Four kinds of capping materials for controlling phosphorus and nitrogen release from contaminated sediment using a static simulation experiment

• Lanthanum modified bentonite (LMB) can effectively absorb phosphorus (P). • Water treatment plant sludge (WTPS) capping is effective for controlling P release. •Aluminum-based P-inactivation agent (Al-PIA) is an efficient P control material. •The P adsorbed by WTPS and Al-PIA is mainly in the form of NAIP. We determined the effects of quartz sand (QS), water treatment plant sludge (WTPS), aluminum-based P-inactivation agent (Al-PIA), and lanthanum-modified bentonite (LMB) thin-layer capping on controlling phosphorus and nitrogen release from the sediment, using a static simulation experiment. The sediment in the experiment was sampled from Yundang Lagoon (Xiamen, Fujian Province, China), which is a eutrophic waterbody. The total phosphorus (TP), ammonium nitrogen (NH₄⁺-N), and total organic carbon (TOC) levels in the overlying water were measured at regular intervals, and the changes of different P forms in WTPS, Al-PIA, and sediment of each system were analyzed before and after the test. The average TP reduction rates of LMB, Al-PIA, WTPS, and QS were 94.82, 92.14, 86.88, and 10.68%, respectively, when the release strength of sediment TP was 2.26–9.19 mg/(m²·d) and the capping strength of the materials was 2 kg/m². Thin-layer capping of LMB, WTPS, and Al-PIA could effectively control P release from the sediment (P<0.05). However, thin-layer capping of LMB, Al-PIA, and QS did not significantly reduce the release of ammonium N and organic matter (P > 0.05). Based on our results, LMB, Al-PIA, and WTPS thin-layer capping promoted the migration and transformation of easily released P in sediment. The P adsorbed by WTPS and Al-PIA mainly occurred in the form of NAIP.     

Monitoring and estimating the flow conditions and fish presence probability under various flow conditions at reach scale using genetic algorithms and kriging methods

The combination of current velocity and water depth influences stream flow conditions, and fish activities prefer particular flow conditions. This study develops a novel optimal flow classification method for identifying types of stream flow based on the current velocity and the water depth using a genetic algorithm. It is applied to the Datuan stream in northern Taiwan. Fish were sampled and their habitat investigated at the study site during the spring, summer, fall and winter of 2008-2009. The current velocity, water depth and maps of the presence probability of fish were estimated by ordinary and indicator kriging. The optimal classification results were compared with the classification results obtained using the Froude number and empirical methods. The flow classification results demonstrate that the proposed optimal flow classification method that considers depth-velocity and optimally identified criteria for classifying flow types, yields a current velocity and water depth of 0.32 (m/s) and 0.29 (m), respectively, and classifies the flow conditions in the study area as pool, run, riffle and slack. The variography results of the current velocity and the water depth data reveal that seasonal flows are not spatially stationary among seasons in the study area. Kriging methods and a two-dimensional hydrodynamic model (River 2D) with empirical and optimal flow classification methods are more effective than the Froude number method in classifying flow conditions in the study area. The flow condition classifications and probability maps were generated by River 2D, ordinary kriging and indicator kriging, to quantify the flow conditions preferred by Sicyopterus japonicus in the study area. However, the proposed optimal classification method with kriging and River 2D is an effective alternative method for mapping flow conditions and determining the relationship between flow and the presence probability of target fish in support of stream restoration.     

A mathematical model to estimate nitrate release from ocher pellets applied to anaerobic benthic sediment

A mathematical model was developed to estimate nitrate release from ocher pellets in benthic sediment. Ocher pellets, called “limnomedicine,” consisting of ocher and calcium nitrate were used to suppress phosphorus release from contaminated sediment under anaerobic conditions. The proposed model represents the fate and transport of nitrate released from the pellets, in both the water column and the sediment. Most of the nitrate (83.6%) released from the pellets was consumed in the degradation of organic matter and FeS in the sediment over a period of 12 days. While an increase in pellet dosage helps to accelerate the sediment treatment rate, it also has the effect of increasing the mass of nitrate that diffuses into the water column. Quantitative analysis of these effects using the proposed mathematical model makes it possible to determine the proper pellet dosage based on sediment conditions such as organic matter content.     

