Health risk assessment posed by primary diesel particulate matter and vapor air toxics in Southeastern US

Air toxics concentrations and health effects that come from different sources emission scenarios by linking Models-3/CMAQ and cancer risk assessment were predicted. The year 1999 was used to emissions inventory and the year 2003 for meteorological data and modeling performance. To demonstrate the system's effectiveness, this study was performed on priority mobile sources air toxics; benzene, 1,3-butadiene, formaldehyde, acetaldehyde, and diesel particulate matter (DPM). The analysis was applied mainly to Nashville in the Southeastern US. Ten emissions scenarios were selected to compare the principal results. DPM posed a cancer risk that was 4.2 times higher than the combined total cancer risk from all other four air toxics. Those high cancer risk levels were due mainly to non-road sources (57.9%). For the on-road diesel fueled sources, the principal reductions were due to the DPM generated by heavy duty diesel vehicles. The main on-road reductions were due to the air toxics generated by gasoline light duty vehicles, principally benzene and 1,3-butadiene. Reducing ambient DPM concentrations would lead to improvement in human health more than other air toxics, indicating that better technologies and regulations must be applied to the mobile diesel engines, principally, over non-road diesel sources. This is an abstract of a paper presented at the AWMA's 99th Annual Conference and Exhibition (New Orleans, LA 6/20-23/2006)

Modeling and source apportionment of diesel particulate matter

The fine and ultra fine sizes of diesel particulate matter (DPM) are of greatest health concern. The composition of these primary and secondary fine and ultra fine particles is principally elemental carbon (EC) with adsorbed organic compounds, sulfate, nitrate, ammonia, metals, and other trace elements. The purpose of this study was to use an advanced air quality modeling technique to predict and analyze the emissions and the primary and secondary aerosols concentrations that come from diesel-fueled sources (DFS). The National Emissions Inventory for 1999 and a severe southeast ozone episode that occurred between August and September 1999 were used as reference. Five urban areas and one rural area in the Southeastern US were selected to compare the main results. For urban emissions, results showed that DFS contributed (77.9% ± 8.0) of EC, (16.8% ± 8.2) of organic aerosols, (14.3% ± 6.2) of nitrate, and (8.3% ± 6.6) of sulfate during the selected episodes. For the rural site, these contributions were lower. The highest DFS contribution on EC emissions was allocated in Memphis, due mainly to diesel non-road sources (60.9%). For ambient concentrations, DFS contributed (69.5% ± 6.5) of EC and (10.8% ± 2.4) of primary anthropogenic organic aerosols, where the highest DFS contributions on EC were allocated in Nashville and Memphis on that episode. The DFS contributed (8.3% ± 1.2) of the total ambient PM2.5 at the analyzed sites. The maximum primary DPM concentration occurred in Atlanta (1.44 μg/m3), which was 3.8 times higher than that from the rural site. Non-linearity issues were encountered and recommendations were made for further research. The results indicated significant geographic variability in the EC contribution from DFS, and the main DPM sources in the Southeastern U.S. were the non-road DFS. The results of this work will be helpful in addressing policy issues targeted at designing control strategies on DFS in the Southeastern U.S

A hybrid ARIMA and artificial neural networks model to forecast particulate matter in urban areas: The case of Temuco, Chile

Box-Jenkins Time Series (ARIMA) and the multivariate linear models (MLM) have been important and popular linear tools in air quality forecasting during the past decade for urban areas. On the other hand, artificial neural networks (ANN) recently have been used successfully as a nonlinear tool in several research studies of pollution forecasting. A hybrid model that combines both ARIMA and ANN tools was proposed to improve the unique capabilities of ARIMA and ANN tools in linear and non linear modeling on particulate matter forecasting. To examine the effectiveness of the proposed hybrid model over real particulate matter data, the time series of PM10 and meteorological data observed in ambient air during 2000-2006 at a site in Temuco, Chile, was used In 2005, this city was declared a non-attainment area for PM10, whose pollution is the result of a great economic growth, a fast urban expansion, woodstoves, industrial sources, and a strong diesel vehicles growth. Experimental results with meteorological and PM10 data sets indicated that the hybrid model can be an effective tool to improve the forecasting accuracy obtained by either of the models used separately, and compared with a statistical multivariate linear regression. This is an abstract of a paper presented at the 100th Annual Conference and Exhibition of the Air and Waste Management Association 2007 (Pittsburgh, PA, 6/26-29/2007)

