Surveying the applicability of energy recovery technologies for waste treatment: Case study for anaerobic wastewater treatment in Minnesota.

Waste treatment is an important part of the future global energy portfolio. Challenges associated with implementing energy recovery technology at waste treatment sites include interwoven technical, economic, and policy considerations. This work focuses on the tradeoff of input waste energy content to output electrical power, i.e. efficiency for waste-to-energy systems. Also presented is an approach for conversion technology selection based on characteristics of the waste stream, energy content of biogas generated from anaerobic waste treatment, and commercial applicability of five major prime movers across a large gradient of power output including: gas turbines, steam turbines, microturbines, reciprocating internal combustion engines, and solid oxide fuel cells. An efficiency model developed from fundamental thermodynamic principles is used to estimate the amount of power available from a waste treatment site, using data from a comprehensive data set of prime mover characteristics. A case study is presented, illustrating prime mover selection for three types of waste systems in Minnesota, United States: wastewater treatment plants, landfill sites and dairy farms. The results show that gas and steam turbines are recommended for large-scale systems with millions of gallons per day of wastewater generation, up to 60% of waste treatment sites. For small-scale systems applicable to distributed waste treatment and wastewater treatment facilities processing less than 10,000 gallons of water per day, fuel cells are recommended solely based on their high efficiency. Given the potential growth of decentralized waste-to-energy, the scarcity of highly efficient, affordable and fuel flexible power generation options necessitates further innovation in small-scale prime mover technologies.Implications: Energy recovery from waste has not reached its potential due to several decision-influencing factors and technical challenges. Here an efficiency model is presented that theoretically validates efficiency curves for prime movers often shown in previous literature, but without physical verification. The developed regime model has significant practical utility as it concisely estimates power generation potential of a given waste treatment site. This work decouples decision factors by providing a practical template to better identify applicability of a prime mover to waste processing scenarios. In addition, the applicability analysis highlights areas in need of innovation, technology, and policy to address the changing landscape of waste treatment scale and potential opportunity to recover energy from small-scale distributed treatment facilities.

Dicarboxylic Acid Emissions from Aftertreatment Equipped Diesel Engines.

Dicarboxylic acids play a key role in atmospheric particle nucleation. Though long assumed to originate from primary sources, little experimental evidence exists directly linking combustion to their emissions. In this work, we sought definitive proof that dicarboxylic acids are produced in diesel engines and that they can slip through a modern aftertreatment system (ATS) at low exhaust temperatures. One difficulty in measuring dicarboxylic acid emissions is that they cannot be identified using conventional mass spectroscopy techniques. In this work, we refined a derivatization gas chromatography-mass spectroscopy technique to measure 11 mono- and dicarboxylic acids from plain and KOH impregnated quartz filters. Filters were loaded with exhaust from a modern passenger car diesel engine on a dynamometer sampled before and after an ATS consisting of an oxidation catalyst and diesel particulate filter. Our findings confirm that dicarboxylic acids are produced in diesel engine combustion, especially during low temperature combustion modes that emit significant concentrations of partially combusted hydrocarbons. Exhaust acids were largely removed by a fully warmed-up ATS, mitigating their environmental impact. Our results also suggest that dicarboxylic acids do not participate in primary particle formation in dilute engine exhaust as low quantities were collected on unimpregnated filters.

Markov chain solution of photon multiple scattering through turbid slabs.

This work introduces a Markov Chain solution to model photon multiple scattering through turbid slabs via anisotropic scattering process, i.e., Mie scattering. Results show that the proposed Markov Chain model agree with commonly used Monte Carlo simulation for various mediums such as medium with non-uniform phase functions and absorbing medium. The proposed Markov Chain solution method successfully converts the complex multiple scattering problem with practical phase functions into a matrix form and solves transmitted/reflected photon angular distributions by matrix multiplications. Such characteristics would potentially allow practical inversions by matrix manipulation or stochastic algorithms where widely applied stochastic methods such as Monte Carlo simulations usually fail, and thus enable practical diagnostics reconstructions such as medical diagnosis, spray analysis, and atmosphere sciences.

Lagrangian Hotspots of In-Use NOX Emissions from Transit Buses.

In-use, spatiotemporal NOX emissions were measured from a conventional powertrain transit bus and a series electric hybrid bus over gradients of route kinetic intensity and ambient temperature. This paper introduces a new method for identifying NOX emissions hotspots along a bus route using high fidelity Lagrangian vehicle data to explore spatial interactions that may influence emissions production. Our study shows that the studied transit buses emit higher than regulated emissions because on-route operation does not accurately represent the range of engine operation tested according to regulatory standards. Using the Lagrangian hotspot detection, we demonstrate that NOX hotspots occurred at bus stops, during cold starts, on inclines, and for accelerations. On the selected routes, bus stops resulted in 3.3 times the route averaged emissions factor in grams/km without significant dependence on bus type or climate. The buses also emitted 2.3 times the route averaged NOX emissions factor at the beginning of each route due to cold selective catalytic reduction aftertreatment temperature. The Lagrangian hotspot detection technique demonstrated here could be employed in future connected vehicles empowered by advances in computational power, data storage capability, and improved sensor technology to optimize emissions as a function of spatial location.

Gaseous and Particulate Emissions from Diesel Engines at Idle and under Load: Comparison of Biodiesel Blend and Ultralow Sulfur Diesel Fuels.

Diesel exhaust emissions have been reported for a number of engine operating strategies, after-treatment technologies, and fuels. However, information is limited regarding emissions of many pollutants during idling and when biodiesel fuels are used. This study investigates regulated and unregulated emissions from both light-duty passenger car (1.7 L) and medium-duty (6.4 L) diesel engines at idle and load and compares a biodiesel blend (B20) to conventional ultralow sulfur diesel (ULSD) fuel. Exhaust aftertreatment devices included a diesel oxidation catalyst (DOC) and a diesel particle filter (DPF). For the 1.7 L engine under load without a DOC, B20 reduced brake-specific emissions of particulate matter (PM), elemental carbon (EC), nonmethane hydrocarbons (NMHCs), and most volatile organic compounds (VOCs) compared to ULSD; however, formaldehyde brake-specific emissions increased. With a DOC and high load, B20 increased brake-specific emissions of NMHC, nitrogen oxides (NOx), formaldehyde, naphthalene, and several other VOCs. For the 6.4 L engine under load, B20 reduced brake-specific emissions of PM2.5, EC, formaldehyde, and most VOCs; however, NOx brake-specific emissions increased. When idling, the effects of fuel type were different: B20 increased NMHC, PM2.5, EC, formaldehyde, benzene, and other VOC emission rates from both engines, and changes were sometimes large, e.g., PM2.5 increased by 60% for the 6.4 L/2004 calibration engine, and benzene by 40% for the 1.7 L engine with the DOC, possibly reflecting incomplete combustion and unburned fuel. Diesel exhaust emissions depended on the fuel type and engine load (idle versus loaded). The higher emissions found when using B20 are especially important given the recent attention to exposures from idling vehicles and the health significance of PM2.5. The emission profiles demonstrate the effects of fuel type, engine calibration, and emission control system, and they can be used as source profiles for apportionment, inventory, and exposure purposes.