Level Of Environmental Pollution Research Articles

An evaluation of glass beads from the southwestern coastal state of Goa, India, as a potential pollutant in marine ecosystem.

Glass beads laid on the road, mainly used for better visibility, can contribute to harmful anthropogenic waste to the marine environment, and it is a prerequisite to distinguish the chemical properties associated with it. This is the first systematic approach and evaluation of the toxic and non-toxic characteristics of the glass beads from the Indian coastal region (Goa state), which originated from the wearing of road paint over a period. Glass beads ranging from a few hundred to ~ 1000µm were found on various beaches far from the roadside throughout the coastal state. Examination of these glass beads revealed the possible contribution of toxic elements such as arsenic, lead, cadmium, chromium, and barium beyond the global regulatory limit. Mercury and other analyzed elements are within acceptable limits. However, a quantitative assessment of their environmental impact indicates that glass beads can impact the marine ecosystem and increase the background level of environmental pollutants.

Exploring Alkali Hydroxide Influence on Calcium Titanate Formation for Application in Biodiesel Catalysts

Biodiesel has been recognized as the most widely utilized biofuel around the world due to its significant role in reducing the consumption of crude oil and lowering environmental pollution levels. By serving as a renewable alternative to fossil fuels, bioethanol helps decrease greenhouse gas emissions and contributes to a more sustainable energy future. Traditionally, alkali hydroxides like NaOH and KOH have been mainstays in biodiesel synthesis. However, their overuse can lead to unwanted byproducts and operational complexities. Since calcium titanate can occur at a strong base condition, it presents an alternative avenue worth exploring. In this study, we investigate the influence of alkali hydroxides, namely LiOH, NaOH, and KOH, on the formation of calcium titanate through hydrothermal methods, with varying heating times. We aim to understand how different hydroxides affect the synthesis process and the resultant properties of calcium titanate. We delve into the vibrational properties of Ca‒O‒Ti and Ti‒O bonds using Fourier transform infrared spectroscopy (FTIR), confirming the presence of calcium titanate (JCPDS No.42-0423) through X-ray diffractometry (XRD). This thorough characterization provides insight into the structural integrity and composition of the synthesized materials. Moreover, scanning electron microscopy (SEM) reveals the intriguing cube-like morphology of calcium titanate, offering visual evidence of its unique structure. The fatty acid methyl ester Iimpressively, our results show that calcium titanate synthesized in 7 M NaOH and KOH solutions, heated for 24 hours, emerges as a promising biodiesel catalyst. We observe fatty acid methyl ester provides the percentages of 63.67% and 90.02%, respectively, indicating the catalytic efficacy of these materials in biodiesel production. These findings not only contribute to the understanding of calcium titanate synthesis but also pave the way for a sustainable future in biodiesel production by introducing efficient and eco-friendly catalysts.

New Eco-Friendly Thermal Insulation and Sound Absorption Composite Materials Derived from Waste Black Tea Bags and Date Palm Tree Surface Fibers

A tremendous amount of waste black tea bags (BTBs) and date palm surface fibers (DPSFs), at the end of their life cycle, end up in landfills, leading to increased pollution and an increase in the negative impact on the environment. Therefore, this study aims to utilize these normally wasted materials efficiently by developing new composite materials for thermal insulation and sound absorption. Five insulation composite boards were developed, two were bound (BTB or DPSF with polyvinyl Acetate resin (PVA)) and three were hybrids (BTB, DPSF, and resin). In addition, the loose raw waste materials (BTB and DPSF) were tested separately with no binder. Thermal conductivity and sound absorption coefficients were determined for all boards. Thermal stability analysis was reported for the components of the tea bag (string, label, and bag) and one of the composite hybrid boards. Mechanical properties of the boards such as flexural strain, flexural stress, and flexural elastic modulus were determined for the bound and hybrid composites. The results showed that the thermal conductivity coefficients for all the hybrid composite sample boards are less than 0.07 at the ambient temperature of 24 °C and they were enhanced as the BTB ratio was reduced in the hybrid composite boards. The noise reduction coefficient for bound and all hybrid composite samples is greater than 0.37. The composite samples are thermally stable up to 291 °C. Most composite samples have a high flexure modulus between 4.3 MPa and 10.5 MPa. The tea bag raw materials and the composite samples have a low moisture content below 2.25%. These output results seem promising and encouraging using such developed sample boards as eco-friendly thermal insulation and sound absorption and competing with the synthetic ones developed from petrochemicals in building insulation. Moreover, returning these waste materials to circulation and producing new eco-friendly composites can reduce the number of landfills, the level of environmental pollution, and the use of synthetic materials made from fossil resources.

