Coastal Nuclear Power Plants Research Articles

Numerical modelling of radionuclide uptake by bluefin tuna along its migration routes in the Mediterranean Sea after a nuclear accident

A numerical model which simulates the adsorption of radionuclides by migrating bluefin tuna in the Mediterranean Sea is described, in order to determine the level of contamination of these fish after a hypothetical nuclear accident and thus be able to assess the possible impact on human consumption. A 4–species foodweb model is incorporated into a Lagrangian model describing physical transport (advection, mixing, radioactive decay and interactions of radionuclides with sediments). Tuna is the last trophic level in the foodweb model and the equation providing the temporal evolution of radionuclide concentration in its flesh is solved along the fish trajectories, which were obtained through electronic tagging of fishes. The model was applied to the western Mediterranean, where several worst–case hypothetical accidents were simulated, both from a coastal nuclear power plant and from a vessel. Resulting 137Cs concentrations in migrating tuna were similar, or slightly higher, than reported background concentrations in these fishes and well below established safety levels. Maximum calculated concentrations in tuna flesh is in the order of 1 Bq/kg (wet weight). This is due to the rapid movement of the fishes, which spend only limited time over the most contaminated spots.

Key environmental parameters and numerical prediction model of jellyfish bloom in Qingchuan Bay Nuclear Power Plant, China

In recent years, there has been a notable increase in cooling water intake blockage caused by marine organism blooms at coastal nuclear power plants worldwide, resulting in shutdowns of nuclear power plants and large economic losses. A sizable portion of these incidents were caused by blooms from jellyfish, a planktonic invertebrate with a unique growth pattern. Suitable external conditions are conducive to the rapid growth of jellyfish, and blooms can occur within a few days. In order to better predict jellyfish bloom and enable nuclear power plants to prepare for it in advance, this study explores the numerical relationship between jellyfish biomass and environmental parameters. A series of time windows (evaluation intervals) were defined and constructed by a time-series recursive approach, which solved the problem of poor correlation between jellyfish biomass and environmental parameters at non-bloom points. The optimal time window length D = 10 was obtained, and the key environmental parameters affecting jellyfish biomass were screened as sea surface temperature, salinity, voltage value, dissolved oxygen, and chlorophyll. According to the ADF and KPSS tests, the key parameters have no significant time dependence, which ensures the stability and reliability of the subsequent predictions. The jellyfish bloom prediction model was derived by calculating the score F through the recursive Principal Component Analysis of the key environmental parameter in the time interval preceding the prediction point. The sudden change moments of score F correspond well to the jellyfish bloom moments, and the sudden change moments are all advanced for a period of time compared to the bloom time, which can provide valuable time for the nuclear power plant to organize manpower to deal with the blockage. Finally, a maximum score F threshold model was proposed to be coupled with the jellyfish bloom prediction model to provide a more robust basis for early warning of jellyfish at nuclear power plants.

The Thermal Effects of Coastal Nuclear Power Plant Thermal Discharge on Two Fish Species Based on the Probabilistic Frequency of Temperature Increment

This study selected Trachinotus ovatus and Nibea albiflora as the focal subjects to investigate the impacts of probabilistic frequency of temperature increment through laboratory simulations that mimicked the seasonal water elevated temperature adjacent to two coastal nuclear power plants. This research was underpinned by the probabilistic analysis of temperature increase frequencies, aiming to evaluate the thermal tolerance of these species across different seasonal contexts. Results demonstrated that the T. ovatus did not exhibit mortality in the spring, autumn, and winter. Mortality in T. ovatus occurred only during the summer in temperature-duration probability experimental groups subjected to 8.5ºC above ambient temperature with exposure probabilities of 50%, 75%, and 100%. The average survival rates were (93.3±3.3) %, (93.3±5.1) %, and (86.7±2.9) % respectively. The N. albiflora experienced mortality in spring, summer, autumn, and winter, with the highest mortality rate in summer. Compared to N. albiflora, T. ovatus exhibited significantly higher thermal tolerance across all seasons. As the experimental temperature increased and the duration probability rose, the mortality rates of both fish species showed an upward trend. There was an interaction between elevated temperature and duration probability, with the duration of different elevated temperature amplitudes significantly impacting the fish’s survival rates.

Integrated monitoring and prediction of thermal discharge from nuclear power plants using satellite, UAV, and numerical simulation.

