Impact of High Temporal Resolution Data on Water Quality Modeling: Insights from Erhai Case Study DOI Open Access
Xiaomeng Shi, Yu Li, Bo Yao

и другие.

Processes, Год журнала: 2025, Номер 13(6), С. 1726 - 1726

Опубликована: Май 31, 2025

Lake monitoring is essential for sustaining aquatic ecosystems, and accurate estimation/prediction of water quality parameters crucial to this effort. Despite its importance, the performance predictive models built on varying temporal resolutions remains underexplored systematically. This study used daily 4 h high resolution (HTR) datasets assess multiple machine learning models—namely, Support Vector Regression (SVR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Long Short-Term Memory (LSTM) networks—under consistent data scales. The results indicate that dissolved oxygen (DO) exhibits pronounced sensitivity resolution, while total nitrogen (TN), phosphorus (TP), ammonia (NH3-N) show distinct, parameter-specific response patterns align with characteristics their underlying biogeochemical processes. research helps deepen understanding how influences model in prediction, offering valuable insights selecting optimal modeling techniques enhance lake protection strategies.

Язык: Английский

Non-target Screening of Emerging Contaminants in Tropical Island Rivers: A Case Study of the Nandu River DOI

Chuanjie Zheng,

Xiangshun Zeng,

Tianyao Wang

и другие.

Environmental Pollution, Год журнала: 2025, Номер unknown, С. 126225 - 126225

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

Resilience of Endemic Macroalga Ulva ovata (Ulvaceae, Chlorophyta) to Heavy Metal Contamination in the Gulf of Khambhat, India DOI Creative Commons
Sachin G. Rathod, Anjana K. Vala, Vaibhav A. Mantri

и другие.

Journal of Hazardous Materials Advances, Год журнала: 2025, Номер unknown, С. 100614 - 100614

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Monitoring Heavy Metal Pollution in the Aras River: A Comprehensive Evaluation Using Pollution Indexes DOI
Mohammad Ali Kiani,

Seyed Amirhosein Khatamnezhad,

Faiqotul Falah

и другие.

International Journal of Environmental Research, Год журнала: 2025, Номер 19(3)

Опубликована: Март 11, 2025

Язык: Английский

Процитировано

0

The impact of salinity on heavy metal accumulation in seaweed DOI
Muhamad Syaifudin, Mohamed G. Moussa, Tangcheng Li

и другие.

Marine Pollution Bulletin, Год журнала: 2025, Номер 214, С. 117819 - 117819

Опубликована: Март 12, 2025

Язык: Английский

Процитировано

0

Drivers of toxic element accumulation in terrestrial ecosystems across elevational gradients DOI
Baba Imoro Musah, Jie Yang, Guorui Xu

и другие.

Ecological Indicators, Год журнала: 2025, Номер 174, С. 113446 - 113446

Опубликована: Апрель 10, 2025

Язык: Английский

Процитировано

0

Long-Term Heavy Metal Bioaccumulation in Sprat (Sprattus sprattus) from the Romanian Black Sea: Ecological and Human Health Risks in the Context of Sustainable Fisheries DOI Creative Commons
Andra Oros, Mădălina Galațchi

Fishes, Год журнала: 2025, Номер 10(4), С. 178 - 178

Опубликована: Апрель 15, 2025

This study evaluates the heavy metals concentrations in sprat (Sprattus sprattus, Linnaeus, 1758) from Romanian Black Sea, assessing both ecological implications and human health risks associated with consumption. Using long-term data spanning 1994–2019, levels of copper (Cu), cadmium (Cd), lead (Pb), nickel (Ni), chromium (Cr) dorsal muscle tissues were analyzed to identify contamination trends episodic pollution events. Although most remained below regulatory thresholds, occasional exceedances Cd Pb suggest intermittent inputs. Health assessed using dietary indices including estimated daily intake (EDI), target hazard quotient (THQ), total (TTHQ), carcinogenic risk index (CRI). Findings indicate that, under current exposure levels, regular consumption poses minimal risk. However, prolonged during peak periods may contribute cumulative toxic effects, for ecosystem stability food safety. Given persistence their interactions co-occurring pollutants, such as persistent organic pollutants (POPs) polycyclic aromatic hydrocarbons (PAHs), ongoing monitoring remains essential. supports development sustainable environmental policies aimed at protecting marine biodiversity consumer Sea region.

Язык: Английский

Процитировано

0

Impact of High Temporal Resolution Data on Water Quality Modeling: Insights from Erhai Case Study DOI Open Access
Xiaomeng Shi, Yu Li, Bo Yao

и другие.

Processes, Год журнала: 2025, Номер 13(6), С. 1726 - 1726

Опубликована: Май 31, 2025

Lake monitoring is essential for sustaining aquatic ecosystems, and accurate estimation/prediction of water quality parameters crucial to this effort. Despite its importance, the performance predictive models built on varying temporal resolutions remains underexplored systematically. This study used daily 4 h high resolution (HTR) datasets assess multiple machine learning models—namely, Support Vector Regression (SVR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Long Short-Term Memory (LSTM) networks—under consistent data scales. The results indicate that dissolved oxygen (DO) exhibits pronounced sensitivity resolution, while total nitrogen (TN), phosphorus (TP), ammonia (NH3-N) show distinct, parameter-specific response patterns align with characteristics their underlying biogeochemical processes. research helps deepen understanding how influences model in prediction, offering valuable insights selecting optimal modeling techniques enhance lake protection strategies.

Язык: Английский

Процитировано

0