Fast-hyperspectral imaging remote sensing: Emission quantification of NO<sub>2</sub> and SO<sub>2</sub> from marine vessels

Chengzhi Xing; Shaocong Wei; Yikai Li; Peiyuan Jiao; Chao Liu; Jian Chen; Weiheng Wang; Haochen Peng; Yuhang Song; Cheng Liu

doi:10.1038/s41377-025-01922-x

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Fast-hyperspectral imaging remote sensing: Emission quantification of NO₂ and SO₂ from marine vessels

Original Articles

- Fast-hyperspectral imaging remote sensing: Emission quantification of NO₂ and SO₂ from marine vessels
- Fast-hyperspectral imaging remote sensing: Emission quantification of NO₂ and SO₂ from marine vessels
- Light: Science & Applications 2025年14卷第10期页码：3226-3236
- Affiliations：
  
  1.Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, 230031 Hefei, China
  2.Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, 230026 Hefei, China
  3.School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, 230026 Hefei, China
  4.Institute for Atmospheric and Climate Science, Eidgenössische Technische Hochschule Zürich, 8006 Zürich, Switzerland
  5.Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, 361021 Xiamen, China
  6.Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, 230026 Hefei, China
- Author bio：
  
  Cheng Liu (chliu81@ustc.edu.cn)
- Funds：
- DOI：10.1038/s41377-025-01922-x
  中图分类号：
- 收稿：2025-01-08，
  
  修回：2025-05-15，
  
  录用：2025-06-16，
  
  网络出版：2025-09-08，
  
  纸质出版：2025-10-31
- Accepted：
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Chengzhi Xing, Shaocong Wei, Yikai Li, 等. Fast-hyperspectral imaging remote sensing: Emission quantification of NO₂ and SO₂ from marine vessels[J]. Light: Science & Applications, 2025,14(10):3226-3236.

Xing, C. Z. et al. Fast-hyperspectral imaging remote sensing: Emission quantification of NO₂ and SO₂ from marine vessels. Light: Science & Applications, 14, 3226-3236 (2025).
Chengzhi Xing, Shaocong Wei, Yikai Li, 等. Fast-hyperspectral imaging remote sensing: Emission quantification of NO₂ and SO₂ from marine vessels[J]. Light: Science & Applications, 2025,14(10):3226-3236. DOI： 10.1038/s41377-025-01922-x.

Xing, C. Z. et al. Fast-hyperspectral imaging remote sensing: Emission quantification of NO₂ and SO₂ from marine vessels. Light: Science & Applications, 14, 3226-3236 (2025). DOI： 10.1038/s41377-025-01922-x.

摘要

Abstract

Marine vessels play a vital role in the global economy; however

their negative impact on the marine atmospheric environment is a growing concern. Quantifying marine vessel emissions is an essential prerequisite for controlling these emissions and improving the marine atmospheric environment. Optical imaging remote sensing is a vital technique for quantifying marine vessel emissions. However

the available imaging techniques have suffered from insufficient detection accuracy and inadequate spatiotemporal resolution. Herein

we propose a fast-hyperspectral imaging remote sensing technique that achieved precise imaging of nitrogen dioxide (NO

) and sulfur dioxide (SO

) from marine vessels. Several key techniques are developed

including the coaxial design of three camera systems (hyperspectral camera

visible camera

and multiwavelength filters) and a high-precision temperature control system for a spectrometer (20 ℃ ± 0.5 ℃). Moreover

based on the variation of O

within them

plumes are categorized as aerosol-present and aerosol-absent

with different air mass factor (AMF) calculation schemes developed accordingly. Multiwavelength filters combined with spectral analysis enable precise identification of the plume outline and a detailed observation of the trace gas distribution inside the plume emitted from marine vessels. In addition

we focuse on the emission characteristics of NO

and SO

from large ocean cargo ships and small offshore cargo ships. Although there are still many emerging issues

such as measurement of cross-sections of trace gases at different temperature

nighttime imaging

and greenhouse gas imaging

this study opens a gate for synergies in pollution and carbon reductions and the conti

nuous improvement of the marine atmospheric environment.

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Keywords

references

Toscano, D. & Murena, F. Atmospheric ship emissions in ports: a review. Correlation data ship traffic Atmos. Environ.: X 4 , 100050 (2019)..

Zhang, Y. et al. Shipping emissions and their impacts on air quality in China. Sci. Total Environ. 581–582 , 186–198 (2017)..

Ytreberg, E., Åström, S. & Fridell, E. Valuating environmental impacts from ship emissions-the marine perspective. J. Environ. Manag. 282 , 111958 (2021)..

Berg, N. et al. Ship emissions of SO 2 and NO 2 : DOAS measurements from airborne platforms. Atmos. Meas. Tech. 5 , 1085–1098, https://doi.org/10.5194/amt-5-1085-2012 (2012)..

Liu, Z. M. et al. Influence of ship emissions on urban air quality: a comprehensive study using highly time-resolved online measurements and numerical simulation in Shanghai. Environ. Sci. Technol. 51 , 202–211 (2017)..

