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Mangin T, Blanchard EK, Kelly KE. Effect of Three-Dimensional-Printed Thermoplastics Used in Sensor Housings on Common Atmospheric Trace Gasses. SENSORS (BASEL, SWITZERLAND) 2024; 24:2610. [PMID: 38676227 PMCID: PMC11053552 DOI: 10.3390/s24082610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 04/06/2024] [Accepted: 04/16/2024] [Indexed: 04/28/2024]
Abstract
Low-cost air quality sensors (LCSs) are becoming more ubiquitous as individuals and communities seek to reduce their exposure to poor air quality. Compact, efficient, and aesthetically designed sensor housings that do not interfere with the target air quality measurements are a necessary component of a low-cost sensing system. The selection of appropriate housing material can be an important factor in air quality applications employing LCSs. Three-dimensional printing, specifically fused deposition modeling (FDM), is a standard for prototyping and small-scale custom plastics production because of its low cost and ability for rapid iteration. However, little information exists about whether FDM-printed thermoplastics affect measurements of trace atmospheric gasses. This study investigates how five different FDM-printed thermoplastics (ABS, PETG, PLA, PC, and PVDF) affect the concentration of five common atmospheric trace gasses (CO, CO2, NO, NO2, and VOCs). The laboratory results show that the thermoplastics, except for PVDF, exhibit VOC off-gassing. The results also indicate no to limited interaction between all of the thermoplastics and CO and CO2 and a small interaction between all of the thermoplastics and NO and NO2.
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Affiliation(s)
- Tristalee Mangin
- Department of Chemical Engineering, University of Utah, Salt Lake City, UT 84112, USA
| | | | - Kerry E. Kelly
- Department of Chemical Engineering, University of Utah, Salt Lake City, UT 84112, USA
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2
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Tripathi AK, Aruna M, Parida S, Nandan D, Elumalai PV, Prakash E, Isaac JoshuaRamesh Lalvani JSC, Rao KS. Integrated smart dust monitoring and prediction system for surface mine sites using IoT and machine learning techniques. Sci Rep 2024; 14:7587. [PMID: 38555354 PMCID: PMC10981741 DOI: 10.1038/s41598-024-58021-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Accepted: 03/25/2024] [Indexed: 04/02/2024] Open
Abstract
The mining industry confronts significant challenges in mitigating airborne particulate matter (PM) pollution, necessitating innovative approaches for effective monitoring and prediction. This research focuses on the design and development of an Internet of Things (IoT)-based real-time monitoring system tailored for PM pollutants in surface mines, specifically PM 1.0, PM 2.5, PM 4.0, and PM 10.0. The novelty of this work lies in the integration of IoT technology for real-time measurement and the application of machine learning (ML) techniques for accurate prediction based on recorded dust pollutants data. The study's findings indicate that PM 1.0 pollutants exhibited the highest concentration in the atmosphere of the ball clay surface mine sites, with the stockyard site registering the maximum levels of PM pollutants (28.45 µg/m3, 27.89 µg/m3, 26.17 µg/m3, and 27.24 µg/m3, respectively) due to the dry nature of clay materials. Additionally, the research establishes four ML models-Decision Tree (DT), Gradient Boosting Regression (GBR), Random Forest (RF), and Linear Regression (LR)-for predicting PM pollutant concentrations. Notably, Random Forest demonstrates superior performance with the lowest Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) at 1.079 and 1.497, respectively. This comprehensive solution, combining IoT-based monitoring and ML-based prediction, contributes to sustainable mining practices, safeguarding worker well-being, and preserving the environment.
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Affiliation(s)
- Abhishek Kumar Tripathi
- Department of Mining Engineering, Aditya Engineering College, Surampalem, Andhra Pradesh, 53347, India.
| | - Mangalpady Aruna
- Department of Mining Engineering, National Institute of Technology Karnataka, Surathkal, 575025, India
| | - Satyajeet Parida
- Department of Mining Engineering, Aditya Engineering College, Surampalem, Andhra Pradesh, 53347, India
| | - Durgesh Nandan
- School of Computer Science & Artificial Intelligence, SR University, Warangal, Telangana, 506004, India
| | - P V Elumalai
- Department of Mechanical Engineering, Aditya Engineering College, Surampalem, India
- Metharath University, Bang Toei, 12160, Thailand
| | - E Prakash
- Department of Mechtronics Engineering, Rajalaskhmi Engineering College, Mevalurkuppam, India
| | | | - Koppula Srinivas Rao
- Department of Computer Science and Engineering, MLR Institute of Technology, Hyderabad, Telangana, India
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Corona J, Tondini S, Gallichi Nottiani D, Scilla R, Gambaro A, Pasut W, Babich F, Lollini R. Environmental Quality bOX (EQ-OX): A Portable Device Embedding Low-Cost Sensors Tailored for Comprehensive Indoor Environmental Quality Monitoring. SENSORS (BASEL, SWITZERLAND) 2024; 24:2176. [PMID: 38610386 PMCID: PMC11014031 DOI: 10.3390/s24072176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 03/10/2024] [Accepted: 03/15/2024] [Indexed: 04/14/2024]
Abstract
The continuous monitoring of indoor environmental quality (IEQ) plays a crucial role in improving our understanding of the prominent parameters affecting building users' health and perception of their environment. In field studies, indoor environment monitoring often does not go beyond the assessment of air temperature, relative humidity, and CO2 concentration, lacking consideration of other important parameters due to budget constraints and the complexity of multi-dimensional signal analyses. In this paper, we introduce the Environmental Quality bOX (EQ-OX) system, which was designed for the simultaneous monitoring of quantities of some of the main IEQs with a low level of uncertainty and an affordable cost. Up to 15 parameters can be acquired at a time. The system embeds only low-cost sensors (LCSs) within a compact case, enabling vast-scale monitoring campaigns in residential and office buildings. The results of our laboratory and field tests show that most of the selected LCSs can match the accuracy required for indoor campaigns. A lightweight data processing algorithm has been used for the benchmark. Our intent is to estimate the correlation achievable between the detected quantities and reference measurements when a linear correction is applied. Such an approach allows for a preliminary assessment of which LCSs are the most suitable for a cost-effective IEQ monitoring system.
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Affiliation(s)
- Jacopo Corona
- Institute for Renewable Energy, Eurac Research, 39100 Bolzano, Italy
| | - Stefano Tondini
- Center for Sensing Solutions, Eurac Research, 39100 Bolzano, Italy (R.S.)
- Photonics Integration, Electrical Engineering Department, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands
| | - Duccio Gallichi Nottiani
- Environmental Sciences, Informatics and Statistics Department, University Ca’ Foscari, 30172 Venezia, Italy (A.G.)
- Dipartimento di Ingegneria e Architettura, Università di Parma, 43124 Parma, Italy
| | - Riccardo Scilla
- Center for Sensing Solutions, Eurac Research, 39100 Bolzano, Italy (R.S.)
| | - Andrea Gambaro
- Environmental Sciences, Informatics and Statistics Department, University Ca’ Foscari, 30172 Venezia, Italy (A.G.)
| | - Wilmer Pasut
- Environmental Sciences, Informatics and Statistics Department, University Ca’ Foscari, 30172 Venezia, Italy (A.G.)
