airenergyrfa_20190418_clean_4.pdf

OVERVIEW INFORMATION

U.S. Environmental Protection Agency Office of Research and Development Science to Achieve Results (STAR) Program

CHEMICAL MECHANISMS TO ADDRESS NEW

CHALLENGES IN AIR QUALITY MODELING

This is the initial announcement of this funding opportunity.

Funding Opportunity Numbers:

EPA-G2019-STAR-C1, Chemical Mechanisms to Address New Challenges in Air Quality Modeling EPA-G2019-STAR-C2, Early Career: Chemical Mechanisms to Address New Challenges in Air Quality Modeling

Catalog of Federal Domestic Assistance (CFDA) Number: 66.509

Solicitation Opening Date: May 8, 2019 Solicitation Closing Date: June 24, 2019: 11:59:59 pm Eastern Time

Table of Contents

SUMMARY OF PROGRAM REQUIREMENTS

Synopsis of Program Award Information Eligibility Information Application Materials Agency Contacts

I. FUNDING OPPORTUNITY DESCRIPTION

A. Introduction

B. Background C. Authority and Regulations D. Specific Areas of Interest/Expected Outputs and Outcomes E. References F. Special Requirements

II. AWARD INFORMATION

III. ELIGIBILITY INFORMATION

A. Eligible Applicants B. Cost Sharing C. Other

IV. APPLICATION AND SUBMISSION INFORMATION

A. Grants.gov Submittal Requirements and Limited Exception Procedures B. Application Package Information C. Content and Form of Application Submission D. Submission Dates and Times E. Funding Restrictions F. Submission Instructions and Other Submission Requirements

V. APPLICATION REVIEW INFORMATION

A. Peer Review B. Relevancy Review C. Past Performance History Review D. Human Subjects Research Statement (HSRS) Review E. Funding Decisions F. Additional Provisions for Applicants Incorporated into the Solicitation

VI. AWARD ADMINISTRATION INFORMATION

A. Award Notices B. Disputes C. Administrative and National Policy Requirements

VII. AGENCY CONTACTS

Access Standard STAR Forms (https://www.epa.gov/research-grants/research-funding-opportunities-how-apply-and-required-forms) View research awarded under previous solicitations (https://www.epa.gov/research-grants/research-grant-areas)

SUMMARY OF PROGRAM REQUIREMENTS

Synopsis of Program:

The U.S. Environmental Protection Agency (EPA), as part of its Science to Achieve Results (STAR) program, is seeking applications proposing research to improve air quality models relevant to ozone, particulate matter (PM), regional haze, air toxics, and emerging pollutants.

Specifically, this Request for Applications (RFA) is seeking research on the development of the component of an air quality model that represents the relevant atmospheric chemical reactions, which is known in this field of modeling as “the chemical mechanism.” The RFA seeks research on:

1. Development of data, methods, and software tools for generating explicit chemical mechanisms that a) have a coherent and integrated treatment of gas, aerosol, aqueous, and heterogenous chemistry, b) can be easily updated to reflect evolving kinetic, mechanistic, and theoretical knowledge and understanding, and c) are applicable to a wide range of atmospheric concentration regimes and environmental conditions;

2. Development and evaluation of algorithms, numerical techniques and software tools to reduce (i.e., simplify) detailed, integrated chemical mechanisms into application-specific condensed mechanisms appropriate for use in global and regional air quality models; and https://www.epa.gov/research-grants/research-funding-opportunities-how-apply-and-required-forms https://www.epa.gov/research-grants/research-funding-opportunities-how-apply-and-required-forms https://www.epa.gov/research-grants/research-grant-areas https://www.epa.gov/research-grants/research-grant-areas

3. Applications of new condensed mechanisms generated for broad applications or for specific conditions in global and regional air quality models to investigate air quality research topics relevant to air quality management in the United States.

The focus of this solicitation is on the development of chemical mechanisms relevant over multiple regimes (a wide range of concentrations, oxidant ratios, and temperatures, and multiple phases) and spatiotemporal scales within a framework that can generate mechanisms for current air quality assessments and have the flexibility to generate updated mechanisms as understanding of atmospheric chemistry evolves and new concerns emerge.

This solicitation provides the opportunity for the submission of applications for projects that may involve human subjects research. Human subjects research supported by the EPA is governed by EPA Regulation 40 CFR Part 26 (Protection of Human Subjects). This includes the Common Rule at subpart A and prohibitions and additional protections for pregnant women and fetuses, nursing women, and children at subparts B, C, and D. Research meeting the regulatory definition of intentional exposure research found in subpart B is prohibited by that subpart in pregnant women, nursing women, and children. Research meeting the regulatory definition of observational research found in subparts C and D is subject to the additional protections found in those subparts for pregnant women and fetuses (subpart C) and children (subpart D). All applications must include a Human Subjects Research Statement (HSRS, as described in Section IV.C.7.c of this solicitation), and if the project involves human subjects research, it will be subject to an additional level of review prior to funding decisions being made as described in Sections V.D and V.E of this solicitation.

Guidance and training for investigators conducting EPA-funded research involving human subjects may be obtained here:

https://www.epa.gov/osa/basic-information-about-human-subjects-research-0 https://www.ecfr.gov/cgi-bin/text-idx?tpl=/ecfrbrowse/Title40/40cfr26_main_02.tpl

The STAR Program’s goal is to stimulate and support scientific and engineering research that advances EPA’s mission to protect human health and the environment. It is a competitive, peer-reviewed, extramural research program that provides access to the nation’s best scientists and engineers in academic and other nonprofit research institutions. STAR funds research on the environmental and public health effects of air quality, environmental changes, water quality and quantity, hazardous waste, toxic substances, and pesticides.

