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1
Ashmore, M. R., and C. Dimitroulopoulou. "Personal exposure of children to air pollution." Atmospheric Environment 43, no. 1 (January 2009): 128–41. http://dx.doi.org/10.1016/j.atmosenv.2008.09.024.
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Gulliver, J., and D. J. Briggs. "Personal exposure to particulate air pollution in transport microenvironments." Atmospheric Environment 38, no. 1 (January 2004): 1–8. http://dx.doi.org/10.1016/j.atmosenv.2003.09.036.
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Johnston, James D., Scott C. Collingwood, James D. LeCheminant, Neil E. Peterson, Paul R. Reynolds, Juan A. Arroyo, Andrew J. South, et al. "Personal Exposure to Fine Particulate Air Pollution among Brick Workers in Nepal." Atmosphere 14, no. 12 (December 2, 2023): 1783. http://dx.doi.org/10.3390/atmos14121783.
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Prior studies suggest brick workers in Nepal may be chronically exposed to hazardous levels of fine particulate matter (PM2.5) from ambient, occupational, and household sources. However, findings from these studies were based on stationary monitoring data, and thus may not reflect a worker’s individual exposures. In this study, we used RTI International’s MicroPEMs to collect 24 h PM2.5 personal breathing zone (PBZ) samples among brick workers (n = 48) to estimate daily exposures from ambient, occupational, and household air pollution sources. Participants were sampled from five job categories at one kiln. The geometric mean (GM) PM2.5 exposure across all participants was 116 µg/m3 (95% confidence interval [CI]: 94.03, 143.42). Job category was significantly (p < 0.001) associated with PBZ PM2.5 concentrations. There were significant pairwise differences in geometric mean (GM) PBZ PM2.5 concentrations among workers in administration (GM: 47.92, 95% CI: 29.81, 77.03 µg/m3) vs. firemen (GM: 163.46, 95 CI: 108.36, 246.58 µg/m3, p = 0.003), administration vs. green brick hand molder (GM: 163.35, 95% CI: 122.15, 218.46 µg/m3, p < 0.001), administration vs. top loader (GM: 158.94, 95% CI: 102.42, 246.66 µg/m3, p = 0.005), firemen vs. green brick machine molder (GM: 73.18, 95% CI: 51.54, 103.90 µg/m3, p = 0.03), and green brick hand molder vs. green brick machine molder (p = 0.008). Temporal exposure trends suggested workers had chronic exposure to hazardous levels of PM2.5 with little to no recovery period during non-working hours. Multi-faceted interventions should focus on the control of ambient and household air pollution and tailored job-specific exposure controls.
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Chatzidiakou, Lia, Anika Krause, Olalekan A. M. Popoola, Andrea Di Antonio, Mike Kellaway, Yiqun Han, Freya A. Squires, et al. "Characterising low-cost sensors in highly portable platforms to quantify personal exposure in diverse environments." Atmospheric Measurement Techniques 12, no. 8 (August 30, 2019): 4643–57. http://dx.doi.org/10.5194/amt-12-4643-2019.
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Abstract. The inaccurate quantification of personal exposure to air pollution introduces error and bias in health estimations, severely limiting causal inference in epidemiological research worldwide. Rapid advancements in affordable, miniaturised air pollution sensor technologies offer the potential to address this limitation by capturing the high variability of personal exposure during daily life in large-scale studies with unprecedented spatial and temporal resolution. However, concerns remain regarding the suitability of novel sensing technologies for scientific and policy purposes. In this paper we characterise the performance of a portable personal air quality monitor (PAM) that integrates multiple miniaturised sensors for nitrogen oxides (NOx), carbon monoxide (CO), ozone (O3) and particulate matter (PM) measurements along with temperature, relative humidity, acceleration, noise and GPS sensors. Overall, the air pollution sensors showed high reproducibility (mean R‾2=0.93, min–max: 0.80–1.00) and excellent agreement with standard instrumentation (mean R‾2=0.82, min–max: 0.54–0.99) in outdoor, indoor and commuting microenvironments across seasons and different geographical settings. An important outcome of this study is that the error of the PAM is significantly smaller than the error introduced when estimating personal exposure based on sparsely distributed outdoor fixed monitoring stations. Hence, novel sensing technologies such as the ones demonstrated here can revolutionise health studies by providing highly resolved reliable exposure metrics at a large scale to investigate the underlying mechanisms of the effects of air pollution on health.
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Gerding, Thomas, Jun Wang, and Nicholas Newman. "Examining Work Stress and Air Pollutants Exposure of Home Healthcare Workers." Atmosphere 14, no. 9 (September 3, 2023): 1393. http://dx.doi.org/10.3390/atmos14091393.
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Occupational exposures in on-campus healthcare settings have increasingly been investigated, while the sector of home healthcare typically receives less focus. This study explored work stress exposure and air pollution’s effects on home healthcare workers through the collection of multiple salivary cortisol samples per day, the completion of stress diaries, and the use of low-cost personal air monitors. This study was designed to identify the physiological responses to various types of stress, as well as the impact of air pollution on the home healthcare workforce. Due to the sample size and duration, the data showed that neither the stress levels recorded in the diaries (p = 0.754), nor the air pollution data (with only VOC and PM1 having Pearson correlation coefficients of >0.25), exhibited a significant association with the cortisol levels. The air sensor data were inconsistent with previously published indoor air pollutant literature. Forty percent of events reported by participants were identified as high stressor (level 6–10) events. One participant in this study accounted for 18% of these high-stress events. The most common emotional responses to these stressor events included feelings of frustration, irritation, anger, and fury, which together comprised 22.4% of the reactions. Future work should include studies with a larger sample size, a more robust air quality monitor, and a longer study duration to improve the power to detect potential associations. Although previous studies have indicated that home healthcare workers experience workplace stress and exposure to multiple air pollutants, this study did not detect a consistent relationship between these exposures and the physiological stress response.
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Han, Yiqun, Wu Chen, Lia Chatzidiakou, Anika Krause, Li Yan, Hanbin Zhang, Queenie Chan, et al. "Effects of AIR pollution on cardiopuLmonary disEaSe in urban and peri-urban reSidents in Beijing: protocol for the AIRLESS study." Atmospheric Chemistry and Physics 20, no. 24 (December 18, 2020): 15775–92. http://dx.doi.org/10.5194/acp-20-15775-2020.
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Abstract. Beijing, as a representative megacity in China, is experiencing some of the most severe air pollution episodes in the world, and its fast urbanization has led to substantial urban and peri-urban disparities in both health status and air quality. Uncertainties remain regarding the possible causal links between individual air pollutants and health outcomes, with spatial comparative investigations of these links lacking, particularly in developing megacities. In light of this challenge, Effects of AIR pollution on cardiopuLmonary disEaSe in urban and peri-urban reSidents in Beijing (AIRLESS) was initiated, with the aim of addressing the complex issue of relating multi-pollutant exposure to cardiopulmonary outcomes. This paper presents the novel methodological framework employed in the project, namely (1) the deployment of two panel studies from established cohorts in urban and peri-urban Beijing, with different exposure settings regarding pollution levels and diverse sources; (2) the collection of detailed measurements and biomarkers of participants from a nested case (hypertensive) and control (healthy) study setting; (3) the assessment of indoor and personal exposure to multiple gaseous pollutants and particulate matter at unprecedented spatial and temporal resolution with validated novel sensor technologies; (4) the assessment of ambient air pollution levels in a large-scale field campaign, particularly the chemical composition of particulate matter. Preliminary results showed that there is a large difference between ambient and personal air pollution levels, and the differences varied between seasons and locations. These large differences were reflected on the different health responses between the two panels.
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Kim, Kyung Hwan, Kyung-Hwan Kwak, Jae Young Lee, Sung Ho Woo, Jong Bum Kim, Seung-Bok Lee, Sung Hee Ryu, Chang Hyeok Kim, Gwi-Nam Bae, and Inbo Oh. "Spatial Mapping of a Highly Non-Uniform Distribution of Particle-Bound PAH in a Densely Populated Urban Area." Atmosphere 11, no. 5 (May 12, 2020): 496. http://dx.doi.org/10.3390/atmos11050496.
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In this work, a 2-D gridded air pollution map with a high resolution of 50 × 50 m2 was proposed to help the exposure assessment studies focusing on the association between air pollutants and their health effects. To establish a reliable air pollution map in a 2 × 2 km2 urban area, a mobile monitoring procedure and a data process were developed. Among the various vehicle-related air pollutants, the particle-bound polycyclic aromatic hydrocarbon (pPAH) was chosen as a sensitive indicator. The average pPAH concentration on major roads (293.1 ng/m3) was found to be 35 times higher than that at a background location (8.4 ng/m3). Based on the cell-based pPAH concentrations, the 50 × 50 m2 cells in the air pollution map were categorized into five pollution levels. The higher air pollution levels were generally shown by the cells close to the major traffic emission points. The proposed map can be used to make various policies regarding land use and traffic flow control in urban areas. Estimation of the personal exposure level to air pollutants is possible at a reliable location using the highly resolved 2-D gridded air pollution map in exposure assessment studies.
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Lyon-Caen, Sarah, Valérie Siroux, Johanna Lepeule, Philippe Lorimier, Pierre Hainaut, Pascal Mossuz, Joane Quentin, et al. "Deciphering the Impact of Early-Life Exposures to Highly Variable Environmental Factors on Foetal and Child Health: Design of SEPAGES Couple-Child Cohort." International Journal of Environmental Research and Public Health 16, no. 20 (October 14, 2019): 3888. http://dx.doi.org/10.3390/ijerph16203888.
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In humans, studies based on Developmental Origins of Health and Disease (DOHaD) concept and targeting short half-lived chemicals, including many endocrine disruptors, generally assessed exposures from spot biospecimens. Effects of early-life exposure to atmospheric pollutants were reported, based on outdoor air pollution levels. For both exposure families, exposure misclassification is expected from these designs: for non-persistent chemicals, because a spot biospecimen is unlikely to capture exposure over windows longer than a few days; for air pollutants, because indoor levels are ignored. We developed a couple-child cohort relying on deep phenotyping and extended personal exposure assessment aiming to better characterize the effects of components of the exposome, including air pollutants and non-persistent endocrine disruptors, on child health and development. Pregnant women were included in SEPAGES couple-child cohort (Grenoble area) from 2014 to 2017. Maternal and children exposure to air pollutants was repeatedly assessed by personal monitors. DNA, RNA, serum, plasma, placenta, cord blood, meconium, child and mother stools, living cells, milk, hair and repeated urine samples were collected. A total of 484 pregnant women were recruited, with excellent compliance to the repeated urine sampling protocol (median, 43 urine samples per woman during pregnancy). The main health outcomes are child respiratory health using early objective measures, growth and neurodevelopment. Compared to former studies, the accuracy of assessment of non-persistent exposures is expected to be strongly improved in this new type of birth cohort tailored for the exposome concept, with deep phenotyping and extended exposure characterization. By targeting weaknesses in exposure assessment of the current approaches of cohorts on effects of early life environmental exposures with strong temporal variations, and relying on a rich biobank to provide insight on the underlying biological pathways whereby exposures affect health, this design is expected to provide deeper understanding of the interplay between the Exposome and child development and health.
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Aljofi, Halah E., Thomas J. Bannan, Michael Flynn, James Evans, David Topping, Emily Matthews, Sebastian Diez, et al. "Study of the Suitability of a Personal Exposure Monitor to Assess Air Quality." Atmosphere 15, no. 3 (March 2, 2024): 315. http://dx.doi.org/10.3390/atmos15030315.
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Low-cost personal exposure monitors (PEMs) to measure personal exposure to air pollution are potentially promising tools for health research. However, their adoption requires robust validation. This study evaluated the performance of twenty-one Plume Lab Flow2s (PLFs) by comparing its air pollutant measurements, particulate matter with a diameter of 2.5 μm or less (PM2.5), 10 μm or less (PM10), and nitrogen dioxide (NO2), against several high-quality air pollution monitors under field conditions (at indoor, outdoor, and roadside locations). Correlation and regression analysis were used to evaluate measurements obtained by different PLFs against reference instrumentation. For all measured pollutants, the overall correlation coefficient between the PLFs and the reference instruments was often weak (r < 0.4). Moderate correlation was observed for one PLF unit at the indoor location and two units at the roadside location when measuring PM2.5, but not for PM10 and NO2 concentration. During periods of particularly higher pollution, 11 PLF tools showed stronger regression results (R2 values > 0.5) with one-hour and 9 PLF units with one-minute time interval. Results show that the PLF cannot be used robustly to determine high and low exposure to poor air. Therefore, the use of PLFs in research studies should be approached with caution if data quality is important to the research outputs.
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Piedrahita, Ricardo, Evan R. Coffey, Yolanda Hagar, Ernest Kanyomse, Christine Wiedinmyer, Katherine L. Dickinson, Abraham Oduro, and Michael P. Hannigan. "Exposures to Carbon Monoxide in a Cookstove Intervention in Northern Ghana." Atmosphere 10, no. 7 (July 16, 2019): 402. http://dx.doi.org/10.3390/atmos10070402.
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Biomass burning for home energy use is a major environmental health concern. Improved cooking technologies could generate environmental health benefits, yet prior results regarding reduced personal exposure to air pollution are mixed. In this study, two improved stove types were distributed over four study groups in Northern Ghana. Participants wore real-time carbon monoxide (CO) monitors to measure the effect of the intervention on personal exposures. Relative to the control group (those using traditional stoves), there was a 30.3% reduction in CO exposures in the group given two Philips forced draft stoves (p = 0.08), 10.5% reduction in the group given two Gyapa stoves (locally made rocket stoves) (p = 0.62), and 10.2% reduction in the group given one of each (p = 0.61). Overall, CO exposure for participants was low given the prevalence of cooking over traditional three-stone fires, with 8.2% of daily samples exceeding WHO Tier-1 standards. We present quantification methods and performance of duplicate monitors. We analyzed the relationship between personal carbonaceous particulate matter less than 2.5 microns (PM2.5) and CO exposure for the dataset that included both measurements, finding a weak relationship likely due to the diversity of identified air pollution sources in the region and behavior variability.
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Tawiah, Theresa, Matthew Shupler, Stephaney Gyaase, Rachel Anderson de Cuevas, Jason Saah, Emily Nix, Mieks Twumasi, et al. "The Association between Household Air Pollution and Blood Pressure in Obuasi Municipality, Ghana." Atmosphere 13, no. 12 (December 3, 2022): 2033. http://dx.doi.org/10.3390/atmos13122033.
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Emerging evidence suggests a possible link between exposure to household air pollution (HAP) from a reliance on polluting solid fuels (SFs) (e.g., wood and charcoal) for cooking and high blood pressure. As part of the CLEAN-Air(Africa) project, we measured the blood pressure among 350 cooks in Obuasi Municipality, Ghana after 24 h exposure to particulate matter (PM2.5) from the combustion of either solid fuels (n = 35) or liquefied petroleum gas (LPG) (n = 35). Multinomial regression models were used to describe the relationship between different stages of blood pressure (mmHg) and the respondents’ main fuel type used, adjusting for key covariates. A linear regression model was used to describe the relationship between personal exposure to PM2.5 and the respondent’s systolic as well as diastolic blood pressure, adjusting for key covariates. Blood pressure was higher in cooks using SFs for cooking than in those using LPG. A significant exposure–response relationship was not observed between increasing exposure to PM2.5 and increasing blood pressure (systolic: β = −2.42, 95% CI: −8.65, 3.80, p-value = 0.438, and diastolic: β = −0.32, 95% CI: −5.09; 4.45, p-value = 0.893).
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Berlinger, Balázs, Péter Fehérvári, Csaba Kővágó, Katalin Lányi, Gábor Mátis, Máté Mackei, and László Könyves. "There Is Still a Need for a Comprehensive Investigation of the Health Consequences of Exposure to Urban Air with Special Regard to Particulate Matter (PM) and Cardiovascular Effects." Atmosphere 15, no. 3 (February 28, 2024): 296. http://dx.doi.org/10.3390/atmos15030296.
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Air pollution is a foremost public health problem worldwide. The pulmonary effects of air pollution have been well established for decades, and substantial epidemiological evidence is consistently showing that both acute and chronic exposure to air pollution is linked to cardiovascular morbidity and mortality. The underlying cause for this link is, however, still unknown, and many questions remain open. Most of the epidemiological studies focusing on health consequences of exposure to urban air used data from air monitoring stations or—when applying personal sampling or monitoring—measured a limited number of components to assess the exposure. On the other hand, studies conducting a decent exposure characterization and measuring a relatively large number of components with personal sampling had little or no focus on the effects and investigated only a few biomarkers. The number of research studies on this topic is huge, but at the same time, it seems as if there was no need for a comprehensive examination of the effects of urban air pollution on health. Researchers and research supporting organizations, in their fascination with the search for “novelty” and “beyond state-of-the-art”, do not seem to be aware of that they will never be able to assemble the whole picture from the puzzle pieces of research activities focusing only on certain aspects. Without a comprehensive investigation, we might never be able to answer such questions as (i) which of the urban air pollutants are forerunners in causing health effects, especially cardiovascular effects? (ii) Which biomarkers have the best predictor performance in early effects? (iii) Are there biomarkers or combinations of biomarkers that can help determine the degree of individual susceptibility and sensitivity and the dependence of these by different factors (e.g., age, gender, and physical activity)? The authors of this article aim to go through the already investigated—at the same time, essential—elements of the topic and propose a more comprehensive study, which, of course, can be expanded, debated, and improved.
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Pal, Vineet Kumar, and Haider A. Khwaja. "Personal Exposure and Inhaled Dose Estimation of Air Pollutants during Travel between Albany, NY and Boston, MA." Atmosphere 13, no. 3 (March 9, 2022): 445. http://dx.doi.org/10.3390/atmos13030445.
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Out of eight deaths caused worldwide, one death is caused due to air pollution exposure, making it one of the top global killers. Personal exposure measurement for real-time monitoring has been used for inhaled dose estimation during various modes of workplace commuting. However, dose-exposure studies during long commutes are scarce and more information on inhaled doses is needed. This study focuses on personal exposures to size-fractionated particulate matter (PM1, PM2.5, PM4, PM7, PM10, TSP) and black carbon (BC) inside a bus traveling more than 270 kms on a highway between Albany, NY and Boston, MA. Measurements were also made indoors, outdoors, and while walking in each city. Mean PM (PM1, PM2.5, PM4, PM7, PM10, TSP) and mean BC concentrations were calculated to estimate the inhaled exposure dose. The highest average PM2.5 and PM10 exposures concentrations were 30 ± 12 and 111 ± 193 µg/m3, respectively, during Boston to Albany. Notably, personal exposure to BC on a bus from Albany to Boston (5483 ± 2099 ng/m3) was the highest measured during any commute. The average inhaled dose for PM2.5 during commutes ranged from 0.018 µg/km to 0.371 µg/km. Exposure concentrations in indoor settings (average PM2.5 = 37 ± 55 µg/m3, PM10 = 78 ± 82 µg/m3, BC = 5695 ± 1774 ng/m3) were higher than those in outdoor environments. Carpeted flooring, cooking, and vacuuming all tended to increase the indoor particulate level. A high BC concentration (1583 ± 1004 ng/m3) was measured during walking. Typical concentration profiles in long-haul journeys are presented.
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Piedrahita, Ricardo, Evan R. Coffey, Yolanda Hagar, Ernest Kanyomse, Katelin Verploeg, Christine Wiedinmyer, Katherine L. Dickinson, Abraham Oduro, and Michael P. Hannigan. "Attributing Air Pollutant Exposure to Emission Sources with Proximity Sensing." Atmosphere 10, no. 7 (July 13, 2019): 395. http://dx.doi.org/10.3390/atmos10070395.
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Biomass burning for home energy use contributes to negative health outcomes and environmental degradation. As part of the REACCTING study (Research on Emissions, Air quality, Climate, and Cooking Technologies in Northern Ghana), personal exposure to carbon monoxide (CO) was measured to gauge the effects of introducing two different cookstove types over four intervention groups. A novel Bluetooth Low-Energy (BLE) Beacon system was deployed on a subset of those CO measurement periods to estimate participants’ distances to their most-used cooking areas during the sampling periods. In addition to presenting methods and validation for the BLE Beacon system, here we present pollution exposure assessment modeling results using two different approaches, in which time-activity (proximity) data is used to: (1) better understand exposure and behaviors within and away from homes; and (2) predict personal exposure via microenvironment air quality measurements. Model fits were improved in both cases, demonstrating the benefits of the proximity measurements.
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Huang, Xinheng. "The Impact of PM10 and Other Airborne Particulate Matter on the Cardiopulmonary and Respiratory Systems of Sports Personnel under Atmospheric Exposure." Atmosphere 14, no. 11 (November 17, 2023): 1697. http://dx.doi.org/10.3390/atmos14111697.
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Respirable particulate matter (PM10) is atmospheric particulate matter with a kinetic diameter of less than or equal to 10 μm in air. According to the definition of the World Health Organization, it is called thoracic-enterable particulate matter because it can enter the body through the respiratory tract and be deposited into the lungs or absorbed into the blood and lymphatic systems. The toxic substances in it can enter the bloodstream directly and cause serious harm to human health. In addition, PM10 has unique physiological and biological effects, making it an important area of atmospheric chemistry research. In this study, two urban neighborhoods and sports companies were selected for the purpose of investigating the effects of PM10 concentrations in the air of neighborhoods and workplaces on people living and working in these environments for a long period of time, as well as synergistic effects between PM10 concentrations and changes in temperature and the incidence of related diseases. By assessing the extent of PM10’s impact on the respiratory system, this study provides basic data for assessing the health hazards of particulate matter in community environments. This study also analyzed the synergistic effects between air pollutant concentrations, temperature changes, and the incidence of related diseases in two cities to investigate the spatial and temporal distribution characteristics of air pollution and the meteorological causes of pollution in China. On this basis, we established a prediction model for related sensitivity diseases to provide theoretical and technical support for the prediction of related sensitivity diseases on a nationwide scale. Meanwhile, our study also provides support to relevant government departments to formulate a scientific basis and preventive and control measures for dealing with air pollution and its effects on human health.
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Breen, Michael, Shih Ying Chang, Miyuki Breen, Yadong Xu, Vlad Isakov, Saravanan Arunachalam, Martha Sue Carraway, and Robert Devlin. "Fine-Scale Modeling of Individual Exposures to Ambient PM2.5, EC, NOx, and CO for the Coronary Artery Disease and Environmental Exposure (CADEE) Study." Atmosphere 11, no. 1 (January 3, 2020): 65. http://dx.doi.org/10.3390/atmos11010065.
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Air pollution epidemiological studies often use outdoor concentrations from central-site monitors as exposure surrogates, which can induce measurement error. The goal of this study was to improve exposure assessments of ambient fine particulate matter (PM2.5), elemental carbon (EC), nitrogen oxides (NOx), and carbon monoxide (CO) for a repeated measurements study with 15 individuals with coronary artery disease in central North Carolina called the Coronary Artery Disease and Environmental Exposure (CADEE) study. We developed a fine-scale exposure modeling approach to determine five tiers of individual-level exposure metrics for PM2.5, EC, NOx, and CO using outdoor concentrations, on-road vehicle emissions, weather, home building characteristics, time-locations, and time-activities. We linked an urban-scale air quality model, residential air exchange rate model, building infiltration model, global positioning system (GPS)-based microenvironment model, and accelerometer-based inhaled ventilation model to determine residential outdoor concentrations (Cout_home, Tier 1), residential indoor concentrations (Cin_home, Tier 2), personal outdoor concentrations (Cout_personal, Tier 3), exposures (E, Tier 4), and inhaled doses (D, Tier 5). We applied the fine-scale exposure model to determine daily 24 h average PM2.5, EC, NOx, and CO exposure metrics (Tiers 1–5) for 720 participant-days across the 25 months of the CADEE study. Daily modeled metrics showed considerable temporal and home-to-home variability of Cout_home and Cin_home (Tiers 1–2) and person-to-person variability of Cout_personal, E, and D (Tiers 3–5). Our study demonstrates the ability to apply an urban-scale air quality model with an individual-level exposure model to determine multiple tiers of exposure metrics for an epidemiological study, in support of improving health risk assessments.
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Madueño, Leizel, Simonas Kecorius, Marcos Andrade, and Alfred Wiedensohler. "Exposure and Respiratory Tract Deposition Dose of Equivalent Black Carbon in High Altitudes." Atmosphere 11, no. 6 (June 5, 2020): 598. http://dx.doi.org/10.3390/atmos11060598.
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The traffic microenvironment accounts for a significant fraction of the total daily dose of inhaled air pollutants. The adverse effects of air pollution may be intensified in high altitudes (HA) due to increased minute ventilation (MV), which may result in higher deposition doses compared to that at sea level. Despite this, air quality studies in regions with combined high pollution levels and enhanced inhalation are limited. The main goals of this study are to investigate how the choice of travel mode (walking, microbus, and cable car ride) determines (i) the personal exposure to equivalent black carbon (eBC) and (ii) the corresponding potential respiratory deposited dose (RDD) in HA. For this investigation, we chose La Paz and El Alto in Bolivia as HA representative cities. The highest eBC exposure occurred in microbus commutes (13 μg m−3), while the highest RDD per trip was recorded while walking (6.3 μg) due to increased MV. On the other hand, the lowest eBC exposure and RDD were observed in cable car commute. Compared with similar studies done at sea level, our results revealed that a HA city should reduce exposure by 1.4 to 1.8-fold to achieve similar RDD at sea level, implying that HA cities require doubly aggressive and stringent road emission policies compared to those at sea level.
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McNabola, Aonghus. "New Directions: Passive control of personal air pollution exposure from traffic emissions in urban street canyons." Atmospheric Environment 44, no. 24 (August 2010): 2940–41. http://dx.doi.org/10.1016/j.atmosenv.2010.04.005.
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Sankhyan, Sumit, Nicholas Clements, Allison Heckman, Aniya K. Hollo, Dulce Gonzalez-Beltran, Jonathan Aumann, Cora Morency, Luke Leiden, and Shelly L. Miller. "Optimization of a Do-It-Yourself Air Cleaner Design to Reduce Residential Air Pollution Exposure for a Community Experiencing Environmental Injustices." Atmosphere 14, no. 12 (November 25, 2023): 1734. http://dx.doi.org/10.3390/atmos14121734.
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The large-scale deployment of Do-it-yourself (DIY) air cleaners, especially in communities that historically bear the brunt of air pollution exposure-related injustices, provides communities a cost-effective option to reduce personal indoor exposure to particulate matter. In this study, we developed nine air cleaner prototypes, altering filter depth and the number and type of filters, and compared their PM2.5 removal effectiveness and maintenance-related parameters prior to deployment in North Denver, Colorado homes. Prototypes containing multiple high efficiency particulate air filters with a minimum reporting value of 13 (MERV13) had higher clean air delivery rates (CADR, >300 m3 h−1) compared to prototypes using a single filter (100–200 m3 h−1), but single-filter designs had comparable values of CADR normalized by initial and annual operating costs. Based on performance, cost, build time, and feedback from the community regarding concerns related to volatile organic compound exposure, the selected prototype (P9) used a combination of an activated carbon filter and single MERV13 filter with a 10.16 cm (4-inch) depth. Following this assessment, 120 of the selected air cleaner prototypes were built and deployed in homes around the communities in North Denver for two separate cohorts; feedback regarding their usage over the course of the deployment showed that in addition to the increased noise levels perceived by the participants, factors such as cold air flow from the air cleaner impacting the thermal comfort and aesthetics of the design reduced their usage time in homes. Future designs of DIY air cleaners could incorporate this feedback to help design improved features such as quieter air cleaners and real-time pollutant monitoring feedback to prompt users to keep them operational at all times of the day.
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Reyna, Marco A., Daniel Cuevas-González, Roberto L. Avitia, Efrain C. Nieblas, Juan V. Mérida, and Martha L. Nava. "Identification of Surveillance Procedures for Diseases and Deaths Potentially Caused by Air Pollution and Possible Solutions as a Proposal for a Binational Surveillance System: A Case Study of Mexicali B.C., México-Imperial Valley, United States." Atmosphere 14, no. 3 (March 7, 2023): 515. http://dx.doi.org/10.3390/atmos14030515.
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In this paper, an integrative analysis is conducted for both sides of the border of Mexicali B.C. and Imperial Valley, regarding the official procedures and ways in which the collection, organization and disposal of data is carried out for the following: pollutant molecules such as PM2.5, PM10, CO, and O3; meteorological data such as temperature and relative humidity; data produced by epidemiological surveillance of acute respiratory infections; and deaths from all causes minus external ones. Some points around the binational surveillance system, raised in a technical report, are collected, giving continuity to the previous work carried out on this matter. Challenges are identified, recommendations are made, and possible solutions are offered to achieve a binational, unified and integrative system that centralizes meteorological, clinical, and pollution data, and that guarantees the quality and expeditious availability of the data concerning of the effects of air pollution on respiratory diseases and/or natural deaths of the local population. According to our results, air monitoring in Mexicali, clinical data on acute respiratory infections, morbidity, and mortality records must be improved, as well as the cooperation and coordination with the institutions of Imperial Valley. Finally, we show that despite the deficiencies and limitations found in the data generated in the locality, especially data on pollution and clinical data, it is possible, with great effort, to build models that measure and explain the effects of air pollution on health. Examples include the relative risk of death from exposure to PM2.5, PM10, CO, and O3; particulate matter air pollution effects on activation of pulmonary tuberculosis; the association between personal PM10 exposure and pulmonary function; and the estimation of costs and public health benefits by PM10 mitigation, among others.
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Masri, Shahir, Jose Rea, and Jun Wu. "Use of Low-Cost Sensors to Characterize Occupational Exposure to PM2.5 Concentrations Inside an Industrial Facility in Santa Ana, CA: Results from a Worker- and Community-Led Pilot Study." Atmosphere 13, no. 5 (May 1, 2022): 722. http://dx.doi.org/10.3390/atmos13050722.
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PM2.5 is an air contaminant that has been widely associated with adverse respiratory and cardiovascular health, leading to increased hospital admissions and mortality. Following concerns reported by workers at an industrial facility located in Santa Ana, California, workers and community leaders collaborated with experts in the development of an air monitoring pilot study to measure PM2.5 concentrations to which employees and local residents are exposed during factory operating hours. To detect PM2.5, participants wore government-validated AtmoTube Pro personal air monitoring devices during three separate workdays (5 AM–1:30 PM) in August 2021. Results demonstrated a mean PM2.5 level inside the facility of 112.3 µg/m3, nearly seven-times greater than outdoors (17.3 µg/m3). Of the eight workers who wore personal indoor sampling devices, five showed measurements over 100 μg/m3. Welding-related activity inside the facility resulted in the greatest PM2.5 concentrations. This study demonstrates the utility of using low-cost air quality sensors combined with employee knowledge and participation for the investigation of workplace air pollution exposure as well as facilitation of greater health-related awareness, education, and empowerment among workers and community members. Results also underscore the need for basic measures of indoor air pollution control paired with ongoing air monitoring within the Santa Ana facility, and the importance of future air monitoring studies aimed at industrial facilities.
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Tong, Weifang, Xuelei Zhang, Feinan He, Xue Chen, Siqi Ma, Qingqing Tong, Zeyi Wen, and Bo Teng. "Health Risks Forecast of Regional Air Pollution on Allergic Rhinitis: High-Resolution City-Scale Simulations in Changchun, China." Atmosphere 14, no. 2 (February 17, 2023): 393. http://dx.doi.org/10.3390/atmos14020393.
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Accurate assessments of exposure to urban air pollution with higher traffic emissions and its health risks still face several challenges, such as intensive computation of air pollution modeling and the limited availability of personal activity data. The macroscopic health effects can be transmitted to the whole population for personal prevention via air quality health index (AQHI), but the possibility risk index of the specific allergic diseases is still lacking. This interdisciplinary study aims at evaluating the forecasted results of high-resolution air quality with updated traffic emissions and accessing the potential impacts of outdoor pollution on morbidity of rhinitis for urban residents. A high-resolution modelling system (1 km × 1 km) containing the online traffic emission model (VEIN), meteorological and air quality model (WRF-CHIMERE) and the health impact module was developed. A new health index of Potential Morbidity Risk Index (PMRI) was further established using higher resolution health risk coefficients of major air pollutants on allergic rhinitis, and different methods (with/without considering population distributions) targeting different user groups (residents, hospitals and health administrations) were calculated and analyzed. Operational forecasted results of hourly PMRI can be further combined with online map services to serve as an effective tool for patients with allergic rhinitis to arrange their daily activities so as to avoid acute exacerbation. The forecasted PMRIs accessible to the public will also be beneficial for the public health administrations in planning the medical resource and improving the outpatient efficiency.
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Cordell, Rebecca L., Rikesh Panchal, Emmanuel Bernard, Michael Gatari, Ezekiel Waiguru, Moses Ng’ang’a, James Nyang’aya, et al. "Volatile Organic Compound Composition of Urban Air in Nairobi, Kenya and Lagos, Nigeria." Atmosphere 12, no. 10 (October 12, 2021): 1329. http://dx.doi.org/10.3390/atmos12101329.
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Sub-Saharan Africa is seeing rapid urbanization, with the population of cities such as Lagos and Nairobi growing at a rate of 3–4% a year. The region is extremely under-sampled for all air pollutants, particularly VOCs, which are useful markers for source apportionment as well as toxic in their own right. There are many contributors to air pollution in the region, and studies examining fine particulate pollution implicate traffic as the primary source in urban areas. In this pilot study, VOCs were analysed at a selection of roadside and urban background locations in Nairobi and Lagos, and 74 VOCs were quantified. GC×GC–MS/FID analysis revealed all locations were dominated by hydrocarbons typical of vehicle emissions, with the aromatic hydrocarbons benzene and toluene among the most abundant VOCs. Typical personal exposure scenarios for citizens of the cities were calculated to far exceed those of a resident in a city in Europe/US. Finally, the calculated ozone forming potential of the VOCs measured was found to be similarly high to other large cities studied with similar air pollution problems. Further study is therefore essential to determine the full extent of VOC pollution in the region and its impact on tropospheric chemistry.
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Pervez, S., A. Koshle, and Y. Pervez. "Study of spatiotemporal variation of atmospheric mercury and its human exposure around an integrated steel plant, India." Atmospheric Chemistry and Physics 10, no. 12 (June 22, 2010): 5535–49. http://dx.doi.org/10.5194/acp-10-5535-2010.
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Abstract. Mercury release by coal combustion has been significantly increased in India. Mercury content in coal has been analyzed to 0.272 ppm by Central Pollution Control Board. Toxicological effects of elemental Hg (Hg0) exposure include respiratory and renal failures, cardiac arrest, and cerebral oedema, while subclinical exposure may induce kidney, behavioral, and cognitive dysfunctions. The present work is focused on dispersion pattern and inter-phase exchange phenomena of ambient mercury between air-particulate matter evaluations of alongwith dominance of various major routes of human exposure-dose response using regression analysis around an integrated steel plant in central India. Source-downwind type stratified random sampling plan using longitudinal study design has been adopted for ambient monitoring of total mercury, while representative sampling plant has been adopted for persona exposure-dose response study In space-time framework. Control sites and subjects have been chosen from uncontaminated area (100 km away from any industrial activities). 06 ambient air monitoring stations and 17 subjects from workers, non-workers but local residents' categories and from controlled sites have been chosen for the study. Samples of mercury biomarkers (blood, breast milk and urine) have also been collected from same subjects in each month during sampling period. The sampling period was March 2005 to February 2006 . Samples of 30% acidified KMnO4 for air-Hg absorption, PM10, RPM and biological samples were analyzed for total mercury by ICP-AES using standard methods. Local soils and ground water were also monitored for total mercury content during the sampling period. Results have shown that mercury concentration is very high compared to prescribed limits in all receptors. Results of exchange phenomenon have shown the higher transfer of mercury from air to particulate during combustion in steel plant environment due to presence of huge amount of iron particles, in contrast to results obtained in other industrial locations earlier. Plant workers have shown 1.5 to 2.5 times higher personal RPM-Hg levels compared to Category 2 and 20–30 times higher than Category 3. All biomarkers have shown higher Hg presence compared to prescribed standards. Regression analysis between exposure routes and bio-receptors has been investigated. Dominance status of selected routes of bio-accumulation has been varied from category to category.
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Zapata, Christina B., Chris Yang, Sonia Yeh, Joan Ogden, and Michael J. Kleeman. "Low-carbon energy generates public health savings in California." Atmospheric Chemistry and Physics 18, no. 7 (April 10, 2018): 4817–30. http://dx.doi.org/10.5194/acp-18-4817-2018.
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Abstract. California's goal to reduce greenhouse gas (GHG) emissions to a level that is 80 % below 1990 levels by the year 2050 will require adoption of low-carbon energy sources across all economic sectors. In addition to reducing GHG emissions, shifting to fuels with lower carbon intensity will change concentrations of short-lived conventional air pollutants, including airborne particles with a diameter of less than 2.5 µm (PM2.5) and ozone (O3). Here we evaluate how business-as-usual (BAU) air pollution and public health in California will be transformed in the year 2050 through the adoption of low-carbon technologies, expanded electrification, and modified activity patterns within a low-carbon energy scenario (GHG-Step). Both the BAU and GHG-Step statewide emission scenarios were constructed using the energy–economic optimization model, CA-TIMES, that calculates the multi-sector energy portfolio that meets projected energy supply and demand at the lowest cost, while also satisfying scenario-specific GHG emissions constraints. Corresponding criteria pollutant emissions for each scenario were then spatially allocated at 4 km resolution to support air quality analysis in different regions of the state. Meteorological inputs for the year 2054 were generated under a Representative Concentration Pathway (RCP) 8.5 future climate. Annual-average PM2.5 and O3 concentrations were predicted using the modified emissions and meteorology inputs with a regional chemical transport model. In the final phase of the analysis, mortality (total deaths) and mortality rate (deaths per 100 000) were calculated using established exposure-response relationships from air pollution epidemiology combined with simulated annual-average PM2.5 and O3 exposure. Net emissions reductions across all sectors are −36 % for PM0.1 mass, −3.6 % for PM2.5 mass, −10.6 % for PM2.5 elemental carbon, −13.3 % for PM2.5 organic carbon, −13.7 % for NOx, and −27.5 % for NH3. Predicted deaths associated with air pollution in 2050 dropped by 24–26 % in California (1537–2758 avoided deaths yr−1) in the climate-friendly 2050 GHG-Step scenario, which is equivalent to a 54–56 % reduction in the air pollution mortality rate (deaths per 100 000) relative to 2010 levels. These avoided deaths have an estimated value of USD 11.4–20.4 billion yr−1 based on the present-day value of a statistical life (VSL) equal to USD 7.6 million. The costs for reducing California GHG emissions 80 % below 1990 levels by the year 2050 depend strongly on numerous external factors such as the global price of oil. Best estimates suggest that meeting an intermediate target (40 % reduction in GHG emissions by the year 2030) using a non-optimized scenario would reduce personal income by USD 4.95 billion yr−1 (−0.15 %) and lower overall state gross domestic product by USD 16.1 billion yr−1 (−0.45 %). The public health benefits described here are comparable to these cost estimates, making a compelling argument for the adoption of low-carbon energy in California, with implications for other regions in the United States and across the world.
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Zimmerman, Naomi, Albert A. Presto, Sriniwasa P. N. Kumar, Jason Gu, Aliaksei Hauryliuk, Ellis S. Robinson, and Allen L. Robinson. "A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring." Atmospheric Measurement Techniques 11, no. 1 (January 15, 2018): 291–313. http://dx.doi.org/10.5194/amt-11-291-2018.
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Abstract. Low-cost sensing strategies hold the promise of denser air quality monitoring networks, which could significantly improve our understanding of personal air pollution exposure. Additionally, low-cost air quality sensors could be deployed to areas where limited monitoring exists. However, low-cost sensors are frequently sensitive to environmental conditions and pollutant cross-sensitivities, which have historically been poorly addressed by laboratory calibrations, limiting their utility for monitoring. In this study, we investigated different calibration models for the Real-time Affordable Multi-Pollutant (RAMP) sensor package, which measures CO, NO2, O3, and CO2. We explored three methods: (1) laboratory univariate linear regression, (2) empirical multiple linear regression, and (3) machine-learning-based calibration models using random forests (RF). Calibration models were developed for 16–19 RAMP monitors (varied by pollutant) using training and testing windows spanning August 2016 through February 2017 in Pittsburgh, PA, US. The random forest models matched (CO) or significantly outperformed (NO2, CO2, O3) the other calibration models, and their accuracy and precision were robust over time for testing windows of up to 16 weeks. Following calibration, average mean absolute error on the testing data set from the random forest models was 38 ppb for CO (14 % relative error), 10 ppm for CO2 (2 % relative error), 3.5 ppb for NO2 (29 % relative error), and 3.4 ppb for O3 (15 % relative error), and Pearson r versus the reference monitors exceeded 0.8 for most units. Model performance is explored in detail, including a quantification of model variable importance, accuracy across different concentration ranges, and performance in a range of monitoring contexts including the National Ambient Air Quality Standards (NAAQS) and the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. A key strength of the RF approach is that it accounts for pollutant cross-sensitivities. This highlights the importance of developing multipollutant sensor packages (as opposed to single-pollutant monitors); we determined this is especially critical for NO2 and CO2. The evaluation reveals that only the RF-calibrated sensors meet the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. We also demonstrate that the RF-model-calibrated sensors could detect differences in NO2 concentrations between a near-road site and a suburban site less than 1.5 km away. From this study, we conclude that combining RF models with carefully controlled state-of-the-art multipollutant sensor packages as in the RAMP monitors appears to be a very promising approach to address the poor performance that has plagued low-cost air quality sensors.
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Masri, Shahir, Kathryn Cox, Leonel Flores, Jose Rea, and Jun Wu. "Community-Engaged Use of Low-Cost Sensors to Assess the Spatial Distribution of PM2.5 Concentrations across Disadvantaged Communities: Results from a Pilot Study in Santa Ana, CA." Atmosphere 13, no. 2 (February 11, 2022): 304. http://dx.doi.org/10.3390/atmos13020304.
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PM2.5 is an air pollutant that is widely associated with adverse health effects, and which tends to be disproportionately located near low-income communities and communities of color. We applied a community-engaged research approach to assess the distribution of PM2.5 concentrations in the context of community concerns and urban features within and around the city of Santa Ana, CA. Approximately 183 h of one-minute average PM2.5 measurements, along with high-resolution geographic coordinate measurements, were collected by volunteer community participants using roughly two dozen low-cost AtmoTube Pro air pollution sensors paired with real-time GPS tracking devices. PM2.5 varied by region, time of day, and month. In general, concentrations were higher near the city’s industrial corridor, which is an area of concern to local community members. While the freeway systems were shown to correlate with some degree of elevated air pollution, two of four sampling days demonstrated little to no visible association with freeway traffic. Concentrations tended to be higher within socioeconomically disadvantaged communities compared to other areas. This pilot study demonstrates the utility of using low-cost air pollution sensors for the application of community-engaged study designs that leverage community knowledge, enable high-density air monitoring, and facilitate greater health-related awareness, education, and empowerment among communities. The mobile air-monitoring approach used in this study, and its application to characterize the ambient air quality within a defined geographic region, is in contrast to other community-engaged studies, which employ fixed-site monitoring and/or focus on personal exposure. The findings from this study underscore the existence of environmental health inequities that persist in urban areas today, which can help to inform policy decisions related to health equity, future urban planning, and community access to resources.
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Winiger, Patrik. "Passenger exposure to aerosols on intra-European train travel." Air Quality, Atmosphere & Health 15, no. 3 (January 12, 2022): 491–501. http://dx.doi.org/10.1007/s11869-021-01143-2.
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AbstractKnowledge about personal aerosol exposure in different environments is fundamental for individual and common decision-making, shaping the way we build our infrastructure or change our social behaviours. Aerosols are a leading cause of death and well-known vector for infectious diseases. Yet, passenger exposure to aerosols during long-distance train travel is surprisingly underexplored. Two small, light-weight personal monitoring instruments were employed during a train journey across Europe, to measure the fine particle (PM2.5) and equivalent black carbon (eBC) passenger exposure, respectively. The journey was divided into three legs, inside three different trains, and two layovers in city environments. Highest mean concentrations of PM2.5 and eBC were found within the oldest train type, and revealed PM2.5 concentrations of 58.4 ± 12.7 μg m−3 and eBC of 5.4 ± 2.9 μg m−3. The more modern the train system was, the lower the measured concentrations were to be found. In the newest tested system, the air quality was considerably better inside the train than outdoor air measured by a monitoring network, or simulated by the Copernicus Atmosphere Monitoring Service (CAMS) model ensemble analysis. The mean PM2.5 concentration was roughly 20% lower inside the train than the outdoor air simulated by CAMS. Both the light-weight personal monitoring and the monitoring network indicate that the CAMS ensemble substantially underestimates PM2.5 concentrations for the day of the journey. Effective ventilation and air filtration significantly decrease the passenger’s aerosol exposure, as compared to a stay in outdoor air, leading to a small statistical increase in life expectancy. If this could also reduce the risk of contagion with an infectious disease remains to be explored.
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Pervez, S., A. Koshle, and Y. Pervez. "Study of spatiotemporal variation of atmospheric mercury and its human exposure around an integrated steel plant, India." Atmospheric Chemistry and Physics Discussions 10, no. 1 (January 15, 2010): 885–923. http://dx.doi.org/10.5194/acpd-10-885-2010.
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Abstract. Mercury release by coal combustion has been significantly increased in India. Mercury content in coal has been analyzed to 0.272 ppm by Central Pollution Control Board. Toxicological effects of elemental Hg (Hg0) exposure include respiratory and renal failures, cardiac arrest, and cerebral oedema, while subclinical exposure may induce kidney, behavioral, and cognitive dysfunctions. The present work is focused on dispersion pattern and inter-phase exchange phenomena of ambient mercury between air-particulate matter evaluations of alongwith dominance of various major routes of human exposure-dose response using regression analysis around an integrated steel plant in central India. Source-downwind type stratified random sampling plan using longitudinal study design has been adopted for ambient monitoring of total mercury, while representative sampling plant has been adopted for persona exposure-dose response study In space-time framework. Control sites and subjects have been chosen from uncontaminated area (100 km away from any industrial activities). 06 ambient air monitoring stations and 17 subjects from workers, non-workers but local residents' categories and from controlled sites have been chosen for the study. Samples of mercury biomarkers (blood, breast milk and urine) have also been collected from same subjects in each month during sampling period. The sampling period was March 2005 to February 2006 . Samples of 30% acidified KMnO4 for air-Hg absorption, PM10, RPM and biological samples were analyzed for total mercury by ICP-AES using standard methods. Local soils and ground water were also monitored for total mercury content during the sampling period. Results have shown that mercury concentration is very high compared to prescribed limits in all receptors. Results of exchange phenomenon have shown the higher transfer of mercury from air to particulate during combustion in steel plant environment due to presence of huge amount of iron particles, in contrast to results obtained in other industrial locations earlier. Plant workers have shown 1.5 to 2.5 times higher personal RPM-Hg levels compared to Category 2 and 20–30 times higher than Category 3. All biomarkers have shown higher Hg presence compared to prescribed standards. Regression analysis between exposure routes and bio-receptors has been investigated. Dominance status of selected routes of bio-accumulation has been varied from category to category.
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Novak, Rok, Johanna Amalia Robinson, Tjaša Kanduč, Dimosthenis Sarigiannis, and David Kocman. "Assessment of Individual-Level Exposure to Airborne Particulate Matter during Periods of Atmospheric Thermal Inversion." Sensors 22, no. 19 (September 20, 2022): 7116. http://dx.doi.org/10.3390/s22197116.
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Air pollution exposure is harmful to human health and reducing it at the level of an individual requires measurements and assessments that capture the spatiotemporal variability of different microenvironments and the influence of specific activities. In this paper, activity-specific and general indoor and outdoor exposure during and after a period of high concentrations of particulate matter (PM), e.g., an atmospheric thermal inversion (ATI) in the Ljubljana subalpine basin, Slovenia, was assessed. To this end, personal particulate matter monitors (PPM) were used, worn by participants of the H2020 ICARUS sampling campaigns in spring 2019 who also recorded their hourly activities. ATI period(s) were determined based on data collected from two meteorological stations managed by the Slovenian Environmental Agency (SEA). Results showed that indoor and outdoor exposure to PM was significantly higher during the ATI period, and that the difference between mean indoor and outdoor exposure to PM was much higher during the ATI period (23.0 µg/m3) than after (6.5 µg/m3). Indoor activities generally were associated with smaller differences, with cooking and cleaning even having higher values in the post-ATI period. On the other hand, all outdoor activities had higher PM values during the ATI than after, with larger differences, mostly >30.0 µg/m3. Overall, this work demonstrated that an individual-level approach can provide better spatiotemporal resolution and evaluate the relative importance of specific high-exposure events, and in this way provide an ancillary tool for exposure assessments.
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Posadas-Sánchez, Rosalinda, Gilberto Vargas-Alarcón, Andres Cardenas, José Luis Texcalac-Sangrador, Citlalli Osorio-Yáñez, and Marco Sanchez-Guerra. "Long-Term Exposure to Ozone and Fine Particulate Matter and Risk of Premature Coronary Artery Disease: Results from Genetics of Atherosclerotic Disease Mexican Study." Biology 11, no. 8 (July 27, 2022): 1122. http://dx.doi.org/10.3390/biology11081122.
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(1) Background: Epidemiological studies have identified associations between fine particulate matter (PM2.5) and ozone exposure with cardiovascular disease; however, studies linking ambient air pollution and premature coronary artery disease (pCAD) in Latin America are non-existing. (2) Methods: Our study was a case–control analysis nested in the Genetics of Atherosclerotic Disease (GEA) Mexican study. We included 1615 participants (869 controls and 746 patients with pCAD), recruited at the Instituto Nacional de Cardiología Ignacio Chávez from June 2008 to January 2013. We defined pCAD as history of myocardial infarction, angioplasty, revascularization surgery or coronary stenosis > 50% diagnosed before age 55 in men and age 65 in women. Controls were healthy individuals without personal or family history of pCAD and with coronary artery calcification equal to zero. Hourly measurements of ozone and PM2.5 from the Atmospheric Monitoring System in Mexico City (SIMAT in Spanish; Sistema de Monitero Atmosférico de la Ciudad de México) were used to calculate annual exposure to ozone and PM2.5 in the study participants. (3) Results: Each ppb increase in ozone at 1-year, 2-year, 3-year and 5-year averages was significantly associated with increased odds (OR = 1.10; 95% CI: 1.03–1.18; OR = 1.17; 95% CI: 1.05–1.30; OR = 1.18; 95% CI: 1.05–1.33, and OR = 1.13; 95% CI: 1.04–1.23, respectively) of pCAD. We observed higher risk of pCAD for each 5 µg/m3 increase only for the 5-year average of PM2.5 exposure (OR = 2.75; 95% CI: 1.47–5.16), compared to controls. (4) Conclusions: Ozone exposure at different time points and PM2.5 exposure at 5 years were associated with increased odds of pCAD. Our results highlight the importance of reducing long-term exposure to ambient air pollution levels to reduce the burden of cardiovascular disease in Mexico City and other metropolitan areas.
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Zhu, Xiaoxuan, Xueyan Wang, Li Lei, and Yuting Zhao. "The influence of roadside green belts and street canyon aspect ratios on air pollution dispersion and personal exposure." Urban Climate 44 (July 2022): 101236. http://dx.doi.org/10.1016/j.uclim.2022.101236.
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Saleem, Naof Faiz, Mahmoud Fathy ElSharkawy, and Ayman M. Azoz. "Effect of Airborne Particulate Matter on Cardiovascular Diseases." Atmosphere 13, no. 12 (December 2, 2022): 2030. http://dx.doi.org/10.3390/atmos13122030.
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Context: Airborne particulate matter (PM) attracts heightened attention due to its implication in various diseases, especially cardiovascular diseases. Although numerous epidemiological studies have been published worldwide in developing countries on risks associated with exposure to PM, such studies are still scarce in developing countries such as Saudi Arabia. Objective: To examine the association between the concentration of airborne particulate matter (PM) and hospital admissions resulting from cardiovascular diseases (CVD) in the Eastern Region of Saudi Arabia, specifically in the cities of Dammam and Khobar. Methodology: The daily concentrations of PM10 and PM2.5 were obtained from 10 monitoring stations distributed around the two hospitals. There was an examination of the discharge data of patients diagnosed with cardiac arrhythmias, acute myocardial infarction, and heart failure as their primary diagnoses. The data were obtained from two big governmental hospitals in the Eastern Region. The primary cause of hospital admission of 259 patients was identified as acute cardiac condition. Results: For PM10 and PM2.5, the 24 h mean was calculated as 101.2 and 37.1 µg/m3, respectively; such means are considered higher than the Air Quality Guidelines (AQGs). We found evidence of an increased risk of cardiovascular events for long-term exposure to PM2.5–10 concentrations, and a correlation with the IHD hospital admission within 6 days of the peak PM10 or PM2.5 concentration. In addition, the increased PM2.5 concentration also had a correlation with hospital admissions; however, analysis shows an increase in mortality at lag1, lag2, and lag3 prior to hospital admission. Conclusions: Hospital admissions for several cardiovascular diseases acutely increase in response to higher ambient PM concentrations. It is recommended that residents need to use personal protection, especially those residents with cardiovascular disease, while the government needs to strengthen the governance of air pollution in areas with lighter air pollution.
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Fameli, Kyriaki-Maria, Konstantinos Moustris, Georgios Spyropoulos, and Dimitrios-Michael Rodanas. "Exposure to PM2.5 on Public Transport: Guidance for Field Measurements with Low-Cost Sensors." Atmosphere 15, no. 3 (March 7, 2024): 330. http://dx.doi.org/10.3390/atmos15030330.
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Air pollution is one of the most important problems in big cities, resulting in adverse health effects. The aim of the present study was to characterize the personal exposure to indoor and outdoor pollution in the Greater Athens Area in Greece by taking measurements during a journey from suburban to mixed industrial–urban areas, encompassing walking, waiting, bus travel, and metro travel at various depths. For this reason, low-cost (LC) sensors were used, and the inhaled dose of particulate matter with an aerodynamic diameter of less than or equal to 2.5 μm (PM2.5) in different age groups of passengers was calculated. Specific bus routes and the Athens metro network were monitored throughout different hours of the day. Then, the average particulate matter (PM2.5) exposure for a metro passenger was calculated and evaluated. By considering the ventilation rate of a passenger, an estimation of the total PM2.5 inhaled dose for males and females as well as for different age groups was made. The results showed that the highest PM2.5 concentrations were observed inside the wagons with significant increases during rush hours or after rush hours. Furthermore, there should be a concern regarding older individuals using the subway network in Athens during rush hours and in general for sensitive groups (people with asthma, respiratory and cardiovascular problems, etc.).
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de Ferreyro Monticelli, Davi, Jane Meri Santos, Elisa Valentim Goulart, José Geraldo Mill, Jeferson da Silva Corrêa, Vanessa Dias dos Santos, and Neyval Costa Reis. "Comparison of methods for assessment of children exposure to air pollution: dispersion model, ambient monitoring, and personal samplers." Air Quality, Atmosphere & Health 15, no. 4 (November 12, 2021): 645–55. http://dx.doi.org/10.1007/s11869-021-01123-6.
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McNabola, Aonghus, Andrew McCreddin, Laurence W. Gill, and Brian M. Broderick. "Analysis of the relationship between urban background air pollution concentrations and the personal exposure of office workers in Dublin, Ireland, using baseline separation techniques." Atmospheric Pollution Research 2, no. 1 (January 2011): 80–88. http://dx.doi.org/10.5094/apr.2011.010.
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Li, Qingman, Jie Liang, Qun Wang, Yuntong Chen, Hongyu Yang, Hong Ling, Zhiwen Luo, and Jian Hang. "Numerical Investigations of Urban Pollutant Dispersion and Building Intake Fraction with Various 3D Building Configurations and Tree Plantings." International Journal of Environmental Research and Public Health 19, no. 6 (March 16, 2022): 3524. http://dx.doi.org/10.3390/ijerph19063524.
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Rapid urbanisation and rising vehicular emissions aggravate urban air pollution. Outdoor pollutants could diffuse indoors through infiltration or ventilation, leading to residents’ exposure. This study performed CFD simulations with a standard k-ε model to investigate the impacts of building configurations and tree planting on airflows, pollutant (CO) dispersion, and personal exposure in 3D urban micro-environments (aspect ratio = H/W = 30 m, building packing density λp = λf = 0.25) under neutral atmospheric conditions. The numerical models are well validated by wind tunnel data. The impacts of open space, central high-rise building and tree planting (leaf area density LAD= 1 m2/m3) with four approaching wind directions (parallel 0° and non-parallel 15°, 30°, 45°) are explored. Building intake fraction <P_IF> is adopted for exposure assessment. The change rates of <P_IF> demonstrate the impacts of different urban layouts on the traffic exhaust exposure on residents. The results show that open space increases the spatially-averaged velocity ratio (VR) for the whole area by 0.40–2.27%. Central high-rise building (2H) can increase wind speed by 4.73–23.36% and decrease the CO concentration by 4.39–23.00%. Central open space and high-rise building decrease <P_IF> under all four wind directions, by 6.56–16.08% and 9.59–24.70%, respectively. Tree planting reduces wind speed in all cases, raising <P_IF> by 14.89–50.19%. This work could provide helpful scientific references for public health and sustainable urban planning.
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Simoncic, Valentin, Virginie Hamann, Loriane Huber, Phillipe Deruelle, Nicolas Sananes, Christophe Enaux, Maxime Alter, Charles Schillinger, Severine Deguen, and Wahida Kihal-Talantikite. "Study protocol to explore the social effects of environmental exposure and lifestyle behaviours on pregnancy outcome: an overview of cohort of pregnant women study." BMJ Open 12, no. 9 (September 2022): e058883. http://dx.doi.org/10.1136/bmjopen-2021-058883.
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Introduction A growing number of international studies have highlighted the adverse consequences of lived experience in the first thousand days of pregnancy and early life on the probability of stillbirth, child mortality, inadequate growth and healthy development during both childhood and adulthood. The lived experience of the fetus inside the womb and at the birth is strongly related to both maternal health during pregnancy and maternal exposure to a set of environmental factors known as ‘exposome’ characteristics, which include environmental exposure, health behaviours, living conditions, neighbourhood characteristics and socioeconomic profile. The aim of our project is to explore the relationships between exposome characteristics and the health status of pregnant women and their newborns. We are particularly interested in studying the relationships between the social inequality of adverse pregnancy outcomes and (1) short-term exposure to atmospheric pollution (MobiFem project) and (2) pregnancy lifestyle (EnviFem project). Methods and analysis Ours is a prospective, observational and multisite cohort study of pregnant women, involving one teaching hospital across two sites in the Strasbourg metropolitan area. The research team at University Hospital of Strasbourg (HUS) Health collects data on outcomes and individual characteristics from pregnancy registries, clinical records data and questionnaires administered via email to study participants. Recruitment began in February 2021 and will be complete by December 2021. Participants are recruited from first trimester antenatal ultrasound examinations (conducted on weekdays across both sites); each woman meeting our inclusion criteria enters the cohort at the end of her first trimester. Study participants receive a total of three online questionnaires covering sociodemographic characteristics, travel behaviour patterns and lifestyle. Participants complete these questionnaires at recruitment, during the second and third trimester. The level of personal exposure to air pollution is characterised using a dynamic spatiotemporal trajectory model that describes the main daily movements of pregnant women and the time spent in each place frequented. Univariate, multilevel and Bayesian model will be used to investigate the relationships between exposome characteristics and the health status of pregnant women and their newborns. Ethics and dissemination Our research was approved by the Commission de Protection des Personnes (CPP) Ile de France VI (Paris) on 9 December 2020 (File reference No. 20.09.15.41703 ID RCB: 2020-A02580-39 and No. 20 080–42137 IDRCB 2020-A02581-38). The Agence Nationale de Sécurité du Médicament was informed of it on 15 December 2020. Findings from the study will be disseminated through publications and international conferences and through presentation at meetings with local stakeholders, researchers and policy-makers. Trial registration numbers NCT04705272 NCT04725734
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Steinemann, Anne. "Fragranced consumer products: effects on autistic adults in the United States, Australia, and United Kingdom." Air Quality, Atmosphere & Health 11, no. 10 (September 25, 2018): 1137–42. http://dx.doi.org/10.1007/s11869-018-0625-x.
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Abstract Fragranced consumer products, such as cleaning supplies, air fresheners, and personal care products, can have adverse effects on both air quality and health. This study investigates the effects of fragranced products on autistic individuals ages 18–65 in the United States, Australia, and United Kingdom. Nationally representative population surveys (n = 1137; 1098; 1100) found that, across the three countries, 4.3% of adults (n = 142) report medically diagnosed autism (2.3%), an autism spectrum disorder (2.4%), or both. Of these autistic adults, 83.7% report adverse health effects from fragranced products, including migraine headaches (42.9%), neurological problems (34.3%), respiratory problems (44.7%), and asthma attacks (35.9%). In particular, 62.9% of autistic adults report health problems from air fresheners or deodorizers, 57.5% from the scent of laundry products coming from a dryer vent, 65.9% from being in a room cleaned with scented products, and 60.5% from being near someone wearing a fragranced product. Health problems can be severe, with 74.1% of these effects considered potentially disabling under legislation in each country. Further, 59.4% of autistic adults have lost workdays or lost a job, in the past year, due to fragranced product exposure in the workplace. More than twice as many autistic as well as non-autistic individuals would prefer that workplaces, health care facilities, and health care professionals were fragrance-free rather than fragranced. Results show that vulnerable individuals, such as those with autism or autism spectrum disorders, can be profoundly, adversely, and disproportionately affected by exposure to fragranced consumer products.
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Vikram, Sharad, Ashley Collier-Oxandale, Michael H. Ostertag, Massimiliano Menarini, Camron Chermak, Sanjoy Dasgupta, Tajana Rosing, Michael Hannigan, and William G. Griswold. "Evaluating and improving the reliability of gas-phase sensor system calibrations across new locations for ambient measurements and personal exposure monitoring." Atmospheric Measurement Techniques 12, no. 8 (August 6, 2019): 4211–39. http://dx.doi.org/10.5194/amt-12-4211-2019.
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Abstract. Advances in ambient environmental monitoring technologies are enabling concerned communities and citizens to collect data to better understand their local environment and potential exposures. These mobile, low-cost tools make it possible to collect data with increased temporal and spatial resolution, providing data on a large scale with unprecedented levels of detail. This type of data has the potential to empower people to make personal decisions about their exposure and support the development of local strategies for reducing pollution and improving health outcomes. However, calibration of these low-cost instruments has been a challenge. Often, a sensor package is calibrated via field calibration. This involves colocating the sensor package with a high-quality reference instrument for an extended period and then applying machine learning or other model fitting technique such as multiple linear regression to develop a calibration model for converting raw sensor signals to pollutant concentrations. Although this method helps to correct for the effects of ambient conditions (e.g., temperature) and cross sensitivities with nontarget pollutants, there is a growing body of evidence that calibration models can overfit to a given location or set of environmental conditions on account of the incidental correlation between pollutant levels and environmental conditions, including diurnal cycles. As a result, a sensor package trained at a field site may provide less reliable data when moved, or transferred, to a different location. This is a potential concern for applications seeking to perform monitoring away from regulatory monitoring sites, such as personal mobile monitoring or high-resolution monitoring of a neighborhood. We performed experiments confirming that transferability is indeed a problem and show that it can be improved by collecting data from multiple regulatory sites and building a calibration model that leverages data from a more diverse data set. We deployed three sensor packages to each of three sites with reference monitors (nine packages total) and then rotated the sensor packages through the sites over time. Two sites were in San Diego, CA, with a third outside of Bakersfield, CA, offering varying environmental conditions, general air quality composition, and pollutant concentrations. When compared to prior single-site calibration, the multisite approach exhibits better model transferability for a range of modeling approaches. Our experiments also reveal that random forest is especially prone to overfitting and confirm prior results that transfer is a significant source of both bias and standard error. Linear regression, on the other hand, although it exhibits relatively high error, does not degrade much in transfer. Bias dominated in our experiments, suggesting that transferability might be easily increased by detecting and correcting for bias. Also, given that many monitoring applications involve the deployment of many sensor packages based on the same sensing technology, there is an opportunity to leverage the availability of multiple sensors at multiple sites during calibration to lower the cost of training and better tolerate transfer. We contribute a new neural network architecture model termed split-NN that splits the model into two stages, in which the first stage corrects for sensor-to-sensor variation and the second stage uses the combined data of all the sensors to build a model for a single sensor package. The split-NN modeling approach outperforms multiple linear regression, traditional two- and four-layer neural networks, and random forest models. Depending on the training configuration, compared to random forest the split-NN method reduced error 0 %–11 % for NO2 and 6 %–13 % for O3.
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Riley, Matthew L., Scott D. Chambers, and Alastair G. Williams. "Inter-Comparison of Radon Measurements from a Commercial Beta-Attenuation Monitor and ANSTO Dual Flow Loop Monitor." Atmosphere 14, no. 9 (August 24, 2023): 1333. http://dx.doi.org/10.3390/atmos14091333.
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Radon (Rn) is a radioactive, colourless, odourless, noble gas that decays rapidly. It’s most stable isotope, 222Rn, has a half-life of around 3.8 days. Atmospheric radon measurements play an important role in understanding our atmospheric environments. Naturally occurring radon can be used as an atmospheric tracer for airmass tracking, to assist in modelling boundary layer development, and is important for understanding background radiation levels and personal exposure to natural radiation. The daughter products from radon decay also play an important role when measuring fine particle pollution using beta-attenuation monitors (BAM). Beta radiation from the 222Rn decay chain interferes with BAM measurements of fine particles; thus, some BAMs incorporate radon measurements into their sampling systems. BAMs are ubiquitous in air quality monitoring networks globally and present a hitherto unexplored source of dense, continuous radon measurements. In this paper, we compare in situ real world 222Rn measurements from a high quality ANSTO dual flow loop, dual filter radon detector, and the radon measurements made by a commercial BAM instrument (Thermo 5014i). We find strong correlations between systems for hourly measurements (R2 = 0.91), daily means (R2 = 0.95), hour of day (R2 = 0.72–0.94), and by month (R2 = 0.83–0.94). The BAM underestimates radon by 22–39%; however, the linear response of the BAM measurements implies that they could be corrected to reflect the ANSTO standard measurements. Regardless, the radon measurements from BAMs could be used with correction to estimate local mixed layer development. Though only a 12-month study at a single location, our results suggest that radon measurements from BAMs can complement more robust measurements from standard monitors, augment radon measurements across broad regions of the world, and provide useful information for studies using radon as a tracer, particularly for boundary layer development and airmass identification.
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Alas, Honey Dawn C., Kay Weinhold, Francesca Costabile, Antonio Di Ianni, Thomas Müller, Sascha Pfeifer, Luca Di Liberto, Jay R. Turner, and Alfred Wiedensohler. "Methodology for high-quality mobile measurement with focus on black carbon and particle mass concentrations." Atmospheric Measurement Techniques 12, no. 9 (September 3, 2019): 4697–712. http://dx.doi.org/10.5194/amt-12-4697-2019.
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Abstract. Measurements of air pollutants such as black carbon (BC) and particle mass concentration in general, using mobile platforms equipped with high-time-resolution instruments, have gained popularity over the last decade due to their wide range of applicability. Assuring the quality of mobile measurement, data have become more essential, particularly when the personal exposure to pollutants is related to their spatial distribution. In the following, we suggest a methodology to achieve data from mobile measurements of equivalent black carbon (eBC) and PM2.5 mass concentrations with high data quality. Besides frequent routine quality assurance measures of the instruments, the methodology includes the following steps: (a) measures to ensure the quality of mobile instruments through repeated collocated measurements using identical instrumentation, (b) inclusion of a fixed station along the route containing quality-assured reference instruments, and (c) sufficiently long and frequent intercomparisons between the mobile and reference instruments to correct the particle number and mass size distributions obtained from mobile measurements. The application of the methodology can provide the following results. First, collocated mobile measurements with sets of identical instruments allow identification of undetected malfunctions of the instruments. Second, frequent intercomparisons against the reference instruments will ensure the quality of the mobile measurement data of the eBC mass concentration. Third, the intercomparison data between the mobile optical particle size spectrometer (OPSS) and a reference mobility particle size spectrometer (MPSS) allow for the adjustment of the OPSS particle number size distribution using physically meaningful corrections. Matching the OPSS and MPSS volume particle size distributions is crucial for the determination of PM2.5 mass concentration. Using size-resolved complex refractive indices and time-resolved fine-mode volume correction factors of the fine-particle range, the calculated PM2.5 from the OPSS was within 5 % of the reference instruments (MPSS+APSS). However, due to the nonsphericity and an unknown imaginary part of the complex refractive index of supermicrometer particles, a conversion to a volume equivalent diameter yields high uncertainties of the particle mass concentration greater than PM2.5. The proposed methodology addresses issues regarding the quality of mobile measurements, especially for health impact studies, validation of modeled spatial distribution, and development of air pollution mitigation strategies.
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Lim, Shanon, Jennifer A. Salmond, and Kim N. Dirks. "Influence of Differing Microenvironments on Personal Carbon Monoxide Exposure in Auckland, New Zealand." Open Atmospheric Science Journal 9, no. 1 (June 26, 2015): 1–8. http://dx.doi.org/10.2174/1874282301509010001.
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Epidemiological studies typically estimate pollutant exposures using data from outdoor fixed monitoring stations (FMS). However, due to individual mobility through space, time spent in indoor environments and the heterogeneity of the urban atmosphere, data from FMS provides a poor representation of the actual personal exposure to air pollutants. The aim of this study is to investigate the relative importance of time spent in common microenvironments (such as commuter, home, work and recreational) to determine personal exposure to air pollution. The study also investigates the extent to which fixed monitoring stations (FMS) are representative of personal exposures. For this purpose, 17 participants monitored their personal exposure to carbon monoxide (CO) for a full working week and completed a time activity diary identifying the particular microenvironments in which they spent their time. Overall, the participants exposure to CO were lower than those observed in other northern hemisphere cities reported upon in the literature. FMS located in central Auckland were found to provide reasonable estimates of mean daily personal exposure but were poorly correlated with diurnal variations in personal exposure. The results found that, while the highest mean exposures were recorded in the commuter microenvironment, the home microenvironment accounted for 55% of the total CO dose during the week. Increased levels of personal CO exposure were observed in indoor areas where gas heating, gas stoves and tobacco smoke were present. Participants recorded highly variable exposure to CO in recreational microenvironments, in part explained by the wide range of recreational activities.
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Suriano, Domenico, Gennaro Cassano, and Michele Penza. "Design and Development of a Flexible, Plug-and-Play, Cost-Effective Tool for on-Field Evaluation of Gas Sensors." Journal of Sensors 2020 (August 1, 2020): 1–20. http://dx.doi.org/10.1155/2020/8812025.
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Atmospheric pollution is one of the biggest concerns for public health. Air quality monitoring is currently performed by expensive and cumbersome monitoring stations. For this reason, they are sparse, and therefore, inadequate to provide enough accurate information on the personal exposure to pollutant gases. The current worldwide trend to address this issue consists in the use of low-cost small gas sensors, already available on the market, with a wide range of costs and performances. However, the performance of these sensors is heavily affected by the environmental conditions of the specific location used for their deployment. For this reason, it is of fundamental importance to test them in real-world scenarios. Field evaluation of sensor performance could be a challenging task because, on the one hand, they have heterogeneous output signals, and on the other hand, there is no widely shared evaluation protocol. The SentinAir system has been designed and developed to facilitate this task. It can carry out performance evaluations for any type of sensor thanks to its configurable and adaptable sensing capability, multiple wireless sensor network compatibility, flexibility, and usability. In order to evaluate SentinAir capabilities and functionalities, the performances of CO2, NO2, and O3 sensors were tested in real-world scenarios against reference instruments. To the best of our knowledge, there is no previous study providing information about the performance of SP-61 (O3 sensor), IRC-A1 (CO2 sensor), and TDS5008 (CO2 sensor) achieved during on-field tests. On the contrary, results obtained by OXB431 (O3 sensor) and NO2B43F (NO2 sensor) are consistent with the ones shown in previous studies carried out in similar conditions. During validation tests, we have found R2=0.507 for the best performing NO2 sensor, and R2=0.668 for the best O3 sensor. Concerning the indoor experiment, the best CO2 sensor performance showed an excellent R2=0.995. In conclusion, the effectiveness of this tool in evaluating the performance of heterogeneous gas sensors in different real-world scenarios has been demonstrated. Therefore, we anticipate that the use of SentinAir will facilitate researchers to carry out these challenging tasks.
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Marinello, Samuele, Francesco Lolli, Antonio Maria Coruzzolo, and Rita Gamberini. "Exposure to Air Pollution in Transport Microenvironments." Sustainability 15, no. 15 (August 3, 2023): 11958. http://dx.doi.org/10.3390/su151511958.
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People spend approximately 90% of their day in confined spaces (at home, work, school or in transit). During these periods, exposure to high concentrations of atmospheric pollutants can pose serious health risks, particularly to the respiratory system. The objective of this paper is to define a framework of the existing literature on the assessment of air quality in various transport microenvironments. A total of 297 papers, published from 2002 to 2021, were analyzed with respect to the type of transport microenvironments, the pollutants monitored, the concentrations measured and the sampling methods adopted. The analysis emphasizes the increasing interest in this topic, particularly regarding the evaluation of exposure in moving cars and buses. It specifically focuses on the exposure of occupants to atmospheric particulate matter (PM) and total volatile organic compounds (TVOCs). Concentrations of these pollutants can reach several hundreds of µg/m3 in some cases, significantly exceeding the recommended levels. The findings presented in this paper serve as a valuable resource for urban planners and decision-makers in formulating effective urban policies.
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Paul, Akshoy Ranjan, Anuj Jain, and Suvash C. Saha. "Exposure Assessment of Air Pollution in Lungs." Atmosphere 13, no. 11 (October 27, 2022): 1767. http://dx.doi.org/10.3390/atmos13111767.
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In this article, a comprehensive literature survey on air pollution and its effects on the human respiratory system is carried out. Based on the knowledge gaps, a computational assessment is proposed to find the impact of air quality on respiratory suspended particulate matter (RSPM) deposition in the human airways. A realistic 3D geometric model of the human airway was constructed to study the airflow characteristics and RSPM (PM2.5 and PM10) transport and deposition in it for normal and moderate inhalation patterns (corresponding to natural breathing) of air having an unhealthy air quality index (AQI). The results identify inertial impact as the primary mechanism of particle deposition in the human airways. They also reveals the significant differences in the deposition patterns of PM2.5 and PM10 in the right and left bronchial airways.
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Gulliver, John, and David J. Briggs. "Journey-time exposure to particulate air pollution." Atmospheric Environment 41, no. 34 (November 2007): 7195–207. http://dx.doi.org/10.1016/j.atmosenv.2007.05.023.
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Thron, Raymond W. "Direct and Indirect Exposure to Air Pollution." Otolaryngology–Head and Neck Surgery 114, no. 2 (February 1996): 281–85. http://dx.doi.org/10.1016/s0194-59989670184-5.
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Hazardous substances that originally are discharged as air pollutants may find their pathway to human exposure through multiple routes, including ingestion and dermal contact, as well as direct inhalation. The mechanisms for modeling and understanding the fate of air pollutants through atmospheric transport, deposition into water and soil, bioaccumulation, and ultimate uptake to receptor organs and systems in the human body are complex. Pollution prevention programs can be better engineered, pollution priorities can be identified, and greater environmental public health gains (attributable to pollution prevention) can be achieved by evaluating the multiple pathways to human exposure and through improved dosage calculations. A single contaminant source often may represent only a fraction of a total body pollutant burden. Further research is needed on source culpability and attributable risk, long-range transport of air pollutants, human dose contributions by various pathways, better techniques for health risk assessment, and an identification of human behavior patterns that affect exposure and dose.
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Baklanov, A., O. Hänninen, L. H. Slørdal, J. Kukkonen, N. Bjergene, B. Fay, S. Finardi, et al. "Integrated systems for forecasting urban meteorology, air pollution and population exposure." Atmospheric Chemistry and Physics 7, no. 3 (February 15, 2007): 855–74. http://dx.doi.org/10.5194/acp-7-855-2007.
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Abstract. Urban air pollution is associated with significant adverse health effects. Model-based abatement strategies are required and developed for the growing urban populations. In the initial development stage, these are focussed on exceedances of air quality standards caused by high short-term pollutant concentrations. Prediction of health effects and implementation of urban air quality information and abatement systems require accurate forecasting of air pollution episodes and population exposure, including modelling of emissions, meteorology, atmospheric dispersion and chemical reaction of pollutants, population mobility, and indoor-outdoor relationship of the pollutants. In the past, these different areas have been treated separately by different models and even institutions. Progress in computer resources and ensuing improvements in numerical weather prediction, air chemistry, and exposure modelling recently allow a unification and integration of the disjunctive models and approaches. The current work presents a novel approach that integrates the latest developments in meteorological, air quality, and population exposure modelling into Urban Air Quality Information and Forecasting Systems (UAQIFS) in the context of the European Union FUMAPEX project. The suggested integrated strategy is demonstrated for examples of the systems in three Nordic cities: Helsinki and Oslo for assessment and forecasting of urban air pollution and Copenhagen for urban emergency preparedness.
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Kim, Younoh, James Manley, and Vlad Radoias. "Air Pollution and Long Term Mental Health." Atmosphere 11, no. 12 (December 14, 2020): 1355. http://dx.doi.org/10.3390/atmos11121355.
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We study the long-term consequences of air pollution on mental health, using a natural experiment in Indonesia. We find that exposure to severe air pollution has significant and persistent consequences on mental health. An extra standard deviation in the pollution index raises the probability of clinical depression measured 10 years past exposure by almost 1%. Women in particular seem to be more affected, but some effects persist for men as well. Pollution exposure increases the likelihood of clinical depression for women and also the severity of depressive symptoms for both sexes. It is not clear if men are more resistant to pollution or they simply recover faster from it. Education, perceived economic status, and marriage seem to be the best mitigators for these negative effects.