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The possibility of analyzing the general and functional diversity of the ecosystem is considered, as is unambiguous interpretation of the results obtained based on our work experience and previously obtained data. The prospects for studying small mammals without removal from the wild are discussed. We discuss distinguishing in a sample the resident component, which makes it possible to characterize local resource flows, and the nonresident component, dependent on the state of the territory as a whole. A description of the capture–mark–recapture protocol, methods for assessing spatial activity, calculating the density of the resident population per unit area, and the completeness of species richness estimate is provided. The estimates of animal numbers per unit of trapping effort in pooled sample, the population density of residents, and the index of the nonresident flow are compared. The possibility of analyzing the resource flows in "historical," "novel," and "hybrid" ecosystems, as well as using data to analyze the resilience of the ecosystem and detect the threshold point, is considered. [ABSTRACT FROM AUTHOR]

Pulp and paper industries emit various odorous gases during the pulp production and paper-making phase, which are unpleasant and have harmful effects on the human body. The working staffs are continuously exposed to these gases and develop various health issues. Hence, regular monitoring and analysis of such gases are necessary to avoid any sudden high concentration exposure and to prevent adverse health effects on the staff. An electronic nose (EN) has an array of gas sensors with an alert system for early detection of gases. Various ENs have been developed for varying applications till date. The detailed knowledge of the sensors used, their sensitivity and technology is helpful in development of any EN. The objective of this study is to comprehensively review various developed ENs with respect to their gas sensing and pattern recognition (PR) technologies. The information on gases released from pulp and paper industries is also compiled. The evolution of EN technology, its various applications, challenges in developing EN and its utility in safeguarding the industrial workers' life have been described. Further, gap analysis among previously developed EN, contemporary EN and wireless sensor network (WSN) is elaborated. It will facilitate future researchers for better selection of sensors and PR technologies while developing EN. The commonly used sensing technologies are described with their advantages, disadvantages and working principles. Metal oxide semiconductor (MOS) gas sensor and ANN algorithm show better result and hence recommended in the development of EN, whereas ZigBee protocol has been widely used for WSN. [ABSTRACT FROM AUTHOR]

An essential requirement for colorimetric paper-sensor is to allow the target analytes (heavy metal ions) to access the chromophore while maintaining strong chromophore immobilization on the porous substrate surface. This work evaluates the selection of sensitive chromophores (dithizone, 1-(2-pyridylazo) 2-naphthol and 4-(2-pyridylazo)-resorcinol) and their immobilization strategies on paper sensors. Dithizone (DTz) are capable of producing a significant color transition at unadjusted pH, observed by UV–Vis absorption spectroscopy and visible recognition. After immobilizing DTz on a paper substrate (cellulose acetate/chitosan substrate), the DTz-paper sensor showed a distinctive color change from blue-green to peach-pink upon reaction with Pb2+ ions, and the color intensity was proportional to the metal concentration. Quantitative analysis using RGB (R:Red; G:Green; B:Blue) plots showed that increasing DTz concentration on the CA/CS paper sensor increases the difference in total color intensity (∆IT) and the difference in red code intensity (∆IR). This is due to the formation of more DTz-Pb2+ complexes on the CA/CS paper substrate. The CA/CS paper strips immobilized with 100 ppm DTz showed practical potential for rapid detection of heavy metal ions. The DTz-CA/CS paper sensor showed significant color change when detecting spiked heavy metals ions (0.1 ppm Pb2+, 2.0 ppm Zn2+, and 0.2 ppm Cu2+) in river water samples that prepared at the maximum permissible limit for industrial effluent in Malaysia. [ABSTRACT FROM AUTHOR]

Microfluidic paper-based analytical devices (μPADs) have developed rapidly in recent years, because of their advantages, such as small sample volume, rapid detection rates, low cost, and portability. Due to these characteristics, they can be used for in vitro diagnostics in the laboratory, or in the field, for a variety of applications, including food evaluation, disease screening, environmental monitoring, and drug testing. This review will present various detection methods employed by μPADs and their respective applications for the detection of target analytes. These include colorimetry, electrochemistry, chemiluminescence (CL), electrochemiluminescence (ECL), and fluorescence-based methodologies. At the same time, the choice of labeling material and the design of microfluidic channels are also important for detection results. The construction of novel nanocomponents and different smart structures of paper-based devices have improved the performance of μPADs and we will also highlight some of these in this manuscript. Additionally, some key challenges and future prospects for the use of μPADs are briefly discussed. [ABSTRACT FROM AUTHOR]

A field paper-based heavy metal strip was designed and implemented for simultaneous detection of the heavy metals Zn, Cr, Cu, Pb and Mn in wastewater samples. The colorimetric paper strip was fabricated by drop-casting of chromogenic reagents onto detection zones. When the fabricated paper strip was exposed to Zn, Cr, Cu, Pb and Mn, multiple colors appeared that were then recorded with a smartphone followed by processing in the Color Picker application. After optimizing the analytical parameters, such as the chromogenic concentration, pH and reaction time, the paper strip achieved detection limits of 0.63, 0.07, 0.17, 0.03 and 0.11 mg/L for Zn, Cr, Cu, Pb and Mn, respectively. Five heavy metals analyses were able to be performed within 1 min on one paper strip. This paper strip is accurate with recoveries from 87 to 107%. The results of the proposed paper strip correlated well with those determined by inductively coupled plasma-optical emission spectrometry of wastewater samples. The use of a single paper strip integrated with a smartphone for the detection of five heavy metals in wastewater represents an all-in-one device with on-site detection, leading to cost-effective and rapid assays that show a great application potential for on-site environmental monitoring. [ABSTRACT FROM AUTHOR]

The recognition and detection of metal ions present in biological and environmental samples have attracted great attention in recent years. Various analytical techniques are used to detect metal ions. Among these, the fluorescence technique is among the emerging methods because of its simplicity, selectivity, and applicability to bioimaging. Thus, this review particularly explores paper-based fluorescence chemosensors involved in metal ion detection. Significantly, the first section addresses relevant research on metal ion detection involving various techniques. In the second section, several sensing strategies such as photoinduced electron transfer, fluorescence resonance energy transfer, intramolecular charge transfer, chelation enhanced fluorescence, excited-state intramolecular proton transfer, and aggregation-induced emission for the detection of target metal ions (aluminum, copper, iron, lead, mercury, and zinc) are investigated. The third section particularly discusses the role of fluorescence sensor materials (e.g., fluorescein, rhodamine, naphthalimide, BODIPY, carbon dots, quantum dots) involved in the detection processes and their advantages and limitations. Overall, this article reviews 90 research articles on paper-based fluorescence chemosensors for metal ion detection published until 2021. [ABSTRACT FROM AUTHOR]

