Aerosol Spectrometer Research Articles

Transmission and reduction of aerosols in classrooms using air purifier systems.

SARS-CoV-2 (COVID-19) as an airborne respiratory disease led to a bunch of open questions: how teaching in classrooms is possible and how the risk of infection can be reduced, e.g., by the use of air purifier systems. In this study, the transmission of aerosols in a classroom is analyzed numerically and experimentally. The aerosol concentration in a classroom equipped with an air purifier system was measured with an aerosol spectrometer (optical particle sizer, TSI Incorporated) at different locations. The transient reduction of the aerosol concentration, which was artificially generated by an aerosol generator (di-ethyl hexyl sebacate-atomizer, detected particle size ranging from 0.3 to 10 μm), was monitored. The experimental results were used to validate a numerical simulation model of the classroom using the Open Source Computational Fluid Dynamics code OpenFOAM® (version 6). With the numerical simulation model, different scenarios with infected persons in the room have been analyzed, showing that the air purifier system leads to a significant reduction of airborne particles in the room dependent on the location of the infected person. The system can support additional ventilation strategies with fresh air, especially in cold seasons.

P0736 / #1895: EVALUATION OF SPLASHGUARDCG PREVENTION OF AEROSOLISED PARTICLE DISPERSION IN A PAEDIATRIC MODEL OF SPONTANEOUS AND NON-INVASIVE VENTILATION

AIMS & OBJECTIVES: The Splashguard (SG) is a plexiglass enclosure placed around the patient's head to limit the risk of transmission of COVID-19 during care. The SG was designed to prevent droplet transmission, but can concentrate aerosolized particles inside the SG. The objective was to evaluate the effectiveness of adding suction to prevent the risk of dispersal of aerosolized particles (AP) from critically ill patients on spontaneous ventilation (SV) and non-invasive ventilation (NIV). METHODS: The Topas Aerosol Generator (ATM-220) was connected to the airways of a high-fidelity manikin (SimBabyTM) with a breathing simulator (ASL 5000 tm), to generate a stable concentration of di-ethyl-hexyl-sebacat aerosol particles for 40 s within the SG. The NIV was applied using a Servo-I ventilator with a full-face mask (Figure). The temporal variation of the particle number density and size distribution was measured using a laser aerosol spectrometer (GRIMM 11-R) over the 0.5 μm to 1.0 mm range inside the SG, just above the manikin's head, with and without suction (92 L/min) inside the enclosure. RESULTS: While the aerosol generator is supplying aerosol to the Simbaby airways, the particle concentration increases steadily in the enclosure, with a larger peak in SV than in NIV. The PA peak was greater in SV than in NIV (1.4x106 vs 6.0x105, respectively). Aspiration decreased both the PA peak in SV and NIV, and the time to achieve a 50% reduction in AP concentration. CONCLUSIONS: The application of suction reduced the aerosol concentration inside the SG and may reduce the risk of airborne transmission when handling the SG.

Particulate matter and airborne endotoxin concentration in calf barns and their association with lung consolidation, inflammation, and infection

