# 2005 MEXICALI EMISSI ONS INVENTORY

Final Report

Prepared for:

Western Governors’ Association

Denver, Colorado
U.S. Environmental Protection Agency, Region 9 San Francisco, California
Secretaría de Protección al Ambiente de Baja Californ ia Mexicali, Baja California, Mexico



### February 27, 2009 Eastern Research Group, Inc.ERG Project No: 3657.00.004.001



## 2005 MEXICALI EMISSI ONS INVENTORY

Final Report

Prepared for:

Western Governors’ Association Denver, Colorado
U.S. Environmental Protection Agency, R egion 9

San Francisco, California
Secretaría de Protección al Ambiente de Baja California

Mexicali, Baja California, Mexico

Prepared by:
Eastern Research Group, Inc. (ERG) Sacramento, California

with
Ingeniería en Control Ambiental y Riesgo Industri al, S. de R.L. (ICAR)

Mexicali, Baja California, Mexico

and
TransEngineering El Paso, Texas

February 27, 20092005 Mexicali Emissions Inventory

Final, 2/27/09 i 

## TABLE OF CONTENTS

Section Page

ES.0 EXECUTIVE SUMMARY

................................ ................................ ........................... ES

- 1 ES.1 Methodology

................................ ................................ ................................ ..... ES

- 1 ES.2 Summary of Results

................................ ................................ .......................... ES

- 2

1.0 INTRODUCTION

................................ ................................ ................................ ........... 1

- 1 1.1 Inventory Characteristics

................................ ................................ ..................... 1

- 2 1.2 Data Management and Formatting

................................ ................................ ....... 1

- 5 1.3 Data Quality Objectives

................................ ................................ ....................... 1

- 5 1.4 Report Organization

................................ ................................ ............................. 1

- 7

2.0 POINT SOURCES

................................ ................................ ................................ ........... 2

- 1 2.1 Federal Jurisdiction Point Source Methodology

................................ .................. 2

- 1 2.2 State Jurisdiction Point Source Methodology

................................ ...................... 2

- 4 2.3 Res ults

................................ ................................ ................................ .................. 2

- 7 2.4 Quality Assurance

................................ ................................ ................................ 2

- 8

3.0 AREA SOURCES

................................ ................................ ................................ ............ 3

- 1 3.1 Met hodology

................................ ................................ ................................ ........ 3

- 1 3.1.1 Fuel Combustion Categories

................................ ................................ .... 3

- 5 3.1.2 Evaporative VOC Categories

................................ ................................ ... 3

- 5 3.1.3 Agricultural Categories

................................ ................................ ............ 3

- 6 3.1.4 Ammonia Categories

................................ ................................ ............... 3

- 8 3.1.5 Paved Road Dust

................................ ................................ ...................... 3

- 8 3.1.6 Unpaved Road Dust

................................ ................................ ............... 3

- 12 3.1.7 Miscellaneous Burning Categories

................................ ........................ 3

- 13 3.1.8 B order Crossings

................................ ................................ .................... 3

- 13 3.1.9 Brick Kilns

................................ ................................ ............................. 3

- 13 3.1.10 Charbroiling, Construction Dust, and Bakeries

................................ .... 3

- 14 3.1.11 Landfills

................................ ................................ ................................ 3

- 14 3.1.12 Wastewater Treatment

................................ ................................ .......... 3

- 14 3.2 Results 3

- 14 3.3 Quality Assurance

................................ ................................ .............................. 3

- 19

4.0 ON

- ROAD MOBILE SOURCES

................................ ................................ .................... 4

- 1 4.1 Methodology

................................ ................................ ................................ ........ 4

- 1 4.2 Results 4

- 2 4.3 Quality Assurance

................................ ................................ ................................ 4

- 4

5.0 NONROAD MOBILE SO URCES

................................ ................................ .................. 5

- 1 5.1 Methodology

................................ ................................ ................................ ........ 5

- 12005 Mexicali Emissions Inventory

Final, 2/27/09 ii 

## TABLE OF CONTENTS (Continued)

Section Page

5.1.1 Aircraft

................................ ................................ ................................ ..... 5

- 1 5.1.2 Locomotives

................................ ................................ ............................. 5

- 2 5.1.3 Agricultural and Construction Equipment

................................ ............... 5

- 2 5.2 Results

................................ ................................ ................................ .................. 5

- 3 5.3 Quality Assurance

................................ ................................ ................................ 5

- 4

6.0 EMISSION INVENTORY RESULTS

................................ ................................ ............ 6

- 1

7.0 REF ERENCES

................................ ................................ ................................ ................ 7

- 1

APPENDIX A: AREA SOURCE CATEGORY FORMS

APPENDIX B: TECHNICAL REPORT (DRAFT), ESTIMATION OF TRAVEL DEMAND

AND VEHICULAR TRAFFIC CONGESTION OF THE MEXICALI REGION

Tables Page

ES

- 1 2005 Mexicali Emissions Inven tory Summary (Tons per Year)

................................ ... ES

- 3
1

- 1 2005 Mexicali Emissions Inventory Summary (Tons per Year)

................................ ..... 1

- 5
2

- 1 Listing of State Jurisdiction Point Sources

................................ ................................ ...... 2

- 5
2

- 2 2005 Mexicali Federal Jurisdiction Point Source Emissions (Tons per Year)

................ 2

- 9
2

- 3 2005 Mexicali Stat e Jurisdiction Point Source Emissions (Tons per Year)

.................... 2

- 9
3

- 1 General Emission Estimation Methodologies for Area Sources in Mexicali

.................. 3

- 2
3

- 2 2005 Mexicali Area Source Emissions (Tons per Year)

................................ ............... 3

- 15
4

- 1 2005 Mexicali On

- Road Mobile Source Emissions (Tons pe r Year)

.............................. 4

- 4
4

- 2 2005 Imperial County and Mexicali On

- Road Mobile Source Emissions (Tons per Year)

................................ ................................ ................................ ................ 4

- 6
5

- 1 2005 Mexicali Nonroad Mobile Source Emissions (Tons per Year)

............................... 5

- 4
6

- 1 2005 Mexicali Emissions Inventory Summary (Tons per Year)

................................ ..... 6

- 12005 Mexicali Emissions Inventory

Final, 2/27/09 iii Figures Page

1

- 1 S tate of Baja California and Five Municipalities

................................ ............................. 1

- 3
1

- 2 Municipality and Mexicali and Most Populous Localities

................................ .............. 1

- 4
2

- 1 Location of Federal and State Jurisdiction Point Sources in the Urban Portion of Mexicali

................................ ................................ ................................ ....................... 2

- 3
3

- 1 Location of Paved and Unpaved Road Dust Sam pling Sites

................................ ........... 3

- 9
3

- 2 Pavement Coverage of Mexicali Roads

................................ ................................ ......... 3

- 11
4

- 1 Mexicali Loaded Roadway Network Under Weekday Conditions

................................ .. 4

- 3
6

- 1 Mexicali NO x Emissions

................................ ................................ ................................ .. 6

- 2
6

- 2 Mexicali SO 2 Emissions

................................ ................................ ................................ .. 6

- 2
6

- 3 Mexicali VOC Emissions

................................ ................................ ................................ 6

- 3
6

- 4 Mexicali CO Emissions

................................ ................................ ................................ ... 6

- 3
6

- 5 Mex icali PM 10 Emissions

................................ ................................ ................................ 6

- 4
6

- 6 Mexicali PM 2.5 Emissions

................................ ................................ ................................ 6

- 4
6

- 7 Mexicali NH 3 Emissions

................................ ................................ ................................ .. 6

- 5
6

- 8 Mexicali CH 4 Emissions

................................ ................................ ................................ .. 6

- 52005 Mexicali Emissions Inventory

Final, 2/27/09 iv 

## ACRONYMS

AGEB area geoestadístics básicas (basic geographic area)
ANAFAPYT Asociación Nacional de Fabricantes de Pinturas y Tintas (Na tional Association

of Paint and Dye Manufacturers)

ARB Air Resources Board, California

BC Baja California
CANALAVA Cámara Nacional de la Industria de Lavanderías (National Chamber of the Dry

Cleaning Industry)
CFE Comisión Federal de Electricidad (Federa l Electric Commission)

CH 4 methane

CO carbon monoxide

COA Cédula de Operación Anual (Annual Operating Report)
DQOs data quality objectives

EIIP Emission Inventory Improvement Program

EIP Emission Inventory Plan

ERG Eastern Research Group, Inc.

FIFRA Federa l Insecticide, Fungicide and Rodenticide Act

GIS geographical information system

HDDV heavy

- duty diesel vehicle

HDGV heavy

- duty gasoline vehicle

IC internal combustion

ICAO International Civil Aviation Organization

ICAR Ingeniería en Control Ambiental y Riesgo Industrial, S. de R.L.

ID identification number

INEGI Instituto Nacional de Estadística, Geografía e Informática (National Institute of

Statistics, Geography, and Computing)
kg kilogram2005 Mexicali Emissions Inventory

Final, 2/27/09 v km kilometers

lb pound

lbs pounds

LDDT light

- duty diesel truc k

LDDV light

- duty diesel vehicle

LDGT light

- duty gasoline truck

LDGV light

- duty gasoline vehicle

LPG liquefied petroleum gas

LTO landing and take

- off

m 2 square meters

m 3 cubic meters

MC motorcycle
Mg megagram mm Hg millimeters of mercury
mph miles per ho ur
NAICS North America Industry Classification System

NEI National Emissions Inventory

NH 3 ammonia

NIF National Emissions Inventory Input Format

NO x nitrogen oxides

NPK nitrogen

- phosphorus

- potassium

PEMEX Petróleos Mexicanos

PM particulate matter

PM 2.5 par ticulate matter less than 2.5 micrometers in equivalent aerodynamic

diameter.

PM 10 particulate matter less than 10 micrometers in equivalent aerodynamic diameter2005 Mexicali Emissions Inventory

Final, 2/27/09 vi PROAIRE Programa para Mejorar la Calidad del Aire (Program to Improve Air Quality)
QA quality assurance QAPP quality assurance project plan
QC quality control

s second

SAGARPA Secretaría de Agricultura, Ganadería, Desarrollo Rural, Pesca y Alimentación

(Secretariat of Agriculture, Livestock, Rural Development, Fisheries, and Food)

SCC source class ification code

scf standard cubic feet

SEMARNAT Secretaría de Medio Ambiente y Recursos Naturales (Secretariat of the

Environment and Natural Resources)

SENER Secretaría de Energía (Secretariat of Energy)

SLRC San Luis Río Colorado, Sonora

SO 2 sulfur dio xide

SPA Secretaría de Protección al Ambiente de Baja California (Secretary of

Environmental Protection of Baja California)

TDM travel demand model

TIM time

- in

- mode

TSP total suspended particulate

U.S. EPA United States Environmental Protection Agency

VKT vehicle kilometers traveled

VMT vehicle miles traveled

VOC volatile organic compound

WGA Western Governors’ Association

WRAP Western Regional Air Partnership

yr year2005 Mexicali Emissions Inventory

Final, 2/27/09 ES

- 1 

## ES.0 EXECUTIVE SUMMARY

In response to requests from the Secretary of Environmental Prote ction of Baja California ( Secretaría de Protección al Ambiente de Baja California

– SPA) and the California Air Resources Board (ARB), the Western Governors’ Association (WGA), with funding from the U.S. Environmental Protection Agency (U.S. EPA), hired a contractor team to develop the 2005 Mexicali inventory. The contractor team was led by Eastern Research Group, Inc. (ERG) and supported by two Mexico

- based subcontractors (i.e., Ingeniería en Control Ambiental y Riesgo Industrial, S. de R.L. [ICAR] and Tr ansEngineering). This 2005 Mexicali emissions inventory updates previous inventories developed for Mexicali, Baja California (BC), including Mexicali’s Programa para Mejorar la Calidad del Aire (PROAIRE) for a base year of 1996 (PROAIRE, 1999) and the 199 9 Mexico National Emissions Inventory (NEI) Program (ERG, 2006).

The 2005 Mexicali emissions inventory was developed for the entire municipality of Mexicali. Annual emissions (both tons per year and megagrams per year) were estimated for point sources, ar ea sources, on

- road mobile sources, and nonroad mobile sources. Emissions were estimated for the following pollutants: nitrogen oxides (NO x ), sulfur dioxide (SO 2 ), volatile organic compounds (VOC), carbon monoxide (CO), particulate matter (PM) less than 10 micrometers (μm) in aerodynamic diameter (PM 10 ), PM less than 2.5 μm in aerodynamic diameter (PM 2.5 ), ammonia (NH 3 ), and methane (CH 4 ).

ES.1 Methodology The point source emissions inventory was developed using existing emissions data provided by the Se cretariat of Environment and Natural Resources (SEMARNAT) and the Secretary of Environmental Protection of Baja California (SPA). The area source and nonroad mobile source emissions inventory were developed using activity data collected from Mexicali

gove rnment agencies and other local contacts. The on

- road mobile source emission inventory was developed using vehicle activity data (i.e., vehicle kilometers traveled [VKT]) obtained from traffic and congestion modeling.2005 Mexicali Emissions Inventory

Final, 2/27/09 ES

- 2 ES.2 Summary of Results
Table ES

- 1 p rovides a summary of the results of the 2005 Mexicali emissions inventory, by source type and pollutant. Table ES

- 1 shows that:

 Emissions from federal jurisdiction point sources are considerably larger than emissions from state jurisdiction point sources, even though the ratio of state

- to

federal jurisdiction point sources is greater than 10

- to

- 1.

 NO x and SO 2 emissions are dominated by point sources.

 VOC emissions are emitted by area (i.e., mainly various evaporative source categories) and on

- road mobile s ources.

 On

- road mobile sources are the predominant source of CO.