- College of Engineering, University of Korea, Seoul 06591, Republic of Korea
| | - Francesco Babich
- Institute for Renewable Energy, Eurac Research, 39100 Bolzano, Italy
| | - Roberto Lollini
- Institute for Renewable Energy, Eurac Research, 39100 Bolzano, Italy
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4
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Wang Z, Yu T, Ye J, Tian L, Lin B, Leng W, Liu C. A novel low sampling rate and cost-efficient active sampler for medium/long-term monitoring of gaseous pollutants. JOURNAL OF HAZARDOUS MATERIALS 2024; 461:132583. [PMID: 37741205 DOI: 10.1016/j.jhazmat.2023.132583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 09/14/2023] [Accepted: 09/17/2023] [Indexed: 09/25/2023]
Abstract
Active sampling is a dependable approach for gaseous pollutants monitoring, offering high accuracy and precision that is unaffected by environmental factors such as wind and temperature in comparison to passive sampling. To measure long-term average concentrations while minimizing the use of materials, a reduced sampling rate is necessary. Thus, this study aims to develop a novel low sampling rate (down to 1 mL/min) and cost-efficient active sampler (LASP) for medium/long-term monitoring of gaseous pollutants. The LASP mainly consisted of a syringe pump, a Y-shaped fitting with two one-way valves, and a control unit for intermittent operation. Results showed that LASP can obtain a sampling rate of less than 1 mL/min and sampling rate exhibited a high level of stability. Daily average concentrations measurements for nitrogen dioxide and formaldehyde by LASP had normalized mean biases of 2.8% and 5.2%, respectively. These numbers were - 5.8% and 6.1% for weekly-average samplings. This study demonstrated applications of LASP in real outdoor (daily-average) and indoor (weekly-average) air quality measurements. It worked well with low noise levels, and without interfering with occupants' daily activities. LASP can assist in improving our ability to monitor air quality and pollutants emissions, thereby supporting health research and policy development. ENVIRONMENTAL IMPLICATION: Gaseous air pollution is an important hazardous factor threatening human health. Medium/long-term air quality monitoring is essential for outdoor and indoor air quality assessment and control. However, air sampler for medium/long-term sampling is lacking. This study developed a novel low sampling rate and cost-efficient active sampler and applied it to medium/long-term air sampling. The sampler can work at a sampling rate of less than 1 mL/min. This technology provides a feasible strategy for medium/long-term monitoring of gaseous air pollutants in both environments and emission hotspots.
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Affiliation(s)
- Zhiyuan Wang
- School of Energy and Environment, Southeast University, Nanjing 210096, China
| | - Tao Yu
- Wuhan Second Ship Design and Research Institute, Wuhan 430205, China
| | - Jin Ye
- School of Energy and Power, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212100, China
| | - Lei Tian
- Tianjin Institute of Environmental and Operational Medicine, Tianjin 300050, China
| | - Bencheng Lin
- Tianjin Institute of Environmental and Operational Medicine, Tianjin 300050, China
| | - Wenjun Leng
- Wuhan Second Ship Design and Research Institute, Wuhan 430205, China
| | - Cong Liu
- School of Energy and Environment, Southeast University, Nanjing 210096, China.
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Wang J, Du W, Lei Y, Chen Y, Wang Z, Mao K, Tao S, Pan B. Quantifying the dynamic characteristics of indoor air pollution using real-time sensors: Current status and future implication. ENVIRONMENT INTERNATIONAL 2023; 175:107934. [PMID: 37086491 DOI: 10.1016/j.envint.2023.107934] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 04/12/2023] [Accepted: 04/12/2023] [Indexed: 05/03/2023]
Abstract
People generally spend most of their time indoors, making indoor air quality be of great significance to human health. Large spatiotemporal heterogeneity of indoor air pollution can be hardly captured by conventional filter-based monitoring but real-time monitoring. Real-time monitoring is conducive to change air assessment mode from static and sparse analysis to dynamic and massive analysis, and has made remarkable strides in indoor air evaluation. In this review, the state of art, strengths, challenges, and further development of real-time sensors used in indoor air evaluation are focused on. Researches using real-time sensors for indoor air evaluation have increased rapidly since 2018, and are mainly conducted in China and the USA, with the most frequently investigated air pollutants of PM2.5. In addition to high spatiotemporal resolution, real-time sensors for indoor air evaluation have prominent advantages in 3-dimensional monitoring, pollution peak and source identification, and short-term health effect evaluation. Huge amounts of data from real-time sensors also facilitate the modeling and prediction of indoor air pollution. However, challenges still remain in extensive deployment of real-time sensors indoors, including the selection, performance, stability, as well as calibration of sensors. In future, sensors with high performance, long-term stability, low price, and low energy consumption are welcomed. Furthermore, more target air pollutants are also expected to be detected simultaneously by real-time sensors in indoor air monitoring.
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Affiliation(s)
- Jinze Wang
- Key Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Wei Du
- Yunnan Provincial Key Laboratory of Soil Carbon Sequestration and Pollution Control, Faculty of Environmental Science & Engineering, Kunming University of Science & Technology, Kunming 650500, China.
| | - Yali Lei
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Yuanchen Chen
- Key Laboratory of Microbial Technology for Industrial Pollution Control of Zhejiang Province, College of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang 310032, China
| | - Zhenglu Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Kang Mao
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, China
| | - Shu Tao
- Key Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Bo Pan
- Yunnan Provincial Key Laboratory of Soil Carbon Sequestration and Pollution Control, Faculty of Environmental Science & Engineering, Kunming University of Science & Technology, Kunming 650500, China
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Tsang TW, Mui KW, Wong LT, Law KY, Shek KW. A Novel IoT-Enabled Wireless Sensor Grid for Spatial and Temporal Evaluation of Tracer Gas Dispersion. SENSORS (BASEL, SWITZERLAND) 2023; 23:3920. [PMID: 37112265 PMCID: PMC10145748 DOI: 10.3390/s23083920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/07/2023] [Accepted: 04/11/2023] [Indexed: 06/19/2023]
Abstract
Current IoT applications in indoor air focus mainly on general monitoring. This study proposed a novel IoT application to evaluate airflow patterns and ventilation performance using tracer gas. The tracer gas is a surrogate for small-size particles and bioaerosols and is used in dispersion and ventilation studies. Prevalent commercial tracer-gas-measuring instruments, although highly accurate, are relatively expensive, have a long sampling cycle, and are limited in the number of sampling points. To enhance the spatial and temporal understanding of tracer gas dispersion under the influence of ventilation, a novel application of an IoT-enabled, wireless R134a sensing network using commercially available small sensors was proposed. The system has a detection range of 5-100 ppm and a sampling cycle of 10 s. Using Wi-Fi communication, the measurement data are transmitted to and stored in a cloud database for remote, real-time analysis. The novel system provides a quick response, detailed spatial and temporal profiles of the tracer gas level, and a comparable air change rate analysis. With multiple units deployed as a wireless sensing network, the system can be applied as an affordable alternative to traditional tracer gas systems to identify the dispersion pathway of the tracer gas and the general airflow direction.
