Illicit Connections Research Articles

Transparent Corruption: The Effect of Illicit Connections and Trusted References on the Demand for Bureaucratic Intermediation

Abstract This article investigates the effect of priming the existence of corrupt connections to the bureaucracy and of trusted references on the demand for intermediary services. We performed an experimental survey with undergraduate students in Caracas, Venezuela. Participants are presented with a hypothetical situation in which they need to obtain the apostille of their professional degrees in order to migrate and are considering whether to hire an intermediary (“gestor”) or not. The survey randomly reveals the existence of an illicit connection between the gestor and the bureaucracy and whether a trusted individual referred the intermediary. Our findings are not consistent with the “market maker” hypothesis that revealing the existence of illicit connections increases demand. Consistent with the view that trust is a key element in inherently opaque transactions, we find that the demand for intermediaries is price inelastic when gestores are referred by trusted individuals.

Advancing illicit connection diagnosis of urban stormwater pipes: Comprehensive analysis with EEM fluorescence spectroscopy

Urban drainage systems are significant contributors to the issue of black-odorous water bodies. The current application of stormwater pipe inspection technologies faces substantial limitations, especially in industrial areas with diverse wastewater. This study introduced an innovative approach using excitation-emission matrix (EEM) fluorescence spectroscopy for rapid and accurate diagnosis, providing a new perspective for diagnosing illicit connections. In single wastewater-type areas like residential zones, the method achieved a remarkable 91.5 % accuracy solely through spectra observation and fluorescence peak intensity comparison, outperforming conventional NH3-N-based techniques, which reached an accuracy of only 68.1 %. For regions with complex wastewater scenarios, after EEM subtraction, the residual spectra can be roughly categorized into four distinctive categories based on characteristics. This provides a preliminary assessment and helps in initially identifying the types and sources of inflowing wastewater. Furthermore, the least squares (LS) method refines diagnosis results, offering calculated coefficients reflecting the probability and severity of suspected wastewater intrusion. Simulation experiments and field sample analyses validated the feasibility and accuracy of the EEM-based method, highlighting its advantages for diagnosing illicit connections in both single and mixed wastewater scenarios. The results can significantly narrow down the investigation scope and enhance the confirmation of wastewater sources, exhibiting promising application prospects.

Simultaneous mitigation of multiple pollutants in urban stormwater systems illicitly connected with wastewater systems by an Fe(vi)-based process

The illicit connection of wastewater pipes to stormwater pipes might result in the direct discharge of wastewater into natural water and even drinking water sources.

Tracking the source of antibiotic resistome in the stormwater network drainage in the presence of sewage illicit connections

Stormwater pipes are illicitly connected with sewage in many countries, which means that sewage enters stormwater pipes and the drainage is discharged to surface water without any treatment. Sewage contains more pathogens and highly risky antibiotic resistance genes (ARGs) than surface runoff. Therefore, sewage may alter the microbial and ARG compositions in stormwater pipe drainage, which in turn leads to an increased risk of resistance in surface water. However, the effects of sewage on ARGs in the drainage of stormwater networks have not been systematically studied. This study characterized the microbial and ARG composition of several environmental compartments of a typical stormwater network and quantified their contributions to those in the drainage. This network transported ARGs and microorganisms from sewage, sediments in stormwater pipes, and surface runoff into the drainage and thus into the river. According to metagenomic analysis, multidrug resistance genes were most abundant in all samples and the numbers and relative abundance of ARGs in the drainage collected during wet weather were comparable to that of sewage. The results of SourceTracker showed that the relative contribution of sewage was double that of rainwater and surface runoff in the drainage during wet weather for both microorganisms and ARGs. Desulfovibrio, Azoarcus, and Sulfuritalea were connected with the greatest number of ARGs and were most abundant in the sediments of stormwater pipes. Furthermore, stochastic processes were found to dominate ARG and microbial assembly, as the effects of high hydrodynamic intensity outweighed the effects of environmental filtration and species interactions. The findings of this study can increase our understanding of ARGs in stormwater pipe drainage, a crucial medium linking ARGs in sewage to environmental ARGs.

A comparative study between low- and high-tech methods for the detection and mitigation of illicit connections in stormwater systems.

