Sustainable cityThe sustainable city, eco-city, or green city is a city designed with consideration for social, economic, environmental impact (commonly referred to as the triple bottom line), and resilient habitat for existing populations, without compromising the ability of future generations to experience the same. The UN Sustainable Development Goal 11 defines sustainable cities as those that are dedicated to achieving green sustainability, social sustainability and economic sustainability.
Efficient energy useEfficient energy use, sometimes simply called energy efficiency, is the process of reducing the amount of energy required to provide products and services. For example, insulating a building allows it to use less heating and cooling energy to achieve and maintain a thermal comfort. Installing light-emitting diode bulbs, fluorescent lighting, or natural skylight windows reduces the amount of energy required to attain the same level of illumination compared to using traditional incandescent light bulbs.
Population declinePopulation decline, also known as depopulation, is a reduction in a human population size. Over the long term, stretching from prehistory to the present, Earth's total human population has continued to grow; however, current projections suggest that this long-term trend of steady population growth may be coming to an end. Until the beginning of the Industrial Revolution, the global population grew very slowly, at about 0.04% per year. After about 1800, the growth rate accelerated to a peak of 2.
Urban densityUrban density is a term used in urban planning and urban design to refer to the number of people inhabiting a given urbanized area. As such it is to be distinguished from other measures of population density. Urban density is considered an important factor in understanding how cities function. Research related to urban density occurs across diverse areas, including economics, health, innovation, psychology and geography as well as sustainability.
System dynamicsSystem dynamics (SD) is an approach to understanding the nonlinear behaviour of complex systems over time using stocks, flows, internal feedback loops, table functions and time delays. System dynamics is a methodology and mathematical modeling technique to frame, understand, and discuss complex issues and problems. Originally developed in the 1950s to help corporate managers improve their understanding of industrial processes, SD is currently being used throughout the public and private sector for policy analysis and design.
Population densityPopulation density (in agriculture: standing stock or plant density) is a measurement of population per unit land area. It is mostly applied to humans, but sometimes to other living organisms too. It is a key geographical term. In simple terms, population density refers to the number of people living in an area per square kilometre, or other unit of land area. Population density is population divided by total land area, sometimes including seas and oceans, as appropriate.
Building performanceBuilding performance is an attribute of a building that expresses how well that building carries out its functions. It may also relate to the performance of the building construction process. Categories of building performance are quality (how well the building fulfills its functions), resource savings (how much of a particular resource is needed to fulfill its functions) and workload capacity (how much the building can do). The performance of a building depends on the response of the building to an external load or shock.
Energy-plus buildingAn energy-plus building (also called: plus-energy house, efficiency-plus house) produces more energy from renewable energy sources, over the course of a year, than it imports from external sources. This is achieved using a combination of microgeneration technology and low-energy building techniques, such as: passive solar building design, insulation and careful site selection and placement. A reduction of modern conveniences can also contribute to energy savings, however many energy-plus houses are almost indistinguishable from a traditional home, preferring instead to use highly energy-efficient appliances, fixtures, etc.
Source–sink dynamicsSource–sink dynamics is a theoretical model used by ecologists to describe how variation in habitat quality may affect the population growth or decline of organisms. Since quality is likely to vary among patches of habitat, it is important to consider how a low quality patch might affect a population. In this model, organisms occupy two patches of habitat. One patch, the source, is a high quality habitat that on average allows the population to increase.
Statistical modelA statistical model is a mathematical model that embodies a set of statistical assumptions concerning the generation of sample data (and similar data from a larger population). A statistical model represents, often in considerably idealized form, the data-generating process. When referring specifically to probabilities, the corresponding term is probabilistic model. A statistical model is usually specified as a mathematical relationship between one or more random variables and other non-random variables.
Greenhouse gas emissionsGreenhouse gas emissions (abbreviated as GHG emissions) from human activities strengthen the greenhouse effect, contributing to climate change. Carbon dioxide (), from burning fossil fuels such as coal, oil, and natural gas, is one of the most important factors in causing climate change. The largest emitters are China followed by the US, although the United States has higher emissions per capita. The main producers fueling the emissions globally are large oil and gas companies.
Agent-based modelAn agent-based model (ABM) is a computational model for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) in order to understand the behavior of a system and what governs its outcomes. It combines elements of game theory, complex systems, emergence, computational sociology, multi-agent systems, and evolutionary programming. Monte Carlo methods are used to understand the stochasticity of these models.