In addition to regular awards, this solicitation includes the opportunity for early career awards.

The purpose of the early career award is to fund research projects smaller in scope and budget by early career PIs. Please see Section III of this Request for Applications (RFA) for details on the early career eligibility criteria.

Award Information:

Anticipated Type of Award: Grant or cooperative agreement Estimated Number of Awards: Approximately 10 awards, 5 regular and 5 early career awards Anticipated Funding Amount: Approximately $6 million total for all awards https://www.epa.gov/osa/basic-information-about-human-subjects-research-0 https://www.ecfr.gov/cgi-bin/text-idx?tpl=/ecfrbrowse/Title40/40cfr26_main_02.tpl

Potential Funding per Award: Up to a total of $800,000 for regular awards, and up to a total of $400,000 for early career awards, including direct and indirect costs, with a maximum duration of three years. Cost-sharing is not required. Applications with budgets exceeding the total award limits will not be considered.

Eligibility Information:

Public and private nonprofit institutions/organizations, public and private institutions of higher education, and hospitals located in the U.S., state and local governments, Federally Recognized Indian Tribal Governments, and U.S. territories or possessions are eligible to apply. Special eligibility criteria apply to the early career award portion of this RFA. See full announcement for more details.

Application Materials:

To apply under this solicitation, use the application package available at Grants.gov (for further submission information see Section IV.F. “Submission Instructions and other Submission Requirements”). Note: With the exception of the current and pending support form (available at https://www.epa.gov/research-grants/research-funding-opportunities-how-apply-and-required-forms), all necessary forms are included in the electronic application package. Make sure to include the current and pending support form in your Grants.gov submission.

If your organization is not currently registered with Grants.gov, you need to allow approximately one month to complete the registration process. Please note that the registration process also requires that your organization have a unique entity identifier (e.g., ‘DUNS number’) and a current registration with the System for Award Management (SAM) and the process of obtaining both could take a month or more. Applicants must ensure that all registration requirements are met in order to apply for this opportunity through Grants.gov and should ensure that all such requirements have been met well in advance of the submission deadline. This registration, and electronic submission of your application, must be performed by an authorized representative of your organization.

If you do not have the technical capability to utilize the Grants.gov application submission process for this solicitation, see Section IV.A below for additional guidance and instructions.

Agency Contacts:

Technical Contact: Serena Chung; phone: 202-564-6069; email: chung.serena@epa.gov Eligibility Contact: Ron Josephson; phone: 202-564-7823; email: josephson.ron@epa.gov Electronic Submissions Contact: Debra M. Jones; phone: 202-564-7839; email:

jones.debram@epa.gov

I. FUNDING OPPORTUNITY DESCRIPTION

A. Introduction https://www.epa.gov/research-grants/research-funding-opportunities-how-apply-and-required-forms mailto:reese.david@epa.gov mailto:josephson.ron@epa.gov mailto:jones.debram@epa.gov

The Environmental Protection Agency (EPA), Office of Research and Development (ORD), in cooperation with the ORD Air and Energy Research Program, announces an extramural funding competition seeking applications proposing research on improving air quality models relevant to ozone, particulate matter (PM), regional haze, air toxics, and emerging pollutants. Specifically, this Request for Applications (RFA) is seeking research on the development of the component of an air quality model that represents the relevant atmospheric chemical reactions, which is known in this field of modeling as “the chemical mechanism.” The RFA seeks research on:

1. Development of data, methods, and software tools for generating explicit chemical mechanisms that a) have a coherent and integrated treatment of gas, aerosol, aqueous, and heterogenous chemistry, b) can be easily updated to reflect evolving kinetic, mechanistic, and theoretical knowledge and understanding, and c) are applicable to a wide range of atmospheric concentration regimes and environmental conditions;

2. Development and evaluation of algorithms, numerical techniques and software tools to reduce (i.e., simplify) detailed, integrated chemical mechanisms into application-specific condensed mechanisms appropriate for use in global and regional air quality models; and

3. Applications of new condensed mechanisms generated for broad applications or specific conditions in global and regional air quality models to investigate air quality research topics relevant to air quality management in the United States.

The focus of this solicitation is on the development of chemical mechanisms relevant over multiple regimes (a wide range of concentrations, oxidant ratios, and temperatures, and multiple phases) and spatiotemporal scales within a framework that can generate chemical mechanisms for current air quality assessments and have the flexibility to generate updated mechanisms as understanding of atmospheric chemistry evolves and new concerns emerge.

In addition to regular awards, this solicitation includes the opportunity for early career awards.

The purpose of the early career award is to fund research projects smaller in scope and budget by early career PIs. Please see Section III of this RFA for details on the early career eligibility criteria.

EPA recognizes that it is important to engage all available minds to address the environmental challenges the nation faces. At the same time, EPA seeks to expand the environmental conversation by including members of communities which may have not previously participated in such dialogues to participate in EPA programs. For this reason, EPA strongly encourages all eligible applicants identified in Section III, including minority serving institutions (MSIs), to apply under this opportunity.

