Environmental Monitoring and Assessment

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Localization of the sampling points in Gorce Mountains, south Poland. Sampling points from the windward side are marked as red squares, and samples points on the leeward side are marked as blue circles. A more detailed part of the map on a larger scale of the area with compacted measuring points is added in the supporting material as Fig. S1.
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The dependences of metal concentration in Gorce soils on the altitude and wind exposition of the slope (red squares – windward, blue circles – leeward). A Cd, B Pb, C Zn. The equations of regression are as follows: cadmium—windward side: y =  −0.0003x + 1.0592, leeward side: y =  −0.0003x + 0.522; lead—windward side: y = 0.0551x + 4.524, leeward side: y = 0.0399x −5.6277; zinc—windward side: y = 0.0129x + 87.529, leeward side: y =  −0.0123x + 67.977
3D chart depicting the dependences between contents of Zn, Pb, and Cd in the soils studied (red balls). Diamonds, triangles, and squares are the projections of the chart on individual 2D planes, showing the relationships between particular two parameters: Cd/Pb (diamonds), Zn/Pb (squares), and Cd/Zn (triangles). The calculated Spearman correlation factors are as follows: Cd/Pb 0.45, Pb/Zn 0.52, Cd/Zn 0.82
The average relative content of zinc, lead, and cadmium in the soils studied, with the divisions on windward and leeward side and in four metal forms gained with the BCR extraction method. FM1, water and light acids soluble part; FM2, the form bound to iron and manganese oxides/hydroxides; FM3, the form bound to organic matter; FM4, the residual part of metal, entrapped within the crystal structure of minerals
  • Paweł MiśkowiecPaweł Miśkowiec
The main objective of this study was to determine the content, mobility, and the variability of concentration of zinc, lead, and cadmium in soils from the Gorce Mountains (south Poland), located over 100 km south-east from the potential industrial sources of contamination—zinc-lead sulfide ore mine and smelter in Bukowno, as well as hard coal mines of Silesia region and Kraków Nowa-Huta steelwork. The abovementioned problem is crucial in the context of the traditional mountain farming still extant in the region, as well as intensively developing tourism. The geoaccumulation index and potential ecological risk index were adopted to evaluate soil pollution in the study area and the BCR sequential extraction technique to assess mobility of the abovementioned elements. The obtained results clearly show that the pollution from distant industrial sources in the mountains is detectable. Apart from the increased concentrations of the tested metals in the soil (especially available forms), there is also a strong correlation between the concentrations of lead, zinc, and cadmium, which proves their common source of origin. The main evidence is the fact that differences in the concentrations of the tested metals on the windward and leeward sides were statistically significant. This also means that the studied mountain area, despite relatively low altitudes (up to 1310 m above sea level), constitutes a measurable barrier to the spread of atmospheric pollutants.
Study area
The function image of Si = f (Di, Pi)
  • Luo XiLuo Xi
  • Zeng QinZeng Qin
  • Yan FengYan Feng
Entropy weight model (EWM) is widely used in water quality evaluation. In the conventional EWM, the weight is a monotone increasing function of the dispersion degree. However, this weighting principle often neglects the heavily polluted indicators. To solve this problem, an improved EWM is designed, in which the weight of the indicator is a compound function of its dispersion degree and pollution degree. In the clean domain, the weight increases with the dispersion degree, while in the polluted domain, the weight decreases with the dispersion degree. And for the same dispersion degree, the larger the pollution degree is, the higher the weight is, and vice versa. Subsequently, the improved EWM is applied to the water quality evaluation of Wucheng Wetland in Poyang Lake, China. Results are as follows: (i) For TP, CODMn, and NH3-N, their dispersion degrees are 0.001, 0.158, and 0.084; and their pollution degrees are 0.971, 0.277, and 0.281, respectively. (ii) According to the improved EWM, the weights of TP, CODMn, and NH3-N are 0.613, 0.197, and 0.190, respectively. (iii) The comprehensive water quality indices of estuary region, wetland region, and the central lake area are 32.5, 30.9, and 35.6, respectively, all of which belong to a “bad” grade. The water environment of Wucheng Wetland suffered serious damage of phosphorus, and the ecosystem faced a high threat. (iv) Compared with the conventional EWM, the improved EWM highlights the importance of polluted indicators, which makes the comprehensive evaluation results more rigorous and reasonable.
Triangular fuzzy number (TFN)
Fuzzy ratings and their membership function
Flow order of the fuzzy DEMATEL approach (Başhan & Demirel, 2019)
Schematic diagram of experimental BMP analysis
The cause-effect relation diagram of BMP parameters
As the transition to renewable energy systems is accelerating, anaerobic digestion, which is one of the methods of energy recovery from organic substrates, continues to be studied with great interest by scientists. Anaerobic digestion research and applications are mostly carried out with biochemical methane potential (BMP) tests to decide the methane potency of sewage sludge, energy crops, and organic wastes. Unlike long and costly continually reactor experiments, actually, BMP tests are cumulative and can be performed with a relatively low investment of materials, technical labor, and also time. For the BMP to give accurate results, the effect of all the tools and technical parameters used in the implementation of the BMP should be well understood. In such situations, it is very useful to apply fuzzy logic methods in multi-criteria decision-making stages when more than one parameter changes at the same time. Therefore, in this study, fifteen parameters were determined and analyzed with the fuzzy DEMATEL (decision-making trial and evaluation laboratory) method to understand the cause-effect mechanism of the technical parameters of BMP. As a result of these analyses, it was seen that the material of the reactor (ri-cj value of 0.55), the particle size (ri-cj value of 0.43), the effect of mixing (ri-cj value of 0.32), and the amount of the total solids (TSA) (ri-cj value of 0.25) had a high effect in the causal sense. It was observed that the first-order parameter (material of reactor) was 27% stronger than the second-order (the particle size) parameter in terms of causality. Likewise, the second-order parameter is 34% stronger than the third-order parameter (the effect of mixing) in terms of cause effect. In addition, it was understood that the most effective parameters in the mechanism of effect were pH (ri + cj value of 3.41), C/N ratio (ri + cj value of 3.26), and temperature (ri + cj value of 3.07), respectively. Besides, high methane yield is seen in mesophilic conditions. The average cumulative biogas yield of the reactor is 282.1 NmL/g VS. The highest percentage of methane formed in the biogas occurred on the 21st day. Briefly, this study is important to provide a facilitating way for researchers working on BMP to understand the cause-effect mechanism of system technical requirements. Graphical abstract
High sediment flux in large rivers provide sufficient dilution to the heavy metals’ concentration. However, sediment starvation caused by hydrological engineering in recent decades has been reported worldwide. Thus, a study is necessary on the influences of recent declining sediment flux on heavy metal pollution change in the suspended sediments. In this study, heavy metals concentrations and speciation (Cd, Pb, Zn, Cu, Co, Ni, and Cr) in suspended sediments were investigated downstream the Three Gorges Dam (TGD) during dry and flood seasons. Substantial changes of Pb, Zn, Cd, and Cu along the river channel were found which were constrained by the dilution efficiency of suspended sediment during the dry season. High proportion of labile fraction revealed anthropogenic sources of heavy metal. Moreover, the historical trend of metal content illustrated TGD construction together with anthropogenic influx both contribute to the increasing environmental risk in the Yangtze River basin.
The effects of toxic substance in soil matrices are evaluated by assessing adult worm survival and reproduction. Throughout the test, hundreds of juvenile potworms can be found. The current method for Enchytraeus crypticus quantification in soil samples is a laborious and time-consuming procedure that involves manual counting. The present work proposes a method for quick and reliable counting of E. crypticus by using an automated image analysis algorithm applied to soil images. Comparisons between automated and manual methods conducted in double-blind trials involving a large, routine batch of tropical artificial soil samples revealed no statistically significant differences for a wide range of worm densities. The proposed method overcomes time-consuming counts in manual methods and is suited to be deployed routinely for soil toxicity studies involving large batches of samples.
The present study has been carried out to assess the ecohydrogeochemical status of Loktak Lake, the largest freshwater lake in the Northeastern region of India, based on the water quality parameters, hydrogeochemistry, water quality indices (WQI) and trophic state index (TSI). The spatio-temporal variations of physicochemical parameters have been assessed, and it was found that parameters such as pH, turbidity, dissolved oxygen, biological oxygen demand, iron, fluoride and coliform concentrations in the water exceeded the permissible limits prescribed by the World Health Organization (WHO) and Bureau of Indian Standards (BIS) during both pre-monsoon (PM) and post-monsoon (PoM) seasons. The water hardness lies within the soft category, except for a few samples found to be moderately hard. WQI values of lake water ranged between 38.19 and 155.47 during PM and 39.48 and 432.26 during PoM. Based on the WQI classification during PM, 8.6% of the samples were in the unsuitable category, 14.3% very poor, 45.7% poor and 31.4% in the good category. During PoM, 22.9% of the samples were in the unsuitable category, 25.7% very poor, 31.4% poor and 20% in the good category. The irrigation water quality was evaluated using indices such as sodium percentage, sodium adsorption ratio, residual sodium carbonate, permeability index and Kelly’s ratio, and the results indicated that the lake water could be used safely for agricultural purposes. The trophic state evaluation revealed an oligotrophic condition of the lake waters during PM (TSI 37.9) and a mesotrophic condition during PoM (TSI 46.9).
Sustainable crop and livestock planning encounter serious challenges when tasked with reducing the associated nutrient pollution entering the watershed environment. To overcome these challenges, approaches for specifying optimal crop pattern and livestock distribution to limit the pollution in the catchment are advised. In this research, a simulation–optimization approach is used in which the Soil and Water Assessment Tool (SWAT) is employed for simulating the complex soil–water–plant quantity and quality relations, and the Harmony Search (HS) algorithm linked with SWAT is used to discover the optimal crop pattern and distribution of livestock in the Ilam Dam basin, Iran. In the developed HS-SWAT model, the cultivation area and the number of livestock in SWAT’s hydrologic response units (HRU) are the decision variables for maximizing the net benefit obtained from the crop’s and livestock’s productions, while the nitrate and phosphate calculated in the outflow of the basin are restrained to meet the allowable rates. Results show that the scattered livestock in the basin have a great impact on the generated pollution where about 90% of the nitrate entering the downstream reservoir is the consequence of animal waste. In the optimum state, by reduction of the cultivation area and the number of livestock across the watershed, the concentration of N and P in the surface runoff is reduced significantly to meet the allowable level. According to the results, the HS-SWAT model performance indicates its capability for solving watershed crop pattern and livestock planning problems.
