Role of upwind precipitation in transboundary pollution and secondary aerosol formation: A case study during the KORUS-AQ field campaign

Clouds and precipitation play critical roles in wet removal of aerosols and soluble gases in the atmosphere, and hence their accurate prediction largely influences accurate prediction of air pollutants. In this study, the impacts of clouds and precipitation on wet scavenging and long-range transboundary transport of pollutants are examined during the 2016 Korea-United States Air Quality (KORUS-AQ) field campaign using the Weather Research and Forecasting model coupled with chemistry. Two simulations in which atmospheric moisture is constrained vs. it is not are performed and evaluated against surface and airborne observations. The simulation with moisture constraints is found to better reproduce precipitation as well as surface PM2.5, whereas the areal extent and amount of precipitation are overpredicted in the simulation without moisture constraints. As a results of overpredicted clouds and precipitation and consequently overpredicted wet scavenging, PM2.5 concentration is generally underpredicted across the model domain in the simulation without moisture constraints. The effects are significant not only in the precipitating region (upwind region, southern China in this study) but also in the downwind region (South Korea) where no precipitation is observed. The difference in upwind precipitation by 77% on average between the two simulations leads to the difference in PM2.5 by ∼39% both in the upwind and downwind regions. The transboundary transport of aerosol precursors, especially nitric acid, has a considerable impact on ammonium-nitrate aerosol formation in the ammonia-rich downwind region. This study highlights that skillful prediction of atmospheric moisture can have ultimate potential to skillful prediction of aerosols across regions.

Aerosol responses to precipitation along North American air trajectories arriving at Bermuda

North American pollution outflow is ubiquitous over the western North Atlantic Ocean, especially in winter, making this location a suitable natural laboratory for investigating the impact of precipitation on aerosol particles along air mass trajectories. We take advantage of observational data collected at Bermuda to seasonally assess the sensitivity of aerosol mass concentrations and volume size distributions to accumulated precipitation along trajectories (APT). The mass concentration of particulate matter with aerodynamic diameter less than 2.5 µm normalized by the enhancement of carbon monoxide above background (PM2.5/ΔCO) at Bermuda was used to estimate the degree of aerosol loss during transport to Bermuda. Results for December–February (DJF) show that most trajectories come from North America and have the highest APTs, resulting in a significant reduction (by 53 %) in PM2.5/ΔCO under high-APT conditions (> 13.5 mm) relative to low-APT conditions (< 0.9 mm). Moreover, PM2.5/ΔCO was most sensitive to increases in APT up to 5 mm (−0.044 µg m−3 ppbv−1 mm−1) and less sensitive to increases in APT over 5 mm. While anthropogenic PM2.5 constituents (e.g., black carbon, sulfate, organic carbon) decrease with high APT, sea salt, in contrast, was comparable between high- and low-APT conditions owing to enhanced local wind and sea salt emissions in high-APT conditions. The greater sensitivity of the fine-mode volume concentrations (versus coarse mode) to wet scavenging is evident from AErosol RObotic NETwork (AERONET) volume size distribution data. A combination of GEOS-Chem model simulations of the 210Pb submicron aerosol tracer and its gaseous precursor 222Rn reveals that (i) surface aerosol particles at Bermuda are most impacted by wet scavenging in winter and spring (due to large-scale precipitation) with a maximum in March, whereas convective scavenging plays a substantial role in summer; and (ii) North American 222Rn tracer emissions contribute most to surface 210Pb concentrations at Bermuda in winter (∼ 75 %–80 %), indicating that air masses arriving at Bermuda experience large-scale precipitation scavenging while traveling from North America. A case study flight from the ACTIVATE field campaign on 22 February 2020 reveals a significant reduction in aerosol number and volume concentrations during air mass transport off the US East Coast associated with increased cloud fraction and precipitation. These results highlight the sensitivity of remote marine boundary layer aerosol characteristics to precipitation along trajectories, especially when the air mass source is continental outflow from polluted regions like the US East Coast.

