Staff View
The spatial distribution of lead in urban residential soil and correlations with urban land cover of Balitmore, Maryland

Descriptive

TypeOfResource
Text
TitleInfo (ID = T-1)
Title
The spatial distribution of lead in urban residential soil and correlations with urban land cover of Balitmore, Maryland
SubTitle
PartName
PartNumber
NonSort
Identifier (displayLabel = ); (invalid = )
ETD_2324
Identifier (type = hdl)
http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052149
Language (objectPart = )
LanguageTerm (authority = ISO639-2); (type = code)
eng
Genre (authority = marcgt)
theses
Subject (ID = SBJ-1); (authority = RUETD)
Topic
Ecology and Evolution
Subject (ID = SBJ-2); (authority = ETD-LCSH)
Topic
Lead--Environmental aspects
Subject (ID = SBJ-3); (authority = ETD-LCSH)
Topic
Soils--Lead content--Maryland--Baltimore
Subject (ID = SBJ-4); (authority = ETD-LCSH)
Topic
Soils--Environmental aspects--Maryland--Baltimore
Abstract
Lead contamination of the urban environment is not a new phenomenon. A great deal of research has focused on the health effects of lead-based paint. Less attention, however, has been given to the potential problem of soil contaminated with lead from the past use of lead-containing products such as lead-based paint and leaded gasoline. Identifying areas of high contamination is necessary in order to prioritize soil remediation and public health efforts. This requires a comprehensive understanding of a highly heterogeneous and dynamic system.
This research addresses whether land use or land cover is a better predictor of lead concentrations in soil. Specifically, this research addresses whether landscape features, including trees, lawns, buildings, and roads, can be used to predict lead concentrations in soil. Through a method of rapid assessment of soil lead concentrations, I gathered spatially explicit data from urban residential yards to generate several models that predict the spatial distribution of lead in soil. Using the results of these models, potential inequities associated with the modeled spatial distribution of lead in soil and socio-demographic features were explored.
The results of this study suggest that the distribution of lead in urban residential soils is more closely correlated with features of urban land cover compared to metrics of land use. Specifically, the spatial distribution of lead in urban residential soils is strongly influenced by three factors: housing age, distance to the major road networks, and distance to built structures. Through the comparison of various spatial models, this research demonstrates that a greater amount of variation in the data is explained by machine learning techniques compared to traditional modeling techniques. In addition, important correlations between the modeled distribution of lead in soil and socio-demographic features such as race and poverty have been identified. Specifically, a greater amount of soil contamination is predicted to be present in high poverty areas.
This research contributes to the growing field of urban ecology by advancing our knowledge of how spatial heterogeneity affects the distribution of a critical pollutant in urban systems. This work also tests the suitability of using land cover as a predictive ecological variable.
PhysicalDescription
Form (authority = gmd)
electronic resource
Extent
vii, 138 p. : ill.
InternetMediaType
application/pdf
InternetMediaType
text/xml
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Kirsten Schwarz
Name (ID = NAME-1); (type = personal)
NamePart (type = family)
Schwarz
NamePart (type = given)
Kirsten
NamePart (type = termsOfAddress)
NamePart (type = date)
1978-
Role
RoleTerm (authority = RULIB); (type = )
author
Description
DisplayForm
Kirsten Schwarz
Name (ID = NAME-2); (type = personal)
NamePart (type = family)
Pickett
NamePart (type = given)
Steward
Role
RoleTerm (authority = RULIB); (type = )
chair
Affiliation
Advisory Committee
DisplayForm
Steward T.A. Pickett
Name (ID = NAME-3); (type = personal)
NamePart (type = family)
Lathrop
NamePart (type = given)
Richard
Role
RoleTerm (authority = RULIB); (type = )
co-chair
Affiliation
Advisory Committee
DisplayForm
Richard G. Lathrop
Name (ID = NAME-4); (type = personal)
NamePart (type = family)
Weathers
NamePart (type = given)
Kathleen
Role
RoleTerm (authority = RULIB); (type = )
internal member
Affiliation
Advisory Committee
DisplayForm
Kathleen C. Weathers
Name (ID = NAME-5); (type = personal)
NamePart (type = family)
McCay
NamePart (type = given)
Bonnie
Role
RoleTerm (authority = RULIB); (type = )
internal member
Affiliation
Advisory Committee
DisplayForm
Bonnie J. McCay
Name (ID = NAME-6); (type = personal)
NamePart (type = family)
Pouyat
NamePart (type = given)
Richard
Role
RoleTerm (authority = RULIB); (type = )
outside member
Affiliation
Advisory Committee
DisplayForm
Richard V. Pouyat
Name (ID = NAME-7); (type = personal)
NamePart (type = family)
Cadenasso
NamePart (type = given)
Mary
Role
RoleTerm (authority = RULIB); (type = )
outside member
Affiliation
Advisory Committee
DisplayForm
Mary L. Cadenasso
Name (ID = NAME-1); (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB); (type = )
degree grantor
Name (ID = NAME-2); (type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm (authority = RULIB); (type = )
school
OriginInfo
DateCreated (point = ); (qualifier = exact)
2010
DateOther (qualifier = exact); (type = degree)
2010-01
Place
PlaceTerm (type = code)
xx
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T32N52DC
Genre (authority = ExL-Esploro)
ETD doctoral
Back to the top

Rights

RightsDeclaration (AUTHORITY = GS); (ID = rulibRdec0006)
The author owns the copyright to this work.
Copyright
Status
Copyright protected
Notice
Note
Availability
Status
Open
Reason
Permission or license
Note
RightsHolder (ID = PRH-1); (type = personal)
Name
FamilyName
Schwarz
GivenName
Kirsten
Role
Copyright Holder
RightsEvent (ID = RE-1); (AUTHORITY = rulib)
Type
Permission or license
Label
Place
DateTime
2009-12-22 21:40:53
Detail
AssociatedEntity (ID = AE-1); (AUTHORITY = rulib)
Role
Copyright holder
Name
Kirsten Schwarz
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject (ID = AO-1); (AUTHORITY = rulib)
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Back to the top

Technical

ContentModel
ETD
MimeType (TYPE = file)
application/pdf
MimeType (TYPE = container)
application/x-tar
FileSize (UNIT = bytes)
2191360
Checksum (METHOD = SHA1)
0271754360e9fcfa897abc523d31508329d35d29
Back to the top
Version 8.3.13
Rutgers University Libraries - Copyright ©2021