Application of Low-Cost Air Quality Monitoring Sensor to Assess the Exposure of Ambient Air Pollution Due to PM2.5 and PM10

<div>Air pollution is a severe problem growing over time. A dense air-quality monitoring network is needed to update the people regarding the air pollution status in cities. A low-cost sensor device (LCSD) based dense air-quality monitoring network is more viable than continuous ambient air quality monitoring stations (CAAQMS). An in-field calibration approach is needed to improve agreements of the LCSDs to CAAQMS. The present work aims to propose a calibration method for PM2.5 using domain adaptation technique to reduce the collocation duration of LCSDs and CAAQMS. A novel calibration approach is proposed in this work for the measured PM2.5 levels of LCSDs. The dataset used for the experimentation consists of PM2.5 values and other parameters (PM10, temperature, and humidity) at hourly duration over a period of three months data. We propose new features, by combining PM2.5, PM10, temperature, and humidity, that significantly improved the performance of calibration. Further, the calibration model is adapted to the target location for a new LCSD with a collocation time of two days. The proposed model shows high correlation coefficient values (R2) and significantly low mean absolute percentage error (MAPE) than that of other baseline models. Thus, the proposed model helps in reducing the collocation time while maintaining high calibration performance.</div>

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An assessment of ambient air quality using AQI and exceedance factor for Udaipur City, Rajasthan (India)

WEENTECH Proceedings in Energy ◽

10.32438/wpe.102021 ◽

2021 ◽

pp. 94-106

Author(s):

Porush Kumar ◽

Kuldeep ◽

Nilima Gautam

Keyword(s):

Air Pollution ◽

Air Quality ◽

Pollution Control ◽

Urban Air Pollution ◽

Ambient Air ◽

Quality Monitoring ◽

Urban Air ◽

Air Quality Monitoring ◽

Ambient Air Quality ◽

Control Board

Air pollution is a severe issue of concern worldwide due to its most significant environmental risk to human health today. All substances that appear in excessive amounts in the environment, such as PM10, NO2, or SO2, may be associated with severe health problems. Anthropogenic sources of these pollutants are mainly responsible for the deterioration of urban air quality. These sources include stationary point sources, mobile sources, waste disposal landfills, open burning, and similar others. Due to these pollutants, people are at increased risk of various serious diseases like breathing problems and heart disease, and the death rate due to these diseases can also increase. Hence, air quality monitoring is essential in urban areas to control and regulate the emission of these pollutants to reduce the health impacts on human beings. Udaipur has been selected for the assessment of air quality with monitored air quality data. Air quality monitoring stations in Udaipur city are operated by the CPCB (Central Pollution Control Board) and RSPCB (Rajasthan State Pollution Control Board). The purpose of this study is to characterize the level of urban air pollution through the measurement of PM10, NO2, or SO2 in Udaipur city, Rajasthan (India). Four sampling locations were selected for Udaipur city to assess the effect of urban air pollution and ambient air quality, and it was monitored for a year from 1st January 2019 to 31st December 2019. The air quality index has been calculated with measured values of PM10, NO2, and SO2. The concentration of PM10 is at a critical level of pollution and primarily responsible for bad air quality and high air quality Index in Udaipur city.

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Measuring Air Quality for Advocacy in Africa (MA3): Feasibility and Practicality of Longitudinal Ambient PM2.5 Measurement Using Low-Cost Sensors

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17197243 ◽

2020 ◽

Vol 17 (19) ◽

pp. 7243

Author(s):

Babatunde I. Awokola ◽

Gabriel Okello ◽

Kevin J. Mortimer ◽

Christopher P. Jewell ◽

Annette Erhart ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Recovery Rate ◽

