Interplay of Wind Pattern and Air Pollutant Emissions on Air Pollution Dispersion in the San
Francisco Bay Area
Understanding the influence meteorology and air pollutant emissions has on air pollution
transport
A senior thesis submitted to the Urban Studies and Planning Program
University of California, San Diego
Henry Pan
USP 187
hepan@ucsd.edu
February 7, 2012
Abstract
The meteorological phenomenon of wind patterns in the San Francisco Bay Area
was analyzed with emission inventory data in order to determine how these two
factors interplay in determining air pollution dispersion in the region. It is
believed that the wind patterns in the San Francisco Bay Area region do have an
impact on the dispersion of air pollution. This study reinforces this theory by
analyzing and integrating data on the wind patterns, topography, and emission
inventories of the region and illustrating the results on a geospatial map created
with the Geographic Information System. The paper presents evidence that the
wind paths determined by the topography of the San Francisco Bay Area region
do influence air pollution dispersion in which the pollutants generally travelled
from the coastal region into the inland region.
Key Terms: air quality, wind pattern, dispersion, San Francisco Bay Area
Introduction
Air pollution is a regional issue that has the potential of crossing multiple jurisdictions
and affecting numerous adjacent regions. Because the dispersion of air pollutant is a
geographical issue, the unique wind patterns pertaining to a given region can greatly determine
the strength of the dispersion. With the highly populated density of the San Francisco Bay Area,
it is important to understand the movement of air pollutants such as particulate matter 2.5
because these particulates may cause adverse health and environmental issues, requiring the
health-sensitive residents to be on constant alert to any changes in pollutant concentration in any
given day. In response to the importance of understanding air pollutant dispersion, this study
Pan 2
seeks to understand how the unique wind patterns in the San Francisco Bay Area can influence
air pollution accumulation and concentration in the coastal and inland regions and to provide
quantitative analytical evidence for promoting greater regional governance as opposed to
individual municipal governance.
In order to understand this meteorological phenomenon, I will examine the specific wind
patterns in the San Francisco Bay Area and the point sources and area sources of pollutant
emissions in the regions with specific interest in tracking PM 2.5 emissions. Because PM 2.5 can
travel great distances due to its small weight, wind pattern is a significant factor in the dispersion
of this particulate (BAAQMD 2012). Therefore, the emission of PM 2.5 becomes a regional
matter, crossing multiple jurisdictions.
In respect to the growing urbanization of the region, it is also important to study the
relationship between wind patterns and air pollution concentration in the San Francisco Bay Area
so we can better understand how much environmental and health impacts air pollution can have
not only within the surrounding area of the source but also the outer surrounding region such as
the inlands of the San Francisco Bay Area. With this, we can make more effective air quality
policy decisions and regulations. However, there is a limitation to this study in which this does
not provide a general model that will be applicable to other areas. It is important to recognize
that each area has unique characteristics in which one must take into consideration while
conducting site analyses. Also, in a more general sense, the results from this research may be less
significant due to financial factors. The operational costs, investments, and regulatory controls
for environmental abatement may lead to economic growth slowdown which may possibly
disinterest policy-makers (Jorgenson and Wilcoxen 1990, 337-339). Lastly, the PM 2.5 emission
data used in this research does not include all sources of emitters as only selected industrial and
Pan 3
commercial businesses have released their data. Automobile emissions are also not included in
the data. Therefore, it should be assumed that the amount of emissions per region would be
greater than reported in this research.
In this research, case studies of different regions around the United States will be
investigated to demonstrate how impactful wind patterns can be on the region’s air pollutant
dispersion. In addition to that, they will also exemplify how air pollution is a regional issue
rather than a municipal issue due to the factor of wind patterns. These case studies will lead into
the importance of analyzing the San Francisco Bay Area wind patterns in contributing to air
pollutant dispersion as the wind patterns will be crossing multiple urban cores such as Oakland,
San Francisco, and San Jose. To demonstrate the interplay of wind patterns and air pollution
emission, multiple maps have been created with ArcGIS. These maps contain the overlaying of
wind vector layers of a time lapse of 24 hours with point source PM2.5 emission data layers.
