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Potential air pollutant emissions and permitting classifications for two biorefinery process designs in the United States Annika Eberle, Arpit Bhatt, Yimin Zhang, and Garvin A. Heath Environ. Sci. Technol., Just Accepted Manuscript • Publication Date (Web): 26 Apr 2017 Downloaded from http://pubs.acs.org on May 1, 2017

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Environmental Science & Technology

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Potential air pollutant emissions and permitting classifications for two

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biorefinery process designs in the United States

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Annika Eberle, Arpit Bhatt, Yimin Zhang,* and Garvin Heath

4

National Renewable Energy Laboratory, Golden, CO, 80401 USA

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Abstract

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Advanced biofuel production facilities (biorefineries), such as those envisioned by the United States

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(U.S.) Renewable Fuel Standard and U.S. Department of Energy’s research and development programs,

8

often lack historical air pollutant emissions data, which can pose challenges for obtaining air emission

9

permits that are required for construction and operation. To help fill this knowledge gap, we perform a

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thorough regulatory analysis and use engineering process designs to assess the applicability of federal

11

air regulations and quantify air pollutant emissions for two feasibility-level biorefinery designs. We find

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that without additional emission-control technologies both biorefineries would likely be required to

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obtain major source permits under the Clean Air Act’s New Source Review program. The permitting

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classification (so-called “major” or “minor”) has implications for the time and effort required for

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permitting and therefore affects the cost of capital and the fuel selling price. Consequently, we explore

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additional technically feasible emission-control technologies and process modifications that have the

17

potential to reduce emissions to achieve a minor source permitting classification. Our analysis of air

18

pollutant emissions and controls can assist biorefinery developers with the air permitting process and

19

inform regulatory agencies about potential permitting pathways for novel biorefinery designs.

20 *

Contact information for corresponding author: National Renewable Energy Laboratory, Strategic Energy Analysis Center, 15013 Denver W Pkwy, Golden, CO, 80401, USA. Email: [email protected].

1 ACS Paragon Plus Environment


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1 Introduction

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The U.S. Department of Energy’s Billion-Ton Studies estimate that by 2030 the United States could,

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without interfering with other vital farm and forest products, sustainably produce enough biomass

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feedstock to displace 30% of U.S. 2005 petroleum consumption using biofuels.1–3 To take advantage of

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the potential benefits associated with biofuels4,5, the United States developed the Renewable Fuel

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Standard6 to increase the use of renewable fuels. However, because cellulosic biofuel conversion

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technologies are still being developed, their non-GHG air pollutant emissions are not well quantified.

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Although prior research has explored the technical and economic feasibility of cellulosic biorefineries7–10

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and the regulatory and legal impediments to commercialization,11–17 none of these studies has

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developed detailed estimates of air pollutant emissions for multiple biofuel conversion pathways. As a

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result, biorefinery developers are often uncertain about the type and quantity of pollutants their

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facilities may emit, and air emission permitting officials are challenged to determine regulatory

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applicability and compliance.

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Despite these challenges, the Clean Air Act (CAA)18 requires new stationary sources that expect to emit

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regulated pollutants greater than specific thresholds to quantify their potential to emit (PTE) and obtain

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air permits before construction. The PTE is defined as the greatest amount of regulated air pollutant

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emissions that a facility could release to the atmosphere under its physical and operational design.19 It

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must be evaluated for several types of pollutants, including criteria air pollutants—those with National

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Ambient Air Quality Standards—and their precursors (e.g., sulfur dioxide [SO2], carbon monoxide [CO],

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particulate matter [PM], nitrogen oxides [NOx], ozone regulated through its precursors such as NOx and

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volatile organic compounds [VOCs], and lead [Pb]); pollutants outlined in the New Source Performance

42

Standards (NSPSs); and hazardous air pollutants (HAPs).20 Uncertainties in determining the applicability

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of certain regulations and estimating the PTE could lead to a lengthy permit review process, which could

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cause construction delays or design modifications and thereby impact production costs. PTE 2 ACS Paragon Plus Environment

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uncertainties could also mean that permitted emission limits are not met, which could cause

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environmental harm and result in compliance violations.

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To help mitigate the risks associated with biorefinery air permitting, we estimate the PTE for two

48

feasibility-level process designs that produce cellulosic biofuels and perform a thorough regulatory

49

analysis to evaluate the applicability of federal regulations. We show that if built according to their

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design specifications these two biorefineries would likely be classified as major sources under the

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federal New Source Review (NSR) program. However, with additional, technically feasible emission

52

control options or design modifications, both biorefineries could achieve minor source permitting

53

classifications.