Forecasting Daily Air Quality Index and Early Warning System for Estimating Ambient Air Pollution on Road Networks Using Gaussian Dispersion Model with Deep Learning Algorithm

The rapid growth of the vehicle population is a major factor in heavy air pollution and public health issues. Traffic-related air pollutants (TRAPs) on roads are often much higher than ambient values, leading to high exposure levels in vehicles. This research proposes a hybrid forecasting model for early detection and early warning systems (EWS) of road networks during real-world travels. Data is collected from Kannur, Calicut, Palakkad, and Coimbatore using real-time sensors, including surrounding discussion information, activity information, vehicle speed, and stopping events. The study predicts ambient air quality (AAQ) levels on the road network using the Gaussian Dispersion model (GDM) and measures the risk sensitivity of PM10 and PM2.5 in selected regions. This helps formulate powerful prevention strategies and prevent negative health impacts. The air pollution module for predicting concentration has an innovative hybridization model that combines an improved cuckoo search (CS) and differential evolution (DE) algorithm with a stacked LSTM model to increase forecasting accuracy of six major environmental pollution levels. This model predicts the AAQ level and is effective and robust for warning one day before the pollutant event occurs based on the risk level of an ambient air pollutant from the RN.

Assessing avian incubation behavior in response to environmental pollution with temperature-humidity loggers

The negative impact of environmental pollution on avian physiology and breeding success is well documented. However, pollution-related behavioral changes during reproduction remain underexplored, despite behavior often being one of the earliest indicators of environmental disturbances and having significant life-history consequences. For example, altered food availability in a polluted environment could potentially perturb the incubation behavior of income breeders. These birds typically alternate between staying in the nest and heating eggs (on-bout) and taking foraging trips (off-bout). In this two-year study (2020 and 2022), we investigated how the incubation behavior of an insectivorous passerine, the pied flycatcher (Ficedula hypoleuca), varied with environmental pollution levels around a Cu-Ni smelter. Additionally, we compared two different metrics – temperature and humidity within the nest – to evaluate their use as indicators of incubation rhythm. We found that temperature- and humidity-based incubation rhythm parameters correlated, but those based on humidity matched better the true incubation behavior documented by simultaneous video recording. This was because the humidity curve showed a more immediate and intensive response to the female's incubation behavior. Birds in the polluted area took slightly more (11%) but shorter (11%) off-bouts, possibly reflecting smaller energetic constraints or better food availability in the polluted area. However, we found no difference in total incubation intensity between polluted and control areas, with F. hypoleuca females incubating their eggs 75% of the daytime in both environments. Hence, incubating females in the polluted area did not allocate more time for gathering their energy reserves than the birds in the control area, and there was also no difference in the hatching success. Our study is the first to use humidity variation to record incubation rhythm, and our results indicate that measuring humidity inside the nest is a promising technique to test and develop further. For example, further studies are needed to test if this method would work in different types of nests. From an environmental protection standpoint, our results also contribute valuable insights to the relatively limited information on pollution-related behavioral changes.

