Pub Date : 2024-09-11DOI: 10.1007/s13762-024-06006-8
D. D. L. Soren, K. C. Roy, B. Biswas
The study was focused on analyzing the land use and land cover status, change patterns, and future scenarios in the Mayurakshi basin in Jharkhand and West Bengal state of eastern India. The dataset collected for image classification included Landsat 5 (TM) (1991–2008) and Landsat 8 (OLI) (2020). Various sequential preprocessing steps such as atmospheric correction, image enhancement, mosaicking, masking, and clipping were performed using QGIS 3.16 and ArcGIS 10.8 software. The land use and land cover classes found in the study area were water, vegetation, bare land, agriculture, and built-up, and classification was executed by using the Random Forest machine learning algorithm. The accuracy of the classified land use and land cover was validated and accepted with Kappa agreements of 0.89, 0.85, and 0.88 for the years 1991, 2005, and 2020, respectively. Throughout the study period, agriculture emerged as the dominant land use class, followed by vegetation and bare land. The area under the land use and land cover categories of water, vegetation, and bare land continuously decreased between the years 1991–2005 and 2005–2020, while agriculture and built-up areas recorded an increase of 4.49%, 0.76%, 17.81%, and 2.04%, respectively. To project future land use and land cover status, the popular Cellular Automata Markov Chain Model was employed. The projected results indicate that agriculture will remain the dominant land cover with a share of 70.24%, followed by vegetation at 17.72% and built-up areas at 5.09%. However, a marginal decline is expected in both the agriculture and built-up classes.
{"title":"Land/use land /cover dynamics and future scenario of Mayurakshi river basin by random forest and CA–Markov model","authors":"D. D. L. Soren, K. C. Roy, B. Biswas","doi":"10.1007/s13762-024-06006-8","DOIUrl":"https://doi.org/10.1007/s13762-024-06006-8","url":null,"abstract":"<p>The study was focused on analyzing the land use and land cover status, change patterns, and future scenarios in the Mayurakshi basin in Jharkhand and West Bengal state of eastern India. The dataset collected for image classification included Landsat 5 (TM) (1991–2008) and Landsat 8 (OLI) (2020). Various sequential preprocessing steps such as atmospheric correction, image enhancement, mosaicking, masking, and clipping were performed using QGIS 3.16 and ArcGIS 10.8 software. The land use and land cover classes found in the study area were water, vegetation, bare land, agriculture, and built-up, and classification was executed by using the Random Forest machine learning algorithm. The accuracy of the classified land use and land cover was validated and accepted with Kappa agreements of 0.89, 0.85, and 0.88 for the years 1991, 2005, and 2020, respectively. Throughout the study period, agriculture emerged as the dominant land use class, followed by vegetation and bare land. The area under the land use and land cover categories of water, vegetation, and bare land continuously decreased between the years 1991–2005 and 2005–2020, while agriculture and built-up areas recorded an increase of 4.49%, 0.76%, 17.81%, and 2.04%, respectively. To project future land use and land cover status, the popular Cellular Automata Markov Chain Model was employed. The projected results indicate that agriculture will remain the dominant land cover with a share of 70.24%, followed by vegetation at 17.72% and built-up areas at 5.09%. However, a marginal decline is expected in both the agriculture and built-up classes.</p>","PeriodicalId":589,"journal":{"name":"International Journal of Environmental Science and Technology","volume":"53 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-11DOI: 10.1007/s13762-024-05945-6
A. Khazaei, M. Abbaspour, S. K. Babaei, L. Taghavi, Y. Rashidi
Metropolises in developing countries have many problems. These problems include land use changes, environmental pollution, and temperature changes due to the expansion of industrial areas, population growth and high traffic. In this study, the spatio-temporal relationship of urban heat islands (UHI) with land use changes in the period from 2000 to 2020 and the modeling of the future changes of these UHI until 2050 were studied in Tehran. For this purpose, satellite images, LCM (Land Change Modeler) model, modeling of the relationship among surface temperatures with environmental parameters, and simulation of UHI using regression model were used to predict the future condition of these UHI until 2050. The findings demonstrated that the area of residential areas increased during the study period and the area of gardens and urban green spaces decreased. Analyzing the future scenario maps reveals that the last 20 years’ pattern is still continuing. The UHI of city had an increasing trend until 2020, especially in the west and south of Tehran. Regions 21, 22, and 9, followed by regions 18, 19, and 20 in the south, have the most UHI. A significant positive correlation between green spaces and surface temperature shows the effect of vegetation in controlling the intensity of UHIs in Tehran. The results of surface temperature prediction modeling showed that the trend of temperature increase continues, and 2050 will be the most critical year of the predicted period.
