Filter Samples Research Articles

Comparison of liquid and filter sampling techniques for recovery of Bacillus spores and Escherichia coli from environmental water

Historically, detecting water contamination has involved collecting and directly analyzing liquid samples, but recent advances in filter sampling methods offer numerous potential advantages. Emerging technologies, including environmental DNA (eDNA) samplers, could be used for remote microbial contamination sampling, but work is needed to determine if target microorganisms can be recovered from filters at comparable levels to traditional sampling methods. In this study, Escherichia coli and a surrogate for Bacillus anthracis spores were sampled from synthetic stormwater and quantified using both direct liquid and filter methods, and dwell time tests compared microorganism persistence in water and on filters. At nearly all tested timepoints, the recoveries of spores from membrane filters were within 0.5 log10 colony forming units per sample (CFU/sample) compared to the liquid-only samples, suggesting that the use of filter sampling is a feasible alternative to liquid-based sampling, and samples were held for up to 4 weeks without significant sample degradation. Recoveries for E. coli remained relatively consistent for ∼3 days in phosphate buffered saline (PBS), in synthetic stormwater, and on membrane filters, but decreases in recoveries were observed for samples held for >3 days. These results indicate that emerging water sampling technologies, which reduce logistical burdens and offer potential cost savings, can be leveraged to characterize biological contamination in water matrices with multiple types of microbiological agents.

Schools and Indoor Air Quality: seasonal variation

Abstract Background Indoor Air Quality (IAQ) in schools is a public health concern, given the vulnerability of children as a demographic group and substantial amount of time that they spend in (highly occupied) classrooms. Conditions specific for school buildings, as well as location and outdoor air quality (OAQ), can adversely affect IAQ and children’s health. The aim of this study was to examine the seasonal variation in IAQ and the influence of OAQ herein in primary schools. Methods Sampling was carried out in summer and winter in 5 schools in central Poland. A culture-dependent method using impactors was applied to examine the total number of bacteria and fungi. Gas chromatography with flame ionization detector (quartz filters for sampling) was applied to determine concentrations of 16 polycyclic aromatic hydrocarbons (PAHs), crucial for their health impact. Results In poorly ventilated classrooms bacteria levels exceeded that of fungi. Bacterial contamination decreased in efficiently ventilated rooms, and before/after the lessons. In summer fungi concentration in indoor air was higher than in winter and reached the level of fungi outdoors. PAHs concentrations (especially those with 4 and more rings, which are biologically active) and the mutagenicity and carcinogenicity equivalents were elevated in winter and related to changes in concentrations in outdoor air. Conclusions IAQ in schools depends on a season. Occupants in classrooms are the main source of bacteria, but the type and number of microorganisms also depend on ventilation conditions. PAHs characteristic of coal/wood combustion indicates that in the absence of internal emission sources, external sources most likely affect IAQ in schools in winter.

Desorption efficiency and holding capacity of acid-treated filters for nicotine sampling in vape shops.

Efficient sampling materials are essential for assessing nicotine levels in vape shops and other settings where nicotine exposures may exist. Two different treatments of Whatman glass fiber type A (GF/A) filters (sodium bisulfate treated and citric acid treated) were evaluated for nicotine capture, desorption efficiency, and holding capacity using Gas Chromatography-Mass Spectrometry (GC-MS). The Filters were treated with 0.8mL of 0.1 M sodium bisulfate or citric acid solution and oven-dried (80 °C) for 30min. Nicotine was desorbed off the filters using a modified analytical method. The average nicotine desorption efficiency for sodium bisulfate-treated GF/A filters (98.4%) was significantly higher than that of citric acid-treated GF/A filters (60.9%) over a range of 1-100 µg nicotine. Sodium bisulfate-treated and citric acid-treated GF/A filters experienced a 10% nicotine breakthrough after being dosed with about 550 and 2,750 µg of nicotine, respectively compared to 75 µg for untreated GF/A filters. Citric acid-treated GF/A filters had a much greater nicotine-holding capacity, but nicotine desorption from citric acid-treated GF/A filters was below the recommended criteria. Therefore, we recommend that sodium bisulfate-treated GF/A filters are employed for sample of nicotine with the GC-MS method.

