Matching Items (3)

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Spatiotemporal patterns, monitoring network design, and environmental justice of air pollution in the Phoenix metropolitan region: a landscape approach

Description

Air pollution is a serious problem in most urban areas around the world, which has a number of negative ecological and human health impacts. As a result, it's vitally important

Air pollution is a serious problem in most urban areas around the world, which has a number of negative ecological and human health impacts. As a result, it's vitally important to detect and characterize air pollutants to protect the health of the urban environment and our citizens. An important early step in this process is ensuring that the air pollution monitoring network is properly designed to capture the patterns of pollution and that all social demographics in the urban population are represented. An important aspect in characterizing air pollution patterns is scale in space and time which, along with pattern and process relationships, is a key subject in the field of landscape ecology. Thus, using multiple landscape ecological methods, this dissertation research begins by characterizing and quantifying the multi-scalar patterns of ozone (O3) and particulate matter (PM10) in the Phoenix, Arizona, metropolitan region. Results showed that pollution patterns are scale-dependent, O3 is a regionally-scaled pollutant at longer temporal scales, and PM10 is a locally-scaled pollutant with patterns sensitive to season. Next, this dissertation examines the monitoring network within Maricopa County. Using a novel multiscale indicator-based approach, the adequacy of the network was quantified by integrating inputs from various academic and government stakeholders. Furthermore, deficiencies were spatially defined and recommendations were made on how to strengthen the design of the network. A sustainability ranking system also provided new insight into the strengths and weaknesses of the network. Lastly, the study addresses the question of whether distinct social groups were experiencing inequitable exposure to pollutants - a key issue of distributive environmental injustice. A novel interdisciplinary method using multi-scalar ambient pollution data and hierarchical multiple regression models revealed environmental inequities between air pollutants and race, ethnicity, age, and socioeconomic classes. The results indicate that changing the scale of the analysis can change the equitable relationship between pollution and demographics. The scientific findings of the scale-dependent relationships among air pollution patterns, network design, and population demographics, brought to light through this study, can help policymakers make informed decisions for protecting the human health and the urban environment in the Phoenix metropolitan region and beyond.

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Created

Date Created
  • 2014

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Synoptic typing of high ozone events in Arizona (2011-2013)

Description

This thesis examines the synoptic characteristics associated with ozone exceedance events in Arizona during the time period of 2011 to 2013. Finding explanations and sources to the ground level ozone

This thesis examines the synoptic characteristics associated with ozone exceedance events in Arizona during the time period of 2011 to 2013. Finding explanations and sources to the ground level ozone in this state is crucial to maintaining the state’s adherence to federal air quality regulations. This analysis utilizes ambient ozone concentration data, surface meteorological conditions, upper air analyses, and HYSPLIT modeling to analyze the synoptic characteristics of ozone events. Based on these data and analyses, five categories were determined to be associated with these events. The five categories all exhibit distinct upper air patterns and surface conditions conducive to the formation of ozone, as well as distinct potential transport pathways of ozone from different nearby regions. These findings indicate that ozone events in Arizona can be linked to synoptic-scale patterns and potential regional transport of ozone. These results can be useful in the forecasting of high ozone pollution and influential on the legislative reduction of ozone pollution.

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Created

Date Created
  • 2016

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Novel image-based methods for quantitative real time environmental monitoring

Description

Environmental pollution has been one of the most challenging problems in modern society and more and more health issues are now linked to environmental pollution and especially, air pollution. Certain

Environmental pollution has been one of the most challenging problems in modern society and more and more health issues are now linked to environmental pollution and especially, air pollution. Certain sensitive group like patients with asthma are highly influenced by the environmental air quality and knowledge of the daily air pollution exposure is of great importance for the management and prevention of asthma attack. Hence small form factor, real time, accurate, sensitive and easy to use portable devices for environmental monitoring are of great value.

Three novel image-based methods for quantitative real time environmental monitoring were introduced and the sensing principle, sensor performances were evaluated through simulation and field tests. The first sensing principle uses surface plasmon resonance (SPR) image and home-made molecular sieve (MS) column to realize real time chemical separation and detection. SPR is sensitive and non-specific, which makes it a desirable optical method for sensitive biological and chemical sensing, the miniaturized MS column provides small area footprint and makes it possible for SPR to record images of the whole column area. The innovative and system level integration approach provide a new way for simultaneous chemical separation and detection. The second sensor uses scattered laser light, Complementary metal-oxide-semiconductor (CMOS) imager and image processing to realize real-time particulate matter (PM) sensing. Complex but low latency algorithm was developed to obtain real time information for PM including PM number, size and size distribution. The third sensor uses gradient based colorimetric sensor, absorbance light signal and image processing to realize real-time Ozone sensing and achieved high sensitivity and substantially longer lifetime compared to conventional colorimetric sensors. The platform provides potential for multi-analyte integration and large-scale consumer use as wearable device.

The three projects provide novel, state-of-the-art and sensitive solutions for environmental and personal exposure monitoring. Moreover, the sensing platforms also provide tools for clinicians and epidemiologists to conduct large scale clinical studies on the adverse health effects of pollutants on various kinds of diseases.

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Agent

Created

Date Created
  • 2019