微孔曝气与覆盖对城市重污染河道底泥磷形态分布及释放过程的影响

采用自行研发的泥-水界面微孔曝气系统,开展了底泥表面曝气和覆盖对城市重污染河道底泥磷释放及形态分布规律的影响研究.结果表明,微孔曝气能够有效提高上覆水的溶解氧(DO)和沉积物的氧化还原电位(Eh),能够将泥-水界面Eh维持在-100 m V左右,DO提高到6 mg·L-1以上.与对照比较,原位覆盖处理的上覆水DO和Eh有一定提高,但仍明显低于微孔曝气处理.与对照相比较,微孔曝气处理均有效降低上覆水中总磷(TP)和溶解性正磷酸盐(PO3-4)的含量.试验结束时,微孔曝气(A)和微孔曝气+原位覆盖处理(A+C)上覆水中TP含量由初始的0.201 mg·L-1分别降至0.062 mg·L-1和0.050 mg·L-1;上覆水中PO3-4含量由0.086 mg·L-1和0.078 mg·L-1分别降至0.026 mg·L-1和0.023 mg·L-1.与对照相比,微孔曝气处理明显降低了底泥间隙水中TP的浓度,在整个培养期间,其TP含量平均下降38.8%(A)和47.9%(A+C).底泥原位覆盖处理对抑制泥-水界面磷释放能力要弱于微孔曝气处理,而且在试验后期(50 d),上覆水中TP和PO3-4的含量均有所反弹.不管有无覆盖,泥-水界面微孔曝气处理均显著改变了表层底泥磷形态分布特征,显著降低了底泥中铁铝结合态磷(Fe/Al-P)组分比例,而钙结合态磷(Ca-P)含量比例却出现明显增加.单一的表面覆盖处理对底泥磷形态分布特征没有显著影响(P0.05).研究表明,与单一的处理效果相比较,泥-水界面纳米微孔曝气处理,并结合底泥原位覆盖,更有利于抑制城市重污染河道泥-水界面中磷的释放风险.     

The application of artificial neural networks to flow and phosphorus dynamics in small streams on the Boreal Plain,with emphasis on the role of wetlands

Historically, management strategies in Canada's boreal forest have focused on forest polygons and terrestrial biodiversity to address ecological considerations in forest management. The Forest Watershed and Riparian Disturbance (FORWARD) project examines the problem from a watershed perspective rather than a forest polygon viewpoint. The main objective of this study was to devise an artificial neural network (ANN) modeling tool that can predict flow and total phosphorus (TP) concentration for ungauged watersheds (where daily flow is not monitored). This dictates that all inputs should be easily accessed via a public domain database, like the Environment Canada weather database, without the need to install flow gauges in each modeled watershed. Daily flow and TP concentration for two of the project watersheds were modeled using ANNs. The two watersheds (1A Creek, 5.1 km² and Willow Creek, 15.6 km²) were chosen to reflect variations in wetland area and composition in the study area. Flow was modeled with a feed-forward multilayer perceptron ANN trained with the error back-propagation algorithm. Simulated values for flow were then used, as inputs, to model TP concentration using the same neural networks algorithm. One hidden layer with three slabs; each operating with a different activation function was utilized to simulate the conceptual differences between base flow, snowmelt, and storm events. Time domain analysis was conducted to identify possible model time-lagged inputs reflecting the time dependency of the modeled variables. Spectral analysis was used to address data hystereses. Our results highlight the capabilities of ANN in modeling complex ecosystems and highly correlated variables. Results also indicated that more research towards the phosphorus dynamics in wetlands is required to better represent the impact of wetland area and composition on the water-phase phosphorus in ANN modeling.     

Using algal biomass-phosphorus (P) relationships and nutrient limitation theory to evaluate the adequacy of P water quality criteria for regulated monsoon rivers and reservoirs

Different P criteria have been set for lotic and lentic waters where the latter had stricter criteria than the former. The binary P criteria have been developed due to differences in limnological features and this helps avoid unneeded costs with stricter criteria for flowing waters that normally have lower potential of algal blooms. However, if different criteria are warranted, the responses of Chl a to TP and TN:TP ratio should vary distinctively between rivers and reservoirs. Contrary to these predictions, inconsistent and statistically indistinguishable variations have been observed between the two types of waterbody in Chl a yield per unit TP. Additionally, there was no significant difference in the strength of relationship between Chl a and TN:TP ratio between waterbody types, although the mass ratio of TN to TP was significantly higher in reservoirs than in rivers. Hence, the data suggest that there is no scientifically defensible reason that lotic and lentic waters require different TP standards and specifically that lentic waters do not necessarily require stricter P criteria. A more holistic and nuanced approach would aid in developing revised or new TP criteria in which water quality issues can be addressed scientifically as well as pragmatically.     

Water-level based discrete integrated dynamic control to regulate the flow for sewer-WWTP operation

• A model-free sewer-WWTP integrated control was proposed. • A dynamic discrete control based on the water level was developed. • The approach could improve the sewer operation against flow fluctuation. • The approach could increase transport capacity and enhance pump efficiency. This study aims to propose a multi-point integrated real-time control method based on discrete dynamic water level variations, which can be realized only based on the programmable logic controller (PLC) system without using a complex mathematical model. A discretized water level control model was developed to conduct the real-time control based on data-automation. It combines the upstream pumping stations and the downstream influent pumping systems of wastewater treatment plant (WWTP). The discretized water level control method can regulate dynamic wastewater pumping flow of pumps following the dynamic water level variation in the sewer system. This control method has been successfully applied in practical integrated operations of sewer-WWTP following the sensitive flow disturbances of the sewer system. The operational results showed that the control method could provide a more stabilized regulate pumping flow for treatment process; it can also reduce the occurrence risk of combined sewer overflow (CSO) during heavy rainfall events by increasing transport capacity of pumping station and influent flow in WWTP, which takes full advantage of storage space in the sewer system.     

