The Fort Collins commuter study: Variability in personal exposure to air pollutants by microenvironment

Variability in personal exposure to ultrafine and fine particles by microenvironment among adolescents in Cincinnati

Personal exposure to air pollution is influenced by an individual's time-activity patterns, but data regarding personal exposure to air pollution among children populations is lacking. The objective of this study was to characterize personal exposure to both PM2.5 and ultrafine particles (UFPs) using two portable real-time monitors, combined with GPS logging, and describe the relationship between these exposures across time and microenvironments among adolescents with asthma. Participants completed personal exposure monitoring for seven consecutive days and PM2.5 and UFP concentrations experienced in five microenvironments were determined using GPS location and mobility data. Average UFP and PM2.5 exposure varied across microenvironments with the highest average UFP exposure concentrations observed in transit (10,910 ± 27,297 p/cc), though correlations between UFP and PM2.5 concentrations in transit were low (0.24) and did not reach statistical significance (p > 0.05). We calculated exposure time ratios for each participant. Across participants, UFP exposures within the transit environment demonstrated the highest ratio (average exposure-time ratio = 1.91) though only 3 % of overall sampling time among all participants was monitored in transit (74/2840 h). We did not observe similar trends among PM2.5 exposures. The correlations between UFP and PM2.5 exposures varied throughout the day, with an overall correlation ranging from moderate to high among participants. Identifying microenvironments and activities where high exposure to PM occurs may offer potential targets for interventions to reduce overall exposures among sensitive groups.

Personal exposure to ultrafine particles in multiple microenvironments among adolescents

BACKGROUND

Experimental studies suggest ultrafine particles (UFPs), the smallest size fraction of particulate matter, may be more toxic than larger particles, however personal sampling studies in children are lacking.

OBJECTIVE

The objective of this analysis was to examine individual, housing, and neighborhood characteristics associated with personal UFP concentrations as well as the differences in exposures that occur within varying microenvironments.

METHODS

We measured weekly personal UFP concentrations and GPS coordinates in 117 adolescents ages 13-17 to describe exposures across multiple microenvironments. Individual, home, and neighborhood characteristics were collected by caregiver completed questionnaires.

RESULTS

Participants regularly exposed to secondhand tobacco smoke had significantly higher indoor concentrations of UFPs compared to participants who were not. We observed that the 'home' microenvironment dominated the relative contribution of overall UFP concentrations and sampling time, however, relative proportion of integrated UFP exposure were higher in 'other' environments.

IMPACT STATEMENT

In this study, we employed a novel panel study design, involving real-time measurement of UFP exposure within the multiple microenvironments of adolescents. We found a combination of personal sampling and detailed activity patterns should be used in future studies to accurately describe exposure-behavior relationships.

EAACI guidelines on environmental science for allergy and asthma: The impact of short-term exposure to outdoor air pollutants on asthma-related outcomes and recommendations for mitigation measures

The EAACI Guidelines on the impact of short-term exposure to outdoor pollutants on asthma-related outcomes provide recommendations for prevention, patient care and mitigation in a framework supporting rational decisions for healthcare professionals and patients to individualize and improve asthma management and for policymakers and regulators as an evidence-informed reference to help setting legally binding standards and goals for outdoor air quality at international, national and local levels. The Guideline was developed using the GRADE approach and evaluated outdoor pollutants referenced in the current Air Quality Guideline of the World Health Organization as single or mixed pollutants and outdoor pesticides. Short-term exposure to all pollutants evaluated increases the risk of asthma-related adverse outcomes, especially hospital admissions and emergency department visits (moderate certainty of evidence at specific lag days). There is limited evidence for the impact of traffic-related air pollution and outdoor pesticides exposure as well as for the interventions to reduce emissions. Due to the quality of evidence, conditional recommendations were formulated for all pollutants and for the interventions reducing outdoor air pollution. Asthma management counselled by the current EAACI guidelines can improve asthma-related outcomes but global measures for clean air are needed to achieve significant impact.

Contamination level, spatial distribution, and sources of potentially toxic elements in indoor settled household dusts in Tehran, Iran

Tehran, the capital city of Iran, has been facing air pollution for several decades due to rapid urbanization, population growth, improper vehicle use, and the low quality of fuels. In this study, 31 indoor dust samples were collected passively from residential and commercial buildings located in the central and densely populated districts of the city. These samples were analyzed after preparation to measure the concentration of elements (As, Be, Cd, Co, Cr, Cu, Fe, Hg, Mn, Mo, Ni, Pb, Se, Sr, V, Zn). Statistical data analyses were employed to compare their relationship across various uses, variations, and for source identification. Geochemical indices of contamination factor (CF) and pollution load index (PLI) were utilized to evaluate the degree of contamination. The mean concentrations of Zn, Cu, and Pb (938, 206, and 176 µg g-1, respectively) are 6, 5, and 3 times higher than their mean values in worldwide urban soils. Additionally, Cd, Mo, and Ni showed concentrations about 1.5 times higher, while As, Co, Cr, Mn, and Sr fell within the range of reference soils. Be, V, and Sb displayed remarkably lower mean values. Building use did not significantly influence element levels in indoor deposited dust except for Pb and Zn. A comparison of indoor concentrations with previously published data for outdoor dusts revealed higher enrichments of Mo, Cu, Pb, and Ni, while As, Cd, and Zn showed lower enrichments in street dust samples. The order of CF values indicated Hg > Zn > Cd > Pb > Cu > As > Ni > Cr > Co > V. For Hg, Zn, Pb, Cd, and Cu, all or almost all samples exhibited very high contamination. PLI values were consistently higher than 1, indicating contamination in all samples. Multivariate statistical analysis and Tehran's specific geological location suggested that mafic-intermediate volcanic rocks are primary sources for Cr, Cu, Fe, and Ni (PC1). As, Pb, and V (PC2) were attributed to fossil fuel combustion in vehicles and residential buildings. Pb is a legacy metal remaining from the use of leaded gasoline, which was phased out in the 1990s. Zn (PC3) is derived from vehicle tires.

Evaluating the impact of varying expired carbon monoxide thresholds on smoking relapse identification: insights from the E3 trial on e-cigarette efficacy for smoking cessation

OBJECTIVES

Expired carbon monoxide (ECO) is often used in smoking cessation trials to biochemically validate self-reported smoking status. The optimal ECO threshold to distinguish individuals who smoke from those who do not is debated.

DESIGN

The data from the 'Evaluating the Efficacy of E-Cigarette use for Smoking Cessation (E3) Trial' were used; the E3 trial was a randomised controlled trial that examined e-cigarettes efficacy for smoking cessation.

