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Remote Sensing
Volume 15
Issue 1
10.3390/rs15010255
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Article

Mapping of Greenhouse Gas Concentration in Peninsular Malaysia Industrial Areas Using Unmanned Aerial Vehicle-Based Sniffer Sensor

by
Mazlan Hashim
1,2,*,
Hui Lin Ng
1,
Dahiru Mohammed Zakari
1,
Dalhatu Aliyu Sani
1,
Musa Muhammad Chindo
1,
Noordyana Hassan
1,2,
Muna Maryam Azmy
3 and
Amin Beiranvand Pour
2,4
1
Faculty of Built Environment & Surveying, Universiti Teknologi Malaysia, Johor Bahru 81310, Johor, Malaysia
2
Geoscience and Digital Earth Centre (INSTeG), Research Institute for Sustainable Environment, Universiti Teknologi Malaysia, Johor Bahru 81310, Johor, Malaysia
3
School of Tourism, Hospitality & Environmental Management, Universiti Utara Malaysia, Sintok 06010, Kedah Darul Aman, Malaysia
4
Institute of Oceanography and Environment (INOS), Universiti Malaysia Terengganu (UMT), Kuala Nerus 21030, Terengganu, Malaysia
*
Author to whom correspondence should be addressed.
Remote Sens. 2023, 15(1), 255; https://doi.org/10.3390/rs15010255
Submission received: 6 November 2022 / Revised: 14 December 2022 / Accepted: 21 December 2022 / Published: 1 January 2023
(This article belongs to the Special Issue Hyperspectral Remote Sensing from Spaceborne and Low Altitude Aerial/Drone-Based Platforms — Differences in Approaches, Data Processing Methods, and Applications)
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Abstract

The increasing concentration of greenhouse gas (GHG) emissions due to increased fossil fuel consumption for manufacturing activities to support population growth is worrisome. Carbon dioxide (CO2) and methane (CH4) remain the two GHGs that contribute to the impact of global warming, and inventorying their concentrations is important for monitoring their changes, which can be used to infer their emissions over time. Hence, this article highlights sniffer4D, an unmanned aerial vehicle (UAV)-based air pollutant mapping system that visualise and analyse three-dimensional (3D) air pollution data in real time, for mapping GHGs concentrations within industrial areas. Consequently, GHGs concentrations for two industrial and adjacent residential areas in Johor, Peninsular Malaysia were mapped. The GHGs concentrations were validated using a ground-based portable gas detector. The results revealed that CO2 has the highest concentration mean of 625.235 mg/m3, followed by CH4 with a mean of 249.239 mg/m3. The mapped UAV GHG concentration also reported good agreement with the in situ observations with an RMSE of 7 and 6 mg/m3 for CO2 and CH4 concentration, respectively. Ozone and nitrogen dioxide mixture (O3 + NO2) with a mean concentration of 249 μg/m3 and an RMSE of 9 μg/m3 are the remaining significant concentrations reported. This approach shall assist in fast-tracking the United Nations climate change mitigation agenda.
Keywords: GHG concentration; industrial area; remote sensing sensor; UAV; mapping GHG concentration; industrial area; remote sensing sensor; UAV; mapping

Share and Cite

MDPI and ACS Style

Hashim, M.; Ng, H.L.; Zakari, D.M.; Sani, D.A.; Chindo, M.M.; Hassan, N.; Azmy, M.M.; Pour, A.B. Mapping of Greenhouse Gas Concentration in Peninsular Malaysia Industrial Areas Using Unmanned Aerial Vehicle-Based Sniffer Sensor. Remote Sens. 2023, 15, 255. https://doi.org/10.3390/rs15010255

AMA Style

Hashim M, Ng HL, Zakari DM, Sani DA, Chindo MM, Hassan N, Azmy MM, Pour AB. Mapping of Greenhouse Gas Concentration in Peninsular Malaysia Industrial Areas Using Unmanned Aerial Vehicle-Based Sniffer Sensor. Remote Sensing. 2023; 15(1):255. https://doi.org/10.3390/rs15010255

Chicago/Turabian Style

Hashim, Mazlan, Hui Lin Ng, Dahiru Mohammed Zakari, Dalhatu Aliyu Sani, Musa Muhammad Chindo, Noordyana Hassan, Muna Maryam Azmy, and Amin Beiranvand Pour. 2023. "Mapping of Greenhouse Gas Concentration in Peninsular Malaysia Industrial Areas Using Unmanned Aerial Vehicle-Based Sniffer Sensor" Remote Sensing 15, no. 1: 255. https://doi.org/10.3390/rs15010255

APA Style

Hashim, M., Ng, H. L., Zakari, D. M., Sani, D. A., Chindo, M. M., Hassan, N., Azmy, M. M., & Pour, A. B. (2023). Mapping of Greenhouse Gas Concentration in Peninsular Malaysia Industrial Areas Using Unmanned Aerial Vehicle-Based Sniffer Sensor. Remote Sensing, 15(1), 255. https://doi.org/10.3390/rs15010255

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