Portable air cleaners should be at the forefront of the public health response to landscape fire smoke
- Environmental health : a global access science source
- Published over 2 years ago
Landscape fires can produce large quantities of smoke that degrade air quality in both remote and urban communities. Smoke from these fires is a complex mixture of fine particulate matter and gases, exposure to which is associated with increased respiratory and cardiovascular morbidity and mortality. The public health response to short-lived smoke events typically advises people to remain indoors with windows and doors closed, but does not emphasize the use of portable air cleaners (PAC) to create private or public clean air shelters. High efficiency particulate air filters and electrostatic precipitators can lower indoor concentrations of fine particulate matter and improve respiratory and cardiovascular outcomes. We argue that PACs should be at the forefront of the public health response to landscape fire smoke events.
Marine debris is a global environmental issue. Smoked cigarette filters are the predominant coastal litter item; 4.5 trillion are littered annually, presenting a source of bioplastic microfibres (cellulose acetate) and harmful toxicants to marine environments. Despite the human health risks associated with smoking, little is known of the hazards cigarette filters present to marine life. Here we studied the impacts of smoked cigarette filter toxicants and microfibres on the polychaete worm Hediste diversicolor (ragworm), a widespread inhabitant of coastal sediments. Ragworms exposed to smoked cigarette filter toxicants in seawater at concentrations 60 fold lower than those reported for urban run-off exhibited significantly longer burrowing times, >30% weight loss, and >2-fold increase in DNA damage compared to ragworms maintained in control conditions. In contrast, ragworms exposed to smoked cigarette filter microfibres in marine sediment showed no significant effects. Bioconcentration factors for nicotine were 500 fold higher from seawater than from sediment. Our results illustrate the vulnerability of organisms in the water column to smoking debris and associated toxicants, and highlight the risks posed by smoked cigarette filter debris to aquatic life.
Airborne biological particles containing viruses, bacteria, and/or fungi can be toxic and cause infections and allergy symptoms. Recently, natural materials such as tea tree oil and Sophora flavescens have shown promising antimicrobial activity when applied as air filter media. Although many of these studies demonstrated excellent antimicrobial efficacy, only a few of them considered external environmental effects such as the surrounding humidity, temperature, and natural degradation of chemicals, all of which can affect the antimicrobial performance of these natural materials. In this study, we investigated the antimicrobial durability of air filters containing airborne nanoparticles from S. flavescens for 5months. Antimicrobial tests and quantitative chemical analyses were performed every 30days. Morphological changes in the nanoparticles were also evaluated by scanning electron microscopy. The major antimicrobial compounds remained stable and active for ~90days at room temperature. After about 90days, the quantities of major antimicrobial compounds decreased noticeably with a consequent decrease in antimicrobial activity. These results are promising for the implementation of new technologies using natural antimicrobial products and provide useful information regarding the average life expectancy of antimicrobial filters using nanoparticles of S. flavescens.
Detecting event related potentials (ERPs) from single trials is critical to the operation of many stimulus-driven brain computer interface (BCI) systems. The low strength of the ERP signal compared to the noise (due to artifacts and BCI irrelevant brain processes) makes this a challenging signal detection problem. Previous work has tended to focus on how best to detect a single ERP type (such as the visual oddball response). However, the underlying ERP detection problem is essentially the same regardless of stimulus modality (e.g. visual or tactile), ERP component (e.g. P300 oddball response, or the error-potential), measurement system or electrode layout. To investigate whether a single ERP detection method might work for a wider range of ERP BCIs we compare detection performance over a large corpus of more than 50 ERP BCI datasets whilst systematically varying the electrode montage, spectral filter, spatial filter and classifier training methods. We identify an interesting interaction between spatial whitening and regularised classification which made detection performance independent of the choice of spectral filter low-pass frequency. Our results show that pipeline consisting of spectral filtering, spatial whitening, and regularised classification gives near maximal performance in all cases. Importantly, this pipeline is simple to implement and completely automatic with no expert feature selection or parameter tuning required. Thus, we recommend this combination as a “best-practice” method for ERP detection problems.
