Characterization of gaseous pollutant and particulate matter emission rates from a commercial broiler operation part I: Observed trends in emissions

This paper characterizes the emission rates of size fractionated particulate matter, inorganic aerosols, acid gases, ammonia and methane measured over four flocks at a commercial broiler chicken facility. Mean emission rates of each pollutant, along with sampling notes, were reported in this paper, the first in a series of two. Sampling notes were needed because inherent gaps in data may bias the mean emission rates.The mean emission rates of PM₁₀ and PM_2.5 were 5.0 and 0.78 g day^?1 [Animal Unit, AU]^?1, respectively, while inorganic aerosols mean emission rates ranged from 0.15 to 0.46 g day^?1 AU^?1 depending on the season. The average total acid gas emission rate was 0.43 g day^?1 AU^?1 with the greatest contribution from nitrous and nitric acids and little contribution from sulfuric acid (as SO₂).Ammonia emissions were seasonally dependent, with a mean emission rate of 66.0 g day^?1 AU^?1 in the cooler seasons and 94.5 g day^?1 AU^?1 during the warmer seasons. Methane emissions were relatively consistent with a mean emission rate of 208 g day^?1 AU^?1.The diurnal pattern in each pollutant’s emission rate was relatively consistent after normalizing the hourly emissions according to each daily mean emission rate. Over the duration of a production cycle, all the measured pollutants’ emissions increased proportionally to the total live mass of birds in the house, with the exception of ammonia.Interrelationships between pollutants provide evidence of mutually dependent release mechanisms, which suggests that it may be possible to fill data gaps with minimal data requirements. In the second paper (Roumeliotis, T.S., Dixon, B.J., Van Heyst, B.J. Characterization of gaseous pollutants and particulate matter emission rates from a commercial broiler operation part II: correlated emission rates. Atmospheric Environment, 2010.), regression correlations are developed to estimate daily mean emission rates for data gaps and, using the normalized hourly diurnal patterns from this paper, emission factors were generated for each pollutant.     

The importance of place in early disaster recovery: a case study of the 2013 Colorado floods

Recovery is an important but understudied phase in the disaster management cycle. Researchers have identified numerous socio-demographic factors that help explain differences in recovery among households, but are less clear on the importance of place, which we define as a household's locality and local governance. In this paper, we examine the influence of place on disaster recovery through a study of the 2013 Colorado floods. Our findings are based on data collected from interviews, observation of recovery meetings, and a survey of 96 flood-affected households. We show that place shapes a household's disaster recovery by structuring: (1) physical exposure to hazards; (2) which local government has jurisdiction over recovery decisions; (3) local planning culture and its approach to citizen participation; and (4) the strength of social capital networks. Our findings expand the recovery literature and show that place-level variables should be taken into consideration when conceptualizing household recovery and resilience.     

A composite measure of habitat loss for entire assemblages of species

Habitat destruction is among the greatest threats facing biodiversity, and it affects common and threatened species alike. However, metrics for communicating its impacts typically overlook the nonthreatened component of assemblages. This risks the loss of habitat going unreported for species that comprise the majority of assemblages. We adapted a widely used measure for summarizing researcher output (the h index) to provide a metric that describes natural habitat loss for entire assemblages, inclusive of threatened and nonthreatened species. For each of 447 Australian native terrestrial bird species, we combined information on their association with broad vegetation groups with distributional range maps to identify the difference between the estimated pre-European and current extents of potential habitat, defined as vegetation groups most closely associated with each species. From this, we calculated the loss index (LI), which revealed that 30% of native birds have each lost at least 30% of their potential natural habitat (LI = 30). At the subcontinental scale, LIs ranged from 15 in arid Australia to 61 in the highly transformed southeastern part of the country. Different subcomponents of the assemblage had different LI values. For example, Australia's parrots (n = 52 species) had an LI of 38, whereas raptors (n = 32 species) had an LI of 25. The LI is simple to calculate and can be determined using readily available spatial information on species distributions, native vegetation associations, and human impacts on natural land cover. This metric, including the curves used to deduce it, could complement other biodiversity indices if it is used for regional and global biodiversity assessments that compare the status of natural habitat extent for assemblages within and among nations, monitor changes through time, and forecast future changes to guide strategic land-use planning. The LI is an intuitive tool that can be used to summarize and communicate how human actions affect whole assemblages, not just threatened species.     

