Optimizing backwash control using data on seasonal changes in the invertebrate community of granular activated carbon filters.

Problems associated with the colonization and leakage of invertebrates in the granular activated carbon (GAC) filters of waterworks have received increased attention in recent years. To study the effect of environmental factors and water quality on invertebrate abundances, and the backwash control for minimizing invertebrate abundance. A survey of the invertebrate community of GAC filters was carried out monthly from March 2021 to May 2022. A pilot-scale GAC system established in the laboratory alongside a lake, with a volume of 35.3 L. 45 invertebrate species were detected, and 40 of these were rotifers. Significant variation in abundance was observed among seasons before and after GAC filtration, the average invertebrate abundance in the inlet water was 11.1 times that in the filtrate. The GAC filter contained invertebrates that might be responsible for the large number of organisms in the filtrate. Invertebrate abundance in the GAC filter decreased gradually with the carbon layer depth, which the mean invertebrate abundances were 6,926, 5,232, and 3818 ind./kg in the top layer (TL), middle layer (ML), and bottom layer (BL), respectively. Invertebrate abundance was correlated with water temperature and varied seasonally. Among eight water quality parameters, chlorophyll a (Chla) and the total plate count (TPC) were most significantly correlated with invertebrate abundance. According to the statistical modeling and the optimization process of response surface methodology (RSM). The predicted optimal values were a flow rate of 6.36 L/h, a backwash cycle of 3.26 d, and a backwash intensity of 14.97 L/(m2·s) for a minimum invertebrate abundance of 3013 ind./kg in the GAC filter. To maintain invertebrate abundance within an acceptable range, some of these measures might need to be modified depending on the actual conditions.

Influence of seasonal activities and traffic conditions on the accumulation and particle size distribution of gully pot sediments.

Gully pots (GPs) are ubiquitously used in urban catchments, to direct surface runoff into piped sewer systems, reduce the risk of sediment-induced pipe blockages and the loading of solids and associated contaminants on the receiving waters. Over time, the build-up of sediments in GPs will lead to impaired hydraulic performance, putting the urban catchment at risk of flooding. However, GP maintenance strategies lack both a robust evidence base and clear aims against which their effectiveness can be benchmarked. An improved understanding of the factors influencing long-term in-situ solids accumulation in GPs is required for further assessment and optimisation of the GP maintenance scheme. As a contribution to addressing these knowledge gaps, sediments from 27 GPs located in urban catchments associated with three street feature types (roundabout; crossing; straight road) and varied traffic intensities were collected on two occasions, representing two distinct seasonal accumulation periods. Parameters including GP fullness levels, particle size distribution (PSD), and solids mass accumulation rates were evaluated with regards to the impacts of seasonal activities, traffic conditions as well as configuration and dimension of GPs. The results indicate impacts of seasonal activities on solids accumulation rates were not consistent across all GPs, with the magnitude of the difference larger following winter-spring catchment practices. Additionally, synergistic impacts of seasonal activities and traffic conditions on PSD and solids accumulation rates were observed. For example, the winter road safety measures may enhance the impacts of the characteristic vehicle turning motions at roundabouts, contributing to the negative correlation identified between traffic intensities and solids accumulation rates. The overall exhibited large variations in sump fullness levels (4 %-73 %) and solids dry mass (0.5-51 kg) directly challenged the commonly adopted generalised GP maintenance frequency without taking the catchment-specific activities into consideration.

Accumulation and contamination of gully pot sediments from varied land-use types: metal loads, concentrations and speciation.

