Impact of atmospheric dust emission schemes on dust production and concentration over the Arabian Peninsula

A multi-objective framework to select numerical options in air quality prediction models: A case study on dust storm modeling

Numerical weather prediction models are very important tools in predicting severe weather phenomena such as dust storms. However, the prediction accuracy in these models depends on the options considered in the modeling. In this study, a multi-objective framework is presented to determine the optimal options of the weather research forecasting with chemistry (WRF-Chem) model. For this purpose, a severe dust storm that occurred in the center of Iran is considered and the effect of 10 options including grid (computational domain size, modeling start time, horizontal, vertical and temporal resolution), physical (initial conditions, boundary layer and land surface schemes) and chemical options (dust emission schemes and dust source functions) are investigated. In general, the results showed that the WRF-Chem model has a high ability to model dust storms, but its results depend on the options considered in the modeling. Evaluation of grid options showed that inappropriate selection of domain size and modeling start time can lead to the failure in dust storm forecasting. Also, the land surface scheme has the greatest impact on dust concentration among the physical options. In addition, chemical options have the greatest impact on the dust storm forecasting as well. Based on the proposed multi-objective framework, the optimal options for dust storm modeling were determined. The proposed approach is comprehensive and can be used for other atmospheric/air quality modeling.

The impact of local fugitive particulate matter and emission inventories on air quality and health in dry and arid areas

The arid and semi-arid regions are facing a huge brunt of fugitive Particulate Matter (fPM) pollution, usually ascribed to the natural dust generated at the regional level (>100 km). In this study, the contribution of locally generated fPM to air pollution and it's environmental risk were assessed at a typical dry-arid area in the Middle East (i.e., State of Qatar, 200 × 200 km² domain) with the use of different emission and dispersion models. Four modelling scenarios were constructed to reflect standard practices (e.g., regional emission models and the World Health Organization's (WHO) Environmental Burden of Disease (EBD) method) and higher resolution calculations with emission models that were developed in past field campaigns. Emphasis was given to the effect on the WHO methodology beyond the typical emission estimates and ambient concentration levels. Eventually, the use of higher spatial resolution population and concentration data revealed fPM hot spots yielding up to 11.0 times higher short-term excess mortalities (an average increase of 1.8 times) compared to the baseline WHO methodology, where the whole population was exposed to a single average concentration. A difference that could be attributed to the improvement of the emission estimations for barren lands and traffic. For example, the estimated PM₁₀ emission fluxes from barren lands, within the main metropolitan area, using the improved emissions model ranged from 0.05 to 42.0 μg m^-2 s^-1, which is considerably higher than the emissions predicted using just the literature models (0.03 to 2.0 μg m^-2 s^-1). Overall, the barren lands emissions accounted for more than 90% of the fPM emissions during the study period. Consequently, this study is one of the first to quantify the significance of locally induced fPM and highlight the need for dedicated field studies and improved emissions estimation tools.

Uptake and hydration of sulfur dioxide on dry and wet hydroxylated silica surfaces: a computational study

We present a first-principles molecular dynamics study on the uptake and hydration of sulfur dioxide on the dry and wet fully hydroxylated surfaces of (0001) α-quartz, which are a proxy for suspended silica dust in the atmosphere. The average adsorption energy for SO₂ is about -10 kcal mol^-1 on both dry and wet surfaces. The adsorption is driven by hydrogen bond formation between SO₂ and the interfacial hydroxyl groups (on dry silica), or with water molecules (in the wet case). In the dry system, we report an additional electrostatic interaction between the interfacial hydroxyl oxygen and the sulfur atom, which further stabilizes the adsorbate. On dry silica, the interfacial hydroxyl group coordinates to SO₂ yielding a surface bound bisulfite (Si-SO₃H) complex. On the wet surface, SO₂ reacts with water forming bisulfite (HSO₃^-), and the latter remains solvated inside the adsorbed water layer. The hydration barrier for sulfur dioxide is 1 kcal mol^-1 and 3 kcal mol^-1 on dry and wet silica, respectively, while for the backward reaction (i.e., bisulfite to SO₂) the barrier is 6 kcal mol^-1 on both surfaces. The modest backward barrier rationalizes earlier experimental findings showing no SO₂ uptake on silica. These results underline the importance of the surface hydroxylation and/or adsorbed water layers for the SO₂ uptake and its hydration on silica. Moreover, the hydration to bisulfite may prevent direct SO₂ photochemistry and be an additional source of sulfate; this is especially relevant in atmospheres subject to a high level of suspended mineral dust, intense solar radiation and atmospheric oxidizers.

