Health benefits and control costs of tightening particulate matter emissions standards for coal power plants - The case of Northeast Brazil.

Exposure to ambient particulate matter (PM) caused an estimated 4.2 million deaths worldwide in 2015. However, PM emission standards for power plants vary widely. To explore if the current levels of these standards are sufficiently stringent in a simple cost-benefit framework, we compared the health benefits (avoided monetized health costs) with the control costs of tightening PM emission standards for coal-fired power plants in Northeast (NE) Brazil, where ambient PM concentrations are below World Health Organization (WHO) guidelines. We considered three Brazilian PM10 (PMx refers to PM with a diameter under x micrometers) emission standards and a stricter U.S. EPA standard for recent power plants. Our integrated methodology simulates hourly electricity grid dispatch from utility-scale power plants, disperses the resulting PM2.5, and estimates selected human health impacts from PM2.5 exposure using the latest integrated exposure-response model. Since the emissions inventories required to model secondary PM are not available in our study area, we modeled only primary PM so our benefit estimates are conservative. We found that tightening existing PM10 emission standards yields health benefits that are over 60 times greater than emissions control costs in all the scenarios we considered. The monetary value of avoided hospital admissions alone is at least four times as large as the corresponding control costs. These results provide strong arguments for considering tightening PM emission standards for coal-fired power plants worldwide, including in regions that meet WHO guidelines and in developing countries.

Integrating toxicity reduction strategies for materials and components into product design: a case study on utility meters.

Using RIO Tronics utility meter products as an industrial case study, the numeric Fraunhofer Toxic Potential Indicator (TPI) assessment tool is used to determine high impact materials with the aim of reducing the content of inherently toxic substances in these products. However, because product redesign with alternative materials affects entire components, overall component toxicity potential must also be explored. To achieve this, material TPI scores are aggregated into component TPI scores by 2 methods: 1) the Sum-Weighted Component TPI method, which considers the mass of materials in the component to assign an overall score, and 2) the Max Component TPI method, which scores the component with the highest impact material. With consideration of uncertainties from materials' toxicity information and mass estimates, key results from both scoring methods prioritized components that contain acrylonitrile-based polymers, polyvinyl chloride (PVC), and stainless steel. Furthermore, an alternative materials assessment is carried out to identify less-toxic substitutes to meet cost and technical constraints. Substitute materials such as Al alloys for stainless steel and high-density polyethylene for PVC show promise for a combination of toxicity reduction and cost-effectiveness. The new screening methodology described can help product designers systematically benchmark toxicity potential in parallel to cost and functionality.

How much e-waste is there in US basements and attics? Results from a national survey.

The fate of used electronic products (e-waste) is of increasing concern because of their toxicity and the growing volume of e-waste. Addressing these concerns requires developing the recycling infrastructure, but good estimates of the volume of e-waste stored by US households are still unavailable. In this context, we make two contributions based on a national random survey of 2136 US households. First, we explain how much e-waste is stored by US households using count models. Significant explanatory variables include age, marital and employment status, ethnicity, household size, previous e-waste recycling behavior, and to some extent education, home ownership, and understanding the consequences of recycling, but neither income nor knowledge of e-waste recycling laws. Second, we estimate that on average, each US household has 4.1 small (

Leaching assessments of hazardous materials in cellular telephones.

Protocols for assessing the risks of discarded electronic products (e-waste) vary across jurisdictions, complicating the tasks of manufacturers and regulators. We compared the Federal Toxicity Characteristic Leaching Procedure (TCLP), California's Waste Extraction Test (WET), and the Total Threshold Limit Concentration (TTLC) on 34 phones to evaluate the consistency of hazardous waste classification. Our sample exceeded TCLP criteria only for lead (average 87.4 mg L(-1); range = 38.2-147.0 mg L(-1); regulatory limit = 5.0 mg L(-1), but failed TTLC for five metals: copper (average 203 g kg(-1); range = 186-224 g kg(-1); limit = 2.50 g kg(-1), nickel (9.25 g kg(-1); range = 6.34-11.20 g kg(-1); limit = 2.00 g kg(-1)), lead (10.14 g kg(-1); range = 8.2211.60 g kg(-1); limit = 1.00 g kg-1), antimony (1.02 g kg(-1); range = 0.86-1.29 g kg(-1); limit = 0.50 g kg(-1)), and zinc (11.01 g kg(-1); range = 8.82-12.80 g kg(-1); limit = 5.00 g kg(-1). Thresholds were not exceeded for WET. We detected several organic compounds, but at concentrations below standards. Brominated flame retardants were absent. These results improve existing environmental databases for e-waste and highlight the need to review regulatory testing for hazardous waste.

Financing electronic waste recycling Californian households' willingness to pay advanced recycling fees.

The growth of electronic waste (e-waste) is of increasing concern because of its toxic content and low recycling rates. The e-waste recycling infrastructure needs to be developed, yet little is known about people's willingness to fund its expansion. This paper examines this issue based on a 2004 mail survey of California households. Using an ordered logit model, we find that age, income, beliefs about government and business roles, proximity to existing recycling facilities, community density, education, and environmental attitudes are significant factors for explaining people's willingness to pay an advanced recycling fee (ARF) for electronics. Most respondents are willing to support a 1% ARF. Our results suggest that policymakers should target middle-aged and older adults, improve programs in communities with existing recycling centers or in rural communities, and consider public-private partnerships for e-waste recycling programs.