Applications of GPS-tracked personal and fixed-location PM(2.5) continuous exposure monitoring

Personal exposure to PM2.5 in different microenvironments and activities for retired adults in two megacities, China

Microenvironmental concentrations and time-activity patterns influence personal exposure to fine particulate matter (PM_2.5). However, the variations and contributions of PM_2.5 exposures from various microenvironments (MEs) and activities remain unclear. In this study, gravimetrically corrected real-time personal PM_2.5 measurements were collected during routine activities in different MEs from 66 non-smoking retired adults. Exposure data were collected for five consecutive days over two seasons in Nanjing (NJ) and Beijing (BJ), China. Measured PM_2.5 concentrations varied substantially both between and within different MEs and activities. The highest average concentrations were observed in restaurants (NJ: mean 192 μg/m³, SD 242 μg/m³; BJ: mean 91 μg/m³, SD 79 μg/m³) and were associated with sources such as passive smoking and cooking emissions. Overall, PM_2.5 concentrations in different MEs and activities were moderately to highly correlated with outdoor PM_2.5 concentrations (Spearman's r = 0.51-0.97) except in restaurants and during passive smoking. The at-home ME contributed approximately 85 % of the total PM_2.5 exposure, corresponding to the participants spending about 87 % of their time there. The majority of household exposures occurred during sleeping, cooking, and other home-based activities. Transportation accounted for <5 % of total exposure. Our results indicate that improving indoor air quality, especially residential indoors, is important to reduce personal exposure to PM_2.5.

Particulate air pollution in the Copenhagen metro part 2: Low-cost sensors and micro-environment classification

In this study fine particulate matter (PM_2.5) levels throughout the Copenhagen metro system are measured for the first time and found to be ∼10 times the roadside levels in Copenhagen. In this Part 2 article, low-cost sensor (LCS) nodes designed for personal-exposure monitoring are tested against a conventional mid-range device (TSI DustTrak), and gravimetric methods. The nodes were found to be effective for personal exposure measurements inside the metro system, with R² values of > 0.8 at 1-min and > 0.9 at 5-min time-resolution, with an average slope of 1.01 in both cases, in comparison to the reference, which is impressive for this dynamic environment. Micro-environment (ME) classification techniques are also developed and tested, involving the use of auxiliary sensors, measuring light, carbon dioxide, humidity, temperature and motion. The output from these sensors is used to distinguish between specific MEs, namely, being aboard trains travelling above- or under- ground, with 83 % accuracy, and determining whether sensors were aboard a train or stationary at a platform with 92 % accuracy. This information was used to show a 143 % increase in mean PM_2.5 concentration for underground sections relative to overground, and 22 % increase for train vs. platform measurements. The ME classification method can also be used to improve calibration models, assist in accurate exposure assessment based on detailed time-activity patterns, and facilitate field studies that do not require personnel to record time-activity diaries.

Differences in Fine Particle Exposure and Estimated Pulmonary Ventilation Rate with Respect to Work Tasks of Wildland Firefighters at Prescribed Burns: A Repeated Measures Study

Wildland firefighters (WLFFs) are exposed to a mixture of chemicals found in wildland fire smoke and emissions from nonwildland-fuel smoke sources such as diesel. We investigated compositional differences in exposure to particulate matter and explored differences in ventilation rate and potential inhaled dose relative to the work tasks of WLFFs. Repeated measures on ten professional and two volunteer firefighters were collected on prescribed burn and nonburn days. Personal monitoring consisted of real-time and gravimetric fine particulate matter (PM2.5), carbon monoxide (CO), and accelerometer measurements to estimate ventilation rate and potential dose of PM2.5. The fine particulate matter was analyzed for levoglucosan (LG) and light absorbing carbon as a surrogate for black carbon (BC). Breathing zone personal exposure concentrations of PM2.5, LG, BC, and CO were higher on burn days (P < 0.05). Differences in exposure concentrations were observed between burn day tasks (P < 0.05) with firefighters managing fire boundaries (holders) being exposed to higher CO and LG concentrations and less BC concentrations than those conducting lighting (lighters). While no statistical difference in PM2.5 exposure measures was observed between the two tasks, holders in the study tended to be exposed to higher PM2.5 concentrations (~1.4×), while lighters tended to have more inhaled amounts of PM2.5 (~1.3×). Our findings demonstrate possible diversity in the sources of particulate matter exposure at the fireline and suggest the potential importance of using dose as a metric of inhalation exposure in occupational or other settings.