Objective. Sensorimotor rhythms (SMRs) are 8-30 Hz oscillations in the electroencephalogram (EEG) recorded from the scalp over sensorimotor cortex that change with movement and/or movement imagery. Many brain-computer interface (BCI) studies have shown that people can learn to control SMR amplitudes and can use that control to move cursors and other objects in one, two or three dimensions. At the same time, if SMR-based BCIs are to be useful for people with neuromuscular disabilities, their accuracy and reliability must be improved substantially. These BCIs often use spatial filtering methods such as common average reference (CAR), Laplacian (LAP) filter or common spatial pattern (CSP) filter to enhance the signal-to-noise ratio of EEG. Here, we test the hypothesis that a new filter design, called an ‘adaptive Laplacian (ALAP) filter’, can provide better performance for SMR-based BCIs. Approach. An ALAP filter employs a Gaussian kernel to construct a smooth spatial gradient of channel weights and then simultaneously seeks the optimal kernel radius of this spatial filter and the regularization parameter of linear ridge regression. This optimization is based on minimizing the leave-one-out cross-validation error through a gradient descent method and is computationally feasible. Main results. Using a variety of kinds of BCI data from a total of 22 individuals, we compare the performances of ALAP filter to CAR, small LAP, large LAP and CSP filters. With a large number of channels and limited data, ALAP performs significantly better than CSP, CAR, small LAP and large LAP both in classification accuracy and in mean-squared error. Using fewer channels restricted to motor areas, ALAP is still superior to CAR, small LAP and large LAP, but equally matched to CSP. Significance. Thus, ALAP may help to improve the accuracy and robustness of SMR-based BCIs.
ABSTRACT Respiratory protection provided by a particulate respirator is a function of particle penetration through filter media and through faceseal leakage. Faceseal leakage largely contributes to the penetration of particles through respirator and compromises protection. When faceseal leaks arise, filter penetration is assumed to be negligible. The contribution of filter penetration and faceseal leakage to total inward leakage (TIL) of submicron size bioaerosols is not well studied. To address this issue, TIL values for two N95 filtering facepiece respirator (FFR) models and two surgical mask (SM) models sealed to a manikin were measured at 8 L and 40 L breathing minute volumes with different artificial leak sizes. TIL values for different size (20-800 nm, electrical mobility diameter) NaCl particles representing submicron size bioaerosols were measured using a scanning mobility particle sizer. Efficiency of filtering devices was assessed by measuring the penetration against NaCl aerosol similar to the method used for NIOSH particulate filter certification. Results showed that the most penetrating particle size (MPPS) was ∼45 nm for both N95 FFR models and one of the two SM models, and ∼350 nm for the other SM model at sealed condition with no leaks as well as with different leak sizes. TIL values increased with increasing leak sizes and breathing minute volumes. Relatively, higher efficiency N95 and SM models showed lower TIL values. Filter efficiency of FFRs and SMs influenced the TIL at different flow rates and leak sizes. Overall, the data indicate that good fitting higher efficiency FFRs may offer higher protection against submicron size bioaerosols.
Terrestrial laser scanning is of increasing importance for surveying and hazard assessments. Digital terrain models are generated using the resultant data to analyze surface processes. In order to determine the terrain surface as precisely as possible, it is often necessary to filter out points that do not represent the terrain surface. Examples are vegetation, vehicles, and animals. Filtering in mountainous terrain is more difficult than in other topography types. Here, existing automatic filtering solutions are not acceptable, because they are usually designed for airborne scan data. The present article describes a method specifically suitable for filtering terrestrial laser scanning data. This method is based on the direct line of sight between the scanner and the measured point and the assumption that no other surface point can be located in the area above this connection line. This assumption is only true for terrestrial laser data, but not for airborne data. We present a comparison of the wedge filtering to a modified inverse distance filtering method (IDWMO) filtered point cloud data. Both methods use manually filtered surfaces as reference. The comparison shows that the mean error and root-mean-square-error (RSME) between the results and the manually filtered surface of the two methods are similar. A significantly higher number of points of the terrain surface could be preserved, however, using the wedge-filtering approach. Therefore, we suggest that wedge-filtering should be integrated as a further parameter into already existing filtering processes, but is not suited as a standalone solution so far.
