex-math></inline-formula> corresponds more closely to UHII with a larger Spearman’s coefficient (<inline-formula> <tex-math notation="LaTeX">$p < 0.05$ </tex-math></inline-formula>). This study presents the effect of building structure on heat flux and could provide an insight for future <inline-formula> <tex-math notation="LaTeX">$Q_{\mathrm {S}}$ </tex-math></inline-formula> and urban heat island (UHI) studies.