With the current COVID-19 pandemic being spread all over the world, lockdown measures are being implemented, making air pollution levels go down in several countries. In this context, the air quality ...changes in the highly populated and trafficked Brazilian states of São Paulo (SP) and Rio de Janeiro (RJ) were addressed using a combination of satellite and ground-based daily data analysis. We explored nitrogen dioxide (NO2) and fine particulate matter (PM2.5) daily levels for the month of May from 2015–2020. Daily measurements of NO2 column concentrations from the Ozone Monitoring Instrument (OMI) aboard NASA’s Aura satellite were analyzed and decreases of 42% and 49.6% were found for SP and RJ, respectively, during the year 2020 compared to the 2015–2019 average. Besides NO2 column retrievals, ground-based data measured by the Brazilian States Environmental Institutions were analyzed and correlated with satellite retrievals. Correlation coefficients between year-to-year changes in satellite column and ground-based concentrations were 77% and 53% in SP and RJ, respectively. Ground-based data showed 13.3% and 18.8% decrease in NO2 levels for SP and RJ, respectively, in 2020 compared to 2019. In SP, no significant change in PM2.5 was observed in 2020 compared to 2019. To further isolate the effect of emissions reduction due to the lockdown, meteorological data and number of wildfire hotspots were analyzed. NO2 concentrations showed negative and positive correlations with wind speed and temperature, respectively. PM2.5 concentration distributions suggested an influence by the wildfires in the southeast region of the country. Synergistic analyses of satellite retrievals, surface level concentrations, and weather data provide a more complete picture of changes to pollutant levels.
The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of ...Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O
) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM
) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O
mixing ratios, primarily due to reduced cloudiness and attenuation of photolysis in the model. Updates to the aerosol chemistry result in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing summertime PM
bias (PM
is typically underestimated by CMAQ in the summer), while updates to the gas chemistry result in slightly higher O
and PM
on average in January and July. Overall, the seasonal variation in simulated PM
generally improves in CMAQv5.1 (when considering all model updates), as simulated PM
concentrations decrease in the winter (when PM
is generally overestimated by CMAQ) and increase in the summer (when PM
is generally underestimated by CMAQ). Ozone mixing ratios are higher on average with v5.1 vs. v5.0.2, resulting in higher O
mean bias, as O
tends to be overestimated by CMAQ throughout most of the year (especially at locations where the observed O
is low); however, O
correlation is largely improved with v5.1. Sensitivity simulations for several hypothetical emission reduction scenarios show that v5.1 tends to be slightly more responsive to reductions in NO
(NO + NO
), VOC and SO
(SO
+ SO
) emissions than v5.0.2, representing an improvement as previous studies have shown CMAQ to underestimate the observed reduction in O
due to large, widespread reductions in observed emissions.
Concentrations of airborne chemical and biological agents from a hazardous release are not spread uniformly. Instead, there are regions of higher concentration, in part due to local atmospheric flow ...conditions which can attract agents. We equipped a ground station and two rotary-wing unmanned aircraft systems (UASs) with ultrasonic anemometers. Flights reported here were conducted 10 to 15 m above ground level (AGL) at the Leach Airfield in the San Luis Valley, Colorado as part of the Lower Atmospheric Process Studies at Elevation-a Remotely-Piloted Aircraft Team Experiment (LAPSE-RATE) campaign in 2018. The ultrasonic anemometers were used to collect simultaneous measurements of wind speed, wind direction, and temperature in a fixed triangle pattern; each sensor was located at one apex of a triangle with ∼100 to 200 m on each side, depending on the experiment. A WRF-LES model was used to determine the wind field across the sampling domain. Data from the ground-based sensors and the two UASs were used to detect attracting regions (also known as Lagrangian Coherent Structures, or LCSs), which have the potential to transport high concentrations of agents. This unique framework for detection of high concentration regions is based on estimates of the horizontal wind gradient tensor. To our knowledge, our work represents the first direct measurement of an LCS indicator in the atmosphere using a team of sensors. Our ultimate goal is to use environmental data from swarms of sensors to drive transport models of hazardous agents that can lead to real-time proper decisions regarding rapid emergency responses. The integration of real-time data from unmanned assets, advanced mathematical techniques for transport analysis, and predictive models can help assist in emergency response decisions in the future.
A new Reynolds-averaged Navier-Stokes （RANS） turbulence model is developed in order to correctly predict the mean flow field in a draft tube operating under partial load using 2-D axisymmetric ...simulations. It is shown that although 2-D axisymmetric simulations cannot model the 3-D unsteady features of the vortex rope, they can give the average location of the vortex rope in the draft tube. Nevertheless, RANS simulations underpredict the turbulent kinetic energy （TKE） production and diffusion near the center of the draft tube where the vortex rope forms, resulting in incorrect calculation of TKE profiles and, hence, poor prediction of the axial velocity. Based on this observation, a new k- c turbulence RANS model taking into account the extra production and diffusion of TKE due to coherent structures associated with the vortex rope formation is developed. The new model can successfully predict the mean flow velocity with significant improvements in comparison with the realizable k - c model. This is attributed to better prediction of TKE production and diffusion by the new model in the draft tube under partial load. Specifically, the new model calculates 31% more production and 46% more diffusion right at the shear layer when compared to the k - ~ model.
