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Achieving net-zero CO2 emissions from indirect co-combustion of biomass and natural gas with carbon capture using a novel amine blend
No full textA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Applied Science in Process Systems Engineering, University of Regina. xvi, 166 p.Due to the aggravating effect of climate change as a result of unprecedented levels of greenhouse gases, particularly CO2, in the atmosphere, the need to minimize CO2 emissions into the atmosphere has become very crucial. The energy sector remains the largest source of CO2 emissions, therefore, a technology which allows for achieving netzero CO2 emissions in this sector is imperative.
This research work evaluated the possibility of achieving net-zero emissions (on the minimum) through the application of co-combustion of natural gas and biomass for electricity generation. Based on the study, it is was identified that indirect co-combustion of natural gas with biomass (in the form of producer gas) with carbon capture technology is the way to go towards achieving net-zero CO2 emissions. To effectively describe the process as being a net-zero CO2 emissions approach, Life Cycle Assessment data was applied to the various processes involved in the indirect co-combustion of biomass and natural gas coupled with carbon capture technology.
In the first phase of this work, 5M MEA, which is the benchmark solvent for CO2 capture was used as the worst-case scenario to determine the ratio of producer gas-to natural gas (on energy basis) sufficient for achieving net-zero CO2 emissions. Using the SaskPower forecasted electricity generation capacity for 2025/2026 as a case study and applying LCA data to 5M MEA as the solvent for CO2 capture, it was determined that on energy basis, 14.5% of producer gas (balance natural gas) is sufficient for achieving netzero CO2 emissions while satisfying the set electricity generation target.
The next phase of the work was to develop an amine blend with an improved CO2 removal efficiency compared to the bench-scale 5M MEA. Four different blends were screened to assess their respective performance against 5M MEA. These included 2:2 AMP: 1-(2HE) PRLD, 2:2 AMP: DEA-1,2-PD, 3:1 1-(2HE) PRLD: AMP and 3:1 1-(2HE) PRLD: DEA-1,2-PD bi-blends. Among these solvents, 2:2 AMP: 1-(2HE) PRLD was the optimum solvent as it demonstrated a high CO2 absorption-desorption parameter compared to the other blends. The absorption parameter for 2:2 AMP:1-(2HE) PRLD was 4.5% higher than that for 5M MEA and the desorption parameter 1,667% higher than 5M MEA.
In the last phase, the increased CO2 removal efficiency of the solvent was applied to LCA data to determine the ratio of electricity generation from natural gas and producer gas towards achieving net-zero CO2 emissions when the optimum solvent developed is used in place of 5M MEA. It was determined that at a desorption temperature of 110℃, nearly all the CO2 in the rich amine for the optimum was removed. The CO2 removal efficiency of this solvent is about 31% higher than that for 5M MEA, implying this solvent allows for the removal of higher amount of CO2 in the flue gas stream. From the life cycle massessment, using 2:2 AMP: 1-(2HE) PRLD as the absorbent for CO2 capture in place of 5M MEA, it was determined that the producer gas requirements on energy basis, for cocombusting indirectly with natural gas towards achieving net-zero CO2 emissions is just about 8%.
The findings from this work demonstrates that co-combusting biomass with natural gas (which is a lesser emitter of CO2 compared to other fossil fuels) allows for satisfying the energy demands while achieving net-zero CO2 emissions when CO2 capture is applied. The major limitation that has faced the application of bioenergy with carbon capture technology has been concerns over its competition with farmlands for food production. The results obtained from this work has showed that lower amount of biomass would be needed for energy generation via co-combustion with natural gas towards achieve net-zero emissions when a solvent with an improved CO2 removal ability is used as the absorbent in the CO2 capture process.Studentye
Feature Story: U Prairie Challenge Presented by SaskMilk begins with women's soccer
No full textThe inaugural U Prairie Challenge presented by SaskMilk is officially underway - and watching the varsity sports rivalry play out between the University of Regina and University of Saskatchewan has fans invested early on.
