Air Quality Monitoring Program at the Port of Los Angeles Year Twelve Data Summary May April 2017

Transcription

1 Air Quality Monitoring Program at the Port of Los Angeles Year Twelve Data Summary May April 2017 Prepared For: Port of Los Angeles Environmental Management Division 425 South Palos Verdes Street San Pedro, California September 2017

2 This page is intentionally left blank.

3 Air Quality Monitoring Program at the Port of Los Angeles Year Twelve Data Summary May April 2017 Prepared for: Port of Los Angeles Environmental Management Division 425 South Palos Verdes Street San Pedro, California Prepared by: Leidos, Inc Campus Point Court, MS-E3 San Diego, California September 2017

4 This page is intentionally left blank.

5 TABLE OF CONTENTS 1 EXECUTIVE SUMMARY INTRODUCTION Siting of the Monitoring s DESCRIPTION OF AIR MONITORING PROGRAM Locations of the Monitoring Network s The Monitoring Network DATA ANALYSIS Regulatory Background Air Quality Data Summary Year PM Data Summary EC Data BC Data PM 2.5 Data PM 10 Data Gaseous Criteria Pollutant Data Summary CO Data Summary NO 2 Data Summary O 3 Data Summary SO 2 Data Summary Summary of Monitoring for Ultrafine Particles Meteorological Data Data Quality Assurance TREND ANALYSIS Trends in EC, BC, PM 2.5, and PM 10 Data Trends in EC Concentrations Trends in BC Concentrations Trends in PM 2.5 Concentrations Trends in PM 10 Concentrations Trends in Gaseous Criteria Pollutants Trends in CO Concentrations Trends in NO 2 Concentrations Trends in O 3 Concentrations Trends in SO 2 Concentrations CONCLUSIONS th Year Annual Air Quality Monitoring Report i September 2017

6 No. FIGURES Page Figure ES-1. Annual Average Elemental Carbon Concentrations at Port of Los Angeles... 4 Figure ES-2. Annual Average PM2.5 Concentrations at the Port of Los Angeles... 5 Figure ES-3. Annual Average PM10 Concentrations at Port of Los Angeles... 5 Figure 2-1. Locations of the Port's Monitoring s... 7 Figure 4-1. Daily Average Ultrafine Particle Counts during March - April Figure 4-2. Wind Roses for Port Air Monitoring s: May 2016 to April Figure 5-1. Annual Average EC Concentrations over the Period of Record Figure 5-2. Annual Average BC Concentrations over the Period of Record Figure 5-3. Annual Average PM2.5 Concentrations over the Period of Record Figure th Percentile of 24-hour Averaged PM2.5 Concentrations over the Period of Record 36 Figure 5-5. Annual Average PM10 Concentrations over the Period of Record Figure 5-6. Maximum 24-hour Average PM10 Concentrations over the Period of Record Figure 5-7. Maximum 1-hour CO Concentrations over the Period of Record Figure 5-8. Maximum 8-hour CO Concentrations over the Period of Record Figure th Percentile of the Daily Maximum 1-hour NO2 Concentration over the Period of Record Figure Maximum 1-hour NO2 Concentrations over the Period of Record Figure Annual NO2 Concentrations over the Period of Record Figure Fourth Highest Average 8-hour O3 Concentrations over the Period of Record Figure Maximum 8-hour O3 Concentrations over the Period of Record Figure Maximum 1-hour O3 Concentrations over the Period of Record Figure th Percentile of 1-hour Daily Maximum SO2 Concentrations over Period of Record. 47 Figure Maximum 1-hour SO2 Concentrations over the Period of Record Figure Maximum 24-hour SO2 Concentration over the Period of Record th Year Annual Air Quality Monitoring Report ii September 2017

7 No. LIST OF TABLES Page Table ES- 1. Exceedances of NAAQS and CAAQS during Reporting Year 12 at the Port s Air Monitoring s... 3 Table 3-1. Air Quality and Meteorological Instrumentation Currently in Operation at the Port of Los Angeles Monitoring s Table 4-1. California and National Ambient Air Quality Standards Table 4-2. Annual Average EC Concentrations at POLA Monitoring s ( ) Table 4-3. Annual Average BC Concentrations at the POLA and POLB s Table 4-4. NAAQS Comparison Three-Year Average of 98 th Percentile of 24-hour and Annual Average PM2.5 Concentrations Table 4-5. CAAQS Comparison Annual Average PM2.5 Concentrations Table 4-6. NAAQS Comparison Highest 24-hour Average PM10 Concentrations Table 4-7. CAAQS Comparison Highest 24-hour and Annual Average PM10 Concentrations Table 4-8. NAAQS Comparison Maximum 1-hour and 8-hour CO Concentrations Table 4-9. CAAQS Comparison Maximum 1-hour and 8-hour CO Concentrations Table NAAQS Comparison Three Year Average of the 98 th Percentile 1-hour Average and Annual Average NO2 Concentrations Table CAAQS Compliance Maximum 1-hour and Annual NO2 Concentrations Table NAAQS Comparison 3-Year Average of Fourth Highest 8-hour Average O3 Concentrations Table CAAQS Comparison Maximum 1-hour and 8-hour Average O3 Concentrations Table NAAQS Comparison 3 year Average of the 99 th Percentile 1-hour Daily Maximum and 2 nd Highest 3-hour Average SO2 Concentrations Table CAAQS Comparison Highest 1-hour and 24-hour Average SO2 Concentrations Table Annual Average Ultrafine Particle Counts th Year Annual Air Quality Monitoring Report iii September 2017

8 ACRONYMS AQ Air Quality BAM Beta Attenuation Monitors BC Black Carbon CAAP Clean Air Action Plan CAAQS California Ambient Air Quality Standards CARB California Air Resources Board CO Carbon Monoxide CPC Condensation Particle Counter DPM Diesel Particulate Matter DRI Desert Research Institute EC Elemental Carbon EPA Environmental Protection Agency FEM Federal Equivalent Method FRM Federal Reference Method MATES Multiple Air Toxics Exposure Study m/s Meters per Second µg/m 3 Micrograms per Meter Cubed µm Micrometer NAAQS National Ambient Air Quality Standards NO Nitrogen Oxide NOX Nitrogen Oxides NO2 Nitrogen Dioxide NWS National Weather Service OC Organic Carbon O3 Ozone PAH Polycyclic Aromatic Hydrocarbons PCAC Port Advisory Committee PM Particulate Matter PM10 Particulate Matter of Aerodynamic Diameter Less than 10 Microns PM2.5 Particulate Matter of Aerodynamic Diameter Less than 2.5 Microns POLA Port of Los Angeles Port Port of Los Angeles ppb Parts per Billion ppm Parts per Million ROI Region of Influence SCAB South Coast Air Basin SCAQMD South Coast Air Quality Management District SFS Sequential Filter Sampler SOx Sulfur Oxides SO2 Sulfur Dioxide SPPS Saints Peter and Paul Elementary School TITP Terminal Island Treatment Plant UFP Ultrafine Particles USEPA U.S. Environmental Protection Agency VOC Volatile Organic Compound 12 th Year Annual Air Quality Monitoring Report iv September 2017

9 1 EXECUTIVE SUMMARY The Port of Los Angeles (Port or POLA) began an air monitoring program in February The program includes a network of four monitoring stations in the vicinity of the Port, including a Coastal Boundary station located in the southern end of the Port between the Cabrillo Marina and the San Pedro Breakwater; a Source-Dominated station located near the center of Port operations; and the San Pedro and Wilmington stations located within those communities. This report provides a summary of the data collected by the Port of Los Angeles Air Quality Monitoring Program during the most recent reporting year, Year 12: May 1, 2016 through April 30, The main objective of the air monitoring program is to estimate ambient levels of diesel particulate matter (DPM) in proximity to the Port. DPM has become a focal point since the California Air Resources Board (CARB) has identified it as an air toxic. DPM levels have often been a significant contributor in health risk assessments conducted in the area. DPM is a complex mixture of pollutants from diesel exhaust, consisting of both gaseous and particle phases. Because of the complex nature of DPM emissions, it cannot be measured directly in the ambient atmosphere; however, elemental carbon (EC) is a surrogate for DPM in air quality monitoring. EC is measured in the Port s air monitoring network and analyzed in this report as a DPM surrogate to show ambient levels and trends in the area. Historical Port emission inventories provide an annual estimate of DPM emissions from Port activities, and these estimates are compared to annual trends in EC measurements. Recent research suggests that Black Carbon (BC) and EC can both be used as surrogates for DPM. The two measurement methods are typically highly correlated, but BC is measured using an optical method, whereas EC is measured using a completely different thermal-optical method. Consequently, the absolute values of BC and EC measurements may differ at a monitoring station. The advantage of BC is that it is measured using an Aethalometer, a real-time instrument that produces a more comprehensive, continuous data set. The Port installed an Aethalometer for measuring BC at the Source-Dominated station in June A secondary objective of the Port s air monitoring program is to estimate ambient gaseous pollutants and particulate matter (PM) levels within adjacent communities. Two different filter-based PM measurements are conducted in this monitoring network, collecting particles less than 10 and 2.5 micrometer (µm) size thresholds (PM10 and PM2.5, respectively). These two particle sizes correspond to National Ambient Air Quality Standards (NAAQS) that have been set for PM. DPM generally consists of very small particles (particle phase) with organic compounds (gaseous phase) adsorbed onto the particle phase. Generally, DPM makes up a small fraction of the particles collected by the PM10 and PM2.5 measurements, so EC measurements are considered a better surrogate for DPM. Expansion of the program in 2008 allows for real-time continuous measurement of additional pollutants. Under this expansion, the following four gaseous criteria air pollutants are measured on a continuous basis in this program: carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3). Additionally, PM2.5, and PM10 are collected using beta attenuation monitors (BAMs), and ultrafine particles (less than 0.1 µm or 100 nanometers) are collected using condensation particle counters (CPCs). In addition to air quality data, meteorological parameters are continuously measured at all four stations. Meteorological measurements are helpful for interpretation of air quality data and for use in special studies such as air quality modeling applications. Preliminary real-time data from the air monitoring stations are available for public view at the San Pedro Bay Ports Clean Air Action Plan (CAAP) website: Historical filter-based particulate monitoring data are also available for public view on the Port s website: The data collected at the Port s monitoring stations during this reporting year were compared to the NAAQS and California Ambient Air Quality Standards (CAAQS) established for each pollutant on the applicable averaging periods. While such comparisons are presented, this report does not make any representations as to compliance with NAAQS or CAAQS, and the information presented herein 12 th Year Annual Air Quality Monitoring Report 1 September 2017

10 should not be construed to the contrary. NAAQS compliance determinations are made by the U.S. Environmental Protection Agency (USEPA) with input from state and regional air agencies. CAAQS compliance determinations are made by the California Air Resources Board (CARB). For the South Coast Air Basin (SCAB), which includes the Los Angeles metropolitan region, the South Coast Air Quality Management District (SCAQMD) is responsible for operating separate air quality monitoring stations that are used for those demonstrations. While the Port s monitoring stations are operated in accordance with these same federal and state regulations and guidelines, the Port s stations are outside the official monitoring network and are not used in those determinations. Ambient air pollution levels near the San Pedro Bay are influenced by a number of factors including local pollutant emissions, regional air pollution levels, and meteorological conditions. Several important criteria air pollutants for which EPA has established air quality standards are created at least in part by chemical reactions (particularly ozone and PM2.5), which occur after the release of primary emissions into the atmosphere. As such, concentrations from these pollutants are expected to be more regional. Other pollutants, like PM10, SO2 or EC, are considered more localized in nature. Emissions from goods movement are an important contributor to air pollution levels in the SCAB region. DPM emissions, an important air toxic, are a contributor to PM2.5 concentrations. Based on the latest available Port Emissions Inventory, emissions from mobile sources operating at the Port are estimated to contribute approximately 4.5% of the regional nitrogen oxide (NOx) emissions and 4.4% of the regional DPM emissions in 2016; the contribution to regional NOx and DPM emissions from mobile sources operating at the Port has been relatively constant during recent years while the Port s contribution to regional SOx emissions continues to trend lower. 1 Between 2005, the CAAP baseline year, and 2016, emissions associated with Port operations showed an 87% reduction in DPM, a 98% reduction in sulfur oxides (SOx) and a 57% reduction in NOx. These emission reductions were due to a number of factors including the successful implementation of control measures under the CAAP and other voluntary tenant actions, along with state regulatory action, which have significantly reduced emissions rates from goods movement sources such as heavy duty trucks, ocean going vessels, and cargo handling equipment. Over the same timeframe, container throughput at the Port has increased by approximately 18%. Variation between the air monitoring results and the Port Emission Inventory is due to the fact that the emission inventory looks at only the five major sources of mobile pollution in and around the Port, while the air monitoring detects all sources, including industry not associated with the Port, such as refineries, and passenger cars. Meteorology can also have a significant influence on regional air pollution levels from one year to the next. While CAAP measures have improved air emissions levels around the Port, the amount of any decrease (or increase) in ambient air pollutant concentrations attributed to goods movement-focused control measures under the CAAP cannot be quantified solely through air quality monitoring. CAAP-related emissions reductions are estimated in the Port s annual Emission Inventories. The data collected during the Year 12 reporting period have been averaged and compared to the various NAAQS and CAAQS established for each pollutant. Table ES-1 presents the results of a comparison between the data collected by the monitoring network and the NAAQS and CAAQS during the most recent 12-month period. No NAAQS was exceeded for any of the pollutants measured in the monitoring network. There were some exceedances of the more restrictive CAAQS. The annual CAAQS for PM10 was exceeded at both the Wilmington and Coastal Boundary stations. Additionally, the eight-hour CAAQS for O3 was exceeded at the Coastal Boundary station. The SCAB is designated as being in nonattainment for O3 and PM2.5, and a maintenance area for PM10. Although the EC data are analyzed and presented in this report, there are no NAAQS or CAAQS associated with this parameter. 1 Port of Los Angeles Inventory of Air Emissions Starcrest Consulting Group LLC. ( July th Year Annual Air Quality Monitoring Report 2 September 2017

