Search Results (92)

PM_2.5 pollution poses significant risks to human health and the environment, underscoring the importance of accurate PM_2.5 simulation. This study simulated a representative PM_2.5 pollution event using the Weather Research and Forecasting model coupled with chemistry (WRF-Chem), incorporating the assimilation of infrared atmospheric motion vector (AMV) data from the Fengyun-4A (FY-4A) satellite. A comprehensive analysis was conducted to examine the meteorological characteristics of the event and their influence on PM_2.5 concentration simulations. The results demonstrate that the assimilation of FY-4A infrared AMV data significantly enhanced the simulation performance of meteorological variables, particularly improving the wind field and capturing local and small-scale wind variations. Moreover, PM_2.5 concentrations simulated with AMV assimilation showed improved spatial and temporal agreement with ground-based observations, reducing the root mean square error (RMSE) by 8.2% and the mean bias (MB) by 15.2 µg/m³ relative to the control (CTL) experiment. In addition to regional improvements, the assimilation notably enhanced PM_2.5 simulation accuracy in severely polluted cities, such as Tangshan and Tianjin. Mechanistic analysis revealed that low wind speeds and weak atmospheric divergence restricted pollutant dispersion, resulting in higher near-surface concentrations. This was exacerbated by cooler nighttime temperatures and a lower planetary boundary layer height (PBLH). These findings underscore the utility of assimilating satellite-derived wind products to enhance regional air quality modeling and forecasting accuracy. This study highlights the potential of FY-4A infrared AMV data in improving regional pollution simulations, offering scientific support for the application of next-generation Chinese geostationary satellite data in numerical air quality forecasting. Full article

Combined air pollution of ozone and PM_2.5 often occurs in coal-based cities of China such as Taiyuan City. In this study, the Weather Research and Forecasting/Chemistry (WRF-Chem) model was employed to simulate a combined high air pollution event of ozone and PM_2.5 in Taiyuan City from 20 May to 29 May 2015,with the maximum daily 8-hour average (MDA8) for ozone exceeding 140 ppbv and PM_2.5 concentrations surpassing $200\mu \mathrm{g}{\mathrm{m}}^{-3}$. We further investigated the drivers of the combined air pollution in Taiyuan during the polluted period. The simulation results showed that the model can well simulate the combined pollution event in Taiyuan, with assessment parameters within reasonable ranges. Moreover, by analyzing the observational data and simulations, the major factors causing the PM_2.5 pollution in Taiyuan during this time period were suggested to be local emissions and pollutant transport from the North China Plain (NCP) located to the east of Taiyuan. In addition, unfavorable meteorological and geographical conditions in Taiyuan also play important roles in forming severe PM_2.5 pollution. Regarding the ozone pollution in Taiyuan, we suggest that the mechanism dominating the pollution event is that of ozone-rich air being transported to Taiyuan at high altitudes and then mixed downwards, resulting in an increase of the ground-level ozone in Taiyuan. Furthermore, we found local emissions and emissions from Taiyuan Basin and Henan Province, which are located to the south of Taiyuan, contributing significantly to the ozone pollution in Taiyuan City during this time. Full article

The northern slope of the Tibetan Plateau (TP) is the crucial affected area for dust originating from the Taklimakan Desert (TD). However, few studies have focused on the meteorological element responses to TD dust over different surface types near the TP. Satellite data and the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) were used to analyze the dust being transported from the TD to the TP and its effect from 30 July to 2 August 2016. In the TD, the middle-upper dust layer weakened the solar radiation reaching the lower dust layer, which reduced the temperature within the planetary boundary layer (PBL) during daytime. At night, the dust’s thermal preservation effect increased temperatures within the PBL and decreased temperatures at approximately 0.5 to 2.5 km above PBL. In the TP without snow cover, dust concentration was one-fifth of the TD, while the cooling layer intensity was comparable to the TD. However, within the PBL, the lower concentration and thickness of dust allowed dust to heat atmospheric continuously throughout the day. In the TP with snow cover, dust diminished planetary albedo, elevating temperatures above 6 km, hastening snow melting, which absorbed latent heat and increased the atmospheric water vapor content, consequently decreasing temperatures below 6 km. Surface meteorological element responses to dust varied significantly across different surface types. In the TD, 2 m temperature (T₂) decreased by 0.4 °C during daytime, with the opposite nighttime variation. In the TP without snow cover, T₂ was predominantly warming. In the snow-covered TP, T₂ decreased throughout the day, with a maximum cooling of 1.12 °C and decreased PBL height by up to 258 m. Additionally, a supplementary simulation of a dust event from 17 June to 19 June 2016 further validated our findings. The meteorological elements response to dust is significantly affected by the dust concentration, thickness, and surface type, with significant day–night differences, suggesting that surface types and dust distribution should be considered in dust effect studies to improve the accuracy of climate predictions. Full article

