Short-term (24 h) effects of mild and severe hypoxia (20% and 5% dissolved oxygen) on metal partitioning in highly contaminated estuarine sediments

2012 ◽  
Vol 99 ◽  
pp. 121-131 ◽  
Author(s):  
Joanne Banks ◽  
D. Jeff Ross ◽  
Michael J. Keough
Keyword(s):  
Dissolved Oxygen ◽  
Estuarine Sediments ◽  
Severe Hypoxia ◽  
Metal Partitioning ◽  
Short Term

scholarly journals The Dynamic Response of Nitrogen Transformation to the Dissolved Oxygen Variations in the Simulated Biofilm Reactor

2021 ◽  
Vol 18 (7) ◽  
pp. 3633
Author(s):  
Qianqian Lu ◽  
Nannan Zhang ◽  
Chen Chen ◽  
Miao Zhang ◽  
Dehua Zhao ◽  
...  
Keyword(s):  
Dissolved Oxygen ◽  
Copy Number ◽  
Stable State ◽  
Quantitative Relationship ◽  
Nitrogen Transformation ◽  
Biofilm Reactor ◽  
Short Term ◽  
Nirs Gene ◽  
Biofilm Reactors ◽  
Recovery Times

Lab-scale simulated biofilm reactors, including aerated reactors disturbed by short-term aeration interruption (AE-D) and non-aerated reactors disturbed by short-term aeration (AN-D), were established to study the stable-state (SS) formation and recovery after disturbance for nitrogen transformation in terms of dissolved oxygen (DO), removal efficiency (RE) of NH4+-N and NO3−-N and activity of key nitrogen-cycle functional genes amoA and nirS (RNA level abundance, per ball). SS formation and recovery of DO were completed in 0.56–7.75 h after transition between aeration (Ae) and aeration stop (As). In terms of pollutant REs, new temporary SS formation required 30.7–52.3 h after Ae and As interruptions, and seven-day Ae/As interruptions required 5.0% to 115.5% longer recovery times compared to one-day interruptions in AE-D and AN-D systems. According to amoA activity, 60.8 h were required in AE-D systems to establish new temporary SS after As interruptions, and RNA amoA copies (copy number/microliter) decreased 88.5%, while 287.2 h were required in AN-D systems, and RNA amoA copies (copy number/microliter) increased 36.4 times. For nirS activity, 75.2–85.8 h were required to establish new SSs after Ae and As interruptions. The results suggested that new temporary SS formation and recovery in terms of DO, pollutant REs and amoA and nirS gene activities could be modelled by logistic functions. It is concluded that temporary SS formation and recovery after Ae and As interruptions occurred at asynchronous rates in terms of DO, pollutant REs and amoA and nirS gene activities. Because of DO fluctuations, the quantitative relationship between gene activity and pollutant RE remains a challenge.

A hybrid model for short-term dissolved oxygen content prediction

2021 ◽  
Vol 186 ◽  
pp. 106216
Author(s):  
Jiande Huang ◽  
Shuangyin Liu ◽  
Shahbaz Gul Hassan ◽  
Longqin Xu ◽  
Cifeng Huang
Keyword(s):  
Dissolved Oxygen ◽  
Oxygen Content ◽  
Hybrid Model ◽  
Short Term

scholarly journals Dissolved Oxygen Forecasting in Aquaculture: A Hybrid Model Approach

2020 ◽  
Vol 10 (20) ◽  
pp. 7079
Author(s):  
Elias Eze ◽  
Tahmina Ajmal
Keyword(s):  
Dissolved Oxygen ◽  
Mean Square Error ◽  
Short Term Memory ◽  
Sensor Data ◽  
Percentage Error ◽  
Forecasting Model ◽  
Mean Square ◽  
Intrinsic Mode Functions ◽  
Short Term ◽  
Do Concentration

Dissolved oxygen (DO) concentration is a vital parameter that indicates water quality. We present here DO short term forecasting using time series analysis on data collected from an aquaculture pond. This can provide the basis of data support for an early warning system, for an improved management of the aquaculture farm. The conventional forecasting approaches are commonly characterized by low accuracy and poor generalization problems. In this article, we present a novel hybrid DO concentration forecasting method with ensemble empirical mode decomposition (EEMD)-based LSTM (long short-term memory) neural network (NN). With this method, first, the sensor data integrity is improved through linear interpolation and moving average filtering methods of data preprocessing. Next, the EEMD algorithm is applied to decompose the original sensor data into multiple intrinsic mode functions (IMFs). Finally, the feature selection is used to carefully select IMFs that strongly correlate with the original sensor data, and integrate into both inputs for the NN. The hybrid EEMD-based LSTM forecasting model is then constructed. The performance of this proposed model in training and validation sets was compared with the observed real sensor data. To obtain the exact evaluation accuracy of the forecasted results of the hybrid EEMD-based LSTM forecasting model, four statistical performance indices were adopted: mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), and mean absolute percentage error (MAPE). Results are presented for the short term (12-h) and the long term (1-month) that are encouraging, indicating suitability of this technique for forecasting DO values.

scholarly journals The 2011 marine heat wave off southwest Australia

2012 ◽  
Vol 9 (2) ◽  
pp. 1691-1703 ◽  
Author(s):  
T. H. Rose ◽  
D. A. Smale ◽  
G. Botting
Keyword(s):  
Dissolved Oxygen ◽  
Heat Wave ◽  
Extreme Events ◽  
Algal Blooms ◽  
Multiple Use ◽  
Short Term ◽  
Oxygen Levels ◽  
Australian Coastline ◽  
Western Australian ◽  
Marine Heat Wave

Abstract. Over 2000 km of Western Australian coastline experienced a significant marine heat wave in February and March 2011. Seawater temperature anomalies of +2–4 °C were recorded at a number of locations and satellite-derived SSTs were the highest on record. Here, we present seawater temperatures from southwestern Australia and describe, in detail, the marine climatology of Cockburn Sound; a large, multiple-use coastal embayment. We compared temperature and dissolved oxygen levels in 2011 with data from routine monitoring conducted from 2002–2010. A significant warming event, 2–4 °C in magnitude, persisted for >8 weeks, and seawater temperatures at 10 to 20 m depth were significantly higher than those recorded in the previous 9 yr. Dissolved oxygen levels were depressed at most monitoring sites, being ~2 mg l−1 lower than usual in early March 2011. Ecological responses to short-term extreme events are poorly understood, but evidence from elsewhere along the Western Australian coastline suggests that the heat wave was associated with high rates of coral bleaching, fish, invertebrate and macroalgae mortalities, and algal blooms. However, more ecological information from Cockburn Sound and other multiple-use embayments is urgently needed. The 2011 heat wave provided insights into conditions that may become more prevalent in Cockburn Sound, and elsewhere, if the intensity and frequency of short-term extreme events increases as predicted.

Short-Term Predicting Model for Dissolved Oxygen of Hyriopsis Cumingii Ponds Based on Elman Neural Network

2011 ◽  
Vol 9 (3) ◽  
pp. 1014-1019 ◽  
Author(s):  
Mingxia Yan ◽  
Daoliang Li ◽  
Yaoguang Wei ◽  
Haijiang Tai ◽  
Qisheng Ding
Keyword(s):  
Neural Network ◽  
Dissolved Oxygen ◽  
Short Term ◽  
Elman Neural Network ◽  
Predicting Model ◽  
Hyriopsis Cumingii
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