Fugitive emissions opacity determination using the digital opacity compliance system (DOCS)

Maintenance of Department of Defense (DoD) weapon systems, conducting battlefield training exercises as well as meeting military construction and/or demolition schedules, invariably generate fugitive air emissions, many of which are visible. Although there is no codified federal method for quantifying fugitive emissions opacity, many state and local air regulatory agencies have instituted enforceable fugitive emission opacity standards at DoD facilities. The current study focused on comparing the performance of the digital opacity compliance system (DOCS) with U.S. Environment Protection Agency Method 9 (Method 9) certified human observers in quantifying the visible opacity associated with fugitive emissions produced using a commercial fog generator. By systematically repositioning both DOCS cameras and Method 9-certified observers during field testing, differences in method performance as a function of observational locations were documented. At both the 30- and 300-ft off-set distances, opacity levels reported by the DOCS technology and Method 9-certified smoke readers were found to be statistically different at the 99% confidence level. Alternatively, at the 90- and 150-ft off-set distances, results suggested that there was an insignificant difference at the 99% confidence level between the two methods. Comparing the magnitude of the each method's standard deviation suggested that, at the 30-ft off-set distance, the DOCS technology was consistently more precise than Method 9-certified readers regardless of the observer's downwind distance. However, at the 90, 150, and 300-ft off-set distances, method precision seemed to vary as a function of both off-set and downwind distance. The primary factor affecting the consistency in opacity measurements appeared to be the impact of ground-level air turbulence on fog plume dispersion and transport. Field observations demonstrated that localized wind shear played a critical and decisive role in how and to what extent fugitive emissions opacity could be determined, regardless of the method selected.     

Backwater Confluences of the Ohio River: Organic and Inorganic Fingerprints Explain Sediment Dynamics in Wetlands and Marinas

In the Ohio River (OR), backwater confluence sedimentation dynamics are understudied, however, these river features are expected to be influential on the system’s ecological and economic function when integrated along the river’s length. In the following paper, we test the efficacy of organic and inorganic tracers for sediment fingerprinting in backwater confluences; we use fingerprinting results to evidence sediment dynamics controlling deposition patterns in confluences used for wetland and marina functions; and we quantify the spatial extent of tributary drainages with wetland and marina features in OR confluences. Both organic and inorganic tracers statistically differentiate sediment from stream and river end‐members. Carbon and nitrogen stable isotopes produce greater uncertainty in fingerprinting results than inorganic elemental tracers. Uncertainty analysis of the nonconservative tracer term in the organic matter fingerprinting application estimates an apparent enrichment of the carbon stable isotopes during instream residence, and the nonconservativeness is quantified with a statistical approach unique to the fingerprinting literature. Wetland and marina features in OR confluences impact 42% and 11% of tributary drainage areas, respectively. Sediment dynamics show wetland and marina confluences experience deposition from river backwaters with longitudinally linear and nonlinear patterns, respectively, from sediment sources.     

Quantifying local traffic contributions to NO2 and NH3 concentrations in natural habitats

NO₂ and NH₃ concentrations were measured across a Special Area for Conservation in southern England, at varying distances from the local road network. Exceedances of the critical levels for these pollutants were recorded at nearly all roadside locations, extending up to 20 m away from roads at some sites. Further, paired measurements of NH₃ and NO₂ concentrations revealed differences between ground and tree canopy levels. At “background” sites, away from the direct influence of roads, concentrations were higher within tree canopies than at ground level; the reverse pattern was, however, seen at roadside locations. Calculations of pollutant deposition rates showed that nitrogen inputs are dominated by NH₃ at roadside sites. This study demonstrates that local traffic emissions contribute substantially to the exceedance of critical levels and critical loads, and suggests that on-site monitoring is needed for sites of nature conservation value which are in close proximity to local transport routes.     

Identification of transport processes in column experiments using a frequency domain approach

When a solute transport process is viewed as a dynamic system with input and output, a system identification technique can be used to study it from input-output data. According to the design of excitation signals in the system identification approach, the commonly used rectangular pulse as input signal for column experiments is not optimum because it does not simultaneously meet the requirements for exciting the studied transport process, i.e., possessing frequency components with high enough amplitude and wide enough passband. In this article, stepped sine signals were proposed to replace the rectangular pulse because their amplitude and passband can be independently chosen. The stepped sine signals of concentration were generated by a High Performance Liquid Chromatography (HPLC) and used as the input for the column experiments to identify parameters of the convection-dispersion equation (CDE) and mobile-immobile model (MIM). In order to test the effect of noise on the identification of transport process, numerical experiments were carried out to identify the CDE under white noise when the input was designed as stepped sine functions and rectangular pulse. The results of the numerical experiments showed that the input signal of a sine function was more robust and accurate in process identification than that of a rectangular pulse.     

