Aerosol Concentrations Research Articles

Aerosol composition, air quality, and boundary layer dynamics in the urban background of Stuttgart in winter

Abstract. Aerosol distributions are of great relevance for air quality, especially for cities like Stuttgart, which has limited air exchange due to its location in a basin. We collected a comprehensive set of data from remote sensing and in situ methods including radiosondes for the urban background of downtown Stuttgart to determine the impact of boundary layer mixing processes on local air quality and to evaluate the simulation results of the high-resolution large eddy simulation (LES) model PALM-4U at 10 m grid spacing. Stagnant meteorological conditions caused accumulation of aerosols, and chemical composition analysis shows that ammonium nitrate (37 ± 9 %) and organic aerosol (OA; 34 ± 9 %) dominated during this winter study. Case studies show that clouds during previous nights can weaken temperature inversion and accelerate boundary layer mixing after sunrise by up to 3 h. This is important for ground-level aerosol dilution during the morning rush hour. Furthermore, our observations validate results of the LES model PALM-4U in terms of boundary layer heights and aerosol mixing for 48 h. The simulated aerosol concentrations follow the trend of our observations but are still underestimated by a factor of 4.5 ± 2.1 due to missing secondary aerosol formation processes and uncertainties of emissions and boundary conditions in the model. This paper firstly evaluates the PALM-4U model performance in simulating aerosol spatio-temporal distributions, which can help to improve the LES model and to better understand sources and sinks for air pollution as well as the role of horizontal and vertical transport.

Hysteresis in Water Content of Ultrafine Glassy Organic Aerosol Particles

AbstractWater content of aerosol particles is atmospherically important. Water content of organic aerosol (OA) particles has been estimated by assuming thermodynamic equilibrium. Here, we discovered that the hysteresis phenomenon occurred to water content of glassy ultrafine OA particles, demonstrating that thermodynamically non‐equilibrium states need to be considered. Hygroscopic growth for monodisperse ultrafine particles (sucrose and glucose) was investigated for the temperature range from 252 to 296 K. Hysteresis was not observable at 296 K, consistent with literature data. However, hysteresis in water content was observed at sub‐273 K. The lowest relative humidity (RH), at which hygroscopic growth of particles did not depend on exposure history to water vapor, was defined as threshold RH. Threshold RH for 100 nm particles was approximately the same as the glass transition points when hysteresis clearly happened, demonstrating that water diffusion in a highly viscous matrix of organic aerosols was the key to the phenomenon. Employment of a kinetic multi‐layer model quantitatively predicted threshold RH as a function of temperature, exposure time, and the particle size. Considering the temperature and RH range of Earth's atmosphere, we hypothesize that hysteresis in water content for organic aerosols ubiquitously occurs in the upper troposphere, impacting chemical aging and cloud formation processes.

Measurement of the nonlinear refractive index of highly scattering aerosols

The quality of air significantly impacts both the quality of life and the health of individuals. Femtosecond laser filament-induced nonlinear spectroscopy effectively measures both aerosol concentration and composition. Specifically, the nonlinear refractive index coefficient of the atmosphere directly influences the nonlinear propagation of femtosecond lasers in the air. The presence of aerosol particles in the atmosphere, particularly water droplets, may affect this nonlinear refractive index coefficient. However, the measurement of the nonlinear refractive index coefficient of highly scattering aerosols has not yet been reported. In this paper, a method to obtain the nonlinear refractive index coefficients of aerosols based on spectral changes is presented. Experiment measured the n2 coefficient of the air and water vapor aerosols respectively. Experimental results show that the n2 coefficients are 2.5 × 10−19 cm2/W and 2.4 × 10−19 cm2/W respectively for air with incident energy of 48 μJ and 68 μJ, the n2 coefficient are 2.5 × 10−19 cm2/W and 2.3 × 10−19 cm2/W respectively for aerosol with attenuation coefficients of 0.029 dB/cm. When the concentration of aerosols was increased to an attenuation coefficient of 0.045 dB/cm, the nonlinear refractive index coefficient of the aerosols was 3.1 × 10−19 cm2/W. The experimental results indicated that low concentrations of aerosols did not affect the nonlinear refractive index coefficient of air, but as the concentration increased to a certain level, the nonlinear refractive index coefficient of air increased. This work provides a simpler and faster technical route for measuring the n2 coefficient of gaseous media, offers a new approach to the problem of measuring the nonlinear refractive index of thick, highly scattering media, and addresses the shortcomings of the z-scan.

