A111-0005
Assessing Nitrogen Dioxide Intra-urban Spatial Variability in the West African City of Dakar, Senegal

Friday, 11 December 2020
Poster
Aissatou Faye1, Mary Angelique G Demetillo1, Demba Niang2, Dallas Tatman3, Mamadou simina Drame2, Katherine Knowles4, Tahi Wiggins5, Kamwoo Lee6, Jeanine Brathwaite7 and Sally E. Pusede8, (1)University of Virginia, Environmental Sciences, Charlottesville, VA, United States, (2)Laboratory of Atmospheric-Ocean Physics Simeon Fongang, Cheikh Anta Diop University, Dakar, Senegal, (3)University of Virginia, Department of Religious Studies, Charlottesville, United States, (4)University of Virginia, Environmental Sciences, Charlottesville, United States, (5)University of Virginia, Charlottesville, United States, (6)University of Virginia, Systems and Information Engineering, Charlottesville, VA, United States, (7)University of Virginia, Frank Batten School of Leadership and Public Policy, Charlottesville, United States, (8)University of Virginia, Department of Environmental Science, Charlottesville, VA, United States
Abstract:
Increasing air pollution levels pose significant challenges for rapidly growing cities like Dakar, Senegal, which is one of the most urbanized and industrialized countries in West Africa. Because there are currently few studies and a lack of the surface measurements in the region, there are large uncertainties in sources, trends, and impacts of urban pollutants such as nitrogen dioxide (NO2). In this context, we are investigating the drivers and impacts of intra-urban NO2variability in Dakar. To do this, we are creating a land-use regression (LUR) model using an array of locally collected datasets, in particular NO2mobile monitoring observations collected in February-March 2020. We are focusing our modeling on daytime workday conditions during the dry season. This study is producing the first LUR model for a West African city based on surface measurements collected in that city, and representing NO2spatial patterns in urban neighborhoods of Dakar at a resolution of 300 m x 300 m.
Increasing air pollution levels pose significant challenges for rapidly growing cities like Dakar, Senegal, which is one of the most urbanized and industrialized countries in West Africa. Because there are currently few studies and a lack of the surface measurements in the region, there are large uncertainties in sources, trends, and impacts of urban pollutants such as nitrogen dioxide (NO2). In this context, we are investigating the drivers and impacts of intra-urban NO2variability in Dakar. To do this, we are creating a land-use regression (LUR) model using an array of locally collected datasets, in particular NO2mobile monitoring observations collected in February-March 2020. We are focusing our modeling on daytime workday conditions during the dry season. This study is producing the first LUR model for a West African city based on surface measurements collected in that city, and representing NO2spatial patterns in urban neighborhoods of Dakar at a resolution of 300 m x 300 m.