Comparing human exposure to fine particulate matter in low and high-income countries: A systematic review of studies measuring personal PM2.5 exposure

BACKGROUND

Due to the adverse health effects of air pollution, researchers have advocated for personal exposure measurements whereby individuals carry portable monitors in order to better characterise and understand the sources of people's pollution exposure.

OBJECTIVES

The aim of this systematic review is to assess the differences in the magnitude and sources of personal PM2.5 exposures experienced between countries at contrasting levels of income.

METHODS

This review summarised studies that measured participants personal exposure by carrying a PM2.5 monitor throughout their typical day. Personal PM2.5 exposures were summarised to indicate the distribution of exposures measured within each country income category (based on low (LIC), lower-middle (LMIC), upper-middle (UMIC), and high (HIC) income countries) and between different groups (i.e. gender, age, urban or rural residents).

RESULTS

From the 2259 search results, there were 140 studies that met our criteria. Overall, personal PM2.5 exposures in HICs were lower compared to other countries, with UMICs exposures being slightly lower than exposures measured in LMICs or LICs. 34% of measured groups in HICs reported below the ambient World Health Organisation 24-h PM2.5 guideline of 15 μg/m3, compared to only 1% of UMICs and 0% of LMICs and LICs. There was no difference between rural and urban participant exposures in HICs, but there were noticeably higher exposures recorded in rural areas compared to urban areas in non-HICs, due to significant household sources of PM2.5 in rural locations. In HICs, studies reported that secondhand smoke, ambient pollution infiltrating indoors, and traffic emissions were the dominant contributors to personal exposures. While, in non-HICs, household cooking and heating with biomass and coal were reported as the most important sources.

CONCLUSION

This review revealed a growing literature of personal PM2.5 exposure studies, which highlighted a large variability in exposures recorded and severe inequalities in geographical and social population subgroups.

Fused Filament Fabrication 3D Printing: Quantification of Exposure to Airborne Particles

Fused Filament Fabrication (FFF) has been established as a widely practiced Additive Manufacturing technique, using various thermoplastic filaments. Carbon fibre (CF) additives enhance mechanical properties of the materials. The main operational hazard of the FFF technique explored in the literature is the emission of Ultrafine Particles and Volatile Organic Compounds. Exposure data regarding novel materials and larger scale operations is, however, still lacking. In this work, a thorough exposure assessment measurement campaign is presented for a workplace applying FFF 3D printing in various setups (four different commercial devices, including a modified commercial printer) and applying various materials (polylactic acid, thermoplastic polyurethane, copolyamide, polyethylene terephthalate glycol) and CF-reinforced thermoplastics (thermoplastic polyurethane, polylactic acid, polyamide). Portable exposure assessment instruments are employed, based on an established methodology, to study the airborne particle exposure potential of each process setup. The results revealed a distinct exposure profile for each process, necessitating a different safety approach per setup. Crucially, high potential for exposure is detected in processes with two printers working simultaneously. An updated engineering control scheme is applied to control exposures for the modified commercial printer. The establishment of a flexible safety system is vital for workplaces that apply FFF 3D printing.

Short-term associations between barbecue fumes and respiratory health in young adults

BACKGROUND

Epidemiological studies have associated biomass combustion with (respiratory) morbidity and mortality, primarily in indoor settings. Barbecuing results in high outdoor air pollution exposures, but the health effects are unknown.

OBJECTIVE

The objective was to investigate short-term changes in respiratory health in healthy adults, associated with exposure to barbecue fumes.

METHODS

16 healthy, adult volunteers were exposed to barbecue smoke in outdoor air in rest during 1.5 h, using a repeated-measures design. Major air pollutants were monitored on-site, including particulate matter <2.5 μm (PM_2.5), particle number concentrations (PNC) and black- and brown carbon. At the same place and time-of-day, subjects participated in a control session, during which they were not exposed to barbecue smoke. Before and immediately after all sessions lung function was measured. Before, immediately after, 4- and 18 h post-sessions nasal expression levels of interleukin (IL)-8, IL6 and Tumor Necrosis Factor alpha (TNFα) were determined in nasal swabs, using quantitative polymerase chain reaction. Associations between major air pollutants, lung function and inflammatory markers were assessed using mixed linear regression models.

