Dataset associated with "Effects of aerosol type and simulated aging on performance of low-cost PM sensors"

These data were collected during a study on the performance of low-cost particulate matter (PM) sensors. All data were collected in an indoor laboratory at Colorado State University in Fort Collins, Colorado, USA between 2019-07-02 and 2019-10-06. The files associated with this dataset include: (1) time-averaged PM mass concentrations reported by the low-cost sensors during each steady-state test point included in the study, (2) time-averaged particle number concentrations reported by the low-cost sensors during each steady-state test point included in the study, (3) time-averaged particle size distribution data measured using an Scanning Mobility Particle Sizer (SMPS) during each steady-state test point included in the study, (4) time-averaged particle size distribution data measured using an Aerodynamic Particle Sizer (APS) Spectrometer during each steady-state test point included in the study, (5) real-time particle size distribution data measured using an APS during an experiment in which the low-cost sensors were exposed to very high Arizona road dust concentrations for 18 hours, (6) PM2.5 concentrations recorded at one-minute intervals by a Tapered Element Oscillating Microbalance (TEOM) during all experiments conducted during the study, (7) PM concentrations recorded at one-minute intervals by a DustTrak during an experiment in which the low-cost sensors were exposed to very high Arizona road dust concentrations for 18 hours, (8) data associated with all gravimetric filter samples of PM collected during the study, (9) real-time data recorded by the low-cost PM sensors during an experiment in which the sensors were exposed to very high Arizona road dust concentrations for 18 hours, (10) all of the raw data recorded by the low-cost PM sensors during the study, and (11) all of the raw data recorded by a DustTrak DRX 8533 during the study.Studies that characterize the performance of low-cost particulate matter (PM) sensors are needed to help practitioners understand the accuracy and precision of the mass and number concentrations reported by different models. We evaluated Plantower PMS5003, Sensirion SPS30, and Amphenol SM-UART-04L PM sensors in the laboratory by exposing them to: (1) four different polydisperse aerosols (ammonium sulfate, Arizona road dust, NIST Urban PM, and wood smoke) at concentrations ranging from 10 to 1000 μg m-3, (2) hygroscopic and hydrophobic aerosols (ammonium sulfate and oil) in an environment with varying relative humidity (15% to 90%), (3) polystyrene latex spheres (PSL) ranging from 0.1 to 2.0 μm in diameter, and (4) extremely high concentrations of Arizona road dust (18-hour mean total PM = 33000 μg m-3; 18-hour mean PM2.5 = 7300 μg m-3). Linear models relating PMS5003- and SPS30-reported PM2.5 concentrations to TEOM-reported ammonium sulfate concentrations up to 1025 μg m-3, nebulized Arizona road dust concentrations up to 540 μg m-3, and NIST Urban PM concentrations up to 330 μg m-3 had R2 ≥ 0.97; however, an F-test identified a significant lack of fit between the model and the data for each sensor/aerosol combination. Ratios of filter-derived to PMS5003-reported PM2.5 concentrations were 1.4, 1.7, 1.0, 0.4, and 4.3 for ammonium sulfate, nebulized Arizona road dust, NIST Urban PM, wood smoke, and oil mist, respectively. For SPS30 sensors, these ratios were 1.6, 2.1, 2.1, 0.6, and 2.2, respectively. Collocated PMS5003 sensors were less precise than collocated SPS30 sensors when measuring ammonium sulfate, nebulized Arizona road dust, NIST Urban PM, oil mist, or PSL. Our results indicated that particle count data reported by the PMS5003 were not reliable. The number size distribution reported by the PMS5003 (a) did not agree with APS data and (b) remained roughly constant whether the sensors were exposed to 0.1 μm PSL, 0.27 μm PSL, 0.72 μm PSL, 2.0 μm PSL, or any of the other laboratory-generated aerosols. The size distribution reported by the SPS30 did not always agree with APS data either, but did shift towards larger particle sizes when the sensors were exposed to 0.72 PSL, 2.0 μm PSL, oil mist, or Arizona road dust from a fluidized bed generator. The proportions of PM mass assigned as PM1, PM2.5, and PM10 by all three sensor models shifted as the PSL size increased. After the sensors were exposed to high concentrations of Arizona road dust for 18 hours, PM2.5 concentrations reported by SPS30 sensors remained consistent, whereas 3/8 PMS5003 sensors and 2/7 SM-UART-04L sensors began reporting erroneously high values.This work was funded by grants OH010635 and OH010662 from the National Institute for Occupational Safety and Health within the US Centers for Disease Control

