Design and Characterization of Electrospun Polyamide Nanofiber Media for Air Filtration Applications

Electrospun polyamide 6 (PA 6) and polyamide 6/6 (PA 6/6) nanofibers were produced in order to investigate their experimental characteristics with the goal of obtaining filtration relevant fiber media. The experimental design model of each PA nanofibers contained the following variables: polymer concentration, ratio of solvents, nanofiber media collection time, tip-to-collector distance, and the deposition voltage. The average diameter of the fibers, their morphology, basis weight, thickness, and resulting media solidity were investigated. Effects of each variable on the essential characteristics of PA 6/6 and PA 6 nanofiber media were studied. The comparative analysis of the obtained PA 6/6 and PA 6 nanofiber characteristics revealed that PA 6/6 had higher potential to be used in filtration applications. Based on the experimental results, the graphical representation—response surfaces—for obtaining nanofiber media with the desirable fiber diameter and basis weight characteristics were derived. Based on the modelling results the nanofiber filter media (mats) were fabricated. Filtration results revealed that nanofiber filter media electrospun from PA6/6 8% (w/vol) solutions with the smallest fiber diameters (62–66 nm) had the highest filtration efficiency (PA6/6_30 = 84.9–90.9%) and the highest quality factor (PA6/6_10 = 0.0486–0.0749 Pa−1)

The air quality impacts of road closures associated with the 2004 Democratic National Convention in Boston

BACKGROUND: The Democratic National Convention (DNC) in Boston, Massachusetts in 2004 provided an opportunity to evaluate the impacts of a localized and short-term but potentially significant change in traffic patterns on air quality, and to determine the optimal monitoring approach to address events of this nature. It was anticipated that the road closures associated with the DNC would both influence the overall air pollution level and the distribution of concentrations across the city, through shifts in traffic patterns. METHODS: To capture these effects, we placed passive nitrogen dioxide badges at 40 sites around metropolitan Boston before, during, and after the DNC, with the goal of capturing the array of hypothesized impacts. In addition, we continuously measured elemental carbon at three sites, and gathered continuous air pollution data from US EPA fixed-site monitors and traffic count data from the Massachusetts Highway Department. RESULTS: There were significant reductions in traffic volume on the highway with closures north of Boston, with relatively little change along other highways, indicating a more isolated traffic reduction rather than an across-the-board decrease. For our nitrogen dioxide samples, while there was a relatively small change in mean concentrations, there was significant heterogeneity across sites, which corresponded with our a priori classifications of road segments. The median ratio of nitrogen dioxide concentrations during the DNC relative to non-DNC sampling periods was 0.58 at sites with hypothesized traffic reductions, versus 0.88 for sites with no changes hypothesized and 1.15 for sites with hypothesized traffic increases. Continuous monitors measured slightly lower concentrations of elemental carbon and nitrogen dioxide during road closure periods at monitors proximate to closed highway segments, but not for PM(2.5 )or further from major highways. CONCLUSION: We conclude that there was a small but measurable influence of DNC-related road closures on air quality patterns in the Boston area, and that a low-cost monitoring study combining passive badges for spatial heterogeneity and continuous monitors for temporal heterogeneity can provide useful insight for community air quality assessments

Land use regression modeling of intra-urban residential variability in multiple traffic-related air pollutants

Background: There is a growing body of literature linking GIS-based measures of traffic density to asthma and other respiratory outcomes. However, no consensus exists on which traffic indicators best capture variability in different pollutants or within different settings. As part of a study on childhood asthma etiology, we examined variability in outdoor concentrations of multiple traffic-related air pollutants within urban communities, using a range of GIS-based predictors and land use regression techniques. Methods: We measured fine particulate matter (PM2.5), nitrogen dioxide (NO2), and elemental carbon (EC) outside 44 homes representing a range of traffic densities and neighborhoods across Boston, Massachusetts and nearby communities. Multiple three to four-day average samples were collected at each home during winters and summers from 2003 to 2005. Traffic indicators were derived using Massachusetts Highway Department data and direct traffic counts. Multivariate regression analyses were performed separately for each pollutant, using traffic indicators, land use, meteorology, site characteristics, and central site concentrations. Results: PM2.5 was strongly associated with the central site monitor (R2 = 0.68). Additional variability was explained by total roadway length within 100 m of the home, smoking or grilling near the monitor, and block-group population density (R2 = 0.76). EC showed greater spatial variability, especially during winter months, and was predicted by roadway length within 200 m of the home. The influence of traffic was greater under low wind speed conditions, and concentrations were lower during summer (R2 = 0.52). NO2 showed significant spatial variability, predicted by population density and roadway length within 50 m of the home, modified by site characteristics (obstruction), and with higher concentrations during summer (R2 = 0.56). Conclusion: Each pollutant examined displayed somewhat different spatial patterns within urban neighborhoods, and were differently related to local traffic and meteorology. Our results indicate a need for multi-pollutant exposure modeling to disentangle causal agents in epidemiological studies, and further investigation of site-specific and meteorological modification of the traffic-concentration relationship in urban neighborhoods

