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Next-Generation Environmental Engineering: Leveraging Microbial Ecology to Mitigate Anthropogenic Pollution
Next-Generation Environmental Engineering: Leveraging Microbial Ecology to Mitigate Anthro...
Next-Generation Environmental Engineering: Leveraging Microbial Ecology to Mitigate Anthropogenic Pollution

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자료유형  
 학위논문 서양
최종처리일시  
20250211152703
ISBN  
9798384051886
DDC  
628
저자명  
DiDominic, Katie L. Duggan.
서명/저자  
Next-Generation Environmental Engineering: Leveraging Microbial Ecology to Mitigate Anthropogenic Pollution
발행사항  
[Sl] : Cornell University, 2024
발행사항  
Ann Arbor : ProQuest Dissertations & Theses, 2024
형태사항  
146 p
주기사항  
Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
주기사항  
Advisor: Walter, Michael.
학위논문주기  
Thesis (Ph.D.)--Cornell University, 2024.
초록/해제  
요약Maintaining water quality is vital for ecological balance and human well-being. This task is increasingly challenging due to the intensifying impact of anthropogenic activity, the effects of which are worsened by climate change. Pollution from diverse sources like industrial discharge, agricultural runoff, and urban sewage (e.g., combined sewer overflows, excess fertilizer treatment) poses a significant threat to nearby water bodies, causing contamination, eutrophication, and ecosystem degradation (Michalak, 2016; Nawaz et al., 2023). The effects of which are worsened by climate change. Developing methods to combat pollution is critical to mitigate these impacts, safeguard aquatic habitats, and protect public health. One way to do this is by focusing research on innovative biosystems for the treatment and/or removal of contaminants. Expanding our understanding of the intricacies within these systems can help us improve existing engineered systems and develop new systems that can mitigate pollution. In doing so, we can ensure the sustainability of water resources and promote a healthier environment for both natural and human communities.In this dissertation, I investigate how innate microbial processes can be optimized for next-generation environmental engineering. Over the course of three studies, I explore the role of microorganisms in two existing feats of environmental engineering: 1) woodchip bioreactors used for treating agricultural drainage, and 2) microbial fuel cells (MFCs) used for producing electrical energy by oxidizing contaminated organic matter.Through a combination of laboratory scale experiments and field collected samples paired with data analytics and bioinformatic analysis, I contribute to the ongoing advancements of woodchip bioreactors and MFCs as successful methods of pollution mitigation. Specifically, I use a field installed woodchip bioreactor to assess the current methodology of studying the microbial communities inhabiting woodchip bioreactors (i.e., analyzing the surface biofilm only) by comparing it to the method of milling the woodchips to reveal potential hidden microbial information within the wood matrix (Chapter 1). I found that milling woodchips was not only a feasible method of studying the microbes in the bioreactor, but that it is important to characterize microbial communities both within woodchips and on woodchip surfaces to gain a more holistic understanding of relevant biogeochemical processes in woodchip bioreactors. In addition, I use a lab-scale column bioreactor study with simulated agricultural drainage to dive deeper and analyze the interactions between various chemical, physical, and biological processes driving nutrient removal (Chapter 2). I found that chemical and physical processes tend to drive phosphorus removal during continuous anoxic conditions while biological activity tends to drive during oxic/anoxic cycling conditions, meaning the ability to manipulate oxygen levels within field woodchip bioreactors would offer a more promising approach to improving nutrient removal capabilities.Finally, I used a soil MFC microcosm incubation study to assess how fluctuating environmental conditions (i.e., diurnal temperature conditions) impact the bioelectrical signals produced by microorganisms with and without a contaminant present, as well as what implications these may have on field deployed MFCs for use as biosensors. I found that the presence of a contaminant (i.e., urea) was the largest driver of decreased microbial diversity and the variation in microbial community composition in soil MFCs, and that temperature condition had a greater impact on microbial community composition when a urea was present versus when it was not. This implies that in a field deployed scenario, a change in microbial community due to a temperature fluctuation when a contaminant is present could mask the shift in bioelectrical signals due to the contaminant, causing potential confusion for the trained model and therefore effect the ability of the MFC biosensor to effectively detect and classify the contaminant.The various approaches taken throughout my work combine a unique use of microbial ecology and computational biology to further advance next-generation environmental engineering. 
일반주제명  
Environmental engineering
일반주제명  
Biogeochemistry
일반주제명  
Ecology
일반주제명  
Microbiology
키워드  
Woodchip bioreactors
키워드  
Microbial fuel cells
키워드  
Environmental conditions
키워드  
Water quality
키워드  
Biological activity
기타저자  
Cornell University Biological and Environmental Engineering
기본자료저록  
Dissertations Abstracts International. 86-03B.
전자적 위치 및 접속  
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MARC