Dataset associated with "Laboratory evaluation of low-cost PurpleAir PM monitors and in-field correction using co-located portable filter samplers"

This dataset consists of data collected during two laboratory evaluations of PurpleAir monitors and one field deployment of PurpleAir monitors co-located with portable filter samplers.The pre-deployment laboratory evaluation took place on 2018-08-20. The post-deployment laboratory evaluation took place on 2018-12-17. The goals of these evaluations were to: (a) assess whether the PurpleAir monitors responded linearly to NIST Urban Particulate Matter concentrations ranging from approximately 0 to 75 micrograms per cubic meter, (b) obtain laboratory-derived gravimetric correction factors for fine particulate matter (PM2.5) concentrations reported by PurpleAir monitors, (c) determine whether the response of the PurpleAir monitors to NIST Urban Particulate Matter changed over the duration of the field deployment, and (d) evaluate the precision of co-located PurpleAir monitors.The field deployment took place in Fort Collins, Colorado, USA between 2018-10-22 and 2018-12-06. The goals of the field deployment were to: (a) determine whether gravimetric correction factors derived from periodic co-locations with portable filter samplers (called "ASPEN boxes") improved the accuracy of 72-hour average PM2.5 concentrations reported by PurpleAir monitors (relative to conventional PM2.5 filter samplers operated at 16.7 L/min) and (b) compare 72-hour average PM2.5 concentrations measured using portable filter samplers and conventional filter samplers.The files associated with this dataset include: (1) the raw data recorded by the PurpleAir monitors during the two laboratory evaluations and the field deployment; (2) the raw data recorded by a tapered element oscillating microbalance (TEOM) during the two laboratory evaluations; (3) the raw data recorded by the ASPEN boxes during the field deployment; (4) a summary file describing the time-averaged concentrations reported by the PurpleAir monitors and the TEOM during the discrete concentration steps that comprised each laboratory evaluation; and (5) a summary file describing the average PM2.5 concentrations measured using the PurpleAir monitors, ASPEN boxes, and conventional filter samplers at each field site during each 72-hour sample period.Low-cost aerosol monitors can provide more spatially- and temporally-resolved data on ambient fine particulate matter (PM2.5) concentrations than are typically available from regulatory monitoring networks; however, low-cost monitors—which do not measure PM2.5 mass directly and tend to be sensitive to variations in particle size and refractive index—sometimes produce inaccurate concentration estimates. We investigated laboratory- and field-based approaches for calibrating low-cost PurpleAir monitors against gravimetric filter samples. First, we investigated the linearity of the PurpleAir response to NIST Urban PM and derived a laboratory-based gravimetric correction factor. Then, we co-located PurpleAir monitors with portable filter samplers at 15 outdoor sites spanning a 3×3-km area in Fort Collins, CO, USA. We evaluated whether PM2.5 correction factors derived from periodic co-locations with portable filter samplers improved the accuracy of PurpleAir monitors (relative to reference filter samplers operated at 16.7 L/min). We also compared 72-hour average PM2.5 concentrations measured using portable and reference filter samplers. Both before and after field deployment, the coefficient of determination for a linear model relating NIST Urban PM concentrations measured by a tapered element oscillating microbalance and the PurpleAir monitors (PM2.5 ATM) was 0.99; however, an F-test identified a significant lack of fit between the model and the data. The laboratory-based correction factor did not translate to the field. Correction factors derived in the field from monthly, weekly, semi-weekly, and concurrent co-locations with portable filter samplers increased the fraction of 72-hour average PurpleAir PM2.5 concentrations that were within 20% of the reference concentrations from 15% (for uncorrected measurements) to 45%, 59%, 56%, and 70%, respectively. Furthermore, 72-hour average PM2.5 concentrations measured using portable and reference filter samplers agreed (bias ≤ 20% for 71% of samples). These results demonstrate that periodic co-location with portable filter samplers can improve the accuracy of 72-hour average PM2.5 concentrations reported by PurpleAir monitors.This work was funded by the National Oceanic and Atmospheric Administration under grant no. 1305M218CNRMW0048

