Enhancing the Reliability of NO2 Monitoring Using Low-Cost Sensors by Compensating for Temperature and Humidity Effects DOI Creative Commons
Daniellys Alejo Sánchez, Olivier Schalm, Arianna Álvarez Cruz

et al.

Atmosphere, Journal Year: 2024, Volume and Issue: 15(11), P. 1365 - 1365

Published: Nov. 13, 2024

The study investigates methods to enhance the reliability of NO2 monitoring using low-cost electrochemical sensors measure gaseous pollutants in air by addressing impacts temperature and relative humidity. within a plastic container was controlled an internal mica heater, external hot blower, or cooling packs, while humidity adjusted glycerine solutions. Findings indicated that auxiliary electrode signal is susceptible moderately affected In contrast, working less humidity; however, adjustments are still required determine gas concentrations accurately. Tests involving on/off cycles showed experiences exponential decay before stabilizing, requiring exclusion initial readings during activities. Additionally, calibration experiments zero allowed determination compensation factor nT across different temperatures levels. These results highlight importance compensating for effects improve accuracy measurements sensors. This refinement makes applicable broader range environmental conditions. However, also show lack repeatability calibration.

Language: Английский

Evaluation of In-Situ Low-Cost Sensor Network in a Tropical Valley, Colombia DOI Creative Commons
L. González, Elena Montilla-Rosero

Sensors, Journal Year: 2025, Volume and Issue: 25(4), P. 1236 - 1236

Published: Feb. 18, 2025

The increase in yearly particulate matter concentrations has been a constant issue since 2017 the Aburrá Valley, located Antioquia, Colombia. Although local certified air quality monitors provide high accuracy, they are limited spatial coverage, limiting chemical transport and pollution dynamic studies this mountainous environment. In work, local, Low-Cost Sensor network is proposed as an alternative installed around valley representative locations heights. To calibrate PM2.5 O3 sensors used by network, temporal delays were analyzed with Dynamic Time Warping linear scale was corrected Single Linear Regression model. As result, correlation coefficient R2 of sensor reached values 0.8 0.9 after calibration. For all stations, rescaled data agrees official historical reports on behavior pollutant meteorological variables. ability to compare results confirms success calibration/validation method employed contributes growing field low-cost Latin America.

Language: Английский

Citations

2
An overview of outdoor low-cost gas-phase air quality sensor deployments: current efforts, trends, and limitations DOI Creative Commons
Kristen Okorn, Laura T. Iraci

Atmospheric measurement techniques, Journal Year: 2024, Volume and Issue: 17(21), P. 6425 - 6457

Published: Nov. 8, 2024

Abstract. We reviewed 60 sensor networks and 17 related efforts (sensor review papers data accessibility projects) to better understand the landscape of stationary low-cost gas-phase deployed in outdoor environments worldwide. This study is not exhaustive every network on globe but rather exists categorize types by their key characteristics explore general trends. also exposes gaps monitoring date, especially regarding availability measurements compared particulate matter (PM) geographic coverage (the Global South, rural areas). ground-based that measure air pollutants into two main subsets based deployment type – quasi-permanent (long term) campaign (short medium commonplace practices, strengths, weaknesses networks. conclude with a summary cross-network unification quality control efforts. work aims help scientists looking build best practices common pathways aid end users finding datasets meet needs.

Language: Английский

Citations

6
Potential of low-cost PM monitoring sensors to fill monitoring gaps in areas of Sub-Saharan Africa DOI Creative Commons
Giovanni Gualtieri,

Khaoula Ahbil,

Lorenzo Brilli

et al.

Atmospheric Pollution Research, Journal Year: 2024, Volume and Issue: 15(7), P. 102158 - 102158

Published: April 27, 2024

Recent advances in low-cost (LC) sensor technology fostered their deployment low-income and undersampled countries such as Sub-Saharan Africa (SSA) regions, affected by the highest particulate matter (PM) concentrations population exposure. The present study is first addressed Niamey, Niger, focuses on assessing LC data global reanalysis products. Three PM2.5 PM10 monitoring stations were deployed successfully operated across ∼8 months at different (urban, suburban rural) locations. Observed revealed consistent patterns, higher during dry Harmattan season, while appreciably lower humid monsoon season. In mean (6.1–20.1 μg/m3) similar to those observed over higher-income countries, confirming hypothesis of strictly depending urbanisation, thus anthropogenic activities. Conversely, (55.3–142.8 remarkably than most measured elsewhere worldwide, predominantly constituted (81–89%) coarse fraction. origin, inferred backtrajectory analysis, was mainly natural (Saharan dust) both Low-resolution gridded estimations Copernicus Atmosphere Monitoring Service (CAMS) not capable adequately resolving spatial variability observations further highlighting importance network improve air quality knowledge. To tackle harmful effects Saharan dust population, create robust datasets integrated with products this challenging region, effort should be put toward creation trans-national networks based sensors SSA.

Language: Английский

Citations

5
Performance Assessment of Two Low-Cost PM2.5 and PM10 Monitoring Networks in the Padana Plain (Italy) DOI Creative Commons
Giovanni Gualtieri, Lorenzo Brilli, Federico Carotenuto

et al.

