Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
64,028
result(s) for
"Air monitoring"
Sort by:
Air Aware IoT: Low-Cost Sensor Solutions for Urban Pollution Monitoring and Public Health
Air pollution, especially in cities, has a considerable impact on human health and contributes to global morbidity and mortality rates. With urban populations increasing and public awareness of air quality being low, there is an urgent need for low-cost portable devices to monitor airborne contaminants in indoor and outdoor settings. This study presents the design and functionality of a low-cost, portable device capable of measuring major air quality parameters, such as gaseous pollutants (CO₂, O₃, TVOC, and PM₂.₅) and physical indicators (i.e., temperature and humidity). The device connects various sensors to an ATmega microcontroller via a signal conditioning circuit, thereby solving current, format, and speed incompatibilities. The data processed by the microcontroller was sent to various devices using IoT technology. The device accurately measures ozone and PM₂.₅, temperature, and humidity with precisions of ±5.02 μg.m- ³, ±7.94 μg.m- ³, ±0.67°C, and ±1.68%, respectively. The results demonstrate the dependability of the system for air quality monitoring, providing an affordable and accessible alternative for environmental surveillance. This innovation has the potential to raise public awareness and enable large-scale pollution monitoring, making it a useful tool for minimizing the negative consequences of air pollution on public health.
Journal Article
Review of the Performance of Low-Cost Sensors for Air Quality Monitoring
A growing number of companies have started commercializing low-cost sensors (LCS) that are said to be able to monitor air pollution in outdoor air. The benefit of the use of LCS is the increased spatial coverage when monitoring air quality in cities and remote locations. Today, there are hundreds of LCS commercially available on the market with costs ranging from several hundred to several thousand euro. At the same time, the scientific literature currently reports independent evaluation of the performance of LCS against reference measurements for about 110 LCS. These studies report that LCS are unstable and often affected by atmospheric conditions—cross-sensitivities from interfering compounds that may change LCS performance depending on site location. In this work, quantitative data regarding the performance of LCS against reference measurement are presented. This information was gathered from published reports and relevant testing laboratories. Other information was drawn from peer-reviewed journals that tested different types of LCS in research studies. Relevant metrics about the comparison of LCS systems against reference systems highlighted the most cost-effective LCS that could be used to monitor air quality pollutants with a good level of agreement represented by a coefficient of determination R2 > 0.75 and slope close to 1.0. This review highlights the possibility to have versatile LCS able to operate with multiple pollutants and preferably with transparent LCS data treatment.
Journal Article
Analysing the performance of low-cost air quality sensors, their drivers, relative benefits and calibration in cities—a case study in Sheffield
Traditional real-time air quality monitoring instruments are expensive to install and maintain; therefore, such existing air quality monitoring networks are sparsely deployed and lack the measurement density to develop high-resolution spatiotemporal air pollutant maps. More recently, low-cost sensors have been used to collect high-resolution spatial and temporal air pollution data in real-time. In this paper, for the first time, Envirowatch E-MOTEs are employed for air quality monitoring as a case study in Sheffield. Ten E-MOTEs were deployed for a year (October 2016 to September 2017) monitoring several air pollutants (NO, NO
2
, CO) and meteorological parameters. Their performance was compared to each other and to a reference instrument installed nearby. E-MOTEs were able to successfully capture the temporal variability such as diurnal, weekly and annual cycles in air pollutant concentrations and demonstrated significant similarity with reference instruments. NO
2
concentrations showed very strong positive correlation between various sensors. Mostly, correlation coefficients (
r
values) were greater than 0.92. CO from different sensors also had
r
values mostly greater than 0.92; however, NO showed
r
value less than 0.5. Furthermore, several multiple linear regression models (MLRM) and generalised additive models (GAM) were developed to calibrate the E-MOTE data and reproduce NO and NO
2
concentrations measured by the reference instruments. GAMs demonstrated significantly better performance than linear models by capturing the non-linear association between the response and explanatory variables. The best GAM developed for reproducing NO
2
concentrations returned values of 0.95, 3.91, 0.81, 0.005 and 0.61 for factor of two (FAC2), root mean square error (RMSE), coefficient of determination (
R
2
), normalised mean biased (NMB) and coefficient of efficiency (COE), respectively. The low-cost sensors offer a more affordable alternative for providing real-time high-resolution spatiotemporal air quality and meteorological parameter data with acceptable performance.