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■1001  ▼aDiDominic,  Katie  L.  Duggan.▼0(orcid)0000000168295982
■24510▼aNext-Generation  Environmental  Engineering:  Leveraging  Microbial  Ecology  to  Mitigate  Anthropogenic  Pollution
■260    ▼a[Sl]▼bCornell  University▼c2024
■260  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2024
■300    ▼a146  p
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  86-03,  Section:  B.
■500    ▼aAdvisor:  Walter,  Michael.
■5021  ▼aThesis  (Ph.D.)--Cornell  University,  2024.
■520    ▼aMaintaining  water  quality  is  vital  for  ecological  balance  and  human  well-being.  This  task  is  increasingly  challenging  due  to  the  intensifying  impact  of  anthropogenic  activity,  the  effects  of  which  are  worsened  by  climate  change.  Pollution  from  diverse  sources  like  industrial  discharge,  agricultural  runoff,  and  urban  sewage  (e.g.,  combined  sewer  overflows,  excess  fertilizer  treatment)  poses  a  significant  threat  to  nearby  water  bodies,  causing  contamination,  eutrophication,  and  ecosystem  degradation  (Michalak,  2016;  Nawaz  et  al.,  2023).  The  effects  of  which  are  worsened  by  climate  change.  Developing  methods  to  combat  pollution  is  critical  to  mitigate  these  impacts,  safeguard  aquatic  habitats,  and  protect  public  health.  One  way  to  do  this  is  by  focusing  research  on  innovative  biosystems  for  the  treatment  and/or  removal  of  contaminants.  Expanding  our  understanding  of  the  intricacies  within  these  systems  can  help  us  improve  existing  engineered  systems  and  develop  new  systems  that  can  mitigate  pollution.  In  doing  so,  we  can  ensure  the  sustainability  of  water  resources  and  promote  a  healthier  environment  for  both  natural  and  human  communities.In  this  dissertation,  I  investigate  how  innate  microbial  processes  can  be  optimized  for  next-generation  environmental  engineering.  Over  the  course  of  three  studies,  I  explore  the  role  of  microorganisms  in  two  existing  feats  of  environmental  engineering: 1)  woodchip  bioreactors  used  for  treating  agricultural  drainage,  and  2)  microbial  fuel  cells  (MFCs)  used  for  producing  electrical  energy  by  oxidizing  contaminated  organic  matter.Through  a  combination  of  laboratory  scale  experiments  and  field  collected  samples  paired  with  data  analytics  and  bioinformatic  analysis,  I  contribute  to  the  ongoing  advancements  of  woodchip  bioreactors  and  MFCs  as  successful  methods  of  pollution  mitigation.  Specifically,  I  use  a  field  installed  woodchip  bioreactor  to  assess  the  current  methodology  of  studying  the  microbial  communities  inhabiting  woodchip  bioreactors  (i.e.,  analyzing  the  surface  biofilm  only)  by  comparing  it  to  the  method  of  milling  the  woodchips  to  reveal  potential  hidden  microbial  information  within  the  wood  matrix  (Chapter  1).  I  found  that  milling  woodchips  was  not  only  a  feasible  method  of  studying  the  microbes  in  the  bioreactor,  but  that  it  is  important  to  characterize  microbial  communities  both  within  woodchips  and  on  woodchip  surfaces  to  gain  a  more  holistic  understanding  of  relevant  biogeochemical  processes  in  woodchip  bioreactors.  In  addition,  I  use  a  lab-scale  column  bioreactor  study  with  simulated  agricultural  drainage  to  dive  deeper  and  analyze  the  interactions  between  various  chemical,  physical,  and  biological  processes  driving  nutrient  removal  (Chapter  2).  I  found  that  chemical  and  physical  processes  tend  to  drive  phosphorus  removal during  continuous  anoxic  conditions  while  biological  activity  tends  to  drive  during  oxic/anoxic  cycling  conditions,  meaning  the  ability  to  manipulate  oxygen  levels  within  field  woodchip  bioreactors  would  offer  a  more  promising  approach  to  improving  nutrient  removal  capabilities.Finally,  I  used  a  soil  MFC  microcosm  incubation  study  to  assess  how  fluctuating  environmental  conditions  (i.e.,  diurnal  temperature  conditions)  impact  the  bioelectrical  signals  produced  by  microorganisms  with  and  without  a  contaminant  present,  as  well  as  what  implications  these  may  have  on  field  deployed  MFCs  for  use  as  biosensors.  I  found  that  the  presence  of  a  contaminant  (i.e.,  urea)  was  the  largest  driver  of  decreased  microbial  diversity  and  the  variation  in  microbial  community  composition  in  soil  MFCs,  and  that  temperature  condition  had  a  greater  impact  on  microbial  community  composition  when  a  urea  was  present  versus  when  it  was  not.  This  implies  that  in  a  field  deployed  scenario,  a  change  in  microbial  community  due  to  a  temperature  fluctuation  when  a  contaminant  is  present  could  mask  the  shift  in  bioelectrical  signals  due  to  the  contaminant,  causing  potential  confusion  for  the  trained  model  and  therefore  effect  the  ability  of  the  MFC  biosensor  to  effectively  detect  and  classify  the  contaminant.The  various  approaches  taken  throughout  my  work  combine  a  unique  use  of  microbial  ecology  and  computational  biology  to  further  advance  next-generation  environmental  engineering. 
■590    ▼aSchool  code:  0058.
■650  4▼aEnvironmental  engineering
■650  4▼aBiogeochemistry
■650  4▼aEcology
■650  4▼aMicrobiology
■653    ▼aWoodchip  bioreactors
■653    ▼aMicrobial  fuel  cells
■653    ▼aEnvironmental  conditions
■653    ▼aWater  quality
■653    ▼aBiological  activity  
■690    ▼a0775
■690    ▼a0425
■690    ▼a0410
■690    ▼a0329
■690    ▼a0474
■71020▼aCornell  University▼bBiological  and  Environmental  Engineering.
■7730  ▼tDissertations  Abstracts  International▼g86-03B.
■790    ▼a0058
■791    ▼aPh.D.
■792    ▼a2024
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17163402▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.

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