For purposes of this solicitation, the following are considered MSIs:

1. Historically Black Colleges and Universities, as defined by the Higher Education Act (20 U.S.C. § 1061). A list of these schools can be found at Historically Black Colleges and Universities;

https://sites.ed.gov/whhbcu/one-hundred-and-five-historically-black-colleges-and-universities/ https://sites.ed.gov/whhbcu/one-hundred-and-five-historically-black-colleges-and-universities/

2. Tribal Colleges and Universities (TCUs), as defined by the Higher Education Act (20 U.S.C. § 1059c(b)(3) and (d)(1)). A list of these schools can be found at American Indian Tribally Controlled Colleges and Universities;

3. Hispanic-Serving Institutions (HSIs), as defined by the Higher Education Act (20 U.S.C. § 1101a(a)(5)). A list of these schools can be found at Hispanic-Serving Institutions;

4. Asian American and Native American Pacific Islander-Serving Institutions; (AANAPISIs), as defined by the Higher Education Act (20 U.S.C. § 1059g(a)(2)). A list of these schools can be found at Asian American and Native American Pacific Islander-Serving Institutions; and

5. Predominately Black Institutions (PBIs), as defined by the Higher Education Act of 2008, 20 U.S.C. 1059e(b)(6). A list of these schools can be found at Predominately Black Institutions.

B. Background

Multi-pollutant air quality models (AQMs) are an essential tool in advancing scientific knowledge of air quality as well as helping to identify sources of air quality problems and potential strategies to reduce exposure to harmful air pollutants. These models are based on scientific first principles, account for real world environmental conditions, and incorporate environmental data to simulate chemical and physical processes dictating the fate of airborne pollutants. They enable the use of robust research and scientific analysis to inform policy at the local, state, national, and international scales and compliance efforts by industry to meet regulatory requirements. The most widely used AQMs are publicly-available, community models that continue to evolve through improvements provided by users and developers from academia, industry, government, and the broader international scientific community. This RFA is intended to support the atmospheric science community’s efforts to improve current and next generation AQMs used to inform air quality management.

Current AQMs were originally developed when air quality management and scientific studies focused on extreme pollution episodes in urban areas. As U.S. anthropogenic emissions have declined substantially since AQMs were first developed in the 1980s and 1990s, and the ozone and particulate matter National Ambient Air Quality Standards (NAAQS) have been tightened, accurate model prediction at lower and background concentrations has become increasingly important, requiring improvement in modeling the influence of long-range transport and emissions from more diverse sources. AQMs tend to overestimate surface ozone concentrations, especially at locations where observed concentrations are low (Appel et al., 2017), and underestimate ozone sensitivity to decreased oxides of nitrogen (NOx) emissions (Foley et al., 2015). Lack of consistent agreement between measured and modeled oxidant concentrations suggests errors in the modeling of oxidation chemistry among other factors that contribute to model errors and biases (Griffith et. al., 2016). At the same time, accurate prediction of fine particulate matter (PM2.5) using AQMs, necessary for developing strategies to achieve the PM2.5 NAAQS and compliance with the Regional Haze Rule, has continued to be a challenge, partly due to the complexities associated with PM formation and chemical evolution with time.

https://sites.ed.gov/whiaiane/tribes-tcus/tribal-colleges-and-universities/ https://sites.ed.gov/whiaiane/tribes-tcus/tribal-colleges-and-universities/ https://www2.ed.gov/about/offices/list/ope/idues/hsi-eligibles-2016.pdf https://www.google.com/maps/d/viewer?mid=1XVkOWKMDORm53pvU0L8EPsrJC94&msa=0&ie=UTF8&t=m&z=3&source=embed&ll=40.58644586187277%2C-148.28228249999984 https://www.google.com/maps/d/viewer?mid=1wlIi3j7gtlNq_w-0NKAb2bF2VmY&ie=UTF&msa=0&ll=37.35160769312532%2C-96.17229800000001&z=4

A condensed chemical mechanism is a critical component of multi-pollutant air quality models.

A chemical mechanism specifies a series of chemical reaction pathways and reaction rates that are important for predicting concentrations of targeted pollutants. Explicitly tracking the many thousands of chemical compounds emitted in the atmosphere and their reactions is too computationally burdensome for AQM applications. For example, explicit mechanisms generated from the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) can contain millions of species and reactions (Aumont et al., 2005). The semi-explicit Master Chemical Mechanism (MCM) includes thousands of species and reactions to represent chemical degradation of ~140 volatile organic compounds (VOCs) (Jenkin et al., 1997;

http://mcm.leeds.ac.uk/MCM). A condensed chemical mechanism represents the complexities with only tens or hundreds of “lumped” or representative species and reactions. Only compounds considered to be most relevant are included; and compounds of similar structure and/or reactivities (e.g., reaction rates with OH) are grouped together. Multiple reactions can be reduced (i.e., simplified) into a few rate-determining steps if the intermediate compounds are thought to be unimportant. In essence, condensed chemical mechanisms synthesize detailed chemical information into a manageable set of species and reactions that can be implemented by computer programs to numerically simulate pollutant concentrations for regional or global domains.