Illicit connections of wastewater to stormwater systems are the main drawback of separate sewer systems, as they lead to a direct discharge of untreated wastewater to the aquatic environment. Consequently, several inspection methods have been developed for detecting illicit connections. This study simultaneously applied several low- and high-tech methods for the detection of illicit connections in the same catchment (De Heuvel, the Netherlands). The methods included mesh wire screens for capturing coarse contamination, measurements of electroconductivity and temperature, sampling and quantification of Escherichia coli and extended-spectrum ß-lactamase-producing E. coli (ESBL-EC), DNA analysis via quantitative polymerase chain reaction for human-, dog-, and bird-specific fecal indicators, and distributed temperature sensing. Significant illicit connections could be identified using all methods. Nonetheless, hydraulic conditions and, predominantly, the sewage volume determine whether a misconnection can be detected by especially the low-tech methods. Using these results, the identified misconnections were repaired and biological and DNA analyses were repeated. Our results demonstrate that there were no changes in E. coli or ESBL-EC before and after mitigation, suggesting that these common markers of fecal contamination are not specific enough to evaluate the performance of mitigation efforts. However, a marked decrease in human wastewater markers (HF183) was observed.

Direct discharge of sewage to natural water through illicitly connected urban stormwater systems: An overlooked source of dissolved organic matter

The illicit connection of sewage pipes to stormwater pipes commonly occurs in urban stormwater systems. This brings problems that sewage might be directly discharges into natural water and even drinking water sources without treatment, posing risks to ecological safety. Sewage contains various unknown dissolved organic matter (DOM), which could react with disinfectants and lead to the formation of carcinogenic disinfection byproducts (DBPs). Thus, understanding the impacts of illicit connections on downstream water quality is of significance. This study firstly investigated the characteristics of DOM using fluorescence spectroscopy and the formation of DBPs after chlorination in an urban stormwater drainage system in the case of illicit connections. The results found that the concentrations of dissolved organic carbon and dissolved organic nitrogen ranged from 2.6 to 14.9 mg/L and from 1.8 to 12.6 mg/L, respectively, with the highest levels occurring at the illicit connection points. Concerning DBP precursors, pipe illicit connections introduced considerable precursors of highly toxic haloacetaldehydes and haloacetonitriles into the stormwater pipes. Furthermore, illicit connections introduced more contents of tyrosine-like and tryptophan-like aromatic proteins, which may be related to foods, nutrients, personal care products, etc. in the untreated sewage. This indicated that the urban stormwater drainage system was a significant input source of DOM and DBP precursors to natural water. The results of this study are of great significance for protecting the security of water sources and promoting the sustainability of urban water environment.

Locating illicit discharges in storm sewers in urban areas using multi-parameter source tracking: Field validation of a toolbox composite index to prioritize high risk areas

In urban areas served by separate sewerage systems, illicit connections to the storm drain system from residences or commercial establishments are frequent whether these misconnections were made accidentally or deliberately. As a result, untreated and contaminated wastewater enters into storm sewers leading to pollution of receiving waters and non-compliance with water quality standards. Typical procedures for detecting illicit connections to the storm sewer system are time consuming and expensive, especially in a highly urbanised area. In this study, we investigated the use of human wastewater micropollutants WWMPs (caffeine, theophylline, and carbamazepine) and advanced DNA molecular markers (human specific Bacteroides HF183 and mitochondrial DNA) as anthropogenic tracers in order to assist identifying potential cross connections.Water samples from storm outfalls and storm sewer pipes in three urban subcatchments were collected in dry weather from 2013 to 2018. All samples contained various concentrations of these markers especially HF183, caffeine and theophylline, suggesting that the storm pipe system studied is widely contaminated by sanitary sewers. None of the traditional indicators or markers tested is sufficient alone to determine the origin of fecal pollution. In a highly urbanised area, the combination of at least three specific human markers was needed in order to locate the residential section with likely misconnections. The human specific Bacteroides HF183, and theophylline appeared to be the most effective markers (along with E. coli) of crossconnections, whereas carbamazepine can provide an indication of contamination through sanitary sewer exfiltration. A composite sewer cross-connection index was developed, and eight misconnected houses were identified and corrected. The index approach enables the reduction of false positives that could lead to expensive interventions to identify cross-connected households. The results show the multiparameter source tracking toolbox as an effective method to identify sewer cross connections for sustainable storm water management.

