High‐resolution (space, time) anthropogenic heat emissions: London 1970–2025

Iamarino, Mario; Beevers, Sean; Grimmond, Sue

doi:10.1002/joc.2390

Cited by 122 publications

(119 citation statements)

References 19 publications

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“…The highest regional value occurs in Hong Kong, with the value exceeding 100 W m −2 . This value is comparable to those in the most crowded megacities, such as Shanghai (Xie et al, 2016), Tokyo (Ichinose et al, 1999), London (Hamilton et al, 2009;Iamarino et al, 2012) and Singapore (Quah and Roth, 2012). In Nanning and Haikou, the annual mean AH fluxes over the whole administrative district are close to 10 W m −2 .…”

Section: Methods For Model Evaluationmentioning

confidence: 59%

“…The top-down energy inventory method, which predicts AH emissions based on the statistics data of energy consumption, is the most common approach and widely used all over the world (Sailor and Lu, 2004;Flanner, 2009;Hamilton et al, 2009;Lee et al, 2009;Allen et al, 2011;Iamarino et al, 2012;Quah and Roth, 2012;Chen et al, 2014a) as well as in China (Chen et al, 2012;Xie et al, 2015Xie et al, , 2016Lu et al, 2016). On the basis of the previous studies, AH fluxes over the area between (101 • E, 16 • N) and (119 • E, 26 • N) in 1990, 1995, 2000, 2005, 2010 and 2014 are calculated in this study by the following equation:…”

Section: Methods For Estimating Anthropogenic Heat Fluxesmentioning

confidence: 99%

mentioning

confidence: 99%

“…It was reported that the typical values of AH fluxes in urban areas range from 20 to 100 W m −2 (Crutzen, 2004;Sailor and Lu, 2004;Fan and Sailor, 2005;Pigeon et al, 2007;Lee et al, 2009;Iamarino et al, 2012;Lu et al, 2016;Xie et al, 2016). Sometimes, the fluxes might exceed the value of 100 W m −2 (Iamarino et al, 2012;Quah and Roth, 2012;Lu et al, 2016;Xie et al, 2016), with the extreme value of 1590 W m −2 in the densest part of Tokyo at the peak of air-conditioning demand (Ichinose et al, 1999). With regard to their effects, the researchers found that AH fluxes can cause urban air temperatures to increase by several degrees (Fan and Sailor, 2005;Ferguson and Woodbury, 2007;Zhu et al, 2010;Feng et al, 2012Feng et al, , 2014Menberg et al, 2013;Wu and Yang, 2013;Bohnenstengel et al, 2014;Chen et al, , 2014aYu et al, 2014;Xie et al, 2016), induce the atmosphere to be more turbulent and unstable, change the urban heat island circulation, strengthen vertical air movement (Ichinose et al, 1999;Block et al, 2004;Fan and Sailor, 2005;Feng et al, 2012Feng et al, , 2014Bohnenstengel et al, 2014;Yu et al, 2014;Xie et al, 2016), enhance the convergence of water vapor in cities, and change the regional precipitation patterns (Feng et al, 2012(Feng et al, , 2014Xie et al, 2016).…”

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confidence: 99%

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Changes in regional meteorology induced by anthropogenic heat and their impacts on air quality in South China

et al. 2016

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Abstract. Anthropogenic heat (AH) emissions from human activities can change the urban circulation and thereby affect the air pollution in and around cities. Based on statistic data, the spatial distribution of AH flux in South China is estimated. With the aid of the Weather Research and Forecasting model coupled with Chemistry (WRF/Chem), in which the AH parameterization is developed to incorporate the gridded AH emissions with temporal variation, simulations for January and July in 2014 are performed over South China. By analyzing the differences between the simulations with and without adding AH, the impact of AH on regional meteorology and air quality is quantified. The results show that the regional annual mean AH fluxes over South China are only 0.87 W m −2 , but the values for the urban areas of the Pearl River Delta (PRD) region can be close to 60 W m −2 . These AH emissions can significantly change the urban heat island and urban-breeze circulations in big cities. In the PRD city cluster, 2 m air temperature rises by 1.1 • in January and over 0.5 • in July, the planetary boundary layer height (PBLH) increases by 120 m in January and 90 m in July, 10 m wind speed is intensified to over 0.35 m s −1 in January and 0.3 m s −1 in July, and accumulative precipitation is enhanced by 20-40 % in July. These changes in meteorological conditions can significantly impact the spatial and vertical distributions of air pollutants. Due to the increases in PBLH, surface wind speed and upward vertical movement, the concentrations of primary air pollutants decrease near the surface and increase in the upper levels. But the vertical changes in O 3 concentrations show the different patterns in different seasons. The surface O 3 concentrations in big cities increase with maximum values of over 2.5 ppb in January, while O 3 is reduced at the lower layers and increases at the upper layers above some megacities in July. This phenomenon can be attributed to the fact that chemical effects can play a significant role in O 3 changes over South China in winter, while the vertical movement can be the dominant effect in some big cities in summer. Adding the gridded AH emissions can better describe the heterogeneous impacts of AH on regional meteorology and air quality, suggesting that more studies on AH should be carried out in climate and air quality assessments.