Low Cost ◽

Public Health Problem ◽

Ambient Air ◽

Data Recovery ◽

Sub Saharan Africa ◽

Ambient Air Pollution ◽

Important Public Health Problem

Ambient air pollution in urban cities in sub-Saharan Africa (SSA) is an important public health problem with models and limited monitoring data indicating high concentrations of pollutants such as fine particulate matter (PM2.5). On most global air quality index maps, however, information about ambient pollution from SSA is scarce. We evaluated the feasibility and practicality of longitudinal measurements of ambient PM2.5 using low-cost air quality sensors (Purple Air-II-SD) across thirteen locations in seven countries in SSA. Devices were used to gather data over a 30-day period with the aim of assessing the efficiency of its data recovery rate and identifying challenges experienced by users in each location. The median data recovery rate was 94% (range: 72% to 100%). The mean 24 h concentration measured across all sites was 38 µg/m3 with the highest PM2.5 period average concentration of 91 µg/m3 measured in Kampala, Uganda and lowest concentrations of 15 µg/m3 measured in Faraja, The Gambia. Kampala in Uganda and Nnewi in Nigeria recorded the longest periods with concentrations >250 µg/m3. Power outages, SD memory card issues, internet connectivity problems and device safety concerns were important challenges experienced when using Purple Air-II-SD sensors. Despite some operational challenges, this study demonstrated that it is reasonably practicable and feasible to establish a network of low-cost devices to provide data on local PM2.5 concentrations in SSA countries. Such data are crucially needed to raise public, societal and policymaker awareness about air pollution across SSA.

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ASSESSMENT OF SENTINEL-5P PERFORMANCE FOR GROUND-LEVEL AIR QUALITY MONITORING: PREPARATORY EXPERIMENTS OVER THE COVID-19 LOCKDOWN PERIOD

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliv-3-w1-2020-111-2020 ◽

2020 ◽

Vol XLIV-3/W1-2020 ◽

pp. 111-116

Author(s):

D. Oxoli ◽

J. R. Cedeno Jimenez ◽

M. A. Brovelli

Keyword(s):

Air Pollution ◽

Air Quality ◽

Nitrogen Dioxide ◽

Prediction Models ◽

Ambient Air ◽

Data Availability ◽

Quality Monitoring ◽

Strong Positive Correlation ◽

Air Quality Monitoring ◽

Lombardy Region

Abstract. Scientific evidence has demonstrated that deterioration of ambient air quality has increased the number of deaths worldwide by appointing air pollution among the most pressing sustainability concerns. In this context, the continuous monitoring of air quality and the modelling of complex air pollution patterns is critical to protect population and ecosystems health. Availability of air quality observations has terrifically improved in the last decades allowing – nowadays – for extensive spatial and temporal resolved analysis at both global and local scale. Satellite remote sensing is mostly accountable for this data availability and is promising to foster air quality monitoring in support of traditional ground sensors measurements. In view of the above, this study compares observations from the Sentinel-5P mission of the European Copernicus Programme (the most recent Earth Observation platform providing open measurements of atmospheric constituents) with traditional ground measurements to investigate their space and time correlations across the Lombardy region (Northern Italy). The correlation analysis focused on nitrogen dioxide. The use of data collected during the COVID-19 pandemic allowed for a parallel exploration of the lockdown effects on nitrogen dioxide emissions. Results show a marked decrease in nitrogen dioxide concentrations during the lockdown and an overall strong positive correlation between satellite and ground sensors observations. These experiments are preparatory for future activities that will focus on the development of satellite-based air quality local prediction models, aiming at improving the granularity of the ground-based information available for air quality monitoring and exposure modelling.

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MOPGA/Improving Air Quality in West Africa: Low-cost sensors as a solution to improve the understanding of spatial and temporal variability in urban air pollution

10.5194/egusphere-egu21-8210 ◽

2021 ◽

Author(s):

