Evaluation of error inducing factors in unmanned aerial vehicle mounted detector to measure fugitive methane from solid waste landfill

Kim, Yeong Min; Park, Man Ho; Jeong, Sunjoo; Lee, Kyeong Ho; Kim, Jae Young

doi:10.1016/j.wasman.2021.02.023

Cited by 17 publications

(10 citation statements)

References 24 publications

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“…Spatial interpolation is a useful GIS technique for estimating unmeasured data based on measured samples of the same variables (Kim et al, 2021). The advent of remote sensing (RS) and geographical information system (GIS) have proved to solve some challenges emanating from physical infrastructures, time, and financial resources with respect to data access and utilisation.…”

Section: Geostatistical Analysis Inverse Distance Weighingmentioning

confidence: 99%

Impact of Population Dynamics on Solid Waste Generation Trends in Dar Es Salaam Metropolitan

2023

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Rapid population growth observed across the global landscape can be traced from the dawn of the last half of the twentieth century. The period is marked by enormous land use and land cover changes, the rising rate of declining biological resources as well a continuous high rate of urbanisation. Dar es Salaam City, once a fishing village but now the most industrialised and urbanised city in Tanzania, has not been spared of such changes. This article composition intended to uncover the correlation between population growth and solid waste generation in the city of Dar es Salaam. The data inputs involved Tanzania’s national population census for the years 2002, 2012, and 2022, but also shapefiles for Dar es Salaam City and the United Republic of Tanzania. Dar es Salaam city’s wards, the lowest but one administrative level in Tanzania, were central in this study as the lowest unit of analysis. Data management for this spatiotemporal study was done in Microsoft spreadsheet, while data analysis involved the use of the ArcMap platform of ArcGIS version 10.5. The results show a strong relationship between population growth and municipal solid waste generation in Dar es Salaam city. From the visual results, the overall impact of population on solid waste generation is well presented across both census years. Despite varying at different times in the twenty years of the study period, wards such as Kunduchi, Mabibo, Majohe, Mbagala Kuu, Mbezi, Mianzini, Saranga, Segerea, Vingunguti, Wazo, and Charambe produced significant amounts of solid waste. Across the study period, Vingunguti and Majohe were revealed to be the only two wards in the city that have continued generating high solid wastes. These visual results display the almost exact location of a high waste generation hence delivering information necessary for strategic and informed decision-making, henceforth, policy formulation towards solid generation and management.

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Section: Geostatistical Analysis Inverse Distance Weighingmentioning

confidence: 99%

Impact of Population Dynamics on Solid Waste Generation Trends in Dar Es Salaam Metropolitan

2023

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“…UAVs are robust in terms of their spatial resolution, revisit capability and absence of radiometric errors induced by clouds and atmospheric turbulence. Recent studies have successfully demonstrated the use of drones and UAVs for analysing settlement of solid waste landfills (Baiocchi et al, 2019), landfill landcover mapping (Wyard et al, 2022), detecting local thermal anomalies around landfills (Tanda et al, 2020) and for estimation of fugitive landfill gas emissions (Kim et al, 2021). On the other hand, SRS has been considered a multidisciplinary technique, a substitute for costly and time-consuming traditional in situ techniques (Singh, 2019).…”

Section: Environmental Monitoring Of Msw Dumps Using Geospatial Techn...mentioning

confidence: 99%

Geospatial alternatives for quantification of bio-thermal influence zone in the vicinity of a solid waste dump

et al. 2022

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Owing to the release of toxic gases, leachate and thermal emissions that originate from waste dumps, these sites significantly impact environmental sustainability. The study attempts to assess the deleterious impact of municipal solid waste (MSW) dump on surrounding forested landscape by employing geospatial technologies, which are cost and time-effective. For this purpose, temporal period ranging from 2015 to 2020, having 41 valid satellite observations has been selected for study. Firstly, the radii of intense hazardous zone and hazardous zone have been measured, as two separate parameters, which are 580 ± 30 m and 1260 ± 30 m, respectively. Secondly, average spatial extent of bio-influence zone is measured to be 1262 m while the average thermal influence zone extends up to 530 m around the MSW dumping site. A detailed analysis of influence zone variations reveals that the bio-influence zone depends on multitude of meteorological parameters, whereas the thermal influence zone relies mainly on seasonal temperature fluctuations. Moreover, the level of severity of emissions from MSW decomposition directly depends upon temperature. The long-term variability analysis of these hazardous zones reveals the stationarity of their spatial extents, signifying forest resilience. This study has proved significance of geospatial techniques as an alternate of expensive and time intensive assessment methods involving in situ measurements. So the proposed technique is beneficial for environmentalists, decision-makers and municipal authorities for analysing the extent and severity of MSW pollutants for forest community to address the problem of ecological degradation.

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“…For example, in [102], they demonstrated a proof of concept using a chemical multisensor payload for gas monitoring based on the DJI S900 platform. Or in [106], a semiconductor type sensor (Testo Gas Detector, Testo SE & Co. KGaA, Titisee-Neustadt, Germany) was used on a DJI M600 to analyze the spatial distribution of methane at a landfill, as well as compared different spatial interpolation techniques. This required calibration and consideration of the vehicle's critical velocity.…”

Section: Sensors and Equipmentmentioning

confidence: 99%

Advanced Leak Detection and Quantification of Methane Emissions Using sUAS

Hollenbeck

Zulevic

Chen

2021

Drones

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Detecting and quantifying methane emissions is gaining an increasingly vital role in mitigating emissions for the oil and gas industry through early detection and repair and will aide our understanding of how emissions in natural ecosystems are playing a role in the global carbon cycle and its impact on the climate. Traditional methods of measuring and quantifying emissions utilize chamber methods, bagging individual equipment, or require the release of a tracer gas. Advanced leak detection techniques have been developed over the past few years, utilizing technologies, such as optical gas imaging, mobile surveyors equipped with sensitive cavity ring down spectroscopy (CRDS), and manned aircraft and satellite approaches. More recently, sUAS-based approaches have been developed to provide, in some ways, cheaper alternatives that also offer sensing advantages to traditional methods, including not being constrained to roadways and being able to access class G airspace (0–400 ft) where manned aviation cannot travel. This work looks at reviewing methods of quantifying methane emissions that can be, or are, carried out using small unmanned aircraft systems (sUAS) as well as traditional methods to provide a clear comparison for future practitioners. This includes the current limitations, capabilities, assumptions, and survey details. The suggested technique for LDAQ depends on the desired accuracy and is a function of the survey time and survey distance. Based on the complexity and precision, the most promising sUAS methods are the near-field Gaussian plume inversion (NGI) and the vertical flux plane (VFP), which have comparable accuracy to those found in conventional state-of-the-art methods.

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Evaluation of error inducing factors in unmanned aerial vehicle mounted detector to measure fugitive methane from solid waste landfill

Cited by 17 publications

References 24 publications

Impact of Population Dynamics on Solid Waste Generation Trends in Dar Es Salaam Metropolitan

Impact of Population Dynamics on Solid Waste Generation Trends in Dar Es Salaam Metropolitan

Geospatial alternatives for quantification of bio-thermal influence zone in the vicinity of a solid waste dump

Advanced Leak Detection and Quantification of Methane Emissions Using sUAS

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