Genotyping Error Detection and Customised Filtration for SNP Datasets.

A major challenge in analysing single-nucleotide polymorphism (SNP) genotype datasets is detecting and filtering errors that bias analyses and misinterpret ecological and evolutionary processes. Here, we present a comprehensive method to estimate and minimise genotyping error rates (deviations from the 'true' genotype) in any SNP datasets using triplicates (three repeats of the same sample) in a four-step filtration pipeline. The approach involves: (1) SNP filtering by missing data; (2) SNP filtering by error rates; (3) sample filtering by missing data and (4) detection of recaptured individuals by using estimated SNP error rates. The modular pipeline is provided in an R script that allows customised adjustments. We demonstrate the applicability of the method using non-invasive sampling from the Asiatic wild ass (Equus hemionus) population in Israel. We genotyped 756 samples using 625 SNPs, of which 255 were triplicates of 85 samples. The average SNP error rate, calculated based on the number of mismatching genotypes across triplicates before filtration, was 0.0034 and was reduced to 0.00174 following filtration. Evaluating genetic distance (GD) and relatedness (r) between triplicates before and after filtration (expected to be at the minimum and maximum respectively) showed a significant reduction in the average GD, from 58.1 to 25.3 (p = 0.0002) and a significant increase in relatedness, from r = 0.98 to r = 0.991 (p = 0.00587). We demonstrate how error rate estimation enhances recapture detection and improves genotype quality.

Partitioning of Neutral PFAS in Homes and Release to the Outdoor Environment: Results from the IPA Campaign.

The distribution and fate of per- and polyfluoroalkyl substances (PFAS) in homes are not well understood. To address this, we measured nine neutral PFAS in dust, airborne particles, dryer lint, and on heating and air conditioning (HAC) filters in 11 homes in North Carolina as part of the Indoor PFAS Assessment (IPA) Campaign and compared them with concurrently collected gas and cloth measurements. Fluorotelomer alcohols (FTOHs) contributed most (≥75%) to total (∑) measured neutral PFAS concentrations in dust, HAC filter, and dryer lint samples, with mean ∑(FTOH) concentrations of 207 ng/g, 549 ng/g, and 84 ng/g, respectively. In particles, perfluorooctane sulfonamidoethanols (FOSEs) dominated, with a mean ∑(FOSE) concentration of 0.28 ng/m3 or 75,467 ng/g. For FTOHs and FOSEs, resulting mean dust-air, HAC filter-air, dryer lint-air and particle-air partition coefficients in units of log(m3/μg) ranged (across species) from -5.1 to -3.6, -4.9 to -3.5, -5.4 to -4.1, and -3.2 to -0.78, respectively. We estimate that cloth, gas phase, and HAC filters are the largest reservoirs for FTOHs, while cloth, HAC filters, and dust are the largest reservoirs for FOSEs. Release rates of neutral PFAS from homes to the outdoor environment are reported.

Characterization of Lithium-Ion Battery Fire Emissions—Part 2: Particle Size Distributions and Emission Factors

The lithium-ion battery (LIB) thermal runaway (TR) emits a wide size range of particles with diverse chemical compositions. When inhaled, these particles can cause serious adverse health effects. This study measured the size distributions of particles with diameters less than 10 µm released throughout the TR-driven combustion of cylindrical lithium iron phosphate (LFP) and pouch-style lithium cobalt oxide (LCO) LIB cells. The chemical composition of fine particles (PM2.5) and some acidic gases were also characterized from filter samples. The emission factors of particle number and mass as well as chemical components were calculated. Particle number concentrations were dominated by those smaller than 500 nm with geometric number mean diameters below 130 nm. Mass concentrations were also dominated by smaller particles, with PM1 particles making up 81–95% of the measured PM10 mass. A significant amount of organic and elemental carbon, phosphate, and fluoride was released as PM2.5 constituents. The emission factor of gaseous hydrogen fluoride was 10–81 mg/Wh, posing the most immediate danger to human health. The tested LFP cells had higher emission factors of particles and HF than the LCO cells.

