Search

Inspecting sewage outfall into rivers is significant to the precise management of the ecological environment because they are the last gate for pollutants to enter the river. Unmanned Aerial Vehicles (UAVs) have the characteristics of maneuverability and high-resolution images and have been used as an important means to inspect sewage outfalls. UAVs are widely used in daily sewage outfall inspections, but relying on manual interpretation lacks the corresponding low-altitude sewage outfall images dataset. Meanwhile, because of the sparse spatial distribution of sewage outfalls, problems like less labeled sample data, complex background types, and weak objects are also prominent. In order to promote the inspection of sewage outfalls, this paper proposes a low-attitude sewage outfall object detection dataset, namely UAV-SOD, and an attention-guided feature enhancement network, namely AFENet. The UAV-SOD dataset features high resolution, complex backgrounds, and diverse objects. Some of the outfall objects are limited by multi-scale, single-colored, and weak feature responses, leading to low detection accuracy. To localize these objects effectively, AFENet first uses the global context block (GCB) to jointly explore valuable global and local information, and then the region of interest (RoI) attention module (RAM) is used to explore the relationships between RoI features. Experimental results show that the proposed method improves detection performance on the proposed UAV-SOD dataset than representative state-of-the-art two-stage object detection methods.

Abstract The use of gadolinium (Gd) complexes as contrast agents in magnetic resonance imaging (MRI) has resulted in point source releases of anthropogenic Gd into the environment and presents the opportunity to trace the fate of wastewater plumes. Here we collected seawater samples along the coast of Northeast Brazil to investigate the influence of two submarine sewage outfalls on the distribution of Gd and other rare earth elements (REE) in the coastal waters. The shale-normalized REEs only show a small light over heavy REE enrichment and negative Ce anomalies, likely reflecting the influence of freshwater inputs. Positive Gd anomalies are observed at most of the sampling sites, indicating the ubiquitous presence of anthropogenic Gd in coastal waters. The highest Gd anomalies are found in the vicinity of the submarine sewage outfalls and decrease with increasing distance from point source. The total daily discharge of 216 ± 82 g Gd and 92.0 ± 19.3 g Gd was calculated for the Rio Vermelho (ERV) and Boca do Rio (EBR) submarine outfalls, respectively, which on population bases equates to 11.5 ± 4.3 g Gd d−1 for ERV and 15.5 ± 3.3 g Gd d−1 for EBR per 100 000 persons. It is estimated that in 2016 the annual emission of anthropogenic Gd by hospitals and clinics in Brazil varied between 527 kg and 5.3 tons. It was roughly estimated that between 698 and 2021 g Gd d−1 are discharged into the Tropical and South Atlantic waters due to submarine outfall sewage along the coast of Brazil. Graphical abstract Image 1 Highlights • Positive Gd anomalies are attributed to the contamination by MRI contrast agents. • Brazilian submarine outfalls are releasing up to 2 kg Gd d−1 into Atlantic waters. • At least 527 kg of anthropogenic Gd were released by Brazilian hospitals in 2016. • Increasing release of REEs may impair their use as tracers of natural processes. • REE patterns have slight LREE depletions and a small negative Ce anomaly. [ABSTRACT FROM AUTHOR]

Copyright of Wuhan University Journal (Philosophy & Social Sciences) / Wuhan Daxue Xuebao (Zhexue Shehui Kexue Ban) is the property of Wuhan University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The geochemistry, mineralogy, and grain size distribution of several estuarine cohesive sediment samples from potentially human-influenced areas without such an influence were analyzed to determine the natural heavy metal content and evaluate its impact on the Bahía Blanca estuarine environment. The data were compared with different ranges of concentrations for heavy metals in marine sediments established by the NOAA Screening Quick Reference Tables in which values range from background levels to those considered toxic to the marine environment. Our total heavy metal contents were below the established hazardous levels in all the analyzed samples, even though the potentially human-influenced areas (harbors, industry, urban spread) showed the highest total concentration values as well as greater percentages of bioavailable compounds. This would imply a low and not extensive anthropogenic input into the environment. The relatively high proportions in which Cd, Pb, and Cr appear as bioavailable compounds at some sites not influenced by human activity suggest the presence of a natural source for these elements. This could be attributed to the weathering of naturally occurring volcanic minerals, indicating that special care must be taken when monitoring of sediment for anthropogenic activity is carried out within this environment. According to the results obtained, and in order to minimize the environmental impact caused by periodic water injection dredging, relocation of sewage outfalls from vessel mooring areas into open waters is strongly recommended. [ABSTRACT FROM AUTHOR]