 Area sources are the largest contributors of PM 10 and PM 2.5 (i.e., due to unpaved and paved road dust), NH 3 (i.e., from livestock ammonia and fertilizer application), and CH 4 (i.e., from the landfill). The final inventory was formatted to be compatible with U.S. EPA’s National Emissions Inventory Format (NIF), and SMOKE/IDA format (i.e., used for photochemical and other modeling). In addition, spatial surrogates for gridding area source emiss ions into a 4 km grid system for modeling were developed. Also, geographic information system (GIS)

- based shape files obtained for Mexicali’s AGEBs (i.e., area geoestadístics básicas or basic geographic areas) which were used in the development of some ar ea source category emissions, were provided along with the final inventory files for purposes of spatially distributing area source emissions over the inventory domain for purposes of air quality modeling.2005 Mexicali Emissions Inventory

Final, 2/27/09 ES

- 3 Table ES

- 1. 2005 Mexicali Emissions Inventory S ummary (Tons per Year)
Source Type NO x SO 2 VOC CO PM 10 PM 2.5 NH 3 CH 4 Point

– Federal 13,931.7 3,650.9 659.3 3,636.2 1,537.7 128.4
Point

– State 444.0 973.2 73.0 479.9 89.7 Area 1,205.5 131.1 15,301.5 18,854.0 50,879.3 6,753.5 9,015.2 6,033.3 On

- Road Mobile 8,570.4 168.7 8,977.1 60,603.4 765.0 665.8 252.4 144.4
Nonroad Mobile 4,485.0 60.9 542.9 3,206.9 550.2 533.3 0.0 1.5
Total 28,636.5 4,984.8 25,553.8 86,780.4 53,821.8 8,081.0 9,267.6 6,179.2
Blanks indicate that pollutant emissions were no t applicable or were not estimated due to a lack of data.2005 Mexicali Emissions Inventory

Final, 2/27/09 1

- 1 

## 1.0 INTRODUCTION

The first emissions inventory developed for Mexicali, Baja California (BC) was published as part of Mexicali’s Programa para Mejorar la Calidad del Aire (PROAIRE) for a base yea r of 1996 (PROAIRE, 1999). The next and most recent emissions inventory for Mexicali was developed and published as part of the 1999 Mexico National Emissions Inventory (NEI) Program; however, the industrial source emissions in the 1999 Mexico NEI for Mex icali were based on the previous 1996 PROAIRE inventory (ERG, 2006).

The Secretary of Environmental Protection of Baja California ( Secretaría de Protección al Ambiente de Baja California

– SPA) has r equested an update to the emissions inventory for the

m unicipality of Mexicali for the year 2005. In addition, the California Air Resources Board (ARB) has requested an updated inventory for purposes of air quality modeling in the border area of Imperial County, California, and Mexicali.

In response to thes e needs, the Western Governors’ Association (WGA), with funding from the U.S. Environmental Protection Agency (U.S. EPA), sponsored this project to update the Mexicali emissions inventory to 2005. The Contractor team, hired under Contract No. 30430

- 01,

wa s led by Eastern Research Group, Inc. (ERG), and included Ingeniería en Control Ambiental y Riesgo Industrial, S. de R.L. (ICAR), and TransEngineering. ICAR was responsible for data collection related to area and point sources, and TransEngineering was r esponsible for estimating

on

- road motor vehicle activity data which were used to estimate mobile source emissions and to determine the distribution of vehicle activity over paved versus unpaved roads.

The specific objectives of the 2005 Mexicali emissions inventory were to provide a current and accurate technical basis for air quality planning in the municipality of Mexicali. Also, the results of the 2005 Mexicali emissions inventory (for the non

- methane pollutants) are formatted for use in air quality mod eling to better understand the contribution of Mexicali emissions to concentrations of criteria pollutant levels in that region.2005 Mexicali Emissions Inventory

Final, 2/27/09 1

- 2 1.1 Inventory Characteristics The characteristics of the 2005 Mexicali emissions inventory are as follows:

 Base year: 2005.

 Temporal resolution: Annual emissions, in terms of megagrams per year (Mg/year) and tons per year (tons/year). Some intermediate activity data are presented in Imperial units. The inventory results are presented in Imperial units (i.e., tons per year) in the English version of the final report and in metric units (i.e., megagrams [Mg] per year) in the Spanish version of the final report.

 Geographic domain: Entire municipality of Mexicali. Figure 1

- 1 shows the entire state of Baja California and its five municipalities (i.e., Mexicali, Tijuana, Tecate, Playas de Rosarito, and Ensenada). Figure 1

- 2 shows the municipality of Mexicali and location of the most populous “localities” (e.g., cities, towns, communities, etc.) with population greater than 3,000.

 Geographic Resolution: In addition to total municipality

- level emissions by pollutant and source type, emissions were estimated at various other levels of detail, including:

 Exact location (i.e., latitude/longitude) for point sources.

 Spatial surrogates a t the level of basic geographic areas (area geoestadística básica

– AGEB) are also provided. An AGEB is analogous to a census tract in the U.S. These surrogates provide the spatial allocation of emissions to 4 kilometer (km) × 4 km grid cells within the ARB modeling domain (i.e., approximately 36 km to 50 km south of the California

— BC border).

 Pollutants:

 Nitrogen oxides (NO x )

 Sulfur dioxide (SO 2 )

 Volatile organic compounds (VOC)

 Carbon monoxide (CO)

 Particulate matter (PM) less than 10 micrometers (μm) in aerodynamic diameter (PM 10 )

 PM less than 2.5 μm in aerodynamic diameter (PM 2.5 )

 Ammonia (NH 3 )

 Methane (CH 4 ).

 Source Types and Categories: Point sources, area sources, on

- road mobile sources, and nonroad mobile sources. Each of these source types will be discussed in their individual sections.2005 Mexicali Emissions Inventory

Final, 2/27/09 1

- 3

Figure 1

- 1. State of Baja California and Five Municipalities

Figure 2

- 2. Municipality of Mexicali and its Most Populous Localities

Figure 2

- 3. ARB Modeling Domain2005 Mexicali Emissions Inventory

Final, 2/27/09 1

- 4 Figure 1

- 2 . Municipality of Mexicali and its Most Populous Localities2005 Mexicali Emissions Inventory

Final, 2/27/09 1

- 5 1.2 Data Management and Formatting Development of the 2005 Mexicali emissions inventory required the compilation of considerable amounts of emissions and other related inventory data. Electro nic spreadsheets were used to compile, calculate, and summarize emissions data.

The final inventory was formatted to be compatible with U.S. EPA’s National Emissions Inventory Format (NIF), and SMOKE/IDA format (i.e., used for photochemical and other
mode ling). In addition, spatial surrogates for gridding the area source emissions into a 4 km grid system for modeling will be developed. Also, geographic information system (GIS)

- based shape files of the obtained for Mexicali’s AGEBs, which were used in the development of some area source category emissions, will be provided along with the final inventory files for purposes of spatially distributing area source emissions over the inventory domain for purposes of air quality modeling.

1.3 Data Quality Objectives

The data quality objectives (DQOs) were established as part of the Emission Inventory Plan (EIP)/Quality Assurance Project Plan (QAPP) developed for this project. The specific DQOs, and criteria used to evaluate whether the DQOs are achieved for the 2005 Mexicali emissions inventory are as follows:

1. A comprehensive emissions inventory for all source types (i.e., point, area, on

- road motor vehicle, and nonroad mobile sources) and all major categories within these source types. Acceptance criteria: The source types and major categories accounted for in the EIIP guidance documents are present in the Mexicali emissions inventory, and/or any differences are documented.

2. Identification of 80% of all federal jurisdiction and state jurisdiction point source s located within the municipality of Mexicali.
Acceptance criteria: A list of point sources under the federal (SEMARNAT Delegation), and state (SPA) jurisdictions compares to the emissions data, by source, provided by those agencies.

3. Point sources: Emissions estimates with an accuracy of ± 25% for at least 10% of the facilities.2005 Mexicali Emissions Inventory

Final, 2/27/09 1

- 6

Acceptance criteria: Estimated emissions for 10% of the total facilities compare to measured emissions of all pollutants with ± 25% accuracy. The emissions data

measuremen ts will be obtained from subcontractor ICAR, and will be based on data collected over the past five years in Mexicali.

4. Area, On

- Road Motor Vehicle, and Nonroad Mobile Sources: Emissions estimates with an accuracy of ±50%.
Acceptance criteria: Estima ted emissions using emission factors/models compare to emissions estimated using a fuel

- balance approach for all applicable pollutants. The fuel

- balance approach will use national statistics, while the preferred inventory methodology will use PEMEX and lo cal fuel distribution data.

5. Documentation: All EI results are transparent and reproducible.
Acceptance criteria: Written and electronic inventory documentation provides detailed explanations of data collected, data measured/analyzed, values estimate d/calculated, assumptions made, and emission factors used so that the results can be duplicated.
Most of these acceptance criteria have been met, and in some cases exceeded, in the development of the 2005 Mexicali emissions inventory. Instances where the acceptance criteria could not be met are documented (i.e., see Area Sources, Section 3.3).

In general, the following quality assurance checks were performed to ensure the DQOs
were achieved:

 Accuracy checks

– Spreadsheets were developed to calculate emis sions, and 100% of the formulas were checked for accuracy. 100% of the electronic calculations were checked (50% by hand), and any errors were corrected.

 Completeness checks

– The list of pollutants and source categories for the 1999 Mexico NEI was compare d against all of the inventory files to ensure that emissions are estimated for the correct pollutants and source categories. Any errors were corrected.

 Representativeness

– The emission factors and activity data were reviewed to ensure they are appropriat e and current for the source categories for 100% of the source categories inventories. All adjustment factors (e.g., used to allocate national activity to a state

- or municipality

- level rate) were reviewed to ensure they are representative of actual condit ions affecting emissions generated during the base year of 2005.
Specific quality assurance procedures followed during the estimation of emissions for each source type will be described in report Sections 2.0, 3.0, 4.0, and 5.0 for point sources, area2005 Mexicali Emissions Inventory

Final, 2/27/09 1

- 7 sour ces, on

- road mobile sources, and nonroad mobile sources, respectively, as part of the final report.

1.4 Report Organization The remainder of this report provides a complete and detailed description of all methods, assumptions, data, and calculations used t o develop the emissions inventory, along with the results by source category. The report is organized as follows:

 Section 2.0 describes the point source estimation methodology and results.

 Section 3.0 describes the area source estimation methodology and r esults.

 Section 4.0 describes the on

- road mobile source estimation methodology and results.

 Section 5.0 describes the nonroad mobile source methodology and results.

 Section 6.0 provides the overall 2005 Mexicali emissions inventory results.

 Section 7.0 lis ts all references used in the development of this emissions inventory.

 Appendix A contains the forms showing how each area source category’s emissions were calculated (i.e., method/emission factor/formula, reference, activity data, sample calculation).

 App endix B contains a detailed explanation of the analysis conducted to estimate on

road mobile source activity data.2 005 Mexicali Emissions Inventory

Final, 2/27/09 2

- 1 

## 2.0 POINT SOURCES

Point sources are stationary industrial sources that release emissions from fixed points (e.g., a stack or vent). In Mexico , point source emissions data are transmitted to the federal and/or state environmental agencies (depending upon sector

- based jurisdiction) by means of the Annual Operating Certificate (Cédula de Operación Annual

– COA). As a result, the development of po int source emissions data for the 2005 Mexicali emissions inventory relied heavily on the cooperation of the government agencies that maintain emission registries

– the Secretariat of Environment and Natural Resources (SEMARNAT) for federal jurisdiction po int sources and the SPA for state jurisdiction point sources. The procedures used to compile emissions from the federal and state jurisdiction point sources are described below.

2.1 Federal Jurisdiction Point Source Methodology There are 16 federal jurisd iction point sources located in the municipality of Mexicali, which was confirmed by SEMARNAT. These point sources are listed below with their sector/subsector, as applicable:

 CFE Campo y Centrales Geotermoeléctrico de Cerro Prieto (Electricity Generation )

 CFE Central Turbo Gas (Electricity Generation)

 Dafmex, S. de R.L. de C.V. (Metallurgical/Ferrous Metal Foundry)

 Energía Azteca X, S. de R.L. de C.V. (Electricity Generation)

 Energía de Baja California, S. de R.L. de C.V., Central Termoeléctrica (Electr icity Generation)

 Fábrica de Papel San Francisco, S.A. de C.V. (Pulp and Paper/Paper Production)

 Fevisa Industrial, S.A. de C.V. (Glass/Container Glass Manufacture)

 Fundiciones San Martin o Felix Jesus del Valle Zamora (Metallurgical/Iron and Steel Foundr y)

 Infra, S.A. de C.V., Sucursal Mexicali (Chemical/Industrial Gases)

 Kenworth Mexicana, S.A. de C.V. (Automotive/Truck Manufacture)

 Kyowa Mexicali, S.A. de C.V. (Plastic Parts Manufacturing)2 005 Mexicali Emissions Inventory

Final, 2/27/09 2

- 2  Maquiladora San Diego, S.A. de C.V. (Metallurgical

– Iron and S teel Foundry)

 Petróleos Mexicanos (PEMEX) Refinación Planta Mexicali (Petroleum/Petroleum Products Storage and Distribution

 Quimical, S.A. de C.V. (Chemical/Pesticides and Agricultural Chemicals)

 Termoeléctrica de Mexicali, S. de R.L. de C.V. (Electricity Generation)

 Vitro AFG, S.A. de C.V. (Glass/Plane Glass Manufacture)
The physical location of some of the federal jurisdiction (and state jurisdiction) point sources in the urban portion of Mexicali is illustrated in Figure 2

- 1. The federal jurisdiction

p oint sources are shown as red dots (and the state jurisdiction point sources are shown as green dots). Some addition federal and state jurisdiction point sources located in the rural areas of Mexicali are not shown on Figure 2

- 1.

ICAR made the initial da ta request to SEMARNAT for existing information regarding emissions for the year 2005 from Mexicali federal jurisdiction point sources. SEMARNAT provided two electronic files in Excel format: “ Empresas Comp Federal (EMIS 230108).xls ” and “DATGEN_MEXICALI _05.xls”. The “ Empresas Comp Federal (EMIS 230108).xls ” file provided a listing of all federal jurisdiction sources located in the state of Baja California, as well as those federal jurisdiction sources that reported 2005 emissions to SEMARNAT. The
“DATG EN_MEXICALI_05.xls” file consisted of several sheets of which the following were most relevant for the compilation of emissions:

 Hoja1

– Complete facility description;

 EqComb

– Emissions from combustion equipment;

 ActProc

– Emissions from non

- combustion eq uipment and processes;

 Chim

– Stack parameters; and

 EqCont

– Description of control equipment. In general, the information contained in the “DATGEN_MEXICALI_05.xls” file was fairly complete. However, much of the data contained in this file was represente d in codes,2 005 Mexicali Emissions Inventory

Final, 2/27/09 2

- 3 Figure 2

- 1. Location of Federal and State Jurisdiction Point Sources in the Urban Portion of Mexicali2 005 Mexicali Emissions Inventory

Final, 2/27/09 2

- 4 abbreviations, and acronyms. As a result, ICAR made a subsequent request to SEMARNAT to provide the relevant data dictionaries needed to decipher the file. Subsequently, SEMARNAT provided two data dictionary files associated with the “DATGEN_MEXICALI_05.xls” file: “Diccionario_Datos_Datgen.xls” and “Codigos_catalogo.xls”. The “Diccionario_Datos_Datgen.xls” file provided the data dictiona ry and formats used by the “DATGEN_MEXICALI_05.xls” file, while the “Codigos_catalogo.xls” file provided a key for all of the codes, abbreviations and acronyms.