Literature Review
The influence of meteorology on an area with air pollution is significant in evaluating any
air pollutant concentrations and dispersion. Previous studies have shown that there is a positive
relationship between wind patterns and air pollutants (Henry, et. al. 2002, 2237). Understanding
the effects of these two factors is important for policy-making and regulations because due to the
interplay of meteorology and air pollutant emissions, air pollutants can travel well far off from
the point source emitters. Therefore, the promotion of regional collaboration and effort in
mitigation of air pollution must be practiced. One case study that exemplifies this relationship is
focused on Ventura County and Los Angeles County. In Ventura and Los Angeles counties, a
study was conducted to trace the transport and dispersion of atmospheric pollutants between the
two counties (Lamb et. al. 1978, 2089). In this greater region, the terrain and the wind field were
Pan 4
specifically analyzed to show their influence on the movement of the pollutants. It was
concluded that the pollutants from the Oxnard Plain in Ventura County can travel into the
inlands of San Fernando Valley in the Los Angeles Basin due to the unique terrain and wind
patterns in this region. The transport of pollutants in this study crosses multiple jurisdictions
where one’s mitigation efforts may not be entirely successful due to the failure of addressing the
primary source of emission. Therefore, it is important to consider regional governance in air
pollution legislations. Furthermore, this research will produce data analysis for the support of
regional participation in mitigation of air pollution in the San Francisco Bay Area.
Although many jurisdictions do not practice regional governance, air pollution is
increasingly considered to be a regional issue. This issue is exemplified by a case study
conducted in the Los Angeles air basin. Here, because of the sea breeze coming from the west of
Los Angeles, the accumulated air pollutant from source areas are then transported into areas such
as Riverside and San Bernardino (Blumenthal 1978, 893). This case study provides us an
example of how wind patterns can greatly influence pollution concentrations from one area to
another. It also provides us a perspective on regional effects of air pollution where local
mitigation efforts in the inland communities would be fruitless due to the major source of
pollution coming from other municipalities. However, because there is great sensitivity of
location characteristics on the results, the same effect of the interplay of meteorology and
topography may not be assumed for the San Francisco Bay Area region. Although the results
from this study may not be directly applied to the San Francisco Bay Area region, it would
however provide us an outlook of what we may expect to occur with the wind field and
topography of the San Francisco Bay Area region.
Pan 5
Another factor that needs to be addressed is the recirculation of wind in a region that can
promote the accumulation of air pollutants. For example, in the case study of the Great Lakes
lake-breeze circulation and its effects on pollutant transport in the surrounding region, the
inversion and circulation of air from the Great Lakes has been demonstrated to have an impact in
the accumulation of air pollutants around the urbanized shoreline such as Chicago, Illinois
(Lyons and Olsson 1973, 387). This case study adds more emphasize on the impact wind
patterns may have on air pollution dispersion in a particular area. Although the physical
characteristics of the Great Lakes is not comparable to the Pacific Ocean enclosing the San
Francisco Bay Area, we can, however, use this as an example of how recirculation may affect the
concentration of air pollutants in an area since according to wind pattern makes, there are some
presence of recirculating wind patterns (Ludwig and Kehaloa1974, 31).
The meteorology and topography of the region have been demonstrated to be highly
influential in the dispersion and transport of air pollutants. However, because there is a great
dependence on the region’s landscape and characteristics, this concept must be analyzed and
evaluated for case by case scenarios. In this study, I will specifically target the San Francisco
Bay Area and analyze how the wind field in the Bay area influences air pollutant concentrations
in the region in a large scale perspective. Moreover, this study will revolve around a couple
fundamental questions: how does the wind patterns in the San Francisco Bay Area influence the
dispersion and transport of air pollution from the coastal region into the inland regions in the San
Francisco Bay Area and why it is important to consider the interplay of meteorology and air
pollutant emissions in policy making and regulations.
There have also been studies conducted on the transport of air pollutants on a global scale.
One example of this is a case study on the transport of air pollution from Asia to North America.
Pan 6
In this study, air pollutants have been traced in the air from East Asia to North America to
discover the length of time it takes for the pollutants to be transported (Jaffe et. al. 1999, 711).
The study reported that it takes about six days for the air pollutants to travel between these two
far-stretching regions. This study demonstrates how great of an impact wind has on the
movement of air pollutants and their transport from one region to another. However, because this
study focuses on a global scale, it is difficult to determine the full impact of the transport of air
pollutants because as the area of study increases, the situation becomes more complex. For
example, in this study, local sources of pollution must be considered in the increased
concentration of air pollutants.