Natural resource management relies on identifying the ecological constraints, assessing land suitability, and considering the socio-economic demands in the region. However, in many developing countries, natural resources are extensively overused in favor of economic growth. This is due to the fact that conservation and natural constraints are not always taken into consideration during the planning phase, especially when the decision-making process is mainly influenced by political or economical views. To avoid these subjective plannings, environmental planners are encouraged to consider quantitative planning approaches that can integrate environmental, social, economic, and political matters through a non-bias procedure. The present study, therefore, examines the application of three multi-criteria decision-making methods (MCDM), namely, analytic hierarchical process (AHP), fuzzy analytic hierarchical process (fuzzy AHP), and technique for order of preference by similarity to ideal solution (TOPSIS), for the assessment of land suitability afforestation. Siahpoosh Watershed, in Iran, is used as a case study to compare three MCDM methods. To achieve this, a set of land suitability criteria (i.e., slope, elevation, aspect, soil texture, soil depth, drainage, erosion, temperature, rainfall, and vegetation type and cover) was defined and weighted using the AHP and fuzzy AHP methods. TOPSIS was then used to prioritize and rank the suitability of different sections of the study area for afforestation. The study demonstrates that the fuzzy AHP method combined with TOPSIS generates more reliable outcomes than the AHP method. The results could be useful for making more informed decisions about afforestation in the region.
Particulate organic carbon (POC) and its variability were studied to assess the accuracy of ocean colour retrieval algorithms over the eastern Arabian Sea (EAS) as it controls the carbon sequestration, oxygen minimum zone and biogeochemical (C, N and P) cycles. The seasonality in the physical and biological processes strongly influenced the distribution of POC along the EAS. Higher POC and chlorophyll a (chl a) during the spring inter monsoon (SIM) in the north EAS were due to detrainment bloom. The lower POC:chl a ratios during the winter monsoon (WM) (299.8 ± 190.8) than the SIM (482.1 ± 438.3) were due to the influence of freshly derived organic matter with high nutrient levels. The moderate coefficient of regression values of POC with chl a (R² = 0.49, N = 59) suggests the importance of dead organic materials in controlling the POC distribution in the EAS. Validation between satellite and in situ POC using the four ocean colour retrieval algorithms showed that the algorithm based on the ratio of remote sensing reflectance (Rrs) performed better (R² = 0.6, N = 17). It also showed a linear trend of POC with absorption coefficients suggesting it as an optical proxy for the POC retrieval.
Geographic location of Antarctica (a), Half Moon Island (b), Deception Island (c), and Horseshoe Island (d)
Percentage reduction of KClO4⁻ concentration from marine sediment samples taken from Deception, Horseshoe and Half Moon Islands. Effect after 15 d of contact at an optical density (OD) of 600 and optimal pH of 7.0 ± 0.5
Morphological and biochemical characteristics of isolates from Antarctic marine sediment samples
Perchlorate is a contaminant that can persist in groundwater and soil, and is frequently detected in diferent ecosystems at concentrations relevant to human health. This study isolated and characterised halotolerant bacteria that can potentially perform perchlorate reduction. Bacterial microorganisms were isolated from marine sediments on Deception, Horseshoe and Half Moon Islands of Antarctica. The results of the 16S ribosomal RNA (rRNA) gene sequence analysis indicated that the isolates were phylogenetically related to Psychrobacter cryohalolentis, Psychrobacter urativorans, Idiomarina loihiensis, Psychrobacter nivimaris, Sporosarcina aquimarina and Pseudomonas lactis. The isolates grew at a sodium chloride concentration of up to 30% and a perchlorate concentration of up to 10,000 mg/L, which showed their ability to survive in saline conditions and high perchlorate concentrations. Between 21.6 and 40% of perchlorate was degraded by the isolated bacteria. P. cryohalolentis and P. urativorans degraded 30.3% and 32.6% of perchlorate, respectively. I. loihiensis degraded 40% of perchlorate, and P. nivimaris, S. aquimarina and P. lactis degraded 22%, 21.8% and 21.6% of perchlorate, respectively. I. loihiensis had the highest reduction in perchlorate, whereas P. lactis had the lowest reduction. This study is signifcant as it is the frst fnding of P. cryohalolentis and. P. lactis on the Antarctic continent. In conclusion, these bacteria isolated from marine sediments on Antarctica ofer promising resources for the bioremediation of perchlorate contamination due to their ability to degrade perchlorate, showing their potential use as a biological system to reduce perchlorate in highsalinity ecosystems. Keywords: Extremophiles • Halotolerant bacteria • Psychrotolerant microorganism • Psychrophilic bacteria • Perchlorate biodegradation • Toxicity
Kolkata has a reputation for being one of the world’s most polluted cities, particularly in the post-monsoon months of October, November, and December. Diwali, a Hindu festival, coincides with these months where a large number of firecrackers are set off followed by high emissions of air pollutants. As a result, the air quality index (AQI) deteriorates to “very poor” (301 ≤ AQI ≤ 400) and “poor” (201 ≤ AQI ≤ 300) categories. This situation stays for several days to a month. The present study aims to identify the thresholds for PM2.5 and PM10 that cause the AQI of Kolkata to deteriorate to “very poor” and “poor.” For this purpose, we have used a rough set theory-based condition-decision support system to predict the aforementioned categories of AQI. We have developed a Z-number-based novel quantification measure of semantic information of AQI to assess the reliability of the outcomes, as generated from the condition-decision-based decision rules, during post-monsoon season. The result reveals the best possible forecast of AQI with linguistic summarization of the reliability or confidence for different threshold ranges of PM10 and PM2.5. Inverse-decision rules based on rough set theory are utilized to justify and validate the forecasts. The explainability of the condition-decision support system is demonstrated/visualized using a flow graph that maps rough-rule-based different decision paths between input and output with strength, certainty, and coverage. The investigation resulted in an advanced intelligent environmental decision support system (IEDSS) for air-quality prediction.
Pulp and paper industries are very important for developing the Brazilian economy. During production processes, many effluents are generated with high polluting potential. The objective of this study is to conduct an extensive literature review on the characteristics of effluents and treatment forms adopted by Brazilian mills in this industrial sector. Most consulted studies address raw (without treatment) and secondary (after biological treatment) effluents, considering their main characteristics like pH, chemical and biochemical oxygen demands (COD and BOD, respectively), color, solids, organochlorines, toxicity, estrogenic activity, and phenols. Raw effluents differ considerably in composition, depending on the type of paper produced, the pulping process employed, and other steps, like pulp bleaching. Raw effluent characteristics indicate that this effluent cannot be directly disposed of into water bodies, because it does not comply with federal and state disposal standards. Secondary effluents normally comply with Brazilian legislations, although some studies have reported COD and total phenol concentrations higher than disposal standards, suggesting that additional treatments are necessary. Treated effluent reuse was verified in some Brazilian mills, while its disposal in eucalyptus plantations has been considered a promising alternative for irrigation purposes.
Research shows that regularly performed land use/land cover (LU/LC) variation detection is recommended to support different prospect organizations and management activities to resolve a variety of environmental problems. The current research aims to investigate the LU/LC pattern and measure the corresponding alteration in the arid and semi-arid climatic conditions by considering the Lesser Zab catchment, northeastern Iraq, as a typical basin area. Data from Landsat imageries for the years 1989, 1999, 2009, 2019, and 2021 were utilized. Generally, seven general classes have been noted within the study area through a supervised image classification process. Urban lands in 1989 covered 0.46%; however, in 2021, the urban lands increased to 5.59% compared to 1989. Agricultural lands were reduced by 11.1% between 1989 and 2021. It was identified that there has been a quick transformation from agri-cultural lands to urban lands. The studied basin witnessed a reduction trend in barren and agricultural lands, although urban lands experienced expansion. Whereas, a fluctuation in the occupied area by the water bodies and forest lands has been recorded during the studied period. Analyzing the spatiotemporal pattern of LU/LC would support strategy makers’ detection to cope with the undesired impact of such an event. The unwanted effect of difficult ecological dynamics in the basin would be mitigated by giving particular attention to recovering the affected area to protect the basin’s natural resources.
The geographic location of study area
Workflow of wildfire risk (WR) model construction, which consists of datasets, data processing, and results
Information layers used to develop the wildfire risk (WR) map in a study area. A NDVI; B elevation; C slope; D aspect; E land cover; and F evaporation
Wildfire risk (WR) map of the study area (in white are the residential areas)
Share of the wildfire risk index (WRI) areas in the study’s area
This study aimed at delineating the wildfire risk zones in a fire-prone region located in a rarely addressed area of western Iran (Paveh city) by assessing the potential of factors such as NDVI, topographic factors (elevation, slope, and aspect), land cover, and evaporation in explaining the fire occurrence probability. Analytic hierarchy process (AHP) and geographical information system (GIS) methods were used synergistically to integrate the mentioned factors into analysis, following an informed categorization of each factor based on the information on previous fire occurrence. In the AHP process, elevation and evaporation data were considered to be the most critical factors. It was found that the predicted wildfire risk areas were in agreement with past fire events by the use of the methodology proposed by this study. Accordingly, the study’s final wildfire risk map indicated that approximately 64.7% of the study area is located in the high- and very high-risk zones. Land-use planners and decision-makers may use the developed map to setup and implement fire prevention strategies and enhance or develop the fire-surveillance logistics and infrastructure, including but not limited to the positions of fire watchtowers, fire lines, and fire sensors, with the aim to minimize potential fire impacts.