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There are both positive and negative implications of analyzing feasibility-level process designs. Since the

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final process design, location, and size of each facility may differ from the designs explored here, our

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estimated PTE is considered preliminary. However, by analyzing these biorefinery designs near the

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beginning of their development, this work can help biorefinery developers formulate permitting

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strategies and mitigate permitting risks. Our work may also inform regulatory agencies about PTE

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uncertainties and control options that could lead to more streamlined permitting processes.

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2 Methods

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We performed regulatory analyses, estimated the PTE, and assessed the potential permitting

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classifications for two feasibility-level biorefinery process designs. We focused solely on federal air

63

regulations because state air regulations depend on a variety of factors such as the local air quality

64

status and state implementation plans. We performed this analysis for permits required to construct

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and, when applicable, to operate the biorefinery.



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Our analysis is based on two process designs capable of processing 2000 dry megagrams (Mg) of

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biomass feedstock per day into hydrocarbon biofuel products: (1) a biochemical technology pathway

68

focused on biological conversion of cellulosic sugars (hereafter referred to as sugars-to-hydrocarbons)21

69

and (2) a thermochemical pathway focused on fast pyrolysis of whole biomass.22 Several baseline

70

emission control technologies were included in these designs, including baghouses, flue gas

71

desulfurization (FGD), and selective non-catalytic reduction and over-fire air systems to reduce PM, SO2,

72

and NOx emissions, respectively (see Supporting Information [SI] for details).

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To help identify mitigation strategies and to understand whether a given pollutant is emitted from

74

operations key to biofuel conversion or from supporting operations, we disaggregated each design into

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four emission-release areas: core operations (e.g., pre-processing, conversion), supporting operations,

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truck traffic, and equipment leaks (Figure 1). Additional details about our methods and results are

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documented in Zhang et al.17 and Bhatt et al.23


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Figure 1. Overarching emission release areas and potential air pollutants emitted from two process designs:

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sugars-to-hydrocarbons and fast pyrolysis. Although the conversion processes differ for these two

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biorefineries, their sub-processes can be categorized into four overarching emission release areas: core

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operations, supporting operations, truck traffic, and equipment leaks.



83 84

To identify the types of pollutants likely to be emitted from each area, we analyzed each unit

85

operation,21,22 consulted the process design engineers, utilized the U.S. Environmental Protection

86

Agency’s (EPA’s) Compilation of Air Pollution Emission Factors (AP-42) report,24 and examined air

87

permits for facilities employing similar processes. We then reviewed the Code of Federal Regulations

88

(CFR) for all NSPSs (Title 40, Part 60)25 and NESHAPs (Title 40, Parts 61 and 63)26,27 that may apply to the

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entire biorefinery and/or to specific equipment and operations. We also used the EPA’s Applicability

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Determination Index database28 to assess applicability or monitoring requirements under the NSPS and

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NESHAP programs. If the biorefinery or a specific portion of the facility met the applicability criteria of

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an NSPS or NESHAP, we determined the federal regulation to be applicable.

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The Standard Industrial Classification (SIC) of the facility determines which NSPSs and NESHAPs apply to

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the entire facility. Since permits for similar cellulosic biorefineries indicate that these facilities will fall

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under SIC 28 (chemicals and allied products), we conducted our analysis under the assumption that both

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biorefineries would fall under this SIC (see SI for details).29,30 The results presented here are for two

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specific biorefinery designs; biorefinery developers and owners should consider all NSPSs and NESHAPs

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when planning compliance measures for their facility.

99

2.1 Estimating the Potential to Emit

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According to the EPA31, there are four standard methods that can be used to calculate PTE: (1)

101

test data, (2) material balances, (3) source-specific models, and (4) emission factors. We used

102

three of these approaches (i.e., material balances, emission factors, and source-specific models),

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along with a variety of data sources to estimate the PTE for each process and unit operation

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(Table 1; Tables S2-S4 in the SI).

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Table 1. Methods and data sources used to estimate the PTE for both the sugars-to-hydrocarbons and fast

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pyrolysis designs. (Additional details, including pollutant-specific emission factors, are provided in Tables S2-

108

S4 in the Supporting Information.)

Emission Source for Each Biofuel Pathway Emission Release

PTE Estimation Data Sources

Sugars-toArea

Approach

Fast Pyrolysis Hydrocarbons

Core operations

[1]

Feedstock handling

Fast pyrolysis system ;

and pretreatment;

Hydrotreating and

1. Air permits for analogous equipment/operations Enzymatic hydrolysis;

hydrocracking;

Emission factor

[3]

[2] 24

2. EPA’s AP-42 report Product recovery and

Product separation;

upgrading

Hydrogen production

Enzyme production

Fast pyrolysis system

3. Engineering judgment

1. Process models [1]

Material balance 2. Engineering judgment

Supporting

1. Air permits for analogous

operations

equipment/operations

[3]

24

2. EPA’s AP-42 report

3. EPA’s Emission Estimation Loading operations;

Loading operations;

