Towards a model for aerosol removal by rain scavenging: The role of physical-chemical characteristics of raindrops

Influence of rainfall on size-resolved bioaerosols around a livestock farm

Bioaerosols, capable of transporting microorganisms, can impact human health and agriculture by spreading to nearby communities. Their transmissions are influenced by various factors, including weather conditions and human activities. However, the scarcity of detailed, taxon-specific data on bioaerosols' sizes limits our ability to assess risks associated with bioaerosols' generation and spread. This study examined the composition and size of bioaerosols at a livestock farm and a non-agricultural site, focusing on how bioaerosols evolve at different locations and meteorological conditions. The location had an impact on bioaerosol samples. We conducted 16S rRNA gene amplicon sequencing to identify bacteria genera in bioaerosols. We observed consistently higher concentrations of bioaerosols across all sizes at the livestock farm, and samples from the livestock farm exhibited greater bacterial diversity, where we identified Staphylococcus and Corynebacterium as the most abundant species. The effects of rainfall on bioaerosol diversity are complex, suggesting a dynamic interplay between bioaerosol removal and generation. After rainfall, the bioaerosol fraction of particles larger than 2.5 μm increased by nearly 400% compared to post-rain levels. Conversely, for bioaerosols below 1 μm size, the fraction decreased by 50%. Furthermore, the sequencing results showed that precipitation differentially responded to the abundance of various genera in the bioaerosols. Moreover, even for the same genus, the response to precipitation varied depending on the size of the bioaerosols. Our research reveals how size, location, and environmental conditions influence bioaerosol dynamics, enhancing our understanding of bioaerosol formation and transmission.

Atmospheric microplastic deposition in a coastal city of India: The influence of a landfill source on monsoon winds

Coastal zones experience various wind events that may influence the characteristics, distribution, and dynamics of atmospheric microplastic pollutants. In the present study, we investigated the characteristics of the bulk atmospheric microplastic deposition in Kochi, Kerala, India, during three distinct seasons: Northeast Monsoon (NEM), Summer (SMR), and Southwest monsoon (SWM). Seasonally, the highest microplastic fallout rate was recorded for the NEM (37.29 particles m-2d-1), followed by SMR (15.17 particles m-2 d-1) and the SWM (11.57 particles m-2d-1). The microplastic abundance was not correlated to the amount of rainfall. Further, the wind rose and HYSPLIT trajectory analysis illustrated the arrival of northeast monsoon winds to the city via the region in and around the municipal landfill, which could be a major source of airborne microplastic to the sampling stations, and the forward trajectories from the landfill site extended into the Arabia Sea, providing evidence on the potential atmospheric transport and subsequent deposition of microplastics into the ocean. With respect to the qualitative characteristics, blue-coloured and fibrous microplastics dominated the samples with a considerable number of particles belonging to the size range of 200-500 μm. The practice of drying synthetic clothes under natural sunlight may have substantially contributed to the increased prevalence of airborne microfibers. The higher numbers of polyethylene (PE) and polypropylene (PP) in the bulk microplastic deposition reinforce the concept of low-density polymers being more susceptible to deflation by the wind. Overall, the work signifies the role of monsoon winds in transporting microplastics from an unscientifically managed municipal landfill site and also highlights the importance of reducing the quantity of plastic waste ending up at the landfill to reduce the emission of microplastics proportionately.

The role of snow in scavenging aerosol particles: A physical-chemical characterization

The below cloud scavenging of aerosols by snow has been analysed in León (NW Spain). Six snow events were registered over the course of one year of study. Ultrafine and accumulation aerosol particles were measured using a scanning mobility particle sizer spectrometer, while hydrometeors were characterized using a disdrometer. Furthermore, the chemical composition of the melted snow-water samples (soluble and insoluble fractions) was analysed. The scavenging coefficient (λ) showed a great variability among events. An effective washing of particles was observed during the first 30 min of snowfall. The mean change in the scavenging efficiency (%ΔC) of particle number concentration (PNC) and λ coefficient during this time interval were: i) nucleation mode: 36.3 % and 3.02 · 10-4 s-1; ii) Aitken mode: 30.4 % and 2.37 · 10-4 s-1 and iii) accumulation mode: 22.4 % and 1.77 · 10-4 s-1. The range of particle sizes that is less efficiently scavenged by snowfall was observed between 400 and 600 nm. When analyzing the whole snow event, an increase of PNC was observed. Two possible explanations underlie this behaviour: it could be caused by changes in air masses or by the resuspension of aerosol particles scavenged by snowflakes upon reaching the ground. A clear relationship was observed between Ca2+, SO42- and NO3- concentrations of aerosol particles before the snow event and the concentrations registered in the melted snow-water. The largest and smallest changes in aerosol number concentrations were caused by snowflakes of 3 and 6 mm in diameter, respectively. The particle size distributions (PSD) were fitted to log-normal distributions and the parameters were compared before and after snowfall.

