Physics and Chemistry of the Earth最新文献

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Virtual arable land trade reveals inequalities in the North China Plain: Regional heterogeneity and influential determinants

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2025-02-17 DOI: 10.1016/j.pce.2025.103889

Chuyao Weng , Yuping Bai , Yecui Hu , Wanen Cai , Shibin Zhang , Jiayao Shu

Arable land supply in North China Plain (NCP) has significantly contributed to national food security and economic development in China. To clarify the complex arable land use relationships between NCP and other provinces in China, this study applied an environmentally extended multi-regional input-output model to analyze the spatio-temporal variation characteristics of virtual arable land (VAL) trade in China associated with the food supply in NCP from 2007 to 2017. The driving forces of VAL trade were further identified using structural decomposition analysis (SDA). The results showed that NCP exported 10.280 Mha of VAL to other provinces in China in 2017, with a decrease of 2.85% compared to 2007. At the same time, NCP imported 13.799 Mha of VAL from other provinces, with an increase of 4.39%. The top net importers from NCP were Zhejiang (1.355 Mha), Shanxi (0.862 Mha) and Guangdong (0.746 Mha), which are mostly located on the developed southern coast. The top three provinces of NCP that supplied the largest proportions of VAL to the outside were Henan (30.89%), Anhui (26.32%) and Hebei (22.93%). Meanwhile, the gap between per capita consumption-based arable land of provinces in NCP is decreasing. The findings of SDA revealed that resource intensity caused a reduction of 23.09 Mha of VAL, while per capita consumption caused an increase of 27.39 Mha of VAL from 2007 to 2017. This study helps support optimization of the interregional supply mode, promotion of resource complementarity and industrial cooperation among different regions, and achievement of sustainable agricultural development.

{"title":"Virtual arable land trade reveals inequalities in the North China Plain: Regional heterogeneity and influential determinants","authors":"Chuyao Weng , Yuping Bai , Yecui Hu , Wanen Cai , Shibin Zhang , Jiayao Shu","doi":"10.1016/j.pce.2025.103889","DOIUrl":"10.1016/j.pce.2025.103889","url":null,"abstract":"<div><div>Arable land supply in North China Plain (NCP) has significantly contributed to national food security and economic development in China. To clarify the complex arable land use relationships between NCP and other provinces in China, this study applied an environmentally extended multi-regional input-output model to analyze the spatio-temporal variation characteristics of virtual arable land (VAL) trade in China associated with the food supply in NCP from 2007 to 2017. The driving forces of VAL trade were further identified using structural decomposition analysis (SDA). The results showed that NCP exported 10.280 Mha of VAL to other provinces in China in 2017, with a decrease of 2.85% compared to 2007. At the same time, NCP imported 13.799 Mha of VAL from other provinces, with an increase of 4.39%. The top net importers from NCP were Zhejiang (1.355 Mha), Shanxi (0.862 Mha) and Guangdong (0.746 Mha), which are mostly located on the developed southern coast. The top three provinces of NCP that supplied the largest proportions of VAL to the outside were Henan (30.89%), Anhui (26.32%) and Hebei (22.93%). Meanwhile, the gap between per capita consumption-based arable land of provinces in NCP is decreasing. The findings of SDA revealed that resource intensity caused a reduction of 23.09 Mha of VAL, while per capita consumption caused an increase of 27.39 Mha of VAL from 2007 to 2017. This study helps support optimization of the interregional supply mode, promotion of resource complementarity and industrial cooperation among different regions, and achievement of sustainable agricultural development.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"138 ","pages":"Article 103889"},"PeriodicalIF":3.0,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A sustainable and cost-effective approach for efficient removal of Direct Blue-14 azo dye from wastewater using North American Zeolite for developing countries

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2025-02-12 DOI: 10.1016/j.pce.2025.103888