PM_2.5 levels increase in cities during the first hours of the year due to combustion activities and the use of fireworks. In Quito (2800 masl), the capital of Ecuador, air quality records at the beginning of 2020 to 2025 (6 years) ranged between 13.4 and 217.8 µg m⁻³ (maximum mean levels for 24 h), most of them being higher than 15.0 µg m⁻³, the current recommended concentration by the World Health Organization (WHO), highlighting the need to decrease these emissions and promote actions to reduce the exposure to these extreme events. Air pollution forecasting as a preventive warning system could help achieve this objective. Therefore, the primary aim of this research was to analyze the variation in PM_2.5 levels in this city during the initial hours of the year to define, through numerical experiments, the spatiotemporal configuration of PM_2.5 emissions to reproduce the observed PM_2.5 levels and obtain insights to build an emission-based forecasting tool. For this purpose, we modeled atmospheric variables and the PM_2.5 levels using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. Consistent with the behavior suggested by records of associated meteorological variables, the modeled planetary boundary layer height (PBLH) was generally lower in the city’s south compared with the center and the north. The records and modeled results indicated that in the south, the higher PM_2.5 levels were produced by higher emissions and lower values of the PBLH compared with the center and north, highlighting the importance of reducing the PM_2.5 emissions. The emission maps used for modeling the dispersion at the beginning of 2024 and 2025 are proposed as inputs for the future forecasting of the PM_2.5 levels at the start of the year, as preventive information for the public, to discourage, in advance, both combustion activities and the use of fireworks and to take action to avoid exposure. Full article

Having good replication of the soil moisture evolution is desirable to properly simulate the dust emissions and atmospheric dust load because soil moisture increases the cohesive forces of soil particles, modulating the wind erosion threshold above which emissions occur. To reduce errors, one can use soil moisture retrievals from space-borne microwave radiometers. Here, we explore the potential of inserting soil moisture retrievals from the Soil Moisture Active Passive (SMAP) satellite into the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to improve dust simulations. We focus our analysis on the contiguous U.S. due to the presence of important dust sources and good observational networks. Our analysis extends over the first year of SMAP retrievals (1 April 2015–31 March 2016) to cover the annual soil moisture variability and go beyond extreme events, such as dust storms, in order to provide a statistically robust characterization of the potential added value of the soil moisture retrievals. We focus on the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model from the Air Force Weather Agency (GOCART-AFWA) dust emission parameterization that represents soil moisture modulations of the wind erosion threshold with a parameterization developed by fitting observations. The dust emissions are overestimated by the GOCART-AFWA parameterization and result in an overestimation of the aerosol optical depth (AOD). Sensitivity experiments show that emissions reduced to 25% in the GOCART-AFWA simulations largely reduced the AOD bias over the Southwest and lead to better agreement with the standard WRF-Chem parameterization of dust emissions (GOCART) and with observations. Comparisons of GOCART-AFWA simulations with emissions reduced to 25% with and without SMAP soil moisture insertion show added value of the retrievals, albeit small, over the dust sources. These results highlight the importance of accurate dust emission parameterizations when evaluating the impact of remotely sensed soil moisture data on numerical weather prediction models. Full article

Accurate identification of dust emission sources is crucial for simulating dust aerosols in atmospheric chemical models. Therefore, a dynamically updated dust source function (DSF) was developed within the dust emission scheme of the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) to simulate an East Asian dust storm event from 13 to 16 March 2021. Utilizing satellite-derived input of vegetation cover, snow cover, soil texture, and land use, the DSF was updated to better identify dust source areas over bare soils and sparsely vegetated regions in western China and central-western Mongolia. With the updated DSF, simulated dust emissions increase significantly over western China and Mongolia. The dust aerosol simulations demonstrate substantial improvements in near-surface PM₁₀ concentrations, a better agreement with remotely sensed dust aerosol optical depth (DOD), and a more accurate representation of the vertical distribution of dust extinction coefficients compared to observations. This study highlights the importance of integrating real-time data to accurately characterize dust emission sources, thereby improving atmospheric environment simulations. Full article