Using the “ Empresas Comp Federal (EMIS 230108).xls” and “DATGEN_MEXICALI_05.xls”, along with th e data dictionary files, ICAR compiled emissions from the federal jurisdiction point sources.

2.2 State Jurisdiction Point Source Methodology There are 173 state jurisdiction point sources located in the municipality of Mexicali. As seen in Figure 2

- 1, ma ny of these state jurisdiction point sources are clustered in the city’s industrial parks, which was confirmed by SEMARNAT. The names for these facilities are listed
in Table 2

- 1.

ICAR made an initial request to SPA for existing information regarding emis sions for the year 2005 from Mexicali state jurisdiction point sources. SPA provided two electronic files: “2

- REGISTROS (2005).xls” and “SIARE.mdb”. The “2

- REGISTROS (2005).xls” file provided a listing of all companies that submitted 2005 emission estim ates to SPA and identified the paper
file location within SPA offices of these emission submittals. The “SIARE.mdb” file is an
Access database which contains such information as:

 Facility name

 File number

 Inventory year

 Type and number of process that gen erate emissions

 Emission controls (if any)

 Pollutant type (in units of kg/hr and kg/year)2005 Mexi

cali Emissions Inventory

2 - 5 Final, 2/27/09 Table 2

- 1. Listing of State Jurisdiction Point Sources

Facility Name Facility Name Facility Name Accuride International, S.A. de C.V. (Nelson 6) Cervecería de Baja California, S.A. de C.V. Expopartes, S.A. de C.V. Accuride International, S.A. de C.V. (Pta

- Oeste, Nelson

- 12) Chromalloy, S.A. de C.V. (Planta 1) Fabricaciones y Montajes Metálicos, S.A. de C.V. Agribrands Purina México, S.A. de C.V. Chromalloy, S.A. de C.V. (Planta Ii) Fanosa, S.A. de C.V. Alimentos y Frituras de Baja California, S.A. de C.V. Cias. Periodísticas del Sol de Pacífico, S.A. de C.V. Femsa, S. de R.L. de C.V. American Meter de Mexico, S.A. de C.V. Compre Block Sucursal Criba Fetasa Culiacá n, S.A. de C.V. Amp Industrial Mexicana, S.A. de C.V. Compre Block, S.A. de C.V. Fetasa Industrial, S.A. de C.V Arrendadora del Colorado del Norte, S.A. de C.V. Con Mex de Mexicali, S.A. Fetasa Mexicali, S.A. de C.V. Ascotech, S.A. de C.V. Concretos Apa sco, S.A. de C.V. Flexcel

- Mexicali, S.A. de C.V. Asociacion Rural de Interes Colectivo de Baja California  ́80 de R.I. Concretos Bajanor de Mexicali, S.A. de C.V. Frituras de Mexicali, S.A. de C.V. Benq Mexicana, S.A. de C.V. Constructora Gallego, S.A. de C.V. (Planta 1) Fruvemex Mexicali, S.A. de C.V. Bi Technologies, S.A. de C.V. Constructora Gallego, S.A. de C.V. (Planta 2) Furukawa Mexico, S.A.de C.V. Bimbo, S.A. de C.V. Constructora Gusa, S.A. de C.V. Grayline de México, S.A. de C.V. Black & Decker Hhi México, S. de R.L. de C.V. (Pta

- 2) Controles de Mexicali, S. de R.L. Grupo Industrial Persal, S.A. de C.V. Black & Decker Hhi México, S. de R.L. de C.V. K1 Dafmex, S. de R.L. de C.V. Guaycan Quimicos y Petroliferos, S.A. de C.V. Black & Decker Hhi M éxico, S. de R.L. de C.V. K2 Dataproducts Imaging Solution, S.A. de C.V. Harinera de Maíz de Mexicali, S.A. de C.V. Black & Decker Hhi México, S. de R.L. de C.V. P1 Delivamex, S. de R.L. de C.V. Helados y Mezclas, S.A. de C.V. Block Centinela, S.A. de C. V. Display Orion Mexicana, S.A. de C.V. Honeywell Aerospace de México, S.A. de C.V.
Bloquera Moderna, S.A. de C.V. Eco Constructora, S.A. de C.V. Honeywell Productos Automotrices, S.A. de C.V. (Radiadores)

Blue Star, S.A. de C.V. Electronica Vanguard, S. A. de C.V. Honeywell Productos Automotrices, S.A. de C.V. (Turbos) Breg México, S. de R.L. de C.V. Embotelladora de Mexicali, S.A. de C.V. Hykam Electronica de Mexico, S.A. de C.V. Cajas Agricolas, S.A. de C.V. Emermex, S.A de C.V. Ideas Y/O Enrique Hern ández Santiago

Calidad Internacional de Pulido, S.A. de C.V. Emermex, S.A. de C.V. (Edif

- 3) Iluminación Cooper de Las Californias, S. de R.L. de C.V. Carley de México, S.A. de C.V. Empaques de Cartón Titán Impresora y Editorial, S.A. de C.V. Cd Electrón ica de Mexico, S.A de C.V. Empresas L.M., S. de R.L. de C.V. Industria de Refrescos del Noreste, S. de R.L. de C.V.

Cementos Químicos Industriales, S.A. de C.V. Energéticos y Grasas del Norte, S.A. de C.V. Industrial Vallera de Mexicali, S.A. de C.V. (Cot o Technologies)

Cemex Concretos, S.A. de C.V. Ensambladores Electrónicos de México, S.A. Industrial Vallera de Mexicali, S.A. de C.V. (Div. Vishay)

Cemex México, S.A. de C.V. Ensambles de Mexicali, S.A. de C.V. Industrial Vallera de Mexicali, S.A. de C.V

. (Loveday)

Centro Camionero de Mexicali, S.A. de C.V. Ensambles de Silleria Mexicana, S.A. de C.V. Industrial Vallera de Mexicali, S.A. de C.V. (Manik Motors)Table 2

- 1. Continued

2005 Mexicali Emissions Inventory

2 - 6 Final, 2/27/09 Facility Name Facility Name Facility Name Industrial Vallera de Mexicali, S.A. de C.V. (Martech

- Mdi West) Mextearinas, S.A. de C.V. Sabr itas, S. de R.L. de C.V.

Industrial Vallera de Mexicali, S.A. de C.V. (Másimo) Molinerea del Valle, S.A. de C.V. Sánchez Quiñónez César (Servicios y Acabados Industriales) Industrial Vallera de Mexicali, S.A. de C.V. (Merchants Metals) Muebles y Diseños El Bajio, S.A. de C.V. Sds de Mexico, S.A. de C.V. Industrial Vallera de Mexicali, S.A. de C.V. (Taymar Plastics) Navarrete Rayos Noel Alejandro Service Container de Baja, S. de R.L. de C.V. Industrias SL, S.A. de C.V. North Safety de Mexicali, S. de R.L . de C.V. Sigma Lapos, S.A. de C.V. Industrias Zahori, S.A. de C.V. Novamex México, S.A. de C.V. Sigma Lapos, S.A. de C.V. (Sucursal) Inovación en Concretos, S.A. de C.V. NSF Mexicali, S. de R.L. de C.V. Skyworks Solutions, S.A. de C.V.

International As sembly Specialists, S.A. de C.V. Nutricion Maxima de Baja California, S.A. de C.V. Solís Meraza María de La Cruz (Transformadora de Maderas Satélite) Isoclima de México, S.A. de C.V. Nutrimentos Mexicanos, S.A. de C.V. SPG de México, S.A. de C.V. Isoclim a de México, S.A. de C.V. Omega Industries, S.A. de C.V. Stone Container de México, S. de R.L. de C.V. J. Cox de México, S.A. de C.V. Operaciones de Clase Mundial, S.A. de C.V. Strategic Materials Mexicana, S.A. de C.V. Jean Charles Mexicali, S.A. de C.V

. Orthodental, S.A. de C.V. Sukarne Produccion, S.A. de C.V. Jumex Mexicali, S.A. de C.V. Panasonic Electric Works Mexicana, S.A. de C.V. Suntek Manufacturing Technologies, S.A. de C.V. Kang Seo Mexicana, S.A. de C.V. Partes Remanufacturadas de México, S .A. de C.V. Super Muros, S.A. de C.V. Kb Foam de Mexicali, S.A. de C.V. Pegamentos Industriales Galileo, S.A. de C.V. Technologies Solutions And Services, S.A. de C.V.
Kerns Beverages de México, S. de R.L. de C.V. Pims, S.A. de C.V. Tecnologías Internaci onales de Manufactura, S.A. de C.V. Kwang Sung Electronics México, S.A. de C.V. (Pta

- 1) Placas Termodinámicas, S.A. de C.V. Tecnomex Industrial, S.A. de C.V. Kyowa Mexicali, S.A. de C.V. Ponce Elizalde Armida (Transformadora de Maderas Tramex) Tecnomex I ndustrial, S.A. de C.V. L.G. Innotek Mexicali, S.A. de C.V. Procesadora y Empacadora de Carnes del Norte, S.A. de C.V. Temcomex, S.A. de C.V.

Lam

- Mex, S.A. Prodofi, S. de R.L. de C.V. Teradyne Connection Systems de México, S.A. de C.V. Lancer Orthodonti cs de México, S.A. de C.V. Productos de Acero de Baja, S.A. de C.V. Thomson Lechera Mexicana, S.A. de C.V. Productos de Barro, S.A. de C.V. Tri

- State de Mexico, S.A. de C.V. LG Electronics Mexicali, S.A. de C.V. Productos Hola del Noroeste, S.A. de C.V. Tubos de Acero Internacional, S.A. de C.V.
L

- N Safety Glass, S.A. de C.V. Productos Urólogos de Mexico, S.A de C.V. Valutech Out Sourcing, S.A. de C.V. Lopez Cazares Rafael Promotora Industrial Per, S.A. de C.V. Veladoras del Pacifico, S.A. de C.V. Lop ez Cazares Rafael (Rancho) Pulidora de Baja California, S.A. de C.V. Vimifos, S.A. de C.V. Maquiladora San Diego, S.A. de C.V. Pulidora Los Ángeles, S.A. de C.V. Wabash Technologies de México, S. de R.L. de C.V. Marko de México, S. de R.L. de C.V. Puliga mex, S.A. de C.V. Yiro Fabrica, S. de R.L. de C.V. Masterwork Electronics de México, S.A. de C.V. Rheem Mexicali, S. de R.L. de C.V. Zahori, S.A. de C.V. Megaplast, S.A. de C.V. Robert Bosch Tool de México, S.A. de C.V.2005 Mexicali Emissions Inventory

Final, 2/27/09 2

- 7  Type of fuel combusted

 Number of stacks
It should be noted that emissions were reported at the facility

- level, but not at the process

- or equipment

- level. Also, stack parameters (i.e., stack coordinates, stack height, stack diameter, exit gas velocity, and exit gas temperature) were n ot included in the “SIARE.mdb” file.

Based upon information contained in these two files, ICAR developed an Excel spreadsheet (“state_point_source_R0.xls”) that compiled the following data for each facility:

 Facility name

 Facility identification number (ID)

 Main activity

 Facility address

 Facility point of contact

 SCIAN code

 Emission quantification (kg/year)

 Type of control

 Facility latitude

 Facility longitude

 Emission points (i.e., the quantity and type of processes that generate emissions)

 Material type (i.e., type of fuel used)

 Basis of emissions estimate. All of these data were based upon information obtained from the “SIARE.mdb” file.

2.3 Results The federal jurisdiction point source emissions are shown in Table 2

- 2. Some
conclusions that can be draw n from Table 2

- 2 are that the power plants are the largest sources of
NO x , CO, and PM 10 . The PEMEX facility is the largest source of VOC emissions, while the2005 Mexicali Emissions Inventory

Final, 2/27/09 2

- 8 glass plants (i.e., Fevisa and Vitro AFG) and the paper plant (i.e., Fábrica de Papel San
Francis co) are the three largest sources of SO 2 . It should be noted that there are no emissions reported from the Federal Electric Commission (Comisión Federal de Electricidad

- CFE) geothermal power plant in Cerro Prieto.

Emissions for the 173 state jurisdictio n point sources are shown in Table 2

- 3, by industry group. From Table 2

- 3, it is clear that the Petroleum and Coal Products Manufacturing sector is the largest emitter of SO 2 and a significant contributor of NO x . The Other Industrial Manufacturing sector has the largest NO x emissions. Computer, Communication, and Electronic Manufacturing is the largest emitter of VOC, while Food Manufacturing and Primary Metals are the primary contributors of CO emissions. Emissions for PM 2.5 , NH 3 , and CH 4 are not inclu ded
in Table 2

- 2 because emissions of these pollutants were not estimated by SPA.