Identification of promoter-binding proteins of the <i>fbp</i> A and C genes in <i>Mycobacterium tuberculosis</i>

The antigen 85 (Ag85) complex of Mycobacterium tuberculosis represents a promising candidate as a novel drug target and pathogenesis factor. Ag85 comprises three proteins Ag85A, B and C, (encoded by the genes fbpA, B, and C), which participate in cell wall biosynthesis, and interact with the host macrophage as fibronectin-binding proteins (fbps). Ag85 is also involved in the response to isoniazid (INH) treatment. The objective of this study was to identify potential fbp gene activators involved in the over-expression of fbp genes in response to INH. The biotinylated upstream promoter regions of fbpA and fbpC were used together with streptavidin-coated magnetic beads in DNA-binding assays, to isolate proteins with high-binding affinities from cytosolic extracts of INH-treated M. tuberculosis. Resolution of the DNA-binding proteins by 1D SDS-PAGE revealed 6 proteins with high-affinity for the fbpA promoter, and 7 with specificity the fbpC promoter. Mass spectrometric analyses [LC-ES(MS/MS)] identified proteins associated with drug resistance and stress/treatment responses, intermediary metabolism and cellular division, hypothetical proteins including a member of the MarR family of bacterial transcriptional regulators. The DNA-binding MarR protein shows potential as an authentic activator of fbp genes and functional validation of this factor is warranted

Recombinant Factor C (rFC) Assay and Gas Chromatography/Mass Spectrometry (GC/MS) Analysis of Endotoxin Variability in Four Agricultural Dusts

Endotoxin exposure is a significant concern in agricultural environments due to relatively high exposure levels. The goals of this study were to determine patterns of 3-hydroxy fatty acid (3-OHFA) distribution in dusts from four types of agricultural environments (dairy, cattle feedlot, grain elevator, and corn farm) and to evaluate correlations between the results of gas chromatography/mass spectrometry (GC/MS) analysis (total endotoxin) and biological recombinant factor C (rFC) assay (free bioactive endotoxin). An existing GC/MS-MS method (for house dust) was modified to reduce sample handling and optimized for small amount ( dairy (0.53) > corn farm (0.33) > grain elevator (0.11). In livestock environments, both odd- and even-numbered carbon chain length 3-OHFAs correlated with rFC assay response. The GC/EI-MS method should be especially useful for identification of specific 3-OHFAs for endotoxins from various agricultural environments and may provide useful information for evaluating the relationship between bacterial exposure and respiratory disease among agricultural workers

Personal Exposure to PM2.5 Black Carbon and Aerosol Oxidative Potential using an Automated Microenvironmental Aerosol Sampler (AMAS).

Traditional methods for measuring personal exposure to fine particulate matter (PM2.5) are cumbersome and lack spatiotemporal resolution; methods that are time-resolved are limited to a single species/component of PM. To address these limitations, we developed an automated microenvironmental aerosol sampler (AMAS), capable of resolving personal exposure by microenvironment. The AMAS is a wearable device that uses a GPS sensor algorithm in conjunction with a custom valve manifold to sample PM2.5 onto distinct filter channels to evaluate home, school, and other (e.g., outdoors, in transit, etc.) exposures. Pilot testing was conducted in Fresno, CA where 25 high-school participants ( n = 37 sampling events) wore an AMAS for 48-h periods in November 2016. Data from 20 (54%) of the 48-h samples collected by participants were deemed valid and the filters were analyzed for PM2.5 black carbon (BC) using light transmissometry and aerosol oxidative potential (OP) using the dithiothreitol (DTT) assay. The amount of inhaled PM2.5 was calculated for each microenvironment to evaluate the health risks associated with exposure. On average, the estimated amount of inhaled PM2.5 BC (μg day-1) and OP [(μM min-1) day-1] was greatest at home, owing to the proportion of time spent within that microenvironment. Validation of the AMAS demonstrated good relative precision (8.7% among collocated instruments) and a mean absolute error of 22% for BC and 33% for OP when compared to a traditional personal sampling instrument. This work demonstrates the feasibility of new technology designed to quantify personal exposure to PM2.5 species within distinct microenvironments