Exploring microplastic distribution in Western North American snow

Microplastic (MP) transport in the atmosphere, one of the least studied environmental compartments because of the relatively small size of air-borne MPs and the challenges in identifying them, may be inferred from their occurrence in snowfall. In this study, 11 sites across western coastal North America were sampled and analyzed for MP presence in fresh snowfall, months-old summer surface snow, and stratified deposits in snow pits. MPs were detected and characterized using a method integrating linear array µ-Fourier Transform Spectroscopy (µFTIR) and batch spectral analysis with open-source platform Open Specy. Recovery rate analysis from sample filtration to data analysis was conducted, and analysis of field or laboratory blanks suggested negligible contamination (≤ 1 polyamide fragment per blank). Concentrations of MPs in the fresh snowfall of remote sites and those proximal to sources were 5.1–150.8 p/L and 104.5–325 p/L of snowmelt water, respectively. Summer surface snow that was several months old had MP concentrations ranging from 57.5–539 p/L of meltwater, and snow sampled at different depths within a snowpack had concentrations ranging from 35–914 p/L. Our results demonstrate a streamlined method that may be used for measuring MPs in remote or pristine environments, contributing to a better understanding of long-range MP transport.

Evaluation of testing face-mask filter samples with LAMP shows high rates of detection in pulmonary TB.

<sec><title>BACKGROUND</title>Detection of Mycobacterium tuberculosis (MTB) in bioaerosols derived from patients with active pulmonary TB is a potential alternative diagnostic method for patients with presumed TB who cannot expectorate sputum.</sec><sec><title>OBJECTIVE</title>To assess the efficacy of a bioaerosol particle collection method to capture MTB and diagnose TB.</sec><sec><title>METHODS</title>A mask-like filter holder (3D mask) with a water-soluble gelatine filter (GF) and one containing a water-insoluble polypropylene filter (PPF) were prepared. Eligible patients wore the 3D mask with GF or PPF within 3 days of starting anti-TB drugs. The GF and PPF filters were collected after 2 and 8 h. DNA was extracted from the filter samples and tested using loop-mediated isothermal amplification (LAMP).</sec><sec><title>RESULTS</title>Filter samples were collected from 57 and 20 patients with and without active pulmonary TB, respectively. The GF and PPF sensitivity was 76.2% and 83.3%, respectively. The specificity of both methods was 100%. Of the 57 patients diagnosed with non-expectorated sputum samples, including suction phlegm, gastric lavage, and bronchial lavage fluid, 55.6% and 50.0% were positive by GF and PPF, respectively.</sec><sec><title>CONCLUSION</title>We present a 3D mask filter sampling method for exhaled bioaerosol particles that can be used in clinical practice to diagnose patients with presumed TB.</sec>.

Generative model-assisted sample selection for interest-driven visual analytics

We propose interest-driven visual analytics. The core idea is to filter samples with features of interest to analysts from the given dataset for analysis. The approach relies on a generative model (GM) trained using the given dataset as the training set. The GM characteristics make it convenient to find ideal generated samples from its latent space. Then, we filter the original samples similar to the ideal generated ones to explore patterns. Our research involves two methods for achieving and applying the idea. First, we give a method to explore ideal samples from a GM’s latent space. Second, we integrate the method into a system to form an embedding-based analytical workflow. Patterns found on open datasets in case studies, results of quantitative experiments, and positive feedback from experts illustrate the general usability and effectiveness of the approach.