Impact of Policy Intensity on Carbon Emission Reductions: Based on the Perspective of China’s Low-Carbon Policy

Economic development often results in significant greenhouse gas emissions, contributing to global climate change, which demands immediate attention. Despite implementing various low-carbon policies to promote sustainable economic and environmental progress, current evaluations reveal limitations and deficiencies. Therefore, this study utilizes a dataset detailing policy intensity at a prefecture-level city in China to investigate the impacts of these policies on carbon emission reduction from 2007 to 2022 in 334 prefecture-level cities, employing a fixed-effects model. Additionally, it assesses the policies’ efficacy. The findings indicate a significant negative correlation between China’s low-carbon policies and carbon emissions, supported robustly by multiple tests. Specifically, a one-unit increase in China’s policy intensity correlates with a 0.53-unit reduction in carbon emissions. Furthermore, the heterogeneity analysis shows that variations in urban agglomerations, environmental resource endowments, pollution levels, and low-carbon policy intensities influence the effectiveness of these policies in reducing carbon emissions. This analysis underscores that policy intensity achieves emission reductions through technological innovation, industrial transformation, welfare crowding out, and pollution transfer, with varying impacts across different environmental contexts, pollution levels, and policy intensities. Based on this analysis, we recommend several policies: formulating low-carbon strategies tailored to local conditions, enhancing regional low-carbon policies, establishing cross-regional coordination mechanisms, and so on. These recommendations not only offer valuable policy insights for China but also serve as useful references for the green and sustainable development of other developing countries.

Response of bacterial and fungal communities in natural biofilms to bioavailable heavy metals in a mining-affected river

Biofilms, known as “microbial skin” in rivers, respond to rapid and sensitive environmental changes. However, the ecological response mechanisms of bacterial and fungal communities in river biofilms toward heavy metal pollution (HMP) remains poorly understood. This study focused on the key driving factors of bacterial and fungal community diversity and composition and their ecological response mechanisms within periphytic biofilms of Asia's largest Pb–Zn mining area. The diversity, dominant bacterial taxa, and bacteria structure in biofilms were influenced by biologically available heavy metal (HM) fractions, with Ni-F3 (17.96 %) and Pb-F4 (16.27 %) as the main factors affecting the bacterial community structure. Fungal community structure and α-diversity were more susceptible to physicochemical parameters (pH and nutrient elements). Partial least squares path modeling revealed that environmental factors influencing bacterial and fungal communities in biofilms were ranked as water quality > metal fractions > total metals. Dispersal limitation was the most critical ecological process in bacterial (56.9 %) and fungal (73.4 %) assembly. The proportion of heterogeneous selection by bacteria (39.5 %) was higher than that of fungus (26.2 %), which increased with increasing HMP. Bacterial communities had a higher migration rate (0.48) and ecological drift proportion (3.6 %), making them more prone to escape environmental stress. Fungal communities exhibited more keystone species, larger niche width (23.24 ± 13.04 vs. 9.72 ± 5.48), higher organization level, and a more stable co-occurrence network than bacterial communities, which enabled them to better adapt to high environmental pollution levels. These findings expanded the understanding of the spatiotemporal dynamics of microbial communities within biofilms in HM-polluted watersheds and provided new insights into the ecological responses of microbial communities to HMP.

Reduced copper uptake and efflux by the mussel Mytilus coruscus after Cu exposure: Implication for biomonitoring

The hard-shell mussels Mytilus coruscus have been extensively employed in pollution biomonitoring. Earlier studies indicated that metal concentrations in Mytilus coruscus may not accurately reflect the true metal contamination levels in the sampling areas, possibly due to their modified metal uptake and efflux. Given the likelihood of mussels in the field being exposed to intermittent metal contaminants, this study investigated whether different Cu pre-exposures significantly affected its uptake and efflux upon Cu exposure. We found significant reduction in Cu uptake rate constant (ku) and efflux rate constant (ke) in the mussels with varying Cu pre-exposure regimes. Specifically, the ku decreased from 1.55 ± 0.37 L g−1 d−1 in the control group to 0.65 ± 0.19 after 5 days and 0.53 ± 0.28 after 15 days of exposure to 20 μg L−1 Cu, respectively, and then was further reduced to as low as 0.096 ± 0.046 L g−1 d−1 following a 5-day exposure at 50 μg L−1 Cu. Similarly, the ke decreased from 0.18 ± 0.020 to 0.15 ± 0.015 d−1 following 5–15 days of exposure to 20 μg L−1 Cu, and further decreased to 0.081 ± 0.023 d−1 after a 5-day exposure at 50 μg L−1 Cu. Our subcellular distribution analysis underscored the critical role of the metallothionein-like protein (MTLP) fraction in modifying both Cu ku and ke during the rapid-depuration phase (ke1), whereas the metal-rich granule (MRG) fraction influenced the ke during the second depuration phase (ke2). This study demonstrated that environmental assessments utilizing biomonitoring species should consider the exposure of these organisms to ensure accurate interpretations of metal contamination in marine ecosystems and enhance the effectiveness of these species in environmental monitoring. This crucial factor is often overlooked, potentially skewing data and leading to misinterpretations of environmental health and pollution levels.

