# DEVELOPMENT OF MEXICO NATIONAL EMISSIONS INVENTORY PROJECTIONS FOR 2008, 2012, AND 2030

Final

Prepared for:

Instituto Nacional de Ecología Mexico City, Mexico
National Renewable Energy Laboratory



## January 9, 2009

### ERG Project No: 3667.00.001.001



## DEVELOPMENT OF MEXICO NATIONAL EMISSIONS INVENTORY PROJECTIONS FOR 2008, 2012, AND 2030

Final

Prepared for:
Instituto Nacional de Ecología Mexico City, Mexico

National Renewable Energy Laboratory

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

January 9, 2009Mexico Projections Final, January 9, 2009 

### i 

## TABLE OF CONTENTS

Section Page

1.0 INTRODUCTION ............................................................................................................... 1

2.0 SCOPE ...................................................................................................................... ...........2

3.0 NEW MUNICIPALITY ADJUSTMENTS .........................................................................2

4.0 METHODOLOGY ..............................................................................................................3 4.1 General Projections Methodology............................................................................ 3 4.2 Source Type-Specific Projections Methodology...................................................... 4

4.2.1 Point Source Projections......................................................................................... 5 4.2.2 Area Source Projections.......................................................................................... 8 4.2.3 On-Road Motor Vehicle Projections .................................................................... 14 4.2.4 Nonroad Mobile Source Projections..................................................................... 19 4.3 Projections Summary ............................................................................................. 20

5.0 CONTROL SCENARIOS .................................................................................................20 5.1 Control Scenario 1 – Increased Fuel Economy ...................................................... 20 5.2 Control Scenario 2 – Use of Ethanol in Oxygenated Fuel ..................................... 21 5.3 Control Scenario 3 – Combined Increased Fuel Economy and Use of Ethanol in Oxygenated Fuel..................................................................................................... 21 5.4 Projections Summar y with Controls....................................................................... 22

6.0 HARMONIZATION WITH GREENHOUSE GAS EMISSIONS INVENTORIES........23

7.0 REFERENCES ................................................................................................................. .24

Tables......................................................................................................................... ....................27
Figures........................................................................................................................ ....................53Mexico Projections Final, January 9, 2009 

### 1 1.0 INTRODUCTION
Future year emission inventory projections are essential to ev aluating the future benefits of air quality control measures and supporting various modeling analyses. Eastern Research Group, Inc. (ERG) was contracted by Wester n Governors Association (WGA) to develop emissions inventory projections for Mexico’s National Institute of Ecology (INE – Instituto Nacional de Ecología) based upon the 1999 Mexico National Emissions Inventory (MNEI). In addition, the projection inventor y process supports the fourth phase of the Integrated Environmental Strategies (IES) Program spons ored by the U.S. Environmental Protection Agency (U.S. EPA) and the National Renewable En ergy Laboratory (NREL) to evaluate the cobenefits of air quality control measures in Mexico at the national level.

The 1999 MNEI, previously developed by ERG, includes emission estimates for point, area, on-road, nonroad, and natural source types, at the municipality-level for the year 1999. Under this current project, ERG projected the 1999 emissions estimates for point, area, on-road, and nonroad sources to the future years of 2008, 2012, and 2030. The projected emission inventory was developed at the municipality-lev el. Also, ERG analyzed emission impacts in Mexico from three control scenarios developed in consultation with INE. The remainder of this report discusses the results and findings of this study.

The remainder of this report is organized as follows:

• Section 2.0 – Scope. This section provides a brief outline of the scope of this current project.

• Section 3.0 – New Municipality Adjustments. This section describes the adjustments made to the 1999 MNEI to account for 11 new Mexican municipalities that were created since 1999.

• Section 4.0 – Methodology. This section de scribes the methodology used to develop growth factors for point sources, area s ources, on-road motor vehicles, and nonroad mobile sources.

• Section 5.0 – Control Scenarios. This section presents the control scenarios that were developed and applied to the future year emissions.

• Section 6.0 – Harmonization with Greenhous e Gas Emission Inventories. This section describes how the projections were harmonized (i.e., standardized, or havingMexico Projections Final, January 9, 2009 

### 2 increased comparability and/ or convergence) with existing greenhouse gas emission inventories in Mexico, as well as with other inventories thatare currently under development in Mexico.

• Section 7.0 – References. This section presen ts references for all documents, reports, data, and personal communication used to develop the future year emissions.

• Tables. All tables are presented sequentially at the end of the report, rather than in the body of the text.

2.0 SCOPE
Since the future year emission inventory projections are based upon the 1999 MNEI, the scope of the future year pr ojections is similar to the MNEI, and includes the following
characteristics:

• Source types – Point sources, area sources , on-road motor vehicles, and nonroad mobile sources. Natural sources (i.e., biogenic and volcanic sources) are not part of the scope of the future year projections.

• Pollutants – Nitrogen oxides (NO x 

### ), sulfur dioxide (SO 2 

### ), volatile organic compounds (VOC), carbon monoxide (CO), particulate ma tter with an aerodynamic diameter of 10 micrometers (μm) or less (PM 10 

### ), particulate matter with an aerodynamic diameter of 2.5 μm or less (PM 2.5 

### ), and ammonia (NH 3 

### ).

• Spatial aggregation – Municipality-level for the 2,454 municipalities in Mexico. In the 1999 MNEI, there were 2,443 munici palities. Since 1999, 11 additional municipalities were formed in Mexico, so adjustments were made to include these 11 additional municipalities.

• Reported units – Megagrams (Mg) per year (i.e., 1,000 kilograms [kg] or 1 metric ton).

• Projected emission results are provided in spreadsheets, U.S. EPA Emissions Inventory Format (NIF) 3.0, and SMOKE/IDA (modeling) files.

3.0 NEW MUNICIPALITY ADJUSTMENTS
Prior to projecting the 1999 Mexico Nati onal Emissions Inventory (MNEI) forward to 2008, 2012, and 2030, it was necessary to adjust the ba seline municipality-level emissions to account for municipality reali gnments since 1999. The 1999 MN EI contained a total of 2,443 municipalities for the entire count ry (ERG, 2006). However, th e national municipality-level population projections that we re provided by the National Council on Population (CONAPO –Mexico Projections Final, January 9, 2009 

### 3 Consejo Nacional de Población) in dicated that there were a tota l of 2,454 municipalities as of 2005 (CONAPO, 2008). The 11 new municipalities were formed in the states of Guerrero, México, Veracruz, and Zacatecas. Seven new muni cipalities were formed by the division of an existing municipality; four new municipalities were formed by the reorganization of multiple existing municipalities. Table 1 (at the back of this document) lists th e new municipalities and their associated municipality codes.

Emissions from the 1999 MNEI older municipali ties listed in Table 1 were allocated to the new municipalities. If this allocati on had not been performed, then these 11 new municipalities would have zero em issions in the 1999 baseline inve ntory, as well as the future year projected inventories.

The emissions allocation for area sources, on- road motor vehicles, and nonroad mobile sources was based upon the ratio of 2005 popula tion estimates. For example, Iliatenco (Guerrero) was formed from the municipalities of Ma linaltepec and San Luis Acatlán. The 2005 populations of these municipalitie s were as follows: Malinalte pec – 27,231; San Luis Acatlán – 41,917; Iliatenco – 9,762; and three m unicipality total – 78,910. The calculated ratios were then: Malinaltepec – 0.3451 (i.e., 27,231/ 78,910); San Luis Acatlán – 0.5312; and Iliatenco – 0.1237.

For point source emissions, Geographic Inform ation System (GIS) was used to plot the point source locations to determin e if any were located within th e municipalities that were split to form new municipalities. It was confirmed that no reallocation of poi nt source emissions was needed because none of the point sources were within the 11 new municipalities.

4.0 METHODOLOGY
This section provides the general methodology used for developing future year growth projections (Section 4.1), as well as the source-type speci fic methodologies (Section 4.2).
4.1 General Projections Methodology At the most basic level, future year projected emissions are estimated by multiplying base year emissions by a projection factor as shown in the following equation:

E fy = E by × PMexico Projections Final, January 9, 2009 

### 4 Where: E fy 

### = projected future year emissions E by 

### = base year emissions P = projection factor

A projection factor of 1.0 represen ts a situation of no growth (i.e ., projected emissions are equal to base year emissions). A pr ojection factor greater than 1.0 represents increasing emissions, while a projection factor less than 1.0 represents decreasing emissions.

However, in practice, the projection fact or is typically disaggregated into two components: a growth factor and a control fact or. This results in the following modified equation:

E fy = E by × G × C



### Where: E fy 

### = projected future year emissions E by 

### = base year emissions G = growth factor C = control factor

The growth factor is often derived by projections of surr ogates (i.e., population, economic growth, land development, etc.). For in stance, a 15 percent projected growth rate for population could be used to estimate a growth fa ctor of 1.15. The contro l factor is typically derived from expected future laws, regulations, policies, industry trends, or control implementation. For example, the expected impl ementation of a control device with 40 percent
lower emissions across an entire industrial sector could be used to estimate a control factor of 0.60 (i.e., 40 percent control co rresponds to controlled emissi ons that are 60 percent of uncontrolled emissions).
4.2 Source Type-Specific Projections Methodology For the purposes of this project, base line growth projections for 2008, 2012, and 2030 were developed initially assuming no future cont rols. The methodologies used for these baseline growth projections are described below; the met hodologies used to incor porate control scenarios are provided in Section 5.0. Id eally, the development of growth factors would be conducted at the facility- or pro cess-level. However, information conc erning expected futu re year conditions was typically limited due to the lack of data. As a result, facility- or process-level growth factors were not developed; instead, na tional- and regional-level gr owth factors were developed.Mexico Projections Final, January 9, 2009 

### 5 After the baseline growth projections were de veloped, then three control scenarios were applied to the baseline growth projections. These control scenarios were developed in conjunction with INE staff.
4.2.1 Point Source Projections The 1999 MNEI point source emissions we re projected to 2008, 2012, and 2030. The first step was to classify all of the 1999 MNEI point sources in to one of six groups based upon 3- digit North American Industry Cl assification System (NAICS) codes. The assignment of the 3- digit NAICS codes is presented in Table 2. The six groups were:

• Electricity generating units (EGUs)

• Refineries and other petroleum-related sources

• Primary metals

• Manufacturing industries

• Miscellaneous industries

• Services
The methodology used to develop growth fact ors for each of these point source groups is
described below.

Growth Factors – EGUs The growth factors for EGUs were developed fr om historical fuel us e statistics and fuel use projections. The actual fuel consumption by the EGU sector for 1999 was obtained from the 1999 Mexico NEI fuel balance (ERG, 2003a). Projec tions of fuel used for electricity generation for 2008, 2012, and 2030 were generated using the Long-Range Energy Alternatives Planning System (LEAP) (Cuatecontzi, 2008). These projected fuel consumption data (in petajoules [PJ]) are shown in Table 3. The growth factors for each future year were estimated by calculating the ratio of the projected future year demand data relative to the actual 1999 fuel combustion.

Fuel-specific growth factors were only de veloped for natural gas, combustóleo (i.e., residual fuel oil), and coal. The EGUs containe d in the 1999 MNEI were assigned a fuel type based upon power plant information from the Commission for Environmental Cooperation ofMexico Projections Final, January 9, 2009 

### 6 North America (CEC) (CEC, 2004). Based upon th e CEC power plant information, fuel types were assigned to 41 of 73 EGUs. For the remaini ng 32 EGUs were assigned either natural gas or combustóleo based upon comparative SO 2 

### emissions relative to NO x 

### emissions at the facility level (i.e., EGUs with low SO 2 

### emissions were assigned to natural gas, while EGUs with high
SO 2 

### emissions were assigned to combustóleo.

Growth Factors – Refineries and Other Petroleum-Related Sources The growth factors for refineries and othe r petroleum-related sources were developed
from historical crude oil production statistics and futu re production projections.

The 1999 crude oil production was obtained fr om an analysis of the Department of Energy (DOE)/Energy Informa tion Administration’s (EIA) International Energy Outlook (Blanchard, 2001); this study indicated a daily to tal crude production of 2.87 million barrels for Mexico in 1999. Future year crude produc tion forecast data were obtained from the Organization of the Petroleum Exporting Countries’ (OPEC) World Oil Outlook (OPEC, 2007). The crude oil production data used to develop projection factors ar e presented in Table 4. These data indicate a decrease in crude production for Mexico in future years (e.g., the crude production in 2030 is almost equal to that in 1999).

Growth Factors – Primary Metals The growth factors for primary metals facili ties were based upon hi storic copper, lead, and zinc production data in Mexi co. Historic Mexican copper, lead, and zinc production data
from 1990 to 2006 were obtained from the United States Geological Survey (USGS) Mineral Resources Program (USGS, 2008). Aggregated c opper, lead, and zinc statistics for primary refined metal were used to develop a linear re gression equation to pred ict annual primary metal production for the years 2008, 2012, and 2030. Growth factors were then developed by dividing the projected future year primary metal produc tion by the actual 1999 primary metal production.

Growth Factors – Manufacturing Industr ies and Miscellaneous Industries The growth factors for manufact uring industries, as well as miscellaneous industries were based upon Mexican gross domestic product (GDP). An annual GDP rate of 3.5 percent hasMexico Projections Final, January 9, 2009 

### 7 been recently used for various environmental an d economic studies; this annual growth rate was adopted for projecting these sectors (Galindo Paliza, 2008).