Urban stormwater typically enters sewer networks through gully pots, which allow a primary sedimentation of solids upstream of the piped network. The regular removal and disposal of retained sediment are necessary, costly and can involve environmental risks due to the contamination of sediments with substances from the urban environment such as metals. The concentrations and speciation of Cd, Cr, Cu, Ni, Pb and Zn were analysed in sediments from 26 gully pots located in different land use areas in Stockholm, Sweden. In addition, accumulation rates of both sediment and metal masses were evaluated, providing a basis for optimising maintenance practices and better understanding of impacts of characteristic urban land use types. Metal concentrations varied by at most a factor of eight between samples and were always below Swedish polluted site guidelines for less sensitive land use, with only eight samples exceeding the guideline values for Cu and Zn for sensitive land use. Sequential extraction showed Pb and Zn to be the most mobile metals. Sediment accumulation rates varied from 0.003 to 0.197 kg/m2 impermeable surface/year. Metal accumulation rates were much more variable than metal concentrations, with a factor of up to 172 between the highest and lowest rates and the highest metal accumulation rates corresponding to the lower range of mass loads in road runoff. Differences in metal concentrations, sediment or metal mass accumulations could not be solely attributed to either traffic or catchment land use. In contrast, traction grit used for winter road maintenance, which has low (but detectable) metal concentrations, is identified as a major component of gully pot sediments, with a combined effect of both moderating metal concentrations and contributing to total mass.

Are wastewater treatment plants as the source of microplastics in surface water and soil?

Microplastics (MPs) are widely detected in wastewater treatment plants (WWTPs) and natural environment, while the relationship of MPs pollution in both media is not fully understood. In this study, the occurrence of MPs in WWTPs and in surface water and soil was investigated, and their relationship was critically formulated. Results showed although wastewater treatment could effectively remove MPs (58.2%), the effluent was still the important source of MPs in the river, while sludge was not as important as the effluent of MPs in the soil. Specifically, the dominant size ranges of MPs were 0-200 µm, with main type of PE in all wastewater, sludge, river and soil. The dominant shape of MPs in wastewater and river was film. However, the shapes were different between sludge (52.1% of fibers) and soil (40.6% of fragment). Overall, WWTP input and surface runoff were the main source of MPs pollution in surface water, and the abrasion of agricultural films accounted for the MPs pollution in soil. The findings revealed the distribution and interconnection of MPs in WWTPs and environmental media, which could help to trace the sources of MPs pollution and assess the ecological risks in the environment.

A study of 101 organic substances in gully pot sediments accumulated over a one-year period in Stockholm, Sweden.

Stormwater runoff is a key pathway for diffuse pollutants to enter receiving waters. Mitigating measures include pollutant substitution, restricting their release into the urban technosphere and limiting the (re-)mobilisation of substances to minimise their negative impacts on receiving waters. Gully pots (GPs) are one of the most ubiquitous urban drainage infrastructure components, providing both a drainage function and limiting the onward transport of pollutants through in-pot sedimentation processes. In this study, sediments accumulated over a one-year period were collected from 26 GPs in catchments of four land-use types in Stockholm, Sweden. Sediments were analysed for 101 organic substances from eight substance groups (hydrocarbons, polycyclic aromatic hydrocarbons, alkylphenols, polychlorinated biphenyls, phthalates, organotins, per- and polyfluoroalkyl substances and brominated fire retardants) to inform an assessment of their occurrence and net accumulation rates over a typical unit operation period. A total of 63 substances were quantified in at least one GP, with aliphatic hydrocarbons, phthalates and organotins quantified in all GP sediments, highlighting their ubiquitous use. The identification of 14 and 21 organic substances in two pedestrian/bike path GPs emphasise the contribution of non-vehicular sources to diffuse pollutant loads. Significantly higher mass accumulation rates of 4-tert-octylphenol, 4-nonylphenols, formaldehyde, dioctyltin and dibutyltin are identified in commercial catchment GPs suggesting the need to enhance source-tracing and runoff quality-control measures within catchments of this land-use type. Sediments in 25 GPs were identified with at least one substance exceeding toxicology-based threshold values, highlighting the runoff quality-control function of GPs in reducing the potential ecotoxic impacts on recipients.

Experimental optical encryption based on random mask encoding and deep learning.

We present an experimental scheme for optical encryption using random mask encoding and deep learning technique. A phase image is encrypted into a speckle pattern by a random amplitude modulation in the optical transmission. Before decryption processing, a neural network model is used to learn the mapping relationship between the pure-phase object and the speckle image rather than characterizing the filter film used in the scheme explicitly or parametrically. The random binary mask is made by a polyethylene terephthalate film and 2500 object-speckle pairs are used for training. The experimental results demonstrate that the proposed scheme based on deep learning could be successfully used as a random binary mask encrypted image processor, which can quickly output the primary image with high quality from the cyphertext.