Digital Shoreline Analysis System (DSAS) is the most frequently used coastal engineering system for shoreline change quantification. Factors like human and system errors, wrong perception of the shoreline changes, and non-exact data sources may cause errors in the measured data. Detection and modification of such data can increase the accuracy of results. At present, the DSAS tool lacks this capability, so this research aimed to present a new module for DSAS to detect uncertain data in shoreline change rate measurements. The module’s basis for detecting uncertain data is to use statistical methods: adjusted boxplot, Grubbs’ test, standard deviation tests, median test, modified Z-score test, and voting method. The module’s performance was evaluated based on a data set obtained through Qeshm Island shoreline change quantification in Iran. The details of these methods, the prepared module, the case study, and the shoreline change measurement statistical methods were discussed in this study. The results showed the acceptable output of this module in detecting uncertain data.
Site locations a inside the whole studied area for sampling of municipal composts (red) and community composts (orange) or b inside an allotment garden area for sampling of home composts made of green waste (green) or a mixture of green and food waste (blue). Satellite views, May 26, 2020 (IGN)
Physicochemical properties of industrial composts (IC), municipal composts (MC), home composts made of green waste (HC GW) or a mixture of green and food waste (HC GW+FW), and community composts (CC). Squares: means. Whiskers: ranges of observations, statistical outliers excluded. (a, b): significant differences (Dunn test, p < 0.05)
Contents of As, Pb, Cu, and Zn in industrial composts (IC), municipal composts (MC), home composts made of green waste (HC GW) or a mixture of green waste and food waste (HC GW+FW), and community composts (CC). Squares: means. Whiskers: ranges of observations, statistical outliers excluded. (a, b): significant differences (Dunn test, p < 0.05). Dashed lines: thresholds of conventional farming regulations (NFU44-051, AFNOR, 2006). Dotted lines: thresholds of Eco-label regulations (2006/799/EC). Dashed dotted lines: thresholds of organic farming regulations (2092/91/EC)
Principal component analysis of the contents in fine fraction (FF), organic matter (OM), major elements (Ca, K, S, Ti), a trace metalloid (As), and trace metals (Cu, Mn, Pb, Rb, Zn, Zr) in industrial composts (IC), municipal composts (MC), home composts made of green waste (HC-GW) or a mixture of green and food waste (HC-GW+FW), and community composts (CC)
Description of the compost types
Home and community composting are key strategies for local organic waste management. The quality and safety of industrial composts are controlled, but those of home and community composts are not, and this could make them unsafe for use in kitchen gardens. Home (n = 20) and community (n = 41) composts, from urban and suburban areas including mildly Pb-contaminated allotment gardens, were analyzed for quality and safety regarding trace metals and metalloids (TMM) using mid-infrared Fourier transform spectrometry (FT-MIR) and portable X-ray fluorescence spectrometry, respectively. Home composts had a significantly higher Pb content (98 mg.kg⁻¹ ± 10 mg.kg⁻¹) than community composts (21 mg.kg⁻¹ ± 2 mg.kg⁻¹). Numerous home composts (85%) and a few community composts (17%) exceeded the organic farming thresholds for Pb (45 mg.kg⁻¹) and Zn (100 mg.kg⁻¹). The high mineral matter content and the relative abundance of chemical functions attributable to silicates (up to 35%) highly paralleled with TMM contents, mostly concentrated in the fine fraction. Co-inertia analysis highlighted strong and significant links between TMM contents and the whole chemical signature delivered by FT-MIR spectrometry. Pb-contaminated soil could be carried into home compost by green waste or by voluntary addition. Covariance analyses indicated that mineral matter and chemical functions only partly explained the variability in Pb content, suggesting a more complex combination of drivers. Community composting appears as a suitable local solution resulting in high-quality compost that complies with European organic farming regulations, while home composting from allotment gardens should be seriously evaluated to comply with such safety requirements.
Rice cultivation is a major source of methane (CH4) emissions. Intermittent irrigation systems in rice cultivation, such as the mid-season drainage (MSD), are effective strategies to mitigate CH4 emissions during the growing season, though the reduction rates are variable and dependent on the crop context. Aeration periods induce alteration of soil CH4 dynamics that can be prolonged after flooding recovery. However, whether these changes persist beyond the growing season remains underexplored. A field experiment was conducted in Spain to study the effect of MSD implemented during the rice growing season on greenhouse gas (GHG) emissions in relation to the standard permanently flooded water management (PFL). Specifically, the study aimed at (1) assessing the CH4 mitigation capacity of MSD in the studied area and (2) testing the hypothesis that the mitigating effect of MSD can be extended into the following winter flooded fallow season. Year-round GHG sampling was conducted, seasonal and annual cumulative emissions of CH4 and N2O as well as the global warming potential were calculated, and grain yield was measured. MSD reduced growing season CH4 emissions by ca. 80% without yield penalties. During the flooded fallow season, MSD reduced CH4 emissions by ca. 60%, despite both fields being permanently flooded. The novelty of our observations lies in the amplified mitigation capacity of MSD by extending the CH4 mitigation effect to the following flooded winter fallow season. This finding becomes especially relevant in rice systems with flooded winter fallow season given the large contribution of this season to the annual CH4 emissions.
Kelani River is the most polluted river in Sri Lanka and the lower catchment is more polluted than the upper catchment. In the present study, freshwater fish species of the lower catchment of the river were investigated for the use of assessing the water quality. Cast net sampling and identification recorded 34 freshwater fish species from the lower catchment, the majority represented by family Cyprinidae. Fish species richness, diversity indices, distribution, abundance and the regression analysis of fish species with water quality parameters revealed high sensitivity and tolerance of three fish species with certain water quality parameters. Dawkinsia singhala was tolerant to the fluctuations of the chemical parameters of the water, while Rasbora daniconius and Pethia reval were tolerant to the physical parameters. Positive correlations were evident between the ammonium and phosphate concentrations of the water and distribution and abundance of D. singhala, while R. daniconius and P. reval showed positive correlations with turbidity of water and pH value respectively. Furthermore, the study reveals that D. singhala is more suitable for predicting the water quality of urban and peri-urban locations of the river, while P. reval and R. daniconius are more suitable for assessing the water quality of rural locations. Thus, the present study reveals a strong possibility of using D. singhala, R. daniconius and P. reval, as biological indicators for assessing the variation of water quality of the lower catchment of the Kelani River. However, despite the fact that such a study has been conducted for the first time in Sri Lanka, it is restrained by certain limitations, and seasonal variations of water quality parameters with fish parameters, adaptations inherent to fish species and food availability in different locations combined with long-term monitoring of fish assemblages have not been considered. Future studies investigating these aspects will further enhance the value of the study.
Accurate renditions of country-scale methane (CH4) emissions are critical in understanding the regional CH4 budget and essential for adapting national climate mitigation policies to curtail the atmospheric build-up of this greenhouse gas with high warming potential. India housing 30% of the Asian population is currently appraised as a region of CH4 source based on the inventories. To date, there have not been many reported efforts to estimate the regional CH4 emissions using direct measurements of boundary layer CH4 concentrations at multiple locations over India. Here, 2 years (2017–2018) of in situ CH4 observations from three distantly placed stations over the peninsular India is combined with state-of-the-art inversion using a Lagrangian particle dispersion model for the estimation of CH4 emission. This study updates CH4 emission over the peninsular India (land area south of 21.5°N) as ~ 10.63 Terra gram (Tg) CH4 year⁻¹, which is 0.13 Tg CH4 year⁻¹ higher than the existing inventory-based emission. On seasonal scale, the changes from the existing CH4 emission inventories are 0.12, 0.05, 0.055 and 0.28 Tg CH4 year⁻¹ during winter, pre-monsoon, monsoon and post-monsoon seasons respectively. Spatial distributions of seasonal variability of posterior emissions suggest an enhancement over the eastern region of peninsular India compared to the western part. The study with observations from three stations over the peninsular India provides an update on the inventory-based estimation of CH4 emissions and urges the importance of more observations over the Indian region for the accurate estimation of fluxes.
Concurrent adsorptive removal of methylene blue (MB) and rhodamine B (RhB) onto durian rind (DR) agricultural waste, from an aqueous binary solution as a model of wastewater containing multiple synthetic dyes, was investigated. The concurrent adsorption of the dyes followed pseudo-second-order kinetics. The adsorption isotherm was well simulated by the Langmuir model, implying a monolayer adsorption to the surface with a homogeneous binding energy. The adsorption process was governed by external mass transfer through two-step intraparticle diffusion of the dyes onto the adsorbent surface. The adsorption efficiency of MB (96.4%) is much higher than that of RhB (56.3%). This is attributed to the higher rate constant for the adsorption of MB (0.348 g mg⁻¹ min⁻¹) as compared to that of RhB (0.151 g mg⁻¹ min⁻¹). The adsorption behavior suggested that the two cationic dyes in the binary solution diffused and adsorbed independently and randomly onto the DR surface. The adsorption capacity of MB and RhB in the binary solution (47.4 mg g⁻¹ and 32.9 mg g⁻¹, respectively) is lower than those of their single solute solutions (93.3 mg g⁻¹ and 62.8 mg g⁻¹, respectively), suggesting a competitive effect in their concurrent adsorption. This was confirmed based on the adsorption characteristics of the binary solution with different molar ratios. The competitive effect was attributed to either non-interactive or repulsive electrostatic interactions between the positively charged dyes in the binary system. The domination of MB is attributed to its smaller molecular size, higher planarity, and faster adsorption kinetics compared with RhB.
Microplastics had been collected at two sites namely Trou d’eau Douce (TD) and La Cambuse (LC) public beaches, lying in the east coast and south-east coast of Mauritius, respectively, over 6 months from September 2019 to February 2020. The sizes of the latter varied from 180 µm to 4 mm. A higher amount of microplastics collected/6-kg sand sample was recorded at LC. Two-way ANOVA revealed that (1) there was a considerable gap in the variability regarding quantity and size distribution of microplastics on the two beaches. The post-hoc analysis showed that the majority of the microplastics at LC were > 1.40 mm, whereas the smaller plastic fragments < 1.40 mm were more dominant at TD. (2) There was a significant interaction between location and event (p value = 0.025). The post-hoc analysis showed that the torrential rain hitting the island prior to sampling week 7 had decreased the microplastic counts at both TD and LC, but not significantly. Interestingly, the two hurricanes, prior to weeks 8 and 9, had appreciably reduced the microplastic counts at TD and, on the other hand, there was an increase in the amount of microplastics at LC, but not to a significant effect. The chemical nature (qualitative analysis) of microplastics was determined by density flotation and FTIR spectroscopy. Microplastics at TD were exclusively high-density polyethylene (HDPE) in origin, whereas, at LC, microplastics were both HDPE and polypropylene (PP) in origin.
