Number Concentration Research Articles

62°S Witnesses the Transition of Boundary Layer Marine Aerosol Pattern Over the Southern Ocean (50°S–68°S, 63°E–150°E) During the Spring and Summer: Results From MARCUS (I)

AbstractThe Atmospheric Radiation Measurement Mobile Facility‐2 was installed onboard the research vessel Aurora Australis to measure aerosol properties during the 2017–2018 Measurement of Aerosols, Radiation, and CloUds over the pristine Southern ocean (MARCUS) Experiment, providing unique data on aerosols latitudinal and seasonal variation, including south of 60°S where previous observations are scarce. Data from a Cloud Condensation Nuclei (CCN) counter and Ultra‐High‐Sensitivity Aerosol Spectrometer show that both the number concentration (NCCN) and size distribution of CCN‐active aerosols, with diameters (D) between 60 nm < D < 1,000 nm are different over the North Southern Ocean (NSO) (50°S–60°S) and the South Southern Ocean (SSO) (62°S–68°S). The average NSO NCCN at 0.2% and 0.5% supersaturation were 28% and 49% less than that over the SSO. This increase of CCN over the SSO is caused by the increase of aerosols with 60 nm < D < 200 nm, consistent with calculations of Aerosol Scattering Angstrom Exponents derived from a nephelometer. Aerosol hygroscopicity growth factor measured by the Hygroscopic Tandem Differential Mobility Analyzer stayed close to 1.41 for aerosols with 50 nm < D < 250 nm over the SSO, but increased from 1.30 to 1.67 over the NSO, indicating different chemical compositions. Both CCN and Ice Nucleating Particles (INPs) showed a stronger variation with season than with latitude. The variation of heat‐labile and presumably proteinacous INPs suggests an increase of ice nucleating‐active microbes in summer.

The relative contributions of traffic and non-traffic sources in ultrafine particle formations in Tehran mega city

Emissions of ultrafine particles (UFPs; diameter < 100 nm) are strongly associated with traffic-related emissions and are a growing global concern in urban environments. The aim of this study was to investigate the variations of particle number concentration (PNC) with a diameter > 10 nm at nine stations and understand the major sources of UFPs (primary vs. secondary) in Tehran megacity. The study was carried out in Tehran in 2020. NOx and PNC were reported from a total of nine urban site locations in Tehran and BC concentrations were examined at two monitoring stations. Data from all stations showed diurnal changes with peak morning and evening rush hours. The hourly PNC was correlated with NOx. PNCs in Tehran were higher compared to those of many cities reported in the literature. The highest concentrations were at District 19 station (traffic) and the lowest was at Punak station (residential) such that the average PNC varied from 8.4 × 103 to 5.7 × 104 cm−3. In Ray and Sharif stations, the average contributions of primary and secondary sources of PNC were 67 and 33%, respectively. Overall, we conclude that a decrease in primary emission leads to a decrease in the total concentration of aerosols, despite an increase in the formation of new particles by photo nucleation.

Vertical Profiles of Aerosol Mass, Number, and Cloud Droplet Number Concentrations: Comparisons of GEOS‐Chem‐APM Simulations With ATom Airborne Measurements and CloudSat Retrievals

AbstractA better understanding of vertical distributions of aerosol and cloud droplet number concentrations is important for the study of aerosol‐cloud interaction which is one of the key uncertainties in climate change projection. In this study, we compared the aerosol mass and number concentrations simulated by a size‐resolved advanced particle microphysics (APM) package coupled with a global 3‐D chemical transport model (GEOS‐Chem) with the NASA’s Atmospheric Tomography Mission (ATom) measurements at the Pacific Ocean and the Atlantic Ocean during ATom‐1 and ATom‐2 campaign periods. Generally, the model captured the spatial pattern and seasonal variation of aircraft observed aerosol mass and number concentrations. The model simulated cloud droplet number concentrations (CDNC) were compared with CloudSat retrievals whose orbits were nearby ATom's flight tracks on the same days. Correlation coefficients of simulated and retrieved CDNC at ATom‐1 Pacific Ocean, ATom‐1 Atlantic Ocean, ATom‐2 Pacific Ocean, and ATom‐2 Atlantic Ocean are 0.83, 0.97, 0.87, and 0.73, respectively. Both satellite retrievals and model simulations indicated that the averaged values of CDNC at the Pacific Ocean and the Atlantic Ocean during ATom‐1 and ATom‐2 periods decreased with altitudes. The ratio of CDNC in the lower troposphere (1,000–800 hPa) to those in the middle troposphere (600–400 hPa) was 1.9 (1.6–2.3) based on CloudSat retrievals and 2.2 (1.2–3.0) based on the model simulations. Model analysis indicated that secondary particles dominate CDNC in the atmosphere and primary organic aerosols have important contributions to CDNC, especially at the Atlantic Ocean during ATom‐1.