Improved Wet Scavenging Schemes for Air Dispersion Modeling of Cs-137 in the Fukushima Accident

Wet scavenging process is critical for air dispersion modeling of Cs-137 in the Fukushima Daiichi Nuclear power plant (FDNPP) accident. Although intensively investigated, wet scavenging simulation is still subject to uncertainties caused by the biases in wet scavenging modeling and meteorological input. To reduce these uncertainties, the on-line coupled modeling feature of the Weather Research and Forecasting-Chemistry (WRF-Chem) model was utilized and both the in-cloud and below-cloud scavenging processes are considered. In this study, the in-cloud scheme Environ and below-cloud scheme Baklanov are combined with each other to form Environ-Bakla to simulate the wet deposition of Cs-137. The model is systematically compared with a previous WRF-Chem model with a single below-cloud scheme Baklanov, based on both the cumulative deposition and ambient concentration of Cs-137 based on the FDNPP accident observation. The results demonstrate that the in-cloud scavenging scheme substantially improves the cumulative deposition simulation in regions with light rain like Tochigi, Nakadori etc. With respect to the atmospheric concentration, the inclusion of in-cloud scavenging doesn’t necessarily improve the performances and the Environ-Bakla only shows fair performance under plume events with no rain or light rain.

Inter-annual variations of wet deposition in Beijing from 2014–2017: implications of below-cloud scavenging of inorganic aerosols

Wet scavenging is an efficient pathway for the removal of particulate matter (PM) from the atmosphere. High levels of PM have been a major cause of air pollution in Beijing but have decreased sharply under the Air Pollution Prevention and Control Action Plan launched in 2013. In this study, 4 years of observations of wet deposition have been conducted using a sequential sampling technique to investigate the detailed variation in chemical components through each rainfall event. We find that the major ions, SO42-, Ca2+, NO3-, and NH4+, show significant decreases over the 2013–2017 period (decreasing by 39 %, 35 %, 12 %, and 25 %, respectively), revealing the impacts of the Action Plan. An improved method of estimating the below-cloud scavenging proportion based on sequential sampling is developed and implemented to estimate the contribution of below-cloud and in-cloud wet deposition over the four-year period. Overall, below-cloud scavenging plays a dominant role to the wet deposition of four major ions at the beginning of the Action Plan. The contribution of below-cloud scavenging for Ca2+, SO42-, and NH4+ decreases from above 50 % in 2014 to below 40 % in 2017. This suggests that the Action Plan has mitigated PM pollution in the surface layer and hence decreased scavenging due to the washout process. In contrast, we find little change in the annual volume weighted average concentration for NO3- where the contribution from below-cloud scavenging remains at ∼ 44 % over the 2015–2017 period. While highlighting the importance of different wet scavenging processes, this paper presents a unique new perspective on the effects of the Action Plan and clearly identifies oxidized nitrogen species as a major target for future air pollution controls.

Aerosol Responses to Precipitation Along North American Air Trajectories Arriving at Bermuda

North American pollution outflow is ubiquitous over the western North Atlantic Ocean, especially in winter, making this location an ideal natural laboratory for investigating the impact of precipitation on aerosol particles along air mass trajectories. We take advantage of observational data collected at Bermuda to seasonally assess the sensitivity of aerosol mass concentrations and volume size distributions to accumulated precipitation along trajectories (APT). The mass concentration of particulate matter with aerodynamic diameter less than 2.5 µm normalized by the enhancement of carbon monoxide above background (PM2.5/∆CO) at Bermuda was used to estimate the degree of aerosol loss during transport to Bermuda. Results for December–February (DJF) show most trajectories come from North America and have the highest APTs, resulting in significant reduction (by 53 %) in PM2.5/∆CO under high APT conditions (> 13.5 mm) relative to low APT conditions (< 0.9 mm). Moreover, PM2.5/∆CO was most sensitive to increases in APT up to 5 mm (−0.044 µg m−3 ppbv−1 mm−1) and less sensitive to increases in APT over 5 mm. While anthropogenic PM2.5 constituents (e.g., black carbon, sulfate, organic carbon) decrease with high APT, sea salt in contrast was comparable between high and low APT conditions owing to enhanced local wind and salt emissions in high APT conditions. The greater sensitivity of the fine mode volume concentrations (versus coarse mode) to wet scavenging is evident from AERONET volume size distribution data. A combination of GEOS-Chem model simulations of 210Pb submicron aerosol tracer and its gaseous precursor 222Rn reveal that (i) surface aerosol particles at Bermuda are most impacted by wet scavenging in winter/spring (due to large-scale precipitation) with a maximum in March, whereas convective scavenging plays a substantial role in summer; and (ii) North American 222Rn tracer emissions contribute most to surface 210Pb concentrations at Bermuda in winter (~75–80 %), indicating that air masses arriving at Bermuda experience large-scale precipitation scavenging while traveling from North America. A case study flight from the ACTIVATE field campaign on 22 February 2020 reveals a significant reduction in aerosol number and volume concentrations during air mass transport off the U.S. East Coast associated with increased cloud fraction and precipitation. These results highlight the sensitivity of remote marine boundary layer aerosol characteristics to precipitation along trajectories, especially when the air mass source is continental outflow from polluted regions like the U.S. East Coast.