Unraveling the complex interactions between ozone pollution and agricultural productivity in China's main winter wheat region using an interpretable machine learning framework

Surface ozone has become a significant atmospheric pollutant in China, exerting a profound impact on crop production and posing a serious threat to food security. Previous studies have extensively explored the physiological mechanisms of ozone damage to plants. However, the effects of ozone interactions with other environmental factors, such as climate change, on agricultural productivity at the regional scale, particularly under natural conditions, remain insufficiently understood. In this study, we employed an interpretable machine learning framework, specifically the eXtreme Gradient Boosting (XGBoost) algorithm enhanced by SHapley Additive exPlanations (SHAP), to investigate the influence of ozone and its interactions with environmental factors on crop production in China's primary winter wheat region. Additionally, a structural equation model was developed to elucidate the mechanisms driving these interactions. Our findings demonstrate that ozone pollution exerts a significant negative effect on winter wheat productivity (r = −0.47, P < 0.001), with productivity losses escalating from −12.28 % to −22.09 % as ozone levels increase. Notably, the impact of ozone is spatially heterogeneous, with western Shandong province identified as a hotspot for ozone-induced damage. Furthermore, our results confirm the complexity of the relationship between ozone pollution and agricultural productivity, which is influenced by multiple interacting environmental factors. Specifically, we found that severe ozone pollution, when combined with high aerosol concentrations or elevated temperatures, significantly exacerbates crop productivity losses, although drought conditions can partially mitigate these adverse effects. Our study highlights the importance of incorporating the interactive effects of air pollution and climate change into future crop models. The comprehensive framework developed in this study, which integrates statistical modeling with explainable machine learning, provides a valuable methodological reference for quantitatively assessing the impact of air pollution on crop productivity at a regional scale.

A new procedure to validate and optimize 210Po measurements in atmospheric aerosols

The exposure to air fine aerosols can cause health effects due to inhalations of alpha emitters such as 222Rn daughters. Lead-210 and 210Po are mainly associated to aerosols with median aerodynamic diameter lower than 1 μm. The 210Po is characterized by having a high radiotoxicity. The precise measurement of 210Po in surface air aerosols is usually quite complex due to the significant contribution of the 210Pb on their concentrations. Additionally, there is no possible means to manufacture a certified material to validate the measurements of 210Pb and 210Po concentrations in surface air aerosols. For these reasons, this study aims to develop a novel and comprehensive methodology to validate 210Po measurements in surface air aerosols by preparing in our laboratory “standard samples” with known activities of both 210Pb and 210Po. A detailed sensitivity analysis on the precision of 210Po concentration measurements has been carried out as a function of the involved variables such as sampling time, time elapsed between the sampling start and 210Po self-deposition and the 210Po/210Pb activity ratio in surface air aerosols. This study is necessary to find the optimum conditions for a precise measurement of 210Po in surface air aerosols. In addition, this methodology has been applied for the determination of 210Po concentrations in 30 samplings campaigns of atmospheric aerosols carried out at the El Carmen campus (Huelva province) from March 25th to July 15th, 2022. The results obtained for 210Pb and 210Po concentrations and atmospheric aerosol residence times (via 210Po/210Pb activity ratio) were consistent with other previous works.

Impact of Model Spatial Resolution on Global Geophysical Satellite-Derived Fine Particulate Matter.