Reconsidering freeze-induced protein aggregation: Air bubbles as the root cause of ice-water interface stress

Freeze-induced stress causing aggregation of proteins has typically been primarily attributed to the ice-water interface. However, we hypothesize that the underlying observed and perceived detrimental effect of ice is, to some extent, attributed to air bubbles expelled from ice crystal lattices or to nanobubbles existing prior to freezing. The reduction of dissolved air was achieved via a deaeration process by placing samples in a reduced pressure chamber, while the reduction of nanobubbles was achieved by filtering samples via a syringe filter. The results showed that the reduction of both dissolved air molecules and stable colloidal nanobubbles in a bovine IgG solution prior to freezing led to a significant decrease in aggregation after thawing compared to untreated samples (∼6,000 vs. ∼ 40,000 particles/mL at a freezing rate of 100 K/s, respectively). The deaeration-filtration treatment works additively with cryoprotectants such as trehalose, further reducing the freeze-induced aggregation of IgG. The results also demonstrated that air–water interfacial aggregation of IgG in bulk liquid samples is a time-dependent process. The number of IgG subvisible particles increased with time and temperature, suggesting that random collisions of denatured molecules promoted the formation of aggregates with spherical morphology. In contrast, the IgG subvisible count after freeze-thawing had already reached its nominal value, suggesting a time-independent process where denatured protein molecules were compressed between ice crystals into filament-like aggregates. In summary, the findings shift the current paradigm from ice crystals being the main destabilizing factor during freezing to air bubbles, although the two are intertwined. From a translational aspect, this study underscores the value of deaeration-filtration as an essential supplemental process that can be applied in addition to formulation approaches such as the use of cryoprotectants to further reduce freezing stress on proteins and increase their stability.

Microplastics in surface seawater of Kongsfjorden, Svalbard, Arctic

Microplastics have now become an emerging contaminant with high concern in the Arctic and Sub-Arctic Region. Here, the Kongsfjorden system in the Arctic has been investigated for abundance, distribution, and characteristic of microplastics in surface seawater. Eighteen samples were collected using an in-situ filtration sampling method, and then analyzed by Fourier-transform infrared spectroscopy. The average abundance of microplastics in surface seawater was 3.6 items m−3, with an abundance range of 0.0—10.0 items m−3. The highest abundance of microplastics was located adjacent to the eddy in Kongsfjorden, where a microplastic accumulation zone might have formed. Microplastics transported by ocean currents and those from local discharges might converge in this zone. Two sampling stations were set up at the wastewater treatment plant outfall, which showed an abundance range of 4.0—6.0 items m−3, slightly higher than the average abundance. Of the six polymer types identified, rayon, polyester and polyamide were the most common composition. Proportions in fiber form in surface water was 84.6 %, and blue (28.2 %) and transparent (25.6 %) were predominant colors. Most microplastics (>90.0 %) were less than 1 mm in the longest dimension. This study provided important baseline data as well as a practical microplastic sampling method for polar marine environments.

A High-Resolution Discrete-Time Second-Order ΣΔ ADC with Improved Tolerance to KT/C Noise Using Low Oversampling Ratio.

This work presents a novel ΣΔ analog-to-digital converter (ADC) architecture for a high-resolution sensor interface. The concept is to reduce the effect of kT/C noise generated by the loop filter by placing the gain stage in front of the loop filter. The proposed architecture effectively reduces the kT/C noise power from the loop filter by as much as the squared gain of the added gain stage. The gain stage greatly relaxes the loop filter's sampling capacitor requirements. The target resolution is 20 bit. The sampling frequency is 512 kHz, and the oversampling ratio (OSR) is only 256 for a target resolution. Therefore, the proposed ΔΣ ADC structure allows for high-resolution ADC design in an environment with a limited OSR. The proposed ADC designed in 65 nm CMOS technology operates at supply voltages of 1.2 V and achieves a peak signal-to-noise ratio (SNR) and Schreier Figure of Merit (FoMs) of 117.7 dB and 180.4 dB, respectively.