Research Strategy
In order to conduct this study, a couple mechanisms will be used to collect and analyze
the data on the various aspects of the San Francisco Bay Area. One main tool that will be used in
this research is the Geographic Information System. This tool will essentially assist in analyzing
the interplay of meteorology and topography in the San Francisco Bay Area region.
In order to conduct this analysis, data on the wind patterns of the San Francisco Bay Area
must be collected. This data has been collected from government agencies such as the National
Oceanic and Atmospheric Administration and non-government agencies. Wind vector data layers
have been collected every three hours within a 24 hour period of a given day. By taking wind
vector data every three hours, I can analyze the changing wind patterns and conclude common
patterns that occur throughout the day. Compilation of the data layers has been done with
ArcGIS in order to spatially display them. On the GIS maps created, the wind vectors will
describe the strength of the wind with the direction it is pointing toward. The general direction of
the clusters of wind vectors will illustrate the prevailing wind direction within a given region.
Pan 7
In addition to wind pattern data, emission inventory data from the region has been
collected. This data includes the name of select industrial and commercial companies in the
region and the amount of PM 2.5 they emit along with their regional location. This information
will provide a sense of where major pollutant emitters are concentrated and their relative position
within the San Francisco Bay Area wind field. This information has been collected from the Bay
Area Air Quality Management District which governs the nine bay area counties in regulating
sources of air pollution. The BAAQMD has provided the most updated 2008 Emission Inventory
containing data on the nine counties of the Bay Area where point sources and area sources are
identified with their names, locations, and amount of pollutant emitted (Mangat et. al. 2010, 137).
With the vast amount of data collected on the wind patterns and emission inventory, the
GIS layers containing both data sets will be overlaid onto a single map. This map will illustrate
how the wind directions can assist in the dispersion of air pollutants as the wind travels over the
areas of emission. In addition to this, it will help demonstrate how accumulation of air pollutant
can occur within the region while concentrating in specific areas.
This research will provide the public and government officials a spatial reference of the
interplay of meteorology and point source emission on transporting air pollutants in the San
Francisco Bay Area. This data can provide assistance in future planning within the area that
government officials can refer to. Furthermore, this study will also exemplify the importance in
regional policy-making practices and the necessity of conducting case by case analysis over onesize fits all model approach. The GIS maps created in this research will illustrate how the air
pollutants can migrate from the point source to all over the San Francisco Bay Area region. With
Pan 8
the data collected, compilation of the data collected has been completed in order for it to be
analyzed using ArcGIS that would represent the data in a spatial context.
Findings and Analysis
Possible air pollutant dispersion paths has been analyzed through the interlaying of the
emissions data layer and wind direction layer spanning a 24 hour period in the San Francisco
Bay Area region. Wind patterns change throughout the day as shown in the GIS maps displaying
the overlay of wind directions and PM2.5 emissions. However, certain prevalent patterns can be
seen from the 24 hour time lapse. Therefore, this analysis will break down the wind vector data
of a 24 hour period into three different groups of prevalent wind patterns: the morning from
12:00am-6:00am, the day from 6:00am-3:00pm, and the evening from 3:00pm-12am. Within
each group, common wind patterns can be identified while at times, one group may differ
significantly with another in the change of wind directions.
Data on Wind Vectors
The prevalent wind patterns in the morning follow a circular path throughout the San
Francisco Bay Area region as shown in Figure 1. The wind from the San Francisco peninsula
travels inward toward the East Bay region while the South Bay wind moves northward,
accumulating with the East Bay wind as it go further north onward toward the North Bay.
Afterward, the majority of the wind vectors in the North Bay point westward toward the Pacific
Ocean while the wind vectors at the tip of Marin County points southward into the San Francisco
Peninsula.
Pan 9
Figure 1 Wind Direction at 3:00am with PM2.5 Emission (NOAA, 2012)
The day group presents a significant change in wind pattern in the region. For example, there is a
general convergence of wind heading toward the South Bay as shown in Figure 2.
Pan 10
Figure 2 Wind Direction at 3:00pm with PM2.5 Emission (NOAA, 2012)
The wind vectors in the North Bay point toward the southwest direction of the San Francisco
Peninsula. The wind in the San Francisco Peninsula then travels southward toward the South Bay,
joining the East Bay southbound wind from the northeast. The wind vectors in the South Bay
points south; however, they are weak vectors which represent mild winds of 6-10mph.