The trade of algae for human consumption: The common market competitiveness and impacts of the European Union legislation

The food chain has been confronting diverse limits and challenges. Indeed, the increase in level of environmental pollution, in resource scarcity, in biodiversity loss represents some limits, while guaranteeing the food security of a growing population and develop more sustainable production and consumption systems represents some challenges. In this context, including new foods within the European diet can be a sustainable strategy. With respect to the introduction of foods into the market that do not boast a history of safe consumption within the European Union has prompted regulatory interventions that have aimed to control the level of risk assessment of new products before granting permission for their marketing. This paper aimed in glimpsing the potential effect of this legislation on the trade flow of algae as a novel food, and in assessing the level of self-sufficiency and the comparative advantage of European Union countries. For this purpose, the calculation of specific indices allowed the track of the evolutionary trend of algae for human consumption trade flows, referred to the intra and extra European Union countries. Conclusively, the paper presents an interpretation of the relative trade structure, trade pattern and agri-food competitiveness referred to algae for human consumption while underling the limitation but also the benefit of the legislation intervention in this sector.

Pollutants-mediated viral hepatitis in different types: assessment of different algorithms and time series models

The escalating frequency of environmental pollution incidents has raised significant concerns regarding the potential health impacts of pollutant fluctuations. Consequently, a comprehensive study on the role of pollutants in the prevalence of viral hepatitis is indispensable for the advancement of innovative prevention strategies. Monthly incidence rates of viral hepatitis from 2005 to 2020 were sourced from the Chinese Center for Disease Control and Prevention Infectious Disease Surveillance Information System. Pollution data spanning 2014–2020 were obtained from the National Oceanic and Atmospheric Administration (NOAA), encompassing pollutants such as CO, NO2, and O3. Time series analysis models, including seasonal auto-regressive integrated moving average (SARIMA), Holt-Winters model, and Generalized Additive Model (GAM), were employed to explore prediction and synergistic effects related to viral hepatitis. Spearman correlation analysis was utilized to identify pollutants suitable for inclusion in these models. Concurrently, machine learning (ML) algorithms were leveraged to refine the prediction of environmental pollutant levels. Finally, a weighted quantile sum (WQS) regression framework was developed to evaluate the singular and combined impacts of pollutants on viral hepatitis cases across different demographics, age groups, and environmental strata. The incidence of viral hepatitis in Beijing exhibited a declining trend, primarily characterized by HBV and HCV types. In predicting hepatitis prevalence trends, the Holt-Winters additive seasonal model outperformed the SARIMA multiplicative model ((1,1,0) (2,1,0) [12]). In the prediction of environmental pollutants, the SVM model demonstrated superior performance over the GPR model, particularly with Polynomial and Besseldot kernel functions. The combined pollutant risk effect on viral hepatitis was quantified as βWQS (95% CI) = 0.066 (0.018, 0.114). Among different groups, PM2.5 emerged as the most sensitive risk factor, notably impacting patients with HCV and HEV, as well as individuals aged 35–64. CO predominantly affected HAV patients, showing a risk effect of βWQS (95% CI) = − 0.0355 (− 0.0695, − 0.0016). Lower levels of PM2.5 and PM10 were associated with heightened risk of viral hepatitis incidence with a lag of five months, whereas elevated levels of PM2.5 (100–120 μg/m3) and CO correlated with increased hepatitis incidence risk with a lag of six months. The Holt-Winters model outperformed the SARIMA model in predicting the incidence of viral hepatitis. Among machine learning algorithms, SVM and GPR models demonstrated superior performance for analyzing pollutant data. Patients infected with HAV and HEV were primarily influenced by PM10 and CO, whereas SO2 and PM2.5 significantly impacted others. Individuals aged 35–64 years appeared particularly susceptible to these pollutants. Mixed pollutant exposures were found to affect the development of viral hepatitis with a notable lag of 5–6 months. These findings underscore the importance of long-term monitoring of pollutants in relation to viral hepatitis incidence.

