Real time image-based air quality forecasts using a 3D-CNN approach with an attention mechanism.

This study presented an image-based deep learning method to improve the recognition of air quality from images and produce accurate multiple horizon forecasts. The proposed model was designed to incorporate a three-dimensional convolutional neural network (3D-CNN) and the gated recurrent unit (GRU) with an attention mechanism. This study included two novelties; (i) the 3D-CNN model structure was built to extract the hidden features of multiple dimensional datasets and recognize the relevant environmental variables.

Evaluation of environmental impact of red tide around Pearl River Estuary, Guangdong, China.

This paper presents a case study of red tide hazards around the Pearl River Estuary (PRE). Red tide hazards, meteorological data, and seawater monitoring data were collected from 1996 to 2020 at different locations around the PRE to investigate the internal and external factors influencing the occurrence of red tides. The enhancement of the assessment of estuarine trophic status (ASSETS) method enables us to evaluate the effects of meteorological factors and seawater eutrophication status on the red tide risk level.

Spatiotemporal air quality forecasting and health risk assessment over smart city of NEOM.

Modeling and predicting air pollution concentrations is important to provide early warnings about harmful atmospheric substances. However, uncertainty in the dynamic process and limited information about chemical constituents and emissions sources make air-quality predictions very difficult. This study proposed a novel deep-learning method to extract high levels of abstraction in data and capture spatiotemporal features at hourly and daily time intervals in NEOM City, Saudi Arabia.

Prediction of long-term water quality using machine learning enhanced by Bayesian optimisation.

Water quality assessment is critical to better recognise the importance of water in human society. In this study, a new framework to predict long-term water quality is proposed by using Bayesian-optimised machine learning methods and key pollution indicators collected from monitoring stations in the Pearl River Estuary, Guangdong, China. The optimised stacked generalisation (SG-op) model achieved the best performance with the highest accuracy (0.

A VIKOR-based approach to evaluate river contamination risks caused by wastewater treatment plant discharges.

Wastewater treatment plants (WWTPs) rarely eliminate emerging contaminants from effluents they discharged into waterways, and therefore, represent significant contaminations sources with deleterious environmental risks. This paper presents a VIKOR-based model to assess the contamination risk posed by a cluster of WWTPs. A risk index was defined via building a membership function embodying the performance degrees of WWTPs and risks levels within the framework of fuzzy set theory.

Assessment of red tide risk by integrating CRITIC weight method, TOPSIS-ASSETS method, and Monte Carlo simulation.

This study proposes a red tide risk assessment method based on intercriteria correlation (CRITIC), technique for order preference by similarity to an ideal solution (TOPSIS), assessment of estuarine trophic status (ASSETS) methods and Monte Carlo simulation (MCS) to calculate the probability of each risk level. The integrated TOPSIS-ASSETS method is used to calculate the risk levels of each year, where index weight is determined by CRITIC method. MCS method is employed to calculate the probability of each risk level.

Indices and models of surface water quality assessment: Review and perspectives.

Many technologies have been designed to monitor, evaluate, and improve surface water quality, as high-quality water is essential for human activities including agriculture, livestock, and industry. As such, in this study, we investigated water quality indices (WQIs), trophic status indices (TSIs), and heavy metal indices (HMIs) for assessing surface water quality. Based on these indices, we summarised and compared water assessment models using expert system (ES) and machine learning (ML) methods.

Method for lake eutrophication levels evaluation: TOPSIS-MCS.

Monte Carlo simulation (MCS) is applied in the engineering with great fuzziness and uncertainty. Technique for order preference by similarity to an ideal solution (TOPSIS) method is used to deal with multi-criteria decision-making issue. Membership function is used to determine the membership degree of evaluated index.

Method for a new risk assessment of urban water quality: IFN-SPA.

Water quality is one of the most essential factors to influence human daily life and environment health. Risk assessment of water quality has critical significance to sustainable development of human society and natural systems. Set pair analysis (SPA) methods are widely used in risk assessment, especially in water resources.

Data in intelligent approach for estimation of disc cutter life using hybrid metaheuristic algorithm.