Calculations of the conversion factor from organic carbon to organic matter for aerosol mass balance

Aerosol mass balance studies based on filter samples require a conversion factor to derive organic matter (OM) concentrations from organic carbon (OC) measurements from thermo-optical methods. This factor provides indirect insights on the molecular structure of OM needed in chemical transport models. Site- and season-specific ratios of OC to OM (fOM:OC) were calculated using data from five rural background sites in France between 2012 and 2021 by relating the unidentified chemical fraction in PM2.5 samples to thermo-optical OC concentrations. Further, multiple linear formulations were used to evaluate the impact of possible artefacts on the determination of fOM:OC. The resulting fOM:OC was then compared to other estimates derived from online aerosol mass spectrometry data, showing good agreement. The spatial and temporal variability in fOM:OC is discussed considering factors such as seasonality, meteorological conditions and the atmospheric oxidative potential. Linear-mixed effect models were formulated to quantitatively determine the drivers which influence the fOM:OC at the French rural background sites. Both ozone and relative humidity were variables with statistically significant effects on fOM:OC, indicating that differences in the contributions from both photooxidation and water content, explain the variability in fOM:OC observed at the French rural background sites. Site-specific fOM:OC yielded more accurate PM2.5 mass closure and are therefore recommended in mass-balance exercises. Accurate fOM:OC are critical to maintain consistency in OM time series, especially in cases where filter-based time series may be replaced by state-of-the-art online instrumentation.

Verification and application of qPCR and viability-qPCR for Legionella monitoring in evaporative cooling systems complementing the conventional culture method

To date, in many countries the only legally valid method for evaporative cooling system (ECS) monitoring is the culture method. However, a duration of up to 14 days and a risk of underestimation of Legionella concentrations are seen as limitations of cultivation methods. Rapid cultivation-independent methods are an important step towards a more practicable monitoring of ECS to quickly control interventions if elevated concentrations of Legionella are found.Two commercial kits for quantitative polymerase chain reaction (qPCR) and viability-qPCR (v-qPCR) were studied, comprising sample filtration and DNA extraction. Cryopreserved Legionella pneumophila were established as calibration standard with intact (ILC) and total Legionella count (TLC) determined by flow cytometry before conducting spiking experiments in commercial mineral water and artificial process water. Final assessment was carried out using real ECS samples.Recovery and robustness ranged from 86 to 108 % for qPCR with a drop to 40–60 % for v-qPCR when compared to direct extraction, possibly attributable to cell damage during sample concentration. All methods including culture did perform well regarding linearity with R2 ≥ 0.95 for most trials. Detected concentrations in comparison to spiked Legionella counts differed with culture averaging 25 ± 7 % of spiked ILC and v-qPCR being closest to spiked concentrations with 65–144 %. In comparison, qPCR was several fold above spiked TLC concentrations. For real ECS samples Legionella spp. were detected in concentrations above 103 GU/100 mL by v-qPCR in 70–92 % of samples, depending on the kit used. Most of these samples were either culture-negative or not evaluable on agar plates.This study showed that a cryopreserved bacterial standard based examination is applicable and can be used for future v-qPCR verification. For assessment of differences in results between culture and v-qPCR/qPCR in ECS samples expert knowledge about the operating mode and used analytical methods is required. Guidelines addressing this issue could be a solution.

Clutaxis: an information-driven source search method balancing exploration and exploitation in turbulent environments

Locating unknown emission sources in turbulent environments is a challenging yet crucial task, particularly in emergency response scenarios. Existing studies have developed information-theoretic approaches to fuse intermittent information collected by mobile sensors regarding the sources. This fused information is then used to support source-term estimation (STE) in various search algorithms. Among these, the cognitive strategy—a promising information-driven search algorithm—leverages a reward-based action selection mechanism to balance exploration and exploitation during each search step. However, this mechanism is hampered by a high computational load and rigid search trajectories, limiting its application in real-world systems. To address these issues, this paper proposes a novel information-driven search method called Clutaxis, based on a global exploration and exploitation tradeoff principle. Specifically, a particle filter is leveraged to maintain the STE. After projecting the particle filter samples onto a 2D search scene, the density-based spatial clustering of applications with noise (DBSCAN) algorithm is used to extract the density information of the samples, which is then used to construct a belief source area (BSA). By leveraging the uncertainty of the BSA, Clutaxis adopts explorative or exploitative actions with no restrictions on motion direction. Through dedicated simulations, the experimental results demonstrate the robustness of Clutaxis to key parameters and its advantages in computational complexity and search performance compared to two state-of-the-art algorithms (Infotaxis and Entrotaxis) and two Clutaxis variants (Clutaxis_ER and Clutaxis_EI).

