Study of the uncertainty in NO<Subscript>2</Subscript> chemiluminescence measurements due to the NO–O<Subscript>3</Subscript> reaction in sampling lines

Introduction  

The change in light intensity that takes place when an ambient air sample is drawn into the detection chamber of a chemiluminescence monitor generates changes in the concentrations of several species, such as NO₂, NO and O₃. Although this phenomenon has been known for several decades, there is still no commonly accepted approach on when or how to correct for it in NO₂ and O₃ readings.     

Ecosystem Modeling Applied to Nutrient Criteria Development in Rivers

Threshold concentrations for biological impairment by nutrients are difficult to quantify in lotic systems, yet States and Tribes in the United States are charged with developing water quality criteria to protect these ecosystems from excessive enrichment. The analysis described in this article explores the use of the ecosystem model AQUATOX to investigate impairment thresholds keyed to biological indexes that can be simulated. The indexes selected for this exercise include percentage cyanobacterial biomass of sestonic algae, and benthic chlorophyll a. The calibrated model was used to analyze responses of these indexes to concurrent reductions in phosphorus, nitrogen, and suspended sediment in an enriched upper Midwestern river. Results suggest that the indexes would respond strongly to changes in phosphorus and suspended sediment, and less strongly to changes in nitrogen concentration. Using simulated concurrent reductions in all three water quality constituents, a total phosphorus concentration of 0.1 mg/l was identified as a threshold concentration, and therefore a hypothetical water quality criterion, for prevention of both excessive periphyton growth and sestonic cyanobacterial blooms. This kind of analysis is suggested as a way to evaluate multiple contrasting impacts of hypothetical nutrient and sediment reductions and to define nutrient criteria or target concentrations that balance multiple management objectives concurrently. Any opinions, findings, conclusions, or recommendations expressed in this article are those of the authors alone, and do not necessarily reflect the views of the U.S. Environmental Protection Agency or of the U.S. Government.     

Quantitative trace analysis of polyfluorinated alkyl substances (PFAS) in ambient air samples from Mace Head (Ireland): A method intercomparison

A method intercomparison study of analytical methods for the determination of neutral, volatile polyfluorinated alkyl substances (PFAS) was carried out in March, 2006. Environmental air samples were collected in triplicate at the European background site Mace Head on the west coast of Ireland, a site dominated by ‘clean’ westerly winds coming across the Atlantic. Extraction and analysis were performed at two laboratories active in PFAS research using their in-house methods. Airborne polyfluorinated telomer alcohols (FTOHs), fluorooctane sulfonamides and sulfonamidoethanols (FOSAs/FOSEs) as well as additional polyfluorinated compounds were investigated. Different native and isotope-labelled internal standards (IS) were applied at various steps in the analytical procedure to evaluate the different quantification strategies. Field blanks revealed no major blank problems. European background concentrations observed at Mace Head were found to be in a similar range to Arctic data reported in the literature. Due to trace-levels at the remote site, only FTOH data sets were complete and could therefore be compared between the laboratories. Additionally, FOSEs could partly be included. Data comparison revealed that despite the challenges inherent in analysis of airborne PFAS and the low concentrations, all methods applied in this study obtained similar results. However, application of isotope-labelled IS early in the analytical procedure leads to more precise results and is therefore recommended.     

Using LiDAR Data Analysis to Estimate Changes in Insolation Under Large‐Scale Riparian Deforestation1