An Evaluation and Improvement of Microphysical Parameterization for a Heavy Rainfall Process during the Meiyu Season

The present study assesses the simulated precipitation and cloud properties using three microphysics schemes (Morrison, Thompson and MY) implemented in the Weather Research and Forecasting model. The precipitation, differential reflectivity (ZDR), specific differential phase (KDP) and mass-weighted mean diameter of raindrops (Dm) are compared with measurements from a heavy rainfall event that occurred on 27 June 2020 during the Integrative Monsoon Frontal Rainfall Experiment (IMFRE). The results indicate that all three microphysics schemes generally capture the characteristics of rainfall, ZDR, KDP and Dm, but tend to overestimate their intensity. To enhance the model performance, adjustments are made based on the MY scheme, which exhibited the best performance. Specifically, the overall coalescence and collision parameter (Ec) is reduced, which effectively decreases Dm and makes it more consistent with observations. Generally, reducing Ec leads to an increase in the simulated content (Qr) and number concentration (Nr) of raindrops across most time steps and altitudes. With a smaller Ec, the impact of microphysical processes on Nr and Qr varies with time and altitude. Generally, the autoconversion of droplets to raindrops primarily contributes to Nr, while the accretion of cloud droplets by raindrops plays a more significant role in increasing Qr. In this study, it is emphasized that even if the precipitation characteristics could be adequately reproduced, accurately simulating microphysical characteristics remains challenging and it still needs adjustments in the most physically based parameterizations to achieve more accurate simulation.

A New Melting Model and Its Implementation in Parameterized Forward Operators for Polarimetric Radar Data Simulation With Double Moment Microphysics Schemes

AbstractTo improve short‐term severe weather forecasts through assimilation of polarimetric radar data (PRD), the use of accurate and efficient forward operators for polarimetric radar variables is required. In this study, a new melting model is proposed to estimate the mixing ratio and number concentration of melting hydrometeor species and incorporated in a set of parameterized polarimetric radar forward operators. The new melting model depends only on the mixing ratio and number concentration of rain and ice species and is characterized by its independence from ambient temperature and its simplicity and ease of linearization. To assess the impact of this newly proposed melting model on the simulated polarimetric radar variables, a real mesoscale convective system is simulated using three double‐moment microphysics schemes. Compared with the output of the original implementation of the parameterized forward operators (PFO_Old) that rely on an “old” melting model which only estimates the mixing ratio of the melting species, the updated implementation with the new melting model (PFO_New) that estimates both the mixing ratio and number concentration of melting species eliminates the very large mass/volume‐weighted mean diameter (Dm) at the bottom of the melting layer and produces more reasonable melting layer signatures for all three double‐moment microphysics schemes that more closely match the corresponding radar observations. This suggests that the new melting model has more reasonable implicit estimates of mixing ratios and number concentrations of melting hydrometeor species than the “old” melting model.

Efficient droplet activation of ambient black carbon particles in a suburban environment