RESULTS

High PM_2.5 levels and PNCs were observed during barbecue sessions, with averages ranging from 553 to 1062 μg/m³ and 109,000-463,000 pt/cm³, respectively. Average black- and brown carbon levels ranged between 4.1-13.0 and 5.0-16.2 μg/m³. A 1000 μg/m³ increase in PM_2.5 was associated with 2.37 (0.97, 4.67) and 2.21 (0.98, 5.00) times higher expression of IL8, immediately- and 18 h after exposure. No associations were found between air pollutants and lung function, or the expression of IL6 or TNFα.

DISCUSSION

Short-term exposure to air pollutants emitted from barbecuing was associated with a mild respiratory response in healthy young adults, including prolonged increase in nasal IL8 without a change in lung function and other measured inflammatory markers. The results might indicate prolonged respiratory inflammation, due to short-term exposure to barbecue fumes.

Feasibility and acceptability of monitoring personal air pollution exposure with sensors for asthma self-management

Background

Exposure to fine particulate matter (PM_2.5) increases the risk of asthma exacerbations, and thus, monitoring personal exposure to PM_2.5 may aid in disease self-management. Low-cost, portable air pollution sensors offer a convenient way to measure personal pollution exposure directly and may improve personalized monitoring compared with traditional methods that rely on stationary monitoring stations. We aimed to understand whether adults with asthma would be willing to use personal sensors to monitor their exposure to air pollution and to assess the feasibility of using sensors to measure real-time PM_2.5 exposure.

Methods

We conducted semi-structured interviews with 15 adults with asthma to understand their willingness to use a personal pollution sensor and their privacy preferences with regard to sensor data. Student research assistants used HabitatMap AirBeam devices to take PM_2.5 measurements at 1-s intervals while walking in Philadelphia neighborhoods in May–August 2018. AirBeam PM_2.5 measurements were compared to concurrent measurements taken by three nearby regulatory monitors.

Results

All interview participants stated that they would use a personal air pollution sensor, though the consensus was that devices should be small (watch- or palm-sized) and light. Patients were generally unconcerned about privacy or sharing their GPS location, with only two stating they would not share their GPS location under any circumstances. PM_2.5 measurements were taken using AirBeam sensors on 34 walks that extended through five Philadelphia neighborhoods. The range of sensor PM_2.5 measurements was 0.6–97.6 μg/mL (mean 6.8 μg/mL), compared to 0–22.6 μg/mL (mean 9.0 μg/mL) measured by nearby regulatory monitors. Compared to stationary measurements, which were only available as 1-h integrated averages at discrete monitoring sites, sensor measurements permitted characterization of fine-scale fluctuations in PM_2.5 levels over time and space.

Conclusions

Patients were generally interested in using sensors to monitor their personal exposure to PM_2.5 and willing to share personal sensor data with health care providers and researchers. Compared to traditional methods of personal exposure assessment, sensors captured personalized air quality information at higher spatiotemporal resolution. Improvements to currently available sensors, including more reliable Bluetooth connectivity, increased portability, and longer battery life would facilitate their use in a general patient population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40733-021-00079-9.

The Exposome in the Era of the Quantified Self

Human health is regulated by complex interactions among the genome, the microbiome, and the environment. While extensive research has been conducted on the human genome and microbiome, little is known about the human exposome. The exposome comprises the totality of chemical, biological, and physical exposures that individuals encounter over their lifetimes. Traditional environmental and biological monitoring only targets specific substances, whereas exposomic approaches identify and quantify thousands of substances simultaneously using nontargeted high-throughput and high-resolution analyses. The quantified self (QS) aims at enhancing our understanding of human health and disease through self-tracking. QS measurements are critical in exposome research, as external exposures impact an individual's health, behavior, and biology. This review discusses both the achievements and the shortcomings of current research and methodologies on the QS and the exposome and proposes future research directions.

