Characterization of gaseous pollutant and particulate matter emission rates from a commercial broiler operation part II: Correlated emission rates

Emission rates of ammonia, acid gases, inorganic aerosols, methane, and size fractionated particulate matter were measured from a commercial broiler facility. This paper discusses the statistically influential parameters on numerous pollutants’ emission from a broiler chicken facility and generates emission correlations to fill data gaps and develop averaged emission factors.Live mass of the birds was commonly a significant variable to each pollutant’s emission. Some variables significantly impacted the pollutants’ emissions, such as litter moisture content, but were measured discretely and cannot be used for filling in data gaps.House parameter correlations were, therefore, developed using parameters measured at the facility, such as indoor temperature, relative humidity, and the live mass of the birds, and relied on the mutual behaviour of discretely measured explanatory parameters and continuously monitored confounding variables. The live mass and the difference in the indoor temperature and the house set-point temperature were the most significant variables in each pollutant’s correlation.The correlations predicted each pollutants emission to within 20% (total mass basis) over most broiler production cycles. Their validation on independent datasets also successfully estimated the flocks’ emissions to within 3%.Emission factors (EFs) were developed for methane, ammonia, and size fractionated particulate matter using measured data and correlated emissions to fill in data gaps. PM₁₀ (particulate matter ≤10 microns) EFs were estimated to be 4.6 and 5.9 g d^?1 [Animal Unit, AU]^?1 for five and six week production cycles, respectively. PM_2.5 (PM ≤ 2.5 microns) EFs were 0.8 and 1.4 g d^?1 AU^?1 for five and six week cycles, respectively. Ammonia and methane emission factors were estimated at 120.8 and 197.0 g d^?1 AU^?1, respectively for a five week production cycle.     

South Philadelphia passive sampler and sensor study

From June 2013 to March 2015, in total 41 passive sampler deployments of 2 wk duration each were conducted at 17 sites in South Philadelphia, PA, with results for benzene discussed here. Complementary time-resolved measurements with lower cost prototype fenceline sensors and an open-path ultraviolet differential optical absorption spectrometer were also conducted. Minimum passive sampler benzene concentrations for each sampling period ranged from 0.08 ppbv to 0.65 ppbv, with a mean of 0.25 ppbv, and were negatively correlated with ambient temperature (–0.01 ppbv/°C, R² = 0.68). Co-deployed duplicate passive sampler pairs (N = 609) demonstrated good precision with an average and maximum percent difference of 1.5% and 34%, respectively. A group of passive samplers located within 50 m of a refinery fenceline had a study mean benzene concentration of 1.22 ppbv, whereas a group of samplers located in communities >1 km distant from facilities had a mean of 0.29 ppbv. The difference in the means of these groups was statistically significant at the 95% confidence level (p < 0.001). A decreasing gradient in benzene concentrations moving away from the facilities was observed, as was a significant period-to-period variation. The highest recorded 2-wk average benzene concentration for the fenceline group was 3.11 ppbv. During this period, time-resolved data from the prototype sensors and the open-path spectrometer detected a benzene signal from the west on one day in particular, with the highest 5-min path-averaged benzene concentration measured at 24 ppbv.

Implications: Using a variation of EPA’s passive sampler refinery fenceline monitoring method, coupled with time-resolved measurements, a multiyear study in South Philadelphia informed benzene concentrations near facilities and in communities. The combination of measurement strategies can assist facilities in identification and mitigation of emissions from fugitive sources and improve information on air quality complex air sheds.     

Predictions of Maximum Ground-Level H2S Concentrations Resulting from Two Sour Gas Well Blowouts

Alberta has recently experienced two sour gas well blowouts: Lodgepole and Claresholm. Sulphur emissions associated with the blowouts were about 1400 and 2 tonnes per day, respectively. The Lodgepole blowout was not only of much greater magnitude but also lasted significantly longer than the Claresholm blowout (67 vs. 4 days). Special air quality monitoring with respect to H₂S was conducted to assess impacts of the blowouts. Monitoring was especially extensive for the Lodgepole incident. Maximum observed ground-level H₂S concentrations were compared to predictions obtained using a Gaussian model which makes allowance for the effects of sonic exit velocity on plume spread and the effects of wind shear on plume transport. There was appreciable agreement between predicted and observed values.     

Field evaluation of digital optical method to quantify the visual opacity of plumes

Visual Determination of the Opacity of Emissions from Stationary Sources (Method 9) is a reference method established by U.S. Environmental Protection Agency (EPA) to quantify plume opacity. However, Method 9 relies on observations from humans, which introduces subjectivity. In addition, it is expensive to teach and certify personnel to evaluate plume opacity on a semiannual basis. In this study, field tests were completed during a "smoke school" and a 4-month monitoring program of plumes emitted from stationary sources with a Method 9 qualified observer to evaluate the use of digital photography and two computer algorithms as an alternative to Method 9. This Digital Optical Method (DOM) improves objectivity, costs less to implement than Method 9, and provides archival photographic records of the plumes. Results from "smoke school" tests indicate that DOM passed six of eight tests when the sun was located in the 140 degrees sector behind one of the three cameras, with the individual opacity errors of 15% or less and average opacity errors of 7.5% or less. DOM also passed seven of the eight tests when the sun was located in the 216 degrees sector behind another camera. However, DOM passed only one of the eight tests when the sun was located in the 116 degrees sector in front of the third camera. Certification to read plume opacity by a "smoke reader" for 6 months requires that the "smoke reader" pass one of the smoke school tests during smoke school. The average opacity errors and percentage of observations with individual opacity errors above 15% for the results obtained with DOM were lower than those obtained by the smoke school trainees with the sun was located behind the camera, whereas they were higher than the smoke school trainee results with the sun located in front of the camera. In addition, the difference between plume opacity values obtained by DOM and a Method 9 qualified observer, as measured in the field for two industrial sources, were 2.2%. These encouraging results demonstrate that DOM is able to meet Method 9 requirements under a wide variety of field conditions and, therefore, has potential to be used as an alternative to Method 9.     