Convective dust storms have significant impacts on atmospheric conditions and air quality and are a major source of dust uplift in summertime. However, regional‐to‐global models generally do not ...accurately simulate these storms, a limitation that can be attributed to (1) using a single mean value for wind speed per grid box, i.e., not accounting for subgrid wind variability and (2) using convective parametrizations that poorly simulate cold pool outflows. This study aims to improve the simulation of convective dust storms by tackling these two issues. Specifically, we incorporate a probability distribution function for surface wind in each grid box to account for subgrid wind variability due to dry and moist convection. Furthermore, we use lightning assimilation to increase the accuracy of the convective parameterization and simulated cold pool outflows. This updated model framework is used to simulate a massive convective dust storm that hit Phoenix, AZ, on 6 July 2011. The results show that lightning assimilation provides a more realistic simulation of precipitation features, including timing and location, and the resulting cold pool outflows that generated the dust storm. When those results are combined with a dust model that accounts for subgrid wind variability, the prediction of dust uplift and concentrations are considerably improved compared to the default model results. This modeling framework could potentially improve the simulation of convective dust storms in global models, regional climate simulations, and retrospective air quality studies.
Key Points
Convective dust storms are difficult to simulate in models that use a convective parameterization
Subgrid wind variability and lightning assimilation were used to better model surface winds associated with convection
These two advancements were shown to improve the simulation of a convective dust storm
Identifying atmospheric transport pathways is important to understand the effects of pollutants on weather, climate, and human health. The atmospheric wind field is variable in space and time and ...contains complex patterns due to turbulent mixing. In such a highly unsteady flow field, it can be challenging to predict material transport over a finite-time interval. Particle trajectories are often used to study how pollutants evolve in the atmosphere. Nevertheless, individual trajectories are sensitive to their initial conditions. Lagrangian Coherent Structures (LCSs) have been shown to form the template of fluid parcel motion in a fluid flow. LCSs can be characterized by special material surfaces that organize the parcel motion into ordered patterns. These key material surfaces form the core of fluid deformation patterns, such as saddle points, tangles, filaments, barriers, and pathways. Traditionally, the study of LCSs has looked at coherent structures derived from integrating the wind velocity field. It has been assumed that particles in the atmosphere will generally evolve with the wind. Recent work has begun to look at the motion of chemical species, such as water vapor, within atmospheric flows. By calculating the flux associated with each species, a new effective flux-based velocity field can be obtained for each species. This work analyzes generalized species-weighted coherent structures associated with various chemical species to find their patterns and pathways in the atmosphere, providing a new tool and language for the assessment of pollutant transport and patterns.
Quantifying the impact of hyporheic exchange is crucial for understanding the transport and fate of microplastics in streams. In this study, we conducted several Computational Fluid Dynamics (CFD) ...simulations to investigate near-bed turbulence and analyze vertical hyporheic exchange. Different arranged spheres were used to represent rough and permeable sediment beds in natural rivers. The velocities associated with vertical hyporheic flux and the gravitational force were compared to quantify the susceptibility of microplastics to hyporheic exchange. Four scenario cases representing different channel characteristics were studied and their effects on microplastics movements through hyporheic exchange were quantitatively studied. Results show that hyporheic exchange flow can significantly influence the fate and transport of microplastics of small and light-weighted microplastics. Under certain conditions, hyporheic exchange flow can dominate the behavior of microplastics with sizes up to around 800 μm. This dominance is particularly evident near the sediment-water interface, especially at the top layer of sediments. Higher bed porosity enhances the exchange of microplastics between water and sediment, while increased flow conditions extend the vertical exchange zone into deeper layers of the bed. Changes in the bedform lead to the most pronounced vertical hyporheic exchange, emphasizing the control of morphological features on microplastics transport. Furthermore, it is found that sweep-ejection events are prevailing near the bed surface, serving as a mechanism for microplastics transport in rivers. As moving from the water column to deeper layers in the sediment bed, there's a shift from sweeps dominance to ejections dominance, indicating changes of direction in microplastics movement at different locations.
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•Turbulent hyporheic flow affects the fate and transport of in-stream microplastics.•Small and buoyant microplastics are more susceptible to turbulent hyporheic flow.•High flow, permeable bed, and mounded bedform enhance microplastics transport.