{"title":"Modeling the spatiotemporal dynamics of metropolitan urban heat islands and predicting the future situation (Tehran metropolis)","authors":"A. Khazaei, M. Abbaspour, S. K. Babaei, L. Taghavi, Y. Rashidi","doi":"10.1007/s13762-024-05945-6","DOIUrl":"10.1007/s13762-024-05945-6","url":null,"abstract":"<div><p>Metropolises in developing countries have many problems. These problems include land use changes, environmental pollution, and temperature changes due to the expansion of industrial areas, population growth and high traffic. In this study, the spatio-temporal relationship of urban heat islands (UHI) with land use changes in the period from 2000 to 2020 and the modeling of the future changes of these UHI until 2050 were studied in Tehran. For this purpose, satellite images, LCM (Land Change Modeler) model, modeling of the relationship among surface temperatures with environmental parameters, and simulation of UHI using regression model were used to predict the future condition of these UHI until 2050. The findings demonstrated that the area of residential areas increased during the study period and the area of gardens and urban green spaces decreased. Analyzing the future scenario maps reveals that the last 20 years’ pattern is still continuing. The UHI of city had an increasing trend until 2020, especially in the west and south of Tehran. Regions 21, 22, and 9, followed by regions 18, 19, and 20 in the south, have the most UHI. A significant positive correlation between green spaces and surface temperature shows the effect of vegetation in controlling the intensity of UHIs in Tehran. The results of surface temperature prediction modeling showed that the trend of temperature increase continues, and 2050 will be the most critical year of the predicted period.</p></div>","PeriodicalId":589,"journal":{"name":"International Journal of Environmental Science and Technology","volume":"22 2","pages":"933 - 950"},"PeriodicalIF":3.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-11DOI: 10.1007/s13762-024-05993-y
A. S. Al-Hussaini
Novel polymer composites with unique characteristics as new materials are essentially needed to meet future demands. Terpoly(anthranilic acid, m-aminobenzoic acid, and o-nitroaniline) emeraldine base (EB)/macro-microcomposites were generated from equimolar ratios of the corresponding molecules and different ratios of bentonite via in situ oxidative terpolymerization. Their spectral properties upon joining the m-aminobenzoic acid and the o-nitroaniline moieties in the skeleton of polyanthranilic acid were inspected. The spectral analyses were utilized to emphasize the results of both terpoly(o, m-aminobenzoic acid, and o-nitroaniline) (EB) and poly(o, m-aminobenzoic acid, and o-nitroaniline)/bentonite composites. The TGA analyses of the purified terpolymer with and without bentonite in the N2 atmosphere were investigated. Furthermore, the terpolymer composite morphology was investigated by the SEM technique with the micro-macrometric particle sizes 0.470–2.780 μm at different magnifications.
{"title":"Development of functional materials based on new high content electron withdrawing groups terpolymer composites for potential applications","authors":"A. S. Al-Hussaini","doi":"10.1007/s13762-024-05993-y","DOIUrl":"https://doi.org/10.1007/s13762-024-05993-y","url":null,"abstract":"<p>Novel polymer composites with unique characteristics as new materials are essentially needed to meet future demands. Terpoly(anthranilic acid, <i>m-</i>aminobenzoic acid, and <i>o-</i>nitroaniline) emeraldine base (EB)/macro-microcomposites were generated from equimolar ratios of the corresponding molecules and different ratios of bentonite via in situ oxidative terpolymerization. Their spectral properties upon joining the <i>m</i>-aminobenzoic acid and the <i>o</i>-nitroaniline moieties in the skeleton of polyanthranilic acid were inspected. The spectral analyses were utilized to emphasize the results of both terpoly(<i>o</i>, <i>m</i>-aminobenzoic acid, and <i>o</i>-nitroaniline) (EB) and poly(<i>o</i>, <i>m</i>-aminobenzoic acid, and <i>o</i>-nitroaniline)/bentonite composites. The TGA analyses of the purified terpolymer with and without bentonite in the N<sub>2</sub> atmosphere were investigated. Furthermore, the terpolymer composite morphology was investigated by the SEM technique with the micro-macrometric particle sizes 0.470–2.780 μm at different magnifications.</p><h3 data-test=\"abstract-sub-heading\">Graphical Abstract</h3>","PeriodicalId":589,"journal":{"name":"International Journal of Environmental Science and Technology","volume":"4 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-11DOI: 10.1007/s13762-024-05962-5
E. K. Moore, L. Pittman, M. Heminghaus, D. Heintzelman, A. Hatter
