Spatial-temporal characteristics, source-specific variation and uncertainty analysis of health risks associated with heavy metals in road dust in Beijing, China.

Based on the concentrations of ten heavy metals (As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Zn, Fe) in 144 road dust samples collected from 36 sites across 4 seasons from 2016 to 2017 in Beijing, this study systematically analyzed the levels and main sources of health risks in terms of their temporal and spatial variations. A combination of receptor models (positive matrix factorization and multilinear engine-2), human health risk assessment models, and Monte Carlo simulations were used to apportion the seasonal variation of the health risks associated with these heavy metals. While non-carcinogenic risks were generally acceptable, Cr and Ni induced cautionary carcinogenic risks (CR) to children (confidence levels was approximately 80% and 95%, respectively).. Additionally, fuel combustion posed cautionary CR to children in all seasons, while the level of CR from other sources varied, depending on the seasons. Heavy metal concentrations were the most influential variables for uncertainties, followed by ingestion rate and skin adherence factor. The values and spatial patterns of health risks were influenced by the spatial pattern of risks from each source.

The Next Generation of Risk Assessment Multi-Year Study-Highlights of Findings, Applications to Risk Assessment, and Future Directions.

BACKGROUND: The Next Generation (NexGen) of Risk Assessment effort is a multi-year collaboration among several organizations evaluating new, potentially more efficient molecular, computational, and systems biology approaches to risk assessment. This article summarizes our findings, suggests applications to risk assessment, and identifies strategic research directions. OBJECTIVE: Our specific objectives were to test whether advanced biological data and methods could better inform our understanding of public health risks posed by environmental exposures. METHODS: New data and methods were applied and evaluated for use in hazard identification and dose-response assessment. Biomarkers of exposure and effect, and risk characterization were also examined. Consideration was given to various decision contexts with increasing regulatory and public health impacts. Data types included transcriptomics, genomics, and proteomics. Methods included molecular epidemiology and clinical studies, bioinformatic knowledge mining, pathway and network analyses, short-duration in vivo and in vitro bioassays, and quantitative structure activity relationship modeling. DISCUSSION: NexGen has advanced our ability to apply new science by more rapidly identifying chemicals and exposures of potential concern, helping characterize mechanisms of action that influence conclusions about causality, exposure-response relationships, susceptibility and cumulative risk, and by elucidating new biomarkers of exposure and effects. Additionally, NexGen has fostered extensive discussion among risk scientists and managers and improved confidence in interpreting and applying new data streams. CONCLUSIONS: While considerable uncertainties remain, thoughtful application of new knowledge to risk assessment appears reasonable for augmenting major scope assessments, forming the basis for or augmenting limited scope assessments, and for prioritization and screening of very data limited chemicals. Citation: Cote I, Andersen ME, Ankley GT, Barone S, Birnbaum LS, Boekelheide K, Bois FY, Burgoon LD, Chiu WA, Crawford-Brown D, Crofton KM, DeVito M, Devlin RB, Edwards SW, Guyton KZ, Hattis D, Judson RS, Knight D, Krewski D, Lambert J, Maull EA, Mendrick D, Paoli GM, Patel CJ, Perkins EJ, Poje G, Portier CJ, Rusyn I, Schulte PA, Simeonov A, Smith MT, Thayer KA, Thomas RS, Thomas R, Tice RR, Vandenberg JJ, Villeneuve DL, Wesselkamper S, Whelan M, Whittaker C, White R, Xia M, Yauk C, Zeise L, Zhao J, DeWoskin RS. 2016. The Next Generation of Risk Assessment multiyear study-highlights of findings, applications to risk assessment, and future directions. Environ Health Perspect 124:1671-1682; http://dx.doi.org/10.1289/EHP233.

Application of Probabilistic Risk Assessment in Establishing Perchlorate and Goitrogen Risk Mitigation Strategies.