A Flow-based Multi-agent Data Exfiltration Detection Architecture for Ultra-low Latency Networks

Modern network infrastructures host converged applications that demand rapid elasticity of services, increased security, and ultra-fast reaction times. The Tactile Internet promises to facilitate the delivery of these services while enabling new economies of scale for high fidelity of machine-to-machine and human-to-machine interactions. Unavoidably, critical mission systems served by the Tactile Internet manifest high demands not only for high speed and reliable communications but equally, the ability to rapidly identify and mitigate threats and vulnerabilities. This article proposes a novel Multi-Agent Data Exfiltration Detector Architecture (MADEX), inspired by the mechanisms and features present in the human immune system. MADEX seeks to identify data exfiltration activities performed by evasive and stealthy malware that hides malicious traffic from an infected host in low-latency networks. Our approach uses cross-network traffic information collected by agents to effectively identify unknown illicit connections by an operating system subverted. MADEX does not require prior knowledge of the characteristics or behavior of the malicious code or a dedicated access to a knowledge repository. We tested the performance of MADEX in terms of its capacity to handle real-time data and the sensitivity of our algorithm’s classification when exposed to malicious traffic. Experimental evaluation results show that MADEX achieved 99.97% sensitivity, 98.78% accuracy, and an error rate of 1.21% when compared to its best rivals. We created a second version of MADEX, called MADEX level 2, that further improves its overall performance with a slight increase in computational complexity. We argue for the suitability of MADEX level 1 in non-critical environments, while MADEX level 2 can be used to avoid data exfiltration in critical mission systems. To the best of our knowledge, this is the first article in the literature that addresses the detection of rootkits real-time in an agnostic way using an artificial immune system approach while it satisfies strict latency requirements.

Diagnosis of pipe illicit connections and damaged points in urban stormwater system using an inversed optimization model

Pipe illicit connection and pipe damage are common issues in urban stormwater systems. This challenge brings problems that sewage directly discharges into river and groundwater infiltration occupies drainage capacity. The major task of solving these critical issues is to locate these illicit connections and damaged points. However, the conventional method for direct detection of problem points is expensive and ineffective. Therefore, there is an urgent demand for a critical method to diagnose the illicit connections and damaged points of the pipes. This study developed an effective inversed optimization model to easily and precisely diagnose and locate their place. The inversed algorithm in the model is a trial-and-error method using automatic iteration to optimize its calculation. Firstly, a chemical mass balance model1 (CMB) based on Monte Carlo algorithm is built to calculate the overall illicit sewage and groundwater infiltration flow of stormwater system. Then, an inversed optimization model is established to locate the high-risk accumulation areas of illicit connection and pipe damage. The inversed optimization model consists of USEPA Stormwater Management Model2(SWMM), a Python language software package for SWMM3 (PySWMM) and microbial genetic algorithm4 (MGA), called SWMM-PySWMM-MGA.

Characterization of Localities with a High Likelihood of Illicit Connections between Runoff and Sewage Systems.

Flooding of the sewage system is an environmental hazard often caused by illegal connections between drainage and sewage systems. The timely detection of such illicit connections, often done by property owners in an attempt to remove rainwater promptly from their private courtyards, is a complex task due to the high cost of field surveying and limited manpower of environmental law-enforcement authorities. This paper suggests an empirical approach to the identification and characterization of localities with an elevated likelihood of illegal connections between runoff and sewage systems. The proposed approach is implemented in three stages. First, the association between rainfall and the amount of wastewater arriving to sewage treatment facilities from different localities is analyzed. Next, regression residuals are investigated, to identify localities with an especially strong association between the amount of rainfall and sewage surplus. The identified localities are then analyzed, to determine their geographic location, physical and socioeconomic attributes. In the present study, the proposed approach is tested using data for 623 urban and rural localities in Israel. As the study shows, the probability of association between the amount of rainfall and sewage surplus, which we consider as an indicator of pirate connections between drainage and sewage systems, tends to increase as a function of socioeconomic welfare of the local residents, surface slope, and the level of urbanization. The proposed approach can help law-enforcement authorities to focus their efforts on specific locations and to reduce economic and environmental damages associated with illegal connections between drainage and sewage systems.

Detection of extraneous water ingress into the sewer system using tandem methods - a case study in Trondheim city.

Infiltration and inflow (I/I) of extraneous water in separate sewer systems are serious concerns in urban water management for their environmental, social and economic consequences. Effective reduction of I/I requires knowing where excess water ingress and illicit connections are located. The present study focuses on I/I detection in the foul sewer network of a catchment in Trondheim, Norway, during a period without snowmelt or groundwater infiltration. Fiber-optic distributed temperature sensing (DTS) was used for the first time in Norway to detect I/I sources in tandem with closed-circuit television inspection (CCTV) and smoke testing. DTS was an accurate and feasible method for I/I detection, though it cannot identify exact types of failure and sources of I/I. Therefore, other complementary methods must be used, e.g. CCTV or smoke testing. However, CCTV was not completely useful in confirming the DTS results. This study provides practical insights for the rehabilitation and repair of sewer networks that suffer from the undesirable I/I of extraneous water.

