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Bioenergy is considered a sustainable substitute to fossil-fuel resources and the development of a prudent combination of renewable and innovative conversion technologies are essential for the valorization and effective conversion of biowaste to value-added commodities. Here, a negative pressure-induced carbonization process was proposed for the valorization of lignin-enriched biowaste precursor to bio-oil and environmental materials (biochar) at various temperatures. The high heating values (HHV) of the as-prepared biochars from the lignin enriched precursor under negative pressure (low-medium vacuum) were within 25.9-31.5 MJ/kg, which matched satisfactorily to the commercial charcoal. Whereas, the bio-oils produced from the lignin enriched precursor under vacuum conditions was a blend of complex aromatic and straight-chain hydro-carbons, including aldehyde, ketone, phenol, and furans, exhibiting ability as potential heating-oil with HHV within 21.2-28.2 MJ/kg. Moreover, the biochars produced under vacuum environments at higher temperature showed greater stability (22.5-35.9%) than those produced under N2 atmosphere.

We present Vehicle Energy Dataset (VED), a novel large-scale dataset of fuel and energy data collected from 383 personal cars in Ann Arbor, Michigan, USA. This open dataset captures GPS trajectories of vehicles along with their time-series data of fuel, energy, speed, and auxiliary power usage. A diverse fleet consisting of 264 gasoline vehicles, 92 HEVs, and 27 PHEV/EVs drove in real-world from Nov, 2017 to Nov, 2018, where the data were collected through onboard OBD-II loggers. Driving scenarios range from highways to traffic-dense downtown area in various driving conditions and seasons. In total, VED accumulates approximately 374,000 miles. We discuss participant privacy protection and develop a method to de-identify personally identifiable information while preserving the quality of the data. After the de-identification, we conducted case studies on the dataset to investigate the impacts of factors known to affect fuel economy and identify energy-saving opportunities that hybrid-electric vehicles and eco-driving techniques can provide. The case studies are supplemented with a number of examples to demonstrate how VED can be utilized for vehicle energy and behavior studies. Potential research opportunities include data-driven vehicle energy consumption modeling, driver behavior modeling, machine and deep learning, calibration of traffic simulators, optimal route choice modeling, prediction of human driver behaviors, and decision making of self-driving cars. We believe that VED can be an instrumental asset to the development of future automotive technologies. The dataset can be accessed at https://github.com/gsoh/VED. 11 pages, 15 figures

Abstract This paper formulates a model that assesses the economic and policy implications of the adoption and operation of microgrids. The recent climate agreement between the US and China as well as the historic Lima accord on climate change are prompting a massive demand in climate-friendly technologies. Given the increasing demand for electricity and the mounting costs of electricity supply associated with maximizing system performance through an optimal economic scheduling of microgrids, decision makers and policymakers are already facing the problem of sketching energy management strategies for localized operation and grid penetration. We employ a modified Benders' decomposition approach to explore the optimal scheduling of supply from different technology units in the microgrid in the face of supply and demand uncertainties. We guarantee that the power generated by the units meets systemic load while satisfying the primary operational and technological constraints. We implement our model in a quantitative numerical analysis where we investigate the operational regulation in the light of a public environmental policy. We extend prior research on this subject by uncovering a greater reliance on the grid under simultaneous uncertainties in demand and supply. We unlock a strategy for a proper mitigation of the effects of emissions. We find that carbon abatement policy can be used to motivate microgrids operators to invest in fuel cells and natural gas technologies when dealing with uncertainty.

Building energy flexibility has been increasingly demonstrated as a cost-effective solution to respond to the needs of energy networks, including electric grids and district cooling and heating systems, improving the integration of intermittent renewable energy sources. Adjusting zonal temperature set-points is one of the most promising measures to unlock the energy flexibility potential of central air conditioning systems in complex commercial buildings. However, most existing studies focused on quantifying the energy flexibility on the building level since only building-level energy consumption is normally metered in commercial buildings. This study aims to investigate the impacts of temperature set-point adjustment strategies on zone-level thermal and energy performance by developing a non-intrusive data-driven load disaggregation method (i.e., a virtual zonal power meter). Three university buildings in Northern California were selected to test the proposed load disaggregation method. We found that heterogeneities of energy use and energy flexibility existed across not only buildings but also air handling units (AHUs) and zones. Moreover, a small number of zones accounted for a large amount of energy use and energy flexibility; and the most energy-intensive zones are not necessarily the most energy-flexible zones. For the three tested buildings, the top 30% most energy-intensive zones accounted for around 60% of the total energy use; and the top 30% most energy-flexible zones provided around 80% of the total energy flexibility. The proposed method enables the electric grid or district energy system operators to regard the controlled energy-flexible entities as a fleet of AHUs or zones instead of a fleet of buildings and helps unlock the possibility for targeted demand flexibility strategies that balance zone-by-zone energy reduction with zone-by-zone costs to occupants. 33 pages, 18 figures