Global geophysical satellite-derived ambient fine particulate matter (PM2.5) inference relies upon a geophysical relationship (η) from a chemical transport model to relate satellite retrievals of aerosol optical depth (AOD) to surface PM2.5. The resolution dependence of simulated η warrants further investigation. In this study, we calculate geophysical PM2.5 with simulated η from the GEOS-Chem model in its high-performance configuration (GCHP) at cubed-sphere resolutions of C360 (∼25 km) and C48 (∼200 km) and satellite AOD at 0.01° (∼1 km). Annual geophysical PM2.5 concentrations inferred from satellite AOD and GCHP simulations at ∼25 km and ∼200 km resolutions exhibit remarkable similarity (R 2 = 0.96, slope = 1.03). This similarity in part reflects opposite resolution responses across components with population-weighted normalized mean difference (PW-NMD) increasing by 5% to 11% for primary species while decreasing by -30% to -5% for secondary species at finer resolution. Despite global similarity, our results also identify larger resolution sensitivities of η over isolated pollution sources and mountainous regions, where spatial contrast of aerosol concentration and composition is better represented at fine resolution. Our results highlight the resolution dependence of representing near-surface concentrations and the vertical distribution of chemically different species with implications for inferring ground-level PM2.5 from columnar AOD.

PM2.5 episodes in northern Taiwan under southerly winds in late winter

When northern Taiwan is influenced locally, PM2.5 events occur in specific conditions. If it is also affected by long-range transport from mainland China in the northwest, the probability of these PM2.5 events increases. The current study applies WRF/CMAQ to study such case but focus on the local. From April 7 to 9, 2019, the Pacific high pressure extended westward, causing the prevailing weak southerly wind near Taiwan. The intensity of the Pacific high pressure weakened, and the wind speed near Taiwan also weakened. Therefore, the PM2.5 concentration in Taiwan increased. In northern Taiwan, the hourly PM2.5 concentration will inevitably increase to approximately 70 μg m−3. The ISAM of the CMAQ model demonstrates that local contributions to daily PM2.5 concentrations at the four representative monitoring stations in northern Taiwan are 3.5 to 16.2 μg m−3, greater than those from central, southern, and eastern Taiwan, from 1.8 to 6.7 μg m−3. We use the integrated process rate (IPR) and integrated reaction rate (IRR) of CMAQ to explore the formation mechanisms of PM2.5. The main causes of the increase in PM2.5 concentration are horizontal advection (HADV), aerosol processes (AERO), emissions (EMIS), and a small amount of cloud processes and aqueous chemistry (CLDS). The main source of NO3− is the reaction between OH and NO2 during the day and the reaction between N2O5 and water vapor at night. The gaseous HNO3 concentration reaches a peak near noon or soon after. The aerosol ANO3 concentration is high in the early morning. We also use the Sulfur Tracking Method (STM) of CMAQ to explore the sources of SO42−. Mainly it is from the local reaction of SO2 and H2O2. Finally, we apply AERO7 in CMAQ to explore the main sources of carbon components. The organic carbon (OC) concentration is much greater than the element carbon (EC) concentration, which indicates a strong local photochemical effect in northern Taiwan. OC mainly comes from low-volatility/semivolatile oxidized combustion OC, followed by low-volatility/semivolatile POA. Similar weather conditions occur in autumn, winter, and spring. When the weak southerly wind was around Taiwan, PM2.5 in northern Taiwan was noticed.

CFD modeling of reactive species air cleaner applications in a classroom

Due to increasing concerns related to airborne virus spread indoors, more reactive species air cleaners are being utilized in classrooms. Reactive species generated by air cleaners decompose airborne pathogens chemically, decreasing the risk of infection. Due to the high reactivity of these oxidants, reactive species may be distributed nonuniformly in indoor environments, as are viral aerosols emitted by infectors. Heterogeneous distributions of reactive species may cause spatially non-uniform removal rates of viral aerosols. However, there is little information regarding spatial distributions of either reactive species or viral aerosols in ventilated classrooms. Thus, the objective of this study was to investigate spatial distributions of reactive species and infectious aerosols and to examine how operating conditions of air cleaners affect viral aerosol removal rates. A CFD model simulated the operation of a reactive species air cleaner generating hydrogen peroxide (H2O2) in a mechanically ventilated 237 m3 classroom with nine occupants. The reactive species air cleaner showed a 3–20 times higher equivalent air change rate to a HEPA filter air cleaner with the same inlet and outlet flows. During the operation of reactive species air cleaners, elevated viral aerosol concentration was confined to regions near infectors. This was due to the high reactivity of reactive species, decreasing the infection probability of receptors from 3.2 % to 0.1 % with a 1-hour exposure time. As the room average concentration of reactive species increased from 15.6 to 50.4 ppb, both below the US Occupational Safety and Health Administration (OSHA) Permissible Exposure Limit (PEL) of 1000 ppb, the room average infection probability decreased from 0.3 % to 0.1 %. Due to the residence times of reactive species, the location of reactive species air cleaners affected the inactivation rate of viral aerosol, resulting in a 24 % variation of concentration difference of infectious aerosol with air cleaner locations.

