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The National Renewable Energy Laboratory (NREL) in partnership with USAID Mexico's Low Emissions Development (MLED) II program explored the technical feasibility of transit bus electrification in Mexico City (CDMX) and León. NREL and USAID engaged CDMX and León transit agencies to understand routes of interest and existing fleet fueling and bus specifications.
Abstract A new infaunal pinnotherid crab, Pinnixulala heardin. sp., is described from muddy substrates of the middle to inner continental shelf of the northern Gulf of Mexico. Molecular genetic analysis supports its separation from P. retinens (Rathbun, 1918), the only other western Atlantic member of the genus and a species most commonly found living as a symbiont of large polychaete worms. Both western Atlantic species are clearly separated from several described and undescribed populations of congeners occurring along shorelines of the eastern Pacific. We herein include a rediagnosis of P. retinens to facilitate morphological comparisons with P. heardin. sp. Unlike P. retinens, which is more common in shallow inshore waters and reaches larger sizes, the new species lacks development of a strong distally directed spine on the fourth pereopod ischium and has chelae that are at least as heavily developed as the second and third pereopods. In addition, the mature male first gonopods in P. heardin. sp. are tapered over their terminal one-third and directed distally, rather than being curved in their terminal one-third with the tips directed mesially, as they are in P. retinens. The new species is invariably collected from samples including infaunal worms and other invertebrates, but the specific hosts remain to be determined
Abstract New species of the pinnotherid crab genus GlassellaCampos & Wicksten, 1997 are described from western Atlantic waters along the east and west coasts of Florida, with the generic assignment of one being provisional. Glassella chaneyin. sp., Glassella martinin. sp., and Glassella taylorin. sp., all morphologically resemble the long-known species G. floridana (Rathbun, 1918) and overlap part of its distributional range, there occupying similar habitats and at least sometimes found with similar hosts. While genomic DNA sequencing has previously established the generic assignment of G. floridana, small sizes and suboptimal preservation histories of specimens representing the three new species have rendered all sequencing attempts unsuccessful, and thus not allowed their inclusion in molecular phylogenetic analyses. To facilitate present morphological comparisons, a rediagnosis of G. floridana was undertaken, and previously published illustrations were augmented, the latter now including figures of its previously undescribed male first gonopod and gonopodal plate. Comparisons of G. floridana to the three new species reveal striking diagnostic differences between all four species in their male first gonopods and varied configurations in the gonopodal plate or its probable homologs. These characters support the otherwise established separation of G. floridana from its congeners on the basis of its more strongly armed flexor margins of the fourth and fifth pereopods. In G. taylorin. sp., representing the smallest known member of Glassella, development of the third maxilliped and male first gonopod is so exceptional as to suggest the species may warrant eventual assignment to a separate genus.
The Field Office has a cultural resources program manager. The LANL Management and Operating Contractor has a staff of cultural resource specialists who meet the qualifications set forth in the Secretary of the Interior's Standards and Guidelines for Professional Qualifications (36 CFR Part 61), or work under the supervision of individuals who meet these qualifications. Any future Management and Operating Contractor will have a staff of Secretary of the Interior-qualified cultural resource specialists.
Coccidioidomycosis (Valley fever), caused by Coccidioides spp., is a fungal infection endemic to semi-arid regions of the Americas. Despite 80 years of disease recognition in New Mexico, there is limited disease awareness. We incorporated clinical, epidemiological, and ecological datasets to summarize the knowledge of Valley fever in New Mexico. We analyzed 1541 human cases from 2006 to 2023. On average, 86 cases were reported each year (4.1 cases per 100,000 population per year). The highest levels of incidence were in southwestern New Mexico. American Indian or Alaska Natives in New Mexico had a 1.9 times higher incidence rate of coccidioidomycosis than White people, and among age groups, older populations in New Mexico had the highest incidence rates. We analyzed 300 soil samples near Las Cruces, New Mexico, for the presence of Coccidioides and reported the first known positive soil samples collected from the state, the majority of which were from grassland-dominated sites and from animal burrows. Sequence analyses in clinical specimens, wild animals, and soil samples confirmed that Coccidioides posadasii is the main causative species of coccidioidomycosis in New Mexico. Environmental surveillance validated that locally acquired infections could occur in, but are not limited to, Catron, Doña Ana, Sierra, and Socorro Counties.
