New Methods for Personal Exposure Monitoring for Airborne Particles

A Portable Infrared System for Identification of Particulate Matter

Occupational exposure to airborne dust is responsible for numerous respiratory and cardiovascular diseases. Because of these hazards, air samples are regularly collected on filters and sent for laboratory analysis to ensure compliance with regulations. Unfortunately, this approach often takes weeks to provide a result, which makes it impossible to identify dust sources or protect workers in real time. To address these challenges, we developed a system that characterizes airborne dust by its spectro-chemical profile. In this device, a micro-cyclone concentrates particles from the air and introduces them into a hollow waveguide where an infrared signature is obtained. An algorithm is then used to quantitate the composition of respirable particles by incorporating the infrared features of the most relevant chemical groups and compensating for Mie scattering. With this approach, the system can successfully differentiate mixtures of inorganic materials associated with construction sites in near-real time. The use of a free-space optic assembly improves the light throughput significantly, which enables detection limits of approximately 10 µg/m3 with a 10 minute sampling time. While respirable crystalline silica was the focus of this work, it is hoped that the flexibility of the platform will enable different aerosols to be detected in other occupational settings.

Epigenetic mechanisms of particulate matter exposure: air pollution and hazards on human health

Environmental pollution nowadays has not only a direct correlation with human health changes but a direct social impact. Epidemiological studies have evidenced the increased damage to human health on a daily basis because of damage to the ecological niche. Rapid urban growth and industrialized societies importantly compromise air quality, which can be assessed by a notable accumulation of air pollutants in both the gas and the particle phases. Of them, particulate matter (PM) represents a highly complex mixture of organic and inorganic compounds of the most variable size, composition, and origin. PM being one of the most complex environmental pollutants, its accumulation also varies in a temporal and spatial manner, which challenges current analytical techniques used to investigate PM interactions. Nevertheless, the characterization of the chemical composition of PM is a reliable indicator of the composition of the atmosphere, the quality of breathed air in urbanized societies, industrial zones and consequently gives support for pertinent measures to avoid serious health damage. Epigenomic damage is one of the most promising biological mechanisms of air pollution-derived carcinogenesis. Therefore, this review aims to highlight the implication of PM exposure in diverse molecular mechanisms driving human diseases by altered epigenetic regulation. The presented findings in the context of pan-organic cancer, fibrosis, neurodegeneration and metabolic diseases may provide valuable insights into the toxicity effects of PM components at the epigenomic level and may serve as biomarkers of early detection for novel targeted therapies.

Adequacy of stationary measurements as proxies for residential personal exposure to gaseous and particle air pollutants

People are exposed to myriad of airborne pollutants in their homes. Owing to diverse potential sources of air pollution and human activity patterns, accurate assessment of residential exposures is complex. In this study, we explored the relationship between personal and stationary air pollutant measurements in residences of 37 participants working from home during the heating season. Stationary environmental monitors (SEMs) were located in the bedroom, living room or home office and personal exposure monitors (PEMs) were worn by the participants. SEMs and PEMs included both real-time sensors and passive samplers. During three consecutive weekdays, continuous data were obtained for particle number concentration (size range 0.3-10 μm), carbon dioxide (CO2), and total volatile organic compounds (TVOC), while passive samplers collected integrated measures of 36 volatile organic compounds (VOCs) and semi volatile organic compounds (SVOCs). The personal cloud effect was detected in >80% of the participants for CO2 and >50% participants for PM10. Multiple linear regression analysis showed that a single CO2 monitor placed in the bedroom efficiently represented personal exposure to CO2 (R2 = 0.90) and moderately so for PM10 (R2 = 0.55). Adding a second or third sensor in a residence did not lead to improved exposure estimates for CO2, with only 6-9% improvement for particles. Selecting data from SEMs when participants were in the same room improved personal exposure estimates by 33% for CO2 and 5% for particles. Out of 36 detected VOCs and SVOCs, 13 had at least 50% higher concentrations in personal versus stationary samples. Findings from this study aid improved understanding of the complex dynamics of gaseous and particle pollutants and their sources in residences, and could support the development of refined procedures for residential air quality monitoring and inhalation exposure assessment.

Effectiveness evaluation of water-sprinkling in controlling urban fugitive road dust based on TRAKER method: A case study in Baoding, China

Fugitive road dust (FRD) contributes a great deal to urban rainwater and air pollution and is commonly controlled by water-sprinkling in most Chinese cities. However, there is a lack of information on its effectiveness. We used the Testing Re-entrained Aerosol Kinetic Emissions from Roads (TRAKER) method to monitor different types of roads in Baoding city before and within 1 hr after water-sprinkling and obtained the road dirtiness index (a) and PM concentration in the road environment (T_T^*), to evaluate the removal efficiency for PM deposited on the road surface (η_a) and the reduction efficiency for the PM concentration in the road environment (η_PM). The results give that the η_a for three types of roads is ranked: branch road (87%--100%) > major arterial road (80%-83%) > minor arterial road (68%-77%), and the η_PM ranked: minor arterial road (70%) > branch road (46%-58%) > major arterial road (37%-53%). The η_a and η_PM varied non-linearly with time and presented a quadratic curve. The average effective control time (η_a> 0) was 62 min on the major and minor arterial roads, and much longer than 1 hr on branch roads. The η_PM values diminished completely by 72 min on average from the end of sprinkling for the three types of roads. Water-sprinkling can remove PM₁₀ particles from the road surface and reduce their concentration in the road environment more thoroughly than PM_2.5. Our findings could be helpful for controlling urban FRD emissions more efficiently and precisely.

Efficacy of Low-Cost Sensor Networks at Detecting Fine-Scale Variations in Particulate Matter in Urban Environments

The negative health impacts of air pollution are well documented. Not as well-documented, however, is how particulate matter varies at the hyper-local scale, and the role that proximal sources play in influencing neighborhood-scale patterns. We examined PM_2.5 variations in one airshed within Indianapolis (Indianapolis, IN, USA) by utilizing data from 25 active PurpleAir (PA) sensors involving citizen scientists who hosted all but one unit (the control), as well as one EPA monitor. PA sensors report live measurements of PM_2.5 on a crowd sourced map. After calibrating the data utilizing relative humidity and testing it against a mobile air-quality unit and an EPA monitor, we analyzed PM_2.5 with meteorological data, tree canopy coverage, land use, and various census variables. Greater proximal tree canopy coverage was related to lower PM_2.5 concentrations, which translates to greater health benefits. A 1% increase in tree canopy at the census tract level, a boundary delineated by the US Census Bureau, results in a ~0.12 µg/m³ decrease in PM_2.5, and a 1% increase in "heavy industry" results in a 0.07 µg/m³ increase in PM_2.5 concentrations. Although the overall results from these 25 sites are within the annual ranges established by the EPA, they reveal substantial variations that reinforce the value of hyper-local sensing technologies as a powerful surveillance tool.

Wearable system for outdoor air quality monitoring in a WSN with cloud computing: Design, validation and deployment

Breathing poor-quality air is a global threat at the same level as unhealthy diets or tobacco smoking, so the availability of affordable instrument for the measurement of air pollutant levels is highly relevant for human and environmental protection. We developed an air quality monitoring platform that comprises a wearable device embedding low-cost metal oxide semiconductor (MOS) gas sensors, a PM sensor, and a smartphone for collecting the data using Bluetooth Low Energy (BLE) communication. Our own developed app displays information about the air surrounding the user and sends the gathered geolocalized data to a cloud, where the users can map the air quality levels measured in the network. The resulting device is small-sized, light-weighted, compact, and belt-worn, with a user-friendly interface and a low cost. The data collected by the sensor array are validated in two experimental setups, first in laboratory-controlled conditions and then against referential pollutant concentrations measured by standard instruments in an outdoor environment. The performance of our air quality platform was tested in a field testing campaign in Barcelona with six moving devices acting as wireless sensor nodes. Devices were trained by means of machine learning algorithms to differentiate between air quality index (AQI) referential concentration values (97% success in the laboratory, 82.3% success in the field). Humidity correction was applied to all data.

Assessment of the exposure to PM2.5 in different Lebanese microenvironments at different temporal scales

The weak potential of using the sole outdoor concentrations to represent personal exposure to PM_2.5 is confirmed by the literature; therefore, it is important to account for a person's movements over time when estimating the short-term personal air pollution exposure within different microenvironments (MEs). This study is an example of applying an assessment method of the exposure to PM_2.5 in different microenvironments at different temporal scales. A low-cost particle counter (the Dylos 1700) was used; its performance was validated in comparison with equivalent instruments such the SidePak AM520 Personal Aerosol Monitor (R² = 0.89). This validation also provided a function to convert measured particle number concentrations (PNCs) into calculated particle mass concentrations. The 150 profiles that was collected on a minute-by-minute basis regarding PM_2.5 concentration from December 2018 to May 2021 highlight the influence of individual activities and contextual factors on the air quality, so that Lebanon's annual PM_2.5 mean (24.2 µg⁄m³) is 142% higher than the World Health Organization (WHO) annual mean guideline (10 µg⁄m³). Winter is the most polluted period due to the increased application of space heating devices. Additionally, the occurrence of dusty winds during the spring period leads to the elevated levels of dispersed PM_2.5. Simultaneously, the rural zones are more polluted than urban ones due to the usage of more traditional heating equipment, in addition to the usage of chemical products like pesticides and fertilizers in agricultural activities in such areas. Furthermore, the (outdoor-indoor-transport) MEs indicate that the transport and indoor MEs have similar levels of suspended fine particulates, while outdoor MEs are less polluted. Studies based on the personal exposure to PM_2.5 were generally applied on specific and limited places such as schools, workplaces, or residences. The study aims to shed light on the modern method in an attempt to estimate the personal exposure to PM_2.5 and to inspire similar studies to achieve the maximum efficiency.

Evaluation of City-Scale Disparities in PM2.5 Exposure Using Hyper-Localized Taxi-Based Mobile Monitoring

Efforts have been directed to pollution control of fine particles (PM_2.5) because exposure to PM_2.5 could result in adverse health effects. However, PM_2.5 exposure disparities persisted even with largely declined concentrations. Here, we applied taxi-based measurements to characterize hyper-localized PM_2.5 exposures (30 m resolution) in Xi'an in December 2019 and July 2020. A big data set was derived from the taxi-based measurements (∼6 × 10⁶ hourly PM_2.5) and was used to evaluate the performance of existing regulatory measurements in urban and rural regions. Results from regulatory measurements tend to alleviate PM_2.5 exposure disparities compared with taxi-based measurements. The taxi-based measurements reported higher population-weighted average (PWA) exposure in December 2019 (90 μg/m³) and July 2020 (27 μg/m³) compared to regulatory measurements (76 and 24 μg/m³ in December and July, respectively) with a wider range of relative disparities. Results indicate that the urban region would be overrepresented by regulatory measurements, where regulatory measurements reported that 60.0-84.7% of inhabitants were exposed to PM_2.5 higher than PWA, while taxi-based ones reported a smaller portion (22.6-35.2%). Significant seasonal variability in PM_2.5 exposure levels was found by taxi-based measurements but not regulatory measurements. The results highlight the need for providing complementary measurements (e.g., low-cost) for exposure assessment because the rural regions could be disproportionately exposed and overlooked by existing regulatory measurements.

Feasibility of low-cost particle sensor types in long-term indoor air pollution health studies after repeated calibration, 2019-2021

Previous studies have explored using calibrated low-cost particulate matter (PM) sensors, but important research gaps remain regarding long-term performance and reliability. Evaluate longitudinal performance of low-cost particle sensors by measuring sensor performance changes over 2 years of use. 51 low-cost particle sensors (Airbeam 1 N = 29; Airbeam 2 N = 22) were calibrated four times over a 2-year timeframe between 2019 and 2021. Cigarette smoke-specific calibration curves for Airbeam 1 and 2 PM sensors were created by directly comparing simultaneous 1-min readings of a Thermo Scientific Personal DataRAM PDR-1500 unit with a 2.5 µm inlet. Inter-sensor variability in calibration coefficient was high, particularly in Airbeam 1 sensors at study initiation. Calibration coefficients for both sensor types trended downwards over time to < 1 at final calibration timepoint [Airbeam 1 Mean (SD) = 0.87 (0.20); Airbeam 2 Mean (SD) = 0.96 (0.27)]. We lost more Airbeam 1 sensors (N = 27 out of 56, failure rate 48.2%) than Airbeam 2 (N = 2 out of 24, failure rate 8.3%) due to electronics, battery, or data output issues. Evidence suggests degradation over time might depend more on particle sensor type, rather than individual usage. Repeated calibrations of low-cost particle sensors may increase confidence in reported PM levels in longitudinal indoor air pollution studies.

Household Air Pollution Concentrations after Liquefied Petroleum Gas Interventions in Rural Peru: Findings from a One-Year Randomized Controlled Trial Followed by a One-Year Pragmatic Crossover Trial

BACKGROUND

Household air pollution (HAP) from biomass fuel combustion remains a leading environmental risk factor for morbidity worldwide.

OBJECTIVE

Measure the effect of liquefied petroleum gas (LPG) interventions on HAP exposures in Puno, Peru.

METHODS

We conducted a 1-y randomized controlled trial followed by a 1-y pragmatic crossover trial in 180 women age 25-64 y. During the first year, intervention participants received a free LPG stove, continuous fuel delivery, and regular behavioral messaging, whereas controls continued their biomass cooking practices. During the second year, control participants received a free LPG stove, regular behavioral messaging, and vouchers to obtain LPG tanks from a nearby distributor, whereas fuel distribution stopped for intervention participants. We collected 48-h kitchen area concentrations and personal exposures to fine particulate matter (PM) with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ), black carbon (BC), and carbon monoxide (CO) at baseline and 3-, 6-, 12-, 18-, and 24-months post randomization.

RESULTS

Baseline mean  [ ± standard deviation  ( SD ) ] PM 2.5 (kitchen area concentrations 1,220 ± 1,010 vs. 1,190 ± 880   μ g / m 3 ; personal exposure 126 ± 214 vs. 104 ± 100   μ g / m 3 ), CO (kitchen 53 ± 49 vs. 50 ± 41  ppm ; personal 7 ± 8 vs. 7 ± 8  ppm ), and BC (kitchen 180 ± 120 vs. 210 ± 150   μ g / m 3 ; personal 19 ± 16 vs. 21 ± 22   μ g / m 3 ) were similar between control and intervention participants. Intervention participants had consistently lower mean  ( ± SD ) concentrations at the 12-month visit for kitchen (41 ± 59   μ g / m 3 , 3 ± 6   μ g / m 3 , and 8 ± 13  ppm ) and personal exposures (26 ± 34   μ g / m 3 , 2 ± 3   μ g / m 3 , and 3 ± 4  ppm ) to PM 2.5 , BC, and CO when compared to controls during the first year. In the second year, we observed comparable HAP reductions among controls after the voucher-based intervention for LPG fuel was implemented (24-month visit PM 2.5 , BC, and CO kitchen mean concentrations of 34 ± 74   μ g / m 3 , 3 ± 5   μ g / m 3 , and 6 ± 6  ppm and personal exposures of 17 ± 15   μ g / m 3 , 2 ± 2   μ g / m 3 , and 3 ± 4  ppm , respectively), and average reductions were present among intervention participants even after free fuel distribution stopped (24-month visit PM 2.5 , BC, and CO kitchen mean concentrations of 561 ± 1,251   μ g / m 3 , 82 ± 124   μ g / m 3 , and 23 ± 28  ppm and personal exposures of 35 ± 38   μ g / m 3 , 6 ± 6   μ g / m 3 , and 4 ± 5  ppm , respectively).

DISCUSSION

Both home delivery and voucher-based provision of free LPG over a 1-y period, in combination with provision of a free LPG stove and longitudinal behavioral messaging, reduced HAP to levels below 24-h World Health Organization air quality guidelines. Moreover, the effects of the intervention on HAP persisted for a year after fuel delivery stopped. Such strategies could be applied in LPG programs to reduce HAP and potentially improve health. https://doi.org/10.1289/EHP10054.

Spatiotemporal assessment of aeromycoflora under differing urban green space, sampling height, and meteorological regimes: the atmospheric fungiscape of Thessaloniki, Greece

We studied the diversity and abundance of the airborne fungal spores in the city of Thessaloniki, Greece, for two consecutive years. Air samples were collected at one rooftop station (at 30 m) and six near-ground stations (at 1.5 m) that differed in the size and composition of adjacent green spaces. The effects of meteorological factors on airborne fungal spore concentrations were also explored. Cladosporium spores were dominant everywhere in the air of the city. The total concentration of the airborne fungal spores at 30 m was 10 times lower than near the ground. Differences in concentration and composition were far less pronounced among near-ground stations. The attributes of the fungal spore season did not change in a consistent way among stations and years. Concentrations at the near-ground stations matched the grouping of the latter into stations of high, intermediate, and low urban green space. Minimum air temperature was the primary meteorological factor affecting spore abundance, followed by relative humidity. Airborne fungal spores are more homogeneously distributed in the air of the city, but their concentrations decrease more rapidly with height than pollen.

A systematic review of the use of silicone wristbands for environmental exposure assessment, with a focus on polycyclic aromatic hydrocarbons (PAHs)

BACKGROUND

Exposure assessment is critical for connecting environmental pollutants to health outcomes and evaluating impacts of interventions or environmental policies. Silicone wristbands (SWBs) show promise for multi-pollutant exposure assessment, including polycyclic aromatic hydrocarbons (PAHs), a ubiquitous class of toxic environmental pollutants.

OBJECTIVE

To review published studies where SWBs were worn on the wrist for human environmental exposure assessments and evaluate the ability of SWBs to capture personal exposures, identify gaps which need to be addressed to implement this tool, and make recommendations for future studies to advance the field of exposure science through utilization of SWBs.

METHODS

We performed a systematic search and a cited reference search in Scopus and extracted key study descriptions.

RESULTS

Thirty-nine unique studies were identified, with analytes including PAHs, pesticides, flame retardants, and tobacco products. SWBs were shipped under ambient conditions without apparent analyte loss, indicating utility for global exposure and health studies. Nineteen articles detected a total of 60 PAHs in at least one SWB. Correlations with other concurrent biological and air measurements indicate the SWB captures exposure to flame retardants, tobacco products, and PAHs.

SIGNIFICANCE

SWBs show promise as a simple-to-deploy tool to estimate environmental and occupational exposures to chemical mixtures, including PAHs.

Establishing A Sustainable Low-Cost Air Quality Monitoring Setup: A Survey of the State-of-the-Art

Low-cost sensors (LCS) are becoming popular for air quality monitoring (AQM). They promise high spatial and temporal resolutions at low-cost. In addition, citizen science applications such as personal exposure monitoring can be implemented effortlessly. However, the reliability of the data is questionable due to various error sources involved in the LCS measurement. Furthermore, sensor performance drift over time is another issue. Hence, the adoption of LCS by regulatory agencies is still evolving. Several studies have been conducted to improve the performance of low-cost sensors. This article summarizes the existing studies on the state-of-the-art of LCS for AQM. We conceptualize a step by step procedure to establish a sustainable AQM setup with LCS that can produce reliable data. The selection of sensors, calibration and evaluation, hardware setup, evaluation metrics and inferences, and end user-specific applications are various stages in the LCS-based AQM setup we propose. We present a critical analysis at every step of the AQM setup to obtain reliable data from the low-cost measurement. Finally, we conclude this study with future scope to improve the availability of air quality data.

Fine particulate matter exposure in four transport modes of Greater Cairo

The number of daily commuters in Greater Cairo has exceeded 15 million nevertheless personal exposure studies in transport microenvironments are limited. The aim of this study is to quantify PM_2.5 exposure during peak hours in four transport modes of Greater Cairo - car (windows-open, windows-closed with recirculation and AC-on), microbus (windows-open), cycling and walking - and understand its underlying drivers. Data was collected using a pDR-1500 monitor and analysed to capture concentration variations, spatial variability, exposure doses, commuting costs versus inhaled doses, health burden and economic losses. Car with recirculation resulted in the least average PM_2.5 concentrations (32 ± 6 μg/m³), followed by walking (77 ± 35 μg/m³), car with windows-open (82 ± 32 μg/m³), microbus with windows-open (96 ± 29 μg/m³) and cycling (100 ± 28 μg/m³). Evening hours observed average PM_2.5 concentrations by 26-58% lesser than morning. Spatial variability analysis showed that 75th-90th percentile PM_2.5 concentrations coincided with congested spots. Cycling and walking lanes are rare hence commuters are exposed to surges in PM_2.5 concentrations when passing near construction and solid waste burning sites. Cycling and walking also resulted in inhaling 40-times and 32-times higher PM_2.5 dose per kilometre than for car with recirculation. Commuting by microbus cost (with windows-open) ~45% of car cost (with recirculation) but it resulted in 4-times higher inhaled PM_2.5 dose. As expected due to the lowest PM_2.5 exposure concentrations, health burden resulting from car travel (with recirculation) caused the least death rates of 0.07 (95% CI 0.07-0.08) prematures deaths per 100,000 commuters/year while microbus with windows-open resulted in the highest death rates; 0.52 (95% CI 0.49-0.56). Microbus deaths represent 57% of national economic losses due to PM_2.5 exposure amongst the four transport modes. This study provides real-time exposure data and analyses its implications on commuter health as a first step in informed decision-making and better urban planning.

Techniques to measure particulate matter emissions from stationary sources: A critical technology review using Multi Criteria Decision Analysis (MCDA)

This review article presents an overview of the commercially available methods to measure particulate matter (PM) from stationary sources, focusing on techniques to measure mass concentration. Mass concentration is the requirement for the majority of current regulations not only in the UK and Europe but also Worldwide. The process of particulate emission monitoring has been used and developed over the last 30 years as a result of increasing demands of legislation development and clean air initiatives. When deciding upon the measurement technique, the operator must consider; range of device, portability, usability, installation requirements, expected concentration, purpose of measurement, particle characteristics, cost and diameter of stack. This review aims to; give direction to operators looking for a measurement technique to measure mass concentration of particulate matter emissions, give direction to researchers working within the field of particulate measurement with a view to improving existing and developing new techniques and give strategy for selection of equipment. A literature review, industrial survey and Multi Criteria Decision Analysis (MCDA) were used for comprehensive analysis of nine measurement techniques operating in a full range of applications, highlighting the importance of matching a suitable device with the intended application. There is currently no suitable method available to measure mass both directly and continuously, resulting in using either the Standard Reference Method (SRM) or a continuous particulate monitor which requires calibration to its application using the SRM to obtain meaningful results. There is currently no single continuous particulate monitor available suitable for all applications.

Miniaturizing Wet Scrubbers for Aerosolized Droplet Capture

Aerosols dispersed and transmitted through the air (e.g., particulate matter pollution and bioaerosols) are ubiquitous and one of the leading causes of adverse health effects and disease transmission. A variety of sampling methods (e.g., filters, cyclones, and impactors) have been developed to assess personal exposures. However, a gap still remains in the accessibility and ease-of-use of these technologies for people without experience or training in collecting airborne samples. Additionally, wet scrubbers (large non-portable industrial systems) utilize liquid sprays to remove aerosols from the air; the goal is to "scrub" (i.e., clean) the exhaust of industrial smokestacks, not collect the aerosols for analysis. Inspired by wet scrubbers, we developed a device fundamentally different from existing portable air samplers by using aerosolized microdroplets to capture aerosols in personal spaces (e.g., homes, offices, and schools). Our aerosol-sampling device is the size of a small teapot, can be operated without specialized training, and features a winding flow path in a supersaturated relative humidity environment, enabling droplet growth. The integrated open mesofluidic channels shuttle coalesced droplets to a collection chamber for subsequent sample analysis. Here, we present the experimental demonstration of aerosol capture in water droplets. An iterative study optimized the non-linear flow manipulating baffles and enabled an 83% retention of the aerosolized microdroplets in the confined volume of our device. As a proof-of-concept for aerosol capture into a liquid medium, 0.5-3 μm model particles were used to evaluate aerosol capture efficiency. Finally, we demonstrate that the device can capture and keep a bioaerosol (bacteriophage MS2) viable for downstream analysis.

Assessment of Low-Cost Particulate Matter Sensor Systems against Optical and Gravimetric Methods in a Field Co-Location in Norway

The increased availability of commercially-available low-cost air quality sensors combined with increased interest in their use by citizen scientists, community groups, and professionals is resulting in rapid adoption, despite data quality concerns. We have characterized three out-the-box PM sensor systems under different environmental conditions, using field colocation against reference equipment. The sensor systems integrate Plantower 5003, Sensirion SPS30 and Alphasense OCP-N3 PM sensors. The first two use photometry as a measuring technique, while the third one is an optical particle counter. For the performance evaluation, we co-located 3 units of each manufacturer and compared the results against optical (FIDAS) and gravimetric (KFG) methods for a period of 7 weeks (28 August to 19 October 2020). During the period from 2nd and 5th October, unusually high PM concentrations were observed due to a long-range transport episode. The results show that the highest correlations between the sensor systems and the optical reference are observed for PM1, with coefficients of determination above 0.9, followed by PM2.5. All the sensor units struggle to correctly measure PM10, and the coefficients of determination vary between 0.45 and 0.64. This behavior is also corroborated when using the gravimetric method, where correlations are significantly higher for PM2.5 than for PM10, especially for the sensor systems based on photometry. During the long range transport event the performance of the photometric sensors was heavily affected, and PM10 was largely underestimated. The sensor systems evaluated in this study had good agreement with the reference instrumentation for PM1 and PM2.5; however, they struggled to correctly measure PM10. The sensors also showed a decrease in accuracy when the ambient size distribution was different from the one for which the manufacturer had calibrated the sensor, and during weather conditions with high relative humidity. When interpreting and communicating air quality data measured using low-cost sensor systems, it is important to consider such limitations in order not to risk misinterpretation of the resulting data.

Biomonitoring of Ambient Outdoor Air Pollutant Exposure in Humans Using Targeted Serum Albumin Adductomics

Outdoor air pollution, a spatially and temporally complex mixture, is a human carcinogen. However, ambient measurements may not reflect subject-level exposures, personal monitors do not assess internal dose, and spot assessments of urinary biomarkers may not recapitulate chronic exposures. Nucleophilic sites in serum albumin-particularly the free thiol at Cys³⁴-form adducts with electrophiles. Due to the 4-week lifetime of albumin in circulation, accumulating adducts can serve as intermediate- to long-residence biomarkers of chronic exposure and implicate potential biological effects. Employing nanoflow liquid chromatography-high-resolution mass spectrometry (nLC-HRMS) and parallel reaction monitoring (PRM), we have developed and validated a novel targeted albumin adductomics platform capable of simultaneously monitoring dozens of Cys³⁴ adducts per sample in only 2.5 μL of serum, with on-column limits of detection in the low-femtomolar range. Using this platform, we characterized the magnitude and impact of ambient outdoor air pollution exposures with three repeated measurements over 84 days in n = 26 nonsmoking women (n = 78 total samples) from Qidong, China, an area with a rising burden of lung cancer incidence. In concordance with seasonally rising ambient concentrations of NO₂, SO₂, and PM₁₀ measured at stationary monitors, we observed elevations in concentrations of Cys³⁴ adducts of benzoquinone (p < 0.05), benzene diol epoxide (BDE; p < 0.05), crotonaldehyde (p < 0.01), and oxidation (p < 0.001). Regression analysis revealed significant elevations in oxidation and BDE adduct concentrations of 300% to nearly 700% per doubling of ambient airborne pollutant levels (p < 0.05). Notably, the ratio of irreversibly oxidized to reduced Cys³⁴ rose more than 3-fold during the 84-day period, revealing a dramatic perturbation of serum redox balance and potentially serving as a portent of increased pollution-related mortality risk. Our targeted albumin adductomics assay represents a novel and flexible approach for sensitive and multiplexed internal dosimetry of environmental exposures, providing a new strategy for personalized biomonitoring and prevention.

Development of low-cost indoor air quality monitoring devices: Recent advancements

The use of low-cost sensor technology to monitor air pollution has made remarkable strides in the last decade. The development of low-cost devices to monitor air quality in indoor environments can be used to understand the behaviour of indoor air pollutants and potentially impact on the reduction of related health impacts. These user-friendly devices are portable, require low-maintenance, and can enable near real-time, continuous monitoring. They can also contribute to citizen science projects and community-driven science. However, low-cost sensors have often been associated with design compromises that hamper data reliability. Moreover, with the rapidly increasing number of studies, projects, and grey literature based on low-cost sensors, information got scattered. Intending to identify and review scientifically validated literature on this topic, this study critically summarizes the recent research pertinent to the development of indoor air quality monitoring devices using low-cost sensors. The method employed for this review was a thorough search of three scientific databases, namely: ScienceDirect, IEEE, and Scopus. A total of 891 titles published since 2012 were found and scanned for relevance. Finally, 41 research articles consisting of 35 unique device development projects were reviewed with a particular emphasis on device development: calibration and performance of sensors, the processor used, data storage and communication, and the availability of real-time remote access of sensor data. The most prominent finding of the study showed a lack of studies consisting of sensor performance as only 16 out of 35 projects performed calibration/validation of sensors. An even fewer number of studies conducted these tests with a reference instrument. Hence, a need for more studies with calibration, credible validation, and standardization of sensor performance and assessment is recommended for subsequent research.

STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part 1-Basic theory and simple methods of adjustment

Measurement error and misclassification of variables frequently occur in epidemiology and involve variables important to public health. Their presence can impact strongly on results of statistical analyses involving such variables. However, investigators commonly fail to pay attention to biases resulting from such mismeasurement. We provide, in two parts, an overview of the types of error that occur, their impacts on analytic results, and statistical methods to mitigate the biases that they cause. In this first part, we review different types of measurement error and misclassification, emphasizing the classical, linear, and Berkson models, and on the concepts of nondifferential and differential error. We describe the impacts of these types of error in covariates and in outcome variables on various analyses, including estimation and testing in regression models and estimating distributions. We outline types of ancillary studies required to provide information about such errors and discuss the implications of covariate measurement error for study design. Methods for ascertaining sample size requirements are outlined, both for ancillary studies designed to provide information about measurement error and for main studies where the exposure of interest is measured with error. We describe two of the simpler methods, regression calibration and simulation extrapolation (SIMEX), that adjust for bias in regression coefficients caused by measurement error in continuous covariates, and illustrate their use through examples drawn from the Observing Protein and Energy (OPEN) dietary validation study. Finally, we review software available for implementing these methods. The second part of the article deals with more advanced topics.

Personal strategies to minimise effects of air pollution on respiratory health: advice for providers, patients and the public

As global awareness of air pollution rises, so does the imperative to provide evidence-based recommendations for strategies to mitigate its impact. While public policy has a central role in reducing air pollution, exposure can also be reduced by personal choices. Qualified evidence supports limiting physical exertion outdoors on high air pollution days and near air pollution sources, reducing near-roadway exposure while commuting, utilising air quality alert systems to plan activities, and wearing facemasks in prescribed circumstances. Other strategies include avoiding cooking with solid fuels, ventilating and isolating cooking areas, and using portable air cleaners fitted with high-efficiency particulate air filters. We detail recommendations to assist providers and public health officials when advising patients and the public regarding personal-level strategies to mitigate risk imposed by air pollution, while recognising that well-designed prospective studies are urgently needed to better establish and validate interventions that benefit respiratory health in this context.

The evaluation and optimization of calibration methods for low-cost particulate matter sensors: Inter-comparison between fixed and mobile methods

With the development of the air pollution control, the low-cost sensors are widely used in air quality monitoring, while the data quality of these sensors is always the most concern for users. In this study, data from nine air monitoring stations with standard PM instruments were used as reference and compared with the data of mobile and fixed PM sensors in Jinan, the capital city of Shandong Province, China. Data quality of PM sensors was checked by the cross-comparison among standard method, fixed and mobile sensors. And the impacts of relative humidity and size distribution (PM_2.5/PM₁₀) on the performance of PM sensors were evaluated as well. To optimize the calibration method for both fixed and mobile PM sensors, a two-step model was designed, in which the RH and PM_2.5/PM₁₀ ratio were both used as input parameters. We firstly calibrated the sensors with five independent models, and then all the calibrated data were linearly fitted by the LR-final model. In comparison with standard instruments, the LR-final model increased the R² values of the PM_2.5 and PM₁₀ measured by fixed sensors from 0.89 and 0.79 to 0.98 and 0.97, respectively. The R² values of PM_2.5 and PM₁₀ measured by the mobile sensors both increased to 0.99 from 0.79 and 0.62. Overall, the two-step calibration model appeared to be a promising approach to solve the poor performance of low-cost sensors.

Comparison of next-generation portable pollution monitors to measure exposure to PM2.5 from household air pollution in Puno, Peru

Assessment of personal exposure to PM_2.5 is critical for understanding intervention effectiveness and exposure-response relationships in household air pollution studies. In this pilot study, we compared PM_2.5 concentrations obtained from two next-generation personal exposure monitors (the Enhanced Children MicroPEM or ECM; and the Ultrasonic Personal Air Sampler or UPAS) to those obtained with a traditional Triplex Cyclone and SKC Air Pump (a gravimetric cyclone/pump sampler). We co-located cyclone/pumps with an ECM and UPAS to obtain 24-hour kitchen concentrations and personal exposure measurements. We measured Spearmen correlations and evaluated agreement using the Bland-Altman method. We obtained 215 filters from 72 ECM and 71 UPAS co-locations. Overall, the ECM and the UPAS had similar correlation (ECM ρ = 0.91 vs UPAS ρ = 0.88) and agreement (ECM mean difference of 121.7 µg/m³ vs UPAS mean difference of 93.9 µg/m³ ) with overlapping confidence intervals when compared against the cyclone/pump. When adjusted for the limit of detection, agreement between the devices and the cyclone/pump was also similar for all samples (ECM mean difference of 68.8 µg/m³ vs UPAS mean difference of 65.4 µg/m³ ) and personal exposure samples (ECM mean difference of -3.8 µg/m³ vs UPAS mean difference of -12.9 µg/m³ ). Both the ECM and UPAS produced comparable measurements when compared against a cyclone/pump setup.

Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution

Airborne particulate matter (PM) exposure has been identified as a key environmental risk factor, associated especially with diseases of the respiratory and cardiovascular system and with almost 9 million premature deaths per year. Low-cost optical sensors for PM measurement are desirable for monitoring exposure closer to the personal level and particularly suited for developing spatiotemporally dense city sensor networks. However, questions remain over the accuracy and reliability of the data they produce, particularly regarding the influence of environmental parameters such as humidity and temperature, and with varying PM sources and concentration profiles. In this study, eight units each of five different models of commercially available low-cost optical PM sensors (40 individual sensors in total) were tested under controlled laboratory conditions, against higher-grade instruments for: lower limit of detection, response time, responses to sharp pollution spikes lasting <1 min , and the impact of differing humidity and PM source. All sensors detected the spikes generated with a varied range of performances depending on the model and presenting different sensitivity mainly to sources of pollution and to size distributions with a lesser impact of humidity. The sensitivity to particle size distribution indicates that the sensors may provide additional information to PM mass concentrations. It is concluded that improved performance in field monitoring campaigns, including tracking sources of pollution, could be achieved by using a combination of some of the different models to take advantage of the additional information made available by their differential response.

Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data

Low-cost sensors can be used to improve the temporal and spatial resolution of an individual's particulate matter (PM) intake dose assessment. In this work, personal activity monitors were used to measure heart rate (proxy for minute ventilation), and low-cost PM sensors were used to measure concentrations of PM. Intake dose was assessed as a product of PM concentration and minute ventilation, using four models with increasing complexity. The two models that use heart rate as a variable had the most consistent results and showed a good response to variations in PM concentrations and heart rate. On the other hand, the two models using generalized population data of minute ventilation expectably yielded more coarse information on the intake dose. Aggregated weekly intake doses did not vary significantly between the models (6-22%). Propagation of uncertainty was assessed for each model, however, differences in their underlying assumptions made them incomparable. The most complex minute ventilation model, with heart rate as a variable, has shown slightly lower uncertainty than the model using fewer variables. Similarly, among the non-heart rate models, the one using real-time activity data has less uncertainty. Minute ventilation models contribute the most to the overall intake dose model uncertainty, followed closely by the low-cost personal activity monitors. The lack of a common methodology to assess the intake dose and quantifying related uncertainties is evident and should be a subject of further research.

Personal exposure to NO2 and benzene in the Cape Town region of South Africa is associated with shorter leukocyte telomere length in women

Air pollution exposure is a major global health concern and has been associated with molecular aging. Unfortunately, the situation has not received much attention in the African region. The aim of this study was to investigate whether current personal ambient NO₂ and benzene, toluene, ethyl-benzene and xylenes (ortho (o)-, meta (m)- and para (p)-xylene (BTEX) exposure is associated with leukocyte telomere length (LTL), a marker of molecular ageing, in apparently healthy women (mean ± SD age: 42.5 ± 13.4 years) residing in the Cape Town region of South Africa. The repeated measures study collected data from 61 women. Seven-day median (interquartile range (IQR)) personal NO₂ and BTEX exposure levels were determined via compact passive diffusion samplers carried on the person prior to baseline (NO₂: 14.2 (9.4-17.2) μg/m³; Benzene: 3.1 (2.1-5.3) μg/m³) and 6-month follow-up (NO₂: 10.6 (6.6-13.6) μg/m³; Benzene: 2.2 (1.3-4.9) μg/m³) visits. LTL was measured at baseline and follow-up using a real-time PCR method. Multiple linear mixed model analyses (adjusting for age, body mass index, smoking, employment status, level of education and assessment visit) showed that each IQR increment increase in NO₂ (7.0 μg/m³) and benzene (3.3 μg/m³) was associated with -7.30% (95% CI: -10.98 to -3.46%; p < 0.001) and -6.78% (95% CI: -11.88 to -1.39%; p = 0.015) difference in LTL, respectively. The magnitude of these effects of NO₂ and benzene corresponds to the effect of an increase of 10.3- and 6.0-year in chronological age on LTL. Our study shows that personal exposures to NO₂ and benzene are associated with molecular ageing as indicated by LTL in healthy women residing in the Cape Town region.

Biomarkers of exposure, effect, and susceptibility in occupational exposure to traffic-related air pollution: A review

There is a well-recognized association between environmental air pollution exposure and several human diseases. However, the relationship between diseases related to occupational air pollution exposure on roads and high levels of traffic-related air pollutants (TRAPs) is less substantiated. Biomarkers are essential tools in environmental and occupational toxicology, and studies on new biomarkers are increasingly relevant due to the need to determine early biomarkers to be assessed in exposure conditions. This review aimed to investigate the main advances in the biomonitoring of subjects occupationally exposed to air pollution, as well as to summarize the biomarkers of exposure, effect, and susceptibility. Furthermore, we discuss how biomarkers could be used to complement the current application of methods used to assess occupational exposures to xenobiotics present in air pollution. The databases used in the preparation of this review were PubMed, Scopus, and Science Direct. Considering the significant deleterious effects on health associated with chronic occupational exposure to xenobiotics, this topic deserves attention. As it is difficult to avoid occupational exposure to TRAPs, biomonitoring should be applied as a strategy to reduce the toxic effects of workplace exposure.

Schoolchildren's personal exposure to ultrafine particles in and near Accra, Ghana

Exposure to air pollution is a significant health risk, and children who are exposed to it are likely to have lifelong consequences. Ultrafine particles (UFPs) are emitted by all combustion sources, and can be used as a proxy for the presence of combustion products. The present study, the first of its kind to be conducted in Africa, assessed schoolchildren's exposure to UFPs, and apportioned their daily exposure to seven different microenvironments that they inhabited on a typical school day. The personal exposure of 61 pupils attending three junior high schools was measured for 24 h each using wearable monitors over a period of 10 weeks. Two of the schools were located in suburbs of Accra and the third in Berekuso, a nearby rural community. The results of our study revealed the complex nature of children's UFP exposure and its overall high to very high levels, significantly influenced by the locality (suburb) of residence and the type of activities in which the children were engaged. The mean (±standard error) daily exposure to UFPs (cm^-3) was6.9×10⁴(±6.8×10³),4.9(±1.0)×10⁴ and 1.6×10⁴±1.9×10³for pupils attending the Ashia Mills, Faith Baptist and Berekuso Basic Schools, respectively. Pupils attending the schools in urban Accra received higher exposure than those attending the school in the rural environment of Berekuso. The highest mean microenvironmental exposure was registered in the Home other microenvironment in an urban school and in Bedroom in another urban school and the rural school. The high exposure in Home other was due to pupils conducting trash burning and encountering environmental tobacco smoke, and the high exposure in Bedroom microenvironment was due to the burning of mosquito coils at night to prevent malaria. The principal sources that heightened exposure to UFPs were emissions from cooking (using firewood and charcoal), vehicular traffic and combustion of biomass and trash. All pupils recorded the highest exposure intensity in the Kitchen microenvironment.

Sources of error and variability in particulate matter sensor network measurements

The quality of mass concentration estimates from increasingly popular networks of low-cost particulate matter sensors depends on accurate conversion of sensor output (e.g., voltage) into gravimetric-equivalent mass concentration, typically using a calibration procedure. This study evaluates two important sources of variability that lead to error in estimating gravimetric-equivalent mass concentration: the temporal changes in sensor calibration and the spatial and temporal variability in gravimetric correction factors. A 40-node sensor network was deployed in a heavy vehicle manufacturing facility for 8 months. At a central location in the facility, particulate matter was continuously measured with three sensors of the network and a traditional, higher-cost photometer, determining the calibration slope and intercept needed to translate sensor output to photometric-equivalent mass concentration. Throughout the facility, during three intensive sampling campaigns, respirable mass concentrations were measured with gravimetric samplers and photometers to determine correction factors needed to adjust photometric-equivalent to gravimetric-equivalent mass concentration. Both field-determined sensor calibration slopes and intercepts were statistically different than those estimated in the laboratory (α = 0.05), emphasizing the importance of aerosol properties when converting voltage to photometric-equivalent mass concentration and the need for field calibration to determine slope. Evidence suggested the sensors' weekly field calibration slope decreased and intercept increased, indicating the sensors were deteriorating over time. The mean correction factor in the cutting and shot blasting area (2.9) was substantially and statistically lower than that in the machining and welding area (4.6; p = 0.01). Therefore, different correction factors should be determined near different occupational processes to accurately estimate particle mass concentrations.

Demonstration of a Low-Cost Multi-Pollutant Network to Quantify Intra-Urban Spatial Variations in Air Pollutant Source Impacts and to Evaluate Environmental Justice

Air quality monitoring has traditionally been conducted using sparsely distributed, expensive reference monitors. To understand variations in PM_2.5 on a finely resolved spatiotemporal scale a dense network of over 40 low-cost monitors was deployed throughout and around Pittsburgh, Pennsylvania, USA. Monitor locations covered a wide range of site types with varying traffic and restaurant density, varying influences from local sources, and varying socioeconomic (environmental justice, EJ) characteristics. Variability between and within site groupings was observed. Concentrations were higher near the source-influenced sites than the Urban or Suburban Residential sites. Gaseous pollutants (NO₂ and SO₂) were used to differentiate between traffic (higher NO₂ concentrations) and industrial (higher SO₂ concentrations) sources of PM_2.5. Statistical analysis proved these differences to be significant (coefficient of divergence > 0.2). The highest mean PM_2.5 concentrations were measured downwind (east) of the two industrial facilities while background level PM_2.5 concentrations were measured at similar distances upwind (west) of the point sources. Socioeconomic factors, including the fraction of non-white population and fraction of population living under the poverty line, were not correlated with increases in PM_2.5 or NO₂ concentration. The analysis conducted here highlights differences in PM_2.5 concentration within site groupings that have similar land use thus demonstrating the utility of a dense sensor network. Our network captures temporospatial pollutant patterns that sparse regulatory networks cannot.

Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environment

Exposure to ambient particulate matter (PM) air pollution is a leading risk factor for morbidity and mortality, associated with up to 8.9 million deaths/year worldwide. Measurement of personal exposure to PM is hindered by poor spatial resolution of monitoring networks. Low-cost PM sensors may improve monitoring resolution in a cost-effective manner but there are doubts regarding data reliability. PM sensor boxes were constructed using four low-cost PM micro-sensor models. Three boxes were deployed at each of two schools in Southampton, UK, for around one year and sensor performance was analysed. Comparison of sensor readings with a nearby background station showed moderate to good correlation (0.61 < r < 0.88, p < 0.0001), but indicated that low-cost sensor performance varies with different PM sources and background concentrations, and to a lesser extent relative humidity and temperature. This may have implications for their potential use in different locations. Data also indicates that these sensors can track short-lived events of pollution, especially in conjunction with wind data. We conclude that, with appropriate consideration of potential confounding factors, low-cost PM sensors may be suitable for PM monitoring where reference-standard equipment is not available or feasible, and that they may be useful in studying spatially localised airborne PM concentrations.

Monitoring secondhand tobacco smoke remotely in real-time: A simple low-cost approach

INTRODUCTION

Secondhand smoke (SHS) in the home is a serious cause of ill-health, especially for children. SHS indoors can be indirectly measured using particulate matter monitors, and interventions have been developed using feedback from these monitors to encourage smoke-free homes. These interventions often use data that are several days out of date, as the data must be downloaded manually from monitors. It would be advantageous to access this information remotely in real-time to provide faster feedback to intervention participants.

METHODS

Using off-the-shelf computer components and the Dylos DC1700 air quality monitor, a portable internet-connected monitor was developed that can send data to a server remotely. Four of these monitors were tested in homes in Israel to test the reliability of the connection. Data were downloaded from the monitor's onboard memory and compared to the data sent to the server.

RESULTS

Eight homes were monitored for 4 to 6 days, with a combined total count of 44 days. Less than 1% of data was lost, with no outage lasting longer than 1 hour 45 minutes. There was no significant difference in the mean concentrations measured in homes between mobile-transmitted data and data downloaded directly.

CONCLUSIONS

This system appears to be a reliable way to monitor remotely home air quality for use in intervention studies, and could potentially have applications in other related research. Laboratories that own Dylos DC1700s may wish to consider converting them to such a system to obtain a cost-effective way of overcoming limitations in the Dylos design.

City Scale Particulate Matter Monitoring Using LoRaWAN Based Air Quality IoT Devices

Air Quality (AQ) is a very topical issue for many cities and has a direct impact on citizen health. The AQ of a large UK city is being investigated using low-cost Particulate Matter (PM) sensors, and the results obtained by these sensors have been compared with government operated AQ stations. In the first pilot deployment, six AQ Internet of Things (IoT) devices have been designed and built, each with four different low-cost PM sensors, and they have been deployed at two locations within the city. These devices are equipped with LoRaWAN wireless network transceivers to test city scale Low-Power Wide Area Network (LPWAN) coverage. The study concludes that (i) the physical device developed can operate at a city scale; (ii) some low-cost PM sensors are viable for monitoring AQ and for detecting PM trends; (iii) LoRaWAN is suitable for city scale sensor coverage where connectivity is an issue. Based on the findings from this first pilot project, a larger LoRaWAN enabled AQ sensor network is being deployed across the city of Southampton in the UK.

Wearable sensors for multifactorial personal exposure measurements - A ranking study

Individuals are simultaneously exposed to multiple environmental stressors during their daily life. Studies of adverse health effects and their etiology as well as recommendations for a healthier life style demand for an assessment of multifactorial personal exposure, according to the exposome concept. A challenge is to record exposure while people are moving in heterogeneous urban environments. Therefore wearable sensor technologies are becoming a promising way to measure personal exposure continuously: indoors, outdoors and even on the move. So far, studies which test the accuracy and usability of wearable sensors for multiple stressors are lacking. Performance evaluations are important and should take place beforehand, especially to ensure the success of citizens-oriented studies. For the first time we rigorously examined the accuracy and application suitability of wearable sensors for acoustic noise, heat (temp), particle number counts (PNC) and geo-location (GPS) in different environments. We present an extensive device inter-comparison and a ranking of the sensors based on performance measures, Taylor diagrams, Bland-Altman plots, and ease-of-use aspects. The sensors showed moderate to high correlations with precision reference devices (r = 0.4-0.99). Differences between errors outdoors and indoors suggest that environmental conditions have impact upon the accuracy of the sensors. Reaction time, recording interval, and sensor ventilation are features that play a crucial role for both ease-of-use and accuracy. We conclude with a final performance () ranking: (GPS) >  (noise) >  (temp) >  (PNC). The results are relevant for future epidemiological studies of multifactorial exposure of individuals and their health and should guide the selection of wearables when persons are involved that are technically untaught. Inferences from multifactorial data are based on the performance of all sensors and the weakest chain links are PNC and temp sensors for which our article recommends urgent improvements.

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.

Assessment of exposure to air pollution in children: Determining whether wearing a personal monitor affects physical activity

Personal air pollution monitoring in research studies should not interfere with usual patterns of behavior and bias results. In an urban pediatric cohort study we tested whether wearing an air monitor impacted activity time based on continuous watch-based accelerometry. The majority (71%) reported that activity while wearing the monitor mimicked normal activity. Correspondingly, variation in activity while wearing versus not wearing the monitor did not differ greatly from baseline variation in activity (P = 0.84).

Particle Concentrations in Occupational Settings Measured with a Nanoparticle Respiratory Deposition (NRD) Sampler

There is an increasing need to evaluate concentrations of nanoparticles in occupational settings due to their potential negative health effects. The Nanoparticle Respiratory Deposition (NRD) personal sampler was developed to collect nanoparticles separately from larger particles in the breathing zone of workers, while simultaneously providing a measure of respirable mass concentration. This study compared concentrations measured with the NRD sampler to those measured with a nano Micro Orifice Uniform-Deposit Impactor (nanoMOUDI) and respirable samplers in three workplaces. The NRD sampler performed well at two out of three locations, where over 90% of metal particles by mass were submicrometer particle size (a heavy vehicle machining and assembly facility and a shooting range). At the heavy vehicle facility, the mean metal mass concentration of particles collected on the diffusion stage of the NRD was 42.5 ± 10.0 µg/m3, within 5% of the nanoMOUDI concentration of 44.4 ± 7.4 µg/m3. At the shooting range, the mass concentration for the diffusion stage of the NRD was 5.9 µg/m3, 28% above the nanoMOUDI concentration of 4.6 µg/m3. In contrast, less favorable results were obtained at an iron foundry, where 95% of metal particles by mass were larger than 1 µm. The accuracy of nanoparticle collection by NRD diffusion stage may have been compromised by high concentrations of coarse particles at the iron foundry, where the NRD collected almost 5-fold more nanoparticle mass compared to the nanoMOUDI on one sampling day and was more than 40% different on other sampling days. The respirable concentrations measured by NRD samplers agreed well with concentrations measured by respirable samplers at all sampling locations. Overall, the NRD sampler accurately measured concentrations of nanoparticles in industrial environments when concentrations of large, coarse mode, particles were low.

Evaluation of micro-well collector for capture and analysis of aerosolized Bacillus subtilis spores

Bioaerosol sampling and identification are vital for the assessment and control of airborne pathogens, allergens, and toxins. In-situ analysis of chemical and biological particulate matter can significantly reduce the costs associated with sample preservation, transport, and analysis. The analysis of conventional filters is challenging, due to dilute samples in large collection regions. A low-cost cartridge for collection and analysis of aerosols is developed for use in epidemiological studies and personal exposure assessments. The cartridge collects aerosol samples in a micro-well which reduces particles losses due to the bounce and does not require any coating. The confined particle collection area (dwell~1.4 mm) allows reducing the elution volume for subsequent analysis. The performance of the cartridge is validated in laboratory studies using aerosolized bacterial spores (Bacillus subtilis). Colony forming unit analysis is used for bacterial spore enumeration. Cartridge collection efficiency is evaluated by comparison with the reference filters and found to be consistent with tested flow rates. Sample recovery for the pipette elution is ~80%. Due to the high density of the collected sample, the cartridge is compatible with in-situ spectroscopic analysis and sample elution into the 10-20 μl liquid volume providing a significant increase in sample concentration for subsequent analysis.

Trade-offs of Personal Versus More Proxy Exposure Measures in Environmental Epidemiology

The technological ability to make personal measurements of toxicant exposures is growing rapidly. While this can decrease measurement error and therefore help reduce attenuation of effect estimates, we argue that as measures of exposure or dose become more personal, threats to validity of study findings can increase in ways that more proxy measures may avoid. We use directed acyclic graphs (DAGs) to describe conditions where confounding is introduced by use of more personal measures of exposure and avoided via more proxy measures of personal exposure or target tissue dose. As exposure or dose estimates are more removed from the individual, they become less susceptible to biases from confounding by personal factors that can often be hard to control, such as personal behaviors. Similarly, more proxy exposure estimates are less susceptible to reverse causation. We provide examples from the literature where adjustment for personal factors in analyses that use more proxy exposure estimates have little effect on study results. In conclusion, increased personalized exposure assessment has important advantages for measurement accuracy, but it can increase the possibility of biases from personal factors and reverse causation compared with more proxy exposure estimates. Understanding the relation between more and less proxy exposures, and variables that could introduce confounding are critical components to study design.

Performance of low-cost monitors to assess household air pollution

Exposure to household air pollution is a leading cause of morbidity and mortality globally. However, due to the lack of validated low-cost monitors with long-lasting batteries in indoor environments, most epidemiologic studies use self-reported data or short-term household air pollution assessments as proxies of long-term exposure. We evaluated the performance of three low-cost monitors measuring fine particulate matter (PM_2.5) and carbon monoxide (CO) in a wood-combustion experiment conducted in one household of Spain for 5 days (including the co-location of 2 units of HAPEX and 3 units of TZOA-R for PM_2.5 and 3 units of EL-USB-CO for CO; a total of 40 unit-days). We used Spearman correlation (ρ) and Concordance Correlation Coefficient (CCC) to assess accuracy of low-cost monitors versus equivalent research-grade devices. We also conducted a field study in India for 1 week (including HAPEX in 3 households and EL-USB-CO in 4 households; a total of 49 unit-days). Correlation and agreement at 5-min were moderate-high for one unit of HAPEX (ρ = 0.73 / CCC = 0.59), for one unit of TZOA-R (ρ = 0.89 / CCC = 0.62) and for three units of EL-USB-CO (ρ = 0.82-0.89 / CCC = 0.66-0.91) in Spain, although the failure or malfunction rate among low-cost units was high in both settings (60% of unit-days in Spain and 43% in India). Low-cost monitors tested here are not yet ready to replace more established exposure assessment methods in long-term household air pollution epidemiologic studies. More field validation is needed to assess evolving sensors and monitors with application to health studies.

Effects of personal air pollution exposure on asthma symptoms, lung function and airway inflammation

BACKGROUND

There is evidence that air pollution increases the risk of asthma hospitalizations and healthcare utilization, but the effects on day-to-day asthma control are not fully understood.

OBJECTIVE

We undertook a prospective single-centre panel study to test the hypothesis that personal air pollution exposure is associated with asthma symptoms, lung function and airway inflammation.

METHODS

Thirty-two patients with a clinical diagnosis of asthma were provided with a personal air pollution monitor (Cairclip NO₂ /O₃ ) which was kept on or around their person throughout the 12-week follow-up period. Ambient levels of NO₂ and particulate matter were modelled based upon satellite imaging data. Directly measured ozone, NO₂ and particulate matter levels were obtained from a monitoring station in central Leicester. Participants made daily electronic records of asthma symptoms, peak expiratory flow and exhaled nitric oxide. Spirometry and asthma symptom questionnaires were completed at fortnightly study visits. Data were analysed using linear mixed effects models and cross-correlation.

RESULTS

Cairclip exposure data were of good quality with clear evidence of diurnal variability and a missing data rate of approximately 20%. We were unable to detect consistent relationships between personal air pollution exposure and clinical outcomes in the group as a whole. In an exploratory subgroup analysis, total oxidant exposure was associated with increased daytime symptoms in women but not men.

CONCLUSIONS AND CLINICAL RELEVANCE

We did not find compelling evidence that air pollution exposure impacts on day-to-day clinical control in an unselected asthma population, but further studies are required in larger populations with higher exposure levels. Women may be more susceptible than men to the effects of air pollution, an observation which requires confirmation in future studies.

Carbon load in airway macrophages as a biomarker of exposure to particulate air pollution; a longitudinal study of an international Panel

Background

Carbon load in airway macrophages (AM) has been proposed as an internal marker to assess long-term exposure to combustion-derived pollutant particles. However, it is not known how this biomarker is affected by changes in exposure. We studied the clearance kinetics of black carbon (BC) in AM, obtained by sputum induction, in a one-year panel study.

Methods

AM BC was measured 8 times with 6 weeks intervals in healthy young subjects: 15 long-term residents in Leuven, Belgium (BE, mean annual PM₁₀ 20–30 μg/m³) and 30 newcomers having arrived recently (< 3 weeks) in Leuven from highly polluted cities (mean annual PM₁₀ > 50 μg/m³) in low and middle-income countries (LMIC, n = 15), or from low to moderately polluted cities in high-income countries (HIC, n = 15). The median and 90th percentile values of AM BC were quantified by image analysis of 25 macrophages per sputum sample; the carbonaceous nature of the black inclusions in AM was verified by Femtosecond Pulsed Laser Microscopy in 30 macrophages. We used a Bayesian hierarchical single-exponential decay model to describe the evolution of AM BC.

Results

In the LMIC group, the mean (95% credible interval) initial quantity (R₀) of median AM BC [1.122 (0.750–1.509) μm²] was higher than in the HIC group [0.387 (0.168–0.613) μm²] and BE group [0.275 (0.147–0.404) μm²]. Median AM BC content decreased in the LMIC group (decay constant 0.013 μm²/day), but remained stable over one year in the other two groups. In the LMIC group, clearance half-lives of 53 (30–99) and 116 (63–231) days, were calculated for median and 90th percentile AM BC, respectively.

Conclusions

In this real-life study of an international panel of healthy young subjects, we demonstrated that carbon load in airway macrophages obtained by induced sputum reflects past long-term exposure to particulate air pollution. Values of AM BC do not change over one year when exposure remains stable, but AM BC decreases upon moving from high to moderate exposure, with average half-lives of 53 and 116 days depending on the carbon load.

Electronic supplementary material

The online version of this article (10.1186/s12989-018-0250-8) contains supplementary material, which is available to authorized users.

End-user perspective of low-cost sensors for outdoor air pollution monitoring

Low-cost sensor technology can potentially revolutionise the area of air pollution monitoring by providing high-density spatiotemporal pollution data. Such data can be utilised for supplementing traditional pollution monitoring, improving exposure estimates, and raising community awareness about air pollution. However, data quality remains a major concern that hinders the widespread adoption of low-cost sensor technology. Unreliable data may mislead unsuspecting users and potentially lead to alarming consequences such as reporting acceptable air pollutant levels when they are above the limits deemed safe for human health. This article provides scientific guidance to the end-users for effectively deploying low-cost sensors for monitoring air pollution and people's exposure, while ensuring reasonable data quality. We review the performance characteristics of several low-cost particle and gas monitoring sensors and provide recommendations to end-users for making proper sensor selection by summarizing the capabilities and limitations of such sensors. The challenges, best practices, and future outlook for effectively deploying low-cost sensors, and maintaining data quality are also discussed. For data quality assurance, a two-stage sensor calibration process is recommended, which includes laboratory calibration under controlled conditions by the manufacturer supplemented with routine calibration checks performed by the end-user under final deployment conditions. For large sensor networks where routine calibration checks are impractical, statistical techniques for data quality assurance should be utilised. Further advancements and adoption of sophisticated mathematical and statistical techniques for sensor calibration, fault detection, and data quality assurance can indeed help to realise the promised benefits of a low-cost air pollution sensor network.

Review of measurement techniques and methods for assessing personal exposure to airborne nanomaterials in workplaces

Exposure to airborne agents needs to be assessed in the personal breathing zone by the use of personal measurement equipment. Specific measurement devices for assessing personal exposure to airborne nanomaterials have only become available in the recent years. They can be differentiated into direct-reading personal monitors and personal samplers that collect the airborne nanomaterials for subsequent analyses. This article presents a review of the available personal monitors and samplers and summarizes the available literature regarding their accuracy, comparability and field applicability. Due to the novelty of the instruments, the number of published studies is still relatively low. Where applicable, literature data is therefore complemented with published and unpublished results from the recently finished nanoIndEx project. The presented data show that the samplers and monitors are robust and ready for field use with sufficient accuracy and comparability. However, several limitations apply, e.g. regarding the particle size range of the personal monitors and their in general lower accuracy and comparability compared with their stationary counterparts. The decision whether a personal monitor or a personal sampler shall be preferred depends strongly on the question to tackle. In many cases, a combination of a personal monitor and a personal sampler may be the best choice to obtain conclusive results.

Aerosol Health Effects from Molecular to Global Scales

Poor air quality is globally the largest environmental health risk. Epidemiological studies have uncovered clear relationships of gaseous pollutants and particulate matter (PM) with adverse health outcomes, including mortality by cardiovascular and respiratory diseases. Studies of health impacts by aerosols are highly multidisciplinary with a broad range of scales in space and time. We assess recent advances and future challenges regarding aerosol effects on health from molecular to global scales through epidemiological studies, field measurements, health-related properties of PM, and multiphase interactions of oxidants and PM upon respiratory deposition. Global modeling combined with epidemiological exposure-response functions indicates that ambient air pollution causes more than four million premature deaths per year. Epidemiological studies usually refer to PM mass concentrations, but some health effects may relate to specific constituents such as bioaerosols, polycyclic aromatic compounds, and transition metals. Various analytical techniques and cellular and molecular assays are applied to assess the redox activity of PM and the formation of reactive oxygen species. Multiphase chemical interactions of lung antioxidants with atmospheric pollutants are crucial to the mechanistic and molecular understanding of oxidative stress upon respiratory deposition. The role of distinct PM components in health impacts and mortality needs to be clarified by integrated research on various spatiotemporal scales for better evaluation and mitigation of aerosol effects on public health in the Anthropocene.

Estimation of inhaled airborne particle number concentration by subway users in Seoul, Korea

Exposure to airborne particulate matter (PM) causes several diseases in the human body. The smaller particles, which have relatively large surface areas, are actually more harmful to the human body since they can penetrate deeper parts of the lungs or become secondary pollutants by bonding with other atmospheric pollutants, such as nitrogen oxides. The purpose of this study is to present the number of PM inhaled by subway users as a possible reference material for any analysis of the hazards to the human body arising from the inhalation of such PM. Two transfer stations in Seoul, Korea, which have the greatest number of users, were selected for this study. For 0.3-0.422 μm PM, particle number concentration (PNC) was highest outdoors but decreased as the tester moved deeper underground. On the other hand, the PNC between 1 and 10 μm increased as the tester moved deeper underground and showed a high number concentration inside the subway train as well. An analysis of the particles to which subway users are actually exposed to (inhaled particle number), using particle concentration at each measurement location, the average inhalation rate of an adult, and the average stay time at each location, all showed that particles sized 0.01-0.422 μm are mostly inhaled from the outdoor air whereas particles sized 1-10 μm are inhaled as the passengers move deeper underground. Based on these findings, we expect that the inhaled particle number of subway users can be used as reference data for an evaluation of the hazards to health caused by PM inhalation.

Validation of a light-scattering PM2.5 sensor monitor based on the long-term gravimetric measurements in field tests

Background

Portable direct-reading instruments by light-scattering method are increasingly used in airborne fine particulate matter (PM_2.5) monitoring. However, there are limited calibration studies on such instruments by applying the gravimetric method as reference method in field tests.

Methods

An 8-month sampling was performed and 96 pairs of PM_2.5 data by both the gravimetric method and the simultaneous light-scattering real-time monitoring (QT-50) were obtained from July, 2015 to February, 2016 in Shanghai. Temperature and relative humidity (RH) were recorded. Mann-Whitney U nonparametric test and Spearman correlation were used to investigate the differences between the two measurements. Multiple linear regression (MLR) model was applied to set up the calibration model for the light-scattering device.

Results

The average PM_2.5 concentration (median) was 48.1μg/m³ (min-max 10.4–95.8μg/m³) by the gravimetric method and 58.1μg/m³ (19.2–315.9μg/m³) by the light-scattering method, respectively. By time trend analyses, they were significantly correlated with each other (Spearman correlation coefficient 0.889, P<0.01). By MLR, the calibration model for the light-scattering instrument was Y(calibrated) = 57.45 + 0.47 × X(the QT – 50 measurements) – 0.53 × RH – 0.41 × Temp with both RH and temperature adjusted. The 10-fold cross-validation R² and the root mean squared error of the calibration model were 0.79 and 11.43 μg/m³, respectively.

Conclusion

Light-scattering measurements of PM_2.5 by QT-50 instrument overestimated the concentration levels and were affected by temperature and RH. The calibration model for QT-50 instrument was firstly set up against the gravimetric method with temperature and RH adjusted.

Community-based participatory research for the study of air pollution: a review of motivations, approaches, and outcomes

Neighborhood level air pollution represents a long-standing issue for many communities that, until recently, has been difficult to address due to the cost of equipment and lack of related expertise. Changes in available technology and subsequent increases in community-based participatory research (CBPR) have drastically improved the ability to address this issue. However, much still needs to be learned as these types of studies are expected to increase in the future. To assist, we review the literature in an effort to improve understanding of the motivations, approaches, and outcomes of air monitoring studies that incorporate CBPR and citizen science (CS) principles. We found that the primary motivations for conducting community-based air monitoring were concerns for air pollution health risks, residing near potential pollution sources, urban sprawl, living in "unmonitored" areas, and a general quest for improved air quality knowledge. Studies were mainly conducted using community led partnerships. Fixed site monitoring was primarily used, while mobile, personal, school-based, and occupational sampling approaches were less frequent. Low-cost sensors can enable thorough neighborhood level characterization; however, keeping the community involved at every step, understanding the limitations and benefits of this type of monitoring, recognizing potential areas of debate, and addressing study challenges are vital for achieving harmony between expected and observed study outcomes. Future directions include assessing currently unregulated pollutants, establishing long-term neighborhood monitoring sites, performing saturation studies, evaluating interventions, and creating CS databases.