Personal exposure to equivalent black carbon in children in Milan, Italy: Time-activity patterns and predictors by season

Comparison of personal exposure to black carbon levels with fixed-site monitoring data and with dispersion modelling and the influence of activity patterns and environment

BACKGROUND

Short-term studies of health effects from ambient air pollution usually rely on fixed site monitoring data or spatio-temporal models for exposure characterization, but the relation to personal exposure is often not known.

OBJECTIVE

We aimed to explore this relation for black carbon (BC) in central Stockholm.

METHODS

Families (n = 46) with an infant, one parent working and one parent on parental leave, carried battery-operated BC instruments for 7 days. Routine BC monitoring data were obtained from rural background (RB) and urban background (UB) sites. Outdoor levels of BC at home and work were estimated in 24 h periods by dispersion modelling based on hourly real-time meteorological data, and statistical meteorological data representing annual mean conditions. Global radiation, air pressure, precipitation, temperature, and wind speed data were obtained from the UB station. All families lived in the city centre, within 4 km of the UB station.

RESULTS

The average level of 24 h personal BC was 425 (s.d. 181) ng/m3 for parents on leave, and 394 (s.d. 143) ng/m3 for working parents. The corresponding fixed-site monitoring observations were 148 (s.d. 139) at RB and 317 (s.d. 149) ng/m3 at UB. Modelled BC levels at home and at work were 493 (s.d. 228) and 331 (s.d. 173) ng/m3, respectively. UB, RB and air pressure explained only 21% of personal 24 h BC variability for parents on leave and 25% for working parents. Modelled home BC and observed air pressure explained 23% of personal BC, and adding modelled BC at work increased the explanation to 34% for the working parents.

IMPACT

Short-term studies of health effects from ambient air pollution usually rely on fixed site monitoring data or spatio-temporal models for exposure characterization, but the relation to actual personal exposure is often not known. In this study we showed that both routine monitoring and modelled data explained less than 35% of variability in personal black carbon exposure. Hence, short-term health effects studies based on fixed site monitoring or spatio-temporal modelling are likely to be underpowered and subject to bias.

Systematic review of best practices for GPS data usage, processing, and linkage in health, exposure science and environmental context research

Global Positioning System (GPS) technology is increasingly used in health research to capture individual mobility and contextual and environmental exposures. However, the tools, techniques and decisions for using GPS data vary from study to study, making comparisons and reproducibility challenging.

OBJECTIVES

The objectives of this systematic review were to (1) identify best practices for GPS data collection and processing; (2) quantify reporting of best practices in published studies; and (3) discuss examples found in reviewed manuscripts that future researchers may employ for reporting GPS data usage, processing and linkage of GPS data in health studies.

DESIGN

A systematic review.

DATA SOURCES

Electronic databases searched (24 October 2023) were PubMed, Scopus and Web of Science (PROSPERO ID: CRD42022322166).

ELIGIBILITY CRITERIA

Included peer-reviewed studies published in English met at least one of the criteria: (1) protocols involving GPS for exposure/context and human health research purposes and containing empirical data; (2) linkage of GPS data to other data intended for research on contextual influences on health; (3) associations between GPS-measured mobility or exposures and health; (4) derived variable methods using GPS data in health research; or (5) comparison of GPS tracking with other methods (eg, travel diary).

DATA EXTRACTION AND SYNTHESIS

We examined 157 manuscripts for reporting of best practices including wear time, sampling frequency, data validity, noise/signal loss and data linkage to assess risk of bias.

RESULTS

We found that 6% of the studies did not disclose the GPS device model used, only 12.1% reported the per cent of GPS data lost by signal loss, only 15.7% reported the per cent of GPS data considered to be noise and only 68.2% reported the inclusion criteria for their data.

CONCLUSIONS

Our recommendations for reporting on GPS usage, processing and linkage may be transferrable to other geospatial devices, with the hope of promoting transparency and reproducibility in this research.

PROSPERO REGISTRATION NUMBER

CRD42022322166.