Uncertainty assessment of mapping mercury contaminated soils of a rapidly industrializing city in the Yangtze River Delta of China using sequential indicator co-simulation

Accurate characterization of heavy-metal contaminated areas and quantification of the uncertainties inherent in spatial prediction are crucial for risk assessment, soil remediation, and effective management recommendations. Topsoil samples (0–15 cm) (n = 547) were collected from the Zhangjiagang suburbs of China. The sequential indicator co-simulation (SIcS) method was applied for incorporating the soft data derived from soil organic matter (SOM) to simulate Hg concentrations, map Hg contaminated areas, and evaluate the associated uncertainties. High variability of Hg concentrations was observed in the study area. Total Hg concentrations varied from 0.004 to 1.510 mg kg⁻¹ and the coefficient of variation (CV) accounts for 70%. Distribution patterns of Hg were identified as higher Hg concentrations occurred mainly at the southern part of the study area and relatively lower concentrations were found in north. The Hg contaminated areas, identified using the Chinese Environmental Quality Standard for Soils critical values through SIcS, were limited and distributed in the south where the SOM concentration is high, soil pH is low, and paddy soils are the dominant soil types. The spatial correlations between Hg and SOM can be preserved by co-simulation and the realizations generated by SIcS represent the possible spatial patterns of Hg concentrations without a smoothing effect. Once the Hg concentration critical limit is given, SIcS can be used to map Hg contaminated areas and quantitatively assess the uncertainties inherent in the spatial prediction by setting a given critical probability and calculating the joint probability of the obtained areas.     

The Scottish Raptor Monitoring Scheme: objectives, achievements in the first four years, and plans for future development

The Scottish Raptor Monitoring Scheme (SRMS) comprises 7 partner organizations and was established in 2002 after i) the publication of the UK Government's Raptor Working Group Report that made recommendations for enhanced monitoring, ii) increased applied data needs (e.g., for site designation), and iii) concerns for the status of some species. The SRMS has 3 major objectives: i) to facilitate cooperation between parties; ii) to provide robust information on Scottish raptor populations by determining trends in numbers, range, survival, and productivity and understanding the causes of change; and iii) to maintain high and uniform standards for the collection, collation, auditing, and analysis of data and reporting of information. Data are collected for 19 species: 14 diurnal raptors, 4 owls, and 1 corvid, the Common Raven. Here we describe the development of the scheme, challenges, and achievements during its first 4 y, the nature and value of the data collected, and plans for the future.     

A field trial of nutrient stimulation of methanotrophs to reduce greenhouse gas emissions from landfill cover soils

Landfills are among the major sources of anthropogenic methane (CH₄) estimated to reach 40?×?10⁹kg per year worldwide by 2015 (IPCC, 2007 IPCC. 2007. Intergovernmental Panel on Climate Change, Synthesis Report on Contributions of Work Groups 1, 2, and 3 to the Fourth Assessment Report Core Writing Team, Edited by: Pauchar, R.K. and Reisinger, A. Geneva, Switzerland: IPCC.  [Google Scholar]). A 2½-year field experiment was conducted at a closed landfill in western Michigan where methanotrophs, methane-consuming bacteria, were stimulated by nutrient addition to the soil without significantly increasing biogenic nitrous oxide (N₂O) production. The effects of the nitrogen amendments (KNO₃ and NH₄Cl), phenylacetylene (a selective inhibitor of nitrifying bacteria that contribute to N₂O production), and a canopy (to reduce direct water infiltration) on the vertical soil gas profiles of CH₄, CO₂, and O₂ were measured in the top meter of the soil. Methane and nitrous oxide fluxes were calculated from the corresponding soil gas concentration gradients with respect to depth and a Millington–Quirk diffusivity coefficient in soil derived empirically from soil porosity, water content, and diffusivity coefficients in air from the literature. Methane flux estimates were as high as 218.4 g m^?2 day^?1 in the fall and 12.8 g/m^?2 day^?1 in the summer. During the spring and summer, CH₄ fluxes were reduced by more than half by adding KNO₃ and NH₄Cl into the soil as compared to control plots, while N₂O fluxes increased substantially. The concurrent addition of phenylacetylene to the amendment decreased peak N₂O production by half and the rate of peak methane oxidation by about one-third. The seasonal average methane and N₂O flux data were extrapolated to estimate the reduction of CH₄ and N₂O fluxes into the atmosphere by nitrogen and inhibitor addition to the cover soils. The results suggest that such additions coupled with soil moisture management may provide a potential strategy to significantly reduce greenhouse gas emissions from landfills.

