4.5 Other Food & Agricultural Processing
Category 33
4.5.1 Introduction
Category 33 includes emissions from processing plants of miscellaneous food and agricultural products for human or animal consumption. These facilities include coffee and cocoa bean roasting, grain feed milling/packaging, spice/flavoring handling, sugar refinery, onion, garlic, corn, and pet food processing etc.
This category includes combustion related emissions of five criteria pollutants, namely PM, organics, NOx, SOx, and CO, but the majority of emissions are process related emissions of PM. Carbon dioxide (CO2) emissions are produced during the fermentation process of beer production and in the combustion of organic waste from coffee and cocoa beans roasting in abatement devices, such as an afterburner. The CO2 emissions emitted from beer production are considered biogenic.
4.5.2 Methodology
Point Sources are operations that emit air pollution into the atmosphere at a fixed location within a facility, for which the Air District has issued 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, 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 CEPAM’s 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. 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.
Category 33 is considered a point source category and follows the above methodology for emissions estimates.
The PM2.5/PM and the PM10/PM ratios applied to this category or this group of related categories are consistent with size fractions of speciation profiles developed by the California Air Resources Board (CARB) and published on their emissions inventory web-page44. For this category(s), CARB’s speciation profile number is 900; PM2.5 constitutes 42% of total PM and PM10 constitutes 70% of total PM.
4.5.3 Changes in Methodology
No changes in methodology were made in this version of the base year emissions inventory as compared to the previous version.
4.5.4 Emissions
A summary of emissions by category, county, and year are available via the associated data dashboard for this inventory publication.
This category primarily accounts for PM emissions. Total PM emissions from this category have ranged from ~200 to 500 tons/year from 1990 to 2020. While in the past decade, PM emissions have remained steady at ~240 tons/year on average, making this category an important PM source.
4.5.5 Trends
PM emissions peaked in the mid-1990s and have steadily decreased since then. While overall production and throughput processed in the food processing industry have gone up. This is mostly due to increased installation of abatement devices.
(a) Historical Emissions / History
Historical emissions for point source emissions are derived from source-specific throughputs provided by the permitted facility, compiled/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.
Emissions through the years were estimated by using agricultural production data in the District. In 1963-1964 there was at least 50% reduction of particulate emissions from equipment such as coffee roaster and food dryers brought about by the District’s Regulation 645 on visible emissions from the Ringlemann 2 standard46. In 1970 there was at least an additional 25% reduction in particulates from the Ringlemann 1 standard. Currently, there is an estimated 98% overall control of particulates from this category.
The historical growth profile is based on a combination of prior emissions data (back to year 1987) and the Association of Bay Area Government’s (ABAG’s) 2009 Manufacturing & Wholesale Employment data (back to year 1990).
(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 this 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 past or 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
The inventory staff determines a growth profile to be used for forecasting future emissions for a given category(s) based on data available from a handful of resources. These resources may include employment- and population-based growth projections generated by the Association of Bay Area Governments47, fixed-percentage growth profiles derived by EI staff based on historical data trends, custom-growth profiles derived using relevant regional and sub-national data sources (e.g. county-specific wine production data from Wine Institute for wine fermentation category, California crude oil distillation capacity from Energy Information Administration for refinery category projections, California Energy Commission natural-gas usage projection data for projecting emissions of residential and commercial natural-gas combustion categories, and more).
Projections of emissions to 2040 for this category are based on Association of Bay Area Government’s year 2017 Agricultural and Natural Resources job growth profile featured in the last version of Plan Bay Area3.
4.5.6 Uncertainties
This category is a historical category without much changes in the methodology, applied controls or emission factors over time. The emission factors used to derive facility-specific PM emissions is a combination of facility-reported specific emission factors and general factors. The general factors are AP-42 based and may be outdated. As such, this category can see an improvement in emissions estimates based on more of the emissions relying on use of specific emission factors in the future.
4.5.7 Contact
Author: Abhinav Guha
Reviewers: Tan M. Dinh and Yuan Du
Last Update: November 06, 2023
4.5.8 References & Footnotes
CARB. 2022. PMSIZE. https://ww2.arb.ca.gov/speciation-profiles-used-carb-modeling↩︎
BAAQMD. 2019. Regulation 6: Particulate Matter - Common Definitions and Test Methods. https://www.baaqmd.gov/rules-and-compliance/rules/regulation-6-particulate-matter---common-definitions-and-test-methods↩︎
Bureau of Mines. 1967. Ringlemann Smoke Chart, United States Department of Interior. https://www.cdc.gov/niosh/mining/userfiles/works/pdfs/ic8333.pdf↩︎
ABAG. 2017. Plan Bay Area 2040. http://2040.planbayarea.org/files/2020-02/Final_Plan_Bay_Area_2040.pdf↩︎