The present study demonstrates the spatial analysis and mapping of fish and different measures of environmental parameters and fish diversity of Pong reservoir, Himachal Pradesh, using Kriging spatial interpolation methods for geographical information system mapping. Seasonal data on environmental parameters, potential fish habitat and fish diversity was collected from lentic (dam), lentic (reservoir), transitional and lotic zone of the reservoir.. Important environmental parameters like water temperature, dissolved oxygen, electrical conductivity, water depth and transparency showed variations across the different zones of the reservoir. The sediment of the reservoir was sandy clay loam in nature as per texture analysis. Fish species richness, Shannon index and evenness index showed a similarity of the lotic and lentic (reservoir) zones of the reservoir. Six potential fish breeding grounds were identified in the reservoir indicating high conservation significance. The analysis of data showed a declining trend in fish production from 456.9 tonnes during the decade 1976–1987 to 347.91 tonnes during 2009–2020. The factors like anthropogenic climate change, predation of a stocked fish juvenile by water birds, undersized fish stocking and unscientific management are the probable reasons for the decreasing fish production. The spatial variation pattern of the water spread area, environmental parameters, fish catch and potential fish breeding grounds depicted in the GIS platform can be used as an important information base by the policy makers for fisheries management. The stocking of large size fish as a stocking material and adequate protection of the potential fish breeding grounds are the key advisories for the sustainable enhancement of fisheries as well as conservation.
Drought episodes across the Himalayas are inevitable due to rapidly increasing atmospheric temperatures and uncertainties in rainfall patterns. Tarai of Nepal is a tropical region located in the foothills of the Central Himalaya as a country’s food granary with a contribution of over 50% to the entire country’s agricultural production. However, there is a lack of detailed studies exploring the spatiotemporal occurrence of drought in these regions under the changing climate. In this study, we used the ensemble of nine climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under two shared socio-economic pathways (SSPs), namely SSP245 (an intermediate development pathway) and SSP585 (a high development pathway), to assess anticipated drought during the mid-century. We used bias-corrected gridded data from the Worldclim to project drought events by the end of the mid-century based on the historical period (1989–2018). We computed historical and projected Thornthwaite moisture index (TMI) to evaluate soil moisture conditions on a seasonal scale for the Tarai region’s Eastern, Central, and Western parts. The model ensemble projected a significant increase in precipitation and temperature for the entire Tarai by the end of mid-century. However, the winter and spring seasons are projected to suffer precipitation deficiency and a temperature rise. Our results indicated that the Eastern Tarai would likely experience a decrease in winter precipitation. We emphasize that the presented spatiotemporal pattern of the MI will be instrumental in addressing the irrigation facility’s needs, choice, and rotation of crops under the changing climate scenarios and in improving our mitigation measures and adaptation plans for sustainability of the agriculture in drought-prone areas.
Many shipping companies have started using scrubbers in their fleet to eliminate sulfur emissions from ships, per IMO (International Maritime Organization) rules. Before and during the scrubbers’ selection, the scrubbers’ operational failures have also started to appear and cause serious concerns. In this study, classified scrubber types are explained and open type, closed type, and hybrid scrubber systems are evaluated. To contribute to this gap in the literature, scrubber failures were identified, five experts with different perspectives were consulted, and the most common and critical malfunctions were evaluated with the fuzzy best–worst method (F-BWM) and fuzzy technique for order preference by similarity to an ideal solution (F-TOPSIS). F-BWM was used to determine the importance weights of the risk parameters used in evaluating failures since it provides fewer comparisons among pairwise comparison–based decision-making methods and a more consistent judgment in the evaluation. F-TOPSIS, on the other hand, was used to determine the final priority scores of the scrubber failures, taking into account the risk parameter weights obtained in the first stage. It has been preferred due to its easy to useness and based on its closeness to the ideal solution and applicability to risk and failure analysis problems. Considering all different systems in general, important issues such as collection efficiency, sulfur emission problem, abrasion, leakages, pump failures, heat exchanger failures, air fan sealing failures, sensors and failures in monitoring the whole system have been investigated. Results show that too high axial velocity for separator and flooded separator, too high solids concentration in recirculation liquid (SF2), piping leakages (SF5), poor quality or inappropriate consumables and chemicals (SF11), and feed circulation pump problems (SF6) are found to be the most important problems among thirteen failures.
Sources of antibiotic wastes and their degradation mechanisms. Natural and commercial sources of the antibiotic contaminate the lithosphere and hydrosphere and are the major triggering factor behind the rise of the antimicrobial resistance. The antibiotics present in the environment can be deactivated or degraded both by chemical treatment and by biological treatment
Antibiotics are the major pharmaceutical wastes that are being exposed to the environment from the pharmaceutical industries and for the anthropogenic activities. The use of antibiotics for disease prevention and treatment in humans has been surpassed by the amount used in agriculture, particularly on livestock. It is stipulated that the overuse of antibiotics is the single largest reason behind the rise of bacterial anti-microbial resistance (AMR). The development of alternative therapy, like gene therapy, immunotherapy, use of natural products, and various nanoparticles, to control bacterial pathogens might be an alternative of antibiotics for mankind but the remediation of already exposed antibiotics from the lithosphere and hydrosphere needs to be envisioned with priority. The ever-increasing release of antibiotics in the environment makes it one of the major emerging contaminants (ECs). Decomposition of such antibiotic contaminants is a great challenge to get a cleaner environment. There are reports describing the degradation of antibiotics by photolysis, hydrolysis, using cathode and metal salts, or by degradation via microbes. Antimicrobials like sulfonamides are recalcitrant to natural biodegradation, exhibiting high thermal stability. There are recent reports on microbial degradation of a few common antibiotics and their derivatives but their applications in waste management are scanty. It could however be a major concern to the scientists whether to use the antibiotic degradation traits of a microbe for the removal of antibiotic wastes. The complexity of the genetic clusters of a microbe that are responsible for degradation is crucial, as a small genetic cluster might have higher chance of horizontal transfer into sensitive species of the normal microbial flora that in turn triggers the rise of antimicrobial resistance.
We sought to investigate the impact of air purifiers in the removal of particular matter (PM)10, PM2.5, PM1, and particle number concentration (PNC) in the indoor air of dormitories located at Iran’s largest medical university, Tehran University of Medical Sciences. Twelve rooms were selected and randomly assigned to two rooms: sham air purifier system deployed room (SR) and true air purifier system deployed room (TR). All study samples were drawn simultaneously from assigned rooms using portable GRIMM dust monitors for 24 h. The PM monitors of air were positioned in the middle of each room next to the air purifier at the height of the breathing zone (1.5 m in height). The mean PM10, PM2.5, PM1, and PNC removal efficiency in rooms with and without a smoker were measured to be 40.7 vs 83.8%, 31.2 vs 78.4%, 29.9 vs 72.3%, and 44.3 vs 75.6%, respectively. The results showed that smoking is an important influencing factor on the indoor air quality; smoking lowered the removal efficiency of PM10, PM2.5, PM1, and PNC by 43%, 47%, 43%, and 31%, respectively. An air purifier could decline the PM10 and PM2.5 even lower than the WHO 24-h guideline level in non-smoker rooms. This study revealed that using household air purifiers in rooms with smokers and non-smokers significantly reduces the non-carcinogenic risks of exposure to PM10 and PM2.5.
In running waters, the concentration of components that define water quality can be subjected to ample fluctuations quantitatively linked to flow rate. If not properly considered, such variability may hinder assessment of the evolution of water quality, of the effects of management actions, and ultimately the understanding of processes driving water quality. The functional response to flow rate was characterized for multiple biogeochemical variables in a pristine, low order stream. Variability of responses spanned between a factor of 2 and > 34, and in all cases were associated to flow rate according to one of three patterns: positive asymptotic (for variables: seston, suspended particles, total nutrients, dissolved and particulated organic matter, dissolved inorganic nitrogen), negative asymptotic (conductivity and dissolved reactive silicon), and humped (dissolved inorganic phosphorous). Building on those results, a rationale is presented for an unambiguous, cost-effective approach to water quality evaluation in running systems with predominantly diffuse sources.
Map of the study area showing sampling sites for sediment and roadside soil samples and locations of thermal power plant (TPP) and cement factory (CF) in Ropar wetland and its environs
Spatial maps showing comparative distribution of PTEs in sediments and roadside soil samples from Ropar wetland and its environs during pre-monsoon and post-monsoon seasons
Diagram showing potential ecological risk posed by PTEs present in sediments and roadside soil samples from Ropar wetland and its environs during pre-monsoon and post-monsoon seasons
Sediments from banks of the Sutlej River and roadside soils from vicinity of Ropar wetland (collected during pre- and post-monsoon seasons, 2013) were analysed to determine the spatiotemporal distribution of potentially toxic elements (PTEs, viz. arsenic, cadmium, cobalt, chromium, copper, iron, manganese, lead and zinc), which when present in high concentrations may pose health hazards and ecological risk. Contamination factor, degree of contamination, modified degree of contamination, metal pollution index, pollution load index, enrichment factor, geoaccumulation index and ecological risk index were also determined for these PTEs in the study area. Sediment and soil samples were found to be alkaline and non-saline (pH > 7.0; EC < 4500 μS cm−1) with sodium and potassium as major ions. Iron (mg kg−1) was found to be most abundant in sediments (1477.59–6512.45) and soils (922.64–12,455.00). Cadmium content in sediments exceeded the threshold value (0.99 mg kg−1) at 2 (pre-monsoon) and 3 (post-monsoon) sampling sites. In both seasons, cadmium (0.10–2.05) and cobalt (11.40–17.52) contents (mg kg−1) exceeded the threshold limits (0.06 and 8.00 respectively) in all roadside soils. Significant spatiotemporal variation (p ≤ 0.05) was observed for pH; EC; and calcium, magnesium, copper, iron and zinc contents. Low to moderate potential ecological risk was observed for both roadside soils (31.80–213.82) and sediments (41.47–236.73). Contamination factor, enrichment factor and geoaccumulation index for cadmium were highest in roadside soils (6.84, 46.91 and 2.19, respectively) and sediments (7.64, 167.46 and 2.35, respectively) due to settlement of coal fly ash released from the industrial setups, on sediments/soils of the study area.
a Sampling stations: 1, the deepest part of the lake (near aerator); 2, shallower part of the lake; 3, Cybina River Inflow; 4, Cybina River Outflow; 5, Mielcuch Stream (Kozak et al., 2018, changed) and b precipitation in Poznań before (BR I, BR II), during sustainable (SR), and limited restoration (LR).
