Monitoring and analysis of carbon monoxide and methane using Sensors and Remotely Piloted Aircraft Systems


  • Luis Alberto Holgado-Apaza Amazon National University of Madre de Dios image/svg+xml
  • Edgar Julian-Laime Amazon National University of Madre de Dios image/svg+xml
  • Justo Bautista Baca Amazon National University of Madre de Dios image/svg+xml
  • Ralph Miranda Castillo Amazon National University of Madre de Dios image/svg+xml
  • Jaime Cesar Prieto-Luna Amazon National University of Madre de Dios image/svg+xml
  • Pedro Córdova-Mendoza Saint Aloysius Gonzaga National University image/svg+xml
  • Norberto Sixto Miranda Zea Universidad Nacional del Altiplano image/svg+xml
  • Miguel Valles-Coral Universidad Nacional de San Martín



arduino, atmospheric pollution, drone, air monitoring, RPAS


INTRODUCTION: Air pollution in urban areas becomes a severe challenge to global health; exposure to polluting gases can lead to different diseases and even human mortality. In this sense, monitoring the concentration of polluting gases such as carbon monoxide and methane is important.

OBJECTIVES: This document focuses on developing a Remotely Piloted Aircraft System (RPAS) to monitor the concentration of carbon monoxide and methane at different altitudes.

METHODS: This includes a Parrot AR Drone 2.0, where the measurement prototype was mounted. The data was transmitted and reception at a ground control station through an application programmed in LabVIEW 15.0.

RESULTS: The experimental measurements showed that the concentration of carbon monoxide remains almost unchanged regardless of variations in altitude. In contrast, methane concentration reduces linearly with the increase in height with respect to ground level in Puerto Maldonado.

CONCLUSION: We implemented an RPAS to monitor in real time, record data in a control station and analyze the concentration of carbon monoxide and methane in the South Eastern Peruvian Amazon.


Download data is not yet available.


T. Hu and R. Yoshie, “Effect of atmospheric stability on air pollutant concentration and its generalization for real and idealized urban block models based on field observation data and wind tunnel experiments,” J. Wind Eng. Ind. Aerodyn., vol. 207, p. 104380, Dec. 2020, doi: 10.1016/J.JWEIA.2020.104380. DOI:

V. Tabunschik, R. Gorbunov, and T. Gorbunova, “Unveiling Air Pollution in Crimean Mountain Rivers: Analysis of Sentinel-5 Satellite Images Using Google Earth Engine (GEE),” Remote Sens. 2023, Vol. 15, Page 3364, vol. 15, no. 13, p. 3364, Jun. 2023, doi: 10.3390/RS15133364. DOI:

Á. Leelőssy, F. Molnár, F. Izsák, Á. Havasi, I. Lagzi, and R. Mészáros, “Dispersion modeling of air pollutants in the atmosphere: a review,” Cent. Eur. J. Geosci., vol. 6, no. 3, pp. 257–278, Sep. 2014, doi: 10.2478/S13533-012-0188-6/XML. DOI:

R. Kastratović, “Impact of foreign direct investment on greenhouse gas emissions in agriculture of developing countries,” Aust. J. Agric. Resour. Econ., vol. 63, no. 3, pp. 620–642, Jul. 2019, doi: 10.1111/1467-8489.12309. DOI:

A. K. Patra, S. Gautam, and P. Kumar, “Emissions and human health impact of particulate matter from surface mining operation—A review,” Environ. Technol. Innov., vol. 5, pp. 233–249, Apr. 2016, doi: 10.1016/J.ETI.2016.04.002. DOI:

A. A. Almetwally, M. Bin-Jumah, and A. A. Allam, “Ambient air pollution and its influence on human health and welfare: an overview,” Environ. Sci. Pollut. Res. 2020 2720, vol. 27, no. 20, pp. 24815–24830, May 2020, doi: 10.1007/S11356-020-09042-2. DOI:

T. Supasri, S. H. Gheewala, R. Macatangay, A. Chakpor, and S. Sedpho, “Association between ambient air particulate matter and human health impacts in northern Thailand,” Sci. Reports 2023 131, vol. 13, no. 1, pp. 1–15, Aug. 2023, doi: 10.1038/s41598-023-39930-9. DOI:

PAHO, “Calidad del aire - OPS/OMS | Organización Panamericana de la Salud,” 2023. (accessed Aug. 23, 2023).