Preventive Conservation (PC) aims to minimize the risk of irreversible damage to cultural artifacts caused by environmental factors. Strategies for PC include implementing environmental recommendations and monitoring conditions. However, environmental monitoring alone is not enough, and predictive analysis is needed to assess the risk of damage. The collection "Preventive Conservation, Predictive Analysis and Environmental Monitoring" presents technological advances in studying material degradation and environmental monitoring. Papers cover topics such as paper degradation, wood degradation, canvas paintings, dyed textiles, sensor electronics, wireless communications, cloud computing, and machine learning. The collection provides valuable insights for the design of preventive conservation strategies. [Extracted from the article]

A study was conducted in a marine inlet to assess the effects of untreated discharges from a pulp and paper mill, a municipality, and industries in western Newfoundland on winter flounder ( Pleuronectes americanus), a fish species shown previously to be sensitive to environmental contaminants in sediment. The fish were captured by SCUBA divers about 2 km down-current from the mill discharging effluent containing resin acids, and at three reference sites 2 to 11 km away near the opposite shore, each spring in five consecutive years and the fish were necropsied on site. A total of 360 and 339 flounder were examined near the mill and references sites, respectively. Several bioindicators were used to assess fish health including parasites. More fish exhibiting external and microscopic lesions in several tissues, lower condition factors, elevated hepatosomatic index, and delayed reproductive development were observed in samples taken near the paper mill than at the reference sites. A higher prevalence of an ectoparasite, Cryptocotyle lingua, but a significantly lower mean abundance of three metazoans infecting the digestive tract was noted in fish near the mill than in the reference samples. These results, comprising abnormal fish size distribution, low body condition factor, external and internal lesions, enlarged liver, delayed gonadal development, and changes in parasitism, were stress-related, indicative of impaired health, and associated primarily with untreated discharges from the pulp and paper mill. This integrated and multidisciplinary study also provides further evidence on the use of fish parasites as a valid and an additional bioindicator in programs monitoring environmental contaminants. [ABSTRACT FROM AUTHOR]

Paper is a widely used support for use in devices for point-of-care testing (POCT) in clinical diagnosis, food safety monitoring and environmental pollution. Paper is inexpensive, biocompatible, biodegradable and allows a sample fluid to flow by capillary force. Numerous method have been developed recently for chemical modification of papers in order to introduce different functionalities. This review (with 148 refs.) summarizes the recent progress in paper-based POCT devices. The introduction summarizes the state of the art of paper-based POCT devices and the physicochemical properties of existing unmodified materials (including cellulose, cellulose-based composites, cotton fibers, glass fibers, nitrocellulose, thread). Methods for paper modification for sample pretreatment are summarized next, with subsections on sample storage and collection, sample separation, nucleic acid extraction and sample preconcentration. Another main section covers approaches for paper modification for improving POCTs, with subsections on assays for proteins, nucleic acids, drugs, ion and organic molecules. The advantages and disadvantages of these approaches are compared. Several tables are presented that summarize the various modification techniques. A concluding section summarizes the current status, addresses challenges and gives an outlook on future perspectives of POCTs. [ABSTRACT FROM AUTHOR]

The purpose of this inquiry is to identify how environmental indicators and environmental technology in the science/policy boundary alternately facilitate and encumber international environmental negotiations. In a case involving a dispute between Sweden and Finland over one another’s contribution to the organochlorine pollution load to the Baltic Sea, indicators of environmental risk, including measures of allegedly toxic concentrations of organochlorines in Swedish and Finnish chemical pulp wastewater, did not bring the two sides closer to a settlement. Also, ironically, advances in technological solutions to the problem were unhelpful to the negotiation. For many months, the disputants failed to acknowledge that deliberations were slowed down by the parties’ pride and confidence in their respective national scientific, technological, and regulatory institutions. In recent years, the problems caused by organochlorine emissions from Swedish and Finnish pulp mills have been all but solved—a comparatively rare transboundary environmental “success story.” With the tackling of the problem, the competition between Sweden and Finland’s preferred engineering solutions has dramatically faded. [ABSTRACT FROM AUTHOR]

During the past decade, new biological assessment methods have been developed for use in inland waters. Less work has gone into objective testing of the individual methods and their diagnostic or other capabilities, and very little effort has been devoted to comparing methods. This special issue of Hydrobiologia brings together a number of the most recently developed bioassessment methods, or aspects of them, so readers can begin to compare their potential value and practical usefulness. [ABSTRACT FROM AUTHOR]

Impedance analysis is a powerful technique that has become increasingly important in various applications, it represents a leap forward in the field of electronic measurments and diagnostics. In this work, we present the development of miniaturized, multiplexed, and connected platform for impedance spectroscopy. Designed for online measurements and adapted to wireless network architectures, our platform has been tested and optimized to be used for multi-selective chemical organic sensor nodes. This compact and versatile circuit is built from low cost and low power consumption (250 mW) microelectronics components that achieve long duration operability (5 days and 16 h) without compromising on sensor measurement accuracy and precision. We used the well-known impedance network analyzer AD5933 (Analog Devices, Norwood, MA, USA) chip which can measure a spectrum of impedances in the range 5 kHz to 100 kHz. The proposed system is based on ESP32-C3 Microcontroller enabling the management of the AD5933 through its I2C interface. Our system benefits from two multiplexer components CD74HC4067 allowing calibration process and the interface of 15 conductimetric sensors with real time acquisition (less than 90 ms per acquisition). The system is capable of relaying information through the network for data analysis and storage. The paper describes the microelectronics design, the impedance response over time, the measurement’s sensitivity and accuracy and the testing of the platform with embedded chemical sensors for gas classification and recognition.Article Highlights: Single calibration process: The main contribution of this paper is to propose a portable multiplexed impedance measurement system with a unique self-calibration capability. This capability is facilitated through the use of a single calibration resistor, which significantly enhances the speed of data acquisition. Materials study: To validate our system, a materials study was conducted, focusing on the use of a conductive polymer poly(3hexylthiophene) P3HT doped with various triflate metals. This research aims to assess the system's effectiveness in gas recognition applications, demonstrating its potential for accuracy and speed crucial attributes for modern detection technologies. Gas recognition: Our developed system has been designed to be suitable to assess volatile samples by their quality, to systematically expose them to the miniaturized array under a static blow (the PCA of the partial dataset of resistance modulation published in our former studies quantifies on the systematicity of the exposures by the organization of the data clusters).These labels are indeed crucial to quantify the materials response with environmental physical variables which may greatly vary within an environment. [ABSTRACT FROM AUTHOR]

