As the world continues to urbanize at an unprecedented rate,the energy demand in cities is rising.Buildings account for over 75%of all the energy consumed in cities and are responsible for over two-thirds of the emiss...As the world continues to urbanize at an unprecedented rate,the energy demand in cities is rising.Buildings account for over 75%of all the energy consumed in cities and are responsible for over two-thirds of the emissions.Assessment of energy demand in buildings is a highly integrative endeavour,bringing together the interdisciplinary fields of energy and urban studies,along with a host of technical domains namely,geography,engineering,economics,sociology,and planning.In the last decade,several urban building energy modelling tools(UBEMs)have been developed for estimation as well as prediction of energy demand in cities.These models are useful in policymaking as they can evaluate future urban energy scenarios.However,data acquisition for generating the input database for UBEM has been a major challenge.In this review,a comprehensive assessment of the potential of remote sensing and GIS techniques for UBEM has been presented.Firstly,the most common input variables of UBEM have been identified by reviewing recent publications on UBEM and then studies related to the acquisition of data corresponding to these variables have been explored.More than 140 research papers and review articles relevant to remote sensing and GIS applications for building level data extraction in urban areas and UBEM applications have been investigated for this purpose.After going through level of details required for each of the input components of UBEM and studying the possibility of acquiring some of those data using remote sensing,it has been inferred that satellite remote sensing and Unmanned Aerial Vehicles(UAVs)have a strong potential in enhancing the input data space for UBEM but their applicability has been limited.Further,the challenges of the usage of these technologies and the possible solutions have also been presented in this study.It is recommended to utilise the existing methodologies of extracting information from remote sensing and GIS for UBEM,along with newer techniques such as machine learning and artificial intelligence.展开更多
Rapid urbanization pressure and poverty have created a push for affordable housing within the global south.The design of affordable housing can have consequences on the thermal(dis)comfort and behaviour of the occupan...Rapid urbanization pressure and poverty have created a push for affordable housing within the global south.The design of affordable housing can have consequences on the thermal(dis)comfort and behaviour of the occupants,hence requiring an occupant-centric approach to ensure sustainability.This paper investigates occupant behaviour within the urban poor households of Mumbai,India and its impact on their thermal comfort and energy use.This study is a first-of-its-kind attempt to explore the socio-demographic characteristics and energy-related behaviour of low-income occupants within Indian context.Three occupant archetypes,Indifferent Consumers;Considerate Savers;and Conscious Conventionals,were identified from the behavioural and psychographic characteristics gathered through a transverse field survey.A two-step clustering approach was adopted for occupant segmentation that highlighted considerable diversity in occupants’adaptation measures,energy knowledge,energy habits,and their pro-environmental behaviour within similar socio-economic group.Building energy simulation of the representative archetype behaviour estimated up to 37%variations for air-conditioned and up to 8%variation for fan-assisted naturally ventilated housing units during peak summer months.The results from this study establish the significance of occupant factors in shaping energy demand and thermal comfort within low-income housing and pave way for developing occupant-centric building design strategies to serve this marginalized population.The developed low-income occupant archetypes would be useful for architects and energy modelers to generate realistic energy use profiles and improve building performance simulation results.展开更多
This study optimized the ventilator and furniture location of a tenement unit in a low-income urban habitat to obtain maximum experiential indoor environmental quality(e-IEQ)over the breathing zone.Hypothetical interi...This study optimized the ventilator and furniture location of a tenement unit in a low-income urban habitat to obtain maximum experiential indoor environmental quality(e-IEQ)over the breathing zone.Hypothetical interior layouts using a combination of the two design parameters of ventilator location and bed position were generated for optimizing the design layout.This layout could promote maximum indoor airflow and minimum indoor air temperature and contaminant concentration.In this study,an improved indoor environment is hypothesized to be attainable through improved natural ventilation and thermal performance in the occupied zones.A sequential methodology involving“parametric design modeling ecomputational simulationemultiobjective optimizationemulticriteria decision making”-based framework was selected.Results exhibited that the currently designed tenement unit had a poor indoor environment,whereas the hypothesized iterated layout“optimized design layout,scenario 3(ODL 3)”derived from the optimization and decision-making algorithm performed effectively in providing e-IEQ.An increase in experiential indoor air velocity by 0.2 m/s and a decrease in temperature by 2C were observed over the monitoring point in the ODL 3 considering the existing scenario.Therefore,this study can find a way toward the development of sustainable habitat design guidelines under upcoming slum redevelopment policies across the nation.展开更多