This data in brief presents the monitoring data measured during shield tunnelling of Guangzhou-Shenzhen intercity railway project. The monitoring data includes shield operational parameters, geological conditions, and geometry at the site. The presented data were arbitrarily split into two subsets including the training and testing datasets.

A novel method to calculate pressure on the twin-tunnel in layered strata.

Tunnel pressure from the surrounding rocks plays a critical role for the safety of tunnel. The existing methods for calculate twin-tunnel pressure supposed that the tunnel is buried in a uniform soil layer. This work presents detailed equations of an analytical method to calculate the twin-tunnel pressure in layered strata, which can consider the effects from soil layers.

Assessment and management of lake eutrophication: A case study in Lake Erhai, China.

Some wastewater sources, such as agricultural waste and runoff, and industrial sewage, can degrade water quality. This study summarises the sources and corresponding mechanisms that trigger eutrophication in lakes. Additionally, the trophic status index and water quality index (WQI) which are effective tools for evaluating the degree of eutrophication of lakes, have been discussed.

Approach based on TOPSIS and Monte Carlo simulation methods to evaluate lake eutrophication levels.

This study presents an approach for eutrophication evaluation based on the technique for order preference by similarity to an ideal solution (TOPSIS) method and Monte Carlo simulation (MCS). The MCS is employed to produce a normally distributed dataset based on the observed data while the TOPSIS method and membership function are used to evaluate the level of eutrophication. Herein, a eutrophication problem in Lake Erhai is evaluated to check the performance of the proposed approach.

Data on a coupled ENN / t-SNE model for soil liquefaction evaluation.

The data presented in this paper pertain to case records of liquefaction potential surveys in earthquake prone areas. Field performances of 219 sites obtained from various regions (U.S.

Data in risk assessment of mega-city infrastructures related to land subsidence using improved trapezoidal FAHP.

Land subsidence caused serious damages of mage-city infrastructures. This data in brief presents a new questionnaire to establish judgment matrix during the risk assessment of land subsidence. The data source of the assessment factors is provided.

Risk assessment of mega-city infrastructures related to land subsidence using improved trapezoidal FAHP.

This study presents an improved trapezoidal fuzzy analytic hierarchy process (FAHP) to assess the risk of mega-city infrastructures related to land subsidence. The trapezoidal fuzzy numbers are used to express the relative importance between assessment factors. A new questionnaire is proposed in this study to collect judgements from consulting experts.

Data in flood risk assessment of metro systems in a subsiding environment using the interval FAHP-FCA approach.

Floods in the metro system have caused catastrophic damages in mega-cities, especially in subsiding environment. This data in brief gives a detailed description for the calculation of judgment matrixes during decision making process for the flood risk assessment of the metro system. The data source of the assessment factors is provided.

New Policy and Implementation of Municipal Solid Waste Classification in Shanghai, China.

To promote sustainable development, the Chinese government launched a new municipal solid waste (MSW) classification strategy in 2017. Shanghai was selected as one of the first pilot cities for MSW classification. The Shanghai municipal government first established the new MSW classification policy in 2017.

Land Subsidence Control Zone and Policy for the Environmental Protection of Shanghai.

Land subsidence was once a major geo-hazard in the city of Shanghai, China. From 1921 to 1965, the maximum cumulative land subsidence in the urban areas of China reached 2.6 m.

Flood risk assessment in metro systems of mega-cities using a GIS-based modeling approach.

Metro system is a vital component of mass transportation infrastructure, providing crucial social and economic service in urban area. Flood events may cause functional disruptions to metro systems; therefore, a better understanding of their vulnerability would enhance their resilience. A comparative study of flood risk in metro systems is presented using the analytic hierarchy process (AHP) and the interval AHP (I-AHP) methods.

High calcium fly ash geopolymer stabilized lateritic soil and granulated blast furnace slag blends as a pavement base material.

Granulated Blast Furnace Slag (GBFS) was used as a replacement material in marginal lateritic soil (LS) while class C Fly Ash (FA) was used as a precursor for the geopolymerization process to develop a low-carbon pavement base material at ambient temperature. Unconfined Compression Strength (UCS) tests were performed to investigate the strength development of geopolymer stabilized LS/GBFS blends. Scanning Electron Microscopy and X-ray Diffraction analysis were undertaken to examine the role of the various influencing factors on UCS development.