First results of the polar regional climate model RACMO2.4

Abstract. The next version of the polar Regional Atmospheric Climate Model (referred to as RACMO2.4p1) is presented in this study. The principal update includes embedding of the package of physical parameterizations of the Integrated Forecast System (IFS) cycle 47r1. This constitutes changes in the precipitation, convection, turbulence, aerosol and surface schemes and includes a new cloud scheme with more prognostic variables and a dedicated lake model. Furthermore, the standalone IFS radiation physics module ecRad is incorporated into RACMO, and a multilayer snow module for non-glaciated regions is introduced. Other updates involve the introduction of a fractional land–ice mask, new and updated climatological data sets (such as aerosol concentrations and leaf area index), and the revision of several parameterizations specific to glaciated regions. As a proof of concept, we show first results for Greenland, Antarctica and a region encompassing the Arctic. By comparing the results with observations and the output from the previous model version (RACMO2.3p3), we show that the model performs well regarding the surface mass balance, surface energy balance, temperature, wind speed, cloud content and snow depth. The advection of snow hydrometeors strongly impacts the ice sheet's local surface mass balance, particularly in high-accumulation regions such as southeast Greenland and the Antarctic Peninsula. We critically assess the model output and identify some processes that would benefit from further model development.

Modeling Indoor Inorganic Aerosol Concentrations During the ATHLETIC Campaign with IMAGES.

In 2018, the ATHLETIC campaign was conducted at the University of Colorado Dal Ward Athletic Center and characterized dynamic indoor air composition in a gym environment. Among other parameters, inorganic particle and gas-phase species were alternatingly measured in the gym's supply duct and weight room. The Indoor Model of Aerosols, Gases, Emissions, and Surfaces (IMAGES) uses the inorganic aerosol thermodynamic equilibrium model, ISORROPIA, to estimate the partitioning of inorganic aerosols and corresponding gases. In this study herein, measurements from the ATHLETIC campaign were used to evaluate IMAGES' performance. Ammonia emission rates, nitric acid deposition, and particle deposition velocities were related to observed occupancy, which informed these rates in IMAGES runs. Initially, modeled indoor inorganic aerosol concentrations were not in good agreement with measurements. A parametric investigation revealed that lowering the temperature or raising the relative humidity used in the ISORROPIA model drove the semivolatile species more toward the particle phase, substantially improving modeled-measured agreement. One speculated reason for these solutions is that aerosol water was enhanced by increasing the RH or decreasing the temperature. Another is that thermodynamic equilibrium was not established in this indoor setting or that the thermodynamic parametrizations in ISORROPIA are less accurate for typical indoor settings. This result suggests that applying ISORROPIA indoors requires further careful experimental validation.

Insights into chemical aging of urban aerosols over Delhi, India

Atmospheric particles can undergo aging as they are transported over long distances and mix with particles from other sources. This can lead to the accumulation of pollutants and the formation of complex aerosol mixtures with diverse chemical and physical properties. To investigate the process of aging in ambient atmosphere, 24h sampling of PM2.5 aerosol particles on Quartz microfiber filter with a tin substrate was carried out from November 2020 to March 2021 at CSIR-National Physical Laboratory, New Delhi (28°38'10″ N and 77°10′17" E), using fine particle sampler. Based on the observations of weather and meteorological parameters, a few episodic cases have been selected, and samples were analyzed at bulk and individual particle level. The objective of the present study is to investigate the aging characteristics of aerosols, enabling us to understand the mixing of aerosols (at both bulk and individual particle levels) and the variation in fresh and deformed (aged with other species) graphitic content in the episodic cases. The Raman Spectroscopy technique employed measures the intensity of graphitic (G band; around 1580 cm−1) and disordered graphitic (D band; around 1320 cm−1) content of aerosols. Individual particle microscopic observations reveal the occurrence of open chain fractals of black carbon in variable monomer sizes, sometimes agglomerated with metals like Cu, Cr, Ca etc., along with the presence of S- rich and organic aerosols while the Raman Spectrum (bulk sample analysis) highlights graphitic and disordered (when graphite interacts with other chemical species) graphitic intensities. Comparing the intensities of heavy haze and moderate haze with non-haze days (for comparison purpose, March 23, 2021 with the lowest PM2.5 concentration ∼ 62 μg/m3, has been considered as a non-haze day), it was observed that the intensities recorded on haze days were 45 to 200 times higher for the G band and 43 to 93 times higher for the D band; while for moderate haze days, the intensities were 4 to 61 times higher for the G band and 2 to 29 times higher for the D band. These findings suggest chemical processing of BC during haze days.

