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Optimization Models for Long-Term Planning of Municipal Solid Waste Management Systems: A Review with An Emphasis on Mass Balances J. Environ. Inform. (IF 7.0) Pub Date : 2024-01-31 M. K. Korucu, İ. Kucukoglu
The vast majority of decision-making approaches used for long-term planning of municipal solid waste management systems (LPMSWMS) are ground on scenario-based structures. However, the scenario-based structures may overlook many real-world possibilities because of their restricted mass balances. This study is the first attempt to review the current state of optimization models, which are used as a decision-making
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Recent Advances in Constructing Three-Dimensional Graphitic Carbon Nitride Based Materials and Their Applications in Environmental Photocatalysis, Photo-Electrochemistry, and Electrochemistry J. Environ. Inform. (IF 7.0) Pub Date : 2024-01-31 W. Xia, X. Li, M. Cheng, W. P. Xiong, B. Song, Y. Liu, Y. Yang, W. J. Wang, S. Chen, G. M. Zeng, C. Y. Zhou
Recently, graphitic carbon nitride (g-C3N4), a promising visible-light-driven semiconductor material, has received enormous attention for photocatalytic water splitting, organic pollutant degradation, and CO2 reduction. However, the photocatalytic activity of bulk g-C3N4 is restricted due to the insufficient light adsorption, ineffective utilization of photogenerated charge carriers, and low specific
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Development and Optimization of A Low-Pressure Microbubble Scrubber for Air Pollutants Removal Using CFD J. Environ. Inform. (IF 7.0) Pub Date : 2024-01-31 H. Park, S. Yang, Y. Yoo, J. Jung, I. Moon, H. Cho, J. Kim
A microbubble scrubber is a hybrid type scrubber that combines the advantages of a general scrubber with the advantages of the microbubble. Microbubble which has generally under 50 μm diameter is one of the effective ways to remove air pollutants, like PM, NOx, and SOx. The low-pressure microbubble (LPMB) scrubber is a low-power, high-efficiency method that uses a blower to draw flue gas into the solution
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Suaeda salsa in Relation to Hydrological Connectivity: From the View of Plant Trait Networks J. Environ. Inform. (IF 7.0) Pub Date : 2024-01-31 Z. B. Yu, S. Yin, J. H. Bai, C. Wang, G. Z. Chen, W. Wang, Y. Q. Wang, B. S. Cui, X. H. Liu, X. W. Li
How plant traits respond to environment changes has been given more concerns worldwide. However, it is hard to reveal the integrative responses of plants only based on independent plant traits without considering the close links among plant traits. Plant trait network (PTN) is emerging as a new way to study how plant traits adapt to changing environment and to find out the key plant trait. We collected
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Optimal Configuration and Planning of Distributed Energy Systems Considering Renewable Energy Resources J. Environ. Inform. (IF 7.0) Pub Date : 2024-01-31 H. Taraghi Nazloo, R. Babazadeh, M. Varmazyar
With increasing electricity demand, conventional centralized power generation systems encounter numerous challenges, including transmission and distribution losses, limited capacity, and high operational costs. In response, distributed energy systems have emerged as a promising solution by enabling electricity generation in close proximity to consumption points. These systems leverage renewable energy
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Super Real-Time Forecast of Wildland Fire Spread by A Dual-Model Deep Learning Method J. Environ. Inform. (IF 7.0) Pub Date : 2024-01-31 Y. Z. Li, Z. L. Wang, X. Y. Huang
Driven by climate change, more frequent and extreme wildfires have brought a greater threat to humans globally. Fastspreading wildfires endanger the safety of residents in the wildland-urban interface. To mitigate the hazards of wildfires and facilitate early evacuation, a rapid and accurate forecast of wildfire spread is critical in emergency response. This study proposes a novel dualmodel deep learning
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Optimization Models for Long-Term Planning of Municipal Solid Waste Management Systems: A Review with An Emphasis on Mass Balances J. Environ. Inform. (IF 7.0) Pub Date : 2024-01-31 M. K. Korucu, İ. Kucukoglu
The vast majority of decision-making approaches used for long-term planning of municipal solid waste management systems (LPMSWMS) are ground on scenario-based structures. However, the scenario-based structures may overlook many real-world possibilities because of their restricted mass balances. This study is the first attempt to review the current state of optimization models, which are used as a decision-making
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Recent Advances in Constructing Three-Dimensional Graphitic Carbon Nitride Based Materials and Their Applications in Environmental Photocatalysis, Photo-Electrochemistry, and Electrochemistry J. Environ. Inform. (IF 7.0) Pub Date : 2024-01-31 W. Xia, X. Li, M. Cheng, W. P. Xiong, B. Song, Y. Liu, Y. Yang, W. J. Wang, S. Chen, G. M. Zeng, C. Y. Zhou
