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Ever-growing energy demand since the Industrial Revolution is likely to continue over the upcoming decades, and making the transition to renewable energy sources takes longer than anticipated. Solar energy is one of the most important renewable energy sources, and the cost of installing photovoltaic solar systems has decreased significantly as the global photovoltaic solar system industry has grown since the beginning of this century. In the United States, the adoption of residential photovoltaic solar systems has the potential to add up to a significant change, considering the ubiquity of solar irradiation and the prevalence of low-density residential development. This study investigated the diffusion of photovoltaic solar systems in residential buildings to support sustainable development goals. I built a series of regression models to analyze the impact of socio-economic, geographical, and technical factors on the photovoltaic solar panel adoption rate in residential buildings. I aggregated more than 1 million photovoltaic solar panel installation records at the ZIP code level, which allowed me to calculate the adoption rate and control the abovementioned factors. Moreover, I conducted in-depth interviews with key actors from the solar industry in New Jersey to understand how the solar industry adapts to the changes in solar policies and attitudes of residential users. The results indicate that electricity prices and solar irradiation are the most significant factors for residential users to install photovoltaic solar systems. Moreover, renewable energy policies increase the relative advantage of these systems and directly impact the adoption rates. Investigating California and New Jersey examples revealed that financial programs such as tax credits and renewable energy certificate trading mechanisms create the highest incentive for homeowners. Besides, standardization of the application process, permit fees, and inspections help to reduce the soft costs associated with installations. The case study on New ...

Climate change is an emerging global health crisis, disproportionately affecting low- and middle-income countries (LMICs) where health outcomes are increasingly compromised by environmental stressors such as pollution, natural disasters, and human migration. With a focus on promoting health equity, Global Surgery advocates for expanding access to surgical care and enhancing health outcomes, particularly in resource-limited and disaster-affected areas like LMICs. The healthcare industry—and more specifically, surgical care—significantly contributes to the global carbon footprint, primarily through resource-intensive settings, i.e. operating rooms that generate greenhouse gases and substantial medical waste. Therefore, Global Surgery efforts aimed at improving surgical access through an increase in surgical volumes may inadvertently exacerbate health challenges for vulnerable populations by further contributing to environmental degradation. This predicament is particularly pronounced in LMICs, who already suffer from a disproportionate share of the global burden of disease, and where the demand for surgery is rising without corresponding resilient infrastructure. LMICs face a double jeopardy of health inequity coupled with climate vulnerability. As a movement positioned to improve health around the world, Global Surgery has an increasingly significant role in envisioning and ensuring a sustainable future. Global Surgery initiatives must prioritise sustainable infrastructure in both high-income countries (HICs) and LMICs, all while accounting for the unequal polluting contributions between HICs and LMICs and, consequently, moral responsibilities moving forward. Moreover, through targeting upstream causes of poor health at urban and perioperative levels, Global Surgery’s interventions may help to reduce the global burden of disease—avoiding preventable surgeries and their carbon footprints from the outset. Altogether, Global Surgery and climate change are two matters of social justice whose solutions must synergistically centralise the health of both the planet and its most vulnerable people.

Aggregate and limestone mining in San Antonio’s Bexar and Comal counties in Texas, USA, has caused considerable health concerns as of late. Aggregate mining actions can result in localized air quality issues in any neighborhood. Furthermore, heavy truck traffic, hauling, and transportation of the mined material contribute to pollution. In this research, PM species were sampled at four locations north of the San Antonio city limits. The data were collected using a TSI Air Quality Sampler that sampled PM1, PM2.5, PM4, PM10, wind speed, wind direction, temperature, and relative humidity. Continuous data with 1 min averages were recorded during the study period from August to September 2019. The instrument was stationed at every location for a period of 7 days each. The four locations were a ranch, an open field, a residential compound, and an elementary school. PM1 and PM2.5 concentration levels were lower compared to PM10 concentrations at all four studied sites. Our results suggest that PM concentrations are primarily impacted by mining activities. PM species were highest at the residential compound due to its proximity to an active mining area, resulting in deleterious health effects for neighbors living in the vicinity of the sampled site.

