Particulate matter 1μm (PM1) dataset collected by low-cost sensors in residential and industrial areas at the neighborhood level
| Audiencia | Público en general | es_ES |
| Cobertura | México | es_ES |
| Fecha de ingreso | 2026-10-05T16:32:24Z | |
| Fecha de publicación | 2024-01-01 | |
| Resumen | The incursion of low-cost sensors (LCS) for monitoring particulate matter in different fractions of particles (PM10, PM2.5, and PM1) allows the characterization of the concentration levels of specific sources or events, including the analysis of ultrafine fractions (PM1). Several studies have documented adverse effects on human health due to exposure to PM1, such as morbidity and mortality from respiratory, cardiovascular, and, in some cases, carcinogenic diseases. Hence, studying the concentration levels and the sources that cause PM1 is imperative. LCS is an alternative to understanding contaminant concentration levels by considering spatial and temporal community dynamics by monitoring critical zones. Furthermore, collecting and managing large amounts of data through automatic processing and analysis generates information to support decision -making to reduce exposure and risks to people's health. The dataset presents the concentration level of PM1 (mu g/m(3)) calculated from the particles of size 0.03 mu m, 0.05 mu m, and 1.0 mu m recorded and counted by the sensor in a sample per minute for 24 h for seven continuous days. The values of the meteorological factors of relative humidity, temperature, and heat index complement these attributes. The dataset comprises records collected (in the same period) at four particulate matter monitoring stations, which compose an LCS network supported by Internet of Things (IoT) technologies. The data collection points were located in different areas of Reynosa, Mexico, considering strategic places for monitoring environmental pollution, such as industrial parks, residential areas, avenues with high vehicular traffic and transportation of heavy cargo, and an airport. (c) 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/) | es_ES |
| Doi | https://doi.org/10.1016/j.dib.2024.110411 | es_ES |
| URI | https://riuat.uat.edu.mx/handle/123456789/4214 | |
| Idioma | en | es_ES |
| Editorial | ELSEVIER | es_ES |
| Relación | Data in Brief | es_ES |
| URL relacionado | https://doi.org/10.1016/j.dib.2024.110411 | es_ES |
| Derechos | Acceso abierto (Metadatos de producción científica) | es_ES |
| Licencia | http://purl.org/coar/access_right/c_abf2 | es_ES |
| Fuente | Data in Brief | |
| Palabra clave | Air pollution | es_ES |
| Palabra clave | Air quality | es_ES |
| Palabra clave | LCS | es_ES |
| Palabra clave | IoT | es_ES |
| Palabra clave | Data science | es_ES |
| Título | Particulate matter 1μm (PM1) dataset collected by low-cost sensors in residential and industrial areas at the neighborhood level | es_ES |
| Tipo | Artículo | es_ES |
| Arbitrado | Ha sido Arbitrado | es_ES |
| Autor | Garcia-Garza, Luis A. | |
| Autor | Tello-Leal, Edgar | |
| Autor | Macias-Hernandez, Barbara A. | |
| Autor | Romero, Gerardo | |
| Autor | Hernandez-Resendiz, Jaciel David | |
| Autor | Garcia-Garza, Luis A. | es_ES |
| Autor | Tello-Leal, Edgar | es_ES |
| Autor | Macias-Hernandez, Barbara A. | es_ES |
| Autor | Romero, Gerardo | es_ES |
| Autor | Hernandez-Resendiz, Jaciel David | es_ES |
| Institución | Universidad Autónoma de Tamaulipas | |
| Institución | Universidad Autónoma de Tamaulipas | es_ES |
| URL relacionada | https://doi.org/10.1016/j.dib.2024.110411 | |
| Tipo de artículo | Indexado | |
| Tipo de artículo | Indexado | es_ES |
| Volumen | 54 | es_ES |