Due to the benefits of the high sensitivity, real-time response, no labeling requirement, and good selectivity, fiber optic sensors based on surface plasmon resonance (SPR) have gained popularity in biochemical sensing in recent years. The current research on such sensors is hot in enhancing sensitivity, improving detection accuracy, and achieving the detection of biochemical molecules. The goal of this work is to present a thorough overview of recent developments in the optical fiber SPR biosensor research. Firstly, it explores the basic principles and sensing structures of optical fiber SPR biosensors, focusing on four aspects. Subsequently, this paper introduces three fiber optic surface plasmon biosensors: SPR, localized surface plasmon resonance (LSPR), and long-range surface plasmon resonance (LRSPR). Each concept is explained from the perspective of the basic principles of fiber optic SPR biosensors. Furthermore, a classification of fiber optic SPR biosensors in health monitoring, food safety, environmental monitoring, marine detection, and other applications is introduced and analyzed. Eventually, this paper summarizes the current research directions of SPR biosensors. Meanwhile, it provides a prospective outlook on how fiber optic SPR sensors will develop in the future. [ABSTRACT FROM AUTHOR]

Intelligent Transport System (ITS) is a typical class of Cyber-Physical Systems (CPS), and due to the special characteristics of such systems, higher requirements are placed on system security. Runtime verification is a lightweight verification technique which is used to improve the security of such systems. However, current runtime verification methods often ignore the effects of the physical environment (e.g., the effects of rain, snow, and other weather changes on road conditions), which results in the inability of the monitor to effectively monitor the system according to the changes in the environment. To address this problem, this paper proposes a method for constructing a runtime monitor with environmental context-awareness capability. First, the physical environment factors affecting the system are formally described and constructed into an environment model, then the system statute is transformed into a Büchi automaton, and then a synthesis algorithm combining the environment model and the Büchi automaton is designed based on the network of automatons, and the corresponding monitor is generated. Finally, the proposed method is applied and verified on simulation and real objects. The experimental results show that the monitors generated based on the method of this paper can effectively monitor unsafe events in different environments, thus improving the safety of intelligent driving systems. [ABSTRACT FROM AUTHOR]

Analyzing scientific advances and networks in NPs research can provide valuable insights into the evolving trends, research gaps, and priorities for future research efforts, highlighting the importance of scientific research in pollution control and risk management of uncontrolled and unknown nanoplastics (NPs) that pose a potential global threat, and have raised concerns in the scientific community and media. A total of 2055 nanoplastics (NPs) studies published from 1995 onwards were retrieved from the Web of Science Core Collection database. Bibliometric methods were applied to assess evolving scientific advances and networks. The general term, "nanoplastics," was first introduced in 1995 as "intelligent" materials. Before 2009, defined as the ambiguous stage, NPs were produced and applied in many different manufacturing areas and processes. The first research referring to nano-scale plastic particles/debris as potential hazardous contaminants appeared in 2010. Thereafter, the number of annual publications on NPs has increased rapidly, particularly from 2018 onwards. Results showed China published 822 scientific papers, overtaking the United States' 229 papers, whereas European researches, i.e., the Netherlands, Portugal, German, and the United Kingdom, led in quality and citation with extensive international collaborations. Furthermore, we concluded three main research themes from keyword cluster analysis: environmental monitoring (identification, quantification, fresh-water, marine-environment); environmental behaviors (fate, adsorption, aggregation, transport); and toxicology (toxicity, exposure, ingestion, oxidative stress). Toxicology and environmental behaviors of NPs were the leading themes. An overview of the current understanding of NPs in the above three major themes provides perspectives to identify future research directions based on knowledge gaps, e.g., advancing analytical methods, and exploring the mobility and fate of NPs in different ecosystems. Scientific research on NPs is a key fundamental requirement for their pollution control and risk management. To bridge the gap between research and reality, future efforts are required to promote the dissemination of scientific research findings and encourage actions in engineering, policy, education, etc., to support a sustainable society. [ABSTRACT FROM AUTHOR]

Economists have greatly criticized regulations that impose uniform environmental standards. Such a critic ignores that the implementation of the standards may vary significantly across plants, thus giving rise in fact to non-uniform standards. The purpose of this paper is to analyze the determinants of the regulator's monitoring activities. We show that greater inspection effort, ceteris paribus, is allocated towards those plants whose emissions are likely to generate a higher level of damages. On the other hand, we show that the behavior of the regulator is also a function of variables that may not be directly related to abatement cost and damages. In particular, we show that variables pertaining to local labor market conditions have an impact on the monitoring strategy adopted by the regulator. [ABSTRACT FROM AUTHOR]

The Canadian Environmental Assessment Act (CEAA) defines the federal environmental assessment (EA) process for evaluating the likelihood that development projects (e.g., roads, buildings, factories) will have impacts on the environment. Environmental effects monitoring (EEM) programs for mining and pulp and paper mills under the Federal Fisheries Act, define the process that is to be used to evaluate existing effects caused by liquid effluents discharged by operating facilities. The EA process occurs before a project is approved, and involves predicting whether the project is going to cause significant environmental impacts. The EEM process occurs after a project is operational, and involves determining whether an existing project has had or is continuing to have significant impacts on the environment. Ideally, the processes are complimentary, with the EA process identifying environmental attributes considered important, and the EEM process demonstrating whether predicted or unpredicted impacts occurred. The two processes are usually done in isolation so potential synergies are lost. The point of this manuscript is to justify bridging the two processes. We use the aquatic environment as the example, and briefly describe the EEM process, aquatic environment indicators, experimental designs, and typical environmental thresholds, to illustrate how the EEM and EA processes link. [ABSTRACT FROM AUTHOR]

The Daling River Basin is an important ecological functional area in the western region of Liaoning with outstanding environmental problems. The monitoring of ecological and environmental quality in the basin and the analysis of driving factors are of great importance for the protection of the ecological environment and the improvement of economic quality. In this paper, the three periods of Landsat remote sensing images in 1995, 2010 and 2020 are used as the basic data, and platforms and technical means such as RS and GIS are used to decipher and extract the three periods of land use information, and to construct the land use type transfer matrix. The remote sensing ecological index (RSEI) was improved, and the principal component analysis method was applied to construct the improved remote sensing ecological index (IRSEI) model based on the greenness (NDVI), moisture (WET), heat (LST) and new dryness (N-NDBSI), so as to realize the dynamic monitoring of ecological and environmental quality in the study area. Based on the land use change, combined with the trend of improved remote sensing ecological index (IRSEI) of Daling River Basin, thus achieving the purpose of rapid and efficient dynamic monitoring of ecological quality of Daling River Basin from 1995 to 2020. A geoprobe model was then used to systematically assess the drivers of ecological quality in the catchment. The results show that the improved remote sensing ecological index (IRSEI) can efficiently and accurately obtain the spatial distribution pattern and temporal variation trend of IRSEI in the study area, which is more in line with the characteristics of indicators in this study area. The IRSEI in the study area showed an increasing trend from 1995 to 2020, from 0.4794 to 0.5615, and the proportion of benign ecological classes increased year by year during the period. Among the evaluation indicators, NDVI and N-NDBSI are the main factors affecting the environmental and ecological quality of the Daling River Basin, and the increase of vegetation cover, climate regulation and human activities have obvious promoting effects on the improvement of the ecological environment of the Daling River Basin. This study provides a scientific theoretical basis for the implementation of further ecological environmental protection measures. [ABSTRACT FROM AUTHOR]

