text
stringlengths 0
1.75k
|
|---|
A comparative assessment of resource efficiency in petroleum refining
|
Jeongwoo Han a,⇑, Grant S. Forman b, Amgad Elgowainy a, Hao Cai a, Michael Wang a, Vincent B. DiVita c
|
a Systems Assessment Group, Energy Systems Division, Argonne National Laboratory, 9700 S. Cass Avenue, Argonne, IL 60439, United states
|
b Sasol Synfuels International, 900 Threadneedle, Suite 100, Houston, TX 77079, United States
|
c Jacobs Consultancy Inc., 5995 Rogerdale Road, Houston, TX 77072, United States
|
h i g h l i g h t s
|
Investigate refineries with various complexities and operational flexibilities.
|
Categorize refineries into three groups by crude density and heavy products yield.
|
Estimate GHG emissions cost to produce more of the desirable fuels.
|
Complex refineries can process heavier crude into more gasoline and distillate.
|
Complex refineries are more resource efficient, but more energy and GHG intensive.
|
a r t i c l e
|
i n f o
|
Article history:
|
Received 12 January 2015
|
Received in revised form 4 March 2015
|
Accepted 10 March 2015
|
Available online 25 March 2015
|
Keywords:
|
Petroleum refinery
|
Life-cycle analysis
|
Energy efficiency
|
Resource efficiency
|
Greenhouse gas emissions
|
a b s t r a c t
|
Because of increasing environmental and energy security concerns, a detailed understanding of energy
|
efficiency and greenhouse gas (GHG) emissions in the petroleum refining industry is critical for fair
|
and equitable energy and environmental policies. To date, this has proved challenging due in part to
|
the complex nature and variability within refineries. In an effort to simplify energy and emissions refin-
|
ery analysis, we delineated LP modeling results from 60 large refineries from the US and EU into broad
|
categories based on crude density (API gravity) and heavy product (HP) yields. Product-specific efficien-
|
cies and process fuel shares derived from this study were incorporated in Argonne National Laboratory’s
|
GREET life-cycle model, along with regional upstream GHG intensities of crude, natural gas and electricity
|
specific to the US and EU regions. The modeling results suggest that refineries that process relatively
|
heavier crude inputs and have lower yields of HPs generally have lower energy efficiencies and higher
|
GHG emissions than refineries that run lighter crudes with lower yields of HPs. The former types of
|
refineries tend to utilize energy-intensive units which are significant consumers of utilities (heat and
|
electricity) and hydrogen. Among the three groups of refineries studied, the major difference in the
|
energy intensities is due to the amount of purchased natural gas for utilities and hydrogen, while the
|
sum of refinery feed inputs are generally constant. These results highlight the GHG emissions cost a refi-
|
ner pays to process deep into the barrel to produce more of the desirable fuels with low carbon to hydro-
|
gen ratio.
|
2015 Argonne National Laboratory. Published by Elsevier Ltd. This is an open access article under the CC
|
BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
|
1. Introduction
|
Increasing concerns with the consequences of climate change
|
turns scrutiny towards the source and efficiency of energy produc-
|
tion and consumption. Within this context, petroleum is a major
|
source of global energy demand and a primary component of
|
transportation fuels. In 2011, petroleum accounted for 34% of
|
global energy consumption and 36% of global greenhouse gas
|
(GHG) emissions [1], while the transportation sector in the US
|
and the EU consumed 71% and 62% of total petroleum products,
|
respectively, as shown in Fig. S1 [2,3].
|
Regulations are being developed in the US and EU to reduce pet-
|
roleum consumption, encourage use of alternative fuels and pro-
|
mote energy efficiency. In the US, the Renewable Fuel Standard
|
(RFS) mandates the production of 36 billion gallons of renewable
|
fuels with various GHG emissions reduction thresholds relative
|
to conventional gasoline and diesel [4]. California implemented
|
the Low Carbon Fuel Standard (LCFS) in 2009 to reduce the GHG
|
intensity of transportation fuels [5]. The Renewable Energy
|
http://dx.doi.org/10.1016/j.fuel.2015.03.038
|
0016-2361/ 2015 Argonne National Laboratory. Published by Elsevier Ltd.
|
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
|
⇑Corresponding author. Tel.: +1 630 262 6519.
|
E-mail
|
addresses:
|
jhan@anl.gov
|
(J.
|
Han),
|
grant.forman@us.sasol.com
|
(G.S.
|
Forman),
|
aelgowainy@anl.gov
|
(A.
|
Elgowainy),
|
hcai@anl.gov
|
(H.
|
Cai),
|
mqwang@anl.gov (M. Wang), Vince.Divita@jacobs.com (V.B. DiVita).
|
Fuel 157 (2015) 292–298
|
Contents lists available at ScienceDirect
|
Fuel
|
journal homepage: www.elsevier.com/locate/fuel
|
Directive (RED) in the EU requires 10% of transportation energy
|
consumption to be produced from renewable sources by 2020
|
[6]. The production of energy from these renewable sources must
|
achieve a minimum 35% reduction in life-cycle GHG emissions
|
against conventional, petroleum-derived baseline fuels, with the
|
threshold being elevated to 50% in 2018 [7].
|
Notably, all of these regulations require a reliable estimation of
|
life-cycle
|
GHG
|
emissions
|
of
|
alternative
|
transportation
|
fuels,
|
including petroleum-derived gasoline and diesel baseline fuels.
|
End of preview. Expand
in Data Studio
No dataset card yet
- Downloads last month
- 20