Analysis and apportionment of organic carbon and fine particulate matter sources at multiple sites in the midwestern United States

Speciated fine particulate matter (PM2.5) data collected as part of the Speciation Trends Network at four sites in the Midwest (Detroit, MI; Cincinnati, OH; Indianapolis, IN; and Northbrook, IL) and as part of the Interagency Monitoring of Protected Visual Environments program at the rural Bondville, IL, site were analyzed to understand sources contributing to organic carbon (OC) and PM2.5 mass. Positive matrix factorization (PMF) was applied to available data collected from January 2002 through March 2005, and seven to nine factors were identified at each site. Common factors at all of the sites included mobile (gasoline)/secondary organic aerosols with high OC, diesel with a high elemental carbon/OC ratio (only at the urban sites), secondary sulfate, secondary nitrate, soil, and biomass burning. Identified industrial factors included copper smelting (Northbrook, Indianapolis, and Bondville), steel/manufacturing with iron (Northbrook), industrial zinc (Northbrook, Cincinnati, Indianapolis, and Detroit), metal plating with chromium and nickel (Detroit, Indianapolis, and Bondville), mixed industrial with copper and iron (Cincinnati), and limestone with calcium and iron (Bondville). PMF results, on average, accounted for 96% of the measured PM2.5 mass at each site; residuals were consistently within tolerance (+/-3), and goodness-of-fit (Q) was acceptable. Potential source contribution function analysis helped identify regional and local impacts of the identified source types. Secondary sulfate and soil factors showed regional characteristics at each site, whereas industrial sources typically appeared to be locally influenced. These regional factors contributed approximately one third of the total PM2.5 mass, on average, whereas local mobile and industrial sources contributed to the remaining mass. Mobile sources were a major contributor (55-76% at the urban sites) to OC mass, generally with at least twice as much mass from nondiesel sources as from diesel. Regional OC associated with secondary sulfate and soil was generally low.     

Source apportionment of fine particulate matter in Phoenix, AZ, using positive matrix factorization

Speciated particulate matter (PM)2.5 data collected as part of the Interagency Monitoring of Protected Visual Environments (IMPROVE) program in Phoenix, AZ, from April 2001 through October 2003 were analyzed using the multivariate receptor model, positive matrix factorization (PMF). Over 250 samples and 24 species were used, including the organic carbon and elemental carbon analytical temperature fractions from the thermal optical reflectance method. A two-step approach was used. First, the species excluding the carbon fractions were used, and initially eight factors were identified; non-soil potassium was calculated and included to better refine the burning factor. Next, the mass associated with the burning factor was removed, and the data set rerun with the carbon fractions. Results were very similar (i.e., within a few percent), but this step enabled a separation of the mobile factor into gasoline and diesel vehicle emissions. The identified factors were burning (on average 2% of the mass), secondary transport (7%), regional power generation (13%), dust (25%), nitrate (9%), industrial As/Pb/Se (2%), Cu/Ni/V (7%), diesel (9%), and general mobile (26%). The overall contribution from mobile sources also increased, as some mass (OC and nitrate) from the nitrate and regional power generation factors were apportioned with the mobile factors. This approach allowed better apportionment of carbon as well as total mass. Additionally, the use of multiple supporting analyses, including air mass trajectories, activity trends, and emission inventory information, helped increase confidence in factor identification.     

Evaluation of Absorption Sampling Devices

The information presented in this paper is directed to those with the responsibility of designing and operating air quality monitoring networks. An analytical model for location of monitor sites based upon maximizing a sum of coverage factors for each source is developed. An heuristic solution method from the facilities location analysis literature is used for solution of the model. Results of an example problem are presented and compared with the monitoring network currently In place. The model is shown to be a valuable addition to the methods available to the air quality monitor network designer. Needs for further research are pointed out.     

Variation partitioning involving orthogonal spatial eigenfunction submodels

When partitioning the variation of univariate or multivariate ecological data with respect to several submodels of spatial eigenfunctions (e.g., Moran's eigenvector maps, MEM) acting as explanatory data, a problem occurs: although the submodels are constructed to be orthogonal to one another, the partitioning based on adjusted R2 statistics produces nonzero values in the intersections between spatial submodels. This phenomenon is described and two solutions are proposed. The first solution is to apportion the intersection fractions proportionally to the variation explained by each submodel. The second solution consists in creating a hierarchy among the spatial submodels, in accordance with hierarchy theory. These solutions lead to new partitioning equations that are described in the Appendix. R functions are provided to carry out partitioning with respect to environmental variables and spatial eigenfunction submodels. This development is important for the correct interpretation of spatial modeling results implying explanatory environmental data as well as submodels of spatial eigenfunctions involving two or more spatial scales.     

Uncertain sightings and the extinction of the Ivory-billed Woodpecker

The extinction of a species can be inferred from a record of its sightings. Existing methods for doing so assume that all sightings in the record are valid. Often, however, there are sightings of uncertain validity. To date, uncertain sightings have been treated in an ad hoc way, either excluding them from the record or including them as if they were certain. We developed a Bayesian method that formally accounts for such uncertain sightings. The method assumes that valid and invalid sightings follow independent Poisson processes and use noninformative prior distributions for the rate of valid sightings and for a measure of the quality of uncertain sightings. We applied the method to a recently published record of sightings of the Ivory-billed Woodpecker (Campephilus principalis). This record covers the period 1897-2010 and contains 39 sightings classified as certain and 29 classified as uncertain. The Bayes factor in favor of extinction was 4.03, which constitutes substantial support for extinction. The posterior distribution of the time of extinction has 3 main modes in 1944, 1952, and 1988. The method can be applied to sighting records of other purportedly extinct species.     

