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.     

UV-VIS spectroscopy of 2,4,6-trinitrotoluene-hydroxide reaction

Contamination of groundwater, surface water and soil by explosives has occurred at military sites throughout the world as a result of manufacture of explosive compounds, assembly of munitions, and deployment of explosives containing devices. Due to the adverse effects of explosives on humans and other natural receptors, a low cost means of decontaminating these areas of contamination is needed. Base-induced transformation of explosives has shown promise as a rapid, low cost, and minimally resource-intensive technology for detoxifying explosives in soil and water. In order to understand the reaction mechanism, a reaction mixture of 2:1:1 (water:2,4,6-trinitrotoluene (TNT):1 N KOH) was analyzed by UV/VIS spectrometry from 190 to 1,100 nm. Time course measurements were conducted at 25, 20, 15, and 12 degrees C. A factor analysis program was used to analyze the spectral data. Principal component analysis indicated that six principal components explained the spectra to within experimental error, with four factors explaining the majority of the variance. Test spectral vectors for four components were developed, including TNT, two intermediates, and the final product, and were tested against the abstract vectors. Two possible reaction mechanisms were suggested and tested to explain the spectral data.     

Are sustainable cities “happy” cities? Associations between sustainable development and human well-being in urban areas of the United States

In this paper, we assess the associations between self-reported happiness, measured using the Gallup Healthways Well-Being Index (2012), and four US city sustainability indices: the Green City Index (2011), Our Green Cities (2012), Popular Science US City Rankings (2008) and the SustainLane US Green City Rankings (2007). Based on the examination of nonparametric, rank-based correlations, we found positive associations between sustainable development and happiness on all scales and statistically significant correlations for two of the four SD indices. Results support previous research, emphasize the value of explicit consideration of happiness when measuring urban sustainability and highlight the need for future research that assesses the influence of specific subsystems of urban development on self-reported happiness.     

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.     

Modeling traffic air pollution in street canyons in New York City for intra-urban exposure assessment in the US Multi-Ethnic Study of atherosclerosis and air pollution

We evaluated the Danish AirGIS air quality and exposure model system using air quality measurement data from New York City in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Measurements were used from three US EPA Air Quality System (AQS) monitoring stations and a comprehensive MESA Air measurement campaign including about 150 different locations and about 650 samples of about 2 week measurements of NO_x, NO₂ and PM_2.5. AirGIS is a deterministic exposure model system based on the dispersion models Operational Street Pollution Model (OSPM) and the Urban Background Model (UBM). The UBM model reproduced the annual levels within 1–26% depending on station and pollutant at the three urban background EPA monitor stations, and generally reproduced well the seasonal and diurnal variation. The full model with OSPM and UBM reproduced the MESA Air measurements with a correlation coefficient of r² = 0.51 for NO_x, r² = 0.28 for NO₂ and r² = 0.73 for PM_2.5.     

Loading effect correction for real-time aethalometer measurements of fresh diesel soot

In this study, a correction was developed for the aethalometer to measure real-time black carbon (BC) concentrations in an environment dominated by fresh diesel soot. The relationship between the actual mass-specific absorption coefficient for BC and the BC-dependent attenuation coefficients was determined from experiments conducted in a diesel exposure chamber that provided constant concentrations of fine particulate matter (PM; PM(2.5); PM < 2.5 microm in aerodynamic diameter) from diesel exhaust. The aethalometer reported BC concentrations decreasing with time from 48.1 to 31.5 microg m(-3) when exposed to constant PM(2.5) concentrations of 55 +/- 1 microg m(-3) and b(scat) = 95 +/- 3 Mm(-1) from diesel exhaust. This apparent decrease in reported light-absorbing PM concentration was used to derive a correction K(ATN) for loading of strong light-absorbing particles onto or into the aethalometer filter tape, which was a function of attenuation of light at 880 nm by the embedded particles.     

Climatic niche divergence or conservatism? Environmental niches and range limits in ecologically similar damselflies

The factors that determine species' range limits are of central interest to biologists. One particularly interesting group comprises odonates (dragonflies and damselflies), which show large differences in secondary sexual traits and respond quickly to climatic factors, but often have minor interspecific niche differences, challenging models of niche-based species coexistence. We quantified the environmental niches at two geographic scales to understand the ecological causes of northern range limits and the coexistence of two congeneric damselflies (Calopteryx splendens and C. virgo). Using environmental niche modeling, we quantified niche divergence first across the whole geographic range in Fennoscandia, and second only in the sympatric part of this range. We found evidence for interspecific divergence along the environmental axes of temperature and precipitation across the northern range in Fennoscandia, suggesting that adaptation to colder and wetter climate might have allowed C. virgo to expand farther north than C. splendens. However, in the sympatric zone in southern Fennoscandia we found only negligible and nonsignificant niche differences. Minor niche differences in sympatry lead to frequent encounters and intense interspecific sexual interactions at the local scale of populations. Nevertheless, niche differences across Fennoscandia suggest that species differences in physiological tolerances limit range expansions northward, and that current and future climate could have large effects on the distributional ranges of these and ecologically similar insects.     

