Towards a circular economy: A comprehensive study of higher heat values and emission potential of various municipal solid wastes.

Maximizing resource recovery from waste streams (e.g., energy) is a critical challenge for municipalities. Utilizing the ultimate analysis and high heat value (HHV), we investigated the energy recovery and emission characteristics for 252 solid wastes of a diverse range of geographical origins classifications (e.g., 30 paper, 12 textile, 12 rubber and leather, 29 MSW mixture, 34 plastic, 61 wood, 20 sewage sludge and 53 other wastes) under the thermal waste-to-energy operation. Given the significance of wastes' HHV data, we proposed a rapid and cost-effective methodology for filling the gaps in the experimental data by prediction of the missing or uncertain wastes' HHV. We further employed wastes' nitrogen and sulphur contents to assess their atmospheric emissions. The results from this analysis show the highest energy content belonged to plastic waste, but higher levels of air pollution (mainly due to nitrogen and sulfur) could be emitted during thermal energy recovery of sewage sludge, rubber, and textile wastes. Also, we demonstrated more significant potential for recovering energy from plastic, wood, and paper wastes, while emitting less nitrogen and sulphur compounds to the atmosphere. Finally, our presented HHV models outperform concerning generalizability, validity, and accuracy when comparing the obtained results to those of previously published models. The results from this present study are particularly advantageous in designing sustainable thermal waste-to-energy systems to facilitate cities' transition into a circular economy.

Energy and material flows of megacities.

Understanding the drivers of energy and material flows of cities is important for addressing global environmental challenges. Accessing, sharing, and managing energy and material resources is particularly critical for megacities, which face enormous social stresses because of their sheer size and complexity. Here we quantify the energy and material flows through the world's 27 megacities with populations greater than 10 million people as of 2010. Collectively the resource flows through megacities are largely consistent with scaling laws established in the emerging science of cities. Correlations are established for electricity consumption, heating and industrial fuel use, ground transportation energy use, water consumption, waste generation, and steel production in terms of heating-degree-days, urban form, economic activity, and population growth. The results help identify megacities exhibiting high and low levels of consumption and those making efficient use of resources. The correlation between per capita electricity use and urbanized area per capita is shown to be a consequence of gross building floor area per capita, which is found to increase for lower-density cities. Many of the megacities are growing rapidly in population but are growing even faster in terms of gross domestic product (GDP) and energy use. In the decade from 2001-2011, electricity use and ground transportation fuel use in megacities grew at approximately half the rate of GDP growth.

The energy for growing and maintaining cities.

Herein we develop a means to differentiate between the energy required to expand and the energy required to maintain the economies of cities. A nonlinear model is tested against historical data for two cities, Hong Kong and Singapore. A robust fit is obtained for Hong Kong, with energy for maintenance close to that for growth, while Singapore, with a weaker fit, is growth dominated. The findings suggest that decreases in either of the per unit maintenance or growth demands can simultaneously cause gross domestic product (GDP) and total energy use to increase. Furthermore, increasing maintenance demands can significantly limit growth in energy demand and GDP. Thus, the low maintenance demands for Hong Kong, and especially Singapore, imply that, all other things being equal, GDP and energy use of these cities will continue to grow, though Singapore's higher energy use for growth means it will require more energy than Hong Kong.

Greenhouse gas emissions from waste management--assessment of quantification methods.

Of the many sources of urban greenhouse gas (GHG) emissions, solid waste is the only one for which management decisions are undertaken primarily by municipal governments themselves and is hence often the largest component of cities' corporate inventories. It is essential that decision-makers select an appropriate quantification methodology and have an appreciation of methodological strengths and shortcomings. This work compares four different waste emissions quantification methods, including Intergovernmental Panel on Climate Change (IPCC) 1996 guidelines, IPCC 2006 guidelines, U.S. Environmental Protection Agency (EPA) Waste Reduction Model (WARM), and the Federation of Canadian Municipalities-Partners for Climate Protection (FCM-PCP) quantification tool. Waste disposal data for the greater Toronto area (GTA) in 2005 are used for all methodologies; treatment options (including landfill, incineration, compost, and anaerobic digestion) are examined where available in methodologies. Landfill was shown to be the greatest source of GHG emissions, contributing more than three-quarters of total emissions associated with waste management. Results from the different landfill gas (LFG) quantification approaches ranged from an emissions source of 557 kt carbon dioxide equivalents (CO2e) (FCM-PCP) to a carbon sink of -53 kt CO2e (EPA WARM). Similar values were obtained between IPCC approaches. The IPCC 2006 method was found to be more appropriate for inventorying applications because it uses a waste-in-place (WIP) approach, rather than a methane commitment (MC) approach, despite perceived onerous data requirements for WIP. MC approaches were found to be useful from a planning standpoint; however, uncertainty associated with their projections of future parameter values limits their applicability for GHG inventorying. MC and WIP methods provided similar results in this case study; however, this is case specific because of similarity in assumptions of present and future landfill parameters and quantities of annual waste deposited in recent years being relatively consistent.

Interpretation of monte carlo simulations using parameter space plots.

Multimodal distribution functions that result from Monte Carlo simulations can be interpreted by superimposing joint probability density functions onto the contour space of the simulated calculations. The method is demonstrated by analysis of the pathway of a radioactive groundwater contaminant using an analytical solution to the transport equation. Simulated concentrations at a fixed time and distance produce multimodal histograms, which are understood with reference to the parameter space for the two random variables-velocity and dispersivity. Numerical integration under the joint density function up to the contour of the analytical solution gives the probability of contaminant exceeding a target concentration. This technique is potentially more efficient than Monte Carlo simulation for low probability events. Visualization of parameter space is restricted to two random variables. Nevertheless, analyzing the two most pertinent random variables in a simulation might still offer insights into the multimodal nature of output histograms.

Effects of post-exercise supplements on glycogen repletion in skeletal muscle.

Post-exercise carbohydrate supplementation has been routinely used to enhance glycogen concentrations in skeletal muscle, particularly during multiple-day athletic events. Consumption of protein hydrolysates mixed with carbohydrate supplements during the post-exercise period may increase insulin response and cause glycogen repletion in skeletal muscle. A group of Alaskan sled dogs were selected to examine post-exercise supplementation in a paired crossover study design. The dogs were subjected to the same exercise regimen and provided one of three treatments-water, glucose polymers, or glucose polymers with protein hydrolysates-over a 2-month period. Parameters tested at various post-exercise time points included plasma insulin, glucagon and glucose concentrations, and skeletal muscle glycogen content to gain a better understanding of glucose metabolism and glycogen repletion. The results showed an enhanced insulin, glucose, and glucagon response immediately after supplementation and significantly increased glycogen concentrations in skeletal muscle within 24 hours when dogs received either of the glucose-containing supplements compared with water alone. There were no differences in the plasma parameters or skeletal muscle glycogen stores in dogs provided the glucose polymers alone or the glucose polymers plus protein hydrolysates. Thus, post-exercise carbohydrate supplementation increased muscle glycogen repletion, but inclusion of protein hydrolysates in the supplements provided no additional benefits.