Spatio-temporal models can be used to analyze data collected at various spatial locations throughout multiple time points. However, even with a finite number of spatial locations, there may be insufficient resources to collect data from every spatial location at every time point. We develop a spatio-temporal finite-population block kriging (ST-FPBK) method to predict a quantity of interest, such as a mean or total, across a finite number of spatial locations. This ST-FPBK predictor incorporates an appropriate variance reduction for sampling from a finite population. Through an application to moose surveys in the east-central region of Alaska, we show that the predictor has a substantially smaller standard error compared to a predictor from the purely spatial model that is currently used to analyze moose surveys in the region. We also show how the model can be used to forecast a prediction for abundance in a time point for which spatial locations have not yet been surveyed. A separate simulation study shows that the spatio-temporal predictor is unbiased and that prediction intervals from the ST-FPBK predictor attain appropriate coverage. For ecological monitoring surveys completed with some regularity through time, use of ST-FPBK could improve precision. We also give an R package that ecologists and resource managers could use to incorporate data from past surveys in predicting a quantity from a current survey. Supplementary materials accompanying this paper appear on-line. [ABSTRACT FROM AUTHOR]

Fluorescent probes are sensitive, selective, nontoxic in detection and thus provided a new solution in biomedical, environmental monitoring, and food safety. In order to expand the application of fluorescent probes in various fields, the paper discusses the design, synthesis, and characterization of fluorescent probes, explores new design and development trends of fluorescent probes in various fields, and improves the performance and applicability of fluorescent probes by using new materials and technologies to meet the evolving demands of molecular detection in various fields. [ABSTRACT FROM AUTHOR]

The traditional monitoring method of water resources environment mainly relies on manual sampling and laboratory analysis, which is limited in time and space and can not realize the comprehensive monitoring of water resources environment. With the continuous development of computer technology and network communication technology, real-time data monitoring method of water resources environment based on computer remote data acquisition and image analysis has gradually become a new solution. This paper aims to propose a real-time data monitoring method of water resources environment based on computer remote data acquisition and image analysis, in order to achieve accurate and efficient monitoring of water resources environment, timely acquisition and analysis of key data of water resources environment, and provide scientific basis for relevant decisions. In this paper, the key parameters of water quality, water quantity and water ecology are collected by using computer remote data acquisition and image analysis. Using computer image analysis technology, the collected image data are processed and analyzed, and the related characteristics and indicators of water resources environment are extracted. The results show that the real-time data monitoring method of water resources environment based on computer remote data acquisition and image analysis can monitor the data changes of water resources environment accurately and efficiently. Through the analysis and processing of the real-time data, the problems in the water resources environment can be found and warned in time, and the corresponding measures can be taken to regulate and manage. [ABSTRACT FROM AUTHOR]

The widespread application of pesticides in Morocco's agriculture renders their monitoring in food and environmental samples very necessary. Recent years have witnessed a growing interest in reporting studies related to the monitoring of pesticide residues in food, water, groundwater, and soil as well as their quantitative health risk assessment. Most published studies have been done by university researchers. However, the lack of research reproducibility remains a problem that considerably limits the possibility of exploiting data from the literature. Our study involves an extensive literature review utilizing search engines with keywords like "pesticide residues," "monitoring," "vegetables and fruits," "water and soil," "risk assessment," and "Morocco" from 2009 to 2023. Analysis of pesticide residues in foodstuffs and environmental samples highlights concerns over compliance with EU regulations, the health risks associated with pesticide exposure, and the necessity for comprehensive monitoring and risk assessment strategies. This paper could help influence policies to develop a strategy and action plan for the sound management of pesticides, including measures to reduce their use, raise awareness, and monitor compliance. Also, this paper could be useful for scientists interested in understanding the current situation and challenges regarding pesticide residues in Morocco, as well as countries with which commercial links exist. [ABSTRACT FROM AUTHOR]

Improved environmental monitoring of microorganisms is currently an important issue, since traditional detection methods are costly and time consuming (often requiring 2-3 days). In contrast, microfluidic chip-based technologies provide promising alternatives. The presence of environmental contaminants, especially bacterial, viral, and parasitic pathogens and their toxins, is creating a major public health problem. The detection of microbial communities in environmental samples is the first step to recognizing these organisms and insuring health and safety against their infection. This review addresses both the existing and innovative technologies for the detection of pathogens present in the environmental samples. First, impacts and challenges related to pathogens in the environmental samples are discussed, and standard techniques for their identification are addressed. Next, the microfluidic technologies are introduced as an alternative strategy with a particular focus on the detection of environmental contaminants. Challenges that still need to be overcome are also discussed. The review concludes with a section on paper-based microfluidic device and a discussion on future prospects. [ABSTRACT FROM AUTHOR]

The article focuses on several aspects involved for the preparation and implementation of an environmental monitoring program. It notes that the monitoring program aims at obtaining measurement result for parameters considering an evaluation as the ground for action. Furthermore, the evaluation criteria provide an effect that is critical on the performance of monitoring schemes which cover from the improvement of a strategy to the procedure utilized in measuring the gathered data.