The mean (dot or square) with 0.95 confidence interval (whisker) of temperature and oxygen content (a), conductivity (b), pH (c), TSS content and chlorophyll a concentration (d), TP concentration (e) and TN concentration (f) during the 4 periods: BR I, BR II, SR and LR at 5 sampling stations: Cybina Inflow, Station 1, Mielcuch, Station 2, Cybina Outflow
CVA diagrams of significant physico-chemical parameters depending on sampling stations (Cybina Inflow, Cybina Outflow, Mielcuch, St 1, Station 1; St 2, Station 2) during the whole studied period (a) and periods at the Cybina Outflow (BR I, 2000–2002; BR II, 2011; SR, 2012–2014; LR, 2015–2016) (b); the significance threshold p < 0.05
To fill the knowledge gap about the functioning of the lake–river system subjected to restoration treatments, two tributaries, a shallow, restored lake and its outflow, were examined. The quality of water inflows, lake and outflow was compared before (BR), during sustainable (SR, deep water aeration, phosphorus inactivation and biomanipulation for 3 years) and limited lake restoration (LR, only aeration for 2 years). Physico-chemical parameters were analysed monthly at five stations. The nutrient concentrations at the inflows decreased over the years due to the improvement of water and sewage management in the catchment (in Mielcuch from 18.0 to 8.0 mgN L ⁻¹ and 1.0 to 0.6 mgP L ⁻¹ ). The decline at the outflow was the result of a better quality of water at the tributaries and SR in the lake. During LR, decrease of phosphorus concentration still occurred (0.11 mgP L ⁻¹ ), but nitrogen concentration slightly increased (3.9 mgN L ⁻¹ ). Although the outflowing waters still transported a high content of chlorophyll a and suspended solids during SR, their amount was lower (34.5 μg L ⁻¹ and 17 mg L ⁻¹ , respectively) than that during BR and LR. During restoration, it is significant to monitor the water quality not only in the lake but also at the outflow. The slow deterioration of water quality at the outflow indicated that introducing changes in the applied restoration methods must be done carefully because the previously achieved effect may be lost. Hence, restoration of the upstream lake and good quality of its tributaries are of great importance for water bodies located downstream.
Ribeirão das Pedras, a 10-km-long stream from the source to mouth, is part of a predominantly urban catchment located in Campinas metropolitan area in the state of São Paulo, Brazil, and it is also surrounded by sugarcane farms. Monthly sampling of 31 selected emerging contaminants (ECs) was conducted for 1 year (October 2018 to October 2019) in five points, including the spring, agricultural, and urban areas, to assess the dynamics and impact of ECs on the stream. The ECs were quantified using LC–MS/MS analysis. Out of the 31 ECs monitored in this study, 13 were detected in the Ribeirão das Pedras catchment, which were mainly pesticides and caffeine. Eight ECs (hexazinone, malathion, desethylatrazine (DEA), desisopropylatrazine (DIA), fipronil, ametryn, 2-hidroxyatrazine, and diuron) were detected with risk quotients higher than 1, indicating some level of environmental concern. Statistical analyses showed that caffeine, hexazinone, atrazine, DEA, and DIA were the most statistically important contaminants in temporal analysis, with caffeine concentrations varying randomly. Hexazinone, atrazine, DIA, and DEA concentrations increased from November 2018 to January 2019, and atrazine, hexazinone, and DEA concentrations increased from June 2019 to September 2019. Spatial analysis indicates that the spring of Ribeirão das Pedras is the only statistically different sampling point, with lower concentrations of EC. Points 3 and 5, both located in urban areas next to the stream’s mouth, differ from each other due to the possible dilution of caffeine downstream of point 3 and domestic sewage discharge upstream of point 5. Graphical Abstract
A recently conducted study by the Centers for Disease Control and Prevention encouraged access to urban green space for the public over the prevalence of COVID-19 in that exposure to urban green space can positively affect the physical and mental health, including the reduction rate of heart disease, obesity, stress, stroke, and depression. COVID-19 has foregrounded the inadequacy of green space in populated cities. It has also highlighted the extant inequities so as to unequal access to urban green space both quantitatively and qualitatively. In this regard, it seems that one of the problems related to Malatya is the uncoordinated distribution of green space in different parts of the city. Therefore, knowing the quantity and quality of these spaces in each region can play an effective role in urban planning. The aim of the present study has been to evaluate urban green space per capita and to investigate its distribution based on the population of the districts of Battalgazi county in Malatya city through developing an integrated methodology (remote sensing and geographic information system). Accordingly, in Google Earth Engine by images of Sentinel-1 and PlanetScope satellites, it was calculated different indexes (NDVI, EVI, PSSR, GNDVI, and NDWI). The data set was prepared and then by combining different data, clas-sification was performed according to support vec-tor machine algorithm. From the landscaping maps obtained, the map was selected with the highest accu-racy (overall accuracy: 94.43; and kappa coefficient: 90.5). Finally, by the obtained last map, the distribu-tion of urban green space per capita and their func-tions in Battalgazi county and its districts were evalu-ated. The results of the study showed that the existing urban green spaces in the Battalgazi/Malatya were not distributed evenly on the basis of the districts. The per capita of urban green space is twenty-four regions which is more than 9m2 and in twenty-three ones is less than 9m2. The recommendation of this study was that Türkiye city planners and landscape designers should replan and redesign the quality and equal dis-tribution of urban green spaces, especially during and following COVID-19 pandemic. Additionally, draw-ing on the Google Earth Engine cloud system, which has revolutionized GIS and remote sensing, is recom-mended to be used in land use land cover modeling. It is straightforward to access information and analyze them quickly in Google Earth Engine. The published codes in this study makes it possible to conduct fur-ther relevant studies.
The EU Water Framework Directive requires the monitoring and evaluation of surface water sediment quality based on the assessment of risk posed by contamination on the biotic receptors. Floodplain sediments are important receptors of potentially toxic element (PTE) contamination from the upstream catchment areas, and floodplains host climate-sensitive riverine ecosystems and fertile agricultural areas at the same time. This study investigates the effect of PTE contamination on microbial communities in floodplain sediments and soils using the fast, inexpensive and reliable fluorescein diacetate (FDA) method in order to estimate its applicability for sediment quality monitoring and preliminary toxicity-based risk assessment. Sediment and soil samples were collected from the actively flooded alluvial plain and the river terrace areas along a 130-km stretch of the large Drava River floodplain known to be widely contaminated by historical mining, smelting and the associated industry in the upstream Alpine region. Results of detailed data analysis show that the total microbial activity represented by the measured FDA values is related to PTE (As, Cu, Zn, Cd, Pb) concentrations, but this relationship shows significant heterogeneity and depends on the spatial location and on the soil properties such as organic matter content, dissolved salt and nutrient content, and it is specific to the toxic elements. Results show that some microbe species appear to be able to adapt to the elevated PTE concentrations in toxic soil micro-environments, over time. Despite the observed heterogeneity of microbial activity, the results revealed a breakpoint in the FDA dataset around the FDA = 3 FC (fluorescein concentration) value suggesting that microbial activity is controlled by thresholds.
As new persistent organic compounds, polybrominated diphenyl ethers (PBDEs) have aroused important concern because of their potential bioaccumulation and possible ecological and health risk. To examine the sources and temporal variation of PBDEs in Chaohu Lake in eastern China, the surface sediments from Nanfei River (NFR) and core sediments from four estuaries were measured. It showed that low-brominated congeners were dominant, from MonoBDEs to HeptaBDEs (referred to as Σ39PBDE). Concentrations of ∑39PBDE and the ratios of (BDE-47 + BDE-99 + BDE-100)/(BDE-153 + BDE-154) were much greater in surface sediments than in core sediments. The highest concentration was observed in a site close to the outfall of a municipal sewage treatment plant (MSTP), and the ratio was significantly correlated with ∑39PBDE. These results suggested that PentaBDE and OctaBDE commercial mixtures were widely used around Chaohu Lake and the effluent of municipal sewage was a dominant source of PBDEs to surface sediment. Compared to data from other freshwater systems around the world, the concentrations of BDE-47 and BDE-99 in this study were in the middle of the range of global data, but BDE-183 concentrations were at the high end of the range. Due to restrictions on the usage of PentanBDE and OctaBDE commercial mixtures, reductions of PBDE levels from subsurface to superficial layer were observed in all estuaries. Elevated contribution by MonoBDEs to ∑39PBDE in the estuary of the only outflow river suggests significant congener fractionation. TriBDEs, TetraBDEs, and HexaBDEs appeared to pose low risks in all surface sediments, but moderate to high risks may be expected for PentaBDEs. Overall, the results would contribute to a better understanding of the sources and environmental fate of PBDEs in the studied eutrophicated lake.
Water quality monitoring is very important in agricultural catchments. UV–Vis spectrometry is widely used in place of traditional analytical methods because it is cost effective and fast and there is no chemical waste. In recent years, artificial neural networks have been extensively studied and used in various areas. In this study, we plan to simplify water quality monitoring with UV–Vis spectrometry and artificial neural networks. Samples were collected and immediately taken back to a laboratory for analysis. The absorption spectra of the water sample were acquired within a wavelength range from 200 to 800 nm. Convolutional neural network (CNN) and partial least squares (PLS) methods are used to calculate water parameters and obtain accurate results. The experimental results of this study show that both PLS and CNN methods may obtain an accurate result: linear correlation coefficient (R ² ) between predicted value and true values of TOC concentrations is 0.927 with PLS model and 0.953 with CNN model, R ² between predicted value and true values of TSS concentrations is 0.827 with PLS model and 0.915 with CNN model. CNN method may obtain a better linear correlation coefficient (R ² ) even with small number of samples and can be used for online water quality monitoring combined with UV–Vis spectrometry in agricultural catchment.