The environment as a factor of production

This paper uses firm-level data about electric utilities to develop an empirical model of how electric utilities use and bank SO₂ pollution permits under the Acid Rain Program. The empirical model considers emissions, fuels, and labor as variable inputs with quasi-fixed stocks of permits and capital. Consequently, substitution possibilities between the environment and other production factors can be measured and tested. The results reveal substantial substitution between emissions, permit stocks, capital, fuel, and labor. The empirical findings also indicate that firms bank permits primarily as a hedge against uncertainty and for other firm-specific reasons. Overall, the results suggest that cap-and-trade approaches can reduce the cost of meeting environmental goals by providing a mechanism for addressing regulatory and market risks and by signaling an appropriate price for factor use, especially irreversible capital investments.     

Comparing universal kriging and land-use regression for predicting concentrations of gaseous oxides of nitrogen (NOx) for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

BACKGROUND: Epidemiological studies that assess the health effects of long-term exposure to ambient air pollution are used to inform public policy. These studies rely on exposure models that use data collected from pollution monitoring sites to predict exposures at subject locations. Land use regression (LUR) and universal kriging (UK) have been suggested as potential prediction methods. We evaluate these approaches on a dataset including measurements from three seasons in Los Angeles, CA. METHODS: The measurements of gaseous oxides of nitrogen (NOx) used in this study are from a "snapshot" sampling campaign that is part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). The measurements in Los Angeles were collected during three two-week periods in the summer, autumn, and winter, each with about 150 sites. The design included clusters of monitors on either side of busy roads to capture near-field gradients of traffic-related pollution. LUR and UK prediction models were created using geographic information system (GIS)-based covariates. Selection of covariates was based on 10-fold cross-validated (CV) R(2) and root mean square error (RMSE). Since UK requires specialized software, a computationally simpler two-step procedure was also employed to approximate fitting the UK model using readily available regression and GIS software. RESULTS: UK models consistently performed as well as or better than the analogous LUR models. The best CV R(2) values for season-specific UK models predicting log(NOx) were 0.75, 0.72, and 0.74 (CV RMSE 0.20, 0.17, and 0.15) for summer, autumn, and winter, respectively. The best CV R(2) values for season-specific LUR models predicting log(NOx) were 0.74, 0.60, and 0.67 (CV RMSE 0.20, 0.20, and 0.17). The two-stage approximation to UK also performed better than LUR and nearly as well as the full UK model with CV R(2) values 0.75, 0.70, and 0.70 (CV RMSE 0.20, 0.17, and 0.17) for summer, autumn, and winter, respectively. CONCLUSION: High quality LUR and UK prediction models for NOx in Los Angeles were developed for the three seasons based on data collected for MESA Air. In our study, UK consistently outperformed LUR. Similarly, the 2-step approach was more effective than the LUR models, with performance equal to or slightly worse than UK.     

Distribution and dietary regulation of an associated facultative Rhizobiales-related bacterium in the omnivorous giant tropical ant,Paraponera clavata

We document a facultative Bartonella-like Rhizobiales bacterium in the giant tropical ant, Paraponera clavata. In a lowland tropical rainforest in Costa Rica, 59 colonies were assayed for the prevalence of the Bartonella-like bacterium (BLB), 14 of which were positive. We addressed three questions: First, how does the prevalence of BLB within colonies vary with environmental conditions? Second, how does diet affect the prevalence of BLB in P. clavata? Third, how does the distribution of BLB among colonies reflect ambient differences in food resources and foraging habits? A variety of environmental variables that may be predictive of the presence of BLB were measured, and diet manipulations were conducted to test whether the prevalence of BLB responded to supplemental carbohydrate or prey. The ambient frequency of BLB is much higher in young secondary forests, but is nearly absent from older secondary forests. The prevalence of BLB inside field colonies increased over the duration of a 2-week carbohydrate supplementation; however, water and prey supplementation did not alter the prevalence of BLB. The diets of the colonies located in young secondary forest, compared to other habitats, have a diet richer in carbohydrates and lower in prey. The abundance of carbohydrate, or the relative lack of N, in a colony’s diet influences the occurrence of the BLB microbe in P. clavata. As experimental diet manipulations can affect the facultative presence of an N-cycling microbe, a consistent diet shift in diet may facilitate the emergence of tighter symbioses.