International Journal of Environmental Science and Technology最新文献

Five different soil compositions were prepared, each with varying montmorillonite (Mt) content of 2%, 5%, 10%, 15%, and 20% in a simulated column and irrigated with TC contaminated solution. The transfer kinetics of TC in different soil compositions were found to be primarily influenced by the Mt content. Increasing the Mt percentage resulted in a reduction in transfer kinetics. Furthermore, as the percentage of Mt increased, so did the amount of absorption and the holdup capacity of the soil. Conversely, when it came to release kinetics, an increase in Mt content significantly reduced the amount of TC released from the contaminated soil. In an optimal scenario with 15% Mt content, approximately 10% of absorbed TC was desorbed into the environment while 90% remained absorbed within the soil structure. In contrast, in samples with 0% Mt present, 95% of absorbed IC was desorbed and less than 5% remained. The adsorption process primarily occurred within the interlayer spaces of Mt, indicating strong adsorption capabilities for TC within the soil and a reduced likelihood for release. The FTIR results corroborated the previous findings by demonstrating the emergence or alteration of distinct peaks associated with the bonds of TC functional groups following adsorption and desorption on the examined soil. Consequently, these findings have potential applications across various scientific disciplines, enabling the mitigation of antibiotic transfer kinetics and enhancing soil's capacity to retain antibiotics, thereby addressing the issue of antibiotic-contaminated water bodies.

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The escalating use of agrochemicals in agriculture presents significant challenges to human health, the environment, and agricultural workers. In response, the United Nations' Sustainable Development Goal 2 encourages sustainable farming approaches, like the adoption of eco-friendly farming methods and innovations for localized weed control. Remotely piloted aircraft fitted with imaging sensors have emerged as a viable option for specific weed control. However, addressing technological challenges is necessary to enable widespread adoption. This study aims to evaluate the efficiency of an identification algorithm designed to generate maps for targeted pesticide application. Georeferenced images were acquired through remotely piloted aircraft flights conducted over commercial soybean and second-crop corn areas. Post-processed kinematic corrections of Global Navigation Satellite System coordinates achieved centimeter-level image accuracy. Orthomosaics generated from processed images provided the data for the analyzed algorithm, which produced localized application maps. Field validation data were gathered to create a ground truth map, and the weed identification performed by the algorithm was evaluated using the two-classes confusion matrix method. The performance indicators demonstrated average results of 0.78 for precision, 0.95 for recall, 0.77 for accuracy, 0.80 for F-score, and 0.56 for the Pearson’s correlation. These values reveal the algorithm's proficient identification of weeds with surface areas exceeding 400 cm². Utilizing artificial intelligence techniques for aerial images categorization offers a viable strategy for weed recognition and location-specific pesticide application. Nonetheless, further refinement is required to improve the algorithm's exactness and consistency, particularly to recognize weeds smaller than 400 cm².

Genetic Algorithm (GA) and Particle Swarm Optimization Algorithm (PSOA) have positive effects on the allocation and scheduling of the stations, this research seeks to find which one of these two methods is more appropriate to shorten the time to reach fire/incident site in the Region 19 of Tehran. This is an applied type of research. Data analysis was carried out using NFPA standards and MATLAB software. The statistical population includes 8 fire stations and 250 personnel of the stations, and sampling volume was obtained using Morgan’s table (n = 148). In order to efficiently assign and schedule fire stations to arrive at the site, a linear numerical programming model was presented with the aim of minimizing the arrival time and taking into account the effect of firemen's fatigue (α = 0.1). Findings of the research showed that the operation processing time (of fire extinguishing) had a normal distribution with a mean of 40 min and a variance of 10 min, independent of the severity of the incident. Also, fatigue coefficient was calculated 0.1 by analyzing the sensitivity of the solution time of the algorithm with changes [0–1]. Initial standard travel time, with an average speed of 47 km/h and a density factor of 1.24, was 5_min:20_s. Solving the problem in large and small dimensions showed that the initial power effect of each fire station is 0.36 according to the fatigue level of the forces. Based on the obtained results, GA performs better in terms of problem solution time, and the improved PSOA also has higher quality answers.

