Microplastics have been noticed as widespread in an aquatic environment at the microscale. They have nonstop increased due to the increase in the production of synthetic plastics, population and poor waste management. They are ubiquitous in nature and slowly degrade in water and soil. They are emerging pollutants that have received interest from public audiences and research communities. They have great stability and can adsorb various other pollutants like pesticides, heavy metals, etc. After entering the freshwater environment, microplastics can be stored in the tissue of organisms and stay for a long time. They can generate a serious threat to freshwater ecosystems and can cause physical damage to organisms. Visual identification, Raman spectroscopy, pyrolysis–gas chromatography–mass spectrometry (Pyro–GC–MS), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and combined methods are the commonly known methods for the quantification and identification of microplastics. The detected concentration of microplastics depends on the sampling method, locations and identification techniques. The authors assessed the sources, transport, impacts, identification and characterization, and treatment of microplastics in freshwater environments in detail. The authors are also giving some recommendations for the minimization of the MPs from the freshwater environment. This review article will provide the baseline facts for the investigators to do more research on microplastic pollution in the future.
{"title":"Microplastic contamination, an emerging threat to the freshwater environment: a systematic review","authors":"Laxmi Kant Bhardwaj, Prangya Rath, Poornima Yadav, Urvashi Gupta","doi":"10.1186/s40068-024-00338-7","DOIUrl":"https://doi.org/10.1186/s40068-024-00338-7","url":null,"abstract":"Microplastics have been noticed as widespread in an aquatic environment at the microscale. They have nonstop increased due to the increase in the production of synthetic plastics, population and poor waste management. They are ubiquitous in nature and slowly degrade in water and soil. They are emerging pollutants that have received interest from public audiences and research communities. They have great stability and can adsorb various other pollutants like pesticides, heavy metals, etc. After entering the freshwater environment, microplastics can be stored in the tissue of organisms and stay for a long time. They can generate a serious threat to freshwater ecosystems and can cause physical damage to organisms. Visual identification, Raman spectroscopy, pyrolysis–gas chromatography–mass spectrometry (Pyro–GC–MS), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and combined methods are the commonly known methods for the quantification and identification of microplastics. The detected concentration of microplastics depends on the sampling method, locations and identification techniques. The authors assessed the sources, transport, impacts, identification and characterization, and treatment of microplastics in freshwater environments in detail. The authors are also giving some recommendations for the minimization of the MPs from the freshwater environment. This review article will provide the baseline facts for the investigators to do more research on microplastic pollution in the future. ","PeriodicalId":12037,"journal":{"name":"Environmental Systems Research","volume":"166 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140011083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The problem of soil quality degradation has been becoming more severe in the highlands of Ethiopia due to soil erosion; land use and land cover change, and poor land management. The level of soil quality degradation was not well known and documented in the study area and the results of this study could provide new information to improve soil conditions. The present study was conducted to evaluate soil quality in terms of its physical and chemical fertility under different land use types in the Suha watershed, northwestern highlands of Ethiopia. A total of 27 composite surface soil samples (0–30 cm) were collected from adjacently located land-uses in three replications from two elevation gradients. Standard procedures were followed to analyze selected soil physical and chemical quality indicators. The differences in the mean values of the parameters were tested using a two-way analysis of variance. In addition, Soil Quality Degradation Index was evaluated to see the direction and magnitude of change in soil quality indicators. The analysis of variance results revealed that soil quality indicators such as index of soil aggregate stability, organic carbon (OC), total nitrogen (TN), and C:N ratio were significantly decreased in the cultivated land use system compared to other land use systems. On the other hand, the content of available Phosphorus was significantly higher in the cultivated land. Soil quality deterioration index values were highly negative for SOC (− 71.3%) and TN (− 67.7%) in the cultivated land, followed by grazing land (SOM = − 35.5% and TN = − 27.7%). Aggregated Soil Quality Index values also indicated that the status of soil quality under cultivated fields is rated as low, grazing land as optimal, and forest land as high. Generally, results indicated that land use and cover changes had adverse effects on soil quality indicators. Hence, soil management strategies, mainly Integrated Soil Fertility Management which integrates soil and water conservation strategies, are required to alleviate the problem of soil quality deterioration and improve agricultural productivity.