Eman A. Al-Abbad , Rabia Rehman , Muhammad Sadiq Hussain

North American Zeolite (NAZ) is an affordable and widely available mineral in the United States, Asia, and Africa. So, the potential for detoxifying wastewater comprising azo dyes is investigated. It has the capacity to adsorb a hazardous life-threatening, and carcinogenic direct blue 14 dye (DB-14) from water bodies. Mechanistic and operational optimization experiments demonstrated that 0.05 g of NAZ resulted in 96.4% adsorption degradation of 20 ppm DB-14 via a multilayer chemisorption process with intra-particle diffusion, as evidenced by isothermal and kinetic assessments of equilibrium data. Maximum sorption potential of NAZ for DB-14 is 122 mg g⁻¹ following pseudo-second order kinetics. The negative Gibbs free energy (ΔG^o) associated with the adsorption spontaneity behavior of DB-14 on NAZ. These promising results favor its use on commercial scale dye removal especially in poor Asian and African countries in ecofriendly and cost effective manner.

引用次数: 0

Climate change impact assessment on the river discharge of the upper Ganga Subbasin

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2025-02-11 DOI: 10.1016/j.pce.2025.103887

Rajeev Ranjan , Ajanta Goswami , C.S.P. Ojha , Sanjay Jain , Praveen Kumar Singh

The HKH region has many glaciers, providing fresh water to a large population downstream. The hydrological system is susceptible to climate change, especially temperature and precipitation. The present study aims to investigate the impact of climate change on the discharge and water balance of the snow-dominated upper Ganga Basin. The study utilized CMIP6 scenarios SSP2-4.5 and SSP5-8.5 with SPHY to simulate future hydrological changes in the basin. We calibrated and validated the model for simulation by using observed discharge data at Devprayag. The historical period (1985–2014) calibrated at Devprayag showed rainfall, snow, glacier, baseflow, and total discharge of 509.5 m3/s, 117.5 m³/s, 86.1 m³/s, 78.9 m³/s, and 792.0 m³/s, respectively. Contribution to total flow was 63.3% (rain), 10.8% (glaciermelt), 14.9% (snowmelt), and 10.0% (baseflow). Total runoff increased, with rainfall runoff, contributing the most, followed by glaciermelt runoff and baseflow, while snowmelt decreased. By the end of 21st century, temperature and precipitation is anticipated to rise under SSP5-8.5. The model estimates substantially impacted the basin hydrology and water balance, with a 50% increase in total flow in the Far Future (2076–2100). The snowmelt contribution is estimated to decrease by 57% by 2090, but the water supply is not expected to desrease. The analysis showed that snowmelt runoff will be reduced through time, and river discharge will be highly impacted by climate change. This work will improve understanding of water availability, snowmelt, and glacier melt dynamics, which, along with climate change, lead to sustainable water resource management.

{"title":"Climate change impact assessment on the river discharge of the upper Ganga Subbasin","authors":"Rajeev Ranjan , Ajanta Goswami , C.S.P. Ojha , Sanjay Jain , Praveen Kumar Singh","doi":"10.1016/j.pce.2025.103887","DOIUrl":"10.1016/j.pce.2025.103887","url":null,"abstract":"<div><div>The HKH region has many glaciers, providing fresh water to a large population downstream. The hydrological system is susceptible to climate change, especially temperature and precipitation. The present study aims to investigate the impact of climate change on the discharge and water balance of the snow-dominated upper Ganga Basin. The study utilized CMIP6 scenarios SSP2-4.5 and SSP5-8.5 with SPHY to simulate future hydrological changes in the basin. We calibrated and validated the model for simulation by using observed discharge data at Devprayag. The historical period (1985–2014) calibrated at Devprayag showed rainfall, snow, glacier, baseflow, and total discharge of 509.5 m3/s, 117.5 m<sup>3</sup>/s, 86.1 m<sup>3</sup>/s, 78.9 m<sup>3</sup>/s, and 792.0 m<sup>3</sup>/s, respectively. Contribution to total flow was 63.3% (rain), 10.8% (glaciermelt), 14.9% (snowmelt), and 10.0% (baseflow). Total runoff increased, with rainfall runoff, contributing the most, followed by glaciermelt runoff and baseflow, while snowmelt decreased. By the end of 21st century, temperature and precipitation is anticipated to rise under SSP5-8.5. The model estimates substantially impacted the basin hydrology and water balance, with a 50% increase in total flow in the Far Future (2076–2100). The snowmelt contribution is estimated to decrease by 57% by 2090, but the water supply is not expected to desrease. The analysis showed that snowmelt runoff will be reduced through time, and river discharge will be highly impacted by climate change. This work will improve understanding of water availability, snowmelt, and glacier melt dynamics, which, along with climate change, lead to sustainable water resource management.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"138 ","pages":"Article 103887"},"PeriodicalIF":3.0,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An integrated comprehensive approach describing structural features and comparative petrophysical analysis between conventional and machine learning tools to characterize carbonate reservoir: A case study from Upper Indus Basin, Pakistan

