Design and Implementation of a Field Test for Biological Based VOC Emission Control for an Oil and Gas Production Facility in East Texas
Bibliographic record
Abstract
Abstract Biological based emissions control has been demonstrated to be an efficient and cost effective alternative to thermal oxidation technology or flaring for volatile organic compounds (VOCs) from the forest products and paint and coatings industries. This type of technology applicationhas promising advantages such as the potential for a low carbon footprint, low secondary pollutants such as NOx and SOx, lower energy demands, and lower cost. The objective of this project was to design and implement a sequential field scale biotrickling-biofilter treatment unit to remove VOCs and hazardous air pollutants (HAPs) emissions at the Apache TAMU#2 well storage tank battery in Snook, Texas. The field scale biotreatment system included a biotrickling filter followed by a biofilter with the total treatment volume of 100 ft3, skid mounted on a 22 foot trailer. The biotrickling filter was packed with structured cross flow media with large surface area and high void fraction designed to remove the more water soluble compounds and control the humidity and temperature variations of the inlet gas stream. The biofilter unit was loaded with plastic spheres packed with compost which is referred to as the engineered media. Each of the bio-oxidation units was operated at the air flow rate of 25 CFM and empty bed residence time (EBRT) of 2 minutes. The system was inoculated with local stormwater and wastewater from a sedimentation basinclarifier of a local refinery to provide a mixed culture of microorganisms for degradation of the VOC emissions. VOC emissions were collected from the headspace of a storage tank battery leading into a pressure relief vent system. Based on the photo ionization detector (PID) measurements at the inlet of the bio-oxidation unit, the VOC concentration loadings was cyclic and appeared to be correlated to the gas lift cycle of liquid loading to the crude oil storage tank. During the evaluation period, the biotrickling unit demonstrated a surprisingly higher removal efficiency compared to the biofilter. This may be related to the more stable and higher density of biomass growth observed on the surface of the cross flow media. The lower removal efficiency in the biofilter unit could be due to the lack of uniform moisture and nutrients in the second vessel as a result of spray nozzle inefficiency. This aspect of operation can be further optimized by changing the nozzle and the frequency of watering/spraying of the compost media. A removal efficiency of 50-60% for the total VOCs, across the complete unit, was achieved during the 3 month evaluation period while the unit was operated at an average inlet VOC concentration of 400 ppm. The relatively high concentration of alkenes and alkanes (compared to aromatics and water soluble organics in this crude oil vapor), may have decreased the degradation of the total VOCs in the bio-oxidation unit because these long-chain compounds are more difficult to biodegrade by bacterial biofilms in an aerobic environment. The results suggest biological emission treatment systems may be cost effective when compared to thermal oxidizers and flares and should be evaluated as a Maximum Achievable Control Technology (MACT) to mitigate HAPs (and VOCs) from some oil and gas operations. This innovative biological emissions control technology effectively controlled the cyclic emissions produced at the remote site. The strong increase in removal of VOCs after the oil refinery wastewater inoculation suggests an important optimization parameter for more rapid acclimation and increased efficiency for the system in the future applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".