2.4 Quality Assurance

After compiling emissions for federal jurisdiction and state jurisdiction point sources, ICAR conducted quality assurance (QA) of these emissions. ICAR’s QA of the federal jurisdiction point sources used a QA checklist that focused on the following aspects:

 Facility information (i.e., North American Industry Classification System [NAICS] codes, address, latitude and longitude)

 Process/equipment infor mation (i.e., process/equipment description, source classification code [SCC], stack assignment)

 Emissions (i.e., pollutant completeness, emissions contribution, particulate matter, hydrocarbons, emission units, emission reasonableness)

 Stack parameters (i .e., stack height, stack diameter, exit gas temperature, exit gas velocity, stack latitude and longitude)

 Operating schedule (i.e., days per week, hours per day)

 Controls (i.e., control device, control efficiency)
Overall, ICAR’s QA evaluation indicated fa irly complete data for the federal jurisdiction point sources. However, a few specific data elements needed to satisfy the required characteristics of the Mexicali inventory were missing from some or all of the federal jurisdiction2005 Mexicali Emissions Inventory

Final, 2/27/09 2

- 9 Table 2

- 2. 2005 Mexic ali Federal Jurisdiction Point Source Emissions (Tons per Year)
Facility Name NO x SO 2 VOC CO PM 10 PM 2.5 CFE Central Turbo Gas Mexicali 27.4 11.8 1.9 2.4 CFE Campo y Centrales Geothermoeléctrico de Cerro Prieto Dafmex, S. de R.L. de C.V. 0.4 0.1 0.0 0.3 0.0 0.0 Energía Azteca X, S. de R.L. de C.V. 5,757.9 7.5 12.4 1,433.2 548.4 Energía de Baja California, S. de R.L. de C.V. Central Termoeléctrica 2,385.5 3.1 5.1 593.8 227.2 Fevisa Industrial, S.A. de C.V. 277.4 2,500.2 0.5 29.0 140.2 91 .6 Fábrica de Papel San Francisco, S.A. de C.V. 206.8 788.6 0.5 80.6 44.7 29.3 Infra, S.A. de C.V. Sucursal Mexicali 0.2 Kyowa Mexicali, S.A. de C.V. 0.1 0.0 76.3 0.1 0.0 0.0 Kenworth Mexicana, S.A. de C.V. 9.4 1.8 75.6 1.3 0.1 0.1 Maquiladora S an Diego, S.A. de C.V. 0.9 0.4 0.2 30.0 2.4 2.2 PEMEX Refinación Planta Mexicali 458.9 Quimical, S.A. de C.V. 0.0 0.0 0.0 0.0 0.0 0.0 Termoeléctrica de Mexicali, S. de R.L. de C.V. 4,664.2 6.1 10.1 1,161.0 444.2 Vitro AFG, S.A. de C.V. 601.4 330. 1 19.4 233.9 128.0 5.1 Fundiciones San Martin o Felix Jesus del Valle Zamora 0.2 1.1 0.1 71.1 0.0 0.0 Total 13,931.7 3,650.9 659.3 3,636.2 1,537.7 128.4
Table 2

- 3. 2005 Mexicali State Jurisdiction Point Source Emissions (Tons per Year)
3

- Digit NAICS NA ICS Description NO x SO 2 VOC CO PM 10 212 Mining (metallic and nonmetallic) 1.47 0.00 0.00 0.09 12.92 311 Food industry 70.11 60.84 0.00 243.61 22.53 312 Beverages/tobacco industry 1.80 0.00 0.00 0.23 0.00 321 Wood products industry 0.00 0.00 0.00 0.00 0 .72 322 Paper industry 5.58 0.00 3.35 2.67 2.80 323 Publishing industry 0.00 0.00 0.14 0.00 0.00 324 Petroleum and coal products manufacturing 133.76 732.91 0.00 10.07 2.71 325 Chemical industry 0.31 0.00 0.00 0.03 0.00 326 Plastics and rubber industr y 27.22 116.90 2.08 9.03 7.97 327 Nonmetallic materials manufacturing 11.04 0.12 4.48 7.06 3.27 331 Primary metals industry 11.31 19.95 0.00 121.58 0.24 332 Metal products manufacturing 4.81 0.00 7.64 16.05 6.89 333 Equipment and machinery manufacturin g 5.94 0.00 2.36 7.48 0.48

334 Computer, communication, electronics manufacturing 2.13 0.19 33.98 16.09 9.45 335 Electricity generation equipment manufacturing 0.00 0.00 0.03 0.00 0.02 336 Transportation equipment manufacturing 0.71 0.00 1.42 12.90 12.2 8 337 Furniture manufacturing 1.99 0.00 14.53 6.06 1.28 339 Other industrial manufacturing 157.76 0.00 3.22 26.85 5.99 493 Storage service 8.02 42.27 0.00 0.08 0.00 Total 443.97 973.19 73.23 479.88 89.552005 Mexicali Emissions Inventory

Final, 2/27/09 2

- 10 point sources. The first data element was pr ocess/equipment SCC, which was missing from all sources; this was gap filled using engineering judgment based upon the specific process equipment description and fuel type. The stack latitude and longitude coordinates were also missing from a number of th e sources. In most cases, these coordinates were for sources with a large number of processes that typically did not have well

- defined stacks (e.g., vents, etc.). For these sources, the facility latitude and longitude coordinates were assigned to the sta ck(s).

The most significant data problem identified by ICAR’s QA evaluation of the state jurisdiction point sources was that none of the facilities had process

- or stack

- level emissions. After identifying this issue, ERG and ICAR focused on the seven most significant state jurisdiction point source emitters (i.e., Bimbo, Chromalloy, Sabritas, Sukarne, Temcomex, Thomson, and Zahori). ICAR searched the SPA paper files to obtain process

- and stack

- level
emissions for these seven sources. Data obtained from the SPA paper files included the following:

 Number of sources

 Process/equipment description and codes

 Stack assignment

 Emission units

 Stack coordinates

 Stack height

 Stack diameter

 Exit gas velocity

 Exit gas temperature

 Operating schedule (days/year, hours/ day)

 Controls (device and efficiency)
In addition to the detailed data collected for the seven most significant state jurisdiction point source emitters listed above, similar process

- and stack

- level data from the SPA files were2005 Mexicali Emissions Inventory

Final, 2/27/09 2

- 11 subsequently researched for another 85 state jurisdiction point sources. However, project constraints prevented similar data collection for the remaining 81 facilities.
Two of the five data quality objectives (DQOs) for the Mexicali inventory project are applicable to point source emissions. These are as follows:

1. Identification of 80% of all federal jurisdiction and state jurisdiction point sources located within the municipality of Mexicali.
Acceptance criteria: A list of point sources under the federal (SEMARNAT Delegation), and state (SPA) jurisdictions compares to the emissions data, by source, provided by those agencies.

2. Point sources: Emissions estimates with an accuracy of ± 25% for at least 10% of the facilities.
Acceptance criteria: Estimated emissions for 10% o f the total facilities compare to measured emissions of all pollutants with ± 25% accuracy. The emissions data measurements will be obtained from subcontractor ICAR, and will be based on data collected over the past five years in Mexicali.

Based on the fe deral jurisdiction and state jurisdiction point source methodologies and quality assurance used, both DQOs were met. With regard to DQO #1, all federal jurisdiction and state jurisdiction point sources were included. The lists of federal jurisdiction and state jurisdiction point sources were checked multiple times with SEMARNAT and SPA to ensure completeness. For DQO #2, ICAR checked process

- and stack

- level data obtained from SEMARNAT electronic files (for federal jurisdiction sources) and from SPA pape r files (for state jurisdiction sources) against information they had previously obtained from their industrial clients (2 federal jurisdiction sources and 38 state jurisdiction sources). Overall, emissions data were within ± 25% accuracy.2005 Mexicali Emissions Inventory

Final, 2/27/09 3

- 1 

## 3.0 AREA SOURCE S

Area sources are sources that are too numerous and dispersed to be effectively included in the point source inventory. Area sources include some commercial and/or industrial sources such as autobody shops and dry cleaners, fugitive sources such as pave d and unpaved road dust, and fuel combustion in small boilers. The methodology used to estimate the 2005 Mexicali area
source emissions is described below.

3.1 Methodology

Wherever possible, local activity data were collected in Mexicali and used to es timate area source emissions. Local activity data collection was facilitated by ICAR, who are conveniently located in Mexicali. ICAR contacted some local sources of activity data directly (e.g., PEMEX, fire departments, etc.); in other situations, ICAR w orked through SPA to reach these contacts (e.g., natural gas and LPG distributors, Department of Health, etc.).

If local activity data could not be collected from local contacts, then data from publicly available government agencies were used. In addition , some methodologies and data from the development of the 1999 Mexico NEI and recent emissions inventory work conducted in 2007 in San Luis Río Colorado, Sonora and the northeastern (agricultural) portion of Mexicali were also used (ERG, 2006; ENVIRON and ERG, 2008).

General estimation methodologies for related groups of area source categories are
described below and summarized in Table 3

- 1. Detailed documentation for each area source category is provided through the Area Source Category Forms, which are l ocated in Appendix A. The Area Source Category Forms succinctly summarize the following for each source category: category description, pollutants, method, activity data, emission factors, notes and assumptions, emission calculations, and spatial allocat ion surrogates.2005 Mexicali Emissions Inventory

3 - 2 Final, 2/27/09 Table 3

- 1. General Emission Estimation Methodologies for Area Sources in Mexicali

Source Category Pollutants Methodology Activity Data Spatial Allocation Notes Industrial Fuel Combustion

– Distillate & Residual Fuel Oil, Natural Gas, L PG NO x , SO 2 , VOC, CO, PM 10 , PM 2.5 , CH 4 AP

- 42 emission factors Local use statistics Employee data by sector Reconciled with point

sources. Commercial/Institutional Fuel Combustion

– Natural Gas & LPG NO x , SO 2 , VOC, CO, PM 10 , PM 2.5 , CH 4 AP

- 42 emission facto rs Local use statistics Employee data by sector Residential Fuel Combustion

– Natural Gas & LPG NO x , SO 2 , VOC, CO, PM 10 , PM 2.5 , CH 4 AP

- 42 emission factrs Local use statistics Household data

Architectural Coating VOC Mexico

- specific per capita emission factors Population Population Emissions estimated for solvent

- and water

- based coatings.

Industrial Surface Coating VOC Mexico

- specific per employee emission factors Employment data by sector Employee data by

sector Seven subcategories.

Reconciled with po int

sources. Autobody Refinishing VOC Mexico

- specific per employee emission factors Employment data Employee data
Graphic Arts VOC Mexico

- specific per capita emission factors Population Population
Dry Cleaning VOC Mexico

- specific per employee emission factors Employment data Employee data Petroleum

- based solvents only; no perchloroethylene

Degreasing VOC EIIP per employee emission factors Employment data by sector Employee data Four subcategories. Reconciled with point

sources.

Consumer Solvents VOC EIIP per capita emission factors (slightly adjusted) Population Population U.S. emission factors

– household and automotive factors modified to represent Mexican conditions.

Traffic Markings VOC 1999 Mexico NEI results N/A Paved road network Local applied quantities

were unavailable. Used information from 1999 Mexico NEI.

Asphalt Application VOC 1999 Mexico NEI results N/A Paved road network Local applied quantities

were unavailable. Used information from 1999 Mexico NEI.Table 3

- 1. Continued

2005 Mexicali Emissions Inventory

3 - 3 Final, 2/27/09 Source Category Pollutants Methodology Activity Data Spatial Allocation Notes

Petroleum Transport and Distribution VOC EIIP emission factors Local fuel throughput Population Stage I controls (submerged with vapor balance; no Stage II controls)

Agricultural Burning NO x , SO 2 , VOC, CO, PM 10 , PM 2.5 ARB emission factors Burned acreage Agricultural land use da ta Burning limited to wheat,

sorghum, and weeds in irrigation canals and ditchbanks.
Agricultural Tilling PM 10 , PM 2.5 ARB emission factors Planted acreage Agricultural land use data
Agricultural Harvesting PM 10 , PM 2.5 ARB emission factors Harvested acre age Agricultural land use data

Agricultural Pesticides VOC EIIP emission factors Harvested acreage, type and quantity of pesticides applied Agricultural land

use data Pesticide application rates

limited to eight crop types

Beef Cattle Feedlots PM 10 ARB emission factors Number of slaughtered cattle Agricultural land

use data

Livestock VOC VOC ARB emission factors Number of livestock head Agricultural land

use data

Livestock Ammonia NH 3 WRAP NH 3 model emission factors Number of head Agricultural land

u se data

Fertilizer Application NH 3 WRAP NH 3 model emission factors Planted acreage, type and quantity of fertilizers applied Agricultural land

use data Fertilizer application rates

limited to eight crop types

Paved Road Dust PM 10 , PM 2.5 AP

- 42 emission f actor equation Local VKT, silt loading, vehicle speed, precipitation Paved road

network VKT to be developed in

conjunction with motor vehicle emissions/ consideration of silt loading samples

Unpaved Road Dust PM 10 , PM 2.5 AP

- 42 emission factor equation Loc al VKT, silt content, moisture content, vehicle weight and speed, precipitation Unpaved road

network VKT to be developed in

conjunction with motor vehicle emissions/ consideration of silt content and moisture content samples

Structural Fires NO x , VOC, CO, PM 10 , PM 2.5 , CH 4 EIIP emission factors Number of houses burned PopulationTable 3

- 1. Continued

2005 Mexicali Emissions Inventory

3 - 4 Final, 2/27/09 Source Category Pollutants Methodology Activity Data Spatial Allocation Notes

Border Crossing (idling vehicles from Mexicali to California) NO x , SO 2 , VOC, CO, PM 10 , PM 2.5 , NH 3 MOBILE6

- Mexico emission factors Local traffic counts, idling times Border crossing Emission factors from MOBILE6

- Mexico

Brick Kilns NO x , SO 2 , VOC, CO, PM 10 , PM 2.5 Utilization of previous inventory Not applicable Brick kiln locations

Charbroiling/Street Vendors NO x , SO 2 , VOC, CO, PM 10 , PM 2.5 1999 Mexico NEI results N/A Population Local data were unavailable. Used information from 1999 Mexico NEI grown based on population.

Construction Dust PM 10 , PM 2.5 1999 Mexico NEI results N/A Population Local data were unavailable. Used information from 1999 Mexico NEI grown based on population.

Landfills VOC, CH 4 AP

- 42 emission factors Annual quantity of waste landfilled, opening year Landfill location

Wastewater Treatment Plant VOC U.S. EPA emission factor Wastewater flow rates Plant location Local data unavailable to run mod el.2005 Mexicali Emissions Inventory

Final, 2/27/09 3

- 5 3.1.1 Fuel Combustion Categories Fuel combustion categories include industrial fuel combustion, commercial/institutional fuel combustion, and residential fuel combustion. Wherever possible, local collected data were
used to estimate emissions. If local data were unavailable, publicly available government fuel
statistics at the national

- and regional

- level were disaggregated down to the Mexicali municipality.

Industrial fuel combustion includes distillate fuel oil, residual fuel oil, liquefied petro leum gas (LPG), and natural gas while the commercial/institutional and residual fuel combustion source categories are limited to LPG and natural gas. Attempts were made by SPA and ICAR to contact all of the Mexicali fuel distributors. Natural gas statist ics were obtained from Ecogas Mexico, S. de R.L. de C.V. (Vivo, 2008). Four LPG distributors were contacted; three of these distributors provided 2005 sales information (Álvarez Sánchez, 2008; Escalante, 2008; Félix Robles, 2008). Sales information from the three LPG distributors that provided information were averaged together and then applied to the LPG distributor that did not provide
information.

The PEMEX terminal in Mexicali provided sales information regarding gasoline and distillate fuel (inclu ding motor vehicle, agricultural, and industrial uses), but did not respond to requests for information regarding residual fuel oils (Parra Armenta, 2008). Residual fuel oil information was obtained from the PEMEX terminal in Rosarito, which markets resid ual fuel oil in Mexicali (Miranda Palazuelos, 2008).

Biomass combustion appears to be virtually nonexistent; most heating during the mild winters is electric heating (Martinez, 2007).

3.1.2 Evaporative VOC Categories Evaporative VOC categories include t he following area source categories: architectural surface coating, industrial surface coating, degreasing, graphic arts, traffic markings, dry cleaning, consumer products, asphalt application, and gasoline distribution.