AbstractLarge conductance potassium (BK) channels are among the most sensitive molecular targets of ethanol and genetic variations in the channel-forming α subunit have been nominally associated with alcohol use disorders. However, whether the action of ethanol at BK α influences the motivation to drink alcohol remains to be determined. To address this question, we first tested the effect of systemically administered BK channel modulators on voluntary alcohol consumption in C57BL/6J males. Penitrem A (blocker) exerted dose-dependent effects on moderate alcohol intake, while paxilline (blocker) and BMS-204352 (opener) were ineffective. Because pharmacological manipulations are inherently limited by non-specific effects, we then sought to investigate the behavioral relevance of ethanol’s direct interaction with BK α by introducing in the mouse genome a point mutation known to render BK channels insensitive to ethanol while preserving their physiological function. The BK α K361N substitution prevented ethanol from reducing spike threshold in medial habenula neurons. However, it did not alter acute responses to ethanol in vivo, including ataxia, sedation, hypothermia, analgesia, and conditioned place preference. Furthermore, the mutation did not have reproducible effects on alcohol consumption in limited, continuous, or intermittent access home cage two-bottle choice paradigms conducted in both males and females. Notably, in contrast to previous observations made in mice missing BK channel auxiliary β subunits, the BK α K361N substitution had no significant impact on ethanol intake escalation induced by chronic intermittent alcohol vapor inhalation. It also did not affect the metabolic and locomotor consequences of chronic alcohol exposure. Altogether, these data suggest that the direct interaction of ethanol with BK α does not mediate the alcohol-related phenotypes examined here in mice.

AbstractUnderstanding the mechanisms controlling forest carbon accumulation is crucial for predicting and mitigating future climate change. Yet, it remains unclear whether the dominance of ectomycorrhizal (EcM) trees influences the carbon accumulation of entire forests. In this study, we analyzed forest inventory data from over 4000 forest plots across Northeast China. We find that EcM tree dominance consistently exerts a positive effect on tree, soil, and forest carbon stocks. Moreover, we observe that these positive effects are more pronounced during unfavorable climate conditions, at lower tree species richness, and during early successional stages. This underscores the potential of increasing the dominance of native EcM tree species not only to enhance carbon stocks but also to bolster resilience against climate change in high-latitude forests. Here we show that forest managers can make informed decisions to optimize carbon accumulation by considering various factors such as mycorrhizal types, climate, successional stages, and species richness.

The impedance-based stability criteria are widely adopted for small-signal stability analysis of power systems. Among them, the determinant-based multi-input multi-output (MIMO) Nyquist criterion is particularly attractive since it simplifies the stability determination process without calculating the eigenvalues of MIMO systems. However, it is found in this letter that the determinant-based Nyquist criterion can potentially result in incorrect stability analysis results with pure inductance models in the MIMO models of the power network. This letter illustrates the issue and its root cause through mathematical derivation and numerical analysis. Then, the issue is demonstrated through an example system, and the corresponding solutions are provided as well.

Different species within the same community may exhibit distinct phenological responses to climate change, so it is necessary to study species differences in the green-up date among abundant species within a wide area, and a suitable phenology model should be introduced to explain the associated climate-driven mechanism. Although various models have been developed, very few studies have aimed to compare their efficiency and robustness, and the relative contributions of climate driving factors have not been sufficiently examined. We analyzed phenology data for 12 species across 17 stations in Inner Mongolia and found that essential spatiotemporal and interspecies differences existed in the green-up date. Five process-based models were established for each species and their performance was comprehensively evaluated. The two-phase models (sequential model, parallel model, unified model and unified model combined with precipitation driving) generally performed better than the one-phase model (thermal time model), and the model considering precipitation performed the best, which indicates that it is necessary to introduce the chilling effect and precipitation driving effect to improve the model accuracy in arid environments. We proposed a method to estimate the contribution rates of various climate driving factors, and significant differences in the relative demand for the various climate driving factors among different species were clearly revealed. The results indicated that for natural vegetation in Inner Mongolia, the need for the chilling and temperature driving is relatively high, and the precipitation driving is very important for herbaceous vegetation, which leads to considerable spatial and interspecies differences in green-up date. We demonstrated the feasibility of quantitatively evaluating the contributions of different climate driving factors with a process-based model, and the contradiction in phenological changes among different studies may eventually be clarified.