World War II marked a turning point in how science, government, and industry collaborated to solve problems of production, efficiency, and scale for an increasingly consumptive domestic economy. This technoacceleration is well illustrated in the unprecedented production of milk, premised upon the tightly controlled dairy cow reproductive system. Focusing on estrus synchronization, this research demonstrates how military research and agricultural innovation during and after the war reshaped the biological and technological foundations of U.S. farming. Now the industry norm, estrus synchronization reflects a broader cultural post-war turn towards logics of efficiency, control, and scale. Evidence shows that these practices redefined expectations surrounding livestock reproduction, time management on the farm, and what counted as “efficient” in institutional settings. Building on feminist science studies and agricultural history, this research considers how the adoption of estrus synchronization aligned with broader cultural investments in regulation and productivity that intensified during the war years and have since transformed the way society relates to animals and food more broadly. This project uses archival material including county agricultural reports, extension bulletins, and dairy association records to argue that animal reproductive cycles were reframed as temporal problems rather than natural rhythms, reshaping farm labor, human-animal relations, and agricultural efficiency.

Wildfires burned far more frequently across western US forests prior to widespread fire suppression in the 20th century. Because modern observational data do not exist for the pre-suppression era, annual fire occurrence is reconstructed from scars in the growth rings of trees that survive fires. However, tree-ring fire scar data are spatially sparse and cannot directly provide the continuous, gridded estimates of fire return intervals (FRI) required for landscape-scale ecosystem modeling. Landfire, the primary gridded dataset of pre-suppression FRI in the western US, is derived from modeling exercises informed by regional experts. To evaluate the reliability of Landfire for simulating historical fire regimes, we compare its FRI estimates with those derived from the North American tree-ring fire scar network (NAFSN), a dataset of over 2,500 sites, for the period 1750-1880. We preliminarily find that Landfire FRI estimates have weak correlations with NAFSN (r < 0.2 at regional scales) and exhibit a systematic bias toward less frequent fire. Our analysis identifies where and how Landfire FRI estimates diverge from the tree-ring record, providing critical insights for the use and interpretation of gridded fire frequency datasets in simulations of past fire, ecosystem, and climate dynamics.

While electric vehicles are often marketed as having "zero-emissions" they still contribute to overall emissions through non-exhaust sources such as brake wear and tire degradation. This study focuses on PM2.5, a type of particulate matter pollutant that is associated with adverse effects to human health. Tirewear is a known source of PM.25, , a phenomenon we hypothesized would increase in electric vehicles as a result of their greater weight in comparison to traditional internal combustion vehicles. This study examines the extent to which PM2.5 emissions from tire wear, attributed to the heavier weight of light-duty battery electric vehicles (BEVs), disproportionately impact air quality across different communities in Los Angeles, as assessed through localized case studies. We first explored this research question through the Emissions Factors model (EMFAC) from the California Air Resource Board, where pollutants produced by different categories of vehicles can be examined. The data was then used to analyze the environmental justice implications and impact on lower income communities in Los Angeles. Validating the results of the EMFAC model, we carried out a long-term sampling of tread depth across a controlled group of electric and combustion vehicles, to determine if tire wear rates significantly differ between the two categories. Preliminary statistical analysis indicates that BEVs exhibit higher rates of tire-wear, suggesting increased contributions to PM.25 emissions relative to internal combustion engine vehicles.

Amid the boom in AI and large-scale data centers (DC), a flurry of recent research has shown that such facilities significantly degrade air and water quality and increase noise pollution and surface temperatures. These burdens can be attributed to their development, reliance on diesel generators, and immense resource demand for operation and cooling. However, this research has yet to account for the existing heat vulnerability of communities neighboring these centers. Using the California Heat Assessment Tool and California DC locations, our study indicates a significant positive association between census tract heat vulnerability and the number of DCs located within a 3-mile radius. Our analysis reveals that DC development is disproportionately concentrated in census tracts with elevated heat vulnerability. This data reveals how DCs intensify compounding environmental injustices. Not only are environmental burdens exacerbated through DCs’ resource usage and waste, but these impacts are concentrated in communities already vulnerable to heat. This pattern raises concerns about the ability to address future capacity to adapt to and mitigate thermal realities.

Recent research into tire-derived chemicals (TDCs) has found that they are extremely toxic to some aquatic organisms, which may devastate ecosystems and food supplies. One of these TDCs is 6PPDQ, which is an oxidation product of the antioxidant 6PPD used in tires. Due to the structure of 6PPDQ, there is potential for it to be bioremediated using oxidoreductase enzymes produced by fungi. Our research aims to identify whether or not the fungal species Trametes versicolor is able to degrade 6PPDQ and, if so, the potential role of these oxidoreductase enzymes in doing so through biotransformation experiments and molecular approaches. In the first phase, T. versicolor was inoculated with 6PPDQ in aqueous media to determine if this fungi is capable of degrading the compound. At various time points, liquid samples were collected and analyzed using Liquid Chromatography-Mass Spectrometry (LC-MS) to detect for 6PPDQ and UV-Vis Spectrophotometry to measure enzyme activity. Early results suggest that T. versicolor was able to remove 6PPDQ and showed elevated levels of oxidoreductase enzyme activity. In the ongoing phase, T. versicolor is being inoculated with 6PPDQ again, and similar enzyme activity and 6PPDQ concentration measurements are being taken. In addition, biomass samples are being taken, which can be used to measure the differential expression of enzyme-encoding genes produced by T. versicolor using qPCR and give us insight into the potential role of these enzymes in fungal 6PPDQ biotransformation.