Growth Factors – Services The growth factors for service sector point sources were based upon municipality-level population estimates for the time period from 2005 to 2030 (CONAPO, 2008). As shown in Table 2, services category point sources include repair and maintenance shops; dry cleaners; wastewater treatment plants; and government and public service facilities such as hospitals, schools, and office buildings. The growth of these types of point sources can largely be attributed to growth in popul ation. Therefore, municipality -level population was used as a surrogate to project emissions from these sources.

Results The overall projected baseline point source emission totals ar e presented in Table 5; the baseline point source emission totals are also disaggregated by group in Table 6. The disaggregated emissions are also presen ted on a percentage basis in Table 7.

Table 5 indicates an approximately three-fold increase in baseline NO x 

### emissions from
1999 to 2030. Most of this increase can be attrib uted to the EGU sources, where the baseline
NO x 

### emissions in 2030 increased by 279 percen t from the 1999 levels. Similarly, the manufacturing sector saw a th ree-fold increase in 2030 NO x 

### emissions compared to the 1999 levels. However, the 2030 NO x 

### emissions in the refineries sect or was nearly unchanged relative
to the 1999 NO x 

### emissions.

According to Table 5, baseline SO 2 

### emissions in the year 2030 increased by a little over 25 percent from 1999. Of the total SO 2 

### emissions from the EGU sector in 1999, power plants fired with combustóleo (residual fu el oil) contributed approximatel y 75 percent of the emissions. As Mexico is moving away from use of residual fuel oil in power plants, SO 2 

### emissions in 2030 from residual fuel fired power plants dropped by almost 87 percent. On the other hand, SO 2 

### emissions from natural gas fired power plants experienced an increase of 30 percent and those from coal fired power plants increase d by approximately 279 percent. Also, SO 2 

### emissions in the year 2030 from the manufactur ing sector increased almost th ree-fold from the 1999 levels.Mexico Projections Final, January 9, 2009 

### 8 Over 50 percent of the VOC emissions from poi nt sources in 1999 were from refineries. The 2030 emissions were relatively unchanged comp ared to the 1999 emissions. The increase in
VOC emissions from 1999 levels to 2030 levels can be attributed to manufacturing industries with 2030 VOC emissions increasing by almo st 200 percent from their 1999 levels.

Approximately 72 percent of the total point source CO emissions in 1999 originate from refineries and manufacturing. While the emission s from refineries stayed the same, emissions from manufacturing are projec ted to increase by approximate ly 200 percent. Manufacturing contributes to slightly less than half of the total CO increase from 1999 to the year 2030. EGUs are responsible for a similar increase in CO emissions.

A majority of PM 10 

### emissions (i.e., 44 percent) and PM 2.5 

### emissions (i.e., 41 percent) in 1999 are from manufacturing. By 2030, particulat e emissions from these sources are projected to increase by approximately 190 percent compar ed to their 1999 levels. Out of the total increase in particulate emissi ons, manufacturing sources contribu te approximately 73 percent of
the PM 10 

### increase and 70 percent of the PM 2.5 

### emissions increase. In addition, EGUs contribute approximately 11 percent of the PM 10 

### increase and 26 percent of the PM 2.5 

### increase. Particulate emissions in the year 2030 from refineries stays almost the same as their 1999 levels.
4.2.2 Area Source Projections
The 1999 MNEI area source emissions were projected to 2008, 2012, and 2030 using various growth surrogates, as shown in Table 8. A majority of the area source categories were projected to 2008, 2012, and 2030 using population and fu el use surrogates. The growth factor development methodologies for each of the surrogates shown in Table 8.

Growth Factors – Population A population surrogate was used to projec t emissions growth for the 14 area source categories shown in Table 8. M unicipality-level population estim ates for Mexico for the time period 2005-2030 were obtained from CONAP O (CONAPO, 2008); 1999 municipality-level population data were obtained from the 1999 MNEI (ERG, 2006). Municipality-level population growth factors were calculat ed by dividing 2008, 2012, and 2030 population by 1999 population.Mexico Projections Final, January 9, 2009 

### 9 Growth Factors – Fuel Use Fuel use surrogates were used to project em issions growth for fuel combustion of six different fuels (i.e., distillate, residual, natural gas, LPG, kerosene, and wood), as well as
commercial marine vessels and th e distribution of gasoline and LPG. Future year fuel use projections were generated usi ng LEAP (Cuatecontzi, 2008). Th e projection data consisted of actual energy demand data for the years 1999 through 2006 and forecasted energy demand data for the years 2007 through 2030. These data were available by sector (e.g., industrial, commercial, residential, agricultural, transporta tion, etc.) and by fuel t ype. Sector- and fuelspecific growth factors were calcu lated by dividing the future year energy demand (in petajoules [PJ]) by 1999 energy demand (in PJ).

LPG demand for all sectors was summed togeth er to estimate the growth factors for the LPG distribution source category. Gasoline dema nd for the transportation sector was used to calculate growth factors for the ga soline distribution source category.

Growth Factors – Gross Domestic Product (GDP) Mexican GDP was used as a growth surroga te to project 1999 emissions to 2008, 2012, and 2030, for three area source categories (i.e., locomotives, industrial surface coatings, and degreasing). As discussed for poi nt sources, a GDP rate of 3.5 per cent has been recently used for various environmental and economic studies (Ga lindo Paliza, 2008). This annual growth rate was used for projecting these three source categories.

A slightly different method was used for lo comotives. The annual growth rate of 3.5 percent was used to develop the 2008 and 2012 growth factors; however, no growth was assumed to occur after 2012 (i.e ., the 2030 growth factor was assumed to be the same as the 2012 growth factor) (L ópez Villegas, 2008a).

Growth Factors – Planted Acreage Historical planted acreage by state was used to develop growth factors for the pesticide application, agricultural tilling, fertilizer application, and agricultural burni ng. State-level historical planted acreage from 1980 to 2006 was obtained from the Secret ariat of Agriculture, Livestock, Rural Development, Fisheries, and Food (SAGARPA – Secretaría de Agricultura,Mexico Projections Final, January 9, 2009 

### 10 Ganadería, Desarrollo Rural, Pesca y Aliment ación) (SAGARPA, 2008a). Using these data, a long-term annual average planted acreage was ca lculated for each state. Long-term annual average planted acreage was used rather than lin ear regressions because the state-level year-toyear statistics appeared to have some reporting gaps and tend to be very erratic. It was then assumed that the planted acreage in 2008, 2012, a nd 2030 will be equal to the long-term annual average planted acreage. Growth factors we re developed by dividing the long-term annual average planted acreage by the state-level 1999 pl anted acreage. In some cases, the growth factor was less than 1.0 (i.e., the long-term a nnual average planted acre age was less than the 1999 planted acreage). For agricult ural burning, only historical av erages of wheat and sugarcane planted acreages were used to deri ve growth factors. Burning of sugarcane prior to harvest is a common agricultural practice throughout the world in order to remove leafy trash. Post-harvest burning of wheat is commonly practiced to elimin ate wheat stubble; recent inventory efforts in San Luis Río Colorado, Sonora and Mexicali, Baja Cali fornia indicate that th e practice is fairly common in Mexico (ENVIRON and ERG, 2007; ERG, 2008).

Growth Factors – Livestock Population
Historical livestock populati on by state was used to develop growth factors for the
livestock ammonia and beef cattle feedlots. St ate-level livestock populat ions from 1996 to 2005 were obtained from SAGARPA for the following se ven livestock categories: beef cows, dairy cows, pigs, sheep, horses, chickens, and tu rkeys (SAGARPA, 2008b). Using these data, historical average populations were calculated for each livestock category fo r each state. It was then assumed that the livestock populations in 2008, 2012, and 2030 would be equal to the historical average populations. Gr owth factors were developed by dividing the historical average populations by the state-level 1999 li vestock populations. In some cases, the growth factor was less than 1.0 (i.e., the histor ical average populations were less than the 1999 livestock populations). The overall 1999 MNEI emissions for livestock ammonia were split into emissions by livestock type, and growth fact ors were applied to each livestock type to project emissions to 2008, 2012, and 2030.Mexico Projections Final, January 9, 2009 

### 11 Growth Factor – Burned Forest Acreage Historical data on burned forest acreage by stat e were used to develop growth factors for wildfires. State-level burned forest acreag e from 1970 to 2005 was obtained from the National Forest Commission (CONAFOR – Comisión Naci onal Forestal) (CONAFOR, 2008). Historical burned forest acreage was calculated at the state le vel and was assumed to be equal to the burned forest acreage in 2008, 2012, and 2030. Growth fact ors were developed by dividing the statelevel historical burned forest acreage by the 1999 burned forest acreage.

Growth Factor – Border Crossing Vehicle Traffic Historical border crossing vehicle traffic data were used to develop growth factors for border crossings. Historical tr affic data from the year 1995 to 2007 (including buses, trucks, and personal vehicles) were obtained from the U.S. Bu reau of Transportation Statistics (BTS) (BTS, 2008). These data were used to develop a linear regression equation to pred ict the total vehicular traffic at border crossings in 2008, 2012, and 2030. After predicting the annual traffic counts for 2008, 2012, and 2030, growth factors were develope d by dividing the future year vehicular traffic by 1999 vehicular traffic. Traffic data were limited to bor der crossing traffic for vehicles crossing from Mexico into the U.S. Emission esti mates for vehicles crossing from the U.S. into Mexico were not estimated as part of the 1999 MN EI because of insignificant wait times. Also,
the 1999 MNEI did not include em issions for border crossings at Mexico’s borders with Guatemala and Belize because of data unavailability.

Growth Factor – Aircraft Passenger Volume Annual air passenger traffic data were used to develop growth factors for aircraft emissions. Total passenger volume data (both domestic and international) from January 2001 through August 2008 were obtained from Grupo Aeroportu ario del Centro Norte, S.A.B. de C.V. (OMA) for 13 airports in north and central Mexi co (OMA, 2008). Although there are more than 13 airports located in Mexi co, it was assumed that the 13 OMA airports reasonably approximated the national level of aircraft activ ity. For the year 2008, the eight months of data from January to August were extrapolated to obtain an annual estimate for 2008. After completing the extrapolation of the 2008 annual es timate, the data from 2001 to 2008 were used to develop a linear regression equation to pred ict annual total passenger volume for 2012 andMexico Projections Final, January 9, 2009 

### 12 2020. Once the annual air passenger volumes for the years 2008, 2012, and 2030 was obtained, growth factors were developed by dividing the future year air passenger volume by 1999 air passenger volume.

Growth Factors – Public Wastewater Treatment
Historical public treated wast ewater quantities were used to develop growth factors for
wastewater treatment. Annual treated wastew ater quantities from 1999 to 2006, as well as planned treatment rate increas es until 2012, were obtained from the National Water Commission (CNA, 2007). Due to the unavailability of data , it was assumed that 2030 treatment quantities would be equal to 2012. The 2008 and 2012 planni ng values were divided by the 1999 actual treated quantities to obtai n the growth factors.

Results The projected baseline area source emission totals are summarized in Table 9, along with the initial 1999 area source emission totals. Baseline area source emissions disaggregated by SCC are presented in Tables 10 through 13.

As can be seen from the tables, SO 2 

### emissions in 2030 are pr ojected to decrease by almost 88 percent compared to the 1999 ba se year emissions. This decrease in SO 2 

### emissions can be primarily attributed to changes in th e industrial and commerc ial residual combustion category. SO 2 

### emissions from residual fuel com bustion in 1999 were approximately 56,000 Mg/year. The energy demand projections from LE AP (Cuatecontzi, 2008) indicated that there
will be no residual fuel combustion in the commercial sector after 2002; therefore, SO 2 

### emissions from commercial re sidual fuel combustion in 2008, 2012, and 2030 were set to zero. Similarly, the energy demand data also indicated that emissions from industrial residual fuel combustion are projected to dr op to 10 percent of 1999 levels.

The 2030 NO x 

### emissions, on the other hand, are proj ected to increase to nearly 200 percent of their 1999 level. Most of this increase can be attr ibuted to the commercial marine vessel and LPG combustion source categories. The NO x 

### emissions from commercial marine vessels are projected to incr ease from approximately 76,000 Mg/yr in 1999 to almost 282,000 Mg/yr in 2030. The energy demand projections from LEAP (Cuatecontzi, 2008) indicated aMexico Projections Final, January 9, 2009 

### 13 threefold increase in commercial marine diesel use in 2030 comp ared to 1999 levels. Also, NO x 

### emissions for all the LPG combustion categories (i.e., industrial, commercial, residential, transportation, and agriculture) are projecte d to grow from 72,750 Mg/yr in 1999 to 384,230 Mg/yr in 2030.

Tables 9 through 13 show a steady increase in VOC emission levels from 1999 to 2030. In 1999, approximately half the VOC emissions are from the solvent evaporation categories (e.g., industrial surface coatings, architectural su rface coatings, degreasing, consumer solvent usage, etc.). The growth factors for these categories were based upon either population or GDP and the VOC growth tends to mi rror these two growth factors.

Like VOC, the CO emission estimates also indicate a steady increase from the 1999 levels. However, it should be noted that almo st all of the CO increase can be attributed to growth in transportation LPG combustion. Th e 1999 CO emissions fr om transportation LPG combustion are approximately 279,000 Mg/yr, corre sponding to 11 percent of the total area source CO emissions. In 2030, the CO emissions for the same category projected to be 2,167,194 Mg/yr (i.e., an emissions increase of a factor of 8). This is due to an expected major increase in LPG usage by transportation sources, from 35.3 petajoules (PJ) in 1999 to 274.7 PJ in 2030 (Cuatecontzi, 2008). Other si gnificant area source contribut ors of CO emissions in 1999 (e.g., wildfires, agricultural bur ning, and residential wood combusti on) are projected to decrease by 2030.

