Variation characteristics of atmospheric methane and carbon dioxide in summertime at a coastal site in the South China Sea

Yangyan Cheng, Ye Shan, Yuhuan Xue, Yujiao Zhu, Xinfeng Wang, Likun Xue, Yanguang Liu, Fangli Qiao, Min Zhang

PDF(13477 KB)
PDF(13477 KB)
Front. Environ. Sci. Eng. ›› 2022, Vol. 16 ›› Issue (11) : 139. DOI: 10.1007/s11783-022-1574-z
RESEARCH ARTICLE

Variation characteristics of atmospheric methane and carbon dioxide in summertime at a coastal site in the South China Sea

Author information +
History +

Highlights

● Diurnal patterns of CH4 and CO2 are clearly extracted using EEMD.

● CH4 and CO2 show mid-morning high and evening low patterns during sea breezes.

● Wind direction significantly modulates the diurnal variations in CH4 and CO2.

Abstract

Methane (CH4) and carbon dioxide (CO2) are the two most important greenhouse gases (GHGs). To examine the variation characteristics of CH4 and CO2 in the coastal South China Sea, atmospheric CH4 and CO2 measurements were performed in Bohe (BH), Guangdong, China, in summer 2021. By using an adaptive data analysis method, the diurnal patterns of CH4 and CO2 were clearly extracted and analysed in relation to the sea breeze (SB) and land breeze (LB), respectively. The average concentrations of CH4 and CO2 were 1876.91 ± 31.13 ppb and 407.99 ± 4.24 ppm during SB, and 1988.12 ± 109.92 ppb and 421.54 ± 14.89 ppm during LB, respectively. The values of CH4 and CO2 during SB basically coincided with the values and trends of marine background sites, showing that the BH station could serve as an ideal site for background GHG monitoring and dynamic analysis. The extracted diurnal variations in CH4 and CO2 showed sunrise high and sunset low patterns (with peaks at 5:00–7:00) during LB but mid-morning high and evening low patterns (with peaks at 9:00) during SB. The diurnal amplitude changes in both CH4 and CO2 during LB were almost two to three times those during SB. Wind direction significantly modulated the diurnal variations in CH4 and CO2. The results in this study provide a new way to examine the variations in GHGs on different timescales and can also help us gain a better understanding of GHG sources and distributions in the South China Sea.

Graphical abstract

Keywords

Methane / Carbon dioxide / Diurnal pattern / Ensemble empirical mode decomposition / South China Sea / Sea breeze

Cite this article

Download citation ▾
Yangyan Cheng, Ye Shan, Yuhuan Xue, Yujiao Zhu, Xinfeng Wang, Likun Xue, Yanguang Liu, Fangli Qiao, Min Zhang. Variation characteristics of atmospheric methane and carbon dioxide in summertime at a coastal site in the South China Sea. Front. Environ. Sci. Eng., 2022, 16(11): 139 https://doi.org/10.1007/s11783-022-1574-z