Abstract. The cloud condensation nuclei (CCN) activity of black carbon (BC) particles importantly determines their impacts on cloud microphysics and atmospheric lifetime. This process is crucially influenced by the number of hygroscopic coating materials that BC acquire during the ageing process. It remains a challenge for ambient measurements to capture this process and link this with CCN activity of BC. Here, we directly measured the droplet activation diameter (D50) and activation fraction of BC-containing (BCc) particles (Fact,BC) in suburban Beijing using coupled measurements of size-resolved number concentrations of CCN at configured water supersaturation (SS) and BCc particles. The number concentration of BCc particles was found to peak at diameter 180–210 nm after acquiring coatings, larger than that for all particles (50–150 nm). Consequently, the initially smaller BC particles become enlarged and more hygroscopic, thereby exhibiting CCN activities than other particles. The Fact,BC increased from 42 % to 69 % in number and from 67 % to 85 % in mass as SS increased from 0.1 % to 0.2 % but tended to reach a plateau when SS &gt; 0.2 %. Notably, Fact,BC and D50 linearly correlated with equivalent photochemical age, at a rate of +2 % h−1 and −3 nm h−1, respectively. The results suggest BCc particles from anthropogenic sources can readily serve as CCN at a relatively low SS, and more than half of the BC population can be activated within a few hours, indicating that the surface-sourced BC can efficiently incorporate into clouds and potentially exert important indirect radiative impacts.

In-situ observations of cloud microphysics over Arabian Sea during dust transport events

The unique in situ measurements of clouds and precipitation within the shallow and deep cumulus over the north-eastern Arabian Sea region during the Indian monsoon are illustrated in this study with a focus on droplet spectral parameters. The observational period showed a significant incursion of Arabian dust and the presence of giant cloud condensation nuclei (GCCN), modifying the cloud and precipitation spectral properties. Warm rain microphysics supported the mixed-phase development in these clouds and exhibited hydrometeors of snow, graupel and large aggregates as part of ice processes. Cloud base droplet number concentration is about 142 ± 79 cm−3 which is one third of the cloud condensation nuclei (CCN) number concentration at 0.2% supersaturation. A rapid broadening of droplet size distribution (DSD) near to the cloud base was noted in contrast to polluted continental clouds. Relationship between the relative dispersion ( ε; the ratio of DSD spectral width ( σ ) to mean radius ( rm )) and liquid water adiabatic fraction (AF) indicates that the entrainment effect has increased relative dispersion significantly (2–3 times larger) in these clouds. Effective radius ( reff ) is found to be proportional to mean volume radius ( rv ) with a proportionality constant ( β ) that varies between 1.0–1.6, depending on the spectral dispersion parameter. Drop size distributions for the small cloud droplets with size range 2–50 μ m and the large drizzle drops (or ice hydrometeors) with size range 100–6400 μ m are parameterized using the gamma function distributions useful for large-scale cloud models.

Influence of the twisting and nano fluids on performance of a triangular double tube heat exchanger

Abstract The hydraulic and thermals performance of flow in a double-tube heat exchanger with an inner twisted triangle tube of length L = 1 m has been studied numerically. Equations for energy, turbulence, and Navier–Stokes were used to model the fluid flow and heat transfer in a double-tube heat exchanger with an inner twisted triangle tube. The Reynolds number range was 5000–30,000 for nanofluid (water-Al2O3) as a working fluid under a turbulent flow regime. The considered configuration was examined by varying the volume concentration of nanofluid while keeping the twist ratio constant (Tr = 5). Different cases of volume concentration of nanofluid are triggered (0.05 %, 1 %, 2.5 %, and 4 %, respectively). The numerical outcomes of a double-twisted tube heat exchanger with an inner triangle-twisted tube are validated with the obtainable numerical data. The governing equations were solved with ANSYS Fluent 18.2. The findings reveal that the larger volume concentration of nanofluid (4 %) gives a greater Nusselt number and vice versa due to the increased thermal conductivity of the nanofluid in the double twist tube heat exchanger compared with a plain tube. However, the nanofluid Nusselt number grows with the rise of both the Reynolds number and volume concentration (Ø), and the best value of the Nusselt number is 210 when Reynolds number = 30,000 and Ø = 4 %. The effectiveness of the heat exchanger grows with an increase in the concentration of the nanofluid and a reduction in the torsion ratio compared to the normal tube. The effectiveness of the double-tube heat exchanger with an inner twist triangle tube increases to the highest value of 0.38 at Reynolds 30,000 and Ø = 4 %.

