Vehicle derived pollutants as well as industrial emissions simultaneously release deleterious fine-grained particulates and magnetic particles into the atmosphere These magnetic particles are derived ...from the presence of iron (as impurities in fuels, industrial emissions, street dust, rock dust etc.), often a mix of strongly magnetic (magnetite-like) and weakly magnetic (haematite-like) iron oxides. Present review discusses the problem of particulate matter (PM) pollution, its environmental geomagnetic studies with special reference to biomagnetic monitoring through roadside plant leaves. Biomagnetic monitoring with the roadside plant leaves, is very recent thrust area in the field of PM pollution science. An overview of the researches on implications of environmental geo-magnetic studies is presented in this paper for sediments, street dust and vegetation. The concept of environmental magnetism as a proxy for atmospheric pollution levels has been reported by several researchers based on analysis of soils and street or roof dust; however, very few researches have emphasized the use of roadside plant leaves in monitoring the dust. Magnetic biomonitoring of pollutants by measurements taken from roadside tree leaves is potentially efficient and cost-effective. Finally, several case studies on biomagnetic monitoring in Indian subcontinent by our group have been mentioned in detail. Nevertheless, there is still paucity of focused research works in the multifaceted environmental dimensions of magnetic monitoring particularly biomagnetic monitoring of particulate pollution with roadside plant leaves which possess the potential to become a new frontier in the field of atmospheric science and technology.
► An overview on the global problem of particulate matter (PM) pollution. ► Implications of environmental magnetism in PM study. ► Critical review on bio-magnetic monitoring of the PM through roadside plant leaves. ► Case studies on bio-magnetic monitoring.
Food security is a high-priority issue for sustainable global development both quantitatively and qualitatively. In recent decades, adverse effects of unexpected contaminants on crop quality have ...threatened both food security and human health. Heavy metals and metalloids (e.g., Hg, As, Pb, Cd, and Cr) can disturb human metabolomics, contributing to morbidity and even mortality. Therefore, this review focuses on and describes heavy metal contamination in soil–food crop subsystems with respect to human health risks. It also explores the possible geographical pathways of heavy metals in such subsystems. In-depth discussion is further offered on physiological/molecular translocation mechanisms involved in the uptake of metallic contaminants inside food crops. Finally, management strategies are proposed to regain sustainability in soil–food subsystems.
•Heavy metal pollution has perturbed the environment to pose serious health hazards.•Therefore, the diverse and emerging issues of food security have become a global concern.•A better understanding on the soil-food crop transfer mechanisms is prerequisite for remediation.•This review provides a general view on the global geographical pattern of heavy metal sources.•The review discusses state-of-the-art remediation approaches to manage soil metal pollution.
The current advancement in Unmanned Aerial Vehicles (UAVs) and the proliferation of the Internet of Things (IoT) devices is revolutionizing conventional farming operations into precision agriculture. ...The agricultural UAVs combined with IoT use an open channel i.e., the Internet to assist cultivators with data collection, processing, monitoring, and making correct decisions on the farm. However, the use of the Internet opens up a wide range of challenges such as security (e.g., performing cyber-attacks), risk of data privacy (e.g., data poisoning and inference attacks), etc. The usage of current conventional centralized security measures has limitations in terms of a single point of failure, verifiability, traceability, and scalability. Motivated from the aforementioned challenges, we propose a Secured Privacy-Preserving Framework (SP2F) for smart agricultural UAVs. The proposed SP2F framework has two main engines, a two-level privacy engine, and a deep learning-based anomaly detection engine. In the two-level privacy engine, a blockchain, and smart contract-based enhanced Proof of Work (ePoW) is designed for data authentication, and to mitigate data poisoning attacks. A Sparse AutoEncoder (SAE) is applied for transforming data into a new encoded format for preventing inference attacks. In the anomaly detection engine, a Stacked Long-Short-Term Memory (SLSTM) is used to train and evaluate the results of the proposed two-level privacy engine using two publicly accessible IoT-based datasets, namely ToN-IoT and IoT Botnet. Finally, based on thorough analysis, and comparison, we identify that the SP2F framework outperforms several state-of-the-art techniques in both non-blockchain and blockchain frameworks.