Estimating exposure to traffic-related PM2.5 for women commuters using vehicle and personal monitoring

Exposure to traffic-related fine particulate matter air pollution (tr-PM_2.5) has been associated with adverse health outcomes including preterm birth and low birthweight. In-vehicle exposure to tr-PM_2.5 can contribute substantially to total tr-PM_2.5 exposure. Because average commuting habits of women differ from men, a research gap is estimating in-vehicle tr-PM_2.5 exposures for women commuters. For 46 women commuters in the Washington, D.C. metro area, we measured personal exposure to PM_2.5 during all vehicle trips taken in a 48-h sampling period. We also measured 48-h integrated PM_2.5 chemical constituents including black carbon and zinc. We identified trip times using vehicle monitors, specifically on-board diagnostics data loggers and dashboard cameras. For 386 trips, we estimated associations between PM_2.5 exposure and trip characteristics using linear mixed models accounting for participant, day, and time of day. Additionally, we estimated associations between rush hour trip PM_2.5 and 48-h integrated PM_2.5 chemical constituents using linear models. Exposure to PM_2.5 during trips was 1.9 μg/m³ (95% confidence interval (CI): 0.9, 2.9) higher than non-trip exposures and rush hour trip exposures were 3.2 μg/m³ (95% CI: 1.8, 4.6) higher than non-trip exposures on average. We did not find differences in PM_2.5 exposure by trip length. Although concentrations of tr-PM_2.5 chemical constituents were generally positively associated with rush hour trip PM_2.5, associations were weak indicating that other settings contribute to total tr-PM_2.5 exposure. Our study demonstrates the utility of combining vehicle monitors and personal PM_2.5 monitors for estimating personal exposure to tr-PM_2.5. Future work will investigate whether additional data collected by vehicle monitors, such as traffic and speed, can be leveraged to better understand tr-PM_2.5 exposure among commuters.

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.

PM2.5 and NO2 exposure errors using proxy measures, including derived personal exposure from outdoor sources: A systematic review and meta-analysis

BACKGROUND

The use of proxy exposure estimates for PM_2.5 and NO₂ in air pollution studies instead of personal exposures, introduces measurement error, which can produce biased epidemiological effect estimates. Most studies consider total personal exposure as the gold standard. However, when studying the effects of ambient air pollution, personal exposure from outdoor sources is the exposure of interest.

OBJECTIVES

We assessed the magnitude and variability of exposure measurement error by conducting a systematic review of the differences between personal exposures from outdoor sources and the corresponding measurements for ambient concentrations in order to increase understanding of the measurement error structures of the pollutants.

DATA SOURCES AND ELIGIBILITY CRITERIA

We reviewed the literature (ISI Web of Science, Medline, 2000-2016) for English language studies (in any age group in any location (NO₂) or Europe and North America (PM_2.5)) that reported repeated measurements over time both for personal and ambient PM_2.5 or NO₂ concentrations. Only a few studies reported personal exposure from outdoor sources. We also collected data for infiltration factors and time-activity patterns of the individuals in order to estimate personal exposures from outdoor sources in every study.

STUDY APPRAISAL AND SYNTHESIS METHODS

Studies using modelled rather than monitored exposures were excluded. Type of personal exposure monitor was assessed. Random effects meta-analysis was conducted to quantify exposure error as the mean difference between "true" and proxy measures.

RESULTS

Thirty-two papers for PM_2.5 and 24 for NO₂ were identified. Outdoor sources were found to contribute 44% (range: 33-55%) of total personal exposure to PM_2.5 and 74% (range: 57-88%) to NO₂. Overall estimates of personal exposure (24-hour averages) from outdoor sources were 9.3 μg/m³ and 12.0 ppb for PM_2.5 and NO₂ respectively, while the corresponding difference between these exposures and the ambient concentrations (i.e. the measurement error) was 5.72 μg/m³ and 7.17 ppb. Our findings indicated also higher error variability for NO₂ than PM_2.5. Large heterogeneity was observed which was not explained sufficiently by geographical location or age group of the study sample.

LIMITATIONS, CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS

Relying only on information available in published studies led to some limitations: the contribution of outdoor sources to total personal exposure for NO₂ had to be inferred, individual variation in exposure misclassification was unavailable and instrument error could not be addressed. The larger magnitude and variability of errors for NO₂ compared with PM_2.5 has implications for biases in the health effect estimates of multi-pollutant epidemiological models. Results suggest that further research is needed regarding personal exposure studies and measurement error bias in epidemiological models.