The wind patterns in the evening are quite similar to the day patterns with minor
differences. The wind vectors in the North Bay mostly points toward two directions: the San
Francisco Peninsula and the East Bay. In the western region, the North Bay wind converges with
the San Francisco Peninsula wind and travels southward into the South Bay. In the eastern region,
the North Bay wind meets the East Bay wind and travels southward toward the South Bay,
joining the San Francisco Peninsular wind.
Figure 3 Wind Direction at 6:00pm with PM2.5 Emission (NOAA, 2012)
Pan 11
Although the night group presents some commonalities in wind patterns, there are slight
differences in the wind vectors at midnight as shown in Figure 4.
Figure 4 Wind Direction at 12:00am with PM2.5 Emission (NOAA, 2012)
At midnight, the wind patterns are generally heading southeastward from all directions. The
wind vectors in the North Bay predominately point toward east into the inner East Bay region
while the San Francisco Peninsula and East Bay wind vectors point southeast toward the east of
the South Bay. However, there is still a general convergence of wind around the South Bay area.
Data on Particulate Matter 2.5 Emissions
Emission data of particulate matter, 2.5 are collected from selected industrial and
commercial companies and are visually represented on the GIS maps in terms of the amount of
emissions released. There are three main clusters of emitters illustrated on the GIS maps. The
smallest and most dispersed is located around the South Bay. The East Bay possesses a small
group of emitters, generally centered on Alameda County. The largest cluster is centered in the
upper East Bay. This cluster is split into two individual groups of emitters between Contra Costa
Pan 12
County and Solano County. Although there are three main clusters, there are also many scattered
points of emission along the San Francisco Peninsula.
This GIS map that contains the overlaying of wind vectors and PM2.5 emission illustrates
how the two can be interconnected in the dispersion of air pollution throughout the San
Francisco Bay Area region. Because PM2.5 can remain suspended in the air for a long period of
time and can travel great distances before settling, wind patterns become a significant factor in
the dispersion of PM2.5 (BAAQMD 2012).
As shown from the maps, the wind patterns change throughout the day but they also
sustain common patterns. In general, the wind vectors in the North Bay point toward the
southern direction. When this occurs, the wind from the north joins the wind in the southwest
and southeast. Therefore, there is a possibility of accumulation of air pollutants from the North
Bay with the air pollutants in the San Francisco Peninsula and the East Bay with the exception in
the morning time where the East Bay wind vectors point toward north. This greater concentration
of air pollutants is further carried from the San Francisco Peninsula and the East Bay southward,
converging in the South Bay. Therefore, drawing from the maps generated, the South Bay has a
greater possibility of having accumulated air pollutants not only from its own production but also
from the whole Bay Area region.
Comparing Assumption to Real-Time Data
On the day the wind vector data was collected, the total quantity of PM2.5 in the air was
also collected by the Bay Area Air Quality Management District. The data shown in Figure 5
contains the maximum amount of PM2.5 in each region in the given 24 hour period.
Pan 13
Area
North Bay
East Bay
South Bay
San Francisco
Peninsula
PM2.5 in a day
82
63
83
25
(microgram per
meter cubed)
Figure 5 PM 2.5 Continuous Concentration over 24 Hours (BAAQMD, 2012)
The San Francisco Peninsula had the lowest amount of PM2.5 while the South Bay had the
highest amount. The reason why San Francisco Peninsula have the lowest amount of PM2.5 can
be explained by the low emissions in the area and the strong wind patterns travelling through the
San Francisco Peninsula into the other parts of the Bay Area region. However, the North Bay
also had about the same amount as the South Bay. The reason for this may be that the North Bay
region covers a greater amount of land compared to the South Bay since the North Bay includes
Marin County, Napa County, Sonoma County, and Solano County while the South Bay only
includes Santa Clara County and parts of Alameda County and San Mateo County. Nevertheless,
it can be claimed that much of the PM2.5 present in the South Bay could have originated from
the other parts of the Bay Area region as most of them have a much lower concentration of
PM2.5.
Conclusion
The data from this research will assist in spatializing the effects of wind patterns on air
pollution dispersion. In analyzing the data, we have seen that meteorology and emission of air
pollutants from point sources may have significant impacts on the transport of airborne
pollutants. In particular, this research has illustrated the movement of air pollutants generated
near the coastal area of the San Francisco Bay Area into the inland areas causing an
accumulation of pollutants in the South Bay region. By comparing between the wind pattern map
layers and air quality data of each subarea, the increase in air pollutant concentration due to the
transport and dispersion by wind patterns in the inland region has become noticeable.