Greenberg, Jonathan Asher, Erin L. Hestir, David Riano, George J. Scheer, and Susan L. Ustin, 2012. Using LiDAR Data Analysis to Estimate Changes in Insolation Under Large‐Scale Riparian Deforestation. Journal of the American Water Resources Association (JAWRA) 48(5): 939‐948. DOI: 10.1111/j.1752‐1688.2012.00664.x Abstract: Riparian vegetation provides shade from insolation to stream channels. A consequence of removing vegetation may be an increase in insolation that can increase water temperatures and negatively impact ecosystem health. Although the mechanisms of riparian shading are well understood, spatially explicit, mechanistic models of shading have been limited by the data requirements of precisely describing the three‐dimensional structure of a riparian corridor. Remotely acquired, high spatial resolution LiDAR data provide detailed three‐dimensional vegetation structure and terrain topography over large regions. By parameterizing solar radiation models that incorporate terrain shadowing with LiDAR data, we can produce spatially explicit estimates of insolation. As a case study, we modeled the relative change in insolation on channels in the Sacramento‐San Joaquin River Delta under current conditions and under a hypothesized deforested Delta using classified LiDAR, rasterized at a 1‐m resolution. Our results suggest that the removal of levee vegetation could result in a 9% increase in solar radiation incident on Delta waters, and may lead to water temperature increases. General, coarse‐scale channel characteristics (reach width, azimuth, levee vegetation cover, and height) only accounted for 72% of the variation in the insolation. This indicates that the detailed information derived from LiDAR data has greater explanatory power than coarser reach‐scale metrics often used for insolation estimates.     

Distribution of polybrominated diphenyl ethers and dust particle size fractions adherent to skin in indoor dust,Pretoria, South Africa

In order to determine human exposure to the indoor toxicant, selection of dust fraction and understanding dust particle size distribution in settled indoor dust are very important. This study examined the influence of dust particle size on the concentration of polybrominated diphenyl ethers (PBDEs) congeners, assessed the distribution of dust particle size and characterized the main indoor emission sources of PBDEs. Accordingly, the concentrations of PBDE congeners determined in different indoor dust fractions were found to be relatively higher in the order of dust particle size: 45–106 μm?>?(<45 μm)?>?106–150 μm. The finding shows arbitrary selection of dust fractions for exposure determination may result in wrong conclusions. Statistically significant moderate correlation between the concentration of Σ₉PBDEs and organic matter content calculated with respect to the total dust mass was also observed (r?=?0.55, p?=?0.001). On average, of total dust particle size <250 μm, 93.4 % (m/m%) of dust fractions was associated with less than 150 μm. Furthermore, of skin adherent dust fractions considered (<150 μm), 86 % (v/v%) is in the range of particle size 9.25–104.7 μm. Electronic materials treated with PBDEs were found the main emission sources of PBDE congeners in indoor environment. Based on concentrations of PBDEs determined and mass of indoor dust observed, 150 μm metallic sieve is adequate for human exposure risk assessment. However, research in this area is very limited and more research is required to generalize the fact.     

Predicting emissions from oil and gas operations in the Uinta Basin,Utah

In this study, emissions of ozone precursors from oil and gas operations in Utah’s Uinta Basin are predicted (with uncertainty estimates) from 2015–2019 using a Monte-Carlo model of (a) drilling and production activity, and (b) emission factors. Cross-validation tests against actual drilling and production data from 2010–2014 show that the model can accurately predict both types of activities, returning median results that are within 5% of actual values for drilling, 0.1% for oil production, and 4% for gas production. A variety of one-time (drilling) and ongoing (oil and gas production) emission factors for greenhouse gases, methane, and volatile organic compounds (VOCs) are applied to the predicted oil and gas operations. Based on the range of emission factor values reported in the literature, emissions from well completions are the most significant source of emissions, followed by gas transmission and production. We estimate that the annual average VOC emissions rate for the oil and gas industry over the 2010–2015 time period was 44.2E+06 (mean) ± 12.8E+06 (standard deviation) kg VOCs per year (with all applicable emissions reductions). On the same basis, over the 2015–2019 period annual average VOC emissions from oil and gas operations are expected to drop 45% to 24.2E+06 ± 3.43E+06 kg VOCs per year, due to decreases in drilling activity and tighter emission standards.

Implications: This study improves upon previous methods for estimating emissions of ozone precursors from oil and gas operations in Utah’s Uinta Basin by tracking one-time and ongoing emission events on a well-by-well basis. The proposed method has proven highly accurate at predicting drilling and production activity and includes uncertainty estimates to describe the range of potential emissions inventory outcomes. If similar input data are available in other oil and gas producing regions, then the method developed here could be applied to those regions as well.     

