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High variability between regional histories of long-term atmospheric Pb pollution.

ABSTRACT: The advent of metal processing was one of the key technological evolutions presaging the development of modern society. However, the interplay between metal use and the long-term changes it induced in the development and functioning of past societies remains unclear. We present a compilation of global records of anthropogenic atmospheric lead (Pb) spanning the last 4000 years, an effective indirect proxy for reliably assessing Pb emissions directly linked to human activities. Separating this global Pb pollution signal into regionally representative clusters allows identification of regional differences in pollution output that reflect technological innovations, market demands, or demise of various human cultures for last 4000 years. Our European reconstruction traces well periods of intensive metal production such as the Roman and Medieval periods, in contrast to clusters from the Americas, which show low levels of atmospheric Pb until the Industrial Revolution. Further investigation of the European synthesis results displays clear regional variation in the timing and extent of past development of polluting activities. This indicates the challenges of using individual reconstructions to infer regional or global development in Pb output and related pollution.

SUBMITTER: Longman J

PROVIDER: S-EPMC7708465 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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High variability between regional histories of long-term atmospheric Pb pollution.

Longman Jack J Ersek Vasile V Veres Daniel D

Scientific reports 20201201 1

The advent of metal processing was one of the key technological evolutions presaging the development of modern society. However, the interplay between metal use and the long-term changes it induced in the development and functioning of past societies remains unclear. We present a compilation of global records of anthropogenic atmospheric lead (Pb) spanning the last 4000 years, an effective indirect proxy for reliably assessing Pb emissions directly linked to human activities. Separating this glo ...[more]

PMID: 33262534

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Project description:BackgroundAir pollution exposures have been shown to adversely impact health through a number of biological pathways associated with glucose metabolism. However, few studies have evaluated the associations between air pollution and glycosylated hemoglobin (HbA1c) levels. Further, no studies have evaluated these associations in US populations or investigated whether associations differ in diabetic as compared to non-diabetic populations. To address this knowledge gap, we investigated the associations between airborne fine particulate matter (PM2.5) and nitrogen dioxide (NO2) and HbA1c levels in both diabetic and non-diabetic older Americans. We also examined the impact of PM2.5 and NO2 on prevalent diabetes mellitus (DM) in this cohort.MethodsWe used multilevel logistic and linear regression models to evaluate the association between long-term average air pollutant levels and prevalence of DM and HbA1c levels, respectively, among 4121 older (57+ years) Americans enrolled in the National Social Life, Health, and Aging Project between 2005 and 2011. All models adjusted for age, sex, body mass index, smoking status, race, household income, education level, neighborhood socioeconomic status, geographic region, urbanicity and diabetic medication use. We estimated participant-specific exposures to PM2.5 on a six-kilometer grid covering the conterminous U.S. using spatio-temporal models, and to NO2 using nearest measurements from the Environmental Protection Agency's Air Quality System. HbA1c levels were measured for participants in each of two data collection waves from dried blood spots and log-transformed prior to analysis. Participants were considered diabetic if they had HbA1c values≥6.5% or reported taking diabetic medication.ResultsThe prevalence of diabetes at study entry was 22.2% (n=916) and the mean HbA1c was 6.0±1.1%. Mean one-year moving average PM2.5 and NO2 exposures were 10.4±3.0μg/m3 and 13.1±7.0 ppb, respectively. An inter-quartile range (IQR, 3.9μg/m3) increase in one-year moving average PM2.5 was positively associated with increased diabetes prevalence (prevalence odds ratio, POR 1.35, 95% CI: 1.19, 1.53). Similarly, an IQR (8.6 ppb) increase in NO2 was also significantly associated with diabetes prevalence (POR 1.27, 95% CI: 1.10, 1.48). PM2.5 (1.8%±0.6%, p<0.01) and NO2 (2.0%±0.7%, p<0.01) exposures were associated with higher HbA1c levels in diabetic participants, while only NO2 was significantly associated with HbA1c in non-diabetic participants (0.8%±0.2%, p<0.01). Significant dose response relationships were identified for both pollutants in diabetic participants and for NO2 in non-diabetic participants.Conclusions/interpretationsIn a cohort of older men and women in the United States, PM2.5 and NO2 exposures were significantly associated with prevalence of DM and increased HbA1c levels among both non-diabetic and diabetic participants. These associations suggest that air pollution could be a key risk factor for abnormal glucose metabolism and diabetes in the elderly.

Project description:Mobile monitoring has provided a means for broad spatial measurements of air pollutants that are otherwise impractical to measure with multiple fixed site sampling strategies. However, the larger the mobile monitoring route the less temporally dense measurements become, which may limit the usefulness of short-term mobile monitoring for applications that require long-term averages. To investigate the stationarity of short-term mobile monitoring measurements, we calculated long term medians derived from a mobile monitoring campaign that also employed 2-week integrated passive sampler detectors (PSD) for NOx, Ozone, and nine volatile organic compounds at 43 intersections distributed across the entire city of Baltimore, MD. This is one of the largest mobile monitoring campaigns in terms of spatial extent undertaken at this time. The mobile platform made repeat measurements every third day at each intersection for 6-10 minutes at a resolution of 10 s. In two-week periods in both summer and winter seasons, each site was visited 3-4 times, and a temporal adjustment was applied to each dataset. We present the correlations between eight species measured using mobile monitoring and the 2-week PSD data and observe correlations between mobile NOx measurements and PSD NOx measurements in both summer and winter (Pearson's r = 0.84 and 0.48, respectively). The summer season exhibited the strongest correlations between multiple pollutants, whereas the winter had comparatively few statistically significant correlations. In the summer CO was correlated with PSD pentanes (r = 0.81), and PSD NOx was correlated with mobile measurements of black carbon (r = 0.83), two ultrafine particle count measures (r =0.8), and intermodal (1-3 ?m) particle counts (r = 0.73). Principal Component Analysis of the combined PSD and mobile monitoring data revealed multipollutant features consistent with light duty vehicle traffic, diesel exhaust and crankcase blow by. These features were more consistent with published source profiles traffic-related air pollutants than features based on the PSD data alone. Short-term mobile monitoring shows promise for capturing long-term spatial patterns of traffic-related air pollution, and is complementary to PSD sampling strategies.

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High variability between regional histories of long-term atmospheric Pb pollution.

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High variability between regional histories of long-term atmospheric Pb pollution.

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