Pan 14
The results from this research can be applied to future policy-making decisions in areas
such as public health, environmental abatement projects, and regional air pollution mitigation
plans. An example of this is the recognition of the spatial area of influence air pollution has due
to meteorological factors and the enforcement of the reallocation of pollution tax dollars.
Traditionally, allocation of pollution tax dollars would go to the surround community of the
point source emitter (Henderson 1977, 89). However, this reallocation would also consider
allocating funding to communities where point sources are not necessarily located within their
boundaries but do cause significant pollution impact.
In addition to reallocation of tax dollars, initiatives for public health improvements may
result from the use of the results of the research. The data from this research would illustrate how
stricter health regulations can indirectly yield to greater health and economic benefits (Ostro and
Chestnut 1998, 94). For example, by creating heavy regulations on air pollution emission, the
amount of pollutant in general decrease; therefore, the amount of pollutant transported and
dispersed would plunge. This may ultimately yield greater health and economic benefit for the
entire region.
In addition to this, because the trajectory of air pollutant movement is boundless,
municipalities can use this data to collaborate with neighboring cities in order to mitigate
potential hazards. The San Francisco Bay Area region is a highly dense area with significant
populations centered on the Peninsula, South Bay, East Bay, and North Bay. The absence of
regional governance and cooperation can cause potential environmental and public health
hazards in which the health of people with sensitive conditions such as asthma can be greatly
affected by changes in air pollutant concentration. In order to minimize the concentration, cities
must work together in mitigating the sources of the problem.
Pan 15
Bibliography
Bay Area Air Quality Management District. 2012. PM2.5 Continuous. Real Time Air Quality
Data. < http://gate1.baaqmd.gov/aqmet/aq.aspx>.
Blumenthal, D. L., W.H. White, and T.B. Smith. 1978. Anatomy of a Los Angeles Smog
Episode: Pollutant Transport in the Daytime Sea Breeze Regime. Atmospheric
Environment. 12: 893-907.
Henderson, J.V. 1977. Externalities in a Spatial Context. Journal of Public Economics. 7: 89-110.
Henry, Ronald C., Yu-Shuo Chang, and Clifford H. Spiegelman. 2002. Locating nearby sources
of air pollution by nonparametric regression of atmospheric concentrations on wind
direction. Atmospheric Environment. 36: 2237-2244.
Jaffe, Dan, Theodore Anderson, Dave Covert, Robert Kotchenruther, Barbara Trost, Jen
Danielson, William Simpson, Terje Bernstsen, Sigrun Karlsdottir, Donald Blake, Joyce
Harris, Greg Carmichael, and Itsushi Uno. Transport of Asian Air Pollution to North
America. Geophysical Research Letters. 26(6): 711-714.
Jorgenson, Dale W. and Peter J. Wilcoxen. 1990. Environmental Regulation and U.S. Economic
Growth. Journal of Economics. 21(2): 314-340.
Lamb, Brian K., Arndt Lorenzen, and Frederick H. Shair. 1978. Atmospheric Dispersion and
Transport Within Coastal Regions – Part I. Tracer Study of Power Plant Emissions from
the Oxnard Plain. Atmospheric Environment. 12: 2089-2100.
Ludwig, F.L. and J.H.S. Kealoha. 1974. Present and Prospective San Francisco Bay Area Air
Quality. Stanford Research Institute.
Lyons, Walter A. and Lars E. Olsson. 1973. Detailed Mesometeorological Studies of Air
Pollution Dispersion in the Chicago Lake Breeze. Monthly Weather Review. 101(5):
387-403.
Mangat, Tirlochan S., Sukarn J. Claire, Tan M. Dinh, Amir K. Fanai, Michael H. Nguyen, and
Stuart A. Schultz. 2010. Source Inventory of Bay Area Greenhouse Gas Emissions. Bay
Area Air Quality Management District.
National Oceanic and Atmospheric Administration. 2012. GIS Weather Data. National Weather
Service Forecast Office. < http://www.wrh.noaa.gov/gis/shape.php?area=oncc>.
Ostro, Bart and Lauraine Chestnut. 1998. Assessing the Health Benefits of Reducing Particulate
Matter Air Pollution in the United States. Environmental Research. 76: 94-106.