Current uses of the EPA lead model to assess health risk and action levels for soil

The EPA lead model predicts mean blood lead levels and risk of elevated blood lead levels in children based on lead uptake from multiple sources. In the latest model versions, environmental data from individual homes within a community can be used to predict the overall blood lead distribution and percent risk of exceeding a specific blood lead level (i.e. 10 g dl^–1). Recent criteria used by the EPA to evaluate this information include no more than 5% of houses with a greater than 5% lead risk, and a community weighted-average risk below 5%. Environmental (primarily soil) and blood lead data from a residential community near a smelter were used to illustrate recent uses of the model. Scheduled remediation in the community will remove soil for approximately 60% of the houses (i.e. those with lead levels > 1000 mg kg^–1). After remediation, the model results indicate a relatively low community risk (0.5–1.9%), although the percentage of houses with lead risks above 5% ranged from 3 to as high as 13%, depending on the variation in blood lead and assuming the model's 7 g dl^–1 increase in blood lead with each 1000 mg kg^–1 increase in soil lead level. A comparison of the limited blood lead data with soil lead levels below 1000 mg kg^–1, however, indicated no apparent relationship. Given these uncertainties, less invasive actions than additional soil removal (e.g. exposure intervention, monitoring conditions, and follow-up as necessary) may be appropriate under the new EPA guidance for lead in soil.     

脱硫石膏改良碱化土壤种植水稻施用量研究

选择具有典型代表性的宁夏西大滩碱化土壤,采用拉丁方田间试验设计进行脱硫石膏改良碱化土壤种植水稻(Oryza sativa)的施用量研究.试验研究表明施用脱硫石膏能够降低土壤碱化度、总碱度和pH值,提高水稻的出苗率和产量.但是,脱硫石膏施用量不同,土壤碱化度、总碱度和pH值降低的值不同.根据脱硫石膏施用量与土壤碱化度、总碱度、pH值降低的模拟曲线关系,当脱硫石膏施用量为2.8～3.1kg·m~(-2)时,土壤碱化度、总碱度、pH值降低的值达到最大.同时,根据脱硫石膏施用量与水稻出苗率和产量的模拟曲线关系,当脱硫石膏施用量为2.86kg·m~(-2),水稻出苗率达到最大,为84.7%;当脱硫石膏施用量为2.79kg·m~(-2)时,水稻产量达到最大,为0.75kg·m~(-2).因此,建议脱硫石膏改良碱化土壤种植水稻的施用量为2.8～3.1kg·m~(-2).     

Global perspectives and future research directions for the phytoremediation of heavy metal-contaminated soil: A knowledge mapping analysis from 2001 to 2020

• The overall global perspective of the PHMCS field was obtained. • PHMCS research has flourished over the past two decades. • In total, 8 clusters were obtained, and many new hot topics emerged. • “Biochar,” “Drought,” “Nanoparticle,” etc., may be future hot topics. • Five future directions are proposed. In total, 9,552 documents were extracted from the Web of Science Core Collection and subjected to knowledge mapping and visualization analysis for the field of phytoremediation of HM-contaminated soil (PHMCS) with CiteSpace 5.7 R3 software. The results showed that (1) the number of publications increased linearly over the studied period. The top 10 countries/regions, institutions and authors contributing to this field were exhibited. (2) Keyword co-occurrence cluster analysis revealed a total of 8 clusters, including “Bioremediation,” “Arsenic,” “Biochar,” “Oxidative stress,” “Hyperaccumulation,” “EDTA,” “Arbuscular mycorrhizal fungi,” and “Environmental pollution” clusters (3) In total, 334 keyword bursts were obtained, and the 25 strongest, longest duration, and newest keyboard bursts were analyzed in depth. The strongest keyword burst test showed that the hottest keywords could be divided into 7 groups, i.e., “Plant bioremediation materials,” “HM types,” “Chelating amendments,” “Other improved strategies,” “Bioremediation characteristics,” “Risk assessment,” and “Other.” Almost half of the newest topics had emerged in the past 3 years, including “biochar,” “drought,” “health risk assessment,” “electrokinetic remediation,” “nanoparticle,” and “intercropping.” (4) In total, 9 knowledge base clusters were obtained in this study. The studies of Ali et al. (2013), Blaylock et al. (1997), Huang et al. (1997), van der Ent et al. (2013), Salt et al. (1995), and Salt (1998), which had both high frequencies and the strongest burst scores, have had the most profound effects on PHMCS research. Finally, future research directions were proposed.