Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Uncertainty and bias in Liggio et al. (2019) on CO₂ emissions from oil sands operations.

ABSTRACT:

SUBMITTER: Fu L

PROVIDER: S-EPMC10482826 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Uncertainty and bias in Liggio et al. (2019) on CO2 emissions from oil sands operations.

Fu Long L Legge Allan H AH

Nature communications 20230906 1

PMID: 37673887

Similar Datasets

Feng et al 2019 - Microarray Raw Data

Project description:In order to identify mechanisms of drug resistance to HER2-targeted therapy, we performed cDNA microarray analysis on drug naiive BT474 and drug resistant BT474 cells treated with lapatinib for 0, 10, and 20 hrs.

2020-04-14 | GSE136304 | GEO

Measured Canadian oil sands CO2 emissions are higher than estimates made using internationally recommended methods.

Project description:The oil and gas (O&G) sector represents a large source of greenhouse gas (GHG) emissions globally. However, estimates of O&G emissions rely upon bottom-up approaches, and are rarely evaluated through atmospheric measurements. Here, we use aircraft measurements over the Canadian oil sands (OS) to derive the first top-down, measurement-based determination of the their annual CO2 emissions and intensities. The results indicate that CO2 emission intensities for OS facilities are 13-123% larger than those estimated using publically available data. This leads to 64% higher annual GHG emissions from surface mining operations, and 30% higher overall OS GHG emissions (17 Mt) compared to that reported by industry, despite emissions reporting which uses the most up to date and recommended bottom-up approaches. Given the similarity in bottom-up reporting methods across the entire O&G sector, these results suggest that O&G CO2 emissions inventory data may be more uncertain than previously considered.

| S-EPMC6478833 | biostudies-literature

Aircraft and satellite observations reveal historical gap between top-down and bottom-up CO2 emissions from Canadian oil sands.

Project description:Measurement-based estimates of greenhouse gas (GHG) emissions from complex industrial operations are challenging to obtain, but serve as an important, independent check on inventory-reported emissions. Such top-down estimates, while important for oil and gas (O&G) emissions globally, are particularly relevant for Canadian oil sands (OS) operations, which represent the largest O&G contributor to national GHG emissions. We present a multifaceted top-down approach for estimating CO2 emissions that combines aircraft-measured CO2/NOx emission ratios (ERs) with inventory and satellite-derived NOx emissions from Ozone Monitoring Instrument (OMI) and TROPOspheric Ozone Monitoring Instrument (TROPOMI) and apply it to the Athabasca Oil Sands Region (AOSR) in Alberta, Canada. Historical CO2 emissions were reconstructed for the surface mining region, and average top-down estimates were found to be >65% higher than facility-reported, bottom-up estimates from 2005 to 2020. Higher top-down vs. bottom-up emissions estimates were also consistently obtained for individual surface mining and in situ extraction facilities, which represent a growing category of energy-intensive OS operations. Although the magnitudes of the measured discrepancies vary between facilities, they combine such that the observed reporting gap for total AOSR emissions is ≥(31 ± 8) Mt for each of the last 3 years (2018-2020). This potential underestimation is large and broadly highlights the importance of continued review and refinement of bottom-up estimation methodologies and inventories. The ER method herein offers a powerful approach for upscaling measured facility-level or regional fossil fuel CO2 emissions by taking advantage of satellite remote sensing observations.

| S-EPMC10165801 | biostudies-literature

Feldman et al. 2019 Nat Comm

Project description:Late Pleistocene human genome suggests a local origin for the first farmers of central Anatolia

| PRJEB24794 | ENA

Feldman et al.,Science Advances, 2019

Project description:Ancient DNA sheds light on the genetic origins of early Iron Age Philistines.

| PRJEB31035 | ENA

2019 Brecht et al. RAG1 vAbl BioID LC-MS/MS

Project description:To identify mechanisms that regulate V(D)J recombination, we used proximity-dependent biotin identification to analyze the interactomes of full length and truncated forms of RAG1 in pre-B cells. This revealed an association of RAG1 with numerous nucleolar proteins in a manner dependent on amino acids 216-383 and allowed identification of a motif required for nucleolar localization. Experiments in transformed pre-B cell lines and cultured primary pre-B cells reveal a strong correlation between disruption of nucleoli, reduced association of RAG1 with a nucleolar marker, and increases in V(D)J recombination activity. Mutation of the RAG1 nucleolar localization motif boosts recombination while removal of the first 215 amino acids of RAG1, which are required for efficient egress from nucleoli, reduces recombination activity. Our findings indicate that nucleolar sequestration of RAG1 is a negative regulatory mechanism in V(D)J recombination and identify regions of the RAG1 N-terminal region that control nucleolar association and egress.

2020-04-02 | PXD016221 | Pride

Oil contaminated sands

Project description:Oil contaminated sands Raw sequence reads

| PRJNA690167 | ENA

oil sands metagenome

Project description:Base Mine Lake metagenomes

| PRJNA1045392 | ENA

oil sands metagenome

Project description:oil sands metagenome Targeted loci environmental

| PRJNA492880 | ENA

Reply to Soman et al, Alffenaar et al, Metcalfe et al, and Raoult.

Project description: Not available