A novel positive-polarity electrostatic precipitator (ESP) was developed using an ionization stage (0.4 x 0.4 x 0.14 m(3) ) with 16 carbon fiber ionizers in each channel and a collection stage (0.4 x 0.4 x 0.21 m(3) ) with parallel metallic plates. The single-pass collection efficiency and clean air delivery rate (CADR) were measured by standard tests using KCl particles in 0.25-0.35 μm. Performance was determined using the Deutsch equation and established diffusion and field-charging theories, and also compared with the commercialized HEPA filter type air cleaner. Experimental results showed that the single-pass collection efficiency of the ESP ranged from 50 to 95% and decreased with the flow rate (10 to 20 m(3) /min) but increased with the voltage applied to the ionizers (6 to 8 kV) and collection plates (-5 to -7 kV). The ESP with 18 m(3) /min achieved a CADR of 12.1 m(3) /min with a voltage of 8 kV applied to the ionization stage, and with a voltage of -6 kV applied to the collection stage. The concentration of ozone in the test chamber (30.4 m(3) ), a maximum value of 5.4 ppb over 12 hours of continuous operation, was much lower than the current indoor regulation (50 ppb). © 2013 John Wiley & Sons A/S. Published by Blackwell Publishing Ltd.
This paper presents a robust and fully automatic filter-based approach for retinal vessel segmentation. We propose new filters based on 3D rotating frames in so-called orientation scores, which are functions on the Lie-group domain of positions and orientations R2oS1. By means of a wavelet-type transform, a 2D image is lifted to a 3D orientation score, where elongated structures are disentangled into their corresponding orientation planes. In the lifted domain R2 o S1, vessels are enhanced by means of multi-scale second-order Gaussian derivatives perpendicular to the line structures. More precisely, we use a leftinvariant rotating derivative (LID) frame, and a locally adaptive derivative (LAD) frame. The LAD is adaptive to the local line structures and is found by eigensystem analysis of the leftinvariant Hessian matrix (computed with the LID). After multiscale filtering via the LID or LAD in the orientation score domain, the results are projected back to the 2D image plane giving us the enhanced vessels. Then a binary segmentation is obtained through thresholding. The proposed methods are validated on six retinal image datasets with different image types, on which competitive segmentation performances are achieved. In particular, the proposed algorithm of applying the LAD filter on orientation scores (LAD-OS) outperforms most of the state-ofthe- art methods. The LAD-OS is capable of dealing with typically difficult cases like crossings, central arterial reflex, closely parallel and tiny vessels. The high computational speed of the proposed methods allows processing of large datasets in a screening setting.
Tanner et al. (2015. Psychophysiology, 52(8), 1009. doi: 10.1111/psyp.12437) convincingly demonstrate how a late deflection like the N400 or the P600 is reflected into both earlier and later latencies by the application of high-pass filters with cutoff frequencies higher than 0.1Hz. It nicely underlines the importance of test-wise application of filters with different parameters to electrophysiological data to identify such unwanted filter effects. In general, we agree with the their approach and conclusions, particularly with the notions that the application of a high-pass filter is reasonable if it improves the signal-to-noise ratio (SNR) of the signal of interest, and that low frequency signals may carry important information. However, we disagree in two aspects: First, the test data of Tanner et al. are not optimally suited to demonstrate the benefits of high-pass filtering as they are only minimally contaminated by low frequency noise, and second, the standard baseline correction for particular applications in M/EEG data analysis should be replaced with high-pass filtering-as recommended by Widmann et al. (2015. J Neurosci Methods, 250, 46. doi: 10.1016/j.jneumeth.2014.08.002).