{"title":"Monitoring soil quality of different land use systems: a case study in Suha watershed, northwestern highlands of Ethiopia","authors":"Nigussie Yeneneh, Eyasu Elias, Gudina Legese Feyisa","doi":"10.1186/s40068-024-00336-9","DOIUrl":"https://doi.org/10.1186/s40068-024-00336-9","url":null,"abstract":"The problem of soil quality degradation has been becoming more severe in the highlands of Ethiopia due to soil erosion; land use and land cover change, and poor land management. The level of soil quality degradation was not well known and documented in the study area and the results of this study could provide new information to improve soil conditions. The present study was conducted to evaluate soil quality in terms of its physical and chemical fertility under different land use types in the Suha watershed, northwestern highlands of Ethiopia. A total of 27 composite surface soil samples (0–30 cm) were collected from adjacently located land-uses in three replications from two elevation gradients. Standard procedures were followed to analyze selected soil physical and chemical quality indicators. The differences in the mean values of the parameters were tested using a two-way analysis of variance. In addition, Soil Quality Degradation Index was evaluated to see the direction and magnitude of change in soil quality indicators. The analysis of variance results revealed that soil quality indicators such as index of soil aggregate stability, organic carbon (OC), total nitrogen (TN), and C:N ratio were significantly decreased in the cultivated land use system compared to other land use systems. On the other hand, the content of available Phosphorus was significantly higher in the cultivated land. Soil quality deterioration index values were highly negative for SOC (− 71.3%) and TN (− 67.7%) in the cultivated land, followed by grazing land (SOM = − 35.5% and TN = − 27.7%). Aggregated Soil Quality Index values also indicated that the status of soil quality under cultivated fields is rated as low, grazing land as optimal, and forest land as high. Generally, results indicated that land use and cover changes had adverse effects on soil quality indicators. Hence, soil management strategies, mainly Integrated Soil Fertility Management which integrates soil and water conservation strategies, are required to alleviate the problem of soil quality deterioration and improve agricultural productivity.","PeriodicalId":12037,"journal":{"name":"Environmental Systems Research","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139926774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-12DOI: 10.1186/s40068-024-00333-y
Simeneh Gedefaw Abate, Mihret Bizuye Anteneh
This research aimed at evaluation of a given land resource suitable for selected rain fed crops production (malt barley, wheat and teff) in Ambesh watershed. It also quantified suitable land and classified into the land mapping units (LMUs), and presents a land suitability map. Land suitability assessment (LSA) made using climatic condition, topography, soil physical and chemical properties as a major factor integrated with a multi criteria decision making (MCDM) analysis in Ambesh watershed. Fourteen composite soil samples were taken by categorizing the watershed into different land mapping units (LMUs) and analyzed in a soil laboratory. Climatic data, rainfall was obtained from two meteorological stations nearby to the study area. Temperature data derived from Landsat 8 satellite thermal bands data. Data obtained from the soil laboratory and others were finally analyzed using ArcGIS environment and priority estimation tool (PriEsT) software’s. Weighted Sum Overlay was implemented to investigate the final LSA map of the watershed. Results revealed that LMUs, VRe–LPq and LPK.Pq–FLc LMUs has higher overall suitability for all the selected rain fed crops. However, LMUs (VRe–NTu and NTu–VRe) has lower overall suitability values particularly for S1 suitability class (0.05% and 10.6%, respectively). The least suitable LMU is VRe–NTu with 0.05% S1 suitability class and above 99% of the land laid under the suitability classes of moderately suitable, marginally suitable and not suitable for the selected land utilization types. Moreover, about 219.06 ha (17.76%), 217.6 ha (17.64%), 168.9 ha (13.7%), of land are highly suitable for malt barley, teff and wheat crop production, respectively. In conclusion, during MCDM, classifying the land into closer homogeneities (LMU) an important application of LSA integrated with remote sensing and GIS for a better decision making. Meanwhile, majority (above two third’s) of the land in the watershed is under moderate and marginally suitable, it needs intensive land management activities to increase the land qualities and obtain high yields. LSA recommended before land utilization decision has to be made. It is also important to classifying the land into LMUs to make it more homogeneous for sample taking and reducing the prestigious soil laboratory analysis costs.
