Air quality indexAn air quality index (AQI) is an indicator developed by government agencies to communicate to the public how polluted the air currently is or how polluted it is forecast to become. As air pollution levels rise, so does the AQI, along with the associated public health risk. Children, the elderly, and individuals with respiratory or cardiovascular problems are typically the first groups affected by poor air quality. When the AQI is high, governmental bodies generally encourage people to reduce physical activity outdoors, or even avoid going out altogether.
Carbon leakageCarbon leakage a concept to quantify an increase in greenhouse gas emissions in one country as a result of an emissions reduction by a second country with stricter climate change mitigation policies. Carbon leakage is one type of spill-over effect. Spill-over effects can be positive or negative; for example, emission reductions policy might lead to technological developments that aid reductions outside of the policy area. Carbon leakage is defined as "the increase in emissions outside the countries taking domestic mitigation action divided by the reduction in the emissions of these countries.
Particulate pollutionParticulate pollution is pollution of an environment that consists of particles suspended in some medium. There are three primary forms: atmospheric particulate matter, marine debris, and space debris. Some particles are released directly from a specific source, while others form in chemical reactions in the atmosphere. Particulate pollution can be derived from either natural sources or anthropogenic processes. Atmospheric particulate matter, also known as particulate matter, or PM, describes solids and/or liquid particles suspended in a gas, most commonly the Earth's atmosphere.
Average absolute deviationThe average absolute deviation (AAD) of a data set is the average of the absolute deviations from a central point. It is a summary statistic of statistical dispersion or variability. In the general form, the central point can be a mean, median, mode, or the result of any other measure of central tendency or any reference value related to the given data set. AAD includes the mean absolute deviation and the median absolute deviation (both abbreviated as MAD). Several measures of statistical dispersion are defined in terms of the absolute deviation.
Median absolute deviationIn statistics, the median absolute deviation (MAD) is a robust measure of the variability of a univariate sample of quantitative data. It can also refer to the population parameter that is estimated by the MAD calculated from a sample. For a univariate data set X1, X2, ..., Xn, the MAD is defined as the median of the absolute deviations from the data's median : that is, starting with the residuals (deviations) from the data's median, the MAD is the median of their absolute values. Consider the data (1, 1, 2, 2, 4, 6, 9).
Standard errorThe standard error (SE) of a statistic (usually an estimate of a parameter) is the standard deviation of its sampling distribution or an estimate of that standard deviation. If the statistic is the sample mean, it is called the standard error of the mean (SEM). The sampling distribution of a mean is generated by repeated sampling from the same population and recording of the sample means obtained. This forms a distribution of different means, and this distribution has its own mean and variance.
Deviation (statistics)In mathematics and statistics, deviation is a measure of difference between the observed value of a variable and some other value, often that variable's mean. The sign of the deviation reports the direction of that difference (the deviation is positive when the observed value exceeds the reference value). The magnitude of the value indicates the size of the difference. Errors and residuals A deviation that is a difference between an observed value and the true value of a quantity of interest (where true value denotes the Expected Value, such as the population mean) is an error.
Domain-specific modelingDomain-specific modeling (DSM) is a software engineering methodology for designing and developing systems, such as computer software. It involves systematic use of a domain-specific language to represent the various facets of a system. Domain-specific modeling languages tend to support higher-level abstractions than general-purpose modeling languages, so they require less effort and fewer low-level details to specify a given system.
Greenhouse gas inventoryGreenhouse gas inventories are emission inventories of greenhouse gas emissions that are developed for a variety of reasons. Scientists use inventories of natural and anthropogenic (human-caused) emissions as tools when developing atmospheric models. Policy makers use inventories to develop strategies and policies for emissions reductions and to track the progress of those policies. Regulatory agencies and corporations also rely on inventories to establish compliance records with allowable emission rates.
Uncertainty quantificationUncertainty quantification (UQ) is the science of quantitative characterization and estimation of uncertainties in both computational and real world applications. It tries to determine how likely certain outcomes are if some aspects of the system are not exactly known. An example would be to predict the acceleration of a human body in a head-on crash with another car: even if the speed was exactly known, small differences in the manufacturing of individual cars, how tightly every bolt has been tightened, etc.