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2025-02-08 DOI: 10.1016/j.pce.2025.103885

Zohaib Naseer , Urooj Shakir , Muyyassar Hussain , Qazi Adnan Ahmad , Kamal Abdelrahman , Muhammad Fahad Mahmood , Mohammed S. Fnais , Muhsan Ehsan

More than 70% of the global hydrocarbon reserves are present in carbonated rocks. Evaluating prospects in carbonate reservoirs is a complicated task because of their unique depositional features. The Eocene carbonates in the Joyamair oil field are heterogeneous and present challenges defining the entrapment and sealing mechanism by applying traditional methods. Although structural interpretation revealed a positive triangular geometry, estimating accurate reservoir properties requires an effective model for assessing hydrocarbon presence. Therefore, an optimized machine learning (ML) approach has been deployed to address reservoir challenges and delineate the potential with a high success rate after drawing a comparison with the conventional approach. Two wells were utilized for petrophysical evaluation in the conventional method, while one well (Joyamair-04) was kept blind in a supervised ML approach. Extra Tree Regressor (ETR) produced a low volume of shale and effective porosity (PHIE) high results with more than 99% R² and least mean square error score. Random Forest Regressor (RFR) showed water saturation (S_w) results with about 100% accuracy compared to conventional interpretation at a blind well. Volumetric reserve estimation also proved economical hydrocarbon reserves present in the reservoir formation. The study revealed that integrating conventional and ML techniques along with structural geometry aided better reservoir characterization and reserve estimation. The study proved that ML algorithms outperformed traditional petrophysical methods in accuracy and efficiency.

{"title":"An integrated comprehensive approach describing structural features and comparative petrophysical analysis between conventional and machine learning tools to characterize carbonate reservoir: A case study from Upper Indus Basin, Pakistan","authors":"Zohaib Naseer , Urooj Shakir , Muyyassar Hussain , Qazi Adnan Ahmad , Kamal Abdelrahman , Muhammad Fahad Mahmood , Mohammed S. Fnais , Muhsan Ehsan","doi":"10.1016/j.pce.2025.103885","DOIUrl":"10.1016/j.pce.2025.103885","url":null,"abstract":"<div><div>More than 70% of the global hydrocarbon reserves are present in carbonated rocks. Evaluating prospects in carbonate reservoirs is a complicated task because of their unique depositional features. The Eocene carbonates in the Joyamair oil field are heterogeneous and present challenges defining the entrapment and sealing mechanism by applying traditional methods. Although structural interpretation revealed a positive triangular geometry, estimating accurate reservoir properties requires an effective model for assessing hydrocarbon presence. Therefore, an optimized machine learning (ML) approach has been deployed to address reservoir challenges and delineate the potential with a high success rate after drawing a comparison with the conventional approach. Two wells were utilized for petrophysical evaluation in the conventional method, while one well (Joyamair-04) was kept blind in a supervised ML approach. Extra Tree Regressor (ETR) produced a low volume of shale and effective porosity (PHIE) high results with more than 99% R<sup>2</sup> and least mean square error score. Random Forest Regressor (RFR) showed water saturation (S<sub>w</sub>) results with about 100% accuracy compared to conventional interpretation at a blind well. Volumetric reserve estimation also proved economical hydrocarbon reserves present in the reservoir formation. The study revealed that integrating conventional and ML techniques along with structural geometry aided better reservoir characterization and reserve estimation. The study proved that ML algorithms outperformed traditional petrophysical methods in accuracy and efficiency.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"138 ","pages":"Article 103885"},"PeriodicalIF":3.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Strong mining pressure characteristics and stability control in large height coal face under continuous extraction: A case study