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Affiliation(s)
- Tsz-Wun Tsang
- Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Kwok-Wai Mui
- Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Ling-Tim Wong
- Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Kwok-Yung Law
- Department of Mechanical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Ka-Wing Shek
- Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hong Kong, China
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7
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Okeme JO, Koelmel JP, Johnson E, Lin EZ, Gao D, Pollitt KJG. Wearable Passive Samplers for Assessing Environmental Exposure to Organic Chemicals: Current Approaches and Future Directions. Curr Environ Health Rep 2023:10.1007/s40572-023-00392-w. [PMID: 36821032 DOI: 10.1007/s40572-023-00392-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/11/2023] [Indexed: 02/24/2023]
Abstract
PURPOSE OF REVIEW We are continuously exposed to dynamic mixtures of airborne contaminants that vary by location. Understanding the compositional diversity of these complex mixtures and the levels to which we are each exposed requires comprehensive exposure assessment. This comprehensive analysis is often lacking in population-based studies due to logistic and analytical challenges associated with traditional measurement approaches involving active air sampling and chemical-by-chemical analysis. The objective of this review is to provide an overview of wearable passive samplers as alternative tools to active samplers in environmental health research. The review highlights the advances and challenges in using wearable passive samplers for assessing personal exposure to organic chemicals and further presents a framework to enable quantitative measurements of exposure and expanded use of this monitoring approach to the population scale. RECENT FINDINGS Overall, wearable passive samplers are promising tools for assessing personal exposure to environmental contaminants, evident by the increased adoption and use of silicone-based devices in recent years. When combined with high throughput chemical analysis, these exposure assessment tools present opportunities for advancing our ability to assess personal exposures to complex mixtures. Most designs of wearable passive samplers used for assessing exposure to semi-volatile organic chemicals are currently uncalibrated, thus, are mostly used for qualitative research. The challenge with using wearable samplers for quantitative exposure assessment mostly lies with the inherent complexity in calibrating these wearable devices. Questions remain regarding how they perform under various conditions and the uncertainty of exposure estimates. As popularity of these samplers grows, it is critical to understand the uptake kinetics of chemicals and the different environmental and meteorological conditions that can introduce variability. Wearable passive samplers enable evaluation of exposure to hundreds of chemicals. The review presents the state-of-the-art of technology for assessing personal exposure to environmental chemicals. As more studies calibrate wearable samplers, these tools present promise for quantitatively assessing exposure at both the individual and population levels.
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Affiliation(s)
- Joseph O Okeme
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, Room 523, New Haven, CT, 06510, USA
| | - Jeremy P Koelmel
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, Room 523, New Haven, CT, 06510, USA
| | - Emily Johnson
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, Room 523, New Haven, CT, 06510, USA
| | - Elizabeth Z Lin
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, Room 523, New Haven, CT, 06510, USA
| | - Dong Gao
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, Room 523, New Haven, CT, 06510, USA
| | - Krystal J Godri Pollitt
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, Room 523, New Haven, CT, 06510, USA.
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Sá JP, Chojer H, Branco PTBS, Alvim-Ferraz MCM, Martins FG, Sousa SIV. Two step calibration method for ozone low-cost sensor: Field experiences with the UrbanSense DCUs. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 328:116910. [PMID: 36495826 DOI: 10.1016/j.jenvman.2022.116910] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 09/26/2022] [Accepted: 11/26/2022] [Indexed: 06/17/2023]
Abstract
Urban air pollution is a global concern impairing citizens' health, thus monitoring is a pressing need for city managers. City-wide networks for air pollution monitoring based on low-cost sensors are promising to provide real-time data with detail and scale never before possible. However, they still present limitations preventing their ubiquitous use. Thus, this study aimed to perform a post-deployment validation and calibration based on two step methods for ozone low-cost sensor of a city-wide network for air pollution and meteorology monitoring using low-cost sensors focusing on the main challenges. Four of the 23 data collection units (DCUs) of the UrbanSense network installed in Porto city (Portugal) with low-cost sensors for particulate matter (PM), carbon monoxide (CO), ozone (O3), and meteorological variables (temperature, relative humidity, luminosity, precipitation, and wind speed and direction) were evaluated. This study identified post-deployment challenges related to their validation and calibration. The preliminary validation showed that PM, CO and precipitation sensors recorded only unreliable data, and other sensors (wind speed and direction) very few data. A multi-step calibration strategy was implemented: inter-DCU calibration (1st step, for O3, temperature and relative humidity) and calibration with a reference-grade instrument (2nd step, for O3). In the 1st step, multivariate linear regression (MLR) resulted in models with better performance than non-linear models such as artificial neural networks (errors almost zero and R2 > 0.80). In the 2nd step, the calibration models using non-linear machine learning boosting algorithms, namely Stochastic Gradient Boosting Regressor (both with the default and post-tuning hyper-parameters), performed better than artificial neural networks and linear regression approaches. The calibrated O3 data resulted in a marginal improvement from the raw data, with error values close to zero, with low predictability (R2 ∼ 0.32). The lessons learned with the present study evidenced the need to redesign the calibration strategy. Thus, a novel multi-step calibration strategy is proposed, based on two steps (pre and post-deployment calibration). When performed cyclically and continuously, this strategy reduces the need for reference instruments, while probably minimising data drifts over time. More experimental campaigns are needed to collect more data and further improve calibration models.
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Affiliation(s)
- J P Sá
- LEPABE - Laboratory for Process Engineering, Environment, Biotechnology and Energy, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal; ALiCE - Associate Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal
| | - H Chojer
- LEPABE - Laboratory for Process Engineering, Environment, Biotechnology and Energy, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal; ALiCE - Associate Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal
| | - P T B S Branco
- LEPABE - Laboratory for Process Engineering, Environment, Biotechnology and Energy, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal; ALiCE - Associate Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal
| | - M C M Alvim-Ferraz
- LEPABE - Laboratory for Process Engineering, Environment, Biotechnology and Energy, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal; ALiCE - Associate Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal
| | - F G Martins
- LEPABE - Laboratory for Process Engineering, Environment, Biotechnology and Energy, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal; ALiCE - Associate Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal
| | - S I V Sousa
- LEPABE - Laboratory for Process Engineering, Environment, Biotechnology and Energy, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal; ALiCE - Associate Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal.
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Wiryasaputra R, Huang CY, Kristiani E, Liu PY, Yeh TK, Yang CT. Review of an intelligent indoor environment monitoring and management system for COVID-19 risk mitigation. Front Public Health 2023; 10:1022055. [PMID: 36703846 PMCID: PMC9871550 DOI: 10.3389/fpubh.2022.1022055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 12/23/2022] [Indexed: 01/12/2023] Open
Abstract
The coronavirus disease (COVID-19) outbreak has turned the world upside down bringing about a massive impact on society due to enforced measures such as the curtailment of personal travel and limitations on economic activities. The global pandemic resulted in numerous people spending their time at home, working, and learning from home hence exposing them to air contaminants of outdoor and indoor origins. COVID-19 is caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which spreads by airborne transmission. The viruses found indoors are linked to the building's ventilation system quality. The ventilation flow in an indoor environment controls the movement and advection of any aerosols, pollutants, and Carbon Dioxide (CO2) created by indoor sources/occupants; the quantity of CO2 can be measured by sensors. Indoor CO2 monitoring is a technique used to track a person's COVID-19 risk, but high or low CO2 levels do not necessarily mean that the COVID-19 virus is present in the air. CO2 monitors, in short, can help inform an individual whether they are breathing in clean air. In terms of COVID-19 risk mitigation strategies, intelligent indoor monitoring systems use various sensors that are available in the marketplace. This work presents a review of scientific articles that influence intelligent monitoring development and indoor environmental quality management system. The paper underlines that the non-dispersive infrared (NDIR) sensor and ESP8266 microcontroller support the development of low-cost indoor air monitoring at learning facilities.