Recently, graphitic carbon nitride (g-C3N4), a promising visible-light-driven semiconductor material, has received enormous attention for photocatalytic water splitting, organic pollutant degradation, and CO2 reduction. However, the photocatalytic activity of bulk g-C3N4 is restricted due to the insufficient light adsorption, ineffective utilization of photogenerated charge carriers, and low specific
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Development and Optimization of A Low-Pressure Microbubble Scrubber for Air Pollutants Removal Using CFD J. Environ. Inform. (IF 7.0) Pub Date : 2024-01-31 H. Park, S. Yang, Y. Yoo, J. Jung, I. Moon, H. Cho, J. Kim
A microbubble scrubber is a hybrid type scrubber that combines the advantages of a general scrubber with the advantages of the microbubble. Microbubble which has generally under 50 μm diameter is one of the effective ways to remove air pollutants, like PM, NOx, and SOx. The low-pressure microbubble (LPMB) scrubber is a low-power, high-efficiency method that uses a blower to draw flue gas into the solution
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Suaeda salsa in Relation to Hydrological Connectivity: From the View of Plant Trait Networks J. Environ. Inform. (IF 7.0) Pub Date : 2024-01-31 Z. B. Yu, S. Yin, J. H. Bai, C. Wang, G. Z. Chen, W. Wang, Y. Q. Wang, B. S. Cui, X. H. Liu, X. W. Li
How plant traits respond to environment changes has been given more concerns worldwide. However, it is hard to reveal the integrative responses of plants only based on independent plant traits without considering the close links among plant traits. Plant trait network (PTN) is emerging as a new way to study how plant traits adapt to changing environment and to find out the key plant trait. We collected
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Optimal Configuration and Planning of Distributed Energy Systems Considering Renewable Energy Resources J. Environ. Inform. (IF 7.0) Pub Date : 2024-01-31 H. Taraghi Nazloo, R. Babazadeh, M. Varmazyar
With increasing electricity demand, conventional centralized power generation systems encounter numerous challenges, including transmission and distribution losses, limited capacity, and high operational costs. In response, distributed energy systems have emerged as a promising solution by enabling electricity generation in close proximity to consumption points. These systems leverage renewable energy
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Super Real-Time Forecast of Wildland Fire Spread by A Dual-Model Deep Learning Method J. Environ. Inform. (IF 7.0) Pub Date : 2024-01-31 Y. Z. Li, Z. L. Wang, X. Y. Huang
Driven by climate change, more frequent and extreme wildfires have brought a greater threat to humans globally. Fastspreading wildfires endanger the safety of residents in the wildland-urban interface. To mitigate the hazards of wildfires and facilitate early evacuation, a rapid and accurate forecast of wildfire spread is critical in emergency response. This study proposes a novel dualmodel deep learning
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Assessing Canopy Phenological Variations and Gross Primary Productivity in A Savanna Ecosystem in Yuanjiang, Yunnan Province of Southwest China J. Environ. Inform. (IF 7.0) Pub Date : 2023-09-17 S. T. Z. Myo, Y. P. Zhang, Q. H. Song , A. G. Chen, D. X. Yang, L. G. Zhou , Y. X. Lin, Z. Phyo, X. H. Fei , and N. S. Liang
Vegetation phenology is an important indicator of environmental change and strongly connected to forest ecosystem productivity change. This study aimed to analyse the pattern of phenological variations derived from digital imagery for the interpretation of ecosystem productivity. For 2014, 2015 and 2016, the seasonal phenological development of savanna was analysed by using towerbased imagery from
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A Comprehensive Review of Ontologies in the Hydrology Towards Guiding Next Generation Artificial Intelligence Applications J. Environ. Inform. (IF 7.0) Pub Date : 2023-09-17 Ö. Baydaroğlu, S. Yeşilköy, Y. Sermet, I. Demir
Big data generated by remote sensing, ground-based measurements, models and simulations, social media and crowdsourcing, and a wide range of structured and unstructured sources necessitates significant data and knowledge management efforts. Innovations and developments in information technology over the last couple of decades have made data and knowledge management possiblefor an insurmountable amount
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Numerical Modeling of Transboundary Groundwater Flow in the Bug and San Catchment Areas for Integrated Water Resource Management (Poland–Ukraine) J. Environ. Inform. (IF 7.0) Pub Date : 2023-09-17 T. Solovey, R. Janica, V. Harasymchuk, M. Przychodzka1, L. Yanush
