Plastic pollution is one of the growing environmental problems in the world currently. The situation of microplastics (MPs) in the South China Sea (SCS) is not yet fully understood. This study investigated the spatial distribution, morphological characterization, and chemical composition of MPs in surface seawater in the southwestern SCS, based on cruise data in 2018. Our analysis shows that the average abundance of surface MPs in seawater was 0.072 ± 0.053 particles/m³ and 88.4% of MPs were <2 mm. 97.3% of MPs were fibers and fragments. Polyethylene terephthalate (PET), polyvinyl chloride (PVC), and cellophane were predominant polymer components of surface MPs. Higher MPs abundance (0.083 ± 0.063 particles/m³) and bigger MPs sizes were found at surface water in Nansha Islands than in Xisha Islands (0.032 ± 0.01 particles/m³). In addition, more polymer types of MPs were found in Nansha Islands, while more MPs films were found in Xisha Islands. PET and cellophane dominated in Nansha Islands, while PVC dominated in Xisha Islands with no cellophane detected. The surface MPs were low in abundance and diverse in polymers in the southwestern SCS with apparent differences between islands and between onshore and offshore, owing to plastics wastes from vessel traffics and some inhabited islands.

This paper uses the Argo sea surface salinity (SSS_Argo) before and after the passage of 25 tropical cyclones (TCs) in the Bay of Bengal from 2015 to 2019 to evaluate the sea surface salinity (SSS) of the Soil Moisture Active Passive (SMAP) remote sensing satellite (SSS_SMAP). First, SSS_Argo data were used to evaluate the accuracy of the 8-day SMAP SSS data, and the correlations and biases between SSS_SMAP and SSS_Argo were calculated. The results show good correlations between SSS_SMAP and SSS_Argo before and after TCs (before: SSS_SMAP = 1.09SSS_Argo−3.08 (R² = 0.69); after: SSS_SMAP = 1.11SSS_Argo−3.61 (R² = 0.65)). A stronger negative bias (−0.23) and larger root-mean-square error (RMSE, 0.95) between the SSS_SMAP and SSS_Argo were observed before the passage of 25 TCs, which were compared to the bias (−0.13) and RMSE (0.75) after the passage of 25 TCs. Then, two specific TCs were selected from 25 TCs to analyze the impact of TCs on the SSS. The results show the significant SSS increase up to the maximum 5.92 psu after TC Kyant (2016), which was mainly owing to vertical mixing and strong Ekman pumping caused by TC and high-salinity waters in the deep layer that were transported to the sea surface. The SSS_SMAP agreed well with SSS_Argo in both coastal and offshore waters before and after TC Roanu (2016) and TC Kyant (2016) in the Bay of Bengal.