Recent advances in portable devices for environmental monitoring applications.

Environmental pollution remains a major societal problem, leading to serious impacts on living organisms including humans. Human activities such as civilization, urbanization, and industrialization are major causes of pollution. Imposing stricter rules helps control environmental pollutant levels, creating a need for reliable pollutant monitoring in air, water, and soil. The application of traditional analytical techniques is limited in low-resource areas because they are sophisticated, expensive, and bulky. With the development of biosensors and microfluidics technology, environmental monitoring has significantly improved the analysis time, low cost, portability, and ease of use. This review discusses the fundamentals of portable devices, including microfluidics and biosensors, for environmental control. Recently, publications reviewing microfluidics and biosensor device applications have increased more than tenfold, showing the potential of emerging novel approaches for environmental monitoring. Strategies for enzyme-, immunoassay-, and molecular-based analyte sensing are discussed based on their mechanisms and applications. Microfluidic and biosensor platforms for detecting major pollutants, including metal ions, pathogens, pesticides, and antibiotic residues, are reviewed based on their working principles, advantages, and disadvantages. Challenges and future trends for the device design and fabrication process to improve performance are discussed. Miniaturization, low cost, selectivity, sensitivity, high automation, and savings in samples and reagents make the devices ideal alternatives for in-field detection, especially in low-resource areas. However, their operation with complicated environmental samples requires further research to improve the specificity and sensitivity. Although there is a wide range of devices available for environmental applications, their implementation in real-world situations is limited. This study provides insights into existing issues that can be used as references and a comparative analysis for future studies and applications.

Effect of Different Parameters on Enzymatic Hydrolysis of Hazelnut Shells

In the last few decades, the increasing levels of environmental pollution have prompted a shift towards alternative energy sources and biobased solutions, such as lignocellulosic biomass. Lignocellulosic biomass (LB) is primarily derived from plants and is composed mainly of polysaccharides, namely cellulose, hemicellulose, and the aromatic polymer lignin. Hazelnut shells (HS), with a high lignin content of 43%, hemicellulose of 30%, and cellulose of 26%, hold promise as a valuable source of LB. In order to process those LB, lignin and hemicellulose are separated using various treatment methods. However, instead of being used solely for combustion, lignin-containing materials can be valorized for a range of purposes, from biomedical applications to the energy sector. In this study, the enzymatic hydrolysis of HS was conducted over different time periods (24, 48, 72, and 96 hours), at different temperature values with varying enzyme concentrations (0.05, 0.1, and 0.25 mL of cellulase/xylanase enzyme cocktail). To enhance the enzymatic hydrolysis, an alkaline pretreatment method using sodium hydroxide (NaOH) was employed. The results demonstrate that the maximum sugar concentration was achieved at 50°C, after 72 hours, and with a cellulase/xylanase cocktail concentration of 0.1 mL.

Modeling 2,4-dichlorophenoxyacetic acid adsorption on candle bush pod-derived activated carbon: Insights from advanced statistical physics models

The widespread usage of 2,4-Dichlorophenoxyacetic acid (2,4-D) as an herbicide has led to alarming levels of environmental pollution, presenting severe risks to ecosystems and human health. This study aimed to synthesize a new adsorbent, activated carbon from candle bush pods (CBAC) via low-temperature phosphoric acid activation and investigate its ability for adsorptive elimination of 2,4-D. The setup of a new adsorption system requires the experimental determination of adsorption isotherms and their thorough modeling, which is achieved through advanced statistical physics models (ASPMs). The characterization of CBAC revealed a porous morphology with a remarkable specific surface area (415.31 m2/g). XRD revealed graphitic carbon structures, while XPS detected phosphate groups, graphitic structures, and oxygen-containing functional groups. Double layer with single energy (DLSE) model – one of the ASPMs revealed both non-parallel and parallel orientation of 2,4-D molecules on CBAC, with saturation adsorption capacity values increasing with temperature (up to 252.35 mg/g) at pH 2. The adsorption was physisorption (ΔE = 12.62–16.26 kJ/mol) and spontaneous and endothermic. Hence, the findings herein demonstrate the potential of CBAC as a sustainable and effective adsorbent for mitigating environmental pollution caused by 2,4-D.