The health impact of freight transport-related air pollution on vulnerable population groups

Every year, over 364,200 people in Europe die prematurely due to the effects of air pollution, in which the transportation sector plays an important role. In Brussels, freight transport generates €61,604 of air pollution health costs daily. Research has shown that dynamic spatiotemporal modeling of both emission sources and exposed people (using mobile phone data) renders more accurate impact results when analyzed in microenvironments. However, mobile data underrepresent population segments that are more sensitive to the effects of air pollution, such as toddlers, children and elderly individuals. This paper examined the link between vulnerable people aged 0-3, 3-18 and >65 years and freight transport-related air pollution concentrations in the Brussels-Capital Region (BCR). To this end, dynamic tailpipe emissions and their spatiotemporal dispersion were calculated using output from the Transport Agent-Based Model (TRABAM) on a daily basis. Population densities were calculated as a function of the residences' occupancy rate and school/class size and opening hours. The effects of exposure were then evaluated using age- and sex-differentiated exposure-response functions and monetized using local hospital cost factors. Data were compiled for 2021. A strong overlap between people's presence at the institutions' locations was noticed with a peak in (freight) transportation movements in the city. The results showed that €37,000 [€34,517.47-€40,047.13] of freight transport-related air pollution health costs were incurred daily by vulnerable population segments. While these vulnerable groups made up 25.34% of the total BCR population, they incurred 60% [56.03%-65.01%] of the engendered transportation air pollution costs. The results were then geographically analyzed to identify 465 traffic-related air pollution hotspots across the territory, which accounted for €36,000 [€33,677.85-€39,101.31] of total costs. The latter can be used in future studies to assess sector-specific freight transportation policies, which should take into consideration spatiotemporal population densities on the local level.

Characteristics of peak exposure to black carbon pollution in school, commute and home environments among school children in an urban community

Although real-time personal exposure monitoring devices have the ability to capture a wealth of data regarding fluctuations in pollutant levels, only a few studies have defined 'peaks' in black carbon (BC) exposure utilizing high-resolution data. Furthermore, studies to assess and characterize various features of peak exposure are very limited especially among children. A better understanding of characteristics of BC peak exposure would improve our understanding of health risks associated with BC. By capturing personal BC exposure at 5-min intervals using a real-time monitor during 24-hr monitoring periods among children in New York City (NYC), we defined 'peak characteristics' in 4 different ways across three major microenvironments (school vs. commute vs. home): 1) mean concentrations of BC across the 3 microenvironments, 2) 'peak duration' or time spent above the peak threshold (i.e., ≥1.5 μg/m3), 3) 'peak intensity' or the rate of exposure, defined as time spent above the threshold within each microenvironment divided by the total time spent in the microenvironment and 4) a novel metric of 'peak variability', defined as frequency of peaks (i.e., data points with +50% and -50% changes compared to the preceding and the subsequent data points), divided by the total time spent in the microenvironment. While peak duration was greatest at home, the intensity of peak exposure was greatest during commute hours, despite the short time spent in commute (p < 0.05). Peak variability was highest during commute, yet lowest in home environments (p < 0.05), particularly during non-sleeping hours. Children residing in a high-density urban setting spent on average, 5.4 hr per day above our peak threshold (≥1.5 μg/m3) in their everyday environments. Policies that limit children's exposure during high traffic periods and improved efforts to increase the number of vehicles using clean air technology could reduce the intensity of peaks and peak variability in children's BC exposure.

Biological monitoring and personal exposure to traffic-related air pollutants of elementary school-age children living in a metropolitan area

An ever-growing burden of scientific evidence links air pollution to different aspects of human health even at very low concentrations; the impact increases for those living in urban environments, especially the youngest and the elderly. This study investigated the exposure to air pollution of urban school children of Milan, Italy, by personal and biological monitoring, in the frame of the MAPS-MI project. A total of 128 primary school children (7-11 years) were involved in a two-season monitoring campaign during spring 2018 and winter 2019. Personal exposure to airborne VOCs and eBC, and biological monitoring of urinary benzene (BEN-U) and methyl-tert-butyl ether (MTBE-U) were performed. Time-activity patterns, environmental tobacco smoke (ETS), spatial, and meteorological information were evaluated as determinants in mixed effects regression analysis. Children personal exposure was mostly quantifiable with median (5th-95th percentile) levels 1.9 (0.8-7.5) μg/m³ for eBC, and 1.1 (<0.6-3.4) and 0.8 (0.3-1.8) μg/m³ for benzene and MTBE, respectively; with values 2-3-fold higher in winter than in spring. In urine, median (5th-95th) BEN-U and MTBE-U levels were 44.9 (25.7-98.6) and 11.5 (5.0-35.5) ng/L, respectively. Mixed effect regression models explained from 72 to 93 % of the total variability for air pollutants, and from 58 to 61 % for biomarkers. Major contributors of personal exposure were season, wind speed, mobility- or traffic-related variables; biomarkers were mostly predicted by airborne exposure and ETS. Our results suggest that traffic-mitigation actions, together with parents' educational interventions on ETS and commuting mode, should be undertaken to lower children exposure to air pollution.

Living Lab Experience in Turin: Lifestyles and Exposure to Black Carbon

State-of-the-art, continuous personal monitoring is a reference point for assessing exposure to air pollution. European air-quality standards for particulate matter (PM) use mass concentration of PM (PM with aerodynamic diameters ≤ 10 μm (PM10) or ≤2.5 μm (PM2.5)) as the metric. It would be desirable to determine whether black carbon (BC) can be used as a better, newer indicator than PM10 and PM2.5. This article discusses the preliminary results of one of the three living laboratories developed in the project "Combination of traditional air quality indicators with an additional traffic proxy: Black Carbon (BC)". The Living Lab#1 (LL#1) involved 15 users in the city of Turin, Italy. Three portable aethalometers (AE51) were used to detect personal equivalent black carbon (eBC) concentrations in the respiratory area of volunteers at 10-s intervals as they went about their normal daily activities. The Geo-Tracker App and a longitudinal temporal activity diary were used to track users' movements. The sampling campaign was performed in November for one week. and each user was investigated for 24 h. A total of 8640 eBC measurements were obtained with an average daily personal exposure of 3.1 µg/m³ (±SD 1.3). The change in movement patterns and the variability of microenvironments were decisive determinants of exposure. Preliminary results highlight the potential utility of Living Labs to promote innovative approaches to design an urban-scale air-quality management plan which also includes BC as a new indicator.

Whole blood fatty acid profile of young subjects and adherence to the Mediterranean diet: an observational cohort study

Background

Relatively little is known about the physiological whole blood fatty acid composition in young people. Likewise, few studies have addressed the question of correlations between Mediterranean diet (MedDiet) adherence and blood fatty acids in childhood.

Methods

The fatty acid profile in whole blood from subjects, 46 days-19 years old (n = 152), without acute, chronic, or inflammatory diseases was analysed by gas chromatography. Dietary data was extracted from a 24-h recall in a subgroup of subjects (n = 60) into a modified Diet Quality Index for Children (KIDMED) questionnaire to evaluate MedDiet adherence. The cohort was divided into three age groups: < 2, 2- < 10, and 10–19 years. Kruskal-Wallis test and Bonferroni post hoc test were used to check for age group fatty acid differences. For correlations, Spearman’s correlation coefficient and partial Spearman’s correlation coefficient were used.

Results

Linoleic acid, EPA, DHA, palmitic acid, and total saturated fatty acids were stable over age groups. Dihomo-gamma-linolenic acid (DGLA), arachidonic acid (AA), total polyunsaturated FAs (PUFA), and total omega-6 PUFA increased from age group < 2 years; alpha-linolenic acid, total omega-3 PUFA, oleic acid, and total monounsaturated FAs decreased. Adherence to the MedDiet was at low-medium level in 91.7% of the subjects. In the age group 2- < 10 yrs., the degree of adherence correlated positively with total MUFA and PUFA balance, negatively with total PUFA, total n6-PUFA, AA/DHA, AA/EPA, and n6/n3. Age did not influence the correlations as to PUFA balance and AA/EPA.

Conclusions

Increased FA proportions with age were seen in the n6-series of PUFA. The n3-FA species decreased or were stable. The vast majority of the subjects with dietary data, 92%, obtained a KIDMED score indicative of low-medium adherence to the MedDiet. The score correlated negatively with various n6-species, i.e. the MedDiet suppressed circulating n6-PUFA. Whole blood may be used to investigate FAs and MedDiet adherence correlations which may be applied in the study of health issues in childhood.

Quantify individual variation of real-time PM2.5 exposure in urban Chinese homes based on a novel method

Fine particulate matter (PM_2.5 ) concentrations show high variations in different microenvironments indoors, which has considerable impact on risk management. However, the real-time variations of PM_2.5 exposure associated with per activity/microenvironment and intra-variation among family members remain undefined. In this study, real-time monitors were used to collect real-time PM_2.5 data in different microenvironments in 32 households in urban community of China. Peak concentrations of PM_2.5 were found in kitchen. The parallel levels of PM_2.5 household indoor and outdoor indicated the benefit of clean energies use. To validly assess the health risk of individuals, we proposed a novel method to estimate the real-time exposure of all residents and firstly investigate the intra-variation of PM_2.5 exposure among family members. The member who is responsible for cooking in the family had the maximum PM_2.5 exposure. The ratios among intraindividual variations demonstrated children usually had lower exposure compared to the adults as they stayed more time in lower polluted microenvironments such as living room and bedroom. The exposure intensity in living room was above 1.0 for most residents, indicating it is warranted to alleviate the air pollution in living room. This study firstly focused on the intra differences of PM_2.5 exposure among family members and provided a new insight for indoor air pollution management. The results suggested when adopting measures to reduce exposure, the microenvironments pattern of each member should be taken into consideration. Future work is welcomed to move another big step on this issue to protect the human health.

Smoking habit in parents and exposure to environmental tobacco smoke in elementary school children of Milan

INTRODUCTION

Children with smoking parents are potentially exposed to Environmental Tobacco Smoke (ETS). The aims of this study were: 1) to assess ETS exposure in Milan schoolchildren, by measuring urinary cotinine (COT-U), 2) to compare the parents' perception of children ETS exposure, with the actual ETS exposure measured by COT-U, 3) to explore the factors influencing COT-U, including smoking bans at home, the season, and children characteristics.

METHODS

One-hundred school children (7-11 years) and their parents were recruited for the study in Spring 2018 (n = 81) and in Winter 2019 (n = 94), 75 children participated to both campaigns, for a sum of 175 observations. A questionnaire was submitted to parents to collect information about smoking habits in the house. COT-U was measured by LC-MS/MS in spot urine sample collected in the morning from children.

RESULTS

Detectable COT-U levels were found in 42% and 57% of children, in spring and winter, in contrast with 17% and 13% of parents acknowledging ETS exposure. Children living with smokers or e-cigarette users (vapers) (30% of the participants) had higher COT-U levels than children not living with smokers or vapers (median 0.67, 0.46, and <0.1 μg/L in spring, and 0.98, 0.85, and 0.11 μg/L in winter, respectively). Increasingly higher COT-U levels were observed in children living in homes where smoking was completely banned, allowed in the external parts of the home, or allowed in some rooms. The multiple regression analysis confirmed the positive significant effect of living with smokers, a partial smoking ban and absence of smoking ban at home, the winter season, and BMI as determinants of COT-U.

CONCLUSION

ETS exposure resulted in measurable urinary cotinine in children. Smoking parents underestimate exposure to ETS of their children. Living with smokers is a determinant of COT-U, only slightly mitigated by adopting partial smoking ban.

Atmospheric black carbon in urban and traffic areas in Shanghai: Temporal variations, source characteristics, and population exposure

Black carbon (BC) measurements were performed at Pudong (PD) urban supersite and Gonghexin (GH) roadside station from December 1, 2017 to August 10, 2020 to investigate the variations, source characteristics, and population exposure levels of BC in traffic and urban areas in Shanghai, China. The BC median concentration at GH was more than two-fold that at PD. Absorption Ångström exponent (AAE) values were 1.27 ± 0.17 and 1.31 ± 0.17 at PD and GH, respectively, suggesting the dominance of liquid fossil fuel combustion sources (i.e., traffic exhaust) at these stations. The higher BC and AAE values in winter at PD indicated the relatively increasing contribution of solid fuels (i.e., biomass burning) to BC concentration in urban Shanghai. The diurnal variation in BC showed similar twin-peak patterns at PD and GH, implying that traffic emission mainly contributed to ambient BC concentration in urban Shanghai. The estimated daily intakes (EDIs) of BC were generally higher in males than in females at both PD and GH. The highest BC EDIs at PD were found in age subgroups 1-<2 and 2-<3 years. In contrast, the BC EDIs at GH were observed in age subgroups 6-<9, 12-<15, and 15-<18 years, which were higher than those determined at PD, indicating that more attention must be paid to BC exposure of the population in these age subgroups. These results provide scientific insights into variations, source characteristics, and population exposure levels of BC in urban and traffic areas and could help in the development of BC control strategies in Shanghai.

Long-term residential exposure to air pollution is associated with hair cortisol concentration and differential leucocyte count in Flemish adolescent boys

BACKGROUND

Exposure to air pollution and traffic noise are associated with adverse health outcomes in adolescents. Chronic endocrine stress and systemic inflammation have been hypothesized to underlie the adverse health effects. Simultaneous assessment of inflammation and chronic endocrine stress in epidemiological studies is lacking. The aim of the study was to investigate biomarkers of chronic endocrine stress and inflammation in relation to long-term residential exposure to air pollution and traffic noise in adolescents.

METHODS

In Flemish adolescents (14-15 years), we determined hair cortisol concentration (HCC) as a chronic stress biomarker in 3-cm scalp-near hair sections (n = 395), and leucocyte and leucocyte subtype counts (neutrophils, monocytes, lymphocytes) as inflammatory biomarkers in peripheral blood (n = 385). Daily particulate matter (PM_2.5, PM₁₀), nitrogen dioxide (NO₂) and black carbon (BC) concentrations were modelled at the residential address and averaged over 3-month and 1-year periods prior to sampling. Residential traffic noise level was estimated and classified in 5 dB intervals. Sex-specific associations between residential exposures and effect biomarkers were studied using linear regression models, adjusted for a priori selected covariates.

RESULTS

In boys, HCC increased with a factor 1.30 (95% CI: 1.10, 1.54) for an increase in 1-year mean NO₂ from the 25th to 75th percentile (p75/p25), after adjustment for age, BMI, personal and neighborhood socioeconomic status. The corresponding estimate for PM₁₀ was 1.24 (95% CI: 1.02, 1.51). Total leucocyte count in boys, adjusted for the aforementioned covariates and recent health complaints, was positively associated with PM_2.5, PM₁₀, NO₂ and BC. In particular, the neutrophil count increased with a factor 1.11 (95% CI: 1.03, 1.19) for a (p75/p25)-factor increase in 1-year mean BC, corresponding estimates for PM_2.5, PM₁₀ and NO₂ were 1.10 (95% CI: 1.01, 1.19), 1.10 (95% CI: 1.01, 1.20) and 1.08 (95% CI: 1.00, 1.16). Lymphocyte count increased with a factor 1.05 (95% CI: 1.01, 1.10) for a (p75/p25)-factor increase in 1-year mean NO₂. Similar results were observed for 3-month mean exposures. Results were robust to adjustment for recent air pollution exposure. In girls, air pollutants were not associated with HCC or differential leucocyte count. Residential traffic noise level was not associated with HCC or leucocyte counts in boys nor girls.

CONCLUSIONS

Long-term residential exposure to air pollutants was positively associated with chronic endocrine stress and inflammation in adolescent boys, not in girls. This study may contribute to a better understanding of the early pathophysiological changes that may underlie adverse health effects of air pollution exposure in adolescents.