4.7 Article

An inversion method for estimating strong point carbon dioxide emissions using a differential absorption Lidar

期刊

JOURNAL OF CLEANER PRODUCTION
卷 271, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2020.122434

关键词

Energy conservation; CO2 emission; ECO development

资金

  1. National Natural Science Foundation of China [41971283, 41801261, 41827801, 41901274, 41801282]
  2. National Key Research and Development Program of China [2017YFC0212600]
  3. Postdoctoral Science Foundation of China [2017T100580]
  4. Natural Science Foundation of Jiangsu Province [BK20180809]
  5. Programs for Science and Technology Development of Henan Province [192102310008]
  6. Key Scientific Research Project of Henan Institutions of Higher Learning [18B170007]

向作者/读者索取更多资源

Anthropogenic carbon emissions increase the atmospheric concentration of carbon dioxide, resulting in global warming and climate change. To complement the existing carbon emission verification system, it is crucial to develop a novel measurement-based estimation method for determining the carbon emissions produced by strong point sources. This study determines the feasibility of measuring point source carbon emissions using differential absorption Lidar (DIAL). First, for measuring carbon emissions, an estimation method is introduced that utilizes a Gaussian dispersion model with range-resolved carbon dioxide concentrations for the inversion of carbon emissions produced at specific localized point sources. On this basis, a sensitivity analysis is conducted to study the quantitative effect of different parameters on the performance of the proposed method. The inversion method yields less than 0.01% error in ideal conditions. Considering the uncertainties in the relevant input parameters, we found that the errors in the estimates of point source carbon emissions can be maintained below 5.8% using hypothetical equipment with a configuration identical to that of the planned DIAL. Such a novel framework for estimating point source carbon emissions is important for monitoring, reporting, and verifying anthropogenic carbon emissions. (C) 2020 Elsevier Ltd. All rights reserved.

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