On the Polish–Ukrainian borderlands, there is the Lublin–Lviv transboundary groundwater aquifer system, which is of key importance in shaping strategic groundwater resources. Due to the particular importance of this aquifer system, the two neighboring countries are obliged to undertake joint actions to protect it. The integrated management of the Lublin–Lviv aquifer system seems difficultdue to the
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Differences in China Greening Characteristics and its Contribution to Global Greening J. Environ. Inform. (IF 7.0) Pub Date : 2023-09-17 X. Zhang, D. H. Yan, T. L. Qin, C. H. Li, H. Wang
With the rapid emergence of the global greening phenomenon under remote sensing monitoring, the prevailing trend of phenomenon analysis and traceability research is self-evident. However, identifying characteristics is basic research of the greening phenomenon, which sometimes subverts research results. The choice of method may directly affect the difference in the greening-browning range, which is
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How Landscape Patterns Affect River Water Quality Spatially and Temporally: A Multiscale Geographically Weighted Regression Approach J. Environ. Inform. (IF 7.0) Pub Date : 2023-09-17 X. Li, J. Zhang, W. Yu, L. Liu, W. Wang, Z. Cui, W. Wang, R. Wang, and Y. Li
The water quality of a river can be considered a function of its surrounding landscape. Understanding the relationship between landscape patterns and river water quality is essential for optimizing landscape patterns to reduce watershed pollution and has not yet been solved. A multiscale geographically weighted regression (MGWR) model was used to explore the associations between the landscape patterns
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The Effects of Intra-Annual Variability of River Discharge on the Spatio-Temporal Dynamics of Saltmarsh Vegetation at River Mouth Bar: Insights from an Ecogeomorphological Model J. Environ. Inform. (IF 7.0) Pub Date : 2023-08-10 S. Zhang, W. Gao, D. Shao, W. Nardin, C. Gualtieri, T. Sun
Natural or human-induced intra-annual variation of river discharge alters estuarine hydrological regimes and further affects habitat conditions for saltmarsh vegetation, particularly at the river mouth bar. In this study, numerical experiments were performed in Delft3D to simulate the evolution of a schematized river mouth bar under prototypical unsteady river discharge scenarios. The simulated hydrodynamic
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Machine Learning Enhances Flood Resilience Measurement in a Coastal Area – Case Study of Morocco J. Environ. Inform. (IF 7.0) Pub Date : 2023-06-27 N. Satour, B. Benyacoub, N. El Moçayd, Z. Ennaimani, S. Niazi, N. Kassou, I. Kacimi
Understanding the characteristics contributing to enhancing flood resilience is a matter of urgency in managing urban areas, especially for developing countries, given the challenges imposed by climate change, social growth and urbanization. Identifying resilience metrics remains challenging, mainly because the concept is relatively new, methodological approaches are almost absent, and many types of
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Improving Predictions by Nonlinear Regression Models from Outlying Input Data J. Environ. Inform. (IF 7.0) Pub Date : 2023-05-25 W. W. Hsieh
When applying machine learning/statistical methods to the environmental sciences, nonlinear regression (NLR) models often perform only slightly better and occasionally worse than linear regression (LR). The proposed reason for this conundrum is that NLR models can give predictions much worse than LR when given input data which lie outside the domain used in model training. Continuous unbounded variables
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Time-Series Forecasting of Chlorophyll-a in Coastal Areas Using LSTM, GRU and Attention-Based RNN Models J. Environ. Inform. (IF 7.0) Pub Date : 2023-05-25 S. S. Wu, Z. H. Du, F. Zhang, Y. Zhou, R. Y. Liu
The chlorophyll-a (Chl-a) concentration is commonly considered as the main indicator of phytoplankton biomass in coastal waters. Forecasting and understanding the status of Chl-a is beneficial to coastal ecosystem management and is an important emergency management measure for algae blooms. To obtain accurate predictions, the long short-term memory neural network (LSTM) and gated recurrent unit neural
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Sb (III) Removal from Aqueous Solutions by the Mesoporous Fe 3 O 4 /GO Nanocomposites: Modeling and Optimization Using Artificial Intelligence J. Environ. Inform. (IF 7.0) Pub Date : 2023-05-25 X. L. Wu, R. S. Cao, J. W. Hu, C. Zhou, X. H. Wei
The mesoporous graphene oxide-supported ferroferric oxide (Fe3O4/GO) nanocomposites (the average size of 30.08 nm) were controllably synthesized in the present study. The successful in situ growth of Fe3O4 nanoparticles on GO surface was ascribed to the oxygen-containing groups on GO. The magnetic separation was employed for Sb(III) removal from aqueous solutions and artificial intelligence techniques