SETTINGS

Participants were recruited from 17 Canadian sites across 4 provinces.

PARTICIPANTS

This substudy included data from participants who returned for at least one of the clinical visits at week 4 (291), 12 (257) or 24 (218) and provided both self-reported smoking status and ECO measures. Analyses were based on 766 paired measures (ie, self-reported smoking status with corresponding ECO).

RESULTS

The ability of ECO measurements to discriminate between adults who reported smoking and those who reported abstinence varied with the threshold used. ECO thresholds of 6, 7, 8 and 9 parts per million (ppm) yielded the greatest area under the receiver operating characteristic curve (0.84). These thresholds produced sensitivities of 84%, 82%, 78% and 76% and specificities of 84%, 87%, 90% and 91%, respectively. However, at a threshold of 6 ppm, intersecting sensitivity (84%) and specificity (84%) were maximised with respect to each other. Biochemical validation had the highest agreement with self-report at an ECO threshold of 6 ppm (κ=0.57; 95% CI, 0.51 to 0.64).

CONCLUSION

The classification of participants' smoking status depends on the ECO threshold used for biochemical validation. We recommend that future smoking cessation trial investigators analyse and report the impact that varying ECO thresholds has on trial results.

TRIAL REGISTRATION NUMBER

NCT02417467.

Infinite hidden Markov models for multiple multivariate time series with missing data

Exposure to air pollution is associated with increased morbidity and mortality. Recent technological advancements permit the collection of time-resolved personal exposure data. Such data are often incomplete with missing observations and exposures below the limit of detection, which limit their use in health effects studies. In this paper, we develop an infinite hidden Markov model for multiple asynchronous multivariate time series with missing data. Our model is designed to include covariates that can inform transitions among hidden states. We implement beam sampling, a combination of slice sampling and dynamic programming, to sample the hidden states, and a Bayesian multiple imputation algorithm to impute missing data. In simulation studies, our model excels in estimating hidden states and state-specific means and imputing observations that are missing at random or below the limit of detection. We validate our imputation approach on data from the Fort Collins Commuter Study. We show that the estimated hidden states improve imputations for data that are missing at random compared to existing approaches. In a case study of the Fort Collins Commuter Study, we describe the inferential gains obtained from our model including improved imputation of missing data and the ability to identify shared patterns in activity and exposure among repeated sampling days for individuals and among distinct individuals.

Effects of radon exposure on gut microbiota and its metabolites short-chain fatty acids in mice

Radon (²²²Rn) is a naturally occurring radioactive gas. Forty percent of the natural radiation to which the human body is exposed comes from radon gas. Long-term exposure to high concentrations of radon induces systemic damage. However, the effect of such exposure on gut microbiota still remains unclear. We explored the effects of radon exposure on gut microbiota and its metabolites short-chain fatty acids (SCFAs) in BALB/c mice by cumulative inhalation of radon at 30, 60, and 120 working level months (WLM). The radon-exposed mice showed slow body weight gain, decreased serum triglycerides and low-density lipoproteins, decreased diversity, lower community structure, and altered abundance of the gut microbiota. Lachnospiraceae, Amaricoccus, and Enterococcus could differentiate the IR30, 60, and 120 WLM groups, respectively. Meanwhile, radon exposure affected the metabolic functions of the gut microbiota, mainly carbohydrate, amino acid, and lipid metabolic pathways. The altered abundance of microbiota and resulting reduced levels of SCFAs may aggravate the damage caused by radon exposure.

Impact of environmental factors and bacterial interactions on dust mite allergens in different indoor dust

Indoor dust is the main carrier of indoor pollutants, especially dust mite allergens and bacteria, they can trigger asthma, rhinitis, eczema and other allergic diseases. However, the interactions between dust mite allergens and bacterial communities in different types of indoor dust are not clear. The study focused on particulate and flocculent fibrous dust, explored the concentrations of Der p 1 (Dermatophagoides pteronyssinus) and Der f 1 (D. farinae) in 46 households in Changchun and their environmental influences, characterized the bacterial communities by high-throughput sequencing, and the interactions between Der p 1, Der f 1 and bacterial communities were explored. The results showed that Der p 1 and Der f 1 tended to accumulate more in flocculent fibrous dust, and Der p 1 predominated in the indoor dust samples. The floor height, years of housing occupancy and the living areas all affected the concentrations of dust mite allergens. In bacterial community, Proteobacteria, Firmicutes and Actinobacteria were leading phyla in the two types of dust. Kocuria, Blastococcus and Massilia were dominating genera in particulate dust and Acinetobacter, Lactobacillus, Corynebacterium_1 were dominating genera in flocculent fibrous dust. The overall diversity and species richness of bacteria in particulate dust were significantly higher than those in flocculent dust (p < 0.001). The living area was an important environmental factor affecting the bacterial community in flocculent fibrous dust (p < 0.01). The interaction between the relative abundance of Proteobacteria, Firmicutes and Actinobacteria and dust mite allergen concentrations significantly differed between the two dust types, indicating that bacteria could be used both as food and to establish symbiotic relationships with household dust mites (HDMs) hosts and provide nutrition.

Potential ecological and health risks of heavy metals for indoor and corresponding outdoor dust in Hefei, Central China

The harm caused by indoor dust has received increasing attention in recent years. However, current studies have ignored comparisons with the corresponding outdoor dust. This study aimed to investigate the distribution of heavy metals in indoor and corresponding outdoor dust and the ecological and health risks they pose in Hefei, Central China. We analyzed O/I (outdoor/indoor concentration ratios) values, background comparison, and correlation analysis (heavy metal concentrations vs. particle size) and found that Cu, Zn, and Cd mainly existed in indoor sources, while V, Co, and As mainly existed in outdoor sources, and both family sizes and floor number influenced the variation of O/I. Through a new potential ecological risk assessment method, we determined that Cd risk levels in indoor and outdoor dust were extreme and high to extreme, respectively. Additionally, the carcinogenic risks of Ni, As, and Cr were not negligible. The risk of indoor dust was higher than that of outdoor dust for the heavy metals studied, implying a poor indoor environment. Notably, indoor dust from families with smaller sizes, lower floors, and smokers had higher ecological and carcinogenic risks.

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.