Impact of biomass burnings in Southeast Asia on air quality and pollutant transport during the end of the 2019 dry season

At the end of the dry season, March and April in Southeast Asia (SEA), agricultural refuse burnings occur over the region, mainly in the countries of Myanmar, Thailand, Laos, Cambodia and Vietnam, in preparation for the wet rice plantation. In this study, the impact of biomass burnings at the height of the burning period in March 2019 in mainland SEA on air quality and pollutant transport is modelled using the Weather Research Forecast WRF-Chem air quality model with emission input from the National Center for Atmospheric Research (NCAR) Fire Emission Inventory from NCAR (FINN). FINN is derived from satellite remote sensing data and species emission factors. A simulation of the dispersion of pollutants from biomass burnings from 13 to 19 March 2019, when the burnings was most intense, was performed. Validation of the model prediction using observed meteorological and pollutant data such as AOD measurements on ground from AERONET (Aerosol Robotic Network) and data from MODIS and CALIPSO satellites is carried out at various sites in the region. The results show that impact on air quality was most pronounced in Thailand and Laos but the effect of biomass burnings in mainland SEA at the end of the dry season is widespread in terms of pollutant dispersion and population exposure over the whole region and beyond. It is also shown that the transport of pollutants from biomass burnings in SEA to southern China, Taiwan and beyond is facilitated by the Truong Son mountain range, when under westerly wind, acting as a launching pad to uplift the pollutant plumes to higher altitude which then can be dispersed widely and transported farther from the biomass burning sources in Thailand and Laos.

Assessing Desert Dust Indirect Effects on Cloud Microphysics through a Cloud Nucleation Scheme: A Case Study over the Western Mediterranean

In this study, the performance and characteristics of the advanced cloud nucleation scheme of Fountoukis and Nenes, embedded in the fully coupled Weather Research and Forecasting/Chemistry (WRF/Chem) model, are investigated. Furthermore, the impact of dust particles on the distribution of the cloud condensation nuclei (CCN) and the way they modify the pattern of the precipitation are also examined. For the simulation of dust particle concentration, the Georgia Tech Goddard Global Ozone Chemistry Aerosol Radiation and Transport of Air Force Weather Agency (GOCART-AFWA) is used as it includes components for the representation of dust emission and transport. The aerosol activation parameterization scheme of Fountoukis and Nenes has been implemented in the six-class WRF double-moment (WDM6) microphysics scheme, which treats the CCN distribution as a prognostic variable, but does not take into account the concentration of dust aerosols. Additionally, the presence of dust particles that may facilitate the activation of CCN into cloud or rain droplets has also been incorporated in the cumulus scheme of Grell and Freitas. The embedded scheme is assessed through a case study of significant dust advection over the Western Mediterranean, characterized by severe rainfall. Inclusion of CCN based on prognostic dust particles leads to the suppression of precipitation over hazy areas. On the contrary, precipitation is enhanced over areas away from the dust event. The new prognostic CCN distribution improves in general the forecasting skill of the model as bias scores, the root mean square error (RMSE), false alarm ratio (FAR) and frequencies of missed forecasts (FOM) are limited when modelled data are compared against satellite, LIDAR and aircraft observations.

UV Index Forecasting under the Influence of Desert Dust: Evaluation against Surface and Satellite-Retrieved Data

Human exposure to healthy doses of UV radiation is required for vitamin D synthesis, but exposure to excessive UV irradiance leads to several harmful impacts ranging from premature wrinkles to dangerous skin cancer. However, for countries located in the global dust belt, accurate estimation of the UV irradiance is challenging due to a strong impact of desert dust on incoming solar radiation. In this work, a UV Index forecasting capability is presented, specifically developed for dust-rich environments, that combines the use of ground-based measurements of broadband irradiances UVA (320–400 nm) and UVB (280–315 nm), NASA OMI Aura satellite-retrieved data and the meteorology-chemistry mesoscale model WRF-Chem. The forecasting ability of the model is evaluated for clear sky days as well as during the influence of dust storms in Doha, Qatar. The contribution of UV radiation to the total incoming global horizontal irradiance (GHI) ranges between 5% and 7% for UVA and 0.1% and 0.22% for UVB. The UVI forecasting performance of the model is quite encouraging with an absolute average error of less than 6% and a correlation coefficient of 0.93. In agreement with observations, the model predicts that the UV Index at local noontime can drop from 10–11 on clear sky days to approximately 6–7 during typical dusty conditions in the Arabian Peninsula—an effect similar to the presence of extensive cloud cover.