11 Table ES-1. Exceedances of NAAQS and CAAQS during Reporting Year 12 at the Port s Air Monitoring s Monitoring s Parameter Wilmington Coastal Boundary San Pedro Source- Dominated PM hour and annual NAAQS PM 2.5 Annual CAAQS PM hour NAAQS n/a* n/a* PM hour CAAQS n/a* n/a* PM 10 annual CAAQS Yes Yes n/a* n/a* CO 1-hour and 8-hour NAAQS CO 1-hour and 8-hour CAAQS NO 2 1-hour and annual NAAQS NO 2 1-hour and annual CAAQS O 3 8-hour NAAQS O 3 1-hour CAAQS O 3 8-hour CAAQS -- Yes SO 2 1-hour and 3-hour NAAQS SO 2 1-hour and 24-hour CAAQS n/a*: PM 10 data not collected at this station The POLA air monitoring network now has a 12-year period of record for PM data that can be used to determine trends over this period. Over this period of record, annual average EC concentrations have decreased by an average of 66 percent over all four stations (Figure ES-1). A comparison is made between decreases in calculated DPM emissions (as reported in the annual Port Emissions Inventory) and measured ambient EC concentrations, since EC is considered a surrogate of DPM in monitoring applications. Over the 12-year monitoring period, to , annual Port-wide DPM emissions decreased by 87 percent, while average ambient EC concentrations at the Source-Dominated station, located in the center of Port operations, decreased by 79 percent over a similar 12-year period (May April 2017). This indicates a strong correlation between the reductions observed in annual DPM emission estimates and average annual EC concentrations. While the reductions in annual DPM emissions and measured EC concentrations are similar, they are not expected to be exactly the same since both components in this comparison have different characteristics. Annual DPM emissions estimates are calculated over the entire Port area for only Port operational sources, while annual average EC concentrations are passive measurements conducted at specific locations that may be impacted by emission sources beyond simply Port 12 th Year Annual Air Quality Monitoring Report 3 September 2017

12 operations. However, even with inherent limitations, drawing a comparison between calculated DPM emission estimates and measured EC concentrations provides valuable insight to validating that the Port s DPM emission reduction measures are translating into improved air quality in the San Pedro Bay region. From monitoring year to monitoring year , annual average PM2.5 concentrations decreased by 52 percent at the Source-Dominated station, much less than the 85 percent reduction in Port-wide PM2.5 emissions during the period (Figure ES-2). Ambient PM2.5 levels around the Port have not followed decreases in PM2.5 emissions nearly as well as ambient EC levels appear to have followed decreases in DPM emissions. This is likely due to differing sources and characteristics of these two pollutants. For example, ambient PM2.5 levels can be affected by regional emission sources, through processes such as the secondary formation of PM2.5. Thus, PM2.5 levels measured in the vicinity of the Port do not appear to be as sensitive to the Port-focused emission reduction measures in the CAAP as EC, which is considered more of a localized pollutant. PM10 measurements have only been recorded for the entire 12-year period of record at the Wilmington station; additional PM10 measurements were incorporated into the monitoring program in 2009 at the Coastal Boundary station, as shown in Figure ES-3. PM10 concentrations tend to have a low correlation with CAAP emission reduction measures, due to the localized nature of PM10 particulates, which are often released as fugitive emissions from construction activities or wind-blown dust. Overall, there has been a 15 percent decrease in PM10 concentrations over the 12-year period of record. The only large yearly increase occurred during monitoring year , which was attributed to extensive construction projects near the Port monitoring stations during that timeframe. Figures ES-1 through ES-3 present annual average EC, PM2.5, and PM10 concentrations measured at the Port s air monitoring network since commencement of the monitoring program in Figure ES-1. Annual Average Elemental Carbon Concentrations at Port of Los Angeles 12 th Year Annual Air Quality Monitoring Report 4 September 2017

13 Figure ES-2. Annual Average PM 2.5 Concentrations at the Port of Los Angeles * Coastal Boundary SFS data incomplete for Year 11; sample data unavailable from November 2015 through April 2016 due to an instrument issue. Figure ES-3. Annual Average PM 10 Concentrations at Port of Los Angeles 12 th Year Annual Air Quality Monitoring Report 5 September 2017

14 2 INTRODUCTION The Port of Los Angeles (Port or POLA) began its air quality monitoring program in February Under the initial program, representative ambient elemental carbon (EC, as a surrogate for diesel particulate matter (DPM)), particulate matter (PM), and meteorological data were collected within the Port s operational region of influence (ROI). The collected PM data included two sizes of particulate matter: (1) fine PM that is less than 2.5 micrometers in diameter (PM2.5) and (2) PM that is less than 10 micrometers in diameter (PM10). In early 2008, the Port completed an expansion of the monitoring program to include continuous monitoring of four gaseous criteria air pollutants ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO). The Port also expanded the particulates monitoring to include continuous sampling of PM2.5, PM10, and ultrafine particle counts (UFP). In July of 2013, the Port added an Aethalometer to the Source Dominated to measure black carbon (BC) concentrations. The driver of this program was the increased concern over long-term health effects from DPM. The expanded monitoring program provides additional data to help provide an indication of the Port s area compliance with air quality standards, access to real-time data and presentation of that data for public review on a website. Furthermore, it provides the opportunity to conduct additional detailed analyses and an enhanced evaluation of source-receptor relationships in future studies. The monitoring program consists of a network of four stations located in the vicinity of the Port of Los Angeles: one each in San Pedro and Wilmington, the two communities adjacent to the Port; one near the southern coastal boundary of the Port; and one on Terminal Island, near the operational center of the Port. The station locations are shown in Figure 2-1. The design of the network was developed during 2003 and A monitoring work plan was developed and extensive discussions were held with the Port Advisory Committee (PCAC), and with the South Coast Air Quality Management District (SCAQMD) and the California Air Resources Board (CARB). The monitoring work plan was revised in 2008 to reflect the upgrades made to the air monitoring program to include the continuous, real-time instrumentation SITING OF THE MONITORING STATIONS The locations of the monitoring stations were selected to be representative of ambient air quality conditions within the Port and the adjacent communities of San Pedro and Wilmington. Each monitoring site was selected based on three factors: (1) sites that met EPA criteria for locating monitoring stations (particularly unobstructed exposure to the local air flow), (2) site availability, and (3) site security. The candidate locations for the San Pedro and Wilmington stations were subjected to a validation monitoring study to ensure the representativeness of the locations, and that the best available site was chosen in each community. Additional details of this selection process are provided in earlier annual reports 3. In late 2007/early 2008, the air monitoring program was expanded to include real-time monitoring of gaseous criteria pollutants and particulates. During the planning stage of this expansion, it was discovered that the San Pedro and Source-Dominated station had to be moved short distances, because the existing rooftop locations used at those sites could not support the shelters required to house the real-time monitoring instruments. Validation studies were conducted for each of these moves, which were detailed in previous annual reports 3. 2 The Port of Los Angeles Air Quality Monitoring Program Maintenance Plan, Port of Los Angeles, Air Quality Monitoring Program at the Port of Los Angeles Summary of Data Collected During the Fifth Year, May 2009 April Available at: 12 th Year Annual Air Quality Monitoring Report 6 September 2017

15 Figure 2-1. Locations of the Port's Monitoring s 12 th Year Annual Air Quality Monitoring Report 7 September 2017

16 3 DESCRIPTION OF AIR MONITORING PROGRAM The following discussion presents a summary of the Port s air monitoring network. The main objective of the air monitoring program is to estimate ambient levels of DPM in proximity to the Port to determine long-term trends. Although DPM is a focal point of the monitoring program, it cannot be measured directly in the ambient atmosphere, so the network has been monitoring EC as a surrogate of DPM. EC is a regulatory-accepted surrogate of DPM in monitoring, and has been monitored at each station since the inception of the program. This allows estimates of ambient levels of EC in the vicinity of the Port, and as well as trends in EC over the 12-year program. In addition, Port emission inventories provide annual estimates of DPM emissions from maritime-related activities, which have been used to determine if there are correlations between the trends in EC measurements and trends in DPM emissions. In June 2013, an Aethalometer was added to the Source-Dominated to measure ambient black carbon (BC) levels. Recent studies have shown that both BC and EC can be used as a surrogate for DPM emissions. BC and EC measurements are unique, in that they are defined by their respective measurement techniques. BC concentrations are measured with a real-time continuous instrument (Aethalometer), which uses an optical measurement method. EC concentrations are measured using a monitor that collects an integrated air sample on a filter, which is then analyzed using a thermaloptical methodology in a laboratory. Because BC and EC are analyzed using two different methodologies, the absolute values of the BC and EC concentrations at the same location may differ, even though simultaneous BC and EC measurements are typically highly correlated. That is, they are estimating the same surrogate parameter (DPM), but by two different methods. Although the historical record of BC data at the Port is much shorter than the EC data, the advantage of the BC data is that the real-time Aethalometer produces a more comprehensive, continuous BC data set, similar to those produced by the real-time PM2.5, PM10, CO, NO2, O3, and SO2 analyzers deployed within the POLA monitoring network. This more robust dataset allows additional insight and analysis into BC measurements, as shown later in the report. A secondary program objective is to estimate ambient levels of gaseous pollutants and particulate matter (PM) levels within adjacent communities. The monitoring network uses two different size measures of PM, PM10 and PM2.5, which refer to the maximum particle sizes measured, 10 and 2.5 micrometers (µm). These two particle sizes correspond to National Ambient Air Quality Standards (NAAQS) that have been set for PM. One component of PM, DPM, consists of very small particles (the particle phase) with organic compounds (the gaseous phase) adsorbed onto the particle phase, Generally, DPM makes up a small fraction of the particles collected by the PM2.5 and PM10 measurements, so EC and BC measurements are considered much better surrogates for DPM. A third objective of the monitoring program is to estimate ambient gaseous pollutants and PM levels within adjacent communities. Expansion of the program in 2008 allowed for continuous, real-time monitoring of additional pollutants, using gaseous analyzers to measure carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3), and beta attenuation monitors (BAMs) to measure PM2.5 and PM10. In May 2011, additional real-time condensation particle counters were deployed to provide ultrafine particle count (UFP) measurements at all four stations in the monitoring network. 3.1 LOCATIONS OF THE MONITORING NETWORK STATIONS The locations of the four stations currently in operation in the Port s air monitoring network are shown in Figure 2-1 and include the following stations: Wilmington Monitoring (33 o N, 118 o W) This station is located at the Saints Peter and Paul Elementary School (SPPS) in the City of Wilmington. This station is designed to collect air quality data that are representative of the residential areas of Wilmington. It is centrally located and is approximately 0.5 miles north of Port operations. 12 th Year Annual Air Quality Monitoring Report 8 September 2017

17 San Pedro Monitoring (33 o N, 118 o W) This station is located adjacent to the Promenade walkway along Harbor Drive, across the street from the intersection of Harbor Boulevard and West 3 rd Street. This station is designed to collect air quality data that are representative of the residential areas of San Pedro. It is centrally located and is approximately 0.1 mile west of the main ship channel. Coastal Boundary (33 o N, 118 o W) This station is located at Berth 47 (Berth 47 station) in the southern end of the Port between the Cabrillo Marina and the San Pedro Breakwater. This location has the least direct exposure to emissions from Port operations. Source-Dominated (33 o N, 118 o W) This station is located on Pier 300, at the Terminal Island Treatment Plant (TITP) on Ferry Street. This station is expected to have the highest exposure to emissions from Port operations, as it is in direct proximity to terminal operations which use a large number of diesel engine sources (trucks, trains, ships, and cargo handling equipment). It is also referred to as the Source-Dominated station, because of the predominance of on-road and off-road diesel emission sources in the area. 3.2 THE MONITORING NETWORK All four stations have an identical set of instruments, which collect a comprehensive set of integrated 24-hour average filter-based PM2.5 and PM10 samples, as well as real-time measurement of gaseous criteria pollutants, PM2.5 and PM10, ultrafine particle counts, and meteorological data, as shown in Table 3-1. In addition, the Wilmington and Coastal Boundary Monitoring stations include a few supplemental instruments, as shown in the table and discussed below. 12 th Year Annual Air Quality Monitoring Report 9 September 2017

