Practical Particulate Matter Sensing and Accurate Calibration System Using Low-Cost Commercial Sensors
TL;DR: In this paper, the authors proposed a practical particulate matter sensing and accurate calibration system using low-cost commercial sensors, which mainly dealt with three types of error caused in the light scattering method: short-term noise, part-to-part variation, and temperature and humidity interferences.
Abstract: Air pollution is a social problem, because the harmful suspended materials can cause diseases and deaths to humans. Specifically, particulate matters (PM), a form of air pollution, can contribute to cardiovascular morbidity and lung diseases. Nowadays, humans are exposed to PM pollution everywhere because it occurs in both indoor and outdoor environments. To purify or ventilate polluted air, one need to accurately monitor the ambient air quality. Therefore, this study proposed a practical particulate matter sensing and accurate calibration system using low-cost commercial sensors. The proposed system basically uses noisy and inaccurate PM sensors to measure the ambient air pollution. This paper mainly deals with three types of error caused in the light scattering method: short-term noise, part-to-part variation, and temperature and humidity interferences. We propose a simple short-term noise reduction method to correct measurement errors, an auto-fitting calibration for part-to-part repeatability to pinpoint the baseline of the signal that affects the performance of the system, and a temperature and humidity compensation method. This paper also contains the experiment setup and performance evaluation to prove the superiority of the proposed methods. Based on the evaluation of the performance of the proposed system, part-to-part repeatability was less than 2 μg/m3 and the standard deviation was approximately 1.1 μg/m3 in the air. When the proposed approaches are used for other optical sensors, it can result in better performance.
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TL;DR: In this paper , smoke-specific calibration curves for Airbeam 1 and 2 PM sensors were created by directly comparing simultaneous 1-min readings of a Thermo Scientific Personal DataRAM PDR-1500 unit with a 2.5 µm inlet.
Abstract: Previous studies have explored using calibrated low-cost particulate matter (PM) sensors, but important research gaps remain regarding long-term performance and reliability. Evaluate longitudinal performance of low-cost particle sensors by measuring sensor performance changes over 2 years of use. 51 low-cost particle sensors (Airbeam 1 N = 29; Airbeam 2 N = 22) were calibrated four times over a 2-year timeframe between 2019 and 2021. Cigarette smoke-specific calibration curves for Airbeam 1 and 2 PM sensors were created by directly comparing simultaneous 1-min readings of a Thermo Scientific Personal DataRAM PDR-1500 unit with a 2.5 µm inlet. Inter-sensor variability in calibration coefficient was high, particularly in Airbeam 1 sensors at study initiation. Calibration coefficients for both sensor types trended downwards over time to < 1 at final calibration timepoint [Airbeam 1 Mean (SD) = 0.87 (0.20); Airbeam 2 Mean (SD) = 0.96 (0.27)]. We lost more Airbeam 1 sensors (N = 27 out of 56, failure rate 48.2%) than Airbeam 2 (N = 2 out of 24, failure rate 8.3%) due to electronics, battery, or data output issues. Evidence suggests degradation over time might depend more on particle sensor type, rather than individual usage. Repeated calibrations of low-cost particle sensors may increase confidence in reported PM levels in longitudinal indoor air pollution studies.
4 citations
TL;DR: In this paper , the authors present progress in the design of the wireless emission monitoring system intended for use in non-industry heating appliances in households, and two experimental prototypes were constructed.
Abstract: The aim of the article is to present progress in the design of the wireless emission monitoring system intended for use in nonindustry heating appliances in households. Two experimental prototypes were constructed. The first prototype successfully transmitted air quality data via the SIM900 technology, measuring VOC, CO, and CO2 concentrations simultaneously, transmitting the data via cloud onto a mobile application every 15 seconds. This demonstrated proof of concept of the “MQ-series” sensors, the Arduino, and ThingSpeak Internet of Things (IoT) platform. The second monitoring prototype was used to analyze flue gases from a solid-fuel stove using three types of fuel: dry wood, cardboard, and wet grass emulating inappropriate fuel. Successful cooling was achieved within the sampling tube (average flue gas temperature of 106 °C–35 °C). Powered by batteries alone, the system wirelessly measured a significant increase in VOC and CO2 concentrations from the chimney as darker smoke rose, produced by incorrect fuel burn (nominal value of 0.35 ppm up to 62 ppm). The article concludes with future design plans, alterations, optimalization steps of the individual system components, and plans for further experiments.
04 Nov 2022
TL;DR: In this article , the effect of design parameters on particulate detection and sensor compliance sensitivity is investigated by using the finite element method, and the sensor structure is optimized to detect lower particulate concentrations.