Dust Storm Event of February 2019 in Central and East Coast of Australia and Evidence of Long-Range Transport to New Zealand and Antarctica

Between 11 and 15 February 2019, a dust storm originating in Central Australia with persistent westerly and south westerly winds caused high particle concentrations at many sites in the state of New South Wales (NSW); both inland and along the coast. The dust continued to be transported to New Zealand and to Antarctica in the south east. This study uses observed data and the WRF-Chem Weather Research Forecast model based on GOCART-AFWA (Goddard Chemistry Aerosol Radiation and Transport–Air Force and Weather Agency) dust scheme and GOCART aerosol and gas-phase MOZART (Model for Ozone And Related chemical Tracers) chemistry model to study the long-range transport of aerosols for the period 11 to 15 February 2019 across eastern Australia and onto New Zealand and Antarctica. Wildfires also happened in northern NSW at the same time, and their emissions are taken into account in the WRF-Chem model by using the Fire Inventory from NCAR (FINN) as the emission input. Modelling results using the WRF-Chem model show that for the Canterbury region of the South Island of New Zealand, peak concentration of PM10 (and PM2.5) as measured on 14 February 2019 at 05:00 UTC at the monitoring stations of Geraldine, Ashburton, Timaru and Woolston (Christchurch), and about 2 h later at Rangiora and Kaiapoi, correspond to the prediction of high PM10 due to the intrusion of dust to ground level from the transported dust layer above. The Aerosol Optical Depth (AOD) observation data from MODIS 3 km Terra/Aqua and CALIOP LiDAR measurements on board CALIPSO (Cloud-Aerosol LiDAR and Infrared Pathfinder Satellite Observations) satellite also indicate that high-altitude dust ranging from 2 km to 6 km, originating from this dust storm event in Australia, was located above Antarctica. This study suggests that the present dust storms in Australia can transport dust from sources in Central Australia to the Tasman sea, New Zealand and Antarctica.

Simulating the meteorology and PM10 concentrations in Arizona dust storms using the Weather Research and Forecasting model with Chemistry (Wrf-Chem)

Nine dust storms in south-central Arizona were simulated with the Weather Research and Forecasting with Chemistry model (WRF-Chem) at 2 km resolution. The windblown dust emission algorithm was the Air Force Weather Agency model. In comparison with ground-based PM₁₀ observations, the model unevenly reproduces the dust-storm events. The model adequately estimates the location and timing of the events, but it is unable to precisely replicate the magnitude and timing of the elevated hourly concentrations of particles 10 µm and smaller ([PM₁₀]).Furthermore, the model underestimated [PM₁₀] in highly agricultural Pinal County because it underestimated surface wind speeds and because the model's erodible fractions of the land surface data were too coarse to effectively resolve the active and abandoned agricultural lands. In contrast, the model overestimated [PM₁₀] in western Arizona along the Colorado River because it generated daytime sea breezes (from the nearby Gulf of California) for which the surface-layer speeds were too strong. In Phoenix, AZ, the model's performance depended on the event, with both under- and overestimations partly due to incorrect representation of urban features. Sensitivity tests indicate that [PM₁₀] highly relies on meteorological forcing. Increasing the fraction of erodible surfaces in the Pinal County agricultural areas improved the simulation of [PM₁₀] in that region. Both 24-hr and 1-hr measured [PM₁₀] were, for the most part, and especially in Pinal County, extremely elevated, with the former exceeding the health standard by as much as 10-fold and the latter exceeding health-based guidelines by as much as 70-fold. Monsoonal thunderstorms not only produce elevated [PM₁₀], but also cause urban flash floods and disrupt water resource deliveries. Given the severity and frequency of these dust storms, and conceding that the modeling system applied in this work did not produce the desired agreement between simulations and observations, additional research in both the windblown dust emissions model and the weather research/physicochemical model is called for.

IMPLICATIONS

While many dust storms can be considered to be natural, in semi-arid climates such storms often have an anthropogenic component in their sources of dust. Applying the natural, exceptional events policy to these storms with strong signatures of anthropogenic sources would appear not only to be misguided but also to stifle genuine regulatory efforts at remediation. Those dust storms that have resulted, in part, from passage over abandoned farm land should no longer be considered "natural"; policymakers and lawmakers need to compel the owners of such land to reduce its potential for windblown dust.