The development of Mexico

- specific emission factors as part of the 1999 Mexico NEI for architectural surface coating, industrial surface coating, graphic arts, and dry cleaning was a2005 Mexicali Emissions Inventory

Final, 2/27/09 3

- 6 significant advance. These emission factors were based upon data from the National Association
of Paint an d Dye Manufacturers (Asociación Nacional de Fabricantes de Pinturas y Tintas

– ANAFAPYT) and the National Chamber of the Dry Cleaning Industry (Cámara Nacional de la
Industria de Lavanderías

– CANALAVA) (ANAFAPYT, 2003; ANAFAPYT, 2004; CANALAVA, 2002). Th ese Mexico

- specific emission factors were combined with Mexicali population and sector

- specific employee counts. The industrial surface coating emissions were also reconciled with emissions from point source industrial surface coating operations

Because M exico

- specific emission factors were not developed for degreasing and consumer products, per capita and per employee emission factors were obtained from the Emission Inventory Improvement Program (EIIP) guidance documents (EIIP, 1996; EIIP, 1997).
However , recent health survey data collected in San Luis Río Colorado, Sonora indicate lower usage of household products corresponding to increased usage of bleach and a virtual absence of windshield fluid (Fierro and O’Rourke, 2007; Fierro, 2007; Gonzalez

- Ayala, 2007); the EIIP emission factors were adjusted to account for these findings. The degreasing emissions were also reconciled with emissions from point source degreasing operations.

Traffic markings and asphalt application quantities were requested from th e Mexicali Public Works Department; however, these quantities were not available (Reynoso Ambriz, 2008). As a result, the emission estimates for traffic markings and asphalt application from the 1999 Mexico NEI were used for the municipality of Mexicali.

Gasoline sales statistics were obtained from PEMEX (Parra Armenta, 2008), while gasoline distribution emission factors were obtained from EIIP guidance (EIIP, 2001a).

3.1.3 Agricultural Categories The northeast portion of Mexicali has significant agricultu ral activity. Activity data for four specific agricultural categories (i.e., pesticides, burning, tilling, and harvesting) were requested from both the state and federal agricultural agencies. These four agricultural categories were previously estimated for the 2005 San Luis Río Colorado and northeastern Mexicali inventory (ENVIRON and ERG, 2008). Originally, it was anticipated that improved information could be collected from the state and federal agricultural agencies for Mexicali; however, the only us eful agricultural information that could be obtained was estimates of2005 Mexicali Emissions Inventory

Final, 2/27/09 3

- 7 burning of wheat residues, sorghum residues, and weeds in irrigation canals and drainages (Rodríguez Hernández, 2008; López Bojorques, 2008). Agricultural burning methodologies
from the California Air Resources Board (ARB) were used to estimate emissions (ARB, 2005).

Crop acreage information was provided for the agricultural tilling and harvesting source categories; however, this information had previously been obtained from a government database (SAGARPA, 2007a). For the previous inventory work in San Luis Río Colorado and northeastern Mexicali, municipality

- level emissions for agricultural tilling and harvesting were spatially allocated in order to estimate the portion of emissions tha t were contained within that project’s modeling domain (ENVIRON and ERG, 2008). For the 2005 Mexicali inventory, the previously estimated municipality

- level emissions were simply used without the modeling domain spatial allocation. The previous agricultu ral tilling and harvesting estimates were based upon ARB methodologies (ARB, 2003a; ARB, 2003b).

Emissions from agricultural pesticides were estimated by applying pesticide

- specific emission factors to the quantities of pesticides applied. Typical crop

- sp ecific pesticide application rates were obtained from state

- specific cost production estimates (SAGARPA, 2007b). However, the application rates were only available for a limited number of crops (i.e., garlic, green alfalfa, cotton, broccoli, asparagus, to matoes [green and red], and wheat). These pesticide application rates were applied to the crop

- specific planted acres. specific pesticide application rates. Pesticide emission factors were obtained from EIIP guidance (EIIP, 2001b). Active ingredients we re identified based upon Mexico’s Registry of Authorized Pesticides (COFEPRIS, 2007). Formulation types were also assumed based upon the predominant formulation types listed in the Registry. Active and inactive ingredient fractions, as well as inert ingr edient VOC fractions, were obtained from the EIIP guidance. Pesticide information (i.e., density, % active ingredient, and vapor pressure) was obtained from various databases maintained by California’s Department of Pesticide Regulation (DPR, 2007).

Beef cattle feedlots are a source of fugitive dust caused by cattle movement over dusty ground. Slaughter statistics were used to estimate the number of cattle in feedlots. There are approximately 11 feedlots in Mexicali, all located outside of the urban area (Rodr í guez Hern á ndez, 2008). It has been estimated that cattle stay in the feedlots for approximately 902005 Mexicali Emissions Inventory

Final, 2/27/09 3

- 8 days prior to being slaughtered (Sukarne, 2008). The beef cattle feedlot emission factor was obtained from ARB (ARB, 2004).

VOC emissions from lives tock (i.e., beef cattle, dairy cattle, swine, sheep, and goats were
also estimated. State

- and district

- level livestock headcounts were obtained from a SAGARPA database and then allocated to the municipality

- level based on slaughter statistics (SAGARPA,
2 007c). The livestock VOC emission factors were obtained from ARB (ARB, 2004).

3.1.4 Ammonia Categories Two important ammonia area source categories in a regional inventory are typically livestock ammonia and agricultural fertilizers. State

- and distri ct

- level livestock headcounts were obtained from a SAGARPA database and then allocated to the municipality

- level based on slaughter statistics (SAGARPA, 2007c). The livestock ammonia e mission factors were based on information gathered from literature revi ews that is currently being implemented in the latest Western Regional Air Partnership (WRAP) NH 3 modeling (Chinkin et al., 2003).

Emissions from agricultural fertilizers were estimated by applying fertilizer

- specific emission factors to the quantities of fertilizer applied. Similar to agricultural pesticides, typical

crop

- specific fertilizer application rates were obtained from state

- specific cost production estimates (SAGARPA, 2007b). As with the pesticides, application rates were only available for
a l imited number of crops (i.e., garlic, green alfalfa, cotton, broccoli, asparagus, tomatoes [green and red], and wheat). Ammonia emission estimates from fertilizer application were developed using emission factors from the European Environment Agency (EEA, 2002) as recommended in the development and application of the WRAP NH 3 model.

3.1.5 Paved Road Dust Paved road dust emissions were estimated using the most recent emission factor equation presented in the U.S. EPA Compilation of Air Pollutant Emission Factors (AP

- 42), Section 13.2.1 (revised November 2006) (U.S. EPA, 1995). Silt samples were collected at 10 locations in Mexicali by ICAR in July 2008. The 10 locations are shown in Figure 3

- 1 (numbered 1 through 10) and are as follows:

 1

– Calzada Lázar o Cárdenas between Calzada Benito Juárez and Calzada Venustiano Carranza2005 Mexicali Emissions Inventory

3 - 9 Final, 2/27/09 Figure 3

- 1. Location of Paved and Unpaved Road Dust Sampling Sites2005 Mexicali Emissions Inventory

Final, 2/27/09 3

- 10  2

– Calzada Independencia between Boulevard Adolfo López Mateos and Calle Río Culiacán

 3

– Calzada Industrial Palaco between Calzada M. Gómez Morin and Calzada Lázaro Cárdenas

 4

– Francisco I. Madero between Calle Justo Sierra and Calle “F”

 5

– Calzada Anahuac between Avenida Torino and Avenida Gobernador

 6

– Avenida Oaxaca between Calle Uxmal and Heroico Colegio Militar

 7

– Calle Río Mocorito between Calzada Cuauhtémoc and Avenida F. Montes de Oca

 8

– Calzada Laguna de Xochimilco between Calzada Anahuac and Granada

 9

– Avenida Río Verde between Calle Cuarta and Calle Novena

 10

– Avenida Centauro del Norte between Calzada Lázaro Cárdenas and Calzada Héctor Terán Terán
All samples were collected according to the sampling procedures presented in Appendix
C.1 of AP

- 42 (U.S. EPA, 1995). The samples were analyzed by a laboratory in Tijuana, Laboratorio de Muestreo y Aná lisis, S.A. de C.V., according to the analytical procedures presented in Appendix C.2 of AP

- 42 (LMA, 2008a). The paved road dust emission factors (PM 10 and PM 2.5 ) were calculated using the AP

- 42 methodology; emission factors were calculated for each sampl ing site and then averaged together. A precipitation adjustment factor of 0.98562 corresponding to 21 “wet” days was also used (NWS, 2005).

The vehicle kilometers traveled (VKT) estimate used to estimate paved road dust emissions was developed in conjunct ion with the on

- road mobile source VKT development (see Section 4.0 of this report for details). Figure 3

- 2 demonstrates a portion of the analysis to determine the split of paved and unpaved analysis; further details are located in Appendix B, Section VI, of this report. The estimated paved road dust emission factors were then combined
with the link

- level paved road VKT to obtain link

- level paved road dust emissions (Gonzalez

Ayala, 2008a).2005 Mexicali Emissions Inventory

Final, 2/27/09 3

- 11

Figure 3

- 2. Pavement Coverage of Mexicali Roads

Pavement coverage detail for urban Mexicali2005 Mexicali Emissions Inventory

Final, 2/27/09 3

- 12 3.1.6 Unpaved Road Dust Unpaved road dust emissions were estimated using the most recent emission factor equation presented in AP

- 42, Section 13.2.2 (revised November 2006) (U.S. EPA, 1995). Silt samples were collected at 10 locations in Mexicali by ICAR in July 2008. The 10 locations are shown in Figure 3

- 1 (marked with letters A through J) and are as follows:

 A

– Calle Caoba between Calle Mauto and Calle Olivo

 B

– Calle Mérida between Avenida Nayarit and Avenida Puebla

 C

– Avenida Río Atoyac between Calle Onceava an d Calle Terceava

 D

– Avenida Camino Real between Avenida Campestre and Avenida Valle Verde

 E

– Calle Texcoco between Calzada Laguna de Xochimilco and Avenida Acolman

 F

– General Jesus M. Garza at Calle Federación

 G

– Avenida Ricardo Flores Magón between Ca lle Bernardo Reyes and Calle Filomeno Mata

 H

– Calle de las Delicias between Avenida de los Insurgentes and Avenida Juan Álvarez

 I

– Calle Venustiano Carranza between Avenida Nuevo León and Avenida Querétaro

 J

– Carretera Relleno Sanitario (on the road to Hipolito Landfill; location in Figure 3

- 1 is not to scale)
All samples were collected according to the sampling procedures presented in Appendix
C.1 of AP

- 42. The samples were analyzed by Laboratorio de Muestreo y Análisis, S.A. de C.V. in Tijuana accordi ng to the analytical procedures presented in Appendix C.2 of AP

- 42 (LMA, 2008b). The unpaved road dust emission factors were calculated using the AP

- 42 methodology. Three different emission factors were calculated at each sampling site using different ve hicle speeds: urban (11 miles per hour [mph]), suburban (18 mph), and rural (25 mph). Three average emission factors (i.e., urban, suburban, and rural) were then calculated by averaging together the emission factors over all of the sites. A precipitatio n adjustment factor of 0.94247 corresponding to 21 “wet” days was also used (NWS, 2005).2005 Mexicali Emissions Inventory

Final, 2/27/09 3

- 13 Three different sets of unpaved emission factors (PM 10 and PM 2.5 ) were estimated for urban, suburban, and rural unpaved roads. The estimated unpaved road dust emissio n factors
were then combined with the link

- level unpaved road VKT to obtain link

- level unpaved road dust emissions (Gonzalez

- Ayala, 2008b).

The VKT estimate used for estimating paved road dust emissions was developed in conjunction with the on

- road mobile source VKT development (see Section 4.0 of this report). Figure 3

- 2 demonstrates a portion of the analysis to determine the split of paved and unpaved analysis; further details are located in Appendix B, Section VI, of this report.

3.1.7 Miscellaneous Bur ning Categories Area source inventories can potentially have a number of miscellaneous burning categories. These include wildfires, prescribed fires, on

- site incineration, open burning, and structural fires. Based on site visits and interviews, the only miscellaneous burning activity that
occurs in Mexicali is structural fires. The number of structural fires was obtained from the Mexicali fire department (Ruiz Burgue ñ o, 2008), while the appropriate emission factors were obtained from EIIP guidance (EIIP, 2001a).

3.1.8 Border Crossings Emissions from idling vehicles queued to enter the United States were estimated as an area source, and were not included in the on

- road mobile sources estimates. There are three border crossings in Mexicali: Calexico and Calexico East (both across from urban Mexicali) and Andrade (across from Algodones). Vehicle count and queue waiting times were obtained from the Bureau of Transportation Statistics (BTS, 2008). Emission factors were estimated using the
MOBILE6

- Mexico em ission factor model (ERG, 2003).

3.1.9 Brick Kilns The municipality of Mexicali has two distinct brick kiln areas. The first area is in Colonia Campestre and the second area is in Algodones (i.e., northeast Mexicali). Emissions from the Algodones brick k iln area were previously estimated as part of the 2007 inventory work in San Luis Río Colorado and northeastern Mexicali (ENVIRON and ERG, 2008); these
emissions were re

- used for the Mexicali inventory. Accurate activity data could not be collected
at Col onia Campestre, therefore emission estimates from the smaller San Luis Río Colorado2005 Mexicali Emissions Inventory

Final, 2/27/09 3

- 14 brick kiln area (i.e., Colonia La Grullita) were assumed to be representative of the Colonia Campestre brick kiln emissions.

3.1.10 Charbroiling, Construction Dust, and Ba keries
Detailed Mexicali

- specific activity data for charbroiling (restaurants and street vendors), construction dust, and bakeries could not be obtained. Emissions for these area source categories were extrapolated from the 1999 Mexico NEI (ERG, 2006). C onstruction dust emissions were disaggregated into two categories: residential construction and industrial/commercial
construction.

3.1.11 Landfills The municipality of Mexicali has one landfill (Hipolito landfill) which is located south of
the urban are a. Emissions were estimated using U.S. EPA’s theoretic first order kinetic model of methane production (U.S. EPA, 1995). Many of the site

- specific data needed to make an accurate estimation of emissions (e.g., methane generation potential, methane genera tion rate constant, temperature, etc.) were not available. The only information that was obtained regarding the landfill was the year it opened and the daily quantity of waste landfilled (Villegas Ibarra, 2008). Default values were used for all other nec essary parameter variables.

3.1.12 Wastewater Treatment The municipality of Mexicali has eight wastewater treatment facilities: four in Mexicali and single facilities in Ciudad Morelos (Cuervos), Guadalupe Victoria (Km. 43), Vicente Guerrero (Algodones), and San Felipe. These facilities have a combined installed capacity of 2.964 cubic meters per second (m 3 /s) with an actual treatment rate of 1.8494 m 3 /s (CNA, 2007). This treatment rate translates to an annual flow of 58,322,678,400 liters. The VOC emis sion factor for wastewater treatment was then applied to this annual flow (U.S. EPA, 1991).