文摘As the world continues to urbanize at an unprecedented rate,the energy demand in cities is rising.Buildings account for over 75%of all the energy consumed in cities and are responsible for over two-thirds of the emissions.Assessment of energy demand in buildings is a highly integrative endeavour,bringing together the interdisciplinary fields of energy and urban studies,along with a host of technical domains namely,geography,engineering,economics,sociology,and planning.In the last decade,several urban building energy modelling tools(UBEMs)have been developed for estimation as well as prediction of energy demand in cities.These models are useful in policymaking as they can evaluate future urban energy scenarios.However,data acquisition for generating the input database for UBEM has been a major challenge.In this review,a comprehensive assessment of the potential of remote sensing and GIS techniques for UBEM has been presented.Firstly,the most common input variables of UBEM have been identified by reviewing recent publications on UBEM and then studies related to the acquisition of data corresponding to these variables have been explored.More than 140 research papers and review articles relevant to remote sensing and GIS applications for building level data extraction in urban areas and UBEM applications have been investigated for this purpose.After going through level of details required for each of the input components of UBEM and studying the possibility of acquiring some of those data using remote sensing,it has been inferred that satellite remote sensing and Unmanned Aerial Vehicles(UAVs)have a strong potential in enhancing the input data space for UBEM but their applicability has been limited.Further,the challenges of the usage of these technologies and the possible solutions have also been presented in this study.It is recommended to utilise the existing methodologies of extracting information from remote sensing and GIS for UBEM,along with newer techniques such as machine learning and artificial intelligence.
基金The work is also supported by Ministry of Human Resource Development,Government of India under the MHRD-FAST Grant[14MHRD005]IRCC-IIT Bombay Fund,Grant No.[16IRCC561015]。
文摘Rapid urbanization pressure and poverty have created a push for affordable housing within the global south.The design of affordable housing can have consequences on the thermal(dis)comfort and behaviour of the occupants,hence requiring an occupant-centric approach to ensure sustainability.This paper investigates occupant behaviour within the urban poor households of Mumbai,India and its impact on their thermal comfort and energy use.This study is a first-of-its-kind attempt to explore the socio-demographic characteristics and energy-related behaviour of low-income occupants within Indian context.Three occupant archetypes,Indifferent Consumers;Considerate Savers;and Conscious Conventionals,were identified from the behavioural and psychographic characteristics gathered through a transverse field survey.A two-step clustering approach was adopted for occupant segmentation that highlighted considerable diversity in occupants’adaptation measures,energy knowledge,energy habits,and their pro-environmental behaviour within similar socio-economic group.Building energy simulation of the representative archetype behaviour estimated up to 37%variations for air-conditioned and up to 8%variation for fan-assisted naturally ventilated housing units during peak summer months.The results from this study establish the significance of occupant factors in shaping energy demand and thermal comfort within low-income housing and pave way for developing occupant-centric building design strategies to serve this marginalized population.The developed low-income occupant archetypes would be useful for architects and energy modelers to generate realistic energy use profiles and improve building performance simulation results.
基金Part of this study is funded by the Ministry of Human Resource Development(MHRD)the Government of India(GoI)project titled CoE-FAST,Grant No.14MHRD005 and IRCC-IIT Bombay Fund,Grant No.16IRCC561015.Any opinions,findings,and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the MHRD,GoI and/or IRCC-IIT Bombay.
文摘This study optimized the ventilator and furniture location of a tenement unit in a low-income urban habitat to obtain maximum experiential indoor environmental quality(e-IEQ)over the breathing zone.Hypothetical interior layouts using a combination of the two design parameters of ventilator location and bed position were generated for optimizing the design layout.This layout could promote maximum indoor airflow and minimum indoor air temperature and contaminant concentration.In this study,an improved indoor environment is hypothesized to be attainable through improved natural ventilation and thermal performance in the occupied zones.A sequential methodology involving“parametric design modeling ecomputational simulationemultiobjective optimizationemulticriteria decision making”-based framework was selected.Results exhibited that the currently designed tenement unit had a poor indoor environment,whereas the hypothesized iterated layout“optimized design layout,scenario 3(ODL 3)”derived from the optimization and decision-making algorithm performed effectively in providing e-IEQ.An increase in experiential indoor air velocity by 0.2 m/s and a decrease in temperature by 2C were observed over the monitoring point in the ODL 3 considering the existing scenario.Therefore,this study can find a way toward the development of sustainable habitat design guidelines under upcoming slum redevelopment policies across the nation.
