Generating a long-term high-spatiotemporal resolution global PM dataset is of great significance for environmental management to mitigate the air pollution concerns worldwide. However, the current long-term (2003-2020) global reanalysis dataset Coper...
The Black Sea is an important ecosystem, which is affected by various anthropogenic pressures, such as shipping activities and wastewater inputs from large coastal cities. Significant loads of chemical pollutants are being continuously brought in by ...
The transport and retention of microorganisms are typically described using attachment/detachment and straining/liberation models. However, the parameters in the models varied significantly, posing a significant challenge to describe microbial transp...
The processes underpinning the environmental risk assessment (ERA) of chemicals have not changed appreciably in the last 30 years. It is unclear how successful these processes are in protecting the environment from any adverse effects of chemicals. T...
Viticulture, as well as other crops, is facing obligation to reduce the use of herbicides and to develop alternatives solutions to chemical weed control. These alternatives can be achieved by mechanical weeding either using tractors or weeding robots...
Nowadays, estuarial areas have been strongly affected by the construction of electrical power dams from upstream, downstream urbanization and many types of hazards along the coastal regions. It has resulted in significant changes in estuarine wetland...
The development of machine learning and deep learning provided solutions for predicting microbiota response on environmental change based on microbial high-throughput sequencing. However, there were few studies specifically clarifying the performance...
As the driving force behind the new wave of technological advancement, artificial intelligence (AI) paves the way for a new era of green economic growth. This paper uses the case of China and constructs a relevant mathematical model to propose the tw...
This study proposes a new model for the spatiotemporal prediction of PM concentration at hourly and daily time intervals. It has been constructed on a combination of three-dimensional convolutional neural network and gated recurrent unit (3D CNN-GRU)...
Remote sensing of suspended sediment in shallow waters is challenging because of the increased optical variability of the water, resulting from the influence of suspended matter in the water column and the heterogeneous bottom properties. To overcome...