Polyhydroxyalkanoates (PHAs) are biodegradable polymer biosynthesized via bacterial fermentation of sugars and fatty acids. PHA are considered a promising material to aid in mitigating plastic pollution due to their biodegradability. However, major bottleneck in the commercial feasibility of PHA production is the cost of PHA which remains a distinct challenge in the upscale production substituting the petroleum-based synthetic plastics for wider usage. The discharge of wastes and by-products of agricultural and industrial origins has created severe environmental pollution. Hence, waste utilization as carbon sources in the production of polyhydroxyalkanoates (PHA) would reduce the production costs, lessen waste and reduce pollution. This review provides an overview of utilisation of wastes and by-products for PHA production and the possibility of large-scale production. Potential drawbacks and opportunities are discussed in this review in integrating the sustainable production of PHAs into the global circular economy. This can pave the way in embracing low carbon bioeconomy.

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In recent decades, active measures have begun to be taken to solve global problem due to the increase in the concentration of carbon dioxide in the atmosphere. The article presents a review of the literature over the past 30 years. It focuses on changes in natural and anthropogenic CO₂ emissions over time. Forest fires are also included in a separate group. Annual natural CO₂ emissions 550–848 billion tons (from 1990 to 2022). The main natural sources are the respiration of living organisms; soil respiration; processes occurring in the oceans; volcanic eruptions and the formation of minerals. The released carbon dioxide is absorbed by the oceans and photosynthesis of plants. The literature data confirm the fact that there is an imbalance in the natural cycle of carbon dioxide in relation to its emissions. One of the main factors influencing this is anthropogenic emissions. Their share increased from 2.9 to 5.3% of total carbon dioxide emissions between 1990 and 2022 (from 25 to 41 billion t/year). The main contribution to emissions is made by burning fossil fuels, agriculture, cement and concrete production, and deforestation. Up to 50% of anthropogenic gas is absorbed by natural ecosystems and involved in the carbonation of cement. The rest of the gas is trapped in the atmosphere. This led to a large accumulation of CO₂ in the atmosphere over several decades. The carbon dioxide content increased by 20% (from 1990 to 2022). The share of total carbon dioxide emissions from forest fires is 0.9–1.3%.

Inorganic arsenic has toxicity to animals, plants, and humans, which is often detected over environmental limits. The development of fast, accurate, and convenient methods for its detection is therefore of utmost importance. Biosensors based on nanomaterials have emerged as a promising tool for the detection of inorganic arsenic due to their high sensitivity, selectivity, and portability. This review covers the current progress in the development of biosensors based on nanomaterials for the detection of inorganic arsenic. According to different transducers, various biosensors (e.g., electrochemical biosensors, fluorescent biosensors, and colorimetric biosensors) are summarized in the aspect of their construction, mechanism, nanomaterials modification, and applications. The combination of biosensors and microfluidics for the detection of inorganic arsenic was analyzed. Moreover, the underlying problems and outlook are proposed to further advance the development of biosensors for the detection of inorganic arsenic. In summary, this review provides valuable insights into the design and development of novel biosensors for the detection of inorganic arsenic, which can contribute to the protection of the environment and human health.

Soil and groundwater contaminated with petroleum hydrocarbons poses an ever increasing and serious danger to human life. Due to their toxicity, environmental cleaning from petroleum products is necessary. Among the various methods for soil remediation, the electrokinetic approach has more applicability due to its high speed and low cost. The purpose of this research is to assess the effectiveness of the electrokinetic method for removing diesel-contaminated soil while incorporating the surfactants Triton X100 and Tween 80. Moreover, the impact of regulating pH control in catholyte and anolyte and different concentrations of surfactants on the process of modifying soil through electrokinetics has been studied. It is observed that without the presence of a surfactant, the electrokinetic technique exhibits minimal effectiveness in cleaning diesel from the soil, while in the presence of a surfactant, the removal efficiency increases significantly and therefore this method is effective in reducing soil pollution. Also, by controlling the pH in the catholyte and anolyte and increasing the concentration of surfactant, the removal efficiency of diesel from soil increases. Tween 80 indicated higher removal deficiencies with the ability to eliminate approximately 39% of diesel at the 0.15% intensity of surfactant after 10 days experiment. The uniaxial testing was carried out to distinguish the geotechnical properties of the dust, such as the cohesive strength of the soil sample under axial compression without any external confining pressure. It showed that the cleaning procedure improved the compacted stability of the soil and soil resistance parameters about 12 percent.