Single particle inductively coupled plasma mass spectrometry metrology: Revisiting the transport efficiency paradigm

Transport efficiency has become a critical parameter in single particle inductively coupled plasma mass spectrometry (SP-ICP-MS) since it is involved in the calibrations to determine different measurands (element mass per particle, particle size and particle number concentration). Specific methods for its determination based on the use of particle standards have been developed and widely applied (particle frequency and particle size methods). A refined indirect method not relying on particle standards is also available (dynamic mass flow method). A number of discrepancies on the accuracy of these methods and their adequacy have become evident, making a revision of the topic pertinent. In fact, the application of the particle frequency and particle size methods determine the transport efficiencies corresponding to the particles or the dissolved element respectively, whereas the solvent transport efficiency is actually measured by the dynamic mass flow method. The use of each of these methods requires assuming different conditions that must be considered. These conditions, together with the sources of bias associated to each method are critically discussed to provide a holistic and harmonized view of transport efficiency in the context of SP-ICP-MS metrology.

OPC-Pod: A New Sensor Payload to Measure Aerosol Particles for Small Uncrewed Aircraft Systems

Abstract Atmospheric aerosols affect human health and influence atmospheric and biological processes. Dust can be transported long distances in the atmosphere, and the mechanisms that influence dust transport are not fully understood. To improve the database for numerical models that simulate dust transport, measurements are needed that cover both the vertical distribution of the dust and its size distribution. In addition to measurements with crewed aircraft, uncrewed aircraft systems (UASs) provide a particularly suitable platform for this purpose. In this paper, we present a payload for the small fixed-wing UAS of the type Multiple-Purpose Airborne Sensor Carrier 3 (MASC-3) for aerosol particle measurements that is based on the optical particle counter (OPC) OPC-N3 (Alphasense, United Kingdom), modified by the addition of a dryer and a passive aspiration system (OPC-Pod). Based on field tests with a reference instrument in Mannheim, Germany, wind tunnel tests, and a comparison measurement with the UAS-mounted aerosol particle measurement Universal Cloud and Aerosol Sounding System (UCASS) during a dust event over Cyprus, we show that the OPC-Pod can measure particle number concentrations in the range of 0.66–31 μm as well as particle size distributions. The agreement of the OPC-Pod with UCASS is good. Both instruments resolve a vertical profile of the Saharan dust event, with a prominent dust layer between 1500 and 2800 m MSL, with particle number concentrations up to 35 cm−3 for particles between 0.66 and 31 μm.

Secondary Ice Production in Simulated Deep Convective Clouds: A Sensitivity Study

Abstract Multiple mechanisms have been proposed to explain secondary ice production (SIP), and SIP has been recognized to play a vital role in forming cloud ice crystals. However, most weather and climate models do not consider SIP in their cloud microphysical schemes. In this study, in addition to the default rime splintering (RS) process, two SIP processes, namely, shattering/fragmentation during freezing of supercooled rain/drizzle drops (DS) and breakup upon ice–ice collisions (BR), were implemented into a two-moment cloud microphysics scheme. Besides, two different parameterization schemes for BR were introduced. A series of sensitivity experiments were performed to investigate how SIP impacts cloud microphysics and cloud phase distributions in warm-based deep convective clouds developed in the central part of Europe. Simulation results revealed that cloud microphysical properties were significantly influenced by the SIP processes. Ice crystal number concentrations (ICNCs) increased up to more than 20 times and surface precipitation was reduced by up to 20% with the consideration of SIP processes. Interestingly, BR was found to dominate SIP, and the BR process rate was larger than the RS and DS process rates by four and three orders of magnitude, respectively. Liquid pixel number fractions inside clouds and at the cloud top decreased when implementing all three SIP processes, but the decrease depended on the BR scheme. Peak values of ice enhancement factors (IEFs) in the simulated deep convective clouds were 102–104 and located at −24°C with the consideration of all three SIP processes, while the temperature dependency of IEF was sensitive to the BR scheme. However, if only RS or RS and DS processes were included, the IEFs were comparable, with peak values of about 6, located at −7°C. Moreover, switching off the cascade effect led to a remarkable reduction in ICNCs and ice crystal mass mixing ratios. Significance Statement The cloud phase is found to have a significant impact on cloud evolution, radiative properties, and precipitation formation. However, the simulation of the cloud phase is a big challenge for cloud research because multiple processes are not well described or missing in numerical models. In this study, we implemented two secondary ice production (SIP) processes, namely, shattering/fragmentation during the freezing of supercooled rain/drizzle drops and breakup upon ice–ice collisions, which are missing in most numerical models. Sensitivity experiments were conducted to investigate how SIP impacts cloud microphysics and cloud phase in deep convective clouds. We found that SIP significantly impacts in-cloud and cloud-top phase distribution. We also identified that the collisional breakup of ice particles is the dominant SIP process in the simulated deep convective clouds.