The Rouge River Area of Concern - A multi-year, multi-level successful approach to restoration of Impaired Beneficial Uses

Citizen outcry in the 1960s led to passage of the 1972 U.S. Clean Water Act. Expansion of industrial permitting and availability of federal grants to municipalities controlled industrial waste and untreated municipal sewage entering the Rouge River. However, many sources persisted – notably wet weather discharges, stormwater runoff, and contaminated sediments. This remaining pollution led state officials to cooperatively craft the Rouge River Remedial Action Plan in 1985. This plan addressed all pollution sources, but was not substantially implemented until 1993 when the federal government, encouraged by Congressmen Dingell and Knollenberg, committed to the Rouge River National Wet Weather Demonstration Project. The federal government ultimately delivered $350 million that was matched by $700 million in local funds. Efforts have been sustained through multi-year state and federal grants, with additional funding from local communities and other stakeholders. Early focus of the Rouge Project was on untreated sewage from combined sewer overflows, but quickly expanded to address other impairments from sanitary sewer overflows, stormwater runoff, illicit connections and failing septic systems. With major sewage discharges under control, efforts shifted to remediating contaminated sediments and improving in-stream water quality and habitat. In total, over 380 projects were completed by 75 communities and agencies at a cost of over $1 billion since 1988, resulting in improved water, sediment, and biological quality. Prior to the U.S. Clean Water Act, the Rouge River nearly continuously failed to meet water quality standards. After decades of effort and investment, it now rarely violates standards. This miraculous recovery was initiated by a small handful of citizens, facilitated by local municipal leaders, and supported by the federal government. The Rouge River is a model for how a holistic, ecosystem approach to water pollution can result in cost-effective and greater and faster achievement of restoration, while meeting local needs.

Characterization and risk assessment of seasonal and weather dynamics in organic pollutant mixtures from discharge of a separate sewer system

Sites of wastewater discharge are hotspots for pollution of freshwaters with organic micropollutants and are often associated with adverse effects to aquatic organisms. The assessment, monitoring and managment of these hotspots is challenged by variations in the pollutant mixture composition due to season, weather conditions and random spills. In this study, we unraveled temporal exposure patterns in organic micropollutant mixtures from wastewater discharge and analyzed respective acute and sublethal risks for aquatic organisms. Samples were taken from two components of a separate sewer system i) a wastewater treatment plant (WWTP) and ii) a rain sewer of a medium size town as well as from the receiving river in different seasons. Rain sewer samples were separately collected for rain and dry - weather conditions. We analyzed 149 compounds by liquid chromatography-tandem mass spectrometry (LC-MS/MS). By considering the pollution dynamics in the point sources, we reduced the complexity of pollutant mixtures by k-means clustering to a few emission groups representing temporal and weather-related pollution patterns. From these groups, we derived biological quality element (BQE) - specific risk patterns. In most cases, one main risk driving emission group and a few individual risk driving compounds were identified for each BQE. While acute risk for fish was quite low, algae were exposed to seasonally emitted herbicides (terbuthylazine, spiroxamine) and crustaceans to randomly spilled insecticides (diazinon, dimethoate). Sublethal risks for all BQE were strongly influenced by constantly emitted pollutants, above all, pharmaceuticals. Variability of risks in the river was mainly driven by water discharge of the river rather than by season or peak events. Overall, the studied WWTP represented the major pollution source with a specific emission of agricultural compounds. However, the investigated rain sewer showed to be a constant pollution source due to illicit connections and was an important entry route for high loads of insecticides and biocides due to spills or incorrect disposal. By considering these pollution and risk dynamics, monitoring strategies may be optimized with a special focus on times of low flow conditions in the river, rain events and seasonally emitted risk drivers.

Invocations of the Driver Assists

Invocations of the Driver Assists

Detection and quantification of lateral, illicit connections and infiltration in sewers with Infra-Red camera: Conclusions after a wide experimental plan

Separate sewer systems are sensitive to illegal or mis-connections. Several techniques (including the Distributed Temperature Sensor) are now available to identify and locate those connections. Based on thermal fingerprints, DTS allows the localization of each lateral connection along a reach. The use of Infra-Red camera has been investigated with 748 laboratory experiments (artificial connections along a flume). The tested connections vary in diameters (from 75 to 200 mm), lengths of intrusion (from 0 to 200 m), shapes (circular or linear i.e. cracks), depths, discharge rates between the lateral connection and the main flume, and temperatures. IR frame analysis (for detection) and 2D temperature mapping (at the free water surface, for quantification) demonstrate that: i) the detection limit is very low (ratio between lateral and main discharges: 0.025) and ii) the quantification of the lateral discharge is impossible. Application of an IR camera seems to be a promising technique to detect lateral connections.