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Affiliation(s)
- Rita Wiryasaputra
- Department of Industrial Engineering and Enterprise Information, Tunghai University, Taichung, Taiwan
- Department of Informatics, Krida Wacana Christian University, Jakarta, Indonesia
| | - Chin-Yin Huang
- Department of Industrial Engineering and Enterprise Information, Tunghai University, Taichung, Taiwan
| | - Endah Kristiani
- Department of Informatics, Krida Wacana Christian University, Jakarta, Indonesia
- Department of Computer Science, Tunghai University, Taichung, Taiwan
| | - Po-Yu Liu
- Division of Infection, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- Ph.D. Program in Translational Medicine, National Chung Hsing University, Taichung, Taiwan
- Rong Hsing Research Center for Translational Medicine, National Chung Hsing University, Taichung, Taiwan
- Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung, Taiwan
- Genomic Center for Infectious Diseases, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Ting-Kuang Yeh
- Division of Infection, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- Genomic Center for Infectious Diseases, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Chao-Tung Yang
- Department of Computer Science, Tunghai University, Taichung, Taiwan
- Research Center for Smart Sustainable Circular Economy, Tunghai University, Taichung, Taiwan
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10
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Rosenberger J, Guo Z, Coffman A, Agdas D, Barooah P. An Open-Source Platform for Indoor Environment Monitoring with Participatory Comfort Sensing. SENSORS (BASEL, SWITZERLAND) 2022; 23:364. [PMID: 36616962 PMCID: PMC9824258 DOI: 10.3390/s23010364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 12/08/2022] [Accepted: 12/13/2022] [Indexed: 06/17/2023]
Abstract
We present an open-source wireless network and data management system for collecting and storing indoor environmental measurements and perceived comfort via participatory sensing in commercial buildings. The system, called a personal comfort and indoor environment measurement (PCIEM) platform, consists of several devices placed in office occupants' work areas, a wireless network, and a remote database to store the data. Each device, called a PCFN (personal comfort feedback node), contains a touchscreen through which the occupant can provide feedback on their perceived comfort on-demand, and several sensors to collect environmental data. The platform is designed to be part of an indoor climate control system that can enable personalized comfort control in real-time. We describe the design, prototyping, and initial deployment of a small number of PCFNs in a commercial building. We also provide lessons learned from these steps. Application of the data collected from the PCFNs for modeling and real-time control will be reported in future work. We use hardware components that are commercial and off-the-shelf, and our software design is based on open-source tools that are freely and publicly available to enable repeatability.
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11
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Blaauw SA, Maina JW, O'Connell J. Exposure of construction workers to hazardous emissions in highway rehabilitation projects measured with low-cost sensors. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 313:119872. [PMID: 35995294 DOI: 10.1016/j.envpol.2022.119872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 07/22/2022] [Accepted: 07/26/2022] [Indexed: 06/15/2023]
Abstract
Construction workers on highway rehabilitation projects can be exposed to a combination of traffic- and construction-related emissions. To assess the personal exposure a worker experiences, a portable battery-operated Air Quality Device (AQD) was utilised to measure emissions during normal construction operations of a major road rehabilitation project. Emissions measured were nitrogen dioxide (NO2), Total Volatile Organic Compounds (TVOCs) and Particulate Matter (PM10, PM2.5, and PM1). The objective of the paper is to document the hazardous emissions that construction workers may be exposed to and allow for a basis of informed decision making to mitigate the risks of a road construction project. Most critically, this article is designed to raise awareness of the potential impact to a worker's wellbeing as well as highlight the need for further research. Through statistical analysis, asphalt paving was identified as the most hazardous activity in terms of exposure relative to other activities. This activity was further assessed using discrete-time Markov chain Monte Carlo simulations with results indicating a high probability that workers may be exposed to greater hazardous emission concentrations than measured. Limiting the distance to the source of emissions, large-scale use of warm-mix asphalt and reducing the idling times of construction vehicles were identified as practical mitigation measures to reduce exposure and aid in achieving zero-harm objectives. Finally, it is found that males are more susceptible to long-term implications of hazardous emission inhalation and should be more aware if the scenarios they might work in expose them to this.
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Affiliation(s)
- Sheldon A Blaauw
- Arup, 1st Floor City Gate West, Tollhouse Hill, Nottingham, NG1 5AT, UK; Department of Civil Engineering, University of Pretoria, Private Bag X20, Hatfield, 0028, South Africa.
| | - James W Maina
- Department of Civil Engineering, University of Pretoria, Private Bag X20, Hatfield, 0028, South Africa.
| | - Johan O'Connell
- Department of Civil Engineering, University of Pretoria, Private Bag X20, Hatfield, 0028, South Africa; Smart Mobility, Council for Scientific and Industrial Research (CSIR), Private Bag 395, Pretoria, 0001, South Africa.
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12
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Szagri D, Dobszay B, Nagy B, Szalay Z. Wireless Temperature, Relative Humidity and Occupancy Monitoring System for Investigating Overheating in Buildings. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22228638. [PMID: 36433234 PMCID: PMC9699293 DOI: 10.3390/s22228638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 11/06/2022] [Accepted: 11/07/2022] [Indexed: 05/14/2023]
Abstract
With the climate change we are experiencing today, the number and intensity of heatwaves are increasing dramatically, significantly impacting our buildings' overheating. The majority of the prefabricated concrete panel buildings in Hungary are considered outdated from an energy point of view. These buildings may be at greater risk from extreme weather events. To examine this, long-term monitoring measurements are needed. Therefore, we developed a unique, reliable, and cost-effective wireless monitoring system, which can track in real time the indoor air quality data (temperature, relative humidity, CO2) of the investigated apartment building, as well as users' habits, such as resident presence, window opening, and blind movement. The data were used to analyse and quantify the summer overheating of the dwelling and user habits. The measurements showed that the average temperature in all rooms was above 26 °C, and there were several occasions when the temperature exceeded 30 °C. Overheating in apartment buildings in summer is a significant problem that needs to be addressed. Further investigation of ventilation habits will help develop favourable ventilation strategies, and using these measurements in dynamic simulations will also help improve the models' validity for further studies.