Assessment of Daily Personal PM2.5 Exposure Level According to Four Major Activities among Children

Particulate matters less than 2.5 micrometers in diameter (PM2.5), whose concentration has increased in Korea, has a considerable impact on health. From a risk management point of view, there has been interest in understanding the variations in real-time PM2.5 concentrations per activity in different microenvironments. We analyzed personal monitoring data collected from 15 children aged 6 to 11 years engaged in different activities such as commuting in a car, visiting a commercial building, attending an education institute, and resting inside home from October 2018 to March 2019. The fraction of daily mean exposure duration per activity was 72.7 ± 18.7% for resting inside home, 27.2 ± 14.4% for attending an education institute, and 11.5 ± 9.6% and 5.3 ± 5.9% for visiting a commercial building, commuting in a car, respectively. Daily median (interquartile range) PM2.5 exposure amount was 88.9 (55.9–159.7) μg in houses and that in education buildings was 43.3 (22.9–55.6) μg. Real-time PM2.5 exposure levels varied by person and time of day (p-value < 0.05). This study demonstrated that our real-time personal monitoring and data analysis methodologies were effective in detecting polluted microenvironments and provided a potential person-specific management strategy to reduce a person’s exposure level to PM2.5.

Youth Engaged Participatory Air Monitoring: A 'Day in the Life' in Urban Environmental Justice Communities

Air pollution in Southern California does not impact all communities equally; communities of color are disproportionately burdened by poor air quality and more likely to live near industrial facilities and freeways. Government regulatory monitors do not have the spatial resolution to provide air quality information at the neighborhood or personal scale. We describe the A Day in the Life program, an approach to participatory air monitoring that engages youth in collecting data that they can then analyze and use to take action. Academics partnered with Los Angeles-based youth environmental justice organizations to combine personal air monitoring, participatory science, and digital storytelling to build capacity to address local air quality issues. Eighteen youth participants from four different neighborhoods wore portable personal PM2.5 (fine particles <2.5 µm in diameter) monitors for a day in each of their respective communities, documenting and mapping their exposure to PM2.5 during their daily routine. Air monitoring was coupled with photography and videos to document what they experienced over the course of their day. The PM2.5 exposure during the day for participants averaged 10.7 µg/m3, although the range stretched from <1 to 180 µg/m3. One-third of all measurements were taken <300 m from a freeway. Overall, we demonstrate a method to increase local youth-centered understanding of personal exposures, pollution sources, and vulnerability to air quality.

Combining sensor-based measurement and modeling of PM2.5 and black carbon in assessing exposure to indoor aerosols

Accurate, cost-effective methods are needed for rapid assessment of traffic-related air pollution (TRAP). Typically, real-time data of particulate matter (PM) from portable sensors have been adjusted using data from reference methods such as gravimetric measurement to improve accuracy. The objective of this study was to create a correction factor or linear regression model for the real-time measurements of the RTI's Micro Personal Exposure Monitor (MicroPEM^™) and AethLab's microAeth® black carbon (AE51) sensor to generate accurate real-time data for PM_2.5 (PM_2.5RT) and black carbon (BC_RT) in Cincinnati metropolitan homes. The two sensors and an SKC PM_2.5 Personal Modular impactor were collocated in 44 indoor sampling events for 2 days in residences near major roadways. The reference filter-based analyses conducted by a laboratory included particle mass (SKC PM_2.5 and MicroPEM^™ PM_2.5) and black carbon (SKC BC); these methods are more accurate than real-time sensors but are also more cumbersome and costly. For PM_2.5, the average correction factor, a ratio of gravimetric to real-time, for the MicroPEM^™ PM_2.5 and SKC PM_2.5 utilizing the PM_2.5RT and was 0.94 and 0.83, respectively, with a coefficient of variation (CV) of 84% and 52%, respectively; the corresponding linear regression model had a CV of 54% and 25%. For BC, the average correction factor utilizing the BC_RT and SKC BC was 0.74 with a CV of 36% with the associated linear regression model producing a CV of 56%. The results from this study will help ensure that the real-time exposure monitors are capable of detecting an estimated PM_2.5 after an appropriate statistical model is applied.

Assessment of PM2.5 monitoring using MicroPEM: A validation study in a city with elevated PM2.5 levels

Portable monitors such as MicroPEM can accurately characterize personal exposure of pollutants, which is critical for linking exposure and health effects of air pollution. The RTI (RTI International, Research Triangle Park, NC, USA) MicroPEM V3.2A provides both real-time fine particulate matter (PM_2.5) concentrations and time-integrated PM samples collected onto Teflon filters that can be used to correct real-time data as well as allow further lab chemical analysis of species on filters (e.g., metal, black carbon). Due to the optical reflectivity of local PM sources can be very different from available standard reference particles used for calibration by RTI, there is a need for gravimetric correction and validation at each study location. However, assessments of MicroPEM have been limited in locations with severe air pollution, such as Beijing. We selected a variety of weather and air quality conditions, including both clear and hazy days in Beijing, to compare PM_2.5 data among MicroPEMs as well as between MicroPEM and other types of samplers. We also compared MicroPEM real-time PM_2.5 concentrations with data from nearby fixed-sites. The results show MicroPEM performed well across a wide range of PM_2.5 concentrations (6-461 μg/m³) and MicroPEM data, after gravimetric correction, were consistent with those from moderate-volume samplers. Good agreement was also found between real-time data from MicroPEM and fixed-site data. The present study covered a wide range of pollution levels in actual environments and validated the usage of MicroPEM as a PM_2.5 monitor in locations with elevated PM_2.5 levels.

Environmental Health Indicators for China: Data Resources for Chinese Environmental Public Health Tracking

Many developed countries use environmental public health tracking to gain a better understanding of the link between environmental hazards and public health. To respond to complicated environmental health issues, the National Institute of Environmental Health (NIEH), Chinese Center for Disease Control and Prevention (China CDC), has begun to build a Chinese Environmental Public Health Tracking (CEPHT) system. On behalf of the CEPHT, authors provide insight into the CEPHT's development, current status, and future plans. In the initial stage of CEPHT, an indicator framework linking environment and public health that included a list of publicly available data sources regarding environmental hazards, public health outcomes, and risk factors in China was developed. An analysis of data availability, along with a comparison between CEPHT's indicator system and other tracking networks, revealed the existence of barriers and gaps in data integration that affect China's ability to track environmental public health. The lack of access to data, combined with inadequate data quality, has led to difficulties linking environmental hazards to their effects on public health. Current CEPHT efforts will help integrate environmental factors and exposure data with public health outcomes. For the near future, CEPHT plans to focus on increasing collaboration among data tracking agencies, improving data quality, and expanding proper data sharing. https://doi.org/10.1289/EHP4319.

Bio3Air, an integrative system for monitoring individual-level air pollutant exposure with high time and spatial resolution

BACKGROUND

Air pollution is a leading cause of global disease burden. Lack of suitable methods for long term measuring exposure level at individual level is crippling environmental epidemiology research of air pollution.

METHODS

We report an integrative system, Bio³Air, for long term measurement of individual level air pollution exposure, currently focusing on ambient particulate matter (PM). The novel system in real-time quantifies individual's outdoor/indoor status, geological location, lung ventilation rate and PM concentration of individual's surrounding environment, and these metrics are subsequently incorporated in calculating PM exposure.

RESULTS

The system is fully developed and tested in China, USA and Canada, and has been successfully applied in epidemiology study. Bio³Air offers high reliability, sensitivity, reproducibility (>99%) and accuracy. It has high time- and spatial- resolution (≤ 2 min and ≤ 20 m, respectively). Bio³Air achieved 91.89% consistency with "gold-standard" method (membrane collection and off-line analysis).

CONCLUSIONS

Bio³Air represents a substantial methodological advance in environmental health research of air pollution. It captures information relevant in measuring individual's PM exposure (e.g. real-time outdoor/indoor status, location and lung ventilation rate). Such information is typically missed by conventional approaches. Additional features of Bio³Air include easy-to-use, cost-effectiveness and automated data collection, making it a powerful tool facilitating studies of air pollution exposure and health consequences.

Measuring Micrometers of Matter and Inventing Indices: Entangling Social Perception within Discrete and Continuous Measurements of Air Quality

Environmental protection agencies around the globe are establishing different methods for measuring particulates, and then integrating those measurements into a single air quality index with other pollutants. At the same time, scientific inquiry has also shifted to a theory of measurement that incorporates discrete and continuous measurement. This article reviews the relationship between discrete measurements and indices, while also speculating on the way that the continuous measurement of air pollution could stimulate awareness and action. The paper argues that continuous measurement must include the way people of different backgrounds perceive air pollution in their lives. After reviewing the methods of measuring particulates and their inclusion into various indices, the article argues that in order to take action to mitigate the health impacts of air pollution, we must allow for the social perception of air pollution to become entangled within our scientific measurements.