Different erosion characteristics of sediment deposits in combined and storm sewers.

To investigate the different erosion patterns of sediments in combined and storm sewers, sediments from three separate sewer systems and two combined sewer systems in urban Shanghai were collected for the flushing experiments. These experiments were conducted with different consolidation periods and shear velocities. As the consolidation period increases, dissolved oxygen exhibits a positive effect on the microbial transformations of organic substrates. Potential structural changes and separations of the surface and bottom layers of sediments are observed. The results also reveal that the organic matter, particle size and moisture have different effects on the erosion resistance of sediments. Furthermore, illicit connections behaved as an important factor affecting the viscosity and static friction force of particles, which directly alter the erosion resistance of sewer sediments.

Anthropogenic Influences of Paved Runoff and Sanitary Sewage on the Dissolved Organic Matter Quality of Wet Weather Overflows: An Excitation-Emission Matrix Parallel Factor Analysis Assessment.

The quality of dissolved organic matter (DOM) in a wet weather overflow (WWF) can be broadly influenced by anthropogenic factors, such as nonpoint sources of paved runoff and point sources of sanitary sewage within the drainage networks. This study focused on the anthropogenic influences of the paved runoff and sanitary sewage on the DOM quality of WWF using excitation-emission matrix parallel factor analysis (EEM-PARAFAC). Results show that (1) EEM-PARAFAC fitted terrestrial humic-like, anthropogenic humic-like, tryptophan-like, and tyrosine-like components can be regarded as indicators to identify the types of sewage overflows and the illicit connection status of drainage systems. (2) A short emission wavelength (em: 302-313 nm) peak of the tyrosine-like component occurred in the reserved sanitary sewage, while a type of longer emission wavelength (em: 321-325 nm) peak came from the sump deposit. These tyrosine-like components were gradually evacuated in the initial phase of the overflow process with the fading of their EEM signals. Fluorescence signal transformations of all the components confirmed the potential ability of EEM-PARAFAC to monitor the dynamic changes of the primary pollutant sources. (3) The input of the newly increased sanitary sewage had a dominant influence on the quality and yield of the WWF DOM.

To analyze the Urban Water Pollution Discharge System using the tracking and tracing approach

For the purpose of analyzing and managing Urban Water Pollution Discharge Systems (UWPDS) comprehensively, a systematic approach of tracking and tracing analyses was developed based on environmental systems analysis theory, in which the directed graph, the nodal flow balance and the network analysis of Geographic Information System (GIS) were used. Based on the digitalized UWPDS of GIS which was established by collecting and processing a large amount of topographic, sewage discharge and drainage data, this scientific approach can be applied to make the tracking and tracing analyses on wastewater treatment plants, pumping stations, illicit sewage outlets, pollution sources and drainage pipelines systematically. The upstream and downstream information about sources, discharging paths, flow quantities and final destinations of pollutants was obtained, and potential problems in the UWPDS analysis such as illicit connections between different drainage pipelines were identified, with the spatial analysis. This developed approach was tested using the UWPDS of Chaohu City (Anhui Province, China). The study results are important for the implementation of sewage interception engineering, the determination of load reduction, and the optimization of drainage pipelines and pumping stations in future.

Detection of Wastewater Discharges into Stormwater Sewers: Effects of Travel Distance on Parameters

In separate sewer systems, there is a risk that wastewater from illicit connections may enter a stormwater sewer and ultimately outfall into receiving waters, adversely affecting receiving water qu ...

Uncertainty assessment of water quality modeling for a small-scale urban catchment using the GLUE methodology: a case study in Shanghai, China.

There is often great uncertainty in water quality modeling for urban drainage systems because water quality variation in systems is complex and affected by many factors. The stormwater management model (SWMM) was applied to a small-scale urban catchment with a simple and well-maintained stormwater drainage system without illicit connections. This was done to assess uncertainty in build-up and wash-off modeling of pollutants within the generalized likelihood uncertainty estimation (GLUE) methodology, based on a well-calibrated water quantity model. The results indicated great uncertainty of water quality modeling within the GLUE methodology. Comparison of uncertainties in various pollutant build-up and wash-off models that were available in SWMM indicated that those uncertainties varied slightly. This may be a consequence of the specific characteristics of rainfall events and experimental sites used in the study. The uncertainty analysis of water quality parameters in SWMM is conducive to effectively evaluating model reliability, and provides an experience base for similar research and applications.