The effect of switching mobile sources to natural gas on the ozone in the great smoky mountains national park

Mobile sources are among the largest contributors of NOx in the Great Smoky Mountains National Park region (GSMNP). In 2001, these sources contributed 45% of NOx emissions. From 1990 to 2001, the growth of vehicle miles traveled (VMT) increased 60% and 55% in neighboring Sevier and Blount counties respectively. These emissions combined with the high volatile organic compounds (VOC) emissions in the Southeast area have caused the ozone ground level concentration to be as high as some major metropolitan areas in the summer season. In 2001, the maximum 8-hr ozone concentration inside the park was 103 parts per billion. In response to high ozone levels in other areas, federal, state, and local governments are promoting the use of alternative, clean, and reformulated fuel vehicles as a means to improve local air pollution. One of these fuels is compressed natural gas (CNG). The purpose of this project was to use USEPA's CMAQ system in order to model the air quality and compare the ozone ground level formation in the GSMNP from light duty vehicles (LDVs) operating with 100% CNG within 100 miles around GSMNP. A severe southeast ozone episode between August and September 1999 was used as a reference and 2004 was used as a future case. Results showed that LDVs fueled with 100% CNG in the domain could reduce ozone level by 10% and 8% for 1-hr and 8-hr ozone formation respectively in the GSMNP on the modeled time period. Scavenging occurred around the GSMNP in the morning time during the selected episode

Interspecies Differences in the Metabolism of a Multiester Prodrug by Carboxylesterases

The penta-ethyl ester prodrug of the chelating agent diethylene triamine pentaacetic acid (DTPA) referred to as C2E5, is being developed as an orally bioavailable radionuclide decorporation agent. The predicted human efficacy obtained in these experimental animals is confounded by interspecies variations of metabolism. Therefore, in the present study, carboxylesterase-mediated metabolism of [14C]-C2E5 was compared in the S9 intestinal and hepatic fractions of human, dog and rat and their respective plasma. Intestinal hydrolysis of C2E5, resulting in the formation of the tetraethyl ester of DTPA (C2E4), was only detected in human and rat. The primary metabolite in human and dog hepatic fractions was C2E4 whereas the predominant species identified in rat hepatic fractions was the triethyl ester (C2E3). Hepatic hydrolysis of C2E5 causes the formation of C2E4 in human, dog and rat and C2E3 in rat only. Minimal C2E5 hydrolysis was observed in human and dog plasma whereas in rat plasma C2E5 converted to C2E3 rapidly, followed by slower further metabolism. Both recombinant CES1 and CES2 play roles in C2E5 metabolism. Together, these data suggest that dogs may be the most appropriate species for predicting human C2E5 metabolism whereas rats might be useful for clarifying the potential toxicity of C2E5 metabolites

A hybrid ARIMA and artificial neural networks model to forecast particulate matter in urban areas: The case of Temuco, Chile

Air quality time series consists of complex linear and non-linear patterns and are difficult to forecast. Box-Jenkins Time Series (ARIMA) and multilinear regression (MLR) models have been applied to air quality forecasting in urban areas, but they have limited accuracy owing to their inability to predict extreme events. Artificial neural networks (ANN) can recognize non-linear patterns that include extremes. A novel hybrid model combining ARIMA and ANN to improve forecast accuracy for an area with limited air quality and meteorological data was applied to Temuco, Chile, where residential wood burning is a major pollution source during cold winters, using surface meteorological and PM10 measurements. Experimental results indicated that the hybrid model can be an effective tool to improve the PM10 forecasting accuracy obtained by either of the models used separately, and compared with a deterministic MLR. The hybrid model was able to capture 100% and 80% of alert and pre-emergency episodes, respectively. This approach demonstrates the potential to be applied to air quality forecasting in other cities and countries

Study of flare energy release using events with numerous type III-like bursts in microwaves