Julien Bahino ◽

Michael Giordano ◽

Véronique Yoboué ◽

Arsène Ochou ◽

Corinne Galy-Lacaux ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

West Africa ◽

Low Cost ◽

West African ◽

Passive Samplers ◽

Quality Monitoring ◽

Spatial And Temporal Variability ◽

Air Quality Monitoring ◽

Calibration Models

This study was carried out within the framework of the Improving Air Quality in West Africa&#160;(IAQWA) project funded by the Make Our Planet Great Again (MOPGA) program. In recent years, West African countries have experienced an economic upturn driven by GDP growth of nearly 3.7% in 2019 (AfDB, 2020). This economic boom is mainly felt in the cities where it promotes the construction of highway infrastructure, real estate development, and industry. All these activities are sources of air pollution. Unfortunately, there is almost no air quality monitoring in these cities partly due to the high cost of monitoring instruments. Low-cost air quality monitoring instruments can help improve the spatial and temporal resolution of measurements at relatively lower cost. However, the installation of these instruments in West African environments characterized by high relative humidity requires their calibration through collocation with reference instruments. The IAQWA project aims to improve our understanding of air pollutants such as fine particulate matter mass (PM2.5), ozone (O3), nitrogen oxides (NOx), sulfur dioxide (SO2), and carbon monoxide (CO) in Abidjan and Accra, two major West African capitals, through the deployment of Real-time Affordable Multi-Pollutant (RAMP) monitors.Since February 2020, five RAMPs have been installed and are operating continuously at various sites&#160;in Abidjan and Lamto in Cote d'Ivoire, and four RAMPs have been operating in Accra, Ghana. Some of the RAMPs have been collocated with PM and/or NOx reference instruments. At other sites the RAMPs have been collocated with INDAAF passive samplers and passive aerosol collectors. These collocations have allowed for the development of calibration models for these low-cost sensors. The performance of these calibration models is presented here along with the diurnal and seasonal variations of air pollution at the different sites in Abidjan and Accra. These results will eventually be used to improve our understanding of the drivers of air pollution in these major West African cities, which is essential to choosing sustainable development pathways in the future.

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The applicability of low-cost PM10 sensors for atmospheric air quality monitoring

SHS Web of Conferences ◽

10.1051/shsconf/20185702013 ◽

2018 ◽

Vol 57 ◽

pp. 02013

Author(s):

Bartosz Szulczyński ◽

Jacek Gębicki

Keyword(s):

Air Quality ◽

Measurement Uncertainty ◽

Low Cost ◽

Ambient Air ◽

Quality Monitoring ◽

Air Quality Monitoring ◽

Monitoring Methods ◽

Atmospheric Air ◽

Reference Methods ◽

The Impact

Described in this work are the results of field tests carried out in the Tricity Agglomeration between 01 April 2018 and 30 June 2018 in order to evaluate the usefulness of low-cost PM10 sensors in atmospheric air quality monitoring. The results were juxtaposed with the results obtained using reference methods. The results were validated based on the measurement uncertainty as described in the EU report "Demonstration of Equivalence of Ambient Air Monitoring Methods. EC Working Group on Guidance for the Demonstration of Equivalence". Moreover, the impact of external factors (humidity, pressure, temperature) on the obtained results was also assessed. It was shown that the low-cost sensors display measurement uncertainty which exceeds the acceptable values as compared to the reference methods and correction factors depending on the measured PM10 concentration need to be introduced in order to fulfil the criteria of equivalence.

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Methodological Approaches to Optimizing Ambient Air Quality Monitoring Programs within the Framework of the Federal Clean Air Project (on the example of Nizhny Tagil)

ЗДОРОВЬЕ НАСЕЛЕНИЯ И СРЕДА ОБИТАНИЯ - ЗНиСО / PUBLIC HEALTH AND LIFE ENVIRONMENT ◽

10.35627/2219-5238/2020-330-9-38-47 ◽

2020 ◽

pp. 38-47

Author(s):

