scholarly journals A low-cost monitor for simultaneous measurement of fine particulate matter and aerosol optical depth – Part 3: Automation and design improvements

2021 ◽  
Vol 14 (9) ◽  
pp. 6023-6038 ◽  
Author(s):  
Eric A. Wendt ◽  
Casey Quinn ◽  
Christian L'Orange ◽  
Daniel D. Miller-Lionberg ◽  
Bonne Ford ◽  
...  

Abstract. Atmospheric particulate matter smaller than 2.5 µm in diameter (PM2.5) has a negative impact on public health, the environment, and Earth's climate. Consequently, a need exists for accurate, distributed measurements of surface-level PM2.5 concentrations at a global scale. Existing PM2.5 measurement infrastructure provides broad PM2.5 sampling coverage but does not adequately characterize community-level air pollution at high temporal resolution. This motivates the development of low-cost sensors which can be more practically deployed in spatial and temporal configurations currently lacking proper characterization. Wendt et al. (2019) described the development and validation of a first-generation device for low-cost measurement of AOD and PM2.5: the Aerosol Mass and Optical Depth (AMODv1) sampler. Ford et al. (2019) describe a citizen-science field deployment of the AMODv1 device. In this paper, we present an updated version of the AMOD, known as AMODv2, featuring design improvements and extended validation to address the limitations of the AMODv1 work. The AMODv2 measures AOD and PM2.5 at 20 min time intervals. The sampler includes a motorized Sun tracking system alongside a set of four optically filtered photodiodes for semicontinuous, multiwavelength (current version at 440, 500, 675, and 870 nm) AOD sampling. Also included are a Plantower PMS5003 sensor for time-resolved optical PM2.5 measurements and a pump/cyclone system for time-integrated gravimetric filter measurements of particle mass and composition. AMODv2 samples are configured using a smartphone application, and sample data are made available via data streaming to a companion website (https://csu-ceams.com/, last access: 16 July 2021). We present the results of a 9 d AOD validation campaign where AMODv2 units were co-located with an AERONET (Aerosol Robotics Network) instrument as the reference method at AOD levels ranging from 0.02 ± 0.01 to 1.59 ± 0.01. We observed close agreement between AMODv2s and the reference instrument with mean absolute errors of 0.04, 0.06, 0.03, and 0.03 AOD units at 440, 500, 675, and 870 nm, respectively. We derived empirical relationships relating the reference AOD level to AMODv2 instrument error and found that the mean absolute error in the AMODv2 deviated by less than 0.01 AOD units between clear days and elevated-AOD days and across all wavelengths. We identified bias from individual units, particularly due to calibration drift, as the primary source of error between AMODv2s and reference units. In a test of 15-month calibration stability performed on 16 AMOD units, we observed median changes to calibration constant values of −7.14 %, −9.64 %, −0.75 %, and −2.80 % at 440, 500, 675, and 870 nm, respectively. We propose annual recalibration to mitigate potential errors from calibration drift. We conducted a trial deployment to assess the reliability and mechanical robustness of AMODv2 units. We found that 75 % of attempted samples were successfully completed in rooftop laboratory testing. We identify several failure modes in the laboratory testing and describe design changes that we have since implemented to reduce failures. We demonstrate that the AMODv2 is an accurate, stable, and low-cost platform for air pollution measurement. We describe how the AMODv2 can be implemented in spatial citizen-science networks where reference-grade sensors are economically impractical and low-cost sensors lack accuracy and stability.

2021 ◽  
Author(s):  
Eric A. Wendt ◽  
Casey Quinn ◽  
Christian L'Orange ◽  
Daniel D. Miller-Lionberg ◽  
Bonne Ford ◽  
...  