The analysis of narrowband drifting of type III-like structures in radio bursts dynamic spectra allows to obtain unique information about primary energy release mechanisms in solar flares. The SSRT spatially resolved images and a high spectral and temporal resolution allow direct determination not only the positions of its sources but also the exciter velocities along the flare loop. Practically, such measurements are possible during some special time intervals when the SSRT (about 5.7 GHz) is observing the flare region in two high-order fringes; thus, two 1D scans are recorded simultaneously at two frequency bands. The analysis of type III-like bursts recorded during the flare 14 Apr 2002 is presented. Using-muliwavelength radio observations recorded by SSRT, SBRS, NoRP, RSTN we study an event with series of several tens of drifting microwave pulses with drift rates in the range from -7 to 13 GHz/s. The sources of the fast-drifting bursts were located near the top of the flare loop in a volume of a few Mm in size. The slow drift of the exciters along the flare loop suggests a high pitch-anisotropy of the emitting electrons.Comment: 16 pages, 6 figures, Solar Physics, in press, 201

Results from the 4PI Effective Action in 2- and 3-dimensions

We consider a symmetric scalar theory with quartic coupling and solve the equations of motion from the 4PI effective action in 2- and 3-dimensions using an iterative numerical lattice method. For coupling less than 10 (in dimensionless units) good convergence is obtained in less than 10 iterations. We use lattice size up to 16 in 2-dimensions and 10 in 3-dimensions and demonstrate the convergence of the results with increasing lattice size. The self-consistent solutions for the 2-point and 4-point functions agree well with the perturbative ones when the coupling is small and deviate when the coupling is large.Comment: 14 pages, 11 figures; v5: added numerical calculations in 3D; version accepted for publication in EPJ

Weak ferromagnetism with very large canting in a chiral lattice: (pyrimidine)2FeCl2

The transition metal coordination compound (pyrimidine)2FeCl2 crystallizes in a chiral lattice, space group I 4_1 2 2 (or I4_3 2 2). Combined magnetization, Mossbauer spectroscopy and powder neutron diffraction studies reveal that it is a canted antiferromagnet below T_N = 6.4 K with an unusually large canting of the magnetic moments of 14 deg. from their general antiferromagnetic alignment, one of the largest reported to date. This results in weak ferromagnetism with a ferromagnetic component of 1 mu_B. The large canting is due to the interplay between the antiferromagnetic exchange interaction and the local single-ion anisotropy in the chiral lattice. The magnetically ordered structure of (pyrimidine)2FeCl2, however, is not chiral. The implications of these findings for the search of molecule based materials exhibiting chiral magnetic ordering is discussed.Comment: 6 pages, 5 figure

Formation and Evolution of Supermassive Black Holes

The correlation between the mass of supermassive black holes in galaxy nuclei and the mass of the galaxy spheroids or bulges (or more precisely their central velocity dispersion), suggests a common formation scenario for galaxies and their central black holes. The growth of bulges and black holes can commonly proceed through external gas accretion or hierarchical mergers, and are both related to starbursts. Internal dynamical processes control and regulate the rate of mass accretion. Self-regulation and feedback are the key of the correlation. It is possible that the growth of one component, either BH or bulge, takes over, breaking the correlation, as in Narrow Line Seyfert 1 objects. The formation of supermassive black holes can begin early in the universe, from the collapse of Population III, and then through gas accretion. The active black holes can then play a significant role in the re-ionization of the universe. The nuclear activity is now frequently invoked as a feedback to star formation in galaxies, and even more spectacularly in cooling flows. The growth of SMBH is certainly there self-regulated. SMBHs perturb their local environment, and the mergers of binary SMBHs help to heat and destroy central stellar cusps. The interpretation of the X-ray background yields important constraints on the history of AGN activity and obscuration, and the census of AGN at low and at high redshifts reveals the downsizing effect, already observed for star formation. History appears quite different for bright QSO and low-luminosity AGN: the first grow rapidly at high z, and their number density decreases then sharply, while the density of low-luminosity objects peaks more recently, and then decreases smoothly.Comment: 31 pages, 13 figures, review paper for Astrophysics Update