{"title":"Assessment of agricultural land suitability for cereal crops based on the analysis of soil physico-chemical characteristics","authors":"Simeneh Gedefaw Abate, Mihret Bizuye Anteneh","doi":"10.1186/s40068-024-00333-y","DOIUrl":"https://doi.org/10.1186/s40068-024-00333-y","url":null,"abstract":"This research aimed at evaluation of a given land resource suitable for selected rain fed crops production (malt barley, wheat and teff) in Ambesh watershed. It also quantified suitable land and classified into the land mapping units (LMUs), and presents a land suitability map. Land suitability assessment (LSA) made using climatic condition, topography, soil physical and chemical properties as a major factor integrated with a multi criteria decision making (MCDM) analysis in Ambesh watershed. Fourteen composite soil samples were taken by categorizing the watershed into different land mapping units (LMUs) and analyzed in a soil laboratory. Climatic data, rainfall was obtained from two meteorological stations nearby to the study area. Temperature data derived from Landsat 8 satellite thermal bands data. Data obtained from the soil laboratory and others were finally analyzed using ArcGIS environment and priority estimation tool (PriEsT) software’s. Weighted Sum Overlay was implemented to investigate the final LSA map of the watershed. Results revealed that LMUs, VRe–LPq and LPK.Pq–FLc LMUs has higher overall suitability for all the selected rain fed crops. However, LMUs (VRe–NTu and NTu–VRe) has lower overall suitability values particularly for S1 suitability class (0.05% and 10.6%, respectively). The least suitable LMU is VRe–NTu with 0.05% S1 suitability class and above 99% of the land laid under the suitability classes of moderately suitable, marginally suitable and not suitable for the selected land utilization types. Moreover, about 219.06 ha (17.76%), 217.6 ha (17.64%), 168.9 ha (13.7%), of land are highly suitable for malt barley, teff and wheat crop production, respectively. In conclusion, during MCDM, classifying the land into closer homogeneities (LMU) an important application of LSA integrated with remote sensing and GIS for a better decision making. Meanwhile, majority (above two third’s) of the land in the watershed is under moderate and marginally suitable, it needs intensive land management activities to increase the land qualities and obtain high yields. LSA recommended before land utilization decision has to be made. It is also important to classifying the land into LMUs to make it more homogeneous for sample taking and reducing the prestigious soil laboratory analysis costs.","PeriodicalId":12037,"journal":{"name":"Environmental Systems Research","volume":"138 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139761993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-05DOI: 10.1186/s40068-024-00332-z
Gemechis B. Mosisa, Nega Tassie, Motuma Adula
Eucalyptus globulus is a species endemic to southeastern Australia. It has naturalized non-native ranges in other parts of Australia, Europe, Africa, and the western United States. This study is the first of its kind in Ethiopia to model and map the spatiotemporal distribution of the species using species distribution models (SDMs). A total of 874 occurrence records were used from the online Global Biodiversity Information Facility (GBIF) database and field observation. Three environmental variables, including terrain, climate, and soil were used to predict the species’ distribution. The terrain, climate, and soil raster grids were resampled to a 200-meter resolution. The Global Circulation Model (GCM) HadGEM3-GC3.1 was used to extract future climate data. This GCM has a good match between the atmospheric and oceanic components showing little drift in its surface climate. Besides, it has the best coverage of Africa. Three climate change scenarios (SSPs 1-2.6, SSPs 2-4.5, and SSPs 5-8.5) were used for predicting suitable habitat of the species. The jackknife test was chosen to assess the importance of each environmental predictor variable. The model’s performance was evaluated using the Area under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve. The model had excellent predictive performance with an average AUC of 0.94. Altitude, rooting conditions, slope, dry-month precipitation, and temperature seasonality are the most important environmental factors in shaping E. globulus distribution. Ethiopian highlands are predicted to be more suitable to the species, but the increase in temperature seasonality may reduce suitable habitat under the high-forcing climate change scenario. Climate change is expected to create more suitable habitats for eucalyptus in the future which may encourage plantations in potential distribution areas. Consequently, ensuring long-term forest health necessitates robust management systems prioritizing native trees and responsible grower or farmer practices.
{"title":"Current and future distribution of Eucalyptus globulus under changing climate in Ethiopia: implications for forest management","authors":"Gemechis B. Mosisa, Nega Tassie, Motuma Adula","doi":"10.1186/s40068-024-00332-z","DOIUrl":"https://doi.org/10.1186/s40068-024-00332-z","url":null,"abstract":"Eucalyptus globulus is a species endemic to southeastern Australia. It has naturalized non-native ranges in other parts of Australia, Europe, Africa, and the western United States. This study is the first of its kind in Ethiopia to model and map the spatiotemporal distribution of the species using species distribution models (SDMs). A total of 874 occurrence records were used from the online Global Biodiversity Information Facility (GBIF) database and field observation. Three environmental variables, including terrain, climate, and soil were used to predict the species’ distribution. The terrain, climate, and soil raster grids were resampled to a 200-meter resolution. The Global Circulation Model (GCM) HadGEM3-GC3.1 was used to extract future climate data. This GCM has a good match between the atmospheric and oceanic components showing little drift in its surface climate. Besides, it has the best coverage of Africa. Three climate change scenarios (SSPs 1-2.6, SSPs 2-4.5, and SSPs 5-8.5) were used for predicting suitable habitat of the species. The jackknife test was chosen to assess the importance of each environmental predictor variable. The model’s performance was evaluated using the Area under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve. The model had excellent predictive performance with an average AUC of 0.94. Altitude, rooting conditions, slope, dry-month precipitation, and temperature seasonality are the most important environmental factors in shaping E. globulus distribution. Ethiopian highlands are predicted to be more suitable to the species, but the increase in temperature seasonality may reduce suitable habitat under the high-forcing climate change scenario. Climate change is expected to create more suitable habitats for eucalyptus in the future which may encourage plantations in potential distribution areas. Consequently, ensuring long-term forest health necessitates robust management systems prioritizing native trees and responsible grower or farmer practices.","PeriodicalId":12037,"journal":{"name":"Environmental Systems Research","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139688792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-05DOI: 10.1186/s40068-024-00335-w
