Climate change is likely to have profound economic consequences for Egypt. This study evaluates the potential economic impacts resulting from changes in water supplies, agricul- ture, air quality, heat stress, and tourism. Other sensitive sectors, including water pollution, energy consumption, and biodiversity, were not assessed. Sea level rise threatens agricultural land and property in the Nile Delta. Higher temperatures can reduce agricultural production, a situation that can be made worse with lower water supplies. As a result, unemployment and food prices may increase, risking increased malnutrition. Human health in Cairo could be adversely affected by increased particulate matter and heat stress, potentially leading to thousands of deaths valued at tens of billions of Egyptian pounds per year. Annual tourist revenues are estimated to decrease as well. Total economic losses for the sectors mentioned above are estimated to reach ~200 to 350 billion Egyptian pounds (EGP; US $36�64 billion), which is equivalent to 2�6% of future gross domestic product.

This paper applies city-specific mortality relationships for extremely hot and cold temperatures for 33 Metropolitan Statistical Areas in the United States to develop mortality projections for historical and potential future climates. These projections, which cover roughly 100 million of 310 million U.S. residents in 2010, highlight a potential change in health risks from uncontrolled climate change and the potential benefits of a greenhouse gas (GHG) mitigation policy. Our analysis reveals that projected mortality from extremely hot and cold days combined increases significantly over the 21st century because of the overwhelming increase in extremely hot days. We also find that the evaluated GHG mitigation policy could substantially reduce this risk. These results become more pronounced when accounting for projected population changes. These results challenge arguments that there could be a mortality benefit attributable to changes in extreme temperatures from future warming. This finding of a net increase in mortality also holds in an analog city sensitivity analysis that incorporates a strong adaptation assumption. While our results do not address all sources of uncertainty, their scale and scope highlight one component of the potential health risks of unmitigated climate change impacts on extreme temperatures and draw attention to the need to continue to refine analytical tools and methods for this type of analysis.

The relative contributions of PM2.5 and ozone precursor emissions to air pollution-related premature mortality modulated by climate change are estimated for the U.S. using sensitivities of air pollutants to precursor emissions and health outcomes for 2001 and 2050. Result suggests that states with high emission rates and significant premature mortality increases induced by PM2.5 will substantially benefit in the future from SO2, anthropogenic NOX and NH3 emissions reductions while states with premature mortality increases induced by O3 will benefit mainly from anthropogenic NOX emissions reduction. Much of the increase in premature mortality expected from climate change-induced pollutant increases can be offset by targeting a specific precursor emission in most states based on the modeling approach followed here.

The potential health impact of ambient ozone and PM2.5 concentrations modulated by climate change over the United States is investigated using combined atmospheric and health modeling. Regional air quality modeling for 2001 and 2050 was conducted using CMAQ Modeling System with meteorology from the GISS Global Climate Model, downscaled regionally using MM5,keeping boundary conditions of air pollutants, emission sources, population, activity levels, and pollution controls constant. BenMap was employed to estimate the air pollution health outcomes at the county, state, and national level for 2050 caused by the effect of meteorology on future ozone and PM2.5 concentrations. The changes in calculated annual mean PM2.5 concentrations show a relatively modest change with positive and negative responses (increasing PM2.5 levels across the northeastern U.S.) although average ozone levels slightly decrease across the northern sections of the U.S., and increase across the southern tier. Results suggest that climate change driven air quality-related health effects will be adversely affected in more then 2/3 of the continental U.S. Changes in health effects induced by PM2.5 dominate compared to those caused by ozone. PM2.5-induced premature mortality is about 15 times higher then that due to ozone. Nationally the analysis suggests approximately 4000 additional annual premature deaths due to climate change impacts on PM2.5 vs 300 due to climate change-induced ozone changes. However, the impacts vary spatially. Increased premature mortality due to elevated ozone concentrations will be offset by lower mortality from reductions in PM2.5 in 11 states. Uncertainties related to different emissions projections used to simulate future climate, and the uncertainties forecasting the meteorology, are large although there are potentially important unaddressed uncertainties (e.g., downscaling, speciation, interaction, exposure, and concentration-response function of the human health studies).

As part of its periodic re-evaluation of particulate matter (PM) standards, the U.S. Environmental Protection Agency estimated the health risk reductions associated with attainment of alternative PM standards in two locations in the United States with relatively complete air quality data: Philadelphia and Los Angeles. PM standards at the time of the analysis were defined for particles of aerodynamic diameter less than or equal to 10 microm, denoted as PM-10. The risk analyses estimated the risk reductions that would be associated with changing from attainment of the PM-10 standards then in place to attainment of alternative standards using an indicator measuring fine particles, defined as those particles of aerodynamic diameter less than or equal to 2.5 microm and denoted as PM-2.5. Annual average PM-2.5 standards of 12.5, 15, and 20 microg/m3 were considered in various combinations with daily PM-2.5 standards of 50 and 65 microg/m3. Attainment of a standard or set of standards was simulated by a proportional rollback of "as is" daily PM concentrations to daily PM concentrations that would just meet the standard(s). The predicted reductions in the incidence of health effects varied from zero, for those alternative standards already being met, to substantial reductions of over 88% of all PM-associated incidence (e.g., in mortality associated with long-term exposures in Los Angeles, under attainment of an annual standard of 12.5 microg/m3). Sensitivity analyses and integrated uncertainty analyses assessed the multiple-source uncertainty surrounding estimates of risk reduction.

As part of its assessment of the health risks associated with exposure to particulate matter (PM), the U.S. Environmental Protection Agency analyzed the risks associated with current levels, and the risk reductions that might be achieved by attainment of alternative PM standards, in two locations in the United States, Philadelphia, and Los Angeles. The concentration – response function describing the relation between a health endpoint and ambient PM concentrations is an important component, and a source of substantial uncertainty, in such risk analyses. In the absence of location‐specific estimates, the concentration –r esponse functions necessary for risk assessments in Philadelphia and Los Angeles must be inferred from the available information in other locations. Although the functional form of the concentration – response relations is assumed to be the same everywhere, the value of the PM coefficient in that function may vary from one location to another. Under this model, a distribution describes the probability that the PM coefficient in a randomly selected location will lie in any range of interest. An empirical Bayes estimation technique was used to improve the estimation of location‐specific concentration – response functions relating mortality to short‐term exposure to particles of aerodynamic diameter less than or equal to 2.5 μm (PM‐2.5), for which functions have previously been estimated in several locations. The empirical Bayes‐adjusted parameter values and their SEs were used to derive an estimate of the distribution of PM‐2.5 coefficients for mortality associated with short‐term exposures. From this distribution, distributions of relative risks corresponding to different specified changes in PM‐2.5 concentrations could be derived.

This paper compares, via simulation, the performance of the multinomial logit and hedonic models in estimating consumer preferences for product attributes. We ascribe preferences over the attributes of houses to a population of consumers, and, by having them bid for a set of houses calculate equilibrium prices. The resulting data are used to estimate the two models.We find that the gradient of a linear Box-Cox hedonic price function estimates marginal attribute bids at least as well as a linear logit model, although the difference between the two is small when some variables are not observed or are replaced by proxies. The logit model, however, outperforms the hedonic model in valuing non-marginal attribute changes. This is true when the researcher knows the true form of consumers' utility functions and when the utility function must be approximated.