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Specificality, Quality Variation, Assessment and Treatment of Estuarine Water in the Pearl River Delta, South China J. Environ. Inform. (IF 7.0) Pub Date : 2023-05-25 H. F. Tian, H. N. Ren, X. Y. Li, X. D. Zhang, X. Xu, S. G. Wang
The Pearl River Delta (PRD) is a major economic and manufacturing area in South China. Using the comprehensive and authoritative monitoring data, this study conducted a systematic review of the regularity of marine disasters (e.g., storm surges, saltwater intrusions, and red tides), water quality variations, water quality risk assessments and wastewater treatment in seven sections of the Pearl River
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Assessing Environmental Oil Spill Based on Fluorescence Images of Water Samples and Deep Learning J. Environ. Inform. (IF 7.0) Pub Date : 2023-02-17 D. P. Liu, M. Liu, G. Y. Sun, Z. Q. Zhou, D. L. Wang, F. He, J. X. Li, J. C. Xie, R. Gettler, E. Brunson, J. Steevens, D. Xu
Measuring oil concentration in the aquatic environment is essential for determining the potential exposure, risk, or injury for oil spill response and natural resource damage assessment. Conventional analytical chemistry methods require samples to be collected in the field, shipped, and processed in the laboratory, which is also rather time-consuming, laborious, and costly. For rapid field response
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Rice Plant Leaf Disease Detection and Classification Using Optimization Enabled Deep Learning J. Environ. Inform. (IF 7.0) Pub Date : 2023-02-17 T. Daniya, S. Vigneshwari
An automatic identification and classification of rice diseases are very important in the domain of agriculture. Deep learning (DL) is an effective research area in the identification of agriculture pattern identification where it can effectively resolve the issues of diseases identification. In this paper, a hybrid optimization algorithm is developed to categorize the plant diseases. The pre-processing
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Spatial Heterogeneity of Food Webs in A River-Lake Ecotone under Flow Regulation – A Case Study in Northern China J. Environ. Inform. (IF 7.0) Pub Date : 2023-02-17 W. Yang, X. T. Fu, X. X. Li, B. S. Cui, X. A. Yin
The river–lake ecotone supports diverse aquatic life, but its food web structure and topology are poorly understood. Baiyangdian Lake, northern China’s largest shallow lake, depends on external environmental flows, of which the Fu River provides the most stable water supply. Here, we used stable isotopes and topological analysis to explore the food web structure along a spatial gradient using data
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Hybrid Forecasting of Wind for Air Pollution Dispersion over Complex Terrain J. Environ. Inform. (IF 7.0) Pub Date : 2023-02-16 M. Perne, J. Kocijan, M. Z. Božnar, B. Grašič, P. Mlakar
In case of an unplanned emission event from a nuclear power plant, the local population can be protected more efficiently when valid atmospheric dispersion model results are available. Atmospheric dispersion models use local meteorological variables as inputs. When atmospheric dispersion in the future is being predicted, a forecast of the local meteorological variables is needed. The most important
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Rapid Prototyping of An Automated Sensor-to-Server Environmental Data Acquisition System Adopting A FAIR-Oriented Approach J. Environ. Inform. (IF 7.0) Pub Date : 2023-01-13 P. Celicourt, R. D. Sam, M. Piasecki
Most existing environmental data acquisition systems are not designed to support automatic field data streaming to a data management system, but instead involve manual data exports therein. This paper introduces a FAIR-oriented (Findable, Accessible, Interoperable, and Reusable) approach and prototype of an automated sensor-to-web services and analytics wireless sensor network in which the aspects
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Lateral Hydrological Connectivity Driven by Tidal Flooding Regulates Range-Expansion of Invasive Spartina alterniflora in Tidal Channel-Salt Marsh Systems J. Environ. Inform. (IF 7.0) Pub Date : 2023-01-13 Z. H. Ning, C. Chen, S. Y. Zhang, A. D. Wang, Q. Wang, T. Xie, J. H. Bai, B. S. Cui
Understanding how hydrological features affect habitat invasibility is crucial for predicting whether variations of such hydrological features may act as important inducement regulating range-expansion of invasive species in tidal channel-salt marsh systems. Although lateral hydrological connectivity (LC), or the hydrological connections between tidal channels and adjacent marsh flats, is an important
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Centennial Assessment of Greenhouse Gases Emissions of Young and Old Hydroelectric Reservoir in Mediterranean Mainland J. Environ. Inform. (IF 7.0) Pub Date : 2023-01-13 E. Amanatidou, G. Samiotis, E. Trikoilidou, L. Tsikritzis, N. Taousanidis
The quantities of emitted greenhouse gases (GHG) from hydroelectric reservoirs around the world, especially in warm latitudes, have tarnished the green credentials of hydroelectric energy. The accurate measurement and evaluation of the emitted GHG, which is a critical element in climate change policy, present a significant challenge. Many works have been focused on GHG emissions assessment from reservoirs
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Multifunctional PVDF Membrane Coated with ZnO-Ag Nanocomposites for Wastewater Treatment and Fouling Mitigation: Factorial and Mechanism Analyses J. Environ. Inform. (IF 7.0) Pub Date : 2023-01-13 X. J. Chen, C. Z. Huang, R. F. Feng, P. Zhang, Y. H. Wu, W. W. Huang
In this study, a multifunctional poly(vinylidene fluoride) (PVDF) membrane was developed through chemical binding with ZnO-Ag nanocomposites to increase wastewater treatment efficiency. The unique characteristics of ZnO-Ag nanocomposites endowed the membrane with high surface hydrophilicity, organic/bio fouling resistance, and photocatalytic antibacterial activity. The significantly decreased water
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A Two-Stage Stochastic Fuzzy Mixed-Integer Linear Programming Approach for Water Resource Allocation under Uncertainty in Ajabshir Qaleh Chay Dam J. Environ. Inform. (IF 7.0) Pub Date : 2023-01-13 J. Nematian
Due to the dry climate and unsuitable distribution of rainfall in Iran, sustainable agriculture depends on the proper use of water resources. In this study, the optimal allocation of water at Ajabshir Qaleh Chay Dam in agricultural sector is investigated using an interval parameter two-stage stochastic mixed-integer linear programming approach. Indeed, interval parameters two-stage stochastic programming
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Spatiotemporal Variation of Nitrogen Dioxide and Nighttime Light Dataset of Iranian Metropolises in the COVID-19 Outbreak J. Environ. Inform. (IF 7.0) Pub Date : 2023-01-13 S. Sangi, S. Falahatkar, M. Gholamalifard
COVID-19 lockdown has caused a reduction in traffic volume and industrial activities which are the main sources of air pollution in whole of the world. As tropospheric NO2 pollutant and nighttime light (NTL) are the representative of human activities, this study focused to quantify the annual and monthly change of NO2 concentration and NTL in 14 metropolises of Iran before, during and after the lockdown
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Toward An Assessment of Runoff and Thermal Connectivity in A River-Lake System within An Urban Environment J. Environ. Inform. (IF 7.0) Pub Date : 2022-09-28 Y. L. Liu, J. Z. Du, Q. Wang, W. Yang, B. S. Cui
The term ‘hydrological connectivity’ is used in different disciplines to refer to the water-mediated transfer of matter, energy, and/or organisms within or between elements of the hydrologic cycle. Extensive research has been devoted to methods of evaluating hydrological connectivity. However, most of these methods pertain to the connectivity of runoff, sediment, chemicals, and organisms. To our knowledge
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Technology Development for the Removal of Covid-19 Pharmaceutical Active Compounds from Water and Wastewater: A Review J. Environ. Inform. (IF 7.0) Pub Date : 2022-09-28 S. Hashemi Safaei, S. Young, Z. Samimi, F. Parvizi, A. Shokrollahi, M. Baniamer
The novel coronavirus (SARS-CoV-2) outbreak has given rise to an inevitable worldwide application of a wide variety of drugs. Some of these pharmaceutical compounds pass through water and wastewater treatment processes and appear in treated water, wastewater and biosolids. These have posed potential risks to the water quality of aquatic ecosystems and public health. As a result, the failure to lessen
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Statistical Optimization of Microcystis Growth and Microcystin Production in Natural Phytoplankton Community using Microcosm Bioassays J. Environ. Inform. (IF 7.0) Pub Date : 2022-07-03 Z. Y. Wang, P. F. Wang, C. Wang, S. H. Zhang, J. Hou, Y. H. Ao
Eutrophication of freshwater lakes and reservoirs causing toxic cyanobacterial blooms has become a global health concern. Commonly used approaches of statistical modelling have not fully captured the complex response of cyanobacterial biomass and mi- crocystin concentration in response to stochastic variation of ambient conditions. This study applied statistically-based experimental design to screen
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In-Situ Construction of La-B Co-Doped g-C3N4 for Highly Efficient Photocatalytic H2 Production and RhB Degradation J. Environ. Inform. (IF 7.0) Pub Date : 2022-07-03 L. N. Wang, L. H. Xiao, Q. Jin, Q. Chang
Doped graphitic carbon nitride (g-C3N4) has been investigated as the visible light photocatalyst for photocatalytic H2 production and organic pollution removal. The elements doping could change the nanostructures, surface composition, and electronic structurescompared to pure g-C3N4. Such changes will provide better light-harvesting, more active sites and enhanced charge separation. In this work, we
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A Non-Parametric Approach for Change-Point Detection of Multi-Parameters in Time-Series Data J. Environ. Inform. (IF 7.0) Pub Date : 2022-05-23 Y. M. Hu, C. X. Yang, Z. M. Liang, X. Y. Luo, Y. X. Huang, C. Tang
Change-point analysis of time-series data plays a vital role in various fields of earth sciences under changing environments. Most of the analysis approaches were usually designed to detect the change-point in the level of time-series mean. In this study, we aimed to propose a non-parametric approach to detect the change-point of different parameters of time-series data. In this approach, the Boot-
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Reduction of Pollution through Sustainable and Flexible Production by Controlling By-Products J. Environ. Inform. (IF 7.0) Pub Date : 2022-05-23 D. Yadav, R. Singh, A. Kumar, B. Sarkar
Every manufacturing system produces toxic by-products that cause a hazardous impact on society and the environment. As a result, pollution control authorities’ role has gained importance for the betterment of society and the preservation of a clean and green environment. As a result, one of the goals of this research is to develop a sustainable smart manufacturing model with less waste and controlled
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Design and Application of the Tank Simulation Model (TSM): Assessing the Ability of Rainwater Harvesting to Meet Domestic Water Demand J. Environ. Inform. (IF 7.0) Pub Date : 2022-04-28 C. J. Schuster-Wallace, S. E. Dickson-Anderson, S. M. Papalexiou, A. El Ganzouri
Rainwater harvesting (RWH) is a necessary technology to supplement and/or replace insufficient ground and surface water resources for domestic water supplies, especially under changing climate conditions. An accessible and flexible Excel-based RWH simulation tool is developed and applied to investigate the utility of RWH in two regional case studies, under both present conditions and future climate
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Solar Photovoltaic Utilization in Electricity Generation to Tackle Climate Change J. Environ. Inform. (IF 7.0) Pub Date : 2022-04-28 H. Demirhan
Climate change is threatening nature by impacting the vital processes of life. The efforts to mitigate climate change mainly focus on utilizing renewable energy sources in high energy consumption areas. This article studies the contribution of solar photovoltaic (PV) utilization in electricity generation to climate change mitigation through a comprehensive modeling framework. The mean temperature anomalies
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Development of A Simulation-Based Multi-Objective Optimization Method for Improving the Advanced Oxidizing Capacity of Hydrodynamic Cavitation Reactor - A Case Study of Self-Excited Oscillation Cavity J. Environ. Inform. (IF 7.0) Pub Date : 2022-01-22 S. L. Nie, J. K. Zhou, H. Ji, Z. Y. Dai, Z. H. Ma
In this study, a simulation-based multi-objective optimization method is developed for optimizing the structural design of hydrodynamic cavitation (HC) reactor and improving the cavitation effect of HC reactor. The developed method integrates simulation technique of computational fluid dynamics (CFD) and optimization techniques of surrogate model and nondominated sorting genetic algorithm II (NSGA-II)
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Dye Pollutant Removal from Synthetic Wastewater: A New Modeling and Predicting Approach Based on Experimental Data Analysis, Kriging Interpolation Method, and Computational Intelligence Techniques J. Environ. Inform. (IF 7.0) Pub Date : 2022-01-08 M. Valikhan Anaraki, F. Mahmoudian, F. Nabizadeh Chianeh, S. Farzin
In the present study, a new approach by coupling the interpolation method with computation-based technique (data-mining algorithms and an optimization algorithm) is introduced for modeling and optimization removal of Reactive Orange 7 (RO7) dye removal from synthetic wastewater. To this end, four significant factors like pH, electrolyte concentration, current density, and electrolysis time are considered
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Projection Pursuit Method Based on Connection Cloud Model for Assessment of Debris Flow Disasters J. Environ. Inform. (IF 7.0) Pub Date : 2022-01-08 M. W. Wang, Y. Wang, F. Q. Shen, J. L. Jin
A rational evaluation of the danger of debris flow disasters at the regional scale is essential for developing effective disas-ter prevention measures and economic planning in debris flow-prone areas. A novel projection pursuit method based on the connection cloud model and fruit fly optimization algorithm is addressed to analyze the dangerous degree of debris flow disasters at the regional scale,
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Social Media Integration of Flood Data: A Vine Copula-Based Approach J. Environ. Inform. (IF 7.0) Pub Date : 2022-01-08 L. Ansell, L. Dalla Valle
Floods are the most common and among the most severe natural disasters in many countries around the world. As global warming continues to exacerbate sea level rise and extreme weather, governmental authorities and environmental agencies are facing the pressing need of timely and accurate evaluations and predictions of flood risks. Current flood forecasts are generally based on historical measurements
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Combining Scientific Facts and Significance Criteria to Predict the Result of an Environmental Impact Assessment Review J. Environ. Inform. (IF 7.0) Pub Date : 2022-01-01 K. F. R. Liu,H. H. Liang,C. W. Chen,J. S. Chen,Y. S. Shen
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Integrating Linear Physical Programming and Fuzzy Programming for the Management of Third Party Reverse Logistics Providers J. Environ. Inform. (IF 7.0) Pub Date : 2021-12-08 M. A. Ilgin
ABSTRACT. Shorter product lifecycles, more liberal return policies and the rise of internet marketing increased the amount of product returns in recent years. Companies must have a well-managed reverse logistics system to ensure the timely and cost-effective collection, processing and disposal of returned products. However, high fixed cost of reverse logistics infrastructure and high level of uncertainty
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Spatiotemporal Modelling of Groundwater Flow and Nitrate Contamination in An Agriculture-Dominated Watershed J. Environ. Inform. (IF 7.0) Pub Date : 2021-12-08 M. Eryiğit, B. Engel
In this study, both groundwater flow and nitrate transport were simulated in the Upper White River Watershed (Indiana, US) dominated by agricultural production. MODFLOW and MT3DMS were used for groundwater flow and contaminant transport modelling of the watershed under transient conditions. The input files for MODFLOW and MT3DMS were obtained by the GMS groundwater simulator. Model simulations were
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Assessment of Pollution and Ecological Risk Index of Heavy Metals in the Surface Sediment of Estuary and the Coastal Environment of Bay of Bengal J. Environ. Inform. (IF 7.0) Pub Date : 2021-09-09 M. K. Khadanga, R. K. Mishra, B. K. Sahu
The Mahanadi River, surrounding estuaries along the coastal water are important to understand the relationship between heavy metals, ecosystem and human health, as the region being used largely by fisher communities for the potential fishing ground and agriculture. The study evaluates the ecological risk index of heavy metals in the surface sediments along the coastal environment of the Bay of Bengal
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Preparation of Diatomite Based Porous Slow-Release Materials and its Adsorption-Release Properties on Phoxim J. Environ. Inform. (IF 7.0) Pub Date : 2021-08-31 Y. Liu, Y. Zhang, X. R. Sheng, N. Li, Q. W. Ping, M. H. Niu, P. Lu, J. Zhang
Slow-release materials have the property of controlling the slow-release of drugs. At present, polymer slow-release materials have been widely studied, but the stability is poor and the release effect of components is difficult to control. The diatomite mineral is light in weight, small in volume and stable in physical and chemical properties. A series of diatomite based porous slow-release materials
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EVI Indicated Spatial-Temporal Variations in Vegetation and Their Responses to Climatic and Anthropogenic Factors in the Chinese Mainland Since 2000s J. Environ. Inform. (IF 7.0) Pub Date : 2021-08-31 Z. Yuan, J. J. Xu, J. Chen, Y. Q. Wang, J. Yin
Terrestrial ecosystems of China play an important role in global carbon cycle. Identifying spatial-temporal variation of vegetation and their driving forces in China is necessary. This study used recent Enhanced Vegetation Index (EVI) data (2000 to 2019) to analyze interannual changes of vegetation activity in mainland China, and examined their responses to climatic (precipitation and temperature)
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Method for Determining Optimum Operational Conditions of Microbubble Scrubber Using Image Processing J. Environ. Inform. (IF 7.0) Pub Date : 2021-07-06 Y. Yoo, H. Park, Y. Choi, J. Jung, H. Song, J. Kim, H. Cho
This paper presents an image-processing-based model for calculating the interfacial-area concentration (IAC) of a low-pressure microbubble (LPMB) scrubber, which facilitates the determination of operational conditions of the scrubber via flow-pattern analysis. The LPMB scrubber maximizes the interfacial area of two-phase systems using the bubbly flow. Microbubbles have received attention due to their
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Parameter Uncertainty and Sensitivity Evaluation of Copula-Based Multivariate Hydroclimatic Risk Assessment J. Environ. Inform. (IF 7.0) Pub Date : 2021-07-28 K. Huang, Y. R. Fan
Extensive uncertainties exist in hydroclimatic risk analysis. Especially in multivariate hydrologic risk inferences, uncertainties in individual hydroclimatic extremes such as floods and their dependence structure may lead to bias and uncertainty in future hydrologic risk predictions. In this study, a parameter uncertainty and sensitivity evaluation (PUSE) framework is proposed to quantify parameter
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Development of An Integrated Method (MGCMs-SCA-FER) for Assessing the Impacts of Climate Change – A Case Study of Jing-Jin-Ji Region J. Environ. Inform. (IF 7.0) Pub Date : 2021-07-28 H. Mei, Y. P. Li, J. Lv, X. J. Chen, C. Lu, C. Suo, Y. Ma
In this study, an integrated method (abbreviated as MGCMs-SCA-FER) is developed for assessing the impacts of climate change, which incorporates multiple global climate models (MGCMs), stepwise cluster analysis (SCA), and fixed-effects regression (FER) within a general framework. MGCMs-SCA-FER is capable of (i) dealing with the uncertainty in climate change projection caused by heterogeneity of structures
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Assessing Human Health Risk to DNAPLs Exposure in Bayesian Uncertainty Analysis J. Environ. Inform. (IF 7.0) Pub Date : 2021-07-18 Y. Pan, X. K. Zeng, X. Y. Gao, H. X. Xu, Y. Y. Sun, D. Wang, J. C. Wu
The human health risk (HHR) assessment to dense non-aqueous phase liquids (DNAPLs) exposure has become an important part of groundwater environment management. Usually, DNAPL transport models are applied to simulate the concentration distribution of contaminant for HHR assessment. The present paper studied the influences of model uncertainties on the HHR assessment, and the metric of Incremental Lifetime
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Regulation and Management of Lake Eutrophication in Urban Regions Based on the Improved Model-Yan-Model II J. Environ. Inform. (IF 7.0) Pub Date : 2021-07-08 Z. Q. Yan, M. Y. Jiao, Y. F. Wang, B. C. Xia
The construction of a model based on an analytic system and dynamic structure is an important technique in lake manage-ment. The Yan-Model conducts system simulations based on the dynamics of the main aquatic species but does not include filter-feeding fish and N elements, which have important effects on eutrophication. Based on the Yan-Model, modules for the filter-feeding fish A. nobilis and the
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A New Method for Computing the Sediment Delivery Ratio for the Hyper-Concentrated Flow Areas of the Loess Plateau, China J. Environ. Inform. (IF 7.0) Pub Date : 2021-06-16 T. H. Li, W. C. Xie
The sediment delivery ratio (SDR) is an important index for understanding sediment erosion, transportation and deposition features in a river basin. Based on the commonly accepted definition of SDR and the characteristics of the sediment delivery process in hyper-concentrated flow areas of the Loess Plateau, China, a new model for computing the SDR is proposed. The model is a functional relation of
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Time Variant Interval Linear Programming for Environmental Management Systems J. Environ. Inform. (IF 7.0) Pub Date : 2021-06-09 Z. Xiao, J. Y. Du, Y. Guo, X. Li, L. Guo
Optimization technology is widely applied to maximize economic profit under ecology constrains in environmental management systems. To tackle the inherent uncertainties, inexact optimization methods have been proposed. Interval linear program- ming (ILP) model has drawn increasing scholarly attention. ILP model describe uncertainty by one coarse scaled stochastic process. However, uncertainty often
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Predicting the Potential Distribution of Three Allergenic Invasive Ambrosia (ragweed) Species in Asia J. Environ. Inform. (IF 7.0) Pub Date : 2021-05-18 Z. Qin, J. E. Zhang, A. DiTommaso, J. M. Diez, Y. Zhao, F. G. Wang
Three ragweed species native to North America (Ambrosia artemisiifolia L., A. psilostachya DC, and A. trifida L.) that have been introduced into Asia are now spreading quickly in many regions. Predicting which specific areas may be vulnerable to the invasion of these allergenic Ambrosia species can provide valuable insights for early detection and for prioritizing preventive actions. Species distribution
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Spatial-Temporal Distribution of Disability-Adjusted Life-Years of Lung Cancer Attributable to Ambient PM2.5 in Guangzhou, China, 2010 ~ 2013: A Population-Based Study J. Environ. Inform. (IF 7.0) Pub Date : 2021-03-29 X. Lin, H. Dong, G. Z. Lin, Y. Li, Q. Y. Yang, Y. Liao, A. Luo, B. L. Liang, Z. C. Yang, Y. T. Hao
The authors describe district-specific disability-adjusted life-year (DALY) of lung cancer attributable to ambient particulate matter < 2.5 um in diameter (PM2.5) for Guangzhou city in China, so as to help prioritizing environmental health action from geospatial perspective. Comparative risk assessment and satellite-derived PM2.5 concentrations were used to investigate the spatial-temporal distribution