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Nuclear reactions play a crucial role in determining the nucleosynthesis that occurs in astrophysical events. The rates of many reactions that significantly impact certain nucleosynthesis processes can not be currently measured via direct means. These reactions must be constrained in another manner, such as determining the level energies and other structure properties of the compound nuclei. In order to measure level energies of nuclei relevant to nuclear astrophysics, the Enge split-pole spectrograph has been installed and commissioned at the University of Notre Dame’s Nuclear Science Laboratory. The first scientific measurement has also been performed. Structure properties of 58Cu were measured via the reaction 58Ni(3He,t)58Cu to provide the first experimental constraint of the 57Ni(p,γ)58Cu reaction rate, which impacts the production of of 44Ti, 57Fe, and 59Ni in core-collapse supernovae. Preliminary analysis of this measurement confirms the level energies of states in 58Cu that could lead to significant resonances in the 57Ni(p,γ)58Cu reaction rate, while suggesting the presence of additional states that have not been previously observed but could also lead to significant resonances.

Wildfires are a significant threat to human health, in part through degraded air quality. Prescribed burning can reduce wildfire severity but can also lead to an increase in air pollution. The complexities of fires and atmospheric processes lead to uncertainties when predicting the air quality impacts of fire and make it difficult to fully assess the costs and benefits of an expansion of prescribed fire. By modeling differences in emissions, surface conditions, and meteorology between wildfire and prescribed burns, we present a novel comparison of the air quality impacts of these fire types under specific scenarios. One wildfire and two prescribed burn scenarios were considered, with one prescribed burn scenario optimized for potential smoke exposure. We found that PM2.5 emissions were reduced by 52%, from 0.27 to 0.14 Tg, when fires burned under prescribed burn conditions, considerably reducing PM2.5 concentrations. Excess short-term mortality from PM2.5 exposure was 40 deaths for fires under wildfire conditions and 39 and 15 deaths for fires under the default and optimized prescribed burn scenarios, respectively. Our findings suggest prescribed burns, particularly when planned during conditions that minimize smoke exposure, could be a net benefit for the impacts of wildfires on air quality and health.

The intensity and frequency of wildfires in California (CA) have increased in recent years, causing significant damage to human health and property. In October 2007, a number of small fire events, collectively referred to as the Witch Creek Fire or Witch Fire started in Southern CA and intensified under strong Santa Ana winds. As a test of current mesoscale modeling capabilities, we use the Weather Research and Forecasting (WRF) model to simulate the 2007 wildfire event in terms of meteorological conditions. The main objectives of the present study are to investigate the impact of horizontal grid resolution and planetary boundary layer (PBL) scheme on the model simulation of meteorological conditions associated with a Mega fire. We evaluate the predictive capability of the WRF model to simulate key meteorological and fire-weather forecast parameters such as wind, moisture, and temperature. Results of this study suggest that more accurate predictions of temperature and wind speed relevant for better prediction of wildfire spread can be achieved by downscaling regional numerical weather prediction products to 1 km resolution. Furthermore, accurate prediction of near-surface conditions depends on the choice of the planetary boundary layer parameterization. The MYNN parameterization yields more accurate prediction as compared to the YSU parameterization. WRF simulations at 1 km resolution result in better predictions of temperature and wind speed than relative humidity during the 2007 Witch Fire. In summary, the MYNN PBL parameterization scheme with finer grid resolution simulations improves the prediction of near-surface meteorological conditions during a wildfire event.

Marine phytoplankton are primary producers in ocean ecosystems and emit dimethyl sulfide (DMS) into the atmosphere. DMS emissions are the largest biological source of atmospheric sulfur and are one of the largest uncertainties in global climate modeling. DMS is oxidized to methanesulfonic acid (MSA), sulfur dioxide, and hydroperoxymethyl thioformate, all of which can be oxidized to sulfate. Ice core records of MSA are used to investigate past DMS emissions but rely on the implicit assumption that the relative yield of oxidation products from DMS remains constant. However, this assumption is uncertain because there are no long-term records that compare MSA to other DMS oxidation products. Here, we share the first long-term record of both MSA and DMS-derived biogenic sulfate concentration in Greenland ice core samples from 1200 to 2006 CE. While MSA declines on average by 0.2 µg S kg-1 over the industrial era, biogenic sulfate from DMS increases by 0.8 µg S kg-1. This increasing biogenic sulfate contradicts previous assertions of declining North Atlantic primary productivity inferred from decreasing MSA concentrations in Greenland ice cores over the industrial era. The changing ratio of MSA to biogenic sulfate suggests that trends in MSA could be caused by time-varying atmospheric chemistry and that MSA concentrations alone should not be used to infer past primary productivity.

