26 research outputs found
Consideration of Black Carbon and Primary Organic Carbon Emissions in Life-Cycle Analysis of Greenhouse Gas Emissions of Vehicle Systems and Fuels
The
climate impact assessment of vehicle/fuel systems may be incomplete
without considering short-lived climate forcers of black carbon (BC)
and primary organic carbon (POC). We quantified life-cycle BC and
POC emissions of a large variety of vehicle/fuel systems with an expanded
Greenhouse gases, Regulated Emissions, and Energy use in Transportation
model developed at Argonne National Laboratory. Life-cycle BC and
POC emissions have small impacts on life-cycle greenhouse gas (GHG)
emissions of gasoline, diesel, and other fuel vehicles, but would
add 34, 16, and 16 g CO<sub>2</sub> equivalent (CO<sub>2</sub>e)/mile,
or 125, 56, and 56 g CO<sub>2</sub>e/mile with the 100 or 20 year
Global Warming Potentials of BC and POC emissions, respectively, for
vehicles fueled with corn stover-, willow tree-, and Brazilian sugarcane-derived
ethanol, mostly due to BC- and POC-intensive biomass-fired boilers
in cellulosic and sugarcane ethanol plants for steam and electricity
production, biomass open burning in sugarcane fields, and diesel-powered
agricultural equipment for biomass feedstock production/harvest. As
a result, life-cycle GHG emission reduction potentials of these ethanol
types, though still significant, are reduced from those without considering
BC and POC emissions. These findings, together with a newly expanded
GREET version, help quantify the previously unknown impacts of BC
and POC emissions on life-cycle GHG emissions of U.S. vehicle/fuel
systems
Efficient adsorptive removal of Congo red from aqueous solution by synthesized zeolitic imidazolate framework-8
<p>Dyes exposure in aquatic environment creates risks to human health and biota due to their intrinsic toxic mutagenic and carcinogenic characteristics. In this work, a metal-organic frameworks materials, zeolitic imidazolate framework-8 (ZIF-8), was synthesized through hydrothermal reaction for the adsorptive removal of harmful Congo red (CR) from aqueous solution. Results showed that the maximum adsorption capacity of CR onto ZIF-8 was ultrahigh as 1250 mg g<sup>−1</sup>. Adsorption behaviors can be successfully fitted by the pseudo-second order kinetic model and the Langmuir isotherm equation. Solution conditions (pH condition and the co-exist anions) may influent the adsorption behaviors. The adsorption performance at various temperatures indicated the process was a spontaneous and endothermic adsorption reaction. The enhanced adsorption capacity was determined due to large surface area of ZIF-8 and the strong interactions between surface groups of ZIF-8 and CR molecules including the electrostatic interaction between external active sites Zn−OH on ZIF-8 -and −SO<sub>3</sub> or –N=N– sites in CR molecule, and the <i>π</i>–<i>π</i> interaction.</p
RLIM negatively regulates c-Myc transcriptional activity.
<p>(A) 293T cells were transfected with an E-box-luciferase (Firefly) reporter plasmid and a Renilla luciferase plasmid (as an internal control) together with c-Myc and RLIM plasmids as indicated. Firefly luciferase activity was measured and normalized by Renilla luciferase activity. Three independent experiments were conducted with similar results and one representative result is shown. Data is presented as mean ± SD. **p<0.01, ***p<0.001. (B) and (C) U2OS cells were transfected with c-Myc and RLIM plasmids as indicated (B) or with siRNAs against RLIM (C). Real-time PCR was carried out to examine <i>E2F2</i> and <i>Nucleolin</i> gene expression. Three independent experiments were conducted with similar results and one representative result is shown. Data is presented as mean ± SD. *p<0.05, **p<0.01, ***p<0.001. (D) RLIM overexpression and control stable U2OS cell lines were transfected with scramble or c-Myc siRNAs. 2 days after transfection, cells were plated in 96 well plates. Cell growth were monitored by cell counting kit-8. (E) U2OS cells were transfected with scramble siRNA or siRNAs against RLIM and/or c-Myc as indicated. 2 days after transfection, cells were plated in 96 well plates. Cell growth were monitored by cell counting kit-8. Three independent experiments were conducted with similar results and one representative result is shown. Data shown is relative cell number as compared to day 1 after plating. Data is presented as mean ± SD. *p<0.05, ***p<0.001. Lower WB figures show the expression of RLIM and c-Myc at day 3 after plating. (F) H1299 cells were transfected with scramble siRNA or siRNAs against RLIM and/or c-Myc as indicated. 2 days after transfection, cells were plated in 96 well plates. Cell growth were monitored by cell counting kit-8. Three independent experiments were conducted with similar results and one representative result is shown. Data shown is relative cell number as compared to day 1 after plating. Data is presented as mean ± SD. **p<0.01. Lower WB figure show the expression of RLIM and c-Myc at day 4 after plating.</p
RLIM does not affect c-Myc protein degradation.
