Impact of percentile computation method on PM 24-h air quality standard

Salako, Gbenga Oladoyin; Hopke, Philip K.

doi:10.1016/j.jenvman.2012.04.006

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…The mean is usually the most used aggregation function because the median presents better descriptive power when the data do not follow normal behaviour; therefore, some countries prefer to use the percentile method to assess air quality (Salako and Hopke 2012).…”

Section: Data Preparationmentioning

confidence: 99%

Data Mining Paradigm in the Study of Air Quality

et al. 2019

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Air pollution is a serious global problem that threatens human life and health, as well as the environment. The most important aspect of a successful air quality management strategy is the measurement analysis, air quality forecasting, and reporting system. A complete insight, an accurate prediction, and a rapid response may provide valuable information for society's decision-making. The data mining paradigm can assist in the study of air quality by providing a structured work methodology that simplifies data analysis. This study presents a systematic review of the literature from 2014 to 2018 on the use of data mining in the analysis of air pollutant measurements. For this review, a data mining approach to air quality analysis was proposed that was consistent with the 748 articles consulted. The most frequent sources of data have been the measurements of monitoring networks, and other technologies such as remote sensing, low-cost sensors, and social networks which are gaining importance in recent years. Among the topics studied in the literature were the redundancy of the information collected in the monitoring networks, the forecasting of pollutant levels or days of excessive regulation, and the identification of meteorological or land use parameters that have the most substantial impact on air quality. As methods to visualise and present the results, we recovered graphic design, air quality index development, heat mapping, and geographic information systems. We hope that this study will provide anchoring of theoretical-practical development in the field and that it will provide inputs for air quality planning and management. Keywords Air quality . Environmental management . Air pollution . Data miningHighlights & 748 papers were published between 2014 and 2018 using data mining algorithms in the analysis of air pollutants. & 48 were selected and rigorously analyzed, from which a data mining approach was proposed for air quality management.

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Section: Data Preparationmentioning

confidence: 99%

Data Mining Paradigm in the Study of Air Quality

et al. 2019

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“…Table S2 presents the statistical forms for the 24-h mean and annual mean concentrations of PM 2.5 and PM 10 , as well as the 1-h mean, MDA8, and peak season concentration of O 3 in AAQSs of major countries or regions. The percentile-based method is usually adopted in the statistical form to relieve the impact of extreme values and missing observation data, which is sorting the daily concentration in one year from small to large and taking a specific percentile as the representative value for daily attainment evaluation, as shown in Table S2 [ 36 ]. For example, the annual 99th percentile (equivalent to three to four exceedance days per year) of daily mean concentration or MDA8 concentration is set in AQG 2021, and the percentile values in Chinese NAAQS are 90%, 95%, or 98% ( Table S2 ).…”

Section: Design Of the Proposed World-class Local Aaqssmentioning

confidence: 99%

The development of local ambient air quality standards: A case study of Hainan Province, China

Song,

Zhang,

Zhang

et al. 2024

Eco-Environment & Health

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“…Aunque la media suele ser la función de agregación más utilizada, la mediana presenta un mejor poder descriptivo cuando los datos no siguen el comportamiento normal. Por esto último, algunos países han preferido utilizar el método del percentil para evaluar la calidad del aire [Salako & Hopke, 2012]. Dado que la convención en las publicaciones científicas es utilizar la media para comparar distintos escenarios, se ha buscado comunicar ambos parámetros estadísticos cuando esto no resultaba confuso para el lector.…”

Section: Integraciónunclassified

Elaboración e implementación de una propuesta metodológica para la evaluación y gestión de la calidad del aire mediante el enfoque de la ciencia de datos

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Impact of percentile computation method on PM 24-h air quality standard

Cited by 5 publications

References 16 publications

Data Mining Paradigm in the Study of Air Quality

Data Mining Paradigm in the Study of Air Quality

The development of local ambient air quality standards: A case study of Hainan Province, China

Elaboración e implementación de una propuesta metodológica para la evaluación y gestión de la calidad del aire mediante el enfoque de la ciencia de datos

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