Quantification and Comparison of Risks Associated with Wastewater Use in Spray Irrigation.

In the U.S., spray irrigation is the most common method used in agriculture and supplementing with animal wastewater has the potential to reduce water demands. However, this could expose individuals to respiratory pathogens such as Legionella pneumophila and nontuberculosis Mycobacteria (NTM). Disinfection with methods like anaerobic digestion is an option but can increase concentrations of cytotoxic ammonia (personal communication). Our study aimed to model the annual risks of infection from these bacterial pathogens and the air concentrations of ammonia and determine if anaerobically digesting this wastewater is a safe option. Air dispersion modeling, conducted in AERMOD, generated air concentrations of water during the irrigation season (May-September) for the years 2013-2018. These values fed into the quantitative microbial risk assessments for the bacteria and allowed calculation of ammonia air concentrations. The outputs of these models were compared to the safety thresholds of 10-4 infections/year and 0.5 mg/m3 , respectively, to determine their potential for negative health outcomes. It was determined that infection from NTM was not a concern for individuals near active spray irrigators, but that infection with L. pneumophila could be a concern, with a maximum predicted annual risk of infection of 3.5 × 10-3 infections/year and 25.2% of parameter combinations exceeding the established threshold. Ammonia posed a minor risk, with 1.5% of parameter combinations surpassing the risk threshold of 0.5 mg/m3 . These findings suggest that animal wastewater should be anaerobically digested prior to use in irrigation to remove harmful pathogens.

Lidar equation inversion methods and uncertainties in measuring fugitive particulate matter emission factors.

Measurements from two field campaigns that employed a micropulse lidar are used to compare the near-end and the far-end lidar equation inversion methods for estimating emission factors (EFs) of particulate matter (PM) from three types of anthropogenic fugitive sources: vehicles moving on unpaved roads, open burning, and open detonation. As optical depth increased from 0 to 2, relative EF uncertainty increased from 54% to 300% using the near-end method and decreased from 69% to 42% using the far-end method. To the best of our knowledge, this research is the first to use field measurements to compare results from these methods for anthropogenic PM plumes and quantify their uncertainties.

Open burning and open detonation PM10 mass emission factor measurements with optical remote sensing.

Emission factors (EFs) of particulate matter with aerodynamic diameter <10 microm (PM10) from the open burning/open detonation (OB/OD) of energetic materials were measured using a hybrid-optical remote sensing (hybrid-ORS) method. This method is based on the measurement of range-resolved PM backscattering values with a micropulse light detection and ranging (LIDAR; MPL) device. Field measurements were completed during March 2010 at Tooele Army Depot, Utah, which is an arid continental site. PM10 EFs were quantified for OB of M1 propellant and OD of 2,4,6-trinitrotoluene (TNT). EFs from this study are compared with previous OB/OD measurements reported in the literature that have been determined with point measurements either in enclosed or ambient environments, and with concurrent airborne point measurements. PM10 mass EFs, determined with the hybrid-ORS method, were 7.8 x 10(-3) kg PM10/kg M1 from OB of M1 propellant, and 0.20 kg PM10/kg TNT from OD of TNT. Compared with previous results reported in the literature, the hybrid-ORS method EFs were 13% larger for OB and 174% larger for OD. Compared with the concurrent airborne measurements, EF values from the hybrid-ORS method were 37% larger for OB and 54% larger for OD. For TNT, no statistically significant differences were observed for the EFs measured during the detonation of 22.7 and 45.4 kg of TNT, supporting that the total amount of detonated mass in this mass range does not have an effect on the EFs for OD of TNT.

Influence of rye cover cropping on denitrification potential and year-round field N2O emissions.