With the advancement in sensor technology and the proliferation of low-cost electronic circuits, Internet of Things (IoT) is emerging as a promising technology for realization of smart cities. ...However, challenges such as security, privacy, trust, scalability, verifiability, and centralization prevent faster adaptations of IoT-driven smart cities. Thus, in this paper, a Trustworthy Privacy-Preserving Secured Framework (TP2SF) for smart cities is presented. This framework includes three modules namely: a trustworthiness module, a two-level privacy module, and an intrusion detection module. In trustworthiness module, address-based blockchain reputation system is designed. In the two-level privacy module, a blockchain based enhanced Proof of Work (ePoW) technique is simultaneously applied with Principal Component analysis (PCA) to transform data into a new reduced shape for preventing inference and poisoning attacks. In the intrusion detection module, an optimized gradient tree boosting system (XGBoost) is deployed. Finally, due to inherited strengths and weaknesses of Fog–Cloud architecture, we present a blockchain-IPFS integrated Fog–Cloud infrastructure namely, CloudBlock and FogBlock to deploy proposed TP2SF framework in smart city. The TP2SF framework is evaluated using two realistic IoT-based datasets, namely ToN-IoT and BoT-IoT. The findings indicate the superiority of TP2SF framework over other state-of-the-art techniques in both nonblockchain and blockchain systems.
The rapid pace of industrialization and urbanization has given birth to heavy metal pollution. Heavy metals are one of the most hazardous contaminants that may be present in the aquatic environment. ...It derives its origin from both natural and anthropogenic sources. Heavy metal pollution in aquatic ecosystem poses a serious threat to aquatic biodiversity, and drinking contaminated water poses severe health hazards in humans. The economic aspects and side effects of conventional treatment technologies in aquatic ecosystems paved the way to phytoremediation technology. In phytoremediation, plants are used to ameliorate the environment from various hazardous pollutants. It is cost-effective and eco-friendly technology for environmental cleanup. The characteristics, general mechanism, and ecology of metal hyper-accumulation have been discussed previously. The present review examines the role of aquatic macrophytes in phytoremediation studies. Macrophytes are potent tools in the abatement of heavy metal pollution in aquatic ecosystems receiving industrial effluents and municipal wastewater. They are preferred over other bio-agents due to low cost, frequent abundance in aquatic ecosystems, and easy handling. Aquatic macrophytes usually follow the mechanism of rhizo-filtration for metal removal. The efficiency and selection of potent aquatic plants is done through microcosm investigation, and an overview of significant works is given here. Aquatic macrophytes in natural and constructed wetlands proved to be a potent tool for the treatment of heavy metals from industrial effluents. Physico-chemical factors like temperature, pH, light, salinity, and presence of other heavy metal may affect the metal uptake. Both live and dead biomass of macrophytes may be used in phytoremediation, though dead biomass is generally preferred in the treatment of industrial effluents due to reduced cost, easy disposal, and lack of active biochemical machinery leading to metal toxicity and death of plants. Biomass disposal problem and seasonal growth of aquatic macrophytes are some of the limitations in the transfer of phytoremediation technology from the lab to the field. However, an eco-sustainable model has been developed through our various works that may curb some of the limitations. Disposed biomass of macrophytes may be used for many fruitful applications. Genetic engineering, biodiversity prospecting, and X-ray diffraction spectroscopy are promising future prospects regarding the use of macrophytes in phytoremediation studies. A multidisciplinary and integrated approach may enable this embryonic technology to become the new frontier in environmental science and technology.