Protocol for Petroleum Emission factor

Boiler; Utilities

[2] 32

Utilities

Refineries

4. Emission limits in NSPS Subpart IIII

33

5. SCAQMD’s Guidelines for 34

Cooling Towers

Source-specific Storage

model

Wastewater

1. EPA’s TANKS 4.09D

Storage

Wastewater treatment

Material balance


35

software

1. Process models


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treatment;


Boiler Equipment leaks

[4]

Leaks from process

Leaks from process

vents, process

vents, process

equipment, storage

equipment, storage

1. EPA’s Protocol for Leak Emission Estimates Emission factor

[2]

Truck traffic

[4]

2. Air permits for analogous equipment/operations

tanks, and wastewater tanks, and wastewater treatment

36

treatment

[3]


On-site transportation On-site transportation of of feedstock, raw

feedstock, raw materials, Emission factor

[2]

24

1. EPA’s AP-42 report

materials, and finished and finished products products

109

Abbreviations include EPA for Environmental Protection Agency, NSPS for New Source Performance Standards, and SCAQMD

110

for South Coast Air Quality Management District.

111

[1]

112

handling, and the fast pyrolysis reactor. As a result, we use multiple PTE estimation approaches to estimate emissions from this

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system (see SI for details).

114

[2]

115

activity factors (AFs)—the amount of activity associated with a unit operation or piece of equipment (e.g., heat input capacity of

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the boiler). AFs were derived from the process designs, process models (e.g., Aspen Plus), and engineering judgment.

117

[3]

118

enzymatic hydrolysis in the sugars-to-hydrocarbons design while Cool Planet LLC air permit is relevant for the ash and sand

119

handling in fast pyrolysis). When appropriate, we scaled the emission factor based on the facility size or production rate for the

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corresponding operation.

121

[4]

The fast pyrolysis system is a combination of several areas, including the on-site char combustor (sand heater), sand

The emission factor approach multiplies emission factors (EFs)—the amount of pollutant emitted per rate of activity—by

37

Relevant air permits may vary by unit process (e.g., the air permit for Abengoa Bioenergy Biomass of Kansas is relevant for 38

Emissions from equipment leaks and truck traffic are considered to be fugitive emissions (emissions not feasibly collected).

122 123 124

After identifying the emission calculation methods in Table 1, we estimated the PTE by adhering to the

125

following guidelines prescribed by federal regulations:19,39


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126


1)

127 128

Assume the maximum capacity under the biorefinery’s physical and operational design (i.e., continuous operation at design capacity with the highest possible throughput);

2)

Use the worst-case emission factor (e.g., if multiple fuel sources are possible for a

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combustion unit, assume year-round usage of the fuel that emits the most of each

130

pollutant); and

131 132

3)

Account for federally enforceable limitations (e.g., regulatory provisions and practically enforceable, EPA-approved permit limits).

133

As required by regulations for chemical processing plants, we also included fugitive emissions (emissions

134

not feasibly collected) in the form of equipment leaks and truck traffic.

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PTE estimates for biorefineries are often uncertain because air permitting processes are

136

location-specific and emissions data for novel processes are often unavailable (see SI for details).

137

However, the regulatory definition of PTE does not allow for the inclusion of uncertainty. PTE is

138

intended to provide a conservative estimate for the upper bound of potential emissions. It

139

should always be larger—and often much larger—than the facility’s actual emissions. As a result,

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we present only a single value for the PTE of each regulated pollutant, which represents the

141

maximum amount of emissions the biorefinery may emit.

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To evaluate how much the PTE is impacted by federally enforceable limitations not imposed by physical

143

and operational design (item 3 above), we report two estimates of potential emissions: the uncontrolled

144

PTE (includes items 1 and 2) and the PTE (includes items 1-3). The PTE is always less than or equal to the

145

uncontrolled PTE because PTE takes into account additional controls to achieve emission limits required

146

by applicable federal rules (NSPSs, NESHAPs) or included in an approved air permit. The PTE value, not

147

the uncontrolled PTE, determines the source’s permitting classification.



148

2.2 Determining the Permitting Classification

149

Before constructing a new chemical process plant like a biorefinery, a developer must apply for a

150

construction permit under the NSR program.40 In general, if a source exceeds an applicable major source

151

threshold for at least one regulated pollutant under the NSR program, it is classified as a major source;

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otherwise it is classified as a minor source. If the facility is classified as a major source under NSR, or if

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the PTE of HAPs exceeds the major source threshold, then the developer must also apply for an

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operating permit under the Clean Air Act’s Title V program.41

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We made a preliminary determination of the permitting classification for each biorefinery by comparing

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the facility’s PTE to the corresponding major source thresholds. These thresholds vary by pollutant,

157

permitting program, industrial classification, and attainment status; lower thresholds may apply in non-

158

attainment areas but only for the non-attainment pollutant(s) (see Table S8 in the SI and Zhang et al.17).