To discuss current evidence of global climate change and its implications for allergic rhinitis and other allergic respiratory diseases.Global climate change is evidenced by increasing average earth temperature, increasing anthropogenic greenhouse gas levels, and elevated pollen levels. Pollutants of interest include carbon dioxide (CO2), ozone (O3), and nitrous oxide (NO2) because they can enhance the allergic response and lead to increased symptoms of allergic respiratory diseases. Heightened CO2 levels stimulate pollen production via photosynthesis and increased growth in multiple plant species investigated. Although worsened air quality appears to increase prevalence of allergic rhinitis, the effects of increased temperature are less certain. The findings of increased aeroallergen levels likely contribute to increases in presentation of allergic diseases, although more healthcare impact studies are necessary.Although recent literature indicates and strongly supports changes in temperature, pollution levels, and aeroallergen levels, more longitudinal epidemiologic surveillance of allergic diseases in relation to climate change as well as pathophysiologic studies on changing aeroallergen effects on allergic diseases are needed.

A promising route to transition wastewater treatment facilities (WWTFs) from energy-consuming to net energy-positive is to retrofit existing facilities with process modifications, residual biosolid upcycling, and effluent thermal energy recovery. This study assesses the economics and life cycle environmental impacts of three proposed retrofits of WWTFs that consider thermochemical conversion technologies, namely, hydrothermal liquefaction, slow pyrolysis, and fast pyrolysis, along with advanced bioreactors. The results are in turn compared to the reference design, showing the retrofitting design with hydrothermal liquefaction, and an up-flow anaerobic sludge blanket has the highest net present value (NPV) of $177.36MM over a 20-year plant lifetime despite 15% higher annual production costs than the reference design. According to the ReCiPe method, chlorination is identified as the major contributor for most impact categories in all cases. There are several uncertainties embedded in the techno-economic analysis and life cycle assessment, including the discount rate, capital investment, sewer rate, and prices of main products; among which, the price of biochar presents the widest variation from $50 to $1900/t. Sensitivity analyses reveal that the variation of discount rates causes the most significant changes in NPVs. The impact of the biochar price is more pronounced in the slow pyrolysis-based pathway compared to the fast pyrolysis since biochar is the main product of slow pyrolysis.

Abstract Bamboo has been considered a potential feedstock of energy for the future. It can be subjected to the pyrolysis for biofuels production. The thermogravimetric analysis (TGA) combined with differential thermogravimetric analysis (DTG) for bamboo was carried out prior to pyrolysis. The thermal degradation of bamboo was mainly between 230 and 420 °C. The conventional pyrolysis of bamboo was investigated in a bubbling fluidized-bed reactor using silica sand. The product distribution and composition of pyrolysis bio-oil were dependent on biomass component and operating conditions such as pyrolysis temperature, fluidization velocity, and particle size of biomass. The fractional catalytic pyrolysis of bamboo was also studied to upgrade the pyrolysis vapor, using HZSM-5 and red mud. The highest yield of bio-oil was 54.03 wt% compared to 49.14 wt% and 50.34 wt% of HZSM-5 and red mud catalyst, respectively. In the red mud catalytic pyrolysis, the oxygen content was rejected from pyrolysis vapor mostly via decarboxylation to produce more CO2 than CO; in contrast, for the HZSM-5 catalytic pyrolysis, the production of CO through decarbonylation was more favored than CO2. The main composition of catalytic pyrolysis bio-oil was 4-vinylphenol, which was employed as a raw material source to synthesize valuable material for energy storage.

The work described in this report was performed under the direction of the Industrial Assessment Center (IAC) at University of Texas at Arlington. The IAC at The University of Texas at Arlington is managed by Rutgers University under agreement with the United States Department of Energy Office of Industrial Technology, which financially supports the program. The objective of the IAC is to identify, evaluate, and recommend, through analysis of an industrial plant’s operations, opportunities to conserve energy and prevent pollution, thereby reducing the associated costs. IAC team members visit and survey the plant. Based upon observations made in the plant, preventive/corrective actions are recommended. At all times we try to offer specific and quantitative recommendations of cost savings, energy conservation, and pollution prevention to the plants we serve.