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Affiliation(s)
- Dóra Szagri
- Department of Construction Materials and Technologies, Faculty of Civil Engineering, Budapest University of Technology and Economics, Műegyetem rkp. 3, 1111 Budapest, Hungary
| | - Bálint Dobszay
- Building Construction Design Kft., Harmat u. 20, 1105 Budapest, Hungary
| | - Balázs Nagy
- Department of Construction Materials and Technologies, Faculty of Civil Engineering, Budapest University of Technology and Economics, Műegyetem rkp. 3, 1111 Budapest, Hungary
- Correspondence: ; Tel.: +36-1-463-1175
| | - Zsuzsa Szalay
- Department of Construction Materials and Technologies, Faculty of Civil Engineering, Budapest University of Technology and Economics, Műegyetem rkp. 3, 1111 Budapest, Hungary
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13
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Xu Q, Goh HC, Mousavi E, Nabizadeh Rafsanjani H, Varghese Z, Pandit Y, Ghahramani A. Towards Personalization of Indoor Air Quality: Review of Sensing Requirements and Field Deployments. SENSORS (BASEL, SWITZERLAND) 2022; 22:3444. [PMID: 35591133 PMCID: PMC9104953 DOI: 10.3390/s22093444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 04/20/2022] [Accepted: 04/26/2022] [Indexed: 06/15/2023]
Abstract
As humans spend more time indoors, ensuring acceptable indoor air quality (IAQ) through ubiquitous sensing systems has become a necessity. Although extensive studies have been conducted on the IAQ sensing systems, a holistic review of the performance and deployment of Ubiquitous IAQ Sensing (UIAQS) systems with associated requirements in IAQ sensing standards is still lacking. In this study, we first reviewed IAQ pollutants and other IAQ-related factors and the associated requirements in the prominent IAQ sensing standards. We found that while non-pollutant factors are influential on occupants' perception of IAQ and their satisfaction, they do not have evaluation metrics in the IAQ standards. Then, we systematically reviewed field studies on UIAQS technologies in the literature. Specific classes of information were recorded and analyzed further. We found that the majority of the UIAQS systems did not meet the requirements of the prominent IAQ sensing standards and identified four primary research gaps. We concluded that a new holistic and personalized approach that incorporates UIAQS measurements and subjective feedback is needed. This study provides valuable insights for researchers and policymakers to better improve UIAQS technologies by developing personalized IAQ sensors and sensing standards.
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Affiliation(s)
- Qian Xu
- Department of the Built Environment, College of Design and Engineering, National University of Singapore, Singapore 119077, Singapore; (Q.X.); (H.C.G.)
| | - Hui Ci Goh
- Department of the Built Environment, College of Design and Engineering, National University of Singapore, Singapore 119077, Singapore; (Q.X.); (H.C.G.)
| | - Ehsan Mousavi
- Department of Construction Science and Management, Clemson University, Clemson, SC 29634, USA;
| | | | - Zubin Varghese
- Trane Technologies PLC Engineering & Technology Centre, Bangalore 560029, India; (Z.V.); (Y.P.)
| | - Yogesh Pandit
- Trane Technologies PLC Engineering & Technology Centre, Bangalore 560029, India; (Z.V.); (Y.P.)
| | - Ali Ghahramani
- Department of the Built Environment, College of Design and Engineering, National University of Singapore, Singapore 119077, Singapore; (Q.X.); (H.C.G.)
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14
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Data-Driven Techniques for Low-Cost Sensor Selection and Calibration for the Use Case of Air Quality Monitoring. SENSORS 2022; 22:s22031093. [PMID: 35161837 PMCID: PMC8839978 DOI: 10.3390/s22031093] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 01/07/2022] [Accepted: 01/25/2022] [Indexed: 12/10/2022]
Abstract
With the emergence of Low-Cost Sensor (LCS) devices, measuring real-time data on a large scale has become a feasible alternative approach to more costly devices. Over the years, sensor technologies have evolved which has provided the opportunity to have diversity in LCS selection for the same task. However, this diversity in sensor types adds complexity to appropriate sensor selection for monitoring tasks. In addition, LCS devices are often associated with low confidence in terms of sensing accuracy because of the complexities in sensing principles and the interpretation of monitored data. From the data analytics point of view, data quality is a major concern as low-quality data more often leads to low confidence in the monitoring systems. Therefore, any applications on building monitoring systems using LCS devices need to focus on two main techniques: sensor selection and calibration to improve data quality. In this paper, data-driven techniques were presented for sensor calibration techniques. To validate our methodology and techniques, an air quality monitoring case study from the Bradford district, UK, as part of two European Union (EU) funded projects was used. For this case study, the candidate sensors were selected based on the literature and market availability. The candidate sensors were narrowed down into the selected sensors after analysing their consistency. To address data quality issues, four different calibration methods were compared to derive the best-suited calibration method for the LCS devices in our use case system. In the calibration, meteorological parameters temperature and humidity were used in addition to the observed readings. Moreover, we uniquely considered Absolute Humidity (AH) and Relative Humidity (RH) as part of the calibration process. To validate the result of experimentation, the Coefficient of Determination (R2), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) were compared for both AH and RH. The experimental results showed that calibration with AH has better performance as compared with RH. The experimental results showed the selection and calibration techniques that can be used in designing similar LCS based monitoring systems.
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15
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Abstract
Radon poses significant health risks. Thus, the continuous monitoring of radon concentrations in buildings’ indoor air is relevant, particularly in schools. Low-cost sensors devices are emerging as promising technologies, although their reliability is still unknown. Therefore, this is the first study aiming to evaluate the performance of low-cost sensors devices for short-term continuous radon monitoring in the indoor air of nursery and primary school buildings. Five classrooms of different age groups (infants, pre-schoolers and primary school children) were selected from one nursery and one primary school in Porto (Portugal). Radon indoor concentrations were continuously monitored using one reference instrument (Radim 5B) and three commercially available low-cost sensors devices (Airthings Wave and RandonEye: RD200 and RD200P2) for short-term sampling (2–4 consecutive days) in each studied classroom. Radon concentrations were in accordance with the typical profiles found in other studies (higher on weekends and non-occupancy periods than on occupancy). Both RadonEye low-cost sensors devices presented similar profiles with Radim 5B and good performance indices (R2 reaching 0.961), while the Airthings Wave behavior was quite different. These results seem to indicate that the RadonEye low-cost sensors devices studied can be used in short-term radon monitoring, being promising tools for actively reducing indoor radon concentrations.
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16
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Narayana MV, Jalihal D, Nagendra SMS. Establishing A Sustainable Low-Cost Air Quality Monitoring Setup: A Survey of the State-of-the-Art. SENSORS (BASEL, SWITZERLAND) 2022; 22:394. [PMID: 35009933 PMCID: PMC8749853 DOI: 10.3390/s22010394] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 12/09/2021] [Accepted: 12/14/2021] [Indexed: 05/27/2023]
Abstract
Low-cost sensors (LCS) are becoming popular for air quality monitoring (AQM). They promise high spatial and temporal resolutions at low-cost. In addition, citizen science applications such as personal exposure monitoring can be implemented effortlessly. However, the reliability of the data is questionable due to various error sources involved in the LCS measurement. Furthermore, sensor performance drift over time is another issue. Hence, the adoption of LCS by regulatory agencies is still evolving. Several studies have been conducted to improve the performance of low-cost sensors. This article summarizes the existing studies on the state-of-the-art of LCS for AQM. We conceptualize a step by step procedure to establish a sustainable AQM setup with LCS that can produce reliable data. The selection of sensors, calibration and evaluation, hardware setup, evaluation metrics and inferences, and end user-specific applications are various stages in the LCS-based AQM setup we propose. We present a critical analysis at every step of the AQM setup to obtain reliable data from the low-cost measurement. Finally, we conclude this study with future scope to improve the availability of air quality data.