We used WRF-Chem to simulate ash transport from eruptions of Chile’s Calbuco volcano on 22–23 April 2015. Massive ash and SO₂ ejections reached the upper troposphere, and particulates transported over South America were observed over Argentina, Uruguay, and Brazil via satellite and surface data. Numerical simulations with the coupled Weather Research and Forecasting–Chemistry (WRF-Chem) model from 22 to 27 April covered eruptions and particle propagation. Chemical and aerosol parameters utilized the GOCART (Goddard Chemistry Aerosol Radiation and Transport) model, while the meteorological conditions came from NCEP-FNL reanalysis. In WRF-Chem, we implemented a more efficient methodology to determine the Eruption Source Parameters (ESP). This permitted each simulation to consider a sequence of eruptions and a time varying ESP, such as the eruption height and mass and the SO₂ eruption rate. We used two simulations (GCTS1 and GCTS2) differing in the ash mass fraction in the finest bins (0–15.6 µm) by 2.4% and 16.5%, respectively, to assess model efficiency in representing plume intensity and propagation. Analysis of the active synoptic components revealed their impact on particle transport and the Andes’ role as a natural barrier. We evaluated and compared the simulated Aerosol Optical Depth (AOD) with VIIRS Deep Blue Level 3 data and SO₂ data from Ozone Mapper and Profiler Suite (OMPS) Limb Profiler (LP), both of which are sensors onboard the Suomi National Polar Partnership (NPP) spacecraft. The model successfully reproduced ash and SO₂ transport, effectively representing influencing synoptic systems. Both simulations showed similar propagation patterns, with GCTS1 yielding better results when compared with AOD retrievals. These results indicate the necessity of specifying lower mass fraction in the finest bins. Comparison with VIIRS Brightness Temperature Difference data confirmed the model’s efficiency in representing particle transport. Overestimation of SO₂ may stem from emission inputs. This study demonstrates the feasibility of our implementation of the WRF-Chem model to reproduce ash and SO₂ patterns after a multi-eruption event. This enables further studies into aerosol–radiation and aerosol–cloud interactions and atmospheric behavior following volcanic eruptions. Full article

Forests are vital for life on Earth but are threatened by forest fires, which have significant impacts on climate change both locally and globally. This study examines a forest fire that lasted from 15 to 26 February 2019 in Karnataka, India, using the Weather Research and Forecasting model with Chemistry (WRF-Chem) model to analyze the effects and atmospheric spread of fire-emitted aerosols. Model simulations are analyzed to understand the horizontal and vertical transport and radiative effects of the fire. The results show high aerosol levels and smoke particles reaching up to 3.5 km altitude and above. The fire raised near-surface air temperatures by ~1–1.5 °C. The net atmospheric forcing due to the fire over the affected area ranged from approximately 10 to 14 W/m², resulting in heating rates between about 0.002 and 0.005 K/day in the impacted region. Full article

At the end of the dry season, from early March to early April each year, extensive agricultural biomass waste burnings occur throughout insular mainland Southeast Asia. During this biomass-burning period, smoke aerosols blanketed the whole region and were transported and dispersed by predominant westerly and southwesterly winds to southern China, Taiwan, and as far southern Japan and the Philippines. The extensive and intense burnings coincided with some wildfires in the forests due to high temperatures, making the region one of the global hot spots of biomass fires. In this study, we focus on the effect of pollutants emitted from biomass burnings in March 2019 at the height of the burning period on the exposed population and their health impact. The Weather Research Forecast-Chemistry (WRF-Chem) model was used to predict the PM_2.5 concentration over the simulating domain, and health impacts were then assessed on the exposed population in the four countries of Southeast Asia, namely Thailand, Laos, Cambodia, and Vietnam. Using the health impact based on log-linear concentration-response function and Integrated Exposure Response (IER), the results show that at the peak period of the burnings from 13 to 20 March 2019, Thailand experienced the highest impact, with an estimated 2170 premature deaths. Laos, Vietnam, and Cambodia followed, with estimated mortalities of 277, 565, and 315 deaths, respectively. However, when considering the impact per head of population, Laos exhibited the highest impact, followed by Thailand, Cambodia, and Vietnam. The results highlight the significant health impact of agricultural waste burnings in Southeast Asia at the end of the dry season. Hence, policymakers should take these into account to design measures to reduce the negative impact of widespread burnings on the exposed population in the region. Full article