This paper applies probabilistic risk assessment in quantifying risks from cumulative and aggregate risk pathways for selected goitrogens in water and food. Results show that the percentages of individuals with a Hazard Index (HI) value above 1 ranges between 30% and 50% both with and without serum half-life correction when a traditional regulatory assessment approach based on establishment of a No Observed Effects Level (NOEL) is used. When an exposure-response curve is instead used and a threshold of 50% inhibition is assumed, 1.1% or less of the population exceeds an HI value of 1 with no serum half-life correction, rising to as high as 11% when serum half-life correction is applied. If 0% to 5% threshold for iodide uptake inhibition is assumed for production of adverse effects, the percentage of the population with an HI above 1 is 46.2% or less with no serum half-life correction, and 47.2% or less when serum half-life correction is applied. The probabilistic analysis shows that while there are exposed groups for whom perchlorate exposures are the primary cause of individuals having HI values above 1, these constitute significantly less than 1% of the population. Instead, the potential risk from exposure to goitrogens is dominated by nitrates without serum half-life correction and thiocyanates with serum half-life correction, suggesting public health protection is better accomplished by a focus on these and other goitrogens expect in highly limited cases where waterborne perchlorate is at unusually high concentrations.

Reduced carbon emission estimates from fossil fuel combustion and cement production in China.

Nearly three-quarters of the growth in global carbon emissions from the burning of fossil fuels and cement production between 2010 and 2012 occurred in China. Yet estimates of Chinese emissions remain subject to large uncertainty; inventories of China's total fossil fuel carbon emissions in 2008 differ by 0.3 gigatonnes of carbon, or 15 per cent. The primary sources of this uncertainty are conflicting estimates of energy consumption and emission factors, the latter being uncertain because of very few actual measurements representative of the mix of Chinese fuels. Here we re-evaluate China's carbon emissions using updated and harmonized energy consumption and clinker production data and two new and comprehensive sets of measured emission factors for Chinese coal. We find that total energy consumption in China was 10 per cent higher in 2000-2012 than the value reported by China's national statistics, that emission factors for Chinese coal are on average 40 per cent lower than the default values recommended by the Intergovernmental Panel on Climate Change, and that emissions from China's cement production are 45 per cent less than recent estimates. Altogether, our revised estimate of China's CO2 emissions from fossil fuel combustion and cement production is 2.49 gigatonnes of carbon (2 standard deviations = ±7.3 per cent) in 2013, which is 14 per cent lower than the emissions reported by other prominent inventories. Over the full period 2000 to 2013, our revised estimates are 2.9 gigatonnes of carbon less than previous estimates of China's cumulative carbon emissions. Our findings suggest that overestimation of China's emissions in 2000-2013 may be larger than China's estimated total forest sink in 1990-2007 (2.66 gigatonnes of carbon) or China's land carbon sink in 2000-2009 (2.6 gigatonnes of carbon).

The influence of spatial resolution on human health risk co-benefit estimates for global climate policy assessments.

Assessment of the ability of climate policies to produce desired improvements in public health through co-benefits of air pollution reduction can consume resources in both time and research funds. These resources increase significantly as the spatial resolution of models increases. In addition, the level of spatial detail available in macroeconomic models at the heart of climate policy assessments is much lower than that available in traditional human health risk modeling. It is therefore important to determine whether increasing spatial resolution considerably affects risk-based decisions; which kinds of decisions might be affected; and under what conditions they will be affected. Human health risk co-benefits from carbon emissions reductions that bring about concurrent reductions in Particulate Matter (PM10) emissions is therefore examined here at four levels of spatial resolution (Uniform Nation, Uniform Region, Uniform County/city, Health Risk Assessment) in a case study of Taiwan as one of the geographic regions of a global macroeceonomic model, with results that are representative of small, industrialized nations within that global model. A metric of human health risk mortality (YOLL, years of life lost in life expectancy) is compared under assessments ranging from a "uniform simulation" in which there is no spatial resolution of changes in ambient air concentration under a policy to a "highly spatially resolved simulation" (called here Health Risk Assessment). PM10 is chosen in this study as the indicator of air pollution for which risks are assessed due to its significance as a co-benefit of carbon emissions reductions within climate mitigation policy. For the policy examined, the four estimates of mortality in the entirety of Taiwan are 747 YOLL, 834 YOLL, 984 YOLL and 916 YOLL, under Uniform Taiwan, Uniform Region, Uniform County and Health Risk Assessment respectively; or differences of 18%, 9%, 7% if the HRA methodology is taken as the baseline. While these differences are small compared to uncertainties in health risk assessment more generally, the ranks of different regions and of emissions categories as the focus of regulatory efforts estimated at these four levels of spatial resolution are quite different. The results suggest that issues of risk equity within a nation might be missed by the lower levels of spatial resolution, suggesting that low resolution models are suited to calculating national cost-benefit ratios but not as suited to assessing co-benefits of climate policies reflecting intersubject variability in risk, or in identifying sub-national regions and emissions sectors on which to focus attention (although even here, the errors introduced by low spatial resolution are generally less than 40%).