NREL's feasibility assessment of offshore wind in the Gulf of Mexico concluded that hurricane risk was one of the major challenges that would need to be overcome for a mature offshore wind industry to develop in the Gulf of Mexico. To ensure the robust design of wind turbines in the Gulf of Mexico, it is critical to understand the added risk posed by the threat of major hurricanes, as those affecting the Gulf of Mexico region have a significant potential to exceed design limits prescribed by the International Electrotechnical Commission (IEC) wind design standards. To satisfy this charge, this project defines the wind hazard for the Gulf of Mexico Offshore Wind Energy area using the hurricane hazard model develop by Applied Research Associates and published extensively in the open literature. In doing so, the return periods associated with the IEC Class 1A and Typhoon Class limit-state hurricanes are estimated on a grid with nominal resolution of 10 km to determine where hurricane risk results in the exceedance of the IEC design criteria. On the same grid, wind speeds hazard contours associated with return periods varying from 50 to 1,000 years are also estimated. An additional challenge in assessing hurricane wind speed risk in the Gulf of Mexico arises from inconsistent terminology across the Saffir-Simpson hurricane scale and the IEC design criteria. Saffir-Simpson definitions are based on 1-minute sustained wind speeds estimated at 10-m height over marine terrain, while the IEC uses a different averaging period (3-second versus 1-minute) and reference height (assumed herein a hub height of 150 m versus 10 m). Employing the latest research on turbulence characteristics of the hurricane boundary layer, conversions between various durations (e.g., 3-seconds, 1-minute, 10-minutes, 1-hour) and between elevations near the surface (10 m) to near hub height (assumed herein 150 m) are developed. IEC Class 1A and Typhoon Class limit states are also provided in terms of an equivalent Saffir-Simpson hurricane wind speed category.
The ability to effectively and efficiently connect offshore wind energy resources to end users in the Gulf of Mexico, requires coordinated transmission planning to ensure that electric transmission facilities can adequately support future offshore development. The Gulf of Mexico has substantial wind resources in both shallow shelf waters and deeper waters off the shelf where fixed bottom and floating wind technologies would be most appropriate. Most interest in offshore wind development to date has been in the central and western portions of the Gulf of Mexico (Louisiana and Texas) in federal and state waters. As a companion study to other federal activities in the offshore wind transmission space, including the Atlantic Offshore Wind Transmission Literature Review and Gaps Analysis, the Atlantic Offshore Wind Transmission Study, the West Coast Offshore Wind Transmission Literature Review and Gaps Analysis, the West Coast Offshore Wind Transmission Study, and the Advancing Offshore Wind Energy in the United States: U. S. Department of Energy Strategic Contributions Toward 30 Gigawatts and Beyond Report, this literature review and gaps analysis for offshore wind transmission in the Gulf of Mexico builds off previous literature reviews and supports the role of federal leadership to facilitate offshore wind energy. The overarching goal of this document is to identify gaps and lay the groundwork to inform coordinated transmission planning, ocean co-use, existing energy infrastructure, and siting associated with offshore wind energy development in the Gulf of Mexico. There are unique regional considerations for offshore wind transmission, which are summarized herein based on a review and assessment of publicly available information.
Predicting nutrient loads is essential to understanding and managing one of the environmental issues faced by the northern Gulf of Mexico hypoxic zone, which poses a severe threat to the Gulf’s healthy ecosystem and economy. The development of hypoxia in the Gulf of Mexico is strongly associated with the eutrophication process initiated by excessive nutrient loads. Due to the complexities in the excessive nutrient loads to the Gulf of Mexico, it is challenging to understand and predict the underlying temporal variation of nutrient loads. The study was aimed at identifying an optimal predictive machine learning model to capture and predict nonlinear behavior of the nutrient loads delivered from the Mississippi/Atchafalaya River Basin (MARB) to the Gulf of Mexico. For this purpose, monthly nutrient loads (N and P) in tons were collected from US Geological Survey (USGS) monitoring station 07373420 from 1980 to 2020. Machine learning models—including autoregressive integrated moving average (ARIMA), gaussian process regression (GPR), single-layer multilayer perceptron (MLP), and a long short-term memory (LSTM) with the single hidden layer—were developed to predict the monthly nutrient loads, and model performances were evaluated by standard assessment metrics—Root Mean Square Error (RMSE) and Correlation Coefficient (R). The residuals of predictive models were examined by the Durbin–Watson statistic. The results showed that MLP and LSTM persistently achieved better accuracy in predicting monthly TN and TP loads compared to GPR and ARIMA. In addition, GPR models achieved slightly better test RMSE score than ARIMA models while their correlation coefficients are much lower than ARIMA models. Moreover, MLP performed slightly better than LSTM in predicting monthly TP loads while LSTM slightly outperformed for TN loads. Furthermore, it was found that the optimizer and number of inputs didn’t show effects on the LSTM performance while they exhibited impacts on MLP outcomes. This study explores the capability of machine learning models to accurately predict nonlinearly fluctuating nutrient loads delivered to the Gulf of Mexico. Further efforts focus on improving the accuracy of forecasting using hybrid models which combine several machine learning models with superior predictive performance for nutrient fluxes throughout the MARB.