Cumulus parameterization schemes model the subgrid-scale effects of moist convection, affecting the prognosis of cloud formation, rainfall, energy levels reaching the surface, and air quality. Working with a spatial resolution of 1 km, we studied the influence of cumulus parameterization schemes coded in the Weather Research and Forecasting with Chemistry Version 3.2 (WRF-Chem 3.2) for modeling in an Andean city in Southern Ecuador (Cuenca, 2500 masl), during September 2014. To assess performance, we used meteorological records from the urban area and stations located mainly over the Cordillera, with heights above 3000 masl, and air quality records from the urban area. Firstly, we did not use any cumulus parameterization (0 No Cumulus). Then, we considered four schemes: 1 Kain–Fritsch, 2 Betts–Miller–Janjic, 3 Grell–Devenyi, and 4 Grell-3 Ensemble. On average, the 0 No Cumulus option was better for modeling meteorological variables over the urban area, capturing 66.5% of records and being the best for precipitation (77.8%). However, 1 Kain–Fritsch was better for temperature (78.7%), and 3 Grell–Devenyi was better for wind speed (77.0%) and wind direction (37.9%). All the options provided acceptable and comparable performances for modeling short-term and long-term air quality variables. The results suggested that using no cumulus scheme could be beneficial for holistically modeling meteorological and air quality variables in the urban area. However, all the options, including deactivating the cumulus scheme, overestimated the total amount of precipitation over the Cordillera, implying that its modeling needs to be improved, particularly for studies on water supply and hydrological management. All the options also overestimated the solar radiation levels at the surface. New WRF-Chem versions and microphysics parameterization, the other component directly related to cloud and rainfall processes, must be assessed. In the future, a more refined inner domain, or an inner domain that combines a higher resolution (less than 1 km) over the Cordillera, with 1 km cells over the urban area, can be assessed. Full article

Based on the Weather Research and Forecasting Model Coupled with Chemistry (WRF-Chem) atmospheric chemistry model, a parameterization scheme for the radioactive isotope caesium (¹³⁷Cs), considering processes such as advection, turbulent diffusion, dry deposition, and wet deposition, was constructed, enabling the spatial distribution simulation of the concentration and deposition of ¹³⁷Cs. The experimental simulation studies were carried out during the high emission period of the Fukushima nuclear accident (from 11 to 17 March 2011). Two sets of comparison experiments, with or without deposition, were designed, the effects of wind field and precipitation on the spatial transport and ground deposition of ¹³⁷Cs were analyzed, and the influence of wind field and precipitation on ¹³⁷Cs vertical transport was analyzed in detail. The results indicate that the model can accurately simulate the meteorological and ¹³⁷Cs variables. On 15 March, ¹³⁷Cs dispersed towards the Kanto Plain in Japan under the influence of northeastern winds. In comparison to the experiment without deposition, the concentration of ¹³⁷Cs in the Fukushima area decreased by approximately 286 Bq·m⁻³ in the deposition experiment. Under the influence of updrafts in the non-deposition experiment, a ¹³⁷Cs cloud spread upward to a maximum height of 6 km, whereas in the deposition experiment, the highest dispersion of the ¹³⁷Cs cloud only reach a height of 4 km. Affected by the wind field, dry deposition is mainly distributed in Fukushima, the Kanto Plain, and their eastern ocean areas, with a maximum dry deposition of 5004.5 kBq·m⁻². Wet deposition is mainly influenced by the wind field and precipitation, distributed in the surrounding areas of Fukushima, with a maximum wet deposition of 725.3 kBq·m⁻². The single-station test results from the deposition experiment were better than those for the non-deposition experiment: the percentage deviations of the Tokyo, Chiba, Maebashi, and Naraha stations decreased by 61%, 69%, 46%, and 51%, respectively, and the percentage root mean square error decreased by 46%, 25%, 38%, and 48%, respectively. Full article

Carbon sinks provided by land ecosystems play a crucial role in achieving carbon neutrality. However, the future potential of carbon sequestration remains highly uncertain. The impact of pollutant emission reduction (PER) introduced by the proposed synergistic approach to air pollution control and carbon neutrality on carbon sinks in China has not yet been fully evaluated. In this study, we analyzed the effects of regional carbon-neutral PER policies, global climate change, and their coupled effects on China’s terrestrial gross primary productivity (GPP) by conducting numerical experiments using the weather research and forecasting model coupled with chemistry (WRF-Chem) and the moderate resolution imaging spectroradiometer photosynthesis algorithm (MODIS-PSN). We found that carbon-neutral PER policies could promote GPP growth in most regions of China in 2060, particularly during April and October, resulting in a total increase of at least 21.84 TgC compared to that in 2016, which offset the adverse effects of global climate change up to fourfold. The aerosol radiative effects drive GPP growth under carbon-neutral PER policies, primarily through an increase in daily minimum temperature during winter and an increase in shortwave radiation during other seasons. Our research highlights that reducing pollutant emissions enhances future potential for carbon sequestration, revealing positive feedback towards achieving the target of carbon neutrality. Full article