Shaon Kumar Das
By expanding the surface area and/or by other chemical reactions, soil additives such as biochar help retain nutrients in the soil. n this work, the effects of biochar on the adsorption and desorption of heavy metals and soil elements necessary for plant growth were investigated. To illustrate the adsorption of nutrients and heavy metals from solution on biochar, the Freundlich isotherm was employed. The rise in mineral nutrients, pH, and EC was linked to an increase in CEC with warmth. Because of its high CEC, biochar improves soil health and increases plant nutrient availability, which can boost agricultural yield when applied to the soil. In manure + biochar at 2.5 + 7.5 t/ha application rate the NH4+-N adsorption capacity was minimum in T7 (15.9 and 117.66) followed by T4 (17.6 and 130.24), T13 (18.7 and 138.38) and maximum in T10 (20.1 and 148.74) at 25 and 200 mg kg-1 level of added NH4+-N, respectively than control T1 (10.3 and 75.3). An increase in the rate of biochar application led to a favourable effect by increasing the NO3–N adsorption capability. The effect on P adsorption was more with biochar than manures. In manure + biochar at 2.5 + 7.5 t/ha application rate the Pb adsorption capacity was minimum in T7 (4.46 and 30.77) followed by T10 (4.71 and 32.49), T13 (5.16 and 35.60) and maximum in T4 (5.48 and 37.81) at 10 and 100 mg kg-1 level of added Pb, respectively than control T1 (1.86 and 12.83). Goat manure, FYM, vermicompost, and poultry manure had the greatest effects on desorption. The desorption of all heavy metals Cd, Pb, Zn, and As decreased as the rate of biochar application increased. Based on excess nutrients and heavy metals, this study supports the use of biochar to mitigate environmental concerns.
{"title":"Adsorption and desorption capacity of different metals influenced by biomass derived biochar","authors":"Shaon Kumar Das","doi":"10.1186/s40068-024-00335-w","DOIUrl":"https://doi.org/10.1186/s40068-024-00335-w","url":null,"abstract":"By expanding the surface area and/or by other chemical reactions, soil additives such as biochar help retain nutrients in the soil. n this work, the effects of biochar on the adsorption and desorption of heavy metals and soil elements necessary for plant growth were investigated. To illustrate the adsorption of nutrients and heavy metals from solution on biochar, the Freundlich isotherm was employed. The rise in mineral nutrients, pH, and EC was linked to an increase in CEC with warmth. Because of its high CEC, biochar improves soil health and increases plant nutrient availability, which can boost agricultural yield when applied to the soil. In manure + biochar at 2.5 + 7.5 t/ha application rate the NH4+-N adsorption capacity was minimum in T7 (15.9 and 117.66) followed by T4 (17.6 and 130.24), T13 (18.7 and 138.38) and maximum in T10 (20.1 and 148.74) at 25 and 200 mg kg-1 level of added NH4+-N, respectively than control T1 (10.3 and 75.3). An increase in the rate of biochar application led to a favourable effect by increasing the NO3–N adsorption capability. The effect on P adsorption was more with biochar than manures. In manure + biochar at 2.5 + 7.5 t/ha application rate the Pb adsorption capacity was minimum in T7 (4.46 and 30.77) followed by T10 (4.71 and 32.49), T13 (5.16 and 35.60) and maximum in T4 (5.48 and 37.81) at 10 and 100 mg kg-1 level of added Pb, respectively than control T1 (1.86 and 12.83). Goat manure, FYM, vermicompost, and poultry manure had the greatest effects on desorption. The desorption of all heavy metals Cd, Pb, Zn, and As decreased as the rate of biochar application increased. Based on excess nutrients and heavy metals, this study supports the use of biochar to mitigate environmental concerns.","PeriodicalId":12037,"journal":{"name":"Environmental Systems Research","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139762527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-24DOI: 10.1186/s40068-023-00329-0
Hana Melese, Habte Jebessa Debella
We investigated the spatio-temporal dynamics of phytoplankton composition, chlorophyll-a as a proxy for algal biomass, and abundance in relation to environmental parameters in four Ethiopian soda lakes: Arenguade, Beseka, Chittu, and Shala. Triplicate water samples were collected from each lake from January to December 2020, four times in different seasons. Lake Chittu had the highest chlorophyll-a concentration, followed by Lake Arenguade, Beseka and Shala. Chlorophyll-a concentrations generally increased during the post rainy and dry season. The results of LR models are high for lakes Arengude, Beseka and Chittu. Lakes Shala and Beseka had the highest number of phytoplankton taxa, with both taxa composition and abundance dominated by Bacillariophyceae. Cyanoprokaryota, particularly Limnospira fusiformis, predominated in the abundance of Lakes Arenguade and Chittu. Water temperature, Secchi depth, turbidity, electrical conductivity, soluble reactive phosphorus, nitrate and silica significantly influenced the phytoplankton community structure. Long-term trend analysis revealed changes in phytoplankton biomass and lake taxonomic composition. The alteration in phytoplankton biomass and species composition of the lakes could be attributed to three factors: (1) frequent high-velocity explosions conducted for seismological studies in the past. This impact caused a dramatic increase in lake level in the case of Lake Beseka leading to a drop in nutrient concentration; (2) climate change and (3) salt content. Overall, our findings suggest that phytoplankton composition, biomass, and abundance varied according to seasonal fluctuations, emphasizing the possible effects of anthropogenic and natural causes on their community structure.