Processes Controlling the Entrainment and Liquid Water Response to Aerosol Perturbations in Nonprecipitating Stratocumulus Clouds

Abstract It has been widely reported that an increase in aerosol concentration in nonprecipitating clouds leads to a decrease in their liquid water path. Here, we examine the physical mechanisms that drive this response in both subtropical and Arctic stratocumulus clouds using large-eddy simulations and mechanism suppression tests. Three processes have been previously identified to contribute to the decrease, namely, the size dependency of evaporation, sedimentation, and radiation and all act to modulate the rate of entrainment of warm, dry air at the boundary layer top. We find that the liquid water path decrease is correlated with the increased entrainment, as expected, but that decrease is enhanced by a reduction in cloud radiative cooling. The reduced cloud radiative cooling can occur even though locally at cloud top, the radiative cooling rates are stronger and helping to enhance entrainment. We find that slower droplet sedimentation contributes to the increased entrainment and decreased liquid water in both cases. Faster evaporation caused directly by smaller, more numerous droplets decreases the liquid water path but does not necessarily increase the entrainment rate. On the other hand, stronger radiative cloud-top cooling caused directly by smaller droplets increases the entrainment as much as slower sedimentation does but does not decrease the liquid water path as much. In general, processes that either directly or indirectly increase radiative cooling at cloud top are more important in the Arctic case and processes that increase the evaporation rate are more important in the subtropical case.

Seasonal variation in airborne microbial communities of the Akiyoshido Cave: Lampenflora dispersed by phototrophic bioaerosols

Lampenflora, such as phototrophic microorganisms, multiply on speleothem surfaces under the show-cave lighting, causing deterioration of the natural and cultural heritages of the caves. Speleothems change color from white to green through microbial photosynthesis and are destroyed by microbial metabolisms. Aerosol transmission are suspected to disperses photosynthetic microorganisms. However, the mechanism underlying the process remains unclear, because the complexity of air ventilation affects the cave atmosphere. In the present study, we collected aerosol samples from the Akiyoshido Cave, which is a special natural monument in Japan and possesses various types of speleothems, to analyze microbial concentrations and communities in the cave atmosphere. Under a fluorescence microscope, phototrophic and heterotrophic microorganisms were observed in the aerosols with in the cave. The aerosol concentrations showed seasonal changes depending on air-flow variations in cave ventilation. High-throughput DNA sequencing targeting 16S rRNA genes revealed that the airborne bacterial communities inside the cave were dominated by members of the phyla Actinomycetota, Bacillota, and Pseudomonadota, originating from the external terrestrial, phyllosphere or freshwater environments, as well as its interior (guano). Cyanobacteria showed small relative abundances (from 1.0 to 10%) randomly in the aerosol samples at several locations in the cave, suggesting that the lampenflora-derived cyanobacteria were dispersed throughout the cave by the ventilation. Additionally, phototrophic microorganisms closely related to the relatives of the genera Leptolyngbya, Calothrix, and Chroococcidiopsis from the phylum Cyanobacteria were isolated from the aerosol samples. These results confirm that Cyanobacteria are one of the candidate microorganisms responsible for lampenflora dispersion and are “alive and airborne” in caves.

