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Physical and Biological Release of Poly- and Perfluoroalkyl Substances (PFASs) from Municipal Solid Waste in Anaerobic Model Landfill Reactors
A wide variety of consumer products that are treated with poly- and perfluoroalkyl substances (PFASs) and related formulations are disposed in landfills. Landfill leachate has significant concentrations of PFASs and acts as secondary point sources to surface water. Here, we model how PFASs enter leachate using four lab-scale anaerobic bioreactors filled with municipal solid waste (MSW) and operated over 273 days. Duplicate reactors were monitored under live and abiotic conditions to evaluate influences attributable to biological activity. The biologically-active reactors simulated the methanogenic conditions that develop in all landfills, producing ~140 mL CH₄/dry g refuse. The average total PFAS leaching measured in live reactors (16.7 nmol/kg dry-refuse) was greater than the average for abiotic reactors (2.83 nmol/kg dry-refuse), indicating biological processes were primarily responsible for leaching. The low level leaching in the abiotic reactors was primarily due to PFCAs ≤C8 (2.48 nmol/kg dry-refuse). Concentrations of known biodegradation intermediates, including methylperfluorobutane sulfonamide acetic acid and the n:2 and n:3 fluorotelomer carboxylates, increased steadily in concentration after the onset of methanogenesis, with the 5:3 fluorotelomer carboxylate becoming the single most concentrated PFAS observed in live reactors (9.53 nmol/kg dry-refuse)
Optimization of municipal solid waste management using externality costs
Economic and environmental impacts associated with solid waste management (SWM) systems should be considered to ensure sustainability of such systems. Societal life cycle costing (S-LCC) can be used for this purpose since it includes “budget costs” and “externality costs.” While budget costs represent market goods and services in monetary terms, i.e. economic impacts, externality costs include effects outside the economic system such as environmental impacts (translated in monetary terms).1 Numerous models have been developed to determine the environmental and economic impacts associated with SWM systems (e.g., EASETECH2) by using “what-if” scenario analyses. While these models are an essential foundation that enables a systematic integrated analysis of SWM systems, they do not provide information about the overall optimal solution as done with optimization models such as SWOLF.3 This study represents the first attempt to optimize SWM systems using externality costs in SWOLF. The assessment identifies the waste strategy that minimizes externality costs and other criteria (budget costs and landfilling) for a specific case study. The latter represents a hypothetical U.S. county with annual waste generation of 320,000 Mg. The externality cost includes the damage costs of fossil CO2, CH4, N2O, PM2.5, PM10, NOX, SO2 , VOC, CO, NH3, CO, Hg, Pb, Cd, Cr (VI), Ni, As, and dioxins.
Table 1 shows the results of the optimization including: i) optimization criteria, ii) waste flows and iii) eco-efficiency indicator (ratio between externality costs and budget costs). Minimal externality costs are obtained when incinerating most of the waste (88%) and commingled collection of recyclables (12%). The eco-efficiency of this waste strategy corresponds to -0.6, i.e. its environmental benefits (negative externality costs) correspond to approximately half of its budget costs. On the other hand, there is the solution with minimal budget costs (100% of the waste is landfilled) in which the environmental load (positive externality cost) represent one third of the budget costs (positive eco-efficiency indicator). In between these options, there is a strategy with minimal landfilling in which the organic waste is sent to anaerobic digestion, the recyclables to a single stream MRF and the residual to a mixed waste MRF. Most of the externality costs of the three strategies stem from SO2, NOx and GHG as suggested by Woon & Lo.4 The case study shows that waste solutions identified by optimization modelling differ from common SWM systems selected for analysis in state-of-the-art accounting modelling
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Evaluation of Externality Costs in Life-Cycle Optimization of Municipal Solid Waste Management Systems
The
development of sustainable solid waste management (SWM) systems
requires consideration of both economic and environmental impacts.
Societal life-cycle costing (S-LCC) provides a quantitative framework
to estimate both economic and environmental impacts, by including
“budget costs” and “externality costs”.
Budget costs include market goods and services (economic impact),
whereas externality costs include effects outside the economic system
(e.g., environmental impact). This study demonstrates the applicability
of S-LCC to SWM life-cycle optimization through a case study based
on an average suburban U.S. county of 500 000 people generating
320 000 Mg of waste annually. Estimated externality costs are
based on emissions of CO<sub>2</sub>, CH<sub>4</sub>, N<sub>2</sub>O, PM<sub>2.5</sub>, PM<sub>10</sub>, NO<sub><i>x</i></sub>, SO<sub>2</sub>, VOC, CO, NH<sub>3</sub>, Hg, Pb, Cd, Cr (VI), Ni,
As, and dioxins. The results indicate that incorporating S-LCC into
optimized SWM strategy development encourages the use of a mixed waste
material recovery facility with residues going to incineration, and
separated organics to anaerobic digestion. Results are sensitive to
waste composition, energy mix and recycling rates. Most of the externality
costs stem from SO<sub>2</sub>, NO<sub><i>x</i></sub>, PM<sub>2.5</sub>, CH<sub>4</sub>, fossil CO<sub>2</sub>, and NH<sub>3</sub> emissions. S-LCC proved to be a valuable tool for policy analysis,
but additional data on key externality costs such as organic compounds
emissions to water would improve future analyses
Toward Identifying the Next Generation of Superfund and Hazardous Waste Site Contaminants
Reproduced with permission from Environmental Health Perspectives."This commentary evolved from a workshop sponsored by the National Institute of Environmental Health Sciences titled "Superfund Contaminants: The Next Generation" held in Tucson, Arizona, in August 2009. All the authors were workshop participants." doi:10.1289/ehp.1002497Our aim was to initiate a dynamic, adaptable process for identifying contaminants of emerging concern (CECs) that are likely to be found in future hazardous waste sites, and to identify the gaps in primary research that cause uncertainty in determining future hazardous waste site contaminants. Superfund-relevant CECs can be characterized by specific attributes: they are persistent, bioaccumulative, toxic, occur in large quantities, and have localized accumulation with a likelihood of exposure. Although still under development and incompletely applied, methods to quantify these attributes can assist in winnowing down the list of candidates from the universe of potential CECs. Unfortunately, significant research gaps exist in detection and quantification, environmental fate and transport, health and risk assessment, and site exploration and remediation for CECs. Addressing these gaps is prerequisite to a preventive approach to generating and managing hazardous waste sites.Support for the workshop, from which this article evolved, was provided by the National Institute of Environmental Health Sciences Superfund Research Program (P42-ES04940)
Toward Identifying the Next Generation of Superfund and Hazardous Waste Site Contaminants
Reproduced with permission from Environmental Health Perspectives."This commentary evolved from a workshop sponsored by the National Institute of Environmental Health Sciences titled "Superfund Contaminants: The Next Generation" held in Tucson, Arizona, in August 2009. All the authors were workshop participants." doi:10.1289/ehp.1002497Our aim was to initiate a dynamic, adaptable process for identifying contaminants of emerging concern (CECs) that are likely to be found in future hazardous waste sites, and to identify the gaps in primary research that cause uncertainty in determining future hazardous waste site contaminants. Superfund-relevant CECs can be characterized by specific attributes: they are persistent, bioaccumulative, toxic, occur in large quantities, and have localized accumulation with a likelihood of exposure. Although still under development and incompletely applied, methods to quantify these attributes can assist in winnowing down the list of candidates from the universe of potential CECs. Unfortunately, significant research gaps exist in detection and quantification, environmental fate and transport, health and risk assessment, and site exploration and remediation for CECs. Addressing these gaps is prerequisite to a preventive approach to generating and managing hazardous waste sites.Support for the workshop, from which this article evolved, was provided by the National Institute of Environmental Health Sciences Superfund Research Program (P42-ES04940)
Improvement in biohythane production using organic solid waste and distillery effluent
Biohythane is a two-stage anaerobic fermentation process consisting of biohydrogen production followed by biomethanation. This serves as an environment friendly and economically sustainable approach for the improved valorization of organic wastes. The characteristics of organic wastes depend on their respective sources. The choice of an appropriate combination of complementary organic wastes can vastly improve the bioenergy generation besides achieving the significant cost reduction. The present study assess the suitability and economic viability of using the groundnut deoiled cake (GDOC), mustard deoiled cake (MDOC), distillers’ dried grain with solubles (DDGS) and algal biomass (AB) as a co-substrate for the biohythane process. Results showed that maximum gaseous energy of 23.93, 16.63, 23.44 and 16.21 kcal/L were produced using GDOC, MDOC, DDGS and AB in the two stage biohythane production, respectively. Both GDOC and DDGS were found to be better co-substrates as compared to MDOC and AB. The maximum cumulative hydrogen and methane production of 150 and 64 mmol/L were achieved using GDOC. 98% reduction in substrate input cost (SIC) was achieved using the co-supplementation procedure
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