Global nuclear power is surging ahead in its quest for global carbon neutrality, eyeing an anticipated installed capacity of 436 GW for coastal nuclear power plants by 2040. As these plants operate, they emit substantial amounts of warm water into the ocean, known as thermal discharge, to regulate the temperature of their nuclear reactors. This discharge has the potential to elevate the temperature of the surrounding seawater, potentially influencing the marine ecosystem in the discharge vicinity. Therefore, our study area is on the Qinshan and Jinqimen Nuclear Power Plants in China, employing a blend of Landsat 8/9, and unmanned aerial vehicle (UAV) imagery to gather sea surface temperature (SST) data. In situ measurements validate the temperature data procured through remote sensing. Leveraging these SST observations alongside hydrodynamic and meteorological data from field measurements, we input them into the MIKE 3 model to prognosticate the three-dimensional (3D) spatial distribution and temperature elevation resulting from thermal discharge. The findings reveal that (1) satellite remote sensing can instantly acquire the horizontal distribution of thermal discharge, but with a spatial resolution much lower than that of UAV. The spatial resolution of UAV is higher, but the imaging efficiency of UAV is only 1/40,000 of that of satellite remote sensing. (2) Numerical simulation models can predict the 3D spatial distribution of thermal discharge. Although UAV and satellite remote sensing cannot directly obtain the 3D spatial distribution of thermal discharge, using remotely sensed SST as the temperature field input for the MIKE 3 model can reduce the quantity of measured temperature data and lower the cost of numerical simulation. (3) In the process of monitoring and predicting the thermal discharge of nuclear power plants, achieving an effective balance between monitoring accuracy and cost can be realized by comprehensively considering the advantages and costs of satellite, UAV, and numerical simulation technologies.

Improved Design and Economic Estimation of Cold-End Systems for Inland Nuclear Power Plants

Improved Design and Economic Estimation of Cold-End Systems for Inland Nuclear Power Plants

Responses of microeukaryotic community structure to a Phaeocystis globosa bloom in a semi-enclosed subtropical bay

The occurrence of Phaeocystis globosa, a harmful algal bloom species in Chinese coastal waters, has significant impacts on marine organisms and poses a threat to the safety of coastal nuclear power plants. Although previous studies have established a close association between P. globosa blooms and the bacterial community, the relationship between the microeukaryotic community and P. globosa blooms remains poorly understood. In this study, the variations in the microeukaryotic community resulting from a P. globosa bloom were analyzed using 18S rRNA gene amplicon sequencing. The results indicated that the diversity of the microeukaryotic community during the bloom phase was significantly higher than that during the dissipation phase. The microeukaryotic community compositions varied significantly between the two phases of the P. globosa bloom. During the bloom phase, the dominant microeukaryotic was Viridiplantae, which was then replaced by Dinoflagellata during the dissipation phase. Co-occurrence network analysis showed that the relationship among the microeukaryotic community during the bloom phase was more complex than that during the dissipation phase, and the keystone taxa varied as the bloom progressed. Additionally, microeukaryotic community assembly was primarily driven by stochastic processes during the bloom phase based on the β-nearest taxon distance, whereas it was driven by both deterministic processes and stochastic processes during the dissipation phase. Overall, our findings provide novel insight into the mechanisms and interactions involved in microeukaryotic community dynamics in environments disturbed by P. globosa blooms.

Elimination of uranium pollution from coastal nuclear power plant by marine microorganisms: Capability and mechanism

Uranium is one of the sensitive radionuclides in the wastewater of nuclear powers. Due to the fact that nuclear powers are mainly located in coastal areas, the elimination of uranium (U(VI)) pollution from coastal nuclear power is ultimately rely on marine microorganisms. The fixing of U(VI) on V. alginolyticus surface or converting it into sediments is an effective elimination strategy for U(VI) pollution. In this work, typical marine microorganism V. alginolyticus was used to evaluate the elimination of U(VI) pollution by marine microorganisms. Effects of solution conditions (such as pH, temperature, and bacterium concentrations) on the physicochemical properties and elimination capabilities of V. alginolyticus were studied in detail. FT-IR, XPS and XRD results reveal that COOH, NH2, OH and PO4 on V. alginolyticus were main functional groups for U(VI) elimination and formed (UO2)3(PO4)2·H2O. The elimination of U(VI) by V. alginolyticus includes two stages of adsorption and biomineralization. The theoretical maximum adsorption capacity (Cs,max) of V. alginolyticus for U(VI) can reach up to 133 mg/g at pH 5 and 298 K, and the process reached equilibrium in 3 h. Results show that V. alginolyticus play important role in the elimination of U(VI) pollution in seawater.