Exploring Variation and Predictors of Residential Fine Particulate Matter Infiltration

Although individuals spend the majority of their time indoors, most epidemiological studies estimate personal air pollution exposures based on outdoor levels. This almost certainly results in exposure misclassification as pollutant infiltration varies between homes. However, it is often not possible to collect detailed measures of infiltration for individual homes in large-scale epidemiological studies and thus there is currently a need to develop models that can be used to predict these values. To address this need, we examined infiltration of fine particulate matter (PM2.5) and identified determinants of infiltration for 46 residential homes in Toronto, Canada. Infiltration was estimated using the indoor/outdoor sulphur ratio and information on hypothesized predictors of infiltration were collected using questionnaires and publicly available databases. Multiple linear regression was used to develop the models. Mean infiltration was 0.52 ± 0.21 with no significant difference across heating and non-heating seasons. Predictors of infiltration were air exchange, presence of central air conditioning, and forced air heating. These variables accounted for 38% of the variability in infiltration. Without air exchange, the model accounted for 26% of the variability. Effective modelling of infiltration in individual homes remains difficult, although key variables such as use of central air conditioning show potential as an easily attainable indicator of infiltration

Fibrous polycaprolactone-based 3D scaffolds for in vitro cell models /

INTRODUCTION. Cancer is one of the major health challenges of our time, affecting millions of people around the world. It is a complex and multi-faceted disease that can affect people of all ages, genders, and ethnicities. Currently, cancer is treated with surgical resection, radiation therapy, and chemotherapy. Unfortunately, these treatments are often not successful and can cause serious side effects. In vitro scaffold adaptation is a new approach to treating cancer that could be more effective in treating the disease. This approach uses a scaffold made of inert materials such as polymers, hydrogels, etc., to provide a 3D structure that can be used to study the behavior of cancer cells. The scaffold provides a supportive environment for cancer cells, allowing them to grow and spread in a controlled manner. In addition, the scaffold can be adapted to provide a more targeted form of therapy, such as targeted drug delivery [1, 2]. METHODS. 3D fibrous polymer-based scaffolds were produced by 3D fibre printer (3Df-01C, Bious Labs, Lithuania, https://life.biouslabs.com/), which is a combination of melt electrospinning and fused deposition modelling [3]. To prevent cell migration away from the scaffold, a nanofibrous layer was added to the bottom of the scaffold via solution electrospinning. The hydrophilicity of the scaffolds was improved through lowtemperature plasma treatment. The cytotoxicity of the 3D fibrous scaffolds was evaluated according to ISO 10993-5:2009 using mouse fibroblast cells L929. Additionally, the scaffolds were cultivated with human breast cell line MDA-MB-231 and glioblastoma cell line U87-MG. RESULTS. Three different PCL scaffolds were produced with varying fiber and pore sizes, fiber width ranging between 8 and 25 μm, and pores between 35 and 155 μm (see Fig.1). After lowtemperature plasma treatment, the scaffolds were more hydrophilic, with the WCA 60 ± 5°. Results of the MTT test demonstrated that the viability of the human breast cell lines MDA-MB-231 and U87-MG was equal to or higher than that of the 2D cultures during the seven-day period. Moreover, the scaffold supported the cellular growth and viability effectively. Additionally, the MDA-MB-231 cells had a more elongated shape, which was closer to their natural form. [...]

Optimisation of factors affecting the electrospinning for prediction of the morphology of biobased poly(butylene succinate) nanofibrous mats /

