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Interpretable Machine Learning-Based Spring Algal Bloom Forecast Model for the Coastal Waters of Zhejiang

Journal of Ocean University of China 2025年第1期24卷 1-12页

作者： HUANG Guoqiang BAO Min ZHANG Zhao GU Dongming LIANG Liansong TAO Bangyi State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of OceanographyMinistry of Natural ResourceHangzhou 310012China wenzhou marine Center Ministry of Natural ResourcesWenzhou 325000China Observation and Research station of Yangtze River Delta marine Ecosystems Ministry of Natural ResourcesZhoushan 316000China Key Laboratory of marine Ecological monitoring and Restoration Technologies Ministry of Natural ResourceShanghai 201206China

The 2016–2022 monitoring data from three ecological buoys in the wenzhou coastal region of Zhejiang Province and the dataset European Centre for Medium-Range Weather Forecasts were examined to clarify the elaborate relationship between variations in ecological parameters during spring algal bloom incidents and the associated changes in temperature and wind fields in this study.A long short-term memory recurrent neural network was employed,and a predictive model for spring algal bloom in this region was *** model integrated various inputs,including temperature,wind speed,and other pertinent variables,and chlorophyll concentration served as the primary output *** model training used chlorophyll concentration data,which were supplemented by reanalysis and forecast temperature and wind field *** model demonstrated proficiency in forecasting next-day chlorophyll concentrations and assessing the likelihood of spring algal bloom occurrences using a defined chlorophyll concentration *** historical validation from 2016 to 2019 corroborated the model's accuracy with an 81.71%probability of correct prediction,which was further proven by its precise prediction of two spring algal bloom incidents in late April 2023 and early May *** interpretable machine learning-based model for spring algal bloom prediction,displaying effective forecasting with limited data,was established through the detailed analysis of the spring algal bloom mechanism and the careful selection of input *** insights gained from this study offer valuable contributions to the development of early warning systems for spring algal bloom in the wenzhou coastal area of Zhejiang Province.

关键词： spring algal bloom forecast LSTM interpretable

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Emission characteristics of biogenic volatile organic compounds in a subtropical pristine forest of southern China

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Journal of environmental Sciences 2025年第2期148卷 665-682页

作者： Xi Chen Daocheng Gong Youjing Lin Qiao Xu Yujin Wang Shiwei Liu Qinqin Li Fangyuan Ma Jiangyong Li Shuo Deng Hao Wang Boguang Wang Institute for environmental and Climate Research Jinan UniversityGuangzhou 511443China Guangdong Provincial Observation and Research station for Atmospheric Environment and Carbon Neutrality in Nanling Forests China Australia-China Centre for Air Quality Science and Management(Guangdong) Guangzhou 511443China Hainan Provincial Ecological and environmental monitoring Center Haikou 571126China

Emission characteristics of biogenic volatile organic compounds(BVOCs)from dominant tree species in the subtropical pristine forests of China are extremely *** we conducted in situ field measurements of BVOCs emissions from representative mature evergreen trees by using dynamic branch enclosures at four altitude gradients(600-1690ma.s.l.)in the Nanling Mountains of southern *** characteristics as well as seasonal and altitudinal variations were *** emission rates and canopyscale emission factors were then *** showed that BVOCs emission intensities in the wet season were generally higher than those in the dry *** were the dominant BVOCs emitted from most broad-leaved trees,accounting for over 70%of the *** superba,Yushania basihirsuta and Altingia chinensis had relatively high emission intensities and secondary pollutant formation *** localized emission factors of isoprene were comparable to the defaults in the Model of Emissions of Gases and Aerosols fromNature(MEGAN),while emission factors of monoterpenes and sesquiterpenes were 2 to 58 times of those in the *** results can be used to update the current BVOCs emission inventory in MEGAN,thereby reducing the uncertainties of BVOCs emission estimations in forested regions of southern China.

关键词： Biogenic volatile organic compounds(BVOCs) Dynamic enclosure system Nanling Mountains Emission factors Emission rates Chemical reactivity

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Exaptation of pectoral fins for olfaction in the spiny red gurnard(Chelidonichthys spinosus)through an ancient receptor

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Science China(Life Sciences) 2025年第2期68卷 582-585页

作者： Lisen Li Deqian Fan Chenglong Zhu Zhuoya Liu Wenji Huang Peidong Xin Huishan Yue Mengying Li Yufei Wang Wenjie Xu Jiangmin Zheng Ye Li Ziwei Yu Jianzhong Ling Qiang Qiu Wen Wang Chenguang Feng Xiaojing Song Kun Wang Shaanxi Key Laboratory of Qinling Ecological Intelligent monitoring and Protection School of Ecology and EnvironmentNorthwestern Polytechnical UniversityXi’an 710072China Shanghai Fisheries Research Institute Shanghai Fisheries Technical Extension StationShanghai 200433China East China Sea Fisheries Research Institute Chinese Academy of Fishery SciencesShanghai 200090China Laboratory for marine Biology and Biotechnology Qingdao Marine Science and Technology CenterQingdao 266237China

Dear Editor,Exaptation is defined as characters evolved for other usages(or for no function at all)and later“coopted”for their current role(Gould and Vrba,1982).Exaptation has occurred in many organisms,sometimes as an outcome of organ specialization for *** process is exemplified in the family Triglidae,commonly known as gurnards or sea robins.

关键词： pectoral olfaction

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Statistical Prediction for Annual Start Date and Duration of Sea-Ice Coverage at Qinhuangdao Observation station

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Journal of Ocean University of China 2019年第6期18卷 1265-1272页

作者： JIAO Chunshuo ZHANG Wanlei DONG Sheng College of Engineering Ocean University of ChinaQingdao 266100China Qinhuangdao marine environmental monitoring central station of SOA Qinhuangdao 066002China

Qinhuangdao City is located in the mid-latitude monsoon-affected region,and the timing of sea-ice coverage changes from year to year,making sea-ice forecasting *** this paper,we propose a statistical model using the 1980-2013 data collected at the Qinhuangdao observation *** start date and the duration of ice coverage are fitted with four marginal distributions,from which the best-fitted,i.e.,the Weibull distribution,is selected to form a joint probability density function(PDF),built by the Gaussian copula method,for the two *** a given start date forecast by the Gray-Markov model(GMM),the joint PDF becomes a conditional probability model,which predicts that the duration of ice coverage is most likely 33 days at the Qinhuangdao observation station in *** predicted duration value is only two days less than the actual *** results prove that the new prediction model is feasible and effective to predict the period of ice *** general sea-ice conditions that the sea ice would most likely form on December 8 and last for 80 days at the Qinhuangdao observation station could also be obtained from the joint *** statistical model provides a useful tool to forecast ice conditions for planning and management of maritime activities.

关键词： start date of sea ice duration of sea ice statistical prediction Weibull distribution Gaussian copula

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Variation of PM_(2.5) concentration in Hangzhou,China

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Particuology 2013年第1期11卷 55-62页

作者： Shengmao Hong Li Jiao Wanli Ma Environment Science Hangzhou Central Station for Environmental Monitoring Hangzhou Bureau of Meteorology

This observational study investigates the variation of PM2.5 concentration and its ratio against PM10 concentration under different weather systems and pollution types. The study was conducted in Hangzhou on east China＇s Yangtze River Delta using data collected at seven ambient air quality monitoring stations around the metropolitan area between 2006 and 2008 and using weather information in the same period. Nine predominant weather systems affecting the city were classified through careful analysis of the 11- year surface and upper air weather charts from 1996 to 2006. Each observational day was then assigned to one of the nine weather systems. It was found that the PM2.5 concentration varied greatly for different weather systems, with the highest PM2.5 concentration associated with the post-cold-frontal system at 0.091 mg/m^3 and the lowest PM2.5 concentration with the easterlies system at 0.038 mg/m^3, although the PM2.5/PM10 ratio remained consistently above 0.5 for all systems. The post-cold-frontal system typically occurs in autumn and winter while the easterlies system is more a summer phenomenon. Among all types of pollution, the highest PM2.5 concentration of 0.117 mg/m^3 coincided with the large-scale continuous pollution events, suggesting that this type of pollution was more conducive to the formation of secondary particulate matters. The ratio of PM2.5/PM10 was above 0.5 in non-pollution days and all pollution types but one under the influence of dust storms when the ratio decreased to 0.3 or less. The outcomes of this study could be used to develop a rudimental predictive model of PM2.5 concentration based on weather system and pollution type.

关键词： PM2.5 Concentration Weather system Secondary particulate matter Post-cold-frontal Large-scale continuous pollution

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Revisiting the seasonal wave height variability in the South China Sea with merged satellite altimetry observations

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Acta Oceanologica Sinica 2017年第11期36卷 38-50页

作者： SU Hui WEI Chunlei JIANG Shaocai LI Peiliang ZHAI Fangguo central marine environmental monitoring station of Xiamen East China Sea BranchState Oceanic Administration Beihai marine environmental monitoring Center South China Sea BranchState Oceanic Administration College of Oceanic and Atmospheric Sciences Ocean University of China

The seasonal variability of the significant wave height（SWH） in the South China Sea（SCS） is investigated using the most up-to-date gridded daily altimeter data for the period of September 2009 to August 2015. The results indicate that the SWH shows a uniform seasonal variation in the whole SCS, with its maxima occurring in December/January and minima in May. Throughout the year, the SWH in the SCS is the largest around Luzon Strait（LS） and then gradually decreases southward across the basin. The surface wind speed has a similar seasonal variation, but with different spatial distributions in most months of the year. Further analysis indicates that the observed SWH variations are dominated by swell. The wind sea height, however, is much smaller. It is the the largest in two regions southwest of Taiwan Island and southeast of Vietnam Coast during the northeasterly monsoon, while the largest in the central/southern SCS during the southwesterly monsoon. The extreme wave condition also experiences a significant seasonal variation. In most regions of the northern and central SCS, the maxima of the 99 th percentile SWH that are larger than the SWH theoretically calculated with the wind speed for the fully developed seas mainly appear in August–November, closely related to strong tropical cyclone *** with previous studies, it is also implied that the wave climate in the Pacific Ocean plays an important role in the wave climate variations in the SCS.

关键词： significant wave height seasonal variability South China Sea satellite observations

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environmental characteristics of annual pico/nanophytoplankton blooms along the Qinhuangdao Coast

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Journal of Oceanology and Limnology 2018年第2期36卷 281-292页

作者： CAO Xihua YU Zhiming WU Zaixing CHENG Fangjin HE Liyan YUAN Yongquan SONG Xiuxian ZHANG Jianle ZHANG Yongfeng ZHANG Wanlei Key Laboratory of marine Ecology and environmental Sciences Institute of Oceanology Chinese Academy of Sciences Qingdao 266071 China Qinhuangdao marine environmental monitoring central station State Oceanic Administration （SOA） Qinhuangdao 066002 China

Abstract Blooms of some pico/nanophytoplankton have occurred frequently along the Qinhuangdao coast since 2009, and it is necessary to identify the critical environmental factors inducing them. In this study, variations in the physical and nutrient characteristics of the seawater were analyzed following the development of local blooms in 2013. The local environmental characteristics were also compared with those of the Changjiang River estuary, China, and the Long Island estuaries in the USA, which are also prone to blooms of special algal species. In Qinhuangdao the local water temperature varied seasonally and rose above 15~C in 2013 early summer, coincident with the water discoloration. The salinity was more than 28 with a variation range of 〈3 throughout the year. Our results suggest that the physical conditions of the Qinhuangdao coastal area were suitable for the explosive proliferation of certain pico/nanophytoplankton, e.g. Aureococcus anophagefferens. The water supporting the bloom was not in a condition of serious eutrophication, but there were relatively high concentrations of reduced nitrogen （especially ammonium）, which acted as an important nitrogen source for the pico/nanophytoplankton bloom. There was also a large gap between total nitrogen （TN） and dissolved inorganic nitrogen （DIN）. Although the phosphate concentration was relatively low, there was no evidence of phosphorus limitation to the growth of pico/ nanophytoplankton during bloom events.

关键词： pico/nanophytoplankton harmful algae blooms eutrophication physical conditions Qinhuangdao coastal area

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An Automatic Solid Phase Extraction and Ultra-Performance Liquid Chromatography Tandem Mass Spectrometry for Determination of Seven Microcystins at Ultra-Trace Levels in Surface Water

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Wuhan University Journal of Natural Sciences 2019年第1期24卷 30-36页

作者： SHEN Fei XU Yanjuan WANG Ye CHEN Jing School of environmental and Civil Engineering Jiangnan University Wuxi environmental monitoring central station

A method was developed for the detection of seven microcystins(microcystin-LR, RR, YR, LA, LY, LW and LF) in surface water using automatic solid-phase extraction(A-SPE) coupled with ultra-performance liquid chromatography tandem mass spectrometry(UPLC-MS/MS). The automated solid-phase extraction system was used to extract microcystins(MCs) from water samples. UPLC-MS/MS was used to determine MCs concentrations in just 5 min. Method detection limits were from 0.3 to 0.9 ng/L, microcystin recoveries ranged from 83.8% to 114%, and the relative standard deviation(RSD) varied from 5.6% to 12.5%. This analytical approach was found to be simple, highly sensitive, accurate, which required little manual operation. Additionally, to validate this analytical method, A-SPE+UPLC-MS/MS was applied to characterize the concentration of MCs in Taihu Lake, Wuxi, China.

关键词： microcystins automatic solid-phase extraction ultra-performance liquid chromatography tandem mass spectrometry(UPLC-MS/MS)

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Prediction of Spatial Distribution of Cation Exchange in Agricultural Soils Based on Machine Learning

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Huanjing Kexue/environmental Science 2025年第3期46卷 1737-1750页

作者： Ma, Ji-Long Ma, Kun Xie, Tie-Na Li, Hong Yue, Xiang Ji, Li Han, Lin-Pu Qi, Yong-Jie Jia, Biao College of Agriculture Ningxia University Yinchuan750021 China College of Ecology and Environment Ningxia University Yinchuan750021 China Research Institute of Science and Technology Ningxia University Yinchuan750021 China Agricultural environmental Protection monitoring station of Ningxia Hui Autonomous Region Yinchuan750002 China

Cation exchange capacity（CEC）reflects the ability of soil to sequester exchangeable cations and is an important indicator of the fertility and environmental quality of agricultural soils. The indoor titration method for determining soil cation exchange is expensive and cumbersome. To this end，565 soil samples from the 0-20 cm plough layer were collected from farmland in Ningxia，and the parameters of soil pH，organic carbon，and mechanical composition were determined. A field - scale soil cation exchange（CEC）estimation model was constructed using multiple linear regression and machine learning methods to obtain soil CEC values rapidly and accurately. The results showed that：① The mean CEC value of farmland soils in Ningxia was 9.39 cmol·kg−1，with a coefficient of variation of 40.74%. This indicated a high degree of variability，with the spatial distribution of the CEC values generally showing higher values in the periphery of the Yellow River Basin（Ningxia section）and the southern mountainous areas of Ningxia and lower values in the central arid zone and the east-central region. ② The soil parameters selected for modeling the total dataset were as follows：Soil organic carbon，clay content，pH，and sand content were the important factors influencing the CEC of farmland soil in Ningxia，with correlation coefficients of 0.55，0.72，−0.41，and −0.44，respectively. ③ The results of multiple linear regression modeling showed that dividing the total dataset according to the urban area and constructing a multiple linear-type regression model within the urban area was more conducive to the prediction of the CEC of farmland soils. ④ Compared with the multiple linear regression method，the machine learning method was more effective in the prediction of the total dataset. Further，using the multiple linear regression model as a reference，the prediction accuracy（R2）of the back propagation neural network，convolutional neural network，back propagation neural network optimized by the particle swa

关键词： Backpropagation

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Effect of Antimony on Physiological Responses of Green Chinese Cabbage and Enzyme Activities of Allitic Udic Ferrisols

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Pedosphere 2015年第1期25卷 124-129页

作者： XIAO Xi-Yuan GUO Zhao-Hui LUO Yue-Ping BI Jun-Ping YANG Miao HUANG Dong-Qin Institute of environmental Engineering School of Metallurgy and Environment Central South University environmental monitoring Center station of Hunan Province State environmental Protection Key Laboratory of Heavy Metal Pollution monitoring

High concentrations of antimony(Sb) in soils and vegetables can cause potential health risk. However, the effect of Sb on the growth and response of crops are not well known and to date, there is still no Sb limit standard for Allitic Udic Ferrisols in China. In this study, a greenhouse experiment was carried out to investigate the effect of antimony(Sb) on biomass, physiological performances,and macro- and micronutrient element concentrations of green Chinese cabbage(Brassica chinensis L.), as well as enzyme activities,in Allitic Udic Ferrisols from Hunan Province, China. Antimony was supplied at rates of 0(control), 2, 5, 10, 20, and 50 mg kg-1and thus with the background value of 1.0 mg kg-1, the Sb concentrations in the treated soil samples were 1, 3, 6, 11 21, and 51 mg kg-1, respectively. The results showed the leaf biomass and ascorbic acid content of cabbage significantly(P < 0.05) decreased by 30.6% and 48.3%, respectively, and soil urease and dehydrogenase activities also significantly(P < 0.05) decreased by 33.6%and 32.5%, respectively, when soil Sb concentration was 21 mg kg-1as compared with the control. The uptake of essential nutrient elements such as Mg, Cu, and Zn by cabbage was obviously affected, while the leaf soluble sugar content slightly changed when the soil Sb concentration exceeded 21 mg kg-1. Based on cabbage physiological responses and soil enzyme activities, the permissible concentration of 21 mg kg-1for Sb in Allitic Udic Ferrisols should be recommended.

关键词： ascorbic acid biomass dehydrogenase nutrient elements permissible Sb concentration soluble sugar urease

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