18 Table 3-1. Air Quality and Meteorological Instrumentation Currently in Operation at the Port of Los Angeles Monitoring s Monitoring s Parameter Wilmington Coastal Boundary San Pedro Source- Dominated PM 2.5 Integrated Filter Sampler (PM 2.5 mass and EC/OC) PM 2.5 Continuous Monitor (PM 2.5 mass) PM 10 Continuous Monitor (PM 10 mass) PM 2.5 FRM Filter Monitor (PM 2.5 mass) X X X X X X X X X X X X X PM 10 FRM Filter Monitor (PM 10 mass) X X Ultrafine Particle Counters X X X X Aethalometer (BC) X CO Monitor X X X X NO 2 Analyzer X X X X O 3 Analyzer X X X X SO 2 Analyzer X X X X Meteorological Instruments (wind speed & direction, temp.) Supplemental Meteorological Instruments (rel. humidity, solar radiation, barometric pressure) X X X X X Note: Instrumentation located at individual stations is identified by checked boxes. The stations in the Port s network are equipped with the following components: 1. Detailed 24-hour Sampling for PM2.5 Each station is equipped with a multi-port PM2.5 sequential filter sampler (SFS) monitor that simultaneously collects samples on a 24-hour basis on two different filter media (Teflon and quartz). This allows for the analysis of samples for mass (Teflon filters) and detailed chemical speciation (quartz and Teflon filters combined), including carbon fractions (elemental carbon/organic carbon), metals, and soluble ions. Samples are collected at each site every third day, following EPA s nationwide schedule. This allows direct comparison of the data collected at stations in the POLA and POLB monitoring networks and at other agency stations in the vicinity. 2. Continuous Monitoring of PM2.5 and PM10 In addition to the detailed 24-hr PM2.5 sampling described above, each of the Port s monitoring stations are equipped to monitor PM2.5 and PM10 on a continuous and real-time hourly basis using Met One Instruments Beta Attenuation Monitors (BAMs). 12 th Year Annual Air Quality Monitoring Report 10 September 2017

19 3. PM10 Filter-based Monitoring The Wilmington and Coastal Boundary stations have Federal Reference Method (FRM) PM10 monitors with EPA design certification to measure PM2.5 concentrations for compliance with the NAAQS and CAAQS. 4. PM2.5 Filter-based Monitoring The Wilmington station has an FRM PM2.5 monitor to verify operation of the SFS monitors and to measure PM2.5 concentrations for compliance with the NAAQS and CAAQS. 5. Continuous Gaseous Pollutant Monitoring Each station is equipped with analyzers to determine real-time air pollutant concentrations for the gaseous pollutants (i.e. NO-NO2-NOx, O3, CO, and SO2). These analyzers are FRM or federal equivalent method (FEM) designated monitors and include the following: a. Pulsed Fluorescence SO2 Analyzer b. Chemiluminescent NO-NO2-NOx Analyzer c. Gas Filter Correlation CO Analyzer d. U.V. Photometric Ozone (O3) Analyzer 6. Ultrafine Particle Monitoring In May 2011, water-based ultrafine particle (UFP) counters (TSI Model 3783) were installed at each station in the network. 7. Black Carbon Monitoring In June 2013, a real-time Aethalometer (Teledyne API Model 633) was installed at Source-Dominated. A data logger is located at each site, which automatically calculates 1-hour average of the data from the real-time continuous monitors. Averages for other time periods specified in the NAAQS and CAAQS (such as 8 hours, 24 hours or annually), are calculated after the real-time data have been reviewed and incorporated into a master database in Leidos San Diego offices. Filter-based PM data are collected as continuous samples over a 24-hour period, as reported by our analytical laboratory. 4 DATA ANALYSIS 4.1 REGULATORY BACKGROUND Air quality is determined by the size and topography of the air basin, the local and regional meteorological influences, and the type and concentration of pollutants in the atmosphere, which are generally expressed in units of parts per million (ppm) or micrograms per cubic meter (μg/m 3 ). Comparison of these pollutant concentrations with the federal and state ambient air quality standards is often made to evaluate air quality conditions in an area. The USEPA has established the NAAQS which are maximum pollutant limits averaged over specific time periods (e.g., 1-hour, 8-hours, 24- hours, annually) and shall not be exceeded more than specified in the individual NAAQS. Annual pollutant averages are never to exceed the annual NAAQS. Primary standards are set at levels designed to protect public health with an adequate margin of safety, including the health of sensitive populations such as children and the elderly. Secondary standards set limits to protect public welfare, including protection against decreased visibility and damage to animals, crops, vegetation, and buildings. The Clean Air Act and its subsequent amendments delegate the enforcement of these standards to the states, which may adopt the NAAQS as state standards or establish more stringent acceptable pollutant concentration levels if they deem necessary. CARB has established a set of state standards (CAAQS) that are often more stringent than the NAAQS. There are no regulatory standards at the present time for EC, BC or UFP counts. Table 4-1 presents the California and national ambient air quality standards. 12 th Year Annual Air Quality Monitoring Report 11 September 2017

20 Table 4-1. California and National Ambient Air Quality Standards Pollutant Averaging Times California Standards Primary National Standards Secondary Ozone (O3) Carbon Monoxide (CO) Nitrogen Dioxide (NO2) Sulfur Dioxide (SO2) Lead Respirable Particulate Matter (PM10) Fine Particulate Matter (PM2.5) 8-hour ppm ppm* 1-hour ppm --- Same as Primary 8-hour 9.0 ppm 9.0 ppm hour 20.0 ppm 35.0 ppm --- Annual ppm ppm 1-hour ppm ppm Same as Primary 24-hour ppm hour ppm 1-hour ppm ppm day 1.5 µg/m Rolling 3-Month µg/m 3 Same as Primary Annual 20 µg/m Same as Primary 24-hour 50 µg/m µg/m 3 Annual 12 µg/m 3 12 µg/m 3 ** 24-hour µg/m 3 Same as Primary Notes: National Primary Standards: Levels of air quality necessary, with an adequate margin of safety to protect public health. National Secondary Standards: Levels of air quality necessary to protect the public welfare from any known or anticipated adverse effects of a pollutant. * The new 8-hour O 3 NAAQS was promulgated on October 26, ** The new annual PM 2.5 NAAQS was promulgated on December 14, AIR QUALITY DATA SUMMARY YEAR 12 The following analysis summarizes the data collected from May 2016 through April 2017 and draws comparisons to the NAAQS and CAAQS. These summaries include the following parameters: [1] EC, [2] BC, [3] PM2.5, [4] PM10, [5] CO, [6] NO2, [7] SO2, [8] O3, and [9] UFP counts. Wind speed and direction measurements collected during this period are also summarized. In addition to written summaries, the data are presented in several ways: 1. A graphical format (Figures A-1 through A-20 in Appendix A-1 4 ). 2. Wind roses (Figures A-21 through A-24 in Appendix A-1). 3. Summaries in Tables A-1 through A-24 (Appendix A-2). This data summary is a compilation and presentation of data collected during the twelfth year of ambient monitoring (May April 2017). The filter-based particulate matter data are also available on the Port s website at Real-time data are available on the Port s Clean Air Action Plan (CAAP) website at The data summary is presented below. 4 The tabular and graphic data presentations are quite extensive, such that most figures and tables have been included in Appendix A of this report. 12 th Year Annual Air Quality Monitoring Report 12 September 2017

21 4.2.1 PM Data Summary PM data are summarized and presented for EC, BC, PM2.5, and PM10 measurements. Filter-based PM monitoring began in early Real-time PM monitoring (using BAMs) was initiated in 2008, while real-time BC monitoring began in June EC Data EC is a pollutant that has been measured for the entire period of record, and is considered to be the most representative pollutant for assessing impacts from Port operations, because of the diesel emissions from mobile sources operating at the Port (e.g., ships, locomotives, trucks, cargo handling equipment, and harbor craft). There are currently no federal or state standards for EC, but it has been used as a surrogate for DPM in SCAQMD s Multiple Air Toxics Exposure Studies (MATES). Therefore, measured EC data are included to supplement data for which there are standards. EC concentrations are measured by analyzing the PM2.5 filters collected using the sequential filter samplers (SFS) located at each station. The EC data shows several patterns and trends over the course of the monitoring program. The data in Table A-1 (Appendix A-2) is also shown graphically in Figure A-1, which presents a bar graph of annual average EC concentrations measured using the SFS monitors over the 12-year period of record. Figure A-1 shows that over the period of record, annual average EC concentrations have decreased at a greater rate than the annual average PM2.5 or PM10 concentrations (Figures A-4 and A-8, respectively). With a few exceptions, annual average EC concentrations measured at the four stations have decreased in a relatively steady manner over the five-year period starting in around 2006 (Year 2). Between and , EC levels were relatively unchanged. However over the last two reporting periods, there are additional decreases in the annual average EC concentrations measured across the monitoring network. Over the 12-year period of record, annual EC concentrations have shown a 66% reduction, when averaged over the Port-wide network. This trend is discussed in more detail in Section 5.1. Table A-1 presents Year 12 s EC data, which was collected following the EPA s 3-day PM2.5 filterbased monitoring schedule. The data are also shown graphically in Figure A-2 as monthly average EC concentrations over the reporting year. Figure A-2 shows that EC concentrations were generally lower during the spring and early summer months and higher in the late fall and winter months. The observed variability in monthly average EC concentrations is likely due to seasonal meteorological variations associated with the frequency of atmospheric inversions. During the fall and winter months, when atmospheric inversions are most common, light winds and stable atmospheric conditions limit the dispersion of emissions near the earth s surface. Under these conditions, DPM emissions are effectively confined to the lower atmosphere with little convective or mechanical turbulence present to disperse emissions. During months when atmospheric inversions are most frequent, measured EC concentrations tend to increase as greater atmospheric stability at the near-surface level tends to limit dispersion and increase pollutant concentrations. In addition, EC is considered to be a more localized pollutant; therefore, EC measurements tend to be more site-specific than PM2.5 levels since concentrations are more influenced by local emission sources. Figure A-3 in Appendix A-1 shows monthly average EC concentrations over the period of record for each station. The dramatic seasonal variations are clearly evident with peaks of maximum EC concentrations in the late fall/early winter and lower EC concentrations during the spring and summer periods. Also evident in Figure A-3 is the strong trend of decreasing maximum and decreasing minimum EC concentrations within each year through the 12-year period of record, with the exception of years 6-9 (May April 2014). If Years 6-9 are ignored, the pattern of decreasing EC concentrations that appeared in the first years of the monitoring program has continued unabated through the current year. As discussed above, Figure A-3 shows that monthly average EC levels have displayed a remarkably consistent seasonal pattern of EC concentrations over the entire period of record, with maximum 12 th Year Annual Air Quality Monitoring Report 13 September 2017

22 values occurring the fall and winter months, and minimum values during the late spring/summer months. This seasonal pattern is also seen in the corresponding figure for PM2.5 (A-6), but it is not as consistent or dramatic. A similar seasonal pattern for PM10 (Figure A-10) is even less apparent. The strong trend of reduced seasonal fall and winter peaks of EC concentrations in the last three years, as shown in Figure A-3, is reflected in the lower annual average EC concentrations at all stations, as shown in Figure A-1 and in Table 4-2 below. The only exception is the relatively remote Coastal Boundary station, which has seen virtually no change in annual average EC concentrations over this time period. Table 4-2 presents annual average EC concentrations at the Port s monitoring stations during the past four years. Table 4-2 shows that annual average EC concentrations measured in the Port s network, with the exception of the Coastal Boundary station, have demonstrated consistent reductions over the past four monitoring years. Table 4-2. Annual Average EC Concentrations at POLA Monitoring s ( ) Averaging Time Annual Annual Annual Annual Period May April 2014 May April 2015 May April 2016 May April 2017 Wilmington EC Concentration (µg/m 3 ) Coastal Boundary San Pedro Source- Dominated BC Data Ambient BC concentrations have been measured at the Port s Source-Dominated station since June 2013, using a real-time Aethalometer (API Model 633). This is the newest air quality parameter to be monitored within the POLA network, and is being measured only at the Source-Dominated station at this time. The following summary includes results from the first four full years of BC monitoring (June April 2017) at the Source-Dominated station. As discussed previously, BC and EC are of interest because they are both considered surrogates for diesel particulate matter (DPM) by regulatory agencies including the SCAQMD and CARB. DPM is a very complex mixture of gases and particulates, and ambient concentrations of DPM cannot be measured directly. Hourly BC averages are collected by the real-time Aethalometers, in contrast to EC data which is collected as an integrated 24-hour filter-based sample following the EPA s three-day sampling schedule and analyzed by a laboratory. As discussed in the introduction (Section 3), BC and EC are analyzed using two different methodologies. Consequently, the absolute values of the BC and EC concentrations at the same location may differ, even though BC and EC measurements are typically highly correlated. The continuous BC dataset, measured by the Aethalometer, provides additional insight and increased temporal resolution to DPM levels in the vicinity of the Source-Dominated station. Although BC data are collected only at the Source-Dominated station in the POLA network, the Port of Long Beach (POLB) air quality monitoring program also deploys identical real-time Aethalometers at their Inner Harbor and Outer Harbor stations. POLB allowed BC data from these stations to be 12 th Year Annual Air Quality Monitoring Report 14 September 2017