The effects of major sewage and estuarine discharges on nutrient distributions in central New South Wales (NSW) coastal waters were investigated. The hinterland of the study region includes the sewerage and rainwater catchments of major population centres of Newcastle, Sydney and Wollongong. New South Wales discharges the majority of its treated sewage to the ocean, with about 80% from just three deepwater outfalls off Sydney. These discharges were found to be the principal, continuous, anthropogenic source of nutrients to NSW coastal waters. The deepwater outfalls delivered most of their nitrogen as ammonia and were responsible for nutrient (NH4-N and PO4-P) enrichment within usually submerged effluent plumes. Direct observations and modelling indicate that after initial dilution, effluent plumes typically occupy ~30 m of the water column (60-80 m). Rapid initial dilution was observed with subsequent gradual far field dispersion typically broadening the effluent field to1-2 kilometres by about 10 kilometres downstream. Flows generally follow isobaths, predominantly to the south. Vertical and seasonal distributions of sewage derived nutrients, were estimated from a 6 year record of initial dilution modelling and effluent data. Comparisons were made with ambient nutrient distributions derived from long term monitoring prior to the commissioning of the outfalls (1990), at the CSIRO Port Hacking Station (5 to 10 kilometres south of the deepwater outfalls). The pycnocline seasonally limited the vertical extent of sewage plumes emitted from the deepwater outfalls. Upwelling/uplifting processes were associated with stratified conditions during spring and summer. Therefore, density stratification was a critical factor in determining the vertical movement of oceanic and sewage derived nutrients into the euphotic zone. Despite clear nutrient enrichment due to sewage discharges, no new evidence has been presented to contradict previous findings that algal blooms are principally driven by oceanic nutrient enrichment. However, by considering simulations of near field effluent plume behaviour in relation to long term ambient nutrient patterns we have identified specific periods of the year and depth intervals with maximum risk of outfall impacts, such as the upper half of the water column during late summer. [ABSTRACT FROM AUTHOR]

Sewage outfalls are the ideal locations for water pollution monitoring as they are the final gate that pollutants must pass before entering rivers and oceans. Strengthening the supervision and control of industrial sewage outfalls has become the most important task in water pollution control. Most rivers in China are highly polluted, especially those flowing through cities. It is difficult to investigate, monitor, trace, and remediate sewage outfalls because information regarding the distribution of sewage outfalls into rivers is incomplete and the existing methods of monitoring sewage outfalls into rivers are outdated. This paper proposes an innovative method for feasible and efficient acquisition of sewage outfall data through a combination of web crawler and remote sensing interpretation technologies, employing data from the Luan River Basin as a testing site. We crawled industrial information and spatial location data on the Internet and obtained the locations of industrial sewage outfalls by interpreting remote sensing images. We modeled the distribution of sewage inflow from major industries into the tributaries of the Luan River Basin. We verified the accuracy and reliability of the developed method by comparing its results with actual data collected during our field investigation. Sample field tests confirmed the high accuracy (89%) of the proposed method, indicating its successful application in the Luan River Basin. We believe that the proposed method can be used to verify and supervise sewage outfalls in other locations in the future, especially owing to its improved acquisition system, which ensures feasible and efficient measurements without the need for manual investigation. This study provides a scientific basis for decision-making with regard to sustainable development. ∙Strengthen supervision of industry sewage outfalls help river pollution control ∙Web crawler combined with remote sensing interpretation were innovatively employed ∙Web crawler successfully designed to collect industry sewage outfalls for water pollution monitoring ∙Verified new method's accuracy (89%) and reliability by field investigation ∙Measurement driven by new method is applicable to other rivers and countries [ABSTRACT FROM AUTHOR]

To better manage water environment in highly polluted rivers, the influence factors on water quality need to be investigated. With the effects of oxygen-demanding contaminants, it is difficult to resolve the complex interdependencies of the various factors using conventional methods. The Bayesian Networks (BNs), in which each variable only depends on its immediate parent variables, can solve this problem. In this study, the BNs were developed to assess the impacts of land use and sewage outfalls on Ammonia Nitrogen (AN) and Dissolved Oxygen (DO) concentrations in the Huaihe River Basin (HRB) for different seasons and spatial scales, where AN was a typical oxygen-demanding contaminant and the most serious contaminant in the area. The BNs gave the best explanations for variations in AN (NSE = 0.80) and DO (NSE = 0.72) concentrations by using land use and sewage outfalls data at the local scale (less than 20 km radii around monitor stations), suggesting that controlling water contaminant sources at local scales can improve water quality efficiently. AN negatively affected DO concentration, which was more significant in dry seasons. Wastewater from sewage outfalls was the largest contributor (26.2%) to AN pollution in dry seasons, which was weakened in wet seasons by an intensive dilution process. Farmland acted as a "sink" in dry seasons and as a "source" in wet seasons. The transition between two states was caused by large variations in surface runoff between dry and wet seasons. Urban land made a disproportionately large contribution to water pollution compared to other kinds of land use. These findings improve our understanding of influence factors on water quality and will contribute to effective river management. Unlabelled Image • A model was developed to describe complex interdependencies in polluted rivers. • Ammonia nitrogen negatively affected dissolved oxygen, especially in dry seasons. • Land use and sewage outfalls had the most effects on water quality at local scales. • Farmland acted as "sink" for contaminants in dry seasons and "source" in wet seasons. • Urban made a disproportionately large contribution to water pollution in rivers. [ABSTRACT FROM AUTHOR]