A highly-ionized absorber as a new explanation for the spectral changes during dips from X-ray binaries

Until now, the spectral changes observed from persistent to dipping intervals in dipping low-mass X-ray binaries were explained by invoking progressive and partial covering of an extended emission region. Here, we propose a novel and simpler way to explain these spectral changes, which does not require any partial covering and hence any extended corona, and further has the advantage of explaining self-consistently the spectral changes both in the continuum and the narrow absorption lines that are now revealed by XMM-Newton. In 4U 1323-62, we detect Fe XXV and Fe XXVI absorption lines and model them for the first time by including a complete photo-ionized absorber model rather than individual Gaussian profiles. We demonstrate that the spectral changes both in the continuum and the lines can be simply modeled by variations in the properties of the ionized absorber. From persistent to dipping the photo-ionization parameter decreases while the equivalent hydrogen column density of the ionized absorber increases. In a recent work (see Diaz Trigo et al. in these proceedings), we show that our new approach can be successfully applied to all the other dipping sources that have been observed by XMM-Newton.Comment: 5 pages, 5 figures, to appear in the proceedings of "The X-ray Universe 2005", San Lorenzo de El Escorial (Spain), 26-30 September 200

Relativity violations and beta decay

In some quantum theories of gravity, deviations from the laws of relativity could be comparatively large while escaping detection to date. In the neutrino sector, precision experiments with beta decay yield new and improved constraints on these countershaded relativity violations. Existing data are used to extract bounds of $3×10^{−8}  \text{GeV}$ on the magnitudes of two of the four possible coefficients, and estimates are provided of future attainable sensitivities in a variety of experiments

Perturbative Lorentz and CPTCPT violation for neutrino and antineutrino oscillations

The effects of perturbative Lorentz and $CPT$ violation on neutrino oscillations are studied. Features include neutrino-antineutrino oscillations, direction dependence, and unconventional energy behavior. Leading-order corrections arising from renormalizable operators are derived in the general three-flavor effective field theory. The results are applied to neutrino-beam experiments with long baselines, which offer excellent sensitivity to the accompanying effects. Key signatures of Lorentz and $CPT$ violation using neutrino beams include sidereal variations in the oscillation probabilities arising from the breakdown of rotational symmetry, and $CPT$ asymmetries comparing neutrino and antineutrino modes. Attainable sensitivities to coefficients for Lorentz violation are estimated for several existing and future experiments

Testing relativity with high-energy astrophysical neutrinos

The recent observation of high-energy astrophysical neutrinos can be used to constrain violations of Lorentz invariance emerging from a quantum theory of gravity. We perform threshold and Čerenkov analyses that improve existing bounds by factors ranging from about a million to $10^{20}$

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

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)

Emission Scenarios and the Health Risks Posed by Priority Mobile Air Toxics in an Urban to Regional Area: An Application in Nashville, Tennessee

Toxic air pollutants, also known as hazardous air pollutants, are those that are known or suspected to cause cancer or other serious health effects, such as birth defects or adverse environmental outcomes. The aim of this research was to predict air toxics related health risks due to different emission scenarios by linking Models-3/CMAQ and cancer risk assessments. To demonstrate the effectiveness of this approach, this study was performed on the priority mobile source air toxics (PMSAT) of benzene, 1,3-butadiene, formaldehyde, acetaldehyde, and diesel particulate matter (DPM), based on data from 2003. The analysis was carried out in the eastern US, and mainly in Nashville, TN. Ten emissions scenarios were examined, including a 2020 scenario with the effects of on-road mobile source regulations. The results show that DPM poses a cancer risk that is 4.2 times higher than the combined total cancer risk from all of four other PMSAT. These high cancer risk levels are mainly due to non-road sources (57.9%). The main cancer risk from acetaldehyde, benzene, formaldehyde, and 1,3-butadiene (4HAPs) is due to biogenic sources, which account for 32.2% of this risk, although these cannot be controlled. Excluding DPM, the main on-road cancer risk contribution was due to the air toxics generated by gasoline light duty vehicles (LDVs), principally benzene and 1,3-butadiene. The scenario for 2020 showed reductions in the adverse health effects related to DPM and 4HAPs of 32.8 and 19.4%, respectively. This research provides strong evidence that reducing ambient DPM concentrations will lead to greater improvements in human health than other air toxics, indicating that better technologies and regulations must be applied to mobile diesel engines, as these have more significant adverse health effects than non-road diesel sources

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

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