Understanding the drivers of energy and material flows of cities is important for addressing global environmental challenges. Accessing, sharing, and managing energy and material resources is particularly critical for megacities, which face enormous social stresses because of their sheer size and complexity. Here we quantify the energy and material flows through the world’s 27 megacities with populations greater than 10 million people as of 2010. Collectively the resource flows through megacities are largely consistent with scaling laws established in the emerging science of cities. Correlations are established for electricity consumption, heating and industrial fuel use, ground transportation energy use, water consumption, waste generation, and steel production in terms of heating-degree-days, urban form, economic activity, and population growth. The results help identify megacities exhibiting high and low levels of consumption and those making efficient use of resources. The correlation between per capita electricity use and urbanized area per capita is shown to be a consequence of gross building floor area per capita, which is found to increase for lower-density cities. Many of the megacities are growing rapidly in population but are growing even faster in terms of gross domestic product (GDP) and energy use. In the decade from 2001–2011, electricity use and ground transportation fuel use in megacities grew at approximately half the rate of GDP growth.

No abstract

No abstract

The management of urban run-off is considered a success when the issues of flood and pollution are properly addressed. Flood can be controlled by reduction of peak flows and by treating polluted run-off. Best management practices (BMPs) are important tools for reducing pollutants and run-offs. Location of BMPs is an important factor in determining their optimum arrangement. In this paper, based on simulation-optimisation model, a methodology has been proposed to select proper BMPs with optimum arrangements. Quality and quantity of water flow in urban area were modelled, using Storm Water Management Model. Multi objective particle swarm optimisation was also used to reach the BMP layouts so that the peak flow and pollutant concentration can be effectively minimised. The proposed methodology was developed for district number 10 of Tehran municipality. The results showed that the proposed methodology could lead to an improvement in quantity and quality of run-off. For example, different combination of 32 BMPs led to a decrease in peak flow for 2, 5 and 10-year return periods as much as 10%, 21%, and 13%, respectively, while the combination of 45 BMPs decreased the total suspended solids mean concentration for 2, 5 and 10-year return periods as much as 50%, 57%, and 59%, respectively.