The Australian Air Quality Forecasting System: the use of green scenarios of motor vehicle usage as an educational tool

The Australian Air Quality Forecasting System (AAQFS) is one of several newly emerging, high-resolution, numerical air quality forecasting systems. The system is briefly described. A public education application of the air quality impact of motor vehicle usage is explored by computing the concentration and dosage of particulate matter less than 10 microm in aerodynamic diameter (PM10) for a commuter traveling to work between Geelong and Melbourne, Victoria, Australia, under "business-as-usual" and "green" scenarios. This application could be routinely incorporated into systems like AAQFS. Two methodologies for calculating the dosage are described: one for operational use and one for more detailed applications. The Clean Air Research Programme-Personal Exposure Study in Melbourne provides support for this operational methodology. The more detailed methodology is illustrated using a system for predicting concentrations due to near-road emissions of PM10 and applied in Sydney.     

Nitrate reduction by fluoride green rust modified with copper

Nitrate reduction by the fluoride form of green rust modified with copper (GR-F(Cu)) was investigated using a batch reactor system. The extent of nitrate reduction was measured by measuring the increase in concentration of ammonia, which is the final product of nitrate reduction by GR. This approach was required, because nitrate could be removed from solution by ion exchange without reduction. The rate of ammonium production was investigated over the range of pH 7.8-11. The fastest reaction was achieved at pH 9 when GR was present at a concentration of 0.083M as Fe(II) and 1mM of Cu(II) was added. The rate at pH 9 was enhanced by a factor of 2.5 compared to that at pH 7.8 by comparing the time elapsed to transform all nitrate to ammonium. Kinetics of nitrate reduction by GR-F at pH 7.8 were affected by the concentration of Cu(II) added. The rate constants for ammonium production increased from 0.012 to 1.52h(-1) as Cu(II) additions increased from 0 to 2.5mM, but the reaction rate at 5mM was slightly decreased to 1.25h(-1). The mechanism of enhanced rates of nitrate reduction by addition of Cu(II) could not be fully determined in this study. However, XRD results showed that magnetite was produced in the reaction of Cu(II) and GR-F and SEM shows the production of nano-size particles which were not fully identified in this study. In addition, the concentration of Fe(II) in GR was observed to linearly decrease with concentration of Cu(II) added.     

Hydrogeochemical characterization and groundwater quality assessment in intruded coastal brine aquifers (Laizhou Bay,China)

Environmental Science and Pollution Research - The aquifer in the coastal area of the Laizhou Bay is affected by salinization processes related to intense groundwater exploitation for brine...     

Brominated flame retardants,a cornelian dilemma

Environmental Chemistry Letters -     

A structural equation model to integrate changes in functional strategies during old-field succession

From a functional perspective, changes in abundance, and ultimately species replacement, during succession are a consequence of integrated suites of traits conferring different relative ecological advantages as the environment changes over time. Here we use structural equations to model the interspecific relationships between these integrated functional traits using 34 herbaceous species from a Mediterranean old-field succession and thus quantify the notion of a plant strategy. We measured plant traits related to plant vegetative and reproductive size, leaf functioning, reproductive phenology, seed mass, and production on 15 individuals per species monitored during one growing season. The resulting structural equation model successfully accounts for the pattern of trait covariation during the first 45 years post-abandonment using just two forcing variables: time since site abandonment and seed mass; no association between time since field abandonment and seed mass was observed over these herbaceous stages of secondary succession. All other predicted traits values are determined by these two variables and the cause-effect linkage between them. Adding pre-reproductive vegetative mass as a third forcing variable noticeably increased the predictive power of the model. Increasing the time after abandonment favors species with increasing life span and pre-reproductive biomass and decreasing specific leaf area. Allometric coefficients relating vegetative and reproductive components of plant size were in accordance with allometry theory. The model confirmed the trade-off between seed mass and seed number. Maximum plant height and seed mass were major determinants of reproductive phenology. Our results show that beyond verbal conceptualization, plant ecological strategies can be quantified and modeled.     

Air emission inventories in North America: a critical assessment

Although emission inventories are the foundation of air quality management and have supported substantial improvements in North American air quality, they have a number of shortcomings that can potentially lead to ineffective air quality management strategies. Major reductions in the largest emissions sources have made accurate inventories of previously minor sources much more important to the understanding and improvement of local air quality. Changes in manufacturing processes, industry types, vehicle technologies, and metropolitan infrastructure are occurring at an increasingly rapid pace, emphasizing the importance of inventories that reflect current conditions. New technologies for measuring source emissions and ambient pollutant concentrations, both at the point of emissions and from remote platforms, are providing novel approaches to collecting data for inventory developers. Advances in information technologies are allowing data to be shared more quickly, more easily, and processed and compared in novel ways that can speed the development of emission inventories. Approaches to improving quantitative measures of inventory uncertainty allow air quality management decisions to take into account the uncertainties associated with emissions estimates, providing more accurate projections of how well alternative strategies may work. This paper discusses applications of these technologies and techniques to improve the accuracy, timeliness, and completeness of emission inventories across North America and outlines a series of eight recommendations aimed at inventory developers and air quality management decision-makers to improve emission inventories and enable them to support effective air quality management decisions for the foreseeable future.