Regional Air Quality: Forest Fires Impacts of SO2 Emissions on Air Pollutants in the Himalayan Region of Uttarakhand, India

Sulfur dioxide (SO2) is a toxic with adverse health effects on respiratory tract, eyes, mucous membranes and skin. In the present study, the continuous ground-based SO2 monitoring has planned over Srinagar Garhwal Valley of Uttarakhand. In the monsoon (M-2018), Post-monsoon (PoM-2018), Winter (W-2019) & Pre-monsoon (PrM-2019) & & M-2019 have high SO2 concentrations (3.66 ± 2.05 µg/m3, 5.54 ± 2.23 µg/m3, 6.42 ± 1.79 µg/m3, 7.56 ± 3.53 µg/m3 6.45 ± 3.49 µ g/m3) at1900 LT, 2000 LT, 1800 LT, 1900 LT &1900 LT attributed mainly due to biomass burning and long-range transportation of pollutants. A drastic change in the SO2 concentration has been observed from 4.81 to 17.39 µg/m3 during May 2019 with a strong correlation of 0.61 with fire-counts during extensive forest fire. Whereas Jul 2018 (1.07 ± 0.82 µg/m3) showed the lowest SO2 concentration due to wet scavenging process. Temperature, humidity and wind speed have significant correlation with SO2 in different season. Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model trajectories and cluster analysis indicate the transportation of air mass from the Gulf region, Sahara Desert, Pakistan, Afghanistan to Srinagar with a significant contribution of 40.43–72.29% air mass. We have also observed weekend effects (reduction in the pollutant concentration) in Jul 2018, Sep 2018, Feb 2019, Apr 2019 and May 2019.

Urban inland wintertime N₂O₅ and ClNO₂ influenced by snow-covered ground, air turbulence, and precipitation

The atmospheric multiphase reaction of dinitrogen pentoxide (N2O5) with chloride-containing aerosol particles produces nitryl chloride (ClNO2), which has been observed across the globe. The photolysis of ClNO2 produces chlorine radicals and nitrogen dioxide (NO2), which alter pollutant fates and air quality. However, the effects of local meteorology on near-surface ClNO2 production are not yet well understood, as most observational and modeling studies focus on periods of clear conditions. During a field campaign in Kalamazoo, Michigan from January–February 2018, N2O5 and ClNO2 were measured using chemical ionization mass spectrometry, with simultaneous measurements of atmospheric particulate matter and meteorological parameters. We examine the impacts of atmospheric turbulence, precipitation (snow, rain) and fog, and ground cover (snow-covered and bare ground) on the abundances of ClNO2 and N2O5. N2O5 mole ratios were lowest during periods of lower turbulence and were not statistically significantly different between snow-covered and bare ground. In contrast, ClNO2 mole ratios were highest, on average, over snow-covered ground, due to saline snowpack ClNO2 production. Both N2O5 and ClNO2 mole ratios were lowest, on average, during rainfall and fog because of scavenging, with N2O5 scavenging by fog droplets likely contributing to observed increased particulate nitrate concentrations. These observations, specifically those during active precipitation and with snow-covered ground, highlight important processes, including N2O5 and ClNO2 wet scavenging, fog nitrate production, and snowpack ClNO2 production, that govern the variability in observed atmospheric chlorine and nitrogen chemistry and are missed when considering only clear conditions.