The dust storms with local and non-local dust sources mostly affect Khuzestan province in southwest (SW) Iran. In this study, the role of the low-level jet in the activation of the internal dust events in SW Iran during two severe dust cases was investigated. For this purpose, the fifth-generation ECMWF reanalysis for the global climate and weather (ERA5) data was used to identify the synoptic patterns and the low-level jet (LLJ) characteristics in the study area. Furthermore, the images of the moderate resolution imaging spectroradiometer (MODIS) sensor, the outputs of the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model, and a weather research and forecasting model coupled with chemistry (WRF-Chem) were used to investigate the propagation and transport of the dust particles. The results of the synoptic analysis in both dust cases show the simultaneous occurrence of the divergence zone associated with cyclonic curvature in the subtropical jet stream (STJ) at 300 hPa, causing convergence at 925 hPa, upward motion, and the development of low surface pressure in SW Iran. Examining the vertical wind profile shows the existence of the maximum horizontal wind speeds of 975 to 875 hPa, along with the positive and negative shear below and above it, respectively, which emphasizes the existence of the LLJ and its role in local dust emission. The results of the comparison between the satellite images, WRF-Chem, and HYSPLIT model outputs show the formation and transportation of dust particles from the inner regions of Khuzestan in SW Iran. The horizontal dust surface distribution, vertical raised dust mass, and kinetic energy transfers are well simulated by the WRF-Chem model when LLJ broke at 09:00 to 12:00 UTC. The most important finding of this research is that, for the first time, the role of low-level jet is investigated in the activation of internal dust events in SW Iran. Full article

Volcanic eruptions pose a major natural hazard influencing the environment, climate and human beings at different temporal and spatial scales. Nevertheless, several volcanoes worldwide are poorly monitored and assessing the impact of their eruptions remains, in some cases, challenging. Nowadays, different numerical dispersion models are largely employed in order to evaluate the potential effects of volcanic plume dispersion due to the transport of ash and gases. On 28 August 2019, both Mt. Etna and Stromboli had eruptive activity; Mt. Etna was characterised by mild-Strombolian activity at summit craters, while at Stromboli volcano, a paroxysmal event occurred, which interrupted the ordinary typical-steady Strombolian activity. Here, we explore the spatial dispersion of volcanic sulphur dioxide (SO${}_2$) gas plumes in the atmosphere, at both volcanoes, using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) considering the ground-measured SO${}_2$ amounts and the plume-height as time-variable eruptive source parameters. The performance of WRF-Chem was assessed by cross-correlating the simulated SO${}_2$ dispersion maps with data retrieved by TROPOMI and OMI sensors. The results show a feasible agreement between the modelled dispersion maps and TROPOMI satellite for both volcanoes, with spatial pattern retrievals and a total mass of dispersed SO${}_2$ of the same order of magnitude. Predicted total SO${}_2$ mass for Stromboli might be underestimated due to the inhibition from ground to resolve the sin-eruptive SO${}_2$ emission due to the extreme ash-rich volcanic plume released during the paroxysm. This study demonstrates the feasibility of a WRF-Chem model with time-variable ESPs in simultaneously reproducing two eruptive plumes with different SO${}_2$ emission and their dispersion into the atmosphere. The operational implementation of this method could represent effective support for the assessment of local-to-regional air quality and flight security and, in case of particularly intense events, also on a global scale. Full article

Atmospheric pollutant gases emitted from straw burning and forest fires can lead to air quality and human health problems. This work explored the evolutionary trends of atmospheric CO${}_2$ and other pollutant gases in five countries of Peninsular Southeast Asia (PSEA) over a long time series using various satellite remote sensing data. The research results indicate that a considerable number of fires occur in the region every spring, which negatively affects air quality. The concentration of CO${}_2$ increased every year, indicating a correlation coefficient of 0.57 with the number of fire points. The concentration of CO and NO${}_2$, respectively, showed a correlation coefficient of 0.87 and 0.95 with the number of fire points as well. Additionally, the AOD reflects the relationship between fire points and air quality. The study also used the meteorological and air quality Weather Research and Forecasting with Chemistry (WRF-Chem) to simulate the fire season in March 2016. In this sensitivity study, we examined the impact of air pollutant gases on air quality in PSEA under a hypothetical scenario with and without fire emissions. The simulation results were also compared with satellite observations, which showed that the WRF-Chem model and the FINN (Fire INventory from NCAR) inventory could effectively simulate the spatial distribution and spatial–temporal variability characteristics of CO concentration in the fire, but the simulation result of NO${}_2$ was not satisfactory. This study suggests that spring wildfires affect not only air quality, but also short-term weather in the region. Full article