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2025-02-06 DOI: 10.1016/j.pce.2025.103886

Xu Liang , Zhen Zhang , Qianjin Liu , Zhen Li

In underground coal mining, the strong dynamic pressure resulting from continuous extraction frequently leads to instability accidents. A case study was conducted at Xiaobaodang No. 1 Coal Mine to address the issues, utilizing numerical simulation, microseismic (MS) monitoring, and site observation methods. The findings indicate that significant mining pressure is observed when the damage zone above the tailgate of the current working face extends through the overlying strata of the pillar towards the neighboring gob during the second mining phase. The damage zones within the overlying rock layers of the two working faces ultimately converge, resulting in significant mining pressure at the site. The safety valve opening rate is generally above 80%, indicating significant mining pressure intensity, particularly in the tailgate. MS events and active roof movement are concentrated in the tailgate and neighboring gob during the second mining phase. The plastic zone radius at No. 112204 tailgate expands from 3 m to 7 m, with MS events primarily occurring 80 m behind to 40 m ahead of the working face, necessitating the need for reinforcement support. Following the implementation of various measures, such as coordinated support using anchors and anchor rods, continuous slotting and floor breaking, along with multi-zone grouting, the integrity of the surrounding rocks is ultimately preserved. Controlling concepts considering geological and mining factors are finally discussed and recommended. The study serves as a significant reference for the prevention and control of intense mining pressure during ongoing extraction processes.

{"title":"Strong mining pressure characteristics and stability control in large height coal face under continuous extraction: A case study","authors":"Xu Liang , Zhen Zhang , Qianjin Liu , Zhen Li","doi":"10.1016/j.pce.2025.103886","DOIUrl":"10.1016/j.pce.2025.103886","url":null,"abstract":"<div><div>In underground coal mining, the strong dynamic pressure resulting from continuous extraction frequently leads to instability accidents. A case study was conducted at Xiaobaodang No. 1 Coal Mine to address the issues, utilizing numerical simulation, microseismic (MS) monitoring, and site observation methods. The findings indicate that significant mining pressure is observed when the damage zone above the tailgate of the current working face extends through the overlying strata of the pillar towards the neighboring gob during the second mining phase. The damage zones within the overlying rock layers of the two working faces ultimately converge, resulting in significant mining pressure at the site. The safety valve opening rate is generally above 80%, indicating significant mining pressure intensity, particularly in the tailgate. MS events and active roof movement are concentrated in the tailgate and neighboring gob during the second mining phase. The plastic zone radius at No. 112204 tailgate expands from 3 m to 7 m, with MS events primarily occurring 80 m behind to 40 m ahead of the working face, necessitating the need for reinforcement support. Following the implementation of various measures, such as coordinated support using anchors and anchor rods, continuous slotting and floor breaking, along with multi-zone grouting, the integrity of the surrounding rocks is ultimately preserved. Controlling concepts considering geological and mining factors are finally discussed and recommended. The study serves as a significant reference for the prevention and control of intense mining pressure during ongoing extraction processes.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"138 ","pages":"Article 103886"},"PeriodicalIF":3.0,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Snow avalanche in the Indian Himalayas: Hazard zonation and climate change trends in Kullu region of Himachal Pradesh, India

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2025-02-06 DOI: 10.1016/j.pce.2025.103882

