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A decision framework for estimating the cost of marine plastic pollution interventions.

ABSTRACT: Marine plastic pollution has emerged as one of the most pressing environmental challenges of our time. Although there has been a surge in global investment for implementing interventions to mitigate plastic pollution, there has been little attention given to the cost of these interventions. We developed a decision support framework to identify the economic, social, and ecological costs and benefits of plastic pollution interventions for different sectors and stakeholders. We calculated net cost as a function of six cost and benefit categories with the following equation: cost of implementing an intervention (direct, indirect, and nonmonetary costs) minus recovered costs and benefits (monetary and nonmonetary) produced by the interventions. We applied our framework to two quantitative case studies (a solid waste management plan and a trash interceptor) and four comparative case studies, evaluating the costs of beach cleanups and waste-to-energy plants in various contexts, to identify factors that influence the costs of plastic pollution interventions. The socioeconomic context of implementation, the spatial scale of implementation, and the time scale of evaluation all influence costs and the distribution of costs across stakeholders. Our framework provides an approach to estimate and compare the costs of a range of interventions across sociopolitical and economic contexts.

SUBMITTER: Murphy EL

PROVIDER: S-EPMC9292852 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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A decision framework for estimating the cost of marine plastic pollution interventions.

Murphy Erin L EL Bernard Miranda M Iacona Gwenllian G Borrelle Stephanie B SB Barnes Megan M McGivern Alexis A Emmanuel Jorge J Gerber Leah R LR

Conservation biology. 20210901 2

Marine plastic pollution has emerged as one of the most pressing environmental challenges of our time. Although there has been a surge in global investment for implementing interventions to mitigate plastic pollution, there has been little attention given to the cost of these interventions. We developed a decision support framework to identify the economic, social, and ecological costs and benefits of plastic pollution interventions for different sectors and stakeholders. We calculated net cost ...[more]

PMID: 34467557

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Project description:BackgroundAustralian governments are increasingly mandating the use of cost-benefit analysis (CBA) to inform the efficient allocation of government resources. CBA is likely to be useful when evaluating preventive health interventions that are often cross-sectoral in nature and require Cabinet approval prior to implementation. This study outlines a CBA framework for the evaluation of preventive health interventions that balances the need for consistency with other agency guidelines whilst adhering to guidelines and conventions for health economic evaluations.MethodsWe analysed CBA and other evaluation guidance documents published by Australian federal and New South Wales (NSW) government departments. Data extraction compared the recommendations made by different agencies and the impact on the analysis of preventive health interventions. The framework specifies a reference case and sensitivity analyses based on the following considerations: (1) applied economic evaluation theory; (2) consistency between CBA across different government departments; (3) the ease of moving from a CBA to a more conventional cost-effectiveness/cost-utility analysis framework often used for health interventions; (4) the practicalities of application; and (5) the needs of end users being both Cabinet decision-makers and health policy-makers.ResultsNine documents provided CBA or relevant economic evaluation guidance. There were differences in terminology and areas of agreement and disagreement between the guidelines. Disagreement between guidelines involved (1) the community included in the societal perspective; (2) the number of options that should be appraised in ex ante analyses; (3) the appropriate time horizon for interventions with longer economic lives; (4) the theoretical basis and value of the discount rate; (5) parameter values for variables such as the value of a statistical life; and (6) the summary measure for decision-making.ConclusionsThis paper addresses some of the methodological challenges that have hindered the use of CBA in prevention by outlining a framework that is consistent with treasury department guidelines whilst considering the unique features of prevention policies. The effective use and implementation of a preventive health CBA framework is likely to require considerable investment of time and resources from state and federal government departments of health and treasury but has the potential to improve decision-making related to preventive health policies and programmes.

Project description:Waste collection services are uncommon in rural areas of low-resource countries, causing waste accumulation and subsequent dumping and burning of garbage. Air pollution from household garbage burning, including plastics, has been observed in Jalapa, Guatemala in addition to household air pollution (HAP) from cooking. Adolescent girls often help with these cooking and household tasks, but little is known about their exposures. We characterized 24-h exposures to HAP and household garbage burning in adolescent girls by measuring fine particulate matter (PM2.5), black carbon (BC), urinary biomarkers of polycyclic aromatic hydrocarbons (PAHs), bisphenol A (BPA), and phthalates. We recruited 60 girls between 13 and 17 years of age who helped with cooking activities and lived with participants of the Household Air Pollution Intervention Network (HAPIN) trial. We recruited n = 30 girls each from the control (wood-burning stove) and intervention (liquefied petroleum gas stove) arms. We also measured real-time kitchen concentrations of BC in 20 homes (33%). PM2.5 and BC were measured in n = 21 control and n = 20 intervention participants. Median concentrations of personal PM2.5 and BC and kitchen BC were lower (p < 0.05) in the intervention arm by 87%, 80%, and 85%, respectively. PAH metabolite concentrations were lower (p < 0.001) for all nine metabolites in intervention (n = 26) compared to control participants (n = 29). Urinary BPA concentrations were 66% higher in participants who reported using cosmetics (p = 0.02), and phthalate concentrations were 63% higher in participants who had reported using hair products during the sample period (p = 0.05). Our results suggest that gas stoves can reduce HAP exposures among adolescents who are not primary cooks at home. Biomarkers of plastic exposure were not associated with intervention status, but some were elevated compared to age- and sex-matched participants of the National Health and Nutrition Examination Survey (NHANES).

Project description:Best management practices (BMPs) for agricultural diffuse pollution control are implemented at the field or small-watershed scale. However, the benefits of BMP implementation on receiving water quality at multiple spatial is an ongoing challenge. In this paper, we introduce an integrated approach that combines risk assessment (i.e., Phosphorus (P) index), model simulation techniques (Hydrological Simulation Program-FORTRAN), and a BMP placement tool at various scales to identify the optimal location for implementing multiple BMPs and estimate BMP effectiveness after implementation. A statistically significant decrease in nutrient discharge from watersheds is proposed to evaluate the effectiveness of BMPs, strategically targeted within watersheds. Specifically, we estimate two types of cost-effectiveness curves (total pollution reduction and proportion of watersheds improved) for four allocation approaches. Selection of a ''best approach" depends on the relative importance of the two types of effectiveness, which involves a value judgment based on the random/aggregated degree of BMP distribution among and within sub-watersheds. A statistical optimization framework is developed and evaluated in Chaohe River Watershed located in the northern mountain area of Beijing. Results show that BMP implementation significantly (p >0.001) decrease P loss from the watershed. Remedial strategies where BMPs were targeted to areas of high risk of P loss, deceased P loads compared with strategies where BMPs were randomly located across watersheds. Sensitivity analysis indicated that aggregated BMP placement in particular watershed is the most cost-effective scenario to decrease P loss. The optimization approach outlined in this paper is a spatially hierarchical method for targeting nonpoint source controls across a range of scales from field to farm, to watersheds, to regions. Further, model estimates showed targeting at multiple scales is necessary to optimize program efficiency. The integrated model approach described that selects and places BMPs at varying levels of implementation, provides a new theoretical basis and technical guidance for diffuse pollution management in agricultural watersheds.

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A decision framework for estimating the cost of marine plastic pollution interventions.

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A decision framework for estimating the cost of marine plastic pollution interventions.

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