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For this analysis we assume these facilities will be located in attainment areas where the default major

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source thresholds for pollutants emitted from a chemical process plant are 100 short tons per year (TPY)

161

(90.7 Mg per year) for criteria air pollutants under the NSR program and 10 TPY for a single HAP or 25

162

TPY for any combination of HAPs under the Title V program.

163

2.3 Evaluating the Ability to Obtain Minor Source Classification

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Major sources are subject to more stringent permitting requirements such as the implementation of

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additional emission controls and increased monitoring and reporting (see SI for details). For example,

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under the NSR permitting program, a new major source is required to install the Best Available Control

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Technologies (BACT), conduct an air quality analysis, perform additional impact analysis (e.g., on soils,

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vegetation, visibility), and involve the public in the review process. These additional permitting

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requirements could delay the construction of a proposed project and increase the project’s capital and

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operating costs.


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To mitigate risks and costs, biorefinery developers would prefer their facility to be classified as a minor

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source. Therefore, if our estimated PTE exceeded the major source thresholds, we examined additional

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emission controls and/or process modifications that may allow each biorefinery to be classified as a

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minor source. We used the EPA’s Reasonably Available Control Technology (RACT)/BACT/Lowest

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Achievable Emission Rate (LAER) Clearinghouse database,42 analogous air permit applications (e.g.,

176

Abengoa’s Bioenergy Biomass of Kansas air permit application43), and other EPA documentation44 to

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identify potential emission control technologies. We then consulted with the process design engineers

178

and used engineering judgment to identify which of these potential control options or process

179

modifications could be feasibly implemented.

180

For the sugars-to-hydrocarbons design, we incorporated the additional control technologies and any

181

required process modifications into the process model and executed process simulations to verify the

182

design’s performance. We then used published emission reduction efficiencies of the control devices,

183

along with changes in the design parameters (e.g., heat input capacity of the boiler), to update the PTE

184

estimates and determine whether a minor source permitting classification could be achieved. For the

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fast pyrolysis pathway, we more simply identified the feasible emission control technologies and

186

modified the PTE estimates using the control efficiencies of these technologies.

187

3 Results

188

Both biofuel conversion pathways will likely emit similar types of air pollutants. The supporting

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operations and core operations areas are expected to emit PM, VOCs, NOx, CO, SO2, and HAPs, along

190

with other regulated NSR pollutants. For fugitive emissions, truck traffic will likely emit PM and

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equipment leaks are expected to emit VOCs and HAPs (Figure 1).



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As shown in Table 2 (see Tables S5-S7 in the SI for details), both biorefineries will likely be subject to

193

several federal air regulatory requirements under the NSPSs25 and the NESHAPs27, including

194

•

NSPSs for

195

o

Industrial-Commercial Institutional Steam Generating Units (40 CFR 60, Subpart Db);

196

o

Stationary Compression Ignition Internal Combustion Engines (40 CFR 60, Subpart IIII)

197

o

Volatile Organic Liquid Storage Vessels (40 CFR 60, Subpart Kb)

198

•

NESHAPs for

199

o

Chemical Manufacturing Area Sources (40 CFR 63, Subpart VVVVVV)

200

o

Major Sources: Industrial, Commercial, and Institutional Boilers and Process Heaters (40

201

CFR 63, Subpart DDDDD)

202

o

Miscellaneous Organic Chemical Manufacturing (40 CFR 63, Subpart FFFF)

203

o

Stationary Reciprocating Internal Combustion Engines (40 CFR 63, Subpart ZZZZ).

204 205

Table 2. Federal regulations potentially applicable to the sugars-to-hydrocarbons and fast pyrolysis

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biorefinery designs examined here.

Emission

Sugars-to-Hydrocarbons

Fast Pyrolysis

Release Area

Affected Equipment

Affected Equipment

Potential Federal Regulation

Potential Federal Regulation

If facility is a major source of


HAPs: NESHAP Subpart FFFF

HAPs: NESHAP Subpart FFFF

Bioreactor process Core operations

or

Dryer vent

or

If facility is an area source of

(continuous process)


vent (batch process)

Supporting

Boiler

HAPs: NESHAP Subpart

HAPs: NESHAP Subpart

VVVVVV

VVVVVV

NSPS Subpart Db

Gasoline storage


NSPS Subpart Kb

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tank

operations

If facility is a major source of HAPs: NESHAP Subpart FFFF or If facility is an area source of HAPs: NESHAP Subpart VVVVVV



HAPs: NESHAP Subpart DDDDD Process heaters

HAPs: NESHAP Subpart DDDDD

or

(fired reboiler and

or


methane reformer)