References

[1]
Bai Y N , Wang X N , Zhang F , Zeng R J . (2022). Acid Orange 7 degradation using methane as the sole carbon source and electron donor. Frontiers of Environmental Science & Engineering, 16( 3): 34
[2]
Brandt A R , Heath G A , Kort E A , O’Sullivan F , Pétron G , Jordaan S M , Tans P , Wilcox J , Gopstein A M , Arent D , Wofsy S , Brown N J , Bradley R , Stucky G D , Eardley D , Harriss R . (2014). Methane leaks from North American natural gas systems. Science, 343( 6172): 733– 735
CrossRef Google scholar
[3]
Cai W J , Dai M H , Wang Y C . (2006). Air-sea exchange of carbon dioxide in ocean margins: A province-based synthesis. Geophysical Research Letters, 33( 12): L12603
CrossRef Google scholar
[4]
Canadell J G Monteiro P M S Costa M H Cotrim da Cunha L Cox P M Eliseev A V Henson S Ishii M Jaccard S Koven C. (2021). Global carbon and other biogeochemical cycles and feedbacks. In: Masson-Delmotte V, Zhai P, Pirani A, Connors S L, Péan C, Berger S, Caud N, Chen Y, Goldfarb L, Gomis M I, et al., eds. Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press
[5]
Carslaw D C , Beevers S D . (2013). Characterising and understanding emission sources using bivariate polar plots and k-means clustering. Environmental Modelling & Software, 40 : 325– 329
[6]
Chen X Y , Zhang Y L , Zhang M , Feng Y , Wu Z H , Qiao F L , Huang N E . (2013). Intercomparison between observed and simulated variability in global ocean heat content using empirical mode decomposition, part I: modulated annual cycle. Climate Dynamics, 41( 11−12): 2797– 2815
CrossRef Google scholar
[7]
Clow J Smith J C ( 2016). Using Unmanned Air Systems to Monitor Methane in the Atmosphere. NASA/TM–2016–219008. Hampton: Langley Research Center
[8]
Coumou D , Rahmstorf S . (2012). A decade of weather extremes. Nature Climate Change, 2( 7): 491– 496
CrossRef Google scholar
[9]
Diffenbaugh N S , Singh D , Mankin J S , Horton D E , Swain D L , Touma D , Charland A , Liu Y J , Haugen M , Tsiang M , Rajaratnam B . (2016). Quantifying the influence of global warming on unprecedented extreme climate events. Proceedings of the National Academy of Sciences, 114( 19): 4881– 4886
[10]
Dimitriou K , Bougiatioti A , Ramonet M , Pierros F , Michalopoulos P , Liakakou E , Solomos S , Quehe P Y , Delmotte M , Gerasopoulos E . . (2021). Greenhouse gases (CO2 and CH4) at an urban background site in Athens, Greece: Levels, sources and impact of atmospheric circulation. Atmospheric Environment, 253( 6): 118372
[11]
Dlugokencky E J Nisbet E G Fisher R Lowry D ( 2011). Global atmospheric methane: Budget, changes and dangers. Philosophical Transactions. Series A, Mathematical, physical, and engineering sciences, 369( 1943): 2058− 2072
[12]
Fang S X , Tans P P , Yao B , Luan T , Wu Y L , Yu D J . (2017). Study of atmospheric CO2 and CH4 at Longfengshan WMO/GAW regional station: The variations, trends, influence of local sources/sinks, and transport. Science China. Earth Sciences, 60( 10): 1886– 1895
CrossRef Google scholar
[13]
Forster P Storelvmo T Armour K Collins W Dufresne J L Frame D Lunt D J Mauritsen T Palmer M D Watanabe M. ( 2021). The Earth’s energy budget, climate feedbacks, and climate sensitivity. In: Masson-Delmotte V, Zhai P, Pirani A, Connors S L, Péan C, Berger S, Caud N, Chen Y, Goldfarb L, Gomis M I, et al., eds. Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovemmental Panel on Climate Change. Cambridge: Cambridge University Press
[14]
Gulev S K Thorne P W Ahn J Dentener F J Domingues C M Gerland S Gong D Kaufman D S Nnamchi H C Quaas J. ( 2021). Changing state of the climate system. In: Masson-Delmotte V, Zhai P, Pirani A, Connors S L, Péan C, Berger S, Caud N, Chen Y, Goldfarb L, Gomis M I, et al., eds. Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press
[15]
