Key Points: The rapid growth of anthropogenic reactive nitrogen production now makes it unquestionably dominant relative to the total of natural sources Anthropogenic production of reactive nitrogen has increased almost five‐fold in the last 60 years. This anthropogenic activity is a massive perturbation of a global geochemical cycle in a relatively short period of time.

Global ammonia (NH₃) emissions to the atmosphere are projected to increase in the coming years with the increased use of synthetic nitrogen fertilizers and cultivation of nitrogen‐fixing crops. A statistical model (NH₃_STAT) is developed for characterizing atmospheric NH₃ emissions from agricultural soils and compared to the performance of other global and regional NH₃ models (e.g., Emission Database for Global Atmospheric Research, Magnitude and Seasonality of Agricultural Emissions, MIX, and U.S. Environmental Protection Agency). The statistical model was developed from a multiple linear regression between NH₃ emission and the physicochemical variables. The model was evaluated for 2012 NH₃ emissions. The results indicate that, in comparison to other data sets, the model provides a lower global NH₃ estimate by 58%, (NH₃_STAT: 13.9 Tg N yr⁻¹; Emission Database for Global Atmospheric Research: 33.0 Tg N yr⁻¹). We also performed a region‐based analysis (United States, India, and China) using the NH₃_STAT model. For the United States, our model produces an estimate that is a ~1.4 times higher in comparison to the Environmental Protection Agency. Meanwhile, the NH₃_STAT estimate for India shows NH₃ emissions between 0.8 and 1.4 times lower when compared to other data sets. A lower estimate is also seen for China, where the model estimates NH₃ emissions 0.4 to 5 times lower than other data sets. The difference in the global estimates is attributed to the lower estimates in major agricultural countries like China and India. The statistical model captures the spatial distribution of global NH₃ emissions by utilizing a simplified approach compared to other readily available data sets. Moreover, the NH₃_STAT model provides an opportunity to predict future NH₃ emissions in a changing world.

Ambient concentrations of both fine particulate matter (PM_2.5) and particulate matter with an aerodynamic diameter less than 10 micron (PM₁₀) were measured from 10 June 2015 to 13 July 2015 at three locations surrounding the Cheswick Power Plant, which is located between the boroughs of Springdale and Cheswick, Pennsylvania. The average concentrations of PM₁₀ observed during the periods were 20.5 ± 10.2 μg m⁻³ (Station 1), 16.1 ± 4.9 μg m⁻³ (Station 2) and 16.5 ± 7.1 μg m⁻³ (Station 3). The average concentrations of PM_2.5 observed at the stations were 9.1 ± 5.1 μg m⁻³ (Station 1), 0.2 ± 0.4 μg m⁻³ (Station 2) and 11.6 ± 4.8 μg m⁻³ (Station 3). In addition, concentrations of PM_2.5 measured by four Pennsylvania Department of Environmental Protection air quality monitors (all within a radius of 40 miles) were also analyzed. The observed average concentrations at these sites were 12.7 ± 6.9 μg m⁻³ (Beaver Falls), 11.2 ± 4.7 μg m⁻³ (Florence), 12.2 ± 5.3 μg m⁻³ (Greensburg) and 12.2 ± 5.5 μg m⁻³ (Washington). Elemental analysis for samples (blank – corrected) revealed the presence of metals that are present in coal (i.e., antimony, arsenic, beryllium, cadmium, chromium, cobalt, lead, manganese, mercury, nickel and selenium).

Intensive animal agriculture is an important part of the US and North Carolina’s (NC’s) economy. Large emissions of ammonia (NH₃) gas emanate from the handling of animal wastes at these operations contributing to the formation of fine particulate matter (PM_2.5) around the state causing a variety of human health and environmental effects. The objective of this research is to provide the relationship between ammonia, aerosol optical depth and meteorology and its effect on PM_2.5 concentrations using satellite observations (column ammonia and aerosol optical depth (AOD)) and ground-based meteorological observations. An observational-based multiple linear regression model was derived to predict ground-level PM_2.5 during the summer months (JJA) from 2008–2017 in New Hanover County, Catawba County and Sampson County. A combination of the Cumberland and Johnston County models for the summer was chosen and validated for Duplin County, NC, then used to predict Sampson County, NC, PM_2.5 concentrations. The model predicted a total of six 24 h exceedances over the nine-year period. This indicates that there are rural areas of the state that may have air quality issues that are not captured for a lack of measurements. Moreover, PM_2.5 chemical composition analysis suggests that ammonium is a major component of the PM_2.5 aerosol.