Mangroves, coastal salt marshes and seagrass beds, as the typical coastal blue carbon ecosystems, have been widely recognized for their remarkable capacity in carbon storage. Vegetation carbon pool and sediment (or soil) carbon pool were considered to be the major carbon pools within the coastal blue ecosystems and their variations determined the overall carbon sequestration of the ecosystems. From a perspective of carbon pool interactions, this study summarized the previous research work based on literature review, including the interactions within various vegetation carbon pools and within various sediment carbon pools, as well as the interactions between vegetation and sediment carbon pools. Interspecific competition, allochthonous carbon input and biogeomorphology were found to be the key to understand the carbon pool interactions. Finally, a perspective on the current state-of-the-art of blue carbon pool study is offered, with challenges and suggestions for future directions.
Costal ocean receives a bunch of carbon materials and nutrients from terrestrial sources, relates a lot of carbon-involving interactions. Meanwhile, it is normal that sedimentary reservoir-cap systems with good trap conditions beneath coastal ocean, these entrapments have potentials to storage CO2. This review focuses on the coastal ocean as the research object, and introduces the carbon cycle processes in coastal ocean, their factors which could influence CO2 fluxes in the carbon cycle processes, and the potential carbon storage mechanisms of the coastal marine sedimentary basins. From the perspective of “carbon peaking and carbon neutrality”, the significance of coastal oceans for “Ocean Negative Carbon Emission (ONCE)”, its potential promotion paths, carbon storage potentials in sedimentary basins and the problems faced by coastal oceans are discussed. Overall, the costal ocean is one of the important blue carbon sink areas. In the coastal marine seawater system, improving the reaction efficiency of microbial carbon pump and carbonate carbon pump have positive significance for CO2 negative emissions; The suitable reservoir-cap systems for CO2 storage beneath coastal ocean can not only provide extra spaces, but also guarantee the safety for CO2 storage. In the future, the main research directions should be to inhibit the conversion process of carbon materials to CO2 in coastal oceans and ensure the safety of CO2 storage in sedimentary reservoirs, these could provide theoretical basis and technical guarantee for CO2 negative emissions.
Carbon stock variation observation forms the basis for coastal saltmarsh blue carbon sink accounting. In order to accurately estimate the carbon sequestration rate of coastal saltmarshes over a short-term scale (seasonal to annual), this study carried out field observations and sample collections within a coastal saltmarsh on the south bank of Hangzhou Bay, covering different seasons of 2022. This study was primarily based on high-resolution surface monitoring by Surface Elevation Table (SET) systems. The results revealed a seasonal plant growth pattern between March and September for both the native species Scirpus mariqueter and the exotic species Spartina alterniflora. In terms of belowground biotic carbon stock changes, over the growing season, the carbon stock increase for Scirpus mariqueter reached 11 g C·m-2 whilst this value was 56 g C·m-2 for Spartina alterniflora. The SET data indicated a sedimentation rate of 13.02 cm·a-1 within the Spartina alterniflora saltmarsh, higher than that of the Scirpus mariqueter saltmarsh, 12.30 cm·a-1. Calculating the sedimentation rate data with sediment bulk density and organic carbon content, the sediment carbon accumulation rate of Scirpus mariqueter saltmarsh was estimated to be 460 g C·m-2·a-1, lower than 588 g C·m-2·a-1 of the Spartina alterniflora saltmarsh. Combining the biotic carbon stock increase and sediment carbon stock increase, the carbon sequestration rate for the Spartina alterniflora saltmarsh was found to be 644 g C·m-2·a-1, higher than the value of Scirpus mariqueter saltmarsh, 471 g C·m-2·a-1. Thus, the difference in carbon sequestration abilities of native and exotic species should be considered for future coastal blue carbon management.
Marine gas hydrate deposits are significant temporal reservoirs for hydrocarbons migrating from deep sources. This is crucial to our understanding of ocean carbon cycling. The cold seep, a geological process regarding gas leakage from deep or shallow sources, is usually linked with gas hydrate decomposition. In this thesis, we reviewed the latest applications of in situ monitoring and detecting methods regarding the leakage plumes, migration pathways, and seafloor geomorphologies associated with gas hydrate and cold seep systems, primarily including vessel-and land-based gas plume measurements, surface ocean-lower atmosphere hydrocarbon emission detections, seafloor visualization techniques, and in situ observation networks. The integrated applications of these in situ observation methods provide a nuanced view of the temporal and spatial variability of hydrate and cold seep systems, facilitate understanding of the fate of hydrocarbons, and expand our knowledge of cold-seep biota in a watery desert.