Effects of improved interpolation in the wet-scavenging scheme of FLEXPART

&lt;p&gt;The Lagrangian dispersion model FLEXPART v10.4 uses cloud water content, temperature, and precipitation rates to calculate wet scavenging. Currently, only precipitation fields are interpolated spatially to the particle positions. A simple nearest-neighbour approach is used for cloud parameters and temperature. This is made worse by the fact that precipitation fields from the European Centre for Medium Range Weather Forecasts (ECMWF) are temporal integrals whereas all the other parameters refer to a specific time. The pre-processor flex_extract disaggregates the precipitation fields to construct point values that can preserve the integral quantity when interpolated in FLEXPART. However, this method does not preserve precipitation in each time interval, leading to smoothing, or even shifting precipitation into dry periods.&lt;/p&gt;&lt;p&gt;We have implemented interpolation of all fields relevant for wet scavenging in FLEXPART v10.4 as well as the option to use our improved precipitation disaggregation scheme (https://doi.org/10.5194/gmd-11-2503-2018). It introduces two additional subgrid points within one original time interval. This secures consistency, continuity and mass conservation of precipitation within each time interval.&lt;/p&gt;&lt;p&gt;These updates lead to a massive improvement of the wet deposition fields in a specific test case where we applied a high-resolution outgrid that makes the effects of interpolation issues more visible. Originally, a kind of checkerboard pattern was visible, as well as a banded structure due to the finite time interval between meteorological input fields. Both features are mostly eliminated now. Additionally, the influence of varying the temporal and spatial resolution of the ECMWF input fields was investigated, and the benefit of using the ECMWF cloud water content instead of parametrised values. We also look at the impact of the new version on other, previously used test cases, for example, a lifetime analysis of aerosol particles as well as transport of mineral dust and black carbon.&lt;/p&gt;

Aerosol impacts for convective parameterizations: Recent changes to the Grell-Freitas Convective Parameterization

&lt;p&gt;The Grell-Freitas (GF) cumulus parameterization is an aerosol-aware, scale-aware convective parameterization. This presentation will focus one of the several developmental activities ongoing in GF: the continued development of its aerosol-aware capabilities and the impact in global forecast models.&lt;/p&gt;&lt;p&gt;Previous versions of GF initialized aerosols based on an assumed value of aerosol-optical depth (AOD) that was applied uniformly across the entire globe. Observations of AOD indicate that AOD varies substantially across the globe. Recently, the constant AOD value assumed in GF has been replaced by global AOD data from NASA&amp;#8217;s MERRA2 reanalysis. Thus, the distribution of aerosols at initialization more physically reasonable and geographically appropriate. This is important since the treatment of aerosols in GF should be most sensitive in regions with either very high or very low AOD. This method is extremely efficient, but can be adapted so that other aerosol and AOD products can be used in GF. Other products that could be used for initialization include the aerosol climatology used by the Thompson Aerosol-Aware Microphysical Parameterization or predicted aerosols using NOAA&amp;#8217;s aerosol prediction model, which is currently one ensemble in the Global Ensemble Forecast System &amp;#8211; Aerosols (GEFS-Aerosols).&amp;#160; &amp;#160;&lt;/p&gt;&lt;p&gt;GF includes three aerosol related cloud processes: aerosol-influenced evaporation, aerosol-influenced auto-conversion of cloud water to rain water, and aerosol wet scavenging based on memory. As in Wang (2013) the treatment of wet scavenging has been modified so that the aerosol wet scavenging efficiency is proportional to precipitation efficiency. Additionally, aerosols in GF are now allowed to slowly return to their original concentrations during precipitation-free periods. These changes are important since they allow the aerosols in GF to evolve over time in a physically realistic manner.&lt;/p&gt;&lt;p&gt;The impact of these changes to GF will be shown in a version of NOAA&amp;#8217;s operational global prediction model. &amp;#160;&amp;#160;&lt;/p&gt;