S. Gautam et al., “Vertical profiling of atmospheric air pollutants in rural India: A case study on particulate matter (PM10/PM2.5/PM1), carbon dioxide, and formaldehyde,” Measurement, vol. 185, p. 110061, Nov. 2021, doi: 10.1016/J.MEASUREMENT.2021.110061. DOI:

V. Yavuz, “An analysis of atmospheric stability indices and parameters under air pollution conditions,” Environ. Monit. Assess. 2023 1958, vol. 195, no. 8, pp. 1–16, Jul. 2023, doi: 10.1007/S10661-023-11556-4. DOI:

N. T. Vechi and C. Scheutz, “Measurements of methane emissions from manure tanks, using a stationary tracer gas dispersion method,” Biosyst. Eng., vol. 233, pp. 21–34, Sep. 2023, doi: 10.1016/J.BIOSYSTEMSENG.2023.07.007. DOI:

X. Zhang et al., “Where to place methane monitoring sites in China to better assist carbon management,” npj Clim. Atmos. Sci., vol. 6, no. 1, Dec. 2023, doi: 10.1038/S41612-023-00359-6. DOI:

P. L. Smedley et al., “Monitoring of methane in groundwater from the Vale of Pickering, UK: Temporal variability and source discrimination,” Chem. Geol., vol. 636, Oct. 2023, doi: 10.1016/J.CHEMGEO.2023.121640. DOI:

S. Zhang, J. Ma, X. Zhang, and C. Guo, “Atmospheric remote sensing for anthropogenic methane emissions: Applications and research opportunities,” Sci. Total Environ., vol. 893, Oct. 2023, doi: 10.1016/J.SCITOTENV.2023.164701. DOI:

S. Dehghani, M. Vali, A. Jafarian, V. Oskoei, Z. Maleki, and M. Hoseini, “Ecological study of ambient air pollution exposure and mortality of cardiovascular diseases in elderly,” Sci. Reports 2022 121, vol. 12, no. 1, pp. 1–14, Dec. 2022, doi: 10.1038/s41598-022-24653-0. DOI:

R. Beelen et al., “Effects of long-term exposure to air pollution on natural-cause mortality: an analysis of 22 European cohorts within the multicentre ESCAPE project,” Lancet, vol. 383, no. 9919, pp. 785–795, Mar. 2014, doi: 10.1016/S0140-6736(13)62158-3. DOI:

D. Vienneau et al., “Association between exposure to multiple air pollutants, transportation noise and cause-specific mortality in adults in Switzerland,” Environ. Heal. A Glob. Access Sci. Source, vol. 22, no. 1, Dec. 2023, doi: 10.1186/S12940-023-00983-Y. DOI:

C. Martel and L. Cairampoma, “Cuantificación del carbono almacenado en formaciones vegetales amazónicas en ‘CICRA’, Madre de Dios (Perú),” Ecol. Apl., vol. 11, no. 2, pp. 59–65, 2012, Accessed: Oct. 29, 2023. [Online]. Available: DOI:

G. A. Aguirre et al., “Valor de conservación de un bosque en el sureste de la Amazonia Peruana: El caso de Madre de Dios,” Ecosistemas, vol. 29, no. 3, pp. 1947–1947, Nov. 2020, doi: 10.7818/ECOS.1947. DOI:

J. M. Barron-Adame et al., “Environmental Variables and their Relation with the SARS-COV-2 Transmission: A Data Mining Approach,” Vol. 26, Issue 1, Pages 399 - 409, vol. 26, no. 1, pp. 399–409, 2022, doi: 10.13053/CyS-26-1-4011. DOI:

J. Postigo and K. Young, “Naturaleza Y Sociedad: Perspectivas socio-ecológicas sobre cambios globales en América Latina,” Nat. y Soc. Perspect. socio-ecológicas sobre cambios Glob. en América Lat. Lima desco, IEP e INTE-PUCP., pp. 1–444, 2016.