Following up on a recent analysis of two cold atoms in a time-dependent harmonic trap in one dimension, we explore the entanglement entropy of two and three fermions in the same situation when driven through a parametric resonance. We find that the presence of such a resonance in the two-particle system leaves a clear imprint on the entanglement entropy. We show how the signal is modified by attractive and repulsive contact interactions, and how it remains present for the three-particle system. Additionaly, we extend the work of recent experiments to demonstrate how restricting observation to a limited subsystem gives rise to locally thermal behavior.

Although the Salton Sea was once a thriving destination for humans and wildlife, it has now degraded to the point of ecosystem collapse. Increases in local dust emissions have introduced aeolian (wind-blown) microorganisms that travel, along with contaminants and minerals, into the atmosphere, detrimentally impacting inhabitants of the region. Proliferation of certain microbial groups in regions of the Sea may have a disproportionate impact on local ecological systems. Yet, little is known about how the biogeochemical processes of this drying lakebed influence microbial community composition and dispersal. To elucidate how these microorganisms contribute, and adapt, to the Sea's volatile conditions, we synthesize research on three niche-specific microbiomes — exposed lakebed (playa), the Sea, and aeolian — and highlight modern molecular techniques, such as metagenomics, coupled with physical science methodologies, including transport modeling, to predict how the drying lakebed will affect microbial processes. We argue that an explicit consideration of microbial groups within this system is needed to provide vital information about the distribution and functional roles of ecologically pertinent microbial groups. Such knowledge could help inform regulatory measures aimed at restoring the health of the Sea's human and ecological systems.

The Goddard Earth Observing System with chemistry (GEOS-Chem) model has been updated with the Statewide Air Pollution Research Center version 11 (SAPRC-11) aromatics chemical mechanism, with the purpose of evaluating global and regional effects of the most abundant aromatics (benzene, toluene, xylenes) on the chemical species important for tropospheric oxidation capacity. The model evaluation based on surface and aircraft observations indicates good agreement for aromatics and ozone. A comparison between scenarios in GEOS-Chem with simplified aromatic chemistry (as in the standard setup, with no ozone formation from related peroxy radicals or recycling of NOx) and with the SAPRC-11 scheme reveals relatively slight changes in ozone, the hydroxyl radical, and nitrogen oxides on a global mean basis (1 %-4 %), although remarkable regional differences (5 %-20 %) exist near the source regions. NO x decreases over the source regions and increases in the remote troposphere, due mainly to more efficient transport of peroxyacetyl nitrate (PAN), which is increased with the SAPRC aromatic chemistry. Model ozone mixing ratios with the updated aromatic chemistry increase by up to 5 ppb (more than 10 %), especially in industrially polluted regions. The ozone change is partly due to the direct influence of aromatic oxidation products on ozone production rates, and in part to the altered spatial distribution of NOx that enhances the tropospheric ozone production efficiency. Improved representation of aromatics is important to simulate the tropospheric oxidation.

Surface ozone (O3) pollution levels are strongly correlated with daytime surface temperatures, especially in highly polluted regions. This correlation is nonlinear and occurs through a variety of temperature-dependent mechanisms related to O3 precursor emissions, lifetimes, and reaction rates, making the reproduction of temperature sensitivities - and the projection of associated human health risks - a complex problem. Here we explore the summertime O3- temperature relationship in the United States and Europe using the chemical transport model GEOS-Chem. We remove the temperature dependence of several mechanisms most frequently cited as causes of the O3-temperature "climate penalty", including PAN decomposition, soil NOx emissions, biogenic volatile organic compound (VOC) emissions, and dry deposition. We quantify the contribution of each mechanism to the overall correlation between O3 and temperature both individually and collectively. Through this analysis we find that the thermal decomposition of PAN can explain, on average, 20 % of the overall O3-temperature correlation in the United States. The effect is weaker in Europe, explaining 9 % of the overall O3-temperature relationship. The temperature dependence of biogenic emissions contributes 3 % and 9 % of the total O3-temperature correlation in the United States and Europe on average, while temperaturedependent deposition (6 % and 1 %) and soil NOx emissions (10 % and 7 %) also contribute. Even considered collectively these mechanisms explain less than 46 % of the modeled O3- temperature correlation in the United States and 36 % in Europe. We use commonality analysis to demonstrate that covariance with other meteorological phenomena such as stagnancy and humidity can explain the bulk of the remainder of the O3-temperature correlation. Thus, we demonstrate that the statistical correlation between O3 and temperature alone may greatly overestimate the direct impacts of temperature on O3, with implications for the interpretation of policyrelevant metrics such as climate penalty.