Major Factors Influencing the Health Impacts from Controlling Air Pollutants with Nonlinear Chemistry: An Application to China

Predicting the human‐health effects of reducing atmospheric emissions of nitrogen oxide (NO_x) emissions from power plants, motor vehicles, and other sources is complex because of nonlinearity in the relevant atmospheric processes. We estimate the health impacts of changes in fine particulate matter (PM_2.5) and ozone concentrations that result from control of NO_x emissions alone and in conjunction with other pollutants in and outside the mega‐city of Shanghai, China. The Community Multiscale Air Quality (CMAQ) Modeling System is applied to model the effects on atmospheric concentrations of emissions from different economic sectors and geographic locations. Health impacts are quantified by combining concentration‐response functions from the epidemiological literature with pollutant concentration and population distributions. We find that the health benefits per ton of emission reduction are more sensitive to the location (i.e., inside vs. outside of Shanghai) than to the sectors that are controlled. For eastern China, we predict between 1 and 20 fewer premature deaths per year per 1,000 tons of NO_x emission reductions, valued at $300–$6,000 per ton. Health benefits are sensitive to seasonal variation in emission controls. Policies to control NO_x emissions need to consider emission location, season, and simultaneous control of other pollutants to avoid unintended consequences.     

Urban housing & energy efficiency: a pollution prevention opportunity

In 1999, the New York Power Authority (NYPA) received the annual Governor's Award for Pollution Prevention for its Energy Efficiency Refrigerator Replacement Program, conducted in cooperation with the New York City Housing Authority (NYCHA). There are over 180,000 refrigerators in operation at NYCHA residences. In this article the authors describe how NYPA offered to design, finance and implement a program to replace inefficient refrigerators with more efficient models, recouping the cost of the program through energy savings. NYPA worked in partnership with major appliance manufacturers to develop refrigerators that fit the NYCHA space requirements while providing sufficient energy savings to pay for the program. In addition, refrigerant gas, compressor oil, mercury switches, PCB- and non-PCB capacitors, and metals are all recycled at a dedicated facility under the program; the shipping containers from the new refrigerators are also recycled.Since program inception, almost 48,000 refrigerators have been replaced, weighing an estimated 8.5 million pounds. To date, the program has recycled approximately 14,000 pounds of CFC-12 gas, 215,000 pounds of aluminum, 36,000 pounds of copper, and eight million pounds of steel. From an energy efficiency standpoint, energy consumption has been reduced by 62,000 MWH, which has eliminated air emissions totaling ninety-five tons of SO2, seventy-eight tons of NOx and 52,000 tons of CO2 (using metropolitan New York generation profiles). Likewise, partnerships have been developed with the US Department of Housing and Urban Development and the U.S. Department of Energy.     

A Benefit-Cost Analysis of Retrofitting Diesel Vehicles with Particulate Filters in the Mexico City Metropolitan Area

In the Mexico City metropolitan area, poor air quality is a public health concern. Diesel vehicles contribute significantly to the emissions that are most harmful to health. Harmful diesel emissions can be reduced by retrofitting vehicles with one of several technologies, including diesel particulate filters. We quantified the social costs and benefits, including health benefits, of retrofitting diesel vehicles in Mexico City with catalyzed diesel particulate filters, actively regenerating diesel particulate filters, or diesel oxidation catalysts, either immediately or in 2010, when capital costs are expected to be lower. Retrofit with either type of diesel particulate filter or an oxidation catalyst is expected to provide net benefits to society beginning immediately and in 2010. At current prices, retrofit with an oxidation catalyst provides greatest net benefits. However, as capital costs decrease, retrofit with diesel particulate filters is expected to provide greater net benefits. In both scenarios, retrofit of older, dirtier vehicles that circulate only within the city provides greatest benefits, and retrofit with oxidation catalysts provides greater health benefits per dollar spent than retrofit with particulate filters. Uncertainty about the magnitude of net benefits of a retrofit program is significant. Results are most sensitive to values used to calculate benefits, such as the concentration-response coefficient, intake fraction (a measure of exposure), and the monetary value of health benefits.     