The disposal of solid wastes is a significant problem in urban areas in many developed and developing countries. Waterways are often subjected to pollution by effluents discharged from solid waste dumpsites. The stable isotopes and water quality data provide useful information on tracing pollutant sources and their contaminant pathways. The effect of a major solid waste dumpsite on surface and groundwater quality of the surrounding area was investigated by measuring water quality parameters and stable isotopes of deuterium (²H), oxygen (¹⁸O), ¹⁵ N‐ΝΟ3 and ¹⁸O-NO3 in tropical Sri Lanka. The surface water and groundwater wells close to the dumpsite indicated clear evidence of leachate contamination with enriched total dissolved solids (TDS), total suspended solids (TSS), ammonia, biochemical oxygen demand (BOD5) and Cl⁻ levels. The correlation of groundwater quality parameters, i.e. EC (−r² = 0.8), TDS (−r² = 0.8), TSS (−r² = 0.5), ammonia (−r² = 0.4), phosphates (−0.6), sulphates (−0.5), Cl⁻ (−0.6) and isotope δ²H‰ (−0.9) with distance from the dumpsite, further confirmed the effects of dumpsite on groundwater quality. The composition of δ¹⁵N‐ΝΟ3 and δ¹⁸O-NO3 isotopes in the groundwater indicated that the dominant source of NO3⁻ to groundwater is manure septic originating from the dumpsite. The findings of the study provided clear evidence of the effect of open dumping on the water resources of the surrounding area and the need for remedial measures.
The element found at the highest amount in onion samples was sulfur, and followed by K, Ca, P, Na, and Mg in decreasing order. While K contents of white onion parts are determined between 1406.31 (outer most edible) and 1758.72 mg/kg (inner most edible), K contents of the parts of brown onions were measured between 1779.79 (head) and 2495.89 mg/kg (inner most edible). Also, K amounts of purple onions were detected between 2248.73 (shell) and 3064.64 mg/kg (middle edible). In addition, in general, the highest P, S, and K were detected in the middle edible and inner most edible parts of the edible onion samples. While the highest Ca content was localized in brown and purple onion roots, it was most localized in the shell part of white onions. In edible white and brown onions, the highest Na content was found in the inner most edible part. Fe amounts of white and brown onion samples were identified between 7.94 (head) and 20.41 mg/kg (root) to 9.56 (middle edible) and 23.67 mg/kg (head), respectively. Also, Fe contents of the parts of purple onions varied between 13.04 (shell) and 20.61 mg/kg (inner most edible). While the highest Fe and Zn are determined in the middle edible part in edible white onions, the highest Fe and Zn were determined in the outer most edible part in brown onions. In general, the most heavy metals were localized in the bark, head, and root parts of the onions. This had a positive effect on the safe edibility of onions. The heavy metal detected in the highest amount in onion samples was arsenic, followed by Cr, Al, Ni, Se, Ba, Pb, Mo, Co, and Cd in descending order. Generally, purple onion type showed maximum values. Therefore, results of the present study seen to be beneficial in the way that it allowed us to selected some varieties with nutrition value that could be interesting to introduce in gastronomy.
Layout of sampling location in a respiratory ward, b physician clinic and c emergency department
Identification of 60 bacterial isolates from sampling locations
Distribution of airborne bacteria identified in the respiratory ward (RW), physician clinic (PC) and emergency department (ED)
Bacteria in a hospital environment potentially cause hospital-acquired infections (HAIs), particularly in immunocompromised individuals. Treatments of HAIs with antibiotics, however, are ineffective due to the emergence of antibiotic-resistant bacteria (ARB). This study aims to identify airborne bacteria in a tertiary hospital in Malaysia and screen for their resistance to commonly used broad-spectrum antibiotics. Airborne bacteria were sampled using active sampling at the respiratory ward (RW), physician clinic (PC) and emergency department (ED). Physical parameters of the areas were recorded, following the Industry Code of Practice on Indoor Air Quality 2010 (ICOP IAQ 2010). Bacterial identification was based on morphological and biochemical tests. Antibiotic resistance screening was carried out using the Kirby-Bauer disk diffusion method. Results showed that the highest bacterial population was found in the highest density occupancy area, PC (1024 ± 54 CFU/m³), and exceeded the acceptable limit. Micrococcus spp., Staphylococcus aureus, α- and β-Streptococcus spp., Bacillus spp. and Clostridium spp. colonies were identified at the sampling locations. The antibiotic resistance screening showed a vast percentage of resistance amongst the bacterial colonies, with resistance to ampicillin observed as the highest percentage (Micrococcus spp.: 95.2%, S. aureus: 100%, Streptococcus spp.: 75%, Bacillus spp.: 100% and Clostridium spp.: 100%). This study provides awareness to healthcare practitioners and the public on the status of the emergence of ARB in a hospital environment. Early detection of bacterial populations and good management of hospital environments are important prevention measures for HAI.
Location map of the Sindh River Basin and eleven sampling station
a Dendrogram highlighting 3 clusters (1, 2, 3) of all sites on the basis of physicochemical parameters from Sindh River. b Average silhouette coefficient measures highlighting three clusters and placement of sites in their right cluster
Box and whisker plot of the discriminating parameters
As the run-of-river (RoR) hydropower projects remain understudied, we conducted this study to understand how these projects affect the hydro-chemical dynamics and water quality index (WQI) of the Sindh River in the Kashmir Himalayas. We used multivariate statistical techniques and WQI to identify the spatiotemporal dynamics of 18 physico-chemical parameters from 11 sampling stations distributed along the length of river Sindh from December 2017 to December 2019. The dataset was classified into three groups using hierarchical cluster analysis based on similarities between hydro-chemical characteristics, and the results were confirmed by discriminant analysis. Wilk’s quotient distribution further showed that ions, nutrients, free carbon dioxide, water temperature, and pH contributed to the formation of clusters. Principle component analysis revealed that the chloride (Cl−), total phosphorus (TP), ortho-phosphorus (PO4–P), nitrate-nitrogen (NO3–N), nitrite-nitrogen (NO2–N), and sulfate ion (SO42−) are significant factors that influence the water quality. Furthermore, our results suggest that diverting water for RoR operation did not significantly raise the WQI value to the point where water in the bypassed reaches could be declared unfit for drinking. Our analysis concluded that inclusive assessments are vital for framing policies on expanding RoR hydropower in the region.
Today, different methods are used to measure two-dimensional (2D) and three-dimensional (3D) attributes of trees. One of these methods, which is considered in recent years is using point clouds and a 3D model extracted from terrestrial photogrammetry (TP). This study aims to estimate the 2D and 3D attributes of urban trees at three levels of seedlings, single trees and sample plot using TP. Structure-from-Motion with Multi-View Stereo-photogrammetry (SfM-MVS) method was used to derive the point clouds and the 3D model. Comparing estimated values of diameter at the middle of trunk of seedlings and diameter at breast height (DBH) of trees, using TP with measured values showed that the values of RMSE% were < 2% at three levels of seedlings, single trees and sample plot. Furthermore, validation of the estimated values of total height and crown height attributes of seedlings and trees at three levels showed that the RMSE% did not exceed 4% and 5%, respectively. Considering the overlap of tree crowns with each other in the sample plot, the average diameter of the crown attribute was estimated only in seedlings and single tree levels with RMSE% = 6.51% and 9.34%, respectively. The validation of estimated values of stem volume of seedlings and trees at three levels showed that the lowest errors were returned from trees within a sample plot with RMSE% = 14.37%, whereas the highest rates of errors were achieved for seedlings with RMSE% = 20.99%. As an alternative to approaches such as employing laser scanners, this method is quick, inexpensive, non-destructive, and does not need specialized equipment.
Cu and Zn adsorption isotherms in soils with different clay contents and different levels of organic matter: a, c 1CL = 4% clay; 2CL = 17% clay; 3CL = 31% clay; 4CL = 44% clay; 5CL = 57% clay; 6CL = 70% clay: b, d 1OM = 0.5% OM; 2OM = 2% OM; 3OM = 4% OM; 4OM = 6% OM; 5OM = 8% OM, and 6OM = 9.5% OM. The curves shown represent the adjustment by the Langmuir model. MAC-Cu maximum Cu adsorption capacity and MAC-Zn maximum Zn adsorption capacity
Cu and Zn concentration in water as a function of the amount of Cu an Zn available in the soil extracted by Mehlich-1, in soils with different clay contents: a, b 1CL = 4% clay; 2CL = 17% clay; 3CL = 31% clay; 4CL = 44% clay; 5CL = 57% clay; 6CL = 70% clay; b, d 1OM = 0.5% OM; 2OM = 2% OM; 3OM = 4% OM; 4OM = 6% OM; 5OM = 8% OM, and 6OM = 9.5% OM. The highlighted values indicate the critical limit of Cu and Zn transfer (T-Cu and T-Zn threshold)
Critical limit of Cu and Zn transfer (T-Cu and T-Zn threshold), a function of clay (CL) and organic matter (OM) content. a (threshold) de Cu (T-Cu); b (threshold) de Zn (T-Zn) Clay; c (threshold) de Zn (T-Zn) OM. Equation in black: limit Zn content to increase the release of Zn in water; equation in blue: 80% of T-Zn; equation in red: simplified function to calculate T-Zn
Several studies have reported increased copper (Cu) and zinc (Zn) levels in agricultural soils worldwide, mainly due to organic waste and successive leaf fungicide applications in crops. However, the critical transfer thresholds in soils, which can indicate the real risk of environmental contamination and toxicity to plants, remain poorly understood. This study aimed to define the maximum Cu and Zn adsorption capacity (MAC) and threshold (T-Cu and T-Zn) in different soils in Southern Brazil, which present different clay and organic matter (OM) levels. Bw (Oxisol) and A horizon (Inceptisol) samples were used to obtain soils with clay and OM contents ranging from 4 to 70% and from 0.5 to 9.5%, respectively. Cu and Zn adsorption curves were plotted for MAC determination purposes. Based on Cu and Zn MAC values, different concentrations of these elements were applied to the soils for subsequent quantification of available Cu and Zn levels (Mehlich-1 and water). T-Cu in soils with different clay contents ranged from 81 to 595 mg Cu kg⁻¹, whereas T-Zn, from 195 to 378 mg Zn kg⁻¹. T-Cu in soils with different OM levels ranged from 97 to 667 mg Cu kg⁻¹, whereas T-Zn, from 226 to 495 mg Zn kg⁻¹. T-Cu can be calculated through the equation: T-Cu = 75 × (%CL0.34) × (%OM0.39), whereas T-Zn: T-Zn = 2.7 × (CL) + 126 (by taking into consideration the clay content) and T-Zn = − 9.3 × (%OM)² + 92.4 × (%OM) + 66 (by taking into consideration OM content). T-Cu and T-Zn can be used by researchers, inspection bodies, technical assistance institutions, and farmers as safe indicators to monitor the potential for environmental contamination.