An evaluation of temporal changes in physicochemical properties of gully pot sediments.

Diffuse pollution is recognised as a major challenge in achieving EU Water Framework Directive compliance, with urban runoff being a key pathway connecting various sources to receiving waters. Gully pots, as one of the ubiquitous urban drainage infrastructures, are placed at the inlets of piped drainage pipe network and actively drain runoff from urban catchment with suspended solids proportionally retained. The physiochemical properties of these retained solids reflect the activities within the catchment during the accumulation period. In this work, seven gully pots in two catchment types (highway and housing) in Luleå, Sweden were fully emptied and sediments analysed for total mass, particle size distribution and selected metal concentrations by six size fractions. The results of this sampling campaign are compared with the results of a 2005 study of the same gully pots to identify changes in the physicochemical properties of sediments over time and examine whether changes identified can be linked to changes in wider catchment management practices. The results highlight the potential impacts of winter road maintenance operations (e.g. up to a 15-fold higher solids loading rate in road catchment gully pots), reaching a normalised solids accumulation rate of 0.176-0.819 kg m2 year-1. An increase in tyre and road wear associated with winter road maintenance operations is also understood to contribute to the temporal increase of several metals including Cu, Zn, Co, Cr and V in the < 63-µm solids fraction in the road catchment gully pots. The concentrations of As and Pb decrease in all size fractions in both catchments, with the implementation of unleaded fuels (for Pb in housing catchment only), End-of-Life Vehicle Directive (Directive 2000/53/EC) (for Pb in both catchments), and strengthened industrial emission reduction measures suggested as possible drivers. The high contamination load for Zn, Cu, Cd and Pb in < 63-µm sediments from low-traffic housing catchment also emphasised the necessity of tracing and restricting non-traffic-related metal sources. Further seasonal monitoring of gully pot sediments is recommended to fully follow up the development of metals loading in both catchments.

Alteration in microbial community and antibiotic resistance genes mediated by microplastics during wastewater ultraviolet disinfection.

Microplastics (MPs) could be as a vector to colonize microorganisms and antibiotic resistance gene (ARGs) in surface water. However, little information is known regarding their changes by the presence of MPs in wastewater treatment. Here, the effects of different concentrations and sizes of polystyrene microplastics (PSMPs) on the distribution and removal of microbial communities and ARGs under ultraviolet disinfection of urban sewage have been systematically studied. Results showed that the presence of MPs altered abundance and functions of microorganisms in wastewater, despite different effects on different types of microorganisms. The most abundant ARGs in original disinfection tank sewage was rpoB2 (6.34%). A certain concentration range of MPs can improve the ability of specific types of ARGs in the UV disinfection process. Compared to the system without PSMPs, the content of Deinococcus-Thermus and Bacteroidetes phylum increased, while Actinobacteria and Proteobacteria phylum decreased in the presence of MPs. The microbial functions, especially the genetic information processing and metabolism were altered by the presence of PSMPs. In addition, PSMPs altered the content of ARGs, where the contents of OXA-182 and ErmH were increased, while adeF and ANT3-Iic were decreased. PSMPs also decreased the free ARB content in wastewater by providing colonization sites. The UV disinfection efficiency of microorganisms and ARGs was also intervened by PSMPs since they provided colonization sites and increased the water turbidity. The findings indicated that PSMPs altered the distribution and removal of microbial community and ARGs in ultraviolet disinfection of wastewater, highlighting the combined risks.

Holographic and speckle encryption using deep learning: publisher's note.

This publisher's note contains a correction to Opt. Lett.46, 5794 (2021)10.1364/OL.443398.

Holographic and speckle encryption using deep learning.

