Variability in the relationship between light scattering and chlorophyll a concentration in oligotrophic tropical regions of the Western Pacific Ocean.

It is important to determine the relationship between the concentration of chlorophyll a (Chla) and the inherent optical properties (IOPs) of ocean water to develop optical models and algorithms that characterize the biogeochemical properties and estimate biological pumping and carbon flux in this environment. However, previous studies reported relatively large variations in the particulate backscattering coefficient (bbp(λ)) and Chla from more eutrophic high-latitude waters to clear oligotrophic waters, especially in oligotrophic oceanic areas where these two variables have little covariation. In this study, we examined the variability of bbp(λ) and Chla in the euphotic layer in oligotrophic areas of the tropical Western Pacific Ocean and determined the sources of these variations by reassessment of in-situ measurements and the biogeochemical-argo (BGC-Argo) database. Our findings identified covariation of bbp(λ) and Chla in the water column below the deep Chla maximum (DCM) layer, and indicated that there was no significant correlation relationship between bbp(λ) and Chla in the upper layer of the DCM. Particles smaller than 3.2 µm that were in the water column above the DCM layer had a large effect on the bbp(λ) in the vertical profile, but particles larger than 3.2 µm and smaller than 10 µm had the largest effect on the bbp(λ) in the water column below the DCM layer. The contribution of non-algal particles (NAPs) to backscattering is up to 50%, which occurs in the water depth of 50 m and not consistent with the distribution of Chla. Phytoplankton and NAPs were modeled as coated spheres and homogeneous spherical particles to simulate the bbp(λ) of the vertical profile by Aden-Kerker method and Mie theory, and the results also indicated that the backscattering caused by particles less than 20 µm were closer to the measured data when they were below and above the DCM layer, respectively. This relationship also reflects the bbp(λ) of particles in the upper water was significantly affected particle size, but bbp(λ) in the lower water was significantly affected by Chla concentration. This effect may have relationship with phytoplankton photoacclimation and the relationship of a phytoplankton biomass maximum with particle size distribution in the water column according to the previous relevant studies. These characteristics also had spatial and seasonal variations due to changes of Chla concentration at the surface and at different depths. There was mostly a linear relationship between Chla and bbp(700) during winter. During other seasons, the relationship between these two variables was better characterized by a power function (or a logarithmic function) in the lower layer of the DCM. The spatial and vertical relationships between the bbp(λ) and Chla and the corresponding variations in the types of particles described in this study provide parameters that can be used for accurate estimation of regional geochemical processes.

Climate change drives rapid decadal acidification in the Arctic Ocean from 1994 to 2020.

The Arctic Ocean has experienced rapid warming and sea ice loss in recent decades, becoming the first open-ocean basin to experience widespread aragonite undersaturation [saturation state of aragonite (Ωarag) < 1]. However, its trend toward long-term ocean acidification and the underlying mechanisms remain undocumented. Here, we report rapid acidification there, with rates three to four times higher than in other ocean basins, and attribute it to changing sea ice coverage on a decadal time scale. Sea ice melt exposes seawater to the atmosphere and promotes rapid uptake of atmospheric carbon dioxide, lowering its alkalinity and buffer capacity and thus leading to sharp declines in pH and Ωarag. We predict a further decrease in pH, particularly at higher latitudes where sea ice retreat is active, whereas Arctic warming may counteract decreases in Ωarag in the future.

Impact Mechanism of the Ecological Vulnerability of Highly Developed Islands Based on the Bayesian Network Model-Applied to the Changshan Islands.

Islands are one of the most sensitive interfaces between global changes and land and sea dynamic effects, with high sensitivity and low stability. Therefore, under the dynamic coupling effect of human activities and frequent natural disasters, the vulnerability of the ecological environment of islands shows the characteristics of complexity and diversity. For the protection of island ecosystems, a system for the assessment of island ecosystems and studies on the mechanism of island ecological vulnerability are highly crucial. In this study, the North and South Changshan Islands of China were selected as the study area. Considering various impact factors of island ecological vulnerability, the geographical information systems (GIS) spatial analysis, field surveys, data sampling were used to evaluate island ecological vulnerability. The Bayesian network model was used to explore the impact mechanism of ecological vulnerability. The results showed that the ecological vulnerability of the North Changshan Island is higher than that of the South Changshan Island. Among all the indicators, the proportion of net primary productivity (NPP) and the steep slope has the strongest correlation with ecological vulnerability. This study can be used as references in the relevant departments to formulate management policies and promote the sustainable development of islands and their surrounding waters.

Land subsidence of the Yellow River Delta in China driven by river sediment compaction.