Plastic pollution and microplastic (MP, 1 µm to 5 mm) generation are growing problems affecting the global community and a wide range of natural and disturbed environments. Urban and suburban waterways are directly impacted by plastic pollution due to their proximity to population centers and many different types single use plastic waste sources. In this study, plastic waste accumulation and fragmentation was investigated along the Cooper River in Camden County, NJ. Polymer composition was identified for individual plastic waste particles collected along the Cooper River using Fourier transform infrared (FTIR) spectrometry. Multiple human-built structures (Wallworth Lake, Evans Pond and Hopkins Pond dams) along the Cooper River were found to accumulate different types of plastic waste. The accumulation of plastic waste along these structures resulted in the initial stages of plastic fragmentation and the identification of large MP particles (1 to 5 mm). Quantitative analysis revealed that fragmented polystyrene (PS) particles constituted 82.8% of the total plastic fragments identified, most of which were identified at the Wallworth Lake dam. Many other types of fragmented plastic litter, including polyethylene and polypropylene, were identified at the Wallworth Lake dam, as well. This research demonstrates that engineered structures within urban and suburban aquatic ecosystems serve as significant aggregators of plastic debris, thereby catalyzing its breakdown into microplastics. Considering the escalating ecological and human health ramifications of microplastic proliferation, the fragmentation of plastic waste in an urban and suburban waterway observed in this study can also result in potentially toxic smaller MP particles, and increased exposure to aquatic organisms and humans.
{"title":"Enhanced microplastic fragmentation along human built structures in an urban waterway","authors":"E. K. Moore, L. Pittman, M. Heminghaus, D. Heintzelman, A. Hatter","doi":"10.1007/s13762-024-05962-5","DOIUrl":"https://doi.org/10.1007/s13762-024-05962-5","url":null,"abstract":"<p>Plastic pollution and microplastic (MP, 1 µm to 5 mm) generation are growing problems affecting the global community and a wide range of natural and disturbed environments. Urban and suburban waterways are directly impacted by plastic pollution due to their proximity to population centers and many different types single use plastic waste sources. In this study, plastic waste accumulation and fragmentation was investigated along the Cooper River in Camden County, NJ. Polymer composition was identified for individual plastic waste particles collected along the Cooper River using Fourier transform infrared (FTIR) spectrometry. Multiple human-built structures (Wallworth Lake, Evans Pond and Hopkins Pond dams) along the Cooper River were found to accumulate different types of plastic waste. The accumulation of plastic waste along these structures resulted in the initial stages of plastic fragmentation and the identification of large MP particles (1 to 5 mm). Quantitative analysis revealed that fragmented polystyrene (PS) particles constituted 82.8% of the total plastic fragments identified, most of which were identified at the Wallworth Lake dam. Many other types of fragmented plastic litter, including polyethylene and polypropylene, were identified at the Wallworth Lake dam, as well. This research demonstrates that engineered structures within urban and suburban aquatic ecosystems serve as significant aggregators of plastic debris, thereby catalyzing its breakdown into microplastics. Considering the escalating ecological and human health ramifications of microplastic proliferation, the fragmentation of plastic waste in an urban and suburban waterway observed in this study can also result in potentially toxic smaller MP particles, and increased exposure to aquatic organisms and humans.</p>","PeriodicalId":589,"journal":{"name":"International Journal of Environmental Science and Technology","volume":"1 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-11DOI: 10.1007/s13762-024-06023-7
M. Darbandi, A. Moghaddasfar, M. Eynollahi, A. Mehrdad
The nickel oxide nanoparticles (NPs) were synthesized using the solvothermal method in the oleic acid to remove congo red via an adsorption process. Furthermore, for the first time, in this study subsequently regeneration of deactivated adsorbent by low-energy ultrasound waves as an inventive technique was investigated. The morphology, porosity, and crystallinity of the as-synthesized NPs were investigated by transmission electron microscopy (TEM), Scanning electron microscope (SEM), Brunauer–Emmett–Teller (BET), and X-ray diffraction (XRD) techniques. Congo red, a water-soluble azo dye, is adsorbed by nickel oxide nanoparticles, reaching about 83.20% adsorption within two hours with a pseudo-first-order rate constant of 0.0099 min−1. In the regeneration process, the nanoparticles regenerated by low-frequency ultrasound waves up to 94.35% within 35 min. The obtained data shows that the amount of regenerated nanoparticles increased with the intensity of ultrasonic irradiation. Most importantly, it can be recycled by ultrasound irradiation, which retains high performance in 3 cycles, proving its promising application for different environmental decontamination.