Reflectance and imaging spectroscopy applied to detection of petroleum hydrocarbon pollution in bare soils

Autor(es)

Correa Pabon, Rosa Elvira ^[1] ; de Souza Filho, Carlos Roberto ^[1] ; de Oliveira, Wilson Jose ^[2]

Afiliação do(s) autor(es)

^[1] Univ Campinas UNICAMP, Inst Geosci, POB 6152, BR-13083970 Campinas, SP - Brazil

^[2] PETROBRAS ENG RLE PROJEN, Av Henrique Valadares 28, BR-20231030 Rio De Janeiro, RJ - Brazil

• Tipo de documento: Artigo Científico
• Fonte: Science of The Total Environment; v. 649, p. 1224-1236, FEB 1 2019.
• Citações Web of Science: 10

Resumo

Accidental releases of hazardous waste related to the extraction, refining, and transport of oil and gas are inevitable. Petroleum facilities and intrinsic pipelines present environmental pollution risks, threatening both human health and ecosystems. Research has been undertaken to enhance the conventional methods for monitoring hazardous waste problems and to improve time-consuming and cost-effective ways for leak detection and remediation process. In this study, both diffuse and imaging (hyperspectral) reflectance spectroscopy are used for detection and characterization of petroleum hydrocarbon (PHC) contamination in latosols. Laboratory and field measurements of PHC-contaminated and PHC-free soils were collected from an oil facility using an ASD lieldSpec-3 high-resolution portable spectrometer (2150 channels) covering visible, near infrared and short-wave infrared wavelengths (VNIR-SWIR: 350-2500 nm). The hyperspectral image dataset was acquired with the ProSpecTlR-VS airborne sensor using 357 channels in the VNIR-SWIR range at 1 m of spatial resolution. Narrow intervals of reflectance spectra were analyzed to identify the primary mineral and PHC absorption bands in soil samples and to investigate the spectral match with airborne hyperspectral data. The Multiple Endmember Spectral Mixture Analysis (MESMA) method was employed in three hierarchical levels to classify the hyperspectral imagery. The classification product yielded from MESMA model at the fourth level was 98% accurate in discriminating contaminated soils. The results demonstrated the applicability of both diffuse reflectance and imaging (hyperspectral) spectroscopy to identify bare soils contaminated by PHC leaks and spills. These technologies can also provide useful information for remediation initiatives, thereby avoiding further problems with hazardous waste. (C) 2018 Elsevier B.V. All rights reserved. (AU)

• Processo FAPESP: 15/05728-8 - Caracterização Espectral de Solos Contaminados com Hidrocarbonetos Líquidos: Aplicações Potenciais no Monitoramento de Vazamentos em Instalações Petrolíferas e Dutos de Transporte Associados
• Beneficiário: Rosa Elvira Correa Pabón
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado