The Global NEST Journal is an open access journal that publishes original research articles, short papers and critical reviews on all aspects of Environmental Science and Technology. These comprise, but are not limited to, Pollution Control Technology, Global Environmental Change, Air Quality, Water Quality, Water and Waste Water Treatment, Solid Waste Management, Hazardous Substances and Risk Analysis, Emerging pollutants. Relevant topics incorporating the methodologies and state of the art of disciplines such as Environmental Management Policies, Ecosystems and Natural Resources Management, Hydrology and Water Resources Management, Clean Energy and Sustainability are included.
Submitted manuscripts are initially reviewed by the editor and selected after rigorous peer review by scientists in order to assess the significance, originality and appropriateness for publication.
Articles submitted to Global NEST Journal benefit from its broad scope and readership. We aim for a turnaround time of 4 weeks from submission to first decision.
Global NEST Journal is addressed to professionals in Academic, Consulting Offices, Government Agencies and Organisations, as well as others responsible for the investigations, evaluation of complicated environmental issues of global interest.
The 2024 Scopus CiteScore for the Global NEST Journal is 2.36. It is also ranked in the Q3 quartile for Environmental Science (miscellaneous).
Here's a breakdown of other key metrics:
- H-index: 41
- SJR: 0.250 (Q3)
- SNIP score: 0.48
Journal Impact Factor (JIF): The Journal Impact Factor (JIF) is not directly calculated in Scopus and is based on Web of Science data. Web of Science data. However, the Global NEST Journal does have a JIF, and the Journal Impact Factor (JIF) is 1.5-year Impact Factor is 1.1.
Scimago Journal and Country Rank (Scimago) provides information on the journal's H-index and SJR, while Researcher.Life lists the CiteScore and quartile. Web of Science Journal Info lists the JIF.
Deep Learning and Machine Learning based Air Pollution Prediction Model for Smart Environment Design Planning
Air pollution and health
For the past few decades, owing to human activities, urbanization, and industrialization, air pollution is becoming severe across several countries. Deep Learning (DL) and Machine Learning (ML) techniques had great contribution to the development of methods in various aspects of prediction, planning...
A Real-time Environmental Air Pollution Predictor Model Using Dense Deep Learning Approach in IoT Infrastructure
Air pollution and health
With the technical advancements in Deep Learning (DL), it is probable to construct the predictor model for monitoring and controlling pollution from real-time data. Here, IoT techniques are used for sensing the emission rate from various factors and the predictor model is constructed using the...
Exploiting Drone Images for Forest Fire Detection using Metaheuristics with Deep Learning Model
Environmental management and policy
Forest fires are a global natural calamity causing significant economic damage and loss of lives. Professionals forecast that forest fires would raise in the future because of climate change. Early prediction and identification of fire spread would enhance firefighting and reduce affected zones...
Air Quality Prediction using Ensemble Voting based Deep Learning with Mud Ring Algorithm for Intelligent Transportation Systems
Air pollution and health
In recent times, advanced technologies in transportation are developing like connected and automated vehicles and shared mobility services. A rapidly increasing number of vehicles in intelligent transportation system (ITS) and smart cities causes pollution and degrade the quality of air. Owing to...
Short-Term Prediction of PM2.5 Pollution with Deep Learning Methods
Air pollution and health
Particulate matter (PM), classified according to aerodynamic diameter, is one of the harmful pollutants causing health damaging effects. It is considered as cancerogenic by the World Health Organization (WHO) because of the substances found in the chemical composition of PM. In this study, short...
Integrated Disaster Risk Management for Flood Detection on Remote Sensing Images using Deep Learning techniques
Hydrology and Water Resources Management
Floods are one of the leading causes of damage, prompting mortality and substantial destruction to the structure and total economy of the affected nations. Remote sensing, satellite imagery, global positioning system, and geographic information system (GIS) are widely employed for flood...
An Efficient Flood Forecasting Model Using an Optimal Deep Belief Network
Hydrology and Water Resources Management
Floods inflict significant damage globally each year, underscoring the importance of accurate and timely flood prediction to mitigate property loss and life. Precise flood prediction provides governments with crucial preemptive alerts regarding potential flood disasters, enabling timely evacuations...
Deep Learning Driven Crop Classification and Chlorophyll Content Estimation for the Nexus Food higher Productions using Multi-spectral Remote Sensing Images
Hydrology and Water Resources Management
Due to the development of open access medium-high resolution remote sensing data like multispectral remote sensing images, crop classification becomes a hot research topic to be realized on large scale using machine learning (ML) models. At the same time, chlorophyll content is a critical index used...
A deep learning model and optimization algorithm to forecasting Environment Monitoring of the Air pollution
Air pollution and health
Air pollution monitoring is becoming increasingly important, with an emphasis on the effects on human health. Because nitrogen dioxide (NO2) and sulphur dioxide (SO2) are the principal pollutants, many models for forecasting their potential harm have been created. Nonetheless, making precise...
Water Quality Index Prediction and Classification using Hyperparameter Tuned Deep Learning Approach
Air pollution and health
Water quality (WQ) is hugely important for animals, humans, plants, industries, and the environment. In the past few years, the WQ has been compressed by pollution and contamination. Usually, WQ is assessed utilizing costly laboratory and arithmetical processes, making real observation ineffective...
A Deep Learning-Based Buffalo Optimizer based Squeeze and Excitation Network for Garbage Classification for a Sustainable Environment
Solid Waste Management
A Squeeze and Excitation Network is a deep-learning architectural component designed to enhance networks. The "squeeze" step reduces the spatial dimensions of the input feature maps, and the "excitation" step adaptively recalibrates channel-wise feature responses. This allows the network to focus on...
Modeling of Internet of Things Enabled Sustainable Environment Air Pollution Monitoring System
Air pollution and health
Air quality, radiation pollution, and water pollution were thekey featuresthat possess genuine challenges to the environment. Proper monitoring wasneededin such a way that the world couldaccomplish sustainable development, withkeeping a healthy society. Recently, environment monitoring is become a...
Improving Water Quality Assessment through Anomaly Detection Using Hybrid Convolutional Neural Network Approach
Air pollution and health
Water being a precious commodity for every person around the world needs to be quality monitored continuously for ensuring safety whilst usage. The water data collected from sensors in water plants are used for water quality assessment. The anomaly present in the water data seriously affects the...
Advanced deep learning method for Aerial image segmentation of landscape changes in pre-and post-disaster scenarios
Environmental data analysis and modelling
The precise analysis of conditions in the landscape before and aftermath of the disaster is a mandatory challenge in aerial image landscape monitoring. The change in patterns of landscape, damaged pathways, and damaged areas will have a major impact without monitoring and redevelopment. Therefore...
Enhancement of Advanced Oxidation Processes in Oil Refinery Wastewater Treatment Using Deep Neural Networks
Water and wastewater treatment and reuse
The complex composition of persistent and resistant contaminants in oil refinery wastewater presents a significant environmental challenge that conventional treatment methods frequently fail to effectively address. Advanced Oxidation Processes (AOPs), specifically the photo-Fenton method, and a deep...
Water quality assessment in coastal lagoons using improved back propagation deep neural network with PH level compensation sensors in smart environment
Air pollution and health
In coastal lagoons, eutrophication is a significant ecological and environmental problem. The majority of the pollution and deterioration problems that coastal zones and their ecosystems face are due to human influence through urbanization and industrialization. In this research, evaluations of...
Prediction of Particulate Matter PM2.5 Using Bidirectional Gated Recurrent Unit with Feature Selection
Air pollution and health
In recent years, air pollution has increased with industrialization and urbanization globally. It is an important hazardous factor that causes severe health issues to community’s health. Among the number of pollutants in air, PM2.5 is very dangerous due to its very small, 2.5µm, diameter. The PM2.5...
An Intelligent Weather Prediction Model Using Optimized 1D CNN With Attention GRU
Climate change
One of the main factors affecting human livelihoods is weather events. High weather disasters with forest fires, high air temperature, and global warming that cause drought. An efficient and accurate weather forecasting approach is required to take measures against climate disasters. Therefore, it...
Internet of Things Enabled Smart Solid Waste Management System
Solid Waste Management
The Internet of Things (IoT) paradigm roles a crucial play to enhance smart city applications by controlling and tracking city procedures in real-time. Among the most important problems connected to smart city application is solid waste management that is a negative impression on our people's health...
An intelligent air quality monitoring system using quality indicators and Transfer learning based Lightweight recurrent network with skip connection
Air pollution and health
Rapid industrialization and urbanization have resulted in poor air quality, which poses a risk to human health by causing a variety of lung diseases. The precise forecast of air quality is of practical importance. Consequently, the development of an automated air pollution monitoring system based on...
Rural Tourism Image Optimization by Big Data Technology in Green Environment
Environmental management and policy
In recent years, the need for the rapid development of rural tourism in China has resulted in a large consumption of ecological resources, which has seriously damaged the ecological balance of travel destinations. Rural tourism in many parts of China is increasingly lacking distinctive local...
Effective Deep Learning based Prediction Model for Groundwater Quality Assessment using Physio-chemical Parameters
Air pollution and health
The purpose of this study is to anticipate and investigate the groundwater quality in the regions of the Cauvery basin. In the post-monsoon season of 2020, 800 samples were collected from 200 different places for this paper. The AlexNet model is used in this book to forecast the water quality. In...
Impact of ultraviolet radiation on human skin owing to ozone depletion
Water and wastewater treatment and reuse
Depletion of ozone molecules in the stratospheric layer surges the flow of ultraviolet (UV) rays on the surface of the earth. Generally, UV rays are the hazardous energy waves emitted from the sun that can cause acute and chronic effects on bio species. Exposure to UV rays in humans causes skin...
Air Pollution Prediction using Attention Module With CNN -OptBiLSTM
Air pollution and health
Predicting air pollution using environmental data assessment parameters becomes increasingly significant amid growing fears about climate change and the sustainability of urban areas. The use of sophisticated deep learning (DL) methods to model the intricate relation among these variables represents...
Neutralize the pH of Waste Water Using Intelligent Controllers for Industrial Reuse
Water and wastewater treatment and reuse
Water waste management is one of the major hassles which is faced by the majority of industries. The industries let the wastewater into flowing streams or rivers near them, polluting the water resources in that locality. To prevent and safeguard the water resources, the government has given much...
Climate change
16-05-2025
Water and wastewater treatment and reuse
16-05-2025
Environmental management and policy
13-05-2025
Solid Waste Management
12-05-2025
Circular Economy and Bioeconomy
12-05-2025
Environmental management and policy
09-05-2025
Sustainable Energy
05-05-2025
Water and wastewater treatment and reuse
05-05-2025
Hydrology and Water Resources Management
16-06-2025
Circular Economy and Bioeconomy
12-06-2025
Hydrology and Water Resources Management
12-06-2025
Climate change
04-06-2025
Solid Waste Management
04-06-2025
Sustainable Energy
04-06-2025
Environmental management and policy
04-06-2025
Water and wastewater treatment and reuse
04-06-2025
Hydrology and Water Resources Management
02-06-2025