Data collected during the pilot campaign of the citizen-enabled aerosol measurements for satellites (CEAMS) network in northern Colorado

Files include log files with all output from the AMOD device (including multi-wavelength aerosol optical depth values) for each participant (AD0**txt). To protect the privacy of participants, all GPS location data has been truncated in log files. Log files are separated by participant using unique alphanumeric identifier (bp###). Also included are files with aerosol mass (CEAMS Gravimetric and BC Results.xlsx) and elemental composition (CEAMS XRF Results.csv). Blank filters are noted in the files. Filters can be linked to log files by the log file name (last three numbers in log file name).These measurement data were collected by participants using the Aerosol Mass and Optical Depth (AMOD) sampler during a pilot campaign for the Citizen-Enabled Aerosol Measurements for Satellites (CEAMS) network in Fall/Winter 2017 in northern Colorado. Data include multi-wavelength aerosol optical depth, filter mass and composition, and optical particle mass concentrations (for a subset of the files).This work was funded by NASA grant NNX17AF94A and 80NSSC18M0120

Acute effects on blood pressure following controlled exposure to cookstove air pollution in the STOVES study

Background Exposure to air pollution from solid fuel used in residential cookstoves is considered a leading environmental risk factor for disease globally, but evidence for this relationship is largely extrapolated from literature on smoking, secondhand smoke, and ambient fine particulate matter (PM2.5). Methods and Results We conducted a controlled human‐exposure study (STOVES [the Subclinical Tests on Volunteers Exposed to Smoke] Study) to investigate acute responses in blood pressure following exposure to air pollution emissions from cookstove technologies. Forty‐eight healthy adults received 2‐hour exposures to 5 cookstove treatments (three stone fire, rocket elbow, fan rocket elbow, gasifier, and liquefied petroleum gas), spanning PM2.5 concentrations from 10 to 500 μg/m3, and a filtered air control (0 μg/m3). Thirty minutes after exposure, systolic pressure was lower for the three stone fire treatment (500 μg/m3PM2.5) compared with the control (−2.3 mm Hg; 95% CI, −4.5 to −0.1) and suggestively lower for the gasifier (35 μg/m3PM2.5; −1.8 mm Hg; 95% CI, −4.0 to 0.4). No differences were observed at 3 hours after exposure; however, at 24 hours after exposure, mean systolic pressure was 2 to 3 mm Hg higher for all treatments compared with control except for the rocket elbow stove. No differences were observed in diastolic pressure for any time point or treatment. Conclusions Short‐term exposure to air pollution from cookstoves can elicit an increase in systolic pressure within 24 hours. This response occurred across a range of stove types and PM2.5 concentrations, raising concern that even low‐level exposures to cookstove air pollution may pose adverse cardiovascular effects

Candidate innate immunity genes and cross shift pulmonary function changes among Western US dairy workers