Residential wood combustion a ccounts for 51 percent of PM 10 

### emissions and 68 percent
of PM 2.5 

### emissions in the 1999 MNEI. However, en ergy demand data indicate in a drop in residual wood combustion of almost 30 percent by 2030 (Cuatecontzi, 2008). This decrease in
residential wood combustion demand acc ounts for the corresponding drop in PM 10 

### and PM 2.5 

### emissions in 2030 relative to 1999 levels. As a re sult of this decrease, the agricultu ral tilling category increases in relative importance.

The 2030 NH 3 

### emissions are projected to decr ease by approximately 35 percent compared to the 1999 inventory. Most of this decrease can be attrib uted to reductions in livestock ammonia as a result of projecting historical average livestock statistics.Mexico Projections Final, January 9, 2009 

### 14 4.2.3 On-Road Motor Vehicle Projections The 1999 on-road motor vehicle emissions were projected to 2008, 2012, and 2030 using two different growth factors. The first grow th factor accounted for the increased demand of motor vehicle fuels projected between 1999 and 2030. As with many of the area source categories, future year gasoline use projecti ons were generated usi ng the Long-range Energy Alternatives Planning System (LEAP) (Cuatecontzi, 2008).

The second growth factor addressed the cha nges in vehicle technologies and emissions
due to the turnover of the Mexican fleet. Over time, newer vehicles with improved technologies (e.g., improved catalysts, etc.) and lower emissions will enter the vehicle fleet and gradually replace older vehicles with limited or no tec hnology. The effects of vehicle turnover were estimated using the MOBILE6-Mexico on-road motor vehicle emission factor model (ERG, 2003b). The MOBILE6-Mexico model was run for all years (i.e., 1999, 2008, 2012, and 2030) and fleet average emission rates were generated. The ratio of fleet average emission rates for each future year relative to the 1999 base year was calculated; this ra tio was the “turnover” factor. The overall growth factor for each of the future years was estimated by multiplying the fuel growth factor by the fleet turnover factor . A more detailed explanation of the MOBILE6- Mexico modeling process is provided below.

MOBILE6-Mexico Modeling – Fuel Regulations

The MOBILE6-Mexico model was modified to reflect new gasoline and diesel fuel standards regulations that would come into effect in Mexico in the future. Mexican fuel standards are split into three re gions (i.e., Metropolitan Zone [Z M], Frontier Zone [ZF], and the remainder of the country [RP]) with each region ha ving an applicable gasoline and diesel sulfur
standard.

Table 14 lists the Mexican fuel sulfur standa rds by fuel type and region for the 1999 base year and the three future years. These fuel sulf ur standards were obtained from the fuel standard implementation schedule provided by INE staff (PEMEX, 2008). It should be noted that
individual values in Table 14 represent maximum standards, while split values (e.g., 30/80) represent average/maximum standards, respectiv ely. Also, for Magna gasoline, the Frontier Zone (ZF) is considered to be part of the remainder of the country (RP). Although both MagnaMexico Projections Final, January 9, 2009 

### 15 and Premium gasoline are used in Mexico, onl y Magna gasoline (i.e., the predominant motor vehicle fuel) was used in the modeling r uns in order to simplify the analysis.

MOBILE6-Mexico Modeling – Other Model Parameters The average temperature range for Mexico was assumed to be a minimum of 55.6 o 

### F and
a maximum of 82.9 o 

### F for all the model runs. The fuel Reid Vapor Pressure (RVP) was assumed to be 7.5 psi and the average vehicle speed was assumed to be 18.5 kilometers per hour for all
the model runs.

MOBILE6-Mexico Modeling – Emission Standards

Mexico has motor vehicle emission limits sta ndards that are equivalent to a combination
of U.S. Tier 1 and Tier 2 standards and Eu ropean EURO 3 and EURO 4 standards (López Villegas, 2008b). The equivalency of Mexican motor vehicle emission standards to EURO
standards and U.S. standards is shown in Table 15. Because the MOBILE6-model is based an 80,000 km (i.e., 50,000 miles) certification rather th an a 100,000 km certification, the U.S. Tier 1
and Tier 2 standards were used for the modeli ng runs and the EURO 3 and EURO 4 standards were not investigated further.

The 1999 base year model runs in Mexico were assumed to be equivalent to U.S EPA’s Tier 0 standards. For the future years of 2008, 2012, and 2030, the Mexican A, B, and C standards were incorporated in to the MOBILE6-Mexico model runs. Mexican Standard A is similar to the U.S EPA’s Tier 1 standard for VOC, CO, and NO x 

### . Standards B and C are a
combination of U.S. EPA’s Tier 1 a nd Tier 2 standards for VOC, CO, and NO x 

### . For particulate emissions, Mexican Standards A, B, and C were a ll the same as U.S EPA’s Tier 1 standard. In addition, there are no emissions standards in Mexico for heavy-duty gasoline trucks and vehicles (HDGV and HDGT). Mexican Standards A, B, and C are presented in Tabl e 16 (Diario Oficial, 2005). The vehicle types used in the Mexican standards are defined below:

• PV – Passenger vehicle (light-duty) with a maximum gross vehicle weight rating (GVWR) of 8,500 lbs or less

• LDT1 – Light-duty truck with a maximum loaded vehicle weight (LVW) of 3,750 lbs and GVWR not to exceed 6,000 lbsMexico Projections Final, January 9, 2009 

### 16 • LDT2 – Light-duty truck with a mini mum LVW of 3,750 lbs and GVWR not to exceed 6,000 lbs

• LDT3 – Light-duty truck with a maximum ad justed loaded vehi cle weight (ALVW) of 5,750 lbs and GVWR greater than 6,000 lbs

• LDT4 – Light-duty truck with a mini mum ALVW of 5,750 lbs and GVWR not to exceed 6,000 lbs.
The phase-in schedule of Mexican Standards A, B, and C as a percentage of vehicles within each model year are pr esented in Table 17. As show n in Table 17, the 2008 phase-in schedule indicates a 50 percent allocation for Stan dard A and 50 percent allocation for Standard B. The schedule for 2012 consists of a 75 per cent allocation for Standa rd B and a 25 percent allocation for Standard C. By 2015, Standard C w ill be phased in entirely. Lacking information regarding additional future standards beyond Standard C, it was assumed that the Standard C
would still be in effect in 2030.

MOBILE6-Mexico Modeling – Implem entation Schedule Input File
The external input file that contains information rele vant to the emission standard implementation schedule is calle d the Mex_P94_Imp.dat. This file contains the implementation schedule from model year 1994 thru model year 2025 (inclusive). The file contains the fraction of implementation for different standards for eac h of the above mentioned years by vehicle type (e.g., Tier 0, Tier 1 (interim) Tier 1, Tier 2, Tier LEV (interim), Ti er LEV, etc.). For purposes of this projection analysis, only Tier 1 and Tier 2 standards are analyzed for future year scenarios. The format of the Mex_P94_Imp.dat file (i.e., un modified default file from MOBILE6-Mexico) is shown in Figure 1 (included after all of the tables). Fi gure 1 shows the implementation schedule for LDGV. Columns represent standards (e.g., Tier 0, Tier 1 (interim), Tier 1, Tier 2, etc.), while rows represent model years (i.e., firs t row is 1994 and last row is 2025). In Figure 1,
the first row of values indicate that fo r 1994 model year LDGVs, there was 100 percent implementation of Tier 0 standards, while the four th row of values indicate that for 1997 model year LDGVs, there was 60 percent implement ation of Tier 0 standards and 40 percent implementation of Tier 1 (interim) standards.

The implementation schedule input file (i.e., Mex_P94_Imp.dat) was modified to represent the Mexican implementation schedul e for Standards A, B, and C as follows:Mexico Projections Final, January 9, 2009 

### 17 • 1999 run for HC, CO, and NOx: 100 percent Tier 0

• 2008 run for HC, CO, and NOx: 50 percent Tier 1 and 50 percent Tier 2

• 2012 run for HC, CO, and NOx: 70 percent Tier 1 and 30 percent Tier 2

• 2030 run for HC, CO, and NOx: 100 percent Tier 2

• 1999 run for PM, SO2, and NH3: 100 percent Tier 0

• 2008 run for PM, SO2, and NH3: 100 percent Tier 1

• 2012 run for PM, SO2, and NH3: 100 percent Tier 2

• 2030 run for PM, SO 2 

### , and NH 3 

### : 100 percent Tier 2
MOBILE6-Mexico Modeling – Certification Standards Input File
The external input file th at contains information re garding vehicle manufacturer
certification standards is calle d Mex_T2CERT.dat. The Mex_T2CERT.dat file contains the 50,000 mile certification standa rds by certification bin by pollutant (HC, CO, and NO x 

### ). The format of the Mex_T2CERT.dat file (i.e., unmodi fied default file from MOBILE6-Mexico) is shown in Figure 2. Figure 2 presents the Mexica n certification standards for Mexico for HC and CO by vehicle type. Columns represent vehi cle type (i.e., LDV, LDT1, LDT2, LDT3, and LDT4), while rows represent certification bins 1 through 12 for each pollutant. In the first matrix (i.e., group of 12 rows), the first row indi cates an HC standard of 0.25 g/mile for LDV and LDT1, an HC standard of 0.32 g/mile for LDT2 and LDT3, and an HC standard of 0.38 g/mile for LDT4. The second matrix contains CO standards and the third matrix (not shown in Figure 2) contains NO x 

### standards. In order to represent Mexican Standards A, B, and C, only bins 1, 2, and 3 were used with the remaining bi ns left blank or zero. The Mex_T2CERT.dat file was only applicable for HC, CO, and NO x 

### . The same modified Mex_T2CERT file was used for
all MOBILE6-Mexico runs (i.e., 1999, 2008, 2012, and 2030).

MOBILE6-Mexico Modeling – Exhaust Emission Standards Input File
The external input file that contains information rega rding the phase-in schedule for the
Tier 2 exhaust emission standards is calle d Mex_T2EXH.dat. The format of the Mex_T2EXH.dat is shown in Figure 3. The 12 columns represent model years 2004 through 2015, while the 180 rows represent the 12 certificati on bins for each vehicle type (i.e., LDV,Mexico Projections Final, January 9, 2009 

### 18 LDT1, LDT2, LDT3, and LDT4) by pollutant (i.e., HC, CO, and NO x 

### ). Rows 1 through 12 contain bins 1-12 for LDV HC, rows 13 through 24 contain bins 1-12 for LDV CO, and rows 25 through 36 contain bins 1-12 for LDV NO x 

### . A similar pattern holds for LDT1 HC, CO, and NO x 

### in rows 37 through 72; LDT2 HC, CO, and NO x 

### in rows 73 through 108, etc.

The modified Mex_T2EXH.dat file is presented in Figure 3. Bins 1, 2, and 3 are used to represent Mexican Standards A, B, and C, while bins 4 through 12 are all blank or zeroes. In Row 1, bin1 (i.e., Mexican Standa rd A for HC) indicates 100 pe rcent phase-in from 2004 to 2006; dropping to 75 percent in 2007, 50 percent in 2008, and 30 per cent in 2009; and then total phase-out (i.e., 0 percent) begi nning in 2010. In Row 2, bin 2 (i.e., Mexican Standard B for HC) begins phase-in at 25 percent in 2007, reaches 100 percent phase-in in 2010 and 2011, and then total phase-out in 2015. In Row 3, bin 3 (i.e., Mexican Standard C for HC) phases in at 25 percent in 2012, 50 percent in 2013, 70 percent in 2014, and then re aches 100 percent phase-in in 2015. Similar phase-in schedules are also included in Rows 13 through 15 (for CO) and Rows 25 through 27 (for NO x 

### ). Since this file only contai ns phase-in schedule until 2015, it was
assumed that 2030 standards will be the same as t hose in 2015. This external file is applicable only for HC, CO, and NO x 

### emissions and is same for a ll runs (i.e., 1999, 2008, 1012, and 2030).

MOBILE6-Mexico Emission Factors After making modifications to the Mex_P94_Imp.dat, Mex_T2CERT.dat, and Mex_T2EXH.dat external input f iles, the MOBILE6-Mexico model was then run to generate fleet average emission factors for the base year 1999, as well as fo r the future projection years of 2008, 2012, and 2030. These model runs accounted for both Mexican fuel standards and emission standards. After the fleet average em ission factors were gene rated, turnover factors were calculated by dividing the future year em ission factors by the base year 1999 emission factors. These future year turnover factors we re then multiplied by the future year gasoline growth factors (Cuatecontzi, 2008 ) to develop a set of composit e projection factors that were used to project 1999 base year on-road em issions to 2008, 2012, and 2030. The composite projection factors by pollutant and region are presented in Table 18.

