Estimating the daily peak and annual total electricity demand for cooling in Vienna, Austria by 2050

Bird, David Neil; Wit, Rosmarie de; Schwaiger, H.; Andre, Konrad; Beermann, Martin; Žuvela‐Aloise, Maja

doi:10.1016/j.uclim.2019.100452

Cited by 13 publications

(2 citation statements)

References 42 publications

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“…Here we characterize heterogeneous local climate adaptation by leveraging fine spatial and temporal scale data to model the transient response of electricity to temperature. Our approach draws on substantial empirical literature on the effect of temperature on the demand for energy generally 11 , 13 , 14 , and electricity specifically 9 , 15 – 20 to characterize the response of electric power consumption to temperature in 36 global cities on an hourly time step, and quantify the impact on high-frequency electricity demand of mid-century climate warming.…”

Section: Introductionmentioning

confidence: 99%

Heterogeneous climate change impacts on electricity demand in world cities circa mid-century

Romitti

Wing

2022

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Rising ambient temperatures due to climate change will increase urban populations’ exposures to extreme heat. During hot hours, a key protective adaptation is increased air conditioning and associated consumption of electricity for cooling. But during cold hours, milder temperatures have the offsetting effect of reducing consumption of electricity and other fuels for heating. We elucidate the net consequences of these opposing effects in 36 cities in different world regions. We couple reduced-form statistical models of cities’ hourly responses of electric load to temperature with temporally downscaled projections of temperatures simulated by 21 global climate models (GCMs), projecting the effects of warming on the demand for electricity circa 2050. Cities' responses, temperature exposures and impacts are heterogeneous, with changes in total annual consumption ranging from $$-2.7$$ - 2.7 to 5.7%, and peak power demand increasing by as much as 9.5% at the multi-GCM median. The largest increases are concentrated in more economically developed mid-latitude cities, with less developed urban areas in the tropics exhibiting relatively small changes. The results highlight the important role of the structure of electricity demand: large temperature increases in tropical cities are offset by their inelastic responses, which can be attributed to lower air-conditioning penetration.

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Section: Introductionmentioning

confidence: 99%

Heterogeneous climate change impacts on electricity demand in world cities circa mid-century

Romitti

Wing

2022

Sci Rep

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“…However, LST requires conversion in some manner to air temperatures to be useful with many other studies of the benefits of NBS and the impacts of high urban air temperatures. For example, the daily mean air temperature has been related to human mortality and health [5] and energy demand for cooling [6]. Adding a spatially continuous proxy for weather station air temperature components on multiple days may improve the results of the analyses and identify hot spots (pun intended).…”

Section: Introductionmentioning

confidence: 99%

Combining Spatial and Temporal Data to Create a Fine-Resolution Daily Urban Air Temperature Product from Remote Sensing Land Surface Temperature (LST) Data

et al. 2022

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Remotely sensed land surface temperature (LST) is often used as a proxy for air temperature in urban heat island studies, particularly to illustrate relative temperature differences between locations. Two sensors are used predominantly in the literature, Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS). However, each has shortcomings that currently limit its utility for many urban applications. Landsat has high spatial resolution but low temporal resolution, and may miss hot days, while MODIS has high temporal resolution but low spatial resolution, which is inadequate to represent the fine grain heterogeneity in cities. In this paper, we overcome this inadequacy by combining high spatial frequency Environmental Services (ES), Landsat-driven Normalized Difference Vegetation Index (NDVI), and MODIS low spatial frequency background LST at different spatial frequency bands (spatial spectral composition). The method is able to provide fine scale LST four times daily on any day of the year. Using data from Paris in 2019 we show that (1) daytime cooling by vegetation reaches a maximum of 30 °C, above which there is no further increase in cooling. In addition, (2) the cooling is relatively local and does not extend further than 200 m beyond the boundary of the NBS. This model can be used to quantify the benefits of NBS in providing cooling in cities.

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The Urban Surface and Heatwaves

McGregor

2024

Biometeorology

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Estimating the daily peak and annual total electricity demand for cooling in Vienna, Austria by 2050

Cited by 13 publications

References 42 publications

Heterogeneous climate change impacts on electricity demand in world cities circa mid-century

Heterogeneous climate change impacts on electricity demand in world cities circa mid-century

Combining Spatial and Temporal Data to Create a Fine-Resolution Daily Urban Air Temperature Product from Remote Sensing Land Surface Temperature (LST) Data

The Urban Surface and Heatwaves

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