Wind energy development has expanded the fastest globally among all renewable sources during the last 20 years. However, wind farms have documented adverse impacts on bats, including mortality from collisions with turbine blades and disruptions to habitat and behavior. As the world's sixth most attractive economy for renewables, with 70 operating wind farms, Mexico and its bats now face escalating threats from the country's burgeoning wind industry. Despite this rapid growth, few studies have analyzed Mexico's regulatory framework to prevent, evaluate, and mitigate wind farm effects on bats. In this study, we reviewed Mexican laws and treaties that facilitate wind farm permitting, construction, operation, and decommissioning, and searched for guidelines that specifically address bat conservation. We found eight international pacts that promote wind power adoption along with three relevant articles in Mexico's Constitution. The General Law of Ecological Balance and Environmental Protection proved most pertinent for impact management. Supplementary guidelines from the Ministry of Environment and Natural Resources offer general strategies for evaluating wind farm impacts on bats, but adherence remains voluntary. Given expanding wind power investments across Mexico, we highlight the need for more stringent national standards that require preventative and corrective measures to protect bat populations. Tighter legislation and enforcement offer pathways toward environmentally sustainable wind energy development in Mexico.
This report summarizes results from the CORE-CM project in the San Juan and Raton basins of New Mexico and Colorado and ultimately begins to address what is the future of coal in the San Juan and Raton basins. The objective of this project was to determine the nonfuel carbon-based products (CBP), critical minerals, and rare earth elements (REE) potential in coal and related stratigraphic units in the San Juan and Raton basins and adjacent areas. This project delineated favorable geologic terrains and priority areas containing potential CBP, critical minerals, and REE deposits for the DOE mandate, which also is a priority of the NMBGMR and state of New Mexico. This project is important to the state because CBP, critical minerals, and REE resources must be identified before land use decisions are made by government officials. Future mining of CBP, critical minerals, and REE will directly benefit the economy of New Mexico. Furthermore, it is crucial to re-establish a domestic source of critical minerals and REE in the U.S. to help secure the nation’s clean energy future, to reduce the vulnerability of the U.S. to material shortages related to national defense, and to maintain our global technical and economic competitiveness. In addition to these benefits, students at New Mexico Institute of Mining and Technology (NMT) and San
Klebsiella aerogenes is an opportunistic pathogen and a growing cause of healthcare-associated infections, characterized by multidrug resistance and the emergence of global high-risk clones. However, regional genomic surveillance data remain limited. Here, we sought to characterize the population structure, transmission dynamics and resistance mechanisms of clinical K. aerogenes in Albuquerque, New Mexico. We sequenced 177 clinical isolates collected between 2021 and 2023. We also developed a novel, species-specific PopPUNK database to facilitate rapid, high-resolution typing. The New Mexico K. aerogenes population was diverse but dominated by two global pandemic lineages, ST93 (47.5%) and ST4 (7.9%), which were significantly enriched for the virulence factors yersiniabactin and colibactin. Genomic evidence for recent local transmission was rare, with only four putative transmission pairs identified. The resistome was characterized by intrinsic and adaptive mutations. Nearly all isolates possessed gyrA mutations associated with decreased fluoroquinolone susceptibility. Mutations in the AmpC regulator AmpD and the outer membrane porin Omp36 were common, particularly within the dominant ST93 lineage. These mutations have been associated with increased AmpC-mediated carbapenem resistance. Our findings underscore the critical importance of genomic surveillance to monitor the transmission and evolution of adaptive resistance.
The coronavirus disease (COVID-19) pandemic has highlighted systemic inequities in the United States and resulted in a larger burden of negative social outcomes for marginalized communities. New Mexico, a state in the southwestern US, has a unique population with a large racial minority population and a high rate of poverty that may make communities more vulnerable to negative social outcomes from COVID-19. To identify which communities may be at the highest relative risk, we created a county-level vulnerability index. After the first COVID-19 case was reported in New Mexico on March 11, 2020, we fit a generalized propensity score model that incorporates sociodemographic factors to predict county-level viral exposure and thus, the generic risk to negative social outcomes such as unemployment or mental health impacts. We used four static sociodemographic covariates important for the state of New Mexico—population, poverty, household size, and minority population—and weekly cumulative case counts to iteratively run our model each week and normalize the exposure score to create a time-varying vulnerability index. We found the relative vulnerability between counties varied in the first eight weeks from the initial COVID-19 case before stabilizing. This framework for creating a location-specific vulnerability index in response to an ongoing disaster may be used as a quick, deployable metric to inform health policy decisions such as allocating state resources to the county level.