A Location of the study site within Fiji, and arrangement of aquaculture ponds relative to Navua Irrigation Dam and connecting inlet and drainage channels (B). Inset C identifies Fiji’s location relative to the Pacific Ocean. Countries shapefiles are sourced from https://earthexplorer.usgs.gov/, image used in inset B is sourced from Landsat satellite imagery https://earthexplorer.usgs.gov/. For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article
Microplastic abundance of surface water (MP/L), sediment (MP/100 g dw), and fish (MP/fish), along each of the sampled study sites along an aquaculture system in Fiji. Mean concentration is denoted by “X”
Abundance and composition of form types along each of the sampled study sites along an aquaculture system in Fiji
Microplastics (MPs) have become frequent topics of research within Pacific Islands (PIs) in recent years; however, within PI freshwater aquaculture systems, MPs have not yet been quantified. As such this study is aimed at quantifying and characterizing the MP load from across a freshwater aquaculture system within Fiji. Water, sediment, and fish samples were collected from various stages between water source and drainage channels of an aquaculture facility in Navua, Fiji. MPs were extracted using established protocols and analyzed for abundance, form type, size, and polymer composition. Results show no significant difference in MP abundance between sampling sites for, water (average: 3.2 ± 1.14 MP/L), sediment (average: 2.3 ± 0.7 MP/100 g DW), and fish (average: 2.7 ± 1.4 MP/fish). Fibers were the most frequent form type in all three elements (average: 2.9 ± 0.2 MP/L in water, 2.1 ± 0.75 MP/100 g DW, 2.8 ± 0.14 MP/fish); however, the difference across sites was significant within water samples only. In water and sediments, smaller MPs (< 1.4 mm) were the most frequent comprising > 35% in all three elements; however, the difference was not significant between sites. Polymer analysis found that polypropylene, polyurethane, and nylon were the most abundant polymers, which coupled with observed form type and size characteristics suggest a common sources of MPs across sites.
Drought is an extreme event and its frequency is expected to increase in future under the imminent threats of climate change. The areas vulnerable to drought are increasing due to increase in the spatial extent and severity of droughts. This necessitates the need for development of an integrated framework for assessment of drought vulnerability, which will be vital for water resources management policies focused towards such vulnerable areas. An integrated drought vulnerability assessment framework has been developed considering the physical indicators that vary spatially, social indicators that vary spatially but their temporal variation may be at longer time-frames and spatio-temporal drought indicators that vary spatially and temporally during various months during drought years. This framework has been tested for Bina basin located in the drought prone Bundelkhand region of Madhya Pradesh. The drought indicators used in the study includes, i) Standardized Precipitation Index (SPI) for evaluating meteorological drought characteristics, ii) Surface water Drought Index (SDI) for evaluating streamflow drought characteristics and iii) Groundwater Drought Index (GDI) for evaluating groundwater drought characteristics. Groundwater levels being observed at quarterly (3 monthly) time step. So the relationships between GDI and 3-m SPI, 6-m SPI, and 12-m SPI have been investigated. Based on the best correlation, the 12-m SPI can be used to represent the groundwater drought in Bina basin and has therefore been used to assess the monthly variability in the groundwater drought characteristics. The spatially varying physical indicators including basin reach (elevation band), land use pattern and soil type; the spatio-temporal drought indicators including soil moisture drought, surface water drought and groundwater drought, rainfall departure and number of consecutive dry days; and the spatially varying social indicators including infants and young children, illiterate population, marginal workers and rural population have been used for the development of a Drought Vulnerability Index (DVI). The integrated drought vulnerability assessment framework has been conceptualized on the basis of DVI. Four vulnerability classes have been defined and the study area falls in mild to moderate vulnerable class, based on the analysis carried out for the various drought years in the basin. Appropriate drought management plans and mitigation strategies needs to be developed to target these vulnerable areas in Bina basin.
The study area’s location map shows sample sites around the River’s Swat basin in Khyber Pakhtunkhwa, Pakistan
a Geographical distribution of heavy metal (HM) concentrations (mg/kg) and b total variance and rotated component matrix of individual HMs in surface soil of the River Swat basin
a Average individual heavy metal (HM) contamination factor (CF) and their collective contamination degree. b Average geo-accumulation indices (Igeo) of individual HMs in the study area
a Spatial distribution of potential ecological hazard index (PEHI) values of combined heavy metal contaminations. b Single metal ecological hazard (Eri\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${E}_{r}^{i}$$\end{document}) values and its percentage (%) contributions to combined metal PEHIs
Heavy metals’ non-carcinogenic and carcinogenic hazards posed by the area’s human adults and children population via soil ingestion, inhalation, and skin contact
Soil pollution with heavy metals (HMs) has become a world environmental problem. This study focuses on surface soil contamination with Cr, Mn, Co, Ni, Cu, Zn, Cd, Hg, Pb, Fe, and Al, their sources, and potential hazards along the basin of River Swat, Pakistan. The average concentrations (mg/kg) of HMs were the most abundant for Al (24,730.19) followed by Fe (22,419.41) > Mn (386.78) > Zn (57.75) > Cr (38.07) > Ni (32.46) > Cu (23.43) > Pb (19.59) > Co (10.77) > Cd (3.18) > Hg (0.12). The concentrations of Cr and Mn in 5.45% each, Co in 10.90%, Zn in 27.27%, Cu in 36.36%, Ni in 41.81%, and Hg in 92.72% of the total soil samples exceeded their respective background values. The geostatistical approaches determined the distribution patterns of HM pollution along the basin, whereas the statistics of principal component analysis exposed the likely sources of HM contamination in the area. Pollution indices evaluated the overall HM distribution and pollution status in the area. Contamination factor showed a high degree of HM contamination in 82% of the total sampling sites, while the geo-accumulation index designated low to moderate contamination with Cr, Mn, Co, Ni, Cu, Zn, Hg, and Pb, and moderate to extreme contamination with Cd, Fe, and Al. The trend of ecological toxicity showed potential ups and downs along with the sites from low to considerable hazard (< 95 < PEHI < 190), whereas the human carcinogenic hazard was within the USEPA acceptable limits (1 × 10⁻⁷–1 × 10⁻⁴), but the non-carcinogenic hazard was higher than the threshold (HI > 1) for children because they are more exposed than adults.
The nonlinear groundwater level fluctuations depend on the interaction of many factors such as evapotranspiration, precipitation, groundwater abstraction, and hydrogeological characteristics, making groundwater level prediction a complex task. Groundwater level changes are among the most critical issues in water resource management, which can be predicted to effectively provide management solutions to conserve renewable water resources. Understanding the aquifer status using numerical models is time-consuming and also is associated with inherent uncertainty; therefore, in recent decades, the application of artificial intelligence methods to predict water table fluctuations has significantly gained momentum. In this study, artificial neural network (ANN), fuzzy logic (FL), adaptive neuro-fuzzy inference system (ANFIS), and least square support vector machine (SVM) methods were utilized to predict groundwater level (GWL) with 1-, 2-, and 3-month lead time in Tehran-Karaj plain. Several input scenarios were developed considering groundwater levels, average temperature, total precipitation, total evapotranspiration, and average river flow on a monthly interval. The four error criteria, the correlation coefficient (R), root mean squared error (RMSE), Nash–Sutcliffe efficiency (NSE), and mean absolute error (MAE), were the basis to evaluate the models. Results showed that all the applied methods could provide acceptable GWL prediction, but the ANFIS was the most accurate. However, the ANFIS model showed slightly better performance by yielding R = 0.98 for the training stage and R = 0.98 for the testing stage in the P84 observation well and the second combination of inputs and 1-month lead time. The outcomes also revealed that all the approaches mentioned above could appropriately predict GWL for the leading time of 1 and 2 months, but the models provided unsatisfactory results for a 3-month leading time.