VB Gurvich ◽

DN Kozlovskikh ◽

IA Vlasov ◽

IV Chistyakova ◽

SV Yarushin ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Health Risks ◽

Monitoring Program ◽

Ambient Air ◽

Quality Monitoring ◽

Air Quality Monitoring ◽

Ambient Air Quality ◽

Clean Air ◽

Methodological Approaches

ntroduction: One of the key socially significant results of implementing the Federal Clean Air Project is the maximum possible mitigation of inhalation health risks by achieving the target rate of reducing emissions (by 20 % against the level of 2017) in a number of cities included in the federal project as priority areas. Materials and methods: Ambient air pollution monitoring as a measure of this accomplishment is indispensable both for verification of applying the model to estimating surface concentrations of pollutants, assessing health risks, and evaluating changes in ambient air quality. For the objectivity of such assessments, it is fundamental to determine the list of priority health-threatening air pollutants, to select monitoring sites that best characterize population exposure to these chemicals, and to plan air quality monitoring programs setting sampling frequency and volume. Results: The article presents the results of implementing methodological approaches adopted by the Russian Federal Service for Surveillance in the Sphere of Consumer Rights and Human Wellbeing (Rospotrebnadzor) to optimize ambient air quality monitoring within the framework of solving the tasks of the Federal Clean Air Project in the city of Nizhny Tagil, Sverdlovsk Region, in 2019. The Nizhny Tagil air quality monitoring program for 2020 has been developed and tested. This program, in conjunction with similar programs carried out by the Russian Federal Hydrometeorology and Environmental Monitoring Service (Roshydromet) and the Ministry of Natural Resources and Environment of the Sverdlovsk Region and taking into account their implementation over the past five years, helps provide implementers of the federal project with air pollution data to address its key challenges. Conclusions: The adopted ambient air quality monitoring program implemented in Nizhny Tagil in 2020 by the Center for Hygiene and Epidemiology in the Sverdlovsk Region meets terms and requirements of the Federal Clean Air Project.

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MOPGA/Make Air Quality Great Again: Filling in the air quality data gap in Africa using lower-cost RAMP monitors

10.5194/egusphere-egu2020-10942 ◽

2020 ◽

Author(s):

Ramachandran Subramanian ◽

Matthias Beekmann ◽

Carl Malings ◽

Anais Feron ◽

Paola Formenti ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Electrochemical Sensors ◽

Low Cost ◽

Fine Particulate Matter ◽

Ambient Air ◽

Ambient Air Pollution ◽

Quality Data ◽

Rural Site ◽

Data Gap

Ambient air pollution is a leading cause of premature mortality across the world, with an estimated 258,000 deaths in Africa (UNICEF/GBD 2017). These estimated impacts have large uncertainties as many major cities in Africa do not have any ground-based air quality monitoring. The lack of data is due in part to the high cost of traditional monitoring equipment and the lack of trained personnel. As part of the &#8220;Make Air Quality Great Again&#8221; project under the &#8220;Make Our Planet Great Again&#8221; framework (MOPGA), we propose filling this data gap with low-cost sensors carefully calibrated against reference monitors.Fifteen real-time affordable multi-pollutant (RAMP) monitors have been deployed in Abidjan, C&#244;te d'Ivoire; Accra, Ghana; Kigali, Rwanda; Nairobi, Kenya; Niamey, Niger; and Zamdela, South Africa (near Johannesburg). The RAMPs use Plantower optical nephelometers to measure fine particulate matter mass (PM2.5) and four Alphasense electrochemical sensors to detect pollutant gases including nitrogen dioxide (NO2) and ozone (O3).Using a calibration developed in Cr&#233;teil, France, the deployments thus far reveal morning and evening spikes in combustion-related air pollution. The median hourly NO2 in Accra and Nairobi for September-October 2019 was about 11 ppb; a similar value was observed across November-December 2019 in Zamdela. However, a previous long-term deployment of the RAMPs in Rwanda showed that, for robust data quality, low-cost sensors must be collocated with traditional reference monitors to develop localized calibration models. Hence, we acquired regulatory-grade PM2.5, NO2, and O3 monitors for Abidjan and Accra. We also collocated RAMPs with existing reference monitors in Zamdela, Kigali, Abidjan, and Lamto (a rural site in C&#244;te d'Ivoire). In this talk, we will present results on spatio-temporal variability of collocation-based sensor calibrations across these different cities, source identification, and challenges and plans for future expansion.