In theory, building automation and management systems (BAMSs) can provide all the components and functionalities required for analyzing and operating buildings. However, in reality, these systems can only ensure the control of heating ventilation and air conditioning system systems. Therefore, many other tasks are left to the operator, e.g. evaluating buildings' performance, detecting abnormal energy consumption, identifying the changes needed to improve efficiency, ensuring the security and privacy of end-users, etc. To that end, there has been a movement for developing artificial intelligence (AI) big data analytic tools as they offer various new and tailor-made solutions that are incredibly appropriate for practical buildings' management. Typically, they can help the operator in (i) analyzing the tons of connected equipment data; and; (ii) making intelligent, efficient, and on-time decisions to improve the buildings' performance. This paper presents a comprehensive systematic survey on using AI-big data analytics in BAMSs. It covers various AI-based tasks, e.g. load forecasting, water management, indoor environmental quality monitoring, occupancy detection, etc. The first part of this paper adopts a well-designed taxonomy to overview existing frameworks. A comprehensive review is conducted about different aspects, including the learning process, building environment, computing platforms, and application scenario. Moving on, a critical discussion is performed to identify current challenges. The second part aims at providing the reader with insights into the real-world application of AI-big data analytics. Thus, three case studies that demonstrate the use of AI-big data analytics in BAMSs are presented, focusing on energy anomaly detection in residential and office buildings and energy and performance optimization in sports facilities. Lastly, future directions and valuable recommendations are identified to improve the performance and reliability of BAMSs in intelligent buildings. [ABSTRACT FROM AUTHOR]

Presents papers featured during the 4th Land-Ocean Interactions in the Coastal Zone (LOICZ) Open Science Meeting held on November 1999 in Bahia Blanca, Argentina. Discussion of the linkages between catchment characteristics and water chemistry, a critical determinant for coastal system functioning; Details of the LOICZ project; Examination of the environmental conditions, the future threats and options for societal response in the Russian Arctic and the island of Mauritius.

Accurately acquiring cloud information through cloud images segmentation is of great importance for weather forecasting, environmental monitoring, sites selection of observatory and analysis of climate evolution. In this paper, a cloud segmentation method based on deep learning, called CloudU-Netv2, is proposed to segment daytime and nighttime ground-based cloud images. The CloudU-Netv2 includes encoder, dual attention modules and decoder. The contributions in this paper are four folds as follows. Firstly, it replaces the 'upsampling' in CloudU-Net with 'bilinear upsampling'. Secondly, position and channel attention modules are added to the structure to improve the discrimination ability of features' representation. Thirdly, it chooses rectified Adam as the optimizer in the CloudU-Netv2 structure. Finally, we conduct ablation experiments on the key components of CloudU-Netv2 and compare with the existing four advanced methods using six evaluation metrics. Results show that the key components of the model play the pivotal role in improving the segmentation performance, and the proposed CloudU-Netv2 has the best segmentation performance for daytime and nighttime ground-based cloud images compared with four other methods. [ABSTRACT FROM AUTHOR]

The universal remote sensing image processing software focuses on the preprocessing of remote sensing data, and it is used to implement the monitoring and evaluation functions of the ecological environment such as drought and flood. The operation is complex. In order to simplify the work process of natural geographical environment monitoring and assessment, GIS technology and data mining technology were combined in this paper. With monitoring and evaluation as the core, a decision tree model was constructed. Taking the Dongting Lake as an example, the scale and characteristics of its texture were studied, and combined with other ancillary data, the Dongting land information was explored and the land types were classified. Finally, a conclusion was reached: The algorithm designed in this paper can be applied to the land types of the natural geographical environment. The classification model has a positive guiding role in the judgment of environmental monitoring and assessment. [ABSTRACT FROM AUTHOR]

In Brazil, there are no unified and effective environmental monitoring models for bodies of water. Thus, several methodologies are used that result in information that is often difficult to compare, especially for stakeholders involved in regional water management. Studies in some countries such as Australia, Chile, the USA, and Sweden use the monitoring model implemented in Canada that was developed in the early 1990s. This model was designed to evaluate whether the current environmental regulations are sufficiently protective for pulp and paper effluents and for metal mining effluents. In this study, the Canadian Environmental Effects Monitoring methodologies were applied to three different Brazilian river basins, with the goal of constructing a framework for monitoring environmental effects. Pilot studies were carried out in the estuarine regions of the Benevente, Jucu, and Santa Maria da Vitória river basins, which are important rivers in the state of Espírito Santo. Evaluations included fish health, bioaccumulation studies, benthic invertebrate survey, and physical-chemical analyses of water and sediment. The quality of the environments was evaluated by means of seasonal samplings and comparisons between discharge, upstream, and downstream areas. This study made it possible to identify appropriate fish species to be used in environmental effects monitoring and the environmental quality of the rivers themselves as well as knowledge and policy gaps to implement such monitoring programs in Brazil. The study raises questions about the adequacy of Brazilian environmental legislation concerning tidal rivers. [ABSTRACT FROM AUTHOR]

Background: The accumulation of trace elements in mosses is used as an indirect measure of atmospheric deposition and an important complement to the techniques used to monitor the Geneva Air Pollution Convention. The aim of this paper is to quantify and map temporal and spatial trends of metal enrichment in mosses collected in Germany in 1990, 1995, 2000, 2005, 2015 and 2020. Collection and chemical analysis of the moss samples were carried out according to international guidelines. Results: The analysis shows that since 1990, the median concentrations of As, Cd, Cu, Ni, Pb and Sb in the mosses have been decreasing significantly, with the with the highest decline of Pb (− 86%). This trend reversed in 2000 and 2005 and between 2015 and 2020 by increases in the concentrations of some trace elements. In the 2000 Moss Survey, higher concentrations were measured for Cd, Cu, Ni and Sb than in 2015, ranging from + 26% (Cu) to + 165% (Ni). For As and Pb, no significant changes can be observed in 2020 compared to 2015. The increase in metal concentrations in the mosses over the last five years does not correspond to the corresponding trends in reported metal emissions in Germany (2015–2020). In contrast, the long-term trends of the As, Cd, Cu, Ni and Pb concentrations measured in the mosses showed good overall correspondence with the emission trends in Germany (1990–2020). The long-term trends of the moss data are mostly weaker than those of the emission data. The spatial patterns of the temporal trends were mapped and discussed for As, Cd, Cu, Ni, Pb and Sb. Conclusions: The study shows that for valid monitoring of atmospheric deposition, it is not enough to consider only emission data or the modelled deposition derived from these data. In this respect, the study provides one of many necessary contributions to the discussion on the extent to which analytes of current monitoring programmes are still relevant and up-to-date and whether there are new substances that are also relevant or even more relevant than existing analytes and to what extent this should be taken into account in designing future environmental monitoring. [ABSTRACT FROM AUTHOR]

Multi-sensor fire detection has been widely used, which allows monitoring multiple environmental indicators. However, most multi-sensor detection methods detect fires only by comparing the measurements of environmental indicators at each detection time with the preset thresholds. It is prone to fire false alarms due to neglecting the time series characteristics of environmental information. To improve the robustness and accuracy of fire detection, this paper proposes a new multi-sensor fire detection method based on long short-term memory (LSTM) networks, named EIF-LSTM. EIF-LSTM integrates environmental information fusion, which is divided into two steps. First, EIF-LSTM extracts the time series characteristics of the monitoring environment by processing multi-sensor time series readings, including environmental indicator variation information and environmental level information. Second, the normalized multi-sensor time series readings, environmental indicator variation information and environmental level information are fused together for fire prediction. The LSTM network realizes the extraction of environmental time series characteristics due to its ability to learn long-term dependencies. The addition of two kinds of time series information increases the detection dimension and enhances the fusion effect. Experimental results on a real-world fire dataset show that EIF-LSTM is capable of achieving state-of-the-art detection performance. [ABSTRACT FROM AUTHOR]