Study area in Pokot Central with the location of roads, settlements, and water sources. The study’s base was at Marich Pass Field Studies Centre (MPFSC)
Schematics of assessing the impact on vegetation structures. a The focus area was divided into four quadrants to support comparison within it. b Ten concentric rings were drawn around each (KBM/reference or homestead) plot centre (i) and the mean vegetation density or the SAVI within each buffering (e.g. ii, iii, and iv) extracted from the base layer
Distribution of KBMs, homesteads, and reference plots within the focus area. a distribution of the plot centres across the focus area, the examples b–f are indicated as circled dots. b Aerial view and ground photo from a homestead. c–f Aerial view and ground photo of KBM and surroundings at KBM plots in the four LULC classes, sparsely vegetated (c), open woodland (d), closed woodland (e), and thicket (f). Note that ground images were taken shortly after rainy season and UAS image acquisition was during dry season, which results in more herbal vegetation cover in the ground photos
Mean vegetation density in relation to distance from plot centre. For KBM (a, c, e, g) and reference plots (b, d, f, h). The plots’ centres are located within the LULC class sparsely vegetated (a, b), open woodland (c, d), closed woodland (e, f), and thicket (g, h). The graphs show the mean vegetation density (solid green line), standard deviation (dotted grey line), and the values from the example plots (blue, pink lines) between the plots’ centre and up to 50-m distance in 5-m steps
Other factors impacting vegetation characteristics. Percentage of mapped Kiln burn marks, footpaths, and homesteads (y-axis) in each of the four quadrants of the focus area in relation to the mean vegetation density (x-axis). While most kiln burn marks are located in Q4, it has the second highest mean vegetation density. Q1 with the fewest KBMs has the highest mean vegetation density but also the fewest homesteads and footpaths. Most homesteads and footpaths are located in Q3. This quadrant also has the lowest mean vegetation density and also the second lowest number of KBMs. Negative linear trends (dashed lines) exist between mean vegetation density and number of homesteads as well as footpaths. There is a weak positive correlation between mean vegetation density and number of kiln burn marks
In many regions of Sub-Saharan Africa, charcoal plays an important role as energy source but is widely perceived as a major driver of deforestation and forest degradation. This narrative, however, is mostly based on research within primary production regions. Though space-borne remote sensing applications can be useful in monitoring such large-scale production modes, environmental effects of household-level production are less easy to assess. Therefore, the present study employs an unmanned aerial system (UAS) to assess the impact of small-scale charcoal production on the vegetation density in the immediate vicinity of production sites. The UAS data was complemented by field measurements and very high-resolution WordView-2 satellite imagery. This approach revealed only small differences between charcoal production sites and reference plots which were usually evened out after 20–25-m distance to the plot centre using a concentric ring analysis. Results further show that a distinction between different land-use practices is difficult, even with the high spatial resolution provided by a UAS. Thus, more research and new approaches are needed to evaluate the role of small-scale charcoal production in deforestation and forest degradation processes against the background of other human activities. However, to exploit the full potential of UAS for monitoring environmental effects in charcoal producing areas, official regulations need to be clearer and more reliable.
Carbon emissions and economic growth are two contradictions in urban development, and their decoupling is related to the sustainable development of cities. This paper took urban agglomeration in the middle reaches of the Yangtze River (UAMRYR), China, as the study area. The Kaya model, the Tapio decoupling model, and the Logarithmic Mean Divisia Index (LMDI) model were adopted to analyze the spatiotemporal differentiation of carbon emissions, the decoupling of economic activities, and driving factors. The results indicate that (1) carbon emissions increased by 66% in the study period, but the growth momentum was curbed after 2015. Low level and medium level areas continue to decrease, and relatively high level area gradually become dominant. (2) Spatially, carbon emissions are in a pattern of middle-hot and east-cold. Jiangxi is in the sub-cold and coldspot area, while the hotspot area is driven by the transformation from Wuhan’s single-core to Wuhan and Changsha’s dual-core. (3) Since 2010, most cities have been in a good decoupling state, and weak decoupling cities have risen from 35.5% in the initial period to 87.1% in 2010–2011, but the decoupling situation of industrial cities with more high-energy-consuming industries still rebounded slightly. (4) The economic level and energy intensity effect had the most significant impact on the economic decoupling of carbon emissions, whose absolute contribution rates were greater than 35%. Urbanization and economic level both play a positive role in promoting carbon emissions, and the energy intensity plays a negative role in retarding carbon emissions. The population effect was mainly manifested in carbon increase from 2006 to 2011, and 45.2% of the cities from 2011 to 2017 turned into carbon suppression. Finally, we suggest that decoupling carbon emissions from economic growth requires developing green urbanization and a decarbonized economy, optimizing the structure of energy consumption and guiding rational population flow.
Land subsidence problems have become increasingly prominent. Traditional monitoring methods, such as level measurements, have high costs and low efficiency. Permanent scatterer interferometric synthetic aperture radar (PS-InSAR) has several advantages for land subsidence monitoring based on technological innovations. Aimed at resolving the key problems associated with PS-InSAR technology, the accuracy of three external digital elevations models (DEMs, namely, SRTM, ASTER GDEM, and PleiadesDEM) was analysed and compared. We found that the introduction of ground control points can significantly improve the elevation accuracy of DEMs. Herein, we introduce the specific processing steps and selection of the key parameters for IN-SAR data using the StaMPS software. We discuss the differences between IN-SAR technology and levelling measurements as well as the influence that the different external DEMs have on IN-SAR data. Based on 36 scenes of TerraSAR-X images, we obtained results for land deformation monitoring in Taiyuan City using PS-InSAR technology, which provided satisfactory monitoring results.
The fluctuation in the river ecosystem network due to climate change-induced global warming affects aquatic organisms, water quality, and other ecological processes. Assessment of climate change-induced global warming impacts on regional hydrological processes is vital for effective water resource management and planning. The global warming efect on river water quality has been analyzed in this work. The river Ganga stretch near the Varanasi region has been chosen as the study area for this analysis. The air temperature has been predicted using the seasonal autoregressive integrated moving average (SARIMA) and the Prophet model. The Prophet model has shown better accuracy with a root mean square percent error (RMSPE) value of 3.2% compared to the SARIMA model, which has an RMPSE value of 7.54%. The river temperature, turbidity, and nighttime radiance values have been predicted for the years 2022 and 2025 using the long short-term memory (LSTM) algorithm. The anthropogenic effect on the river has been evaluated by using the nighttime radiance imageries. The predicted average river temperature shows an increment of 0.58 °C and 0.63 °C for the city and non-city river stretches, respectively, in 2025 compared to 2022. Similarly, the river turbidity shows an increment of 1.21 nephelometric turbidity units (NTU) and 1.17 NTU for the city and non-city stretch, respectively, in 2025 compared to 2022. For future predicted years, the nighttime radiance values for the region situated near the city river stretch show a significant rise compared to the region that lies nearby the non-city river stretch.
Map of sample collection areas of Punjab
Chromatograms of aflatoxins standards of 25 µg kg⁻¹ (a) and 50 µg kg⁻¹ (b)
Chromatograms of Ochratoxin-A standards of 25 µg kg⁻¹ (a) and 50 µg kg⁻¹ (b)
Effect of gamma irradiation (a), sunlight (b) ultraviolet (c) and microwave (d) treatments on the reduction of AFB1, total AFs and OTA. Bars of each type of aflatoxins showing different alphabet(s) are statistically different from each other at p<0.05
Effect of activated charcoal (a) and bentonite (b) adsorbents on the reduction of AFB1, total AFs and OTA. Bars of each type of aflatoxins showing different alphabet(s) are statistically different from each other at p<0.05.
The contamination of food commodities with mycotoxins could be a serious health threat to humans and animals. Therefore, identification, quantification and reduction of mycotoxins in food commodities, particularly of aflatoxins (AFs) and ochratoxin A (OTA) in grain foods, is essentially required to guarantee safe food. This study determined the levels of AFs and OTA in 135 maize grains samples belonging to eight salient maize varieties cultivated in Pakistan, and evaluated the usefulness of radiations and adsorbents to reduce their levels. High performance liquid chromatography (HPLC)-based method was validated for the determination of AFs and OTA in maize grains. The results showed that 69 and 61% samples were positive for AFs and OTA, respectively and 54 and 22% of the respective samples had AFs and OTA above the permissible limits set by Pakistan Standards and Quality Control Authority. The concentration of AFs, AFB1and OTA in grains ranged from 14.5 to 92.4, 1.02 to 2.46 and 1.41 to 53.9 μg kg⁻¹, respectively. Among the varieties, Pearl had the highest level of total AFs and OTA, whereas YH-5427 had the highest AFB1 level. The lowest concentration of AFs and OTA was found in Malaka and 30Y87, respectively. The use of 15 kGy gamma irradiation for 24 h, sunlight-drying for 20 h and UV irradiation for 12 h almost completely degraded the mycotoxins. The microwave heating for 120 s resulted in 9–33% degradation of mycotoxins. Moreover, the treatment of grains’ extract with activated charcoal (5% w/w) removed > 96% of total AFs and AFB1, and up to 43% of OTA. The use of bentonite at the same rate removed OTA, total AFs and AFB1 by 93, 73 and 92%, respectively. Thus, it is concluded that contamination of maize grains with mycotoxins was fairly high in the collected maize grain samples in Pakistan, and treatment with radiations and adsorbents can effectively reduce mycotoxins contamination level in maize grains.
the reduction of habitat integrity and canopy cover will lead to a lower richness of the Zygoptera sub-order, due to the restrictions of its thermoregulation and oviposition behavior in relation to Anisoptera, since the higher light input would favor heliother-mic and exophytic species; (3) alterations in habitat integrity create ecological thresholds and points of change in the abundance and frequency of Odonata species, generating gradients in the environmental integrity conditions. Specimens were collected from 24 streams (first to third order), in a gradient of land uses. Canopy cover and stream width were predictors of taxonomic richness and abundance of the subor-ders Anisoptera and Zygoptera, with greater coverage and smaller width, positively affecting Zygop-tera and negatively Anisoptera. The turning points were determined by a habitat integrity index, where below 0.38 there is an increase in generalist taxa and Abstract Aquatic ecosystems are affected by different land uses that modify gradients of environmental conditions. These impacts act directly on the community structure, especially the most sensitive ones, such as aquatic insects. Thus, dragonflies have been used as good models to assess these changes, since their suborders Anisoptera and Zygoptera have different ecophysiological and behavioral requirements. This study aimed to evaluate the following hypotheses: (1) dragonfly species composition differs along the environmental gradients of streams; therefore, we expect a higher proportion of species of the suborder Anisop-tera in environments with a higher degree of disturbance , since these environmental conditions select heliothermic species with exophytic oviposition; (2) Supplementary Information The online version contains supplementary material available at https:// doi. a decline in sensitive taxa. On the other hand, above 0.79, there was a sensitive taxa increase in detriment of generalists. Four individual taxa indicators were selected, two of which associated with a negative response (Perithemis tenera and Acanthagrion aepi-olum) and two with positive responses (Epipleoneura metallica and Zenithoptera lanei) for habitat integrity. Our results are important to guide management strategies, recovery, and protection policies for areas of permanent protection, aiming to conserving biodiversity and natural resources essential to life quality maintenance.
Top-cited authors
Mehmet Çetin
  • Ondokuz Mayıs Üniversitesi
Ghada M.S. Abrahim
Hakan Sevik
  • Kastamonu Üniversitesi
Chidambaram Sabarathinam
  • Kuwait Institute for Scientific Research
Elango Lakshmanan
  • Anna University, Chennai