He J J , Zhang M , Chen X Y , Wang M . (2014). Inter-comparison of seasonal variability and nonlinear trend between AERONET aerosol optical depth and PM10 mass concentrations in Hong Kong (China). Science China. Earth Sciences, 57( 11): 2606– 2615
CrossRef Google scholar
[16]
Huang J , Chan P W . (2011). Progress of marine meteorological observation experiment at Maoming of South China. Journal of Tropical Meteorology, 17( 4): 418– 429
[17]
Huang N E Zheng S Long S R Wu M C Shih H H Zheng Q Yen N C Tung C C Liu H H (1998). The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Philosophical Transactions. Series A, Mathematical, physical, and engineering sciences, 454( 1971): 903– 995
[18]
Ji X L , Liu G M , Gao S , Wang H , Zhang M Y . (2017). Comparison of air-sea CO2 flux and biological productivity in the South China Sea, East China Sea, and Yellow Sea: A three-dimensional physical-biogeochemical modeling study. Acta Oceanologica Sinica, 36( 12): 1– 10
CrossRef Google scholar
[19]
Jiang Y F Wang X Q Wang H Y Xu Y S Lv H G (2021). Study on the concentration variation and impact factors of CH4 in Yongxing Island . China Environmental Science, 41(11): 5054− 5059 (in Chinese)
[20]
Kavitha M Nair P R Girach I A Aneesh S Sijikumar S Renju R ( 2018). Diurnal and seasonal variations in surface methane at a tropical coastal station: Role of mesoscale meteorology. Science of the Total Environment, 631– 632: 631– 632
[21]
Kong S F , Lu B , Han B , Bai Z P , Xu Z , You Y , Jin L M , Guo X Y , Wang R . (2010). Seasonal variation analysis of atmospheric CH4, N2O and CO2 in Tianjin offshore area. Science China. Earth Sciences, 53( 8): 1205– 1215
CrossRef Google scholar
[22]
Li H Y , Zhu Y J , Zhao Y , Chen T S , Jiang Y , Shan Y , Liu Y H , Mu J S , Yin X K , Wu D . . (2020). Evaluation of the performance of low-cost air quality sensors at a high mountain station with complex meteorological conditions. Atmosphere, 11( 2): 212
CrossRef Google scholar
[23]
Li Q , Gogo S , Leroy F , Guimbaud C , Laggoun-Défarge F . (2021). Response of peatland CO2 and CH4 fluxes to experimental warming and the carbon balance. Frontiers of Earth Science, 9 : 631368
CrossRef Google scholar
[24]
Liu S , Fang S X , Liu P , Liang M , Guo M R , Feng Z Z . (2021). Measurement report: Changing characteristics of atmospheric CH4 in the Tibetan Plateau: Records from 1994 to 2019 at the Mount Waliguan station. Atmospheric Chemistry and Physics, 21( 1): 393– 413
CrossRef Google scholar
[25]
Lv H G Wang H Y Jiang Y F Chen H N Qiao R Wang Z G ( 2015). Study on the concentration variation of CO2 in the background area of Xisha . Acta Oceanologica Sinica, 37(6): 21− 30 (in Chinese)
[26]
Pérez I A , Sánchez M L , García M Á , Pardo N . (2019). Sensitivity of CO2 and CH4 annual cycles to different meteorological variables at a rural site in Northern Spain. Advances in Meteorology, 2019 : 9240568
[27]
Qiao F L Yuan Y L Deng J Dai D J Song Z Y (2016). Wave-turbulence interaction-induced vertical mixing and its effects in ocean and climate models. Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences, 374( 2065): 2065.201
[28]
Qu T D , Song Y T , Yamagata T . (2009). An introduction to the South China Sea throughflow: Its dynamics, variability, and application for climate. Dynamics of Atmospheres and Oceans, 47( 1−3): 3– 14
CrossRef Google scholar
[29]
Saunois M , Bousquet P , Poulter B , Peregon A , Ciais P , Canadell J G , Dlugokencky E J , Etiope G , Bastviken D , Houweling S . . (2016). The global methane budget 2000–2012. Earth System Science Data, 8 : 697– 751
CrossRef Google scholar
[30]
Srivastava S , Lal S , Subrahamanyam D B , Gupta S , Venkataramani S , Rajesh T A . (2010). Seasonal variability in mixed layer height and its impact on trace gas distribution over a tropical urban site: Ahmedabad. Atmospheric Research, 96( 1): 79– 87
CrossRef Google scholar
[31]