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Low Cost, Multi-Pollutant Sensing System Using Raspberry Pi for Indoor Air Quality Monitoring

Sustainability ◽

10.3390/su13010370 ◽

2021 ◽

Vol 13 (1) ◽

pp. 370

Author(s):

He Zhang ◽

Ravi Srinivasan ◽

Vikram Ganesan

Keyword(s):

Air Quality ◽

Indoor Air Quality ◽

Indoor Air ◽

Low Cost ◽

Office Building ◽

Quality Monitoring ◽

Raspberry Pi ◽

Air Quality Monitoring ◽

Residential Unit ◽

Pm2.5 And Pm10

Deteriorating levels of indoor air quality is a prominent environmental issue that results in long-lasting harmful effects on human health and wellbeing. A concurrent multi-parameter monitoring approach accounting for most crucial indoor pollutants is critical and essential. The challenges faced by existing conventional equipment in measuring multiple real-time pollutant concentrations include high cost, limited deployability, and detectability of only select pollutants. The aim of this paper is to present a comprehensive indoor air quality monitoring system using a low-cost Raspberry Pi-based air quality sensor module. The custom-built system measures 10 indoor environmental conditions including pollutants: temperature, relative humidity, Particulate Matter (PM)2.5, PM10, Nitrogen dioxide (NO2), Sulfur dioxide (SO2), Carbon monoxide (CO), Ozone (O3), Carbon dioxide (CO2), and Total Volatile Organic Compounds (TVOCs). A residential unit and an educational office building was selected and monitored over a span of seven days. The recorded mean PM2.5, and PM10 concentrations were significantly higher in the residential unit compared to the office building. The mean NO2, SO2, and TVOC concentrations were comparatively similar for both locations. Spearman rank-order analysis displayed a strong correlation between particulate matter and SO2 for both residential unit and the office building while the latter depicted strong temperature and humidity correlation with O3, SO2, PM2.5, and PM10 when compared to the former.

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Measuring Air Quality for Advocacy in Africa (MA3): Feasibility and Practicality of Longitudinal Ambient PM2.5 Measurement Using Low-Cost Sensors

10.20944/preprints202009.0613.v1 ◽

2020 ◽

Author(s):

Babatunde I. Awokola ◽

Gabriel Okello ◽

Kevin J. Mortimer ◽

Christopher P. Jewell ◽

Annette Erhart ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Recovery Rate ◽

Low Cost ◽

Public Health Problem ◽

Ambient Air ◽

Data Recovery ◽

Sub Saharan Africa ◽

Ambient Air Pollution ◽

Important Public Health Problem

Urban cities in sub-Saharan Africa (SSA) are faced with ambient air pollution. This is an important public health problem with models and limited monitoring data indicating high concentrations of pollutants such as fine particulate matter (PM2.5). Going through most global air quality index maps, however, information about ambient pollution from SSA is scarce. We evaluated the feasibility and practicality of longitudinal measurements of ambient PM2.5 using low-cost air quality sensors (Purple Air-II-SD) across thirteen locations in seven countries in SSA. Devices were used to gather data over a 30-day period with the aim of assessing the efficiency of its data recovery rate and identifying challenges experienced by users in each location. The median data recovery rate was 94% (range: 72% to 100%). The mean 24-hour concentration measured across all sites was 38 µg/m3 with the highest PM2.5 period average concentration of 91 µg/m3 measured in Kampala, Uganda and lowest concentrations of 15 µg/m3 measured in Faraja, The Gambia. Kampala-Uganda and Nnewi-Nigeria recorded the longest periods with concentrations>250µg/m3. Power outages, SD memory card issues, internet connectivity problems and device safety concerns were important challenges experienced when using Purple Air-II-SD sensors. Despite some operational challenges, this study demonstrated that it is reasonably practicable and feasible to establish a network of low-cost devices to provide data on local PM2.5 concentrations in SSA countries. Such data are crucially needed to raise public-, societal and policymaker awareness about air pollution across SSA.

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