Many of the world's largest deltas are sinking due to multiple natural and anthropogenic causes. This is particularly evident for the modern Yellow River Delta (YRD) in China, which is one of the most dynamic coastal systems on Earth. The YRD has experienced complicated patterns of accretion and erosion as well as significant compaction settlements. However, spatiotemporal variability and the long-term settlement rates law in this complex delta system remain poorly understood. Evidently, the surface settlement is supposedly controlled by a long-term natural compaction process of sediments. We first combined the Small Baseline Subset (SBAS) Interferometric Synthetic Aperture Radar (InSAR) method with a geotechnical model and geological, geomorphological, hydrogeological, and geotechnical data to assess the delta-wide long-term spatiotemporal settlement triggered by the consolidation and compaction of river sediments. The combination of satellite and field observations allows us to gain insights into the primary processes controlling surface movement. A total of seventy-five SAR images acquired by ERS and Envisat from 1992 to 2010 are used to generate three independent interferometric subsets calibrated with leveling to unveil spatiotemporal settlement variability. The densely distributed spatiotemporal measurements enable us to acquire the characteristics of the spatiotemporal variations of land movements. Moreover, the annual average settlement rates are observed within a range of 0 to >30 mm. Results suggest that the relative inland stability of the delta contrasts with the decreasing coastal margin trend at an average annual rate of 15 mm. Moreover, the variability is significantly correlated with the delta evolution and variations in subsoil architecture. A comparative analysis has also been conducted between time series InSAR measurements and the theoretical estimates of settlement derived from the geotechnical model. The strong agreement between the InSAR measurements and the geotechnical modeled results indicates that long-term settlement (in a decade-to-century scale) is primarily driven by the compaction of river sediments. The more the delta sub-lobe was newly formed, the more significant the settlement. Decreasing trends in annual settlement rates from approximately 70 mm to 0 mm in the long-term deposit compaction process are also identified. These findings are useful to understand the YRD morphological evolution and may provide insights into the changes in other deltas worldwide.

A Universal Approach to Aqueous Energy Storage via Ultralow-Cost Electrolyte with Super-Concentrated Sugar as Hydrogen-Bond-Regulated Solute.

Aqueous energy-storage systems have attracted wide attention due to their advantages such as high security, low cost, and environmental friendliness. However, the specific chemical properties of water induce the problems of narrow electrochemical stability window, low stability of water-electrode interface reactions, and dissolution of electrode materials and intermediate products. Therefore, new low-cost aqueous electrolytes with different water chemistry are required. The nature of water depends largely on its hydroxyl-based hydrogen bonding structure. Therefore, the super-concentrated hydroxyl-rich sugar solutions are designed to change the original hydrogen bonding structure of water. The super-concentrated sugars can reduce the free water molecules and destroy the tetrahedral structure, thus lowering the binding degree of water molecules by breaking the hydrogen bonds. The ionic electrolytes based on super-concentrated sugars have the expanded electrochemical stability window (up to 2.812 V), wide temperature adaptability (-50 to 80 °C), and fair ionic conductivity (8.536 mS cm-1 ). Aqueous lithium-, sodium-, potassium-ion batteries and supercapacitors using super-concentrated sugar-based electrolytes demonstrate an excellent electrochemical performance. The advantages of ultralow cost and high universality enable a great practical application potential of the super-concentrated sugar-based aqueous electrolytes, which can also provide great experimental and theoretical assistance for further research in water chemistry.

[Temporal mixture analysis application in monitoring the Antarctic sea ice concentration variability].

Temporal mixture analysis (TMA) is deduced from spectral mixture analysis (SMA). They are algebraically identical except for that TMA is applied to temporal spectra and thus can extract the temporal characteristics of features. The ice concentration is diverse across the Antarctic sea through different periods, and TMA has a great potential to obtain this variability as an environmental normal. In the present study, sea ice concentration data remotely sensed by AMSR-E from 2003 to 2010 were used and seven typical endmembers were captured, standing for temporally different sea ice classification. TMA can also be utilized in change analysis of Antarctic sea ice concentration for its capability to record the spatial distribution of temporal characteristics, allowing further study of regional or global climatic variations. In short, TMA supplies a new method for researchers to investigate the spatial and temporal variability of polar sea ice.

[The arctic sea ice refractive index retrieval based on satellite AMSR-E observations].

The refractive index of sea ice in the polar region is an important geophysical parameter. It is needed as a vital input for some numerical climate models and is helpful to classifying sea ice types. In the present study, according to Hong Approximation (HA), we retrieved the arctic sea ice refractive index at 6.9, 10.7, 23, 37, and 89 GHz in different arctic climatological conditions. The refractive indices of wintertime first year (FY) sea ice and summertime ice were derived with average values of 1.78 - 1.75 and 1.724 - 1.70 at different frequencies respectively, which are consistent with previous studies. However, for multiyear (MY) ice, the results indicated relatively large bias between modeled results since 10.7 GHz. At a higher frequency, there is larger MY ice refractive index difference. This bias is mainly attributed to the volume scattering effect on MY microwave radiation due to emergence of massive small empty cavities after the brine water in MY ice is discharged into sea. In addition, the retrieved sea ice refractive indices can be utilized to classify ice types (for example, the winter derivation at 89 GHz), to identify coastal polynyas (winter retrieval at 6.9 GHz), and to outline the areal extent of significantly melting marginal sea ice zone (MIZ) (summer result at 6.9 GHz). The investigation of this study suggests an effective tool of passive microwave remote sensing in monitoring sea ice refractive index variability.