The monitoring of carbon flux dynamics and assessment of carbon sink functions of island forest ecosystems are rarely reported due to their special geographical location and few data sources. In this study, the forest ecosystem of the Nanji Island was used as the research object, the carbon sink potential of island forests and their driving factors were assessed. Based on eddy correlation techniques, the temporal variation characteristics and driving factors of net ecosystem productivity (NEP), gross primary productivity (GPP), and ecosystem respiration (Reco) from 2020 to 2021 were explored. Results showed that the forest ecosystem of Nanji Island was carbon sink. Net CO2 uptake in 2020 and 2021 were 516 g C·m-2·a-1 and 598 g C·m-2·a-1, Reco were 1 037 g C·m-2·a-1 and 1 646 g C·m-2·a-1, and GPP were 1 552 g C·m-2·a-1 and 2 244 g C·m-2·a-1, respectively. Total solar radiation (Rg), photosynthetically active radiation (PAR), net radiation (Rn) and sensible heat (H) were significantly and positively correlated with NEP and GPP (p≤0.001); air temperature (Tair) and soil temperature (Tsoil) were significantly and positively correlated with Reco(p≤0.001). The photosynthesis time of Nanji Island forest was longer than the carbon sink time on the daily scale. When Tair reached 10.05-27.76 ℃ and PAR reached 110.47-429.44 μmol·m-2·s-1, the photosynthesis intensity of island forest was higher than that of ecosystem respiration, which showed CO2 absorption. The monitoring and assessment of carbon fluxes in the forest ecosystems of Nanji Island will provide an important theoretical support for the establishment of a dynamic monitoring and assessment management system for blue carbon in China.
Mangroves, salt marshes, and seagrass beds are known as the three major coastal blue carbon ecosystems (CBCEs), which play important roles in marine biodiversity maintenance, water purification, nutrient recycling, carbon sequestration and storage. Guangdong Province and Guangxi Zhuang Autonomous Region in China, where the CBCEs are widely distributed, were selected as the research areas, to investigate the spatial relationship between CBCEs and the marine ecological redlines (MERs). The CBCE conservation gap was analyzed, and the recommended priority conservation areas outside the MERs were proposed. The CBCE distribution data obtained from the satellite images in 2019, combined with field survey and UAV remote sensing data collected during 2020 and 2021 showed that the CBCEs in Guangdong totaled 14 481.39 hm2 (mangroves 11 928.87 hm2, salt marshes 1 258.00 hm2, seagrass beds 1 294.52 hm2), whereas the CBCEs in Guangxi totaled 11 751.30 hm2 (mangroves 10 171.70 hm2, salt marshes 1 450.36 hm2, seagrass beds 129.24 hm2). 62.13% of the CBCEs in Guangdong and 59.88% in Guangxi were covered by the MERs. The distribution areas and protection ratios of mangroves and seagrass beds in Guangdong were both larger than those in Guangxi, while the distribution area and protection ratio of salt marshes in Guangxi were larger than that in Guangdong. As to the 3 types of CBCEs in Guangdong, 62.13% of the mangroves, 38.16% of the salt marshes and 85.41% of the seagrass beds were under protection. For the CBCEs in Guangxi, 61.44% of the mangroves, 49.58% of the salt marshes and 52.99% of the seagrass beds were protected. This research suggests the coast from Rongmujiang Bay to Maowei Sea, the areas of Tieshan Bay, Leizhou Bay, Zhelin Bay and other related locations as the recommended priority conservation areas outside the MERs.
Coastal bays are greatly affected by human activities and natural changes, and the influence mechanism of variation in seawater carbon source and sink patterns is extremely complex. Due to the small spatial scale of the bay, it is necessary to use wide-bands high-spatial resolution satellite remote sensing for monitoring the air-sea CO2 flux. Compared with the traditional kilometer-level ocean color satellite data, the retrieval of the sea surface partial pressure of CO2 (pCO2), the key parameter to calculate air-sea CO2 flux, is extremely challenging in small-scale bays. Taking Xiangshan Bay in Zhejiang Province in autumn as an example, a satellite retrieval algorithm for sea surface pCO2 was proposed based on the in situ pCO2 data and Sentinel-2 satellite images in the past five years, using the machine learning method of support vector machine (SVM). The algorithm validation results showed a good performance with R2 of 0.92 and RMSE of 23.23 μatm, and the satellite-derived results were consistent with the in situ values. On this basis, the satellite products of pCO2 in Xiangshan Bay in autumn from 2017 to 2021 (September to November) were produced. The results revealed that the pCO2 of Xiangshan Bay showed a decreasing trend from the top of the bay to the mouth of the bay, with an average value of 514.56 μatm, of which the average pCO2 in the inner bay was 551.94 μatm and the average pCO2 in the outer bay was 477.19 μatm, which implied that Xiangshan Bay was a source of atmospheric CO2 as a whole. There was no significant trend change of pCO2 in autumn in the past five years. Combined with the analysis of in situ data of multiple parameters, it was found that the sea surface pCO2 of autumn in Xiangshan Bay in 2021 was jointly regulated by physical mixing and biological activities. Sea surface temperature (SST) had a good positive correlation with pCO2, which was mainly reflected by the thermodynamic equilibrium of carbonate system. In addition, the normalized pCO2(NpCO2) with average temperature had a good negative correlation with seawater salinity and dissolved oxygen saturation. The relationship between NpCO2 and salinity resulted from the exchange of sea water inside the bay and offshore coastal water under tidal effect. Long-time series satellite data analysis also confirmed that sea surface pCO2 had a relatively consistent trend with the average tide height inside and outside the bay, and this trend was stronger in the outside bay than that in the inner bay. In this study, a set of pCO2 remote sensing retrieval methods in the small-scale bay was constructed, which laid a good foundation for the subsequent long-time series satellite monitoring of sea-air CO2 fluxes.