Exploring the size-dependent dynamics of photosynthetic cells in rainwater: The influence of atmospheric variables and rain characteristics

The presence of microalgae in the atmosphere raises health and environmental concerns. Despite recent scientific advances, our knowledge of the origins and dynamics of photosynthetic cells in relation to atmospheric processes is limited due to a lack of empirical data. To address this gap, we conducted a one-year survey, collecting and analyzing rainwater samples. This study proposes to investigate the temporal dynamics of photosynthetic cells based on their size in combination with a unique dataset of variables of interest: type of rain and its characteristics, local meteorology, concentrations of inorganic chemical species, and long-range air mass transport. The analysis of the biochemical composition of rainwater, along with its correlation with the origin of air masses using ions as tracers, provides evidence of the long-range transport of photosynthetic cells. Additionally, our study reveals distinct removal mechanisms from the atmosphere for photosynthetic cells depending on their size. Our results suggest that convective events with high-intensity rainfall led to the efficient removal of medium-sized photosynthetic cells (4-15 μm) from the atmosphere. However, removal mechanisms for small (<4 μm) and large-sized cells (>15 μm) are not influenced by microphysical rainfall characteristics and seem to be governed by different atmospheric processes: dry deposition is proposed to be a significant mechanism for the removal of large-sized photosynthetic cells, while small-sized cells detected in rain are correlated with the horizontal wind speed and duration of rainfall, particularly during stratiform events. This implies that the removal of photosynthetic cells from the atmosphere is strongly influenced by environmental variables, which are expected to vary in response to global change. Therefore, it is crucial to enhance the monitoring of photosynthetic cells in relation to atmospheric processes and investigate the potential impact of the dissemination of genetic material from distant sources on recipient ecosystems.

Extreme climate index estimation and projection in association with enviro-meteorological parameters using random forest-ARIMA hybrid model over the Vidarbha region, India

This study aims to estimate and analyse extreme climate indices such as standardised precipitation index (SPI) coupled with enviro-met (air pollutants and meteorological) parameters over the Vidarbha region from 1980 to 2019. Seasonal SPI, also known as the draught index, is derived from rainfall data using the R language. An attempt is made to determine the best combination of enviro-met on SPI using the random forest (RF) models. The study region is divided into four zones to assess the microclimatic impact on the forecast model. Three sets of data combinations, viz., meteorological and air pollution parameters, are applied for SPI prediction using RF. The autoregressive integrated moving average (ARIMA) model is also used for a future scenario projection. It is observed from the projection results that the drought severity is enhancing with time. The drought severity scale from 1980 to 1989 is found to be between - 1 and 1, but the scale increases from 1990 to 2019 (- 3). From 1990 to 2019, SPI's negative (-) scale has become more prominent in all Vidarbha regions. These trends are indicative of drought severity and will have a significant impact on both life and property.

Connection between Weather Types and Air Pollution Levels: A 19-Year Study in Nine EMEP Stations in Spain

This study focuses on the analysis of the distribution, both spatial and temporal, of the PM10 (particulate matter with a diameter of 10 µm or less) concentrations recorded in nine EMEP (European Monitoring and Evaluation Programme) background stations distributed throughout mainland Spain between 2001 and 2019. A study of hierarchical clusters was used to classify the stations into three main groups with similarities in yearly concentrations: GC (coastal location), GNC (north-central location), and GSE (southeastern location). The highest PM10 concentrations were registered in summer. Annual evolution showed statistically significant decreasing trends in PM10 concentration in all the stations covering a range from -0.21 to -0.50 µg m-3/year for Barcarrota and Víznar, respectively. Through the Lamb classification, the weather types were defined during the study period, and those associated with high levels of pollution were identified. Finally, the values exceeding the limits established by the legislation were analyzed for every station assessed in the study.

