Quality Assured Measurements of Animal Building Emissions: Gas Concentrations

Abstract

Comprehensive field studies were initiated in 2002 to measure emissions of ammonia (NH₃), hydrogen sulfide (H₂S), carbon dioxide (CO₂), methane (CH₄), nonmethane hydrocarbons (NMHC), particulate matter <10 µm in diameter, and total suspended particulate from swine and poultry production buildings in the United States.

This paper focuses on the quasicontinuous gas concentration measurement at multiple locations among paired barns in seven states. Documented principles, used in air pollution monitoring at industrial sources, were applied in developing quality assurance (QA) project plans for these studies. Air was sampled from multiple locations with each gas analyzed with one high quality commercial gas analyzer that was located in an environmentally controlled on-farm instrument shelter. A nominal 4 L/min gas sampling system was designed and constructed with Teflon wetted surfaces, bypass pumping, and sample line flow and pressure sensors. Three-way solenoids were used to automatically switch between multiple gas sampling lines with ≥10 min sampling intervals. Inside and outside gas sampling probes were between 10 and 115 m away from the analyzers. Analyzers used chemiluminescence, fluorescence, photoacoustic infrared, and photoionization detectors for NH₃, H₂S, CO₂, CH₄, and NMHC, respectively. Data were collected using personal computer-based data acquisition hardware and software. This paper discusses the methodology of gas concentration measurements and the unique challenges that livestock barns pose for achieving desired accuracy and precision, data representativeness, comparability and completeness, and instrument calibration and maintenance.     

Vehicle emissions of radical precursors and related species observed in the 2009 SHARP campaign

The 2009 Study of Houston Atmospheric Radical Precursors (SHARP) field campaign had several components that yielded information on the primary vehicular emissions of formaldehyde (HCHO) and nitrous acid (HONO), in addition to many other species. Analysis of HONO measurements at the Moody Tower site in Houston, TX, yielded emission ratios of HONO to the vehicle exhaust tracer species NO_x and CO of 14 pptv/ppbv and 2.3 pptv/ppbv, somewhat smaller than recently published results from the Galleria site, although evidence is presented that the Moody Tower values should be upper limits to the true ratios of directly emitted HONO, and are consistent with ratios used in current standard emissions models. Several other Moody Tower emission ratios are presented, in particular a value for HCHO/CO of 2.4 pptv/ppbv. Considering only estimates of random errors, this would be significantly lower than a previous value, though the small sample size and possible systematic differences should be taken into account. Emission factors for CO, NO_x, and HCHO, as well as various volatile organic compounds (VOCs), were derived from mobile laboratory measurements both in the Washburn Tunnel and in on-road exhaust plume observations. These two sets of results and others reported in the literature all agree well, and are substantially larger than the CO, NO_x, and HCHO emission factors derived from the emission ratios reported from the Galleria site.

Implications: Emission factors for the species measured in the various components of the 2009 SHARP campaign in Houston, TX, including HCHO, HONO, CO, CO₂, nitrogen oxides, and VOCs, are needed to support regional air quality monitoring. Components of the SHARP campaign measured these species in several different ways, each with their own potential for systematic errors and differences in vehicle fleets sampled. Comparisons between data sets suggest that differences in sampling place and time may result in quite different emission factors, while also showing that different vehicle mixes can yield surprisingly similar emission factors.     

Incineration Techniques for Control of Volatile Organic Compound Emissions

A review of incineration techniques for control of volatile organic compound emissions is presented in two consecutive issues o/JAPCA. Part I presented an overview of the process including fundamentals and design considerations. Both thermal and catalytic incinerators were considered. Part IIpresents capital and annual operating cost estimates for both thermal and catalytic incinerator systems based on information received from a number of equipment manufacturers.     

The selective role of nitrite in the PAO/GAO competition

Proliferation of Glycogen Accumulating Organisms (GAOs) accounts as one of the major bottlenecks in biological phosphorus removal systems. GAO outcompeting polyphosphate accumulating organisms (PAOs) results in lower P-removal. Thus, finding optimal conditions that favour PAO in front of GAO is a current focus of research. This work shows how nitrite can provide a novel strategy for PAO enrichment. A propionate-fed GAO-enriched biomass (70% Defluviicoccus I, 18% Defluviicoccus II and 10% PAO) was subjected more than 50 d under anaerobic-anoxic conditions with nitrite as electron acceptor. These operational conditions led to a PAO-enriched sludge (85%) where GAO were washed out of the system (<10%), demonstrating the validity of the new approach for PAO enrichment. In addition, the presented suppression of Defluviicocus GAO with nitrite represents an add-on benefit to the nitrite-based systems since the proliferation of non-desirable GAO can be easily ruled out and added to the other benefits (i.e. lower aeration and COD requirements).     

Generation of Ensemble Streamflow Forecasts Using an Enhanced Version of the Snowmelt Runoff Model1

Harshburger, Brian J., Von P. Walden, Karen S. Humes, Brandon C. Moore, Troy R. Blandford, and Albert Rango, 2012. Generation of Ensemble Streamflow Forecasts Using an Enhanced Version of the Snowmelt Runoff Model. Journal of the American Water Resources Association (JAWRA) 48(4): 643‐655. DOI: 10.1111/j.1752‐1688.2012.00642.x Abstract: As water demand increases in the western United States, so does the need for accurate streamflow forecasts. We describe a method for generating ensemble streamflow forecasts (1‐15 days) using an enhanced version of the snowmelt runoff model (SRM). Forecasts are produced for three snowmelt‐dominated basins in Idaho. Model inputs are derived from meteorological forecasts, snow cover imagery, and surface observations from Snowpack Telemetry stations. The model performed well at lead times up to 7 days, but has significant predictability out to 15 days. The timing of peak flow and the streamflow volume are captured well by the model, but the peak‐flow value is typically low. The model performance was assessed by computing the coefficient of determination (R²), percentage of volume difference (Dv%), and a skill score that quantifies the usefulness of the forecasts relative to climatology. The average R² value for the mean ensemble is >0.8 for all three basins for lead times up to seven days. The Dv% is fairly unbiased (within ±10%) out to seven days in two of the basins, but the model underpredicts Dv% in the third. The average skill scores for all basins are >0.6 for lead times up to seven days, indicating that the ensemble model outperforms climatology. These results validate the usefulness of the ensemble forecasting approach for basins of this type, suggesting that the ensemble version of SRM might be applied successfully to other basins in the Intermountain West.