EPA and the California Air Resources Board (CARB) funded major programs in the 1980 - 1990’s to develop the condensed chemical mechanisms that are the foundation for many mechanisms still being used today. These mechanisms focused on rapid ozone formation in a chemical regime of highly polluted urban atmospheres during summertime and were highly parameterized to reproduce measurements of ozone under these conditions (Gery et al., 1988;

Carter et al., 1986). Unknown chemical processes in the mechanism were fit to smog chamber data, and grouping and removal of species were performed for chemicals/processes that did not impact predictions under these conditions. While updates to these earlier mechanisms have been made since their initial derivation, the methodology for condensation is largely intact (Yarwood et al., 2010; Carter, 2010). Chemical mechanisms did not initially consider secondary organic aerosol (SOA), an important component of PM2.5, or hazardous air pollutants. Today, with a few exceptions, AQMs use highly empirical SOA parameterizations that have been added on top of gas-phase mechanisms by introducing semi-volatile and intermediate-volatile surrogate species for which the reactions and chemical identities are disconnected from those of gas-phase and inorganic aerosol species. In addition, aqueous aerosol (Pye et al. 2017; McNeill et al. 2012), in-cloud (Fahey et al 2017; Carlton et al. 2008), and other heterogeneous pathways contribute significantly to SOA. Recent work has also highlighted the interconnected nature of organic and inorganic systems. For example, understanding the fate of organic nitrates is important for understanding NOx, cycling of reactive nitrogen compounds (NOy), and ozone formation (Fisher et al., 2016); nitrogen deposition as a stressor for terrestrial and marine ecosystems (Thompson et

al. 2015; Cornell, 2011; Zhang et al., 2012); and organic aerosol (Pye et al. 2015). Chemical mechanisms with coherent and integrated treatment across multiple gas and particle endpoints are needed to properly describe the interconnected atmospheric system.

AQMs are being utilized for a wider variety of applications using condensed mechanisms that were developed and calibrated more than 2-3 decades ago to represent conditions that reflect substantially changed atmospheric environment and emission sources. AQM applications now http://mcm.leeds.ac.uk/MCM span a wide range of concentrations, VOC-to-NOx ratios, and temperatures to cover urban, rural, and remote environments for warm and cold seasons. As anthropogenic emissions decline, quantifying absolute and relative background contributions, such as those from biogenic VOC, soil NOx, and long-range transport, are increasingly important (Guo et al., 2018), demanding better condensed chemical mechanisms that are applicable for low concentrations and novel environments. AQMs are also used to simulate regional haze in the U.S., where the Regional Haze Rule requires States to quantify the natural level of visibility, thus also requiring capability to accurately simulate speciated PM concentrations at low levels. On the other end of the spectrum, wildfires produce highly polluted conditions and emit many species that have been understudied with respect to their SOA and ozone forming potential (Jen et al., 2019). Several areas in the U.S. experience severe wintertime pollution (Matichuk et al., 2017; Franchin et al., 2018; Kelly et al., 2018; Rappenglück et al., 2014; Shakya and Peltier, 2013). Historically most field campaigns have focused on the summertime, so the development of chemical mechanisms as well as other model processes in AQMs has catered towards representing summertime conditions rather than the darker, colder regimes typical of winter. While recent field campaigns (e.g., 2013 DISCOVER-AQ, 2013 Uinta Basin Winter Ozone Study, 2015 WINTER, 2017 Utah Winter Fine Particle Study) have expanded the understanding of some of these wintertime air quality issues, representation of many wintertime processes in AQMs remains uncertain.

Improving the representation of wintertime chemistry and other related processes in AQMs, e.g.

shifts in gas-particle partitioning and heterogeneous chemistry under cold conditions, a wide range of insolation rates and presences of supercooled water clouds and ice clouds near the surface, will help AQMs more effectively capture air quality issues throughout the year under a wider range of conditions. A framework for creating chemical mechanisms applicable over a wide variety of regimes and phases would ideally have the flexibility to represent chemistry under typical as well as extreme events.

Mechanistic formulation of SOA formation is increasingly needed to properly translate laboratory information to AQMs and fully identify the myriad processes that determine whether emission changes will increase or decrease PM2.5 (McFiggans et al., 2019). Several recently identified pathways to SOA formation have changed the conceptual understanding of what regulates SOA formation in different emission control scenarios. Isoprene aerosol, when represented as soluble uptake of isoprene epoxydiol intermediates followed by acid-catalyzed reactions, leads to SOA that is sensitive to sulfur oxides (SOx) controls (Pye et al. 2013). Large changes in anthropogenic emissions also mean that certain pathways (e.g., autoxidation) may be increasingly important and affect our interpretation of how SOA abundance is modulated. For example, recent work shows that autoxidation leading to highly oxidized molecule (HOM) formation significantly decreases the dependency of SOA on preexisting organic aerosol and that SOA from autoxidation is modulated by NO abundance (Pye et al. 2019). Solvent emissions from volatile chemical products (VCP) may be an important contributor to organic aerosol in anthropogenically dominated locations (McDonald et al. 2018); however, representing the SOA from them is difficult because chemical mechanisms generally lack realistic surrogates for their emissions and transformation products. While intermediate volatility organic compound (IVOC) emissions from combustion sources (vehicles, biomass burning, etc.) have been more widely recognized (Gentner et al., 2017; Jen et al., 2019), they are still not explicitly considered in gas-phase mechanisms.

Reactive halogen species (chlorine, bromine, iodine) in the atmosphere are known to influence a range of chemical systems including ozone formation (Simpson et al., 2015) and mercury cycling (Horowitz et al., 2017). Halogens are released to the atmosphere primarily from the ocean surface and have been implemented into both regional and global AQMs to better represent the chemistry of halogen-affected systems (Sarwar et al., 2015; Sherwen et al., 2016a,b). However, effectively representing both the rapid rates of halogen reactions and the longer time scale chemistry required for hemispheric/global processes poses a challenge for existing chemical mechanisms (Gantt et al., 2017). In addition to halogens, the marine atmosphere is also home to many other complex chemical systems that can be relevant for regional haze and for air quality in coastal areas, including sulfate production from biologically produced dimethyl sulfide (DMS) emissions and organic aerosol emissions from sea spray (Gantt et al., 2015). Due to the high humidity of air over the oceans and unique set of emissions sources, marine environments represent fundamentally different regimes of atmospheric chemistry and physics for AQMs to handle compared to those found over land.

