Engineering Commons^™

Identifying Particulate Matter Spatial Variation In The El Paso Del Norte Region Using Land-Use Regression Modeling And Data Obtained From A Network Of Low-Cost Sensors, Leonardo Demetrio Vazquez-Raygoza

Open Access Theses & Dissertations

The emergence and rise in popularity of low-cost sensors for atmospheric observation aresetting a new precedent in identifying emission hotspots and providing high-resolution spatial and temporal data. Furthermore, low-cost sensors are becoming popular among institutions and the public, allowing community scientists to become more involved in air quality monitoring. However, concerns about the accuracy and precision of low-cost sensors have been questioned. Most recent research has focused on the utility of real-time monitoring and calibration requirements for these sensors. A low-cost monitoring project has deployed sensors in the El Paso del Norte region in low and high annual average daily …

Analysis Of Indoor And Outdoor Particulate Matter At Various Residences In The El Paso Region, Joseph Christopher Pinon

Open Access Theses & Dissertations

This thesis is a presentation of particulate matter data collected from February 2007 to June 2008. Personal environment monitors (PEM), which measured 7-day PM2.5 concentrations, had been deployed at 14 homes during the 2007 year and deployed in 16 different homes during the 2008 sampling year. Within each sampling year, sampling occurred for two one-week (7-day) periods during each season. In addition to PEM sampling, a tapered element oscillating microbalance (TEOM) continuous sampler had been deployed in both indoors and outdoors at one pre-selected household per week. Gravimetric, chemical, and black carbon analysis had been performed on the PEM PM2.5 …

Assessing Annual And Seasonal Spatial Variability Of Ambient Pm10 Using Linear Regression Analysis In A United States-Mexico Urban Sprawl, Mario Ivan Garcia

Open Access Theses & Dissertations

As air quality issues grow progressively in the consciousness of the global community, stakeholders are pressing for epidemiologic studies of air pollution. The effects of chronic exposure to ambient air pollution remain a difficult challenge due to its substantial small-scale spatial variation. Recent approaches to assess intra-urban exposure have employed the use of proximity-based assessment, interpolation methods, emission-meteorological models, dispersions models, and land-use regression (LUR) models.

This thesis assesses the spatial variability of ambient particulate matter (PM10) obtained by five self-governing models for the area of El Paso. Using multiple linear regression analysis five regression-based equations were developed to predict …