Abstract. Atmospheric particulate matter smaller than 2.5 microns in diameter (PM2.5) impacts public health, the environment, and the climate. Consequently, a need exists for accurate, distributed measurements of surface-level PM2.5 concentrations at a global scale. Remote sensing observations of aerosol optical depth (AOD) have been used to estimate surface-level PM2.5 for studies on human health and the Earth system. However, these estimates are uncertain due to a lack of measurements available to validate the derived PM2.5 products, which rely on the ratio of surface PM2.5 to AOD. Traditional monitoring of these two air quality metrics is costly and cumbersome, leading to a lack of surface monitoring networks with high spatial density. In part 1 of this series we described the development and validation of a first-generation device for low-cost measurement of AOD and PM2.5: The Aerosol Mass and Optical Depth (AMODv1) sampler. Part 2 of the series describes a citizen-science field deployment of the AMODv1 device. Here in part 3, we present an autonomous version of the AMOD, known as AMODv2, capable of unsupervised measurement of AOD and PM2.5 at 20-minute time intervals. The AMODv2 includes a set of four optically filtered photodiodes for multi-wavelength (current version at 440, 500, 675, and 870 nm) AOD, a Plantower PMS5003 sensor for time-resolved optical PM2.5 measurements, and a pump and cyclone system for time-integrated gravimetric filter measurements of particle mass and composition. The AMODv2 uses low-cost motors and sensor data for autonomous sun alignment to provide the semi-continuous AOD measurements. Operators can connect to the AMODv2 over Bluetooth® and configure a sample using a smartphone application. A Wi-Fi module enables real-time data streaming and visualization on our website (csu-ceams.com). We present a sample deployment of 10 AMODv2s during a wildfire smoke event and demonstrate the ability of the instrument to capture changes in air quality at sub-hourly time resolution. We also present the results of an AOD validation campaign where AMODv2s were co-located with AERONET (Aerosol Robotics Network) instruments as the reference method at AOD levels ranging from 0.016 to 1.59. We observed close agreement between AMODv2s and the reference instrument with mean absolute errors of 0.046, 0.057, 0.026, and 0.033 AOD units at 440 nm, 500 nm, 675 nm, and 870 nm, respectively. We identified individual unit bias as the primary source of error between AMODv2s and reference units and propose re-calibration to mitigate these biases. The AMODv2 is well suited for citizen-science and other high-spatial-density deployments due to its low cost, compact form, user-friendly interface, and high measurement frequency of AOD and PM2.5. These deployments could provide a rich air pollution data set for evaluating remote sensing observations, atmospheric modeling simulations, and provide communities with the information they need to implement effective public health and environmental interventions.


2019 ◽  
Author(s):  
Bonne Ford ◽  
Jeffrey R. Pierce ◽  
Eric Wendt ◽  
Marilee Long ◽  
Shantanu Jathar ◽  
...  

Abstract. A pilot field campaign was conducted in the fall and winter of 2017 in northern Colorado to test the deployment of the Aerosol Mass and Optical Depth (AMOD) instrument as part of the Citizen-Enabled Aerosol Measurements for Satellites (CEAMS) network. Citizen scientists were recruited to set up the device to take filter and optical measurements of aerosols in their backyards. The goal of the network is to provide more surface particulate matter and aerosol optical depth (AOD) measurements to increase the spatial and temporal resolution of PM2.5 to AOD ratios and to improve satellite-based estimates of air quality. Participants collected 65 filters and 160 multi-wavelength AOD measurements from which 109 successful PM2.5 to AOD ratios were calculated. We show that PM2.5, AOD, and their ratio (PM2.5:AOD) often vary substantially over relatively short spatial scales; this spatial variation is not typically resolved by satellite- and model-based PM2.5 exposure estimates. The success of the pilot campaign suggests that citizen-science networks are a viable means for providing new insight into surface air quality. We also discuss lessons learned and AMOD design modifications, which will be used in future, wider deployments of the CEAMS network.