{"title":"Temporal phytoplankton dynamics and environmental variables in four Ethiopian soda lakes","authors":"Hana Melese, Habte Jebessa Debella","doi":"10.1186/s40068-023-00329-0","DOIUrl":"https://doi.org/10.1186/s40068-023-00329-0","url":null,"abstract":"We investigated the spatio-temporal dynamics of phytoplankton composition, chlorophyll-a as a proxy for algal biomass, and abundance in relation to environmental parameters in four Ethiopian soda lakes: Arenguade, Beseka, Chittu, and Shala. Triplicate water samples were collected from each lake from January to December 2020, four times in different seasons. Lake Chittu had the highest chlorophyll-a concentration, followed by Lake Arenguade, Beseka and Shala. Chlorophyll-a concentrations generally increased during the post rainy and dry season. The results of LR models are high for lakes Arengude, Beseka and Chittu. Lakes Shala and Beseka had the highest number of phytoplankton taxa, with both taxa composition and abundance dominated by Bacillariophyceae. Cyanoprokaryota, particularly Limnospira fusiformis, predominated in the abundance of Lakes Arenguade and Chittu. Water temperature, Secchi depth, turbidity, electrical conductivity, soluble reactive phosphorus, nitrate and silica significantly influenced the phytoplankton community structure. Long-term trend analysis revealed changes in phytoplankton biomass and lake taxonomic composition. The alteration in phytoplankton biomass and species composition of the lakes could be attributed to three factors: (1) frequent high-velocity explosions conducted for seismological studies in the past. This impact caused a dramatic increase in lake level in the case of Lake Beseka leading to a drop in nutrient concentration; (2) climate change and (3) salt content. Overall, our findings suggest that phytoplankton composition, biomass, and abundance varied according to seasonal fluctuations, emphasizing the possible effects of anthropogenic and natural causes on their community structure.","PeriodicalId":12037,"journal":{"name":"Environmental Systems Research","volume":"255 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139553486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-09DOI: 10.1186/s40068-023-00328-1
Shimelash Molla Kassaye, Tsegaye Tadesse, Getachew Tegegne, Aster Tesfaye Hordofa
Extreme hydrological events, like floods and droughts, exert considerable effects on both human and natural systems. The frequency, intensity, and duration of these events are expected to change due to climate change, posing challenges for water resource management and adaptation. In this study, the Soil and Water Assessment Tool plus (SWAT +) model was calibrated and validated to simulate flow under future shared socioeconomic pathway (SSP2-4.5 and SSP5-8.5) scenarios in the Baro River Basin with R2 values of 0.88 and 0.83, NSE of 0.83 and 0.74, and PBIAS of 0.39 and 8.87 during calibration and validation. Six bias-corrected CMIP6 Global Climate Models (GCM) were selected and utilized to investigate the effects of climate change on the magnitude and timing of hydrological extremes. All climate model simulation results suggest a general increase in streamflow magnitude for both emission scenarios (SSP2-4.5 and SSP5-8.5). The multi-model ensemble projections show yearly flow increases of 4.8% and 12.4% during the mid-term (MT) (2041–2070) and long-term (LT) (2071–2100) periods under SSP2-4.5, and 15.7% and 35.6% under SSP5-8.5, respectively. Additionally, the analysis revealed significant shifts in the projected annual 1 day, 3 day, 7 day, and 30 day maximum flows, whereas the annual 3 day and 7 day minimum flow fluctuations do not present a distinct trend in the future scenario compared to the baseline (1985–2014). The study also evaluated the timing of hydrological extremes, focusing on low and peak flow events, utilizing the annual 7 day maximum and minimum flow for this analysis. An earlier occurrence was noted for both peak and low flow in the SSP2-4.5 scenario, while a later occurrence was observed in the SSP5-8.5 scenario compared to the baseline. In conclusion, this study showed the significant effect of climate change on river hydrology and extreme flow events, highlighting their importance for informed water management and sustainable planning.