Agricultural operations are important sources of organic dust containing particulate matter (PM) and endotoxins, which have possible negative health consequences for both humans and animals. Dust concentrations and composition in calf barns, as well as the potential health effects for these animals, are scarcely documented. The objective of this study was to measure PM fractions and endotoxin concentrations in calf barns and study their associations with lung consolidation, respiratory tract inflammation, and infection in group-housed calves. In this cross-sectional study, samples from 24 dairy farms and 23 beef farms were collected in Belgium from January to April 2017. PM1.0, PM2.5 and PM10 (defined as particulate matter passing through a size-selective inlet with a 50% efficiency cut-off at a 1.0-μm, 2.5-μm, and 10-μm aerodynamic diameter, respectively) were sampled during a 24-h period using a Grimm aerosol spectrometer (Grimm Aerosol Technik Ainring GmbH & Co. KG). Endotoxin concentration was measured in the PM10 fraction. Thoracic ultrasonography was performed and broncho-alveolar lavage fluid was collected for cytology and bacteriology. Average PM concentrations were 16.3 µg/m3 (standard deviation, SD: 17.1; range: 0.20-771), 25.0 µg/m3 (SD: 25.3; range: 0.50-144.9), and 70.3 µg/m3 (SD: 54.5; range: 1.6-251.2) for PM1.0, PM2.5, and PM10, respectively. Mean endotoxin in the PM10 fraction was 4.2 endotoxin units (EU)/µg (SD: 5.50; range: 0.03-30.3). Concentrations in air were 205.7 EU/m3 (SD: 197.5; range: 2.32-901.0). Lung consolidations with a depth of ≥1, ≥3, and ≥6 cm were present in 43.1% (146/339), 27.4% (93/339), and 15.3% (52/339) of the calves, respectively. Exposure to fine (PM1.0) PM fractions was associated with increased odds of lung consolidations of ≥1 cm (odds ratio, OR: 3.3; confidence interval (CI): 1.5-7.1), ≥3 cm (OR: 2.8; CI: 1.2-7.1), and ≥6 cm (OR: 12.3; CI: 1.2-125.0). The odds of having lung consolidations of ≥1 cm (OR: 13.9; CI: 3.4-58.8) and ≥3 cm (OR: 6.7; 1.7-27.0) were higher when endotoxin concentrations in the dust mass exceeded 8.5 EU/µg. Broncho-alveolar lavage fluid neutrophil percentage was positively associated with PM10 concentration, and epithelial cell percentage was negatively associated with this fraction. Concentration of PM2.5 was positively associated with epithelial cell percentage and isolation of Pasteurella multocida. Although concentrations of fine dust are lower in calf barns than in poultry and pig housings, in this study they were associated with pneumonia in calves. Dust control strategies for reducing fine dust fractions in calf barns may benefit human and animal respiratory health.

Evaluation and Application of a Novel Low-Cost Wearable Sensing Device in Assessing Real-Time PM2.5 Exposure in Major Asian Transportation Modes

Small low-cost sensing (LCS) devices enable assessment of close-to-reality PM2.5 exposures, though their data quality remains a challenge. This work evaluates the precision, accuracy, wearability and stability of a wearable particle LCS device, Location-Aware Sensing System (LASS, with Plantower PMS3003), which is 104 × 66 × 46 mm3 in size and less than 162 g in weight. Real-time particulate matter (PM) exposures in six major Asian transportation modes were assessed. Side-by-side laboratory evaluation of PM2.5 between a GRIMM aerosol spectrometer and sensors yielded a correlation of 0.98 and a mean absolute error of 0.85 µg/m3. LASS readings collected in the summer of 2016 in Taiwan were converted to GRIMM-comparable values. Mean PM2.5 concentrations obtained from GRIMM and converted LASS values of the six different transportation microenvironments were 16.9 ± 11.7 (n = 1774) and 17.0 ± 9.5 (n = 3399) µg/m3, respectively, showing a correlation of 0.93. The average one-hour PM2.5 exposure increments (concentration increase above ambient levels) from converted LASS values for Mass Rapid Transit (MRT), bus, car, scooter, bike and walk were 15.6, 6.7, −19.2, 8.1, 6.1 and 7.1 µg/m3, respectively, very close to those obtained from GRIMM. This work is one of the earliest studies applying wearable particulate matter (PM) LCS devices in exposure assessment in different transportation modes.

Particulate Matter Profiles along the Rack Railway Route Using Low-Cost Sensor

Air pollution due to Particulate Matter (PM) is an increasing concern of global extent. It has been the focus of many research projects worldwide and the latest low-cost technology is offering an ease and cheap way to monitor PM concentration. In this research, a low-cost PM monitoring platform was built with the objectives of evaluating its feasibility and its performance in mobile measurements, as well as characterizing the concentration profiles of PM along the measurement route. The rack railway in Stuttgart was utilized as means of transportation for this low-cost monitoring system with which the temporal and spatial distribution of the PM10, PM2.5 and PM1 concentration along the route was attained. The measurements were conducted for around two months from mid of January until mid of March 2019, during the operation hours of the rack railway. The results showed that the PM concentrations were dominated by fine particulate matter (PM2.5 and PM1) along the route of the rack railway. Higher PM concentrations were measured near the federal highway and high traffic area as compared to the residential area. An overestimation of PM concentration using low-cost sensor platform was observed during high relative humidity conditions as compared to the professional aerosol spectrometers.

Design and field campaign validation of a multi-rotor unmanned aerial vehicle and optical particle counter

Abstract. Small unmanned aircraft (SUA) have the potential to be used as platforms for the measurement of atmospheric particulates. The use of an SUA platform for these measurements provides benefits such as high manoeuvrability, reusability, and low cost when compared with traditional techniques. However, the complex aerodynamics of an SUA – particularly for multi-rotor airframes – pose difficulties for accurate and representative sampling of particulates. The use of a miniaturised, lightweight optical particle instrument also presents reliability problems since most optical components in a lightweight system (for example laser diodes, plastic optics, and photodiodes) are less stable than their larger, heavier, and more expensive equivalents (temperature-regulated lasers, glass optics, and photomultiplier tubes). The work presented here relies on computational fluid dynamics with Lagrangian particle tracking (CFD–LPT) simulations to influence the design of a bespoke meteorological sampling system: the UH-AeroSAM. This consists of a custom-built airframe, designed to reduce sampling artefacts due to the propellers, and a purpose-built open-path optical particle counter (OPC) – the Ruggedised Cloud and Aerosol Sounding System (RCASS). OPC size distribution measurements from the UH-AeroSAM are compared with the cloud, aerosol, and precipitation spectrometer (CAPS) for measurements of stratus clouds during the Pallas Cloud Experiment (PaCE) in 2019. Good agreement is demonstrated between the two instruments. The integrated dN∕dlog (Dp) is shown to have a coefficient of determination of 0.8 and a regression slope of 0.9 when plotted 1:1.

Synergistic Use of Hyperspectral UV-Visible OMI and Broadband Meteorological Imager MODIS Data for a Merged Aerosol Product

The retrieval of optimal aerosol datasets by the synergistic use of hyperspectral ultraviolet (UV)–visible and broadband meteorological imager (MI) techniques was investigated. The Aura Ozone Monitoring Instrument (OMI) Level 1B (L1B) was used as a proxy for hyperspectral UV–visible instrument data to which the Geostationary Environment Monitoring Spectrometer (GEMS) aerosol algorithm was applied. Moderate-Resolution Imaging Spectroradiometer (MODIS) L1B and dark target aerosol Level 2 (L2) data were used with a broadband MI to take advantage of the consistent time gap between the MODIS and the OMI. First, the use of cloud mask information from the MI infrared (IR) channel was tested for synergy. High-spatial-resolution and IR channels of the MI helped mask cirrus and sub-pixel cloud contamination of GEMS aerosol, as clearly seen in aerosol optical depth (AOD) validation with Aerosol Robotic Network (AERONET) data. Second, dust aerosols were distinguished in the GEMS aerosol-type classification algorithm by calculating the total dust confidence index (TDCI) from MODIS L1B IR channels. Statistical analysis indicates that the Probability of Correct Detection (POCD) between the forward and inversion aerosol dust models (DS) was increased from 72% to 94% by use of the TDCI for GEMS aerosol-type classification, and updated aerosol types were then applied to the GEMS algorithm. Use of the TDCI for DS type classification in the GEMS retrieval procedure gave improved single-scattering albedo (SSA) values for absorbing fine pollution particles (BC) and DS aerosols. Aerosol layer height (ALH) retrieved from GEMS was compared with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data, which provides high-resolution vertical aerosol profile information. The CALIOP ALH was calculated from total attenuated backscatter data at 1064 nm, which is identical to the definition of GEMS ALH. Application of the TDCI value reduced the median bias of GEMS ALH data slightly. The GEMS ALH bias approximates zero, especially for GEMS AOD values of >~0.4 and GEMS SSA values of <~0.95. Finally, the AOD products from the GEMS algorithm and MI were used in aerosol merging with the maximum-likelihood estimation method, based on a weighting factor derived from the standard deviation of the original AOD products. With the advantage of the UV–visible channel in retrieving aerosol properties over bright surfaces, the combined AOD products demonstrated better spatial data availability than the original AOD products, with comparable accuracy. Furthermore, pixel-level error analysis of GEMS AOD data indicates improvement through MI synergy.

Numerical simulation and analysis of pressure distribution and airflow speed around an airborne cloud microphysics measurements instrument

Clouds have an important impact on Earth’s energetic balance, so measuring accurately the microphysical parameters and using them in research has become one important step in atmospheric studies. Regarding the fact that light scattering probes convert the flow rate to concentration, any wrong assumption or measurement of the flow rate can lead to incorrect results. Applying numerical simulation to an airborne cloud microphysics measurements instrument can provide information that can be measured in any point of the sampling volume, and further used in determination of microphysics parameters, providing more accurate data. Taking this into consideration, in this paper are presented the results of numerical simulation applied to Cloud Aerosol and Precipitation Spectrometer and the comparison with results reported in literature.

Filtration efficiency of surgical sterilization fabric for respiratory protection during COVID-19 pandemic

BackgroundDue to COVID-19 and high demand for respirators, some healthcare professionals have been using the Halyard H600 fabric as an alternative to N95 respirators without testing the filtration efficiency of the fabric with established scientific methods. The purpose of this study was to assess the efficiency of the Halyard H600 as a respirator filtering material as compared to the NIOSH-certified N95 and P100 filters, and determine if H600 is a good alternative for respiratory protection for healthcare professionals during the COVID-19 pandemic. MethodsThree filter types (Halyard H600, N95, and P100) were challenged with salt particles inside an exposure chamber at a flow rate of 43 LPM and relative humidity of 40 ± 2%. N95 and P100 respirator filters were tested initially to establish the validity of the chamber, followed by the Halyard H600 fabric. Particle penetration was measured using an aerosol spectrometer. The filtration efficiency was calculated for different particle sizes by measuring the particle number concentration upstream and downstream of the filter. The pressure drop across the filter materials was measured using a manometer. ResultsThe efficiency of the P100 for particles ≥250 nm was 100%. The N95 efficiency was 97 ± 1% at 275 nm, 99 ± 0% at 324 nm, and 100% for larger particles. The Halyard H600 fabric had a variable efficiency with an average of 62 ± 28% at 275 nm, 89 ± 8% at 324 nm, and 100% efficiency for particles >450 nm. The pressure drop values for P100 and N95 were 32 and 8 mmH2O, respectively. The Halyard H600 fabric resistance increased dramatically from 30 mmH2O at the start of the exposure to 65 mmH2O after 16-minutes of exposure. ConclusionThe high variability in filter efficiency for particles ≤324 nm and the increased fabric breathing resistance demonstrate that the Halyard H600 has an inferior performance and is not a good substitute for N95 and P100. Thus, the use of the Halyard H600 fabric for respiratory protection is not recommended.

Performance Assessment of Portable Optical Particle Spectrometer (POPS).

Accurate representation of atmospheric aerosol properties is a long-standing problem in atmospheric research. Modern pilotless aerial systems provide a new platform for atmospheric in situ measurement. However, small airborne platforms require miniaturized instrumentation due to apparent size, power, and weight limitations. A Portable Optical Particle Spectrometer (POPS) is an emerged instrument to measure ambient aerosol size distribution with high time and size resolution, designed for deployment on a small unmanned aerial system (UAS) or tethered balloon system (TBS) platforms. This study evaluates the performance of a POPS with an upgraded laser heater and additional temperature sensors in the aerosol pathway. POPS maintains its performance under different environmental conditions as long as the laser temperature remains above 25 °C and the aerosol flow temperature inside the optical chamber is 15 °C higher than the ambient temperature. The comparison between POPS and an Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) suggests that the coincidence error is less than 25% when the number concentration is less than 4000 cm−3. The size distributions measured by both of them remained unaffected up to 15,000 cm−3. While both instruments’ sizing accuracy is affected by the aerosol chemical composition and morphology, the influence is more profound on the POPS.

Exposure to Fine Particulate Matter and Inflammatory Cytokines and DNA Methylation in Healthy Young Adults

Background/Aim: Protective benefits of indoor air filtration in areas with high pollution levels are not fully understood. This study aims to examine whether short-term air filtration intervention could attenuate the hazards from acute exposure to fine particulate matter (PM2.5), and investigate the potential impact of this exposure on inflammatory cytokines and DNA methylation. Methods: A randomized, double-blind crossover trial of true or sham indoor air filtration was conducted among 29 healthy young adults in Beijing, China. Each episode covered a typical air pollution smog event, and 38 cytokines and their corresponding DNA methylation in the study participants were measured at three time points: pre-smog, during smog, and post-smog. Indoor PM2.5 concentrations were measured using an aerosol spectrometer and outdoor PM2.5 concentrations were collected from fixed-site monitoring stations. Linear mixed-effect models were used to evaluate the associations between exposure and outcome variables. Results: The indoor PM2.5 concentration with true filtration was 67.8% lower than sham filtration (13.8 μg/m3 vs. 42.8 μg/m3). Air filtration was significantly associated with decreases of 6.61% to 35.46% in 13 cytokines. Time-weighted personal PM2.5 exposure was significantly associated with changes in 11 cytokines and methylation at 27 CpGs. Specifically, PM2.5 exposure was associated with increases in MCP-1, MCP-3 and sCD40L, but hypomethylation in corresponding genes. Conclusions: This trial suggests that indoor air filtration might attenuate the adverse effects of PM2.5 exposure through changing cytokines and DNA methylation.

In situ cloud ground-based measurements in the Finnish sub-Arctic: intercomparison of three cloud spectrometer setups

Abstract. Continuous, semi-long-term, ground-based in situ cloud measurements were conducted during the Pallas Cloud Experiment (PaCE) in 2013. The measurements were carried out in Finnish sub-Arctic region at Sammaltunturi station (67∘58′ N, 24∘07′ E; 560 m a.s.l.), part of Pallas Atmosphere – Ecosystem Supersite and Global Atmosphere Watch (GAW) program. The main motivation of the campaign was to conduct in situ cloud measurements with three different cloud spectrometer probes and perform an evaluation of their ground-based setups. Therefore, we mutually compared the performance of the cloud and aerosol spectrometer (CAS), the cloud droplet probe (CDP) and the forward-scattering spectrometer probe (FSSP-100) (DMT; Boulder, CO, USA). We investigated how different meteorological parameters affect each instrument's ground-based setup operation and quantified possible biases and discrepancies of different microphysical cloud properties. Based on the obtained results we suggested limitations for further use of the instrument setups in campaigns where the focus is on investigating aerosol–cloud interactions. Measurements in this study were made by instruments owned by the Finnish Meteorological Institute and results concern their operation in sub-Arctic conditions with frequently occurring supercooled clouds. The measured parameter from each instrument was the size distribution, and additionally we derived the number concentration, the effective diameter, the median volume diameter and the liquid water content. A complete intercomparison between the CAS probe and the FSSP-100 ground setups and additionally between the FSSP-100 and the CDP probe ground setups was made and presented. Unfortunately, there was not a sufficient amount of common data to compare all three probes together due to operational problems of the CDP ground setup in sub-zero conditions. The CAS probe that was fixed to one direction lost a significant number of cloud droplets when the wind direction was out of wind iso-axial conditions in comparison with the FSSP-100 and the CDP, which were both placed on a rotating platform. We revealed that CAS and FSSP-100 had good agreement in deriving sizing parameters (effective diameter and median volume diameter from 5 to 35 µm) even though CAS was losing a significant amount of cloud droplets. The most sensitive derived parameter was liquid water content, which was strongly connected to the wind direction and temperature.

Synoptic characteristics and ozone distributions associated with spring dust classes over the northern Arabian Peninsula

The spring season can be classified into five dust classes over the northern Arabian Peninsula (AP), and they range from free (represented 3.3% of measured period) to strong (represented 21.4% of measured period) and were categorized based on their Total Ozone Mapping Spectrometer (TOMS) aerosol index (AI) values. The horizontal distribution of total ozone and the synoptic characteristics of these classes were analyzed using the TOMS total ozone and National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis meteorological data. The horizontal distribution of total ozone for the dust classes indicated that ozone increased (from 260 DU for dust-free to 280 DU for strong dust classes) over the southern study region. Meanwhile, the amount (from 380 DU for the dust-free to 360 DU for strong dust classes) and gradient of ozone decreased over the subtropical region as the dust class intensified, and the concentration of ozone toward the southern region was related to weak dust classes. The synoptic study indicated that the dust systems over the northern AP intensified when the atmospheric conditions were favorable for deepening the surface low pressure or a trough influenced the area and an upper-level pronounced trough and ridge occurred over the eastern and western AP. An examination of the dust cases indicated that the synoptic features that occurred with dust over the northern AP did not occur via the atmospheric systems themselves but rather via the relative relationships between these systems. Furthermore, the results confirmed that ozone over the northern (southern) AP decreased (increased) as the dust features strengthened (weakened).

Seasonal and Daily Variability of Aerosol Particle Concentrations near St. Petersburg

GRIMM aerosol spectrometer measurements of mass concentrations of PM1, PM2.5, and PM10 near St. Petersburg (Russia) in 2016–2018 are analyzed. The average concentrations of PM1, PM2.5, and PM10 over the measurement period are 4.5, 4.8, and 4.9 μg/m3, respectively. The hourly average PM10 concentrations are compared with the aerosol optical thickness at a wavelength of 500 nm (AOT) for different seasons. The correlation between the PM10 concentration and AOT is found to be the strongest in autumn. According to the distribution of the wind directions, the maximal PM10 concentrations correspond to the eastern winds (from St. Petersburg). The seasonal dependence of the daily variation in the mass concentration of PM10 on the relative air humidity and the height of the atmospheric boundary layer is analyzed. The PM10 concentrations (~8 μg/m3 on the average) and the amplitude of their daily variations are maximal in winter.

Evaluation of Aerosol Optical Depth (AOD) and PM2.5 associations for air quality assessment

Traditional station-based PM2.5 monitoring method has significant spatial gaps. Moderate Resolution Imaging Spectrometer (MODIS) Aerosol Optical Depth (AOD) product (10 km spatial resolution) derived from the imagery of NASA Terra satellite has been used as a tool for regional PM2.5 studies for many years. Literature suggested mixed results on AOD-PM2.5 correlation across geographic location, size of study area, and spatial resolution of MODIS AOD product. Also, correlation coefficient was reported at seasonal or yearly level and seldom any atmospheric research reported the AOD-PM2.5 correlation at daily level, which is crucial to utilize MODIS AOD products in air quality assessment. In this study, MODIS AOD product with 1, 3, and 10 km spatial resolutions were employed to examine their linear relationship with hourly PM2.5 data at daily level in order to evaluate their feasibility for PM2.5 remote monitoring in the state of North Carolina, U.S. First, the daily correlation between MODIS AOD value and ground PM2.5 concentration was statistically analyzed for the day in which both data existed. Next, a site-specific AOD- PM2.5 correlation was examined for each AirNow PM2.5 station in NC at 1 km, 3 km and 10 km spatial resolutions respectively in 2011 and 2012. The significance of all correlations was tested at 95% confidence level for each day at which two pairs of PM2.5 and AOD existed and each station in both years. It was found that the site-specific correlation between MODIS AOD value and ground PM2.5 concentration was statistically significant (95% confidence level) at majority of PM2.5 monitoring stations at 1 km, 3 km and 10 km level in both 2011 and 2012 in NC. Our results suggest that it is practicable to use MODIS AOD data to assess PM2.5 concentrations monthly at both city and state level without incorporating meteorological parameters.Main finding: Significant site-specific AOD-PM2.5 correlations allow the application of MODIS AOD to air quality assessment;

The Great Smog Month and Spatial and Monthly Variation in Air Quality in Ambient Air in Delhi, India.

Background.In recent years, poor urban air quality in Delhi, India has gained significant attention. Episodic events including crop stubble burning and Diwali celebrations are considered major factors in the worsening quality of ambient air.Objective.This study aimed to investigate spatial and monthly variation as well as the role of episodic events in ambient air quality in Delhi, including the ‘Great Smog' month of November 2017.Methods.Monitoring of air pollutants (particulate matter (PM10, PM2.5, PM1) and nitrogen dioxide (NO2)) was carried out at three distinct locations of Delhi from April 2017–February 2018. The concentration of NO2 was measured using a modified Jacob and Hochheiser method and PM was measured using a GRIMM aerosol spectrometer. Air quality index was also determined to identify the effects of air pollution on human health.Results.Overall, the levels of air pollution were found to be approximately 2.1–3.2 times higher along a traffic intersection and about 1.4–2.0 times higher in a commercial area compared with an institutional area. The highest average monthly concentrations of PM10, PM2.5, PM1 and NO2 were 768, 374, 298 and 149 μg/m3, respectively, during the Great Smog month of November 2017. November and August were recorded as the most polluted and cleanest months, respectively, in the city. Generally, poor to severe categories of the air quality index (AQI) were obtained from October to February. Higher concentrations during November were attributed to stubble burning in the nearby states of Delhi with the additive effect of fireworks during Diwali celebrations.Conclusions.Severe ambient air quality as observed in the present study is a serious matter of concern for the health of Delhi's population. To control spikes in poor air quality during episodic events, it is imperative to raise awareness among farmers regarding the severe health hazards of stubble burning.Competing Interests.The authors declare no competing financial interests.

Simultaneous measurement of spatially resolved particle emissions in a pilot plant scale baghouse filter applying distributed low-cost particulate matter sensors

Baghouse filters are widely applied in industrial gas cleaning, for example in waste incineration plants and the cement industry, to meet particle emission standards and for product recovery. The global particle emission of pulse-jet cleaned surface filters is typically monitored end of pipe (e.g. in the stack). Since the particulate matter emission of baghouse filters originates often from leaks and incorrectly installed or damaged filter bags, operators would greatly profit from online measurement technology that monitors the emission contribution of individual filter bags or at least a subset of all installed filter elements to the total emission. Low-cost particulate matter sensors can be deployed inside filter houses in larger quantities due to their compact design and low asset cost compared to conventional aerosol measurement technology. The ability of several low-cost sensors to detect the characteristic PM emission behavior of surface filters has been shown in previous investigations in a filter test rig. This study shows first results regarding the emission contribution of individual filter bags of a pilot plant scale baghouse filter employing distributed low-cost sensors of the model OPC-N3 from the manufacturer Alphasense. A Promo® 2000 aerosol spectrometer with a welas® 2100 sensor serves as reference regarding the particulate matter concentration detected by the low-cost sensors and as end of pipe measurement equipment to monitor the global emission. The selected filter medium was a membrane filter medium with sealed seams to provide low emission levels and defined conditions on the clean gas side. The employed low-cost sensors detect an emission peak right after cleaning of the corresponding filter bag only. The global emission measured in the clean gas duct consists of the overlay of the individual emission peaks detected locally at the corresponding filter bags. By exchanging one filter bag with a filter bag made from a non-membrane filter medium without sealed seams, an increase of the total continuous emission can be detected, both end of pipe in the clean gas duct and locally via the low-cost particulate matter sensor. This demonstrates the applicability of the measurement technology for the detection and identification of leaks and damaged filter bags that serve as emission hotspots in baghouse filters.

Droplet Generation in Standing-Surface-Acoustic-Wave Nebulization at Controlled Air Humidity

Surface-acoustic-wave (SAW) aerosol generators are very promising systems for applications requiring small aerosol sources and adjustable droplet-size distributions at low aerosol flowrates. However, the droplet-generation mechanism by SAW is yet unclear and dedicated experiments are necessary to gain further insights. In this work, the atomization zone is investigated experimentally to gain more insight into the droplet-generation mechanism by SAW. Three regions are observed in the atomization zone showing different acoustofluidic effects, including the formation of liquid films and patterns in a standing SAW (SSAW) wavefield and droplet generation. In addition, the influence of the humidity of surrounding air on the measured droplet-size distribution of the aerosols generated by SSAW is investigated. Therefore, the air humidity is adjusted at constant air temperature in the sophisticated wind-tunnel Turbulent Leipzig Aerosol Cloud Interaction Simulator combined with an optical particle spectrometer with resolution down to the sub-\textmu{}m scale. Besides the humidity influence on the droplet size in the measurement region, water-saturated air allowed us to estimate the initial droplet-size distribution at the atomization zone on the chip surface. This parameter is crucial for the determination of the underlying liquid-film disintegration mechanism, i.e., the droplets' origin. Hereby, a bimodal log-normal droplet-size distribution is obtained. The mean diameter of the main droplet fraction decreases from 7.2 to 5.3 \textmu{}m with increasing relative humidity from 8.6 to 97%, apparently due to evaporation of smaller droplets in unsaturated air. A second peak corresponds to a mean diameter as small as 600 nm at high humidity conditions, which is likely to correspond to a droplet-generation mechanism not reported so far and extremely difficult to measure or visualize with conventional techniques. The droplet-size measurement results from the aerosol spectrometer are compared and validated in respect to existing droplet-generation models with the results of a phase-Doppler anemometry, a high-resolution, nonintrusive local aerosol-measurement technique.

Wildfire Smoke Adjustment Factors for Low-Cost and Professional PM2.5 Monitors with Optical Sensors.

Air quality monitors using low-cost optical PM2.5 sensors can track the dispersion of wildfire smoke; but quantitative hazard assessment requires a smoke-specific adjustment factor (AF). This study determined AFs for three professional-grade devices and four monitors with low-cost sensors based on measurements inside a well-ventilated lab impacted by the 2018 Camp Fire in California (USA). Using the Thermo TEOM-FDMS as reference, AFs of professional monitors were 0.85 for Grimm mini wide-range aerosol spectrometer, 0.25 for TSI DustTrak, and 0.53 for Thermo pDR1500; AFs for low-cost monitors were 0.59 for AirVisual Pro, 0.48 for PurpleAir Indoor, 0.46 for Air Quality Egg, and 0.60 for eLichens Indoor Air Quality Pro Station. We also compared public data from 53 PurpleAir PA-II monitors to 12 nearby regulatory monitoring stations impacted by Camp Fire smoke and devices near stations impacted by the Carr and Mendocino Complex Fires in California and the Pole Creek Fire in Utah. Camp Fire AFs varied by day and location, with median (interquartile) of 0.48 (0.44–0.53). Adjusted PA-II 4-h average data were generally within ±20% of PM2.5 reported by the monitoring stations. Adjustment improved the accuracy of Air Quality Index (AQI) hazard level reporting, e.g., from 14% to 84% correct in Sacramento during the Camp Fire.

Identifying a regional aerosol baseline in the eastern North Atlantic using collocated measurements and a mathematical algorithm to mask high-submicron-number-concentration aerosol events

Abstract. High-time-resolution measurements of in situ aerosol and cloud properties provide the ability to study regional atmospheric processes that occur on timescales of minutes to hours. However, one limitation to this approach is that continuous measurements often include periods when the data collected are not representative of the regional aerosol. Even at remote locations, submicron aerosols are pervasive in the ambient atmosphere with many sources. Therefore, periods dominated by local aerosol should be identified before conducting subsequent analyses to understand aerosol regional processes and aerosol–cloud interactions. Here, we present a novel method to validate the identification of regional baseline aerosol data by applying a mathematical algorithm to the data collected at the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility in the eastern North Atlantic (ENA). The ENA central facility (C1) includes an aerosol observing system (AOS) for the measurement of aerosol physical, optical, and chemical properties at time resolutions from seconds to minutes. A second temporary supplementary facility (S1), located ∼0.75 km from C1, was deployed for ∼1 year during the Aerosol and Cloud Experiments (ACE-ENA) campaign in 2017. First, we investigate the local aerosol at both locations. We associate periods of high submicron number concentration (Ntot) in the fine-mode condensation particle counter (CPC) and size distributions from the Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) as a function of wind direction using a meteorology sensor with local sources. Elevated concentrations of Aitken-mode (< 100 nm diameter) particles were observed in correspondence with the wind directions associated with airport operations. At ENA, the Graciosa Airport and its associated activities were found to be the main sources of high-concentration aerosol events at ENA, causing peaks in 1 min Ntot that exceeded 8000 and 10 000 cm−3 at C1, in summer and winter, respectively, and 5000 cm−3 at S1 in summer. Periods with high Ntot not associated with these wind directions were also observed. As a result, the diverse local sources at ENA yielded a poor relationship between Ntot measurements collected at C1 and S1 (R2=0.03 with a slope =0.05±0.001). As a first approach to mask these events, the time periods when the wind direction was associated with the airport operations (west to northwest and southeast to south at C1 and east to south at S1) were applied. The meteorological masks removed 38.9 % of the data at C1 and 43.4 % at S1, and they did not significantly improve the relationship between the two sites (R2=0.18 with a slope =0.06±0.001). Due to the complexity of high-Ntot events observed at ENA, we develop and validate a mathematical ENA Aerosol Mask (ENA-AM) to identify high-Ntot events using 1 min resolution data from the AOS CPC at C1 and S1. After its parameterization and application, ENA-AM generated a high correlation between Ntot in the summer at C1 and S1 (R2=0.87 with a slope =0.84±0.001). We identified the regional baseline at ENA to be 428±228 cm−3 in the summer and 346±223 cm−3 in the winter. Lastly, we compared masked measurements from the AOS with the ARM Aerial Facility (AAF) during flights over C1 in the summer to understand submicron aerosol vertical mixing over C1. The high correlation (R2=0.71 with a slope of 1.04±0.01) observed between C1 and the AAF Ntot collected within an area of 10 km surrounding ENA and at altitudes < 500 m indicated that the submicron aerosol at ENA was well mixed within the first 500 m of the marine boundary layer during the month of July during ACE-ENA. Our novel method for determining a regional aerosol baseline at ENA can be applied to other time periods and at other locations with validation by a secondary site or additional collocated measurements.