As can be seen in Table 18, there are pr ojected to be significant reductions in NO x 

### , SO 2 

### , VOC, and CO emission factors by 2030, in spite of increased mo tor vehicle fuel use. TheMexico Projections Final, January 9, 2009 

### 19 reductions in NO x 

### , VOC, and CO are due to fleet turnover, which gradually in corporates cleaner
vehicles into the overall fleet ov er time. The reductions in SO 2 

### are attributable to the lower
sulfur contents in the future Mexi can fuel standards. Increased PM 10 

### and PM 2.5 

### emissions are the result of increased fuel use without any future PM standards, while increased NH 3 

### emissions are likely due to fleet turnover (i.e ., new vehicle technologies, such as advanced catalytic converters
tend to reduce NO x 

### , but increase NH 3 

### ).

The projected baseline on-road motor vehicl e emission totals are summarized in Table 19, along with the initial 1999 area source emission totals. Ba seline on-road motor vehicle emissions disaggregated by vehicl e classification are presented in Table 20. The disaggregated emissions are also presented on a percentage basis in Table 21.

4.2.4 Nonroad Mobile Source Projections
The 1999 nonroad mobile source emissions were projected to 2008, 2012, and 2030 using energy demand projections. The 1999 nonroad mobile source categories were limited to dieselpowered agricultural equipment and diesel-pow ered construction equipment, only, due to the lack of Mexico-specific activity data for ot her types of nonroad equipment (e.g., recreational vehicles, lawn and garden equipment, etc.). Fu ture year fuel use projections were generated using LEAP (Cuatecontzi, 2008); th ese projections included disa ggregated demand data for the transportation, industrial, commercial, and agricultural sectors.

Diesel energy demand in the agricultural se ctor was used as a surrogate to project nonroad emissions from the agricultural equipm ent source category. The data indicated an increase of approximately 75 percent in di esel usage for agricultural equipment in 2030 compared to 1999 usage. Diesel energy dema nd in the commercial sector was used as a surrogate to project 1999 nonroad emissions for construction equipm ent. The data indicated an increase of approximately 57 percent in dies el usage for construc tion equipment in 2030 compared to 1999 usage.

A summary of baseline nonroad mobile source emissions is provided in Table 22.Mexico Projections Final, January 9, 2009 

### 20 4.3 Projections Summary The entire projected baseline Mexico NEI emissions are summarized in Table 23 by emission type, along with the initial 1999 inventor y. The projected baseline emissions are also presented on a percentage basis in Table 24.

In general, emissions from point sources, area sources, and nonroad mobile sources are projected to increase in future years relative to the 1999 base year. The projection factors for these source types are primarily driven by popul ation growth, GDP growth, and fuel growth. There are also a few source categories with decreasing emissions (i.e., area source SO 2 

### , PM 10 

### , and PM 2.5 

### ); these are due to projected decreases in certain fuel type s and uses (i.e., commercial
combustion of residual fuel oil and residential wood combustion).

As described in Section 4.2.3, on-road motor vehicle NO x 

### , SO 2 

### , VOC, and CO emissions are projected to decrease in future years relative to the 1999 base year, while PM 10 

### , PM 2.5 

### , and
NH 3 

### emissions increase. Although the demand for moto r vehicle fuel will in crease in the future,
the decreases in NO x 

### , SO 2 

### , VOC, and CO emissions are due to effects of new control technologies that are gradually inco rporated into the overall vehicle fleet due to turnover, as well
as low sulfur fuels. Because new motor vehi cle standards are not be ing implemented for PM 10 

### , PM 2.5 

### , and NH 3 

### , emissions are projected to increase in the future for these pollutants.

5.0 CONTROL SCENARIOS
Following the development of base year emission projections for 2008, 2012, and 2030, additional analysis was conducted involving three control scenarios and their effect on future
emissions. All three control scenarios focus onl y on on-road motor vehicles and do not affect point, area, or nonroad mobile s ources. Details of the control scenarios and the associated control levels were developed by INE staff (Inie stra Gómez, 2008), and are described in the following subsections.
5.1 Control Scenario 1 – Increased Fuel Economy
The first control scenario considers an in crease in fuel economy for new light-duty gasoline vehicles and trucks; the fuel economy fo r all other vehicle type s is assumed to be unchanged. The baseline fuel ec onomy for new vehicles is assu med to be 10.82 kilometers per liter (km/l), and will begin increasing by 1 km /l annual in 2011 until reaching a value of 15.82Mexico Projections Final, January 9, 2009 

### 21 km/l in 2015 and all subsequent years. The pollu tant specific reductions are presented in Table
25. No emission reductions will occur in the fu ture year 2008; reductions will only occur in 2012 and 2030. In addition, no emission reductions were quantified for SO 2 

### or NH 3 

### .
5.2 Control Scenario 2 – Use of Ethanol in Oxygenated Fuel Oxygenated fuels have been used in the ma jor metropolitan zones of Mexico since 1990 in order to reduce ozone levels. The oxygenate d gasoline supplied by PEMEX contains methyl tert-butyl ether (MTBE) and/or tertiary amyl methyl ether (TAME). PEMEX is currently contemplating switching from MTBE/TAME to ethanol.

The second control scenario involves the switch from MTBE/TAME oxygenates to ethanol while maintaining an oxygenate level of 2 percent by weight as required by NOM-086. The switch is assumed to begin in Guadalajar a in 2010, follow in Monterrey in 2011, and finish in Mexico City in 2012. The muni cipalities affected by this switc h are listed in Table 26. All other fuel characteristics (e.g., Reid vapor pr essure [RVP], etc.) are assumed to remain unchanged. The switch to oxygenated fuel with et hanol was assumed to only affect gasolinefueled vehicles (i.e., light-duty gasoline vehicles, light-duty gasolin e trucks, heavy-duty gasoline vehicles, and motorcycles).

The reductions for Guadalajara, Monterrey, and Mexico City are presented in Table 27.
No emission reductions will occur in the future year 2008; reductions will only occur in 2012
and 2030. The emission reductions were a pplied for all inventoried pollutants.
5.3 Control Scenario 3 – Combined Increased Fuel Economy and Use of Ethanol in Oxygenated Fuel

The third control scenario is the combined implementation of Control Scenario 1 and Control Scenario 2 and does not include any new control strategies. The effects of Control Scenarios 1 and 2 are applied by ca lculating the reduced emissions due to Control Scenario 1 and then applying the controls from Control Scenar io 2. The effect of Control Scenario 3 is dependent on the vehicle classification, polluta nt, or geographically location to which it is applied. For example, Control Scenar io 3 for light-duty gasoline vehicle NO x 

### emissions in Guadalajara would include the control effect s from both Control Scenario 1 and ControlMexico Projections Final, January 9, 2009 

### 22 Scenario 2, while Control Scenario 3 for heavy- duty diesel vehicle emissions in the state of
Sonora would have no control effects from C ontrol Scenario 1 or Control Scenario 2.
5.4 Projections Summary with Controls The projected on-road motor vehicle emission totals, including the effects of Control Scenarios 1, 2, and 3 are summarized in Table 2 8. Control Scenarios 1, 2, and 3 are identified with the abbreviations CS1, CS2, and CS3, respec tively. For reference purposes, the baseline projected emission totals for 1999, 2008, 2012, and 2020 from Table 19 have also been included.

The projected on-road motor vehicle emi ssions including controls disaggregated by vehicle classification are presen ted in Table 29. For reference purposes, the baseline projected emission totals for 1999, 2008, 2012, and 2020 from Table 20 have also been included.

Because Control Scenarios 1, 2, and 3 are based upon on-road motor vehicle control strategies, only on-road motor vehicle emissions are presented in Table 28 and Table 29. Point source, area source, and nonroad mobile source em issions are not impacted by Control Scenarios 1, 2, and 3.

The emission reductions due to Control Scenar io 1 vary from 0.1 percent to 0.6 percent for 2012 and from 1.1 percent to 5.0 percent for 2030; Control Scenario 1 does not affect SO 2 

### and NH 3 

### , so these are not included in these reduction values. The percentage reductions due to
Control Scenario 1 relative to baseline emissions increase over time because new vehicles with improved fuel economy gradually pe netrate the overall vehicle fl eet over time, thereby raising the fleet average fuel economy and d ecreasing emissions from the fleet.

The percentage reductions due to Control Scenario 2 vary from 0.6 percent to 1.3 percent for 2012 and from 0.5 percent to 1.3 percent for 2030. The emission reductions due to Control
Scenario 2 relative to baseline emissions ar e fairly constant from 2012 to 2030 because the switch from MTBE/TAME-based oxygenated fuels to ethanol-based oxyge nated fuels is a onetime event that does not have increasing penetration over time.

As expected, emission reductions due to Cont rol Scenario 3 are gr eater than those of Control Scenarios 1 or 2 applied individually, an d range from 0.7 percent to 1.5 percent for 2012, and from 1.0 percent to 5.7 percent for 2030.Mexico Projections Final, January 9, 2009 

### 23 6.0 HARMONIZATION WITH GREENHOUS E GAS EMISSIONS INVENTORIES
An objective to be accomplished as part of the development of emissions projections is to “harmonize” the future year criteria pollutant em ission projections with current and future year greenhouse gas emissions inventories in Mexico. The term “harmonize” refers to standardizing or increasing comparability and/or convergence between inventories.

Because of methodological differences betw een criteria pollutant and greenhouse gas inventories, there are inherent differing aspect s between the two types of inventories. For example, VOC emissions from consumer solvents are typically estimated with an annual per capita emission factor combined with population counts; however , consumer solvents do not generate greenhouse gas emissions. In contrast , fuel combustion is a source of both criteria pollutants (i.e., NO x 

### , SO 2 

### , CO, and VOC) and greenhouse gase s (i.e., carbon dioxide, methane, and nitrous oxide). .

In order to ensure harmony between crit eria pollutant and greenhouse gas emission inventories, INE provided important data and assumptions used in the development of Mexico’s greenhouse gas emissions inventories. For example, future year fuel use projections from LEAP were developed to estimate gree nhouse gas emissions in Mexico (Cuatecontzi, 2008). These future fuel use projections were then used in th is project to generate criteria pollutant growth
factors for a wide number of sour ces categories, including: point source electric generating units (EGUs), area source fuel combustion (i.e., industria l, commercial/institutional, residential, and agricultural), area source fuel distribution (i.e ., gasoline and LPG), on-road motor vehicles (in conjunction with the MOBILE6-Mexico analysis), and nonroad mobile sources. In addition, underlying economic assumptions, such as annual Gross Domestic Product (GDP) growth rates (Galindo Paliza, 2008), were used to develop pr ojection factors for some point sources (i.e., manufacturing industries and miscellaneous indu stries) and some area source categories (i.e., locomotives, industrial surface coating, and degreasing) in this project.

A certain level of harmony was obtained by using information from Mexico greenhouse gas inventories to develop projecti on factors for the future year cr iteria pollutant projections. In some cases, momentary pauses in the project schedule occurred to ensure that the most up-to-Mexico Projections Final, January 9, 2009 

### 24 date greenhouse gas inventory information was obt ained, rather than using outdated information
or information unrelated to greenhouse gas inventories.

7.0 REFERENCES Blanchard, 2001. Analysis of the IEO2001 Non-OPEC Supply Projections . Roger D. Blanchard, Northern Kentucky University, Highland Heights, Kentucky. April 9. Internet address: http://dieoff.org/page231.pdf

BTS, 2008. U.S. Border Crossings/Entries by State/Port and Month/Year . U.S. Bureau of Transportation Statistics. Internet ad dress: http://www. transtats.bts.gov/ bordercrossing.aspx

CEC, 2004. North American Power Plant Air Emissions . Commission for Environmental Cooperation of North America, Montreal, Canada.

CNA, 2008. Estadísticas del Agua en México – Edición 2008 . Prepared by the National Commission on Water ( Comisión Nacional del Agua ). Internet address: http://www.conagua.gob.mx/conagua/Espanio l/TmpContenido.aspx?id=Publicaciones%202008| PUBLICACIONES%20CONAGUA|0|87|0|0|0
CONAFOR, 2008. Historical burned forest acre age from Sistema Nacional de Información Forestal (SNIF), (Comisión Nacional Forestal). Internet address: http://148.223.105.188:2222/snif_portal/index.php?opti on=com_content&task=view&id=44&Ite mid=54

CONAPO, 2008. Proyecciones de la Pobl ación de México 2005-2050 . Consejo Nacional de Población. Internet address: http://www.conapo.gob.mx/00cifras/5.htm
Cuatecontzi, 2008. Long-range Energy Alternatives Planning System (LEAP) fuel projections provided by D. Cuatecontzi, Na tional Autonomous Universi ty of Mexico. August 6.
Diario Oficial, 2005. NORMA Oficial Mexicana NOM-042-SEMARNAT-2003 . Diario Oficial, September 7.
ENVIRON and ERG, 2007. Development of Air Emissions In ventory for the Western Arizona Sonora Border Air Quality Study (WASBAQS) – Emission Inventory Project Report . Prepared for the Arizona Department of Environmental Quality by ENVIRON International Corporation and Eastern Research Group, Inc., June.

ERG, 2003a. Mexico National Fuel Balance . Prepared for the Secretariat of the Environment and Natural Resources and the National Institut e of Ecology of Mexico by Eastern Research Group, Inc., Sacramento, California with sponsorsh ip of the U.S. EPA, Western Governors’ Association, and the North American Commi ssion for Environmental Cooperation. July 17.
ERG, 2003b. MOBILE6-Mexico . Prepared for the Western Gove rnors’ Association by Eastern Research Group, Inc., Austin, Texas. June 27.Mexico Projections Final, January 9, 2009 

### 25 ERG, 2006. Mexico National Emissions Inventory, 1999 – Final . Prepared for the Secretariat of the Environment and Natural Resources and th e National Institute of Ecology of Mexico by Eastern Research Group, Inc., Sacramento, Calif ornia with sponsorship of the U.S. EPA, Western Governors’ Association, and the No rth American Commission for Environmental Cooperation. October 11.