Zhang, C. et al. Impact of air emissions from shipping on marine phytoplankton growth. Sci. Total Environ. 769 , 145488 (2021)..

Blasco, J. et al. Towards an integrated environmental risk assessment of emissions from ships’ propulsion systems. Environ. Int. 66 , 44–47 (2014)..

Moore, T. J. et al. Exploring ship traffic variability off California. Ocean Coast. Manag. 163 , 515–527 (2018)..

Repka, S. et al. Assessing the costs and environmental benefits of IMO regulations of ship-originated SOx and NOx emissions in the Baltic Sea. Ambio 50 , 1718–1730 (2021)..

Beirle, S. et al. Estimate of nitrogen oxide emissions from shipping by satellite remote sensing. Geophys. Res. Lett. 31 , L18102, https://doi.org/10.1029/2004GL020312 (2004)..

Georgoulias, A. K. et al. Detection of NO 2 pollution plumes from individual ships with the TROPOMI/S5P satellite sensor. Environ. Res. Lett. 15 , 124037, https://doi.org/10.1088/1748-9326/abc445 (2020)..

Boersma, K. F., Vinken, G. C. M. & Tournadre, J. Ships going slow in reducing their NOx emissions: changes in 2005-2012 ship exhaust inferred from satellite measurements over Europe. Environ. Res. Lett. 10 , 074007, https://doi.org/10.1088/1748-9326/10/7/074007 (2015)..

Luo, Z. Y. et al. Advancing shipping NO x pollution estimation through a satellite-based approach. PNAS Nexus 3 , pgad430, https://doi.org/10.1093/pnasnexus/pgad430 (2024)..

Kurchaba, S. et al. Anomalous NO 2 emitting ship detection with TROPOMI satellite data and machine learning. Remote Sens. Environ. 297 , 113761, https://doi.org/10.1016/j.rse.2023.113761 (2023)..

Krause, K. et al. Estimation of ship emission rates at a major shipping lane by long-path DOAS measurements. Atmos. Meas. Tech. 14 , 5791–5807, https://doi.org/10.5194/amt-14-5791-2021 (2021)..

Seyler, A. et al. Monitoring shipping emissions in the German Bight using MAX-DOAS measurements. Atmos. Chem. Phys. 17 , 10997–11023, https://doi.org/10.5194/acp-17-10997-2017 (2017)..

Mori, T. & Burton, M. The SO 2 camera: a simple, fast and cheap method for ground-based imaging of SO 2 in volcanic plumes. Geophys. Res. Lett. 33 , L24804 (2006)..

Lee, H., Kim, Y. J. & Lee, C. Estimation of the rate of increase in nitrogen dioxide concentrations fr om power plant stacks using an imaging-DOAS. Environ. Monit. Assess. 152 , 61–70 (2009)..

Pikelnaya, O. et al. Imaging DOAS detection of primary formaldehyde and sulfur dioxide emissions from petrochemical flares. J. Geophys. Res.: Atmospheres 118 , 8716–8728 (2013)..

Luo, Y. H. et al. Estimation of the power plant plume emissions using high resolution imaging DOAS technique. Optical Nanostructures and Advanced Materials for Photovoltaics . (Optica Publishing Group, 2015, Suzhou China, 2015).

Platt, U. et al. Quantitative imaging of volcanic plumes—results, needs, and future trends. J. Volcanol. Geotherm. Res. 300 , 7–21 (2015)..

Wu, Y. et al. Air quality monitoring using mobile microscopy and machine learning. Light Sci. Appl. 6 , e17046 (2017)..

Manago, N. et al. Visualizing spatial distribution of atmospheric nitrogen dioxide by means of hyperspectral imaging. Appl. Opt. 57 , 5970–5977 (2018)..

Foote, M. D. et al. Fast and accurate retrieval of methane concentration from imaging spectrometer data using sparsity prior. IEEE Trans. Geosci. Remote Sens. 58 , 6480–6492 (2020)..

Hu, Y. et al. Three-dimensional reconstruction of a leaking gas cloud based on two scanning FTIR remote-sensing imaging systems. Opt. Express 30 , 25581–25596 (2022)..

Liu, C. et al. Stereoscopic hyperspectral remote sensing of the atmospheric environment: innovation and prospects. Earth-Sci. Rev. 226 , 103958 (2022)..

Xiong, Y. H. et al. Real-time monitoring of SO 2 emissions using a UV camera with built-in NO 2 and aerosol corrections. Sensors 22 , 3900 (2022)..

Knapp, M. et al. Spectrometric imaging of sub-hourly methane emission dynamics from coal mine ventilation. Environ. Res. Lett. 18 , 044030 (2023)..

Lin, J. N. et al. Hyperspectral imaging technique supports dynamic emission inventory of coal-fired power plants in China. Sci. Bull. 68 , 1248–1251 (2023)..