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Affiliation(s)
| | - Devendra Jalihal
- Electrical Engineering, Indian Institute of Technology, Madras 600036, India;
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17
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Park Y, Lee C, Jung JY. Digital Healthcare for Airway Diseases from Personal Environmental Exposure. Yonsei Med J 2022; 63:S1-S13. [PMID: 35040601 PMCID: PMC8790581 DOI: 10.3349/ymj.2022.63.s1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 10/30/2021] [Accepted: 11/15/2021] [Indexed: 11/27/2022] Open
Abstract
Digital technologies have emerged in various dimensions of human life, ranging from education to professional services to well-being. In particular, health products and services have expanded by the use and development of artificial intelligence, mobile health applications, and wearable electronic devices. Such advancements have enabled accurate and updated tracking and modeling of health conditions. For instance, digital health technologies are capable of measuring environmental pollution and predicting its adverse health effects. Several health conditions, including chronic airway diseases such as asthma and chronic obstructive pulmonary disease, can be exacerbated by pollution. These diseases impose substantial health burdens with high morbidity and mortality. Recently, efforts have been made to develop digital technologies to alleviate such conditions. Moreover, the COVID-19 pandemic has facilitated the application of telemedicine and telemonitoring for patients with chronic airway diseases. This article reviews current trends and studies in digital technology utilization for investigating and managing environmental exposure and chronic airway diseases. First, we discussed the recent progression of digital technologies in general environmental healthcare. Then, we summarized the capacity of digital technologies in predicting exacerbation and self-management of airway diseases. Concluding these reviews, we provided suggestions to improve digital health technologies' abilities to reduce the adverse effects of environmental exposure in chronic airway diseases, based on personal exposure-response modeling.
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Affiliation(s)
- Youngmok Park
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Chanho Lee
- Severance Biomedical Science Institute, Yonsei Biomedical Research Institute, Yonsei University College of Medicine, Seoul, Korea
| | - Ji Ye Jung
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
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18
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Indoor Nanoparticle Characterization in Construction Waste Recycling Companies over Time. SUSTAINABILITY 2021. [DOI: 10.3390/su132414071] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Building activity is a significant source of atmospheric contamination by ultrafine dust. Cognizant of this fact, those active in the use and recycling of construction materials must be aware of the risks associated with exposure to nanoparticles (NPs) and ultra-fine particles (UFPs), as well as the associated health impacts. This work analyzed NPs and UFPs generated in a small building-material recycling company using high-resolution electron microscopes and X-ray Diffraction. A self-made passive sampler (LSPS) that can obtain particulate samples without physical and morphological changes, especially where there is a suspension of particulate material, was used in this study. A total of 96 particulate samples, using the LSPS for three months in four seasons, were collected during the study. Thus, the dry deposition of the particles, which are considered highly harmful to human health, was found in each of the four seasons of the year. It is suggested that for future research, the toxicological evaluations of the particulates in the construction industry should be investigated through the consideration of measures to control and mitigate the health risks of workers regarding exposure to NPs and UFPs.
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19
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Fanti G, Borghi F, Spinazzè A, Rovelli S, Campagnolo D, Keller M, Cattaneo A, Cauda E, Cavallo DM. Features and Practicability of the Next-Generation Sensors and Monitors for Exposure Assessment to Airborne Pollutants: A Systematic Review. SENSORS (BASEL, SWITZERLAND) 2021; 21:4513. [PMID: 34209443 PMCID: PMC8271362 DOI: 10.3390/s21134513] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 06/25/2021] [Accepted: 06/28/2021] [Indexed: 11/22/2022]
Abstract
In the last years, the issue of exposure assessment of airborne pollutants has been on the rise, both in the environmental and occupational fields. Increasingly severe national and international air quality standards, indoor air guidance values, and exposure limit values have been developed to protect the health of the general population and workers; this issue required a significant and continuous improvement in monitoring technologies to allow the execution of proper exposure assessment studies. One of the most interesting aspects in this field is the development of the "next-generation" of airborne pollutants monitors and sensors (NGMS). The principal aim of this review is to analyze and characterize the state of the art and of NGMS and their practical applications in exposure assessment studies. A systematic review of the literature was performed analyzing outcomes from three different databases (Scopus, PubMed, Isi Web of Knowledge); a total of 67 scientific papers were analyzed. The reviewing process was conducting systematically with the aim to extrapolate information about the specifications, technologies, and applicability of NGMSs in both environmental and occupational exposure assessment. The principal results of this review show that the use of NGMSs is becoming increasingly common in the scientific community for both environmental and occupational exposure assessment. The available studies outlined that NGMSs cannot be used as reference instrumentation in air monitoring for regulatory purposes, but at the same time, they can be easily adapted to more specific applications, improving exposure assessment studies in terms of spatiotemporal resolution, wearability, and adaptability to different types of projects and applications. Nevertheless, improvements needed to further enhance NGMSs performances and allow their wider use in the field of exposure assessment are also discussed.
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Affiliation(s)
- Giacomo Fanti
- Department of Science and High Technology, University of Insubria, 22100 Como, Italy; (A.S.); (S.R.); (D.C.); (M.K.); (A.C.); (D.M.C.)
| | - Francesca Borghi
- Department of Science and High Technology, University of Insubria, 22100 Como, Italy; (A.S.); (S.R.); (D.C.); (M.K.); (A.C.); (D.M.C.)
| | - Andrea Spinazzè
- Department of Science and High Technology, University of Insubria, 22100 Como, Italy; (A.S.); (S.R.); (D.C.); (M.K.); (A.C.); (D.M.C.)
| | - Sabrina Rovelli
- Department of Science and High Technology, University of Insubria, 22100 Como, Italy; (A.S.); (S.R.); (D.C.); (M.K.); (A.C.); (D.M.C.)
| | - Davide Campagnolo
- Department of Science and High Technology, University of Insubria, 22100 Como, Italy; (A.S.); (S.R.); (D.C.); (M.K.); (A.C.); (D.M.C.)
| | - Marta Keller
- Department of Science and High Technology, University of Insubria, 22100 Como, Italy; (A.S.); (S.R.); (D.C.); (M.K.); (A.C.); (D.M.C.)
| | - Andrea Cattaneo
- Department of Science and High Technology, University of Insubria, 22100 Como, Italy; (A.S.); (S.R.); (D.C.); (M.K.); (A.C.); (D.M.C.)
| | - Emanuele Cauda
- Center for Direct Reading and Sensor Technologies, National Institute for Occupational Safety and Health, Pittsburgh, PA 15236, USA;
- Centers for Disease Control and Prevention, Pittsburgh, PA 15236, USA
| | - Domenico Maria Cavallo
- Department of Science and High Technology, University of Insubria, 22100 Como, Italy; (A.S.); (S.R.); (D.C.); (M.K.); (A.C.); (D.M.C.)
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20
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Kaduwela A, Wexler A. Use of low-cost air sensors to augment regulatory networks. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2021; 71:680-681. [PMID: 33630720 DOI: 10.1080/10962247.2021.1895577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Affiliation(s)
- Ajith Kaduwela
- Air Quality Research Center, University of California at Davis,
| | - Anthony Wexler
- Air Quality Research Center, Department of Mechanical and Aerospace Engineering, Department of Civil and Environmental Engineering, Land, Air, and Water Resources, University of California at Davis
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21
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Monitoring of Particulate Matter Emissions from 3D Printing Activity in the Home Setting. SENSORS 2021; 21:s21093247. [PMID: 34067219 PMCID: PMC8125858 DOI: 10.3390/s21093247] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 05/01/2021] [Accepted: 05/03/2021] [Indexed: 11/16/2022]
Abstract
Consumer-level 3D printers are becoming increasingly prevalent in home settings. However, research shows that printing with these desktop 3D printers can impact indoor air quality (IAQ). This study examined particulate matter (PM) emissions generated by 3D printers in an indoor domestic setting. Print filament type, brand, and color were investigated and shown to all have significant impacts on the PM emission profiles over time. For example, emission rates were observed to vary by up to 150-fold, depending on the brand of a specific filament being used. Various printer settings (e.g., fan speed, infill density, extruder temperature) were also investigated. This study identifies that high levels of PM are triggered by the filament heating process and that accessible, user-controlled print settings can be used to modulate the PM emission from the 3D printing process. Considering these findings, a low-cost home IAQ sensor was evaluated as a potential means to enable a home user to monitor PM emissions from their 3D printing activities. This sensing approach was demonstrated to detect the timepoint where the onset of PM emission from a 3D print occurs. Therefore, these low-cost sensors could serve to inform the user when PM levels in the home become elevated significantly on account of this activity and furthermore, can indicate the time at which PM levels return to baseline after the printing process and/or after adding ventilation. By deploying such sensors at home, domestic users of 3D printers can assess the impact of filament type, color, and brand that they utilize on PM emissions, as well as be informed of how their selected print settings can impact their PM exposure levels.