Design of a tunable center frequency and small size cavity bandpass filter by separating capacitor-loaded resonators

This paper presents a tunable center frequency and small size cavity bandpass filter design method. In this method, a capacitor-loaded open terminal coaxial resonator is employed to reduce the size of cavity filters. The resonator is designed and fabricated separately into two parts to achieve the flexible operating frequency purpose. The first part is called the base of the resonator which is simply a pillar and directly fabricated integrally with the cavity housing. The second part called the hat of the resonator is the main part causing the load capacitance in cavity filters. By using different heights of the base part or/and different shapes and sizes of the hat, the operating frequency of cavity filters can be changed flexibly. This method not only reduces the difficulty and cost of cavity filter processing but also makes cavity filters reconfigurable. To demonstrate the effectiveness of the method, a cavity filter sample with a center frequency of 3.45 GHz and a bandwidth of 80 MHz was designed, fabricated, and measured. The measured results show that the insertion loss was smaller than 1.33 dB in the whole bandwidth, one zero-point at 3.350 GHz reaching -68 dB, the rejection at 3.550 GHz was -41 dB, unloaded Q was 5,898, and the dimension of the filter was 128 mm×86 mm×23 mm.

Corporate Governance Reforms and the Quality of Financial Information of Listed Non-Financial Services Firms in Nigeria

The increasing demand for high quality financial information by the relevant users of financial report has become a serious concern and inevitable on the management of listed non-financial services firms in Nigeria. The primary objective of this study is to examine the nexus between corporate governance reforms and the quality financial information of listed non-financial services firms in Nigeria. Using an ex-post facto as the research design for the study, data was obtained from the secondary sources through the extraction method from the annual financial reports and accounts of the listed firms for 276 firm-year observations, from 2018 to 2023 period. Out of the seventy-five (75) listed non-financial services firms in Nigerian Exchange Group as at 31st December, 2018, a sample size of fourty-six (46) listed firms were used with aid of purposive filter sampling technique. The Feasible Generalized Least Square (FGLS) regression was used as the model estimation technique for the study. Based on the regression analysis, it was found that board size, assurance services and transparency have positive significant impact on financial information quality of listed non-financial services firms in Nigeria. However, sustainability was statistically found to have insignificant impact on quality of financial information of listed non-financial services firms in Nigeria. Therefore, it is recommended that the board of directors of listed non-financial services firms in Nigeria ensure that more members are nominated to participate in the board’s decision. This is because of the fact that larger board sizes are more likely to create avenue for cross-fertilization of ideas thereby, making decisions that can safeguard, uphold and enhance the quality of the financial information of the listed non-financial services firms in Nigeria. The results also underscore the relevance of corporate governance codes and their impacts on FIQ and transparent disclosure. This study offers policy implications to regulatory agencies and standard-setters in their oversight function over the quality of financial information disclosed in annual reports.

Cross-Hopping Graph Networks for Hyperspectral–High Spatial Resolution (H2) Image Classification

