Assessing the Sensitivity of Climate Change Targets to Policies of Land Use, Energy Demand, Low Carbon Energy and Population Growth

A reduced scale model of the coupled carbon cycle, population dynamics, energy system and land use characteristics is used to assess the sensitivity of atmospheric carbon to a variety of policies. Policies simulated include reduction of the rate of growth of the population;reduction of the rate of conversion of forested land to cropland;reduction in per capita energy demand in developed nations;reduction in per capita energy demand in developing nations;reduction in the carbon intensity of energy production in developed nations;and reduction in the carbon intensity of energy production in developing nations. For each policy, both the time to onset of the policy and the fractional annual rate of change in the associated model variable are established. Using as a measure of sensitivity the extension in years required for atmospheric carbon to reach the policy ceiling of 1160 BMT, achieved at a policy that introduces a rate of change in each affected model variable of 0.05 per year (a 5% change per year), then the policies in decreasing order of sensitivity are: Developing nations per capita growth (17 years), Developing nations carbon intensity (17 years), Population control (11 years), Developed nations carbon intensity (2.9 years), Developed nations per capita growth (2.8 years) and Land use (1.3 years). These values are all approximately doubled when population is stabilised first. An analysis of the model results also shows a convergence of the developed and developing nations per capita carbon emissions by 2100 when a portfolio of policies is selected to prevent a doubling of the pre-industrial revolution level of atmospheric carbon at any point in the future, consistent with a principle of “contract and converge”.

Vulnerability of London’s Economy to Climate Change: Sensitivity to Production Loss

A variant of the Adaptive Regional Input-Output model (ARIO) has been developed to explore the sensitivity of the London economy to loss of production capacity in sectors affected by climate change related damage. The model is designed for linking to an Event Accounting Matrix (EAM) produced by climate and engineering teams, and then follow this damage through direct and indirect losses in the economy during a recovery process that is either demand-led (in which recovery of production capacity takes place only as demand recovers) or investment-led (where recovery of production capacity can precede demand). Outputs from the model are used to assess the relative vulnerability of London’s economy to production capacity (Capital stock) loss in each of the 42 economic sectors, for purposes of identifying where to most effectively allocate resources to climate change adaptation strategies or to recovery operations when used in conjunction with an EAM. Measures of impact related to GDP loss, recovery time and the ratio of indirect to direct losses are developed for these scenarios. Results show that indirect losses are a significant component of total losses, with a multiplier of between 1.3 and 2 depending on the scale of initial damage.

Cumulative Risk Assessment Framework for Waterborne Contaminants

A framework is developed and applied for semi-quantitative estimation of cumulative risk from complex mixtures of compounds in water supplies. The framework places these risks onto the unifying metric of Disability Adjusted Life Years (DALYs), and harmonizes cancer and non-cancer, morbidity and mortality, effects. The framework can be used to: 1) calculate a measure of cumulative risk for a given supply, and compare this measure across supplies or across the same supply with candidate treatments applied;2) identify those compounds contributing most significantly to cumulative risk, so risk management measures can be applied most effectively;and 3) quantify the influence of different regulatory limits, for specific compounds, on the cumulative risk from drinking water. Results of application to a hypothetical water supply in which all compounds are at their existing Maximum Contaminant Level (MCL) show the cumulative risk for even a complex mixture may be dominated by a few compounds. In this application, that risk was dominated by as few as 10% of the compounds. The analysis also shows that establishing MCLs based on compounds for which there is an oral slope factor, but where no cancer-based limit has yet been established, probably will have little influence on the relative cumulative risk (as measured by Total Weighted DALY) of different water supplies. This arises primarily because the non-cancer-based MCL is usually more restrictive than the one based on cancer for target probabilities of cancer equal to 1E–4 or 1E–5.

Regulatory Implications of Cumulative Risk for Perchlorate as an Iodide Uptake Inhibitor

This research applies aggregate and cumulative risk assessment considerations to intakes of compounds acting through the sodium-iodide symporter mechanism to produce iodide uptake inhibition into the thyroid. Four approaches to setting regulatory limits considered here based on NOELs/LOELs yield the following estimates of the safe levels of perchlorate in water (when perchlorate in water is the sole intake) or total goitrogens (PEC) acting through the same mechanism: 1) Approach 1: 18 μg/L;2) Approach 2: 400 μg/L (50% required inhibition) or 38 μg/L (5% required inhibition);3) Approach 3: 338 μg/L (without serum half-life correction) or 573 μg/L (with serum half-life correction);4) Approach 4: 737 μg/L (without serum half-life correction) or 973 μg/L (with serum half-life correction) for 50% required inhibition;375 μg/L (without half-life) or 735 μg/L (with half-life) for 5% required inhibition. Where water is not the sole route of exposure and perchlorate is not the sole goitrogen acting through the sodium-iodide symporter mechanism, the results of Approaches 3 and 4 can be applied to mixtures of compounds that produce these values as PECs. Results of the analysis suggest that compound-by-compound regulatory limits may be better dealt with through a change to risk-based management strategies that are built around the concept of focusing limited regulatory resources on the main contributors to risks induced by the mechanism considered here.

Collective Finance Models for Sustainable Water Projects

Waterbasin management is an exemplar problem of collective action, since many actors influence and are influenced by changes in a waterbasin. The present paper uses the example of finance of control of surface water run-off as an instance of (potential) collective action involving finance. Five innovative financing schemes for new waterbasin management infrastructures are assessed with respect to the actors who provide the finance and how the projects are governed: 1) financing through taxes;2) third-party financing;3) financing by stakeholders;4) financing through fullcost pricing;and 5) financing by developers and/or landowners.

Implications of the Reanalysis and Weight of Evidence Determination of Human Health Studies for Exposure to Perchlorates under Cumulative and Aggregate Risk Assessment

This paper applies cumulative and aggregate risk methods and weight of evidence determination to re-analysis of epidemiological and clinical studies of exposure to perchlorates. The implications of cumulative and aggregate risk are considered for 28 epidemiological studies on IUI, serum thyroid hormone levels and clinical indicators. Consideration is given to simultaneous exposures to perchlorates, nitrates, thiocyanates and organohalogens in the study populations. The elevation of effects by perchlorates alone is found only in the studies that use urinary perchlorate as the metric of exposure. These studies are beset by a problem with use of urinary perchlorate concentration in that there is large inter-subject variability in the relationship between intake and urinary concentration due to differences in metabolism and disposition of the compounds following ingestion. As a result, an individual placed into the “high urinary concentration” group may be there due to high values of exposure, to long biological clearance halflives, or due to high transfer fractions from the serum into the urine. The influence could be removed by correcting urinary levels by measured clearance half-times for individuals in a study, but that has not been done in the case of the studies examined here. It is of interest therefore that the studies that use direct measures of intake of perchlorates rather than urine concentration fail to display the hormone effects. The current study uses a “weight of evidence” approach for perchlorates, employing all 28 studies. The result is a slope of the exposure response curve (percentage change in hormone effect per unit exposure) of 0.3% per μg/kg-day, with 95% confidence interval of (?0.05%, 1%). This confidence interval for the slope encompasses 0, indicating no statistically significant slope when all data are combined in a weight of evidence determination. This is consistent with the conclusions of the USEPA and EFSA that the epidemiological studies do not provide compelling evidence for a causal association between exposures to perchlorates and either hormone effects or clinically adverse effects. The conclusions are 1) that current epidemiological results do not provide evidence of effects induced by perchlorates apart from the IUI effects, 2) that the same results provide evidence that the IUI effects induced at environmental levels of exposure are associated with down-stream adverse effects and 3) that effective risk management requires the cumulative and aggregate risk framework adopted here, suggesting a need for risk assessors to return to the original studies and provide separate estimates of exposure response relationships for all four compounds or at the least to control for exposures to nitrates, thiocyanates and organohalogens.

The Role of Advanced Biological Data in the Rationality of Risk-Based Regulatory Decisions

Advanced biological information such as computational biology, in vitro transformation assays, genome pathway analysis, genotoxicity assays, proteomics, gene expression, cell signaling disruption and hormone receptors offer the poten- tial for significant improvements in the ability of regulatory agencies to consider the risks of the thousands of compounds—and mixtures of compounds—currently unexamined. While the science for performing the assays underlying such information is developing rapidly, there is significantly less understanding of the rationality of using these data in specific decision problems. This paper explores these issues of rationality, identifying the issues of rationality that remain to be developed for applications in regulatory risk assessment, and providing a draft decision framework for these applications. The conclusion is that these rapid, high throughput methods hold the potential to significantly improve the protection of public health through better understanding of risks from compounds and mixtures, but incorporating them into existing risk assessment methodologies requires improvements in understanding the reliability and rates of Type I and Type II errors for specific applications.