Disposable sensors are low‐cost and easy‐to‐use sensing devices intended for short‐term or rapid single‐point measurements. The growing demand for fast, accessible, and reliable information in a vastly connected world makes disposable sensors increasingly important. The areas of application for such devices are numerous, ranging from pharmaceutical, agricultural, environmental, forensic, and food sciences to wearables and clinical diagnostics, especially in resource‐limited settings. The capabilities of disposable sensors can extend beyond measuring traditional physical quantities (for example, temperature or pressure); they can provide critical chemical and biological information (chemo‐ and biosensors) that can be digitized and made available to users and centralized/decentralized facilities for data storage, remotely. These features could pave the way for new classes of low‐cost systems for health, food, and environmental monitoring that can democratize sensing across the globe. Here, a brief insight into the materials and basics of sensors (methods of transduction, molecular recognition, and amplification) is provided followed by a comprehensive and critical overview of the disposable sensors currently used for medical diagnostics, food, and environmental analysis. Finally, views on how the field of disposable sensing devices will continue its evolution are discussed, including the future trends, challenges, and opportunities.
Land plants are constantly subjected to multiple unfavorable or even adverse environmental conditions. Among them, abiotic stresses (such as salt, drought, heat, cold, heavy metals, ozone, UV radiation, and nutrient deficiencies) have detrimental effects on plant growth and productivity and are increasingly important considering the direct or indirect effects of climate change. Plants respond in many ways to abiotic stresses, from gene expression to physiology, from plant architecture to primary, and secondary metabolism. These complex changes allow plants to tolerate and/or adapt to adverse conditions. The complexity of plant response can be further influenced by the duration and intensity of stress, the plant genotype, the combination of different stresses, the exposed tissue and cell type, and the developmental stage at which plants perceive the stress. It is therefore important to understand more about how plants perceive stress conditions and how they respond and adapt (both in natural and anthropogenic environments). These concepts were the basis of the Special Issue that International Journal of Molecular Sciences expressly addressed to the relationship between environmental stresses and plants and that resulted in the publication of 5 reviews and 38 original research articles. The large participation of several authors and the good number of contributions testifies to the considerable interest that the topic currently receives in the plant science community, especially in the light of the foreseeable climate changes. Here, we briefly summarize the contributions included in the Special Issue, both original articles categorized by stress type and reviews that discuss more comprehensive responses to various stresses.
This study investigated the proximate composition, mineral content, physicochemical characteristics, bacterial viability, and sensory attributes of soybean–coconut composite milk yoghurts formulated in different ratios (100:0, 75:25, 50:50, 25:75, and 0:100) of soybean to coconut milk, codename SCMY01 to SCMY05. The moisture content of approximately 86% with no significant difference among the samples, dominates the proximate results. A gradual reduction in protein (3.79–1.21%) was observed with higher coconut substitution. Sample SCMY05 had the highest fat content (6.48%). Ash, crude fibre, and carbohydrate were highest in sample SCMY01 (0.71, 0.41, and 7.11%). Mineral analysis revealed that soybean-dominant samples were richer in calcium, sodium, magnesium, iron, and zinc, whereas potassium levels were significantly higher in coconut-rich formulations (202.25 to 220.10mg/100g). Physicochemical assessment revealed a decline in pH (4.35–3.90) and an increase in titratable acidity (0.70–1.05%) as the coconut content increased, accompanied by a substantial improvement in total solids (12.00–21.25%). No significant difference was observed in total soluble solid results. Microbial counts ranged from (7.2–8.5 log₁₀ cfu/ml), with soybean-based samples supporting relatively higher microbial growth. Sensory analysis revealed that 100% coconut milk yoghurt was most favoured in terms of colour, taste, flavour, and overall acceptability, whereas soybean-based yoghurt, despite being nutritionally superior, was less accepted due to its pronounced beany flavour. This study highlight soybean–coconut composite yoghurt as a sustainable and health-promoting alternative to dairy yoghurt, with prospects for broader consumer acceptance and commercialization.
AbstractMany metals are essential for living organisms, but at higher doses they may be toxic and carcinogenic. Metal exposure occurs mainly in occupational settings and environmental contaminations in drinking water, air pollution and foods, which can result in serious health problems such as cancer. Arsenic (As), beryllium (Be), cadmium (Cd), chromium (Cr) and nickel (Ni) are classified as Group 1 carcinogens by the International Agency for Research on Cancer. This review provides a comprehensive summary of current concepts of the molecular mechanisms of metal-induced carcinogenesis and focusing on a variety of pathways, including genotoxicity, mutagenesis, oxidative stress, epigenetic modifications such as DNA methylation, histone post-translational modification and alteration in microRNA regulation, competition with essential metal ions and cancer-related signaling pathways. This review takes a broader perspective and aims to assist in guiding future research with respect to the prevention and therapy of metal exposure in human diseases including cancer.