Grid-based approaches render an efficient framework for data clustering in the presence of incomplete, inexplicit, and uncertain data. This paper proposes an entropy-based grid approach (EGO) for outlier detection in clustered data. The given hard clusters obtained from a hard clustering algorithm, EGO uses entropy on the dataset as a whole or on an individual cluster to detect outliers. EGO works in two steps: explicit outlier detection and implicit outlier detection. Explicit outlier detection is concerned with those data points that are isolated in the grid cells. They are either far from the dense region or maybe a nearby isolated data point and therefore declared as an explicit outlier. Implicit outlier detection is associated with the detection of outliers that are perplexedly deviated from the normal pattern. The determination of such outliers is achieved using entropy change of the dataset or a specific cluster for each deviation. The elbow based on the trade-off between entropy and object geometries optimizes the outlier detection process. Experimental results on CHAMELEON datasets and other similar datasets suggested that the proposed approach(es) detect the outliers more precisely and extend the capability of outliers detection to an additional 4.5% to 8.6%. Moreover, the resultant clusters became more precise and compact when the entropy-based gridding approach is applied on top of hard clustering algorithms. The performance of the proposed algorithms is compared with well-known outlier detection algorithms, including DBSCAN, HDBSCAN, RE3WC, LOF, LoOP, ABOD, CBLOF and HBOS. Finally, a case study for detecting outliers in environmental data has been carried out using the proposed approach and results are generated on our synthetically prepared datasets. The performance shows that the proposed approach may be an industrial-oriented solution to outlier detection in environmental monitoring data. [ABSTRACT FROM AUTHOR]

The Baikal Natural Territory (BNT) and Khuvsgul region have similar environmental problems. It is relevant to carry out integrated scientific studies and monitor the state of the components of the natural environment in these areas. This paper presents the results of a number of joint Russian–Mongolian projects aimed at studying and developing new methods and technologies for integrated environmental monitoring and prediction. A digital platform has been created to support scientific research and environmental monitoring. This platform makes it possible to collect, store, process, and analyze large arrays of heterogeneous spatiotemporal data and predict environmental situations using a set of mathematical and information models, services, and machine learning methods. The authors have also developed methods and web services for environmental monitoring based on the processing of Earth remote sensing (RS) data. A technology for classifying multispectral Sentinel-2 satellite images has been created that makes it possible to distinguish 12 classes of the land cover using artificial intelligence methods. A service for monitoring the state of the atmosphere over large areas has been created based on the processing of Sentinel-5P satellite data. This service makes it possible to display the concentrations of SO2, NO2, CO, CH4, H2O, O3, formaldehydes, and aerosols in the air. [ABSTRACT FROM AUTHOR]

The reform of environmental management systems is key to improving environmental pollution treatment and green technology innovation. Based on panel data on 30 provincial administrative regions in China for 2008 to 2016, this paper analyzes the impacts of environmental decentralization and environmental protection investment on green technology innovation. It is first found that environmental decentralization promotes green technology innovation after inhibition. Similar effects are found for environmental administrative decentralization, environmental monitoring decentralization, and environmental supervision decentralization. Second, in the long run, environmental decentralization in developed and low-emission regions is more conducive to green technology innovation. Third, environmental pollution treatment investment has a significant inhibiting effect on green technology innovation under high levels of environmental decentralization, and the inhibiting effects of industrial pollution source treatment investment and "three simultaneous" construction project investments are particularly obvious. This paper explores green technology innovation as the goal of environmental decentralization, which is the driving force behind pollution control. From the perspective of environmental protection investment, the paper further analyzes the impact of environmental decentralization on green technology innovation. The study has important reference value for determining reasonable levels of environmental decentralization among different levels of governance and in formulating differentiated strategies of environmental decentralization. [ABSTRACT FROM AUTHOR]

Taking China's "Chengde Petroleum College" as an example, this paper analyzes the current situation of computer room monitoring in colleges and universities. The Internet of Things technology is used to remotely and automatically monitor the environment of the network computer room. This paper studies and puts forward the method and model of edge calculation in the network computer room monitoring system. The monitoring methods of critical parameters such as thermal environment and energy consumption of computer room are given. The practical application shows that, compared with the historical data in the same period, the energy saving rate of the scheme is as high as 15% ~ 27%, and has good market promotion value. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) describes embedded devices (things) with Internet-based connectivity, enabling them to receive and send data through the communication network. In addition, it provides infrastructure to let things have interacted with each other and people. This advantage of the IoT can increase reliability, sustainability, and efficiency by enhanced information access fashion. This technology can be used in various fields, such as environmental monitoring, home, and building automation and smart networks. Furthermore, the main aim of Service-Oriented Architecture (SOA) is to select the best services among a pool of services. These services can be selected statically or dynamically regarding the service functionalities and performance limitations. Since the performance of complex services is very important in many distributed domains. This study aims to systematically review the service selection mechanisms in the IoT. The service selection mechanisms are classified into centralized, decentralized, and hybrid classes. Also, the detailed evaluation of these techniques brings a good suggestion for further studies. [ABSTRACT FROM AUTHOR]

The land, oceans, and atmosphere are tightly linked and form the most dynamic component of the climate system. Studies on terrestrial and ocean science enhance the understanding on the impacts of climate change. Across India and the world over, human-driven land use and climate changes are altering the structure, function, and extent of natural terrestrial ecosystems and in turn regional biogeochemical feedbacks. In this special issue, we present 29 manuscripts; those discuss wide-ranging aspects of terrestrial and oceanic characterization and dynamics. These contributions are based on selected presentations made at the 2nd International Workshop on Biodiversity and Climate Change (BDCC-2018) held on 24–27 February 2018 at the Indian Institute of Technology Kharagpur, India. The manuscripts are arranged in five sections such as Ecological Assessment, Plant Invasion, Carbon Dynamics, Ecosystem Characterization, and Ocean Dynamics. We realized that the utility of satellite remote sensing data has been emerging as a dominant trend in environmental monitoring and assessment studies in India. [ABSTRACT FROM AUTHOR]