The impact of renewable energy policies on the energy transition -– An empirical analysis of Chinese cities

Amidst the intensifying global energy crisis, the advancement of renewable energy stands as a critical element in China's strategy for energy transition (ET) and efforts to mitigate climate change. This paper aims to offer fresh insights into the determinants of ET from the renewable energy policy (REP) perspective. By employing panel data from 280 Chinese cities covering the period from 2003 to 2019, and applying the text-mining methodology, this analysis initially explores the impact of REP on the ET. Our empirical findings demonstrate that REP significantly promotes ET, with our proposed hypotheses successfully enduring a series of robustness tests. This acceleration is predominantly through two mechanisms: the stimulation of green technology innovation and the enhancement of ET readiness. However, the influence of energy system performance on this transition is insignificant. This investigation reveals a pronounced regional heterogeneity in the effects that REP on ET. Specifically, the positive impact of these policies is stronger in the eastern cities of China, also in small and medium-sized cities, and cities with high levels of economic development, human capital, finance development, lower environmental pollution levels, and old industry areas. These findings provide valuable references for China and other countries pursuing similar objectives.

Unveiling the Dynamics and Sustainability of the Nubian Aquifer System in El-Marashda, Egypt Through Geophysical, and Hydrogeochemical Investigations

AbstractThis research investigates the geophysical, hydrogeochemical, and geological characteristics of the Nubian Aquifer System in the El-Marashda area, located beneath the Eastern Sahara Desert in northeastern Africa. The primary objective is identifying the aquifer geometry, assessing groundwater quality, and evaluating environmental pollution levels. A Magnetotelluric survey was employed to examine the subsurface geological composition and electrical resistivity characteristics of the aquifer system. The study revealed a freshwater-saturated Nubian Sandstone layer at depths between 986 and 1009 m with resistivity values of 101 to 182 Ohm.m, indicating a substantial and potentially sustainable groundwater resource. Overlying limestone and Marly Limestone layers influence the aquifer’s permeability and storage capacity. The chemical analysis of water from three wells showed suitability for drinking and irrigation, with no sodium and magnesium levels hazards. The Heavy Metal Pollution Index (HPI) and Heavy Metal Evaluation Index (HEI) indicated low to medium contamination, posing potential environmental health risks. Human health risk assessments using USEPA methodology found acceptable non-carcinogenic risks, with Hazard Quotients (HQs) for heavy metals below 1 and a negligible Hazard Index (HI). The comprehensive investigation underscores the potential for sustainable groundwater utilization in El-Marashda. It highlights the aquifer’s suitability for irrigation, with low contamination levels and minimal health risks. These findings provide a foundation for informed and sustainable water resource management, environmental protection, and resilient infrastructure development in the region. The methodologies and results align with global standards, demonstrating their applicability in globally diverse geological contexts. This research contributes valuable baseline data for future studies and monitoring efforts, whether at local or global sites, emphasizing the importance of continued investigation to ensure sustainable groundwater management.

The impact of buying external technology on employment and air quality: an empirical approach in Vietnamese manufacturing SMEs