Small, forested catchments are prototypes of terrestrial ecosystems and have been studied in several disciplines of environmental sciences since several decades. Time series of water and matter fluxes and nutrient concentrations from these systems exhibit a bewildering diversity of spatio-temporal patterns, indicating the intricate nature of processes acting on a large range of time scales. Nonlinear dynamics is an obvious framework to investigate catchment time series. We analyze selected long-term data from three headwater catchments in the Bramke valley, Harz mountains, Lower Saxony in Germany at common biweekly resolution for the period 1991 to 2023. For every time series, we perform gap filling, detrending and removal of the annual cycle using Singular System Analysis (SSA), and then calculate metrics based on ordinal pattern statistics: the permutation entropy, permutation complexity and Fisher information, as well as their generalized versions (q-entropy and α-entropy). Further, the position of each variable in Tarnopolski diagrams is displayed and compared to reference stochastic processes, like fractional Brownian motion, fractional Gaussian noise, and \b{eta} noise. Still another way of distinguishing deterministic chaos and structured noise, and quantifying the latter, is provided by the complexity from ordinal pattern positioned slopes (COPPS). We also construct Horizontal Visibility Graphs and estimate the exponent of the decay of the degree distribution. Taken together, the analyses create a characterization of the dynamics of these systems which can be scrutinized for universality, either across variables or between the three geographically very close catchments.
Hao He, Timothy P Canty, Russell R Dickerson
et al.
Between June 6 and 8, 2023, wildfires in Quebec, Canada generated massive smoke plumes that traveled long distances and deteriorated air quality across the Northeastern United States (US). Surface daily PM _2.5 observations exceeded 100 µ g m ^−3 , affecting major cities such as New York City and Philadelphia, while many areas lacked PM _2.5 monitors, making it difficult to assess local air quality conditions. To address this gap, we developed a WRF-CMAQ-BenMAP modeling system to provide rapid, spatially continuous estimates of wildfire-attributable PM _2.5 concentrations and associated health impacts, particularly benefiting regions lacking air quality monitoring. CMAQ simulations driven by two wildfire emissions datasets and two meteorological drivers showed good agreement with PM _2.5 observations, with linear regression results of R ^2 ∼0.6 and slope ∼0.9. We further quantified uncertainties introduced by varying emissions and meteorological drivers and found the choice of wildfire emissions dataset alone can alter PM _2.5 simulations by up to 40 µ g m ^−3 (∼40%). Short-term health impacts were evaluated using the BenMAP model. Validation against asthma-associated emergency department (ED) visits in New York State confirmed the framework’s ability to replicate real-world outcomes, with ED visits increased up to ∼40%. The modeling results identified counties most severely affected by wildfire plumes, the majority of which lack regulatory air quality monitors. Our approach highlights the value of integrated modeling for identifying vulnerable populations and delivering timely health burden estimates, regardless of local monitoring availability.
Abstract Volcanic eruptions produce plumes of ash, gas and aerosols that present a risk to aviation at all standard flight levels. Here, we investigate atmospheric dispersal of volcanic emissions, whether and how they infiltrate aircraft, and whether ground-level public health exposure thresholds can be related to the pressurised cabin environment. We then review the limited evidence for physical and mental health, and behavioural impacts, resulting from volcanic emissions entering aircraft. Serious health risks are considered low for healthy individuals, but respiratory irritation is likely for a high exposure scenario to sulfur dioxide (SO2). Asthmatics are particularly sensitive to SO2, with even relatively low, short exposures, potentially resulting in severe respiratory impacts. Negative group behaviours are not expected but individual distress is possible. Communicating this evidence to the aviation industry may result in more informed decision-making on flightpath alterations and triggering of emergency protocols, both before and during volcanic emission encounters.
