This paper presents an interdisciplinary perspective on human health in the context of long-term social-ecological systems change. From hunting and gathering bands through modern globalized societies, human health systems have been grounded in the dynamics of the dominant social-ecological regime. These dynamics are ordered by circular feedbacks between ecological processes, available energy sources, levels of social complexity, and cultural ontologies that in turn influence epidemiological patterns, health system structures, and ontologies of health. Today, the environmental signatures of the Anthropocene (ex. climate change, biodiversity loss) are pushing ecosystems across thresholds into new configurations. Vulnerabilities and rigidities are also accumulating in the dominant political economy. Among the most significant vulnerabilities is the dependence of globalized society on economic growth to improve material standards of living and secure the social compact, functions that are coupled with rising rates of individualization and the expanding material and energetic footprint of human activities. Confronted with escalating socio-economic and ecological crises, the Anthropocene brings with it a global-scale transition toward a new social-ecological system. This transition could see the collapse of much of what upholds modern medicine, including welfare state benefits, international pharmaceutical and supply chains, and antibiotic capabilities. Drawing on literatures from medical anthropology, complexity science, and ecological economics, this paper argues that promising alternatives for health systems in the Anthropocene must offer structural and ontological frameworks that can secure long-term planetary health in a context of ecological limits, economic contraction, relocalization, and reemerging networks of reciprocal care. Alternatives that emphasize the systemic relationships between human health outcomes and broader ecological, economic, and social contexts are most likely to generate humane structures for health systems in the Anthropocene. Emerging alternatives include ethnographic cases from the degrowth movement, Transition Initiatives, traditional medicines, alternative approaches to ritual and death, and complexity medicine.
Satellite aerosol optical depth (AOD) data have been used to assess population exposure to fine particulate matter (PM2.5), but are challenged by non-random missingness due to cloud/snow cover and high surface reflectance. Previous studies filled the data gap by spatially smoothing neighboring PM2.5 measurements or predictions; however, this strategy ignored the effect of cloud cover on aerosol loadings and did not perform well when monitoring stations are sparse or there is seasonal large-scale missingness. For example, in the Yangtze River Delta, the monsoon season (summer) leads to, on average, approximately 75% AOD missingness even after combining Aqua and Terra data. Here we present a Multiple Imputation (MI) method that fused the chemical transport model (CTM) simulations and the high-resolution satellite retrievals to fill missing AOD and provide PM2.5 predictions with fine resolution, complete coverage, and high accuracy. First, we fitted daily MI models that employed the spatiotemporal auto-correlation of AOD to impute missing AOD from available satellite data, CTM simulations, and meteorological parameters. Repeated imputations were conducted to account for random error. Then a two-stage hybrid model was fitted to estimate daily ground PM2.5 concentrations from complete-coverage MAIAC AOD, meteorology, and land use information. The daily MI models have an average R2 as 0.77, with an inter quartile range from 0.71 to 0.82. The overall model 10-fold cross validation R2 (relative prediction error) were 0.81 (34%) and 0.73 (29%) for year 2013 and 2014, respectively. Models fitted with only observational AOD or only imputation AOD performed similarly. Using models fitted by data of year 2013 and 2014 to predict monthly PM2.5 concentrations in 2015 gave an R2 as 0.70 and 0.71, respectively. This method provides reliable PM2.5 predictions with complete coverage that can reduce exposure error in air pollution health effect research.
Although lead (Pb) is known to be highly toxic, particularly to children, many developing countries lack the resources to assess exposure by testing for lead in blood or soil. We present here results for a new field kit intended for public use to screen soils for Pb. Before deployment, the kit was used to identify high levels of bioaccessible Pb in 63 soil samples from a range of contaminated settings using a simulated gastric extraction of glycine and hydrochloric acid and sodium rhodizonate as a color indicator. For confirmation, total concentrations of Pb were measured in soil and soil extracts by X-ray fluorescence (XRF) and, for a subset of extracts, by inductively coupled plasma mass spectrometry. During the subsequent deployment of the kit in four mining-impacted Peruvian communities, 90 soil samples were collected by local parents and analyzed in their presence by trained field staff. Combining the two data sets, concentrations of total and extractable soil Pb measured by XRF ranged 40-50,000 mg/kg and 10-7,400 mg/kg. Significantly, parent sampling with the field kit identified an area contaminated with Pb that had been missed during a prior gridded XRF survey. Field kit results are compared to U.S. EPA standards for total soil Pb and bioavailable Pb established by assuming 30% bioavailability. In two trials, all 25 extracted solutions that the kit ranked high visually contained >360 mg/kg extractable Pb (>1200 mg/kg total Pb). With further refinement of the kit, 51 of the 59 samples that were ranked visually high contained over 120 mg/kg extractable Pb (>400 mg/kg total Pb, the EPA standard for bare soil where children play). The results indicate the field test kit could be used by the general public to screen soils for Pb and as a way of prompting further assessment and intervention.
Air pollution in many of India’s cities exceeds national and international standards; effective pollution control strategies require knowledge of the sources that contribute to air pollution and their spatiotemporal variability. In this study, we use daily active fires and bimonthly burned area observations to examine the influence of outdoor biomass burning, one of the hypothesized but poorly quantified sources, on particulate matter (PM) concentrations in the Delhi National Capital Region during the winter burning season (defined as October to November). First, using daily MODIS fire radiative power (FRP) detections, we find that the contribution of agricultural residue burning to outdoor fire emissions can contribute substantially to regional air pollution with high levels of population exposure during the winter burning season but less during the summer. In the area surrounding Delhi, 65 million people (38% in urban areas) are exposed to severely degraded air quality; during the 2013 winter burning season on extreme PM2.5 days (1 SD above the mean), which coincide with high fire activity, Delhi averaged 311 µg/m3, more than 1000% above the 24-hour PM2.5 guideline (25 µg/m3) of the World Health Organization. In the second part of this analysis, we use high spatial resolution (30m x 30m) Landsat burned area observations to supplement those from the coarser spatial resolution (500m x 500m) MODIS. This combined product estimates 2-5 times more burned area in Punjab and Haryana (northwestern agricultural states) during the 2003-2014 winter burning seasons than GFEDv4.1s. In future work, we will combine the bimonthly MODIS and Landsat burned area estimations with daily MODIS FRP observations to build a new emissions inventory for outdoor biomass burning and implement it in a high-resolution atmospheric model to reevaluate public health impacts. Our results suggest that providing viable alternatives to agricultural residue burning could help improve winter air quality in Delhi.
Since plastics degrade very slowly, they remain in the environment on much longer timescales than most natural substrates and can thus provide a novel habitat for colonization by bacterial communities (Zettler et al. 2013 Environ. Sci. Technol. 47:7137). The full spectrum of relationships between plastics and bacteria, however, is little understood. The objective of this study was to examine marine plastic pollution as a substrate for bacteria, with particular focus on Vibrio spp., including the human pathogens, V. cholerae, V. parahaemolyticus, and V. vulnificus. We set up colonization experiments in a tributary of the lower Chesapeake Bay to follow Vibrio spp. colonization and total bacterial community composition over time. We also collected microplastics and paired seawater samples and determined the presence, abundance, and antibiotic-resistance profiles of Vibrio spp. they harbored. We examined Vibrio isolates’ response to six antibiotics and found no differences between the antibiotic susceptibilities of vibrios isolated from plastics compared to those from the surrounding water column. There was, however, a significant difference in antibiotic susceptibility between isolates from colonization experiments and microplastics, with more resistance overall seen in the former. In every instance examined, we found vibrios to be enriched on plastics by at least two orders of magnitude compared to those from paired seawater samples. Bacterial colonization was detected with DNA sequencing as early as day 2 and plastic communities were consistently distinct and more diverse than surrounding seawater. Colonization rates and community structure varied temporally and among substrate types, suggesting that numerous factors should be considered when characterizing microbial communities on plastic. This study demonstrates that plastic pollution serves as a habitat for Vibrio species and confirms the conjecture of Zettler et al. (2013) that plastics may serve as a vector for these and other potentially pathogenic bacteria.
Well logs from heavy oil development wells in the San Joaquin Valley, California, frequently record high gamma ray (GR) values through intervals of the hot, vapor-filled rock that remains after injected steam at temperatures greater than 250 degF displaces heavy oil. GR values that exceed 20,000 GAPI and are 200 to 400 times greater than those in similar, but liquid-filled, rock have been observed. These high GR values occur on open-hole logs through new wells that intersect a steam chamber, after circulation of mud while drilling temporarily cools a well and causes hot vapor to condense. Days later, after a completed well re-heats, GR decreases to normal levels. In one well, circulation of cool water regenerated the high GR, demonstrating that the response is reversible. The GR energy spectra matches the uranium series and identifies highly mobile, naturally-occurring, radon and its progeny as the GR source.
The amplitude of the transient GR is related to vapor properties because radon is more soluble in hydrocarbon than in water. Reservoir studies show that GR increases with residual oil saturation in the steam chamber. In a surprising anomaly, a well-swept heavy oil reservoir that contains very little remaining oil has extremely high GR. This response is explained by the invasion of light hydrocarbons sourced from a deeper reservoir. The high vapor pressure of volatile hydrocarbons increases the efficiency of radon capture, and therefore, GR is higher in the condensate surrounding the well.
For a mixture of radon and pentane, an experiment confirms that large and reversible GR responses are observed as temperature changes and pentane-tagged with radon condenses and vaporizes. This implies that when naturally-occurring radon and condensable-hydrocarbon vapor are present at surface, containment and continuous monitoring are required to ensure that inhalation of radon-enriched hydrocarbon vapor condensate does not occur.
Labeling is a popular policy tool that uses incentives instead of regulation to change firm behavior. We study the effectiveness of a mandatory ingredient label in addressing the unexpected discovery of pollution and potential health risks from microplastics in premium toothpaste. We compare how sales of toothpaste with plastic microbeads change compared to toothpaste without beads before and after news of microbead risk. We first show that consumers are responding to the news and seeking out information on microbeads through the internet. Next, we show that consumers respond to this information and reduce demand for toothpaste with microbeads by a large and statistically significant magnitude. However, consumers appear to rely more on product and brand names than on the ingredient label. Immediately after learning about microbead risk, consumers shift to other products by the same brand and toward brands associated with health and the environment. We explore whether retailers respond to the negative demand shock and find that the response varies across retailers; strategic retailers exploit the shock to price discriminate, toggling between prices higher than before the shock (for loyal consumers) and deep discounts. On net, this strategy increases the total volume of microbead toothpaste sold to a level that exceeds their sales volume before news spread of their risks. We explore why retailers use this pricing strategy in the wake of the news shocks. We are the first to show empirical evidence of an initially successful consumer boycott driven by environmental concerns. We add a richer description of strategic pricing behavior by retailers which may explain why many boycotts ultimately appear to fail.