Linking Meteorological Variables and Particulate Matter PM2.5 in the Aburrá Valley, Colombia DOI Open Access
Juan Camilo Parra,

Miriam Gómez,

Hernán Salas

и другие.

Sustainability, Год журнала: 2024, Номер 16(23), С. 10250 - 10250

Опубликована: Ноя. 23, 2024

Environmental pollution indicated by the presence of PM2.5 particulate matter varies based on prevailing atmospheric conditions described certain meteorological variables. Consequently, it is important to understand behavior in areas such as Aburrá Valley, which experiences recurrent events twice a year. This study examines specific variables and Valley. By using statistical analysis tools correlation coefficients, principal component (PCA), multiple linear regression models, research identifies relationships between daily cycles temperature, rainfall, radiation, wind speed direction. Datasets were analyzed considering periods before after COVID-19 lockdown (pre-pandemic pandemic, respectively), also analyzed. Furthermore, this work considers variables, contrasting pre-pandemic pandemic periods. characterizes diurnal their relationship with PM2.5. There are consistent patterns among boundary layer (ABL) height, solar whereas precipitation relative humidity show opposite behavior. exhibits similar frequency functions during both daytime nighttime, regardless rainfall. An inverse noted levels ABL height at different times day. Moreover, PCA results that first explains around 60% total variance hydrometeorological data. The second PC 10%, rest distributed other three eight PCs. In sense, there no significant difference two PCAs data from period period. Multiple indicates dependence temperature radiation across application Generalized Additive Models (GAMs) our dataset yielded promising results, reflecting complex concentrations. metrics obtained GAM follows: Mean Squared Error (MSE) 98.04, Root (RMSE) 9.90, R-squared (R2) 0.24, Akaike Information Criterion (AIC) 110,051.34, Bayesian (BIC) 110,140.63. comparison, model exhibited slightly higher MSE (100.49), RMSE (10.02), lower (0.22), AIC BIC values 110,407.45 110,460.67, respectively. Although improvement performance over not conclusive, they indicate better fit for complexity dynamics influencing levels. These findings underscore intricate interplay factors concentration, reinforcing necessity advanced modeling techniques environmental studies. presents new insights enhance diagnosis, understanding, pollution, thereby supporting informed decision-making strengthening management efforts.

Язык: Английский

The various synergistic impacts of precursor emission reduction on PM2.5 and O3 in a typical industrial city with complex distributions of emissions DOI
Min Shao,

Shun Lv,

Yajing Wei

и другие.

The Science of The Total Environment, Год журнала: 2024, Номер 940, С. 173497 - 173497

Опубликована: Май 31, 2024

Язык: Английский

Процитировано

9
Contribution and Mechanisms of BVOCs Emitted From a Typical Large Lake With Algal Bloom to O3 Levels in Lakeside Urban Areas DOI Creative Commons
Min Shao,

Yajing Wei,

Shun Lv

и другие.

Journal of Geophysical Research Atmospheres, Год журнала: 2025, Номер 130(4)

Опубликована: Фев. 24, 2025

Abstract Lakes near developed cities often experience algal blooms due to eutrophication, leading odor and biogenic emissions that can potentially interfere with the formation of air pollutants such as O 3 around these lakes. However, impact its pathways remain poorly understood. This study investigates contributions volatile organic compound (BVOC) from Lake Taihu in surrounding regions using a numerical approach. Composite analysis, case studies, process analysis reveal BVOC increase hourly near‐surface concentrations, maximum rise 25.5 μg m −3 , improving model performance. The influence lake is large on northwest side Taihu, primarily determined by spatial emission patterns dominant wind fields. development planetary boundary layer, particularly thermal internal enhanced breeze play important roles increasing levels over land, whereas variations temperature minor role. Vertical cross‐sections show interactions between land‐lake breezes background fields are critical for transport, surface concentrations areas. Additionally, intensify both daytime nighttime gas‐phase chemical consuming nitrates producing additional within lower troposphere. highlights importance local circulations pollution, emphasizing need comprehensive pollution control strategies lakeside cities.

Язык: Английский

Процитировано

0
Mechanisms of O3 and PM2.5 evolution along the cold wave passage in Eastern China DOI Creative Commons
Min Shao,

Changhui Xu,

Shun Lv

и другие.

npj Climate and Atmospheric Science, Год журнала: 2025, Номер 8(1)

Опубликована: Май 24, 2025

Язык: Английский

Процитировано

0
Linking Meteorological Variables and Particulate Matter PM2.5 in the Aburrá Valley, Colombia DOI Open Access
Juan Camilo Parra,

Miriam Gómez,

Hernán Salas

и другие.

Sustainability, Год журнала: 2024, Номер 16(23), С. 10250 - 10250

Опубликована: Ноя. 23, 2024

Environmental pollution indicated by the presence of PM2.5 particulate matter varies based on prevailing atmospheric conditions described certain meteorological variables. Consequently, it is important to understand behavior in areas such as Aburrá Valley, which experiences recurrent events twice a year. This study examines specific variables and Valley. By using statistical analysis tools correlation coefficients, principal component (PCA), multiple linear regression models, research identifies relationships between daily cycles temperature, rainfall, radiation, wind speed direction. Datasets were analyzed considering periods before after COVID-19 lockdown (pre-pandemic pandemic, respectively), also analyzed. Furthermore, this work considers variables, contrasting pre-pandemic pandemic periods. characterizes diurnal their relationship with PM2.5. There are consistent patterns among boundary layer (ABL) height, solar whereas precipitation relative humidity show opposite behavior. exhibits similar frequency functions during both daytime nighttime, regardless rainfall. An inverse noted levels ABL height at different times day. Moreover, PCA results that first explains around 60% total variance hydrometeorological data. The second PC 10%, rest distributed other three eight PCs. In sense, there no significant difference two PCAs data from period period. Multiple indicates dependence temperature radiation across application Generalized Additive Models (GAMs) our dataset yielded promising results, reflecting complex concentrations. metrics obtained GAM follows: Mean Squared Error (MSE) 98.04, Root (RMSE) 9.90, R-squared (R2) 0.24, Akaike Information Criterion (AIC) 110,051.34, Bayesian (BIC) 110,140.63. comparison, model exhibited slightly higher MSE (100.49), RMSE (10.02), lower (0.22), AIC BIC values 110,407.45 110,460.67, respectively. Although improvement performance over not conclusive, they indicate better fit for complexity dynamics influencing levels. These findings underscore intricate interplay factors concentration, reinforcing necessity advanced modeling techniques environmental studies. presents new insights enhance diagnosis, understanding, pollution, thereby supporting informed decision-making strengthening management efforts.

Язык: Английский

Процитировано

0