More than 500 people took in the 2022-23 challenge opener on Sept. 2 at Griffiths Stadium in Saskatoon, where the U of R Cougars and the USask Huskies women's soccer teams battled to a 3-3 draw.Staffn
Feature Story: National Nursing Week: U of R Sask Polytech Collaborative Nurse Practitioner Program
No full textTo honour National Nursing Week and the incredible work nurses do for our community, we're highlighting the University of Regina and Saskatchewan Polytechnic Collaborative Nurse Practitioner Program (CNPP) and two impressive recent graduates, Jocelyn Schrader and Lara Metheral.
In partnership with Saskatchewan Polytechnic, the CNPP offers an innovative approach to primary care nurse practitioner (NP) education.
An NP is a registered nurse (RN) with graduate level educational preparation who possesses advanced clinical knowledge and can autonomously assess; order and interpret diagnostic tests; diagnose; prescribe pharmaceuticals; and perform specific medical procedures within their legislated scope of practice.Staffn
Feature Story: Applications open till March 15 for many U of R entrance scholarships
No full textWill you be a new University of Regina student in the Fall 2022 semester? If so, there are currently 57 different entrance awards and scholarships available that you can apply for today (as well as others that don’t require an application). The Student Awards Management System (SAMS) has a full list of all of the entrance awards available to you, all of which have an application deadline of March 15, 2022.Staffn
Experiment Study of Non-Equilibrium Phase Behavior and Effect of External Vibration on Heavy Oil Production
No full textA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Applied Science in Petroleum Systems Engineering, University of Regina. xviii, 123 p.In this thesis, two types of heavy oil experiments were explored to study the heavy oil
non-equilibrium phase behavior and the influence of external vibration on heavy oil
production performance.
The first experiment was to use a Constant Composition Expansion and Compression
(CCEC) tests to determine the pseudo-bubble point pressure at low (T = 15°C) and high (T
= 75°C) temperature environment with three different volume change rates (“Fast Rate”
1.5 cm3/min; “Moderate Rate” 0.015 cm3/min; and “Slow Rate” 0.0003 cm3/min) and three
different live heavy oil samples (15 mol% C2H6 + 85 mol% STO; 35 mol% C2H6 + 65 mol%
STO; 55 mol% C2H6 + 45 mol% STO). The live oil samples were recombined with ethane
and crude oil at the gas-oil ratio (GOR) of 8.63 cm3/cm3, 24.22 cm3/cm3; and 55.03 cm3/cm3,
respectively. Then the live oil densities and viscosities of the homogenized mixing fluid
were measured at different temperatures and pressures. The factors that affect the pseudo
bubble point pressure of the live oil samples were examined, and it was found that high
temperature, high gas concentration and low volume expansion rate resulted higher pseudo
bubble point pressure. Also, the ethane-heavy oil samples were compared with the
methane-heavy oil sample with the same GOR, and the latter had higher pseudo bubble
point pressure than the former.
The second experiment was to study the external vibration effect on heavy oil
production. The external Vibration-Stimulated Gas Pressure Cycling (VS-GPC) processes
with different vibration durations and frequencies were performed. The enhanced heavy
oil recovery processes were compared in terms of the heavy oil recovery factor (RF),
instantaneous gas production (iGP), production pressure (Pprod) and the production time of
each cycle for all tests. The laboratory tests were conducted by using a cylindrical
sandpacked physical model and the tests include one Gas Pressure Cycling (GPC) process,
one GPC process with pre-vibration stimulation, three VS-GPC processes with 23.5-hour
vibration at the same vibration frequencies, and three VS-GPC processes with 0.5-hour
vibration at different vibration frequencies. The results demonstrated that the differences
caused by vibration time (23.5 hrs vs. 0.5 hour) are marginal, and 2 Hz is the optimal
frequency compared with 5 Hz and 20 Hz tests for this study. The heavy oil RFs for various
VS-GPC process were ranked as follow: 2 Hz 0.5-hour VS-GPC > 5 Hz 23.5-hour VSGPC
> 5 Hz 0.5-hour VS-GPC > 20 Hz 0.5-hour VS-GPC > pre-vibration GPC > GPC.Studentye
Feature Story: Thousands cheer on the Regina Rams at U Prairie Challenge kick-off event
No full textThe Regina Rams charge the field for their first game of the U Prairie Challenge.