3.2 Results The 2005 Mexicali area source emissions inventory is presented in Table 3

- 2.
Examination of Table 3

- 2 indicates the following regarding area source em issions in Mexicali in
2005:

 Agricultural field burning is the largest source of NO x followed by industrial natural

gas combustion and residential LPG combustion.2005 Mexicali Emissions Inventory

3 - 15 Final, 2/27/09 Table 3

- 2. 2005 Mexicali Area Source Emissions (Tons per Year)

Source Category NO x SO 2 VOC CO PM 10 PM 2.5 NH 3 CH 4 Industrial Distillate Combustion 66.47 2.29 0.67 0.00 3.27 0.82 0.00 0.17 Industrial Residual Combustion 0.00 0.00 1.58 0.00 11.06 10.45 0.00 5.64 Industrial Natural Gas Combustion 279.79 0.00 6.30 0.00 8.40 8.73 4.45 Commercial Natural Gas Combustion 2.58 0.02 0.14 2.17 0.20 0.20 0.06 Residential Natural Gas Combustion 7.33 0.05 0.43 3.12 0.59 0.59 0.18 Industrial LPG Combustion 56.33 0.16 3.43 32.09 3.02 3.02 0.82 Commercial LPG Combustion 23.63 0.07 1.44 13.46 1.27 1.27 0.34 Residential LPG Combustion 102.97 0.29 6.27 58.65 5.52 5.52 1.49 Paved Road Dust 4,609.79 422.18 Unpaved Road Dust 42,331.35 4,209.66 Charbroiling/Street Vendors 2.77 9.69 150.18 75.44 60.21 Bakeries 117.94 Construction Ac tivities

– Residential 16.77 3.49 Construction Activities

– Industrial/Commercial 118.59 24.65 Architectural Surface Coating (Solvent

- based) 311.48 Architectural Surface Coating (Water

- based) 167.27 Autobody Refinishing 78. 74 Traffic Markings 57.06 Industrial Surface Coating

- Wood Furniture 64.78 Industrial Surface Coating

- Other Metallic Products 1,007.07Table 3

- 2. Continued

2005 Mexicali Emissions Inventory

3 - 16 Final, 2/27/09 Source Category NO x SO 2 VOC CO PM 10 PM 2.5 NH 3 CH 4 Industrial Surface Coating

– Electronics 32.47 Industrial Surface Coating

– Auto motive 1,281.22 Industrial Surface Coating

- Other Transportation 327.24 Industrial Surface Coating

- Other Manufacturing 1,262.62 Industrial Surface Coating

- Industrial Maintenance 433.48 Degreasing (Vapor and In

- line clea ning

- Other) 323.47 Degreasing (Vapor and In

- line cleaning

– Electronics 284.68 Degreasing (Cold Cleaning

– Other) 744.18 Degreasing (Cold Cleaning

- Automotive Repair) 565.11 Dry Cleaning 145.74 Graphic Arts 346. 90 Consumer Solvents

- Personal Care 993.18 Consumer Solvents

– Household 84.62 Consumer Solvents

- Automotive Aftermarket 67.61 Consumer Solvents

– Coatings 242.98 Consumer Solvents

- Adhesives and Sealants 761.13 Consumer Solvents

- Federal Insecticide, Fungicide and 409.59Table 3

- 2. Continued

2005 Mexicali Emissions Inventory

3 - 17 Final, 2/27/09 Source Category NO x SO 2 VOC CO PM 10 PM 2.5 NH 3 CH 4 Rodenticide Act (FIFRA) Products Consumer Solvents

- Miscellaneous 29.58 Asphalt Application 145.97 Agricultural Pesticides 216.60 Gasoline Distribution

– St age I 12.72 Gasoline Distribution

– Stage II 419.88 Gasoline Distribution

- Spillage 25.45 Underground Tank Breathing 38.17 Tank Truck Transit 4.45 Landfills 235.46 6,019.90 Wastewater Treatment 835.76 Agricultural Tilling 929.76 206.13 Agricultural Harvesting 767.74 170.21 Agricultural Field Burning 621.30 126.57 1,078.07 17,384.11 1,596.17 1,521.23 Fertilizer application

– Anhydrous ammonia 660.75 Fertilizer application

– Urea 4,878.75 Fertilizer application

– N

- P

- K 436.84 Fertilizer application

– Calcium nitrate 2.69 Fertilizer application

– Diammonium phosphate 1.38 Beef cattle feedlots 290.72 Livestock

– Dairy Cattle (NH 3 and VOC) 32 2.77 1,389.78 Livestock

– Beef Cattle (NH 3 and VOC) 1,025.42 1,589.51 Livestock

– Swine (NH 3 and VOC) 10.92 36.65Table 3

- 2. Continued

2005 Mexicali Emissions Inventory

3 - 18 Final, 2/27/09 Source Category NO x SO 2 VOC CO PM 10 PM 2.5 NH 3 CH 4 Livestock

– Sheep (NH 3 and VOC) 4.43 13.63 Livestock

– Goats (NH 3 and VOC) 2.77 3.70
Structure Fires 0.11 0.85 4.64 0.82 0.76 0.22 Border Crossing 20.65 0.41 46.86 428.04 2.28 1.91 1.56 Brick Kilns 21.55 1.23 704.91 777.55 106.51 102.50

Total 1,205.48 131.09 15,301.55 18,854.02 50,879.89 6,753.65 9,015.23 6,033.28

Blanks indicate pollutant(s) are not applicable; 0.00 indicates pollutant emissions are insignificant.2005 Mexicali Emissions Inventory

Final, 2/27/09 3

- 19  Agricultural field burning is also the largest source of SO 2 . Typically, there would be high SO 2 emissions from industrial residual combustion, but reconciliation with the point source i nventory reduced the area source industrial residual combustion emissions to zero. In fact, the estimated SO 2 emissions from industrial residual combustion were 3,275 tons.

 There are a number of VOC sources that emit approximately 1,000 tons per year: ag ricultural field burning, several types of industrial surface coating, several types of consumer solvents, wastewater treatment, and dairy cattle. However, if some of these subcategories are aggregated together, then overall, industrial surface coating an d consumer solvents are the most significant area source emitters of VOC.

 Paved and unpaved road dust are the most important PM 10 and PM 2.5 sources, while agricultural field burning is also an important source of PM 2.5 .

 Fertilizer application and livestock ammonia are the predominant NH 3 sources, while the landfill is the largest CH 4 source. 3.3 Quality Assurance Several general quality assurance checks were conducted for the entire Mexicali inventory. These checks (including hand calculations, completenes s checks against the 1999 Mexico NEI, emission factor checks, etc.) were conducted for all area source categories. In addition, two of the overall five DQOs for the Mexicali inventory project are applicable to area
source emissions:

1. A comprehensive emi ssions inventory for all source types (i.e., point, area, on

- road motor vehicle, and nonroad mobile sources) and all major categories within these source types. Acceptance criteria: The source types and major categories accounted for in the EIIP guidanc e documents are present in the Mexicali emissions inventory, and/or any differences are documented.

2. Area, On

- Road Motor Vehicle, and Nonroad Mobile Sources: Emissions estimates with an accuracy of ±50%.
Acceptance criteria: Estimated emissions using emission factors/models compare to emissions estimated using a fuel

- balance approach for all applicable pollutants. The fuel

- balance approach will use national statistics, while the preferred inventory methodology will use PEMEX and local fuel distributio n data.
The Mexicali area source inventory meets DQO #1. The area source inventory categories were based upon the area source categories previously inventoried in the 1999 Mexico NEI. The2005 Mexicali Emissions Inventory

Final, 2/27/09 3

- 20 1999 Mexico NEI area source categories were selected by reviewing all source categories included in Emission Inventory Improvement Program (EIIP) and other U.S. EPA guidance documents; Mexican federal environmental staff then identified those categories that either did
not exist in Mexico or could be considered to be in significant. Based upon comments to the draft inventory report, one area source category was added (i.e., VOC from beef cattle feedlots) and one area source category was disaggregated into two (i.e., construction activities into residential
construction a ctivities and industrial/commercial construction activities).

With regard to DQO #2, most area source fuel combustion emissions could not be assessed using a fuel

- balance approach due to the lack of specific fuel usage data. However, the accuracy of the b order crossing emission estimates was evaluated. Border crossing emissions (i.e., idling emissions) are typically not estimated in the U.S. since the wait times resulting in increased emissions generally occur on the Mexican side of the border. The prefe rred estimation methodology is to obtain queue waiting times and then calculate the distance based upon the lowest allowable vehicle speed in the MOBILE6 emission factor model (i.e., 2.5 miles per hour or 4 kilometers per hour). This calculated distance i s then multiplied by the emission factor corresponding to the lowest allowable vehicle speed (Brzezinski, 2009). This methodology was used to estimate border crossing emissions in Mexicali. All inputs to the model and all subsequent post

- model emission c alculations were rechecked and no errors were found.

Besides the methodology used to estimate border crossing emissions, accurate idling emissions data are relatively unavailable (Brzezinski, 2009). Only one somewhat relevant source of data (i.e., a guida nce document related to “long duration idling” for heavy

- duty diesel vehicles) was identified (U.S. EPA, 2004). The typical hourly idling emission factors for heavy

duty diesel vehicles identified from this guidance document were 135 g NO x /hour, and 3.68 g PM 10 /hour and g PM 2.5 /hour. The heavy

- duty diesel vehicle emission factors used in the Mexicali emission estimates were 15.96 g NO x /mile, 1.27 g PM 10 /mile, and 1.14 g PM 2.5 /mile. At 2.5 miles per hour, these emission factors translate to 39.9 g NO x /hou r, 3.18 g PM 10 /hour, and 2.85 g PM 2.5 /hour. Although the PM 10 and PM 2.5 emission factors are comparable with those in the guidance document, the NO x emission factor differs by a factor of over 3.2005 Mexicali Emissions Inventory

Final, 2/27/09 3

- 21 However, discussions with U.S. EPA staff familiar with idli ng emissions indicated that long duration idling does not correspond with border crossing idling. Long duration idling involves engine idling of long

- haul heavy

- duty diesel trucks during mandated rest periods (i.e., typically overnight or 10 hours rest fo r every 14 hours of driving) to operate air conditioning, heat, or on

- board appliances (e.g., televisions, computers, microwaves, etc.). This type of idling occurs with higher engine loads and is fundamentally different than idling that occurs at border

c rossings (Brzezinski, 2009). In addition, queue waiting times for the three Mexicali border crossings were considerably shorter than the overnight (or long duration) idling (BTS, 2008). Thus, it is not unexpected that the NO x emissions during long durati on idling would be substantially greater than emissions from idling at border crossings. Given these findings, the border crossing emissions were not adjusted.2005 Me xicali Emissions Inventory

Final, 2/27/09 4

- 1 

## 4.0 ON

- ROAD MOBILE SOURCES

On

- road mobile sources include all motor vehicles that are allowed to operate on public roadways (e.g., cars, trucks, buses, motorcycles). On

- road mobile source emissions include exhaust emissions, as well as various types of evaporative emission processes. Several other types of emissions are caused by on

- road mobile s ources, including paved and unpaved road dust, Stage II vehicle refueling, and emissions from vehicles idling at the border crossings; these source categories are estimated as area sources and are addressed in Section 3.0 of this report.

Based upon previou s experience from developing the 1999 Mexico NEI, availability of
the VKT data needed to estimate emissions from on

- road motor vehicles at the municipality

level is very limited in Mexico (with the exception of Mexico City, Guadalajara, and other large

met ropolitan areas). Therefore, traffic and congestion modeling were used to estimate VKT by road segment (i.e., link) for the municipality of Mexicali. The link

- level VKT estimates were combined with emission factors generated by the MOBILE6

- Mexico model ( i.e., a Mexico

specific version of the MOBILE6 emission factor model) to estimate on

- road motor vehicle emissions (ERG, 2003). The methodology is described below, and a more detailed explanation of the methodology is presented in Appendix B.

4.1 Methodolo gy The traffic volume and congestion modeling used a simplified road network, which included freeways, main arterials, collector roads, and “connectors” (i.e., artificial links that modeled local traffic flows). Although the road network was simplified, t he road network consisted of 3,603 individual links. In general, the road network is primarily concentrated in the Mexicali urban area, but Federal Highway 2 (connecting Mexicali to Tijuana and San Luis R í o Colorado), Federal Highway 5 (connecting Mexical i to Ensenada and San Felipe), as well as rural roads in the agricultural areas in the northeast and rural areas in the south, are also modeled.

The traffic modeling relied upon known Mexican trip generation rates combined with demographic and socio

- econom ic information (i.e., population, household size, income, and employment) for each AGEB (i.e., Mexican equivalent of a census tract). The traffic modeling resulted in daily VKT estimates for daily traffic volumes for each link in the roadway network.2005 Me xicali Emissions Inventory

Final, 2/27/09 4

- 2 Lin k

- level VKT was then estimated by multiplying each link’s daily traffic volume by its length in kilometers. Figure 4

- 1 shows the Mexicali roadway network and traffic volume intensity during a typical week day.

The traffic volumes for individual roadway ne twork links were assigned to corresponding
link

- specific congested speed emissions factors from MOBILE6

- Mexico in order to estimate daily link

- level emissions. Several sets of emission factors were developed to account for different congested speeds (i.e. , from 3 to 65 miles per hour [mph]), variations in ambient temperature, and seasonality. Overall emissions were estimated by summing the link

- level
emissions over the entire Mexicali road network.

Emissions were estimated for the following seven vehicle classifications:

 Light

- Duty Gasoline Vehicles (LDGV)

 Light

- Duty Gasoline Trucks (LDGT)

 Heavy

- Duty Gasoline Vehicles (HDGV)

 Light

- Duty Diesel Vehicles (LDDV)

 Light

- Duty Diesel Trucks (LDDT)

 Heavy

- Duty Diesel Vehicles (HDDV)

 Motorcycles (MC)

4.2 Results
The annual on

- road mobile source emissions are presented in Table 4

- 1. Examination of Table 4

- 1 indicates the following regarding on

- road mobile source emissions in Mexicali in 2005:

 Light

- duty gas vehicle and trucks are the primary sources of VOC, CO, NH 3 , a nd

CH 4 .

 Heavy

- duty diesel vehicles are the major sources of NO x , SO 2 , PM 10 , and PM 2.5 .