ERG, 2008. 2005 Mexicali Emissions Invento ry – Draft Final Report . Prepared for the Western Governors’ Association; U.S. Environmental Pr otection Agency, Region 9; and Secretaría de Protección al Ambiente de Baja California by Eastern Research Group, Inc. October 3.
Galindo Paliza, 2008. Personal communication with L.M. Galindo Paliza (National Autonomous University of Mexico) regarding gross domestic product (GDP) projection assumptions. June 4.
Iniestra Gómez, 2008. Personal communication with R. Iniest ra Gómez regarding control scenarios. December 18.
López Villegas, 2008a. Personal communication with M.T. López Villegas (N ational Institute of Ecology of Mexico) regarding projecti on methodology for locomotives. June 6.
López Villegas, 2008b. Personal communication with M.T. López Villegas (N ational Institute of Ecology of Mexico) regarding equivalence of Mexican and U.S. motor vehicle emission standards. July 4.
OMA, 2008. Monthly traffic repor ts from Grupo Aeroportuario del Centro Norte, S.A.B. de C.V. (OMA). Internet address: http://ir.oma.aero/inde x.cfm?subj=profile

OPEC, 2007. World Oil Outlook . Organization of the Petrol eum Exporting Countries, Vienna, Austria. Internet address: http://www.opec.org/library/ World%20Oil%20Outlook/pdf /WorldOilOutlook.pdf
PEMEX, 2008. Fuel standard implemen tation calendar, PEMEX Refining. May 30.
SAGARPA, 2008a. Historical planted acreage data from Estadística Básica – Agrícola

. Servicio de Información Agroalimentaria y Pesq uera (SIAP); Secretaría de Agricultura, Ganadería, Desarrollo Rural, Pesca y Alimentaci ón. Internet address: http://www.siap.gob.mx/
SAGARPA, 2008b. Historical livestock populations from Estadística Básica – Pecuario

. Servicio de Información Agroalimentaria y Pesq uera (SIAP); Secretaría de Agricultura, Ganadería, Desarrollo Rural, Pesca y Aliment ación. Internet address: http://www.siap.gob.mx/

USGS, 2008. The Mineral Industry of Mexico . United States Geologic Survey, Mineral Resources Program (multiple years). Internet address: http://minerals.usgs.gov/minerals/pubs/ country/latin.html#mqMexico Projections Final, January 9, 2009 

### 26 Table 1. New Munici palities in Mexico
State New Municipality Previously Existing Municipalities Guerrero Marquelia (077) Azoy ú (013); Cuajinicuilapa (023) Guerrero Cochoapa el Gra nde (078) Metlatónoc (043) Guerrero José Joaquín de Herrera (079) A tlixtac (010); Chilapa de Alvarez (028) Guerrero Juchitán (080) Azoyú (013) Guerrero Iliatenco (081) Malinalte pec (041); San Luis Acatlán (052) México Luvianos (123) Tejupilco (082) México San José del Rincón (124) San Felipe del Progreso (074) México Tonanitla (125) Jaltenco (044) Veracruz San Rafael (211) Martínez de la Torre (102) Veracruz Santiago Sochiapan (212) Playa Vicente (130) Zacatecas Santa María de la Paz (058) Apozol (001) ; Atolinga (003); Benito Juárez (004); Jalpa (019); Juchipila (023); Tepechitlán (045); Teul de González Ortega (047)
Note: Parenthetical numbers are municipality codes.Mexico Projections Final, January 9, 2009 

### 27 Table 2. Point Source Groups and Applicable NAICS Codes

Point Source Group 3-Digit NAICS NAICS Description EGUs 221 Utilities 211 Oil & Gas Extraction 324 Petroleum & Coal Products Manufacturing 325 Chemical Manufacturing Refineries 424 Merchant Wholesalers, Nondurable Goods Primary Metals 331 Prim ary Metal Manufacturing 311 Food Manufacturing 312 Beverage & Tobacco Product Manufacturing 313 Textile Mills 314 Textile Product Mills 315 Apparel Manufacturing 316 Leather & Allied Product Manufacturing 321 Wood Product Manufacturing 322 Paper Manufacturing 324 Petroleum & Coal Product Manufacturing 325 Chemical Manufacturing 326 Plastics & Rubber Products Manufacturing 327 Nonmetallic Mineral Product Manufacturing 332 Fabricated Metal Product Manufacturing 333 Machinery Manufacturing 334 Computer & Electronic product Manufacturing 335 Electrical Equipment, Appliance, and Component Manufacturing 336 Transportation Equipment Manufacturing 337 Furniture and Related Product Manufacturing 339 Miscellaneous Manufacturing Manufacturing Industries

999 Undisclosed a 212 Mining (except Oil and Gas) Miscellaneous Industries 424 Merchant Wholesalers, Nondurable Goods 323 Printing and Related Support Activities 562 Waste Management and Remediation Services 811 Repair and Maintenance Services

812 Personal and Laundry Services

a In the 1999 Mexico NEI, state jurisdiction point sources that be longed to a particular NAICS gr oup and numbered fewer than thre e facilities in

any given municipality were assigned NAICS 999 to maintain confidentiality.Mexico Projections Final, January 9, 2009 

### 28 Table 3. Electricity Generation Fuel Consumption (PJ/yr) Fuel Type 1999 2008 2012 2030 Natural Gas 272.97 951.22 1,284.11 3,547.24 Residual Fuel Oil 887.53 386.24 265.10 117.59 Coal 178.69 254.71 304.18 499.82 Distillate Fuel Oil 17.54 34.25 40.37 66.53 Electricity 651.30 43.80 52.96 121.46 Wind NA 5.02 16.59 53.26 Uranium NA 171.05 211.30 362.22 Hydro NA 316.31 357.00 442.68 Geothermal NA 62.12 69.74 80.24 

### Table 4. Crude oil production da ta for Mexico (Barrels/day)

Year Crude Production Projection Factor 1999 2,877,698 NA 2008 3,800,000 1.32 2012 3,800,000 1.32 2030 2,900,000 1.01


### Table 5. 1999, 2008, 2012, and 2030 Base line Point Source Emissions (Mg/yr)

Year NO x SO 2 VOC CO PM 10 PM 2.5 1999 448,826 2,633,799 247,878 167,648 297,264 198,917 2008 603,467 2,572,474 327,424 236,756 357,765 237,438 2012 692,807 2,623,275 349,642 265,297 394,071 261,330 2030 1,250,510 3,372,241 458,669 440,926 647,395 428,476Mexico Projections Final, January 9, 2009 

### 29 Table 6. Projected Baseline Point Source Emissions by Group (Mg/yr)

Group NO x SO 2 VOC CO PM 10 PM 2.5 1999 EGUs 259,804 1,604,803 11,390 25,345 79,506 62,882 Refineries 74,025 755,267 129,135 58,348 43,246 29,871 Primary Metals 25,777 30,525 6,705 11,656 21,469 18,288 Manufacturing Industries 87,091 232,777 95,839 63,820 130,806 80,878 Miscellaneous Industries 2,048 10,223 276 8,466 22,187 6,956 Services 80 204 4,533 13 50 42 Total 448,825 2,633,799 247,878 167,648 297,264 198,917 2008 EGUs 352,425 1,206,163 13,149 46,833 65,673 55,736 Refineries 97,750 997,330 170,523 77,049 57,107 39,444 Primary Metals 31,719 37,561 8,251 14,343 26,418 22,504 Manufacturing Industries 118,696 317,251 130,619 86,980 178,275 110,229 Miscellaneous Industries 2,791 13,933 376 11,538 30,238 9,480 Services 86 236 4,506 13 54 45 Total 603,467 2,572,474 327,424 236,756 357,765 237,438 2012 EGUs 420,201 1,203,778 15,161 59,194 68,184 59,383 Refineries 97,750 997,330 170,523 77,049 57,107 39,444 Primary Metals 35,359 41,872 9,198 15,989 29,450 25,087 Manufacturing Industries 136,207 364,053 149,888 99,812 204,575 126,490 Miscellaneous Industries 3,203 15,989 431 13,240 34,699 10,879 Services 87 253 4,441 13 56 47 Total 692,807 2,623,275 349,642 265,297 394,071 261,330 2030 EGUs 865,129 1,843,612 31,847 148,724 116,210 106,454 Refineries 74,599 761,120 130,136 58,800 43,582 30,102 Primary Metals 51,740 61,270 13,459 23,397 43,094 36,709 Manufacturing Industries 253,002 676,225 278,416 185,400 379,996 234,954 Miscellaneous Industries 5,949 29,699 801 24,593 64,453 20,207 Services 91 315 4,010 12 60 50 Total 1,250,510 3,372,241 458,669 440,926 647,395 428,476Mexico Projections Final, January 9, 2009 

### 30 Table 7. Point Source Emissions by Group (% of Total) Group NO x SO 2 VOC CO PM 10 PM 2.5 1999 EGUs 

### 57.9% 60.9% 4.6% 15.1% 26.7% 31.6% Refineries 

### 16.5% 28.7% 52.1% 34.8% 14.5% 15.0% Primary Metals 

### 5.7% 1.2% 2.7% 7.0% 7.2% 9.2% Manufacturing Industries 

### 19.4% 8.8% 38.7% 38.1% 44.0% 40.7% Miscellaneous Industries 

### 0.5% 0.4% 0.1% 5.0% 7.5% 3.5% Services 

### 0.0% 0.0% 1.8% 0.0% 0.0% 0.0% Total 2008 EGUs 58.4% 46.9% 4.0% 19.8% 18.4% 23.5% Refineries 16.2% 38.8% 52.1% 32.5% 16.0% 16.6% Primary Metals 5.3% 1.5% 2.5% 6.1% 7.4% 9.5% Manufacturing Industries 19.7% 12.3% 39.9% 36.7% 49.8% 46.4% Miscellaneous Industries 0.5% 0.5% 0.1% 4.9% 8.5% 4.0% Services 0.0% 0.0% 1.4% 0.0% 0.0% 0.0% Total 2012 EGUs 60.7% 45.9% 4.3% 22.3% 17.3% 22.7% Refineries 14.1% 38.0% 48.8% 29.0% 14.5% 15.1% Primary Metals 5.1% 1.6% 2.6% 6.0% 7.5% 9.6% Manufacturing Industries 19.7% 13.9% 42.9% 37.6% 51.9% 48.4% Miscellaneous Industries 0.5% 0.6% 0.1% 5.0% 8.8% 4.2% Services 0.0% 0.0% 1.3% 0.0% 0.0% 0.0% Total 2030 EGUs 69.2% 54.7% 6.9% 33.7% 18.0% 24.8% Refineries 6.0% 22.6% 28.4% 13.3% 6.7% 7.0% Primary Metals 4.1% 1.8% 2.9% 5.3% 6.7% 8.6% Manufacturing Industries 20.2% 20.1% 60.7% 42.0% 58.7% 54.8% Miscellaneous Industries 0.5% 0.9% 0.2% 5.6% 10.0% 4.7% Services 0.0% 0.0% 0.9% 0.0% 0.0% 0.0% TotalMexico Projections Final, January 9, 2009 

### 31 Table 8. Area Source Growth Surrogates Surrogate Area Source Categories Population ● Charbroiling/street vendors

● Bakeries

● Construction activities

● Architectural surface coatings

● Autobody refinishing

● Traffic markings

● Dry cleaning

● Graphic arts

● Consumer solvent usage

● Asphalt application

● Open burning

● Structure fires

● Brick kilns

● Domestic ammonia Fuel use ● Distillate fuel combustion (industrial and commercial)

● Residual fuel combustion (industrial and commercial)

● Natural gas fuel combustion (industr ial, commercial, and residential)

● LPG fuel combustion (industrial, commercial, residential, transportation, and agriculture)

● Kerosene fuel combustion (industrial, residential, and agriculture)

● Residential wood combustion

● Commercial marine vessels

● Gasoline distribution

● LPG distribution Gross Domestic Product (GDP) ● Locomotives

● Industrial surface coating

● Degreasing Planted acreage by state ● Pesticide application

● Agricultural tilling

● Fertilizer application

● Agricultural burning Livestock population ● Livestock ammonia

● Beef cattle feedlots Forest acreage burnt by state ● Wildfires Vehicular traffic at border crossings ● Border crossings
Airline passenger volume ● Aircraft Residential wastewater treated quantities ● Wastewater treatment



### Table 9. 1999, 2008, 2012, and 2030 B aseline Area Source Emissions (Mg/yr)

Year NO x SO 2 VOC CO PM 10 PM 2.5 NH 3 1999 276,321 194,642 1,743,587 2,500,852 439,253 320,369 1,130,400 2008 363,963 119,763 2,106,842 3,068,145 483,735 355,488 724,092 2012 415,907 60,094 2,202,932 2,939,976 443,800 317,645 727,417 2030 854,999 23,223 3,170,187 4,167,536 412,043 286,518 738,330Mexico Projections 