Fans and students made sure to document the official launch of the U Prairie Challenge presented by SaskMilk as they poured into Confederation Park Saturday afternoon for the Alumni & Community tailgate party presented by URAA (University of Regina Alumni Association).Staffn
"Chew and pour learning strategy": A co-participant's account in a collaborative narrative research to examine learning challenges
No full textA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Education, University of Regina. x, 261 p.This collaborative narrative research study explores the experiences of three co-participants who studied at different locations in the Ashanti Region of Ghana. The three co-participants include myself, researcher and two of my former junior high school students. I purposively selected my co-participants. The sample comprised of Boateng and Ntim who were students at two of the three respective junior high schools in which I taught. Drawing on two theoretical frameworks, critical-constructivism (Kincheloe, 2005), and language and symbolic power (Bourdieu, 1971; 1990), this study explores stories shared by the co-participants to identify learning challenges and successes over the use of English and Indigenous languages in school. I employed collaborative narrative research as the methodology for this study. To collect the data, I designed a set of semi-structured interview questions (Creswell & Guetterman, 2019) to guide the story narration process. One of the goals of this study is how to influence policymakers to direct their attention to solving challenges associated with current linguistic practices in schools. All three of us recounted memorable stories from our early years of schooling to the post-secondary level. My co-participants reflected on struggles they went through with language of instruction, how their life choices were affected by English, and how accessible public spaces are at places where English speaking is required. The study reveals that co-constructing stories with learners offers teachers opportunity to understand the experiences of their students, both former and present. The study found the enormous benefits of local language instruction and communication inside and outside of the classroom. All three co-participants expressed our challenges of navigating the school environment under the implementation of English-only speaking in our respective schools. Therefore, I recommend that to better understand our students’ needs, teachers should practice co-sharing of experiences with their students. I also recommend to policymakers to, as a matter of necessity, implement bilingualism (local language and English) in school to facilitate effective teaching and learning.Studentye
Release: Beverley Montague receives University of Regina Distinguished Service Award
No full textStaffn
Feature Story: Introducing the Really BIG Deal to save students money
No full textThe U of R understands the financial pressures that students face and is pleased to announce the creation of a new housing and tuition savings offer for both international and domestic students who choose to live on campus while they study at the U of R.
The U of R's Really BIG Deal - a housing and tuition savings offer - is now available to all students who bundle their U of R housing, meal plans, and Campus Store purchases.
Savings bundles feature locked-in tuition and fees, locked-in and discounted housing rates, as well as a variety of other financial benefits for as long as they live in U of R housing.Staffn
Impacts of nested forward validation techniques on machine learning and regression waste disposal time series models
No full textThis is the accepted version of the original article available at https://doi.org/10.1016/j.ecoinf.2022.101897. © 2022 Published by Elsevier Ltd.
Accepted article is CC BY-NC-ND.Dataset partitioning and validation techniques are required in all artificial neural network based waste models. However, there is currently no consensual approach on the validation techniques. This study examines the effects of three time series nested forward validation techniques (rolling origin - RO, rolling window - RW, and growing window - GW) on total municipal waste disposal estimates using recurrent neural network (RNN) models, and benchmarks model performance with respect to multiple linear regression (MLR) models. Validation selection techniques appear important to waste disposal time series model construction and evaluation. Sample size is found as an important factor on model accuracy for both RNN and MLR models. Better performance in Trial RW4 is observed, probably due to a more consistent testing set in 2019. Overall, the MAPE of the waste disposal models ranging from 10.4% to 12.7%. Both GW and RO validation techniques appear appropriate for RNN waste models. However, MLR waste models are more sensitive to the dataset characteristics, and RO validation technique appears more suitable to MLR models. It is found that data characteristics are more important than training period duration. It is recommended data set normality and skewness be examined for waste disposal modeling.The research reported in this paper was supported by a grant from the Natural Sciences and Engineering Research Council of Canada (RGPIN-2019-06154) to the corresponding author, using computing equipment funded by FEROF at the University of Regina