Impact of a nuclear power station effluent on marine forests: A case study in SE Brazil and insights for global warming scenarios

One of the main disturbances caused by coastal nuclear power plants is the discharge of thermal effluents capable of affecting a number of marine systems, including macroalgal forests that support key ecosystem services such as carbon uptake, fisheries increment and coastal protection. This study aimed at describing the long-term trend (1992–2022) in the abundance of Sargassum forests from sites located inside and outside areas affected by the thermal effluent discharged by the Brazilian Nuclear Power Station (BNPS) and at evaluating the relationship between Sargassum cover and seawater temperature. This information is interesting to provide insights on whether and how Sargassum populations would likely be affected by increasing temperature due to climate change. We detected a long-term decline in Sargassum cover inside, but not outside the area affected by the BNPS thermal plume. Mean summer surface seawater temperature above 30 °C was identified as an important factor driving the decline of Sargassum abundance. This study highlights the impact caused by decades of discharge of the BNPS thermal effluent on Sargassum forests, which leads to predict the likely disappearance of marine forests under a climate change scenario in other sites situated in warm temperate regions.

Marine ecological restoration strategies of coastal nuclear power plants in China

Low-carbon and green development model is the choice for responding to climate change. Under the dilemma between ever-growing energy demand and the associated environmental issues, nuclear power is one of the low-carbon and high-efficient energy options which compared to wind power and solar power. It is the only stable power source that can replace fossil energy on a large scale at present and even in the future. This paper briefly describes the operational risks of coastal nuclear power plants (CNPPs) and the upgrade process of nuclear reactors, systematically analyzes and summarizes the ecological environment problems, risk problems and ecological restoration and protection strategies in the construction and operation of CNPPs, including coastal wetland ecological environment, marine ecological environment, and the risk prevention measures for cooling water source. The results show that ecosystem restoration by human does not make up for the weakening of the ecological carrying capacity and ecosystem away from its baseline, nonetheless, the restoration of important wetland habitats is conducive to the improvement of the functions of key marine ecosystems and the maintenance of marine biodiversity.

Early warning and monitoring of the safety risk of coastal nuclear power plant cold source under the stress from Phaeocystis globosa blooms

Context In recent years, Phaeocystis globosa has become a typical red tide species in the Beibu Gulf, posing a safety hazard to the cold-water intake system of the Guangxi Fangchenggang Nuclear Power Plant. Aims To establish an effective early risk-warning monitoring and ensure the safety of nuclear power plant cold-water intakes. Methods In this study, a multifactor and multilevel early risk-warning monitoring system was established using the early warning idea of ‘risk grading’. Key results The results showed that this method can analyse the influence trend of marine-environment changes on the growth of P. globosa and improve the timeliness of early warning and forecasting. Conclusions The method established in this paper can effectively guide coastal nuclear power enterprises to conduct early risk warning and monitoring of P. globosa and improve the accuracy of early warning and forecasting. Implications The methed is of great significance to coastal nuclear power enterprises dealing with red tide disasters caused by P. globosa blooms.

Scenarios of temporal environmental alterations and phytoplankton diversity in a changing bay in the East China Sea

In the context of global change, the stressors of warming and eutrophication have significant ecological implications in coastal waters. In order to examine the diversity of phytoplankton and its relationship with water quality, we conducted a survey of phytoplankton community compositions and their correlation with environmental changes over four seasons in a eutrophic bay located in the East China Sea. Through a systematic analysis, we identified diatoms and dinoflagellates as the primary dominant groups, with the species Skeletonema costatum, Skeletonema marinoi, Biddulphia sinensis, Thalassiosira eccentrica, Leptocylindrus danicus, Coscinodiscus oculus-iridis, Coscinodiscus jonesianus, and Chaetoceros knipowitschi as the most abundant species in all seasons. Significant seasonal alterations were observed in both environmental settings and phytoplankton species richness, dominance, and abundance. The phytoplankton community varied in its response to diverse aquatic environments and was principally affected by temperature, silicic acid concentrations, and suspended solids. Elevated temperatures were found to promote an increase in phytoplankton abundance. However, no clear evidence of diatom and dinoflagellate succession in relation to N:P ratio was observed across seasons. Water quality analysis illustrated that the majority of the study area exhibited a mid-eutrophic with severe organic pollution. The abundance of phytoplankton was significantly influenced by eutrophication and organic pollution. The accelerated warming process related to coastal nuclear power plants and nutrient regime alterations significantly affect the temporal shift of the phytoplankton community. These findings contribute valuable insights into the effects of eutrophic environments on the structure of phytoplankton communities in coastal aquatic systems.