Introduction. Plastics have played an important role in the operation of the modern economy, combining remarkable practical properties with affordability. Plastics consumption has dramatically increased by a factor of twenty over the last fifty years and is expected to continue growing in the next 20 years. Therefore, significant attention has been directed towards biobased plastics derived from renewable resources such as plants and biomass. The adoption of biobased polymers in various applications is critical for promoting sustainability and reducing reliance on non-renewable resources. In this research, we investigated the optimisation of parameters for the fabrication of nanofibrous scaffolds made of biobased poly(butylene succinate) [1]. Methods. Biobased poly(butylene succinate) (PBS) pellets (NaturePlast, France) in the two solvent systems (CHCl3/HCOOH) and (CHCl3/CH3OH) were used to fabricate nanofibrous mats by the solution electrospinning technique [2-3]. The experiment plan was designed based on D-optimal interaction model with MODDE® 10 software. The main factors that were investigated during electrospinning were polymer concentration, type of solvent, solvent ratio, and electric field intensity. The fibre morphology was characterised using scanning electron microscopy (SEM) and analysed with ImageJ software. The data collected from the experiment was fitted to partial least square regression model to obtain the response surface plots for the prediction of fibre morphology. Results. A wide range of fibre and pore morphology of electrospun mats was obtained with an average fibre size ranging from 0.17 ± 0.05 μm to 4.54 ± 1.37 μm and a pore size between 1.12 ± 0.50 μm to 13.52 ± 6.57 μm. The polymer concentration and the solvent system appear to be the most significant two factors directly affecting the morphology of electrospun fibrous mats. The fitted model response surface plots (Fig.1) represent the prediction of the fibrous scaffold morphology depending on PBS concentration and the solvent system (ratio, parts) used in the experiment. [...]

Intensive short term measurements of the ambient aerosol in the Greater Cincinnati airshed

As part of a larger study undertaken in the Greater Cincinnati area to determine if diesel truck emissions are adjuvant to naturally occurring bioaerosols in the initiation of allergies in children, a more detailed intensive measurement campaign was undertaken to elucidate the characteristics of the ambient aerosol and compare to the regular, integrated measurements being conducted. The mass concentration, total number concentration, size distributions, and morphologies were established at several locations including a residential area far from major traffic (Mernic), a suburban area on both sides of a major highway (I-275, Blue Ash), a site in the city center very close to the highway (I-75, Findlay), and an enclosed oval track at a Truck Driving School. Differences between real-time tapered element oscillating microbalance (TEOM) average mass concentrations and integrated Harvard impactor (HI) measurements were observed, with the magnitude of the difference being dependent on location and the organic compounds (OC) concentrations in the sample. Qualitative variation of the peaks in real-time PM 2.5 concentrations were observed with variation in truck traffic at the Findlay site; and no peaks in real-time PM 2.5 levels were observed at Mernic. Minimal variation in PM 2.5 was observed with distance from the highway at the Blue Ash site (fewer trucks). The site at Mernic had a smaller fraction of aggregated particles in comparison to the other sites. The two-dimensional fractal dimensions measured at the Findlay, Blue Ash, and Truck Driving School sites were statistically identical (1.58–1.61) but were higher than that measured at the Mernic site (1.41). Implications of the intensive measurement campaign vis-à-vis the epidemiological study are discussed briefly

Application of capillary flow porometry to predict the filtration efficiency of nanofibrous polymer membranes /

Introduction. Of all pollutants present in the ambient air, particulate matter (PM) is the most dangerous and has the greatest negative impact on human health. Filtration is one of the most technically and economically feasible methods for the removal of particles from air. In recent years, nanofibrous polymer membranes gain popularity due to their high filtration efficiency, which depends on fibre and pore sizes, as well as their size distribution. Capillary flow porometry (CFP) is a widely used method to measure the pore size and pore size distribution of nonwoven fibrous membranes. Here we demonstrate a systematic research of the effects of pore size distributions in nanofibrous membranes to the filtering performance. Methods. Polybutylene succinate (PBS) fibrous mats were electrospun from the chloroform and formic acid (6:4) solution using electrospinning setup (SE-01C, Bious Labs, Lithuania). Different layers of PBS nanofibres were deposited on polypropylene spunbonded nonwoven fabric, by varying deposition duration, which corresponded to a specific weight, and in turn, pore sizes. Pore size distribution was researched using capillary flow porometer (CFP-0410, Bious Labs) and fluorinated hydrocarbon (Porofil, Anton Paar QuantaTec Inc., USA) as a wetting liquid. Scanning electron microscopy (SEM) analysis and ImageJ software were used to obtain optical morphological parameters of the same membranes. Aerosol particle filtration efficiency of fabricated membranes was research using an in-house filtration testing setup [1], where the values of filtration efficiency and pressure drop were obtained. Results and conclusions. Filtering mats were obtained with the basis weight between and 0.88 ± 0.35 g/m2 and 18.05 ± 0.58 g/m2, which corresponded to mean pore sizes between 6.0 ± 0.9 μm and 0.5 ± 0.1 μm, as indicated by the CFP method (Figure 1 A). The filtration efficiency against NaCl particles varied from 31.5 to 99.5 %, while the pressure drop was in the range between 1 to 455 Pa. As expected, the efficiency and pressure drop were adversely affected by the pore size, although relationship was of different nature (Figure 1 B). Pore sizes within the interval between 0.5 and 1 um appear to be critical in terms of pressure drop, while maintaining relatively high filtration efficiency. This allows optimization of filter material in terms of the energy use for the applications of industrial filtration. [...]