23 included in this report for comparative purposes, which allows for a comprehensive review of BC levels in the San Pedro Bay Ports area. The SCAQMD s MATES IV report 5 provides an additional summary of BC measurements collected at ten SCAQMD stations in the South Coast Air Basin (SCAB). The West Long Beach (WLB) station is of particular interest since the station was located approximately 1.4 miles northwest of the POLB Inner Harbor station. BC data for the MATES IV program was collected during an earlier time period (July 2012 to June 2013), so direct comparison of the BC data is not possible. Table 4-3 presents annual average BC concentrations at the POLA Source-Dominated station and at the POLB Inner and Outer Harbor stations. The Inner Harbor monitoring station is in a location similar to POLA s Source-Dominated station, near the center of POLB s operations. The Inner Harbor station is impacted by Port operations from nearby truck distribution sites. The Outer Harbor station is located in the southern portion of the Port s harbor complex adjacent to POLB s main shipping channel, and is comparable to POLA s Coastal Boundary station, with little Port-related sources in the vicinity. Table 4-3 shows that annual average BC concentrations, measured at the three stations, have decreased during the four years that BC has been monitored, and shows a similar pattern to the decrease seen in the EC concentrations at the POLA monitoring stations over the same time period. POLB s Outer Harbor (the site furthest from the center of POLB operations) measured the lowest annual BC concentration (0.90 µg/m 3 ) during the past monitoring year. Conversely, POLB s Inner Harbor station recorded the highest annual average BC concentration at 1.24 µg/m 3, which is expected due to localized emissions from port operations. At POLA s Source-Dominated station, annual average BC concentrations (1.10 µg/m 3 ) are approximately mid-way between the BC concentrations measured at the two POLB stations. Table 4-3. Annual Average BC Concentrations at the POLA and POLB s BC Concentration (µg/m 3 ) Averaging Time Period POLA Source-Dominated POLB Inner Harbor POLB Outer Harbor Annual Annual Annual Annual May April 2014 May April 2015 May April 2016 May April Note: There are no existing regulatory standards for BC data. (1) Partial year - Monitoring at the Source-Dominated station began on 6/2/ PM2.5 Data The results of the PM2.5 monitoring program are shown in Figures A-4 through A-7 in Appendix A-1 and Tables A-3 through A-6 in Appendix A-2. These figures and tables are discussed in this section and in the Trends Section SCAQMD. Multiple Air Toxics Exposure Study in the South Coast Air Basin, MATES IV. Final Report, Appendix VI Copley Drive, Diamond Bar, CA 91765, May, th Year Annual Air Quality Monitoring Report 15 September 2017

24 The data in Table A-3 is shown graphically in Figure A-4, which presents a bar graph of annual average PM2.5 concentrations from the filter-based integrated monitors over the monitoring period (Figure A-4 is also shown as Figure ES-2 in the Executive Summary). The figure shows a relatively constant decrease in PM2.5 concentrations starting around 2006 and continuing until PM2.5 concentrations have been roughly constant (with significant year-to year variability) since the monitoring year. As mentioned in the footnotes accompanying these tables and graphs, due to an instrument problem with the SFS unit at the Coastal Boundary station, the sample year for this site is incomplete. Since PM2.5 data are unavailable for the winter months (when the highest concentrations are generally observed), PM2.5 averages and comparisons with federal and state standards are not likely to be representative at the Coastal Boundary station over that reporting period. Figure A-5 provides monthly average PM2.5 concentrations during the current year. Figure A-6 presents a graph of monthly average PM2.5 concentrations from the filter-based data collected at the four stations over the 12-year monitoring period. At each station, there is a general tendency for elevated PM2.5 concentrations to occur during the late fall and winter months. Since early 2008, PM2.5 concentrations have also been measured at the four Port stations using realtime particulate monitors (BAMs). Figure A-7 presents a graph of real-time BAM PM2.5 concentrations averaged on a monthly basis over the current monitoring year to illustrate the overall trend and remove day-to-day variability in the data. Patterns in filter-based and real-time measurements for the PM2.5 monitors are similar, although real-time BAM data from the Port monitoring stations are consistently higher than PM2.5 data collected on filter media. Real-time PM2.5 data collected by the BAM instruments are used to supplement the integrated 24-hour data collected by the filter-based FRM units, but generally have not been used for direct comparison with the NAAQS. This approach is consistent with the SCAQMD s policy 6 (SCAQMD, 2014), which proposed to EPA to exclude PM2.5 data collected with continuous monitors from comparison with the NAAQS. The EPA offers guidance on how to request a continuous data exclusion per 40 CFR 58.11(e) since, on average this data is from 0% to 60% higher than traditional filter-based FRMs. NAAQS Comparison The 24-hour PM2.5 NAAQS is met when the 98 th percentile of the daily average PM2.5 concentrations, averaged over three years, is equal to or less than 35 g/m 3. The annual average NAAQS for PM2.5 is 12 g/m 3. The three-year averages (May April 2017) of the 98 th percentile of the 24-hour average PM2.5 concentrations at the four Port stations are less than the NAAQS (35 g/m 3 ), as shown in Table 4-4. Thus, data from the monitors show the stations are currently meeting the 24-hour average PM2.5 NAAQS. For the current year, the annual average PM2.5 concentrations measured by the filterbased monitors are also shown in Table 4-4. There were no exceedances of the NAAQS. 6 SCAQMD. Instructions and Template for Requesting that Data from PM 2.5 Continuous FEMs are not compared to the NAAQS Copley Drive, Diamond Bar, CA 91765, April, th Year Annual Air Quality Monitoring Report 16 September 2017

25 Table 4-4. NAAQS Comparison Three-Year Average of 98 th Percentile of 24-hour and Annual Average PM 2.5 Concentrations Averaging Time Period Wilmington PM 2.5 Concentration (µg/m 3 ) Coastal Boundary San Pedro Source- Dominated NAAQS 24-hour 1 Annual May April 2017 May April Three Year Average of 98 th Percentile of 24-hour average. CAAQS Comparison The annual PM2.5 CAAQS is met when the annual average PM2.5 concentration is equal to or less than 12 g/m 3. There is no separate 24-hour PM2.5 CAAQS. For the current monitoring year, the annual average PM2.5 concentrations measured by the filter-based monitors are shown in Table 4-5. There were no exceedances of the CAAQS. Table 4-5. CAAQS Comparison Annual Average PM 2.5 Concentrations PM 2.5 Concentration (µg/m 3 ) Averaging Time Period Wilmington Coastal Boundary San Pedro Source- Dominated CAAQS Annual May April PM10 Data Starting in 2005, the Port s air monitoring program collected filter-based ambient PM10 measurements at two stations within the Port s operational region of influence: the Wilmington and Coastal Boundary stations. However in early 2008, the Port completed an expansion of the monitoring program to include continuous PM10 monitoring (using BAMs) at all four monitoring stations in the network. The results of the filter-based and continuous PM10 monitoring data are shown in Figures A- 8 through A-11 in Appendix A-1 and Tables A-7 through A-9 in Appendix A-2. These figures and tables are discussed in this section and Section 5.1. During the Year 12 reporting period at the Coastal Boundary station, the filter-based PM10 data set is missing approximately three months of data (July to September 2016). This period of missing data was due to an intentional, temporary operational change undergone to assist in trouble-shooting the Coastal Boundary station s PM2.5 filter-based SFS unit. From July through September 2016, the PM10 monitor (FRM) was converted into a PM2.5 monitor (FRM) to sample concurrently with the existing PM2.5 SFS unit. The PM2.5 data (FRM) collected during this time was used to assist in validating the data collected by the existing PM2.5 SFS monitor at the Coastal Boundary station. Since the evaluation process resulted in three months of filter-based PM10 data missing from the current year s data at the Coastal Boundary site, this data set may not be representative. However, review of Figure A-9 in the Appendix demonstrates that monthly average PM10 concentrations at the Wilmington and Coastal Boundary stations compare very well for the nine months when 12 th Year Annual Air Quality Monitoring Report 17 September 2017

26 data are available at both stations. Based on the patterns of data shown in Figure A-9, the PM10 data collected at the Coastal Boundary station could be considered reasonably representative of that site for the Year 12 reporting period. The data in Table A-7 is shown graphically in Figure A-8, which provides a bar graph illustration of the annual average PM10 concentrations from the filter-based PM10 monitors over the reporting period (Figure A-8 is also shown as Figure ES-3 in the Executive Summary). The bar graph shows relatively consistent annual average PM10 concentration for Years 1-3 of the monitoring program ( through ) at the Wilmington station, which is the only long-term monitoring data set for PM10 in this program. This was followed by a relatively steady decrease in PM10 levels during Years 4-6 ( through ). During the reporting period (Year 7), annual average PM10 concentrations increased at both the Wilmington and Coastal Boundary stations compared to the previous year. This increase can be attributed in part to large construction projects in the vicinity of both stations, which typically produce large quantities of fugitive dust due to construction activities (PM10 is a significant component of fugitive dust). Over the past five years, measured PM10 concentrations have demonstrated a slight, but consistent, decrease from the elevated levels observed in The monthly average PM10 data presented in Table A-7 is also shown graphically in Figure A-9. The figure shows that the highest monthly average PM10 concentrations generally occur during the fall and early winter months. This is similar to, but not as consistent as, the pattern observed in the PM2.5 data. There is a sharp decrease in PM10 levels at both stations in February This decline is attributed to an increase in the frequency and amount of precipitation in the SCAB during that period, as nearly 14 inches of rainfall were observed at Long Beach s NWS station during January and February Figure A-10 presents a graph of monthly average PM10 concentrations collected using the filter-based monitors over the 12-year period of record. PM10 levels show considerable variability over the period of record with the highest monthly average PM10 concentration was measured in January This monthly average exceeded the previously highest PM10 concentration in November 2007, when widespread wildfires were present in the Southern California region. The elevated PM10 concentrations observed in January 2014 (and generally observed through the fall and winter of ) were likely due to an increase in Santa Ana wind events in combination with a very dry winter season (Figure A-10). These dry, windy Santa Ana events are conducive to wind erosion at the ground surface, resulting in elevated amounts of fugitive PM10 emissions. In contrast, the effect of increases in the amount and frequency of precipitation events during appears to have resulted in lower PM10 concentrations for the Year 12 reporting period. Since early 2008, PM10 concentrations have also been measured at the four Port stations using realtime particulate monitors (BAMs). This PM10 data is presented in Table A-9 and shown graphically in Figure A-11. This figure illustrates real-time BAM PM10 concentrations averaged on a monthly basis over the current reporting period. The patterns in PM10 concentrations for the filter-based and realtime monitors are similar, but the real-time BAM measurements of PM10 demonstrate more variability and are somewhat higher. NAAQS Comparison The 24-hour PM10 NAAQS is attained when the number of days per calendar year with a 24-hour average concentration above 150 µg/m 3 is equal to or less than one. The annual average NAAQS for PM10 was revoked in The 24-hour maximum PM10 concentrations are shown in Table 4-6. There were no exceedances of the federal 24-hour PM10 NAAQS measured at any of the Port stations during the current year. As discussed above, three months of PM10 data were not available at the Coastal Boundary station during the current year. 12 th Year Annual Air Quality Monitoring Report 18 September 2017

27 Table 4-6. NAAQS Comparison Highest 24-hour Average PM 10 Concentrations PM 10 Concentration (µg/m 3 ) Averaging Time Period Wilmington Coastal Boundary NAAQS 24-hour May April CAAQS Comparison The 24-hour PM10 CAAQS is 50 µg/m 3, and the annual average CAAQS is 20 µg/m 3. There were no exceedance of the 24-hour PM10 CAAQS of 50 g/m 3 measured at the Port s monitoring stations during the current monitoring year, as shown in Table 4-7. Table 4-7 shows that annual average PM10 concentrations measured with the filter-based monitors were above the annual CAAQS of 20 g/m 3 at both monitoring sites during the current year. This is consistent with data collected throughout the SCAB, which has only recently been designated as being in maintenance for PM10. Annual average PM10 monitoring results for the 12-year period of record are presented in Table A-7. Table 4-7. CAAQS Comparison Highest 24-hour and Annual Average PM 10 Concentrations PM 10 Concentration (µg/m 3 ) Averaging Time Period Wilmington Coastal Boundary CAAQS 24-hour Annual May April 2017 May April Gaseous Criteria Pollutant Data Summary The Port monitoring network has collected real-time measurements of the following gaseous pollutants since 2008: CO, NO2, O3, and SO2. Results are discussed below, arranged by individual pollutant CO Data Summary Figure A-12 illustrates monthly average CO concentrations over the period of record. Graphs of average monthly pollutant concentrations have been selected as a convenient scale for illustration of the main features in the data set. The highlights of this graph are: Average CO concentrations are relatively low throughout the period, compared to the short-term standards for this pollutant. There is a slight increase in CO concentrations during the winter months, likely due to decreased atmospheric dispersion from surface-based temperature inversions commonly present during this time of year, which tend to trap pollutants in the lower atmosphere. 12 th Year Annual Air Quality Monitoring Report 19 September 2017

