عنوان

Fine Particulate Matter (PM2.5) Pollution in Intensive Agricultural Region of North Carolina: Satellite Analysis and Integrate Ground-based Measurements

Number

TL52482

.Language of Text, Soundtrack etc

انگلیسی

Title Proper

Fine Particulate Matter (PM2.5) Pollution in Intensive Agricultural Region of North Carolina: Satellite Analysis and Integrate Ground-based Measurements

General Material Designation

[Thesis]

First Statement of Responsibility

Wiegand, Rebecca Diane

Subsequent Statement of Responsibility

Aiyyer, Anantha

Name of Publisher, Distributor, etc.

North Carolina State University

Date of Publication, Distribution, etc.

2019

Text of Note

82 p.

Dissertation or thesis details and type of degree

M.S.

Body granting the degree

North Carolina State University

Text preceding or following the note

2019

Text of Note

Intensive animal agriculture is an important part of North Carolina's economy. About ~ 10 million hogs, and about 1 billion chickens and turkeys are produced annually at animal feeding operations, located primarily in the eastern part of the state. Large emissions of ammonia (NH3) gas and other trace gases emanate from the handling of animal wastes at these operations, NH3 can contribute to the formation of fine particulate matter (PM2.5) around the state causing regional haze events along with human health effects such as respiratory illnesses and premature death. The objective of this research is to provide the relationship between ammonia from these agricultural farms and its effect on PM2.5 concentrations. Satellite derived ammonia and aerosol optical depth (AOD) values were used as a way to mitigate issues with the spatial distribution of ground-based measurement. A multiple linear regression model was derived to predict ground level PM2.5 for a site in Cumberland County, North Carolina, and a site in Johnston County, North Carolina during the summer months (June, July and August) from 2008-2017. The model was created using the AOD retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board NASA's Aqua satellite along with surface PM2.5 monitor used by the Environmental Protection Agency and the North Carolina Department of Environmental Quality. The ammonia data used in the model was obtained through the Infrared Atmospheric Sounding Interferometer (IASI) located on board the MetOp-A satellite. The model also incorporated ground based metrological data as it has a significant impact on PM2.5 concentrations. The model was then utilized to predict PM2.5 concentrations in New Hanover County, Catawba County and Sampson county. A combination of the Cumberland county model and the Johnston county model for the summer was chosen and validated for Duplin County, NC. The model is being used to predict Sampson County, NC, concentrations. The model predicted a total of six 24-hour exceedances over the nine-year period. This indicates that there are areas of the state that could have air quality issues that are not captured due to there not being a monitor. Separately, the idea of investigating ammonia control as a PM2.5 reduction strategy could be useful in areas dominated by or near high agricultural activity.

Subject Term

Aeronomy

Subject Term

Agriculture

Subject Term

Regional studies

Wiegand, Rebecca Diane

Aiyyer, Anantha

North Carolina State University

Electronic name

p

[Thesis]

276903

a

Y