Development of an in-home, real-time air pollutant sensor platform and implications for community use

Air pollution exposure characterization has been shaped by many constraints. These include technologies that lead to insufficient coverage across space and/or time in order to characterize individual or community-level exposures with sufficient accuracy and precision. However, there is now capacity for continuous monitoring of many air pollutants using comparatively inexpensive, real-time sensors. Crucial questions remain regarding whether or not these sensors perform adequately for various potential end uses and whether performance varies over time or across ambient conditions. Performance scrutiny of sensors via lab- and field-testing and calibration across their lifetime is necessary for interpretation of data, and has important implications for end users including cost effectiveness and ease of use. We developed a comparatively lower-cost, portable, in-home air sampling platform and a guiding development and maintenance workflow that achieved our goal of characterizing some key indoor pollutants with high sensitivity and reasonable accuracy. Here we describe the process of selecting, validating, calibrating, and maintaining our platform - the Environmental Multi-pollutant Monitoring Assembly (EMMA) - over the course of our study to-date. We highlight necessary resources and consider implications for communities or researchers interested in developing such platforms, focusing on PM_2.5, NO, and NO₂ sensors. Our findings emphasize that lower-cost sensors should be deployed with caution, given financial and resource costs that greatly exceed sensor costs, but that selected community objectives could be supported at lesser cost and community-based participatory research strategies could be used for more wide-ranging goals.

Development of an approach to correcting MicroPEM baseline drift

BACKGROUND

Fine particulate matter (PM2.5) is associated with various adverse health outcomes. The MicroPEM (RTI, NC), a miniaturized real-time portable particulate sensor with an integrated filter for collecting particles, has been widely used for personal PM2.5 exposure assessment. Five-day deployments were targeted on a total of 142 deployments (personal or residential) to obtain real-time PM2.5 levels from children living in New York City and Baltimore. Among these 142 deployments, 79 applied high-efficiency particulate air (HEPA) filters in the field at the beginning and end of each deployment to adjust the zero level of the nephelometer. However, unacceptable baseline drift was observed in a large fraction (> 40%) of acquisitions in this study even after HEPA correction. This drift issue has been observed in several other studies as well. The purpose of the present study is to develop an algorithm to correct the baseline drift in MicroPEM based on central site ambient data during inactive time periods.

METHOD

A running baseline & gravimetric correction (RBGC) method was developed based on the comparison of MicroPEM readings during inactive periods to ambient PM2.5 levels provided by fixed monitoring sites and the gravimetric weight of PM2.5 collected on the MicroPEM filters. The results after RBGC correction were compared with those using HEPA approach and gravimetric correction alone. Seven pairs of duplicate acquisitions were used to validate the RBGC method.

RESULTS

The percentages of acquisitions with baseline drift problems were 42%, 53% and 10% for raw, HEPA corrected, and RBGC corrected data, respectively. Pearson correlation analysis of duplicates showed an increase in the coefficient of determination from 0.75 for raw data to 0.97 after RBGC correction. In addition, the slope of the regression line increased from 0.60 for raw data to 1.00 after RBGC correction.

CONCLUSIONS

The RBGC approach corrected the baseline drift issue associated with MicroPEM data. The algorithm developed has the potential for use with data generated from other types of PM sensors that contain a filter for weighing as well. In addition, this approach can be applied in many other regions, given widely available ambient PM data from monitoring networks, especially in urban areas.

