The impact of the projected changes in temperature on heating and cooling requirements in buildings in Dhaka, Bangladesh

Dhaka, the capital of Bangladesh, is a fast growing megacity with a population of 12.8 million. Due to its tropical location, dense urban morphology and higher than average density of population, buildings in Dhaka are likely to be adversely affected by the projected changes in climate, in particular by the increases in temperature. Buildings play a vital role in most aspects of our lives and their energy consumption patterns affect climate change mitigation and adaptation strategies. It is important to understand the likely impact of the projected increases in temperature on cooling and heating requirements in buildings in future climates. In this research, global projections on changes in temperature are temporally downscaled using a statistically averaged baseline present-day hourly weather data to generate future weather data in three timeslices: 2020s, 2050s and 2080s. Time series data for the present-day and future climates are analyzed as well as heating and cooling degree-days are calculated. Analysis shows that heating degree-days decrease whereas cooling degree-days continue to increase in future climates. The magnitude of change in monthly cooling degree-days is uneven and is greater in winter months than in summer and monsoon. Increased occurrences of temperatures above comfort threshold throughout the year are likely to have significant consequences for human health and wellbeing. The severity and duration of outdoor temperatures in the form of increased cooling degree-days in future climates will result in a surge in demand for energy for comfort cooling, which will add further stress to the already stressed energy infrastructure in the country. Prompt actions from stakeholders are, therefore, essential to enhance the resilience of Dhaka’s buildings to climate change

Climatic parameters for building energy applications: A temporal-geospatial assessment of temperature indicators

Understanding the climate and location aspects are usually the first step in energy applications -- from buildings to renewable energy. With so many of the renewable energy sources being significantly dependent on weather, it is essential that the temporal and geospatial variability and distribution of climatic design parameters are investigated for effective planning and operation. {ASHRAE-HOF} is the most widely used climatic design conditions database for building energy and HVAC professionals but gap exists in literature on the geospatial and temporal distributions of the HOF dataset. This research explored geospatial distributions of key HOF (2009) climatic parameters: temperature (dry-bulb, wet-bulb, dew-point and mean) and degree-days at various temporal scales. Identified spatial variability illustrate the effects of latitude, elevation, landuse and nearest coastline. Observed trends agree with conventional wisdom; however, sparse coverage in populated areas such as Africa and Asia diminish the versatility of the database. Variations in temperature exist, even between closely spaced sites -- emphasizing the need to use location-specific data for enhancing the accuracy of the weather-related analysis. Moreover, latitudinal similarities in the distribution offer potential in identifying candidate locations for reciprocal transfer of knowledge on environmental design and operation

Development of a distance-learning based post-graduate programme on sustainable architecture

A broad set of multidisciplinary and domain-specific skills is required to create sustainable architecture. Of particular significance are the skills needed for sustainability appraisal and collaborative decision making - highlighted by the construction industry and the government. The development of skills for effective integration of sustainability concepts into the management of architectural projects is vital for the Initial Professional Development (IPD) and Continuing Professional Development (CPD). The Higher Education (HE) is now faced with the challenge to address skills gap and to create a learning environment suitable for IPD and CPD. To reflect the changing needs of the industry, a flexible distance-learning based postgraduate programme on sustainable architecture has been developed at the Department of Built Environment, University of Central Lancashire. This paper reports on the philosophy, course structure and teaching and learning methods of the course

Relationship between annual mean temperature and degree-days

Degree-days are a versatile climatic indicator and used for many applications in the design and operation of energy efficient buildings – from the estimation of energy consumption and carbon emissions due to space heating and cooling to the energy and environmental monitoring of buildings. This research is aimed at developing an equation for calculating degree-days from low-resolution temperature data by exploring the relationship between degree-days and annual mean temperature of 5511 locations around the world, using multiple non-linear regression. Results suggest a very strong relationship between annual mean temperature and degree-days. Incorporating standard deviation (SD) of monthly mean temperature and latitude increases the accuracy of prediction (R2 > :99), demonstrating the strength of the location-agnostic relationship in predicting degree-days from two temperature parameters: annual mean and SD of monthly mean. Research findings can be used to calculate degree-days of locations, for which daily temperature data may not be available. The equation can also be used to calculate degree-days from low-resolution global circulation model (GCM) projections of increasing temperature, for investigating the impact of climate change on building heating and cooling energy demand at global scale without the need to create synthetic weather series through morphing or downscaling