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Section: Methods For Model Evaluationmentioning

confidence: 59%

Section: Methods For Estimating Anthropogenic Heat Fluxesmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Changes in regional meteorology induced by anthropogenic heat and their impacts on air quality in South China

et al. 2016

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“…The fraction of traffic as a function of type and amount of gasoline, the number of vehicles, their fuel efficiency and the travelled distance can be used. Recently, Iamarino et al 2 developed a novel method to estimate the spatial variability of Q F from buildings. It is a top-down approach based on high-resolution resident and workplace population data.…”

Section: Introductionmentioning

confidence: 99%

Anthropogenic heat flux estimation from space: results of the first phase of the URBANFLUXES project

Chrysoulakis

Marconcini

Gastellu-Etchegorry

et al. 2016

Remote Sensing Technologies and Applications in Urban Environments

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H2020-Space project URBANFLUXES (URBan ANthrpogenic heat FLUX from Earth observation Satellites)investigates the potential of Copernicus Sentinels to retrieve anthropogenic heat flux, as a key component of the Urban Energy Budget (UEB). URBANFLUXES advances the current knowledge of the impacts of UEB fluxes on urban heat island and consequently on energy consumption in cities. This will lead to the development of tools and strategies to mitigate these effects, improving thermal comfort and energy efficiency. In URBANFLUXES, the anthropogenic heat flux is estimated as a residual of UEB. Therefore, the rest UEB components, namely, the net all-wave radiation, the net change in heat storage and the turbulent sensible and latent heat fluxes are independently estimated from Earth Observation (EO), whereas the advection term is included in the error of the anthropogenic heat flux estimation from the UEB closure. The project exploits Sentinels observations, which provide improved data quality, coverage and revisit times and increase the value of EO data for scientific work and future emerging applications. These observations can reveal novel scientific insights for the detection and monitoring of the spatial distribution of the urban energy budget fluxes in cities, thereby generating new EO opportunities. URBANFLUXES thus exploits the European capacity for space-borne observations to enable the development of operational services in the field of urban environmental monitoring and energy efficiency in cities.

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Comparing the diurnal and seasonal variabilities of atmospheric and surface urban heat islands based on the Beijing urban meteorological network

et al. 2017

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This study compared the diurnal and seasonal cycles of atmospheric and surface urban heat islands (UHIs) based on hourly air temperatures (Ta) collected at 65 out of 262 stations in Beijing and land surface temperature (Ts) derived from Moderate Resolution Imaging Spectroradiometer in the years 2013–2014. We found that the nighttime atmospheric and surface UHIs referenced to rural cropland stations exhibited significant seasonal cycles, with the highest in winter. However, the seasonal variations in the nighttime UHIs referenced to mountainous forest stations were negligible, because mountainous forests have a higher nighttime Ts in winter and a lower nighttime Ta in summer than rural croplands. Daytime surface UHIs showed strong seasonal cycles, with the highest in summer. The daytime atmospheric UHIs exhibited a similar but less seasonal cycle under clear‐sky conditions, which was not apparent under cloudy‐sky conditions. Atmospheric UHIs in urban parks were higher in daytime. Nighttime atmospheric UHIs are influenced by energy stored in urban materials during daytime and released during nighttime. The stronger anthropogenic heat release in winter causes atmospheric UHIs to increase with time during winter nights, but decrease with time during summer nights. The percentage of impervious surfaces is responsible for 49%–54% of the nighttime atmospheric UHI variability and 31%–38% of the daytime surface UHI variability. However, the nighttime surface UHI was nearly uncorrelated with the percentage of impervious surfaces around the urban stations.

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High‐resolution (space, time) anthropogenic heat emissions: London 1970–2025

Cited by 122 publications

References 19 publications

Changes in regional meteorology induced by anthropogenic heat and their impacts on air quality in South China

Changes in regional meteorology induced by anthropogenic heat and their impacts on air quality in South China

Anthropogenic heat flux estimation from space: results of the first phase of the URBANFLUXES project

Comparing the diurnal and seasonal variabilities of atmospheric and surface urban heat islands based on the Beijing urban meteorological network

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