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Design of a high-coverage ground-based CO2 monitoring layout using a novel information theory-based optimization model

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Abstract

Over the past decade, monitoring of the carbon cycle has become a major concern accented by the severe impacts of global warming. Here, we develop an information theory-based optimization model using the NSGA-II algorithm that determines an optimum ground-based CO2 monitoring layout with the highest spatial coverage using a finite number of stations. The value of information (VOI) concept is used to assess the efficacy of the monitoring stations given their construction cost. In conjunction with VOI, the entropy theory—in terms of transinformation—is adopted to determine the redundant (overlapping) information rendered by the selected monitoring stations. The developed model is used to determine a ground-based CO2 monitoring layout for Iran, the eighth-ranked country emitting CO2 worldwide. An NSGA-II optimization model provides a tradeoff curve given the objectives of (1) minimizing the size of monitoring network; (2) maximizing VOI, i.e., spatial coverage; and (3) minimizing transinformation, i.e., overlapping information. Borda count method is then employed to select the most appropriate compromise monitoring layout from the Pareto-front solutions given regional priorities and concerns.

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Data availability

Daily bias-corrected OCO2_L2_Lite_FP.9r products were downloaded from https://disc.gsfc.nasa.gov.

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Authors and Affiliations

  1. Department of Civil and Environmental Engineering, Shiraz University, Shiraz, Iran

    Parnian Hashempour Bakhtiari & Mohammad Reza Nikoo

  2. Department of Water Engineering, College of Agriculture, Oceanic and Atmospheric Research Center, Shiraz University, Shiraz, Iran

    Foroogh Golkar

  3. Department of Civil Engineering, Boise State University, Boise, Idaho, USA

    Mojtaba Sadegh

  4. Department of Soils, Water, and Agricultural Engineering, Sultan Qaboos University, Muscat, Oman

    Malik Al-Wardy

  5. Department of Civil and Architectural Engineering, Sultan Qaboos University, Muscat, Oman

    Ghazi Ali Al-Rawas

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  1. Parnian Hashempour Bakhtiari
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  2. Mohammad Reza Nikoo
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  3. Foroogh Golkar
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  4. Mojtaba Sadegh
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  6. Ghazi Ali Al-Rawas
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Correspondence to Mohammad Reza Nikoo.

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Bakhtiari, P.H., Nikoo, M.R., Golkar, F. et al. Design of a high-coverage ground-based CO2 monitoring layout using a novel information theory-based optimization model. Environ Monit Assess 193, 150 (2021). https://doi.org/10.1007/s10661-021-08933-2

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