Surface ozone has become a significant atmospheric pollutant in China, exerting a profound impact on crop production and posing a serious threat to food security. Previous studies have extensively explored the physiological mechanisms of ozone damage...
When investigating the relationship between the acoustic environment and human wellbeing, there is a potential problem resulting from data source self-correlation. To address this data source self-correlation problem, we proposed a third-party assess...
Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are widely used across a spectrum of industrial and consumer goods. Nonetheless, their persistent nature and tendency to accumulate in biological systems pose substantial environmental and health t...
The COVID-19 pandemic has altered the circulation of non-SARS-CoV-2 respiratory viruses. In this study, we carried out wastewater surveillance of SARS-CoV-2 and influenza A virus (IAV) in three key port cities in China through real-time quantitative ...
Investigating the interaction between influent particles and biomass is basic and important for the biological wastewater treatment. The micro-level methods allow for this, such as the microscope image analysis method with the conventional ImageJ pro...
The traditional prediction of the Cd content in grains (Cd) of crops primarily relies on the multiple linear regression models based on soil Cd content (Cd) and pH, neglecting inter-factorial interactions and nonlinear causal links between external e...
The potential for machine learning to answer questions of environmental science, monitoring, and regulatory enforcement is evident, but there is cause for concern regarding potential embedded bias: algorithms can codify discrimination and exacerbate ...
Accurate crop yield predictions are crucial for farmers and policymakers. Despite the widespread use of ensemble machine learning (ML) models in computer science, their application in crop yield prediction remains relatively underexplored. This study...
The world's largest mangrove forest (Sundarbans) is facing an imminent threat from heavy metal pollution, posing grave ecological and human health risks. Developing an accurate predictive model for heavy metal content in this area has been challengin...
Combining single-species ecological modeling with advanced machine learning to investigate the long-term population dynamics of the rheophilic fish spirlin offers a powerful approach to understanding environmental changes and climate shifts in aquati...