Implications The results of a 2½-year study of effects of nutrient stimulation on methane oxidation in landfill cover soils demonstrates that nutrient addition does decrease methane emissions. The work further underscores the control which soil moisture exerts on methane oxidation. Water management is critical to the success of methane oxidation strategies.     

Assessing the Relationship between Personal Particulate and Gaseous Exposures of Senior Citizens Living in Baltimore,MD

ABSTRACT

We conducted a multi-pollutant exposure study in Baltimore, MD, in which 15 non-smoking older adult subjects (>64 years old) wore a multi-pollutant sampler for 12 days during the summer of 1998 and the winter of 1999. The sampler measured simultaneous 24-hr integrated personal exposures to PM₂₅, PM₁₀, SO₄ ^2-, O₃, NO₂, SO₂, and exhaust-related VOCs.

Results of this study showed that longitudinal associations between ambient PM_2.5 concentrations and corresponding personal exposures tended to be high in the summer (median Spearman's r = 0.74) and low in the winter (median Spearman's r = 0.25). Indoor ventilation was an important determinant of personal PM_2.5 exposures and resulting personal-ambient associations. Associations between personal PM₂₅ exposures and corresponding ambient concentrations were strongest for well-ventilated indoor environments and decreased with ventilation. This decrease was attributed to the increasing influence of indoor PM_{2 5} sources. Evidence for this was provided by SO₄ ^2-measurements, which can be thought of as a tracer for ambient PM₂₅. For SO₄ ^2-, personal-ambient associations were strong even in poorly ventilated indoor environments, suggesting that personal exposures to PM_2.5 of ambient origin are strongly associated with corresponding ambient concentrations. The results also indicated that the contribution of indoor PM_2.5 sources to personal PM_2.5 exposures was lowest when individuals spent the majority of their time in well-ventilated indoor environments.

Results also indicate that the potential for confounding by PM_2.5 co-pollutants is limited, despite significant correlations among ambient pollutant concentrations. In contrast to ambient concentrations, PM_2.5 exposures were not significantly correlated with personal exposures to PM_2.5-10, PM_2.5 of non-ambient origin, O₃, NO₂, and SO₂. Since a confounder must be associated with the exposure of interest, these results provide evidence that the effects observed in the PM_2.5 epidemiologic studies are unlikely to be due to confounding by the PM_2.5 co-pollutants measured in this study.     

Development and Preliminary Evaluation of a Particulate Matter Emission Factor Model for European Motor Vehicles

ABSTRACT

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 um, either from published data or from user-defined size distributions.

A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM₁₀, PM₅, PM₂₅, and PM₁] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway).

A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM₁₀ was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.     

Measurements of atmospheric aerosol size distributions by co-located optical particle counters

Ambient aerosol number concentrations and size distributions were measured in both indoor and outdoor environments using two identical co-located and concurrently operated optical particle counters (OPCs). Indoor measurements were performed in a research laboratory, whereas two different locations were used for outdoor measurements; the sampling duration exceeded 12 hours and one hour respectively. Results from the two OPCs have been presented for eight size classes between 0.5 and 20 [micro sign]m, represented by central value diameters 0.875, 1.5, 2.75, 4.25, 6.25, 8.75, 12.5 and 15 microm. Overall, for the six indoor and outdoor experiments conducted at different times of day, the mean particle count ratios from the two OPCs for the individual samples showed +/-20% variation for indoor experiments and +/-50% variations for outdoor experiments. Significant random departures of the mean ratios from unity at all size classes were noticed even for indoor sample periods exceeding 20 hours. However, the coefficient of determination (R(2)) for the plots of readings from the two OPCs indicated higher consistency for "fine" particles (0.5-3.5 microm) than for "coarse" particles (10-20 microm), with average R(2) > 0.8 and R(2) < 0.5 respectively. Poisson counting statistics help to explain the divergence in the latter case where number concentrations were very low for the outdoor experiments. However, it cannot explain the divergence for indoor measurements where the concentrations were much higher. Increasing the averaging period reduced the scatter, especially in size classes with low number concentration. However, this procedure may lead to over-smoothing of data for environments with rapidly changing number concentration. These results indicate that, when two such analysers are used for comparative studies, the divergence between their responses may generate significant values of source contribution or deposition flux, even for nominally similar aerosol populations.