28 NAAQS Comparison The NAAQS for CO are 9 ppm during an 8-hour period and 35 ppm during a 1-hour period, and are not to be exceeded more than once per year. During the current monitoring year, no exceedances of the NAAQS for CO were recorded at the Port s monitoring stations. For Year 12, the maximum 1-hour average CO concentration recorded within the monitoring network was 3.4 ppm at the Wilmington station (shown in Table 4-8). This is well below the 1-hour NAAQS of 35 ppm. The maximum 8-hour average CO concentration was 2.7 ppm, measured at the Coastal Boundary station, as shown in Table 4-8. Thus, there were no exceedances of the 8-hour NAAQS of 9 ppm. Table 4-8. NAAQS Comparison Maximum 1-hour and 8-hour CO Concentrations CO Concentration (ppm) Averaging Time Period Wilmington Coastal Boundary San Pedro Source- Dominated NAAQS Max 1-hr CO Concentration Max 8-hr CO Concentration May April 2017 May April CAAQS Comparison The CAAQSs for CO are 9 ppm during an 8-hour period and 20 ppm over a 1-hour period, and are not to be exceeded. During the current monitoring year, no exceedances of the CAAQS for CO were recorded at the Port s monitoring stations, as shown in Table 4-9 below. Table 4-9. CAAQS Comparison Maximum 1-hour and 8-hour CO Concentrations CO Concentration (ppm) Averaging Time Period Wilmington Coastal Boundary San Pedro Source- Dominated CAAQS Max 1-hr CO Concentration Max 8-hr CO Concentration May April 2017 May April th Year Annual Air Quality Monitoring Report 20 September 2017

29 NO2 Data Summary Figure A-13 shows the average monthly concentrations of NO2 over the current monitoring year. The graph illustrates an annual cyclical pattern in the NO2 concentrations. Monthly average NO2 concentrations fall to a minimum during the summer and gradually increase through the winter months. There are two possible explanations for this pattern: 1. The lower concentrations in the summer may be due to the complex series of atmospheric chemical reactions that exist between NO2 and ground-level O3, which is generally higher during the summer. 2. Surface-based temperature inversions commonly present during the winter months may trap the NO2 closer to the ground, increasing ground level concentrations of this pollutant. NO2 data at the Coastal Boundary station are missing for February and March 2017 due to ongoing issues with the instrument at this site. A new NO2 instrument was deployed on April 24, NAAQS Comparison The NAAQS for NO2 is an annual arithmetic mean of ppm. In addition, effective January 22, 2010, EPA established a new 1-hour NAAQS for NO2 which is attained when the 3-year average of the 98 th percentile of the daily maximum 1-hour average does not exceed ppm. During the 12-month reporting period, neither the 1-hour average nor the annual average NO2 NAAQS were exceeded at any of the Port s monitoring stations, as shown in Table The latest 3-year (May April 2017) average of the 98 th percentile 1-hour NO2 concentration ranged from ppm at the Coastal Boundary station to ppm at the Source-Dominated station. Average concentrations from all stations were below the NAAQS of ppm. The maximum annual average NO2 concentration observed in the monitoring network during the current reporting year was ppm at the Wilmington station, which is below the NO2 annual average NAAQS of ppm. Table NAAQS Comparison Three Year Average of the 98 th Percentile 1-hour Average and Annual Average NO 2 Concentrations NO2 Concentrations (ppm) Averaging Time 1-hour * Annual Period May April 2017 May April 2017 Wilmington Coastal Boundary San Pedro Source- Dominated NAAQS * Three Year Average of 98 th Percentile of 1-hour Average 12 th Year Annual Air Quality Monitoring Report 21 September 2017

30 CAAQS Comparison The annual average CAAQS for NO2 is ppm, and the 1-hour CAAQS for NO2 is ppm. Both are not to be exceeded. During the current monitoring year, the 1-hour NO2 CAAQS of ppm was not exceeded at any of the stations, as shown in Table A maximum concentration of ppm was recorded at the Source-Dominated station. The maximum annual average NO2 concentration observed in the monitoring network during the current reporting year was ppm at the Wilmington station, which is below the NO2 annual average CAAQS of ppm. Table CAAQS Compliance Maximum 1-hour and Annual NO 2 Concentrations NO2 Concentrations (ppm) Averaging Time Period Wilmington Coastal Boundary San Pedro Source- Dominated CAAQS 1-hour Annual May April 2017 May April O3 Data Summary Figure A-14 shows the average monthly concentration of O3 for the current monitoring year. The graph shows that O3 concentrations peak during the summer months at each station, as photochemical reactions required to produce O3 are stronger during the summer (O3 is a secondary pollutant formed from VOCs and NOx in presence of sunlight). The monthly average O3 concentrations measured at the Coastal Boundary station are generally slightly higher than the other stations, despite the fact that this station is more removed from Port operations and other localized emission sources. All of the stations are exposed to similar regional levels of O3, but it is likely that the NOx emissions from local sources are more effective in depleting the local ozone levels at the other stations through atmospheric chemical reactions. From February to May 2017, there was an issue with the manifold inlet at the Wilmington station, such that ozone measurements were lower than expected and not representative of the historical ambient O3 levels at the site. However, the NAAQS and CAAQS standards for O3 concentrations are for short-term periods only (e.g. - 1-hour and 8-hour). Historically, the highest O3 measurements in the Port s monitoring program (and the broader SCAB) generally occur during the summer months. Since this manifold issue occurred only during the late winter and spring of 2017, it is likely that the maximum O3 measurements observed during the current reporting year were collected during the summer of As such, it is likely that the maximum O3 values presented in Tables 4-12 and 4-13 were unaffected by this issue. 12 th Year Annual Air Quality Monitoring Report 22 September 2017

31 NAAQS Comparison The 8-hour average O3 NAAQS is met when the fourth-highest 8-hour concentration in a year, averaged over three years, is equal to or less than ppm. During the reporting period none of the Port monitoring sites were in exceedance of the 8-hour NAAQS for ozone, as shown in Table The three year average of the fourth-highest 8-hour O3 concentrations ranged from ppm at the San Pedro station to ppm at the Coastal Boundary station. Table NAAQS Comparison 3-Year Average of Fourth Highest 8-hour Average O 3 Concentrations O3 Concentrations (ppm) Averaging Time Period Wilmington Coastal Boundary San Pedro Source- Dominated NAAQS 8-hour * May April * 3 Year Average of Fourth Highest 8-hr Average CAAQS Comparison The two CAAQS for O3 are ppm for an 8-hour period and ppm over a 1-hour period, and are not to be exceeded. During the current monitoring year, exceedances of the maximum 8-hour average CAAQS were observed at the Coastal Boundary station, and there were no exceedances of the 1-hour CAAQS at the Port monitoring stations. Maximum 1-hour average O3 concentrations did not exceeded the 1-hour O3 CAAQS of ppm at any of the Port monitoring stations Table 4-13 shows that the Wilmington and Source-Dominated stations had the highest 1-hour O3 concentration of ppm. During the current monitoring year, the maximum 8-hour average O3 CAAQS was exceeded on two days at the Coastal Boundary station. The 8-hour O3 CAAQS was not exceeded at any other site. Table CAAQS Comparison Maximum 1-hour and 8-hour Average O3 Concentrations O3 Concentrations (ppm) Averaging Time Period Wilmington Coastal Boundary San Pedro Source- Dominated CAAQS 1-hour 8-hour May April 2017 May April th Year Annual Air Quality Monitoring Report 23 September 2017

32 SO2 Data Summary Figure A-15 shows monthly average SO2 concentrations for the current monitoring year. Figure A-15 shows that SO2 concentrations remained low and fairly constant over the current monitoring period. NAAQS Comparison Effective August 23, 2010, EPA established the 1-hour NAAQS for SO2 which is attained when the 3- year average of the 99 th percentile of the daily maximum 1-hour average does not exceed ppm. The secondary NAAQS for SO2 is a 3-hour average that is attained if the second highest daily 3-hour maximum does not exceed ppm. Primary standards are designed to protect public health, while secondary standards are designed to protect public welfare, including protection against visibility impairment and damage to animals, crops, vegetation and buildings. During the reporting period, no exceedances of the primary and secondary NAAQS for SO2 were recorded at the Port s monitoring stations. The latest 3-year (May April 2017) average of the 99 th percentile SO2 concentrations ranged from ppm at the Coastal Boundary station to ppm at the San Pedro station, as shown in Table These are well below the 1-hour NAAQS for SO2 of ppm. The second highest 3-hour average SO2 concentrations measured during the current monitoring year ranged from ppm at the Coastal Boundary station to ppm at the San Pedro station, as shown in Table These concentrations are well below the 3-hour average SO2 secondary NAAQS of ppm. Table NAAQS Comparison 3 year Average of the 99 th Percentile 1-hour Daily Maximum and 2 nd Highest 3-hour Average SO 2 Concentrations SO2 Concentrations (ppm) Averaging Time Period Wilmington Coastal Boundary San Pedro Source- Dominated NAAQS 1-hour * 3-hour ** May April 2017 May April * Three Year Average of 99 th Percentile of 1-hour daily maximums ** Second highest 3-hour Average 12 th Year Annual Air Quality Monitoring Report 24 September 2017

33 CAAQS Comparison The CAAQS for SO2 are ppm over a 1-hour period and ppm over a 24-hour period, and are not to be exceeded. During the current monitoring year, maximum 1-hour SO2 concentrations ranged from ppm at the Coastal Boundary station to ppm at the San Pedro station, as shown in Table These concentrations are well below the SO2 1-hour CAAQS of ppm. The maximum 24-hour average SO2 concentrations measured during the current monitoring year ranged from ppm at the Wilmington station to ppm at the Source-Dominated station, as shown in Table These concentrations are well below the SO2 maximum 24-hour average CAAQS of ppm. Table CAAQS Comparison Highest 1-hour and 24-hour Average SO 2 Concentrations SO2 Concentrations (ppm) Averaging Time Period Wilmington Coastal Boundary San Pedro Source- Dominated CAAQS 1-hour 24-hour May April 2016 May April Summary of Monitoring for Ultrafine Particles Particulate matter is broadly classified as coarse PM with a diameter of 2.5 to 10 µm, or fine PM with a diameter of less than 2.5 µm. Ultrafine particles (UFP) are generally defined as those with a diameter less than 0.1 µm (100 nm or nanometers). Due to their small size, UFP generally make up a very small fraction of the ambient PM2.5 or PM10 mass, but constitute the majority of airborne particles by number. For example, a particle mass concentration of 10 µg/m 3 is equivalent to one particle per cm 3 for particulates with a diameter of 2.5 µm, but more than 2 million particles per cm 3 for particles of a diameter of 0.02 µm (SCAQMD, 2007) 7. UFP counts are typically in the range of 10,000 to 40,000 particles/cm 3 in urban air and 40,000 to 1,000,000 particles/cm 3 near freeways, because motor vehicles are a major source of UFP (SCAQMD, 2007). A sharp reduction in the UFP count has been shown to occur meters downwind of roadways (SCAQMD, 2007). Interest in UFP arises as several health-related studies have shown that the ultrafine portion of PM may be important in determining the toxicity of ambient particulates (SCAQMD, 2007). Because of the interest in this new parameter, the Port began initial monitoring for UFP counts in May The instrument selected for this task is the TSI Model 3783 and measures UFP in number of particles/cm 3. This annual report includes a summary of the five complete years of UFP data. Table 4-16 shows annual average UFP counts at the four stations during the last five years of monitoring. Annual average UFP counts have ranged between 4,560 to 14,800 particles/cm 3. 7 South Coast Air Quality Management District, Final 2007 Air Quality Management Plan. Diamond Bar, CA. Available at: 12 th Year Annual Air Quality Monitoring Report 25 September 2017

34 Historically, average UFP levels have been higher at the Source-dominated station and the two stations, in comparison to the Coastal Boundary station. There are heavily-travelled roadways in the proximity of all of these stations with the exception of the Coastal Boundary station, so it is likely these UFP levels reflect the influence of nearby traffic. Only the Coastal Boundary station did not record at least one hour when UFP counts exceeded 50,000 particles/cm 3. During the current year, there were some operational problems with the UFP monitoring instruments, and each of the instruments were sent back on a rotating schedule to the manufacturer for repairs, refurbishment and recalibration. This process took approximately six to eight weeks for each instrument, so the UFP data set at each station is missing a significant fraction of the total annual hours. Consequently, although the data set shows similar results to previous years, there is not as much confidence in the UFP data for as in earlier years. The three stations with heavily-travelled roads nearby (the Source-Dominated and stations) had quite variable UFP levels during the five years of record, but year-to-year changes at the three stations had similar patterns. Particle counts were moderately high at these stations in years and , considerably lower in years , , and in the current year It is not clear if this pattern results from external events, or if it simply reflects typical year-to-year variability in particle counts in the area. In contrast to the UFP patterns at the Source-Dominated and stations, annual average UFP counts at the Coastal Boundary station demonstrate a small but fairly consistent decrease over the five-year period of record. As mentioned above, there are no heavily-travelled roads in the vicinity of the Coastal Boundary station, and it is located adjacent to the ocean, so it has significantly lower exposure to localized sources of ultrafine particles. Table Annual Average Ultrafine Particle Counts Ultrafine Particle Counts (particles/cm 3 ) Period Wilmington Coastal Boundary San Pedro Source- Dominated May April ,800 6,600 12,700 12,100 May April ,800 6,300 8,000 9,000 May April ,000 5,400 14,000 12,400 May April ,500 4,800 8,300 9,700 May April ,900 4,600 8,300 9,100 Distribution of UFP Data Another manner to present UFP data is through the use of pollution roses, which plot hourly UFP data with the corresponding hourly wind direction. Pollution roses provide an indication of wind directions during periods of low and high UFP measurements. UFP pollution roses are also helpful in providing insight into the location of potential sources impacting a particular station. The concept is similar to a wind rose and provides a distribution of the UFP count levels by wind direction. Figures A-17 through A-20 provide UFP pollution plots for each station. To clarify the graphs, the UFP counts are subdivided into three color-coded categories: <25,000 particles/cm 3 (green); between 25,000 and 50,000 particles/cm 3 (blue); and >50,000 particles/cm 3 (red). Each point on the graph represents the average hourly UFP count (number/cm 3 ) and associated average wind direction during that hour. The distance the point is located from the center of the graph 12 th Year Annual Air Quality Monitoring Report 26 September 2017