<p>(A) and (B) 293T (A) and H1299 (B) cells were transfected with myc-c-Myc and increasing amount of HA-RLIM or HA-RLIM<sup>C596A</sup> plasmids as well as GFP plasmid. Ectopic c-Myc protein was detected by anti-myc antibody. GFP was used to monitor transfection efficiency. c-Myc and GFP levels were quantified using ImageJ software and the ratios of c-Myc to GFP are shown. (C) and (D) 293T (C) and H1299 (D) cells were transfected with scramble siRNAs or siRNAs against RLIM. Endogenous c-Myc protein was detected by anti-c-Myc antibody. c-Myc and actin levels were quantified using ImageJ software and the ratios of c-Myc to actin are shown. (E) and (F) 293T cells were transfected with HA-RLIM (E) plasmid or siRNA against endogenous RLIM (F). Cells were harvested at different time points after cycloheximide treatment and subjected to WB. Quantification of c-Myc protein level relative to actin are summarized from 3 independent experiments and shown in the right panels.</p
RLIM promotes c-Myc ubiquitination.
<p>(A) 293T cells were transfected with Flag-Ub, myc-c-Myc, HA-RLIM and HA-RLIM<sup>C596A</sup> in combinations as indicated. Ectopically expressed c-Myc was immunoprecipitated by anti-myc antibody followed by WB with anti-Flag antibody. (B) 293T cells were transfected as in (A) except using 6 × His-Ub instead of Flag-Ub. Ubiquitinated proteins were precipitated with nickel (Ni)-NTA beads and subjected to WB with anti-myc antibody. (C) 293T cells were transfected with His-Ub, HA-RLIM, myc-c-Myc and myc-c-Myc<sup>DM</sup> (S62A and T58A) as indicated. Ubiquitinated proteins were precipitated with nickel (Ni)-NTA beads and subjected to WB with anti-myc antibody.</p
RLIM interacts with c-Myc.
<p>(A) 293T cells were transfected with HA-RLIM and myc-c-Myc expression vectors and immunoprecipitation was carried out with anti-myc or anti-HA antibodies as indicated. Immunoprecipitates were subjected to WB with anti-HA and anti-myc antibodies. (B) and (C) 293T cell lysate was subjected to immunoprecipitation with control IgG antibody and anti-RLIM (B) or anti-c-Myc (C) antibodies. Immunoprecipitates were subjected to WB with anti-c-Myc and anti-RLIM antibodies. * indicates the heavy chain of IgG. (D) Purified bacterial-expressed GST or GST-c-Myc proteins were incubated with bacterial-expressed His-RLIM protein. Interaction between RLIM and c-Myc were detected by GST pull-down and subsequent WB with anti-His antibody. (E) 293T cells were transfected with WT or catalytic dead HA-RLIM together with myc-c-Myc. Cells were subjected to immunoprecipitation with anti-myc antibody followed by WB with anti-HA and anti-myc antibodies.</p
U.S. Refinery Efficiency: Impacts Analysis and Implications for Fuel Carbon Policy Implementation
In
the next two decades, the U.S. refining industry will face significant
changes resulting from a rapidly evolving domestic petroleum energy
landscape. The rapid influx of domestically sourced tight light oil
and relative demand shifts for gasoline and diesel will impose challenges
on the ability of the U.S. refining industry to satisfy both demand
and quality requirements. This study uses results from Linear Programming
(LP) modeling data to examine the potential impacts of these changes
on refinery, process unit, and product-specific efficiencies, focusing
on current baseline efficiency values across 43 existing large U.S.
refineries that are operating today. These results suggest that refinery
and product-specific efficiency values are sensitive to crude quality,
seasonal and regional factors, and refinery configuration and complexity,
which are determined by final fuel specification requirements. Additional
processing of domestically sourced tight light oil could marginally
increase refinery efficiency, but these benefits could be offset by
crude rebalancing. The dynamic relationship between efficiency and
key parameters such as crude API gravity, sulfur content, heavy products,
residual upgrading, and complexity are key to understanding possible
future changes in refinery efficiency. Relative to gasoline, the efficiency
of diesel production is highly variable, and is influenced by the
number and severity of units required to produce diesel. To respond
to future demand requirements, refiners will need to reduce the gasoline/diesel
(G/D) production ratio, which will likely result in greater volumes
of diesel being produced through less efficient pathways resulting
in reduced efficiency, particularly on the marginal barrel of diesel.