Purpose The purpose of this paper is to evaluate the current situation of buying external technology in Vietnamese manufacturing small and medium enterprises (SMEs) from 2013 to 2018. This paper also aims to examine the effect of buying technology on employment and environmental quality in Vietnam. Design/methodology/approach External technology purchase and its impact on employment and environmental quality are taken from the Vietnam annual enterprise survey and the using technology in production survey from 2013 to 2018. The estimation is based on a feasible generalized least squares method. Findings This study finds that external technology purchase in manufacturing SMEs increases the employment rate in the industries. External technology purchase in Vietnamese manufacturing SMEs also increases the level of environmental pollution. This is a negative side of purchasing technology for production because if the technology used is old, outdated and of poor quality, it will increase environmental pollution. In addition, the growth in employment increases air pollution. This shows that purchasing advanced technology selectively helps to increase the employment rate in Vietnamese manufacturing sector, which is followed by a positive impact on environmental quality. Research limitations/implications The limitation of this study is that the research period was only investigated from 2013 to 2018 because the General Statistics Office of Vietnam no longer surveys the dataset about using technology in production surveys after 2018. This study has been conducted at the firm level, so results cannot be easily extended to the macroeconomic level, also taking into account the data limitations in terms of sector coverage. Practical implications This paper provides necessary policy recommendations for the government and manufacturing SMEs to solve negative technology issues related to the labour market and air quality in Vietnam. The results are expected to help policymakers in Vietnam propose appropriate national science and technology programmes towards sustainable development in the coming decades. Originality/value This paper focuses on assessing the effects of buying external technology by Vietnamese small and medium-sized manufacturing enterprises on employment and air quality.

INTENSITY OF GREENHOUSE GAS FORMATION DUE TO LIVESTOCK FARMING ACTIVITIES – AS AN ENVIRONMENTAL FACTOR

According to numerous expert assessments by international organizations and specialists, animal husbandry makes a significant negative contribution to global climate change due to the emission of greenhouse gases (GHG), which are formed at different stages of livestock production as a result of various chemical and biological processes in the body of animals and in livestock waste. The domestic animal husbandry is developing mainly due to the intensification of production in the industry, but traditional farming methods as well as small-scale production in the individual sector also take place. Since the use of various technologies in animal husbandry has different effects on the level of environmental pollution and GHG emissions, the aim of the research was to study the differences in the intensity of GHG gas formation by one animal reared with individual features of animal rearing technologies and business activities. The intensity of gas formation and emission of CH4 and N2O in typical farms for pork production and milk production by one animal reared was determined, analyzed and substantiated. A significant variation in this indicator was found depending on the individual economic and technological features of the studied farms. The average weighted annual intensity of CH4 emission from animal manure in pig farms varied within the range of 0.95–25.71, in cattle farm – 2.74; CH4 from intestinal fermentation of dairy cows – 110.8–148.4; N2O (direct) in pig farms – 0.0–0.106, in cattle farm – 0.229; N2O (indirect) in pig farms – 0.071–0.097, in cattle farm – 0.174. The emission intensity is characterized separately in each age and sex group of animals in the herd structure of farms and the average weighted emission intensity in pork producing farms depending on the season. Based on the research results, it is proposed to use the generalized average annual indicator of greenhouse gas emissions per one average weighted animal reared (kg/head/year) as an indicator of the environmental load of livestock farms on the environment, which will allow planning production volumes with minimal environmental risks in the context of climate change.

Heavy Metal Pollutants Or Contaminant In Soil Samples Obtained From Wash Boreholes Within Pantisawa, Yorro L.G.A. Of Taraba State

The problem of environmental pollution and its compartments due to an increase in contamination as a result of the accumulation of heavy metals and microorganisms from soil has raised wide-spread of concerns in different parts of the nations and this has compromised the ability of the environments to foster life and render them an intrinsic value. Hence the study aimed to ascertain the level of environmental pollution in soil from wash borehole within Pantisawa Yorro Local Government Area of Taraba State, Nigeria. A total of 45 samples for soil were collected aseptically from the five different zones (Pantisawa Main Market YM, Kapazang YG, Dola YD, Kallau YK and Zabi YZ) of Pantisawa. The levels of trace metals in soil samples were determined using Atomic Absorption Spectroscopy (AAS) PG-990. The results were analyzed using SPSS Version 20. The soil samples result for these metals revealed that iron concentration was between 3000-4010mg/kg most especially for site SD which is higher than all other elements analyzed. Zinc ranges from 2.54-6800mg/kg which is above the standard as prescribed by WHO and FEPA in soil and also exceeded the dutch target values of (Zn: 50mg/kg and Cu: 30mg/kg) in some of the sampling sites. Nickel was between 8.47-19.09 mg/kg in soil samples, this is below the toxicity threshold limit of 35mg/kg for safe environment as stated by WHO. Arsenic ranges from 53.06mg/kg–141mg/kg, which is higher than the admissible limit of 50mg/kg in soil recommended by UNEP. The order of all the metal concentration in the areas was Fe>Zn>Mn>As>Pb>Cu>Mn>Co and Cd respectively. Based on this study, the high concentration of the metals such as Zn, As, Cd, Pb, and Co in some of these sites most especially SK, SM and SD within Pantisawa revealed that some of the soil samples collected from these areas were contaminated with heavy metal pollutants which may have serious health risk to the people using it for various activities. The higher concentrations of these toxic metals in soils need to be monitored regularly for heavy metal enrichment.

