Other test method (OTM) 33A has been used to quantify emissions from natural gas sites since it was introduced by the Environmental Protection Agency (EPA). The method relies on point source Gaussian (PSG) assumptions to estimate emissions rates from a targeted site or source. However, the method often results in low accuracy (typically ±70%, even under conducive conditions). These accuracies were verified with controlled-release experiments. Typically, controlled releases were performed for short periods (15–20 min) under atmospheric conditions that were ideal for effective plume transport. We examined three methane release rates from three distances over various periods of time ranging from seven hours to seven days. Data were recorded continuously from a stationary tower. Atmospheric conditions were highly variable and not always conducive to conventional OTM 33A calculations. OTM 33A estimates were made for 20-min periods when the mean wind direction corresponded to ±90° of the direction from the controlled release to the tower. Further analyses were performed by varying the frequency of the data, the length of the individual OTM 33A periods and the size of the wind angle used to filter data. The results suggested that different (than conventionally used) period lengths, wind filters, data acquisition frequencies and data quality filters impacted the accuracy of OTM 33A when applied to long term measurements.

Dissolved oxygen (DO) is a key indicator of stream water quality and ecosystem health (Abdul-Aziz et al., 2007a, 2007bChapra, 2008). It plays a pivotal role in maintaining the life-cycle functions (e.g., growth, maintenance, and reproduction) and habitat distributions of aquatic organisms (Thomann & Mueller, 1987;Williams & Boorman, 2012). It is, therefore, immensely important to achieve and maintain a healthy DO level (e.g., at least 5 mg/l) in water bodies (

No abstract

Researchers have utilized Other Test Method (OTM) 33A to quantify methane emissions from natural gas infrastructure. Historically, errors have been reported based on a population of measurements compared to known controlled releases of methane. These errors have been reported as 2σ errors of ±70%. However, little research has been performed on the minimum attainable uncertainty of any one measurement. We present two methods of uncertainty estimation. The first was the measurement uncertainty of the state-of-the-art equipment, which was determined to be ±3.8% of the estimate. This was determined from bootstrapped measurements compared to controlled releases. The second approach of uncertainty estimation was a modified Hollinger and Richardson (H&R) method which was developed for quantifying the uncertainty of eddy covariance measurements. Using a modified version of this method applied to OTM 33A measurements, it was determined that uncertainty of any given measurement was ±17%. Combining measurement uncertainty with that of stochasticity produced a total minimum uncertainty of 17.4%. Due to the current nature of stationary single-sensor measurements and the stochasticity of atmospheric data, such uncertainties will always be present. This is critical in understanding the transport of methane emissions and indirect measurements obtained from the natural gas industry.

Relative Linkages of Stream Dissolved Oxygen with the Environmental Drivers across the Gulf Coast of U.S.A. Aron Gebreslase Dynamics of coastal stream water quality and ecosystem health is influenced by a multitude of interacting environmental drivers. A systematic data analytics approach was employed to determine the relative environmental controls on stream dissolved oxygen (DO) dynamics across the Gulf Coast of U.S.A. Pearson's correlation, principal component, and factor analyses were utilized to examine the interrelations among DO, solar radiation, water temperature, atmospheric pressure, flow rate, nutrients, pH, and specific conductance (a surrogate of salinity) in 36 streams. Relative linkages of DO and the environmental drivers were then reliably estimated by resolving multicollinearity with power-law based partial least squares regression (Nash-Sutcliffe efficiency = 0.58-0.94). Based on the dominant controls of DO, streams were grouped into three regions across the U.S. Gulf Coast. In the northern part of Gulf Coast states (Texas, Louisiana, Mississippi, Alabama, and West Florida), water temperatures had the strongest and dictated control on stream DO. However, in the southern part of Texas and Florida coasts, pH showed the most dominant control on stream DO. Further, streams in between these two regions demonstrated notable controls of multiple drivers (water temperature, stream flow, and specific conductance) on DO. Four dynamic process components adequately described the system data variance in all three regions along the Gulf Coast. For example, the 'climate component' (temperature, solar radiation) in the northern part of Gulf Coast showed 2.7, 3.1, and 3.6 times stronger linkages with stream DO than that of the redox (pH, specific conductance), nutrient (total nitrogen, total phosphorus), and hydro-atmospheric (flow rate, atmospheric pressure) components, respectively. In contrast, in the southern part of Gulf Coast region, the redox components showed 1.6, 2.3, and 2.6 times stronger linkages with stream DO than that of the climate, nutrient, and hydro-atmospheric components, respectively. The identified environmental regimes and estimated linkages of stream DO provide important information into the dominant drivers and dynamic process components of water quality in urban/natural streams across the U.S. Gulf Coast. The knowledge and insights would help coastal managers and stakeholders to achieve a good stream water quality and ecosystem health.