Cloud response to co-condensation of water and organic vapors over the boreal forest

Abstract. Accounting for the condensation of organic vapors along with water vapor (co-condensation) has been shown in adiabatic cloud parcel model (CPM) simulations to enhance the number of aerosol particles that activate to form cloud droplets. The boreal forest is an important source of biogenic organic vapors, but the role of these vapors in co-condensation has not been systematically investigated. In this work, the environmental conditions under which strong co-condensation-driven cloud droplet number enhancements would be expected over the boreal biome are identified. Recent measurement technology, specifically the Filter Inlet for Gases and AEROsols (FIGAERO) coupled to an iodide-adduct chemical ionization mass spectrometer (I-CIMS), is utilized to construct volatility distributions of the boreal atmospheric organics. Then, a suite of CPM simulations initialized with a comprehensive set of concurrent aerosol observations collected in the boreal forest of Finland during spring 2014 is performed. The degree to which co-condensation impacts droplet formation in the model is shown to be dependent on the initialization of temperature, relative humidity, updraft velocity, aerosol size distribution, organic vapor concentration, and the volatility distribution. The predicted median enhancements in cloud droplet number concentration (CDNC) due to accounting for the co-condensation of water and organics fall on average between 16 % and 22 %. This corresponds to activating particles 10–16 nm smaller in dry diameter that would otherwise remain as interstitial aerosol. The highest CDNC enhancements (ΔCDNC) are predicted in the presence of a nascent ultrafine aerosol mode with a geometric mean diameter of ∼ 40 nm and no clear Hoppel minimum, indicative of pristine environments with a source of ultrafine particles (e.g., via new particle formation processes). Such aerosol size distributions are observed 30 %–40 % of the time in the studied boreal forest environment in spring and fall when new particle formation frequency is the highest. To evaluate the frequencies with which such distributions are experienced by an Earth system model over the whole boreal biome, 5 years of UK Earth System Model (UKESM1) simulations are further used. The frequencies are substantially lower than those observed at the boreal forest measurement site (&lt; 6 % of the time), and the positive values, peaking in spring, are modeled only over Fennoscandia and the western parts of Siberia. Overall, the similarities in the size distributions between observed and modeled (UKESM1) are limited, which would limit the ability of this model, or any model with a similar aerosol representation, to project the climate relevance of co-condensation over the boreal forest. For the critical aerosol size distribution regime, ΔCDNC is shown to be sensitive to the concentrations of semi-volatile and some intermediate-volatility organic compounds (SVOCs and IVOCs), especially when the overall particle surface area is low. The magnitudes of ΔCDNC remain less affected by the more volatile vapors such as formic acid and extremely low- and low-volatility organic compounds (ELVOCs and LVOCs). The reasons for this are that most volatile organic vapors condense inefficiently due to their high volatility below the cloud base, and the concentrations of LVOCs and ELVOCs are too low to gain significant concentrations of soluble mass to reduce the critical supersaturations enough for droplet activation to occur. A reduction in the critical supersaturation caused by organic condensation emerges as the main driver of the modeled ΔCDNC. The results highlight the potential significance of co-condensation in pristine boreal environments close to sources of fresh ultrafine particles. For accurate predictions of co-condensation effects on CDNC, also in larger-scale models, an accurate representation of the aerosol size distribution is critical. Further studies targeted at finding observational evidence and constraints for co-condensation in the field are encouraged.