A systematic analysis of European markers of balanced environmental management under the conditions of economic circularity

The main task of the article is to research the role of balanced environmental management in the construction of a circular model of the European countries’ economy by using environmental and economic markers. It determines the level of environmental pollution and other environmental problems, including those caused by resource waste. It proposes a technological method of wastewater treatment from estrogen, microplastic particles and oil by using iron oxide. The rate of population for which secondary wastewater treatment is available and its importance for water efficiency under the conditions of significant water crisis in Europe was determined. The paper identifies the main indicators of economic losses of European countries that depend on climate change, because the weather anomalies have a significant impact on economic processes. It studies the dynamics of changes in the area of forested land according to FAO of the European G7 members, the current potential of forest resources of Ukraine and identifies the necessity of systematic electronic wood accounting. It is established that in the EU countries the practice of returning many types of raw materials to production after waste processing has long been accepted, and the need for the fastest possible introduction of innovative processing technologies is identified. Mathematical formulas for calculating the coefficient of cyclicality, circular use of materials and establishes the level of using cyclical materials by European manufacturers are derived. It is established that to identify the efficiency and dynamism of waste transformation, it is appropriate to use an indicator that measures the fraction of recycled household waste in the total volume of its generation. The article establishes the share of fossil fuels in the total available energy of European countries and analyses the dynamics of primary energy consumption based on the example of the Scandinavian countries. It identifies the level of revenues from environmental taxes in most European countries and their importance for the circular economy. It is recommended for Ukraine to study and use the experience of the European Union countries for construction its own model of circular economy based on the principles of balanced nature management and sustainable development.

Enhanced electrochemical oxidation and machine learning-assisted sensing of tetrabromobisphenol A using activated carbon facilitated CoWO4 heterostructures

The escalating levels of environmental pollution, particularly from commercially used products, highlight the imperative of efficient sensor technologies to facilitate timely and effective remediation strategies. Herein, a simple method is proposed to enhance the electrochemical performance of CoWO4 structures by coupling them with activated carbon (AC) for direct tetrabromobisphenol A (TBPA) oxidation. The systematic comparison shows that incorporation of AC with CoWO4 not only improves the overall effective surface area (ESA) of the catalyst by 1.8-fold but also improves the cyclic voltammetry (CV) based irreversible oxidation current by 2.0-fold owing to improved conductivity and surface characteristics. Differential pulse voltammetry (DPV) based optimization of the sensory characteristics confirmed robust electrocatalytic TBPA oxidation within a 0.1 to 1.0 µM concentration range, achieving a 0.024 µM detection limit within PBS (0.1 M) (pH 5.0). Moreover, density functional theory (DFT) analysis confirms the non-covalent interaction favorability between TBPA and CoWO4 surface, validating TBPA’s easy adsorption onto the catalytic surface and, thus, facilitated electron mobility between the molecule and the catalyst during the surface oxidation process. The DPV sensing interpreted using machine learning (ML) algorithms confirmed the detection accuracy of the developed sensor. Among the adopted models, artificial neural networks (ANN) achieved the highest R2 score (0.9659) and the lowest values across Mean Squared Error (MSE), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE) error matrices confirming its suitability in deciphering DPV correlations.Integrating ANN with DPV based electrocatalytic oxidation sensing underscores machine learning’s potential in analyzing complex electrochemical signatures, thus advancing intelligent sensing for precise environmental monitoring.