Alison C. Cullen

Are Women as Likely to Take Risks and Compete? Behavioural Findings from Central Vietnam

Abstract Using controlled experiments to compare the risk attitude and willingness to compete of husbands and wives in 500 couples in rural Vietnam, we find that women are more risk averse than men and that, compared to men, women are less likely to choose to compete, irrespective of how likely they are to succeed. Relevant to development programmes concerned with lifting women out of poverty, our findings suggest that women may be more reluctant to adopt new technologies, take out loans, or engage in economic activities that offer higher expected returns, in order to avoid setups that require them to be more competitive or that have less predictable outcomes.

Metagenomic Frameworks for Monitoring Antibiotic Resistance in Aquatic Environments

Background: High-throughput genomic technologies offer new approaches for environmental health monitoring, including metagenomic surveillance of antibiotic resistance determinants (ARDs). Although natural environments serve as reservoirs for antibiotic resistance genes that can be transferred to pathogenic and human commensal bacteria, monitoring of these determinants has been infrequent and incomplete. Furthermore, surveillance efforts have not been integrated into public health decision making. Objectives: We used a metagenomic epidemiology–based approach to develop an ARD index that quantifies antibiotic resistance potential, and we analyzed this index for common modal patterns across environmental samples. We also explored how metagenomic data such as this index could be conceptually framed within an early risk management context. Methods: We analyzed 25 published data sets from shotgun pyrosequencing projects. The samples consisted of microbial community DNA collected from marine and freshwater environments across a gradient of human impact. We used principal component analysis to identify index patterns across samples. Results: We observed significant differences in the overall index and index subcategory levels when comparing ecosystems more proximal versus distal to human impact. The selection of different sequence similarity thresholds strongly influenced the index measurements. Unique index subcategory modes distinguished the different metagenomes. Conclusions: Broad-scale screening of ARD potential using this index revealed utility for framing environmental health monitoring and surveillance. This approach holds promise as a screening tool for establishing baseline ARD levels that can be used to inform and prioritize decision making regarding management of ARD sources and human exposure routes. Citation: Port JA, Cullen AC, Wallace JC, Smith MN, Faustman EM. 2014. Metagenomic frameworks for monitoring antibiotic resistance in aquatic environments. Environ Health Perspect 122:222–228; http://dx.doi.org/10.1289/ehp.1307009

Environmental impacts and constraints associated with the production of major food crops in Sub-Saharan Africa and South Asia

Many environmental factors constrain the production of major food crops in Sub-Saharan Africa and South Asia. At the same time, these food production systems themselves have a range of negative impacts on the environment. In this paper we review the published literature and assess the depth of recent research (since 2000) on crop x environment interactions for rice, maize, sorghum/millets, sweetpotato/yam and cassava in these two regions. We summarize current understandings of the environmental impacts of crop production systems prior to crop production, during production and post-production, and emphasize how those initial environmental impacts become new and more severe environmental constraints to crop yields. Pre-production environmental interactions relate to agricultural expansion or intensification, and include soil degradation and erosion, the loss of wild biodiversity, loss of food crop genetic diversity and climate change. Those during crop production include soil nutrient depletion, water depletion, soil and water contamination, and pest resistance/outbreaks and the emergence of new pests and diseases. Post-harvest environmental interactions relate to the effects of crop residue disposal, as well as crop storage and processing. We find the depth of recent publications on environmental impacts is very uneven across crops and regions. Most information is available for rice in South Asia and maize in Sub-Saharan Africa where these crops are widely grown and have large environmental impacts, often relating to soil nutrient and water management. Relatively few new studies have been reported for sorghum/millets, sweetpotato/yam or cassava, despite their importance for food security on large areas of marginal farmland in Sub-Saharan Africa – however, there is mounting evidence that even these low-input crops, once thought to be environmentally benign, are contributing to cycles of environmental degradation that threaten current and future food production. A concluding overview of the emerging range of published good practices for smallholder farmers highlights many opportunities to better manage crop x environment interactions and reduce environmental impacts from these crops in developing countries.

Personal exposure to particles in Banská Bystrica, Slovakia *

Epidemiological studies have associated adverse health impacts with ambient concentrations of particulate matter (PM), though these studies have been limited in their characterization of personal exposure to PM. An exposure study of healthy nonsmoking adults and children was conducted in Banska Bystrica, Slovakia, to characterize the range of personal exposures to air pollutants and to determine the influence of occupation, season, residence location, and outdoor and indoor concentrations on personal exposures. Twenty-four-hour personal, at-home indoor, and ambient measurements of PM10, PM2.5, sulfate (SO42−) and nicotine were obtained for 18 office workers, 16 industrial workers, and 15 high school students in winter and summer. Results showed that outdoor levels of pollutants were modest, with clear seasonal differences: outdoor PM10 summer/winter mean=35/45 µg/m3; PM2.5 summer/winter mean=22/32 µg/m3. SO42− levels were low (4–7 µg/m3) and relatively uniform across the different sample types (personal, indoor, outdoor), areas, and occupational groups. This suggests that SO42− may be a useful marker for combustion mode particles of ambient origin, although the relationship between personal exposures and ambient SO42− levels was more complex than observed in North American settings. During winter especially, the central city area showed higher concentrations than the suburban location for outdoor, personal, and indoor measures of PM10, PM2.5, and to a lesser extent for SO42−, suggesting the importance of local sources. For PM2.5 and PM10, ratios consistent with expectations were found among exposure indices for all three subject groups (personal>indoor>outdoor), and between work type (industrial>students>office workers). The ratio of PM2.5 personal to indoor exposures ranged from 1.0 to 3.9 and of personal to outdoor exposures from 1.6 to 4.2. The ratio of PM10 personal to indoor exposures ranged from 1.1 to 2.9 and the ratio of personal to outdoor exposures from 2.1 to 4.1. For a combined group of office workers and students, personal PM10/PM2.5 levels were predicted by statistically significant multivariate models incorporating indoor (for PM2.5) or outdoor (for PM10) PM levels, and nicotine exposure (for PM10). Small but significant fractions of the overall variability, 15% for PM2.5 and 17% for PM10, were explained by these models. The results indicate that central site monitors underpredict actual human exposures to PM2.5 and PM10. Personal exposure to SO42− was found to be predicted by outdoor or indoor SO42− levels with 23–71% of the overall variability explained by these predictors. We conclude that personal exposure measurements and additional demographic and daily activity data are crucial for accurate evaluation of exposure to particles in this setting.

The Sensitivity of Probabilistic Risk Assessment Results to Alternative Model Structures: A Case Study of Municipal Waste Incineration

In this analysis, human health risk due to exposure to municipal waste incinerator emissions is assessed as an example of the application of probabilistic techniques (e.g., Monte Carlo or Latin Hypercube simulations). Incinerator risk assessments are characterized by the dominance of indirect exposure, thus this analysis focuses on exposure via the ingestion of locally grown foods. In addition, since exposure to 2,3,7,8-TCDD drives most incinerator risk assessments, this compound is the subject of the illustrative calculations. An important part of probabilistic risk assessment is determining the relative influence of the input parameters on the magnitude of the variance in the output distribution. This constitutes an important step toward prioritizing data needs for additional research. However, under various possible model forms reflecting incompletely understood aspects of contaminant transport, differences may be observed in estimates of risk, variance in risk, and the relative contributions of individual uncertain and variable inputs to the variance. In this analysis, a sequential structural decomposition of the relationships between the input variables is used to partition the variance in the output (i.e., risk) to identify the most influential contributors to overall variance among them. For comparison, the partitioning of variance is repeated, using techniques of multivariate regression. In summary, this study considers the degree to which results of a probabilistic assessment are contingent on critical model assumptions about the representation of deposition velocity. Specifically, this analysis assesses the impact on the results of uncertainty about the best model of the vapor/particle partitioning behavior of semi-volatile airborne pollutants.

Probabilistic Exposure Analysis for Chemical Risk Characterization

This paper summarizes the state of the science of probabilistic exposure assessment (PEA) as applied to chemical risk characterization. Current probabilistic risk analysis methods applied to PEA are reviewed. PEA within the context of risk-based decision making is discussed, including probabilistic treatment of related uncertainty, interindividual heterogeneity, and other sources of variability. Key examples of recent experience gained in assessing human exposures to chemicals in the environment, and other applications to chemical risk characterization and assessment, are presented. It is concluded that, although improvements continue to be made, existing methods suffice for effective application of PEA to support quantitative analyses of the risk of chemically induced toxicity that play an increasing role in key decision-making objectives involving health protection, triage, civil justice, and criminal justice. Different types of information required to apply PEA to these different decision contexts are identified, and specific PEA methods are highlighted that are best suited to exposure assessment in these separate contexts.

Policy implications of genetic information on regulation under the Clean Air Act: The case of particulate matter and asthmatics

The U.S. Clean Air Act (CAA) explicitly guarantees the protection of sensitive human subpopulations from adverse health effects associated with air pollution exposure. Identified subpopulations, such as asthmatics, may carry multiple genetic susceptibilities to disease onset and progression and thus qualify for special protection under the CAA. Scientific advances accelerated as a result of the ground-breaking Human Genome Project enable the quantification of genetic information that underlies such human variability in susceptibility and the cellular mechanisms of disease. In epidemiology and regulatory toxicology, genetic information can more clearly elucidate human susceptibility essential to risk assessment, such as in support of air quality regulation. In an effort to encourage the incorporation of genomic information in regulation, the U.S. Environmental Protection Agency (EPA) has issued an Interim Policy on Genomics. Additional research strategy and policy documents from the National Academy of Science, the U.S. EPA, and the U.S. Department of Health and Human Services further promote the expansion of asthma genetics research for human health risk assessment. Through a review of these government documents, we find opportunities for the inclusion of genetic information in the regulation of air pollutants. In addition, we identify sources of information in recent scientific research on asthma genetics relevant to regulatory standard setting. We conclude with recommendations on how to integrate these approaches for the improvement of regulatory health science and the prerequisites for inclusion of genetic information in decision making.

Spatial–temporal and cancer risk assessment of selected hazardous air pollutants in Seattle

In the Seattle Air Toxics Monitoring Pilot Program, we measured 15 hazardous air pollutants (HAPs) at 6 sites for more than a year between 2000 and 2002. Spatial-temporal variations were evaluated with random-effects models and principal component analyses. The potential health risks were further estimated based on the monitored data, with the incorporation of the bootstrapping technique for the uncertainty analysis. It is found that the temporal variability was generally higher than the spatial variability for most air toxics. The highest temporal variability was observed for tetrachloroethylene (70% temporal vs. 34% spatial variability). Nevertheless, most air toxics still exhibited significant spatial variations, even after accounting for the temporal effects. These results suggest that it would require operating multiple air toxics monitoring sites over a significant period of time with proper monitoring frequency to better evaluate population exposure to HAPs. The median values of the estimated inhalation cancer risks ranged between 4.3 × 10⁻⁵ and 6.0 × 10⁻⁵, with the 5th and 95th percentile levels exceeding the 1 in a million level. VOCs as a whole contributed over 80% of the risk among the HAPs measured and arsenic contributed most substantially to the overall risk associated with metals.

Can Carbon Nanomaterials Improve CZTS Photovoltaic Devices? Evaluation of Performance and Impacts Using Integrated Life-Cycle Assessment and Decision Analysis.

In emergent photovoltaics, nanoscale materials hold promise for optimizing device characteristics; however, the related impacts remain uncertain, resulting in challenges to decisions on strategic investment in technology innovation. We integrate multi-criteria decision analysis (MCDA) and life-cycle assessment (LCA) results (LCA-MCDA) as a method of incorporating values of a hypothetical federal acquisition manager into the assessment of risks and benefits of emerging photovoltaic materials. Specifically, we compare adoption of copper zinc tin sulfide (CZTS) devices with molybdenum back contacts to alternative devices employing graphite or graphene instead of molybdenum. LCA impact results are interpreted alongside benefits of substitution including cost reductions and performance improvements through application of multi-attribute utility theory. To assess the role of uncertainty we apply Monte Carlo simulation and sensitivity analysis. We find that graphene or graphite back contacts outperform molybdenum under most scenarios and assumptions. The use of decision analysis clarifies potential advantages of adopting graphite as a back contact while emphasizing the importance of mitigating conventional impacts of graphene production processes if graphene is used in emerging CZTS devices. Our research further demonstrates that a combination of LCA and MCDA increases the usability of LCA in assessing product sustainability. In particular, this approach identifies the most influential assumptions and data gaps in the analysis and the areas in which either engineering controls or further data collection may be necessary.

The Precautionary Principle in Practice: Applying the Ashford Framework to Technological Risk

The precautionary principle reflects an old adage — an ounce of prevention is worth a pound of cure. Its four central components include: taking preventative action in the face of uncertainty; shifting the burden of proof to proponents of an activity; exploring a wide range of alternatives to possibly harmful actions; and increasing public participation in decision processes. Scholars in a range of fields have identified U.S. environmental laws, regulations, and decisions exhibiting precaution de facto. This study moves beyond the traditional treatments of the subject, the morass of definitions systematizing precaution into its basic elements. It poses a further question, within the current legal system and existing laws, how might the precautionary principle be implemented by modifying aspects of a statute? By applying a conceptual legal precautionary framework to a specific example of technological risk management, Washington States energy facility siting statute, we reveal deficiencies in four areas: compensation issues; burden of proof; Type I or II error preferences; and systematic comparisons. Supplying these would, in all likelihood, ensure a more effective statute and process as well as an outcome consistent with legislative goals. However, were an explicit statement of the precautionary principle introduced, parties dissatisfied with an outcome would seek judicial review, and extensive litigation could counter the legislative mandate of abundant energy at a reasonable cost.