{"title":"Quantifying the climate change impacts on the magnitude and timing of hydrological extremes in the Baro River Basin, Ethiopia","authors":"Shimelash Molla Kassaye, Tsegaye Tadesse, Getachew Tegegne, Aster Tesfaye Hordofa","doi":"10.1186/s40068-023-00328-1","DOIUrl":"https://doi.org/10.1186/s40068-023-00328-1","url":null,"abstract":"Extreme hydrological events, like floods and droughts, exert considerable effects on both human and natural systems. The frequency, intensity, and duration of these events are expected to change due to climate change, posing challenges for water resource management and adaptation. In this study, the Soil and Water Assessment Tool plus (SWAT +) model was calibrated and validated to simulate flow under future shared socioeconomic pathway (SSP2-4.5 and SSP5-8.5) scenarios in the Baro River Basin with R2 values of 0.88 and 0.83, NSE of 0.83 and 0.74, and PBIAS of 0.39 and 8.87 during calibration and validation. Six bias-corrected CMIP6 Global Climate Models (GCM) were selected and utilized to investigate the effects of climate change on the magnitude and timing of hydrological extremes. All climate model simulation results suggest a general increase in streamflow magnitude for both emission scenarios (SSP2-4.5 and SSP5-8.5). The multi-model ensemble projections show yearly flow increases of 4.8% and 12.4% during the mid-term (MT) (2041–2070) and long-term (LT) (2071–2100) periods under SSP2-4.5, and 15.7% and 35.6% under SSP5-8.5, respectively. Additionally, the analysis revealed significant shifts in the projected annual 1 day, 3 day, 7 day, and 30 day maximum flows, whereas the annual 3 day and 7 day minimum flow fluctuations do not present a distinct trend in the future scenario compared to the baseline (1985–2014). The study also evaluated the timing of hydrological extremes, focusing on low and peak flow events, utilizing the annual 7 day maximum and minimum flow for this analysis. An earlier occurrence was noted for both peak and low flow in the SSP2-4.5 scenario, while a later occurrence was observed in the SSP5-8.5 scenario compared to the baseline. In conclusion, this study showed the significant effect of climate change on river hydrology and extreme flow events, highlighting their importance for informed water management and sustainable planning.","PeriodicalId":12037,"journal":{"name":"Environmental Systems Research","volume":"187 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139415616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-04DOI: 10.1186/s40068-023-00326-3
Joel Onyango, J. J. A. van Bruggen, Nzula Kitaka, John Simaika, Kenneth Irvine
Fertilisers and pesticides are increasingly used in agriculture to improve productivity and protect crops from fungi and insects. However, these farm inputs may lead to adverse effects on aquatic biodiversity through eutrophication and pesticide toxicity. This study aimed to establish the effects of nutrient-only, pesticide-only, combined nutrients and pesticides, and control on the abundance of Daphnia magna, and algal biomass. In each of the treatments, different concentrations of nutrients and pesticides residues were added separately or in combination. Responses were measured every 24 h, and the experiments ended after 168 h of exposure. The experiment was set in four concentration treatments comprising high, moderately high, moderately low, and low concentrations. Data analysis was done using Multiple Analysis of Variance (MANOVA) and ANOVA to determine the effect of time, concentrations and the interaction of time and concentrations for each of the treatments on D. magna abundance, and algal biomass. Higher concentrations of pesticide additives were associated with lower abundance of D. magna, and higher algal biomass over the exposure periods. There was a significant reduction in the abundance of D. magna in the combined treatment indicating the toxic effect of pesticide addition. Determination of effect concentrations based on combined nutrients-pesticides experiments becomes important in setting water quality standards, and monitoring the quality status, to avoid underestimating the ecological implications of combined contamination.
{"title":"Effects of combined nutrient and pesticide exposure on algal biomass, and Daphnia magna abundance","authors":"Joel Onyango, J. J. A. van Bruggen, Nzula Kitaka, John Simaika, Kenneth Irvine","doi":"10.1186/s40068-023-00326-3","DOIUrl":"https://doi.org/10.1186/s40068-023-00326-3","url":null,"abstract":"Fertilisers and pesticides are increasingly used in agriculture to improve productivity and protect crops from fungi and insects. However, these farm inputs may lead to adverse effects on aquatic biodiversity through eutrophication and pesticide toxicity. This study aimed to establish the effects of nutrient-only, pesticide-only, combined nutrients and pesticides, and control on the abundance of Daphnia magna, and algal biomass. In each of the treatments, different concentrations of nutrients and pesticides residues were added separately or in combination. Responses were measured every 24 h, and the experiments ended after 168 h of exposure. The experiment was set in four concentration treatments comprising high, moderately high, moderately low, and low concentrations. Data analysis was done using Multiple Analysis of Variance (MANOVA) and ANOVA to determine the effect of time, concentrations and the interaction of time and concentrations for each of the treatments on D. magna abundance, and algal biomass. Higher concentrations of pesticide additives were associated with lower abundance of D. magna, and higher algal biomass over the exposure periods. There was a significant reduction in the abundance of D. magna in the combined treatment indicating the toxic effect of pesticide addition. Determination of effect concentrations based on combined nutrients-pesticides experiments becomes important in setting water quality standards, and monitoring the quality status, to avoid underestimating the ecological implications of combined contamination.","PeriodicalId":12037,"journal":{"name":"Environmental Systems Research","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139094534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-19DOI: 10.1186/s40068-023-00327-2
Jobaer Ahmed Saju, Quazi Hamidul Bari, Kazi A. B. M. Mohiuddin, Vladimir Strezov
Atmospheric particles have been significantly affecting urban air quality and urban-oriented living in an increasing share of the population in Bangladesh. This study assessed the concentration of PM1.0, PM2.5, and PM10 in Khulna, one of the largest cities in Bangladesh located near the Bay of Bengal. The maximum average concentrations were recorded 415 ± 184.01 µg/m3 for PM10, 302 ± 109.89 µg/m3 for PM2.5, and 143 ± 45.05 µg/m3 for PM1.0. These values are several times higher than the World Health Organization air quality standard and Bangladesh National Ambient Air Quality Standard. According to the size and fractional distribution of PM, most of the monitoring locations were dominated by fine particles. Carcinogenic and non-carcinogenic risks due to exposure to ambient PM1.0, PM2.5 and PM10 were also quantified to illustrate the relevant potential human health risks. The excess lifetime cancer risk (ELCR) values of PM1.0 ranged from 8.6E0–4 to 6.0E–07 and PM2.5 varied between 8.6E–04 and 6.0E–07 exceeded the allowable limit at every location indicating the potential cancer-developing risk to the urban population. The health quotient (HQ) values also crossed the least permissible value at most of the locations depicting strong non-carcinogenic risks. Average HQ values of PM2.5 varied from 1.07 to 20.13 while PM10 ranged from 0.44 to 8.3. This research revealed children and elderly people as the most vulnerable age groups with the highest carcinogenic risks through exposure to atmospheric PM in Khulna city. Therefore, air pollution reduction plans and risk mitigation strategies should be developed and implemented by the government authorities.