### 32 Final, January 9, 2009Table 10. 1999 Area SourceEmissions by SCC (Mg/yr)SCCSCC DescriptionNOxSO2VOCCOPM10PM2.5NH32102004000 Distillate fuel combustion –Industrial 2,562 637 21 534 107 262102005000 Residual fuel combustion – Industrial10,721 132,466 64 1,141 7,300 4,7542102006000 Natural gas fuel combustion – Industrial 28,404 61 558 8,521 771 7712102007000 LPG fuel combustion – Industrial 710 1 13 121 21 212102011000 Kerosene fuel combustion – Industrial 28 6 0 6 1 02103004000 Distillate fuel combustion– Commercial 235 62 4 59 13 102103005000 Residual fuel combustion – Commercial 5,233 56,173 108 476 590 2192103006000Natural gas fuel combustion –Commercial 305 2 17 256 23 232103007000 LPG fuel combustion – Commercial 4,471 12 110 619 141 1412104006000 Natural gas fuel combustion – Residential 872 6 51 371 71 712104007000 LPG fuel combustion – Residential 22,553 60 556 3,120 711 7112104008000 Wood fuel combustion – Residential 20,762 2,966 392,991 1,711,364 226,897 218,4332104011000 Kerosene fuel combustion – Residential 70 19 3 19 1 12222222222 Border crossings 340 1,998 21,5802267000000 LPG fuel combustion – Transportation 44,927 27,680 278,8812267005000 LPG fuel combustion – Agricultural 91 0 2 13 3 32275020000 Aircraft 4,373 343 2,048 7,4242280000000 Commercial marine vessels 76,096 902 669 7,497 1,867 1,8222285000000 Locomotives 43,489 387 1,640 4,296 1,080 9702302002000 Charbroiling/Street vendors 286 1,001 15,516 7,794 6,2212302050000 Bakeries 12,1852311000000 Construction activities9,448 1,9642401001000 Architectural surface coatings 49,4542401005000 Autobody refinishing 23,4922401008000 Traffic markings 3,0322401990000 Industrial surface coatings 104,5182415000000 Degreasing 167,0202420000370 Dry cleaning 12,6672425000000 Graphic arts 35,8352460000000 Consumer solvent usage 346,6082461021000 Asphalt application 7,7562461800000 Pesticide application 23,5632501060000 Gasoline distribution 91,5592630010000 Wastewater treatment 41,263Table 10. Continued

Mexico Projections 

### 33 Final, January 9, 2009SCCSCC DescriptionNOxSO2VOCCOPM10PM2.5NH32801000003 Agricultural tilling109,866 24,3572801500000 Agricultural burning 14,672 148,569 13,975 13,3272801520004 Kerosene fuel combustion – Agricultural 3 1 0 1 0 02801700000 Fertilizer application 154,9682805000000 Livestock ammonia 876,8072805001000 Beef cattle feedlots8,391 9582810001000 Wildfires 5,942 35,654 207,981 24,270 21,5782810005000 Open burning – Waste 3,225 538 4,599 45,687 20,425 18,7052810030000 Structure fires 7 17 301 19 183333333333 LPG distribution 332,0994444444444 Brick kilns 618 8,059 36,502 5,471 5,2675555555555 Domestic ammonia 98,625Total 276,321 194,642 1,743,587 2,500,852 439,253 320,369 1,130,400Note: Blanks indicate the emissions were not estimated. A zero indicates emissions <0.5 Mg/yr.Mexico Projections 

### 34 Final, January 9, 2009Table 11. 2008 Baseline ProjectedArea Source Emissions (Mg/yr)SCCSCC DescriptionNOxSO2VOCCOPM10PM2.5NH32102004000 Distillate fuel combustion –Industrial 2,022 503 17 421 84 202102005000 Residual fuel combustion – Industrial 9,129 112,796 54 971 6,216 4,0482102006000 Natural gas fuel combustion – Industrial 31,241 67 614 9,372 848 8482102007000 LPG fuel combustion – Industrial 855 2 15 146 25 252102011000 Kerosene fuel combustion – Industrial 103 24 1 22 4 12103004000 Distillate fuel combustion– Commercial 229 60 4 57 13 102103005000 Residual fuel combustion – Commercial2103006000 Natural gas fuel combustion – Commercial 326 2 18 274 25 252103007000 LPG fuel combustion – Commercial 5,009 13 124 693 158 1582104006000 Natural gas fuel combustion – Residential 1,140 7 67 485 92 922104007000 LPG fuel combustion – Residential 22,942 61 566 3,174 723 7232104008000 Wood fuel combustion – Residential 21,828 3,118 413,174 1,799,257 238,550 229,6522104011000 Kerosene fuel combustion – Residential 74 20 3 21 1 12222222222 Border crossings 383 2,251 24,3042267000000 LPG fuel combustion – Transportation 88,483 54,514 549,2502267005000 LPG fuel combustion – Agricultural 93 0 2 13 3 32275020000 Aircraft 10,869 854 5,091 18,4552280000000 Commercial marine vessels 94,332 1,119 830 9,293 2,314 2,2582285000000 Locomotives 59,270 527 2,235 5,855 1,472 1,3222302002000 Charbroiling/Street vendors 3131,096 16,981 8,530 6,8082302050000 Bakeries 13,3362311000000 Construction activities10,664 2,2172401001000 Architectural surface coatings 54,1232401005000 Autobody refinishing 28,2542401008000 Traffic markings 3,1682401990000 Industrial surface coatings 142,4482415000000 Degreasing 227,6312420000370 Dry cleaning 14,3492425000000 Graphic arts 39,2182460000000 Consumer solvent usage 379,3312461021000 Asphalt application 8,1062461800000 Pesticide application 25,5312501060000 Gasoline distribution 132,4902630010000 Wastewater treatment 88,4512801000003 Agricultural tilling 119,206 26,428Table 11. Continued

Mexico Projections 

### 1-35 Draft, November 2008 Mexico Projections 

### 35 Final, January 9, 2009SCCSCC DescriptionNOxSO2VOCCOPM10PM2.5NH32801500000 Agricultural burning 14,909 150,223 14,059 13,4072801520004 Kerosene fuel combustion – Agricultural 2 1 0 1 0 02801700000 Fertilizer application 168,0172805000000 Livestock ammonia 448,2242805001000 Beef cattle feedlots 6,964 7952810001000 Wildfires 11,082 66,493 387,876 45,262 40,2422810005000 Open burning – Waste 3,542 590 5,051 50,177 22,432 20,5432810030000 Structure fires 8 20 329 21 193333333333 LPG distribution 374,3214444444444 Brick kilns 686 8,940 40,495 6,070 5,8435555555555 Domestic ammonia 107,851Total 363,963 119,763 2,106,842 3,068,145 483,735 355,488 724,092Note: Blanks indicate the emissions were not estimated. A zero indicates emissions <0.5 Mg/yr.Mexico Projections 

### 36 Final, January 9, 2009Table 12. 2012 BaselineProjected Area Source Emissions by SCC (Mg/yr)SCCSCC DescriptionNOxSO2VOCCOPM10PM2.5NH32102004000 Distillate fuel combustion –Industrial 2,980 741 25 621 124 302102005000 Residual fuel combustion – Industrial 4,282 52,902 26 456 2,915 1,8982102006000 Natural gas fuel combustion – Industrial 33,596 72 660 10,079 912 9122102007000 LPG fuel combustion – Industrial 737 1 13 125 22 222102011000 Kerosene fuel combustion – Industrial 6 1 0 1 0 02103004000 Distillate fuel combustion– Commercial 240 63 4 60 13 102103005000 Residual fuel combustion – Commercial2103006000 Natural gas fuel combustion – Commercial 341 2 19 286 26 262103007000 LPG fuel combustion – Commercial 5,240 14 129 725 165 1652104006000 Natural gas fuel combustion – Residential 3,011 19 176 1,281 243 2432104007000 LPG fuel combustion – Residential 22,967 61 566 3,178 724 7242104008000 Wood fuel combustion – Residential 18,240 2,606 345,262 1,503,517 199,340 191,9042104011000 Kerosene fuel combustion – Residential 37 10 2 10 1 02222222222 Border crossings 412 2,420 26,1392267000000 LPG fuel combustion – Transportation 113,288 69,797 703,2272267005000 LPG fuel combustion – Agricultural 100 0 3 14 3 32275020000 Aircraft 13,280 1,043 6,221 22,5492280000000 Commercial marine vessels 113,354 1,344 997 11,167 2,780 2,7142285000000 Locomotives 68,014 604 2,565 6,719 1,689 1,5182302002000 Charbroiling/Street vendors 3231,130 17,513 8,797 7,0222302050000 Bakeries 13,7542311000000 Construction activities11,093 2,3062401001000 Architectural surface coatings 55,8192401005000 Autobody refinishing 30,4972401008000 Traffic markings 3,1962401990000 Industrial surface coatings 163,4622415000000 Degreasing 261,2112420000370 Dry cleaning 15,0572425000000 Graphic arts 40,4472460000000 Consumer solvent usage 391,2182461021000 Asphalt application 8,1762461800000 Pesticide application 25,5312501060000 Gasoline distribution 160,6542630010000 Wastewater treatment 120,3412801000003 Agricultural tilling 119,206 26,428Table 12. Continued

Mexico Projections 

### 1-37 Draft, November 2008 Mexico Projections 

### 37 Final, January 9, 2009SCCSCC DescriptionNOxSO2VOCCOPM10PM2.5NH32801500000 Agricultural burning 14,909 150,223 14,059 13,4072801520004 Kerosene fuel combustion – Agricultural 3 1 0 1 0 02801700000 Fertilizer application 168,0172805000000 Livestock ammonia 448,2242805001000 Beef cattle feedlots 6,964 7952810001000 Wildfires 11,082 66,493 387,876 45,262 40,2422810005000 Open burning – Waste 3,651 609 5,206 51,720 23,122 21,1752810030000 Structure fires 8 21 339 21 203333333333 LPG distribution 387,6214444444444 Brick kilns 714 9,305 42,150 6,318 6,0825555555555 Domestic ammonia 111,176Total 415,907 60,094 2,202,932 2,939,976 443,800 317,645 727,417Note: Blanks indicate the emissions were not estimated. A zero indicates emissions <0.5 Mg/yr.Mexico Projections 

### 38 Final, January 9, 2009Table 13. 2030 Baseline Projected Area Source Emissions by SCC (Mg/yr)SCCSCC DescriptionNOxSO2VOCCOPM10PM2.5NH32102004000 Distillate fuel combustion – Industrial 5,242 1,303 44 1,092 218 522102005000 Residual fuel combustion – Industrial 1,041 12,862 6 111 709 4622102006000 Natural gas fuel combustion – Industrial 50,182 108 986 15,054 1,362 1,3622102007000 LPG fuel combustion – Industrial 824 2 15 140 25 252102011000 Kerosene fuel combustion – Industrial 9 2 0 2 0 02103004000 Distillate fuel combustion– Commercial 371 98 6 93 20 162103005000 Residual fuel combustion – Commercial2103006000 Natural gas fuel combustion – Commercial 528 3 29 443 40 402103007000 LPG fuel combustion – Commercial 8,109 22 200 1,122 256 2562104006000 Natural gas fuel combustion – Residential 6,631 42 388 2,822 536 5362104007000 LPG fuel combustion – Residential 26,017 69 642 3,600 820 8202104008000 Wood fuel combustion – Residential 14,570 2,082 275,792 1,200,998 159,231 153,2922104011000 Kerosene fuel combustion – Residential 13 4 1 4 0 02222222222 Border crossings 542 3,185 34,3932267000000 LPG fuel combustion – Transportation 349,129 215,098 2,167,1942267005000 LPG fuel combustion – Agricultural 150 0 4 21 5 52275020000 Aircraft 25,615 2,012 11,998 43,4912280000000 Commercial marine vessels 281,737 3,341 2,478 27,755 6,910 6,7452285000000 Locomotives 68,014 604 2,565 6,719 1,689 1,5182302002000 Charbroiling/Street vendors 3551,242 19,251 9,670 7,7182302050000 Bakeries 15,1182311000000 Construction activities12,433 2,5842401001000 Architectural surface coatings 61,3572401005000 Autobody refinishing 39,2982401008000 Traffic markings 3,2862401990000 Industrial surface coatings 303,6292415000000 Degreasing 485,1972420000370 Dry cleaning 17,6692425000000 Graphic arts 44,4602460000000 Consumer solvent usage 430,0362461021000 Asphalt application 8,4062461800000 Pesticide application 25,5312501060000 Gasoline distribution 404,9752630010000 Wastewater treatment 120,3412801000003 Agricultural tilling119,206 26,428Table 13. Continued

Mexico Projections 

### 39 Final, January 9, 2009SCCSCC DescriptionNOxSO2VOCCOPM10PM2.5NH32801500000 Agricultural burning 14,909 150,223 14,059 13,4072801520004 Kerosene fuel combustion – Agricultural 4 1 0 1 0 02801700000 Fertilizer application 168,0172805000000 Livestock ammonia 448,2242805001000 Beef cattle feedlots 6,964 7952810001000 Wildfires 11,082 66,493 387,876 45,262 40,2422810005000 Open burning – Waste 4,015 669 5,725 56,877 25,428 23,2862810030000 Structure fires 9 23 373 24 223333333333 LPG distribution 598,4844444444444 Brick kilns 811 10,571 47,882 7,177 6,9095555555555 Domestic ammonia 122,089Total 854,999 23,223 3,170,187 4,167,536 412,043 286,518 738,330Note: Blanks indicate the emissions were not estimated. A zero indicates emissions <0.5 Mg/yr.Mexico Projections Final, January 9, 2009 