Abstract: Nanometer-sized carbon particulates generated by incomplete combustion in heavy-duty vehicles are harmful to human health. A high-resolution technique is needed to detect and measure these pollutants. This study aims to optimize a capacitive sensor design for detecting and measuring particulates. Firstly, the effect of design parameters on particulate detection and sensor compliance sensitivity is investigated by using the finite element method. By comparing the simulation results with literature findings for performance validation, the sensor structure is optimized to detect lower particulate concentrations. The simulation result shows that particulate detection sensitivity has linear variations with changes in particulate mass. With optimum electrode spacing and top insulation layer thickness of 5 µm, the sensor can detect a particulate deposition of 0.033 mg/min and generate a maximum capacitance of 581 pF. Since the optimized design can measure particulate deposition at a lower range and with higher sensitivity, it is suitable to be applied to detect nanometer-sized carbon particulates.
TL;DR: In this article , a plano-convex lenticular fiber-based fine/ultrafine dust measurement device for monitoring the density and size of dust is presented. But the fabrication of the device is not yet complete.
Abstract: Measurement of particulate matter (PM), i.e., fine/ultrafine dust, is important for monitoring our surrounding environment. We demonstrate the fabrication of lenticular fiber-based fine/ultrafine dust measurement devices for monitoring the density and size of dust. The plano-convex lenticular fibers were fabricated by the CO2 laser polishing technique. The optical lens, used in the conventional light scattering-based fine/ultrafine dust measurement devices, was replaced by a plano-convex lenticular optical fiber to reduce the size and complexity of the dust measurement device. We utilized a light-emitting diode as the light source of the fine/ultrafine dust density measurement device. The fabricated device could indicate the dust density level (good, normal, bad, and very bad) according to the Korean standard. To estimate the size of the dust particulates, we fabricated a dust size measurement device that consists of a compact laser diode, a lenticular fiber, and a photodetector. We are successful in estimating the size of both fine and ultrafine PMs by detecting the power of the scattered light coming from the dust particulates. The dust size down to $0.9 \mu \text{m}$ was detected using our dust measurement device. Our proposed dust measurement devices are simple, small, and cost-effective and can be considered as a candidate for portable applications.
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TL;DR: Fine particulate and sulfur oxide--related pollution were associated with all-cause, lung cancer, and cardiopulmonary mortality and long-term exposure to combustion-related fine particulate air pollution is an important environmental risk factor for cardiopULmonary and lung cancer mortality.
Abstract: ContextAssociations have been found between day-to-day particulate air pollution
and increased risk of various adverse health outcomes, including cardiopulmonary
mortality. However, studies of health effects of long-term particulate air
pollution have been less conclusive.ObjectiveTo assess the relationship between long-term exposure to fine particulate
air pollution and all-cause, lung cancer, and cardiopulmonary mortality.Design, Setting, and ParticipantsVital status and cause of death data were collected by the American
Cancer Society as part of the Cancer Prevention II study, an ongoing prospective
mortality study, which enrolled approximately 1.2 million adults in 1982.
Participants completed a questionnaire detailing individual risk factor data
(age, sex, race, weight, height, smoking history, education, marital status,
diet, alcohol consumption, and occupational exposures). The risk factor data
for approximately 500 000 adults were linked with air pollution data
for metropolitan areas throughout the United States and combined with vital
status and cause of death data through December 31, 1998.Main Outcome MeasureAll-cause, lung cancer, and cardiopulmonary mortality.ResultsFine particulate and sulfur oxide–related pollution were associated
with all-cause, lung cancer, and cardiopulmonary mortality. Each 10-µg/m3 elevation in fine particulate air pollution was associated with approximately
a 4%, 6%, and 8% increased risk of all-cause, cardiopulmonary, and lung cancer
mortality, respectively. Measures of coarse particle fraction and total suspended
particles were not consistently associated with mortality.ConclusionLong-term exposure to combustion-related fine particulate air pollution
is an important environmental risk factor for cardiopulmonary and lung cancer
mortality.
7,803 citations
TL;DR: The data demonstrate a dose-dependent relationship between PM and human disease, and that removal from a PM-rich environment decreases the prevalence of these diseases.