Environmental protection, Disasters and engineering
Abstract Background Phytolith-occluded organic carbon (PhytOC) is an important mechanism of long-term stable carbon sinks in terrestrial ecosystems. Farmland abandonment is a widespread land use change in the process of urbanization and industrialization and is still ongoing. Farmland abandonment can significantly affect soil carbon cycling. To elucidate the effects of farmland abandonment on soil PhytOC accumulation, in the present study, corn fields abandoned for 0 to 30 years ago in the mountainous areas of southern China were selected as the research objects. The change trends, influencing factors, and driving mechanisms of soil PhytOC accumulation during the abandonment process were studied. Results The following results were obtained: (1) The range of PhytOC content and storage of the 0–15 cm soil profile for both active and abandoned corn fields was 0.39–1.49 g·kg− 1 and 0.27–0.83 t·hm− 2, respectively. (2) There was a notable enhancement in soil PhytOC accumulation as the duration of abandonment lengthened. In particular, after 30 years of abandonment, soil PhytOC accumulation rose significantly. (3) Abandonment noticeably altered the contents and ratios of soil nutrients of C, N, P and Si, along with key soil enzyme activities such as urease, sucrase, alkaline phosphatase, and catalase. (4) In the context of corn field abandonment, increase in soil PhytOC was primarily attributed to modifications in PhytOC inputs due to variations in surface vegetation cover. The impact of soil environment alterations resulting from abandonment on PhytOC decomposition was less pronounced. Conclusions These findings are instrumental for accurately assessing the carbon sequestration potential of farmland abandonment and for developing regional carbon management strategies based on such practices.
Hermit crabs play a crucial role in coastal ecosystems by dispersing seeds, cleaning up debris, and disturbing soil. They serve as vital indicators of marine environmental health, responding to climate change and pollution. Traditional survey methods, like quadrat sampling, are labor-intensive, time-consuming, and environmentally dependent. This study presents an innovative approach combining UAV-based remote sensing with Super-Resolution Reconstruction (SRR) and the CRAB-YOLO detection network, a modification of YOLOv8s, to monitor hermit crabs. SRR enhances image quality by addressing issues such as motion blur and insufficient resolution, significantly improving detection accuracy over conventional low-resolution fuzzy images. The CRAB-YOLO network integrates three improvements for detection accuracy, hermit crab characteristics, and computational efficiency, achieving state-of-the-art (SOTA) performance compared to other mainstream detection models. The RDN networks demonstrated the best image reconstruction performance, and CRAB-YOLO achieved a mean average precision (mAP) of 69.5% on the SRR test set, a 40% improvement over the conventional Bicubic method with a magnification factor of 4. These results indicate that the proposed method is effective in detecting hermit crabs, offering a cost-effective and automated solution for extensive hermit crab monitoring, thereby aiding coastal benthos conservation.
With 2030 quickly approaching and hence the end of the Sustainable Development Goal (SDG) timeline, it is necessary to start the conversation as to what the post-2030 international development goals, that will take over from the SDGs, will look like. Building on the experiences of implementing the Millennium Development Goals (MDGs) and SDGs, there is the possibility of making the post-2030 goals the most efficient and successful to date. This perspective explores the lessons that have been learnt from the MDGs and SDGs, and together with a consideration of emerging global trends develops proposals for post-2030 goals and targets. In total seven goals are suggested: (1) Operate within planetary boundaries (2) Create growth within resource limits (3) Provide access to basic services for all (4) Eliminate poverty and hunger (5) Reduce inequality (6) Deliver good health and education for all (7) Build strong institutions and international partnerships. The goals are categorised as being: (i) Environmental and Economic (ii) Physical Assets (iii) Social, and (iv) Collaboration. System interdependencies and possible causal connections between the proposed post-2030 goals are also explored. A novel approach of five yearly assessments of the risks involved if the targets are not met, together with suggestions for corrective action is discussed, which will help inform governments and decision makers of the urgent actions needed. To avoid a disruptive future, careful formulation of the post SDG period beyond 2030 is urgently needed to provide a fair and consistent framework to hold both government and industry to account at local, national, and international levels. This will require the strengthening of existing international institutions and strategies for the financing of development.
Field determination and ecological risk assessment of dissolved lead (Pb) were performed at two Yellow Sea sites in China using a continuous automated electrochemical system (CAEDS). This CAEDS instrument includes an automatic triple filter sampler and an electrochemical detection water quality analyzer, which might be operated automatically four times daily. The dissolved Pb concentrations varied from 0.29 to 1.57 μg/L in the South Yellow Sea over 16 days and from 0.32 to 2.28 μg/L in the North Yellow Sea over 13 days. During the typhoon and algal bloom periods, the Pb concentration was as high as ten times greater than usual. According to the calculation of contamination factors (C<sub>f</sub>) and subsequent analysis, seawater quality was classified as Grade II. Through species sensitivity distribution (SSD) method experiments and ecological risk analysis, an average risk quotient (RQ) below 1 for both areas was obtained, indicating a low-to-moderate ecological risk. This system will be helpful for Pb monitoring and assessment in seawater and contribute to the biogeochemical cycling study of Pb.
