7.8 Reciprocating Engines
Categories 302, 303, and 304
7.8.1 Introduction
Categories 302, 303, and 304 estimate criteria pollutant emissions (particulate, organic, NOx, SOx, and CO) from reciprocating engines in the San Francisco Bay Area. Category 302 covers engines that use gasoline and contains reciprocating engines for firewater pumps and standby generators at the oil refineries. Category 303 covers engines that use gaseous fuel only and contains mostly internal combustion engines/electric generators at various companies and utility districts. Category 304 covers engines that use liquid fuel only. The majority of sources in 304 are diesel fuel engines. Most of the sources in this category are emergency or standby electric generators.
7.8.2 Methodology
Point Sources are typically operations that emit air pollution into the atmosphere at a fixed location within a facility, for which the Air District has specific operational information. For many of these point sources the Air District issues a permit to operate, e.g., refinery cooling towers. These could also be a collection of similar equipment / sources located across multiple facilities, e.g., reciprocating engines.
During the permit to operate (PTO) issuance process, the BAAQMD collects information from the operating facility and/or determines from published literature, e.g., EPA’s AP-42 document308 characteristics of a source including maximum throughput, emission factors for emitted pollutants, and control factors associated with downstream abatement devices. These characteristics are then stored for future use in the BAAQMD’s internal database. Facilities that hold a permit to operate are required to renew this permit periodically (this period varies based on facility and source type). Upon renewal, the facilities are requested to provide any updates to source characteristics as well as the source throughput for the last 12 months. This throughput, in combination with the emission factors and controls factors stored in the internal database, are used to estimate annual emissions at the source level. These source level emissions are then sorted and aggregated into categories.
Further speciation and quality assurance of emissions are performed as a part of the inventory process. The BAAQMD staff also perform a systematic crosswalk between the California Emissions Projection Analysis Model’s (CEPAM)309 source category classification (Emission Inventory Code - EICs) and the District’s source category classification (category identification number - cat_ids), which ensures consistency in the annual emissions reporting process (CEIDARS) to California Air Resources Board (CARB). The last part of the inventory development process includes forecasting and back casting, and aggregation into sub-sectors and sectors for documentation purposes. For those years where no data is available, emissions data are backcasted to year-1990, as well as forecasted to year-2040 using either interpolation or another mathematical approach (see Trends section). Finally, emissions trends spanning from year 1990-2040 for each category and pollutant are evaluated for anomalies that are then investigated and addressed.
Categories 302, 303, and 304 are point source categories and follow the above methodology for emissions estimates.
The Bay Area Air District’s Regulation 9, Rule 8 controls NOx and SOx emissions of fuel combustion in reciprocating engines.
PM speciation: The PM2.5/PM and the PM10/PM ratios applied to these categories are consistent with size fractions of speciation profiles developed by the California Air Resources Board (CARB) and published on their emissions inventory web-page310.
For category 302, CARB PM speciation profile number is 115 (NA - There were negligible or no emissions for category 302 for year 2015).
For category 303, CARB PM speciation profile number is 120; PM2.5 constitutes 100.0% and PM10 constitutes 100.0% of total PM.
For category 304, CARB PM speciation profile number is 116; PM2.5 constitutes 96.0% and PM10 constitutes 93.6% of total PM.
The ROG/TOG ratios applied to this category, or this group of related categories are based on an Air District internal speciation profile. Multiple data sources have been used for developing speciation profiles, such as Air District-approved source tests, TOG speciation ratios used by other regional air quality agencies, and relevant literature including latest speciation profiles developed by CARB311 and the US Environmental Protection Agency312.
For categories 302, 303, and 304, ROG to TOG ratios are NA, 0.07, and 0.88, respectively. Further assessment and improvement of ROG/TOG speciation profiles has been planned in future inventory updates.
7.8.3 Changes in Methodology
No changes to methodology were made in this version of the base year emissions inventory.
7.8.4 Emissions
A summary of emissions by category, county, and year are available via the associated data dashboard for this inventory publication.
7.8.5 Trends
(a) Historical Emissions / History
Historical emissions for point sources are derived from source-specific data provided by the facility on throughputs, compiled or reported emission factors, and regulation-based control factors. This information is archived in the BAAQMD’s internal database which is queried to retrieve the data for historical and current years. Interpolation techniques to account for missing data are used when necessary, this is the case for years 1991-1992.
For Category 302, emissions have been extremely low and constant over the past years. Emissions for Categories 303 and 304 have generally varied with fuel usage activity in the San Francisco Bay Area.
(b) Future Projections / Growth
Forecasting of point source emissions is done based on calculations as shown in the equation below using recently updated growth profiles and a base year of 2020. The growth profiles for the current base year inventory have been verified and updated to represent the most likely surrogate for growing emissions for a given category up to year 2040. Forecasting for point source emissions includes impact of in-place regulations but does not include estimation of controls that will theoretically be implemented as part of future policy emission targets or proposed regulation and legislation.
\[ \text{PE} = \text{Gr} * \text{Ci} * \text{Ei} \]
\(PE\) = projected emissions of pollutant i in a future year
\(Gr\) = growth rate by economic profile of industry or population
\(Ci\) = control factor of pollutant i based on adopted rules and regulations
\(Ei\) = base year emissions of pollutant i
For Categories 302 and 303, it is assumed that annual emissions, over the years, would tend to follow the industrial sector jobs growth in the Bay Area Air District. For Categories 304, it is assumed that annual emissions, over the years, would tend to follow the manufacturing, wholesale, and transportation sector jobs growth in the Bay Area Air District.
The employment and population data used were obtained from the Association of Bay Area Government’s (ABAG’s) 2017 “Projections” reports313.
7.8.6 Uncertainties
A step-increase in TOG emissions for category 303 may be seen for the period 2007-2008. This is due to a sustained Air District effort to gradually include and update methane emissions factors for various source types over time. For years 1990-2008, high uncertainty in the TOG emissions estimates is expected; further refinement in backcasting of historical TOG emissions is planned in future inventory updates.
7.8.7 Contact
Author: Sukarn Claire
Reviewer: Ariana Husain
Last Update: November 06, 2023
7.8.8 References & Footnotes
USEPA. AP-42. Compilation of Air Pollutant Emission Factors. https://www.epa.gov/air-emissions-factors-and-quantification/ap-42-compilation-air-emissions-factors↩︎
California Emissions Projection Analysis Model (CEPAM). https://ww2.arb.ca.gov/applications/cepam2019v103-standard-emission-tool↩︎
PMSIZE. CARB. 2022. https://ww2.arb.ca.gov/speciation-profiles-used-carb-modeling↩︎
ORGPROF. CARB. 2022. https://ww2.arb.ca.gov/speciation-profiles-used-carb-modeling↩︎
SPECIATE. USEPA. 2022. https://www.epa.gov/air-emissions-modeling/speciate↩︎
The Association of Bay Area Governments (ABAG). https://abag.ca.gov/↩︎