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 …

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 …