Assessing the inhaled dose of nanomaterials by nanoparticle tracking analysis (NTA) of exhaled breath condensate (EBC) and its relationship with lung inflammatory biomarkers

The widespread and increasing use of nanomaterials has resulted in a higher likelihood of exposure by inhalation for nanotechnology workers. However, tracking the internal dose of nanoparticles deposited at the airways level, is still challenging.To assess the suitability of particle number concentration determination as biomarker of internal dose, we carried out a cross sectional investigation involving 80 workers handling nanomaterials. External exposure was characterized by portable counters of particles DISCminiTM (Testo, DE), allowing to categorize 51 workers as exposed and 29 as non-exposed (NE) to nanoparticles. Each subject filled in a questionnaire reporting working practices and health status. Exhaled breath condensate was collected and analysed for the number of particles/ml as well as for inflammatory biomarkers.A clear-cut relationship between the number of airborne particles in the nano-size range determined by the particle counters and the particle concentration in exhaled breath condensate (EBC) was apparent. Moreover, inflammatory cytokines (IL-1β, IL-10, and TNF-α) measured in EBC, were significantly higher in the exposed subjects as compared to not exposed. Finally, significant correlations were found between external exposure, the number concentration of particles measured by the nanoparticle tracking analysis (NTA) and inflammatory cytokines. As a whole, the present study, suggests that NTA can be regarded as a reliable tool to assess the inhaled dose of particles and that this dose can effectively elicit inflammatory effects.

Isolating pollen signals from laser diode aerosol Optical Particle Counter (OPC) data through positive matrix factorization (PMF) and Unmix receptor models

Pollen, a significant natural bioaerosol and allergen for sensitized individuals, is expected to increase in prevalence due to climate change. Mitigating allergy symptoms involves avoiding pollen exposure and pre-medication, emphasizing the importance of real-time knowledge of localized ambient air pollen concentrations. Laser diode Optical Particle Counters (OPCs) are commonly used for monitoring particle number concentrations in ambient air. This study explores the hypothesis that OPCs can monitor pollen but may struggle to distinguish them from other particles. We aimed to isolate the pollen signal from collective particle number concentrations using source apportionment models, specifically Positive Matrix Factorization (PMF) and Unmix, applied to multiple bin OPC data. The pollen signals isolated using PMF show slightly better correlation values than those isolated using Unmix. PMF-derived pollen signals exhibit strong correlations with Holoptelea (r = 0.64) and total pollen (r = 0.54) concentrations, while a moderate correlation is observed with Poaceae (r = 0.47). Exclusion of low pollen events strengthens correlations for Holoptelea and Poaceae to very strong (r = 0.87) and strong (r = 0.67), respectively. Although both model types effectively isolate the pollen signal, metrics suggest that Unmix has the potential for more accurate predictions of both moderate and extreme pollen events simultaneously. The Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Relative Root Mean Square Error (RRMSE) metrics for Holoptelea are 46.2 grains m−3, 72.4 grains m−3, and 15.3; for Poaceae, 3.9 grains m−3, 4.9 grains m−3, and 13.0; and for total pollen, 43.5 grains m−3, 72.1 grains m−3, and 14.1. This study represents a significant development in the use of source apportionment models and ambient OPCs for real-time pollen monitoring, offering a cost-effective alternative to conventional automated pollen sensors. Despite challenges, the proposed methodology provides a practical and accessible solution for pollen monitoring, contributing to the advancement of bioaerosol monitoring technologies.

Ultrafine particle measurements in New York State

Measurements of ultrafine particles (UFP) over several years were carried out across seven different locations in New York State. The locations include urban background sites (Queens College and Albany), near road sites (Queens, Buffalo and Rochester) and rural sites (Pinnacle State Park and Whiteface Mountain). UFP at the urban background and near road sites generally show highest concentrations in the morning during the early commute period. Concentrations decrease during the day but increase again in the afternoon or evening period. Weekday concentrations are higher than on weekends. UFP correlates well with traffic related co-pollutants black carbon (BC) and nitrogen oxides (NOx). At the rural locations, UFP concentrations show less variation during the day with highest concentrations in the early afternoon to late evening hours particularly in spring. Seasonally, UFP concentrations across urban background and near road sites, are highest in winter (Dec, Jan, Feb) and lowest in summer (Jun, Jul, Aug). The variation in UFP concentration with temperature, relative humidity and wind speed was investigated. At the Queens College site, particle number concentrations in six different size fractions were measured using a TSI 3031 instrument. Annual average UFP concentrations at Queens College were found to decrease over time consistent with emission control strategies.