While the majority of air pollution modeling in the past has focused on ozone and PM2.5, other gas, aqueous, and aerosol species of potential importance to human and ecological health are poorly characterized, if included at all, in current atmospheric chemical mechanisms. For example, formaldehyde is the highest cancer driver among hazardous air pollutants (2014 National Air Toxic Assessment; released August 22, 2018; https://www.epa.gov/national-air-toxics-assessment/2014-nata-assessment-results) and is commonly underpredicted by 30% or more in all AQMs (Marvin et al., 2017). Soluble organic nitrogen species produced in the atmosphere can be an important component of nitrogen deposition to ecosystems (Cornell et al., 2011) but the high degree of condensation in current chemical mechanisms does not allow an appropriate description of the chemistry or solubility of atmospheric nitrates. Studying the impact and atmospheric lifetime of new industrial chemicals, such as per- and polyfluorinated alkyl substances or emissions from biomass farming, is generally impossible using AQMs due to the absence of detail in current chemical mechanisms. Methods for developing new chemical mechanisms must have the flexibility to easily include accurate representation of emerging pollutants as we learn more about protecting human health and the environment and as new industries and practices evolve.

Despite many updates to incorporate new kinetic information and mechanistic knowledge, mechanisms have remained comparatively static relative to the increasing knowledge of atmospheric chemistry, growing information on more compounds at lower concentrations measured by increasingly sophisticated analytical techniques, the ability to conduct laboratory experiments at more ambient-relevant concentrations, and the recent advances in computational techniques and resources. Updating existing chemical mechanisms is a slow and tedious process both in terms of incorporating new knowledge and software engineering. Efforts to improve mechanisms are often constrained by the lumping scheme from which the mechanisms were originally developed. When new reaction pathways and intermediate compounds are found to be important, such as those mentioned above, the extent to which they are represented by lumped species and condensed reaction steps in the mechanisms can be difficult to determine. Computer codes are manually updated in ways that are tedious, prone to errors, and difficult to track.

Research is needed to develop comprehensive chemical mechanisms in a way that has the flexibility to easily incorporate new knowledge, and to apply them in an efficient manner in AQMs, so that advances in knowledge can be utilized to improve understanding of the atmosphere and inform air quality management.

Kaduwela et al. (2015) proposed an approach for development of chemical mechanisms for use in AQMs that would address current needs and be adaptable to new knowledge and emerging issues. The approach entails four broad stages: 1) compilation of theoretical, mechanistic, and kinetic knowledge and data; 2) automated computer generation of comprehensive, explicit mechanisms that reflect the state of science; 3) evaluation of mechanisms against experimental data, for subset of a mechanism of selected species as well as for the entire integrated mechanism; and 4) systematic reduction of a detailed, integrated mechanism into application-specific condensed chemical mechanisms practical for use in AQMs. While widely used in engineering research (Battin-Leclerc et al., 2011; Gao et al., 2016; Van de Vijver et al. 2015), development of computer-automated mechanism generation in atmospheric chemistry has been comparatively limited (Aumont et al., 2005; Khan et al., 2009). Such an approach requires an overarching need for improving and extending structure-activity relationships (SARs) for predicting the relevant properties and reactions, especially for multi-functionalized and highly oxidized molecules (Vereecken et al., 2018). Once developed, detailed mechanisms can provide fundamental insights on chemistry; however, considering all species and reactions in detailed chemical mechanisms is computationally impractical for AQM applications. Some condensed mechanisms are more appropriate for broad applications, e.g., annual simulations for the entire continental United States, while others are more suited for targeted applications, e.g., wintertime episodes, marine-influenced environments, summertime in the southeastern U.S. Depending on background concentrations, emissions profiles, sources from long-range transport, meteorological conditions, and pollutants of interest, different sets of chemical species and reactions are relevant. Systematic mechanism reduction techniques using predefined algorithms and user-transparent software tools would provide a consistent, sustained approach to updating condensed mechanisms for broad applications and specific conditions by AQMs. Several chemical mechanism reduction methods that can be computer automated are commonly used in combustion research (Tomlin et al. 1997). Applications in atmospheric chemistry have been limited (Xia et al., 2009; Watson et al., 2008; Whitehouse et al., 2004a,b) and more research is needed to refine existing, or develop new, methodologies and software tools.

A critical component of the development of both detailed and condensed mechanisms is the evaluation against laboratory data (Jeffries et al., 1992; Carter and Lurmann, 1991) and field data to demonstrate their credibility and document their performance under atmospherically relevant conditions. The ability of AQMs to accurately predict concentrations and source contributions in the ambient atmosphere without compensating errors is complicated by the need for accurate predictions of emissions and physical processes such as boundary layer mixing, entrainment from the free troposphere, deposition, stratospheric intrusion, and long-range transport.

Understanding the abilities and limitations of chemical mechanisms in AQMs to predict ambient concentrations requires quantifying uncertainties in modeling of other processes that interact with how pollutants are chemically transformed in the atmosphere.

C. Authority and Regulations

The authority for this RFA and resulting awards is contained in the Clean Air Act, 42 U.S.C.

7403, Section 103(b)(3).

For research with an international aspect, the above statutes are supplemented, as appropriate, by the National Environmental Policy Act, Section 102(2)(F).