 Light

- duty diesel vehicles and trucks, as well as motorcycles are relatively insignificant contributors of all pollutants

- primarily due to their comparatively small fr action of the overall VKT.2005 Me xicali Emissions Inventory

Final, 2/27/09 4

- 3 Figure 4

- 1. Mexicali Loaded Roadway Network Under Weekday Conditions

Detail of loaded roadway network

for urban SLRC

Detail of roadway loaded network for urban Mexicali Daily vehicle flow2005 Me xicali Emissions Inventory

Final, 2/27/09 4

- 4 Table 4

- 1. 2005 Mexicali On

- Road Mobile Source Emissions (Tons per Year)

NO x SO 2 VOC CO PM 10 PM 2.5 NH 3 CH 4 LDGV 1,151.9 25.4 4,550.3 29,441.3 143.3 117.9 124.6 58.4 LDGT 1,523.4 33.1 3,594.6 26,650.3 184.1 155.4 113.5 61.7 HDGV 374.8 4.4 393.5 2,475.8 8.8 6.6 3.3 6.6 LDDV 12.1 0.0 9.9 18.7 2.2 2.2 0.0 0.0 LDDT 7.7 0.0 5.5 11.0 1.1 1.1 0.0 0.0 HDDV 5,463.0 105.8 340.6 1 ,574.1 424.4 382.5 11.0 13.2 MC 37.5 0.0 82.7 432.1 1.1 0.0 0.0 4.4 Total 8,570.4 168.7 8,977.1 60,603.4 765.0 665.8 252.4 144.4

4.3 Quality Assurance

As discussed in Section 1.3, a number of general quality assurance checks were
conducted for the ent ire Mexicali inventory. These checks (including hand calculations, completeness checks against the 1999 Mexico NEI, emission factor checks, etc.) were conducted
for all on

- road mobile source categories. In addition, two of the five data quality objectiv es (DQOs) for the Mexicali inventory project are applicable to on

- road mobile source emissions:

1. A comprehensive emissions inventory for all source types (i.e., point, area, on

- road motor vehicle, and nonroad mobile sources) and all major categories with in these source types. Acceptance criteria: The source types and major categories accounted for in the EIIP guidance documents are present in the Mexicali emissions inventory, and/or any differences are documented.

2. Area, On

- Road Motor Vehicle, and No nroad Mobile Sources: Emissions estimates with an accuracy of ±50%.
Acceptance criteria: Estimated emissions using emission factors/models compare to emissions estimated using a fuel

- balance approach for all applicable pollutants. The fuel

- balance appr oach will use national statistics, while the preferred inventory methodology will use PEMEX and local fuel distribution data.

The Mexicali on

- road mobile source inventory meets DQO #1. Emissions were
estimated for seven on

- road mobile source categories: light

- duty gasoline vehicles (LDGV), light

- duty gasoline trucks (LDGT), heavy

- duty gasoline vehicles (HDGV), light

- duty diesel vehicles (LDDV), light

- duty diesel trucks (LDDT), heavy

- duty diesel vehicles (HDDV), and motorcycles (MC). The MOBILE6

- Mexico e mission factor does provide emission factors for 282005 Me xicali Emissions Inventory

Final, 2/27/09 4

- 5 disaggregated categories; however, the use of 7 categories is consistent with the 1999 Mexico NEI and provides easier reporting.

Also, the Mexicali on

- road mobile source inventory also meets DQO #2. The on

- road mobile source quality assurance took two forms: comparison of inventory VMT estimates with
fuel

- based VMT estimates and comparison of inventory motor vehicle activity data with Imperial County motor vehicle activity data.

The first quality assuran ce step was to compare the Mexicali VMT estimates derived using traffic and congestion modeling with fuel

- based VMT estimates; VMT estimates were used instead of VKT estimates for ease of comparison. As part of the Mexicali traffic and congestion modeling , weekday VMT was estimated to be 7,876,541 miles (Appendix B, Table 11) and weekend day VMT was estimated to be 5,496,411 miles (Appendix B, Table 12). Assuming 52 weeks per year consisting of 5 weekdays and 2 weekend days, then annual VMT
was estimated to be 2.63 × 10 9 miles. As described in the area source fuel combustion and evaporative VOC methodology sections of this report (Sections 3.1.1 and 3.1.2), 2005 fuel sales statistics were provided by the PEMEX Mexicali bulk terminal. Additional research conducted as part of this QA procedure indicated that a significant portion of the fuels sold by the PEMEX Mexicali bulk terminal was sold and transported for consumption in Sonora (e.g., San Luis R í o Colorado, Puerto Pe ñ asco, Sonoyta, etc.) and other part s of Baja California (i.e., Tecate and Ensenada). Therefore, PEMEX staff provided revised fuel sales statistics of the fuel actually sold in the municipality of Mexicali (i.e., 224,800,401 liters of Magna gasoline, 63,773,310 liters of premium gasoline, a nd 84,678,057 liters of diesel) (Parra Armenta, 2009). Based on a PEMEX assumption that 60 percent of the diesel is used in motor vehicles, there is a total of 89,664,609 gallons of motor vehicle fuel used in Mexicali. The new vehicle fuel economy for
Me xico light

- duty vehicles and trucks has been estimated to be 20.5 miles per gallon (mpg) (An and Blumberg, 2005); this value is likely overestimated for the overall in

- use vehicle fleet, but fuel economy statistics for the overall Mexico in

- use vehicle fle et could not be identified. Multiplying the motor vehicle fuel statistics by the fuel economy resulted in an annual VMT
estimate of 1.84 × 10 9 miles. The fuel

- based VMT estimate is approximately 70 percent of the VMT estimate developed using traffic and congestion modeling. Given that the Mexicali VMT estimate developed using traffic and congestion modeling has an approximate uncertainty of ± 202005 Me xicali Emissions Inventory

Final, 2/27/09 4

- 6 percent (Gonzalez

- Ayala, 2008c), then the VMT estimate based on traffic and congestion modeling could potential ly be overestimated slightly. This is within the 50 percent uncertainty specified by DQO #4.

The second quality assurance step was to compare Mexicali motor vehicle activity data with Imperial County motor vehicle activity data for reasonableness based up on comments regarding the draft report. Overall Imperial County and Mexicali on

- road mobile source emissions data are compared in Table 4

- 2.

Table 4

- 2. 2005 Imperial County and Mexicali On

- Road Mobile Source Emissions (Tons per Year) Imperial County (to ns/day) Imperial County

(tons/year) Mexicali

(tons/year) Ratio

(Mexicali/Imperial) NO x 19.59 7,150.4 8,570.4 1.199 SO 2 0.14 51.1 168.7 3.301 VOC 6.41 2,339.7 8,977.1 3.837 CO 56.52 20,629.8 60,603.4 2.938 PM 10 0.86 313.9 765.0 2.437 PM 2.5 0.71 259.2 665.8 2.569 Imperial County emissions data were obtained from ARB’s Almanac Emission Projection Data (ARB, 2007). As can be seen in the ratios in Table 4

- 2, the Mexicali on

- road mobile source emissions exceed the Imperial County emissions by a factor of 1.2 to 3.8.

As described in the area source methodology (Section 3.0 and Appendix A), the 2005 population of the municipality of Mexicali was 855,962 people. The 2005 population of Imperial County was estimated to be 153,857 people (U.S. Census, 2008). The ratio of Mexicali population to Imperial County population is 5.563. If on

- road mobile source emissions were proportional to population, then the Mexicali on

- road mobile source emissions would exceed the Imperial County emissions by a similar factor of 5.563.

One potential reason why the Mexicali/Imperial County emission ratios are lower (i.e., 1.2 to 3.8) than the population ratio (i.e., 5.563) is that there is a significantly higher level of vehicle ownership in Imperial County compared to the munic ipality of Mexicali. Chapter 4 of the Imperial County Air Quality Management Plan (AQMP) provides a count of 121,707 vehicles for the year 2002 and an estimate of 161,231 vehicles for the year 2009 (Imperial, 2008); linear interpolation between these two data points resulted in an estimate of 138,6462005 Me xicali Emissions Inventory

Final, 2/27/09 4

- 7 vehicles for the year 2005. This results in an estimated vehicle ownership rate of 0.901 vehicles per person. Vehicle registration statistics for the municipality of Mexicali obtained from INEGI
indicate a t otal of 422,357 vehicles registered in 2005 (INEGI, 2008), which corresponds to an estimated vehicle ownership rate of 0.493 vehicles per person. Therefore, Imperial County vehicle ownership rates are significantly higher than in Mexicali.

Chapter 4 o f the Imperial County AQMP also provide estimated daily VMT for 2002 and 2009 (4.780 × 10 6 miles and 6.277 × 10 6 miles, respectively) (Imperial, 2008); linear interpolation between these two data points resulted in an estimate of 5,421,571 daily VMT in
200 5, which corresponds to an annual VMT estimate of 1.98 × 10 9 miles. Overall Mexicali VMT is higher than overall Imperial County VMT by a factor of 1.33. Perceptions of even higher levels of vehicle activity in Mexicali compared to Imperial County are pot entially due to Mexicali vehicle activity being concentrated in the urban portion of Mexicali, compared to Imperial County vehicle activity being spread among a number communities located throughout the county (e.g., El Centro, Brawley, Holtville, Calipatr ia, Westmorland, etc.).

Based upon these QA analyses, it was felt that the Mexicali on

- road mobile source emission estimates were reasonably accurate and that additional adjustments were not needed.2005 Mexicali Emissions Inventory

Final, 2/27/09 5

- 1 

## 5.0 NONROAD MOBILE SOURC ES

Nonroad mobile sources inc lude all equipment that move under their own power, or that are portable, and are not allowed to operate on public roadways. For the 2005 Mexicali emissions inventory, nonroad mobile sources include aircraft and airport ground support equipment and auxili ary power units, locomotives, and agricultural and construction equipment.
Another nonroad source type is commercial marine vessels; however, no major ports with significant commercial marine vessel activity exist in Mexicali. Initially, it was thought that there might be some fishing vessels in some of the communities located on the Gulf of California. However, fishing vessel activity data were not available. Some fishing occurs out of San Felipe, but this appears to consist of tourist fishing, rather than commercial fishing. Due to the lack of data and apparent insignificance of these emissions, emissions for commercial marine
vessels were not estimated.
5.1 Methodology The methodologies used to estimate emissions for the various nonroad mobile sourc e types operating in Mexicali are described below.

5.1.1 Aircraft There are two airports located in the municipality of Mexicali: General Rodolfo Sánchez Taboada International Airport (east of the Mexicali urban area) and San Felipe International Airpor t (located in the southern portion of the municipality). Operator

- specific landing and takeoff (LTO) statistics and aircraft fleet composition data were obtained from local airport officials (Sanchez Resendiz, 2008). These data included information for b oth the Mexicali and San Felipe airports; however, the data were not associated with a particular airport. Therefore, it was assumed that all flight data were associated with the General Rodolfo Sánchez Taboada International Airport airport because it is much larger than San Felipe International Airport. Because of the large amount of agricultural activity in Mexicali, crop dusting (or aerial spraying) is a significant activity in the area. Crop dusting activity data (including LTO data, flight lengths, and fuel usage) were provided by staff from the Mexicali crop dusting industry association (Tamayo Moreno, 2008). There were also numerous other general aviation landing2005 Mexicali Emissions Inventory

Final, 2/27/09 5

- 2 strips located throughout Baja California, but these were not included in the invento ry because LTO data for these landing strips were not available.

The aircraft operations information was input into the latest version of the Emissions and Dispersion Modeling System (EDMS 5.0.2, release June 29, 2007) model. The EDMS model was developed b y the Federal Aviation Administration and is recommended for use by U.S.
EPA. The model contains the latest emission factors from the International Civil Aviation Organization’s (ICAO) Engine Exhaust Emissions Data Bank. The default time

- in modes for

tax i out, take off, climb out, approach, and taxi in were used to run the model. The model output included emissions by aircraft type and total emissions, including emissions for aircraft, ground support equipment, and auxiliary power units. Emissions from other airport

- related activities (e.g., parking lots, roadways, stationary sources within airport boundaries, etc.) were not included in the estimates because these sources addressed within other emission inventory categories.

5.1.2 Locomotives A railway l ine extends from Mexicali to Puerto Peñasco, Sonora. In order to estimate emissions for locomotives operating within the municipality of Mexicali (i.e., in the locomotive yard and from line haul activities), local locomotive fuel consumption data are need ed; however, these data were not available. Visual observations ERG staff indicated that there is very limited locomotive activity in the municipality. Due to the lack of data needed to estimate these emissions for Mexicali, the emissions calculated for the 1999 Mexico NEI were used without adjustment. These are felt to be appropriate because of the observed limited locomotive activity.

5.1.3 Agricultural and Construction Equipment As part of the 1999 Mexico NEI project, a Mexico

- specific version of the U.S. EPA’s NONROAD emissions model was developed (i.e., NONROAD

- Mexico), which provided a streamlined way to estimate emissions from agricultural and construction equipment (ERG, 2005). To develop a Mexico

- specific version of this model, various parameter s were adjusted to better reflect conditions in Mexico, including: average annual temperature, altitude, and diesel sulfur content. Also, Mexican state

- level agricultural and construction equipment populations were incorporated into the model. Although ot her nonroad equipment types (lawn and garden,2005 Mexicali Emissions Inventory

Final, 2/27/09 5

- 3 logging, etc.) exist in Mexico, agricultural and construction equipment were given highest priority during the development of the NONROAD

- Mexico model because it was believed that they emitted the most emissio ns as compared to the other equipment types.

Because the NONROAD

- Mexico model contained data which would generate emissions for 1999, only, it was desirable to update the equipment population and operation files to 2005 in
order to estimate 2005 emission s for the municipality of Mexicali. However, sufficient recent
data were not available. Due to the lack of data needed to update the NONROAD

- Mexico model, the municipality

- level nonroad equipment emissions from the 1999 Mexico NEI generated using the
NONR OAD

- Mexico model were extrapolated using 2005 population for Mexicali. This extrapolation method was previously used to estimate nonroad source emissions in the San Luis Río Colorado emission inventory, which included the northeast portion of the municipa lity of Mexicali (ENVIRON and ERG, 2008). First, for agricultural equipment, it was assumed that agricultural land area would be fairly stable over time. As a result, the agricultural equipment population would likely not grow significantly between 1999 and 2005. For construction equipment, it was assumed that equipment population growth was proportional to population growth. The population of the municipality of Mexicali grew from 764,602 to 855,962 over the same time period; this corresponds to a grow th rate of 1.1195 (INEGI, 2000; INEGI, 2006). This growth factor was applied to the 1999 municipality

- level emissions estimated using
NONROAD

- Mexico to obtain 2005 emissions for agricultural and construction equipment.
5.2 Results
The annual nonroad mobil e source emissions are presented in Table 5

- 1; NH 3 and CH 4 emissions were not estimated for nonroad mobile sources. As seen in the table, the largest emissions are from construction and agricultural equipment. The construction and agricultural equipment are dominated by diesel

- powered equipment which will cause relatively high NO x , PM 10 , and PM 2.5 emissions. Locomotives have infrequent activity and the portion of aircraft flight durations that occur in the inventory domain are comparatively short relativ e to the length of an entire flight, with the exception of cropdusters.2005 Mexicali Emissions Inventory

Final, 2/27/09 5

- 4 Table 5

- 1. 2005 Mexicali Nonroad Mobile Source Emissions (Tons per Year) Source Category NO x SO 2 VOC CO PM 10 PM 2.5 Aircraft

– Commercial 15.2 1.9 6.8 31.7 0.3 0.3 Airport Auxiliar y Power Units 3.7 0.3 1.1 32.4 0.1 0.1 Airport Ground Support Equipment 0.6 0.1 0.0 0.4 0.0 0.0 Locomotives 206.2 1.8 7.8 20.4 5.1 4.6 Construction Equipment 3,100.2 41.6 320.4 1,552.3 348.9 338.5 Agricultural Equipment 1,158.5 14.6 195.7 785.3 195.7 1 89.8 Aircraft

– Cropdusters (General) 0.5 0.6 11.1 784.4 0.0 0.0 Total 4,485.0 60.9 542.9 3,206.9 550.2 533.3

5.3 Quality Assurance

As discussed in Section 1.3, a number of general quality assurance checks were
conducted for the entire Mexicali inventor y. These checks (including hand calculations, completeness checks against the 1999 Mexico NEI, emission factor checks, etc.) were conducted for all area source categories. In addition, two of the five DQOs for the Mexicali inventory project are applicab le to nonroad mobile source emissions:

1. A comprehensive emissions inventory for all source types (i.e., point, area, on

- road motor vehicle, and nonroad mobile sources) and all major categories within these source types. Acceptance criteria: The source types and major categories accounted for in the EIIP guidance documents are present in the Mexicali emissions inventory, and/or any differences are documented.