ChatGPT (GPT) has become one of the most talked-about innovations in recent years, with over 100 million users worldwide. However, there is still limited knowledge about the sources of information GPT utilizes. As a result, we carried out a study focusing on the sources of information within the field of environmental science. In our study, we asked GPT to identify the ten most significant subdisciplines within the field of environmental science. We then asked it to compose a scientific review article on each subdiscipline, including 25 references. We proceeded to analyze these references, focusing on factors such as the number of citations, publication date, and the journal in which the work was published. Our findings indicate that GPT tends to cite highly-cited publications in environmental science, with a median citation count of 1184.5. It also exhibits a preference for older publications, with a median publication year of 2010, and predominantly refers to well-respected journals in the field, with Nature being the most cited journal by GPT. Interestingly, our findings suggest that GPT seems to exclusively rely on citation count data from Google Scholar for the works it cites, rather than utilizing citation information from other scientific databases such as Web of Science or Scopus. In conclusion, our study suggests that Google Scholar citations play a significant role as a predictor for mentioning a study in GPT-generated content. This finding reinforces the dominance of Google Scholar among scientific databases and perpetuates the Matthew Effect in science, where the rich get richer in terms of citations. With many scholars already utilizing GPT for literature review purposes, we can anticipate further disparities and an expanding gap between lesser-cited and highly-cited publications.
<p>Ice-nucleating particles (INPs) initiate primary ice formation in Arctic mixed-phase clouds (MPCs), altering cloud radiative properties and modulating precipitation. For atmospheric INPs, the complexity of their spatiotemporal variations, heterogeneous sources, and evolution via intricate atmospheric interactions challenge the understanding of their impact on microphysical processes in Arctic MPCs and induce an uncertain representation in climate models. In this work, we performed a comprehensive analysis of atmospheric aerosols at the Arctic coastal site in Ny-Ålesund (Svalbard, Norway) from October to November 2019, including their ice nucleation ability, physicochemical properties, and potential sources. Overall, INP concentrations (<span class="inline-formula"><i>N</i><sub>INP</sub></span>) during the observation season were approximately up to 3 orders of magnitude lower compared to the global average, with several samples showing degradation of <span class="inline-formula"><i>N</i><sub>INP</sub></span> after heat treatment, implying the presence of proteinaceous INPs. Particle fluorescence was substantially associated with INP concentrations at warmer ice nucleation temperatures, indicating that in the far-reaching Arctic, aerosols of biogenic origin throughout the snow- and ice-free season may serve as important INP sources. In addition, case studies revealed the links between elevated <span class="inline-formula"><i>N</i><sub>INP</sub></span> and heat lability, fluorescence, high wind speeds originating from the ocean, augmented concentration of coarse-mode particles, and abundant organics. Backward trajectory analysis demonstrated a potential connection between high-latitude dust sources and high INP concentrations, while prolonged air mass history over the ice pack was identified for most scant INP cases. The combination of the above analyses demonstrates that the abundance, physicochemical properties, and potential sources of INPs in the Arctic are highly variable despite its remote location.</p>
AbstractDespite substantial strides in diagnosis and treatment, cardiovascular diseases (CVDs) continue to represent the leading cause of death in the USA and around the world, resulting in significant morbidity and loss of productive years of life. It is increasingly evident that environmental exposures during early development can influence CVD risk across the life course. CVDs exhibit marked sexual dimorphism, but how sex interacts with environmental exposures to affect cardiovascular health is a critical and understudied area of environmental health. Emerging evidence suggests that developmental exposures may have multi- and transgenerational effects on cardiovascular health, with potential sex differences; however, further research in this important area is urgently needed. Lead (Pb), phthalate plasticizers, and perfluoroalkyl substances (PFAS) are ubiquitous environmental contaminants with numerous adverse human health effects. Notably, recent evidence suggests that developmental exposure to each of these toxicants has sex-specific effects on cardiovascular outcomes, but the underlying mechanisms, and their effects on future generations, require further investigation. This review article will highlight the role for the developmental environment in influencing cardiovascular health across generations, with a particular emphasis on sex differences and epigenetic mechanisms. In particular, we will focus on the current evidence for adverse multi and transgenerational effects of developmental exposures to Pb, phthalates, and PFAS and highlight areas where further research is needed.