HAPs: NESHAP Subpart JJJJJJ Emergency fire

NSPS Subpart IIII

pump and generator

HAPs: No regulation applies

Same as sugars-to-hydrocarbons NESHAP Subpart ZZZZ

If facility is a major source of HAPs: NESHAP Subpart FFFF or

Not applicable because the cooling water flow rate is


below 8,000 gal/min

Cooling tower

HAPs: NESHAP Subpart VVVVVV If facility is a major source of HAPs: NESHAP Subpart FFFF or

Equipment Equipment leaks [1]

Same as sugars-to-hydrocarbons If facility is an area source of

leaks

HAPs: NESHAP Subpart VVVVVV [1]

Truck traffic

Not applicable

Not applicable



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25

207

Abbreviations include NSPS for New Source Performance Standard in Title 40, Part 60 of the Code of Federal Regulations

208

(CFR) and NESHAP for National Emission Standard for Hazardous Air Pollutants in Title 40, Parts 61 and 63 of the CFR.

26

27

209 210

[1]

Emissions from equipment leaks and truck traffic are considered to be fugitive emissions (emissions not feasibly collected).

211 212 213

3.1 Estimated Potential to Emit and Preliminary Permitting Classification

214

As described in Section 2.1, we report the uncontrolled PTE and the PTE. The uncontrolled PTE accounts

215

for the maximum capacity to emit taking into account physical and operational limitations. For the

216

sugars-to-hydrocarbons design, there were no physical and operational design constraints, and the two

217

constraints that exist in the fast pyrolysis design did not have a substantial impact on the PTE results

218

(see SI for details). The PTE—the value considered under air permitting requirements—adds federally

219

enforceable emission limitations to the uncontrolled PTE. For example, in the fast pyrolysis biorefinery,

220

we assume the facility’s permit application will incorporate additional federally enforceable limitations

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to reduce HAP emissions from the dryer and gasoline loading operations by 95% and 60%, respectively,

222

because these limitations would help the biorefinery avoid more stringent requirements by reducing the

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HAP emissions to below the major source thresholds (see SI for details).

224

The impact of federally enforceable limitations on PTE varies by pollutant (top panel of Figure 2) and can

225

either be substantial (e.g., VOC emissions are reduced by ~93% in the sugars-to-hydrocarbons

226

biorefinery when federally enforceable limitations are included) or trivial (e.g., the uncontrolled PTE and

227

PTE values for CO are similar for both biorefineries). However, even after incorporating federally

228

enforceable limitations, the PTE for both biorefineries likely still exceeds the major source thresholds for

229

specific pollutants (e.g., 100 TPY for criteria air pollutants; 25 TPY for total HAPs). As a result, both


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biorefineries would likely be classified as major sources under the NSR program. In addition, the sugars-

231

to-hydrocarbons biorefinery would likely be a major source of HAPs under the Title V program.

232 233

Figure 2. Preliminary estimates for the uncontrolled potential to emit (PTE), the PTE in tons per year (TPY),

234

and the relative contribution of each emission release area (core operations, supporting operations,

235

equipment leaks, and truck traffic) to the PTE for each biofuel design. The uncontrolled PTE only

236

incorporates physical and operational design constraints, while the PTE includes these constraints plus

237

federally enforceable limitations. Note that the y-axes in the top panel are plotted on a log-scale.

238

Abbreviations include particulate matter (PM), volatile organic compounds (VOCs), nitrogen oxides (NOx),

239

carbon monoxide (CO), sulfur dioxide (SO2), criteria air pollutants (CAPs) and hazardous air pollutants

240

(HAPs), which represent total HAPs.

241 242

The contribution of the emission release areas to the PTE for each pollutant differs for each design

243

(bottom panel of Figure 2). For sugars-to-hydrocarbons, supporting operations (specifically the boiler) 15 ACS Paragon Plus Environment


244

contribute most to the emissions of air pollutants that exceed the major source thresholds (i.e., VOCs,

245

NOx, CO, SO2, and HAPs). For fast pyrolysis, core operations, specifically the methane reformer for

246

hydrogen production and char combustor and dryer for the fast pyrolysis system, contribute most to air

247

pollutant emissions that exceed the major source thresholds (i.e., PM, NOx, and SO2).

248 249

3.2 Additional Emission Controls to Achieve Minor Source Classification

250

Since major source permits are more stringent, complex, and therefore more time- and cost-intensive

251

than minor source permits, we explored feasible, state-of-the-art emission control technologies and

252

process modifications that may allow each biofuel conversion pathway to be classified as a minor source

253

(see Methods). We only evaluated additional control options for the unit operations that contribute

254

most to the air pollutant emissions that exceed the major source thresholds (Table 3). These processes

255

include the boiler system in the sugars-to-hydrocarbons biorefinery and the methane reformer and

256

dryer in the fast pyrolysis biorefinery.