Mining for base metals and some critical raw materials is associated with acid, sulphate, and metal-rich waters (AMD). At the points where these waters are accumulated or discharged, the secondary minerals are precipitated, mostly iron-oxyhydroxides, forming characteristic orange sediments toxic to the environment. The sediment or sludge is prone to leaching of metals and sulphate, thus requiring proper disposal to maintain the waste stability. In this study, we assessed the AMD lake “Robule” sediment electrochemical properties and associated mineralogy in sediment microbial fuel cell (SMFC). The SEM–EDS and XRPD analysis revealed schwertmannite, jarosite, goethite and gypsum as the most abundant mineral forms with efflorescent sulphates salts precipitated on top of the air-open cathode. In the acid lake mine water dominant aquatic species are SO₄²⁻, Mg²⁺, AlSO₄⁺, and Fe³⁺ iron mostly as various sulphate complexes. Although oxidized forms prevail in the lake water and sediment, the possibility of generating electrical current is, to our knowledge, for the first time registered for this type of mining waste. A closed-circuit voltage of 439 ± 60 mV (at 220 Ω external resistance), an average current density of 210 ± 28.6 mA/m² and a maximal power density of 29 mW/m² was measured. The absence of sulphide minerals suggests that the biological oxidation of organic molecules at the anode and the iron cycle drives electricity production. The stability of the SMFC environment and the absence of hydrogen sulphide build-up while generating electrical current opens new directions for sustainable management of AMD and the associated sediment.

The objective of this research was to detect the presence of heavy metals (HMs) in soils polluted with sludge from an industrial wastewater treatment plant and then use Eisenia fetida earthworms to reduce the contamination levels in the soil. The sludge was added to the soil at varying rates of 0, 10, 20, 30, 40, and 50 ton/ha. To examine the impact of organic amendment, 12 Eisenia fetida earthworms were added to all samples for every 500 g of the contaminated soil. After 42 days, the overall concentration and categorization of HMs in the soil, along with the changes in weight and mortality of the earthworms, were determined. The addition of sludge to the soil resulted in an elevation of HM levels, including copper (Cu), zinc (Zn), lead (Pb), nickel (Ni), and cadmium (Cd). Notably, with the exception of Cd, the concentration of HMs decreased after the 42-day period following the introduction of earthworms. The highest absorption of metals by the earthworms occurred when 20 ton/ha of sludge was applied. This suggests that the earthworm species Eisenia fetida possesses the capability to bioaccumulate Zn and Cd, as indicated by a bioaccumulation factor exceeding 1 for these metals. In conclusion, the utilization of earthworms in this study not only resulted in the storage of HMs within the worms’ bodies but also contributed to the improvement of the physicochemical properties of the soil.

In this study, the concentrations of 9 elements (Al, As, Cd, Cr, Fe, Mn, Ni, Se and Zn) in the muscle tissue of 10 different fish species consisting of sea and freshwater fish of certain origin in local markets and the fish market in Konya were determined. According to the findings of the study, the highest mean concentrations of Al, Fe and Cr were found in Flathead grey mullet, As and Se in Gilthead seabream, Mn and Zn in European pilchard, Cd and Ni in Mediterranean horse mackerel. The estimated daily intake, target hazard quotient (THQ), hazard index (HI) and cancer risk (CR) risk values for inorganic arsenic were determined using human health risk assessment methods based on metal levels in muscle tissue of fish. THQ and HI results revealed that non-carcinogenic health effects from the intake of individual or combined metals in fish species are not expected for consumers. This situation indicates that there are no non-cancer health risks. However, consumption of red mullet and European anchovy fish exposes individuals to inorganic arsenic, increasing the risk of cancer as their CR values were found not to be in acceptable ranges. The results were compared with limit values specified in national and international quality criteria. Only the average Cd concentrations in Carp, European barracuda and Mediterranean horse mackerel were found above the limit values of MHPRC (MHPRC (2013) National food safety standard, maximum levels of contaminants in foods), TFC (2011) and EC (Commission regulation no. 1881/2006 of 19 December 2006 setting maximum levels for certain contaminants in foodstuffs. Official Journal of European Union, 20.12.2006).