Reassessing the human health benefits from cleaner air

Recent proposals to further reduce permitted levels of air pollution emissions are supported by high projected values of resulting public health benefits. For example, the Environmental Protection Agency recently estimated that the 1990 Clean Air Act Amendment (CAAA) will produce human health benefits in 2020, from reduced mortality rates, valued at nearly $2 trillion per year, compared to compliance costs of $65 billion ($0.065 trillion). However, while compliance costs can be measured, health benefits are unproved: they depend on a series of uncertain assumptions. Among these are that additional life expectancy gained by a beneficiary (with median age of about 80 years) should be valued at about $80,000 per month; that there is a 100% probability that a positive, linear, no-threshold, causal relation exists between PM(2.5) concentration and mortality risk; and that progress in medicine and disease prevention will not greatly diminish this relationship. We present an alternative uncertainty analysis that assigns a positive probability of error to each assumption. This discrete uncertainty analysis suggests (with probability >90% under plausible alternative assumptions) that the costs of CAAA exceed its benefits. Thus, instead of suggesting to policymakers that CAAA benefits are almost certainly far larger than its costs, we believe that accuracy requires acknowledging that the costs purchase a relatively uncertain, possibly much smaller, benefit. The difference between these contrasting conclusions is driven by different approaches to uncertainty analysis, that is, excluding or including discrete uncertainties about the main assumptions required for nonzero health benefits to exist at all.     

Caveats for Causal Interpretations of Linear Regression Coefficients for Fine Particulate (PM2.5) Air Pollution Health Effects

Recent linear regression analyses have concluded that decreasing levels of fine particulate matter (PM2.5) air pollution have increased life expectancy in the United States. These findings have left unresolved questions about the causal relation between reductions in PM2.5 levels and changes in cause‐specific (especially, cardiovascular disease, CVD) mortality risks. Their robustness (e.g., sensitivity to deletion of a single data point) has also been questioned. We investigate these issues in the National Mortality and Morbidity Air Pollution Study database. Comparing changes in PM2.5 levels and cause‐specific mortality rates for elderly people in 24 cities between two periods separated by a decade (1987–1989 and 1999–2000) shows that reductions in PM2.5 were significantly associated with increases in respiratory mortality rates and with decreases in CVD mortality rates. CVD and all‐cause mortality risks fell equally for all months of the year over this period, but average PM2.5 levels increased significantly for winter months. This casts doubts on the causal interpretation that declines in PM2.5 over the decade caused reduced short‐term mortality risks. Nonlinear regression suggests that reduced or negative marginal health benefits are associated with reductions of PM2.5 below 1999–2000 levels (about 15 μg/m³). Such nonlinear relations imply that risk communication statements that project a constant incremental reduction in mortality risks per unit reduction in PM2.5 do not adequately reflect the realistic possibility of nonlinear exposure‐response relations and diminishing returns to further exposure reductions.     

Assessment of Interindividual and Geographic Variability in Human Exposure to Fine Particulate Matter in Environmental Tobacco Smoke

Environmental tobacco smoke (ETS) is a major contributor to indoor human exposures to fine particulate matter of 2.5 μm or smaller (PM_2.5). The Stochastic Human Exposure and Dose Simulation for Particulate Matter (SHEDS‐PM) Model developed by the U.S. Environmental Protection Agency estimates distributions of outdoor and indoor PM_2.5 exposure for a specified population based on ambient concentrations and indoor emissions sources. A critical assessment was conducted of the methodology and data used in SHEDS‐PM for estimation of indoor exposure to ETS. For the residential microenvironment, SHEDS uses a mass‐balance approach, which is comparable to best practices. The default inputs in SHEDS‐PM were reviewed and more recent and extensive data sources were identified. Sensitivity analysis was used to determine which inputs should be prioritized for updating. Data regarding the proportion of smokers and “other smokers” and cigarette emission rate were found to be important. SHEDS‐PM does not currently account for in‐vehicle ETS exposure; however, in‐vehicle ETS‐related PM_2.5 levels can exceed those in residential microenvironments by a factor of 10 or more. Therefore, a mass‐balance‐based methodology for estimating in‐vehicle ETS PM_2.5 concentration is evaluated. Recommendations are made regarding updating of input data and algorithms related to ETS exposure in the SHEDS‐PM model. Interindividual variability for ETS exposure was quantified. Geographic variability in ETS exposure was quantified based on the varying prevalence of smokers in five selected locations in the United States.     