Freshwater harmful algal blooms (HABs), caused mostly by toxic cyanobacteria, produce a range of cyanotoxins that threaten the health of humans and domestic animals. Climate conditions and ...anthropogenic influences such as agricultural run-off can alter the onset and intensity of HABs. Little is known about the distribution and spread of freshwater HABs. Current sampling protocols in some lakes involve teams of researchers that collect samples by hand from a boat and/or from the shoreline. Water samples can be collected from the surface, from discrete-depth collections, and/or from depth-integrated intervals. These collections are often restricted to certain months of the year, and generally are only performed at a limited number of collection sites. In lakes with active HABs, surface samples are generally sufficient for HAB water quality assessments. We used a unique DrOne Water Sampling SystEm (DOWSE) to collect water samples from the surface of three different HABs in Ohio (Grand Lake St Marys, GLSM and Lake Erie) and Virginia (Lake Anna), United States in 2019. The DOWSE consisted of a 3D-printed sampling device tethered to a drone (uncrewed aerial system, or UAS), and was used to collect surface water samples at different distances (10–100 m) from the shore or from an anchored boat. One hundred and eighty water samples (40 at GLSM, 20 at Lake Erie, and 120 at Lake Anna) were collected and analyzed from 18 drone flights. Our methods included testing for cyanotoxins, phycocyanin, and nutrients from surface water samples. Mean concentrations of microcystins (MCs) in drone water samples were 15.00, 1.92, and 0.02 ppb for GLSM, Lake Erie, and Lake Anna, respectively. Lake Anna had low levels of anatoxin in nearly all (111/120) of the drone water samples. Mean concentrations of phycocyanin in drone water samples were 687, 38, and 62 ppb for GLSM, Lake Erie, and Lake Anna, respectively. High levels of total phosphorus were observed in the drone water samples from GLSM (mean of 0.34 mg/L) and Lake Erie (mean of 0.12 mg/L). Lake Anna had the highest variability of total phosphorus with concentrations that ranged from 0.01 mg/L to 0.21 mg/L, with a mean of 0.06 mg/L. Nitrate levels varied greatly across sites, inverse with bloom biomass, ranging from below detection to 3.64 mg/L, with highest mean values in Lake Erie followed by GLSM and Lake Anna, respectively. Drones offer a rapid, targeted collection of water samples from virtually anywhere on a lake with an active HAB without the need for a boat which can disturb the surrounding water. Drones are, however, limited in their ability to operate during inclement weather such as rain and heavy winds. Collectively, our results highlight numerous opportunities for drone-based water sampling technologies to track, predict, and respond to HABs in the future.
Lake spray aerosols (LSAs) are generated from freshwater breaking waves in a mechanism similar to their saltwater counterparts, sea spray aerosols (SSAs). Unlike the well-established research field ...pertaining to SSAs, studying LSAs is an emerging research topic due to their potential impacts on regional cloud processes and their association with the aerosolization of freshwater pathogens. A better understanding of these climatic and public health impacts requires the inclusion of LSA emission in atmospheric models, yet a major hurdle to this inclusion is the lack of a lake spray source function (LSSF), namely an LSA emission parameterization. Here, we develop an LSSF based on measurements of foam area and the corresponding LSA emission flux in a marine aerosol reference tank (MART). A sea spray source function (SSSF) is also developed for comparison. The developed LSSF and SSSF are then implemented in the Community Multiscale Air Quality (CMAQ) model to simulate particle emissions from the Great Lakes surface from 10 to 30 November 2016. Measurements in the MART revealed that the average SSA total number concentration was 8 times higher than that of LSA. Over the 0.01–10 µm aerosol diameter size range, the developed LSSF was around 1 order of magnitude lower than the SSSF and around 2 orders of magnitude lower for aerosols with diameters between 1 and 3 µm. Model results revealed that LSA emission flux from the Great Lakes surface can reach ∼105 m−2 s−1 during an episodic event of high wind speeds. These emissions only increased the average total aerosol number concentrations in the region by up to 1.65 %, yet their impact on coarse-mode aerosols was much more significant, with up to a 19-fold increase in some areas. The increase in aerosol loading was mostly near the source region, yet LSA particles were transported up to 1000 km inland. Above the lakes, LSA particles reached the cloud layer, where the total and coarse-mode particle concentrations increased by up to 3 % and 98 %, respectively. Overall, this study helps quantify LSA emission and its impact on regional aerosol loading and the cloud layer.
Saharan dust events, having great ecological and environmental impacts, are the largest producers of the world’s dust by far. Identifying the mechanisms by which the dust is transported across the ...Atlantic is crucial for obtaining a complete understanding of these important events. Of these events, the so-called “Godzilla” dust intrusion of June 2020 was the largest and most impactful in the last two decades and underwent a particularly interesting transport pattern. By uncovering dominant, organizing structures derived from the wind velocity fields, known as Lagrangian coherent structures, we demonstrate the ability to describe and qualitatively predict certain aspects related to the evolution of the dust plume as it traverses the atmosphere over the Atlantic. In addition, we identify regions of high hyperbolicity, leading to drastic changes in the shape of the plume and its eventual splitting. While these tools have been quite readily adopted by the oceanographic community, they have still yet to fully take hold in the atmospheric sciences and we aim to highlight some of the advantages over traditional atmospheric transport methods.
•Key structures shaping large-scale plumes found via FTLE applied to wind field.•Northern boundary of Godzilla dust plume is identified as persistent attracting LCS.•Interactions revealed with jet and vortex which significantly affect plume’s fate.•Comparison between traditional methods and coherent structure methods is performed.
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