Effect of time-activity patterns and microenvironments on the personal exposure of undergraduate students to black carbon

In this study, the personal exposure to and potential dose of black carbon (BC) of undergraduate students (22-27 years old, nonsmokers) were determined. BC was continuously measured by a portable device (microAeth^® AE51) for four consecutive days in Istanbul between April and May 2019. The time-activity diaries filled out by each volunteer were assessed to define the activities and microenvironments (home, school, transportation and entertainment) that contributed to daily BC exposure. The overall mean concentration of BC was 2.0 μg/m³, and the mean concentrations on weekdays and weekends were 3.0 μg/m³ and 1.1 μg/m³, respectively. Transportation made the highest contribution to mean BC exposure (42%) and dose (45.8%) on weekdays, while the contributions of home-based activities to BC exposure (66.1%) and dose (63.2%) were higher on weekends. Students had the most intense exposure to (2.8% and 4.6%) and dose (3.1% and 5.8%) of BC in transportation both on weekdays and on weekends, respectively. Between transportation modes, the mean BC concentration was the highest for minibuses (14.8 μg/m³), while walking made the largest contribution to BC exposure (16.8%) on weekdays. Students spent 12.8% of their weekdays at school, and the contributions of the school environment to BC exposure and dose were 8.5% and 7%, respectively. Exposure to BC increased during cooking and eating activities in microenvironments such as the kitchen, cafe and dining hall.

Realistic operation of two residential cordwood-fired outdoor hydronic heater appliances-Part 3: Optical properties of black and brown carbon emissions

Residential biomass combustion is a source of carbonaceous aerosol. Inefficient combustion, particularly of solid fuels produces large quantities of black and brown carbon (BC and BrC). These particle types are important as they have noted effects on climate forcing and human health. One method of measuring these quantities is by measurement of aerosol light-absorption and scattering, which can be performed using an aethalometer and nephelometer, respectively. These instruments are widely deployed in the study of ambient air and are frequently used in air quality modeling and source apportionment studies. In this study, we will describe (1) a method for measuring primary BC and BrC emissions from two residential log-fired wood hydronic heaters and (2) the BC and BrC emission from these devices over a wide range of operating conditions, such as cold-starts, warm-starts, four different levels of output ranging from 15% to 100% maximum rated output, and periods of repeated cycling. The range in flue-gas BC concentrations, measured using an aethalometer at the 880 nanometer (nm) wavelength, were between 5.09 × 10² and 2.24 × 10⁴ micrograms per cubic meter (µg/m³) while the scattering coefficient of the flue-gas, measured by a nephelometer at 880 nm, ranged between 2.20 × 10³ and 8.56 × 10⁵ inverse megameters (Mm^-1). The BrC concentrations, measured using the 370 nm wavelength of an aethalometer, were between 9.10 × 10¹ and 3.56 × 10⁴ µg/m³. The calculated Angstrom Absorption Exponent (AAE) of the flue-gas aerosol ranged between 1.54 and 3.63. Performing a comparison between the measured BC concentration and an external particulate matter (PM) concentration showed that overall BC makes up roughly a quarter of the PM emitted by either of the two appliances. Further for both appliances, the cold-start and the test phase immediately following it had the highest BC and BrC concentrations, the highest measured scattering coefficient, as well as a low AAE.Implications: In this work we provide information on the black and brown carbon emissions from outdoor cordwood-fired hydronic heaters. Aethalometer based black carbon measurements are common in atmospheric science, but are uncommonly used in laboratory studies. This work helps to bridge that gap. This data helps to inform the work of modelers and policy makers interested in hydronic heaters and source apportioning biomass combustion emissions.

Modeling Clothing as a Vector for Transporting Airborne Particles and Pathogens across Indoor Microenvironments

Evidence suggests that human exposure to airborne particles and associated contaminants, including respiratory pathogens, can persist beyond a single microenvironment. By accumulating such contaminants from air, clothing may function as a transport vector and source of "secondary exposure". To investigate this function, a novel microenvironmental exposure modeling framework (ABICAM) was developed. This framework was applied to a para-occupational exposure scenario involving the deposition of viable SARS-CoV-2 in respiratory particles (0.5-20 μm) from a primary source onto clothing in a nonhealthcare setting and subsequent resuspension and secondary exposure in a car and home. Variability was assessed through Monte Carlo simulations. The total volume of infectious particles on the occupant's clothing immediately after work was 4800 μm3 (5th-95th percentiles: 870-32 000 μm3). This value was 61% (5-95%: 17-300%) of the occupant's primary inhalation exposure in the workplace while unmasked. By arrival at the occupant's home after a car commute, relatively rapid viral inactivation on cotton clothing had reduced the infectious volume on clothing by 80% (5-95%: 26-99%). Secondary inhalation exposure (after work) was low in the absence of close proximity and physical contact with contaminated clothing. In comparison, the average primary inhalation exposure in the workplace was higher by about 2-3 orders of magnitude. It remains theoretically possible that resuspension and physical contact with contaminated clothing can occasionally transmit SARS-CoV-2 between humans.

Characteristics and Health Risk Assessment of Mercury Exposure via Indoor and Outdoor Household Dust in Three Iranian Cities

This study aims to increase our current knowledge on the concentration of particulate-bound mercury (PBM) in urban environments of three Iranian cities, where high concentrations of dust particles can act as carriers for mercury transport and deposition. A total of 172 dust samples were collected from Ahvaz, Asaluyeh, and Zabol residential houses and in outdoor air and were analyzed for total mercury content. Ahvaz is a highly industrialized city with large metallurgical plants, refineries, and major oil-related activities, which were assumed to contribute to elevated contents of PBM in this city. Very high levels of Hg contamination in Ahvaz indoor dust samples were calculated (Contamination Factor: CF > 6). Sampling sites in Asaluyeh are influenced by Hg emissions from the South Pars Gas Field. However, the results revealed a relatively lower concentration of PBM in Asaluyeh, with a low-to-moderate level of Hg contamination. This is likely ascribed to the lower content of total mercury in hydrocarbon gases than crude oil, in addition to the absence of metal smelting plants in this city compared to Ahvaz. Zabol, as a city devoid of industrial activity, presented the lowest levels of PBM concentration and contamination. Indoor dust in Ahvaz showed considerable potential to cause a non-carcinogenic health risk for children, mainly through the inhalation of PBM, while the health risk for other cities was below safe limits. The trend of health risk was found in the order of indoor > outdoor and children > adults in all studied cities.

Inter- and Intra-Individual Variability of Personal Health Risk of Combined Particle and Gaseous Pollutants across Selected Urban Microenvironments

Exposure surrogates, such as air quality measured at a fixed-site monitor (FSM) or residence, are typically used for health estimates. However, people spend various amounts of time in different microenvironments, including the home, office, outdoors and in transit, where they are exposed to different magnitudes of particle and gaseous air pollutants. Health risks caused by air pollution exposure differ among individuals due to differences in activity, microenvironmental concentration, as well as the toxicity of pollutants. We evaluated individual and combined added health risks (AR) of exposure to PM_2.5, NO_2, and O₃ for 21 participants in their daily life based on real-world personal exposure measurements. Exposure errors from using surrogates were quantified. Inter- and intra-individual variability in health risks and key contributors in variations were investigated using linear mixed-effects models and correlation analysis, respectively. Substantial errors were found between personal exposure concentrations and ambient concentrations when using air quality measurements at either FSM or the residence location. The mean exposure errors based on the measurements taken at either the FSM or residence as exposure surrogates was higher for NO₂ than PM_2.5, because of the larger spatial variability in NO₂ concentrations in urban areas. The daily time-integrated AR for the combined PM_2.5, NO₂, and O₃ (TIAR_combine) ranged by a factor of 2.5 among participants and by a factor up to 2.5 for a given person across measured days. Inter- and intra-individual variability in TIAR_combine is almost equally important. Several factors were identified to be significantly correlated with daily TIAR_combine, with the top five factors, including PM_2.5, NO₂ and O₃ concentrations at ‘home indoor’, O₃ concentrations at ‘office indoor’ and ambient PM_2.5 concentrations. The results on the contributors of variability in the daily TIAR_combine could help in targeting interventions to reduce daily health damage related to air pollutants.

Design and Testing of a Low-Cost Sensor and Sampling Platform for Indoor Air Quality

Americans spend most of their time indoors at home, but comprehensive characterization of in-home air pollution is limited by the cost and size of reference-quality monitors. We assembled small "Home Health Boxes" (HHBs) to measure indoor PM2.5, PM10, CO2, CO, NO2, and O3 concentrations using filter samplers and low-cost sensors. Nine HHBs were collocated with reference monitors in the kitchen of an occupied home in Fort Collins, Colorado, USA for 168 h while wildfire smoke impacted local air quality. When HHB data were interpreted using gas sensor manufacturers' calibrations, HHBs and reference monitors (a) categorized the level of each gaseous pollutant similarly (as either low, elevated, or high relative to air quality standards) and (b) both indicated that gas cooking burners were the dominant source of CO and NO2 pollution; however, HHB and reference O3 data were not correlated. When HHB gas sensor data were interpreted using linear mixed calibration models derived via collocation with reference monitors, root-mean-square error decreased for CO2 (from 408 to 58 ppm), CO (645 to 572 ppb), NO2 (22 to 14 ppb), and O3 (21 to 7 ppb); additionally, correlation between HHB and reference O3 data improved (Pearson's r increased from 0.02 to 0.75). Mean 168-h PM2.5 and PM10 concentrations derived from nine filter samples were 19.4 μg m-3 (6.1% relative standard deviation [RSD]) and 40.1 μg m-3 (7.6% RSD). The 168-h PM2.5 concentration was overestimated by PMS5003 sensors (median sensor/filter ratio = 1.7) and underestimated slightly by SPS30 sensors (median sensor/filter ratio = 0.91).

Personal exposure to PM2.5 in five commuting modes under hazy and non-hazy conditions

Effective reducing exposure to fine particulate matter (PM_2.5) during commuting can help lower the risk of adverse health effects therefrom; however, few studies have examined the influence of different background levels of air pollution-particularly in China where PM_2.5 concentrations are high globally. In this study, personal sampling was conducted to measure individual exposure during five different modes of commuting (bus, metro, car, bicycle and walking) in Shanghai, China. A total of 125 measurements were conducted for five days under haze and non-haze conditions, following which the corresponding doses of PM_2.5 inhaled were estimated. The mean concentrations (±standard deviation, SD, 1-min averaging) of background PM_2.5 were 155.9 (±98.7) μg/m³ during haze and 36.3 (±17.6) μg/m³ under the non-haze conditions. Under both conditions, active commuters were exposed to higher PM_2.5 concentrations than those using motorized commuting modes (Wilcoxon test, p < 0.01). Moreover, driving with closed windows and air conditioning effectively reduces the PM_2.5 concentrations in cars by 35 %-57 %. Cyclists inhaled the highest doses (539.8 ± 313.2 and 134.8 ± 71.3 μg/h under haze and non-haze conditions, respectively), whereas car drivers inhaled the lowest doses (28.8 ± 21.2 and 3.7 ± 2.6 μg/h under haze and non-haze conditions, respectively). Individual exposure to PM_2.5 during commuting varied with the modes; the discrepancy between the latter depended largely on the ambient concentration. Our findings provided evidence that traffic-related air pollution contributed to daily pollutant exposure and highlighted the importance of taking personal protective measures while commuting, particularly during haze.

A comprehensive exploration on pollution characteristics and health risks of potentially toxic elements in indoor dust from a large Cu smelting area, Central China

Large-scale smelting activities release large amounts of potentially toxic elements (PTEs) in fine particles. These particles floating in the air eventually settle on leaves, roads, and even indoors. In smelting areas, indoor environments are generally considered relatively safe. However, these areas are not taken seriously and need to be assessed. This paper systematically studied pollution characteristics, main sources and health risks of ten potentially toxic elements, PTEs (Mn, Ni, Cu, Zn, Hg, Cd, As, Cr, Pb, and Tl), of dust samples from different indoor environments in smelting areas using various methods. Therefore, this study analyzed dust samples from 35 indoor environments. The enrichment factors showed that the indoor dust samples were extremely enriched by Cd and Cu and significantly enriched by Hg, Pb, As, and Zn. The result of the spatial distribution showed that the high-value PTEs were mainly distributed near the Cu smeltery. Three sources were quantitatively assigned for these PTEs, and they were industrial smelting and traffic activities (44.40%), coal-fired activities (18.11%), and natural existence (37.49%). Based on the calculation of health risk, the value of THI for children was 7.57, indicating a significant non-carcinogenic risk. For carcinogenic risk, the values of TCR for children and adults were 2.91×10^-2 and 2.97×10^-3, respectively, which were much higher than the acceptable risk value 1×10^-4. Combining health risk assessment with source discrimination, we found that the industrial discharges and traffic activities were the most main source of non-cancer and cancer risks. Therefore, smelting activities should be more strictly monitored, and traffic emission management should be strengthened.

Visualising household air pollution: Colorimetric sensor arrays for monitoring volatile organic compounds indoors

Indoor air quality monitoring as it relates to the domestic setting is an integral part of human exposure monitoring and health risk assessment. Hence there is a great need for easy to use, fast and economical indoor air quality sensors to monitor the volatile organic compound composition of the air which is known to be significantly perturbed by the various source emissions from activities in the home. To meet this need, paper-based colorimetric sensor arrays were deployed as volatile organic compound detectors in a field study aiming to understand which activities elicit responses from these sensor arrays in household settings. The sensor array itself is composed of pH indicators and aniline dyes that enable molecular recognition of carboxylic acids, amines and carbonyl-containing compounds. The sensor arrays were initially deployed in different rooms in a single household having different occupant activity types and levels. Sensor responses were shown to differ for different room settings on the basis of occupancy levels and the nature of the room emission sources. Sensor responses relating to specific activities such as cooking, cleaning, office work, etc were noted in the temporal response. Subsequently, the colorimetric sensor arrays were deployed in a broader study across 9 different households and, using multivariate analysis, the sensor responses were shown to correlate strongly with household occupant activity and year of house build. Overall, this study demonstrates the significant potential for this type of simple approach to indoor air pollution monitoring in residential environments.

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.

Commuter types identified using clustering and their associations with source-specific PM2.5

Traffic-related fine particulate matter air pollution (tr-PM_2.5) has been associated with adverse health outcomes such as cardiopulmonary morbidity and mortality, with in-vehicle tr-PM_2.5 exposure contributing to total personal pollution exposure. Trip characteristics, including time of day, day of the week, and traffic congestion, are associated with in-vehicle PM_2.5 exposures. We hypothesized that some commuter characteristics, such as whether commuters travel primarily during rush hour, would also be associated with increased tr-PM_2.5 exposures. The commute data consisted of unscripted personal vehicle trips of 46 commuters in the Washington, D.C. metro area over 48-h, with a total of 320 trips. We identified commuter types using sparse K-means clustering, which identifies the hours throughout the day important for clustering commuters. Source-specific PM_2.5 over 48 h was estimated using Positive Matrix Factorization. Linear regression was used to estimate differences in source-specific PM_2.5 by commuter cluster. Two commuter clusters were identified using the clustering approach: rush hour commuters, who primarily travelled during rush hour, and sporadic commuters, who travelled throughout the day. The hours given the largest weights by sparse K-means were 7-8 a.m. and 6-7 p.m., corresponding to peak travel times. Integrated black carbon (BC) was higher for rush hour commuters (median = 3.1 μg/m³ (IQR = 1.5)) compared to sporadic commuters (2.0 μg/m³ (IQR = 1.9)). Mobile PM_2.5, consisting primarily of tailpipe emissions and brake/tire wear, was also higher for rush hour commuters (2.9 μg/m³ (IQR = 1.6)) compared to sporadic commuters (2.1 μg/m³ (IQR = 2.4)), though this difference was not statistically significant in regression models. Estimated differences between commuter types for secondary/mixed PM_2.5 and road salt PM_2.5 were smaller. Further research may elucidate whether commuter characteristics are an efficient way to identify individuals with highest tr-PM_2.5 exposures associated with commuting and to develop effective mitigation strategies.

Characterising professional drivers' exposure to traffic-related air pollution: Evidence for reduction strategies from in-vehicle personal exposure monitoring

Professional drivers working in congested urban areas are required to work near harmful traffic related pollutants for extended periods, representing a significant, but understudied occupational risk. This study collected personal black carbon (BC) exposures for 141 drivers across seven sectors in London. The aim of the study was to assess the magnitude and the primary determinants of their exposure, leading to the formulation of targeted exposure reduction strategies for the occupation. Each participant's personal BC exposures were continuously measured using real-time monitors for 96 h, incorporating four shifts per participant. 'At work' BC exposures (3.1 ± 3.5 µg/m³) were 2.6 times higher compared to when 'not at work' (1.2 ± 0.7 µg/m³). Workers spent 19% of their time 'at work driving', however this activity contributed 36% of total BC exposure, highlighting the disproportionate effect driving had on their daily exposure. Taxi drivers experienced the highest BC exposures due to the time they spent working in congested central London, while emergency services had the lowest. Spikes in exposure were observed while driving and were at times greater than 100 µg/m³. The most significant determinants of drivers' exposures were driving in tunnels, congestion, location, day of week and time of shift. Driving with closed windows significantly reduced exposures and is a simple behaviour change drivers could implement. Our results highlight strategies by which employers and local policy makers can reduce professional drivers' exposure to traffic-related air pollution.

Heavy Metals in Indoor Dust Across China: Occurrence, Sources and Health Risk Assessment

In this study, the occurrence of heavy metals including cadmium (Cd), chromium (Cr), copper (Cu), lead (Pb), and zinc (Zn) was investigated in indoor dust samples collected from 33 urban and rural areas in 11 provinces, China. The concentrations of the selected heavy metals were determined by an inductively coupled plasma mass spectrometry. The mean concentrations of Zn (166 mg kg^-1), Pb (40.7 mg kg^-1), Cr (19.8 mg kg^-1), Cu (16.9 mg kg^-1), and Cd (2.29 mg kg^-1) in indoor dust are in low or moderate levels compared with other countries or regions. Cd was significantly enriched with the highest enrichment factor of 23.7, followed by Zn, Pb, Cu, and Cr, which were all lower than 3. The concentrations of Pb from Northern China (61.4 mg kg^-1) were significantly higher than those from Southern China (8.88 mg kg^-1). The concentrations of heavy metals in indoor dusts from rural areas were higher than those from urban areas except for Cu. The multivariate analysis of variance revealed that wall cover, fuel types, and air conditioning were dominant factors influencing the levels of heavy metals in indoor dust. Principal component analysis showed that outdoor dust and wall paint were main factors for the high concentrations of Cd, Pb, and Cr, accounting for 40.6% of the total contribution; traffic sources contributed to the high levels of Cu and Zn explained 20.6% of the total variance. The hazard indexes of selected heavy metals were less than 1 and carcinogenic risk value of Cr were between 1.01 × 10^-6 and 1 × 10^-4, indicating minor noncarcinogenic and carcinogenic risks from heavy metals in indoor dust for residents in China. Pb contributed 72.0% and 86.9% to the sum of noncarcinogenic risk values of selected heavy metals for adults and children, respectively. The carcinogenic risk value of Cr was approximately 13-fold higher than that of Cd for both adults and children. Children endured higher risks from heavy metals in indoor dust compared with adults.

Joint effects of ambient air pollution and maternal smoking on neonatal adiposity and childhood BMI trajectories in the Healthy Start study

Coexposure to air pollution and tobacco smoke may influence early-life growth, but few studies have investigated their joint effects. We examined the interaction between fetal exposure to maternal smoking and ozone (O₃) or fine particulate matter (PM_2.5) on birth weight, neonatal adiposity, and body mass index (BMI) trajectories through age 3 years.

Methods

Participants were 526 mother-child pairs, born ≥37 weeks. Cotinine was measured at ~27 weeks gestation. Whole pregnancy and trimester-specific O₃ and PM_2.5 were estimated via. inverse-distance weighted interpolation from stationary monitors. Neonatal adiposity (fat mass percentage) was measured via. air displacement plethysmography. Child weight and length/height were abstracted from medical records. Interaction was assessed by introducing cotinine (<31.5 vs. ≥31.5 ng/mL [indicating active smoking]), O₃/PM_2.5 (low [tertiles 1-2] vs. high [tertile 3]), and their product term in linear regression models for birth weight and neonatal adiposity and mixed-effects models for BMI trajectories.

Results

The rate of BMI growth among offspring jointly exposed to maternal smoking and high PM_2.5 (between 8.1 and 12.7 μg/m³) in the third trimester was more rapid than would be expected due to the individual exposures alone (0.8 kg/m² per square root year; 95% CI = 0.1, 1.5; P for interaction = 0.03). We did not detect interactions between maternal smoking and O₃ or PM_2.5 at any other time on birth weight, neonatal adiposity, or BMI trajectories.

Conclusions

Although PM_2.5 was generally below the EPA annual air quality standards of 12.0 μg/m³, exposure during the third trimester may influence BMI trajectories when combined with maternal smoking.

A Spatiotemporal Prediction Model for Black Carbon in the Denver Metropolitan Area, 2009-2020

Studies on health effects of air pollution from local sources require exposure assessments that capture spatial and temporal trends. To facilitate intraurban studies in Denver, Colorado, we developed a spatiotemporal prediction model for black carbon (BC). To inform our model, we collected more than 700 weekly BC samples using personal air samplers from 2018 to 2020. The model incorporated spatial and spatiotemporal predictors and smoothed time trends to generate point-level weekly predictions of BC concentrations for the years 2009-2020. Our results indicate that our model reliably predicted weekly BC concentrations across the region during the year in which we collected data. We achieved a 10-fold cross-validation R² of 0.83 and a root-mean-square error of 0.15 μg/m³ for weekly BC concentrations predicted at our sampling locations. Predicted concentrations displayed expected temporal trends, with the highest concentrations predicted during winter months. Thus, our prediction model improves on typical land use regression models that generally only capture spatial gradients. However, our model is limited by a lack of long-term BC monitoring data for full validation of historical predictions. BC predictions from the weekly spatiotemporal model will be used in traffic-related air pollution exposure-disease associations more precisely than previous models for the region have allowed.

Dynamic classification of personal microenvironments using a suite of wearable, low-cost sensors

Human exposure to air pollution is associated with increased risk of morbidity and mortality. However, personal air pollution exposures can vary substantially depending on an individual's daily activity patterns and air quality within their residence and workplace. This work developed and validated an adaptive buffer size (ABS) algorithm capable of dynamically classifying an individual's time spent in predefined microenvironments using data from global positioning systems (GPS), motion sensors, temperature sensors, and light sensors. Twenty-two participants in Fort Collins, CO were recruited to carry a personal air sampler for a 48-h period. The personal sampler was retrofitted with a GPS and a pushbutton to complement the existing sensor measurements (temperature, motion, light). The pushbutton was used in conjunction with a traditional time-activity diary to note when the participant was located at "home", "work", or within an "other" microenvironment. The ABS algorithm predicted the amount of time spent in each microenvironment with a median accuracy of 99.1%, 98.9%, and 97.5% for the "home", "work", and "other" microenvironments. The ability to classify microenvironments dynamically in real time can enable the development of new sampling and measurement technologies that classify personal exposure by microenvironment.

Children's microenvironmental exposure to PM2.5 and ozone and the impact of indoor air filtration

BACKGROUND

In highly polluted urban areas, personal exposure to PM_2.5 and O₃ occur daily in various microenvironments. Identifying which microenvironments contribute most to exposure can pinpoint effective exposure reduction strategies and mitigate adverse health impacts.

METHODS

This work uses real-time sensors to assess the exposures of children with asthma (N = 39) in Shanghai, quantifying microenvironmental exposure to PM_2.5 and O₃. An air cleaner was deployed in participants' bedrooms where we hypothesized exposure could be most efficiently reduced. Monitoring occurred for two 48-h periods: one with bedroom filtration (portable air cleaner with HEPA and activated carbon filters) and the other without.

RESULTS

Children spent 91% of their time indoors with the majority spent in their bedroom (47%). Without filtration, the bedroom and classroom environments were the largest contributors to PM_2.5 exposure. With filtration, bedroom PM_2.5 exposure was reduced by 75% (45% of total exposure). Although filtration status did not impact O₃, the largest contribution of O₃ exposure also came from the bedroom.

CONCLUSIONS

Actions taken to reduce bedroom PM_2.5 and O₃ concentrations can most efficiently reduce total exposure. As real-time pollutant monitors become more accessible, similar analyses can be used to evaluate new interventions and optimize exposure reductions for a variety of populations.

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.

Impact of air quality on the gastrointestinal microbiome: A review

BACKGROUND

Poor air quality is increasingly associated with several gastrointestinal diseases suggesting a possible association between air quality and the human gut microbiome. However, details on this remain largely unexplored as current available research is scarce. The aim of this comprehensive rigorous review was to summarize the existing reports on the impact of indoor or outdoor airborne pollutants on the animal and human gut microbiome and to outline the challenges and suggestions to expand this field of research.

METHODS AND RESULTS

A comprehensive search of several databases (inception to August 9, 2019, humans and animals, English language only) was designed and conducted by an experienced librarian to identify studies describing the impact of air pollution on the human gut microbiome. The retrieved articles were assessed independently by two reviewers. This process yielded six original research papers on the animal GI gastrointestinal microbiome and four on the human gut microbiome. β-diversity analyses from selected animal studies demonstrated a significantly different composition of the gut microbiota between control and exposed groups but changes in α-diversity were less uniform. No consistent findings in α or β-diversity were reported among the human studies. Changes in microbiota at the phylum level disclosed substantial discrepancies across animal and human studies.

CONCLUSIONS

A different composition of the gut microbiome, particularly in animal models, is associated with exposure to air pollution. Air pollution is associated with various taxa changes, which however do not follow a clear pattern. Future research using standardized methods are critical to replicate these initial findings and advance this emerging field.

Long-standing LPG subsidies, cooking fuel stacking, and personal exposure to air pollution in rural and peri-urban Ecuador

Ecuador presents a unique case study for evaluating personal air pollution exposure in a middle-income country where a clean cooking fuel has been available at low cost for several decades. We measured personal PM_2.5 exposure, stove use, and participant location during a 48-h monitoring period for 157 rural and peri-urban households in coastal and Andean Ecuador. While nearly all households owned a liquefied petroleum gas (LPG) stove and used it as their primary cooking fuel, one-quarter of households utilized firewood as a secondary fuel and 10% used induction stoves secondary to LPG. Stove use monitoring demonstrated clear within- and across-meal fuel stacking patterns. Firewood-owning participants had higher distributions of 48-h and 10-min PM_2.5 exposure as compared with primary LPG and induction stove users, and this effect became more pronounced with firewood use during monitoring.Accounting for within-subject clustering, contemporaneous firewood stove use was associated with 101 μg/m³ higher 10-min PM_2.5 exposure (95% CI: 94-108 μg/m³). LPG and induction cooking events were largely not associated with contemporaneous PM_2.5 exposure. Our results suggest that firewood use is associated with average and short-term personal air pollution exposure above the WHO interim-I guideline, even when LPG is the primary cooking fuel.

Personal black carbon exposure and its determinants among elderly adults in urban China

Personal exposure to air pollution is affected by its concentration in the microenvironment and individual time-activity patterns. To investigate personal black carbon (BC) exposure levels and identify their potential determinants, we conducted a panel study among 67 elderly residents aged 60-69 years in Jinan, China. Personal BC exposure was measured using portable real-time monitors, while corresponding ambient BC concentrations and meteorological conditions were also collected from the local central site. Time-activity and household characteristics were recorded. A linear mixed-effects model was used to identify potential determinants of personal BC exposure. The daily average personal BC exposure concentration was 4.1 ± 2.0 μg/m³ (±standard deviation, SD), which was significantly lower than the ambient concentration (4.6 ± 2.5 μg/m³) (p < 0.001). Strong correlation (Spearman's r = 0.63, p < 0.001) was found between personal and ambient BC concentrations. The fixed-site monitoring ambient concentration cannot fully reflect the actual personal exposure concentration. Ambient BC concentration, ambient temperature, relative humidity, education level and air purifier use were significant determinants of personal BC exposure. Our findings highlight the need for detailed assessment of personal exposure on health risk assessment of BC and also help develop strategies for targeted risk reduction.

Source identification of heavy metals and stable carbon isotope in indoor dust from different functional areas in Hefei, China

Dust on air conditioning filters can represent the re-suspended particulate matter in indoor air, which may pose potential health risks to humans. However, source identification and influence factors of indoor dust are controversial. The present study investigated the distribution of Cd, Cr, Mn, Ni, Pb, Sb, V, and Zn, as well as stable carbon isotope, in indoor dust from three different functional zones in Hefei to discuss the sources and influence factors of indoor dust. PCA analysis of heavy metals showed that indoor sources (such as cooking and smoking) were the main sources. Negative correlation appeared between family size and heavy metal concentrations. This was because people acted as a sink of pollutants. Concentration analysis of heavy metals revealed that smoking and cooking had weak relevance with heavy metal concentrations. While through the δ¹³C analysis, cooking had a significant correlation with δ¹³C of indoor dust, instructing that cooking was a significant source of indoor dust. Besides, smoking also had a certain correlation with δ¹³C of indoor dust, instructing that smoking was one of the sources of indoor dust.

Logistic Modeling of the Last Mile: Case Study Santiago, Chile

This research proposes a new distribution system of goods in the historical center of the city of Santiago, Chile. For the design of the urban logistic system, the methodology city logistics and last mile are used. This design incorporates to the freight transport flexible solutions that improve the efficiency of the distribution process and trade supply, minimizing the environmental impact of the atmospheric pollution (AP). The proposal was made through the data collection, the characterization of the sector and the diagnosis of the urban logistics processes. The analysis of the factors allowed to evaluate the costs of the AP negative externalities. The causes were used as design criteria for the proposals, with the aim of improving the quality of life of the city users. The physical location selection of the Cross-Docking was made through an optimization model of maximum coverage. The optimization algorithm of the nearest neighbor was proposed for vehicle routing. The analytic hierarchy process (AHP) was used to generate a ranking of the best non-polluting vehicles to be used in the zone. Finally, the results obtained allowed a 53 ton decrease in carbon dioxide in the square kilometer and reduced 1103 h of interruptions per year in the vehicular congestion of the sector.

Assessing the accuracy of low-cost optical particle sensors using a physics-based approach

Low-cost sensors for measuring particulate matter (PM) offer the ability to understand human exposure to air pollution at spatiotemporal scales that have previously been impractical. However, such low-cost PM sensors tend to be poorly characterized, and their measurements of mass concentration can be subject to considerable error. Recent studies have investigated how individual factors can contribute to this error, but these studies are largely based on empirical comparisons and generally do not examine the role of multiple factors simultaneously. Here, we present a new physics-based framework and open-source software package (opcsim) for evaluating the ability of low-cost optical particle sensors (optical particle counters and nephelometers) to accurately characterize the size distribution and/or mass loading of aerosol particles. This framework, which uses Mie theory to calculate the response of a given sensor to a given particle population, is used to estimate the fractional error in mass loading for different sensor types given variations in relative humidity, aerosol optical properties, and the underlying particle size distribution. Results indicate that such error, which can be substantial, is dependent on the sensor technology (nephelometer vs. optical particle counter), the specific parameters of the individual sensor, and differences between the aerosol used to calibrate the sensor and the aerosol being measured. We conclude with a summary of likely sources of error for different sensor types, environmental conditions, and particle classes and offer general recommendations for the choice of calibrant under different measurement scenarios.

Implications of indoor microbial ecology and evolution on antibiotic resistance

The indoor environment is an important source of microbial exposures for its human occupants. While we naturally want to favor positive health outcomes, built environment design and operation may counter-intuitively favor negative health outcomes, particularly with regard to antibiotic resistance. Indoor environments contain microbes from both human and non-human origins, providing a unique venue for microbial interactions, including horizontal gene transfer. Furthermore, stressors present in the built environment could favor the exchange of genetic material in general and the retention of antibiotic resistance genes in particular. Intrinsic and acquired antibiotic resistance both pose a potential threat to human health; these phenomena need to be considered and controlled separately. The presence of both environmental and human-associated microbes, along with their associated antibiotic resistance genes, in the face of stressors, including antimicrobial chemicals, creates a unique opportunity for the undesirable spread of antibiotic resistance. In this review, we summarize studies and findings related to various interactions between human-associated bacteria, environmental bacteria, and built environment conditions, and particularly their relation to antibiotic resistance, aiming to guide "healthy" building design.

Overview of HOMEChem: House Observations of Microbial and Environmental Chemistry

The House Observations of Microbial and Environmental Chemistry (HOMEChem) study is a collaborative field investigation designed to probe how everyday activities influence the emissions, chemical transformations and removal of trace gases and particles in indoor air. Sequential and layered experiments in a research house included cooking, cleaning, variable occupancy, and window-opening. This paper describes the overall design of HOMEChem and presents preliminary case studies investigating the concentrations of reactive trace gases, aerosol particles, and surface films. Cooking was a large source of VOCs, CO2, NOx, and particles. By number, cooking particles were predominantly in the ultrafine mode. Organic aerosol dominated the submicron mass, and, while variable between meals and throughout the cooking process, was dominated by components of hydrocarbon character and low oxygen content, similar to cooking oil. Air exchange in the house ensured that cooking particles were present for only short periods. During unoccupied background intervals, particle concentrations were lower indoors than outdoors. The cooling coils of the house ventilation system induced cyclic changes in water soluble gases. Even during unoccupied periods, concentrations of many organic trace gases were higher indoors than outdoors, consistent with housing materials being potential sources of these compounds to the outdoor environment. Organic material accumulated on indoor surfaces, and exhibited chemical signatures similar to indoor organic aerosol.

Characteristics and health risk assessment of heavy metals in indoor dust from different functional areas in Hefei, China

Metals in indoor dust pose potential health risks to humans. Dust deposition on air conditioner filters can represent the resuspended particulate matter in indoor air. However, few studies have examined this until now. This study investigated the total concentrations and different chemical fractionations of Cd, Cr, Mn, Ni, Pb, Sb, V, and Zn in indoor dust from three different functional zones (the Chief District, Commercial District (CmD), and Industrial District) in Hefei. The mean metal concentrations in indoor dust decreased in the following order: Zn > Mn > Pb > Cr > Ni > V > Cd > Sb. Cd, Pb, and Zn mainly existed in the mobile fraction. Cr and V mainly existed in the residual fraction. The enrichment factor and geo-accumulation index values of heavy metals were all ranked in the order of Cd > Zn > Pb > Sb > Ni > Cr > V, and these values in indoor dust were larger than those in outdoor dust. In addition, the enrichment patterns of these elements were similar in the three functional areas. The orders of non-carcinogenic risk (hazard index; HI) for the different functional areas for children were roughly the same, but there were clear differences for adults. In general, all the HIs were less than 1, which were within the internationally recognized safe range. The total carcinogenic risk (TR) was in the order of Cr > Pb > Cd for both children and adults in the three functional zones. The TRs from Cr exposure were not negligible. The TRs were significantly higher in the CmD.

Variation in gravimetric correction factors for nephelometer-derived estimates of personal exposure to PM2.5

Many portable monitors for quantifying mass concentrations of particulate matter air pollution rely on aerosol light scattering as the measurement method; however, the relationship between scattered light (what is measured) and aerosol mass concentration (the metric of interest) is a complex function of the refractive index, size distribution, and shape of the particles. In this study, we compared 33-h personal PM_2.5 concentrations measured simultaneously using nephelometry (personal DataRAM pDR-1200) and gravimetric filter sampling for working adults (44 participants, 249 samples). Nephelometer- and filter-derived 33-h average PM_2.5 concentrations were correlated (Spearman's ρ = 0.77); however, the nephelometer-derived concentration was within 20% of the filter-derived concentration for only 13% of samples. The nephelometer/filter ratio, which is used to correct light-scattering measurements to a gravimetric sample, had a median value of 0.52 and varied by over a factor of three (10th percentile = 0.35, 90^th percentile = 1.1). When 33-h samples with >50% of 10-s average nephelometer readings below the nephelometer limit of detection were removed from the dataset during sensitivity analyses, the fraction of nephelometer-derived concentrations that were within 20% of the filter-derived concentration increased to 25%. We also evaluated how much the accuracy of nephelometer-derived concentrations improved after applying: (1) a median correction factor derived from a subset of 44 gravimetric samples, (2) participant-specific correction factors derived from one same from each subject, and (3) correction factors predicted using linear models based on other variables recorded during the study. Each approach independently increased the fraction of nephelometer-derived concentrations that were within 20% of the filter-derived concentration to approximately 45%. These results illustrate the challenges with using light scattering (without correction to a concurrent gravimetric sample) to estimate personal exposure to PM_2.5 mass among mobile adults exposed to low daily average concentrations (median = 8 μg m^-3 in this study).

Assessing exposure to outdoor air pollution for epidemiological studies: Model-based and personal sampling strategies

Epidemiologic studies have found air pollution to be causally linked to respiratory health including the exacerbation and development of childhood asthma. Accurately characterizing exposure is paramount in these studies to ensure valid estimates of health effects. Here, we provide a brief overview of the evolution of air pollution exposure assessment ranging from the use of ground-based, single-site air monitoring stations for population-level estimates to recent advances in spatiotemporal models, which use advanced machine learning algorithms and satellite-based data to accurately estimate individual-level daily exposures at high spatial resolutions. In addition, we review recent advances in sensor technology that enable the use of personal monitoring in epidemiologic studies, long-considered the "holy grail" of air pollution exposure assessment. Finally, we highlight key advantages and uses of each approach including the generalizability and public health relevance of air pollution models and the accuracy of personal monitors that are useful to guide personalized prevention strategies. Investigators and clinicians interested in the effects of air pollution on allergic disease and asthma should carefully consider the pros and cons of each approach to guide their application in research and practice.

An accurate filter loading correction is essential for assessing personal exposure to black carbon using an Aethalometer

The AE51 micro-Aethalometer (microAeth) is a popular and useful tool for assessing personal exposure to particulate black carbon (BC). However, few users of the AE51 are aware that its measurements are biased low (by up to 70%) due to the accumulation of BC on the filter substrate over time; previous studies of personal black carbon exposure are likely to have suffered from this bias. Although methods to correct for bias in micro-Aethalometer measurements of particulate black carbon have been proposed, these methods have not been verified in the context of personal exposure assessment. Here, five Aethalometer loading correction equations based on published methods were evaluated. Laboratory-generated aerosols of varying black carbon content (ammonium sulfate, Aquadag and NIST diesel particulate matter) were used to assess the performance of these methods. Filters from a personal exposure assessment study were also analyzed to determine how the correction methods performed for real-world samples. Standard correction equations produced correction factors with root mean square errors of 0.10 to 0.13 and mean bias within ±0.10. An optimized correction equation is also presented, along with sampling recommendations for minimizing bias when assessing personal exposure to BC using the AE51 micro-Aethalometer.