Author(s):  
Eric S. Coker ◽  
Ssematimba Joel ◽  
Engineer Bainomugisha

Background: There are major air pollution monitoring gaps in sub-Saharan Africa. Developing capacity in the region to conduct air monitoring in the region can help estimate exposure to air pollution for epidemiology research. The purpose of our study is to develop a land use regression (LUR) model using low-cost air quality sensors developed by a research group in Uganda (AirQo). Methods: Using these low-cost sensors, we collected continuous measurements of fine particulate matter (PM2.5) between May 1, 2019 and February 29, 2020 at 22 monitoring sites across urban municipalities of Uganda. We compared average monthly PM2.5 concentrations from the AirQo sensors with measurements from a BAM-1020 reference monitor operated at the US Embassy in Kampala. Monthly PM2.5 concentrations were used for LUR modeling. We used eight Machine Learning (ML) algorithms and ensemble modeling; using 10-fold cross validation and root mean squared error (RMSE) to evaluate model performance. Results: Monthly PM2.5 concentration was 60.2 µg/m3 (IQR: 45.4-73.0 µg/m3; median= 57.5 µg/m3). For the ML LUR models, RMSE values ranged between 5.43 µg/m3 - 15.43 µg/m3 and explained between 28% and 92% of monthly PM2.5 variability. Generalized additive models explained the largest amount of PM2.5 variability (R2=0.92) and produced the lowest RMSE (5.43 µg/m3) in the held-out test set. The most important predictors of monthly PM2.5 concentrations included monthly precipitation, major roadway density, population density, latitude, greenness, and percentage of households using solid fuels. Conclusion: To our knowledge, ours is the first study to model the spatial distribution of urban air pollution in sub-Saharan Africa using air monitors developed from the region itself. Non-parametric ML for LUR modeling performed with high accuracy for prediction of monthly PM2.5 levels. Our analysis suggests that locally produced low-cost air quality sensors can help build capacity to conduct air pollution epidemiology research in the region.


2019 ◽  
Vol 12 (12) ◽  
pp. 6385-6399 ◽  
Author(s):  
Bonne Ford ◽  
Jeffrey R. Pierce ◽  
Eric Wendt ◽  
Marilee Long ◽  
Shantanu Jathar ◽  
...  

Abstract. A pilot field campaign was conducted in the fall and winter of 2017 in northern Colorado to test the deployment of the Aerosol Mass and Optical Depth (AMOD) instrument as part of the Citizen-Enabled Aerosol Measurements for Satellites (CEAMS) network. Citizen scientists were recruited to set up the device to take filter and optical measurements of aerosols in their backyards. The goal of the network is to provide more surface particulate matter and aerosol optical depth (AOD) measurements to increase the spatial and temporal resolution of ratios of fine particulate matter (PM2.5) to AOD and to improve satellite-based estimates of air quality. Participants collected 65 filters and 160 multi-wavelength AOD measurements, from which 109 successful PM2.5 : AOD ratios were calculated. We show that PM2.5, AOD, and their ratio (PM2.5 : AOD) often vary substantially over relatively short spatial scales; this spatial variation is not typically resolved by satellite- and model-based PM2.5 exposure estimates. The success of the pilot campaign suggests that citizen-science networks are a viable means for providing new insight into surface air quality. We also discuss lessons learned and AMOD design modifications, which will be used in future wider deployments of the CEAMS network.


Atmosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 400 ◽  
Author(s):  
Evan R. Coffey ◽  
David Pfotenhauer ◽  
Anondo Mukherjee ◽  
Desmond Agao ◽  
Ali Moro ◽  
...  

Household air pollution from the combustion of solid fuels is a leading global health and human rights concern, affecting billions every day. Instrumentation to assess potential solutions to this problem faces challenges—especially related to cost. A low-cost ($159) particulate matter tool called the Household Air Pollution Exposure (HAPEx) Nano was evaluated in the field as part of the Prices, Peers, and Perceptions cookstove study in northern Ghana. Measurements of temperature, relative humidity, absolute humidity, and carbon dioxide and carbon monoxide concentrations made at 1-min temporal resolution were integrated with 1-min particulate matter less than 2.5 microns in diameter (PM2.5) measurements from the HAPEx, within 62 kitchens, across urban and rural households and four seasons totaling 71 48-h deployments. Gravimetric filter sampling was undertaken to ground-truth and evaluate the low-cost measurements. HAPEx baseline drift and relative humidity corrections were investigated and evaluated using signals from paired HAPEx, finding significant improvements. Resulting particle coefficients and integrated gravimetric PM2.5 concentrations were modeled to explore drivers of variability; urban/rural, season, kitchen characteristics, and dust (a major PM2.5 mass constituent) were significant predictors. The high correlation (R2 = 0.79) between 48-h mean HAPEx readings and gravimetric PM2.5 mass (including other covariates) indicates that the HAPEx can be a useful tool in household energy studies.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Caroline Kiai ◽  
Christopher Kanali ◽  
Joseph Sang ◽  
Michael Gatari