Sensors, Journal Year: 2024, Volume and Issue: 24(12), P. 3946 - 3946

Published: June 18, 2024

Two low-cost (LC) monitoring networks, PurpleAir (instrumented by Plantower PMS5003 sensors) and AirQino (Novasense SDS011), were assessed in PM2.5 PM10 daily concentrations the Padana Plain (Northern Italy). A total of 19 LC stations for 20 compared vs. regulatory-grade during a full “heating season” (15 October 2022–15 April 2023). Both sensor networks showed higher accuracy fitting magnitude than reference observations, while lower was shown terms RMSE, MAE R2. under-estimated both (MB = −4.8 −2.9 μg/m3, respectively), over-estimated +5.4 μg/m3) slightly −0.4 μg/m3). finer at capturing time variation (R2 0.68–0.75 0.59–0.61). sensors from failed to capture dynamics PM2.5/PM10 ratio, confirming their well-known issues correctly discriminating size individual particles. These findings suggest need further efforts implementation mass conversion algorithms within units improve tuning outputs.

Language: Английский

Citations

5
Data Evaluation of a Low-Cost Sensor Network for Atmospheric Particulate Matter Monitoring in 15 Municipalities in Serbia DOI Creative Commons
Danka B. Stojanović, Duška Kleut, M. Davidović

et al.

Sensors, Journal Year: 2024, Volume and Issue: 24(13), P. 4052 - 4052

Published: June 21, 2024

Conventional air quality monitoring networks typically tend to be sparse over areas of interest. Because the high cost establishing such systems, some are often completely left out regulatory networks. Recently, a new paradigm in has emerged that utilizes low-cost pollution sensors, thus making it possible reduce knowledge gap levels for not covered by and increase spatial resolution others. The benefits community almost self-evident since information about level can transmitted real time data analysed immediately wider area. However, accuracy reliability newly produced must also taken into account order able correctly interpret results. In this study, we analyse particulate matter from large network monitors was deployed placed outdoor spaces schools central western Serbia under Schools Better Air Quality UNICEF pilot initiative period April 2022 June 2023. consisted 129 devices 15 municipalities, with 11 municipalities having extensive real-time measurements concentration first time. analysis showed maximum concentrations PM2.5 PM10 were winter months (heating season), while during summer (non-heating several times lower. Also, values number daily exceedances (50 μg/m3) much higher than others because diversity differences sensor sampling sites. mass obtained sensors classified according European AQI (air index) applied data. This study confirmed useful providing warnings days episodes, particularly situations where there is lack local or national stations

Language: Английский

Citations

5
Cutting-Edge Approaches in Coastal Air Quality Assessment and Warming Modeling DOI
Naglaa Zanaty, Elham M. Ali, Islam Abou El-Magd

et al.

Springer remote sensing/photogrammetry, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 32

Published: Jan. 1, 2025

Language: Английский

Citations

0
Air Pollution Monitoring Using Cost-Effective Devices Enhanced by Machine Learning DOI Creative Commons

Yanis Colléaux,

Cédric Willaume,

Bijan Mohandes

et al.

Sensors, Journal Year: 2025, Volume and Issue: 25(5), P. 1423 - 1423

Published: Feb. 26, 2025

Given the significant impact of air pollution on global health, continuous and precise monitoring quality in all populated environments is crucial. Unfortunately, even most developed economies, current networks are largely inadequate. The high cost stations has been identified as a key barrier to widespread coverage, making cost-effective devices potential game changer. However, accuracy measurements obtained from low-cost sensors affected by many factors, including gas cross-sensitivity, environmental conditions, production inconsistencies. Fortunately, machine learning models can capture complex interdependent relationships sensor responses thus enhance their readings accuracy. After gathering placed alongside reference station, data were used train such models. Assessments performance showed that tailored individual units greatly improved measurement accuracy, boosting correlation with reference-grade instruments up 10%. Nonetheless, this research also revealed inconsistencies similar prevent creation unified correction model for given type.

Language: Английский

Citations

0
Predictive machine learning and geospatial modeling reveal PM10 hotspots and guide targeted air pollution interventions in Addis Ababa, Ethiopia DOI Creative Commons
Kalid Hassen Yasin, Muhammad Yasin, Anteneh Derribew Iguala

et al.

Deleted Journal, Journal Year: 2025, Volume and Issue: 7(4)

Published: March 26, 2025

Language: Английский

Citations

0
A scalable framework for harmonizing, standardization, and correcting crowd-sourced low-cost sensor PM2.5 data across Europe DOI Creative Commons
Amirhossein Hassani, Vasileios Salamalikis, Philipp Schneider

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 380, P. 125100 - 125100

Published: March 31, 2025

Language: Английский

Citations

0
Assessment of risk components for urban population to heat intensity and air pollution through a dense IoT sensor network DOI Creative Commons

Tommaso Giordano,

Lorenzo Brilli, Giovanni Gualtieri

et al.

Urban Climate, Journal Year: 2025, Volume and Issue: 61, P. 102397 - 102397

Published: April 7, 2025

Language: Английский

Citations

0