Tall tower observations of a northward surging gust front in central Amazon and its role in the mesoscale transport of carbon dioxide

AbstractHigh‐frequency measurements obtained at two micrometeorological towers are investigated for a rare northward surging gust front that impacted the Amazon Tall Tower Observatory (ATTO), in central Amazon. The gust front originated from a decaying mesoscale convective system (MCS) during the morning hours of 27 December 2021 near Manaus, Amazonas state, northern Brazil, and surged north‐eastward towards the ATTO site. Large temperature drops and vigorous, persistent winds were observed at the towers which lasted for over 4 h despite the gust front being detached from its parent, decaying MCS. More importantly, the gust front was responsible for drastic increases of CO2 concentrations throughout the tower depths, which suggests that the gust front winds horizontally advected CO2‐rich air from a source upstream from the ATTO site. The CO2‐rich outflow is hypothesized to originate from downward transport and/or biomass burning from forest fires in southeastern Amazon, both ideas that are supported by large increases of aerosol concentrations measured at ATTO following the gust front passage. Our results stress the need for further investigations addressing the role played by mesoscale convective circulations in the redistribution of trace gases and aerosols in the Amazon.

An Ionization-Based Aerosol Sensor and Its Performance Study.

In recent years, with the rapid development of new energy vehicles, the safety issues of lithium-ion batteries have attracted attentions from all sectors of society. Research has found that during the thermal runaway process of lithium-ion batteries, aerosol emissions usually occur earlier than other gases. Accurate and timely measurement of these aerosol concentrations can help to warn the power battery pack fires. However, existing aerosol sensors are unable to meet the requirements of real-time monitoring and high precision. This article proposes an ionization mechanism based aerosol sensor that works at principles of field emission, field charging and gas discharge, and investigates its static and dynamic response characteristics. The sensor is manufactured and assembled using Microelectro Mechanical Systems processing technology. The sensor exhibits superior performances in terms of range, sensitivity, nonlinearity, repeatability, response time, and other aspects. The study provides a new solution for current aerosol detection with great potential for application.

Evaluation of different computational methods for numerical simulation of aerosol distribution in the operating room

In traditional operating rooms, controlling the concentration of aerosol particles has been necessary to ensure surgical safety. The COVID-19 pandemic has further emphasized the need for protecting medical staff in operating rooms, thereby increasing the focus on aerosol concentrations. Accurate simulation calculations of aerosol concentration and distribution play a crucial role in evaluating these concentrations and the associated risk of exposure. This study aims to assess the distribution of aerosols within an operating room by employing four different calculation methods and comparing them with experimental data. These methods included two turbulence models - Reynolds Averaged Navier Stokes (RANS) and Large Eddy Simulation (LES)-combined with two different aerosol transmission calculation models -Lagrangian and Eulerian. The findings indicate that the LES model yields a more accurate representation of the flow field, whereas no significant differences were observed among the four methods when it came to calculating aerosol concentrations. However, Eulerian-based methods exhibited superior continuity in the results. The errors of the four methods were greater than 50 % at Class II sampling locations and less than 50 % at Class III sampling locations. Consequently, this study serves as a scientific reference for selecting appropriate numerical simulation methods to predict aerosol concentration and distribution in operating rooms.

On the sensitivity of aerosol–cloud interactions to changes in sea surface temperature in radiative–convective equilibrium

Abstract. Clouds play a vital role in regulating Earth's energy balance and are impacted by anthropogenic aerosol concentration (Na) and sea surface temperature (SST) alterations. Traditionally, these factors, aerosols and SST, are investigated independently. This study employs cloud-resolving, radiative–convective-equilibrium (RCE) simulations to explore aerosol–cloud interactions (ACIs) under varying SSTs. ACIs are found to be SST-dependent even under RCE conditions. Notably, changes in cloud radiative effects for both longwave radiation and shortwave radiation lead to a decrease in top-of-atmosphere (TOA) energy gain with increasing Na. The changes in TOA shortwave flux exhibit greater sensitivity to underlying SST conditions compared to longwave radiation. To comprehend these trends, we perform a linear decomposition, analyzing the responses of different cloud regimes and contributions from changes in the cloud's opacity and occurrence. This breakdown reveals that ice and shallow clouds predominantly contribute to the radiative effect, mostly due to changes in the cloud's opacity and due to the Twomey effect, which is proportional to the baseline cloud fraction. Moreover, with an increase in Na, we observe an increase in latent heat release at the upper troposphere associated with heightened production of snow and graupel. We show that this trend, consistently across all SSTs, affects the anvil cloud cover by affecting the static stability at the upper troposphere via a similar mechanism to the stability iris effect, resulting in an increase in outgoing longwave radiation. In conclusion, under the ongoing climate change, studying the sensitivity of clouds to aerosols and SST should be conducted concomitantly as mutual effects are expected.