Health Effects Caused by Primary Fine Particulate Matter (PM2.5) Emitted from Buses in the Helsinki Metropolitan Area, Finland

Fine particle (PM(2.5)) emissions from traffic have been associated with premature mortality. The current work compares PM(2.5)-induced mortality in alternative public bus transportation strategies as being considered by the Helsinki Metropolitan Area Council, Finland. The current bus fleet and transportation volume is compared to four alternative hypothetical bus fleet strategies for the year 2020: (1) the current bus fleet for 2020 traffic volume, (2) modern diesel buses without particle traps, (3) diesel buses with particle traps, and (4) buses using natural gas engines. The average population PM(2.5) exposure level attributable to the bus emissions was determined for the 1996-1997 situation using PM(2.5) exposure measurements including elemental composition from the EXPOLIS-Helsinki study and similar element-based source apportionment of ambient PM(2.5) concentrations observed in the ULTRA study. Average population exposure to particles originating from the bus traffic in the year 2020 is assumed to be proportional to the bus emissions in each strategy. Associated mortality was calculated using dose-response relationships from two large cohort studies on PM(2.5) mortality from the United States. Estimated number of deaths per year (90% confidence intervals in parenthesis) associated with primary PM(2.5) emissions from buses in Helsinki Metropolitan Area in 2020 were 18 (0-55), 9 (0-27), 4 (0-14), and 3 (0-8) for the strategies 1-4, respectively. The relative differences in the associated mortalities for the alternative strategies are substantial, but the number of deaths in the lowest alternative, the gas buses, is only marginally lower than what would be achieved by diesel engines equipped with particle trap technology. The dose-response relationship and the emission factors were identified as the main sources of uncertainty in the model.     

Data Available for Evaluating the Risks and Benefits of MTBE and Ethanol as Alternative Fuel Oxygenates

The wide-scale use of methyl tertiary butyl ether (MTBE) in gasoline has resulted in substantial public controversy and action to ban or control its use due to perceived impacts on water quality. Because oxygenates are still required under federal law, considerable research has focused on ethanol as a substitute for MTBE. In this article, we summarize the currently available literature on the air and water quality risks and benefits of MTBE versus ethanol as alternative fuel oxygenates. We find that MTBE-fuel blends are likely to have substantial air quality benefits; ethanol-fuel blends appear to offer similar benefits, but these may be at least partially negated because of ethanol's propensity to increase emissions and ambient concentrations of some air contaminants. Releases of gasoline containing either MTBE or ethanol could have an impact on some drinking water sources, although the impacts associated with MTBE tend to relate to aesthetics (i.e., taste and odor), whereas the impacts associated with ethanol generally relate to health risk (i.e., greater exposure to gasoline constituents such as benzene). It is likely that these water quality impacts will be outweighed by the air quality benefits associated with MTBE and perhaps ethanol use, which affect a much larger population. A lack of data on environmental exposures and associated health impacts hinders the completion of a comprehensive quantitative risk-benefit analysis, and the available air and water quality data should be evaluated in a broader risk-management context, which considers the potential life-cycle impacts, costs, and feasibility associated with alternative fuel oxygenates.     

Current and Future Particulate‐Matter‐Related Mortality Risks in the United States from Aviation Emissions During Landing and Takeoff

Demand for air travel is projected to increase in the upcoming years, with a corresponding influence on emissions, air quality, and public health. The trajectory of health impacts would be influenced by not just emissions growth, but also changes in nonaviation ambient concentrations that influence secondary fine particulate matter (PM_2.5) formation, population growth and aging, and potential shifts in PM_2.5 concentration‐response functions (CRFs). However, studies to date have not systematically evaluated the individual and joint contributions of these factors to health risk trajectories. In this study, we simulated emissions during landing and takeoff from aircraft at 99 airports across the United States for 2005 and for a 2025 flight activity projection scenario. We applied the Community Multiscale Air Quality (CMAQ) model with the Speciated Modeled Attainment Test (SMAT) to determine the contributions of these emissions to ambient concentrations, including scenarios with 2025 aircraft emissions and 2005 nonaviation air quality. We combined CMAQ outputs with PM_2.5 mortality CRFs and population projections, and evaluated the influence of changing emissions, nonaviation concentrations, and population factors. Given these scenarios, aviation‐related health impacts would increase by a factor of 6.1 from 2005 to 2025, with a factor of 2.1 attributable to emissions, a factor of 1.3 attributable to population factors, and a factor of 2.3 attributable to changing nonaviation concentrations which enhance secondary PM_2.5 formation. Our study emphasizes that the public health burden of aviation emissions would be significantly influenced by the joint effects of flight activity increases, nonaviation concentration changes, and population growth and aging.     

资源政策调整对减排和环境福利影响——以煤炭资源税改革为例

随着环境污染加剧,我国减排形势日益严峻,但目前资源政策设计过度关注社会经济影响,较少涉及减排和环境福利,不利于生态文明建设和社会可持续发展.本文构建动态可计算一般均衡模型(dynamic computable general equilibrium,简称动态CGE模型),以煤炭资源税改革为研究对象模拟资源政策调整的长期影响,分别采用煤炭资源税率调整和资源价值补偿政策场景,探索资源政策调整对促进减排和改善环境福利的作用.研究表明:总体而言,资源政策调整有利于促进减排和环境福利,但不同政策方案设计产生的影响差异性较大;煤炭资源税率提高会在一定程度上抑制资源消费,提高资源利用效率和人均资源盈余,降低环境损失;而资源价值补偿政策实施将对我国环境质量改善产生积极作用,可以有效提高环境福利;因此,在减排和环境福利综合视角下,煤炭资源税改革必须注重资源政策方案设计的协调性和完整性,才能有效发挥资源政策对环境系统的有效引导和激励作用.     

Retrospective Cost-Effectiveness Analyses for Polio Vaccination in the United States

The history of polio vaccination in the United States spans 50 years and includes different phases of the disease, multiple vaccines, and a sustained significant commitment of resources. We estimated cost-effectiveness ratios and assessed the net benefits of polio vaccination applicable at various points in time from the societal perspective and we discounted these back to appropriate points in time. We reconstructed vaccine price data from available sources and used these to retrospectively estimate the total costs of the U.S. historical polio vaccination strategies (all costs reported in year 2002 dollars). We estimate that the United States invested approximately US dollars 35 billion (1955 net present value, discount rate of 3%) in polio vaccines between 1955 and 2005 and will invest approximately US dollars 1.4 billion (1955 net present value, or US dollars 6.3 billion in 2006 net present value) between 2006 and 2015 assuming a policy of continued use of inactivated poliovirus vaccine (IPV) for routine vaccination. The historical and future investments translate into over 1.7 billion vaccinations that prevent approximately 1.1 million cases of paralytic polio and over 160,000 deaths (1955 net present values of approximately 480,000 cases and 73,000 deaths). Due to treatment cost savings, the investment implies net benefits of approximately US dollars 180 billion (1955 net present value), even without incorporating the intangible costs of suffering and death and of averted fear. Retrospectively, the U.S. investment in polio vaccination represents a highly valuable, cost-saving public health program. Observed changes in the cost-effectiveness ratio estimates over time suggest the need for living economic models for interventions that appropriately change with time. This article also demonstrates that estimates of cost-effectiveness ratios at any single time point may fail to adequately consider the context of the investment made to date and the importance of population and other dynamics, and shows the importance of dynamic modeling.     

Maximizing Health Benefits and Minimizing Inequality: Incorporating Local‐Scale Data in the Design and Evaluation of Air Quality Policies

The U.S. Environmental Protection Agency undertook a case study in the Detroit metropolitan area to test the viability of a new multipollutant risk‐based (MP/RB) approach to air quality management, informed by spatially resolved air quality, population, and baseline health data. The case study demonstrated that the MP/RB approach approximately doubled the human health benefits achieved by the traditional approach while increasing cost less than 20%—moving closer to the objective of Executive Order 12866 to maximize net benefits. Less well understood is how the distribution of health benefits from the MP/RB and traditional strategies affect the existing inequalities in air‐pollution‐related risks in Detroit. In this article, we identify Detroit populations that may be both most susceptible to air pollution health impacts (based on local‐scale baseline health data) and most vulnerable to air pollution (based on fine‐scale PM_2.5 air quality modeling and socioeconomic characteristics). Using these susceptible/vulnerable subpopulation profiles, we assess the relative impacts of each control strategy on risk inequality, applying the Atkinson Index (AI) to quantify health risk inequality at baseline and with either risk management approach. We find that the MP/RB approach delivers greater air quality improvements among these subpopulations while also generating substantial benefits among lower‐risk populations. Applying the AI, we confirm that the MP/RB strategy yields less PM_2.5 mortality and asthma hospitalization risk inequality than the traditional approach. We demonstrate the value of this approach to policymakers as they develop cost‐effective air quality management plans that maximize risk reduction while minimizing health inequality.     

Estimates of the Health Risk Reductions Associated with Attainment of Alternative Particulate Matter Standards in Two U.S. Cities

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.     

Exposure Misclassification and Threshold Concentrations in Time Series Analyses of Air Pollution Health Effects

Linear, no-threshold relationships are typically reported for time series studies of air pollution and mortality. Since regulatory standards and economic valuations typically assume some threshold level, we evaluated the fundamental question of the impact of exposure misclassification on the persistence of underlying personal-level thresholds when personal data are aggregated to the population level in the assessment of exposure-response relationships. As an example, we measured personal exposures to two particle metrics, PM2.5 and sulfate (SO4(2-)), for a sample of lung disease patients and compared these with exposures estimated from ambient measurements Previous work has shown that ambient:personal correlations for PM2.5 are much lower than for SO4(2-), suggesting that ambient PM2.5 measurements misclassify exposures to PM2.5. We then developed a method by which the measured:estimated exposure relationships for these patients were used to simulate personal exposures for a larger population and then to estimate individual-level mortality risks under different threshold assumptions. These individual risks were combined to obtain the population risk of death, thereby exhibiting the prominence (and the value) of the threshold in the relationship between risk and estimated exposure. Our results indicated that for poorly classified exposures (PM2.5 in this example) population-level thresholds were apparent at lower ambient concentrations than specified common personal thresholds, while for well-classified exposures (e.g., SO4(2-)), the apparent thresholds were similar to these underlying personal thresholds. These results demonstrate that surrogate metrics that are not highly correlated with personal exposures obscure the presence of thresholds in epidemiological studies of larger populations, while exposure indicators that are highly correlated with personal exposures can accurately reflect underlying personal thresholds.     

The Effects of Urban Form on Ambient Air Pollution and Public Health Risk: A Case Study in Raleigh,North Carolina

Since motor vehicles are a major air pollution source, urban designs that decrease private automobile use could improve air quality and decrease air pollution health risks. Yet, the relationships among urban form, air quality, and health are complex and not fully understood. To explore these relationships, we model the effects of three alternative development scenarios on annual average fine particulate matter (PM_2.5) concentrations in ambient air and associated health risks from PM_2.5 exposure in North Carolina's Raleigh‐Durham‐Chapel Hill area. We integrate transportation demand, land‐use regression, and health risk assessment models to predict air quality and health impacts for three development scenarios: current conditions, compact development, and sprawling development. Compact development slightly decreases (?0.2%) point estimates of regional annual average PM_2.5 concentrations, while sprawling development slightly increases (+1%) concentrations. However, point estimates of health impacts are in opposite directions: compact development increases (+39%) and sprawling development decreases (?33%) PM_2.5‐attributable mortality. Furthermore, compactness increases local variation in PM_2.5 concentrations and increases the severity of local air pollution hotspots. Hence, this research suggests that while compact development may improve air quality from a regional perspective, it may also increase the concentration of PM_2.5 in local hotspots and increase population exposure to PM_2.5. Health effects may be magnified if compact neighborhoods and PM_2.5 hotspots are spatially co‐located. We conclude that compactness alone is an insufficient means of reducing the public health impacts of transportation emissions in automobile‐dependent regions. Rather, additional measures are needed to decrease automobile dependence and the health risks of transportation emissions.     

火力发电企业离散决策及其对碳排放权价格影响

随着碳交易市场的建立,对于参与减排企业,如何制定合理的减排决策从而降低减排成本成为了一个重要问题。在有效市场下,参与减排企业的边际成本将直接影响碳排放权价格的走势。以往研究大多基于连续时间模型,运用动态优化原理解决此类问题。而事实上,企业的决策过程是离散的,这是由于碳排放权不能跨期交易,如果简单连续化会使得企业有过度减排的可能,与现实不符。基于此,本文以电力企业为例,运用动态优化方法,建立电力企业的离散减排决策模型,从而得出企业的最优边际减排成本,为政府调控碳排放权市场提供理论指导。为了验证模型,本文采用深圳碳排放权的相关实际数据进行数值模拟。研究表明,当企业做出离散减排决策时,企业的减排成本及边际减排成本与初始排放量、配额、单位惩罚成本、减排决策次数等因素相关。企业的离散决策会使得企业的边际减排成本波动加大,进而可能引起碳排放权市场的动荡,但企业的离散决策更有利于企业完成减排任务。     

两阶段供应链碳排放目标减排量分配研究

由于不同企业减排成本和减排效率有所差异,将目标减排量在供应链企业间进行合理分配是顺利完成减排目标的关键。本文研究了制造商和零售商组成的两阶段供应链的既定目标减排量分配问题,考虑企业减排对产品需求有正向影响,根据制造商分配和零售商分配两种分配方式,以及制造商领导、零售商领导和垂直纳什三种渠道权力结构,构建了六种决策模型,分析分配方式和渠道权力结构对分配决策和供应链成员以及系统利润的影响。研究表明,在三种渠道权利中：由减排对需求影响大的企业进行分配,制造商和零售商会分摊减排量,由减排对需求影响小的企业进行分配,减排量全部由对方企业承担,市场需求更大;作为领导者比作为跟随者承担更多减排量;由减排对需求影响大且减排效率低的企业分配减排量,可以实现减排量在供应链企业间分摊以及系统利润最大化,由减排对需求影响小且减排效率低或略高于对方的企业分配减排量,虽然系统利润最优,但是以单个企业承担全部减排量为代价。     

Supply vessel planning under cost,environment and robustness considerations

Offshore oil and gas installations need reliable cargo deliveries. The vessels supplying these installations on a periodic basis are expensive and constitute a source of emissions of greenhouse gases. Incorporating vessel speed optimization into the supply vessel planning process may significantly reduce fuel consumption and hence emissions. In addition, speed optimization may yield cost reductions if the number of vessels used does not increase. A main uncertainty factor, especially in the winter season, is the weather conditions which impact sailing and service times. Cost minimization and the application of speed optimization strategies may have implications on the robustness of weekly supply vessel schedules since idle times in the schedules are reduced. We develop a simulation-optimization based methodology that considers costs, emissions and robustness in the generation of weekly supply vessel schedules. Results of analyses conducted on real instances show that robustness requirements may yield both increased emissions and costs in the winter season. However, depending on instance characteristics, different degrees of robustness can be incorporated with both costs and emissions reductions through speed optimization.     

POLICIES AND IMPACT: AN ANALYSIS OF VILLAGE‐LEVEL MICROFINANCE INSTITUTIONS

This paper uses variation in policies and institutional characteristics to evaluate the impacts of village‐level microfinance institutions in rural Thailand. To identify impacts, we use policies related to the successful/unsuccessful provision of services as exogenous variation in effective financial intermediation. We find that institutions, particularly those with good policies, can promote asset growth, consumption smoothing and occupational mobility, and can decrease moneylender reliance. Specifically, cash‐lending institutions—production credit groups and especially women's groups—are successful in providing intermediation and its benefits to members, while buffalo banks and rice banks are not. The policies identified as important to intermediation and benefits: the provision of savings services, especially pledged savings accounts; emergency services; and training and advice. Surprisingly, much publicized policies such as joint liability, default consequences, or repayment frequency had no measured impacts. (JEL: 012, 016)     

An Empirical Bayes Approach to Estimating the Relation of Mortality to Exposure to Particulate Matter

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-response 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 microm (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.