2. Area, On

- Road Motor Vehicle, and Nonroad Mobile Sources: Emissions estimates with an accura cy of ±50%.
Acceptance criteria: Estimated emissions using emission factors/models compare to emissions estimated using a fuel

- balance approach for all applicable pollutants. The fuel

- balance approach will use national statistics, while the preferred in ventory methodology will use PEMEX and local fuel distribution data.
The Mexicali nonroad mobile source inventory meets DQO #1. The nonroad mobile source inventory categories were based upon the nonroad mobile source categories previously
inventoried in the 1999 Mexico NEI. The 1999 Mexico NEI nonroad mobile source categories were selected by reviewing all source categories included in Emission Inventory Improvement Program (EIIP) and other U.S. EPA guidance documents; Mexican federal environmental staff2005 Mexicali Emissions Inventory

Final, 2/27/09 5

- 5 then identified those categories that either did not exist in Mexico or could be considered to be insignificant. Some U.S.

- specific nonroad mobile source categories typically inventoried were excluded in Mexico (e.g., lawn and garden equipment, logging e quipment, recreational vehicles, etc.). It should also be noted that the aircraft and locomotive categories were included as area sources in the 1999 Mexico NEI, but were classified as nonroad mobile sources for the Mexicali inventory. Also, two nonroad mobile source categories not previously inventoried in the 1999 Mexico NEI were included in the Mexico inventory (i.e., airport auxiliary power units and airport ground support equipment). Finally, based upon comments to the draft inventory report,
one ad ditional nonroad mobile source category was added (i.e., cropdusting aircraft).

With regard to DQO #2, there were insufficient fuel usage data to assess the nonroad mobile source emissions using a fuel balance approach.2005 Mexicali Emissions Inventory

Final, 2/27/09 6

- 1 

## 6.0 EMISSION INVENTORY R ESULTS

The overall 2005 Mexicali emissions inventory results are shown in Table 6

- 1. The results are presented by source type and pollutant. Figures 6

- 1 through 6

- 8 show the distribution of emissions by source type for each pollutant. The table and figures show th at:

 Emissions from federal jurisdiction point sources are considerably larger than emissions from state jurisdiction point sources, even though the ratio of state

- to

federal jurisdiction point sources is greater than 10

- to

- 1.

 NO x and SO 2 emissions are prim arily emitted by point sources.

 VOC emissions are emitted by area (i.e., mainly various evaporative source categories) and on

- road mobile sources.

 On

- road mobile sources are the predominant source of CO.

 Area sources are the largest sources of PM 10 and PM 2 .5 (i.e., due to unpaved and paved road dust), as well as NH 3 (i.e., from livestock ammonia and fertilizer application) and CH 4 (i.e., from the landfill).

Table 6

- 1. 2005 Mexicali Emissions Inventory Summary (Tons per Year)
Source Type NO x SO 2 VOC CO PM 10 PM 2.5 NH 3 CH 4 Point

– Federal 13,931.7 3,650.9 659.3 3,636.2 1,537.7 128.4
Point

– State 444.0 973.2 73.0 479.9 89.7 Area 1,205.5 131.1 15,301.5 18,854.0 50,879.3 6,753.5 9,015.2 6,033.3 On

- Road Mobile 8,570.4 168.7 8,977.1 60,603.4 765.0 665 .8 252.4 144.4
Nonroad Mobile 4,485.0 60.9 542.9 3,206.9 550.2 533.3 0.0 1.5
Total 28,636.5 4,984.8 25,553.8 86,780.4 53,821.8 8,081.0 9,267.6 6,179.2
Blanks indicate that pollutant emissions were not applicable or were not estimated due to a lack of d ata.2005 Mexicali Emissions Inventory

Final, 2/27/09 6

- 2 Figure 6

- 1. Mexicali NO x Emissi ons

Figure 6

- 2. Mexicali SO 2 Emissions2005 Mexicali Emissions Inventory

Final, 2/27/09 6

- 3 Figure 6

- 3. Mexicali VOC Emissions

Figure 6

- 4. Mexicali CO Emissions2005 Mexicali Emissions Inventory

Final, 2/27/09 6

- 4 Figure 6

- 5. Mexicali PM 10 Emissions

Figure 6

- 6. Mexicali PM 2.5 Emissions2005 Mexicali Emissions Inventory

Final, 2/27/09 6

- 5 Figure 6

- 7. Mexicali NH 3 Emissions

Figure 6

- 8. Mexicali CH 4 Emissions2 005 Mexicali Emissions Inventory

Final, 2/27/09 7

- 1 

## 7.0 REFERENCES Álvarez Sánchez, 2008. LPG statistics provided by I. Álvarez Sánchez, Gas Silza S.A. de C.V., Mexicali, Baja California. August 22. An and Blumberg, 2005. “The Case for Mexico to Improve Vehicle Fuel Efficiency”, pre sentation by F. An and K. Blumberg at Workshop on Sustainable Transport in Latin America: From Theory to Practice . Washington D.C., January 9.
ANAFAPYT, 2003. National paint sales provided by the National Association of Paint and Ink Manufacturers (As ociación Nacional de Fabricantes de Pinturas y Tintas).
ANAFAPYT, 2004. National ink sales provided by the National Association of Paint and Ink Manufacturers (Asociación Nacional de Fabricantes de Pinturas y Tintas).
ARB, 2002. California Emission Inven tory Development and Reporting System (CEIDARS) Particulate Matter (PM) Speciation Profiles . Updated September 26, 2002. California Air Resources Board, Sacramento, California.
ARB, 2003a. Area Sources Methods

– Section 7.4 (Agricultural Land Preparatio n) . California Air Resources Board, Sacramento, California.
ARB, 2003b. Area Sources Methods

– Section 7.5 (Agricultural Harvest Operations)

. California Air Resources Board, Sacramento, California.
ARB, 2004. Area Sources Methods

– Section 7.6 (Livesto ck Husbandry) . California Air Resources Board, Sacramento, California. May.
ARB, 2005. Area Sources Methods

– Section 7.17 (Agricultural Burning and Other Burning Methodology) . California Air Resources Board, Sacramento, California. June.
ARB, 2007. Almanac Emission Projection Data . California Air Resources Board, Sacramento, California.
Brzezinski, 2009. Personal communication with D. Brzezinski, U.S. Environmental Protection Agency, National Vehicle and Fuel Emissions Laboratory, Ann Arbor, Michi gan. January 13.
BTS, 2007. National Transportation Statistics 2007 (Table 1

- 32

– U.S. Vehicle

- Miles) . Bureau of Transportation Statistics, U.S. Department of Transportation.
BTS, 2008. Border crossing vehicle counts and queue waiting times provide d by the Bureau of Transportation Statistics.
CANALAVA, 2002. National dry cleaning solvent statistics provided by the National Chamber of the Dry Cleaning Industry (Cámara Nacional de la Industria de Lavanderías).2 005 Mexicali Emissions Inventory

Final, 2/27/09 7

- 2 Chinkin, L.R., P.A. Ryan, and D.L. Coe. 2003. “Recommended Improvements to the CMU Ammonia Emission Inventory Model for Use by LADCO”. Prepared for the Lake Michigan Air Directors Consortium.
CNA, 2007. Inventario Nacional de Plantas Municipales de Potabilización y de Tratamiento de Aguas Re siduales en Operación

– Diciembre de 2007

. Prepared by the National Commission on Water (Comisión Nacional del Agua).
COFEPRIS, 2007. Registros de Plaguicidas Autorizados por Categoría Toxicológica. Prepared by the Federal Commission for Sanitary Risk P rotection (Comisión Federal de Protección Contra Riesgos Sanitarios).
DPR, 2007. Pesticide databases. California Department of Pesticide Regulation, http://www.cdpr.ca.gov/dprdatabase.htm
EEA, 2002. Joint EMEP/CORINAIR Atmospheric Emission Inventory Gui debook, Third Edition . European Environment Agency, Copenhagen, Denmark
EIIP, 1996. Consumer and Commercial Solvent Use . Volume III, Chapter 5. Emission Inventory Improvement Program. August.
EIIP, 1997. Solvent Cleaning , Volume III: Chapter 6. Emi ssion Inventory Improvement Program, Area Sources Committee. September.
EIIP, 2001a. Gasoline Marketing (Stage I and Stage II). Volume III. Chapter 11. Emission Inventory Improvement Program, Area Sources Committee. January.
EIIP, 2001b. Pesticides

– Agricultural and Nonagricultural . Volume III, Chapter 9. Emission Inventory Improvement Program, Area Sources Committee. June.
EIIP, 2001c. Structure Fires . Volume III, Chapter 18. Emission Inventory Improvement Program. January.
EIIP, 2001d. Asph alt Paving . Volume III, Chapter 17. Emission Inventory Improvement Program. April.
ENVIRON and ERG, 2007. Development of Air Emissions Inventory for the Western Arizona Sonora Border Air Quality Study (WASBAQS)

– Emission Inventory Project Report . Pre pared for the Arizona Department of Environmental Quality by ENVIRON International Corporation and Eastern Research Group, Inc., June.
ERG, 2003. MOBILE6

- Mexico . Prepared for the Western Governors’ Association by Eastern Research Group, Inc. (ERG), Austi n, Texas. June 27.
ERG, 2005. NONROAD

- Mexico: A Tool for Estimating Emissions from Agricultural and Construction Equipment in Mexico. Prepared for the Western Governors’ Association and the Binational Advisory Committee. Prepared by Eastern Research G roup, Inc., Austin, Texas. July 27.2 005 Mexicali Emissions Inventory

Final, 2/27/09 7

- 3 ERG, 2006. Mexico National Emissions Inventory, 1999

– Final . Prepared for the Secretariat of the Environment and Natural Resources and the National Institute of Ecology of Mexico by Eastern Research Group, Inc. with sponsorship of the U.S. EPA, Western Governors’ Association, and the North American Commission for Environmental Cooperation. October 11, 2006.
Escalante, 2008. LPG statistics provided by E. Escalante, Kino Gas del Noroeste, S.A. de C.V., Mexicali, Baja California. August 7.
Félix Robles, 2008. LPG statistics provided by C.R. Félix Robles, Hidrocarburos del Noroeste, S.A. de C.V., Mexicali, Baja California. August 13.
Fierro, 2007. Personal communication with Marian Fierro (Arizona College of Public Health, University of Arizona, Tucson, Arizona) regarding bleach use in SLRC. May 4.
Fierro, M.A. and M.K. O’Rourke, 2007. Binational Household Product Survey . Prepared by Marian A. Fierro and Mary Kay O’Rourke, College of Public Health, University of Arizona, Tucson, Arizona.

Gonzalez

- Ayala, 2007. Per capita San Luis Río Colorado, Sonora VMT estimates provided by S. Gonzalez

- Ayala, TransEngineering, Ciudad Juárez, Chihuahua. December.

Gonzalez

- Ayala, 2008a. Link

- level paved road dust emission estim ates provided by S. Gonzalez

- Ayala, TransEngineering, Ciudad Juárez, Chihuahua. September.

Gonzalez

- Ayala, 2008b. Link

- level unpaved road dust emission estimates provided by S. Gonzalez

- Ayala, TransEngineering, Ciudad Juárez, Chihuahua. September.

Gonza lez

- Ayala, 2008c. Estimates of Mexicali travel demand modeling uncertainty provided by S. Gonzalez

- Ayala, TransEngineering, Ciudad Juárez, Chihuahua. December 22.
Imperial, 2008. Imperial County Air Quality Management Plan, Chapter 4

– Emissions Invento ry . Imperial County Air Pollution Control District, El Centro, California. April 9.
INEGI, 2000. XII Censo General de Población y Vivienda, 2000 . Prepared by the National Institute of Statistics, Geography, and Information (Instituto Nacional de Estadí stica, Geografía e Informática).
INEGI, 2005. Censos Económicos 2004 medianto el Sistema Automatizado de Información Censal (SAIC), version 5.0. Prepared by the National Institute of Statistics, Geography, and Information (Instituto Nacional de Estadísti ca, Geografía e Informática).
INEGI, 2006. II Conteo de Población y Vivienda, 2005. Prepared by the National Institute of Statistics, Geography, and Information (Instituto Nacional de Estadística, Geografía e Informática).
INEGI, 2008. Vehículos de Moto r Registrados en Circulación. Prepared by the National Institute of Statistics, Geography, and Information (Instituto Nacional de Estadística, Geografía e Informática).2 005 Mexicali Emissions Inventory

Final, 2/27/09 7

- 4 LMA, 2008a. Laboratory analysis results of Mexicali paved road dust samples provide d by Laboratorio de Muestro y Analisis, S.A. de C.V., Tijuana, Baja California. July 24.
LMA, 2008b. Laboratory analysis results of Mexicali unpaved road dust samples provided by Laboratorio de Muestro y Analisis, S.A. de C.V., Tijuana, Baja California. July 24.
López Bojorques, 2008. Personal communication with G. López Bojorques, Secretaría de Agricultura, Ganadería, Desarrollo Rural, Pesca y Alimentación (SAGARPA), Mexicali, Baja California. August 13.
Martinez, 2007. Personal communication wit h K. Martinez, Urban Development and Ecology Office, San Luis Río Colorado, Sonora. January.
Miranda Palazuelos, 2008. Residual fuel oil statistics provided by F.H. Miranda Palazuelos, PEMEX

– Rosarito Terminal, Rosarito, Baja California. October 2.
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