Development of a national anthropogenic heating database with an extrapolation for international cities

Sailor, David J.; Georgescu, Matei; Milne, Jeffrey M.; Hart, Mary

doi:10.1016/j.atmosenv.2015.07.016

Cited by 138 publications

(124 citation statements)

References 20 publications

Supporting

Mentioning

110

Contrasting

Unclassified

Order By: Relevance

“…Vehicle emissions account for 42 -46 per cent of total anthropogenic heat flux, while human metabolism accounted for 4 -5 per cent. This is similar to results for other cities, where vehicles contribute between 47 -62 per cent in Chicago, Atlanta, Los Angeles, San Francisco, Salt Lake City and Philadelphia and 51 per cent in São Paulo, while human metabolism contributes 2 -3 per cent in the previously listed American cities and 8 per cent in São Paulo (Sailor and Lu, 2004, Ferreira et al, 2011, Sailor et al, 2015. In South Korea, vehicle emissions are lower, accounting for between 25 -40 per cent of total emissions (Lee et al, 2009).…”

Section: Discussionsupporting

confidence: 69%

“…Sailor et al (2015), using an equation based on American cities, found a maximum summer value of 24.48 W/m 2 for Sydney, and a maximum winter value of 21.81 W/m 2 . This is much higher than the city-wide average calculated here, but lower than the values found in the city-centre.…”

Section: Discussionmentioning

confidence: 99%

“…The most recent for Brisbane and Sydney were in 2001 and 1971 respectively, and observations were made for Preston, Melbourne in 2007(Khan and Simpson, 2001, Quah and Roth, 2012, Coutts et al, 2007. Anthropogenic heat was also recently estimated for Sydney by Sailor et al (2015), however this was based on an equation developed for American cities. No previous calculations are available for Adelaide.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Large seasonal and diurnal anthropogenic heat flux across four Australian cities

Chapman¹,

Watson²,

McAlpine³

2016

JSHESS

View full text Add to dashboard Cite

Anthropogenic heat release is a key component of the urban heat island. However, it is often excluded from studies of the urban heat island because reliable estimates are not available. This omission is important because anthropogenic heat can contribute up to 4ºC to the urban heat island, and increases heat stress to urban residents. The exclusion of anthropogenic heat means the urban heat island effect on temperatures may be under-estimated. Here we estimate anthropogenic heat for four Australian capital cities (Brisbane, Sydney, Melbourne and Adelaide) to inform the management of the urban heat island in a changing climate. Anthropogenic heat release was calculated using 2011 population census data and an inventory of hourly traffic volume, building electricity and gas use. Melbourne had the highest annual daily average anthropogenic heat emissions, which reached 376 W/m 2 in the city centre during the daytime, while Brisbane's emissions were 261 W/m 2 and Sydney's were 256 W/m 2 . Adelaide had the lowest emissions, with a daily average of 39 W/m 2 in the city centre. Emissions varied within and among the four cities and decreased rapidly with distance from the city centre, to < 5 W/m 2 at 20 km from the city in Brisbane, and 15 km in Adelaide. The highest emissions were found in the city centres during working hours. The peak emissions reached in the centre of Melbourne are similar to the peak emissions in London and Tokyo, where anthropogenic heat is a large component of the urban heat island. This indicates that anthropogenic heat could be an important contributor to the urban heat island in Australian capital cities, and needs to be considered in climate adaptation studies. This is an important problem because climate change, combined with an ageing population and urban growth, could double the deaths from heatwaves in Australian cities over the next 40 years.

show abstract

Section: Discussionsupporting

confidence: 69%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Large seasonal and diurnal anthropogenic heat flux across four Australian cities

Chapman¹,

Watson²,

McAlpine³

2016

JSHESS

View full text Add to dashboard Cite

show abstract

“…Temporally, the predictors (except for LST) have larger gaps than in situ measured daily Ta, thus incapable of characterizing intermediate Ta variations. Particularly, the yearly NSL data, the only dataset that we had access to for accounting for the anthropogenic heat impact, cannot represent intra-annual variations of anthropogenic heat discharge flux [42,89], and it consequently cannot accurately express its dynamic relationship with Ta.…”

Section: Spatio-temporal Resolutions and Extensionsmentioning

confidence: 99%

Enhanced Statistical Estimation of Air Temperature Incorporating Nighttime Light Data

et al. 2016

View full text Add to dashboard Cite

Near surface air temperature (Ta) is one of the most critical variables in climatology, hydrology, epidemiology, and environmental health. In situ measurements are not efficient for characterizing spatially heterogeneous Ta, while remote sensing is a powerful tool to break this limitation. This study proposes a mapping framework for daily mean Ta using an enhanced empirical regression method based on remote sensing data. It differs from previous studies in three aspects. First, nighttime light data is introduced as a predictor (besides land surface temperature, normalized difference vegetation index, impervious surface area, black sky albedo, normalized difference water index, elevation, and duration of daylight) considering the urbanization-induced Ta increase over a large area. Second, independent components are extracted using principal component analysis considering the correlations among the above predictors. Third, a composite sinusoidal coefficient regression is developed considering the dynamic Ta-predictor relationship. This method was performed at 333 weather stations in China during 2001-2012. Evaluation shows overall mean error of −0.01 K, root mean square error (RMSE) of 2.53 K, correlation coefficient (R 2 ) of 0.96, and average uncertainty of 0.21 K. Model inter-comparison shows that this method outperforms six additional empirical regressions that have not incorporated nighttime light data or considered predictor independence or coefficient dynamics (by 0.18-2.60 K in RMSE and 0.00-0.15 in R 2 ).

show abstract

“…This development is accompanied by the dynamic growth of cities and its implications in terms of environmental degradation, given the fact that cities and their inhabitants are major contributors to waste heat and CO 2 emissions [4,5]. Numerous studies have shown that densely developed and populated urban areas show significant anthropogenic heat flux [6][7][8][9][10]. This is in part due to the unbalanced integration of urban infrastructure into the urban fabric, namely the transportation network, and multiple systems for heating, cooling, ventilation, and air-conditioning of buildings.…”

Section: Introductionmentioning

confidence: 99%

Strategies for Development and Improvement of the Urban Fabric: A Vienna Case Study

Vuckovic

Maleki

Mahdavi

2018

Climate

View full text Add to dashboard Cite

Abstract:Numerous studies have shown that densely developed and populated urban areas experience significant anthropogenic heat flux and elevated concentrations of air pollutants and CO 2 , with consequences for human health, thermal comfort, and well-being. This may also affect the atmospheric composition and circulation patterns within the urban boundary layer, with consequences for local, regional, and global climate. One of the resulting local implications is the increase in urban air temperature. In this context, the present contribution explores urban fabric development and mitigation strategies for two locations in the city of Vienna, Austria. Toward this end, the potential of specific planning and mitigation strategies regarding urban overheating was assessed using a state-of-the-art CFD-based (computational fluid dynamics) numeric simulation environment. The results display different levels of effectiveness for selected design and mitigation measures under a wide range of boundary conditions.

show abstract

Development of a national anthropogenic heating database with an extrapolation for international cities

Cited by 138 publications

References 20 publications

Large seasonal and diurnal anthropogenic heat flux across four Australian cities

Large seasonal and diurnal anthropogenic heat flux across four Australian cities

Enhanced Statistical Estimation of Air Temperature Incorporating Nighttime Light Data

Strategies for Development and Improvement of the Urban Fabric: A Vienna Case Study

Contact Info

Product

Resources

About