Experimental studies of the non-stationary heat exchange in the system «environment I – body II» have been carried out. It is established that in the body II, which consists of the fluid and thin-walled metal envelope, the characteristic features of the regular thermal mode occur, i.e., cooling (heating) rate of the body II- m = const; heat transfer coefficient between the water (environment I) and body II is practically stable α1 = const; uneven temperatures distribution coefficient in the body II ψ = const.
This new notion of the heat transfer regularities in the body II is planned to apply for further development of the experimental-calculation method for the forecasting of the heat exchange intensity in the compound fluid media with limited information regarding thermophysical and rheological properties.
AbstractStudies of the evolution of coastal lowlands since the Last Glacial Maximum (LGM) typically ignore radiocarbon data from sediment samples that have undergone reworking. However, these samples contain information on their sediment sources and the timing of their redeposition. We analyzed 738 radiocarbon dates obtained from shell and plant material in samples of post-LGM coastal sediment from north of Tokyo Bay, Japan. Of these samples, 245 (33%) were reworked. Furthermore, the percentage of reworked samples and their average age offsets increased with the depth of the water environment (terrestrial, 15% and 360 ± 250 years, respectively; intertidal, 26% and 470 ± 620 years; subtidal, 39% and 550 ± 630 years). Taking these radiocarbon samples as a proxy for clastic material, our results imply that channel erosion accounted for relatively little clastic removal in the terrestrial and intertidal environments over short timescales, whereas ~ 40% of clastics were removed by storm winnowing and transported in stepwise fashion to deeper water over longer timescales and ~ 60% in the subtidal environment were transported by floods directly from river mouths. These findings imply that radiocarbon ages from reworked samples can be used to quantify clastic recycling processes and their history in coastal areas.
Water ecological civilization (WEC) is a key component and basic guarantee of ecological civilization. This paper sets up an evaluation index system (EIS) for WEC development (WECD) level, which covers such three dimensions as social economic development, control over total water resources and water utilization efficiency, and synthetic environmental governance and adopts set pair analysis (SPA) to measure and analyze the WECD level in Yangtze River Economic Belt (YREB) from 2010 to 2019. The results show that (1) the score of each subsystem in YREB WECD grew continuously in the sample period and poised to increase in future, (2) in general, YREB WECD level steadily increased to a relatively high level, and (3) the good development trend of YREB WECD is inseparable from the fact that YREB stepped up its efforts in capital investment, water utilization, and water environment protection and recovery. Finally, pertinent measures were put forward to further improve the YREB WECD level.
The degree of eutrophication in the water environment is deepening. For the appropriate treatment of eutrophication, it is essential to evaluate it accurately. However, the evaluation of eutrophication has not been well solved because it is full of uncertainty. Herein, a multidimensional connection cloud model, combined with the improved CRITIC (Criteria Importance Through Inter-criteria Correlation) method, was put forward here to assess water eutrophication and depict the randomness, ambiguity, and interaction of evaluation factors. First, an improved CRITIC was adopted to determine indicator weight so that the correlation among different indicators and more information were depicted. Secondly, a multidimensional connection cloud was simulated to characterize fuzzy indicators and ambiguous classification boundary values according to classification criteria. Next, the connection degree was calculated relative to the evaluation standard. The eutrophication grade was specified under the “maximum connection degree” principle. At last, the effectiveness and practicality of the model proposed here were affirmed by two cases and comparisons with supplementary methods. The results suggest that the proposed model can avoid shortcomings of the original CRITIC method and cloud model, and make the assessment result more realistic.
