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Electric vehicles (EVs) are known to reduce emissions and fossil fuel dependency. However, the limited range, long charging time, and inadequate charging infrastructure have hampered the adoption of EVs. The current EV charging infrastructure planning studies and tools require detailed information, extensive resources, and skills that can be a significant barrier to urban areas for finding the required charging infrastructure to support a targeted EV market share. This study generates regression models to estimate the number of direct current fast charging stations and the chargers to support the EV charging demand for urban areas. These models provide macro-level estimates of the required infrastructure investment in urban areas, which can be easily implemented by policy-makers and city planners. This study incorporates data obtained from applying a disaggregate optimization-based charger placement model, developed recently by the same authors, for multiple case studies to generate the required data to calibrate the macro-level models, in the state of Michigan. This simulated data set includes the number of charging stations and chargers for each market share, technology advancement scenario, and the transportation network topology. The results show that the number of charging stations reduces with battery size and charging power and increases with EV market share and the road network lane length. The number of chargers reduces with charging power, whereas it increases with battery size, EV market share, and vehicle miles traveled in the system. The model developed here can be applied to any state having urban characteristics and weather conditions similar to Michigan.

Atmospheric methane (CH4) concentration has more than doubled since per-industrial time. The contribution of natural wetland ecosystems, currently the largest natural emitters of CH4, to this increase is not well known. While temperature may have contributed to an growth in emissions, the extent wetlands has declined over this period due to drainage and land use conversion. In this study, we combine a new reconstruction of global wetland extent with simulated CH4 flux from nine land surface model to estimate wetland CH4 emissions over 1901-2020. Our analysis evaluates: 1) the uncertainty of modelled emissions over the century timescale, 2) the separate and combined effects of climate and land use change on emissions, and 3) the global and regional trends of wetland CH4 emissions. We show that prognostic outputs from model of wetland extent are highly uncertain over the century timescale although most prognostic models suggest an emission increase. We find that inclusion of wetland drainage reducing wetland area primarily in temperate latitudes is sufficient to offset the increase in modeled emission in the absence of land use, with an ensemble mean displaying no significant trend between 1901-1920 and 2001-2020. We evaluate the contribution of individual land uses to the decline in global emissions, in particular the conversion to irrigated rice and wet cultivation which are also methane emitting areas. These results diverge from previous source attributions at the century timescale and may require upward revisions to other biogenic sources to balance the budget and remain within δ13C isotope constraints. In the future, we will investigate the effect of wetland drainage on CO2, CH4 and aquatic carbon export for a more complete accounting of this land use change on global carbon fluxes.

Soil contains immense stocks of carbon, which may accelerate climate change if released. Soil microbes affect these carbon stocks by producing decomposition-catalyzing enzymes, a capacity varying across different microbial groups. Consequently, establishing links between global variation in microbial communities and functions should substantially enhance future projections of soil carbon. To this end, we here reveal global patterns in soil microbial community function using nearly 13,000 observations of microbial biomass, community structure, and enzyme activities (>100,000 measurements). We find total biomass and fungal and Gram-negative bacterial dominance increase with latitude, whereas Gram-positive bacteria predominate near the equator. Enzyme stoichiometry correspondingly suggests greater nitrogen and carbon limitation at higher latitudes. Comparing microbial and enzyme patterns, fungal biomass indicates nitrogen limitation, whereas Gram-negative bacterial biomass indicates carbon limitation. Together, microbial community structure explains significant variation in enzyme profile uncaptured by climate, soil properties, or landcover. Soil microbial communities dominated by fungi and Gram-negative bacteria exhibit less enzyme activity per unit biomass, with two- to four-fold variation in temperature- and biomass-normalized activity rate observed across the Earth. Significant functional differences thus arise with global turnover in microbial communities, indicating that community structure merits a central position in process-based soil models.