Statistical and hydrodynamic numerical modeling to quantify storm surge hazard: Comparison of approaches applied to U.S. North Atlantic coast

Estimating the storm surge magnitude and annual exceedance probability is a key element in the siting and design of coastal nuclear power plants in both the U.S. and France. However, differences in storm climatology, specifically the relative importance of tropical cyclones (TCs) versus extratropical storms (XTCs), have driven differences in estimation method development. This work compares purely statistical modeling with combined statistical and numerical simulation modeling approaches for extreme storm surge applied to the U.S. North Atlantic coast which is subject to both tropical and extratropical storms. Two frequency analysis methods are applied to observed water levels and compared to a copula-based joint probability analysis of TCs and automated frequency analysis of XTCs that is enriched with numerically simulated storms. One frequency analysis method is applied using (1) hourly at-site data and (2) hourly at-site data enriched with additional data from a homogeneous region. The other frequency analysis method is applied using (1) hourly at-site data and (2) hourly at-site data enriched with monthly water level maxima. Variables of interest used in the comparison are skew storm surge, maximum instantaneous storm surge, non-tidal residual and maximum seal level. The performance of the methods (mean surge and water level estimates and confidence intervals) depend on the variable of interest and, to some extent, on return period. Inclusion of additional information (e.g., regional water levels, and monthly maxima) in the frequency analysis methods does not have a large impact on estimated mean surge and water levels, but significantly reduces resulting confidence intervals (over 40% reduction in some cases). However, the confidence intervals still grow with increasing return period. Inclusion of simulated storms in the joint probability analysis results in significantly different mean surge and water level estimates (up to 25% higher than the frequency analysis in some cases). The joint probability analysis confidence intervals are wider than those for the frequency analysis methods lower return periods (e.g., 60%–80% wider at 100 years), but they grow much more slowly and are significantly narrower for higher return periods (e.g., 40%–60% narrower at 1 000 years). Although there are appreciable differences between the results documented in this paper, these are reasonable due to differences in the data and methods used in this comparison.

Research on the influence law of submerged depth and flow rate of diversion canal on free surface vortex in coastal nuclear power plant

In this paper, the impact of flow and submerged depth of diversion canal on free surface vortex is studied by numerical simulation and experiment of water and gas two-phase flow. It can be seen from the calculation results that the lower the submerged depth or the higher the flow, the stronger the vortex intensity on the free surface. The strong vorticity and air content in water will lead to uneven flow in the elbow canal, affecting the stable operation of the circulating pump. According to the results of simulation and experiment, the numerical value of vortex type on the free surface is expressed as a function of flow rate and submerged depth. This function can be utilized to predict the submerged depth limit of diversion canals in coastal nuclear power plants, which provides a favorable guarantee for the stability of circulating pump operation and the economy of pump room construction.

Meta-analysis of the thermal pollution caused by coastal nuclear power plants and its effects on marine biodiversity

The rise in seawater temperature due to industrial activities is one of the main threats to marine biodiversity. In nuclear power plants, large volumes of water are used for their operation, returning to the ecosystem at higher temperatures. A global meta-analysis was performed to evaluate the thermal effects caused by coastal nuclear power plants on marine organisms. We found 853 articles of which, 99 were included in the qualitative analysis and 75 in the meta-analysis. The meta-analysis showed an increase of 4.38 °C in water temperature near the outfall, and the temperature variation of each study was found to be associated with the power plant latitudes. The main effects on organisms were related to changes in the structure and composition of aquatic communities, with species abundance, distribution, dominance, and density being the most cited ones. Among the affected groups, photosynthesizing microorganisms were the most cited, potentially contributing to shifts in ecosystem dynamics.