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22
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Indoor Air Quality in Domestic Environments during Periods Close to Italian COVID-19 Lockdown. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18084060. [PMID: 33921463 PMCID: PMC8070062 DOI: 10.3390/ijerph18084060] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 04/09/2021] [Accepted: 04/10/2021] [Indexed: 11/16/2022]
Abstract
This paper describes the in situ monitoring of indoor air quality (IAQ) in two dwellings, using low-cost IAQ sensors to provide high-density temporal and spatial data. IAQ measurements were conducted over 2-week periods in the kitchen and bedroom of each home during the winter, spring, and summer seasons, characterized by different outside parameters, that were simultaneously measured. The mean indoor PM2.5 concentrations were about 15 μg m−3 in winter, they dropped to values close to 10 μg m−3 in spring and increased to levels of about 13 μg m−3 in summer. During the winter campaign, indoor PM2.5 was found mainly associated with particle penetration inside the rooms from outdoors, because of the high outdoor PM2.5 levels in the season. Such pollution winter episodes occur frequently in the study region, due to the combined contributions of strong anthropogenic emissions and stable atmospheric conditions. The concentrations of indoor volatile organic compounds (VOCs) and CO2 increased with the number of occupants (humans and pets), as likely associated with consequent higher emissions through breathing and metabolic processes. They also varied with occupants’ daily activities, like cooking and cleaning. Critic CO2 levels above the limit of 1000 ppm were observed in spring campaign, in the weeks close to the end of the COVID-19 quarantine, likely associated with the increased time that the occupants spent at home.
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Abstract
The evolution of low-cost sensors (LCSs) has made the spatio-temporal mapping of indoor air quality (IAQ) possible in real-time but the availability of a diverse set of LCSs make their selection challenging. Converting individual sensors into a sensing network requires the knowledge of diverse research disciplines, which we aim to bring together by making IAQ an advanced feature of smart homes. The aim of this review is to discuss the advanced home automation technologies for the monitoring and control of IAQ through networked air pollution LCSs. The key steps that can allow transforming conventional homes into smart homes are sensor selection, deployment strategies, data processing, and development of predictive models. A detailed synthesis of air pollution LCSs allowed us to summarise their advantages and drawbacks for spatio-temporal mapping of IAQ. We concluded that the performance evaluation of LCSs under controlled laboratory conditions prior to deployment is recommended for quality assurance/control (QA/QC), however, routine calibration or implementing statistical techniques during operational times, especially during long-term monitoring, is required for a network of sensors. The deployment height of sensors could vary purposefully as per location and exposure height of the occupants inside home environments for a spatio-temporal mapping. Appropriate data processing tools are needed to handle a huge amount of multivariate data to automate pre-/post-processing tasks, leading to more scalable, reliable and adaptable solutions. The review also showed the potential of using machine learning technique for predicting spatio-temporal IAQ in LCS networked-systems.
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24
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Saini J, Dutta M, Marques G. Sensors for indoor air quality monitoring and assessment through Internet of Things: a systematic review. ENVIRONMENTAL MONITORING AND ASSESSMENT 2021; 193:66. [PMID: 33452599 DOI: 10.1007/s10661-020-08781-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Accepted: 11/30/2020] [Indexed: 06/12/2023]
Abstract
The growing populations around the world are closely associated with rising levels of air pollution. The impact is not restricted to outdoor areas. Moreover, the health of building occupants is also deteriorating due to poor indoor air quality. As per the World Health Organization, indoor air pollution is a leading cause of 1.6 million premature deaths annually. Therefore, numerous companies have started the development of low-cost sensors to monitor indoor air pollution with the Internet of Things-based applications. However, due to the close association of air pollution levels to the mortality and morbidity rates, communities face several limitations while selecting sensors to address this public health challenge. The main contribution of this systematic review is to present a qualitative and quantitative evaluation of low-cost sensors while providing deep insights into the selection criteria for adequate monitoring. The authors in this paper discussed studies published after the year 2015, and it includes an analysis of papers published in the English language only. Moreover, this study highlights crucial research questions, states answers, and provides recommendations for future research studies. The outcomes of this paper will be useful for students, researchers, and industry members concerning the upcoming research and manufacturing activities. The results show that 28 studies (70%) include indoor thermal comfort assessment, 26 (65%) and 12 (30%) studies include CO2 and CO sensors, respectively. In total, 32 (45.7%) out of 71 sensors (whose prices are available) discussed in this study are available in a price below the US $20 over online marketplaces. Furthermore, the authors conclude that 77.5% of the analyzed literature does not include calibration details, and the accuracy specification is missing for 39.4% sensors.
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Affiliation(s)
- Jagriti Saini
- National Institute of Technical Teacher's Training and Research, Chandigarh, 160019, India.
| | - Maitreyee Dutta
- National Institute of Technical Teacher's Training and Research, Chandigarh, 160019, India
| | - Goncalo Marques
- Polytechnic of Coimbra, ESTGOH, 3400-124, Oliveira do Hospital, Portugal
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25
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González E, Casanova-Chafer J, Romero A, Vilanova X, Mitrovics J, Llobet E. LoRa Sensor Network Development for Air Quality Monitoring or Detecting Gas Leakage Events. SENSORS 2020; 20:s20216225. [PMID: 33142820 PMCID: PMC7672618 DOI: 10.3390/s20216225] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Revised: 10/28/2020] [Accepted: 10/30/2020] [Indexed: 12/18/2022]
Abstract
During the few last years, indoor and outdoor Air Quality Monitoring (AQM) has gained a lot of interest among the scientific community due to its direct relation with human health. The Internet of Things (IoT) and, especially, Wireless Sensor Networks (WSN) have given rise to the development of wireless AQM portable systems. This paper presents the development of a LoRa (short for long-range) based sensor network for AQM and gas leakage events detection. The combination of both a commercial gas sensor and a resistance measurement channel for graphene chemoresistive sensors allows both the calculation of an Air Quality Index based on the concentration of reducing species such as volatile organic compounds (VOCs) and CO, and it also makes possible the detection of NO2, which is an important air pollutant. The graphene sensor tested with the LoRa nodes developed allows the detection of NO2 pollution in just 5 min as well as enables monitoring sudden changes in the background level of this pollutant in the atmosphere. The capability of the system of detecting both reducing and oxidizing pollutant agents, alongside its low-cost, low-power, and real-time monitoring features, makes this a solution suitable to be used in wireless AQM and early warning systems.