Vulnerability analysis of optical encryption schemes using deep learning (DL) has recently become of interest to many researchers. However, very few works have paid attention to the design of optical encryption systems using DL. Here we report on the combination of the holographic method and DL technique for optical encryption, wherein a secret image is encrypted into a synthetic phase computer-generated hologram (CGH) by using a hybrid non-iterative procedure. In order to increase the level of security, the use of the steganographic technique is considered in our proposed method. A cover image can be directly diffracted by the synthetic CGH and be observed visually. The speckle pattern diffracted by the CGH, which is decrypted from the synthetic CGH, is the only input to a pre-trained network model. We experimentally build and test the encryption system. A dense convolutional neural network (DenseNet) was trained to estimate the relationship between the secret images and noise-like diffraction patterns that were recorded optically. The results demonstrate that the network can quickly output the primary secret images with high visual quality as expected, which is impossible to achieve with traditional decryption algorithms.

An assessment of gully pot sediment scour behaviour under current and potential future rainfall conditions.

Gully pots actively trap sediments transported by urban runoff to prevent in-pipe blockages and surface flooding. However, due to poor maintenance (resulting in sediment build-up) and increasingly extreme wet weather events, the scour of previously-deposited sediments from gully pots is identified as a potential contributor to EU Water Framework Directive failure. While basal sediment scour deterministic models have been developed and validated using laboratory and field gully pot data sets, the ability of these models to predict behaviour at sites other than those for which they were established has not been addressed. Nor has the impact of future rainfall predictions on the role of gully pots as sediment sources been systematically examined. As a contribution to addressing these knowledge gaps, the performance of two gully pot basal sediment scour models of distinct complexity levels are evaluated under current and future rainfall conditions. The output from Model One suggests that the scour-induced total suspended solids in gully pot discharge can be kept well below 25 mg/L if the gully pot fullness level is maintained at under 60%. Results identify the opportunity to incorporate the actual/targeted ecological status of recipients in scheduling gully pot maintenance operations and that proactive gully pots maintenance will reduce the impacts of increased rainfall intensity/duration on the magnitude of sediment scour. Results from Model Two suggest that fine sediments are particularly susceptible to in-pot scour. For example, sediment with a specific gravity of 1.1 and diameter of >63 µm accounts for 50% of scour-induced total suspended solids in gully pot discharge. The effluent suspended solids concentrations predicted by the two models differ by up to two orders of magnitude. However, without further empirical field data pertaining to their respective competences/applications, neither model could be discounted at this stage. For example, the use of Model One is more appropriate in the establishment of gully pot maintenance schedules, with Model Two more suited to the dimensioning of gully pots based on performance requirements. This application, however, relies on the development and adoption of a more stringent regulation on gully pots discharge.

Sparse Density Estimation with Measurement Errors.

This paper aims to estimate an unknown density of the data with measurement errors as a linear combination of functions from a dictionary. The main novelty is the proposal and investigation of the corrected sparse density estimator (CSDE). Inspired by the penalization approach, we propose the weighted Elastic-net penalized minimal ℓ2-distance method for sparse coefficients estimation, where the adaptive weights come from sharp concentration inequalities. The first-order conditions holding a high probability obtain the optimal weighted tuning parameters. Under local coherence or minimal eigenvalue assumptions, non-asymptotic oracle inequalities are derived. These theoretical results are transposed to obtain the support recovery with a high probability. Some numerical experiments for discrete and continuous distributions confirm the significant improvement obtained by our procedure when compared with other conventional approaches. Finally, the application is performed in a meteorology dataset. It shows that our method has potency and superiority in detecting multi-mode density shapes compared with other conventional approaches.

Alternating Electric Field-Based Static Gesture-Recognition Technology.

Currently, gesture recognition based on electric-field detection technology has received extensive attention, which is mostly used to recognize the position and the movement of the hand, and rarely used for identification of specific gestures. A non-contact gesture-recognition technology based on the alternating electric-field detection scheme is proposed, which can recognize static gestures in different states and dynamic gestures. The influence of the hand on the detection system is analyzed from the principle of electric-field detection. A simulation model of the system is established to investigate the charge density on the hand surface and the potential change of the sensing electrodes. According to the simulation results, the system structure is improved, and the signal-processing circuit is designed to collect the signal of sensing electrodes. By collecting a large amount of data from different operators, the tree-model recognition algorithm is designed and a gesture-recognition experiment is implemented. The results show that the gesture-recognition correct rate is over 90%. With advantages of high response speed, low cost, small volume, and immunity to the surrounding environment, the system could be assembled on a robot that communicates with operators.