The wastewaters from pharmaceutical manufacturing units, hospitals, and domestic sewage contaminated with excretal matters of medicine users are the prime sources of pharmaceutical pollutants (PPs) ...in natural water bodies. In the present study, PPs have been considered one of the emerging pollutants (EPs) and a cause of concern in river health assessment. Beyond the reported increase in antibiotic-resistant bacteria (ABRB), PPs have been found adversely affecting the biotic diversity in such water environments. Considering Algae, Macroinvertebrates, and Fishes as three distinct trophic level indicators, the present study puts forward a framework for showing River Health Condition (RHC) based on the calculation of a River Health Index (RHI). The RHI is calculated using six Indicator Group Scores (IGS) which individually reflect river health in a defined category of water quality characteristics. While Dissolved Oxygen Related Parameters (DORP), Nutrients (NT), and PPs are taken as causative agents affecting RHCs, scores of Algal-Bacterial (AB) symbiosis, Macroinvertebrates (MI), and Fishes (F) are considered as an effect of such environmental conditions. Current wastewater treatment technologies are also not very effective in the removal of PPs. The objective of the present study is to review the harmful effects of PPs on the aquatic environment, particularly on the chemical and biotic indicators of river health. Based on predicted no-effect concentrations (PNEC) for algae, macroinvertebrates, and fishes in the aquatic environment and measured environmental concentration (MEC) in the river, the estimated risk quotient (RQ) for norfloxacin in the Isakavagu-Nakkavagu stream of river Godavari, Hyderabad is found 293 for algae, 39 for MI, and 335 for fish. Among PPs, in Indian rivers, the presence of caffeine is the most frequent, with algae at the highest level of risk (RQmax= 24.5).
Broadly six PPs, including azithromycin, caffeine, diclofenac, naproxen, norfloxacin, and sulfamethoxazole are found above PNEC values in Indian rivers. The application of IGS and RHI in understanding and presenting the river health condition (RHC) through colored hexagons has been demonstrated for the river Ganga near Varanasi (India) as an example. Identification of critical indicator groups, based on IGS provides a scientific basis for planned intervention for river health restoration to achieve an acceptable category.
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•A framework to to determine the RHC has been proposed based on water quality parameters including PPs and biotic indicators.•The toxicity of PPs on aquatic organisms has been projected based on PNEC and critical threshold concentration.•Azithromycin, caffeine, diclofenac, naproxen, norfloxacin, and sulfamethoxazole have been found in concentrations much above their PNEC values for the aquatic environment.•The risk quotient ranges from a modest value of 1.65 (for naproxen on macroinvertebrates) to more than 300 (for norfloxacin on fish).•IGSs and RHI are tools used for river health improvements with time along its course.
Even after 16 years of existence, low energy adaptive clustering hierarchy (LEACH) protocol is still gaining the attention of the research community working in the area of wireless sensor network ...(WSN). This itself shows the importance of this protocol. Researchers have come up with various and diverse modifications of the LEACH protocol. Successors of LEACH protocol are now available from single hop to multi-hop scenarios. Extensive work has already been done related to LEACH and it is a good idea for a new research in the field of WSN to go through LEACH and its variants over the years. This paper surveys the variants of LEACH routing protocols proposed so far and discusses the enhancement and working of them. This survey classifies all the protocols in two sections, namely, single hop communication and multi-hop communication based on data transmission from the cluster head to the base station. A comparitive analysis using nine different parameters, such as energy efficiency, overhead, scalability complexity, and so on, has been provided in a chronological fashion. The article also discusses the strong and the weak points of each and every variants of LEACH. Finally the paper concludes with suggestions on future research domains in the area of WSN.
Over the last few decades, advanced manufacturing and additive printing technologies have made incredible inroads into the fields of engineering, transportation, and healthcare. Among additive ...manufacturing technologies, 3D printing is gradually emerging as a powerful technique owing to a combination of attractive features, such as fast prototyping, fabrication of complex designs/structures, minimization of waste generation, and easy mass customization. Of late, 4D printing has also been initiated, which is the sophisticated version of the 3D printing. It has an extra advantageous feature: retaining shape memory and being able to provide instructions to the printed parts on how to move or adapt under some environmental conditions, such as, water, wind, light, temperature, or other environmental stimuli. This advanced printing utilizes the response of smart manufactured materials, which offer the capability of changing shapes postproduction over application of any forms of energy. The potential application of 4D printing in the biomedical field is huge. Here, the technology could be applied to tissue engineering, medicine, and configuration of smart biomedical devices. Various characteristics of next generation additive printings, namely 3D and 4D printings, and their use in enhancing the manufacturing domain, their development, and some of the applications have been discussed. Special materials with piezoelectric properties and shape-changing characteristics have also been discussed in comparison with conventional material options for additive printing.