Objectives: Organic dust inhalation has been associated with adverse respiratory responses among dairy workers. Worker susceptibility may be driven by dust constituents, e.g. Gramnegative bacteria (endotoxin), Gram-positive bacteria (muramic acid); intrinsic factors, e.g. genetic traits, immune system; and extrinsic factors, e.g. smoking and work-related behaviors. The goal of this study was to characterize genetic markers related to lung disease and the endotoxin pathway by testing associations with cross-shift changes in forced expiratory volume in 1 second (FEV1) and candidate innate immunity genes. Methods: This study quantified breathing-zone personal work-shift exposures and pulmonary function among dairy workers during a variety of tasks. Inhalable dust was collected with Button samplers and analyzed for endotoxin (rFCassay). Pulmonary function tests (PFT) before and after the work shift included: forced vital capacity (FVC), FEV1 and the FEV1/FVC ratio. The maximum of three valid maneuvers was used in analyses. Venous blood samples were collected using Qiagen PAXgene tubes. Following DNA isolation (Puregene), candidate gene single nucleotide polymorphisms (SNPs) were analyzed using a custom genotyping array (Illumina GoldenGate assay on VeraCode technology). The assay was designed to include tagging SNPs for candidate genes in Hispanic populations. Genotyping data were cleaned and exported for analysis using the Illumina BeadStudio. Additive genetic modeling approaches were used to describe the distribution of SNPs and their relation to FEV1 cross-shift changes. Based on the frequency of haplotypes, genes were categorized as major (dominant) homozygous (AA), minor homozygous (bb), or heterozygous (Ab). Results: Eighty-eight participants (91% Hispanic, 88% male) had PFT and genetic results. Geometric mean levels of endotoxin were 469 EU/m3. On average, FEV1 was significantly reduced across the work shift among all dairy workers (-1.6%, 95% CI: -2.5, -0.7). No clear patterns were observed in FEV1 reductions by exposure tertiles. Differences in cross-shift reductions of FEV1 were observed across SNPs of the TLR4 (rs11536878, rs10759930 and rs1927911), TLR2 (rs3804099) and LY96 (rs7838114 and rs16938761) genes. Grouping heterozygous and minor homozygous SNPs (i.e., recessive model) may result in observable trends for CD14 SNPs. Conclusions: This is the first study characterizing candidate gene SNPs associated with the endotoxin pathway among Hispanic dairy workers. Associations with FEV1 changes were observed with SNPs for TLR4, TLR2 and LY96. The direction of the effect was not always consistent with previous literature on other populations, including northern Europeans and children. Next steps include multifactor analysis of relationships among genetic SNPs, exposure and cross-shift FEV1

Candidate TLR and NLR innate immunity genes and cross shift pulmonary function changes among Western US dairy workers

Objectives: Organic dust inhalation has been associated with obstructive and restrictive respiratory disease among dairy workers. Workers are exposed to a wide variety of known agents of respiratory disease including microorganisms and their cellular components which can stimulate innate immune responses through pattern recognition receptors (PRRs) such as Toll‐like (TLR) and NOD‐like (NLR) receptors. The goal of this study was to characterize cross‐shift changes in lung function for various single nucleotide polymorphisms (SNPs) in candidate innate immunity genes in the TLR and NLR pathways. Methods: Breathing‐zone personal work‐shift inhalable dust samples were collected with Button samplers and analyzed for endotoxin (rFCassay), 3‐Hydroxy Fatty Acids, Muramic Acid and Ergosterol (GC‐MSMS). Pulmonary function tests (PFT) before and after the work shift included: forced vital capacity (FVC), Forced Expiratory Volume in 1 second (FEV1), Forced Expiratory Flow (FEF) and the FEV1/FVC ratio. Venous blood samples were collected using Qiagen PAXgene tubes. Following DNA isolation (Puregene), candidate gene SNPs were analyzed using a custom genotyping array (Illumina GoldenGate assay on VeraCode technology) to include tagging SNPs for candidate genes in Hispanic populations. Genotyping data were managed using the Illumina BeadStudio. Additive genetic modeling approaches were used to describe the distribution of SNPs and their relation to PFT cross‐shift changes. Results: Eighty‐eight participants (91% Hispanic, 88% male) had PFT and genetic results. Geometric mean levels of endotoxin were 469 EU/m3. On average, FEV1 was significantly reduced across the work shift among all dairy workers (‐1.6%, 95% CI: ‐2.5, ‐0.7). Cross‐shift PFT changes were observed across SNPs of the TLR4, TLR2, LY96, NOD1, NOD2, interferon gamma (IFNG), and tumor necrosis factor alpha (TNFα) genes. No observable trends were identified for cluster of differentiation 14 (CD14) or TLR 9 genes. Conclusions: This is the first study among Hispanic dairy workers which characterizes candidate gene SNPs associated with the innate immune gene pathways. Crossshift PFT changes across SNPs were not always consistent with previous literature on other populations, including northern Europeans and children; however, evidence suggests that certain genetic pathways may modify the respiratory effects of primarily Hispanic workers exposed to high levels of dust and endotoxin