The impact of (adverse) weather is a common cause of delays, legal claims and economic losses in construction projects. Research has recently been carried out aimed at incorporating the effect of weather in project planning; but these studies have focussed on either a narrow set of weather variables, or a very limited range of construction activities or projects. A method for processing a country’s historical weather data into a set of weather delay maps for some representative standard construction activities is proposed. Namely, sine curves are used to associate daily combinations of weather variables to delay and provide coefficients for expected productivity losses. A complete case study comprising the construction of these maps and the associated sine waves for the UK is presented along with an example of their use in building construction planning. Findings of this study indicate that UK weather extends project durations by an average of 21%. However, using climatological data derived from weather observations when planning could lead to average reductions in project durations of 16%, with proportional reductions in indirect and overhead costs.

Thermal emissions – or anthropogenic heat fluxes (Q_F) – from human activities impact urban climates at a local and larger scale. DASH considers both urban form and function in simulating Q_F through the use of an agent-based structure that includes behavioural characteristics of urban residents. This allows human activities to drive the calculation of Q_F, incorporating dynamic responses to environmental conditions. The spatial resolution of simulations depends on data availability. DASH has simple transport and building energy models to allow simulation of dynamic vehicle use, occupancy and heating–cooling demand, and release of energy to the outdoor environment through the building fabric. Building stock variations are captured using archetypes. Evaluation of DASH in Greater London for periods in 2015 uses a top-down inventory model (GQF) and national energy consumption statistics. DASH reproduces the expected spatial and temporal patterns of Q_F, but the annual average is smaller than published energy data. Overall, the model generally performs well, including for domestic appliance energy use. DASH could be coupled to an urban land surface model and/or used offline for developing coefficients for simpler/faster models.

Overheating in buildings is one of the increasing concerns related to climate change and can lead to an increase in heat-related health issues and higher energy consumption due to the use of air conditioning systems. Literature shows that internal conditions and demand on environmental control systems can vary with height within buildings. However, an architectural trend towards highly glazed façades for tall buildings suggests the vertical gradient of performance is not always considered in the design process. By simulating a high-rise residential building in London, a comparative analysis of the overheating risks and daylighting at different levels in the building was conducted. In this study the model was able to consider the influence of surrounding built environment on solar gain and so influence of urban location on overheating risk was taken into account. Simulations were conducted using typical reference years as well as meteorological data for specific heat-wave periods experienced in London and that are expected to become more intense and frequent due to climate change. Passive mitigation options (external shading) are demonstrated to help reduce overheating occurrence by 74%, at the same time the impact of decreased daylighting (30%) is less problematic at higher levels where daylight factor is greater.