Detection of subsurface hydrodynamic anomalies plays a significant role in groundwater resource management and environmental monitoring. In this paper, based on data from the groundwater level, atmospheric pressure, and precipitation in the Chengdu area of China, a method for detecting outliers considering the factors affecting groundwater levels is proposed. By analyzing the factors affecting groundwater levels in the monitoring site and eliminating them, simplified groundwater data is obtained. Applying sl-Pauta (self-learning-based Pauta), iForest (Isolated Forest), OCSVM (One-Class SVM), and KNN to synthetic data with known outliers, testing and evaluating the effectiveness of 4 technologies. Finally, the four methods are applied to the detection of outliers in simplified groundwater levels. The results show that in the detection of outliers in synthesized data, the OCSVM method has the best detection performance, with a precision rate of 88.89%, a recall rate of 91.43%, an F1 score of 90.14%, and an AUC value of 95.66%. In the detection of outliers in simplified groundwater levels, a qualitative analysis of the displacement data within the field of view indicates that the outlier detection performance of iForest and OCSVM is better than that of KNN. The proposed method for considering the factors affecting groundwater levels can improve the efficiency and accuracy of detecting outliers in groundwater level data. [ABSTRACT FROM AUTHOR]

This paper presents a long-term analysis of ambient PM10 concentrations measured at a background station in Spain, using backward trajectories generated with the HYSPLIT model, together with the identification of synoptic patterns and a fuzzy clustering analysis, to identify the sources present and evaluate their relationship with meteorological variables such as wind speed and direction, temperature, and atmospheric pressure. Ambient PM10 presented maximum values during the summer with mean concentrations of approximately 14 µg m−3 for August, and minimum values during the winter with concentrations of 6 µg m−3 for January. The daily cycle presented two peaks—one in the morning and another in the afternoon—with this variability being associated with transport emissions. African air masses reached the study site extending vertically at least up to 2500 m.a.g.l, with a frequency of 43.5%, and are associated to a mean ground PM10 concentration of 41.3 µg m−3. During the episodes of Saharan intrusions, high pressures with unclassified synoptic patterns (U) prevailed over the Iberian Peninsula. Local, European, maritime and intermittent contributions were the four main sources of pollutants identified through fuzzy clustering analysis. These intermittent contributions are associated with Saharan dust intrusions, with a long-term average PM10 concentration of 1.7 µg m−3, which represents an important contribution of 11.2%. These sources affect seasonal variations of PM10 background concentrations, and reach their maximum when the greatest contributions of desert dust occur—mainly during the spring–summer months. These results provide useful information for future comparisons and environmental monitoring of PM10 levels. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) nanomaterials have been widely used in gas sensing due to their large specific surface area, high surface reactivity, and excellent gas adsorption properties. This paper reviews the typical synthesis methods of various types of 2D nanomaterials and summarizes the recent progress in gas sensors based on 2D materials, such as noble metal nanoparticles (NPs), metal oxides (MOS), conductive polymers, other new 2D materials. The methods of doping, modification, and photoexcitation can effectively improve the gas-sensing properties of 2D materials. The sensitive mechanisms of heterojunction, Schottky junction, and photoexcitation in 2D material sensors are discussed in detail. This paper discusses the application prospects of 2D materials in wearable gas sensors, food safety, and self-powered sensing, and provides ideas for further applications in environmental quality monitoring and disease diagnosis. In addition, the opportunities and challenges for gas sensors based on 2D materials are also discussed. [ABSTRACT FROM AUTHOR]

Disposal of carbonless copy paper (CCP) paper sludge during the 1960s contaminated a site in the USA with PCBs. Despite historic records of CCP sludge disposal and absence of evidence of any other disposal, a dispute arose among the parties over the source of the PCBs. Aroclor 1242 is well documented as the PCB mixture used in CCP, yet Aroclors 1242, 1248, 1254, and 1260 were reported by the analytical laboratory. How could the PCBs at a single, small site be reported as four different Aroclors? Some claimed that there had to be at least four Aroclors source inputs to the site. Disposal of four different Aroclors at this site would simply defy logic and the historic record. Weathering of the mixtures is part of the story. A larger issue is the conflict between the intent of the USEPA 8082 method to determine the total PCB content in environmental samples to facilitate environmental cleanup and disposal decisions within a regulatory context versus the data users’ intent to identify the PCB sources. This inappropriate extension of the data leads to erroneous conclusions. To mitigate problems like this, laboratory analysis requests need to be matched to the intended data usage; conversely, the data must not be over-interpreted beyond the limits of the method. The PCB analysis community needs to develop a better articulation of the limits of Aroclor identification for the broader community that may naïvely assume that if the laboratory reports “Aroclor 1248,” then someone must have placed Aroclor 1248 at the site. After all, when a laboratory reports “lead” or “chloroform,” those identifications are never in question. [ABSTRACT FROM AUTHOR]

The widespread use of the Internet of Things (Iot) makes it possible to connect everything but having enough IP addresses is a fundamental requirement of this paradigm. All previous environmental monitoring systems in China are based on IPv4. In combination with the characteristics and requirements of China's atmospheric environment monitoring system, this paper develops a monitoring system based on IPv6 technology. Users can directly access the monitoring equipment through the IPv6 website to view data and configure operations. This paper first introduces the design and implementation of the software and hardware of the system, then introduces the simplification of IPv6 protocol, the transplantation of IPv6 protocol on ARM and the design and implementation of embedded Web server system. The experimental results show that the developed atmospheric environment monitoring system can realize continuous data acquisition based on IPv6 and provide data-driven support for environmental protection management and decision-making. [ABSTRACT FROM AUTHOR]

In this paper, a novel D-shaped photonic crystal fiber (PCF) refractive index (RI) sensor based on surface plasmon resonance (SPR) effect is proposed. By introducing a smiley-faced hole and Ag-TiO2 composite micro-grating, the high RI sensing performances can be realized. With finite element method, the propagation characteristics of the proposed D-shaped SPR-PCF RI sensor are numerically investigated. The simulation results show that the average wavelength sensitivity (WS) is 5400 nm/RIU, and the maximum WS can reach 15,500 nm/RIU in the RI range from 1.30 to 1.39. Besides, the proposed D-shaped SPR-PCF RI sensor can obtain the maximum resolution (R) of 4.95 × 10−5RIU and the maximum figure of merit (FOM) of 423.78 RIU−1, respectively. It is believed that the proposed SPR-PCF RI sensor has potential applications in the fields of environmental monitoring, biomedical analysis, and food safety management. [ABSTRACT FROM AUTHOR]