Synergistic effects of warming and low salinity enhanced the production of Gracilariopsis lemaneiformis in the warming drainage zone of Tianwan Nuclear Power Plant, China

Tianwan Nuclear Power Plant in China is the world's largest coastal nuclear power plant in terms of its total installed capacity both in operation and under construction. Its operations create a warming drainage zone that is potentially beneficial to the large-scale cultivation of macroalgae. Moreover, natural freshwater river flow and ocean acidification caused by increasing levels of atmospheric CO2 bring new uncertainties to the growth and photophysiology of commercial macroalgae. In this study, two CO2 concentrations (LC, 400 μatm; HC, 1000 μatm), two salinity levels (LS, 20 ppt; HS, 30 ppt), and two temperatures (LT, 20 °C; HT, 26 °C) were tested to examine the synergistic effects of warming and salinity on the economically important macroalga Gracilariopsis lemaneiformis under ocean acidification. The results showed that the synergistic effect of LS and HT treatments significantly promoted the growth of G. lemaneiformis under LC treatment, but this promotion effect was more obvious under HC treatment. In contrast, HSLT conditions inhibited G. lemaneiformis growth under both LC and HC conditions. Under HC treatment, warming and low salinity together increased the maximum photosynthetic rate and the maximum electron transport rate of G. lemaneiformis. Photosynthetic pigment analysis revealed that LS had a significantly negative effect on the contents of chlorophyll a (Chl a) and carotenoids (Car.), and HT had an obviously adverse influence on the contents of Chl a, Car., phycoerythrin, and phycocyanin. Moreover, the dual limitation of LSHT conditions significantly reduced the contents of Chl a and Car. under HC and LC conditions. These findings suggested that warming and low salinity synergically improved the growth and photosynthetic performance of G. lemaneiformis, especially under ocean acidification. The results provide a scientific basis for macroalgal cultivation as part of environmental restoration around nuclear power plants generally and year-round cultivation of G. lemaneiformis in northern China specifically.

Long-term observation of global nuclear power plants thermal plumes using Landsat images and deep learning

Thermal discharge from nuclear power plants poses a threat to the received natural water bodies, but the long-term extent and intensity of their surface thermal plumes remain unclear. In this study, we proposed a method to determine the background area for each drainage outlet and delineate the mixed surface thermal plumes based on 7,172 Landsat thermal infrared images. We further used a deep convolutional neural network integrated with prior location knowledge to extract core surface thermal plumes for 74 drainage outlets of 66 nuclear power plants worldwide. Our final model achieved a mean Intersection over Union (mIoU) of 0.8998 and an F1 score of 0.8886. We found that the mean maximal water surface temperature (WST) increment of the studied plants globally was 4.80 K. The Tianwan plant in China experienced the highest WST increase (8.51 K), followed by the Gravelines plant in France and the Ohi plant in Japan (7.91 K and 7.71 K, respectively). The Bruce plant in Canada had the largest thermal-polluted surface area (7.22 km2). We also provided the dataset, Global Coastal Nuclear power plant Thermal Plume (GCNT-Plume), to describe the long-term occurrence of water surface thermal plumes. Three influencing factors of the water surface thermal plume were further analyzed in this study, including total capacity, drainage type, and location type, which were associated with operating power, drainage method, and geographical features, respectively. Total capacity was more statistically related to the maximum of WST increment under shallow drainage condition. The mean WST increment of shallow drainage was 1.22 K higher than that of deep drainage. Surface plumes larger than 4 km2 frequently occurred in the Great Lakes, while small surface thermal plumes (< 1 km2) were primarily found in estuaries. The proposed method provides an important framework for future operational water surface thermal plume detection using remotely sensed observations and deep learning.

Seismic Response Analysis of a Shield Tunnel in a Coastal Nuclear Power Plant under a Complex Foundation

As a transportation hub connecting sea and land, the seismic safety of an undersea tunnel is very important. Based on the structural and stress characteristics of a shield tunnel, a seismic response analysis of a coastal nuclear power plant under a complex foundation is carried out in this paper. Firstly, adopting the lateral and longitudinal response displacement methods, the authors study the variation and distribution features of the rate of diameter change and joint-stretching value of the shield tunnel segments. On this basis, a three-dimensional refined finite element model of a sinking tube–soil mass under a complex soil foundation is established. Finally, when the joints and segments of the shield tunnel are subjected to ground motion, the deformation and internal force distribution of its lining segments are studied. The findings show that under influence of SL-2-magnitude ground motion, the soft–hard stratum junction is the weak point of the shield tunnel structure’s longitudinal seismic resistance. When the silt layer at the position of the shield segment is thicker and the geological conditions are relatively poorer, the internal force, diameter deformation rate, and joint-stretching value will be larger. The research results can provide a reference for seismic research on shield tunnels in sea areas under complex foundations.