Air pollution is one of the most important environmental and public health concerns worldwide. Urban air pollution has been increasing since the industrial revolution due to rapid industrialization, mushrooming of cities, and greater dependence on fossil fuels in urban centers. Particulate matter (PM) is considered to be one of the main aerosol pollutants that causes a significant adverse impact on human health. Low-cost air quality sensors have attracted attention recently to curb the lack of air quality data which is essential in assessing the health impacts of air pollutants and evaluating land use policies. This is mainly due to their lower cost in comparison to the conventional methods. The aim of this study was to assess the spatial extent and distribution of ambient airborne particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) in Nairobi City County. Seven sites were selected for monitoring based on the land use type: high- and low-density residential, industrial, agricultural, commercial, road transport, and forest reserve areas. Calibrated low-cost sensors and cyclone samplers were used to monitor PM2.5 concentration levels and gravimetric measurements for elemental composition of PM2.5, respectively. The sensor percentage accuracy for calibration ranged from 81.47% to 98.60%. The highest 24-hour average concentration of PM2.5 was observed in Viwandani, an industrial area (111.87 μg/m³), and the lowest concentration at Karura (21.25 μg/m³), a forested area. The results showed a daily variation in PM2.5 concentration levels with the peaks occurring in the morning and the evening due to variation in anthropogenic activities and the depth of the atmospheric boundary layer. Therefore, the study suggests that residents in different selected land use sites are exposed to varying levels of PM2.5 pollution on a regular basis, hence increasing the potential of causing long-term health effects.


2019 ◽  
Vol 12 (10) ◽  
pp. 5431-5441 ◽  
Author(s):  
Eric A. Wendt ◽  
Casey W. Quinn ◽  
Daniel D. Miller-Lionberg ◽  
Jessica Tryner ◽  
Christian L'Orange ◽  
...  

Abstract. Globally, fine particulate matter (PM2.5) air pollution is a leading contributor to death, disease, and environmental degradation. Satellite-based measurements of aerosol optical depth (AOD) are used to estimate PM2.5 concentrations across the world, but the relationship between satellite-estimated AOD and ground-level PM2.5 is uncertain. Sun photometers measure AOD from the Earth's surface and are often used to improve satellite data; however, reference-grade photometers and PM2.5 monitors are expensive and rarely co-located. This work presents the development and validation of the aerosol mass and optical depth (AMOD) sampler, an inexpensive and compact device that simultaneously measures PM2.5 mass and AOD. The AMOD utilizes a low-cost light-scattering sensor in combination with a gravimetric filter measurement to quantify ground-level PM2.5. Aerosol optical depth is measured using optically filtered photodiodes at four discrete wavelengths. Field validation studies revealed agreement within 10 % for AOD values measured between co-located AMOD and AErosol RObotics NETwork (AERONET) monitors and for PM2.5 mass measured between co-located AMOD and EPA Federal Equivalent Method (FEM) monitors. These results demonstrate that the AMOD can quantify AOD and PM2.5 accurately at a fraction of the cost of existing reference monitors.


2020 ◽  
Author(s):  
Vivien Voss ◽  
K. Heinke Schlünzen ◽  
David Grawe

<p>Air pollution is an important topic within urban areas.  Limit values as given in the European Guidelines are introduced to reduce negative effects on humans and vegetation.  Exceedances of the limit values are to be assessed using measurements.  In case of found exceedances of the limit values, the local authorities need to act to reduce pollution levels. Highest values are found for several pollutants (NOx, NO2, particles) within densely build-up urban areas with traffic emissions being the major source and dispersion being very much impacted by the urban structures.  The quality assured measuring network used by the authorities is often too coarse to determine the heterogeneity in the concentration field. Low cost sample devices as employed in several citizen science projects might help to overcome the data sparsity. Volunteers measure the air quality at many sites, contribute to the measurement networks and provide the data on the web. However, the questions arising are: a) Are these data of sufficient high quality to provide results comparable to those of the quality assured networks? b) Is the network density sufficient to determine concentration patterns within the urban canopy layer? <br>One-year data from a citizen science network, which measures particulate matter (PM10, PM2.5) were compared to measurements provided by the local environmental agency, using two hot-spot areas in the city of Hamburg as an example. To determine how well the measurements agree with each other, a regression analyses was performed dependent on seasonal and diurnal cycles. Additionally, model simulations with the microscale obstacle resolving model MITRAS were performed for two characteristic building structures and different meteorological situations. The model results were used to determine local hot spots as well as areas where measurements might represent the concentration of particles for the urban quarter. The low cost sensor measurements show a general agreement to the city’s measurements, however, the values per sensor differ. Moreover, the measurements of the low-cost-sensor show an unrealistic dependence on relative humidity, resulting in over- or underestimations in certain cases. The model results clearly show that only a few sites allow measurements to be representative for a city quarter. The measurements of the citizen science project can provide a good overview about the tendencies of the air quality, but are currently not of sufficient quality to provide measurements calling for legal action.</p><p>The model results were used for the project AtMoDat. AtMoDat is an attempt to create a data standard for obstacle resolving models based on the existing Climate and Forecast (CF) conventions. A web-based survey is developed to get information on the requirements for the data standard. The next step is to extend the collection of model characteristics and eventually to provide a generic scheme.</p><p><strong>Acknowledgements</strong><br>This work contributes to project “AtMoDat” funded by the Federal Ministry of Education and Research under the funding number 16QK02C. Responsibility for the content of this publication lies with the authors.</p>