Note that a project’s focus is to consist of activities within the statutory terms of EPA’s financial assistance authorities; specifically, the statute(s) listed above. Generally, a project must address the causes, effects, extent, prevention, reduction, and elimination of air pollution, water pollution, solid/hazardous waste pollution, toxic substances control, or pesticide control depending on which statute(s) is listed above. Further note applications dealing with any aspect of or related to hydraulic fracking will not be funded by EPA through this program.

Additional applicable regulations include: 2 CFR Part 200, 2 CFR Part 1500, and 40 CFR Part 40 (Research and Demonstration Grants).

D. Specific Areas of Interest/Expected Outputs and Outcomes Note to applicant: The term “output” means an environmental activity, effort, and/or associated work products related to an environmental goal or objective, that will be produced or provided over a period of time or by a specified date. The term “outcome” means the result, effect or consequence that will occur from carrying out an environmental program or activity that is related to an environmental or programmatic goal or objective.

The activities to be funded under this announcement support EPA’s FY 2018-22 Strategic Plan (https://www.epa.gov/planandbudget/strategicplan.html). Activities to be funded under this announcement support Goal 3: Rule of Law and Process, Objective 3.3: Prioritize Robust Science, of EPA’s FY 2018-22 Strategic Plan. Awards made under this announcement will further EPA’s priorities supporting robust science for Air Quality. Specifically, the Agency is soliciting research that will enable and contribute to sustained development of chemical mechanisms for use in global and regional air quality models (AQMs) that can be used to inform air quality management. To sustain development, methodologies and software tools need to be open source; straightforward to update with new understanding, knowledge and data; easy to incorporate into AQMs; transparent to users of chemical mechanisms and AQMs; and have well-documented provenance. All applications must be for projects that support the goal and objective identified above.

EPA also requires that grant applicants adequately describe environmental outputs and outcomes to be achieved under assistance agreements (see EPA Order 5700.7A1, Environmental Results under Assistance Agreements, https://www.epa.gov/grants/epa-order-57007a1-epas-policy-environmental-results-under-epa-assistance-agreements). Applicants must include specific statements describing the environmental results of the proposed project in terms of well-defined outputs and, to the maximum extent practicable, well-defined outcomes that will demonstrate how the project will contribute to the priorities described above.

https://www.epa.gov/planandbudget/strategicplan.html https://www.epa.gov/grants/epa-order-57007a1-epas-policy-environmental-results-under-epa-assistance-agreements https://www.epa.gov/grants/epa-order-57007a1-epas-policy-environmental-results-under-epa-assistance-agreements

Applicants for regular awards should address at least two of the three research areas described below. Regular award applications that do not address a minimum of two research areas may not be rated as highly as those that do (under the Section V.A.2 Responsiveness criteria). Early career applicants should address at least one of the first two research areas. Early career applications that do not address at least one of the first two research areas may not be rated as highly as those that do (under the Section V.A.2 Responsiveness criteria). Applications that address other research areas in addition to those identified below will not necessarily be rated more highly than those that do not.

1. How can the important chemical processes relevant to ozone, PM, regional haze, and air toxics be represented in explicit chemical mechanisms with a coherent and integrated treatment of gas, aerosol, aqueous and heterogenous chemistry accounting for both man-made and naturally occuring substances and reactions and applicability to a wide range of atmospheric concentrations and environmental conditions? Of the thousands of compounds in the atmosphere, such as SOA precursors, halogenated compounds, air toxics, and multifunctional, highly oxidized compounds, what are the most important compounds that should be represented in the chemical mechanisms? What methods can be used and improved to describe the reactions and physiochemical properties of those compounds? What are the most critical mechanistic, kinetic, and theoretical data needed for evaluation and development of detailed chemical mechanisms?

2. What algorithms, numerical techniques, and software tools can be used for systematic reduction of evolving detailed, integrated chemical mechanisms into application-specific condensed mechanisms appropriate for use in global and regional AQMs? What parameterizations are needed to estimate chemical and physical properties of lumped or representative species? How can the fitness for purpose of these condensed mechanisms be evaluated?

3. What are the implications of using condensed mechanisms generated for broad applications or for specific conditions in global or regional air quality models for simulating ozone, PM, regional haze, or air toxics? For example, do the improved chemical mechanisms improve predictions of ozone and PM2.5 in the Northeastern United States as well as in regimes with large biogenic emissions? In cold weather events?

Downwind of major sources?

For Research Area #1, development of explicit mechanisms may focus on a specific system (e.g., isoprene, halogens, combustion IVOCs); however, the proposed research should include incorporation of the newly developed mechanisms into an existing detailed or condensed, integrated mechanism containing a comprehensive list of ozone and PM2.5 precursors.

For Research Area #2, the proposed research may use explicit chemical mechanisms generated from the results of Research Area #1 or may use other detailed chemical mechanisms.

For Research Areas #1 and #2, any newly developed mechanisms or condensation schemes should include testing against existing field and/or laboratory data to demonstrate their performance. Testing against laboratory data should account for experimental artifacts (e.g., chamber wall loss) that may impact the analysis. Proposed research should apply the newly developed chemical mechanisms in box and/or Lagrangian models to gain insights on chemistry and document performance of the mechanisms against experimental data. Research may include improving existing condensed mechanisms provided that the new versions are developed based on systematic reduction from detailed mechanisms. Development of evaluation protocols and diagnostic tools (e.g., chemical process analysis outputs such as production of Ox, ozone, and other key species; isopleths of key end points and drivers) are strongly encouraged.