A shadow–overlapping algorithm for estimating building heights from VHR satellite images

Building height is a key geometric attribute for generating 3D building models. We propose a novel four-stage approach for automated estimation of building heights from their shadows in very-high-resolution (VHR) multispectral images. First, a building’s actual shadow regions are detected by applying ratio-band algorithm to the VHR image. Second, 2D building footprint geometries are identified using graph theory and morphological fuzzy processing techniques. Third, artificial shadow regions are simulated using the identified building footprint and solar information in the image metadata at pre-defined height increments. Finally, the difference between the actual and simulated shadow regions at every height increment is computed using Jaccard similarity coefficient. The estimated building height corresponds to the height of the simulated shadow region that resulted in the maximum value for Jaccard index. The algorithm is tested on seven urban sites in Cardiff, UK with various levels of morphological complexity. Our method outperforms the past attempts, and mean error is reduced by at least 21%

Pitfalls of oil-based expansion of electricity generation in a developing context

In the context of growing demand and the need to rapidly increase access to convenient forms of energy, developing countries face many challenges for the development and upgrading of national energy infrastructures. Constraints on primary fuel sources, lack of capital and socio-political dynamics often result in the adoption of sub-optimal strategies for the expansion and upgrading of the existing infrastructure. Bangladesh is one such example that recently initiated a 10-year expansion program in 2010 to treble its generation capacity to 20 GW by 2021. The majority of about 3 GW capacity increase in the last two years has been based on imported oil such as heavy fuel oil (HFO) and high speed diesel (HSD). Despite having surplus generation capacity in 2011–12, the country continues to experience blackouts almost on a daily basis. By analysing the profiles of electricity demand, generation and shortage, as well as fuel imports, this study on Bangladesh demonstrates that increasing oil-based generation capacity does not always result in a proportionate increase in net electricity production. Moreover, increased dependence on volatile international energy markets for sourcing of fuel results in greater macroeconomic risks. Such macro-scale stress in a developing economy can be counter productive for social and economic development, as it takes resources away from other important sectors. Outcomes of this study can be useful for other developing countries that are undertaking energy sector reforms

Interoperability-based optimisation of architectural design

As a major contributor to the planetary greenhouse effect, construction industry needs to adopt sustainability at the core of its activities - to reverse or slow down the impacts of climate change. Increased collaboration among stakeholders along with analysis/performance based decision making is the way forward for enhanced sustainability. Emphasis is placed on the process of shared creation through multi-disciplinary collaboration, enabled by the implementation of IT (Information Technology) that acts as a platform to augment our ability to communicate. Developments in the Construction IT have been product oriented and aimed at solving particular domain problems usually with a narrow focus - further reducing the accessibility and interoperability of information over the lifecycle stages. Advances in the semantics based interoperable data standards, such as IFC (Industry Foundation Classes) offer significant advantage in removing such barriers to successful vertical and horizontal integration of software tools and process. The use of building simulation in architectural design requires specialist knowledge and a rich set of information about the proposed building which are not available to the design team at early stages. Standards based mapping of information for input processing of the simulation engines can act as an alternative to simplified tools supporting the exploratory nature of design. Detailed based input processing also restricts the use of simulation to occasional validation of solutions - even during detailed design stages. For a directed exploration of the solution space, numerical optimisation methods can be applied to enhance simulation assisted design. Successful application of optimisation methods pivots on the ability of the analysis and decision making components of the software to communicate with each other without the loss of data semantics. To realise this potential, a process-oriented integrated framework based on the interoperability of information and software tools have been developed and implemented in this thesis. For horizontal integration of domain specific tools through intra-software messaging, ardML - an XML (eXtensible Markup Language) based schema has been developed which attempts to connect non-interoperable software tools. Multi-disciplinary environmental design of buildings has been chosen as the domain of discourse. The framework currently employs industry standard zonal building simulation as an analysis tool and gradient-based mathematical optimisation methods for informed decision making. Interoperability among tools, processes and information has been achieved through the implementation of IFC based data model. The modular nature of the object-oriented framework allows incorporation of existing and future tools. The applicability of the framework has been investigated in the early stages of architectural design, in particular the selection of form and orientation - considering the environmental aspects. The implementation of the framework at an ambiguous and exploratory stage of design reinforces its applicability in a wider industry context