•The Water, energy and food (WEF) nexus approach is cross-sectoral methodological approach for sustainable environmental management.•Water security, energy resilience, and food security need to be ...addressed in concert to augment sustainable development goals (SDGs).•WEF nexus address multifaceted aspects linked to facilitate climate action and environmental management, especially in COVID-19.
The demand for water, energy, and food resources increased in tandem with the world's population, industrialization, and urbanization. Anthropogenic sources of environmental pollutants degrade the water resources while population expansion contributes to rising demand for non-renewable energy resources which further enhances the greenhouse gas emissions. Also, maintaining the food security/-safety is another challenge which needs to be addressed for securing ‘planetary public health’. The sustainability programs, pragmatic studies, and strategies from regulatory/scientific institutions attempt to reduce the depletion of these resources and mitigate environmental challenges however, the individualistic approaches proves to be inadequate. Therefore, the present review emphasizes the use of Water-Energy-Food (WEF) Nexus as a tool to combat environmental degradation, address climate action, and achieve the Sustainable Development Goals (SDGs). In this article, we investigate methodological paradigm and application of WEF Nexus in an inter-related framework through case studies on water resources, energy efficiency, urban food production, food waste reduction, cross-sectoral perspectives, and the circular economy. It has been widely observed that excessive exploitation of these resources influences the global food supply and demand, water availability, resilience in energy and socio-economic sector. Also, such perturbations in water, energy, and food sectors were found to be inextricably linked with climate change. The results further revealed that WEF nexus approach stimulates multilevel and inter-sectoral governance, thereby aiding to address the complexities and inefficiencies in achieving the SDGs. The prioritization of WEF Nexus strategy, especially under the event of COVID-19 can be a holistic approach to sustainably utilise natural resources to help achieve the environmental sustainability.
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Peer Review is at the heart of scholarly communications and the cornerstone of scientific publishing. However, academia often criticizes the peer review system as non-transparent, biased, arbitrary, ...a flawed process at the heart of science, leading to researchers arguing with its reliability and quality. These problems could also be due to the lack of studies with the peer-review texts for various proprietary and confidentiality clauses. Peer review texts could serve as a rich source of Natural Language Processing (NLP) research on understanding the scholarly communication landscape, and thereby build systems towards mitigating those pertinent problems. In this work, we present a first of its kind multi-layered dataset of 1199 open peer review texts manually annotated at the sentence level (∼ 17k sentences) across the four layers, viz. Paper Section Correspondence, Paper Aspect Category, Review Functionality, and Review Significance. Given a text written by the reviewer, we annotate: to which sections (e.g., Methodology, Experiments, etc.), what aspects (e.g., Originality/Novelty, Empirical/Theoretical Soundness, etc.) of the paper does the review text correspond to, what is the role played by the review text (e.g., appreciation, criticism, summary, etc.), and the importance of the review statement (major, minor, general) within the review. We also annotate the sentiment of the reviewer (positive, negative, neutral) for the first two layers to judge the reviewer's perspective on the different sections and aspects of the paper. We further introduce four novel tasks with this dataset, which could serve as an indicator of the exhaustiveness of a peer review and can be a step towards the automatic judgment of review quality. We also present baseline experiments and results for the different tasks for further investigations. We believe our dataset would provide a benchmark experimental testbed for automated systems to leverage on current NLP state-of-the-art techniques to address different issues with peer review quality, thereby ushering increased transparency and trust on the holy grail of scientific research validation. Our dataset and associated codes are available at https://www.iitp.ac.in/~ai-nlp-ml/resources.html#Peer-Review-Analyze.
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