Abstract: The World Health Organization estimates that particulate matter (PM) air pollution contributes to approximately 800,000 premature deaths each year, ranking it the 13th leading cause of mortality worldwide. However, many studies show that the relationship is deeper and far more complicated than originally thought. PM is a portion of air pollution that is made up of extremely small particles and liquid droplets containing acids, organic chemicals, metals, and soil or dust particles. PM is categorized by size and continues to be the fraction of air pollution that is most reliably associated with human disease. PM is thought to contribute to cardiovascular and cerebrovascular disease by the mechanisms of systemic inflammation, direct and indirect coagulation activation, and direct translocation into systemic circulation. The data demonstrating PM's effect on the cardiovascular system are strong. Populations subjected to long-term exposure to PM have a significantly higher cardiovascular incident and mortality rate. Short-term acute exposures subtly increase the rate of cardiovascular events within days of a pollution spike. The data are not as strong for PM's effects on cerebrovascular disease, though some data and similar mechanisms suggest a lesser result with smaller amplitude. Respiratory diseases are also exacerbated by exposure to PM. PM causes respiratory morbidity and mortality by creating oxidative stress and inflammation that leads to pulmonary anatomic and physiologic remodeling. The literature shows PM causes worsening respiratory symptoms, more frequent medication use, decreased lung function, recurrent health care utilization, and increased mortality. PM exposure has been shown to have a small but significant adverse effect on cardiovascular, respiratory, and to a lesser extent, cerebrovascular disease. These consistent results are shown by multiple studies with varying populations, protocols, and regions. The data demonstrate a dose-dependent relationship between PM and human disease, and that removal from a PM-rich environment decreases the prevalence of these diseases. While further study is needed to elucidate the effects of composition, chemistry, and the PM effect on susceptible populations, the preponderance of data shows that PM exposure causes a small but significant increase in human morbidity and mortality. Most sources agree on certain “common sense” recommendations, although there are lonely limited data to support them. Indoor PM exposure can be reduced by the usage of air conditioning and particulate filters, decreasing indoor combustion for heating and cooking, and smoking cessation. Susceptible populations, such as the elderly or asthmatics, may benefit from limiting their outdoor activity during peak traffic periods or poor air quality days. These simple changes may benefit individual patients in both short-term symptomatic control and long-term cardiovascular and respiratory complications.
1,332 citations
TL;DR: The nature of the gas response and how it is fundamentally linked to surface structure is explored and Synthetic routes to metal oxide semiconductor gas sensors are discussed and related to their affect on surface structure.
Abstract: Metal oxide semiconductor gas sensors are utilised in a variety of different roles and industries. They are relatively inexpensive compared to other sensing technologies, robust, lightweight, long lasting and benefit from high material sensitivity and quick response times. They have been used extensively to measure and monitor trace amounts of environmentally important gases such as carbon monoxide and nitrogen dioxide. In this review the nature of the gas response and how it is fundamentally linked to surface structure is explored. Synthetic routes to metal oxide semiconductor gas sensors are also discussed and related to their affect on surface structure. An overview of important contributions and recent advances are discussed for the use of metal oxide semiconductor sensors for the detection of a variety of gases—CO, NOx, NH3 and the particularly challenging case of CO2. Finally a description of recent advances in work completed at University College London is presented including the use of selective zeolites layers, new perovskite type materials and an innovative chemical vapour deposition approach to film deposition.
1,189 citations
TL;DR: In this paper, a description of the tapered element oscillating microbalance PM-10 measurement technique is given, and test results are compared to samplers designated as EPA reference methods.
Abstract: The goal of continuous ambient participate monitoring has been realized through the use of tapered element oscillating microbalance technology. This technology measures particle mass inertially as the mass deposits on a filter. As such, it is a direct mass measurement and eliminates the mass uncertainties inherent in indirect methods represented by optical or beta adsorption instrumentation. A description of the tapered element oscillating microbalance PM-10 measurement technique is given. Tests have been conducted on tapered element oscillating microbalance PM-10 monitors both in the United States and Europe. Test results presented include comparisons to samplers designated as EPA reference methods.
352 citations
TL;DR: In this article, a brief overview of solid-state gas sensors is presented, which can be classified into semiconductor, capacitor, and solid-electrolyte type sensors, based on their sensing mechanisms and a simple NDIR instrument.
Abstract: Due to the dramatic growth in industrial development and population, the natural atmospheric environment has become polluted and is rapidly deteriorating. Thus, the monitoring and control of such pollutants is imperative to prevent environmental disasters. Conventional analytic instruments for this purpose are time consuming, expensive, and seldom used in real-time in the field. As such, a solid-state gas sensor that is compact, robust, with versatile applications and a low cost, could be an equally effective alternative. Accordingly, this paper presents a brief overview of solid-state gas sensors, which can be classified into semiconductor, capacitor, and solid-electrolyte type sensors, based on their sensing mechanisms and a simple NDIR instrument. Furthermore, the sensing properties of solid-state gas sensors to environmental gases, such as NO X , SO X , CO 2 , volatile organic compounds (VOCs), plus certain other gases, are also classified and summarized.
261 citations