Wagner, T. et al. MAX-DOAS O 4 measurements: a new technique to derive information on atmospheric aerosols—principles and information content. J. Geophys. Res.: Atmospheres 109 , D22205 (2004)..

Rodgers, C. D. Inverse Methods for Atmospheric Sounding: Theory and Practice. (Singapore: World Scientific Publishing, 2000).

MEIC Team. The multi-resolution emission inventory model for climate and air pollution research. http://meicmodel.org.cn http://meicmodel.org.cn (2012).

EMEP/EEA air pollution emission inventory guidebook 2023. European Environment Agency. https://doi.org/10.2800/795737 https://doi.org/10.2800/795737 (2023).

Kurokawa, J. & Ohara, T. Long-term historical trends in air pollutant emissions in Asia: regional emission inventory in ASia (REAS) version 3. Atmos. Chem. Phys. 20 , 12761–12793 (2020)..

Binkowski, F. S. & Roselle, S. J. Models-3 community multiscale air quality (CMAQ) model aerosol component 1. Model description. J. Geophys. Res.: Atmospheres 108 , 4183 (2003)..

Grell, G. A. et al. Fully coupled “online” chemistry within the WRF model. Atmos. Environ. 39 , 6957–6975 (2005)..

Gégo, E. et al. An objective comparison of CMAQ and REMSAD performances. Atmos. Environ. 40 , 4920–4934 (2006)..

Wang, Y. et al. Carbon peak and carbon neutrality in China: goals, implementation path and prospects. China Geol. 4 , 720–746 (2021)..

Zhao, X. et al. Challenges toward carbon neutrality in China: strategies and countermeasures. Resour. Conserv. Recycling 176 , 105959 (2022)..

Yang, X. W., Guo, X. Y. & Wang, Y. N. Characteristics of carbon emission transfer under carbon neutrality and carbon peaking background and the impact of environmental policies and regulations on it. Sustainability 15 , 7528 (2023)..

Spurr, R. J. D. VLIDORT: a linearized pseudo-spherical vector discrete ordinate radiative transfer code for forward model and retrieval studies in multilayer multiple scattering media. J. Quant. Spectrosc. Radiat. Transf. 102 , 316–342 (2006)..

Liu, C. et al. Ground-based hyperspectral stereoscopic remote sensing network: a promising strategy to learn coordinated control of O 3 and PM 2.5 over China. Engineering 19 , 71–83 (2022)..

Xing, C. Z. et al. A new method to determine the aerosol optical properties from multiple-wavelength O 4 absorptions by MAX-DOAS observation. Atmos. Meas. Tech. 12 , 3289–3302 (2019)..

Vandaele, A. C. et al. Measurements of the NO 2 absorption cross-section from 42 000 cm -1 to 10000 cm -1 (238-1000 nm) at 220 K and 294 K. J. Quant. Spectrosc. Radiat. Transf. 59 , 171–184 (1998)..

Serdyuchenko, A. et al. High spectral resolution ozone absorption cross-sections–part 2: temperature dependence. Atmos. Meas. Tech. 7 , 625–636 (2014)..

Thalman, R. M. & Volkamer, R. Temperature dependent absorption cross-sections of O 2 -O 2 collision pairs between 340 and 630 nm and at atmospherically relevant pressure. Phys. Chem. Chem. Phys. 15 , 15371–15381 (2013)..

Vandaele, A. C., Hermans, C. & Fally, S. Fourier transform measurements of SO 2 absorption cross sections: II.: temperature dependence in the 29000-44000 cm -1 (227-345 nm) region. J. Quant. Spectrosc. Radiat. Transf. 110 , 2115–2126 (2009)..

Rothman, L. S. et al. The HITRAN 2008 molecular spectroscopic database. J. Quant. Spectrosc. Radiat. Transf. 110 , 533–572 (2009)..

Fleischmann, O. C. et al. New ultraviolet absorption cross-sections of BrO at atmospheric temperatures measured by time-windowing Fourier transform spectroscopy. J. Photochemistry Photobiol. A: Chem. 168 , 117–132 (2004)..

Meller, R. & Moortgat, G. K. Temperature dependence of the absorption cross sections of formaldehyde between 223 and 323 K in the wavelength range 225-375 nm. J. Geophys. Res.: Atmospheres 105 , 7089–7101 (2000)..

Aliwell, S. R. et al. Analysis for BrO in zenith-sky spectra: an intercomparison exercise for analysis improvement. J. Geophys. Res.: Atmospheres 107 , 4199 (2002)..

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Fast-hyperspectral imaging remote sensing: Emission quantification of NO2 and SO2 from marine vessels

Fast-hyperspectral imaging remote sensing: Emission quantification of NO2 and SO2 from marine vessels

DOI：10.1038/s41377-025-01922-x

摘要

Abstract

关键词

Keywords

references

Fast-hyperspectral imaging remote sensing: Emission quantification of NO₂ and SO₂ from marine vessels

Fast-hyperspectral imaging remote sensing: Emission quantification of NO₂ and SO₂ from marine vessels