Quantification of Black Carbon Emissions from Gas Flaring and Standardization of the Sky-LOSA Measurement Technique

This thesis details the deployment and refinement of an emergent optical diagnostic for soot/black carbon (BC) emissions from gas flaring alongside investigations into optical properties of flare BC.Research efforts were first focussed on the field-deployment of the existing sky-LOSA (line-of-sight attenuation using skylight) technique to measure BC emissions from gas flares.Fourteen measurements from nine flares revealed BC emissions spanning more than four orders of magnitude, highlighting the disproportionate emissions contributions of individual "super-emitting" flares.BC yields measured at four flares varied with flare gas energy content, permitting extension of a laboratory-based emission factor model to consider field data for actual in-field flares.Available gas flare simulation data were subsequently leveraged to perform numerical simulations of radiative transfer through realistic flare plumes to quantify previously ignored radiative effects in the sky-LOSA algorithm.Refractive index gradientdriven beam steering was found to be negligible through cooled flare plumes.By contrast, multiple scattering was observed to significantly affect inscattering within the radiative transfer theory for sky-LOSA.These data revealed a simple model to correct for multiple scattering effects in the sky-LOSA algorithm with negligible impact on measurement uncertainties as evidenced by case study analyses.Laboratory studies of flare BC were performed in parallel to address a lack of data for flare-relevant BC mass-normalized absorption cross-section (MAC).BC MAC was quantified for myriad flare gas compositions/conditions and varied with numerous flare metrics.A phenomenological model for BC MAC was developed using a novel scaling iii parameter thought to capture the in-flame time-temperature history of BC particulate.The new model reconciled anomalous field data and suggested that flare BC MAC might be >1.3-2.0 times larger than other sources.The final focus of this thesis was the completion of a general uncertainty analysis (GUA) to support standardized setup and measurement protocols for sky-LOSA.Uncertainties over all practical measurement conditions were computed in a variancereduced Monte Carlo framework.GUA data were compiled and presented in a new opensource software tool to allow sky-LOSA users to consistently obtain optimal measurement data for arbitrary measurement conditions, enabling broader deployment of sky-LOSA to quantify and reduce flare BC emissions.First and foremost, I would like to express my tremendous appreciation to my thesis supervisor, Professor Johnson.You are truly a great mentor and have provided such an abundance of opportunities through the years.Thank you for your patience, unwavering support, and dedication to making our efforts as impactful and meaningful as possible.In addition to the amazing academic experiences, there are many life lessons I have learnt along the way.My favourites?"Life's too short for white wine" and (while sharing a trailer in the Ecuadorean jungle) "you can survive anything for a week."To all my EERL colleagues, thank you for making this journey so much fun.I owe extra debts of gratitude to Darcy and Melina as the flare pit-masters and to those involved in field measurements.Also, I would like to specially thank Dave and Brian for the many brain-picking sessions and their valuable insights on any and all topics.My grandparents, my sister, and especially my Mom and Dad, thank you for the continuous love and support in so many ways, I am so grateful to have you all.To my wife, Brit, what can I say?The countless challenges that you have helped me through, the off-hours work that you have put up with, and everything you have done to keep me functioning; I've said it many times, but I am truly so very lucky.This is as much yours as it is mine.It's high time for the next chapter!To Grandpa Hadden.With our early morning math lessons and your endless enjoyment of everything learning, you prepared me for this path since I was a wee bairn.This is for you -how I'd love to chat with you about this.v

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