This decline in diesel efficiency could be offset by blending of Gas
to Liquids (GTL) diesel, which could allow refiners to uplift intermediate
fuel streams into more efficient diesel production pathways, thereby
allowing for the efficient production of incremental barrels of diesel
without added capital investment for the refiner. Given the current
wide range of refinery carbon intensity values of baseline transportation
fuels in LCA models, this study has shown that the determination of
refinery, unit, and product efficiency values requires careful consideration
in the context of specific transportation fuel GHG policy objectives
Energy Efficiency and Greenhouse Gas Emission Intensity of Petroleum Products at U.S. Refineries
This paper describes the development
of (1) a formula correlating
the variation in overall refinery energy efficiency with crude quality,
refinery complexity, and product slate; and (2) a methodology for
calculating energy and greenhouse gas (GHG) emission intensities and
processing fuel shares of major U.S. refinery products. Overall refinery
energy efficiency is the ratio of the energy present in all product
streams divided by the energy in all input streams. Using linear programming
(LP) modeling of the various refinery processing units, we analyzed
43 refineries that process 70% of total crude input to U.S. refineries
and cover the largest four Petroleum Administration for Defense District
(PADD) regions (I, II, III, V). Based on the allocation of process
energy among products at the process unit level, the weighted-average
product-specific energy efficiencies (and ranges) are estimated to
be 88.6% (86.2%–91.2%) for gasoline, 90.9% (84.8%–94.5%)
for diesel, 95.3% (93.0%–97.5%) for jet fuel, 94.5% (91.6%–96.2%)
for residual fuel oil (RFO), and 90.8% (88.0%–94.3%) for liquefied
petroleum gas (LPG). The corresponding weighted-average, production
GHG emission intensities (and ranges) (in grams of carbon dioxide-equivalent
(CO<sub>2e</sub>) per megajoule (MJ)) are estimated to be 7.8 (6.2–9.8)
for gasoline, 4.9 (2.7–9.9) for diesel, 2.3 (0.9–4.4)
for jet fuel, 3.4 (1.5–6.9) for RFO, and 6.6 (4.3–9.2)
for LPG. The findings of this study are key components of the life-cycle
assessment of GHG emissions associated with various petroleum fuels;
such assessment is the centerpiece of legislation developed and promulgated
by government agencies in the United States and abroad to reduce GHG
emissions and abate global warming
Additional file 1: of Cholelithiasis and the risk of intrahepatic cholangiocarcinoma: a meta-analysis of observational studies
Title of dataset: Data extracted from the studies included in the meta-analysis. NOS Newcastle-Ottawa scale, CI confidence interval, CC caseâcontrol study, EHST extrahepatic bile duct stone or choledocholithiasis, GBST gallbladder stone or cholecystolithiasis, BDST bile duct stone, CLD chronic liver diseases, DM diabetes mellitus, ALD alcoholic liver disease, IBD inflammatory bowel disease, HBV hepatitis B virus. (DOC 62Â kb
Energy Intensity and Greenhouse Gas Emissions from Tight Oil Production in the Bakken Formation
The Bakken formation
has contributed to the recent rapid increase
in U.S. oil production, reaching a peak production of >1.2 ×
10<sup>6</sup> barrels per day in early 2015. In this study, we estimate
the energy intensity and greenhouse gas (GHG) emissions from 7271
Bakken wells drilled from 2006 to 2013. We model energy use and emissions
using the Oil Production Greenhouse Gas Emissions Estimator (OPGEE)
model, supplemented with an open-source drilling and fracturing model,
GHGfrack. Overall well-to-refinery-gate (WTR) consumption of natural
gas, diesel, and electricity represent 1.3%, 0.2%, and 0.005% of produced
crude energy content, respectively. Fugitive emissions are modeled
for a “typical” Bakken well using previously published
results of atmospheric measurements. Flaring is a key driver of emissions:
wells that flared in 2013 had a mean flaring rate that was ≈500
standard cubic feet per barrel or ≈14% of the energy content
of the produced crude oil. Resulting production-weighted mean GHG
emissions in 2013 were 10.2 g of CO<sub>2</sub> equivalent GHGs per
megajoule (henceforth, gCO<sub>2</sub>eq/MJ) of crude. Between-well
variability gives a 5–95% range of 2–28 gCO<sub>2</sub>eq/MJ. If flaring is completely controlled, Bakken crude compares
favorably to conventional U.S. crude oil, with 2013 emissions of 3.5
gCO<sub>2</sub>eq/MJ for nonflaring wells, compared to the U.S. mean
of ≈8 gCO<sub>2</sub>eq/MJ