P. Bieber et al., “A Drone-Based Bioaerosol Sampling System to Monitor Ice Nucleation Particles in the Lower Atmosphere,” Remote Sens. 2020, Vol. 12, Page 552, vol. 12, no. 3, p. 552, Feb. 2020, doi: 10.3390/RS12030552. DOI:

E. D. Pusfitasari, J. Ruiz-Jimenez, I. Heiskanen, M. Jussila, K. Hartonen, and M. L. Riekkola, “Aerial drone furnished with miniaturized versatile air sampling systems for selective collection of nitrogen containing compounds in boreal forest,” Sci. Total Environ., vol. 808, p. 152011, Feb. 2022, doi: 10.1016/J.SCITOTENV.2021.152011. DOI:

L. Järvi et al., “Determinants of spatial variability of air pollutant concentrations in a street canyon network measured using a mobile laboratory and a drone,” Sci. Total Environ., vol. 856, p. 158974, Jan. 2023, doi: 10.1016/J.SCITOTENV.2022.158974. DOI:

A. Simo, S. Dzitac, I. Dzitac, M. Frigura-Iliasa, and F. M. Frigura-Iliasa, “Air quality assessment system based on self-driven drone and LoRaWAN network,” Comput. Commun., vol. 175, pp. 13–24, Jul. 2021, doi: 10.1016/J.COMCOM.2021.04.032. DOI:

A. Hossain, M. J. Anee, R. Faruqui, S. Bushra, P. Rahman, and R. Khan, “A GPS Based Unmanned Drone Technology for Detecting and Analyzing Air Pollutants,” IEEE Instrum. Meas. Mag., vol. 25, no. 9, pp. 53–60, Dec. 2022, doi: 10.1109/MIM.2022.9955468. DOI:

I. A. Limon, A. D. Hossain, K. F. I. Faruque, M. R. Uddin, and M. Hasan, “Drone-Based Real- Time Air Pollution Monitoring for Low-Access Areas by Developing Mobile-Smart Sensing Technology,” Int. Conf. Robot. Electr. Signal Process. Tech., vol. 2023-Janua, pp. 90–94, 2023, doi: 10.1109/ICREST57604.2023.10070050. DOI:

S. Duangsuwan and P. Jamjareekulgarn, “Development of Drone Real-time Air Pollution Monitoring for Mobile Smart Sensing in Areas with Poor Accessibility,” Sensors Mater., vol. 32, no. 2, pp. 511–520, 2020, doi: 10.18494/SAM.2020.2450. DOI:

G. Rohi, O. Ejofodomi, and G. Ofualagba, “Autonomous monitoring, analysis, and countering of air pollution using environmental drones,” Heliyon, vol. 6, no. 1, p. e03252, Jan. 2020, doi: 10.1016/J.HELIYON.2020.E03252. DOI:

L. Cabanillas-Pardo, J. A. Cabanillas-Pardo, A. Mendoza-Pinedo, M. Jimenez-Montalban, C. A. Ríos-López, and L. Pintado-Pompa, “Prototipo secador de madera para procesamiento secundario con tecnología de efecto invernadero, colectores solares de aire y sistemas de control electrónico,” Rev. Científica Sist. e Informática, vol. 3, no. 1, p. e471, Jan. 2023, doi: 10.51252/rcsi.v3i1.471. DOI:

M. Loh et al., “How Sensors Might Help Define the External Exposome,” Int. J. Environ. Res. Public Heal. 2017, Vol. 14, Page 434, vol. 14, no. 4, p. 434, Apr. 2017, doi: 10.3390/IJERPH14040434. DOI:

N. Michel, S. Bertrand, S. Olaru, G. Valmorbida, and D. Dumur, “Design and flight experiments of a Tube-Based Model Predictive Controller for the AR.Drone 2.0 quadrotor,” IFAC-PapersOnLine, vol. 52, no. 22, pp. 112–117, Jan. 2019, doi: 10.1016/J.IFACOL.2019.11.058. DOI:

V. M. Respall, S. Sellami, and I. Afanasyev, “Implementation of autonomous visual detection, tracking and landing for AR.Drone 2.0 quadcopter,” Proc. - Int. Conf. Dev. eSystems Eng. DeSE, vol. October-20, pp. 477–482, Oct. 2019, doi: 10.1109/DESE.2019.00093. DOI:

F. I. Adhim et al., “Carbon Monoxide and Methane Gas Identification System,” 2019 Int. Conf. Adv. Mechatronics, Intell. Manuf. Ind. Autom. ICAMIMIA 2019 - Proceeding, pp. 263–267, Oct. 2019, doi: 10.1109/ICAMIMIA47173.2019.9223367. DOI:

Sparkfun, “SparkFun Electronics,” 2023. (accessed Oct. 16, 2023).

I. S. P. Nagahage, E. A. A. D. Nagahage, and T. Fujino, “Assessment of the applicability of a low-cost sensor–based methane monitoring system for continuous multi-channel sampling,” Environ. Monit. Assess., vol. 193, no. 8, pp. 1–14, Aug. 2021, doi: 10.1007/S10661-021-09290-W/TABLES/4. DOI:

hwsensor, “HANWEI ELECTRONICS MQ-4,” 2020. (accessed Oct. 16, 2023).

Datasheet, “(PDF) MQ-4 Datasheet - Semiconductor Sensor,” 2020. (accessed Oct. 16, 2023).

H. K. Kondaveeti, N. K. Kumaravelu, S. D. Vanambathina, S. E. Mathe, and S. Vappangi, “A systematic literature review on prototyping with Arduino: Applications, challenges, advantages, and limitations,” Comput. Sci. Rev., vol. 40, p. 100364, May 2021, doi: 10.1016/J.COSREV.2021.100364. DOI:

M. Malhotra, I. K. Aulakh, N. Kaur, and N. S. Aulakh, “Air Pollution Monitoring Through Arduino Uno,” Adv. Intell. Syst. Comput., vol. 1077, pp. 235–243, 2020, doi: 10.1007/978-981-15-0936-0_24/COVER. DOI:

ARDUINO®, “Arduino - Software,” 2018. .

S. Ghosh et al., “Development of an IOT based robust architecture for environmental monitoring using UAV,” 2019 IEEE 16th India Counc. Int. Conf. INDICON 2019 - Symp. Proc., Dec. 2019, doi: 10.1109/INDICON47234.2019.9028987. DOI:

Sparkfun, “Preliminary Product Specification v1.0,” 2008.

J. Kodosky and C. Lopes, “LabVIEW,” Proc. ACM Program. Lang., vol. 4, no. HOPL, Jun. 2020, doi: 10.1145/3386328. DOI:

S. Sivaranjani et al., “Visualization of virtual environment through labVIEW platform,” Mater. Today Proc., vol. 45, pp. 2306–2312, Jan. 2021, doi: 10.1016/J.MATPR.2020.10.559. DOI:

E. Martínez Rodríguez, “Errores frecuentes en la interpretación del coeficiente de determinación lineal,” Anu. jurídico y económico Escur., vol. XXXVIII, no. 38, pp. 315–331, 2005, doi: 10.1007/s00259-015-3057-y. DOI:




How to Cite

Holgado-Apaza LA, Julian-Laime E, Baca JB, Castillo RM, Prieto-Luna JC, Córdova-Mendoza P, Zea NSM, Valles-Coral M. Monitoring and analysis of carbon monoxide and methane using Sensors and Remotely Piloted Aircraft Systems. EAI Endorsed Trans Energy Web [Internet]. 2023 Nov. 22 [cited 2024 Jun. 15];10. Available from: