Replacing Recycling Rates with Life-Cycle Metrics as Government Materials Management Targets

In Florida, the passing of the Energy, Climate Change, and Economic Security Act of 2008 established a statewide mass-based municipal solid waste recycling rate goal of 75% by 2020. In this study, we describe an alternative approach to tracking performance of materials management systems that incorporates life-cycle thinking. Using both greenhouse gas (GHG) emissions and energy use as life-cycle indicators, we create two different materials management baselines based on a hypothetical 75% recycling rate in Florida in 2008. GHG emission and energy use footprints resulting from various 2020 materials management strategies are compared to these baselines, with the results normalized to the same mass-based 75% recycling rate. For most scenarios, LCI-normalized recycling rates are greater than mass-based recycling rates. Materials management strategies that include recycling of curbside-collected materials such as metal, paper, and plastic result in the largest GHG- and energy-normalized recycling rates. Waste prevention or increase, determined as the net difference in per-person mass discard rate for individual materials, is a major contributor to the life-cycle-normalized recycling rates. The methodology outlined here provides policy makers with one means of transitioning to life-cycle thinking in state and local waste management goal setting and planning

Translating landfill methane generation parameters among first-order decay models

<p>Landfill gas (LFG) generation is predicted by a first-order decay (FOD) equation that incorporates two parameters: a methane generation potential (<i>L</i>₀) and a methane generation rate (k). Because non-hazardous waste landfills may accept many types of waste streams, multiphase models have been developed in an attempt to more accurately predict methane generation from heterogeneous waste streams. The ability of a single-phase FOD model to predict methane generation using weighted-average methane generation parameters and tonnages translated from multiphase models was assessed in two exercises. In the first exercise, waste composition from four Danish landfills represented by low-biodegradable waste streams was modeled in the Afvalzorg Multiphase Model and methane generation was compared to the single-phase Intergovernmental Panel on Climate Change (IPCC) Waste Model and LandGEM. In the second exercise, waste composition represented by IPCC waste components was modeled in the multiphase IPCC and compared to single-phase LandGEM and Australia’s Solid Waste Calculator (SWC). In both cases, weight-averaging of methane generation parameters from waste composition data in single-phase models was effective in predicting cumulative methane generation from -7% to +6% of the multiphase models. The results underscore the understanding that multiphase models will not necessarily improve LFG generation prediction because the uncertainty of the method rests largely within the input parameters. A unique method of calculating the methane generation rate constant by mass of anaerobically degradable carbon was presented (k_c) and compared to existing methods, providing a better fit in 3 of 8 scenarios. Generally, single phase models with weighted-average inputs can accurately predict methane generation from multiple waste streams with varied characteristics; weighted averages should therefore be used instead of regional default values when comparing models.</p> <p><i>Implications</i>: Translating multiphase first-order decay model input parameters by weighted average shows that single-phase models can predict cumulative methane generation within the level of uncertainty of many of the input parameters as defined by the Intergovernmental Panel on Climate Change (IPCC), which indicates that decreasing the uncertainty of the input parameters will make the model more accurate rather than adding multiple phases or input parameters.</p

Chemical Characterization of High-Temperature Arc Gasification Slag with a Focus on Element Release in the Environment

High-temperature arc gasification (HTAG) has been proposed as a viable technology for the generation of energy and the production of saleable byproducts from municipal solid waste (MSW). Total concentrations of elements in HTAG slag were assessed and indicated a high partitioning of trace elements (Pb, Cd, and As) into the flue gas, an issue of concern when assessing the air pollution control residues (APCR) status as a hazardous waste. Hazardous waste leaching tests [such as the toxicity characteristic leaching procedure (TCLP)] were performed and confirmed that the slag did not meet U.S. criteria for a hazardous waste. Leaching was assessed using batch and column tests; the results revealed that Sb and Al were elevated in respect to risk-based regulatory thresholds. Slag samples were carbonated to simulate weathering effects, and although leachable concentrations of Al did decrease by an order of magnitude, Sb concentrations were found to increase. Low total concentrations of certain trace elements (As, Cd, and Pb), with respect to MSW incineration bottom ashes support the potential for reuse of HTAG slag; however, leaching of elements (Pb, Al, and Sb) in batch and column tests indicate that proper engineering controls would need to be taken to ensure protection of water supplies in a reuse application

Life-Cycle Inventory and Impact Evaluation of Mining Municipal Solid Waste Landfills

Recent research and policy directives have emerged with a focus on sustainable management of waste materials, and the mining of old landfills represents an opportunity to meet sustainability goals by reducing the release of liquid- and gas-phase contaminants into the environment, recovering land for more productive use, and recovering energy from the landfilled materials. The emissions associated with the landfill mining process (waste excavation, screening, and on-site transportation) were inventoried on the basis of diesel fuel consumption data from two full-scale mining projects (1.3–1.5 L/in-place m³ of landfill space mined) and unit emissions (mass per liter of diesel consumption) from heavy equipment typically deployed for mining landfills. An analytical framework was developed and used in an assessment of the life-cycle environmental impacts of a few end-use management options for materials deposited and mined from an unlined landfill. The results showed that substantial greenhouse gas emission reductions can be realized in both the waste relocation and materials and energy recovery scenarios compared to a “do nothing” case. The recovery of metal components from landfilled waste was found to have the greatest benefit across nearly all impact categories evaluated, while emissions associated with heavy equipment to mine the waste itself were found to be negligible compared to the benefits that mining provided

Expanding Per- and Polyfluoroalkyl Substances Coverage in Nontargeted Analysis Using Data-Independent Analysis and IonDecon

Per- and polyfluoroalkyl substances (PFAS) are widespread, persistent environmental contaminants that have been linked to various health issues. Comprehensive PFAS analysis often relies on ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC HRMS) and molecular fragmentation (MS/MS). However, the selection and fragmentation of ions for MS/MS analysis using data-dependent analysis results in only the topmost abundant ions being selected. To overcome these limitations, All Ions fragmentation (AIF) can be used alongside data-dependent analysis. In AIF, ions across the entire m/z range are simultaneously fragmented; hence, precursor–fragment relationships are lost, leading to a high false positive rate. We introduce IonDecon, which filters All Ions data to only those fragments correlating with precursor ions. This software can be used to deconvolute any All Ions files and generates an open source DDA formatted file, which can be used in any downstream nontargeted analysis workflow. In a neat solution, annotation of PFAS standards using IonDecon and All Ions had the exact same false positive rate as when using DDA; this suggests accurate annotation using All Ions and IonDecon. Furthermore, deconvoluted All Ions spectra retained the most abundant peaks also observed in DDA, while filtering out much of the artifact peaks. In complex samples, incorporating AIF and IonDecon into workflows can enhance the MS/MS coverage of PFAS (more than tripling the number of annotations in domestic sewage). Deconvolution in complex samples of All Ions data using IonDecon did retain some false fragments (fragments not observed when using ion selection, which were not isotopes or multimers), and therefore DDA and intelligent acquisition methods should still be acquired when possible alongside All Ions to decrease the false positive rate. Increased coverage of PFAS can inform on the development of regulations to address the entire PFAS problem, including both legacy and newly discovered PFAS