Weekday versus weekend activity patterns for ozone precursor emissions in California's South Coast Air Basin

Ambient O3 concentrations in California's South Coast Air Basin (SoCAB) can be as much as 55% higher on weekends than on weekdays under comparable meteorological conditions. This is paradoxical because emissions of O3 precursors (hydrocarbons, CO, and nitrogen oxides [NOx]) are lower on weekends. Day-of-week emissions activity data were collected and analyzed to investigate the hypothesized causes of the "weekend O3 effect." Emission activity data were collected for various mobile, area, and point sources throughout the SoCAB, including on-road vehicles, lawn and garden equipment, barbecues, fireplaces, solvent use, and point sources with continuous emission monitoring data. The results of this study indicate significant differences between weekday and weekend emission activity patterns and emissions. Their combined effect results in a 12-18% decrease in reactive organic gases (ROGs) and a 35-41% decrease in NOx emissions on Saturdays and Sundays, respectively, relative to weekdays in summer 2000. These changes in emissions result in an increase of more than 30% in the ROG/NOx ratio on weekends compared with weekdays, which, along with lower NOx emissions, leads to increased O3 production on weekends.     

Autoradiographic studies of ethylenediurea distribution in woody plants

Carbon-14-labelled ethylenediurea (EDU), synthesised from diethylenetriamine and (14)C-urea, was stem-injected into 2-year-old seedlings of sugar maple, white ash, flowering dogwood and flowering crabapple. At time intervals ranging from 1 h to 42 days after treatment, macroautoradiographs of leaf, stem and root tissue were made to determine relative distribution patterns of labelled chemical. Translocation of (14)C-EDU was very rapid and predominantly acropetal, especially after the first few hours. Maximum quantities of (14)C were found in leaf tissue approximately 7-10 days following injection, after which the intensity of the labelled chemical declined over the remainder of the study (42 days). Distribution patterns of (14)C-EDU were correlated with observed levels of protection afforded most plants when the chemical is injected 7 days before fumigation with ozone.     

Extrapolating cetacean densities to quantitatively assess human impacts on populations in the high seas

As human activities expand beyond national jurisdictions to the high seas, there is an increasing need to consider anthropogenic impacts to species inhabiting these waters. The current scarcity of scientific observations of cetaceans in the high seas impedes the assessment of population‐level impacts of these activities. We developed plausible density estimates to facilitate a quantitative assessment of anthropogenic impacts on cetacean populations in these waters. Our study region extended from a well‐surveyed region within the U.S. Exclusive Economic Zone into a large region of the western North Atlantic sparsely surveyed for cetaceans. We modeled densities of 15 cetacean taxa with available line transect survey data and habitat covariates and extrapolated predictions to sparsely surveyed regions. We formulated models to reduce the extent of extrapolation beyond covariate ranges, and constrained them to model simple and generalizable relationships. To evaluate confidence in the predictions, we mapped where predictions were made outside sampled covariate ranges, examined alternate models, and compared predicted densities with maps of sightings from sources that could not be integrated into our models. Confidence levels in model results depended on the taxon and geographic area and highlighted the need for additional surveying in environmentally distinct areas. With application of necessary caution, our density estimates can inform management needs in the high seas, such as the quantification of potential cetacean interactions with military training exercises, shipping, fisheries, and deep‐sea mining and be used to delineate areas of special biological significance in international waters. Our approach is generally applicable to other marine taxa and geographic regions for which management will be implemented but data are sparse.     

Effect of eight common Brazilian drugs on Lemna minor and Salvinia auriculata growth

Environmental Science and Pollution Research - The growth of two species of macrophytes (Lemna minor and Salvinia auriculata) under the effect of a mixture of amoxicillin, caffeine, carbamazepine,...     

The perpetual state of emergency that sacrifices protected areas in a changing climate

A modern challenge for conservation biology is to assess the consequences of policies that adhere to assumptions of stationarity (e.g., historic norms) in an era of global environmental change. Such policies may result in unexpected and surprising levels of mitigation given future climate‐change trajectories, especially as agriculture looks to protected areas to buffer against production losses during periods of environmental extremes. We assessed the potential impact of climate‐change scenarios on the rates at which grasslands enrolled in the Conservation Reserve Program (CRP) are authorized for emergency harvesting (i.e., biomass removal) for agricultural use, which can occur when precipitation for the previous 4 months is below 40% of the normal or historical mean precipitation for that 4‐month period. We developed and analyzed scenarios under the condition that policy will continue to operate under assumptions of stationarity, thereby authorizing emergency biomass harvesting solely as a function of precipitation departure from historic norms. Model projections showed the historical likelihood of authorizing emergency biomass harvesting in any given year in the northern Great Plains was 33.28% based on long‐term weather records. Emergency biomass harvesting became the norm (>50% of years) in the scenario that reflected continued increases in emissions and a decrease in growing‐season precipitation, and areas in the Great Plains with higher historical mean annual rainfall were disproportionately affected and were subject to a greater increase in emergency biomass removal. Emergency biomass harvesting decreased only in the scenario with rapid reductions in emissions. Our scenario‐impact analysis indicated that biomass from lands enrolled in the CRP would be used primarily as a buffer for agriculture in an era of climatic change unless policy guidelines are adapted or climate‐change projections significantly depart from the current consensus.