Water surface plastic pollution turns out to be a global issue, having aroused rising attention worldwide. How to monitor water surface plastic waste in real time and accurately collect and analyze the relevant numerical data has become a hotspot in water environment research. (1) Background: Over the past few years, unmanned aerial vehicles (UAVs) have been progressively adopted to conduct studies on the monitoring of water surface plastic waste. On the whole, the monitored data are stored in the UAVS to be subsequently retrieved and analyzed, thereby probably causing the loss of real-time information and hindering the whole monitoring process from being fully automated. (2) Methods: An investigation was conducted on the relationship, function and relevant mechanism between various types of plastic waste in the water surface system. On that basis, this study built a deep learning-based lightweight water surface plastic waste detection model, which was capable of automatically detecting and locating different water surface plastic waste. Moreover, a UAV platform-based edge computing architecture was built. (3) Results: The delay of return task data and UAV energy consumption were effectively reduced, and computing and network resources were optimally allocated. (4) Conclusions: The UAV platform based on airborne depth reasoning is expected to be the mainstream means of water environment monitoring in the future.
Numerous studies have demonstrated that food shapes the structure and composition of the host’s oral and gut microbiota. The disorder of oral and gut microbiota may trigger various host diseases. Here, we collected oral and gut samples from wild water monitor lizards (Varanus salvator) and their captive conspecifics fed with bullfrogs, eggs, and depilated chicken, aiming to examine dietary correlates of oral and gut microbiota. We used the 16S rRNA gene sequencing technology to analyze the composition of the microbiota. Proteobacteria and Bacteroidota were the dominant phyla in the oral microbiota, and so were in the gut microbiota. The alpha diversity of microbiota was significantly higher in the gut than in the oral cavity, and the alpha diversity of oral microbiota was higher in captive lizards than in wild conspecifics. Comparing the relative abundance of oral and gut bacteria and their gene functions, differences among different animal groups presumably resulted from human contact in artificial breeding environments and complex food processing. Differences in gene function might be related to the absolute number and/or the taxonomic abundance of oral and gut microorganisms in the wild and the water environment. This study provides not only basic information about the oral and gut microbiota of captive and wild water monitor lizards, but also an inference that feeding on frogs and aquatic products and reducing human exposure help water monitor lizards maintain a microbiota similar to that in the wild environment.
The Arkansas Department of Transportation (ARDOT) uses different types of metal culverts and cross-drains. Service lives of these culverts are largely influenced by the corrosion of the metals used in these culverts. Corrosion of metallic parts in any soil-water environment is governed by geochemical and electrochemical properties of the soils and waters. Many transportation agencies including ARDOT primarily focus on investigating the physical and mechanical properties of soils rather than their chemical aspects. The main objective of this study is to analyze the geotechnical and geochemical properties of soils in Arkansas to estimate the service lives of different metal pipes in different conditions. Soil resistivity values were predicted after analyzing the United States Department of Agriculture (USDA) soil survey data using neural network (NN) models. The developed NN models were trained and verified by using laboratory test results of soil samples collected from ARDOT, and survey data were obtained from the USDA. The service lives of metal culverts were then estimated based on the predicted soil properties and water quality parameters extracted from the data acquired from the Arkansas Department of Environmental Quality (ADEQ). Finally, Geographic Information System-based corrosion risk maps of three different types of metal pipes were developed based on their estimated service lives. The developed maps will help ARDOT engineers to assess the corrosion potential of the metal pipes before starting the new construction and repair projects and will allow using proper culvert materials to maximize their life spans.
Phosphate sensors have been actively studied owing to their importance in water environment monitoring because phosphate is one of the nutrients that result in algal blooms. As with other nutrients, seamless monitoring of phosphate is important for understanding and evaluating eutrophication. However, field-deployable phosphate sensors have not been well developed yet due to the chemical characteristics of phosphate. In this paper, we report on a luminescent coordination polymer particle (CPP) that can respond selectively and sensitively to a phosphate ion against other ions in an aquatic ecosystem. The CPPs with an average size of 88.1 ± 12.2 nm are embedded into membranes for reusable purpose. Due to the specific binding of phosphates to europium ions, the luminescence quenching behavior of CPPs embedded into membranes shows a linear relationship with phosphate concentrations (3–500 μM) and detection limit of 1.52 μM. Consistent luminescence signals were also observed during repeated measurements in the pH range of 3–10. Moreover, the practical application was confirmed by sensing phosphate in actual environmental samples such as tap water and lake water.