Assessment of clear-sky irradiance from 6S affected by local climatology of India

Accurate estimation of solar power generation is crucial for the effective planning and operation of solar energy sector. Solar potential can be estimated at a location from long-term historical irradiance data processed from atmospheric reanalysis datasets. The current study employs a clear-sky radiative transfer model (6S) to simulate the net surface irradiance at four distinct locations in India, comparing our model's output with mean monthly ground-based measurements of surface irradiance. Our findings reveal that the 6S model marginally underestimates solar irradiance, with potential deviations varying depending on the accuracy of input data. This research evaluates the influence of particulate matter concentration and relative humidity on the scattering and absorption of solar radiation. We also state the variability in surface irradiance across the country with the rainfall trends that enhance assessment accuracy. The study reports an annual deviation of 10–15 % in surface irradiance across the country, where rural settlements show lower deviations in simulations. The radiative transfer calculations mentioned in the study are simplistic yet beneficial for a priori evaluation of solar potential. Transmittance estimated from clear-sky models is further implemented in all-sky (with clouds), and thus, model accuracy is an important parameter. Additionally, we explore the trends in aerosol concentrations and the impact of local climatological factors on surface irradiance, providing insights critical for optimizing solar energy utilization.

Diffusion behavior and transport risk of bioaerosol particles in a domestic waste landfill site in an arid and cold region of northwestern China

Bioaerosols have attracted increasing attention as novel contaminants because of their potential role in the spread of disease. In this study, sampling sites were established in a landfill in northwestern China with the aim of investigating the emission and diffusion characteristics of bioaerosols. The results revealed that the counts of airborne bacteria released by landfill cover area (LCA) and waste dumping area (WDA) located in the landfill area reached 18 193 ± 30 CFU/m3 and 10 948 ± 105 CFU/m3, respectively. These two aeras were the main sources of bioaerosol generation. Meanwhile, Corynebacterium spp., Bacteroidetes spp., and Pseudomonas spp. were identified as potential pathogens. A Gaussian model was applied to simulate the diffusion of the bioaerosols; the influence distance was calculated as 12 km from the boundary of the landfill site. The potential health risks of bioaerosol exposure to on-site workers and nearby residents were calculated and evaluated in terms of aerosol concentration, particle size, and pathogenic bacteria. The present study promotes the recognition of the emission behavior of microorganisms in aerosol particles and provides a basis for controlling bioaerosol contamination from landfill sites, particularly those located in cold and arid northwestern regions of China.

Breathing Clean Air: Navigating Indoor Air Purification Techniques and Finding the Ideal Solution.

The prevalence of airborne pathogens in indoor environments presents significant health risks due to prolonged human occupancy. This review addresses diverse air purification systems to combat airborne pathogens and the factors influencing their efficacy. Indoor aerosols, including bioaerosols, harbor biological contaminants from respiratory emissions, highlighting the need for efficient air disinfection strategies. The COVID-19 pandemic has emphasized the dangers of airborne transmission, highlighting the importance of comprehending how pathogens spread indoors. Various pathogens, from viruses like SARS-CoV-2 to bacteria like Mycobacterium (My) tuberculosis, exploit unique respiratory microenvironments for transmission, necessitating targeted air purification solutions. Air disinfection methods encompass strategies to reduce aerosol concentration and inactivate viable bioaerosols. Techniques like ultraviolet germicidal irradiation (UVGI), photocatalytic oxidation (PCO), filters, and unipolar ion emission are explored for their specific roles in mitigating airborne pathogens. This review examines air purification systems, detailing their operational principles, advantages, and limitations. Moreover, it elucidates key factors influencing system performance. In conclusion, this review aims to provide practical knowledge to professionals involved in indoor air quality management, enabling informed decisions for deploying efficient air purification strategies to safeguard public health in indoor environments.