Two-phase simulation of hydrothermal performance and entropy generation aspects of a biologically prepared nanofluid-cooled heat sink with helical Tesla valve-based microchannels

The continuous development of innovative cooling techniques is imperative for advancing electronic device performance, enhancing efficiency, and prolonging their operational reliability in an ever-evolving technological landscape. In this numerical investigation, the hydrothermal performance and entropy generation aspects of a heat sink featuring Tesla valve-base helical channels are explored using the two-phase mixture method. The chosen heat transfer fluid is a water-silver nanofluid synthesized through a biological method. The study delved into the impact of Reynolds number (Re = 500–2000) and nanofluid concentration (φ = 0–1%) on the system's functional parameters, and the results are subsequently compared with data associated with a heat sink employing the helical plain channels. It was uncovered that elevating Re and diminishing φ result in improved central processing unit (CPU) cooling, lowered thermal resistance, and a reduction in the temperature differential between the maximum and minimum CPU temperatures. Meanwhile, the pumping power of nanofluid increases with higher Re s and lower φ s. Furthermore, it was discovered that the overall hydrothermal performance of the heat sink with Tesla valve-type helical channel consistently surpasses that of the heat sink with helical plain channel. The peak value of the Performance Evaluation Criterion, reaching 1.642, was associated with Case Re = 500 &φ = 0 %. Furthermore, it was found that substituting the Tesla valve-base channel for the plain channel results in a decrease in the total entropy generation up to a Re of 1500.

Use of CAMS near Real-Time Aerosols in the HARMONIE-AROME NWP Model

Near real-time aerosol fields from the Copernicus Atmospheric Monitoring Services (CAMS), operated by the European Centre for Medium-Range Weather Forecasts (ECMWF), are configured for use in the HARMONIE-AROME Numerical Weather Prediction model. Aerosol mass mixing ratios from CAMS are introduced in the model through the first guess and lateral boundary conditions and are advected by the model dynamics. The cloud droplet number concentration is obtained from the aerosol fields and used by the microphysics and radiation schemes in the model. The results show an improvement in radiation, especially during desert dust events (differences of nearly 100 W/m2 are obtained). There is also a change in precipitation patterns, with an increase in precipitation, mainly during heavy precipitation events. A reduction in spurious fog is also found. In addition, the use of the CAMS near real-time aerosols results in an improvement in global shortwave radiation forecasts when the clouds are thick due to an improved estimation of the cloud droplet number concentration.

Ti-containing NPs in raw water and their removal with conventional treatments in four water treatment plants in Taiwan.

The ingestion of Ti-containing nanoparticles from drinking water has emerged as a concern in recent years. This study therefore aimed to characterize Ti-containing nanoparticles in water samples collected from four water treatment plants in Taiwan and to explore the challenges associated with measuring them at low levels using single particle-inductively coupled plasma mass spectrometry. Additionally, the study sought to identify the most effective processes for the removal of Ti-containing nanoparticles. For each water treatment plant, two water samples were collected from raw water, sedimentation effluent, filtration effluent, and finished water, respectively. Results revealed that Ti-containing nanoparticles in raw water, with levels at 8.69μg/L and 296.8 × 103 particles/L, were removed by approximately 35% and 98%, respectively, in terms of mass concentration and particle number concentration, primarily through flocculation and sedimentation processes. The largest most frequent nanoparticle size in raw water (112.0 ± 2.8nm) was effectively reduced to 62.0 ± 0.7nm in finished water, while nanoparticles in the size range of 50-70nm showed limited changes. Anthracite was identified as a necessary component in the filter beds to further improve removal efficiency at the filtration unit. Moreover, the most frequent sizes of Ti-containing nanoparticles were found to be influenced by salinity. Insights into the challenges associated with measuring low-level Ti-containing nanoparticles in aqueous samples provide valuable information for future research and management of water treatment processes, thereby safeguarding human health.