Decoupling analysis and socioeconomic drivers of environmental pressure in China.

China's unprecedented change offers a unique opportunity for uncovering relationships between economic growth and environmental pressure. Here we show the trajectories of China's environmental pressure and reveal underlying socioeconomic drivers during 1992-2010. Mining and manufacturing industries are the main contributors to increasing environmental pressure from the producer perspective. Changes in urban household consumption, fixed capital formation, and exports are the main drivers from the consumer perspective. While absolute decoupling is not realized, China has in general achieved relative decoupling between economic growth and environmental pressure. China's decoupling performance has four distinguishable periods, closely aligning with nation-wide major policy adjustments, which indicates significant impact of China's national socioeconomic policies on its environmental pressure. Material intensity change is the main contributor to the mitigation of environmental pressure, except for ammonia nitrogen, solid wastes, aquatic Cu, and aquatic Zn. Production structure change is the largest contributor to mitigate ammonia nitrogen emissions, and final demand structure change is the largest contributor to mitigate emissions of solid wastes, aquatic Cu, and aquatic Zn. We observe materialization trends for China's production structure and final demand structure during 2002-2007. Environmental sustainability can only be achieved by timely technology innovation and changes of production structure and consumption pattern.

Climate change air toxic co-reduction in the context of macroeconomic modelling.

This paper examines the health implications of global PM reduction accompanying greenhouse gas emissions reductions in the 180 national economies of the global macroeconomy. A human health effects module based on empirical data on GHG emissions, PM emissions, background PM concentrations, source apportionment and human health risk coefficients is used to estimate reductions in morbidity and mortality from PM exposures globally as co-reduction of GHG reductions. These results are compared against the "fuzzy bright line" that often underlies regulatory decisions for environmental toxics, and demonstrate that the risk reduction through PM reduction would usually be considered justified in traditional risk-based decisions for environmental toxics. It is shown that this risk reduction can be on the order of more than 4 × 10(-3) excess lifetime mortality risk, with global annual cost savings of slightly more than $10B, when uniform GHG reduction measures across all sectors of the economy form the basis for climate policy ($2.2B if only Annex I nations reduce). Consideration of co-reduction of PM-10 within a climate policy framework harmonized with other environmental policies can therefore be an effective driver of climate policy. An error analysis comparing results of the current model against those of significantly more spatially resolved models at city and national scales indicates errors caused by the low spatial resolution of the global model used here may be on the order of a factor of 2.

Modeling imbalanced economic recovery following a natural disaster using input-output analysis.

Input-output analysis is frequently used in studies of large-scale weather-related (e.g., Hurricanes and flooding) disruption of a regional economy. The economy after a sudden catastrophe shows a multitude of imbalances with respect to demand and production and may take months or years to recover. However, there is no consensus about how the economy recovers. This article presents a theoretical route map for imbalanced economic recovery called dynamic inequalities. Subsequently, it is applied to a hypothetical postdisaster economic scenario of flooding in London around the year 2020 to assess the influence of future shocks to a regional economy and suggest adaptation measures. Economic projections are produced by a macro econometric model and used as baseline conditions. The results suggest that London's economy would recover over approximately 70 months by applying a proportional rationing scheme under the assumption of initial 50% labor loss (with full recovery in six months), 40% initial loss to service sectors, and 10-30% initial loss to other sectors. The results also suggest that imbalance will be the norm during the postdisaster period of economic recovery even though balance may occur temporarily. Model sensitivity analysis suggests that a proportional rationing scheme may be an effective strategy to apply during postdisaster economic reconstruction, and that policies in transportation recovery and in health care are essential for effective postdisaster economic recovery.

Mapping flows of embodied emissions in the global production system.

Environmentally extended multiregional input-output (MRIO) analysis can be used to investigate final production and consumption attributions of emissions. As the distinction between the two attributions has been brought to the attention of policy-makers, there is an ever greater need to understand how and why they differ, by analyzing the connections between production and consumption activities. Seeking to meet this need, we present an approach for mapping flows of embodied emissions through a Leontief production system. The approach, seen as an extension of Structural Path Analysis (SPA), provides an exhaustive map of supply chain linkages between final production and consumption attributions of emissions. Whereas SPA is traditionally used to extract and rank individual supply chains according to the emissions occurring at the end of each chain, the mapping approach considers emissions embodied in the flows of intermediate products linking different economic sectors along supply chains. Illustrative results are presented from a global MRIO model and CO(2) emissions for 2004. The emissions embodied in a sector's total output of products is also of interest: a method for calculating this is presented and shown to provide further insight into where in the production system a sector's overall emissions impact is concentrated.

Assessing the co-benefits of greenhouse gas reduction: health benefits of particulate matter related inspection and maintenance programs in Bangkok, Thailand.

Since the 1990s, the capital city of Thailand, Bangkok has been suffering from severe ambient particulate matter (PM) pollution mainly attributable to its wide use of diesel-fueled vehicles and motorcycles with poor emission performance. While the Thai government strives to reduce emissions from transportation through enforcing policy measures, the link between specific control policies and associated health impacts is inadequately studied. This link is especially important in exploring the co-benefits of greenhouse gas emissions reductions, which often brings reduction in other pollutants such as PM. This paper quantifies the health benefits potentially achieved by the new PM-related I/M programs targeting all diesel vehicles and motorcycles in the Bangkok Metropolitan Area (BMA). The benefits are estimated by using a framework that integrates policy scenario development, exposure assessment, exposure-response assessment and economic valuation. The results indicate that the total health damage due to the year 2000 PM emissions from vehicles in the BMA was equivalent to 2.4% of Thailand's GDP. Under the business-as-usual (BAU) scenario, total vehicular PM emissions in the BMA will increase considerably over time due to the rapid growth in vehicle population, even if the fleet average emission rates are projected to decrease over time as the result of participation of Thailand in post-Copenhagen climate change strategies. By 2015, the total health damage is estimated to increase by 2.5 times relative to the year 2000. However, control policies targeting PM emissions from automobiles, such as the PM-oriented I/M programs, could yield substantial health benefits relative to the BAU scenario, and serve as co-benefits of greenhouse gas control strategies. Despite uncertainty associated with the key assumptions used to estimate benefits, we find that with a high level confidence, the I/M programs will produce health benefits whose economic impacts considerably outweigh the expenditures on policy implementation.

The built environment and health: impacts of pedestrian-friendly designs on air pollution exposure.

In the wake of the growing popularity of pedestrian-oriented community designs, it is timely to assess potential risk trade-offs of such urban planning strategies. Pedestrian-friendly designs are currently being called for and implemented in the US to tackle in particular problems associated with insufficient physical activity in the population. Unintended consequences may emerge, however, especially due to potential increases in the inhalation of pollutants as the population walking or cycling in polluted environments increases. A risk assessment of such built environment transformations was undertaken to evaluate quantitatively the competing risks and benefits of community design changes in active travel. A simulation model, built incorporating research from the fields of transportation, environmental sciences and exposure analysis, is applied to a case study area that undergoes hypothetical urban transformations. We find that the simulated population experiences roughly the same number of days in a year with decreases as number of days with increases in energy expenditure or inhalation of pollutants. In the 5% of days with greatest shifts, PM(10) inhalation was shown to increase by 175% or more, while the 5% of days of greatest decreases exhibited reductions of 45% or more (with similar results for ozone). Of particular concern, some individuals are shown to double their intake of the pollutants on high pollution days. However, uncertainty in the estimates is high. In particular, interpretations are very different according to the approach used to characterize year-long activity patterns. This innovative risk assessment uncovers critical gaps in the literature that must be further researched to allow essential comprehensive analyses of planning decisions.

Effect of particulate matter air pollution on hospital admissions and medical visits for lung and heart disease in two southeast Idaho cities.

Few, if any, published time series studies have evaluated the effects of particulate matter air exposures by combining hospital admissions with medical visit data for smaller populations. We investigated the relationship between daily particulate matter (<10 microm in aerometric diameter or PM10) exposures with admissions and medical visits (emergency room, urgent care, and family practice) for respiratory and cardiovascular disease in Pocatello and Chubbuck, Idaho (population about 60,000), from November 1994 through March 2000. Within generalized linear models, time, weather, influenza, and day-of-week effects were controlled. In single-pollutant models, respiratory disease admissions and visits increased (7.1-15.4% per 50 microg/m3 PM10) for each age group analyzed, with the highest increases in two groups, children and especially the elderly. Statistical analyses suggest that the results probably did not occur by chance. Sensitivity analyses did not provide strong evidence that the respiratory disease effect estimates were sensitive to reasonable changes in the final degrees of freedom choice for time and weather effects. No strong evidence of confounding by NO2 and SO2 was found from results of multi-pollutant models. Ozone and carbon monoxide data were not available to include multi-pollutant models, but evidence suggests that they were not a problem. Unexpectedly, evidence of an association between PM10 with cardiovascular disease was not found, possibly due to the lifestyles of the mostly Mormon study population. Successful time series analyses can be performed on smaller populations if diverse, centralized databases are available. Hospitals that offer urgent or other primary care services may be a rich source of data for researchers. Using data that potentially represented a wide-range of disease severity, the findings provide evidence that evaluating only hospital admissions or emergency room visit effects may underestimate the overall morbidity due to acute particulate matter exposures. Further work is planned to test this conclusion.

Measuring site-level success in brownfield redevelopments: a focus on sustainability and green building.

This research has met the following four objectives within the broader research topic of characterizing and quantifying success in brownfield revitalization: (1) to define 40 total indicators that define and determine the success of brownfield redevelopments in four categories: environment-health, finance, livability, and social-economic; (2) to use these indicators to develop a partially automated tool that stakeholders in brownfield redevelopment may use to more easily assess and communicate success (or failures) in these projects; (3) to integrate "green" building as an important aspect of successful brownfield redevelopments; and (4) to develop this tool within the framework of a specific multi-attribute decision method (MADM), the analytical hierarchical process (AHP). Future research should include the operationalization and application of this tool to specific sites. Currently, no such indicator framework or automated tool is known to exist or be in use. Indicators were chosen because of their ability to reduce data into comprehensible measurements and to systematically measure success in a standardized fashion. Appropriate indicators were selected based on (1) interviews with prominent private developers and national leaders in brownfield redevelopment, (2) a review of the relevant literature, (3) objective hierarchies created in this project, and (4) the ability for each indicator to serve goals in more than one of the four categories described above. These were combined to form the Sustainable Brownfields Redevelopment (SBR) Tool. A survey was conducted to serve as a preliminary assessment and proposed methodology for judging the validity of the SBR Tool. Professionals in the academic, private, and public sector were asked to provide an evaluation of the management tool and a weighting of the relative importance of each indicator and each of the four categories listed previously. Experts rated the tool at 7.68 out of 10 suggesting that this framework will be useful in evaluating these redevelopments upon completion and in formulating initial site plans and building design.

Inorganic arsenic in drinking water and bladder cancer: a meta-analysis for dose-response assessment.

Most arsenic cancer risk assessments have been based solely on epidemiological studies to characterize the dose-response relationship for arsenic-associated cancer and to perform risk calculations. However, current epidemiological evidence is too inconsistent and fraught with uncertainty regarding arsenic exposure to provide reliable estimates. This makes it hard to draw a firm conclusion about the shape and slope of the dose-response relationship from individual studies. Meta-analysis is a statistical approach to combining results across studies and offers expanded opportunities for obtaining an improved dose-response relationship. In this study, a meta-analysis of arsenic studies was conducted by combining seven epidemiological studies from different regions to get an overall dose-response relationship between the amount of arsenic intake and the excess probability of bladder cancer. Both the fixed-effect and random-effect models were used to calculate the averaged coefficient of the linear-logistic regression model. A homogeneity test was also conducted. The final product of this research is an aggregated dose-response model in the range of empirical observation of arsenic. Considering the most recent arsenic MCL (maximum contaminant level, i.e. 10microg/L), the associated bladder cancer risk (lifetime excess probability) at this MCL is 2.29 x 10-5.

A framework for the integration of ecosystem and human health in public policy: two case studies with infectious agents.

Despite that a significant body of published literature exists in the complex area of interconnection among the environment, ecosystems, and human activity, relatively little attention has been paid to the integration and analysis of ecological and human health data in the form of a conceptual model. Human and ecological health protection generally have been treated as separate domains of policy, with significant differences in both the analytic methods used to characterize risks and the policies developed for risk reduction. Understanding the relationships among population growth, development, natural resource use, the environment, human health, and ecosystems is an important area of both scientific inquiry and environmental policy. The present paper focuses on the development of a conceptual model for understanding disease causation, particularly infectious disease, and the implications of such a model for public policy. The conceptual model incorporates ecological and human health risk assessment information applied to case studies of two infectious diseases. This article takes an initial step toward formalizing the conceptual model so that research and assessment procedures can be developed.

Environmental risk, precaution, and scientific rationality in the context of WTO/NAFTA trade rules.

This article considers the role of scientific rationality in understanding statements of risk produced by a scientific community. An argument is advanced that, while scientific rationality does impose constraints on valid scientific justifications for restrictions on products and practices, it also provides flexibility in the judgments needed to both develop and apply characterizations of risk. The implications of this flexibility for the understanding of risk estimates in WTO and NAFTA deliberations are explored, with the goal of finding an intermediate ground between the view that science unambiguously justifies or rejects a policy, and the view that science is yet another cultural tool that can be manipulated in support of any decision. The result is a proposal for a dialogical view of scientific rationality in which risk estimates are depicted as confidence distributions that follow from a structured dialogue of scientific panels focused on judgments of evidence, evidential reasoning, and epistemic analysis.

Nonlinear dose-response relationships and inducible cellular defence mechanisms.

With the inclusion of inducible radioprotective mechanisms in a radiobiological state-vector model it was possible to explain plateaus in dose-response relationships for neoplastic transformation produced by in vitro irradiation of different cell lines with low-LET irradiation at high dose rates. The current study repeated the simulation of one data set that contains a plateau at mid doses. In contrast to earlier studies, the new one did not model the repair of double-strand breaks (DSBs) located in bulk DNA (likely via non-homologous end joining) as being inducible. Repair of specific DSBs located in actively transcribed genes was assumed to occur via homologous recombination and was considered to be inducible. This reduced the number of parameters that have to be determined by fitting the model to data. In addition, all types of radical scavengers were formerly considered to be inducible by radiation. This was redefined in the current work and the effectiveness of scavengers was implemented in a refined way. The current work investigated whether these and other model adjustments lead to an improved fit of the data set.