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Affiliation(s)
- Ernesto González
- Electronic Engineering, Uiversitat Rovira i Virgili, MINOS, 43007 Tarragona, Spain; (E.G.); (J.C.-C.); (A.R.); (E.L.)
| | - Juan Casanova-Chafer
- Electronic Engineering, Uiversitat Rovira i Virgili, MINOS, 43007 Tarragona, Spain; (E.G.); (J.C.-C.); (A.R.); (E.L.)
| | - Alfonso Romero
- Electronic Engineering, Uiversitat Rovira i Virgili, MINOS, 43007 Tarragona, Spain; (E.G.); (J.C.-C.); (A.R.); (E.L.)
| | - Xavier Vilanova
- Electronic Engineering, Uiversitat Rovira i Virgili, MINOS, 43007 Tarragona, Spain; (E.G.); (J.C.-C.); (A.R.); (E.L.)
- Correspondence: ; Tel.: +34-977-558-502
| | | | - Eduard Llobet
- Electronic Engineering, Uiversitat Rovira i Virgili, MINOS, 43007 Tarragona, Spain; (E.G.); (J.C.-C.); (A.R.); (E.L.)
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Yun H, Yang J, Lee BH, Kim J, Sohn JR. Indoor Thermal Environment Long-Term Data Analytics Using IoT Devices in Korean Apartments: A Case Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17197334. [PMID: 33049930 PMCID: PMC7579249 DOI: 10.3390/ijerph17197334] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 09/29/2020] [Accepted: 10/06/2020] [Indexed: 11/16/2022]
Abstract
IoT-based monitoring devices can transmit real-time and long-term thermal environment data, enabling innovative conversion for the evaluation and management of the indoor thermal environment. However, long-term indoor thermal measurements using IoT-based devices to investigate health effects have rarely been conducted. Using apartments in Seoul as a case study, we conducted long-term monitoring of thermal environmental using IoT-based real-time wireless sensors. We measured the temperature, relative humidity (RH), and CO2 in the kitchen, living room, and bedrooms of each household over one year. In addition, in one of the houses, velocity and globe temperatures were measured for multiple summer and autumn seasons. Results of our present study indicated that outdoor temperature is an important influencing factor of indoor thermal environment and indoor RH is a good indicator of residents’ lifestyle. Our findings highlighted the need for temperature management in summer, RH management in winter, and kitchen thermal environment management during summer and tropical nights. This study suggested that IoT devices are a potential approach for evaluating personal exposure to indoor thermal environmental risks. In addition, long-term monitoring and analysis is an efficient approach for analyzing complex indoor thermal environments and is a viable method for application in healthcare.
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Affiliation(s)
- Hyunjun Yun
- Department of Health and Safety Convergence Science, Graduate School of Korea University, 73, Goryeodae-ro, Seongbuk-gu, Seoul 02841, Korea; (H.Y.); (J.Y.)
- The Environment Technology Institute, Coway Co., LTD, 1, Gwanak-ro, Gwanak-gu, Seoul 08826, Korea; (B.H.L.); (J.K.)
| | - Jinho Yang
- Department of Health and Safety Convergence Science, Graduate School of Korea University, 73, Goryeodae-ro, Seongbuk-gu, Seoul 02841, Korea; (H.Y.); (J.Y.)
| | - Byong Hyoek Lee
- The Environment Technology Institute, Coway Co., LTD, 1, Gwanak-ro, Gwanak-gu, Seoul 08826, Korea; (B.H.L.); (J.K.)
| | - Jongcheol Kim
- The Environment Technology Institute, Coway Co., LTD, 1, Gwanak-ro, Gwanak-gu, Seoul 08826, Korea; (B.H.L.); (J.K.)
| | - Jong-Ryeul Sohn
- Department of Public Health Science, Graduate School of Korea University, 73, Goryeodae-ro, Seongbuk-gu, Seoul 02841, Korea
- Correspondence: ; Tel.: +82-2-3290-5691
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Nieckarz Z, Zoladz JA. Low-cost air pollution monitoring system-an opportunity for reducing the health risk associated with physical activity in polluted air. PeerJ 2020; 8:e10041. [PMID: 33062442 PMCID: PMC7533060 DOI: 10.7717/peerj.10041] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 09/04/2020] [Indexed: 01/13/2023] Open
Abstract
The issue of air pollution by particulate matter (PM) concerns many places in the world. At the same time, many residents undertake physical activity (recreation, rehabilitation, sport) in the open air. Generally, the amount of dust concentration depends on both the place (center or periphery of the city) and the time of day. In the present study we describe the outcome of monitoring of the state of air pollution by particle matter (PM10) in the Kraków agglomeration area in order to show that it can provide information concerning air quality in the area where people practice varied kinds of sports in the open air. The measurements of PM10 have been made by a few stations with identical construction working as one network. The details of the air pollution monitoring system and its data quality verification have been described. The network stations made multipoint observations across the Kraków Metropolitan Area during the year 2017 in eight locations. The locations selected represent a diverse spectrum of terrain conditions in which the Kraków agglomeration community undertakes physical activity. For most months of 2017, the minimum monthly average 4-hour PM10 concentrations were recorded between 10–14 h, regardless of location, whereas the maximum was between 18–22. We also noticed a huge differences in the average monthly value of PM10 in some locations within the Kraków agglomeration—ranging between 4.9–339.0 µg m−3. This indicates that some regions of the city are more suitable for performance of physical activity in the open air than others. In conclusion, we postulate that a low-cost air pollution monitoring system is capable of providing valuable information concerning air quality in a given region, which seems to be of importance also to people who practice varied sports activities in the open air.
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Affiliation(s)
- Zenon Nieckarz
- Experimental Computer Physics Department, Marian Smoluchowski Institute of Physics, Jagiellonian University, Krakow, Poland.,Department of Muscle Physiology, Institute of Basic Sciences, Faculty of Rehabilitation, University School of Physical Education, Krakow, Poland
| | - Jerzy A Zoladz
- Department of Muscle Physiology, Institute of Basic Sciences, Faculty of Rehabilitation, University School of Physical Education, Krakow, Poland
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Environmental Health Surveillance System for a Population Using Advanced Exposure Assessment. TOXICS 2020; 8:toxics8030074. [PMID: 32962012 PMCID: PMC7560317 DOI: 10.3390/toxics8030074] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/23/2020] [Revised: 09/12/2020] [Accepted: 09/17/2020] [Indexed: 01/14/2023]
Abstract
Human exposure to air pollution is a major public health concern. Environmental policymakers have been implementing various strategies to reduce exposure, including the 10th-day-no-driving system. To assess exposure of an entire population of a community in a highly polluted area, pollutant concentrations in microenvironments and population time–activity patterns are required. To date, population exposure to air pollutants has been assessed using air monitoring data from fixed atmospheric monitoring stations, atmospheric dispersion modeling, or spatial interpolation techniques for pollutant concentrations. This is coupled with census data, administrative registers, and data on the patterns of the time-based activities at the individual scale. Recent technologies such as sensors, the Internet of Things (IoT), communications technology, and artificial intelligence enable the accurate evaluation of air pollution exposure for a population in an environmental health context. In this study, the latest trends in published papers on the assessment of population exposure to air pollution were reviewed. Subsequently, this study proposes a methodology that will enable policymakers to develop an environmental health surveillance system that evaluates the distribution of air pollution exposure for a population within a target area and establish countermeasures based on advanced exposure assessment.
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