### 41 Table 14. Mexican Fuel Su lfur Standards by Fuel Type and Region (in ppm) Fuel Type 1999 2008 2012 2030 Premium 500 30/80 (avg/max) 30/80 (avg/max) 30/80 (avg/max) Magna (ZM) 500 421/500 (avg/max) 30/80 (avg/max) 30/80 (avg/max) Magna (RP) 500 421/500 30/80 (avg/max) 30/80 (avg/max) Diesel (ZM) 500 300 300 15 Diesel (ZF) 500 15 15 15 Diesel (RP) 420/500 (avg/max) 420/500 (avg/max) 420/500 (avg/max) 15



### Table 15. Equivalency of Mexican St andards to EURO and U.S. Standards
Mexican Standard Equivalent Standard A U.S. EPA’s Tier 1 B Combination of U.S. EPA’s Tier 1 and Tier 2 for 80,000 km certification or EURO 3 for 100,000 km certification C Combination of U.S. EPA’s Tier 1 and Tier 2 for 80,000 km certification or EURO 4 for 100,000 km certification



### Table 16. Mexican Motor Vehicl e Emission Standards (g/km) CO (g/km) NMHC (g/km) NO x (g/km) PM (g/km)

Standard Vehicle Class Gas, LPG,

NG Diesel Gas, LPG,

NG Diesel Gas, LPG,

NG Diesel Gas, LPG,

NG Diesel PV LDT1 2.11 0.156 0.25 0.62 - 0.050
LDT2 LDT3 2.74 0.200 0.44 0.62 - 0.062 A

LDT4 3.11 0.240 0.68 0.95 - 0.075 PV LDT1 - 0.050
LDT2 2.11 0.099

LDT3 - 0.062 B

LDT4 2.74 0.121 0.249

- 0.075 PV LDT1 - 0.050
LDT2 0.047 0.068

LDT3 - 0.062 C

LDT4 2.11
0.087 0.124 - 0.075

CO = carbon monoxide NMHC = non-methane hydrocarbons NO x = nitrogen oxides PM = particulate matterMexico Projections Final, January 9, 2009 

### 42 Table 17. Phase-In Schedule for Mexican Motor Vehicle Emission Standards(% of Model Year Vehicles)

Model Year Standard A % Standard B % Standard C % 2004 100% - - 2005 100% - - 2006 100% - - 2007 75% 25% - 2008 50% 50% - 2009 30% 70% - 2010 - 100% - 2011 - 100% - 2012 - 75% 25% 2013 - 50% 50% 2014 - 30% 70% 2015 - - 100% 2030 - - 100% 

### Table 18. Composite Proj ection Factors for On-Road Motor Vehicles by Region Region Year NO x SO 2 VOC CO PM 10 PM 2.5 NH 3 ZM 2008 0.9397 1.1012 0.6761 0.5905 1.6599 1.6790 1.6009 ZF 2008 0.9299 0.8057 0.7238 0.6383 1.6450 1.6624 1.6009 RP 2008 0.9299 1.3087 0.7238 0.6383 1.6700 1.6906 1.6009 ZM 2012 0.8599 0.4480 0.5836 0.4378 1.7768 1.7825 1.9523 ZF 2012 0.8492 0.0886 0.6117 0.4508 1.7593 1.7624 1.9523 RP 2012 0.8492 0.6996 0.6117 0.4508 1.7896 1.7965 1.9523 ZM 2030 0.3019 0.2258 0.5628 0.5486 3.7605 3.7276 4.9158 RP 2030 0.3011 0.2258 0.5579 0.6167 3.7605 3.7276 4.9158



### Table 19. 1999, 2008, 2012, and 2030 Baselin e On-Road Motor Vehicle Emissions (Mg/yr)

Year NO x SO 2 VOC CO PM 10 PM 2.5 NH 3 1999 435,665 24,453 573,042 4,671,842 20,567 18,845 7,609 2008 370,177 27,765 399,936 2,872,420 31,890 29,551 11,931 2012 336,519 12,490 340,519 2,065,988 34,019 31,258 14,533 2030 117,883 5,366 317,164 2,731,909 71,402 64,816 36,529Mexico Projections Final, January 9, 2009 

### 43

Table 20. Baseline On-Road Motor Vehicl e Emissions by Vehicle Classification (Mg/yr)
Vehicle Classification NO x SO 2 VOC CO PM 10 PM 2.5 NH 3 1999 LDGV 90,438 9,885 321,776 2,48 5,068 5,655 5,159 3,670 LDGT 58,710 8,738 180,409 1,611,579 4,985 4,551 2,536 HDGV 12,221 1,451 26,992 305,053 219 186 208 MC 1,013 121 3,921 30,372 12 8 100 LDDV 672 31 769 1,466 134 123 30 LDDT 341 20 407 801 66 60 14 HDDV 272,270 4,206 38,768 237,504 9,497 8,756 1,052 Total 435,665 24,453 573,042 4,671,842 20,567 18,845 7,609 2008 LDGV 84,432 11,511 226,961 1,540,345 9,403 8,680 5,875 LDGT 54,811 10,176 127,202 999,217 8,290 7,658 4,060 HDGV 11,404 1,690 18,994 187,792 365 313 334 MC 945 141 2,762 18,743 19 14 160 LDDV 538 31 464 776 190 177 41 LDDT 273 20 245 424 93 87 19 HDDV 217,774 4,196 23,307 125,123 13,529 12,622 1,442 Total 370,177 27,765 399,936 2,872,420 31,890 29,551 11,931 2012 LDGV 77,166 5,186 193,315 1,107,835 10,070 9,218 7,165 LDGT 50,094 4,584 108,357 718,517 8,878 8,132 4,952 HDGV 10,422 761 16,190 135,641 391 332 407 MC 863 64 2,354 13,517 21 15 195 LDDV 487 14 392 554 202 187 49 LDDT 247 9 207 303 99 92 23 HDDV 197,240 1,873 19,704 89,620 14,358 13,283 1,743 Total 336,519 12,490 340,519 2,065,988 34,019 31,258 14,533 2030 LDGV 27,257 2,232 180,128 1,466,991 21,265 19,230 18,041 LDGT 17,694 1,973 100,997 951,772 18,748 16,965 12,468 HDGV 3,683 328 15,115 178,241 825 693 1,025 MC 305 27 2,196 17,811 44 32 490 LDDV 170 6 361 721 421 384 122 LDDT 86 4 191 394 207 189 56 HDDV 68,689 795 18,178 115,978 29,894 27,322 4,327 Total 117,883 5,366 317,164 2,731,909 71,402 64,816 36,529Mexico Projections Final, January 9, 2009 

### 44

Table 21. Baseline On-Road Motor Vehicl e Emissions by Vehicle Classification (% of Total)
Vehicle Classification NO x SO 2 VOC CO PM 10 PM 2.5 NH 3 1999 LDGV 20.8% 40.4% 56.2% 53.2% 27.5% 27.4% 48.2% LDGT 13.5% 35.7% 31.5% 34.5% 24.2% 24.1% 33.3% HDGV 2.8% 5.9% 4.7% 6.5% 1.1% 1.0% 2.7% MC 0.2% 0.5% 0.7% 0.7% 0.1% 0.0% 1.3% LDDV 0.2% 0.1% 0.1% 0.0% 0.7% 0.7% 0.4% LDDT 0.1% 0.1% 0.1% 0.0% 0.3% 0.3% 0.2% HDDV 62.5% 17.2% 6.8% 5.1% 46.2% 46.5% 13.8% Total 2008 LDGV 22.8% 41.5% 56.7% 53.6% 29.5% 29.4% 49.2% LDGT 14.8% 36.7% 31.8% 34.8% 26.0% 25.9% 34.0% HDGV 3.1% 6.1% 4.7% 6.5% 1.1% 1.1% 2.8% MC 0.3% 0.5% 0.7% 0.7% 0.1% 0.0% 1.3% LDDV 0.1% 0.1% 0.1% 0.0% 0.6% 0.6% 0.3% LDDT 0.1% 0.1% 0.1% 0.0% 0.3% 0.3% 0.2% HDDV 58.8% 15.1% 5.8% 4.4% 42.4% 42.7% 12.1% Total 2012 LDGV 22.9% 41.5% 56.8% 53.6% 29.6% 29.5% 49.3% LDGT 14.9% 36.7% 31.8% 34.8% 26.1% 26.0% 34.1% HDGV 3.1% 6.1% 4.8% 6.6% 1.1% 1.1% 2.8% MC 0.3% 0.5% 0.7% 0.7% 0.1% 0.0% 1.3% LDDV 0.1% 0.1% 0.1% 0.0% 0.6% 0.6% 0.3% LDDT 0.1% 0.1% 0.1% 0.0% 0.3% 0.3% 0.2% HDDV 58.6% 15.0% 5.8% 4.3% 42.2% 42.5% 12.0% Total 2030 LDGV 23.1% 41.6% 56.8% 53.7% 29.8% 29.7% 49.4% LDGT 15.0% 36.8% 31.8% 34.8% 26.3% 26.2% 34.1% HDGV 3.1% 6.1% 4.8% 6.5% 1.2% 1.1% 2.8% MC 0.3% 0.5% 0.7% 0.7% 0.1% 0.0% 1.3% LDDV 0.1% 0.1% 0.1% 0.0% 0.6% 0.6% 0.3% LDDT 0.1% 0.1% 0.1% 0.0% 0.3% 0.3% 0.2% HDDV 58.3% 14.8% 5.7% 4.2% 41.9% 42.2% 11.8% Total


### Table 22. 1999, 2008, 2012, and 2030 Baselin e Nonroad Mobile Source Emissions (Mg/year)

Year NO x SO 2 VOC CO PM 10 PM 2.5 1999 263,768 3,486 35,169 153,604 37,240 36,123 2008 281,006 3,709 38,290 165,890 40,447 39,234 2012 296,402 3,911 40,463 175,197 42,734 41,452 2030 437,465 5,777 59,058 256,756 62,449 60,576Mexico Projections Final, January 9, 2009 

### 45 Table 23. Baseline Mexico Emi ssions by Source Type (Mg/yr)
NO x SO 2 VOC CO PM 10 PM 2.5 NH 3 1999 Point 448,826 2,633,799 247,878 167,648 297,264 198,917 Area 276,321 194,642 1,743,587 2,500,852 439,253 320,369 1,130,400 On-Road 435,665 24,453 573,042 4,671,842 20,567 18,845 7,609 Nonroad 263,768 3,486 35,169 153,604 37,240 36,123 Total 1,424,580 2,856,380 2,599,676 7,493,946 794,324 574,254 1,138,009 2008 Point 606,053 2,575,537 328,096 237,926 359,919 239,274 Area 363,963 119,763 2,106,842 3,068,145 483,735 355,488 724,092 On-Road 370,177 27,765 399,936 2,872,420 31,890 29,551 11,931 Nonroad 281,006 3,709 38,290 165,890 40,447 39,234 Total 1,621,199 2,726,774 2,873,164 6,344,381 915,991 663,547 736,023 2012 Point 686,509 2,615,816 348,004 262,449 388,825 256,861 Area 415,907 60,094 2,202,932 2,939,976 443,800 317,645 727,417 On-Road 336,519 12,490 340,519 2,065,988 34,019 31,258 14,533 Nonroad 296,402 3,911 40,463 175,197 42,734 41,452 Total 1,735,337 2,692,311 2,931,918 5,443,610 909,378 647,216 741,950 2030 Point 1,239,873 3,359,643 455,901 436,116 638,533 420,929 Area 854,999 23,223 3,170,187 4,167,536 412,043 286,518 738,330 On-Road 117,883 5,366 317,164 2,731,909 71,402 64,816 36,529 Nonroad 437,465 5,777 59,058 256,756 62,449 60,576 Total 2,650,220 3,394,009 4,002,310 7,592,317 1,184,427 832,839 774,859Mexico Projections Final, January 9, 2009 

### 46 Table 24. Baseline Mexico Emissi ons by Source Type (% of Total)
NO x SO 2 VOC CO PM 10 PM 2.5 NH 3 1999 Point 31.5% 92.2% 9.5% 2.2% 37.4% 34.6% 0.0% Area 19.4% 6.8% 67.1% 33.4% 55.3% 55.8% 99.3% On-Road 30.6% 0.9% 22.0% 62.3% 2.6% 3.3% 0.7% Nonroad 18.5% 0.1% 1.4% 2.0% 4.7% 6.3% 0.0% Total 2008 Point 37.4% 94.5% 11.4% 3.8% 39.3% 36.1% 0.0% Area 22.5% 4.4% 73.3% 48.4% 52.8% 53.6% 98.4% On-Road 22.8% 1.0% 13.9% 45.3% 3.5% 4.5% 1.6% Nonroad 17.3% 0.1% 1.3% 2.6% 4.4% 5.9% 0.0% Total 2012 Point 39.6% 97.2% 11.9% 4.8% 42.8% 39.7% 0.0% Area 24.0% 2.2% 75.1% 54.0% 48.8% 49.1% 98.0% On-Road 19.4% 0.5% 11.6% 38.0% 3.7% 4.8% 2.0% Nonroad 17.1% 0.1% 1.4% 3.2% 4.7% 6.4% 0.0% Total 2030 Point 46.8% 99.0% 11.4% 5.7% 53.9% 50.5% 0.0% Area 32.3% 0.7% 79.2% 54.9% 34.8% 34.4% 95.3% On-Road 4.4% 0.2% 7.9% 36.0% 6.0% 7.8% 4.7% Nonroad 16.5% 0.2% 1.5% 3.4% 5.3% 7.3% 0.0% TotalMexico Projections Final, January 9, 2009 

