Ammonia (NH₃) mixing ratios were measured between the surface and 280 m aboveground level from a moveable carriage at the Boulder Atmospheric Observatory tower in summer 2014 as part of the Front Range Air Pollution and Photochemistry Éxperiment. The campaign median mixing ratio was 3.3 ppb, ranging from below detection limits to 192 ppb. Median vertical profiles show an overall increase in NH₃ mixing ratios toward the surface of 6.7 ppb (89%) during the day and 3.9 ppb (141%) at night. In contrast to the overall increasing trend, some individual profiles show decreasing NH₃ in the lowest 10 m. This suggests that the local surface is capable of acting as either a source or a sink, depending on the relative amounts of NH₃ at the surface, and in advected air parcels. We further use this data set to investigate the variation in diurnal patterns of NH₃ as a function of height above the surface. At higher altitudes (100 ± 5 and 280 ± 5 m), NH₃ mixing ratios reach a gradual maximum during the day between 9:00 and 16:00 local time, likely driven by changes in source region. At lower altitudes (10 ± 5 m), the daytime maximum begins earlier at about 7:00 local time, followed by a sharper increase at 9:00 local time. At this height we also observe a peak in NH₃ mixing ratios during the night, likely driven by the trapping of emitted NH₃ within the shallower nocturnal boundary layer.

Low-cost air quality (LCAQ) sensors are increasingly being used for community air quality monitoring. However, data collected by low-cost sensors contain significant noise, and proper calibration of these sensors remains a widely discussed, but not yet fully addressed, area of concern. In this study, several LCAQ sensors measuring nitrogen dioxide (NO₂) and ozone (O₃) were deployed in six cities in the United States (Atlanta, GA; New York City, NY; Sacramento, CA; Riverside, CA; Portland, OR; Phoenix, AZ) to evaluate the impacts of different climatic and geographical conditions on their performance and calibration. Three calibration methods were applied, including regression via linear and polynomial models and random forest methods. When signals from carbon monoxide (CO) sensors were included in the calibration models for NO₂ and O₃ sensors, model performance generally increased, with pronounced improvements in selected cities such as Riverside and New York City. Such improvements may be due to (1) temporal co-variation between concentrations of CO and NO₂ and/or between CO and O₃; (2) different performance levels of low-cost CO, NO₂, and O₃ sensors; and (3) different impacts of environmental conditions on sensor performance. The results showed an innovative approach for improving the calibration of NO₂ and O₃ sensors by including CO sensor signals into the calibration models. Community users of LCAQ sensors may be able to apply these findings further to enhance the data quality of their deployed NO₂ and O₃ monitors.

High concentrations of ground-level ozone affect human health, plants, and animals. Reducing ozone pollution in rural regions, where local emissions are already low, poses challenge. We use meteorological back-trajectories, air quality model sensitivity analysis, and satellite remote sensing data to investigate the ozone sources in Yuma, Arizona and find strong international influences from Northern Mexico on 12 out of 16 ozone exceedance days. We find that such exceedances could not be mitigated by reducing emissions in Arizona; complete removal of state emissions would reduce the maximum daily 8-h average (MDA8) ozone in Yuma by only 0.7% on exceeding days. In contrast, emissions in Mexico are estimated to contribute to 11% of the ozone during these exceedances, and their reduction would reduce MDA8 ozone in Yuma to below the standard. Using satellite-based remote sensing measurements, we find that emissions of nitrogen oxides (NOx, a key photochemical precursor of ozone) increase slightly in Mexico from 2005 to 2016, opposite to decreases shown in the bottom-up inventory. In comparison, a decrease of NOx emissions in the US and meteorological factors lead to an overall of summer mean and annual MDA8 ozone in Yuma (by ∼1-4% and ∼3%, respectively). Analysis of meteorological back-trajectories also shows similar transboundary transport of ozone at the US-Mexico border in California and New Mexico, where strong influences from Northern Mexico coincide with 11 out of 17 and 6 out of 8 ozone exceedances. 2020 is the final year of the U.S.-Mexico Border 2020 Program, which aimed to reduce pollution at border regions of the US and Mexico. Our results indicate the importance of sustaining a substantial cooperative program to improve air quality at the border area.

Wet‐reduced nitrogen (NH₄⁺) is the main component of atmospheric nitrogen (N) deposition. Due to the poor coverage of ground‐based measurements, it is still challenging to characterize the global wet‐reduced NH₄⁺ deposition. Here we utilize NH₃ measurements from satellite retrievals (Infrared Atmospheric Sounding Interferometer) to estimate global wet NH₄⁺ deposition at 0.1° grids for nine years (2008–2016). We achieve this by developing a novel approach by calculating the feedback ratio between wet NH₄⁺ concentration in precipitation and atmospheric NH₃ columns using a global chemistry transport model (GEOS‐Chem). Satellite‐based wet NH₄⁺ concentration and deposition is relatively highly correlated with the ground‐based measurements (r = 0.88 and bias = 12% for wet deposition). The largest increase in the satellite‐derived wet NH₄⁺ deposition occurs in southern China (>0.5 kg N ha⁻¹ yr⁻¹), followed by northeastern India, North America, and Western Europe. The proposed method is simple, fast, and effective in estimating wet NH₄⁺ deposition using the satellite observations without depending on the ground‐based measurements for constructing the models. It is particularly helpful in estimating wet NH₄⁺ deposition over regions with few monitoring sites. Our unique satellite‐derived wet NH₄⁺ deposition can be applied for evaluating its impacts on ecosystems in the future.