Cover cropping is beneficial for reducing soil erosion and nutrient losses, but there are conflicting reports on how cover cropping affects emissions of nitrous oxide (N2O), a potent greenhouse gas. In this study, we measured N2O fluxes over a full year in Illinois corn plots with and without rye cover crop. We compared these year-round measurements to N2O emissions predicted by the Intergovernmental Panel on Climate Change (IPCC) Tier 1 equation and the Denitrification-Decomposition (DNDC) model. In addition, we measured potential denitrification and N2O production rates. The field measurements showed typical N2O peaks shortly after fertilizer application, as well as a significant late-winter peak. Cover cropping significantly reduced all peak N2O fluxes, with decreases ranging from 39 to 95%. Neither model was able to accurately predict annual N2O fluxes or the decrease in N2O emissions from cover-cropped fields. In contrast to field measurements, lab assays found that cover cropping significantly increased potential denitrification by 90-127% and potential N2O production by 54-106%. The rye cover-cropped plots had lower soil nitrate and higher soil carbon. When limiting nitrate and excess carbon were provided in lab assays, the proportion of N2O resulting from denitrification decreased. These results suggest that the discrepancy between the observed decrease in field N2O emissions and the increase in denitrification potential may be due to the difference in available nutrients between the field and laboratory measurements. Overall, these results suggest the importance of late-winter peaks in N2O emissions and the potential of rye cover cropping to reduce N2O emissions from agricultural fields.

Prediction of N2O emissions under different field management practices and climate conditions.

Due to the contributions of nitrous oxide (N2O) to global climate change and stratospheric ozone destruction, it is important to understand how climate and agricultural management affect N2O emissions. Although the process-based Denitrification Decomposition (DNDC) model is often used for quantifying emissions of N2O, the accuracy of these predictions remains in question, and it is not clear which input variables, environmental or field management, have the greatest effect on model performance. In this study, DNDC was evaluated for prediction of N2O fluxes from two climatically-different corn-field sites in the United States (a Colorado irrigated field and a Minnesota rainfed field). Besides climate, these sites offer the additional advantage that measurements are available for multiple field management practices, including fertilizer application, tillage, and crop rotation. This evaluation found that DNDC did not consistently, correctly predict daily-scale N2O fluxes. Cumulative growing season N2O fluxes were significantly under-predicted in Colorado and were both under- and over-predicted in Minnesota. Model calibration of four soil input parameters did not significantly improve N2O emission predictions at either site or time scale. Modeled and measured N2O fluxes and model error were all strongly correlated with precipitation. Over-predictions of N2O fluxes were associated with heavy precipitation and high modeled denitrification. Based on our results, model improvements to decrease model error for corn cropping systems in temperate climate zones should focus on better accounting for the effects of precipitation on denitrification. Despite discrepancies in daily and cumulative growing season N2O fluxes, DNDC correctly identified the only field management (fertilizer application rate) that significantly influenced the measured N2O fluxes.

Projections of NH3 emissions from manure generated by livestock production in China to 2030 under six mitigation scenarios.

China's rapid urbanization, large population, and increasing consumption of calorie-and meat-intensive diets, have resulted in China becoming the world's largest source of ammonia (NH3) emissions from livestock production. This is the first study to use provincial, condition-specific emission factors based on most recently available studies on Chinese manure management and environmental conditions. The estimated NH3 emission temporal trends and spatial patterns are interpreted in relation to government policies affecting livestock production. Scenario analysis is used to project emissions and estimate mitigation potential of NH3 emissions, to year 2030. We produce a 1km×1km gridded NH3 emission inventory for 2008 based on county-level activity data, which can help identify locations of highest NH3 emissions. The total NH3 emissions from manure generated by livestock production in 2008 were 7.3TgNH3·yr-1 (interquartile range from 6.1 to 8.6TgNH3·yr-1), and the major sources were poultry (29.9%), pigs (28.4%), other cattle (27.9%), and dairy cattle (7.0%), while sheep and goats (3.6%), donkeys (1.3%), horses (1.2%), and mules (0.7%) had smaller contributions. From 1978 to 2008, annual NH3 emissions fluctuated with two peaks (1996 and 2006), and total emissions increased from 2.2 to 7.3Tg·yr-1 increasing on average 4.4%·yr-1. Under a business-as-usual (BAU) scenario, NH3 emissions in 2030 are expected to be 13.9TgNH3·yr-1 (11.5-16.3TgNH3·yr-1). Under mitigation scenarios, the projected emissions could be reduced by 18.9-37.3% compared to 2030 BAU emissions. This study improves our understanding of NH3 emissions from livestock production, which is needed to guide stakeholders and policymakers to make well informed mitigation decisions for NH3 emissions from livestock production at the country and regional levels.