35 represents the magnitude of the UFP count. The three concentric rings (representing 25,000, 50,000 and 100,000 particles/cm 3 ) help the interpretation of UFP levels on the graph. The largest number of high hourly UFP counts (>50,000 particles/cm 3 ) was measured to the northeast of the San Pedro station, in the direction of the ships berthed along the main ship channel, and to the northwest and north of the Wilmington station, in the direction of the heavilytravelled West Anaheim Street. The Coastal Boundary station has the greatest number of green dots (lowest UFP counts) and zero hours recording high UFP counts (>50,000 particles/cm 3 in red). This reinforces the discussion above, which indicates that the Coastal Boundary station is located in an area with less UFP sources. Detailed Daily Analysis of UFP Data During the last two months of the current reporting year (March - April 2017), all of the UFP instruments had been received back from the manufacturer in like-new, factory calibrated condition and reinstalled at each of the stations. Using the UFP count data during this time period, a detailed analysis is conducted to determine how daily UFP count data compared among the stations. Figure 4-1 presents the daily average UFP levels (in counts/cm 3 ) for all four of the stations during March and April The figure shows that daily average UFP levels exhibit wide variations from station-to-station with a minimum of approximately 1,300 counts/cm 3 at the Coastal Boundary station to a maximum of 32,000 counts/cm 3 at the San Pedro station. Figure 4-1. Daily Average Ultrafine Particle Counts during March - April 2017 Three other features of the UFP data set during this period are noteworthy: 1. UFP counts often show similar patterns of peaks and valleys. For example, all stations show short-term maximums on March 2 and March 7-8, with short-term minimums occurring on March th Year Annual Air Quality Monitoring Report 27 September 2017

36 2. The Source-Dominated and stations, all of which have heavilytravelled roads nearby, often show similar levels of UFP counts. 3. The Coastal Boundary station, in contrast, almost always has UFP concentrations well below the other stations, which shows the effect of its location some distance from major UFP sources. In summary, Figure 4-1 indicates that the UFP levels at all of the stations are likely impacted by regional events or general atmospheric conditions, and therefore show similar patterns of maximums and minimums on the same days. However, the Source-Dominated and stations are close to heavily-travelled roads, and localized PM emissions from mobile sources on these roads tend to increase ambient UFP levels at those stations well above those measured at the Coastal Boundary station, which is located a fair distance from major roadways Meteorological Data The meteorological data collected at each of the four stations are useful in interpreting the air quality data collected at each site. In addition, the meteorological data sets can be used in air dispersion modeling and other data analyses. Wind roses, which graphically illustrate the frequency and direction of wind speed at a site, have been constructed using the wind data collected by this monitoring program. By convention, winds are shown in the direction from which they came; for example, a west wind blows from the west. Data from the most recent reporting year ( ) were used to develop the wind roses that are projected on the Port base map in Figure Wind roses were also created using the meteorological data collected at each station for the current monitoring year, and are shown in Appendix A-1 as Figures A-21 through A-24. The wind roses at each station during the reporting period of are very similar to the historical wind roses from earlier years, showing that year-to-year annual wind flow patterns are quite consistent. However, the predominant wind patterns at the individual stations are considerably different, indicating that the San Pedro Bay Ports area experiences complex air flow patterns. The wind data is therefore an important component in improving our understanding of how local emissions are dispersed. 8 The wind speed scale typically included with a wind rose is not shown on Figure 4-1 for clarity. The full wind roses, with wind speed scales included, are provided in Figures A-16 to A-19 in Appendix A th Year Annual Air Quality Monitoring Report 28 September 2017

37 Figure 4-2. Wind Roses for Port Air Monitoring s: May 2016 to April th Year Annual Air Quality Monitoring Report 29 September 2017

38 4.3 DATA QUALITY ASSURANCE A number of quality assurance (QA) measures have been incorporated into both the real-time and filter-based components of this monitoring program to ensure that the air quality and meteorological data collected by this network is representative of the San Pedro Bay region. These QA measures are a combination of automated and manual processes, and include: Real-Time Gaseous and PM Measurements: 1. Daily zero and span calibrations are performed (at 2 AM) on all gaseous instrumentation deployed in the monitoring program. 2. Daily review of the previous day s monitoring data and calibration performance by the program s Operations & Maintenance (O&M) Manager. 3. The program s Onsite Field Technician performs manual checks on all real-time air quality and meteorological instruments on a 3-day basis, when the technician is onsite performing filter setup for particulate matter sampling days. 4. The program s data logging system provides a series of electronic data validation filters, as well as remote tracking of the operation of each individual instrument s internal components for preventative maintenance (e.g. - sample flows, pump performance, high voltage power supply, UV lamp performance, etc.). 5. The program s Onsite Field Technician performs a Monthly Maintenance and Cleaning Procedure where all pertinent instrument flows are checked/calibrated and cleaning procedures are performed on all gaseous and PM inlets, as well as the sample manifold. 6. Monthly QA review of all real-time air quality and meteorological data collected in the monitoring program is conducted by both the O&M Manager and the Technical QA Officer. 7. Upon completion of the monthly data review, the QA d air quality and meteorological data are uploaded to the Port s CAAP website ensuring that representative, QA d data is being reported on the real-time website. The QA d data for the previous month is generally uploaded during the first week of each month. Filter-Based PM Measurements: 1. Co-located monitors are installed at the Wilmington station to validate the operation of the filter-based monitors. The Desert Research Institute (DRI) SFS instruments deployed at each site for PM2.5 speciation samples are not FRM monitors. At the Wilmington station, PM2.5 and PM10 FRM monitors are co-located with the SFS instruments to validate the operation of and the data collected by the SFS monitors in the Port s monitoring network. 2. Field blanks are periodically taken at each monitoring station to ensure that there was no systematic contamination of the filters. 3. Monitoring checklists are routinely completed by the field technicians during every station visit, conducted on the EPA s three-day PM sampling schedule. These monitoring checklists include flow checks before and after each sampling period to ensure the flow rates recorded for each sample day are correct. 4. Bi-monthly review of all filter-based PM measurements by the program s O&M Manager and Technical Director/QA Officer. Independent Semi-Annual Audits: 1. Independent semi-annual audits of all instruments in the monitoring program (both air quality and meteorological) are performed by an independent contractor twice per year. 12 th Year Annual Air Quality Monitoring Report 30 September 2017

39 5 Trend Analysis With twelve years of data for the filter-based monitors and eight years of data for the real-time instruments, an analysis of overall air quality data trends was conducted. This analysis uses annual averages to assess long-term trends in the datasets, even if there are no annual standards for a particular pollutant. Ambient air pollution levels near the San Pedro Bay are influenced by a number of factors including local pollutant emissions, regional air pollution levels, and meteorology. Several important criteria air pollutants (i.e., ozone, PM2.5) are created, in whole or in part, by chemical reactions which occur after the release of emissions into the atmosphere. As such, concentrations from these pollutants are expected to be more regional in nature. Others pollutants, like SO2, are more localized and can be directly influenced by nearby emissions sources. Based on the latest available Port Emissions Inventory, emissions from mobile sources operating at the Port are estimated to contribute approximately 4.5% of the regional nitrogen oxide (NOX) emissions and 4.4% of the regional DPM emissions in 2016; the regional contribution of NOx and DPM emissions from mobile sources operating at the Port has been relatively constant during recent years while the Port s contribution to regional SOx emissions continues to trend lower. 9 Between 2005, the CAAP baseline year, and 2016, emissions associated with Port of Los Angeles operations showed an 87% reduction in DPM, a 98% reduction in sulfur oxides (SOx) and a 57% reduction in NOx. These emission reductions were due to a number of factors including the successful implementation of control measures under the CAAP and voluntary tenant actions, along with state regulatory action, which have significantly reduced emissions rates from goods movement sources such as heavy duty trucks, ocean going vessels, and cargo handling equipment. Over the same timeframe, container throughput at the Port has increased by approximately 18% since 2005, the CAAP baseline year. Meteorology can also have a significant influence on regional air pollution levels from one year to the next. So while CAAP measures have decreased air emission levels, it is not presently known how much of any decrease (or increase) in ambient air pollutant concentrations measured at the Port air monitoring stations can be directly attributed to the Port s goods movement-focused control measures under the CAAP. 5.1 TRENDS IN EC, BC, PM2.5, AND PM10 DATA Twelve years of EC, PM2.5, and PM10 data are now available from the Port s air monitoring network, which allow for trend analysis over the period of record for PM data from the network. Figures 5-1 through 5-4 present the annual and maximum hourly averages EC, PM2.5, and PM10 data collected by the filter-based monitors in the Port s air monitoring network over the 12-year period of record. BC is a pollutant for which monitoring has been conducted only over the last three years. Consequently, the BC dataset is not as extensive as the other PM parameters measured in this monitoring program; however, BC is an important pollutant as it is considered a surrogate for DPM and the initial trends evident in the BC dataset show some interesting characteristics Trends in EC Concentrations Figure 5-1 shows that annual average EC concentrations have decreased significantly over the 12- year monitoring record at the four Port stations. These data are shown in Table A-1 as well. Reductions in annual average EC concentrations over the period of record range from 60 percent at the San Pedro station to 79 percent at the Source-Dominated station. The average reduction in annual EC concentrations is 66 percent across the four-station monitoring network. For 9 Port of Los Angeles Inventory of Air Emissions Starcrest Consulting Group LLC. ( July th Year Annual Air Quality Monitoring Report 31 September 2017

40 the period of record, the 66 percent decrease in EC concentrations is greater than the 46 percent reduction in PM2.5 levels over the same period (Figure 5-7). Figure 5-1. Annual Average EC Concentrations over the Period of Record As previously discussed, EC is considered as a surrogate for DPM. With the 12-year EC dataset, analysis can be performed to estimate of how well measured EC concentrations track with DPM emissions. This analysis employs the Port s Emissions Inventory (EI) to compare reductions in DPM emissions from mobile sources operating at the Port in against measured reductions in EC concentrations over the same time period. Annual EC levels show a consistent trend of decreasing concentrations from the to the reporting periods. After remaining more-or-less flat for several years (with considerable variability) annual average EC concentrations have been decreasing again over the last three years at the Wilmington and San Pedro and Source-Dominated stations. The substantial overall decrease during the 12-year period of record is likely at least partly a reflection of reductions in DPM emissions as a result of the emission control measures implemented by the CAAP program. This hypothesis is supported by the observed data in the Port s monitoring program and the largest decrease in annual EC concentrations (79 percent over the period of record) is observed at the Source-Dominated station, which is located near the center of Port operations. Over the period of record, the larger decrease in annual average EC concentrations compared to other PM parameters, such as PM2.5 and PM10, may be due to the more localized nature of elemental carbon. It appears that the EC concentrations measured in the Port s monitoring network tend to be more sensitive to nearby emission sources than either PM2.5 or PM10. Although EC data are collected at all four stations, data collected at the Source-Dominated station located near the center of Port activity should be most representative of EC levels for Port-related operations. However there are a number of reasons why this analysis is not exact: 12 th Year Annual Air Quality Monitoring Report 32 September 2017

41 1) The variety of DPM emission sources in the area (e.g., non-port-related vehicle emissions); 2) The nature of widely-scattered, individual DPM emission sources around the Port versus passive EC monitoring with measurements collected at a single location; and 3) The influence of long-term meteorological patterns on the dispersion of DPM emissions. Regardless, there appears to be a positive correlation between DPM emission reductions and reductions in measured EC concentrations at the Port monitoring stations. From 2005 to 2016 (the latest available year for Port emissions), annual DPM emissions decreased by 87 percent, while annual average EC measurements at the Source-Dominated station from monitoring year to monitoring year decreased by 79 percent (Table A-1). Thus, EC measurements at the Port appear to track DPM emission reductions well Trends in BC Concentrations Black carbon data is collected only at the Source-Dominated station in the POLA monitoring network. At the conclusion of this reporting period, there is now four years of BC data available at the Port s Source-Dominated station, in addition to longer BC data sets available from POLB s Inner Harbor and Outer Harbor stations. These data sets allow POLA s four-year BC data set to be compared with the most recent four years of the EC data set, to see if the two pollutants show similar measurement patterns. As discussed earlier, BC and EC data are used by the SCAQMD as surrogates for DPM and measurements are often well-correlated. These two parameters are collected using two different monitoring techniques, so a comparison of trends in the BC and EC data sets over the same time period should indicate how well the measurements compare across the Ports networks. BC data, which is collected using a real-time Aethalometer, has an advantage over the EC data in that it is collected with much greater temporal resolution (1-minute readings, then averaged into 1-hour concentrations) versus the 24-hour integrated EC measurement. This allows additional analyses to be conducted using the BC data since the temporal resolution of the BC data provides additional insight into daily trends, such as diurnal variation(s) or time-of-day peaks. Figure 5-2 shows the annual average BC concentrations measured at the Port s Source-Dominated station over the four-year period of record, along with BC data from the POLB stations. Annual average BC concentrations shown in Figure 5-2 illustrate a trend of steady decreases over the four year period at all three stations. Figure 5-1 shows a similar pattern of decreasing EC concentrations in POLA s monitoring network. 12 th Year Annual Air Quality Monitoring Report 33 September 2017