Personal exposure to fine particulate matter concentrations in central business district of a tropical coastal city

In the present study, personal exposure to fine particulate matter (particulate matter with an aerodynamic diameter <2.5 μm [PM_2.5]) concentrations in an urban hotspot (central business district [CBD]) was investigated. The PM monitoring campaigns were carried out at an urban hotspot from June to October 2015. The personal exposure monitoring was performed during three different time periods, i.e., morning (8 a.m.-9 a.m.), afternoon (12.30 p.m.-1.30 p.m.), and evening (4 p.m.-5 p.m.), to cover both the peak and lean hour activities of the CBD. The median PM_2.5 concentrations were 38.1, 34.9, and 40.4 µg/m³ during the morning, afternoon, and evening hours on the weekends. During weekdays, the median PM_2.5 concentrations were 59.5, 29.6, and 36.6 µg/m³ in the morning, afternoon, and evening hours, respectively. It was observed that the combined effect of traffic emissions, complex land use, and micrometeorological conditions created localized air pollution hotspots. Furthermore, the total PM_2.5 lung dose levels for an exposure duration of 1 hr were 8.7 ± 5.7 and 12.3 ± 5.2 µg at CBD during weekends and weekdays, respectively, as compared with 2.5 ± 0.8 µg at the urban background (UB). This study emphasizes the need for mobile measurement for short-term personal exposure assessment complementing the fixed air quality monitoring.

IMPLICATIONS

Personal exposure monitoring at an urban hotspot indicated space and time variation in PM concentrations that is not captured by the fixed air quality monitoring networks. The short-term exposure to higher concentrations can have a significant impact on health that need to be considered for the health risk-based air quality management. The study emphasizes the need of hotspot-based monitoring complementing the already existing fixed air quality monitoring in urban areas. The personal exposure patterns at hotspots can provide additional insight into sustainable urban planning.

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.

Characterization of PM2.5 exposure concentration in transport microenvironments using portable monitors

Recently, portable monitors have been increasingly used to quantify air pollutant concentrations at high spatiotemporal resolution. A sampling campaign was conducted to measure the fine particulate matter (PM_2.5) and carbon monoxide (CO) exposure concentrations in transport microenvironments (TMEs) in Hong Kong in January and June 2015 using TSI DustTrak and Q-Trak portable monitors. The objectives were to: (1) calibrate DustTrak and Q-Trak; (2) evaluate variability between seasons and microenvironments; (3) estimate indoor/outdoor relationships; and (4) determine minimum sample size. Calibration equations, obtained through side-by-side measurement against stationary reference methods in winter and summer, were applied to correct the measured PM_2.5 data set. In general, PM_2.5 concentrations in all TMEs were significantly higher in winter than in summer. The mean PM_2.5 concentration in winter was lower for underground sections of the Mass Transit Railway (MTR) metro system (31 μg/m³) than for other TMEs, whereas in summer TMEs had mean PM_2.5 concentrations in the range of 10-15 μg/m³, with above-ground MTR train as an exception, at 23 μg/m³. PM_2.5 concentrations measured in TMEs were strongly correlated with nearby air quality monitoring stations (AQMSs) measurements in winter, but in summer there was little correlation. The minimum sample size estimates varied more among TMEs in summer versus winter because of the differences in PM_2.5 concentration distributions related to changes in ambient PM_2.5 concentrations and ventilation practices. This study provides a feasible protocol on the calibration and application of portable monitors in TME air quality measurement and develops a method for estimating minimum sample size.

Hemocompatibility of inhaled environmental nanoparticles: Potential use of in vitro testing

Hemocompatibility testing is an important part in the evaluation of nano-based medicines. However, it is not systematically used for the assessment of environmental particles since they do not come in contact with blood immediately. Studies on human exposure to air-borne particles and pulmonary exposure of rodents have reported alterations in blood physiology. It is not clear, whether these effects are majorly caused by tissue inflammation or translocated particles in blood. This review addresses the question, if in vitro hemocompatibility testing could help in the risk evaluation of inhaled particles. Particle blood concentrations were estimated based on exposure levels, ventilation volume, deposition rate, lung surface area, and permeability of the alveolar epithelium to particles. The categories of hemocompatibility, thrombosis, coagulation, platelets, hematology, and immunology, were introduced. Also, concentrations of ultrafine particles, silver nanoparticles, carbon nanotubes that caused adverse effects in human blood samples were compared to the estimated concentrations of translocated particles. The comparison suggested that, it is unlikely for translocated nanoparticles to be the sole cause of adverse blood effects. Nevertheless, the testing of specific hemocompatibility parameters (hemolysis and clotting) in healthy blood might help to compare biological effect of inhaled particles containing different amounts of contamination. Testing of samples from healthy and diseased persons might help to identify pathological dispositions that increase the possibility of adverse reaction of nanoparticles in blood.