Tidal flat is an important part of coastal wetland, and is of great significance for blue carbon. Remote sensing is the most widely used method for tidal flat monitoring, but due to the influence of tides, the area of tidal flat extracted by remote sensing is often greatly underestimated. In this study, Sentinel-2 satellite images from 2016 to 2021 were used to extract the instantaneous area of tidal flats in Yueqing Bay, and the quantitative relationship between tidal flats area and tidal level or the tidal level correction model for tidal flats area was established. On this basis, Landsat satellite images in 7 years from 1988 to 2020 were selected to extract the instantaneous tidal flat area, and the established correction model was used to obtain the corrected multi-year tidal flat area at low tide level, and the change of tidal flat area in Yueqing Bay in recent 30 years and the main driving factors were analyzed. In recent 30 years, the tidal flat area of Yueqing Bay showed a trend of significant increase from 1988 to 1994, sharp decrease from 1994 to 2010, slight increase from 2010 to 2015, and decrease again from 2015 to 2020. The development and utilization of tidal flat by human activities is the main driving factor of tidal flat area change in Yueqing Bay.
Using Argo measured data combined with satellite remote sensing data and moored buoy data, the upper ocean temperature and salinity response caused by super typhoon Rammasun in 2014 was analyzed and studied. The result shows that super typhoon Rammasun resulted in cooling of sea surface temperature and deepening of mixing layer. Meanwhile, mixing length and vertical velocity induced by typhoon were calculated in this research, which explained the causes of temperature changes in the subsurface layer. Strong mixing and weak upwelling led to warming of the subsurface layer, whereas weak mixing and strong upwelling led to cooling of the subsurface layer. Compared with the change of temperature, the response of salinity was more complex. Precipitation first caused the decrease of surface salinity, and then vertical mixing led to a large increase of surface salinity. However, the effect of precipitation could greatly inhibit this process. After the typhoon departed, the vertical mixing was weakened, and the salinity was greatly reduced because of the heavy precipitation, it was even lower than that before the typhoon.
Taking Dazhuzhi Island (Dongtou, Wenzhou) as the research area, UAV equipped with multispectral sensors was used to acquire high-resolution remote sensing images, the optimal spectral band combination was selected to classify the island vegetation, and the vegetation types was divided into arbors, shrubs and herbs by supervised classification. The accuracy of vegetation classification was 99.72%, and the Kappa coefficient was 0.995 4. The spatial distribution of dominant species of arbors and shrubs was obtained by using the deep convolutional neural network (the precision rate was 0.79), and combined with the biomass equations, the spatial distribution of the biomass of dominant species of arbors and shrubs was inversed (arbors’ R2=0.97, shrubs’ R2=0.99). The biomass inversion equations of 3 shrub dominant species (Ficus erecta, Mallotus japonicas, and Eurya emarginata) were constructed by field sampling, and the other dominant species biomass inversion equations were obtained from literature. Based on the biomass and spatial distribution of dominant species, the carbon storage of arbors and shrubbys was 300.36 t and 47.59 t, respectively. Using normalized difference vegetation index (NDVI) to invert the spatial distribution of herb biomass (R2=0.99), combined with the biomass equation of the dominant herb species (Zoysia sinica) constructed from the measured data, the carbon storage of herbs was 21.59 t on Dazhuzhi Island.
Tidal current energy is the kinetic energy carried in the horizontal movement of tidal water, which has great development prospects. Accurate simulation and characterization of regional tidal currents can help to efficiently evaluate the spatial and temporal distribution of tidal energy resources, which is the key to the development and utilization of tidal current energy resources. In this paper, a high-resolution numerical model of tidal currents is constructed by applying FVCOM ocean model in Zhoushan sea area where has rich tidal current energy, and the reliability of the model is confirmed by tidal level and current verification. According to the simulation results, six waterways with dense tidal current energy resources in the Zhoushan sea area were identified, among which the average energy density of Xihoumen waterway, Cezi waterway and Taohuagang waterway exceeds 2.0 kW/m2, and the maximum energy density exceeds 20 kW/m2, and the flow speed over 1.0 m/s of the whole month is more than 80%. During tidal current ebb and flow, the reflow is dominant, while the asymmetry and rotation of tidal current are low. The flow stability coefficient is more than 0.98, so it is more suitable for the development and utilization of tidal current energy than other three waterways. The best location for tidal current energy development in these three waterways was then determined by calculating the significant hours and available hours, and the corresponding exploitable tidal current energy resources were evaluated using the Farm method, which were 27.53 MW, 39.96 MW, and 130.26 MW, respectively.