257

Table 3. Selected, technically feasible emission control options

258

PTE to below major source thresholds.

Biofuel

Emission

pathway

source

Sugars-to-

Boiler

Hydrocarbons

Control option

[2]

[1]

that could be implemented to reduce the

Targeted pollutant(s) and method for emission reduction (as compared to published design)

1. Install a catalytic oxidizer control

CO, VOCs, HAPs: New control technology reduces

technology

emissions of CO by 90%, VOCs by 70%, and HAPs (formaldehyde and acetaldehyde) by 90%

2. Install a selective catalytic

NOx: New control technology has higher emission

reduction system in place of a

reduction efficiency (88%)

selective non-catalytic reduction control technology


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3a. Reduce the amount of lignin fed

CO, HAPs, NOx, VOCs, SO2: Process modification lowers

into boiler and therefore reduce the

the heat input capacity of the boiler, which decreases

size of the boiler

pollutant emissions CO, HAPs, NOx, VOCs: Process modification uses

3b. Change the fuel type being fed to

different fuel, which decreases the worst case emission

the boiler by re-routing all lignin to

factor

produce coproducts (e.g., chemicals) SO2: Process modification decreases the sulfur content of the fuel, which lowers the SO2 combustion emissions Fast Pyrolysis

[3]

Dryer

1. Install flue gas desulfurization

SO2: New control technology reduces emissions by 92%

2. Install a baghouse

PM: New control technology reduces emissions by 99%

Methane

3. Install a selective non-catalytic

NOx: New control technology reduces emissions by 45%

reformer

reduction control technology

259

Abbreviations include carbon monoxide (CO), volatile organic compounds (VOCs), hazardous air pollutants (HAPs), NOx (nitrogen

260

oxides), SO2 (sulfur dioxide), and particulate matter (PM).

261

[1]

262

the primary pollutant contributors in each process design: the boiler in the sugars-to-hydrocarbons design and the methane

263

reformer and dryer in fast pyrolysis design.

264

[2]

265

design, options 1 and 2 are implemented with either 3a) or 3b).

266

[3]

267

feedstock and then released to the atmosphere (see SI for details). No exhaust (or flue gas) from the char combustor is directly

268

discharged to the atmosphere.

We only considered additional emission control options (i.e., emission control technologies and process design modifications) for

We assume that all of the control options are implemented cumulatively for both process designs. In the sugars-to-hydrocarbon

Emissions from the dryer include hot flue gas from the on-site char combustor, which is used to dry the incoming biomass

269 270

While the implementation of these emission control options will change the PTE and therefore impact

271

the applicability of federal regulations, we do not account for any such changes to federally enforceable



272

limitations. Instead, the PTE estimates in this section build directly upon the PTE described in Section 3.1

273

and only account for changes to emissions that result from each control option. Final PTE values will

274

need to be re-evaluated once a final decision is made regarding the control options.

275

3.2.1

276

For the sugars-to-hydrocarbons design, the pollutants that exceed the NSR major source thresholds are

277

CO, SO2, NOx, VOCs, and HAPs, with the boiler contributing the most to these emissions. To reduce these

278

emissions, we considered the cumulative effect of two control technologies: (1) a catalytic oxidizer

279

control technology to reduce CO by 90%, VOCs by 70%, and HAPs (formaldehyde and acetaldehyde, in

280

particular) by 90%;45 followed by (2) a selective catalytic reduction (SCR) system in place of a selective

281

non-catalytic reduction (SNCR) system included in the design to reduce NOx by 88%.46 Despite these

282

additional control technologies, the PTE of several pollutants remained above the major source

283

thresholds; only NOx and VOCs were reduced below their 100 TPY thresholds (see Figure S1 in SI).

284

Since these two control technologies did not reduce the PTE of CO, SO2 and HAPs below their respective

285

major source thresholds, we considered process modifications that could further reduce emissions from

286

the boiler. In the current design, the boiler burns three fuels: (1) lignin from enzymatic hydrolysis, (2)

287

sludge from wastewater treatment, and (3) biogas from anaerobic digestion. Although substituting a

288

natural gas boiler for a biomass boiler could be one feasible strategy to reduce these emissions, there

289

are tradeoffs associated with this option. For example, the sludge has valuable heat content (about 15%

290

of the total heat input to the boiler) and a biomass boiler allows the facility to use this fuel to generate

291

steam rather than disposing of it off-site. Furthermore, the biorefinery will likely want their products to

292

qualify for cellulosic biofuel renewable identification numbers (RINs), which provide an additional

293

economic incentive for selling biofuels that have a GHG reduction relative to petroleum. Replacing the

294

biomass boiler with a natural gas boiler could prevent the produced biofuels from qualifying for RINs

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because CO2 emissions from biomass (including lignin, biogas, sludge) are currently classified as biogenic

296

and therefore do not contribute to the biofuels’ life cycle GHG emissions. As a result, instead of

297

implementing a natural gas boiler, we considered changing the composition of the biomass boiler’s fuel

298

stream to help reduce emissions.

