Fiscal spending and the environment: Theory and empirics

During economic crises, governments often increase fiscal spending to stimulate the economy. While the fiscal spending surge may be temporary, spending composition is often altered in favor of expenditures on social programs and other public goods which may persist over time. We model and measure the impact of fiscal spending patterns on the environment. The model predicts that a reallocation of government spending composition towards social and public goods reduces pollution. However, increasing total government spending without altering its composition does not reduce pollution. We empirically test these predictions for air and water pollutants showing that they are fully supported.     

The effects of adaptation measures on hurricane induced property losses: Which FEMA investments have the highest returns?

This paper evaluates the relative effectiveness of FEMA expenditures on hurricane induced property losses. We find that spending on FEMA ex-ante mitigation and planning projects leads to greater reductions in property losses than spending on ex-post adaptation programs – specifically, a one percent increase in annual spending on ex-ante risk reduction and warning projects reduces damages by 0.21 percent while a one percent increase in ex-post recovery and clean-up spending reduces damages by 0.12. Although both types of program spending are effective, we find the marginal return from spending on programs that target long-term mitigation and risk management to be almost twice that of spending on ex-post recovery programs. With the predicted increases in the frequency and severity of North Atlantic hurricanes in the future, our findings suggest there are important potential gains that could be realized from the further diversification of FEMA spending across project categories.     

Evaluation of the validity of the US EPA's cancer risk assessment of arsenic for low-level exposures: a likelihood ratio approach

Skin cancers associated with ingesting of arsenic have been documented since the 19th century. A study in the southwestern coastal area of Taiwan where people drank well water containing arsenic is generally recognised as providing the best data available for quantifying the risk, and the US Environmental Protection Agency (EPA) used these data to conduct a risk assessment of arsenic ingestion. However, the lowest exposure category in the Taiwan study included arsenic levels up to 290 µg L^–1, which is nearly six times higher than the current EPA maximum contaminant level (MCL), 50 µg L^–1. Therefore, the EPA risk assessment model extrapolated data on high-level exposures to generate risk estimates for low-level exposures. To evaluate the validity of this model, we conducted a quantitative review of epidemiological studies observing arsenic exposures below 290 µg L^–1. A ratio of the likelihood of the EPA model being inappropriate to that of it being appropriate was calculated for each study population as a measurement of the validity of the EPA model. Although existing human data on low-level exposures are limited, the review suggested that the EPA model is unlikely to be able to predict the risk of skin cancer accurately when the arsenic exposure level is between 170 and 270 µg L^–1.     

Avian Conservation under the Endangered Species Act: Expenditures versus Recovery Priorities

Abstract: Budget constraints require the U.S. Fish and Wildlife Service to prioritize species for recovery spending. Each listed species is ranked according to the degree of threat it faces, its recovery potential, and its taxonomic distinctness. We analyzed state and federal government expenditures for recovery of threatened and endangered birds ( n = 85 species) from 1992 to 1995 to determine if the priority system was being followed. Although recovery spending correlated with priority rank, priority rank explained <5% of the variation in spending. A small number of the same moderately ranked species dominated expenditures each year (41–79% of total annual budgets). Species with wide distributions, high recovery potential, and captive breeding programs received the most funding, and more funding than their priority ranks dictated. Island species received significantly less funding than expected based on priority rank. Twelve species, 10 of which resided on islands, received <$5000 at least once from 1992 to 1995. Recovery spending was unrelated to degree of threat, taxonomic distinctness, and migratory status. There also was no relationship between land-purchase expenditures and priority ranks. To improve the relationship between recovery spending on threatened and endangered birds and their priority rank, significant changes need to be made within the private sector ( less litigation and special-interest lobbying  ), U.S. Congress (increased budget and reduced earmarking  ), and the U.S. Fish and Wildlife Service (restructuring of regional offices and increased accountability).     