42 Figure 5-2. Annual Average BC Concentrations over the Period of Record In addition to the general patterns seen within both Ports monitoring networks, the simultaneous collection of BC and EC data at POLA s Source-Dominated station allows a direct comparison of BC and EC trends over the past four years. Tables 4-2 and 4-3 present average annual EC and BC concentrations, respectively, at the Source-Dominated station. Over the most recent four years at the Source-Dominated station, annual average BC concentrations have decreased by 39 percent while annual average EC concentrations have decreased by 41 percent. This similar, decreasing trend in annual average EC and BC concentrations over the four-year period indicates that ambient concentrations of DPM emission surrogates continue to decrease near the center of Port operations Trends in PM2.5 Concentrations Annual average PM2.5 concentrations at each station over the current monitoring year are shown in Figure 5-3, below. The figure shows that annual average PM2.5 concentrations have varied considerably over the 12-year monitoring record. However across the four Port stations, annual average PM2.5 concentrations have decreased by 46 percent over the period of record. The measured reduction in annual average PM2.5 concentrations ranges from a 50 percent decrease at the Source- Dominated station to 42 percent decreases at the Wilmington and San Pedro stations. The slightly larger decrease in PM2.5 concentrations at the Source-Dominated station may reflect, at least in part, the improved emission controls on Port-related operations. The average 46 percent reduction in measured PM2.5 concentrations across the Port air monitoring stations is considerably less than the 85 percent reduction in Port-wide PM2.5 emissions during the period. This difference may be partially due to the fact that PM2.5 measurements are collected at four fixed monitoring stations, whereas the PM2.5 emissions inventory is calculated for the entire Port area. 12 th Year Annual Air Quality Monitoring Report 34 September 2017

43 However, there is another complicating factor to drawing a direct comparison between PM2.5 emission estimates and measured PM2.5 concentrations. PM2.5 is largely considered a regional pollutant with a considerable fraction of ambient PM2.5 concentrations produced by secondary sources. These secondary sources of PM2.5 are formed through chemical reactions in the atmosphere, rather than direct PM2.5 emissions. An example of these chemical reactions are when gases, such as SOx and NOx, are emitted into the atmosphere and undergo chemical reactions to form sulfate and nitrate particulates. This secondary formation process takes time, so secondary PM2.5 material is generally present some distance downwind of the sources. Thus, the localized PM2.5 emission reduction measures instituted by the Port are expected to have less of an impact on ambient PM2.5 levels due to the presence of existing regional sources leading to secondary PM2.5 formation. This is especially evident when compared to pollutants with a more localized signature. It appears that because EC is more localized in nature, the Port-focused emission reduction measures in the CAAP have been more effective in reducing ambient EC levels compared to PM2.5. During the last eight years, annual average PM2.5 concentrations have been below the NAAQS and CAAQS (12 µg/m 3 ) at all stations. These data are also shown in Table A-3. Figure 5-3 illustrates the decreasing trend in annual average PM2.5 concentrations over the period of record. The decreasing trend is fairly consistent over the five-year period from to ; however, over the past seven monitoring years ( to ), annual average PM2.5 concentrations have remained relatively flat, with occasional year-to-year increases (in and ), but with notable decreases in the past two years ( and ). Figure 5-3. Annual Average PM 2.5 Concentrations over the Period of Record * Coastal Boundary station SFS data incomplete for Year 11. * Sample data at Coastal Boundary station unavailable from November 2015 through April 2016 due to an instrument issue. Figure 5-4 shows the 98 th percentile of 24-hour averaged PM2.5 concentration over the 12-year period of record. Overall, these values have varied, from a 51 percent decrease at the Source-Dominated station to a 29 percent decrease at the San Pedro station. This trend is similar to the 12 th Year Annual Air Quality Monitoring Report 35 September 2017

44 decreases observed in annual average PM2.5 concentrations. The 98 th percentile values are presented to be consistent with the form of the 24-hour NAAQS standard. The 98 th percentile of 24-hour average PM2.5 concentrations for the filter-based samplers is the second-highest measurement in a year, and thus it is much more sensitive to the highest concentrations measured within a given year than is the overall annual average. Consequently, there is more variability shown within the period of record at each station in Figure 5-4 (98 th percentile) than in Figure 5-3 (annual average). Nevertheless, the general trend of lower PM2.5 concentrations over the period of record is evident in the figure. Figure th Percentile of 24-hour Averaged PM 2.5 Concentrations over the Period of Record * Coastal Boundary station SFS data incomplete for Year 11. * Sample data at Coastal Boundary station unavailable from November 2015 through April 2016 due to an instrument issue Trends in PM10 Concentrations Figure 5-5 shows that annual average PM10 concentrations at the Wilmington station decreased over the first six years (through 2011) of the 12-year period of record, followed by an increase in , and then a moderate decrease over the past five years. Overall, there has been a 15 percent decrease in PM10 concentrations over the 12-year monitoring record. No distinct year-to-year trend is clearly apparent and annual average PM10 concentrations have been variable over the period of record. The increase in annual average PM10 concentrations in monitoring Year 7 ( ) is believed to be a result of extensive, long-term construction projects near the stations during that year. Localized activities such as construction projects typically produce large quantities of fugitive emissions, which can cause significant increases in PM10 measurements. Annual average PM10 concentrations at both stations over the period of record are shown in Figure 5-5, below (the period of record for the Coastal Boundary station is 7 years). Figure 5-5 illustrates that 12 th Year Annual Air Quality Monitoring Report 36 September 2017

45 most of the decrease in PM10 concentrations has occurred during the three-year period from through , with the increases measured in the monitoring year likely due to construction activities, as discussed earlier. Figure A-10 in Appendix A-1 shows monthly average PM10 concentrations over the period of monitoring record. There is less of a seasonal trend in PM10 concentrations compared to PM2.5 concentrations, which may be due to the characteristics of PM10 emissions sources (primarily fugitive emissions from construction activities, open areas, and roads). Figure 5-5. Annual Average PM 10 Concentrations over the Period of Record Figure 5-6 shows the maximum 24-hour PM10 concentrations at the Wilmington and Coastal Boundary stations over the period of record. It is evident from the figure that the maximum PM10 concentrations measured within a year show greater year-to-year variability than the annual PM10 concentrations. This is likely because the maximum concentrations within a year will result from specific, infrequent, outlier conditions or events, rather than long-term pollutant trends. For example, the highest PM10 concentrations ever recorded during the program occurred in October and November 2007 under unusual conditions, when large wildfires were present throughout southern California. The second highest PM10 concentrations were measured during the year, and were a result of a large weekend carnival that was held in May at the St. Peter and Paul School, where the Wilmington is located. Therefore, the maximum 24-hour PM10 concentrations tend to be dependent on specific events or conditions, and are not necessarily indicative of overall trends in PM10 levels. 12 th Year Annual Air Quality Monitoring Report 37 September 2017

46 Figure 5-6. Maximum 24-hour Average PM 10 Concentrations over the Period of Record 12 th Year Annual Air Quality Monitoring Report 38 September 2017

47 5.2 TRENDS IN GASEOUS CRITERIA POLLUTANTS Real-time instruments measuring gaseous criteria pollutants were installed and operational in early Nine complete years are available to evaluate data trends for gaseous criteria pollutants Trends in CO Concentrations Figure 5-7 presents the maximum 1-hour CO concentrations measured at the four stations within the Port s air monitoring network over the nine-year period that the real-time instrumentation has been operational. These data are also shown in Table A-10. Figure 5-7. Maximum 1-hour CO Concentrations over the Period of Record The maximum 1-hour CO concentrations show no discernible trend, with all stations showing relatively low maximum CO concentrations throughout the period of record. This is likely reflective of the lack of large CO sources present around the monitoring stations. All 1-hour maximum values are well below the 1-hour CO NAAQS of 35 ppm and 1-hour CO CAAQS of 20 ppm. 12 th Year Annual Air Quality Monitoring Report 39 September 2017

48 Figure 5-8 presents the maximum 8-hour CO concentrations measured at the four stations within the Port s air monitoring network over the nine-year period of monitoring record. These data are also shown in Table A-11. The maximum 8-hour CO concentrations also show no discernible trend, and all of the 8-hour maximum values are well below the 8-hour CO NAAQS and CAAQS of 9 ppm. Because these concentrations are the highest daily values recorded during a year, they are likely to be more variable from year to year. Figure 5-8. Maximum 8-hour CO Concentrations over the Period of Record 12 th Year Annual Air Quality Monitoring Report 40 September 2017

49 5.2.2 Trends in NO2 Concentrations Figure 5-9 presents the 98 th percentile of the daily maximum 1-hour NO2 concentrations at the four stations in the Port s air monitoring network over the nine-year period of record. These data are also shown in Table A-13. The figure shows a moderate decrease in the 98 th percentile of daily maximum 1-hour NO2 concentrations over the nine-year period of record. During the current reporting year, these daily maximum NO2 concentrations were below the applicable NAAQS. The 98 th percentile daily maximum 1-hour NO2 concentrations in a given year can be very sensitive to a few high measurements. For example, a detailed review of the data during the reporting year showed that the maximum 1-hour NO2 concentrations ever recorded during this monitoring program occurred at the San Pedro station during December This may have been a result of repaving the parking lot that is adjacent to the station, which occurred during that time period. Therefore, it is likely that the higher NOx concentrations measured during that year were probably an anomaly due to the unusual construction activity near the San Pedro station. In subsequent years, the 98 th percentile daily maximum 1-hour NO2 concentrations have dropped considerably at that station. Figure th Percentile of the Daily Maximum 1-hour NO 2 Concentration over the Period of Record 12 th Year Annual Air Quality Monitoring Report 41 September 2017

50 Figure 5-10 presents maximum 1-hour NO2 concentrations at the four stations in the Port s air monitoring network over the nine-year period of record. These data are also shown in Table A-14. Similar to the data presented in Figure 5-9, the maximum hourly NO2 concentrations were highest at the San Pedro station during the year. This appears to be an anomaly, as discussed above. The maximum 1-hour NO2 concentrations appear to show a slight decrease over the nine-year period of record. Figure Maximum 1-hour NO 2 Concentrations over the Period of Record 12 th Year Annual Air Quality Monitoring Report 42 September 2017

51 Figure 5-11 presents the annual average NO2 concentrations at the four stations over the nine-year period of record. These data are also shown in Table A-15. The annual NO2 concentrations have not exceeded the NAAQS or CAAQS during the period of record. There has been a moderate decrease in annual average NO2 concentrations over the nine-year period of record, ranging from 15 to 27 percent. Figure Annual NO 2 Concentrations over the Period of Record 12 th Year Annual Air Quality Monitoring Report 43 September 2017

52 5.2.3 Trends in O3 Concentrations Figure 5-12 presents the fourth-highest average 8-hour O3 concentrations at the four stations in the Port s air monitoring network over the nine-year period of monitoring record. These data are also shown in Table A-17. Very small trends in O3 concentrations are observed at the individual stations during this period, ranging from a decrease of 10 percent to an increase of 13 percent. Because O3 is a secondary pollutant that takes several hours to form from volatile organic compounds and nitrogen oxides in the presence of sunlight, ozone concentrations are more reflective of regional air quality pollutant levels in the SCAB rather than localized pollutant levels. The decrease in the 8-hour O3 NAAQS, depicted as a dotted red line in Figure 5-12, reflects the revised, lower standard promulgated by EPA in October Figure Fourth Highest Average 8-hour O 3 Concentrations over the Period of Record 12 th Year Annual Air Quality Monitoring Report 44 September 2017

53 Figure 5-13 presents the maximum 8-hour O3 concentration for the nine-year period of record. These data are also shown in Table A-19. The maximum 8-hour concentrations have shown a decrease at each station during the period of record, ranging from 17 percent at the Wilmington station to 26 percent at the Source-Dominated station. Figure Maximum 8-hour O 3 Concentrations over the Period of Record 12 th Year Annual Air Quality Monitoring Report 45 September 2017

54 Figure 5-14 presents the maximum 1-hour O3 concentrations at the four sites for the nine-year period of record. These data are also shown in Table A-18. The maximum 1-hour concentrations do not show a consistent pattern, with highest concentrations measured at all stations in , but relatively similar concentrations for the rest of the period of record, with no consistent trend. Because O3 is generally more of a regional pollutant, and the maximum 1-hour concentrations are based upon the highest measurement occurring at a site within a year, it is difficult to draw any conclusions from these data. Figure Maximum 1-hour O 3 Concentrations over the Period of Record 12 th Year Annual Air Quality Monitoring Report 46 September 2017

55 5.2.4 Trends in SO2 Concentrations Figure 5-15 presents the 99 th percentile of the 1-hour daily maximum SO2 concentrations at the four stations in the Port s air monitoring network over the nine-year period of record. These data are also shown in Table A-21. The figure shows that although there were some yearly fluctuations in maximum SO2 concentrations, there is an overall pattern of decreasing concentrations. During this nine-year period, the 1-hour daily maximum SO2 concentrations decreased an average of 47 percent across the four stations. Figure th Percentile of 1-hour Daily Maximum SO 2 Concentrations over Period of Record 12 th Year Annual Air Quality Monitoring Report 47 September 2017

56 Figure 5-16 presents the maximum 1-hour SO2 concentration for the nine-year period of record. These data are also shown in Table A-22. The maximum 1-hour concentrations vary considerably among the stations and from year-to-year, as might be expected when considering a maximum 1-hr SO2 concentration. The highest maximum 1-hr SO2 concentration was measured during at the Coastal Boundary station and likely occurred during a short-term berthing of a ship at Berth 47, which is adjacent to the Coastal Boundary station. Figure Maximum 1-hour SO 2 Concentrations over the Period of Record 12 th Year Annual Air Quality Monitoring Report 48 September 2017

57 Figure 5-17 presents the maximum 24-hour SO2 concentrations at the four sites for the nine-year period of record. These data are also shown in Table A-23. Maximum 24-hour SO2 concentrations over the period of record have dropped from 47 percent at the San Pedro station to 68 percent at the Wilmington station during the period of record. Figure Maximum 24-hour SO 2 Concentration over the Period of Record 12 th Year Annual Air Quality Monitoring Report 49 September 2017

58 6 Conclusions This report presents a summary of the monitoring data collected by the Port s air quality monitoring program during the 12-month period from May 2016 to April In addition, data trends are presented for filter (PM/EC) measurements for the entire 12-year period of monitoring record (May April 2017) and for gaseous criteria pollutant data for the 9-year period of monitoring record (May April 2017). BC data and trend analysis over the last four years are presented and subsequently compared to similar trends in the filter-based EC measurements, since both pollutants are considered surrogates for DPM emissions. During the current monitoring period there were no exceedances of a NAAQS. However, there were a few exceedances of the more restrictive CAAQS observed in the Port s monitoring program: The annual PM10 CAAQS was exceeded based on the filter-based measurements from the SFS monitors at both the Coastal Boundary and Wilmington stations. The 8-hour O3 CAAQS was exceeded at the Coastal Boundary station. The SCAB has been designated by EPA as a nonattainment area for both ozone and PM2.5, and is designated as a maintenance area for PM10. Average decreases of 43 and 66 percent in annual average PM2.5 and EC concentrations, respectively, have been measured across the four-station monitoring network over the 12-year period of record. BC concentrations in the 4-year period of BC monitoring show a reduction of 39 percent between and No significant change is observed in annual average PM10 concentrations over the same time period. 12 th Year Annual Air Quality Monitoring Report 50 September 2017

59 Appendix A Port of Los Angeles Monitoring Program Annual Report May April 2017 Figures and Tables

60 Appendix A1 Port of Los Angeles Monitoring Program Annual Report May April 2017 Summary Figures of Monitoring Results

61 Appendix A-1 Table of Contents Figure Page Figure A-1. Annual Average Filter-Based Elemental Carbon Concentrations at POLA Monitoring Years A-1 Figure A-2. Monthly Average Filter-Based Elemental Carbon Concentrations at POLA May 2016 April A-2 Figure A-3. Monthly Average Filter-Based Elemental Carbon Concentrations at POLA February 2005 April A-3 Figure A-4. Annual Average Filter-Based PM 2.5 Concentrations at POLA Monitoring Years A-4 Figure A-5. Monthly Average Filter-Based PM 2.5 Concentrations at POLA May 2016 April A-5 Figure A-6. Monthly Average Filter-Based PM 2.5 Concentrations at POLA February 2005 April A-6 Figure A-7. Monthly Average BAM PM 2.5 Concentrations at POLA May 2016 April A-7 Figure A-8. Annual Average Filter-Based PM 10 Concentrations at POLA Monitoring Years A-8 Figure A-9. Monthly Average Filter-Based PM 10 Concentrations at POLA May 2016 April A-9 Figure A-10. Monthly Average Filter-Based PM 10 Concentrations at POLA February 2005 April A-10 Figure A-11. Monthly Average BAM PM 10 Concentrations at POLA May 2016 April A-11 Figure A-12. Monthly Average CO Concentrations at POLA May 2016 April A-12 Figure A-13. Monthly Average NO 2 Concentrations at POLA May 2016 April A-13 Figure A-14. Monthly Average O 3 Concentrations at POLA May 2016 April A-14 Figure A-15. Monthly Average SO 2 Concentrations at POLA May 2016 April A-15 Figure A-16. Monthly Average BC Concentrations at POLA and POLB May 2016 April A-16 Figure A-17. Coastal Boundary Ultrafine Particle Count Pollution Rose May 2016 April A-17 Figure A-18. San Pedro Ultrafine Particle Count Pollution Rose May 2016 April A-18 Figure A-19. Wilmington Ultrafine Particle Count Pollution Rose May 2016 April A-19 Figure A-20. Source-Dominated Ultrafine Particle Count Pollution Rose May 2016 April A-20 Figure A-21. Coastal Boundary Year 12 Wind Rose... A-21 Figure A-22. Source-Dominated Year 12 Wind Rose... A-22 Figure A-23. Wilmington Year 12 Wind Rose... A-23 Figure A-24. San Pedro Year 12 Wind Rose... A-24

62 Figure A-1 Annual Average Elemental Carbon Conc. (µg/m 3 ) Annual Average Filter-Based Elemental Carbon Concentrations at the Port of Los Angeles (Monitoring Years 1-12) Wilmington Coastal Boundary San Pedro Source-Dominated 0 May 05 - Apr 06 May 06 - Apr 07 May 07 - Apr 08 May 08 - Apr 09 May 09 - Apr 10 May 10 - Apr 11 May 11 - Apr 12 May 12 - Apr 13 May 13 - Apr 14 May 14 - Apr 15 May 15 - Apr 16 May 16 - Apr 17 Year A-1

63 Elemental Carbon Concentration (µg/m 3 ) Figure A-2 Monthly Average Filter-Based Elemental Carbon Concentrations at the Port of Los Angeles (May April 2017) Wilmington Coastal Boundary San Pedro Source-Dominated 0 Month A-2

64 Elemental Carbon Concentration (µg/m 3 ) Figure A-3 Monthly Average Filter-Based Elemental Carbon Concentrations at the Port of Los Angeles (February April 2017) Wilmington Coastal Boundary San Pedro Source-Dominated 0 Month A-3

65 Annual Average PM 2.5 Conc. (µg/m 3 ) Figure A-4 Annual Average Filter-Based PM 2.5 Concentrations at the Port of Los Angeles (Monitoring Years 1-12) Coastal Boundary San Pedro Wilmington Source-Dominated Annual Average NAAQS/CAAQS 0 May 05 - Apr 06 May 06 - Apr 07 May 07 - Apr 08 May 08 - Apr 09 May 09 - Apr 10 May 10 - Apr 11 Year May 11 - Apr 12 May 12 - Apr 13 May 13 - Apr 14 May 14 - Apr 15 May 15 - Apr 16 May 16 - Apr 17 A-4

66 Figure A-5 30 Monthly Average Filter-Based PM 2.5 Concentrations at the Port of Los Angeles (May April 2017) Coastal Boundary San Pedro Wilmington Source-Dominated Annual Average NAAQS/CAAQS PM 2.5 Concentration (µg/m 3 ) Month Note: Coastal Boundary SFS data incomplete for Year 12. Sample data unavailable for May and June of 2016 due to an instrument issue. A-5

67 PM 2.5 Concentration (µg/m 3 ) Figure A-6 Monthly Average Filter-Based PM 2.5 Concentrations at the Port of Los Angeles (February April 2017) Coastal Boundary San Pedro Wilmington Source-Dominated Annual Average NAAQS/CAAQS 0 Month Note: On Dec. 14, 2012 the US EPA changed the annual NAAQS from 15 µg/m 3 to 12 µg/m 3.. A-6

68 Figure A-7 PM 2.5 Concentration (µg/m 3 ) Monthly Average BAM PM 2.5 Concentrations at the Port of Los Angeles (May April 2017) Coastal Boundary San Pedro Wilmington Source-Dominated Annual Average NAAQS/CAAQS 0 Month Note: Coastal Boundary and San Pedro s data incomplete for Year 12. Sample data unavailable for August 2016 at Coastal Boundary and November 2016 at San Pedro due to instrument issues. A-7

69 Figure A-8 50 Annual Average Filter-Based PM 10 Concentrations at the Port of Los Angeles (Monitoring Years 1-12) Coastal Boundary Wilmington Annual Average CAAQS Annual Average PM 10 Conc. (µg/m 3 ) May 05 - Apr 06 May 06 - Apr 07 May 07 - Apr 08 May 08 - Apr 09 May 09 - Apr 10 May 10 - Apr 11 Year May 11 - Apr 12 May 12 - Apr 13 May 13 - Apr 14 May 14 - Apr 15 May 15 - Apr 16 May 16 - Apr 17 A-8

70 Figure A-9 50 Monthly Average Filter-Based PM 10 Concentrations at the Port of Los Angeles (May April 2017) Coastal Boundary Wilmington Annual Average CAAQS 40 PM 10 Concentration (µg/m 3 ) Month Note: Coastal Boundary data incomplete for Year 12. Sample data unavailable for July through September of 2016 due to a temporary operational change. A-9

71 Figure A Monthly Average Filter-Based PM 10 Concentrations at the Port of Los Angeles (February April 2017) Coastal Boundary Wilmington Annual Average CAAQS PM 10 Concentration (µg/m 3 ) Month Notes: Monitoring for PM10 at the Coastal Boundary began in August of Coastal Boundary data incomplete for Year 12. Sample data unavailable for July through September of 2016 due to a temporary operational change. A-10

72 Figure A-11 PM 10 Concentration (µg/m 3 ) Monthly Average BAM PM 10 Concentrations at the Port of Los Angeles (May April 2017) Coastal Boundary San Pedro Wilmington Source-Dominated Annual CAAQS 0 Month A-11

73 Figure A Monthly Average CO Concentrations at the Port of Los Angeles (May April 2017) Coastal Boundary San Pedro Wilmington Source-Dominated CO Concentration (ppm) Month A-12

74 Figure A Monthly Average NO 2 Concentrations at the Port of Los Angeles (May April 2017) Coastal Boundary San Pedro Wilmington Source-Dominated NO 2 Concentration (ppm) Month Note: Coastal Boundary data missing from February through March of 2017 due to an ongoing instrument issue. A new instrument was deployed at this station on April 24, A-13

75 Figure A Monthly Average O 3 Concentrations at the Port of Los Angeles (May April 2017) Coastal Boundary San Pedro Wilmington Source-Dominated O 3 Concentration (ppm) Month A-14

76 Figure A Monthly Average SO 2 Concentrations at the Port of Los Angeles (May April 2017) Coastal Boundary San Pedro Wilmington Source-Dominated SO 2 Concentration (ppm) Month Note: Coastal Boundary data missing from February through April of 2017 due to an ongoing instrument issue. A new instrument was deployed at this station on June 22, A-15

77 Figure A-16 5 Average Monthly BC Concentrations at Ports of Los Angeles and Long Beach (May April 2017) POLB - Outer Harbor POLB - Inner Harbor POLA - Source Dominated Black Carbon Concentrations (µg/m 3 ) Day of the Week A-16

78 Figure A-17 Coastal Boundary Ultrafine Particle Count Pollution Rose (May 2016 April 2017) 0 [UFP] = 100,000 #/cm 3 25,000 50, UFP Concentration (#/cm 3 ) Berth 47 Wind Rose [UFP] < 25,000 25,000 < [UFP] < 50,000 50,000 < [UFP] 90 A-17 WIND SPEED (m/s) >= Calms: 2.60%

79 Figure A-18 San Pedro Ultrafine Particle Count Pollution Rose (May 2016 April 2017) 0 [UFP] = 100,000 #/cm 3 25,000 50, UFP Concentration (#/cm 3 ) Berth 87 Wind Rose [UFP] < 25,000 25,000 < [UFP] < 50,000 50,000 < [UFP] 90 A-18 WIND SPEED (m/s) >= Calms: 7.60%

80 Figure A-19 Wilmington Ultrafine Particle Count Pollution Rose (May 2016 April 2017) 0 [UFP] = 100,000 #/cm 3 25,000 50, UFP Concentration (#/cm 3 ) SPPS Wind Rose [UFP] < 25,000 25,000 < [UFP] < 50,000 50,000 < [UFP] 90 A-19 WIND SPEED (m/s) >= Calms: 9.13%