As we take stock of the contemporary issue, remote sensing images are gradually advancing towards hyperspectral–high spatial resolution (H2) double-high images. However, high resolution produces serious spatial heterogeneity and spectral variability while improving image resolution, which increases the difficulty of feature recognition. So as to make the best of spectral and spatial features under an insufficient number of marking samples, we would like to achieve effective recognition and accurate classification of features in H2 images. In this paper, a cross-hop graph network for H2 image classification(H2-CHGN) is proposed. It is a two-branch network for deep feature extraction geared towards H2 images, consisting of a cross-hop graph attention network (CGAT) and a multiscale convolutional neural network (MCNN): the CGAT branch utilizes the superpixel information of H2 images to filter samples with high spatial relevance and designate them as the samples to be classified, then utilizes the cross-hop graph and attention mechanism to broaden the range of graph convolution to obtain more representative global features. As another branch, the MCNN uses dual convolutional kernels to extract features and fuse them at various scales while attaining pixel-level multi-scale local features by parallel cross connecting. Finally, the dual-channel attention mechanism is utilized for fusion to make image elements more prominent. This experiment on the classical dataset (Pavia University) and double-high (H2) datasets (WHU-Hi-LongKou and WHU-Hi-HongHu) shows that the H2-CHGN can be efficiently and competently used in H2 image classification. In detail, experimental results showcase superior performance, outpacing state-of-the-art methods by 0.75–2.16% in overall accuracy.

Pollution Characteristics of Heavy Metals in PM1 and Source-Specific Health Risks in the Tianjin Airport Community, China.

The airport and its surrounding areas are home to a variety of pollution sources, and air pollution is a recognized health concern for local populated regions. Submicron particulate matter (PM1 with an aerodynamic diameter of <1 mm) is a typical pollutant at airports, and the enrichment of heavy metals (HMs) in PM1 poses a great threat to human health. To comprehensively assess the source-specific health effects of PM1-bound HMs in an airport community, PM1 filter samples were collected around the Tianjin Binhai International Airport for 12 h during the daytime and nighttime, both in the spring and summer, and 10 selected HMs (V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd, and Pb) were analyzed. The indicatory elements of aircraft emissions were certified as Zn and Pb, which accounted for more than 60% of the sum concentration of detected HMs. The health risks assessment showed that the total non-cancer risks (TNCRs) of PM1-bound HMs were 0.28 in the spring and 0.23 in the summer, which are lower than the safety level determined by the USEPA, and the total cancer risk (TCR) was 2.37 × 10-5 in the spring and 2.42 × 10-5 in the summer, implying that there were non-negligible cancer risks in the Tianjin Airport Community. After source apportionment with EF values and PMF model, four factors have been determined in both seasons. Consequently, the source-specific health risks were also evaluated by combining the PMF model with the health risk assessment model. For non-cancer risk, industrial sources containing high concentrations of Mn were the top contributors in both spring (50.4%) and summer (44.2%), while coal combustion with high loads of As and Cd posed the highest cancer risk in both seasons. From the perspective of health risk management, targeted management and control strategies should be adopted for industrial emissions and coal combustion in the Tianjin Airport Community.

A high-throughput, turbulent-mixing, condensation aerosol concentrator for direct aerosol collection as a liquid suspension

Trace measurement of aerosol chemical composition in workplace atmospheres requires the development of high-throughput aerosol collectors that are compact, hand-portable, and can be operated using personal pumps. We describe the design and characterization of a compact, high flow, Turbulent-mixing Condensation Aerosol-in-Liquid Concentrator (TCALC) that allows direct collection of aerosols as liquid suspensions, for off-line chemical, biological, or microscopy analysis. The TCALC unit, measuring approximately 12 × 16 × 18 cm, operates at an aerosol sample flowrate of up to 10 L min−1, using rapid mixing of a hot flow saturated with water vapor and a cold aerosol sample flow, thereby promoting condensational growth of aerosol particles. We investigated the effect of operating parameters such as vapor temperature, growth tube wall temperature, and aerosol sample flowrate, along with the effect of particle diameter, inlet humidity, aerosol concentration, and operation time on TCALC performance. Nanoparticles with an initial aerodynamic diameter ≥25 nm could grow to droplet diameters >1400 nm with an efficiency ≥80%. Good droplet growth efficiency was achieved for sampled aerosol relative humidity ≥9%. We measured complete aerosol collection for concentrations of ≤3 × 105 cm−3. The results showed good agreement between the particulate mass collected through the liquid collector and direct filter collection. The TCALC eliminates the need for sample preparation and filter digestion during chemical analysis, thereby increasing sample recovery and substantially improving the limit of detection and sensitivity of off-line trace analysis of collected liquid samples.