Urban warming and future air-conditioning use in an Asian megacity: importance of positive feedback

The impact of feedback between urban warming and air-conditioning (AC) use on temperatures in future urban climates is explored in this study. Pseudo global warming projections are dynamically downscaled to 1 km using a regional climate model (RCM) coupled to urban canopy and building energy models for current and six future global warming (ΔTGW) climates based on IPCC RCP8.5. Anthropogenic heat emissions from AC use is projected to increase almost linearly with ΔTGW, causing additional urban warming. This feedback on urban warming reaches 20% of ΔTGW in residential areas. This further uncertainty in future projections is comparable in size to that associated with: a selection of emission scenarios, RCMs and urban planning scenarios. Thus, this feedback should not be neglected in future urban climate projections, especially in hot cities with large AC use. The impact of the feedback during the July 2018 Japanese heat waves is calculated to be 0.11ºC

Anthropogenic heat flux: advisable spatial resolutions when input data are scarce

Anthropogenic heat flux (QF) may be significant in cities, especially under low solar irradiance and at night. It is of interest to many practitioners including meteorologists, city planners and climatologists. QF estimates at fine temporal and spatial resolution can be derived from models that use varying amounts of empirical data. This study compares simple and detailed models in a European megacity (London) at 500 m spatial resolution. The simple model (LQF) uses spatially resolved population data and national energy statistics. The detailed model (GQF) additionally uses local energy, road network and workday population data. The Fractions Skill Score (FSS) and bias are used to rate the skill with which the simple model reproduces the spatial patterns and magnitudes of QF, and its sub-components, from the detailed model. LQF skill was consistently good across 90% of the city, away from the centre and major roads. The remaining 10% contained elevated emissions and B hot spots ^ representing 30 – 40% of the total city-wide energy. This structure was lost because it requires workday population, spatially resolved building energy consumption and/or road network data. Daily total building and traffic energy consumption estimates from national data were within ± 40% of local values. Progressively coarser spatial resolutions to 5 km improved skill for total Q F , but important features (hot spots, transport network) were lost at all resolutions when residential population controlled spatial variations. The results demonstrate that simple QF models should be applied with conservative spatial resolution in cities that, like London, exhibit time-varying energy use patterns

Analysis of the urban heat island effects on building energy consumption

Urban areas usually experience higher temperatures when compared to their rural surroundings. Several studies underlined that specific urban conditions are strictly connected with the Urban heat island (UHI) phenomenon, which consists in the environmental overheating related to anthropic activities. As a matter of fact, urban areas, characterized by massive constructions that reduce local vegetation coverage, are subject to the absorption of a great amount of solar radiation (short wave) which is only partially released into the atmosphere by radiation in the thermal infrared (long wave). On the contrary, green areas and rural environments in general show a reduced UHI effect, that is lower air temperatures, due to evapo-transpiration fluxes. Several studies demonstrate that urban microclimate affects buildings’ energy consumption and calculations based on typical meteorological year could misestimate their actual energy consumption. In this study, two different sets of meteorological data are used for the calculation of the heating and cooling energy needs of an existing university building. The building is modeled using TRNSYS v.17 software. The first set of data was collected by a weather station located in the city center of Modena, while the second set of data was collected by another station, located in the surrounding area of the city, near to the studied building. The influence of the different meteorological situations described by the two weather stations are analyzed and assumed to be representative of the UHI effect. Furthermore, the effects of UHI mitigation strategies on the building energy needs are evaluated and discussed

Interlayer bond formation in black phosphorus at high pressure

Black phosphorus was compressed at room temperature across the A17, A7 and simple‐cubic phases up to 30 GPa, using a diamond anvil cell and He as pressure transmitting medium. Synchrotron X‐ray diffraction showed the persistence of two previously unreported peaks related to the A7 structure in the pressure range of the simple‐cubic phase. The Rietveld refinement of the data demonstrates the occurrence of a two‐step mechanism for the A7 to simple‐cubic phase transition, indicating the existence of an intermediate pseudo simple‐cubic structure. From a chemical point of view this study represents a deep insight on the mechanism of interlayer bond formation during the transformation from the layered A7 to the non‐layered simple‐cubic phase of phosphorus, opening new perspectives for the design, synthesis and stabilization of phosphorene‐based systems. As superconductivity is concerned, a new experimental evidence to explain the anomalous pressure behavior of Tc in phosphorus below 30 GPa is provided

Energy saving potential of fragmented green spaces due to their temperature regulating ecosystem services in the summer

Urban green spaces help to moderate the urban heat island (UHI) effects, and can provide important temperature regulating ecosystem services and opportunities for savings in cooling energy. However, because explicit market values for these benefits are still lacking, they are rarely incorporated into urban planning actions. Green spaces can generate a three-dimensional (3D) cool island that may reduce the cooling energy requirements within and around urban areas, but such 3D cooling effect has not been considered in previous studies quantifying energy savings from green spaces. This study presents a new and simple approach to quantify potential energy savings due to the temperature regulating ecosystem services of small-scale fragmented green spaces using the 3D simulation of the summer-day outdoor thermal environment in Nanjing, China. Field survey data and the microclimate model ENVI-met were applied to examine the outdoor 3D thermal environmental patterns at Gulou Campus of Nanjing University under two different scenarios: “with” and “without” green spaces. Modeling results were applied to quantify potential cooling energy savings based on the effect of green spaces on the outdoor urban environment and to calculate the cumulative temperature reduction due to green spaces using a regression model. The results show that, in the horizontal direction, the simulated distribution of wind speed and mean air temperature at 1.5 m height were closely related to the spatial distribution of the underlying surface types. Removal of green spaces increased mean air temperature by 0.5 °C (33.1 °C vs. 33.6 °C). In the vertical direction, removal of green spaces had little effect on the near-surface wind field; however, above the surface, the turbulence perpendicular to the main wind direction significantly increased. Quantification of the cooling benefits of green spaces in relation to the mean height of buildings on Gulou Campus yielded 5.2 W/m2 cooling energy, saving totally 1.3 × 104 kW h during a single daytime hot summer period. This case study corroborates the importance of green space for cooling and informs city planners and decision-makers on how microclimate is impacted by the loss of green spaces. These findings will facilitate preservation, planning, and design of green spaces to increase urban environmental benefits and to improve the microclimate of urban areas at neighborhood, city, and regional scales