Thomas G , Zachariah E J . (2012). Ground level volume mixing ratio of methane in a tropical coastal city. Environmental Monitoring and Assessment, 184( 4): 1857– 1863
CrossRef Google scholar
[32]
United Nations Environment Programme ( 2021). Global Methane Assessment: Benefits and Costs of Mitigating Methane Emissions. Nairobi: United Nations Environment Programme
[33]
Webster K D White J R Pratt L M ( 2015). Ground-level concentrations of atmospheric methane in southwest Greenland evaluated using open-path laser spectroscopy and cavity-enhanced absorption spectroscopy. Arctic, Antarctic, and Alpine Research, 47( 4): 599− 609
[34]
Wei C , Wang M H , Fu Q Y , Dai C , Huang R , Bao Q . (2019). Temporal characteristics of greenhouse gases (CO2 and CH4) in the megacity Shanghai, China: Association with air pollutants and meteorological conditions. Atmospheric Research, 235 : 104759
[35]
World Meteorological Organization ( 2019). Greenhouse Gas Bulletin: The State of Greenhouse Gases in the Atmosphere Based on Global Observations through 2018. Geneva: World Meteorological Organization
[36]
World Meteorological Organization ( 2020). Greenhouse Gas Bulletin: The State of Greenhouse Gases in the Atmosphere Based on Global Observations through 2019. Geneva: World Meteorological Organization
[37]
Wu Z H , Huang N E . (2009). Ensemble empirical mode decomposition: A noise-assisted data analysis method. Advances in Adaptive Data Analysis, 1( 01): 1– 41
CrossRef Google scholar
[38]
Wu Z H , Schneider E K , Kirtman B P , Sarachik E S , Huang N E , Tucker C J . (2008). The modulated annual cycle: An alternative reference frame for climate anomalies. Climate Dynamics, 31( 7): 823– 841
[39]
Zang K P Zhao H D Wang J Y Xu X M Huo C Zheng N ( 2013). High-resolution measurement of CH4 in sea surface air based on cavity ring-down spectroscopy technique: The first trial in China Seas . Acta Scientiae Circumstantiae, 33(5): 1362− 1366 (in Chinese)
[40]
Zhang K , Xu J L , Huang Q , Zhou L , Fu Q Y , Duan Y S , Xiu G L . (2020). Precursors and potential sources of ground-level ozone in suburban Shanghai. Frontiers of Environmental Science & Engineering, 14( 6): 92
[41]
Zhang M , Cheng Y Y , Bao Y , Zhao C , Wang G , Zhang Y L , Song Z Y , Wu Z H , Qiao F L . (2022). Seasonal to decadal spatiotemporal variations of the global ocean carbon sink. Global Change Biology, 28( 5): 1786– 1797
CrossRef Google scholar
[42]
Zhang M , Qiao F L , Song Z Y . (2017). Observation of atmospheric methane in the Arctic Ocean up to 87ºN. Science China. Earth Sciences, 60( 1): 173– 179
CrossRef Google scholar
[43]
Zhang M , Wu Z H , Qiao F L . (2018). Deep Atlantic Ocean warming facilitated by the deep western boundary current and equatorial Kelvin waves. Journal of Climate, 31( 20): 8541– 8555
CrossRef Google scholar
[44]
Zhang Y , Xiong X Z , Tao J H , Yu C , Zou M M , Su L , Chen L F . (2014). Methane retrieval from atmospheric infrared sounder using EOF-based regression algorithm and its validation. Chinese Science Bulletin, 59( 14): 1508– 1518
CrossRef Google scholar

Acknowledgements

This work was supported by the Basic Scientific Fund for National Public Research Institutes of China (No. 2018Q01), the Natural Science Foundation of Shandong Province (China) (No. ZR202102190358), the National Natural Science Foundation of China (No. 41821004), the international cooperation project on Indo-Pacific Ocean environmental variability and air-sea interactions (China) (No. GASI-IPOVAI-05), and the Aoshan Talents Cultivation Excellent Scholar Program supported by Qingdao National Laboratory for Marine Science and Technology (China) (No. 2017ASTCP-ES04).

Conflict of Interest

The authors declare that they have no conflicts of interest.

RIGHTS & PERMISSIONS

2022 Higher Education Press
AI Summary AI Mindmap
PDF(13477 KB)

Accesses

Citations

Detail

Sections
Recommended

/