Chemical Compositions of Rainfall Water in Nyingchi City, Tibet

Understanding precipitation chemistry is highlighted as important worldwide due to its close relationship with air quality and impacts on ecosystems. However, the chemical composition of precipitation is limited in Tibet, where alpine ecosystems are sensitive to global change. Here, rainwater samples were collected in Nyingchi city from January 2021 to December 2021, and a total of 44 samples were obtained. Major ions (NO3−, NH4+, Cl−, SO42−, Na+, K+, Ca2+ and Mg2+) were analyzed. Results showed that the predominant ions in the precipitation were Ca2+, Na+, SO42−, and Cl−. Precipitation was mainly concentrated in summer, accounting for 65.2% of all samples collected during the monitoring period. As a result, ion deposition fluxes were mainly concentrated in summer, accounting for 55%, 53%, 84%, 82%, 61%, 63%, 75.8%, and 37.8% of the annual Ca2+, K+, Mg2+, Na+, NH4+, Cl−, SO42−, and NO3−, respectively. Backward trajectory analysis revealed that airmasses were mainly from the southern direction, but the sources varied widely. In addition, Na+ and Cl− ions were dominated by the sea source fraction; the ions of Ca2+ and K+ were dominated by crustal fraction sources. The NH4+ and NO3− ions were mainly influenced by local pollution. However, SO42− was mainly from long distance transports. Our results suggest that ions abundance was varied largely in different direction airmasses in southeast Tibet. Considering that ion deposition fluxes were mainly concentrated in the summer and the airmasses were mainly from the southern direction in this season, the pollutants from the southern direction the environmental effects of those ions should be given more attention in the future.

Links between aerosol radiative forcing and rain characteristics: Stratiform and convective precipitation

The radiative forcing before and after rain events was studied between 12 February 2016 and 14 March 2017 in León, Spain. For this purpose, the radiative forcing fluxes were calculated using the Radiative Transfer Model Global Atmospheric ModEl (RTM GAME). After the application of a set of selection criteria (based on the availability of AERONET data, rain characteristics and lightning maps), 16 stratiform rain events were identified, concentrated in spring and winter, and 15 convective rain events were found concentrated in spring and summer. Rainfall events were grouped according to the atmospheric forcing (ΔF_ATM) before rain: "low" or "high" (lower or higher than 30 W m^-2). The threshold has been set at this value because it is the mean ΔF_ATM of all the selected events before rain. There were significant statistical differences between stratiform and convective events in rain duration, mean raindrop diameter and parameters a and b of radar reflectivity Z and rainfall intensity R relationship (Z = a R^b). When comparing "low" and "high" groups, raindrop diameter was similar in stratiform (0.51 ± 0.08 vs 0.48 ± 0.12 mm) and convective events (0.96 ± 0.98 vs 0.83 ± 0.63 mm), registering higher values for the latter. In stratiform events, the rain scavenging effect on aerosol particles is clearly observed in the "high" group with a decrease of radiative forcing of -27.0 ± 25.3%, and to a lesser extent, in the "low" group, probably because of a lower aerosol load in the atmosphere. In stratiform events, the mode of the raindrop size gamma distribution presented statistical differences between "low" (0.25 ± 0.13 mm) and "high" (0.35 ± 0.05 mm) groups. We claim that this points towards a relationship between radiative forcing before rain and the specific characteristics of rainfall measured at ground level. This study increases our knowledge on the important role of rainwater as a clean agent of the atmosphere and its impact on climate (through radiative forcing).

Effects of Air Pollutants on Summer Precipitation in Different Regions of Beijing

Many studies have shown that air pollutants have complex impacts on urban precipitation. Meteorological weather station and satellite Aerosol Optical Depth (AOD) product data from the last 20 years, combined with simulation results from the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), this paper focuses on the effects of air pollutants on summer precipitation in different regions of Beijing. These results showed that air pollution intensity during the summer affected the precipitation contribution rate (PCR) of plains and mountainous regions in the Beijing area, especially in the plains. Over the past 20 years, plains PCR increased by ~10% when the AOD augmented by 0.15, whereas it decreased with lower pollution levels. In contrast, PCR in mountainous areas decreased with higher pollution levels and increased with lower pollution levels. Our analysis from model results indicated that aerosol increases reduce the effective particle size of cloud droplets and raindrops. Smaller cloud raindrops more readily transport to high air layers and participate in the generation of ice-phase substances in the clouds, increasing the total amount of cloud water in the air in a certain time, which ultimately enhanced precipitation intensity on the plains. The removal of pollutants caused by increased precipitation in the plains decreased rainfall levels in mountainous areas.