A Comparison of Global Conservation Prioritization Models with Spatial Spending Patterns of Conservation Nongovernmental Organizations

Abstract: In recent decades, various conservation organizations have developed models to prioritize locations for conservation. Through a survey of the spending patterns of 281 conservation nongovernmental organizations (NGOs), we examined the relation between 2 such models and spatial patterns of spending by conservation NGOs in 44 countries in sub‐Saharan Africa. We tested whether, at the country level, the proportion of a country designated as a conservation priority was correlated with where NGOs spent money. For one model (the combination of Conservation International's hotspots and High Biodiversity Wilderness Areas, which are areas of high endemism with high or low levels of vegetation loss respectively), there was no relation between the proportion of a country designated as a priority and levels of NGO spending, including by the NGO associated with the model. In the second model (Global 200), the proportion of a country designated as a priority and the amount of money spent by NGOs were significantly and positively related. Less money was spent in countries in northern and western sub‐Saharan Africa than countries in southern and eastern Africa, relative to the proportion of the country designated as a conservation priority. We suggest that on the basis of our results some NGOs consider increasing their spending on the areas designated as of conservation priority which are currently relatively underfunded, although there are economic, political, cultural, historical, biological, and practical reasons why current spending patterns may not align with priority sites.     

When is a Life Too Costly to Save? The Evidence from U.S. Environmental Regulations

Under certain environmental statutes the EPA is required to balance costs and benefits in setting standards, whereas under others this is prohibited. This paper examines EPA regulatory decisions made under three statues, two of which require balancing and one of which does not. Using discrete choice models, we find that costs and benefits are significant explanatory variables for all three sets of decisions. This suggests that balancing occurred in each case; however, the value (implicit in these decisions) of avoiding a cancer case varies widely. We also find that a 1987 court ruling effectively curtailed whatever balancing occurred under the statute that prohibited it.     

Leaching characteristics of bisphenol A from epoxy-resin pavement materials

We investigated the leaching characteristics of bisphenol A (BPA) from two kinds of epoxy-resin pavement materials, one containing epoxy resins (EPs) and the other containing epoxy-acrylate resins (EPAs). Both samples contained residual BPA monomer, at levels of 9.0?µg?g^?1 for the EP resin sample and 4.4?µg?g^?1 for the EPA resin sample. These amounts were larger than amounts previously measured for polycarbonate samples. The amount of BPA leached from the samples increased with temperature. The leaching of BPA from EP was more strongly affected by temperature than the leaching from EPA. The pH also affected the amount of leached BPA. The maximum leached amount was observed under alkaline conditions (pH 10.8) for both sample types. The amounts of BPA that might leach from pavement materials during 1?h of heavy rain were estimated to be 0.9?µg?m^?2 for EP and 3.5?µg?m^?2 for EPA. Our results indicate that EPs disposed of in waste landfills without any treatment may be a source of BPA in leachate at landfill sites.     

太湖流域3种氯酚类化合物水质基准的探讨

按照美国地面水水质基准制定的程序和规范,筛选了太湖流域广泛存在的水生生物物种并收集了相应的基础毒性数据,探讨了五氯酚(PCP)、2,4-二氯酚(2,4-DCP)和2,4,6-三氯酚(2,4,6-TCP)在我国太湖地区的水生态基准的定值.同时采用蒙特卡罗构建物种敏感度分布(SSD)曲线和生态毒理模型方法预测了3种氯酚类化合物对太湖水生生物的急性基准浓度(CMC)和慢性基准浓度(CCC).结果表明,基于EPA规范方法和急慢性毒性比率得到的PCP、2,4-DCP和2,4,6-TCP3种氯酚类化合物的CMC值分别为25、908和594μg·L-1,CCC值分别为12、176和162μg·L-1;基于SSD曲线得到的CMC值分别为25、818和648μg·L-1,CCC值分别为6、75和198μg·L-1;基于生态毒理模型得到的CCC值分别为4、15和67μg·L-1,显示出3种方法得到的氯酚类化合物的CMC或CCC在同一个数量级上,但在数值上由生态毒理模型得出的CCC要小于其它两种方法,并且除PCP的急慢性基准值与美国EPA推出的水生态基准值相近外,其它两种氯酚类化合物的急慢性基准值均低于美国EPA推出的急慢性基准值.研究结果希望能为我国水质基准的制定提供一些有用的线索.     

The economics of enforcing air pollution controls

The goal of this paper is to determine the likely effect on a firm's control actions of alternative implementation and enforcement policies available to the control agency. Three alternatives are studied, legal enforcement through the new source performance standards set forth by EPA, and two effluent fee enforcement alternatives. First, a generalized model of the effects of implementation and enforcement policies on the firm's control action is developed. This model assumes that the firm is an expected cost minimizer. The model is then applied to the case of particulate matter discharges from coal-fired power plants in order to estimate empirically the effect of policy alternatives on the firm's control efforts. Finally, the results of the model and its empirical application are used to develop policy functions which relate control to the values of various policy parameters. These results lead us to several policy recommendations.     

Gaps and Mismatches between Global Conservation Priorities and Spending

Abstract:  Several international conservation organizations have recently produced global priority maps to guide conservation activities and spending in their own and other conservation organizations. Surprisingly, it is not possible to directly evaluate the relationship between priorities and spending within a given organization because none of the organizations with global priority models tracks how they spend their money relative to their priorities. We were able, however, to evaluate the spending patterns of five other large biodiversity conservation organizations without their own published global priority models and investigate the potential influence of priority models on this spending. On average, countries with priority areas received greater conservation investment; global prioritization systems, however, explained between only 2 and 32% of the US$1.5 billion spent in 2002, depending on whether the United States was removed from analyses and whether conservation spending was adjusted by the per capita gross domestic product within each country. We also found little overlap in the spending patterns of the five conservation organizations evaluated, suggesting that informal coordination or segregation of effort may be occurring. Our results also highlight a number of potential gaps and mismatches in how limited conservation funds are spent and provide the first audit of global conservation spending patterns. More explicit presentation of conservation priorities by organizations currently without priority models and better tracking of spending by those with published priorities are clearly needed to help make future conservation activities as efficient as possible.     

Dynamics of insect resistance in Bt-corn

The development of genetically modified Bt-corn, incorporating various toxin genes from Bacillus thuringiensis that act as a chemical defense against insect pests, such as the European Corn Borer, provides farmers with a new pest management option. However, the emergence of insect resistance is a threat to the continued use of Bt-corn. The United States Environment Protection Agency (US EPA) has developed planting strategies, for preventing insect resistance by planting a mixture of Bt- and non-Bt-corn. Decisions about the exact proportion of Bt- and non-Bt-corn are based on complex spatially explicit mathematical models using detailed biological assumptions about the population genetics and life history of the European Corn Borer. We develop an alternative simpler model for the spread of resistance based on the logistic growth model, which we believe has utility in situations where it is impossible or impractical to estimate the different life history and genetics parameters required by more detailed models. We use our model to investigate the US EPA’s planting rules for Bt-corn and find that short-term economic behavior is likely to lead to these rules not being followed. Our results add weight to existing work on this problem. We also investigate the economics of planting Bt-corn in markets where consumers do and do not differentiate between the modes of production for the corn. We find that Bt-corn appears to be economic in markets that do not differentiate and uneconomic in markets where consumers do differentiate.     

Enforcement of pollution regulations in a declining industry

A regulatory agency enforcing compliance in a declining industry might recognize that certain plants would close rather than comply, imposing large costs on the local community. Data on EPA enforcement activity in the U.S. steel industry are examined for evidence of this with a two-equation model linking EPA enforcement decisions and firms' plant-closing decisions. The results indicate that the EPA directed fewer enforcement actions toward plants with a high predicted probability of closing and plants that were major employers in their community; also, plants predicted to face relatively heavy enforcement were more likely to close.     

On Valuing Information in Adaptive‐Management Models

Abstract: Active adaptive management looks at the benefit of using strategies that may be suboptimal in the near term but may provide additional information that will facilitate better management in the future. In many adaptive‐management problems that have been studied, the optimal active and passive policies (accounting for learning when designing policies and designing policy on the basis of current best information, respectively) are very similar. This seems paradoxical; when faced with uncertainty about the best course of action, managers should spend very little effort on actively designing programs to learn about the system they are managing. We considered two possible reasons why active and passive adaptive solutions are often similar. First, the benefits of learning are often confined to the particular case study in the modeled scenario, whereas in reality information gained from local studies is often applied more broadly. Second, management objectives that incorporate the variance of an estimate may place greater emphasis on learning than more commonly used objectives that aim to maximize an expected value. We explored these issues in a case study of Merri Creek, Melbourne, Australia, in which the aim was to choose between two options for revegetation. We explicitly incorporated monitoring costs in the model. The value of the terminal rewards and the choice of objective both influenced the difference between active and passive adaptive solutions. Explicitly considering the cost of monitoring provided a different perspective on how the terminal reward and management objective affected learning. The states for which it was optimal to monitor did not always coincide with the states in which active and passive adaptive management differed. Our results emphasize that spending resources on monitoring is only optimal when the expected benefits of the options being considered are similar and when the pay‐off for learning about their benefits is large.     

A flexible spatio-temporal model for air pollution with spatial and spatio-temporal covariates

The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system covariates. The model presented in this paper has been implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of \(\text {NO}_{x}\) in the Los Angeles area during a 10 year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated \(R^2\) of approximately \(0.7\) at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy.     

Risk assessment for ingested inorganic arsenic: A review and status report

Arsenic presents several unique problems in risk assessment. First, there is no good animal model for arsenic as a carcinogen, although in humans arsenic exposure through inhalation is judged to cause lung cancer and ingested inorganic arsenic is judged to cause skin cancer. Second, detoxification of arsenic through methylation is believed to be important, but the mechanisms and the quantitative relationships are not yet understood.EPA provided a risk assessment for ingested inorganic arsenic in its 1984 Health Assessment Document and a revised version in 1988. In both cases EPA calculated a cancer potency or slope factor using epidemiological data from Taiwan. EPA's standard or default risk assessment procedure is to use the linear coefficient from the multistage model in order to calculate cancer risk. This procedure was challenged by the EPA Science Advisory Board (SAB) in a report to the Administrator in September of 1989. The SAB recommended that EPA (1) develop a revised risk assessment based on estimates of the delivered dose of non-detoxified arsenic to target tissues, and (2) consider the potential reduction in cancer risk due to detoxification in establishing an MCL for arsenic.This paper will draw upon the author's experience with the SAB to summarise major issues in arsenic risk assessment and to examine how these issues might be resolved through further research.     

Geography of conservation spending,biodiversity, and culture

We used linear and multivariate models to examine the associations between geography, biodiversity, per capita economic output, national spending on conservation, governance, and cultural traits in 55 countries. Cultural traits and social metrics of modernization correlated positively with national spending on conservation. The global distribution of this spending culture was poorly aligned with the distribution of biodiversity. Specifically, biodiversity was greater in the tropics where cultures tended to spend relatively less on conservation and tended to have higher collectivism, formalized and hierarchical leadership, and weaker governance. Consequently, nations lacking social traits frequently associated with modernization, environmentalism, and conservation spending have the largest component of Earth's biodiversity. This has significant implications for setting policies and priorities for resource management given that biological diversity is rapidly disappearing and cultural traits change slowly. Therefore, we suggest natural resource management adapt to and use characteristics of existing social organization rather than wait for or promote social values associated with conservation spending. Supporting biocultural traditions, engaging leaders to increase conservation commitments, cross‐national efforts that complement attributes of cultures, and avoiding interference with nature may work best to conserve nature in collective and hierarchical societies. Spending in modernized nations may be a symbolic response to a symptom of economic development and environmental degradation, and here conservation actions need to ensure that biodiversity is not being lost.     

Chronic parasitic infection alters reproductive output in deer mice

Parasitized animals may alter their life histories to minimize the costs of parasitism. Organisms are predicted to decrease investment in current reproduction when parasitism has the greatest impact on current reproductive ability. In contrast, if parasitism decreases residual reproductive value, hosts should increase current reproductive investment, referred to as fecundity compensation or terminal investment. In mammalian hosts, parasitic infection most often leads to reductions in current host reproduction, perhaps attributable to the emphasis on parasites that are unlikely to impact the host’s residual reproductive value. In this study, the life history response of a rodent, Peromyscus maniculatus, to infection with a parasite that should strongly impact the residual reproductive value of its host (Schistosomatium douthitti, Trematoda) was examined. Infection decreased survival for hosts exposed to a high dose of parasites and was chronic in survivors, confirming that infection had strong impacts for the residual reproductive value of the host. As predicted, infected mice increased their reproductive output, producing litters of greater mass due to heavier offspring. However, this increased output was observed after a greater delay to begin breeding in infected mice and was not observed in animals that suffered early mortality. The deer mouse S. douthitti system may provide a rare example of fecundity compensation in mammals.     

Current uses of the EPA lead model to assess health risk and action levels for soil

The EPA lead model predicts mean blood lead levels and risk of elevated blood lead levels in children based on lead uptake from multiple sources. In the latest model versions, environmental data from individual homes within a community can be used to predict the overall blood lead distribution and percent risk of exceeding a specific blood lead level (i.e. 10 g dl^–1). Recent criteria used by the EPA to evaluate this information include no more than 5% of houses with a greater than 5% lead risk, and a community weighted-average risk below 5%. Environmental (primarily soil) and blood lead data from a residential community near a smelter were used to illustrate recent uses of the model. Scheduled remediation in the community will remove soil for approximately 60% of the houses (i.e. those with lead levels > 1000 mg kg^–1). After remediation, the model results indicate a relatively low community risk (0.5–1.9%), although the percentage of houses with lead risks above 5% ranged from 3 to as high as 13%, depending on the variation in blood lead and assuming the model's 7 g dl^–1 increase in blood lead with each 1000 mg kg^–1 increase in soil lead level. A comparison of the limited blood lead data with soil lead levels below 1000 mg kg^–1, however, indicated no apparent relationship. Given these uncertainties, less invasive actions than additional soil removal (e.g. exposure intervention, monitoring conditions, and follow-up as necessary) may be appropriate under the new EPA guidance for lead in soil.     

Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.     

Projecting biodiversity benefits of conservation behavior-change programs

Biodiversity loss is driven by human behavior, but there is uncertainty about the effectiveness of behavior-change programs in delivering benefits to biodiversity. To demonstrate their value, the biodiversity benefits and cost-effectiveness of behavior changes that directly or indirectly affect biodiversity need to be quantified. We adapted a structured decision-making prioritization tool to determine the potential biodiversity benefits of behavior changes. As a case study, we examined two hypothetical behavior-change programs––wildlife gardening and cat containment––by asking experts to consider the behaviors associated with these programs that directly and indirectly affect biodiversity. We assessed benefits to southern brown bandicoot (Isoodon obesulus) and superb fairy-wren (Malurus cyaneus) by eliciting from experts estimates of the probability of each species persisting in the landscape given a range of behavior-change scenarios in which uptake of the behaviors varied. We then compared these estimates to a business-as-usual scenario to determine the relative biodiversity benefit and cost-effectiveness of each scenario. Experts projected that the behavior-change programs would benefit biodiversity and that benefits would rise with increasing uptake of the target behaviors. Biodiversity benefits were also predicted to accrue through indirect behaviors, although experts disagreed about the magnitude of additional benefit provided. Scenarios that combined the two behavior-change programs were estimated to provide the greatest benefits to species and be most cost-effective. Our method could be used in other contexts and potentially at different scales and advances the use of prioritization tools to guide conservation behavior-change programs.