Regional Risk Assessment addressing the impacts of climate change in the coastal area of the Gulf of Gabes (Tunisia)

Sound, cost efficient management strategies in developed coastal zones can be reinforced by a thorough understanding of risks associated with the combination of anthropogenic and natural drivers of change. A Regional Risk Assessment (RRA) methodology was developed for the assessment of the potential impacts of climate change in the Tunisian coastal zone of the Gulf of Gabes. It is based on the use of Multi-Criteria Decision Analysis techniques and Geographic Information Systems and is designed to support the development and prioritization of adaptation strategies. The RRA focuses on sea-level rise and storm surge flooding impacts for human and natural systems, i.e., beaches, wetlands, urban areas, agricultural areas, and terrestrial ecosystems. Results suggest that for both of the studied climate change impacts, i.e., sea-level rise and storm surge flooding, the area potentially exposed is limited to a narrow, low elevation region adjacent to the shoreline. However, the exposed areas showed a high relative risk score, obtained by the integration of exposure and susceptibility factors. Beaches have the lowest relative risk scores, while wetlands and terrestrial ecosystems have the higher relative risk scores. The final outputs of the analysis (i.e., exposure, susceptibility, and risk maps) can support end-users in the establishment of relative priorities for intervention and in the identification of suitable areas for human settlements, infrastructure, and economic activities, thus providing a basis for coastal zoning and land-use planning.     

Estimating Overall Sample Train Efficiency

A common part of many gas analyses using bubblers is to combine the contents of the first n-1 impingers and analyze them separate from the nth. The nth impinger, yielding as it should a nil result, confirms that all of the sample entering the train was caught and that the concentration calculated therefrom represents the “true” value.

Many a hapless analyst has found himself stuck with nonzero nth impingers on occasion. Bemgloath tb reject the whole test, the analyst will often report the concentration based on the total catch (with appropriate qualifiers, of course). Another common practice is to calculate the percentage of the total catch in the first n-1 impingers. Sometimes this is reported, erroneously, as the sampler efficiency. The true sampler efficiency cannot be known (if it is less than 100%) because the presence of sample in the last impinger indicates that some unknown amount has passed through the train entirely.     

Performance and Diagnostic Evaluation of Ozone Predictions by the Eta-Community Multiscale Air Quality Forecast System during the 2002 New England Air Quality Study

Abstract

A real-time air quality forecasting system (Eta-Community Multiscale Air Quality [CMAQ] model suite) has been developed by linking the National Centers for Environmental Estimation Eta model to the U.S. Environmental Protection Agency (EPA) CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting ozone (O₃) over the Northeastern United States during the 2002 New England Air Quality Study (NEAQS). Spatial and temporal performance of the Eta-CMAQ model for O₃ was evaluated by comparison with observations from the EPA Air Quality System (AQS) network. This study also examines the ability of the model to simulate the processes governing the distributions of tropospheric O₃ on the basis of the intensive datasets obtained at the four Atmospheric Investigation, Regional Modeling, Analysis, and Estimation (AIRMAP) and Harvard Forest (HF) surface sites. The episode analysis reveals that the model captured the buildup of O₃ concentrations over the northeastern domain from August 11 and reproduced the spatial distributions of observed O₃ very well for the daytime (8:00 p.m.) of both August 8 and 12 with most of normalized mean bias (NMB) within [H11006]20%. The model reproduced 53.3% of the observed hourly O₃ within a factor of 1.5 with NMB of 29.7% and normalized mean error of 46.9% at the 342 AQS sites.The comparison of modeled and observed lidar O₃ vertical profiles shows that whereas the model reproduced the observed vertical structure, it tended to overestimate at higher altitude. The model reproduced 64 –77% of observed NO₂ photolysis rate values within a factor of 1.5 at the AIRMAP sites. At the HF site, comparison of modeled and observed O₃/nitrogen oxide (NO_x) ratios suggests that the site is mainly under strongly NO_x-sensitive conditions (>53%). It was found that the modeled lower limits of the O₃ production efficiency values (inferred from O₃-CO correlation) are close to the observations.