Surface Ozone in the Huaihe River Economic Belt, China: Spatial-Temporal Variations and Meteorological Driving Force DOI Open Access
Xiaoyong Liu, Yidan Zhang, Xu Feng

et al.

Polish Journal of Environmental Studies, Journal Year: 2024, Volume and Issue: 33(5), P. 5199 - 5209

Published: June 10, 2024

Due to intense population density and rapid economic development, ozone (O 3 ) pollution is serious in the Huaihe River Economic Belt (HREB) of China.Based on pollutant meteorological observation data from 2015 2020, many interdisciplinary methods, e.g., Kernel Density Estimation (KDE), Standard Deviation Ellipse (SDE), Multiple Linear Regression (MLR), were employed investigate spatio-temporal distribution driving force O 27 cities HREB.The results revealed that annual mass concentration increased 2015~2018 then decreased 2019.The seasonal displayed a bimodal structure, with highs spring (122.3 μg/m summer (134.7 ), low autumn (99.1 winter (64.4 ).Spatially, northeastern HREB was higher than southwestern HREB.SDE analysis indicated southeast Shangqiu (33.80°N-33.89°N,116.33°E-116.40°E)was center gravity for concentrations severe clustered northern HREB, forming high-high (HH) type, those southern low-low (LL) type.Meteorological factors, including temperature, pressure, sunshine duration, had relatively significant impact concentration.Based t h e MLR analysis, factors can explain 82.2%~18.2%(60.5% average) variation more affected by conditions HREB.

Language: Английский

Evaluating the relative importance of predictors in Generalized Additive Models using the gam.hp R package DOI Creative Commons
Jiangshan Lai, Jing Tang, Tingyuan Li

et al.

Plant Diversity, Journal Year: 2024, Volume and Issue: 46(4), P. 542 - 546

Published: June 15, 2024

Generalized Additive Models (GAMs) are widely employed in ecological research, serving as a powerful tool for ecologists to explore complex nonlinear relationships between response variable and predictors. Nevertheless, evaluating the relative importance of collinear predictors on variables GAMs remains challenge. To address this challenge, we developed an R package named gam.hp. gam.hp calculates individual R2 values predictors, based concept 'average shared variance', method previously introduced multiple regression canonical analyses. Through these R2s, which add up overall R2, researchers can evaluate each predictor within GAMs. We illustrate utility by emission sources meteorological factors explaining ozone concentration variability air quality data from London, UK. believe that will improve interpretation results obtained

Language: Английский

Citations

20
Sustainable bioremediation and reuse of heavy metal-contaminated dredged sediments using Bacillus subtilis DOI
Kalyani Kulkarni, N. K. Jain,

G. L. Sivakumar Babu

et al.

Biodegradation, Journal Year: 2025, Volume and Issue: 36(3)

Published: April 16, 2025

Language: Английский

Citations

0
Rice husk valorisation by in situ grown MoS2 nanoflowers: a dual-action catalyst for pollutant dye remediation and microbial decontamination DOI Creative Commons
Rahul Ranjan,

Smruti B. Bhatt,

Rohit Rai

et al.

RSC Advances, Journal Year: 2024, Volume and Issue: 14(17), P. 12192 - 12203

Published: Jan. 1, 2024

In this study, we carried out valorization of rice husk through in situ growth MoS 2 nanoflowers for simultaneous pollutant dye remediation and microbial decontamination.

Language: Английский

Citations

2
Surface Ozone in the Huaihe River Economic Belt, China: Spatial-Temporal Variations and Meteorological Driving Force DOI Open Access
Xiaoyong Liu, Yidan Zhang, Xu Feng

et al.

Polish Journal of Environmental Studies, Journal Year: 2024, Volume and Issue: 33(5), P. 5199 - 5209

Published: June 10, 2024

Due to intense population density and rapid economic development, ozone (O 3 ) pollution is serious in the Huaihe River Economic Belt (HREB) of China.Based on pollutant meteorological observation data from 2015 2020, many interdisciplinary methods, e.g., Kernel Density Estimation (KDE), Standard Deviation Ellipse (SDE), Multiple Linear Regression (MLR), were employed investigate spatio-temporal distribution driving force O 27 cities HREB.The results revealed that annual mass concentration increased 2015~2018 then decreased 2019.The seasonal displayed a bimodal structure, with highs spring (122.3 μg/m summer (134.7 ), low autumn (99.1 winter (64.4 ).Spatially, northeastern HREB was higher than southwestern HREB.SDE analysis indicated southeast Shangqiu (33.80°N-33.89°N,116.33°E-116.40°E)was center gravity for concentrations severe clustered northern HREB, forming high-high (HH) type, those southern low-low (LL) type.Meteorological factors, including temperature, pressure, sunshine duration, had relatively significant impact concentration.Based t h e MLR analysis, factors can explain 82.2%~18.2%(60.5% average) variation more affected by conditions HREB.

Language: Английский

Citations

0