Microstructure and Properties of Direct Laser-Deposited CeO2-Modified Cobalt-Based Composite Coatings

The seawater circulation pump is a significant piece of equipment in coastal nuclear power plants that is susceptible to erosion and corrosion in the seawater. In this work, CeO2-modified cobalt-based composite coatings were prepared on the surface of martensitic stainless steel by direct laser deposition. The effect of CeO2 on the phase composition, microstructure, microhardness, corrosion resistance, and erosion properties of the cobalt-based composite coatings was systematically investigated. While the addition of CeO2 did not affect the phase composition of the coatings that comprised γ-Co, γ-Ni, M7C3, and M23C6 (M = Cr, W, Fe) metallic carbides, the eutectic organization showed an obvious phenomenon of contiguous aggregation. Microscopic pores were found in the coatings with 2 wt.% CeO2, and the number of pores increased with the increase in CeO2 content. Despite the higher self-corrosion potential (−0.27668 V) of cobalt-based alloy coating compared to the substrate (−0.37019 V), indicating enhanced corrosion resistance, the difference in self-corrosion potential among coatings with varying CeO2 addition amounts is small (0.027 V), and the corrosion current densities are within one order of magnitude (10−8 A/cm2). These findings suggest that the addition of CeO2 has no significant impact on the coating’s corrosion resistance.

Cooling water intake system safety analysis based on impingement probability

Invasion or aggregation of marine organisms in cooling water intake systems (CWIS) has gradually become an important problem affecting the safety of nuclear power plants with environmental and climate changes. In this study, a 3-dimensional numerical model (TELEMAC-3D) was used to determine the impingement probability in a typical nuclear power plant with a once-through cooling system, and the effect on CWIS safety. The factors controlling impingement probability were also analyzed. Results show that (1) impingement probability decreased rapidly with an increase in distance from the CWIS. In addition, the distance of the impingement effect of a nuclear power plant with six units was mainly within 1 km of the CWIS. (2) Impingement probability increased with water withdrawal, and as distance to the CWIS increased, the increase in probability increased. (3) Generally, an increase in tide strength led to a decrease impingement probability. (4) Near the CWIS, the impingement probabilities of areas upstream or downstream of the CWIS along the tidal flow direction were much higher than those not in those areas. (5) An increase in water depth significantly reduced impingement probability. When the water depth of the CWIS increased from 5 m to 15 m, impingement probability was reduced up to 30%. Based on the above findings, the following suggestions were made to minimize the impingement effects on CWIS safety: first, the CWIS of coastal nuclear power plants should be set in an area with low aquatic biomass, strong tides, deep water, and few surface species within the range of 1 km, and second, the amount of cooling water withdrawal or velocity should be reduced as much as possible.

Elucidating colony bloom formation mechanism of a harmful alga Phaeocystis globosa (Prymnesiophyceae) using metaproteomics

Phaeocystis is a globally distributed Prymnesiophyte genus and usually forms massive harmful colony blooms, which impact marine ecosystem, mariculture, human health, and even threaten coastal nuclear power plant safety. However, the mechanisms behind the colony formation from the solitary cells remain poorly understood. Here, we investigated metabolic processes of both solitary and non-flagellated colonial cells of Phaeocystis globosa at different colony bloom stages in the subtropical Beibu Gulf using a metaproteomic approach. Temperature was significantly correlated with Phaeocystis colony bloom formation, and the flagellated motile solitary cells with abundant flagellum-associated proteins, such as tubulin and dynein, were the exclusive cellular morphotype at the solitary cell stage featured with temperatures ≥21 °C. When the temperature decreased to <21 °C, tiny colonies appeared and the flagellum-associated proteins were down-regulated in both solitary and non-flagellated colonial cells, while proteins involved in biosynthesis, chain polymerization and aggregation of glycosaminoglycan (GAG), a key constituent of gelatinous matrix, were up-regulated, indicating the central role of active GAG biosynthesis during the colony formation. Furthermore, light utilization, carbon fixation, nitrogen assimilation, and amino acid and protein synthesis were also enhanced to provide sufficient energy and substrates for GAG biosynthesis. This study highlighted that temperature induced re-allocation of energy and substances toward GAG biosynthesis is essential for colony bloom formation of P. globosa.