This paper presents a graphene–gold-metasurface sensor designed for rapid and precise detection of heavy metals, particularly Cu2+ and Mg2+ ions, in water samples. By employing COMSOL simulations, the sensor's performance across various cases was comprehensively analyzed. The sensor demonstrates an optimized sensitivity of 1140 GHz/RIU for Cu2+ detection and 1149 GHz/RIU for Mg2+ detection. Furthermore, this sensor achieves minimum figure of merit (FOM) of 2.781 RIU−1 and 2.855 RIU−1 for Cu2+and Mg2+ detection, respectively, showcasing its superior performance in sensing these metal ions. Also the highest quality factors (Q factors) of 11.244 for Cu2+ detection and Q factor 11.247 for Mg2+ detection are attained. The proposed sensor structure additionally demonstrates very low detection limits- which is 0.466 for Cu2+ and 0.485 for Mg2+ detection-and this implies it can detect trace amounts without any difficulty. The excellent promising features of this sensor position it as a self directed candidate for detection of Cu2+ and Mg2+ ions with high accuracy and sensitivity. These solid applications act as the gateway to the monitoring of environmental cleanliness among other applications. Additionally,the proposed sensor can also be used as a 2-bit encoder. [ABSTRACT FROM AUTHOR]

Photoluminescent carbon dots (CDs) have garnered significant interest owing to their distinctive optical and electronic properties. In contrast to semiconductor quantum dots, which incorporated toxic elements in their composition, CDs have emerged as a promising alternative, rendering them suitable for both environmental and biological applications. CDs exhibit astonishing features, including photoluminescence, charge transfer, quantum confinement effect, and biocompatibility. Recently, CDs derived from green sources have drawn a lot of attention due to their strong photostability, reduced toxicity, better biocompatibility, enhanced fluorescence, and simplicity. These attributes have shown great promise in the areas of LED technology, bioimaging, photocatalysis, drug delivery, biosensing, and antibacterial activity. In contrast, this review offers a comprehensive overview of various green sources utilized to produce CDs and methodologies, along with their merits and demerits, with a notable emphasis on physiochemical properties. Additionally, the paper provides insight into the bibliometric analysis and recent advancements of CDs in sensing, photocatalysis, and antibacterial activity. In this field, extensive research is underway, and a total of 7,438 articles have been identified. Among these, 4242 articles are dedicated to sensing applications, while 1518 and 1678 focus on adsorption and degradation. Carbon dots demonstrate exceptional sensing capabilities within the nanomolar range with a selectivity of up to 95% for pollutants. They exhibit excellent degradation efficiency exceeding 90% within 10–130 min and possess an adsorption capacity from 100 to 800 mg/g. These fascinating qualities render them suitable for diverse applications. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSNs) are extensively utilized across diverse applications, ranging from environmental monitoring to industrial automation. These networks deploy autonomous devices equipped with sensors to monitor environmental conditions such as temperature, humidity, and light. They play crucial roles in fields like precision agriculture, healthcare monitoring, and smart cities infrastructure. In the domain of WSNs, ensuring both security and precise localization is vital for sustaining optimal network performance and facilitating timely event detection. Despite numerous localization studies, existing approaches often fall short in 3D localization due to low beacon node accuracy and sparse environment coverage. Furthermore, achieving higher localization accuracy is challenging due to potential attacks that can compromise network integrity and reduce battery life. To address these issues, a novel Secure 3D algorithm is introduced in this paper to combat malicious beacon nodes as well as to enhance localization accuracy. The proposed Secure 3D algorithm demonstrates superior performance compared to the 3D DV-Hop, 3D APIT and Improved 3D localization algorithms in terms of Average Localization Error (ALE), Bad Node Proportion (BNP), and Localized Node Proportion (LNP), while also being energy-efficient. This algorithm achieves an ALE ranging from 3.0 to 6.5, a BNP below 0.2, and an LNP exceeding 0.8, all while consuming 100–130mW of energy. By addressing the challenges of malicious beacon nodes and enhancing localization accuracy, the proposed work not only improves network reliability but also ensures energy-efficient energy localization, making it a promising solution for enhancing the performance and security of WSNs in 3D environments. [ABSTRACT FROM AUTHOR]

The article reports on the environmental dispute between Uruguay and Argentina, which can be resolved by a group of scientists. It says that the controversy, which involves a Uruguayan paper-mill complex on a shared Uruguay River, has sparked protests from many Argentinians prompting Argentina to take its neighbouring country to the International Court of Justice. It adds that a joint river monitoring was agreed by the two countries forming their common border for algal blooms and pollution.

A novel nitrogen doped and surface functionalized fluorescent CDs (T1) was synthesized by one-step and green hydrothermal method, which exhibits a satisfactory fluorescence quantum yield and a series of admirable features such as good aqueous solubility, narrow particle size distribution, resistance to photobleaching as well as excitation-dependent behavior. Benefitting from above merits, T1 can be employed to serve as an outstanding sensing platform for sensitive and accurate detection of ClO– by remarkable fluorescence "on–off" process with rapid and anti-interference. More notably, the good biocompatibility and photostability can ensure enormous bioimaging potential and successful application of T1 in monitoring of exogenous ClO– in MG-63 cells. Meanwhile, T1 can also be regarded as a filter paper sensor providing a convenient and efficient analyzing technology for monitoring of free residual chlorine in practical environmental samples. All these results demonstrate that there exists promising possibility for practical applications of T1 in bioimaging systems and environmental monitoring. [ABSTRACT FROM AUTHOR]

Estimating the greenhouse gas emissions of research-related activities is a critical first step towards the design of mitigation policies and actions. Here we propose and motivate a transparent framework for reporting research-related greenhouse gas emissions, through the inclusion of standardised reporting tables in scientific publications. All human activity generates a carbon footprint and scientific research is no exception; however, given the diversity in research activity, developing a standard approach to monitor environmental impact is complex. In this comment, the authors propose a framework for scientists to self-report emissions of research-related emissions in their papers as a means to gradually build an overview of the potential carbon footprint of scientific activity. [ABSTRACT FROM AUTHOR]

A simple wipe sampling procedure was developed for the surface contamination determination of ten cytotoxic drugs: cytarabine, gemcitabine, methotrexate, etoposide phosphate, cyclophosphamide, ifosfamide, irinotecan, doxorubicin, epirubicin and vincristine. Wiping was performed using Whatman filter paper on different surfaces such as stainless steel, polypropylene, polystyrol, glass, latex gloves, computer mouse and coated paperboard. Wiping and desorption procedures were investigated: The same solution containing 20% acetonitrile and 0.1% formic acid in water gave the best results. After ultrasonic desorption and then centrifugation, samples were analysed by a validated liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) in selected reaction monitoring mode. The whole analytical strategy from wipe sampling to LC-MS/MS analysis was evaluated to determine quantitative performance. The lowest limit of quantification of 10 ng per wiping sample (i.e. 0.1 ng cm) was determined for the ten investigated cytotoxic drugs. Relative standard deviation for intermediate precision was always inferior to 20%. As recovery was dependent on the tested surface for each drug, a correction factor was determined and applied for real samples. The method was then successfully applied at the cytotoxic production unit of the Geneva University Hospitals pharmacy. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]