299

For SO2 emissions, we estimated the PTE via the material balance approach, which involved using the

300

process model to determine the sulfur content present in the fuel stream. For all other pollutants, we

301

estimated changes in the boiler’s PTE using the emission factor approach (Activity Factor [AF] x Emission

302

Factor [EF]). We followed the federal guidelines for boilers that combust multiple fuels and assumed

303

year-round usage of the fuel that emits the most of each pollutant (the worst-case fuel). When the lignin

304

fraction is greater than zero, the value of the EF remains unchanged (i.e., equal to the EF for the worst-

305

case fuel (lignin)). However, removing fractions of lignin from the boiler reduces the required heat input

306

capacity of the boiler, which decreases the AF because less fuel is combusted (electricity is instead

307

imported to satisfy the facility’s power requirements). If lignin is completely removed from the boiler’s

308

fuel stream then sludge is the worst-case fuel for HAPs and CO emissions, which changes the EF.

309

Decreasing the lignin content of the boiler’s fuel stream has a substantial impact on the facility’s PTE for

310

CO, HAPs, and SO2 (Figure 3). Furthermore, because the HAP and CO emission factors are much lower

311

for sludge than for lignin, completely diverting lignin considerably decreases these emissions and

312

reduces the PTE below the major source thresholds for CO, SO2 and HAPs.



313

Figure 3. The emissions of three major pollutants—carbon monoxide (CO), total hazardous air pollutants

314

(HAPs), and sulfur dioxide (SO2)—vary depending on the fraction of lignin in the boiler’s fuel (colored lines;

315

left axis). To better visualize the emission reductions that occurs when lignin is completely diverted from

316

the boiler’s fuel stream (0% lignin fraction), we only show results for lignin fractions less than or equal to

317

fifty percent of the amount assumed in the design case. The large decrease in PTE for 0% lignin fraction

318

occurs because the worst-case emission factor changes from lignin to sludge. If all of the lignin is diverted

319

from the boiler’s fuel stream, the facility-wide PTE values for CO, total HAPs, and SO2 are estimated to be

320

below the major source thresholds: 100 TPY for criteria pollutants under the NSR program (dashed grey

321

line) and 25 TPY for total HAPs under the Title V program (dotted grey line). Although the direct emissions

322

from the facility decrease with lower lignin content, the amount of electricity imported (right axis, black

323

line) increases. Note that these emissions were calculated after implementing two additional controls on

324

the boiler: a catalytic oxidizer and higher efficiency flue gas desulfurization system.

325 326

One additional benefit of this strategy is that the lignin diverted away from the boiler could be used to

327

generate value-added co-products (e.g., chemicals)47,48 or pelleted and sold for off-site use. However,

328

the lower heat content of the non-lignin fuel streams would impact the biorefinery’s energy balance.

329

While the original sugars-to-hydrocarbons design is able to generate enough on-site steam and

330

electricity to meet the biorefinery’s energy demands, diverting lignin would require the facility to import 20 ACS Paragon Plus Environment

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331

electricity from the grid to satisfy its power requirements (it would not need to make any changes to

332

satisfy the facility’s steam demand). This tradeoff could affect the life cycle GHG emissions of the

333

biofuels produced.

334

3.2.2

335

Our preliminary estimate of the PTE for the fast pyrolysis design indicates that NOx, PM, and SO2 will

336

likely exceed the NSR major source thresholds. As a result, we explored three additional, pollutant-

337

specific emission control technologies. We did not explore any process modifications for the fast

338

pyrolysis design because we found that emission control technologies could reduce the PTE below major

339

source thresholds.

340

In the fast pyrolysis design, the dryer is a significant source of SO2 and PM emissions and the methane

341

reformer is a major contributor of NOx emissions. As a result, we considered three additional emission

342

controls: 1) an FGD control system upstream of the dryer exhaust to reduce its SO2 emissions by 92%,49

343

2) a baghouse on the dryer to capture 99%50 of the PM from the vent stream, and 3) an SNCR control

344

technology on the methane reformer to reduce its NOx by 45%.51 The installation of these controls

345

technologies could reduce the PTE of SO2, PM, and NOx below their respective major source thresholds

346

(see Figure S2 in SI) and allow the fast pyrolysis design to achieve minor source classification.

347

4 Discussion

348

Since our results are specific to two feasibility-level process designs and further iterations of these

349

designs may result in process modifications, our results should be considered preliminary. There are

350

significant uncertainties inherent in our analysis due to a lack of specific design parameters and the

351

subsequent use of general procedures and best-available data sources for estimating emissions. To

Reducing Emissions in the Fast Pyrolysis Design



352

more accurately assess the final PTE, future work will need to examine the final process designs and

353

make use of operational data from pilot-scale or larger facilities, when available.