Joshal K. Bansal , Ajanta Goswami , Snehmani , Arijit Roy

This research provides an in-depth analysis of snow avalanche behavior in the Indian Himalayas, specifically targeting the Kullu region. The study integrates climate data, terrain characteristics and field validations to apply Object-Based Image Segmentation (OBIS) analysis for more precise hazard zonation. Over the past few decades, the region has experienced a notable increase in avalanche frequency and intensity, correlating these changes with climatic factors such as rising temperatures, altered precipitation patterns, and anthropogenic influences like infrastructure development. The study emphasizes the complex interplay between meteorological variables—including snow temperature, wind speed etc. and the topographical features contributing to avalanche susceptibility. OBIS, supported by field surveys and literature, allows for a refined identification of high-risk avalanche zones, significantly enhancing prediction models. The findings also reveal that climate change trends are expected to amplify the frequency and magnitude of avalanche occurrences in the future, posing heightened risks to local populations, infrastructure and the region's biodiversity. The study contributes critical insights for developing robust risk management and climate adaptation strategies by systematically identifying avalanche-prone areas and analysing climate change projections. These strategies are essential for safeguarding vulnerable mountain communities and ecosystems. The broader implications of this research extend beyond the Indian Himalayas, contributing to the global understanding of avalanche dynamics and highlighting the need for comprehensive climate adaptation and disaster risk reduction frameworks in high-altitude regions.

{"title":"Snow avalanche in the Indian Himalayas: Hazard zonation and climate change trends in Kullu region of Himachal Pradesh, India","authors":"Joshal K. Bansal , Ajanta Goswami , Snehmani , Arijit Roy","doi":"10.1016/j.pce.2025.103882","DOIUrl":"10.1016/j.pce.2025.103882","url":null,"abstract":"<div><div>This research provides an in-depth analysis of snow avalanche behavior in the Indian Himalayas, specifically targeting the Kullu region. The study integrates climate data, terrain characteristics and field validations to apply Object-Based Image Segmentation (OBIS) analysis for more precise hazard zonation. Over the past few decades, the region has experienced a notable increase in avalanche frequency and intensity, correlating these changes with climatic factors such as rising temperatures, altered precipitation patterns, and anthropogenic influences like infrastructure development. The study emphasizes the complex interplay between meteorological variables—including snow temperature, wind speed etc. and the topographical features contributing to avalanche susceptibility. OBIS, supported by field surveys and literature, allows for a refined identification of high-risk avalanche zones, significantly enhancing prediction models. The findings also reveal that climate change trends are expected to amplify the frequency and magnitude of avalanche occurrences in the future, posing heightened risks to local populations, infrastructure and the region's biodiversity. The study contributes critical insights for developing robust risk management and climate adaptation strategies by systematically identifying avalanche-prone areas and analysing climate change projections. These strategies are essential for safeguarding vulnerable mountain communities and ecosystems. The broader implications of this research extend beyond the Indian Himalayas, contributing to the global understanding of avalanche dynamics and highlighting the need for comprehensive climate adaptation and disaster risk reduction frameworks in high-altitude regions.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"138 ","pages":"Article 103882"},"PeriodicalIF":3.0,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Land use change analysis and prediction of urban growth using multi-layer perceptron neural network Markov chain model in Faridabad- A data-scarce region of Northwestern India

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2025-02-04 DOI: 10.1016/j.pce.2025.103884

Sunil Kumar , Kousik Midya , Swagata Ghosh , Pradeep Kumar , Varun Narayan Mishra

Present research aims to examine the transformations of land use and land cover (LULC) within the Faridabad district, India, using high-resolution remotely-sensed images. LULC change analysis over the years 2007–2022 revealed a significant decline in agricultural land from 65.4% of the total area in 2007 to 53.9% in 2022. Conversely, considerable increases have been observed in urban built-up areas (from 58.2% in 2007 to 93.3% in 2022), industrial areas (from 13.7% to 26.9%). Vegetation coverage decreased from 18.9% in 2007 to 12.7% in 2022 after primarily alleviating in 2017 due to green initiatives. Further, the LULC maps of 2007 and 2012 were used to predict the LULC of 2017 using Multi-Layer Perceptron Neural Network (MLPNN)-integrated Markov Chain Model (MCM). Subsequently, predicted LULC of 2017 were compared with observed LULC of 2017 to validate the model. Additionally, the integrated model has been applied to predict and validate LULC of 2022. Validation results produced R² values and K statistics >0.8 for both 2017 and 2022 confirming the efficacy of the model. Finally, future LULC scenario has been predicted for 2027. Comparison of predicted LULC for 2027 with observed LULC of 2022 revealed that built-up would increase by 3.8% (built-up 149.3 km² in 2022 and 154.9 km² in 2027). Vegetation would decrease by 3.1% (12.7 km² in 2022 and 12.3 km² in 2027). From the present findings, it is recommended that a continuous monitoring is required to analyse the efficacy of implemented measures and adapt strategies as necessary.