Satellites are increasingly seen as a tool for identifying large greenhouse gas point sources for mitigation, but independent verification of satellite performance is needed for acceptance and use by policy makers and stakeholders. We conduct to our knowledge the first single-blind controlled methane release testing of satellite-based methane emissions detection and quantification, with five independent teams analyzing data from one to five satellites each. Teams correctly identified 71% of all emissions, ranging from 0.20 [0.19, 0.21] metric tons per hour (t/h) to 7.2 [6.8, 7.6] t/h. Over three-quarters (78%) of quantified estimates fell within ±50% of the metered value, comparable to airplane-based remote sensing technologies. The relatively wide-area Sentinel-2 and Landsat 8 satellites detected emissions as low as 1.4 [1.3, 1.5, 95% confidence interval] t/h, while GHGSat’s targeted system quantified an 0.20 [0.19, 0.21] t/h emission to within 13%. While the fraction of global methane emissions detectable by satellite remains unknown, we estimate that satellite networks could see 18-81% of total oil and natural gas system emissions detected in a recent survey of a high-emitting basin.

Direct air capture (DAC) has gained traction in climate policy as a promising method for carbon dioxide removal. How – and whether – DAC should be pursued as a climate strategy and deployed as local infrastructure, however, will rely on its ability to secure social license to operate (SLO), given the frequent disconnect between broad public perceptions of technologies and perceptions among host communities. There is also a growing need for the deployment of climate infrastructure like DAC to be responsive to environmental justice (EJ) and just transition (JT) principles. However, relatively little research exists on how communities may respond to DAC deployment locally, and the EJ and JT considerations they may evoke. In this study, we use a mixed-methods approach to evaluate public and community perceptions of DAC. We find that while communities may be generally open to the idea of DAC being deployed in their communities, the conditions under which DAC is realized are likely to determine levels of acceptance and support. The most important determinants of project support are community involvement in planning and implementation and expected benefits. This is perhaps especially important for infrastructure like DAC, which offers few if any direct local benefits (i.e., clean energy or air quality improvements). Building on recent trends, policies aimed at advancing DAC could include designated resources for community involvement and benefits in order to improve the likelihood of projects securing SLO and abiding by EJ and JT principles.

Our patient presents with a unique case of both functional and cosmetic concerns following colectomy for the treatment of Crohn’s disease with subsequent massive weight loss following bariatric surgery. She desires abdominoplasty to address these concerns. Thorough preoperative planning and work up set the ground work for a successful procedure. We’ve shared our intraoperative approach, which has never before been published in the literature. Following her procedure, the patient had a mostly uneventful postoperative course. Her functional and cosmetic concerns were addressed with the procedure. The surgical outcome exceeded her expectations. Patients seeking body contouring surgery following bariatric surgery can be expected to increase. We suspect there may be other patients similar to ours that are experiencing similar functional and cosmetic concerns that can be addressed with cosmetic surgery. Due to the extremely unique nature of this case, we’ve shared our approach in hopes that our success can serve as a resource to other surgeons with similar patients.

Widespread changes in the intensity and frequency of fires across the globe are altering the terrestrial carbon (C) sink1–4. Although the changes in ecosystem C have been reasonably well quantified for plant biomass pools5–7, an understanding of the determinants of fire-driven changes in soil organic C (SOC) across broad environmental gradients remains unclear, especially in global drylands3,4,7–9. Here, we combined multiple datasets and original field sampling of fire manipulation experiments to evaluate where and why fire changes SOC the most, built a statistical model to estimate historical changes in SOC, and compared these estimates to simulations from ecosystem models. We found that drier ecosystems experienced larger relative changes in SOC than humid ecosystems—in some cases exceeding losses from plant biomass pools—primarily explained by high fire-driven declines in tree biomass inputs in dry ecosystems. Ecosystem models provided more mixed insight into potential SOC changes because many models underestimated the SOC changes in drier ecosystems. Upscaling our statistical model predicted that soils in 1.57 million km2 savanna-grassland regions experiencing declines in burned area over the past ca. two decades may have 23% more SOC, equating to 1.78 PgC in topsoils. Consequently, ongoing declines in fire frequencies have likely created an extensive carbon sink in the soils of global drylands that may have been underestimated by ecosystem models.

