2024 / Nitrogen dioxide (NO2) is a criteria air pollutant that is deleterious to human health and the environment, but characterizing its distribution is challenging. This challenge arises from its abundant and heterogeneous sources, short lifetime, and the limited spatial extent of surface monitoring networks. In lieu of comprehensive surface monitoring, space-based retrievals of NO2 abundance may address gaps in our understanding of its spatiotemporal variability. Space-based observations of NO2, however, have coarse-resolution sensors, requiring well-constrained inputs, and until recently have only collected one observation per day (at most), limiting their utility for characterizing diurnal variability or intra-urban heterogeneity. Throughout this dissertation, I constrain the precision of ground- and space-based remote sensing instruments dedicated to retrieving NO2 abundance, as well as explaining the spatiotemporal variability of NO2 to provide new insights relevant to urban air quality. Chapter 1 of this dissertation explains the motivation for this dissertation in more detail. In Chapter 2 of this dissertation, I quantify previously unexamined aspects of the diurnal precision of ground-based spectroscopic column NO2 observations using a high spatiotemporal resolution model of the 2013 DISCOVER-AQ campaign domain around the Houston, TX area. Pandora is a ground-based instrument commonly used to observe NO2 columns in the atmosphere. Networks of these instruments are distributed throughout the world, and their precision and accuracy make the instrument favorable for observing the spatiotemporal variability of NO2 and validating satellite instrument NO2 observations. Pandora-derived NO2 observations are often considered implicitly precise relative to satellite observations, thus motivating this evaluation. With this model I developed an instrument viewing “operator” to simulate the Pandora instrument’s operation. This operator creates synthetic direct-sun (DS) differential optical absorption spectroscopy (DOAS) columns which, when compared with modeled overhead columns, reveal that urban heterogeneity results in late-day (4-6 pm, LT) observations being less precise than previously estimated. In Chapter 3 of this dissertation (Adams et al., 2023) long-term collocated surface and column NO2 observations at Boston University were used to understand drivers of total column NO2 variability in a coastal urban setting. I found that variations in column and surface NO2 abundance were governed by different processes. The temporal variability of NO2 column density was highly dependent upon meteorology, while concentrations of NO2 at the surface were more dependent upon surface emissions patterns and boundary layer entrainment. I found that the apparent equal mixing height of NO2 plumes within the boundary layer were not sensitive to prevailing meteorology or boundary layer stability. Additionally, I found that the sea breeze fostered uniquely large temporal variations in column NO2. I demonstrated that sea breeze conditions challenge the ability of satellite-derived column NO2 observations to accurately characterize day-to-day variation. In Chapter 4 of this dissertation, I use long-term measurements of Pandora-derived total column NO2 at Boston University, Blue Hill Observatory (Milton, MA) and Harvard University. This long-term record confirmed that variation in temporal gradients in column NO2 observed in chapter 3 correspond to spatial gradients. Differences in column NO2 between sites as a function of time of day allowed us to infer the scale and formation of spatial column NO2 gradients. Finally, I evaluated to what extent satellite-derived column NO2 retrievals are capable of interpreting emissions differences across time and space. Generally, the TROPOMI satellite instrument overpasses struggled to characterize changes in column NO2 gradients across the Boston and Harvard University measurement locations between 2020 and 2021 relative to Pandora. However, TROPOMI resolved differences in the distributions of NO2 across urban-suburban scales that were not as obvious in the Pandora measurements. My results suggest that this difference in strengths at various scales is a result of the Pandora’s sensitivity to near-field emissions perturbations, in contrast with TROPOMI’s satellite footprint method which averages across larger-scales. Chapter 5 of this dissertation summarizes the conclusions from Chapters 2, 3, and 4 and provides suggestions for future investigators.