Experimental studies on the effect of Al2O3 + water nanofluid concentrations on dimensionless heat transfer parameters in a cleanroom air handling unit

Nanofluid, a colloidal suspension of nonmetallic or metallic nanoparticles into conventional base fluid and used for heat transfer characteristics enhancement for many industrial applications. Cleanrooms are essential at various industries for controlling airborne contamination and environmental parameters. In this article, heat transfer properties of nanofluid (Al2O3 + water) at various nanoparticle concentrations (1%, 2%, and 3%) on a prototype cleanroom air handling chiller unit was investigated experimentally in laminar flow zone. Thermal conductivity ratio, Nusselt number, Peclet number, and pressure drop were obtained for above nanoparticle concentrations. Experimental investigations indicate the heat transfer properties improvement in a prototype cleanroom air handling chiller unit by using nanoparticle at base fluid. Experimental investigation on varying Al2O3 + water nanofluid concentrations in a cleanroom air handling chiller unit heat exchanger revealed a notable increase in heat transfer by reducing nanoparticle size from 50 to 10 nm and increasing concentration from 1% to 3% volume, resulting in a 17.70% rise in thermal conductivity ratio and a significant 9.23% increase in Nusselt number at higher Peclet numbers. However, this improvement in heat transfer was accompanied by a substantial 72.5% increase in pressure drops, particularly with increased Reynolds number and particle concentration. Manipulating nanoparticle characteristics resulted in substantial improvements in Nusselt number across a wide range of Reynolds numbers, with smaller particle sizes and higher volume concentrations yielding more significant heat transfer improvements. The novelty of this research lies in its investigation of the influence of variable Al2O3 + water nanofluid concentrations, encompassing different nanoparticle sizes, and volume concentrations, on dimensionless heat transfer parameters within a cleanroom air handling unit, offering valuable insights into optimizing heat transfer efficiency in a controlled and critical environment, addressing a significant research gap in the field.

Proteomics Reveals the Obstruction of Cellular ATP Synthesis in the Ruminal Epithelium of Growth-Retarded Yaks.

Growth-retarded yaks are of a high proportion on the Tibetan plateau and reduce the economic income of farmers. Our previous studies discovered a maldevelopment in the ruminal epithelium of growth-retarded yaks, but the molecular mechanisms are still unclear. This study aimed to reveal how the proteomic profile in the ruminal epithelium contributed to the growth retardation of yaks. The proteome of the ruminal epithelium was detected using a high-resolution mass spectrometer. There were 52 proteins significantly differently expressed between the ruminal epithelium of growth-retarded yaks and growth-normal yaks, with 32 downregulated and 20 upregulated in growth-retarded yaks. Functional analysis showed the differently expressed proteins involved in the synthesis and degradation of ketone bodies (p = 0.012), propanoate metabolism (p = 0.018), pyruvate metabolism (p = 0.020), and mineral absorption (p = 0.024). The protein expressions of SLC26A3 and FTH1, enriched in the mineral absorption, were significantly downregulated in growth-retarded yaks. The key enzymes ACAT2 and HMGCS2 enriched in ketone bodies synthesis and key enzyme PCCA enriched in propanoate metabolism had lower protein expressions in the ruminal epithelium of growth-retarded yaks. The ATP concentration and relative mitochondrial DNA copy number in the ruminal epithelium of growth-normal yaks were dramatically higher than those of growth-retarded yaks (p < 0.05). The activities of citrate synthase (CS), the α-ketoglutarate dehydrogenase complex (α-KGDHC), isocitrate dehydrogenase (ICD) in the tricarboxylic acid cycle (TCA), and the mitochondrial respiratory chain complex (MRCC) were significantly decreased in ruminal epithelium of growth-retarded yaks compared to growth-normal yaks (p < 0.05). The mRNA expressions of COQ9, COX4, and LDHA, which are the encoding genes in MRCC I, IV and anaerobic respiration, were also significantly decreased in the ruminal epithelium of growth-retarded yaks (p < 0.05). Correlation analysis revealed that the average daily gain (ADG) was significantly positively correlated to the relative mitochondrial DNA copy number (p < 0.01, r = 0.772) and ATP concentration (p < 0.01, r = 0.728) in the ruminal epithelium, respectively. The ruminal weight was positively correlated to the relative mitochondrial DNA copy number (p < 0.05, r = 0.631) and ATP concentration in ruminal epithelium (p < 0.01, r = 0.957), respectively. The ruminal papillae had a significant positive correlation with ATP concentration in ruminal epithelium (p < 0.01, r = 0.770). These results suggested that growth-retarded yaks had a lower VFA metabolism, ketone bodies synthesis, ion absorption, and ATP synthesis in the ruminal epithelium; it also indicated that the growth retardation of yaks is related to the obstruction of cellular ATP synthesis in rumen epithelial cells.