Journal Article
Recent advancements in low-cost portable sensors for urban and indoor air quality monitoring
The spatiotemporal heterogeneity of the air pollutants complicates appropriate monitoring. The collective measures or crowdsensing is a promising approach to achieve a better air pollution assessment because it includes the local concentration of pollutants, as well as the position and mobility of people. Thus, compared to traditional static monitoring, the participatory sensing data by low-cost sensors can avoid the misclassification of exposition to air pollutants, enabling a comprehensive understanding of their health effects. This systematic review integrates each core part of what is required to achieve crowdsensing for air pollution: sensors, portable devices, and data models. Despite the limitations of sensors in terms of sensitivity and selectivity, it has been possible to use portable air monitors to determine pollution hotspots around the world. However, limited models for data processing, performance issues when using low-cost devices, in addition to lack of community engagement, are the challenges to overcome for the feasibility of air pollution assessment with portable monitors.
Journal Article
Metal oxide semiconducting nanomaterials for air quality gas sensors: operating principles, performance, and synthesis techniques
To meet requirements in air quality monitoring, sensors are required that can measure the concentration of gaseous pollutants at concentrations down to the ppb and ppt levels, while at the same time they exhibiting high sensitivity, selectivity, and short response/recovery times. Among the different sensor types, those employing metal oxide semiconductors (MOSs) offer great promises as they can be manufactured in easy/inexpensive ways, and designed to measure the concentration of a wide range of target gases. MOS sensors rely on the adsorption of target gas molecules on the surface of the sensing material and the consequent capturing of electrons from the conduction band that in turn affects their conductivity. Despite their simplicity and ease of manufacturing, MOS gas sensors are restricted by high limits of detection (LOD; which are typically in the ppm range) as well as poor sensitivity and selectivity. LOD and sensitivity can in principle be addressed by nanostructuring the MOSs, thereby increasing their porosity and surface-to-volume ratio, whereas selectivity can be tailored through their chemical composition. In this paper we provide a critical review of the available techniques for nanostructuring MOSs using chemiresistive materials, and discuss how these can be used to attribute desired properties to the end gas sensors. We start by describing the operating principles of chemiresistive sensors, and key material properties that define their performance. The main part of the paper focuses on the available methods for synthesizing nanostructured MOSs for use in gas sensors. We close by addressing the current needs and provide perspectives for improving sensor performance in ways that can fulfill requirements for air quality monitoring.
Graphical abstract
Journal Article
Fifty years of EPA science for air quality management and control
Research and development has been a key part of the foundation for improvements in US air quality since the establishment of the Environmental Protection Agency (EPA) 50 years ago. Although the scientific accomplishments and advances over the course of EPA’s history are often overshadowed by policy debates, much of the air pollution science and engineering we now consider to be routine did not exist when EPA was established. Many of the advances in air pollutant measurement, monitoring, modeling, and control were developed by EPA researchers or supported by EPA programs. The technical foundation built during EPA’s early years has since given the Agency the scientific ability to respond quickly and effectively to unexpected and emerging issues. Equally important, EPA also developed approaches to conducting and presenting science in policy settings to ensure that the science was as objective and complete as possible and was communicated effectively. A look back at some of the accomplishments of EPA scientists and engineers provides a reminder that the cumulative effect of continual, incremental advances can result in large and lasting benefits to society.
Journal Article
Drone-Assisted Particulate Matter Measurement in Air Monitoring: A Patent Review
Air pollution is caused by the presence of polluting elements. Ozone (O3), carbon monoxide (CO), carbon dioxide (CO2), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter (PM) are the most controlled gasses because they can be released into the atmosphere naturally or as a result of human activity, which affects air quality and causes disease and premature death in exposed people. Depending on the substance being measured, ambient air monitors have different types of air quality sensors. In recent years, there has been a growing interest in designing drones as mobile sensors for monitoring air pollution. Therefore, the objective of this paper is to provide a comprehensive patent review to gain insight into the proprietary technologies currently used in drones used to monitor outdoor air pollution. Patent searches were conducted using three different patent search engines: Google Patents, WIPO’s Patentscope, and the United States Patent and Trademark Office (USPTO). The analysis of each patent consists of extracting data that supply information regarding the type of drone, sensor, or equipment for measuring PM, the lack or presence of a cyclone separator, and the ability to process the turbulence generated by the drone’s propellers. A total of 1473 patent documents were retrieved using the search engine. However, only 13 met the inclusion criteria, including patent documents reporting drone designs for outdoor air pollution monitoring. Therefore, was found that most patents fall under class G01N (measurement; testing) according to the International Patents Classification, where the most common sensors and devices are infrared or visible light cameras, cleaning devices, and GPS tracking devices. The most common tasks performed by drones are air pollution monitoring, assessment, and control. These categories cover different aspects of the air pollution management cycle and are essential to effectively address this environmental problem.
Journal Article