### 47

Table 25. Control Scenario 1 Emissi on Reductions (Increased Fuel Economy for Light-Duty Gasoline Vehicles and Trucks) (%)

Year NO x SO 2 VOC CO PM 10 PM 2.5 NH 3 2008 0.000 NE 0.000 0.000 0.000 0.000 NE 2012 0.439 NE 0.204 0.140 1.028 0.986 NE 2030 3.837 NE 1.785 1.222 8.973 8.610 NE
NE = Not estimatedMexico Projections Final, January 9, 2009 

### 48 Table 26. Control Scenario 2 Municipalities Metropolitan Area Municipality Code State Municipality Guadalajara 14039 Jalísco Guadalajara Guadalajara 14044 Jalísco Ixtlahuacán de los Membrillos Guadalajara 14051 Jalísco Juanacatlán Guadalajara 14070 Jalísco El Salto Guadalajara 14097 Jalísco Tlajomulco de Zúñiga Guadalajara 14098 Jalísco Tlaquepaque Guadalajara 14101 Jalísco Tonalá Guadalajara 14120 Jalísco Zapopan Monterrey 19006 Nuevo León Apodaca Monterrey 19009 Nuevo León Cadereyta Jiménez Monterrey 19018 Nuevo León García Monterrey 19019 Nuevo León San Pedro Garza García Monterrey 19021 Nuevo León General Escobedo Monterrey 19026 Nuevo León Guadalupe Monterrey 19031 Nuevo León Juárez Monterrey 19039 Nuevo León Monterrey Monterrey 19045 Nuevo León Salinas Victoria Monterrey 19046 Nuevo León San Nicolás de los Garza Monterrey 19048 Nuevo León Santa Catarina Monterrey 19049 Nuevo León Santiago Mexico City 09002 Distr ito Federal Azcapotzalco Mexico City 09003 Distrito Federal Coyoacán Mexico City 09004 Distrito Federal Cuajimalpa de Morelos Mexico City 09005 Distrito Federal Gustavo A. Madero Mexico City 09006 Dist rito Federal Iztacalco Mexico City 09007 Distrito Federal Iztapalapa Mexico City 09008 Distrito Federal La Magdalena Contreras Mexico City 09009 Distrito Federal Milpa Alta Mexico City 09010 Distrito Federal Alvaro Obregón Mexico City 09011 Distrito Federal Tláhuac Mexico City 09012 Distrito Federal Tlalpan Mexico City 09013 Distrito Federal Xochimilco Mexico City 09014 Distrito Federal Benito Juárez Mexico City 09015 Distrito Federal Cuauhtémoc Mexico City 09016 Distrito Federal Miguel Hidalgo Mexico City 09017 Distrito Federal Venustiano Carranza Mexico City 13069 Hidalgo Tizayuca Mexico City 15002 México Acolman Mexico City 15009 México Amecameca Mexico City 15010 México Apaxco Mexico City 15011 México Atenco Mexico City 15013 México Atizapán de Zaragoza Mexico City 15015 México Atlautla Mexico City 15016 México Axapusco Mexico City 15017 México Ayapango Mexico City 15020 México Coacalco de Berriozábal Mexico City 15022 México Cocotitlán Mexico City 15023 México Coyotepec Mexico City 15024 México Cuautitlán Mexico City 15025 México Chalco Mexico City 15028 México Chiautla

### Table 26. (Continued)

Mexico Projections Final, January 9, 2009 

### 49 Metropolitan Area Municipality Code State Municipality Mexico City 15029 México Chicoloapan Mexico City 15030 México Chiconcuac Mexico City 15031 México Chimalhuacán Mexico City 15033 México Ecatepec de Morelos Mexico City 15034 México Ecatzingo Mexico City 15035 México Huehuetoca Mexico City 15036 México Hueypoxtla Mexico City 15037 México Huixquilucan Mexico City 15038 México Isidro Fabela Mexico City 15039 México Ixtapaluca Mexico City 15044 México Jaltenco Mexico City 15046 México Jilotzingo Mexico City 15050 México Juchitepec Mexico City 15053 México Melchor Ocampo Mexico City 15057 México Naucalpan de Juárez Mexico City 15058 México Nezahualcóyotl Mexico City 15059 México Nextlalpan Mexico City 15060 México Nicolás Romero Mexico City 15061 México Nopaltepec Mexico City 15065 México Otumba Mexico City 15068 México Ozumba Mexico City 15069 México Papalotla Mexico City 15070 México La Paz Mexico City 15075 México San Martín de las Pirámides Mexico City 15081 México Tecámac Mexico City 15083 México Temamatla Mexico City 15084 México Temascalapa Mexico City 15089 México Tenango del Aire Mexico City 15091 México Teoloyucán Mexico City 15092 México Teotihuacán Mexico City 15093 México Tepetlaoxtoc Mexico City 15094 México Tepetlixpa Mexico City 15095 México Tepotzotlán Mexico City 15096 México Tequixquiac Mexico City 15099 México Texcoco Mexico City 15100 México Tezoyuca Mexico City 15103 México Tlalmanalco Mexico City 15104 México Tlalnepantla de Báez Mexico City 15108 México Tultepec Mexico City 15109 México Tultitlán Mexico City 15112 México Villa del Carbón Mexico City 15120 México Zumpango Mexico City 15121 México Cuautitlán Izcalli Mexico City 15122 México Valle de Chalco SolidaridadMexico Projections Final, January 9, 2009 

### 50 Table 27. Control Scenario 2 Emission Reductions (Switching to Ethanol) (%)

Year Guadalajara Monterrey Mexico City 2008 0.000 0.000 0.000 2012 2.397 4.573 2.782 2030 2.182 3.934 2.709



### Table 28. 1999, 2008, 2012, and 2030 On-R oad Motor Vehicle Emissions with Control Scenarios 1, 2, and 3 (Mg/yr)

Year NO x SO 2 VOC CO PM 10 PM 2.5 NH 3 1999 435,665 24,453 573,042 4,671,842 20,567 18,845 7,609 2008 370,177 27,765 399,936 2,872,420 31,890 29,551 11,931 2012 336,519 12,490 340,519 2,065,988 34,019 31,258 14,533 2030 117,883 5,366 317,164 2,731,909 71,402 64,816 36,529 2012 – CS1 335,960 12,490 339,902 2,063,431 33,824 31,087 14,533 2030 – CS1 116,159 5,366 312,147 2,702,347 67,812 61,699 36,529 2012 – CS2 334,644 12,362 336,077 2,038,494 33,766 31,027 14,372 2030 – CS2 117,269 5,310 313,197 2,699,202 70,904 64,365 36,150 2012 – CS3 334,092 12,362 335,469 2,035,972 33,574 30,859 14,372 2030 – CS3 115,566 5,310 308,247 2,670,003 67,357 61,287 36,150 CS1 = Control Scenario 1, CS2 = Control Scenario 2, CS3 = Control Scenario 3Mexico Projections Final, January 9, 2009 

### 51 Table 29. On-Road Motor Vehicle Emis sions by Vehicle Classification with Control Scenarios 1, 2, and 3 (Mg/yr)
Vehicle Classification NO x SO 2 VOC CO PM 10 PM 2.5 NH 3 1999 LDGV 90,438 9,885 321,776 2,48 5,068 5,655 5,159 3,670 LDGT 58,710 8,738 180,409 1,611,579 4,985 4,551 2,536 HDGV 12,221 1,451 26,992 305,053 219 186 208 MC 1,013 121 3,921 30,372 12 8 100 LDDV 672 31 769 1,466 134 123 30 LDDT 341 20 407 801 66 60 14 HDDV 272,270 4,206 38,768 237,504 9,497 8,756 1,052 Total 435,665 24,453 573,042 4,671,842 20,567 18,845 7,609 2008 LDGV 84,432 11,511 226,961 1,540,345 9,403 8,680 5,875 LDGT 54,811 10,176 127,202 999,217 8,290 7,658 4,060 HDGV 11,404 1,690 18,994 187,792 365 313 334 MC 945 141 2,762 18,743 19 14 160 LDDV 538 31 464 776 190 177 41 LDDT 273 20 245 424 93 87 19 HDDV 217,774 4,196 23,307 125,123 13,529 12,622 1,442 Total 370,177 27,765 399,936 2,872,420 31,890 29,551 11,931 2012 LDGV 77,166 5,186 193,315 1,107,835 10,070 9,218 7,165 LDGT 50,094 4,584 108,357 718,517 8,878 8,132 4,952 HDGV 10,422 761 16,190 135,641 391 332 407 MC 863 64 2,354 13,517 21 15 195 LDDV 487 14 392 554 202 187 49 LDDT 247 9 207 303 99 92 23 HDDV 197,240 1,873 19,704 89,620 14,358 13,283 1,743 Total 336,519 12,490 340,519 2,065,988 34,019 31,258 14,533 2030 LDGV 27,257 2,232 180,128 1,466,991 21,265 19,230 18,041 LDGT 17,694 1,973 100,997 951,772 18,748 16,965 12,468 HDGV 3,683 328 15,115 178,241 825 693 1,025 MC 305 27 2,196 17,811 44 32 490 LDDV 170 6 361 721 421 384 122 LDDT 86 4 191 394 207 189 56 HDDV 68,689 795 18,178 115,978 29,894 27,322 4,327 Total 117,883 5,366 317,164 2,731,909 71,402 64,816 36,529 2012 – CM1 LDGV 76,826 5,186 192,920 1,106,284 9,967 9,127 7,165 LDGT 49,874 4,584 108,136 717,511 8,787 8,052 4,952 HDGV 10,422 761 16,190 135,641 391 332 407 MC 863 64 2,354 13,517 21 15 195 LDDV 487 14 392 554 202 187 49 LDDT 247 9 207 303 99 92 23 HDDV 197,240 1,873 19,704 89,620 14,358 13,283 1,743

### Table 29. (Continued)

Mexico Projections Final, January 9, 2009 

### 52 Total 335,960 12,490 339,902 2,063,431 33,824 31,087 14,533 2030 – CM1 LDGV 26,211 2,232 176,914 1,449,061 19,357 17,575 18,041 LDGT 17,015 1,973 99,194 940,140 17,066 15,505 12,468 HDGV 3,683 328 15,115 178,241 825 693 1,025 MC 305 27 2,196 17,811 44 32 490 LDDV 170 6 361 721 421 384 122 LDDT 86 4 191 394 207 189 56 HDDV 68,689 795 18,178 115,978 29,894 27,322 4,327 Total 116,159 5,366 312,147 2,702,347 67,812 61,699 36,529 2012 – CM2 LDGV 76,112 5,123 190,656 1,092,590 9,939 9,097 7,074 LDGT 49,410 4,528 106,849 708,741 8,762 8,026 4,889 HDGV 10,295 752 15,948 133,381 386 328 402 MC 853 63 2,320 13,305 20 15 192 LDDV 487 14 392 554 202 187 49 LDDT 247 9 207 303 99 92 23 HDDV 197,240 1,873 19,704 89,620 14,358 13,283 1,743 Total 334,644 12,362 336,077 2,038,494 33,766 31,027 14,372 2030 – CM2 LDGV 26,911 2,205 177,755 1,448,872 21,005 18,996 17,828 LDGT 17,470 1,949 99,649 940,152 18,519 16,758 12,320 HDGV 3,641 324 14,898 175,527 815 685 1,013 MC 302 27 2,165 17,558 43 31 484 LDDV 170 6 361 721 421 384 122 LDDT 86 4 191 394 207 189 56 HDDV 68,689 795 18,178 115,978 29,894 27,322 4,327 Total 117,269 5,310 313,197 2,699,202 70,904 64,365 36,150 2012 – CM3 LDGV 75,777 5,123 190,267 1,091,060 9,837 9,008 7,074 LDGT 49,193 4,528 106,631 707,749 8,672 7,947 4,889 HDGV 10,295 752 15,948 133,381 386 328 402 MC 853 63 2,320 13,305 20 15 192 LDDV 487 14 392 554 202 187 49 LDDT 247 9 207 303 99 92 23 HDDV 197,240 1,873 19,704 89,620 14,358 13,283 1,743 Total 334,092 12,362 335,469 2,035,972 33,574 30,859 14,372 2030 – CM3 LDGV 25,879 2,205 174,583 1,431,164 19,120 17,360 17,828 LDGT 16,800 1,949 97,871 928,661 16,857 15,315 12,320 HDGV 3,641 324 14,898 175,527 815 685 1,013 MC 302 27 2,165 17,558 43 31 484 LDDV 170 6 361 721 421 384 122 LDDT 86 4 191 394 207 189 56 HDDV 68,689 795 18,178 115,978 29,894 27,322 4,327 Total 115,566 5,310 308,247 2,670,003 67,357 61,287 36,150Mexico Projections Final, January 9, 2009 

### 53 Figure 1. MOBILE6-Mexico Default Implementation Schedule Input File (Mex_P94_Imp.dat)Mexico Projections Final, January 9, 2009 

### 54 Figure 2. MOBILE6-Mexico Default Certification Standards Input File (Mex_T2CERT.dat)Mexico Projections Final, January 9, 2009 

### 55 Figure 3. MOBILE6-Mexico Modified Exhaust Emissi on Standards Input File (Mex_T2EXH.dat)