For Research Area #3, applicants are strongly encouraged to use new condensed mechanisms generated using the algorithms, techniques, and tools developed in Research Area #2. Also for Research Area #3, applicants are encouraged to investigate topics where current chemical mechanisms have been identified as an important limiting factor for effective representation in AQMs. Proposed analysis should incorporate existing data from long-term networks and intensive field projects. Development of software tools to streamline the incorporation of newly developed condensed mechanisms into open-source AQMs are encouraged.

The focus of this solicitation is on synthesis of data and knowledge, development of methodologies and software tools, and AQM applications. While proposals for laboratory or field studies to collect more data are not the subject of this announcement and therefore not solicited, applicants are strongly encouraged to analyze or synthesize existing laboratory and/or field studies as needed to evaluate the newly developed chemical mechanisms and gain mechanistic understanding of important chemical pathways.

Expected outputs include reports, presentations, and peer-reviewed journal publications describing new methodologies and tools for automated generation of detailed and condensed chemical mechanisms, new insights into atmospheric chemistry, and improved understanding of air quality issues across urban, rural and remote environments. The Agency is primarily interested in funding research that produces open-source software with well-documented provenance. Expected outputs also include:

• Publicly-available and open-source data compilations and software tools for auto-generation of detailed chemical mechanisms in which the tools will flexibly incorporate new chemical understanding to generate new mechanisms.

• Publicly-available detailed chemical mechanisms that reflect current kinetic, mechanistic, and theoretical knowledge and that can be used as benchmarks and as a basis for condensed mechanisms to be used in AQMs.

• Methods/algorithms and open-source tools that create application-specific condensed mechanisms feasible for regional and global AQMs.

• Mechanism evaluation protocols and associated open-source software tools.

The expected outcomes EPA anticipates from this research are improved and sustained development of chemical mechanisms with coherent and integrated treatment of gas, aerosol, aqueous, and heterogenous chemistry for use in global and regional air quality models that will advance understanding of atmospheric chemistry and lead to better air quality management strategies.

To the extent practicable, research applications must embody innovation and sustainability.

Innovation for the purposes of this RFA is defined as the process of making changes; a new method, custom or device. Innovative research can take the form of wholly new applications or applications that build on existing knowledge and approaches for new uses. Research applications must include a discussion on how the proposed research is innovative (see Section IV.C.7.a). The goal of sustainability, derived from the U.S. National Environmental Policy Act of 1969 (NEPA), is to, “create and maintain conditions, under which humans and nature can exist in productive harmony, that permit fulfilling the social, economic, and other requirements of present and future generations.” Research applications must include a discussion on how the proposed research will seek sustainable solutions that protect the environment and strengthen our communities (see Section IV.C.7.a). Reviewers will draw from all of the above-mentioned innovation and sustainability definitions in the review/evaluation process of research applications (see Section V.A).

E. References

1. Appel, K. W., S. L. Napelenok, K. M. Foley, H. O. T. Pye, C. Hogrefe, C., D. J. Luecken, J.

O. Bash, S. J. Roselle, J. E. Pleim, H. Foroutan, W. T. Hutzell, G. A. Pouliot, G. Sarwar, K.

M. Fahey, B. Gantt, R. C. Gilliam, N. K. Heath, D. Kang, R. Mathur, D. B. Schwede, T. L., Spero, D. C. Wong and J. O. Young. Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1, Geoscientific Model Development 10, 1703-1732, doi:10.5194/gmd-10-1703-2017 (2017).

2. Aumont, B., S. Szopa and S. Madronich. Modelling the evolution of organic carbon during its gas-phase tropospheric oxidation: development of an explicit model based on a self generating approach, Atmospheric Chemistry and Physics 5, 2497-2517, doi:10.5194/acp-5- 2497-2005 (2005).

3. Battin-Leclerc, F. E. Blurock, R. Bounaceur, R. Fournet, P. Glaude, O. Herbinet, B. Sirjean and V. Warth. Towards cleaner combustion engines through groundbreaking detailed chemical kinetic models. Chemical Society Reviews 40, 4762-4782 (2011).

4. Carlton, A. G., B. J. Turpin, K. E. Altieri, S. P. Seitzinger, R. Mathur, S. J. Roselle and R. J.

Weber. CMAQ model performance enhanced when in-cloud secondary organic aerosol is included: Comparisons of organic carbon predictions with measurements, Environmental Science & Technology 42(23), 8798–8802, doi:10.1021/es801192n (2008).

5. Carter, W. P. L, F. W. Lurmann, R. Atkinson and A. C. Lloyd. Development and testing of a surrogate species chemical reaction mechanism. Report to the U.S. Environmental Protection Agency, EPA 600/3-86/031, August (1986).

6. Carter, W. P. L and F. W. Lurmann. Evaluation of a detailed gas-phase atmospheric reaction mechanism using environmental chamber data. Atmospheric Environment 25A, 2771-2806 (1991).

7. Carter, W. P. L. Development of the SAPRC-07 chemical mechanism. Atmospheric

Environment 44, 5324-5335, doi:10.1016/j.atmosenv.2010.01.026 (2010).

8. Cornell, S. E. Atmospheric nitrogen deposition: Revisiting the question of the importance of the organic component. Environmental Pollution 159, 2214-2222, doi:10.1016/j.envpol.2010.11.014 (2011).

9. Fahey, K. M., A. G. Carlton, H. O. T. Pye, J. Baek, W. T. Hutzell, C. O. Stanier, K. R. Baker, K. W. Appel, M. Jaoui and J. H. Offenberg. A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1. Geoscientific Model Development 10, 1587-1605. doi: 10.5194/gmd-10-1587-2017 (2017).