354

Although it may be feasible for biorefineries using these two designs to achieve minor source

355

classifications, these determinations might not be practically achievable or cost effective. For instance,

356

while catalytic oxidizers are currently used to reduce CO emissions from gas-fired boilers, their use on

357

biomass-fired boilers has not been proven in a commercial setting. Furthermore, while our prior work

358

has shown that the cost is insignificant of implementing emission controls to achieve compliance with

359

applicable NSPS and NESHAP regulations in the sugars-to-hydrocarbons design,10 installing BACT

360

emission controls could have a significant impact on the economics of the biorefinery (see Bhatt et al.10

361

for cost estimates). A detailed evaluation of how the costs of incorporating the minor-source-

362

classification strategies explored here compare to the costs of being classified as a major source is

363

beyond the scope of this analysis. However, the additional control options analyzed here could be cost

364

prohibitive and should be explored in future research.

365

In addition, the size of a biorefinery can have a significant impact on the cost, emissions, and regulatory

366

requirements. We evaluated these two biorefineries according to the size specified in the process

367

designs, and we do not explore the implications of biorefinery sizing in this work. However, because

368

major source thresholds are independent of facility size, it is possible that a minor source classification

369

could be achieved without the need for additional emission controls, merely by designing the facility at a

370

smaller scale. Such a strategy would have other cost implications, e.g., capital costs, financing options,

371

and economies of scale, which should be considered in a complete cost-benefit analysis.

372

One of the challenges we encountered while estimating the PTE for these two process designs was the

373

lack of data available to estimate the emission factors for some novel processes and non-traditional

374

fuels. In these cases, facilities are allowed to use multiple data sources, including (but not limited to) 22 ACS Paragon Plus Environment

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EPA’s databases, engineering publications, performance test data from the same or a similar emission

376

unit, and manufacturing’s performance tests to develop emission factors. For example, the worst-case

377

emission factors for non-fossil-powered boilers are not well documented so we used EPA’s AP-42 report

378

to identify the most representative emission factors. In addition, no estimates of VOC emissions exist

379

publicly for some specific biofuel conversion processes, e.g., aerobic respiration of cellulosic and

380

hemicellulosic sugars to long-chain fatty acids using enzymatic hydrolysis, so we estimated these

381

emissions using values from publically available air permits with similar processes.

382

As more biorefineries become operational, many will be required to perform stack testing to ensure that

383

the emissions from their facility do not exceed their permit limitations, and these data should eventually

384

make their way into EPA’s emission factor databases. Thus, as more projects become operational and

385

the amount of stack testing data increases, the uncertainty in the PTE estimates for these new processes

386

should be reduced. However, if regulatory agencies were able to decrease the uncertainty associated

387

with the future determination of emission factors for novel processes and non-traditional fuels, either

388

through further research studies or clearer regulatory guidelines, developers could more accurately

389

estimate PTE values for biorefineries and other emerging industries. Such work may help mitigate the

390

uncertainty associated with the air permitting regulations and encourage the development of new

391

biorefineries.

392

The duration of the air permitting process could impact biorefinery developers’ investment risks and

393

potentially the cost of produced fuels. However, the challenges associated with this process are often

394

overlooked. Our work may help regulators and biorefinery developers understand the source and type

395

of emissions, along with which federal regulations might be applicable to various unit operations. Our

396

analysis may also assist biorefinery developers with assessing their PTE, permitting classification, and

397

additional control options to mitigate permitting risks. This information is particularly important for the



398

deployment of new technologies, which typically incur longer permitting processes as developers work

399

to assure regulators that air quality regulations and permitting conditions can be met.

400

5 Acknowledgements

401

This work was funded by the U.S. Department of Energy’s Bioenergy Technologies Office (agreement

402

number 22588). The authors would like to thank Bob Sidner, Mae Thomas, and Jason Renzaglia of

403

Eastern Research Group for technical support and Daniel Inman and Ryan Davis of the National

404

Renewable Energy Laboratory for contributions and comments. The U.S. Government retains and the

405

publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a

406

nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this

407

work, or allow others to do so, for U.S. Government purposes.

408

6 Supporting Information

409 410 411

SI−S.1: Process Design Summaries; SI−S.2: Supplementary Methods; SI−S.3: Supplementary Results; S1S.4: Supplementary Discussion

412

7 Author Contributions

413

A.E. and A.B. contributed equally to this work; A.E. wrote the manuscript and assisted with the analysis;

414

A.B. performed the chemical process modeling and assisted with writing the manuscript; Y.Z. and G.H.

415

supervised the analysis and assisted with writing the manuscript.

416

8 References

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