Relationships between lichen community composition and concentrations of NO2 and NH3

The relationship between different features of lichen communities in Quercus robur canopies and environmental variables, including concentrations of NO₂ and NH₃ was investigated. NO₂ concentration was the most significant variable, it was positively correlated with the proportion of lichen cover comprising nitrophytes and negatively correlated with total lichen cover. None of the lichen community features were correlated with NH₃ concentrations, which were relatively low across the site. Since nitrophytes and nitrophobes are likely to react in opposite directions to nitrogenous compounds, total lichen cover is not a suitable indicator for these pollutants. It is, therefore, suggested that the proportion of lichen cover comprising nitrophytes may be a suitable simple indicator of air quality, particularly in locations where the pollution climate is dominated by oxides of nitrogen.     

Spatial characteristics of fine particulate matter: identifying representative monitoring locations in Seattle, Washington

This study investigates how PM2.5 varies spatially and how these spatial characteristics can be used to identify potential monitoring sites that are most representative of the overall ambient exposures to PM2.5 among susceptible populations in the Seattle, WA, area. Data collected at outdoor sites at the homes of participants of a large exposure assessment study were used in this study. Harvard impactors (HIs) were used at 40 outdoor sites throughout the Seattle metropolitan area. Up to six sites at a time were monitored for 10 consecutive 24-hr average periods. A fixed-effect analysis of variance (ANOVA) model that included date and location effects was used to analyze the spatial variability of outdoor PM2.5 concentrations. Both date and location effects were shown to be highly significant, explaining 92% of the variability in outdoor PM2.5 measurements. The day-to-day variability was 10 times higher than the spatial variability between sites. The site mean square was more than twice the error mean square, showing that differences between sites, while modest, are potentially an important contribution to measurement error. Variances of the model residuals and site effects were examined against spatial characteristics of the monitoring sites. The spatial characteristics included elevation, distance from arterials, and distance from major PM2.5 point sources. Results showed that the most representative PM2.5 sites were located at elevations of 80-120 m above sea level, and at distances of 100-300 m from the nearest arterial road. Location relative to industrial PM2.5 sources is not a significant predictor of residential outdoor PM2.5 measurements. Additionally, for sites to be representative of the average population exposures to PM2.5 among those highly susceptible to the health effects of PM2.5, areas of high elderly population density were considered. These representative spatial characteristics were used as multiple, overlapping criteria in a Geographic Information System (GIS) analysis to determine where the most representative sites are located.     

Source apportionment of indoor, outdoor, and personal PM2.5 in Seattle, Washington, using positive matrix factorization

As part of a large exposure assessment and health-effects panel study, 33 trace elements and light-absorbing carbon were measured on 24-hr fixed-site filter samples for particulate matter with an aerodynamic diameter <2.5 microm (PM2.5) collected between September 26, 2000, and May 25, 2001, at a central outdoor site, immediately outside each subject's residence, inside each residence, and on each subject (personal sample). Both two-way (PMF2) and three-way (PMF3) positive matrix factorization were used to deduce the sources contributing to PM2.5. Five sources contributing to the indoor and outdoor samples were identified: vegetative burning, mobile emissions, secondary sulfate, a source rich in chlorine, and a source of crustal-derived material. Vegetative burning contributed more PM2.5 mass on average than any other source in all microenvironments, with average values estimated by PMF2 and PMF3, respectively, of 7.6 and 8.7 microg/m3 for the outdoor samples, 4 and 5.3 microg/m3 for the indoor samples, and 3.8 and 3.4 microg/m3 for the personal samples. Personal exposure to the combustion-related particles was correlated with outdoor sources, whereas exposure to the crustal and chlorine-rich particles was not. Personal exposures to crustal sources were strongly associated with personal activities, especially time spent at school among the child subjects.     

Cadmium uptake by different rice genotypes that produce white or dark grains

IntroductionCadmium(Cd)isanon essentialtracemetalthathasadverseeffectsonplants,animalsandhumans.EnvironmentalcontaminationwithCdduetoanthropogenicactivities,suchasmining,industry,agricultureandwastedisposalhasbeenincreasingsincethebeginningofthe 2 0thcentury (Alloway,1995) .ResearchoncontrollingCdpollutionassociatedwithassessingandmanagingacuteinjurytohumanhealththroughoccupationalexposureanddisposalofCdfromindustrialpointsourcestolocalpopulationsthroughseveralpathwayshasmadeconsiderableadva…