AUTHOR=Guo Wen-Ning , Sun Qun , Wang Shuai-Qi , Zhang Zhi-Hao 

TITLE=Characterizing spatio-temporal variations of dimethyl sulfide in the Yellow and East China Sea based on BP neural network

JOURNAL=Frontiers in Marine Science

VOLUME=Volume 11 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2024.1394502

DOI=10.3389/fmars.2024.1394502

ISSN=2296-7745

ABSTRACT=Dimethyl sulfide (DMS), an organic volatile sulfide produced from Dimethylsulfoniopropionate (DMSP), exerts a significant impact on the global climate change. Utilizing published literature data spanning from 2005 to 2020, a BP neural network (BPNN) model of the surface seawater DMS in the Yellow and East China Sea(YECS) was developed to elucidate the influence of various marine factors on the DMS cycle. Resultsindicated that the six parameters inputted BPNN model, that include time month, latitude and longitude, sea-surface chlorophyll (Chl-a), sea-surface temperature (SST), and sea-surface salinity (SSS), yielded the optimized simulation results (R 2 =0.72). The optimized estimation of surface seawater DMS in YECS were proved to be closely aligned with the observed data across all seasons, which demonstrated the model's robust applicability. Surface seawater DMS concentration were found to be affected by multiple factors such as chlorophyll and SST. Comparative analysis of the three environmental parameters revealed that chlorophyll exhibited the most significant correlation with surface seawater DMS concentration in YECS (R 2 =0.20). This underscores the pivotal role of chlorophyll in phytoplankton photosynthesis and DMS production, emphasizing its importance as a non-negligible factor in the study of DMS and its sulfur derivatives. Furthermore, surface seawater DMS concentration in YECS exhibited positive correlations with Chl-a and SST, while displaying a negative correlation with SSS. Seasonal variations followed the pattern: summer>spring>autumn>winter (5.69>3.96>3.18>1.60 nmol/L). In the horizontal distribution, there was a gradual decrease of DMS concentration from the nearshore to the offshore, especially with the highest DMS concentration concentrated in the Yangtze River Estuary Basin and the south-central part of Zhejiang Province. Apart from being largely composed by the release of large amounts of nutrients from anthropogenic activities and changes in ocean temperature, the spatial and temporal variability of DMS may be driven by additional physicochemical parameters.