{"title":"Measurement of ambient particulate matter (PM1.0, PM2.5 and PM10) in Khulna City of Bangladesh and their implications for human health","authors":"Jobaer Ahmed Saju, Quazi Hamidul Bari, Kazi A. B. M. Mohiuddin, Vladimir Strezov","doi":"10.1186/s40068-023-00327-2","DOIUrl":"https://doi.org/10.1186/s40068-023-00327-2","url":null,"abstract":"Atmospheric particles have been significantly affecting urban air quality and urban-oriented living in an increasing share of the population in Bangladesh. This study assessed the concentration of PM1.0, PM2.5, and PM10 in Khulna, one of the largest cities in Bangladesh located near the Bay of Bengal. The maximum average concentrations were recorded 415 ± 184.01 µg/m3 for PM10, 302 ± 109.89 µg/m3 for PM2.5, and 143 ± 45.05 µg/m3 for PM1.0. These values are several times higher than the World Health Organization air quality standard and Bangladesh National Ambient Air Quality Standard. According to the size and fractional distribution of PM, most of the monitoring locations were dominated by fine particles. Carcinogenic and non-carcinogenic risks due to exposure to ambient PM1.0, PM2.5 and PM10 were also quantified to illustrate the relevant potential human health risks. The excess lifetime cancer risk (ELCR) values of PM1.0 ranged from 8.6E0–4 to 6.0E–07 and PM2.5 varied between 8.6E–04 and 6.0E–07 exceeded the allowable limit at every location indicating the potential cancer-developing risk to the urban population. The health quotient (HQ) values also crossed the least permissible value at most of the locations depicting strong non-carcinogenic risks. Average HQ values of PM2.5 varied from 1.07 to 20.13 while PM10 ranged from 0.44 to 8.3. This research revealed children and elderly people as the most vulnerable age groups with the highest carcinogenic risks through exposure to atmospheric PM in Khulna city. Therefore, air pollution reduction plans and risk mitigation strategies should be developed and implemented by the government authorities. ","PeriodicalId":12037,"journal":{"name":"Environmental Systems Research","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138746061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-12DOI: 10.1186/s40068-023-00325-4
Meaza Kassahun, Kassahun Ture, Dessie Nedaw
Climate models are basic tools to obtain reliable estimates of future climate change and its effects on the water resources and agriculture in given basin. However, all climate models are not equally valuable for all areas. Therefore, determining the most appropriate climate model for a specific study area is essential. This study examines the performance of 10 CORDEX-AFRICA-220 Regional Climate Models (RCMs), three downscaling institutional based ensembles mean (Reg ensemble, CCLM ensemble and REMOO ensemble) and the multi-model ensemble mean. The models were evaluated based on their ability in replicating the seasonal and annual rainfall, minimum and maximum temperature and inter-annual variability for the period of 1986–2005 using statistical metrics such as BIAS, Root Mean Square Error (RMSE), Pearson correlation coefficient (r), coefficient of variation (CV), Kling Gupta Efficiency (KGE) and Taylor diagram. The findings indicated that HadREMOO, MPI-Reg4-7, HadReg4-7, Reg ensemble, and multi-model ensemble mean performed relatively better in representing the mean annual observed rainfall at the Adiramets, Debarik Ketema, Niguse Maystebri, and Zarima stations, respectively. Whereas, NorESM-CCLM, MPI-CCLM, NorESM-Reg4-7, and NorESM-REMOO exhibited a weak performance in reproducing the observed mean annual rainfall at the Adiramets, Debarik Ketema Niguse, Maystebri, and Zarima stations, respectively. Similarly, RCMs generally capture the mean annual maximum temperature of climatic stationsof Zarima subbasin well. Specifically, the MPI-Reg4-7 simulation performs well in representing the mean annual observed maximum temperature at Adiramets and Maytsebri stations, while the Debarik and Ketema Niguse stations exhibit superior performance in the HadReg4-7 simulation and the Zarima station shows better representation in the CCLM ensemble simulations. The majority of the model simulations exhibit good representation of mean annual minimum temperature at Adiramets, Debarik, and Zarima stations. Specifically, CanESM-RCM, HadReg4-7, REMOOensemble, multi-model ensemble, and Regensemble simulations perform