10. Foley, K. M., C. Hogrefe, G. Pouliot, N. Possiel, S. J. Roselle, H. Simon and B. Timin.

Dynamic evaluation of CMAQ part I: Separating the effects of changing emissions and changing meteorology on ozone levels between 2002 and 2005 in the eastern U.S.

Atmospheric Environment 103, 247–255, doi: 10.1016/j.atmosenv.2014.12.038 (2015).

11. Fisher, J. A., D. J. Jacob, K. R. Travis, P. S. Kim, E. A. Marais, C. C. Miller, K. Yu, L. Zhu, R. M. Yantosca, M. P. Sulprizio, J. Mao, P. O. Wennberg, J. D. Crounse, A. P. Teng, T. B.

Nguyen, J. M. St. Clair, R. C. Cohen, P. Romer, B. A. Nault, P. J. Wooldridge, J. L. Jimenez, P. Campuzano-Jost, D. A. Day, W. Hu, P. B. Shepson, F. Xiong, D. R. Blake, A. H.

Goldstein, P. K. Misztal, T. F. Hanisco, G. M. Wolfe, T. B. Ryerson, A. Wisthaler and T.

Mikoviny. Organic nitrate chemistry and its implications for nitrogen budgets in an isoprene-and monoterpene-rich atmosphere: constraints from aircraft (SEAC4RS) and ground-based (SOAS) observations in the Southeast US, Atmospheric Chemistry and Physics 16, 5969- 5991, doi:10.5194/acp-16-5969-2016 (2016).

12. Franchin, A., D. L. Fibiger, L. Goldberger, E. E. McDuffie, A. Moravek, C. C. Womack, E.

T. Crosman, D. S. Docherty, W. P. Dube, S. W. Hoch, B. H. Lee, R. Long, J. G. Murphy, J.

A. Thornton, S. S. Brown, M. Baasandorj and A. M. Middlebrook. Airborne and ground-based observations of ammonium-nitrate-dominated aerosols in a shallow boundary layer during intense winter pollution episodes in northern Utah, Atmospheric Chemistry and Physics 18, 17259-17276, doi:10.5194/acp-18-17259-2018 (2018).

13. Gantt, B., M. S. Johnson, M. Crippa, A. S. H. Prévôt, and N. Meskhidze. Implementing marine organic aerosols into the GEOS-Chem model, Geoscientific Model Development, 8(3), 619–629, doi:10.5194/gmd-8-619-2015 (2015).

14. Gantt, B., G. Sarwar, J. Xing, H. Simon, D. Schwede, W. T. Hutzell, R. Mathur and A. Saiz-

Lopez. The impact of iodide-mediated ozone deposition and halogen chemistry on surface ozone concentrations across the continental United States, Environmental Science & Technology 51(3), 1458–1466, doi:10.1021/acs.est.6b03556 (2017).

15. Gao, C.W., J.W. Allen, W.H. Green and R.H. West. Reaction mechanism generator:

Automatic construction of chemical kinetic mechanisms. Computer Physics Communications 203, 212-225 (2016).

16. Gentner, D. R., S. H. Jathar, T. D. Gordon, R. Bahreini, D. A. Day, I. El Haddad, P. L.

Hayes, S. M. Pieber, S. M. Platt, J. de Gouw, A. H. Goldstein, R. Harley, J. L. Jimenez, A. S.

H. Prévôt and A. L. Robinson. Review of urban secondary organic aerosol formation from gasoline and diesel motor vehicle emissions, Environmental Science & Technology 51(3), 1074–1093, doi:10.1021/acs.est.6b04509, (2017).

17. Gery, M. W., G. Z. Whitten and J. P. Killus. Development and testing of the CBM-IV for urban and regional modeling. Report to the U.S. EPA, EPA/600/3-88/012, April (1988).

18. Griffith, S. M., R. F. Hansen, S. Dusanter, V. Michoud, J. B. Gilman, W. C. Kuster, P. R.

Veres, M. Graus, J. A. de Gouw, J. Roberts, C. Young, R. Washenfelder, S. S. Brown, R.

Thalman, E. Waxman, R. Volkamer, C. Tsai, J. Stutz, J. H. Flynn, N. Grossberg, B. Lefer, S.

L. Alvarez, B. Rappenglueck, L. H. Mielke, H. D. Osthoff and P. S. Stevens. 2016.

Measurements of hydroxyl and hydroperoxy radicals during CalNex-LA: Model comparisons and radical budgets. Journal of Geophysical Research-Atmospheres 121(8), 4211-4232, doi:

10.1002/2015JD024358 (2016).

19. Guo, J. J., A. M. Fiore, L. T. Murray, D. A. Jaffe, J. L. Schnell, C. T. Moore and G. P. Milly.

Average versus high surface ozone levels over the continental USA: Model bias, background influences, and interannual variability, Atmospheric Chemistry and Physics, 18, 12123- 12140, doi: 10.5194/acp-18-12123-2018 (2018).

20. Horowitz, H. M., D. J. Jacob, Y. Zhang, T. S. Dibble, F. Slemr, H. M. Amos, J. A. Schmidt, E. S. Corbitt, E. A. Marais and E. M. Sunderland. A new mechanism for atmospheric mercury redox chemistry: implications for the global mercury budget, Atmospheric Chemistry and Physics 17(10), 6353–6371, doi:10.5194/acp-17-6353-2017 (2017).

21. Jeffries, H. E., M. W. Gery and W. P. L. Carter.