{"title":"Land use change analysis and prediction of urban growth using multi-layer perceptron neural network Markov chain model in Faridabad- A data-scarce region of Northwestern India","authors":"Sunil Kumar , Kousik Midya , Swagata Ghosh , Pradeep Kumar , Varun Narayan Mishra","doi":"10.1016/j.pce.2025.103884","DOIUrl":"10.1016/j.pce.2025.103884","url":null,"abstract":"<div><div>Present research aims to examine the transformations of land use and land cover (LULC) within the Faridabad district, India, using high-resolution remotely-sensed images. LULC change analysis over the years 2007–2022 revealed a significant decline in agricultural land from 65.4% of the total area in 2007 to 53.9% in 2022. Conversely, considerable increases have been observed in urban built-up areas (from 58.2% in 2007 to 93.3% in 2022), industrial areas (from 13.7% to 26.9%). Vegetation coverage decreased from 18.9% in 2007 to 12.7% in 2022 after primarily alleviating in 2017 due to green initiatives. Further, the LULC maps of 2007 and 2012 were used to predict the LULC of 2017 using Multi-Layer Perceptron Neural Network <strong>(</strong>MLPNN)-integrated Markov Chain Model (MCM). Subsequently, predicted LULC of 2017 were compared with observed LULC of 2017 to validate the model. Additionally, the integrated model has been applied to predict and validate LULC of 2022. Validation results produced R<sup>2</sup> values and K statistics >0.8 for both 2017 and 2022 confirming the efficacy of the model. Finally, future LULC scenario has been predicted for 2027. Comparison of predicted LULC for 2027 with observed LULC of 2022 revealed that built-up would increase by 3.8% (built-up 149.3 km<sup>2</sup> in 2022 and 154.9 km<sup>2</sup> in 2027). Vegetation would decrease by 3.1% (12.7 km<sup>2</sup> in 2022 and 12.3 km<sup>2</sup> in 2027). From the present findings, it is recommended that a continuous monitoring is required to analyse the efficacy of implemented measures and adapt strategies as necessary.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"138 ","pages":"Article 103884"},"PeriodicalIF":3.0,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143350412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Amalgamation of advanced oxidation process with biological techniques for treatment of tannery wastewater

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2025-02-01 DOI: 10.1016/j.pce.2025.103883

Selvabharathi Gopal , Jaya Jayabalan , Dhanalakshmi Jayaraman , Muthumari Perumal , Vivek Mariappan Santhi

This present study was examined by Amalgamation of advanced oxidation process with biological techniques for treatment of tannery wastewater. Non-biodegradable as it confined substantial amount of organic compounds whose degradation was not possible by conventional biological treatment in wastewater. Non-biodegradable as it confined substantial amount of organic compounds whose degradation was not possible by conventional biological treatment in wastewater. The pre-treatment of wastewater by AOP converts the recalcitrant organic pollutants to simpler and biodegradable compounds allowing the wastewater to be treated by subsequent biological treatment. The combined solar photo-Fenton and solar photo catalysis method has been studied by means of central composite design proved that the pH, Fe²⁺, H₂O_2, TiO₂ dosage, COD removal efficacy affected positively. The optimal operation parameters such as pH = 7, Fe²⁺ = 0.5 g/L, H₂O₂ = 1.8 g/L and TiO₂ = 0.2 g/L. Under this condition, removal efficacy COD = 88%, BOD = 82%, colour = 90% and Chromium (III) = 80% attained at 240 min. For the coupling with biological treatment, it was achieved that the removal efficacy COD = 98% and colour = 95% was achieved at 95 min. The combined process proven an alternate and a cost-effective methodology for the treatment of tannery wastewater to comply with applicable current regulations worldwide and ensuring the quality of treated wastewater for reuses purposes.

