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1.
J Environ Manage ; 368: 122185, 2024 Sep.
Artículo en Inglés | MEDLINE | ID: mdl-39151337

RESUMEN

Land use and land cover change (LUCC) can alter surface properties, such as albedo, roughness, and vegetation coverage, directly affecting dust emissions and aerosol concentrations, leading to variations in direct radiative forcing (DRF) of dust aerosols and consequently impacting the climate. This study utilized the Weather Research and Forecasting model with Chemistry (WRF-Chem) to quantify the impact of LUCC in northern China from 2000 to 2020 on dust aerosol DRF. Results indicated that LUCC's influence on shortwave radiative forcing of dust was significantly greater than its influence on longwave radiative forcing and exhibited obvious seasonal variations. Overall, LUCC can cause net direct radiative forcing to increase by 5.3 W m-2 at the surface and decrease by 7.8 W m-2 in the atmosphere. Different types of LUCC transformation showed distinct impacts on dust aerosol DRF, with the conversion from sparse vegetation to barren land had the most significant effect on net radiative intensity, resulting in a decrease of 8.1 W m-2 at the surface, an increase of 12.2 W m-2 in the atmosphere, and an increase of 4.1 W m-2 at the top of the atmosphere. Conversely, the conversion from barren land to sparse vegetation led to surface cooling and atmospheric warming. These findings are of great significance for enhancing our knowledge of the effects of LUCC on the radiative balance of dust aerosols.


Asunto(s)
Aerosoles , Polvo , Aerosoles/análisis , China , Polvo/análisis , Atmósfera , Monitoreo del Ambiente
2.
Environ Res ; 212(Pt C): 113440, 2022 09.
Artículo en Inglés | MEDLINE | ID: mdl-35526583

RESUMEN

This study analyzed an ozone pollution episode that occurred in the summer of 2020 in Zhengzhou, the provincial capital of Henan, China, and quantified the contribution of local and surrounding area anthropogenic emissions to this episode based on the Weather Research and Forecasting with Chemistry (WRF/Chem) model. Simulation results showed that the WRF/Chem model is well suited to simulate the ozone concentrations in this area. In addition, four simulation scenarios (removing the emissions from the northern Zhengzhou, southwestern Zhengzhou, Zhengzhou local and southeastern Zhengzhou) were conducted to explore the specific contributions of local emissions and emissions from surrounding areas within Henan to this ozone pollution episode. We found that contributions from the northern, local, southwestern, and southeastern regions were 6.1%, 5.9%, 1.7%, and 1.5%, respectively. The northern and local emissions of Zhengzhou (only emissions from Zhengzhou) were prominent contributors within the simulation areas. In other words, during this episode, most of the ozone pollution in Zhengzhou appeared to be transported in from regions outside Henan Province.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Ozono , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Contaminación del Aire/estadística & datos numéricos , China , Monitoreo del Ambiente/métodos , Ozono/análisis , Tiempo (Meteorología)
3.
Chemosphere ; 323: 138250, 2023 May.
Artículo en Inglés | MEDLINE | ID: mdl-36849024

RESUMEN

Dust emission induced by agricultural soil wind erosion is one of the main sources of atmospheric particulate matter (PM) in dryland areas. However, most current air quality models do not consider this emission source, resulting in large uncertainties in PM simulations. Here we estimated the agricultural PM2.5 (particulate matter with an aerodynamic diameter <2.5 µm) emission around Kaifeng, a prefecture-level city in central China, using the Wind Erosion Prediction System (WEPS), with the MEIC (Multi-resolution Emission Inventory for China) as an anthropogenic emission source. We then plugged these estimates into the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) to simulate an air pollution episode in Kaifeng, China. Results showed that the addition of agricultural soil PM2.5 emissions significantly improved the ability of WRF-Chem to accurately simulate PM2.5 concentrations. The PM2.5 concentration mean bias and correlation coefficient of not considered and considered agricultural dust emission were -72.35 µg m-|3 and 3.31 µg m-|3 and 0.3 and 0.58, respectively. The PM2.5 emitted by the agricultural soil wind erosion contributed around 37.79% of the PM2.5 in the Kaifeng municipal district during this pollution episode. This study confirmed that the dust emission caused by agricultural soil wind erosion can significantly impact urban PM2.5 concentrations which surrounded by large areas of farmland, and also indicated that coupling dust emissions from farmland with anthropogenic air pollutant emissions can improve the accuracy of air quality models.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Material Particulado/análisis , Viento , Suelo , Monitoreo del Ambiente/métodos , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Polvo/análisis , China
4.
Sci Rep ; 13(1): 8771, 2023 May 30.
Artículo en Inglés | MEDLINE | ID: mdl-37253757

RESUMEN

In this study, we simulated the spatial and temporal processes of a particulate matter (PM) pollution episode from December 10-29, 2019, in Zhengzhou, the provincial capital of Henan, China, which has a large population and severe PM pollution. As winter is the high incidence period of particulate pollution, winter statistical data were selected from the pollutant observation stations in the study area. During this period, the highest concentrations of PM2.5 (atmospheric PM with a diameter of less than 2.5 µm) and PM10 (atmospheric PM with a diameter of less than 10 µm) peaked at 283 µg m-3 and 316 µg m-3, respectively. The contribution rates of local and surrounding regional emissions within Henan (emissions from the regions to the south, northwest, and northeast of Zhengzhou) to PM concentrations in Zhengzhou were quantitatively analyzed based on the regional Weather Research and Forecasting model coupled with Chemistry (WRF/Chem). Model evaluation showed that the WRF/Chem can accurately simulate the spatial and temporal variations in the PM concentrations in Zhengzhou. We found that the anthropogenic emissions south of Zhengzhou were the main causes of high PM concentrations during the studied episode, with contribution rates of 14.39% and 16.34% to PM2.5 and PM10, respectively. The contributions of anthropogenic emissions from Zhengzhou to the PM2.5 and PM10 concentrations in Zhengzhou were 7.94% and 7.29%, respectively. The contributions of anthropogenic emissions from the area northeast of Zhengzhou to the PM2.5 and PM10 concentrations in Zhengzhou were 7.42% and 7.18%, respectively. These two areas had similar contributions to PM pollution in Zhengzhou. The area northeast of Zhengzhou had the lowest contributions to the PM2.5 and PM10 concentrations in Zhengzhou (5.96% and 5.40%, respectively).

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