Patients’ perspectives on the design of hospital outpatient areas

There is a growing interest among healthcare managers and designers in moving towards a ‘patient-centred’ design of health and care facilities by integrating patient perceptions and expectations of the physical environment where care takes place. Increased interests in physical environments can mostly be attributed to our improved understanding of their role in patients’ health outcomes and staff productivity. There is a gap in the literature on users’ perspectives on physical settings in the context of healthcare. Moreover, the connection of care services with the design of the facility is often overlooked partly due to the lack of evidence. This research was aimed at filling the gap by exploring outpatients’ perspectives on design factors related to the areas frequented by them, e.g., hospital waiting areas. A 16-item questionnaire was conducted among randomly selected outpatients in two hospitals in Qingdao, China, with a response rate of 84.3%. Five principal factors were identified: sensory; lighting and thermal; facilities; spatial; and seating design, which agreed with the literature. Non-parametric tests were applied to assess variances in constructed principal dimensions concerning demographic variables. Female outpatients were found to be more perceptive of the ‘sensory design’ factors than males. The number of previous visits to the hospital was found to be associated with ‘spatial’ and ‘seating design’ factors, while respondents’ age had an association with ‘sensory’ and ‘seating design’ factors. Respondents ranked ‘noise’ and ‘air freshness’ and ‘cleanliness’ as highly important

Degree-day based non-domestic building energy analytics and modelling should use building and type specific base temperatures

A deeper understanding of building performance is essential to reduce their energy consumption and corresponding greenhouse gas emissions. Heating degree-days (HDD) encapsulates the severity and duration of cold weather, which is routinely used for weather related analysis of fuel consumption, performance benchmarking, and compliance. The accuracy of HDD-based prediction largely depends on the correct base temperature, which varies depending on building thermal characteristics, and their operation and occupancy. We analysed four years’ (2012-2016) half-hourly metered gas consumption from 119 non-domestic buildings representing seven types, to: (a) identify their base temperature using a three-parameter change point (3PH) regression model, and (b) their relationships with intrinsic building parameters. The highest mean base temperature, 17.7°C was found for clubs and community centres, and the lowest, 12.8°C was for storage buildings. The average of all base temperatures is 16.7°C, which is 1.2°C higher and 1.6°C lower than the British (15.5°C) and American (18.3°C) standards respectively. The current practice of a fixed base temperature degree-days for all buildings has been found to be unrealistic. Building type specific base temperatures must be developed, agreed upon and published for increasing accuracy in energy analytics and legislative compliance, as well as for developing effective standards and policies

Challenges and gaps for energy planning models in the developing-world context

Energy planning models (EPMs) support multi-criteria assessments of the impact of energy policies on the economy and environment. Most EPMs have originated in developed countries and are primarily aimed at reducing greenhouse gas emissions while enhancing energy security. In contrast, most, if not all, developing countries are predominantly concerned with increasing energy access. Here, we review thirty-four widely used EPMs to investigate their applicability to developing countries and find an absence of consideration of the objectives, challenges, and nuances of the developing context. Key deficiencies arise from the lack of deliberation of the low energy demand resulting from lack of access and availability of supply. Other inadequacies include the lack of consideration of socio-economic nuances such as the prevalence of corruption and resulting cost inflation, the methods for adequately addressing the shortcomings in data quality, availability and adequacy, and the effects of climate change. We argue for further research on characterisation and modelling of suppressed demand, climate change impacts, and socio-political feedback in developing countries, and the development of contextual EPMs