better at Adiramets, Debarik, Ketema niguse, Maystebri and Zarima stations respectively. This suggests that these models may have biases or shortcomings in capturing the temperature values in the subbasin. Furthermore, NorESM-CCLM at Adiramets, Ketema niguse, and Zarima stations, NorESM-REMOO at Debarik station, and HadReg4-7 at Maystebri station demonstrate poor performance in representing the observed mean minimum temprature. Majority of the RCMs, all institutional based ensemble means and the multi-model ensemble mean simulations overestimate the observed mean annual rainfall of the Zarima subbasin with minimum bias of 0.02 mm at Ketema niguse HadReg4-7and maximum bias of 2.81 mm at Maytsebri MPI-CCLM simulation. Similarly, HadReg4-7 simulation of Ketama Niguse MPI-CCLM showed a minimum 0.02 mm and Maytsebri simulation kiremit season mean rainfall sho
{"title":"Evaluation of CORDEX Africa regional climate models performance in simulating climatology of Zarima sub-basin northwestern Ethiopia","authors":"Meaza Kassahun, Kassahun Ture, Dessie Nedaw","doi":"10.1186/s40068-023-00325-4","DOIUrl":"https://doi.org/10.1186/s40068-023-00325-4","url":null,"abstract":"Climate models are basic tools to obtain reliable estimates of future climate change and its effects on the water resources and agriculture in given basin. However, all climate models are not equally valuable for all areas. Therefore, determining the most appropriate climate model for a specific study area is essential. This study examines the performance of 10 CORDEX-AFRICA-220 Regional Climate Models (RCMs), three downscaling institutional based ensembles mean (Reg ensemble, CCLM ensemble and REMOO ensemble) and the multi-model ensemble mean. The models were evaluated based on their ability in replicating the seasonal and annual rainfall, minimum and maximum temperature and inter-annual variability for the period of 1986–2005 using statistical metrics such as BIAS, Root Mean Square Error (RMSE), Pearson correlation coefficient (r), coefficient of variation (CV), Kling Gupta Efficiency (KGE) and Taylor diagram. The findings indicated that HadREMOO, MPI-Reg4-7, HadReg4-7, Reg ensemble, and multi-model ensemble mean performed relatively better in representing the mean annual observed rainfall at the Adiramets, Debarik Ketema, Niguse Maystebri, and Zarima stations, respectively. Whereas, NorESM-CCLM, MPI-CCLM, NorESM-Reg4-7, and NorESM-REMOO exhibited a weak performance in reproducing the observed mean annual rainfall at the Adiramets, Debarik Ketema Niguse, Maystebri, and Zarima stations, respectively. Similarly, RCMs generally capture the mean annual maximum temperature of climatic stationsof Zarima subbasin well. Specifically, the MPI-Reg4-7 simulation performs well in representing the mean annual observed maximum temperature at Adiramets and Maytsebri stations, while the Debarik and Ketema Niguse stations exhibit superior performance in the HadReg4-7 simulation and the Zarima station shows better representation in the CCLM ensemble simulations. The majority of the model simulations exhibit good representation of mean annual minimum temperature at Adiramets, Debarik, and Zarima stations. Specifically, CanESM-RCM, HadReg4-7, REMOOensemble, multi-model ensemble, and Regensemble simulations perform better at Adiramets, Debarik, Ketema niguse, Maystebri and Zarima stations respectively. This suggests that these models may have biases or shortcomings in capturing the temperature values in the subbasin. Furthermore, NorESM-CCLM at Adiramets, Ketema niguse, and Zarima stations, NorESM-REMOO at Debarik station, and HadReg4-7 at Maystebri station demonstrate poor performance in representing the observed mean minimum temprature. Majority of the RCMs, all institutional based ensemble means and the multi-model ensemble mean simulations overestimate the observed mean annual rainfall of the Zarima subbasin with minimum bias of 0.02 mm at Ketema niguse HadReg4-7and maximum bias of 2.81 mm at Maytsebri MPI-CCLM simulation. Similarly, HadReg4-7 simulation of Ketama Niguse MPI-CCLM showed a minimum 0.02 mm and Maytsebri simulation kiremit season mean rainfall sho","PeriodicalId":12037,"journal":{"name":"Environmental Systems Research","volume":"309 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138581620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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