2018 ◽  
Author(s):  
Francis D. Pope ◽  
Michael Gatari ◽  
David Ng’ang’a ◽  
Alexander Poynter ◽  
Rhiannon Blake

Abstract. East African countries face an increasing threat from poor air quality, stemming from rapid urbanisation, population growth and a steep rise in fuel use and motorization rates. With few air quality monitoring systems available, this study provides the much needed high temporal resolution data to investigate the concentrations of particulate matter (PM) air pollution in Kenya. Calibrated low cost optical particle counters (OPCs) were deployed in Kenya in three locations: two in the capital of Nairobi and one in a rural location in the outskirts of Nanyuki, which is upwind of Nairobi. The two Nairobi sites consist of an urban background site and a roadside site. The instruments were composed of an Alphasense OPC-N2 optical particle counter (OPC) ran with a raspberry pi low cost microcomputer, packaged in a weather proof box. Measurements were conducted over a two-month period (February–March 2017) with an intensive study period when all measurements were active at all sites lasting two weeks. When collocated, the three OPC-N2 instruments demonstrated good inter-instrument precision with a coefficient of variance of 8.8 ± 2.0 % in the PM2.5 fraction. The low cost sensors had an absolute PM mass concentration calibration using a collocated gravimetric measurement at the urban background site in Nairobi. The mean daily PM1 mass concentration measured at the urban roadside, urban background and rural background sites were 23.9, 16.1, 8.8 µg m−3. The mean daily PM2.5 mass concentration measured at the urban roadside, urban background and rural background sites were 36.6, 24.8, 13.0 µg m−3. The mean daily PM10 mass concentration measured at the urban roadside, urban background and rural background sites were 93.7, 53.0, 19.5 µg m−3. The urban measurements in Nairobi showed that particulate matter concentrations regularly exceed WHO guidelines in both the PM10 and PM2.5 size ranges. Following a Lenschow type approach we can estimate the urban and roadside increments that are applicable to Nairobi. Median urban and roadside increments are 33.1 and 43.3 µg m−3 for PM10, respectively, the median urban and roadside increments are 7.1 and 18.3 µg m−3 for PM2.5, respectively, and the median urban and roadside increments are 4.7 and 12.6 µg m−3 for PM1, respectively. These increments highlight the importance of both the urban and roadside increments to urban air pollution in Nairobi. A clear diurnal behaviour in PM mass concentration was observed at both urban sites, which peaks during the morning and evening Nairobi rush hours; this was consistent with the high measured roadside increment indicating vehicular traffic being a dominant source of particulate matter in the city, accounting for approximately 48.1, 47.5, and 57.2 % of the total particulate matter loading in the PM10, PM2.5 and PM1 size ranges, respectively. Collocated meteorological measurements at the urban sites were collected, allowing for an understanding of the location of major sources of particulate matter at the two sites. The potential problems of using low cost sensors for PM measurement without gravimetric calibration available at all sites are discussed. This study shows that calibrated low cost sensors can be used successfully to measure air pollution in cities like Nairobi. It demonstrates that low cost sensors could be used to create an affordable and reliable network to monitor air quality in cities.


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