{"title":"Amalgamation of advanced oxidation process with biological techniques for treatment of tannery wastewater","authors":"Selvabharathi Gopal , Jaya Jayabalan , Dhanalakshmi Jayaraman , Muthumari Perumal , Vivek Mariappan Santhi","doi":"10.1016/j.pce.2025.103883","DOIUrl":"10.1016/j.pce.2025.103883","url":null,"abstract":"<div><div>This present study was examined by Amalgamation of advanced oxidation process with biological techniques for treatment of tannery wastewater. Non-biodegradable as it confined substantial amount of organic compounds whose degradation was not possible by conventional biological treatment in wastewater. Non-biodegradable as it confined substantial amount of organic compounds whose degradation was not possible by conventional biological treatment in wastewater. The pre-treatment of wastewater by AOP converts the recalcitrant organic pollutants to simpler and biodegradable compounds allowing the wastewater to be treated by subsequent biological treatment. The combined solar photo-Fenton and solar photo catalysis method has been studied by means of central composite design proved that the pH, Fe<sup>2+</sup>, H<sub>2</sub>O<sub>2,</sub> TiO<sub>2</sub> dosage, COD removal efficacy affected positively. The optimal operation parameters such as pH = 7, Fe<sup>2+</sup> = 0.5 g/L, H<sub>2</sub>O<sub>2</sub> = 1.8 g/L and TiO<sub>2</sub> = 0.2 g/L. Under this condition, removal efficacy COD = 88%, BOD = 82%, colour = 90% and Chromium (III) = 80% attained at 240 min. For the coupling with biological treatment, it was achieved that the removal efficacy COD = 98% and colour = 95% was achieved at 95 min. The combined process proven an alternate and a cost-effective methodology for the treatment of tannery wastewater to comply with applicable current regulations worldwide and ensuring the quality of treated wastewater for reuses purposes.</div></div>","PeriodicalId":54616,"journal":{"name":"Physics and Chemistry of the Earth","volume":"138 ","pages":"Article 103883"},"PeriodicalIF":3.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143279799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Accelerating change: Fostering innovation and integration for sustainable resources management for sustainable development in East and Southern Africa

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2025-02-01 DOI: 10.1016/j.pce.2024.103817

Nnenesi Kgabi, Zacharia Katambara, Bloodless Rimuka Dzwairo, Cosmo Ngongondo

引用次数: 0

Earthquake probability assessment using gumbel extreme value statistics and mapping intensity based isoseismal and land use land cover dynamics with machine learning

IF 3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Physics and Chemistry of the Earth

Pub Date : 2025-02-01 DOI: 10.1016/j.pce.2025.103878

R. Siddhardha, Kalyan Kumar Gonavaram

The objective of the present study is to estimate seismicity parameters, evaluate earthquake occurrence probabilities and return periods, perform site characterization, and develop integrated intensity based isoseismal and land use land cover (LULC) maps using advanced statistical and machine learning algorithms for Prakasam district, Andhra Pradesh, in Peninsular India. The estimated seismicity parameters a and b values range from 3.78–4.06 to 0.81–0.83. The probability of occurrence of a 7.5M_w earthquake in the next 1, 25, 50, 75 and 100 years was computed to be 0.2%, 5.6%, 10.9%, 15.9%, and 20.6%, respectively, with a corresponding return period of 434 years. Topography based site characterization was performed utilizing Cartosat-1 PAN Digital elevation model dataset, and spatial variation of V_s30 map was developed for Prakasam district. Intensity based isoseismal maps were developed for six historical earthquakes in the study area, and LULC classification was conducted using advanced statistical and machine learning algorithms such as Maximum likelihood (ML), Random forest (RF), and Support vector machine (SVM) through Landsat satellite imagery. The performance of ML, SVM, and RF was evaluated using overall accuracy (OA), with the SVM classifier achieving the highest OA of 96.21% in classifying various land classes. Finally, integrated intensity based isoseismal and LULC maps for the past six historical earthquakes were developed.

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