Wind energy development causes bat fatalities. Despite emphasis on understanding and reducing these impacts, few data are available for the southwest region of the United States and northern Mexico. We monitored bat fatalities for a full year (March 2017–March 2018) at a wind energy facility in south Texas near the United States–Mexico border. We established search plots of 100-m radius at eight randomly selected turbines (of 255) and searched the roads and pads at an additional 92 turbines. We conducted weekly searches from spring through fall and bimonthly during winter. We used GenEst (Generalized Mortality Estimator) to estimate bat fatalities corrected for searcher efficiency, carcass removal, and density-weighted proportion of area searched. We found 205 bats during standardized searches, the majority of which were Brazilian free-tailed bats (Tadarida brasiliensis, 76%). The corrected fatality estimates were 16 bats/megawatt/year (95% confidence interval [CI]: 12 – 30 bats/megawatt/year) across all species. Species composition at our site is similar to that of northern Mexico, an area of expanding wind energy development with no published studies.
The Gulf of Mexico Risk Analysis Database is comprehensive Esri geodatabase of vector layers, raster layers, and tables curated for risk analysis within the offshore Gulf of Mexico. Datasets include bathymetry, seafloor characteristics (channels, anomalies, faults, etc.), MetOcean data (wind speed, wave height, etc.), ocean current data, sediment data, and machine learning training regions used in NETL's Ocean & Geohazard Analysis (OGA) tool. This database serves as a compliment to the OGA tool by providing many of the datasets used in the design of the OGA tool, including regions used for machine learning. This database also serves as a valuable resource for risk analysis studies within the offshore Gulf of Mexico. This work was completed under the Advanced Offshore Research Portfolio, FWP Number: 1022476.
The United States Gulf of Mexico has historically been a significant oil and gas producing region and continues to produce hydrocarbons today. As such, significant investments have been made to install oil and gas infrastructure such as pipelines, platforms, and wells. As these assets reach the end of their useful life or production associated with the assets is curtailed, the assets become a liability for both the owner/operators and the U.S. and state governments responsible for regulating the assets. There are costs and risks associated with safely decommissioning the assets, and in some cases, the assets may be abandoned (e.g., the owner is no longer a going concern). In parallel, carbon capture and storage (CCS) technology has developed in the United States and interest and incentives for CCS projects have accelerated in recent years, with many public announcements of CCS projects in development in the U.S. Gulf of Mexico region. The region is particularly well-suited to CCS due to the high density of industry on the coastline (i.e., CO 2 sources) and favorable geology in the near-offshore region. CCS also requires the use of many of the same assets required for oil and gas production (pipelines, platforms, wells) and the oil and gas industry has direct experience with CO 2 transport and injection (i.e., EOR). Therefore, the combination of existing infrastructure in close proximity to potential CCS project sites appears to provide a potential “win-win” solution for re-use of existing oil and gas assets. This paper presents a high-level evaluation of oil and gas infrastructure in the Gulf of Mexico with the goals of identifying the scale of the opportunity (e.g., how much existing infrastructure is realistically re-usable), identifying gaps in knowledge/policy/information required to evaluate existing infrastructure for re-use, and proposing key actions that could be pursued to further the assessment of existing infrastructure re-use for CCS.
Shigellosis is a gastrointestinal infection caused by species of Shigella . A large outbreak of Shigella flexneri serotype 2a occurred in Albuquerque, New Mexico between May 2021 and November 2023 that involved humans and non-human primates (NHP) from a local zoo. We analyzed the genomes of 202 New Mexican isolates as well as 15 closely related isolates from other states, and four from NHP. The outbreak was initially detected within men who have sex with men but then predominantly affected people experiencing homelessness. Nearly 70% of cases were hospitalized and there was one human death. The outbreak extended into Albuquerque’s BioPark Zoo, causing high morbidity and six deaths in NHPs. All isolates were multidrug-resistant, including towards fluoroquinolones, a first line treatment option which led to treatment failures in human and NHP populations. We show the circulation of the same S. flexneri strain in humans and NHPs, causing fatalities in both populations. This study demonstrates the threat of antimicrobial resistant organisms to vulnerable human and NHP populations and emphasizes the value of genomic surveillance within a One Health framework.