The potential lubrication mechanisms for articular cartilage remain as complex as the material itself. Many studies have examined systematically the effects of sliding velocity on the frictional response of cartilage but a systematic analysis of contact area remains largely uncharted. Here we explore this potential effect three ways: a constant force experiment, a constant pressure experiment, and a non-constant pressure and force experiment. Hard, impermeable spheres are used as probes and with sizes varied between 1.6 mm and 25.4 mm allowing a sweep of physiologically relevant pressures. The aim is to effectively isolate the influence of the probe curvature on the friction measurements. Articular cartilage samples were collected from horses at necropsy from the left and right distal, medial aspect of the radius. Each test was run for five minutes at a reciprocated sliding speed of 1 mm/s. Two lubrication regimes are observed during testing, an area-dependent regime at lower areas and an area-independent regime at higher areas. Therefore measurements made using different probe sizes will most likely result in different measurements of the friction behavior and great care should be given when comparing these results.

Purpose The trend of atherosclerotic plaque feature evolution is unclear in stroke patients with and without recurrence. We aimed to use three-dimensional whole-brain magnetic resonance vessel wall imaging to quantify the morphological changes of causative lesions during medical therapy in patients with symptomatic intracranial atherosclerotic disease. Methods Patients with acute ischemic stroke attributed to intracranial atherosclerotic disease were retrospectively enrolled if they underwent both baseline and follow-up magnetic resonance vessel wall imaging. The morphological features of the causative plaque, including plaque volume, peak normalized wall index, maximum wall thickness, degree of stenosis, pre-contrast plaque-wall contrast ratio, and post-contrast plaque enhancement ratio, were quantified and compared between the non-recurrent and recurrent groups (defined as the recurrence of a vascular event within 18 months of stroke). Results Twenty-nine patients were included in the final analysis. No significant differences were found in plaque features in the baseline scan between the non-recurrent ( n = 22) and recurrent groups ( n = 7). The changes in maximum wall thickness (–13.32% vs. 8.93%, P = 0.026), plaque-wall contrast ratio (–0.82% vs. 3.42%, P = 0.005) and plaque enhancement ratio (–11.03% vs. 9.75%, P = 0.019) were significantly different between the non-recurrent and recurrent groups. Univariable logistic regression showed that the increase in plaque-wall contrast ratio (odds ratio 3.22, 95% confidence interval 1.55–9.98, P = 0.003) was related to stroke recurrence. Conclusion Morphological changes of plaque features on magnetic resonance vessel wall imaging demonstrated distinct trends in symptomatic intracranial atherosclerotic disease patients with and without stroke recurrence.

Objective: To describe the impact of COVID-19 on acute cerebrovascular disease care across 9 comprehensive stroke centers throughout Los Angeles County (LAC). Methods: Volume of emergency stroke code activations, patient characteristics, stroke severity, reperfusion rates, treatment times, and outcomes from February 1 to April 30, 2020, were compared against the same time period in 2019. Demographic data were provided by each participating institution. Results: There was a 17.3% decrease in stroke code activations across LAC in 2020 compared to 2019 (1,786 vs. 2,159, respectively, χ2 goodness of fit test p < 0.0001) across 9 participating comprehensive stroke centers. Patients who did not receive any reperfusion therapy decreased by 16.6% in 2020 (1,527) compared to 2019 (1,832). Patients who received only intravenous thrombolytic (IVT) therapy decreased by 31.8% (107 vs. 157). Patients who received only mechanical thrombectomy (MT) increased by 3% (102 vs. 99). Patients who received both IVT and MT decreased by 31.8% (45 vs. 66). Recanalization treatment times in 2020 were comparable to 2019. CSCs serving a higher proportion of Latinx populations in the eastern parts of LAC experienced a higher incidence of MT in 2020 compared to 2019. Mild increase in stroke severity was seen in 2020 compared to 2019 (8.95 vs. 8.23, p = 0.046). A higher percentage of patients were discharged home in 2020 compared to 2019 (59.5 vs. 56.1%, p = 0.034), a lower percentage of patients were discharged to skilled nursing facility (16.1 vs. 20.7%, p = 0.0004), and a higher percentage of patients expired (8.6 vs. 6.3%, p = 0.008). Conclusion: LAC saw a decrease in overall stroke code activations in 2020 compared to 2019. Reperfusion treatment times remained comparable to prepandemic metrics. There has been an increase in severe stroke incidence and higher volume of thrombectomy treatments in Latinx communities within LAC during the pandemic of 2020. More patients were discharged home, less patients discharged to skilled nursing facilities, and more patients expired in 2020, compared to the same time frame in 2019.