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Remote sensing for vegetation monitoring in carbon capture storage regions: A review

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  • Chen, Yun
  • Guerschman, Juan P
  • Cheng, Zhibo
  • Guo, Longzhu

Abstract

Carbon Capture and Storage (CCS) is an emerging climate change mitigation technology which prevents carbon dioxide (CO2) from entering the atmosphere, so as to reduce greenhouse gas emissions. Environmental monitoring in CCS sites is critical for ensuring that any CO2 leakage and its effect on biota, especially vegetation, is detectable. It also plays an important role in creating a social license to operate and assuring the general public that the mechanisms for leak detection and remediation are in place. This review overviews current remote sensing technologies for vegetation monitoring of CCS sites/regions (with a focus on rangelands and pastures), including medium-to-high resolution satellite, aerial (both manned and unmanned aircrafts) and in situ sensors and methods. Our literature survey has pointed out that remote sensing, particularly hyperspectral sensors, can accurately detect CO2 leakage derived effects on vegetation. It can compensate the two main drawbacks of operational systems for detecting these effects over large areas. One is the areas affected tend to be relatively small (1–15 m); and the other is symptoms in vegetation tissues tend to be similar to other stresses, such as nutrient or water deficiency. With this in mind, we have recommend that a comprehensive system should be put in place. It integrates continuous monitoring with ad-hoc detection to assess vegetation conditions in a planned CCS site. Site-based pheonocams and area-based medium-resolution satellite remote sensing sources can be used to compare any given point in time (e.g. the injection point) with the condition at the same location in the past. Before an injection commences, a baseline assessment should be conducted using the combination of high-resolution aerial hyperspectral imaging and medium-resolution long-term data from Landsat sensors. Further acquisition of high-resolution aerial imagery (ideally hyperspectral) is particularly useful following specific detected CO2 leaking events. Aiming at bridging the gaps between research, development and implementation of CCS, this review will contribute to environmental and social impacts of sustainable energy policies, including climate change mitigation and environmental pollution reduction.

Suggested Citation

  • Chen, Yun & Guerschman, Juan P & Cheng, Zhibo & Guo, Longzhu, 2019. "Remote sensing for vegetation monitoring in carbon capture storage regions: A review," Applied Energy, Elsevier, vol. 240(C), pages 312-326.
  • Handle: RePEc:eee:appene:v:240:y:2019:i:c:p:312-326
    DOI: 10.1016/j.apenergy.2019.02.027
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    References listed on IDEAS

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    1. Hang Deng & Jeffrey M. Bielicki & Michael Oppenheimer & Jeffrey P. Fitts & Catherine A. Peters, 2017. "Leakage risks of geologic CO2 storage and the impacts on the global energy system and climate change mitigation," Climatic Change, Springer, vol. 144(2), pages 151-163, September.
    2. Daegeun Ko & Gayoung Yoo & Seong‐Taek Yun & Haegeun Chung, 2016. "Impacts of CO 2 leakage on plants and microorganisms: A review of results from CO 2 release experiments and storage sites," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 6(3), pages 319-338, June.
    3. Jiang Jinbao & Michael D Steven & Cai Qingkong & He Ruyan & Guo Haiqiang & Chen Yunhao, 2014. "Detecting bean stress response to CO 2 leakage with the utilization of leaf and canopy spectral derivative ratio," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 4(4), pages 468-480, August.
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    2. João Lucas Della-Silva & Carlos Antonio da Silva Junior & Mendelson Lima & Paulo Eduardo Teodoro & Marcos Rafael Nanni & Luciano Shozo Shiratsuchi & Larissa Pereira Ribeiro Teodoro & Guilherme Fernand, 2022. "CO 2 Flux Model Assessment and Comparison between an Airborne Hyperspectral Sensor and Orbital Multispectral Imagery in Southern Amazonia," Sustainability, MDPI, vol. 14(9), pages 1-15, May.
    3. Quanfeng Li & Wei Liu & Guoming Du & Bonoua Faye & Huanyuan Wang & Yunkai Li & Lu Wang & Shijin Qu, 2022. "Spatiotemporal Evolution of Crop Planting Structure in the Black Soil Region of Northeast China: A Case Study in Hailun County," Land, MDPI, vol. 11(6), pages 1-14, May.
    4. Sara Yasemi & Yasin Khalili & Ali Sanati & Mohammadreza Bagheri, 2023. "Carbon Capture and Storage: Application in the Oil and Gas Industry," Sustainability, MDPI, vol. 15(19), pages 1-32, October.

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