Historical construction, quantitative source identification and risk assessment of heavy metals contamination in sediments from the Pearl River Estuary, South China.

Historical reconstruction of heavy metals (HMs) contamination in sediments is a key for understanding the effects of anthropogenic stresses on water bodies and predicting the variation trends of environmental state. In this work, eighteen sediment cores from the Pearl River Estuary (PRE) were collected to determine concentrations and geochemical fractions of HMs. Then, their potential sources and the relative contributions during different time periods were quantitatively identified by integrating lead-210 (210Pb) radioisotope dating technique into positive matrix factorisation (PMF) method. Pollution levels and potential ecological risks (PERs) caused by HMs were accurately assessed by enrichment factors (EF) based on establishment of their geochemical baselines (GCBs) and multiparameter evaluation index (MPE). HMs concentrations generally showed a particle size- and organic matter-dependent distribution pattern. During the period of 1958-1978, HMs concentrations remained at low levels with agricultural activities and natural processes being identified as the predominant sources and averagely contributing >60%. Since the reform and opening-up in 1978, industrial and traffic factors become the primary anthropogenic sources of HMs (such as Cu, Zn, Cd, Pb, Cr, and Ni), averagely increasing from 22.1% to 28.1% and from 11.6% to 23.4%, respectively. Conversely, the contributions of agricultural and natural factors decreased from 37.0% to 28.5% and from 29.3% to 20.0%, respectively. Subsequently, implementation of environmental preservation policies was mainly responsible for the declining trend of HMs after 2010. Little enrichment of sediment Cu, Zn, Pb, Cr and Ni with EFs (0.15-1.43) was found in the PRE, whereas EFs of Cd (1.16-2.70) demonstrated a slight to moderate enrichment. MPE indices of Cu (50.7-252), Pb (52.0-147), Zn (35.5-130), Ni (19.6-71.5), Cr (14.2-68.8) and Cd (0-9.90) highlighted their potential ecological hazards due to their non-residual fractions and anthropogenic sources.

Improving the efficiency of dissolved oxygen control using an on-line control system based on a genetic algorithm evolving FWNN software sensor.

This work proposes an on-line hybrid intelligent control system based on a genetic algorithm (GA) evolving fuzzy wavelet neural network software sensor to control dissolved oxygen (DO) in an anaerobic/anoxic/oxic process for treating papermaking wastewater. With the self-learning and memory abilities of neural network, handling the uncertainty capacity of fuzzy logic, analyzing local detail superiority of wavelet transform and global search of GA, this proposed control system can extract the dynamic behavior and complex interrelationships between various operation variables. The results indicate that the reasonable forecasting and control performances were achieved with optimal DO, and the effluent quality was stable at and below the desired values in real time. Our proposed hybrid approach proved to be a robust and effective DO control tool, attaining not only adequate effluent quality but also minimizing the demand for energy, and is easily integrated into a global monitoring system for purposes of cost management.

Estimation of water quality variables based on machine learning model and cluster analysis-based empirical model using multi-source remote sensing data in inland reservoirs, South China.

Reservoirs play important roles in the drinking water supply for urban residents, agricultural water provision, and the maintenance of ecosystem health. Satellite optical remote sensing of water quality variables in medium and micro-sized inland waters under oligotrophic and mesotrophic status is challenging in terms of the spatio-temporal resolution, weather conditions and frequent nutrient status changes in reservoirs, etc., especially when quantifying non-optically active components (non-OACs). This study was based on the surface reflectance products of unmanned aerial vehicle (UAV) multispectral images, Sentinel-2B Multispectral instrument (MSI) images and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) by utilizing fuzzy C-means (FCM) clustering algorithm was combined with band combination (BC) model to construct the FCM-BC empirical model, and used mixed density network (MDN), extreme gradient boosting (XGBoost), deep neural network (DNN) and support vector regression (SVR) machine learning (ML) models to invert 12 kinds of optically active components (OACs) and non-OACs. Compared with the unclustered BC (UC) model, the mean coefficient of determination (MR) of the FCM-BC models was improved by at least 46.9%. MDN model showed best accuracy (R2 in the range of 0.60-0.98) and stability (R2 decreased by up to 13.2%). The accuracy of UAV was relatively higher in both empirical methods and machine learning methods. Additionally, the spatio-temporal distribution maps of four water quality variables were mapped based on the MDN model and UAV images, all platforms showed good consistency. An inversion strategy of water quality variables in various monitoring frequencies and weather conditions were proposed finally. The purpose of introducing the UAV platform was to cooperate with the satellite to improve the monitoring response ability of OACs and non-OACs in small and micro-sized oligotrophic and mesotrophic water bodies.

Remobilization characteristics and diffusion kinetic processes of sediment zinc (Zn) in a tidal reach of the Pearl River Estuary, South China.

Exploration of the remobilization mechanism of trace metals in estuarine sediments remain challenging because of dynamic hydrochemical conditions. This study integrated a chemical sequential extraction procedure (BCR), the diffusive gradient in thin films (DGT) and high-resolution dialysis techniques, and Visual MINTEQ ver.3.1 to identify the seasonal mobilization characteristics of sediment Zn within a tidal reach, South China. The mobility of sediment Zn based on the BCR procedure contradicted the results of DGT analysis. In summer, reductive dissolution of Fe/Mn oxides was the key driver of sediment Zn remobilization; during winter, cation exchange reactions facilitated the mobilization of Zn in the brackish water zone. The time-dependence ratios of DGT-labile Zn and dissolved Zn concentrations (mean: 0.34-0.81) indicated the sediment solid phase had partially sustained capacity to resupply Zn to the porewater in both seasons. Sediments generally functioned as a source of Zn in the freshwater zone with organically complexed Zn being diffusively released into the water column at rates of 0.3-15.5 µg·m-2·d-1. In the brackish water zone, the dominant Zn species were transformed into free Zn ions and Zn-inorganic complexes and migrated into sediment, with respective influxes of 18.9-70.7 µg·m-2·d-1 and 18.9-68.3 µg·m-2·d-1, which shifted to a sink of Zn.

Morphological changes in the lower Lancang River due to extensive human activities.

BACKGROUND: Morphological changes in river beds determine the risk for soil erosion within floodplain areas. At present, little is known about river morphological changes in high-altitude mountainous area influenced by extensive human activities. The study has important reference value for clarifying the morphological changes of mountainous rivers due to extensive human activities. METHODS: Based on the long-term multi-source remote sensing image data, we analyzed morphological changes in the lower Lancang River (LCR) in Southwest China at regional and local scales, and determined their influencing factors. Visual interpretation is used to extract the information and unify the interpretation standards of various localities, mainly including water bodies, sandbars, shorelines and beaches. Based on high-resolution remote sensing images, we analyzed the planforms, erosion and accretion conditions in Jinghongba (JHB) reach and Ganlanba (GLB) reach. RESULTS: Our results showed that: (1) during 1993-2016, the planforms of Jinghongba and Ganlanba in the wide valley of the lower LCR changed significantly, (2) In the interval 1993 to 2016, the JHB reach exhibited extensive erosion, with the right bank more eroded seriously than the left bank, and an erosion area of 0.36 km2. The erosion area of the GLB reach was 0.33 km2, with accretion area of 0.61 km2. The right bank was dominated by erosion, while the left bank by sedimentation; (3) Morphological changes in JHB and GLB reches were the result of the combined effects of cascade hydropower development, river regulation, and sand-mining in the river. The results improved the understanding of riverbed evolution, and could help guide sediment management in mountainous areas influenced by extensive human activities.