Energy Biosciences Institute

Trucking is critical for New Zealand’s economy as it is responsible for most of the country’s freight movement. However, the reliance on diesel-powered trucks disproportionately contributes to carbon dioxide (CO 2 ) and air pollutant emissions. Two different technologies have the potential to electrify heavy freight: battery-electric and fuel cell electric trucks; however, it remains unclear which technology will be used to reach New Zealand’s goal of net-zero freight transportation emissions by 2050. In this study, we develop an integrated assessment framework that quantifies present-day heavy truck emissions in New Zealand and compares the energy requirement of decarbonization through battery-electric versus fuel cell trucks in 2035 and 2050. This framework includes freight demand, vehicle powertrain, truck operation and charging, and diesel emission models. Further, we quantify the electricity grid infrastructure requirements of the shift to battery-electric and fuel cell truck fleets using the REMix-NZ capacity expansion model. Results show that the current fleet of heavy diesel trucks in New Zealand emits 2.4 million tonnes of CO 2 eq. annually, which could be fully mitigated by 2050 through battery-electric or fuel cell fleets. A full fleet of battery-electric trucks in 2050 would consume 7.2% of New Zealand’s current electricity generation compared to 13.5% for fuel cell trucks. A sensitivity analysis shows that improved truck design and efficiency can reduce this electricity requirement. Up to 3.6 GW additional capacity would need to be built by 2050, primarily through solar power, to satisfy the energy demand of a battery-electric truck fleet compared to 5.3 GW for a fuel cell fleet. • Electrifying the heavy vehicle fleet in New Zealand would avoid 2.4 million tonnes of on-road CO 2 eq. emissions annually. • A full fleet of battery-electric trucks in 2050 would consume 7.2% of current electricity generation compared to 13.5% for fuel cell trucks. • Policy strategies should target improving aerodynamic truck design, which has the greatest impact on truck energy consumption and can reduce electricity requirements by 13%. • New Zealand should invest in refueling infrastructure for battery-electric and hydrogen vehicles to enable the large-scale deployment of zero-emission trucks. • Coordinating grid and transportation planning will ensure that the appropriate capacity is built to meet the added demand caused by electrifying heavy trucks.

Forest restoration is increasingly promoted to mitigate climate change, conserve biodiversity, and secure food and water sovereignty. Yet many restored forests do not persist in the long term, and the role of land tenure regimes in shaping these outcomes remains poorly understood. We examine restoration reversals (restored forests later deforested) and long-term restoration gains (restored forests that remained intact) across 1.9 million territories in Brazil’s Atlantic Forest from 1985 to 2022. We compare Indigenous lands, Afro-descendant (Quilombola) territories, agrarian-reform settlements, protected areas, and private properties, introducing a statistical matching technique–agglomerative matching–to account for systematic differences between land tenure regimes. We find that Indigenous lands and agrarian-reform settlements exhibit significantly more long-term restoration gains than private properties. Concurrently, and by a smaller margin and on a smaller land area, Indigenous lands and agrarian-reform settlements exhibit higher reversals. These results highlight the relatively low restoration longevity of private properties and emphasize the importance of socio-political conditions in enabling long-term restoration gains.

The interplay between cancer cells and fibroblasts, facilitated by the extracellular matrix metalloproteinase inducer (EMMPRIN), plays a pivotal role in the invasion of cancer cells. The interaction between CD73 on fibroblasts and EMMPRIN on cancer cells is critical for the production of matrix metalloproteinases (MMPs). EMMPRIN is an essential protein that activates the vascular endothelial growth factor receptor (VEGFR), which subsequently governs signaling pathways related to cancer cell invasion, migration, angiogenesis, and metastasis, thereby contributing to the advancement of various cancers. EMMPRIN affects MMP production through direct cell-to-cell interactions and its influence on fibroblasts due to their close contact. It is proposed that disrupting the EMMPRIN-CD73 interaction and utilizing an antagonist for both EMMPRIN and VEGFR-2 may significantly impede cancer metastasis. This review aims to investigate how EMMPRIN regulates MMPs and VEGF in the context of cancer metastasis.

Abstract The percentage of U.S. homes heated with electricity has increased steadily from 1% in 1950 to 40% in 2020. Energy prices, geography, climate, housing characteristics, and income are shown to explain 90% of the increase, with energy prices by far the most important factor. The paper then estimates the cost of an electrification mandate for new homes. Households in warm states tend to prefer electricity anyway, so would be made worse off by less than $350 annually on average. Households in cold states, however, tend to prefer natural gas so would be made worse off by more than $1,000 annually.

The Local Climate Zone (LCZ) framework standardizes a common descriptive methodology to classify land surfaces into ten built and seven natural land cover types, each associated with some prescribed ranges of values for a subset of parameters, providing a more detailed alternative to supply spatially explicit urban parameters to regional and global models than conventional binary or density-class based urban typologies. While recent high-resolution LCZ maps have greatly advanced our understanding of urban areas at large scales in a “universal” way, challenges remain in determining accurate urban canopy parameters (UCPs) from these classifications. The common look-up-table approach, which assigns predefined value ranges to each LCZ type regardless of geographic location, oversimplifies the complexity and heterogeneity of urban surfaces within and across nations with different construction policies and building codes. Furthermore, LCZs, by their very nature, describe primarily urban morphologies, which can be frequently decoupled from radiative properties and construction materials, making the model inputs internally inconsistent. This study explores these limitations using the newly developed global 1km spatially continuous urban surface property dataset (U-Surf). U-Surf leverages the latest advances in remote sensing, machine learning, and cloud computing to provide the most relevant urban surface biophysical parameters, including radiative, morphological, and thermal properties, for urban canopy models at the facet- and canopy-level. Our analysis reveals substantial variabilities and uncertainties in LCZ-derived UCPs across regions and raises questions about the wide adoption of coarse-grained urban representation in urban climate modeling. Through simulations using the Community Earth System Model (CESM), we further discuss the implications of these discrepancies for detecting urban-specific meteorological signals from local to regional scales. Our results highlight the importance of spatially continuous, internally consistent UCPs in high-resolution urban climate modeling.

We study here by direct numerical simulations how geometrical and wetting properties of rectangular pillar-shaped microstructured superhydrophobic surfaces affect the process of particle-droplet coalescence and jumping. Such a process represents a passive mechanism of self cleaning where a single droplet coalesces with a particle of micrometer size, spreads on the particle and drives particle-droplet jumping. An in-house volume of fluid-immersed boundary framework is used to study the influence of characteristic dimensions of pillars (width, solid area fraction and height) and contact angles on particle-droplet coalescence and jumping. We relate our results for pillared surfaces to those obtained when using corresponding planar superhydrophobic surfaces. A range of different behaviors are disclosed when it comes to energy dissipation mechanisms and outcome of the coalescence and jumping process for these two types of superhydrophobic surfaces. We quantify and explain how the detachment of the particle-droplet system from a pillared substrate takes place at a later stage than that from a corresponding planar substrate. A reduced effect is demonstrated on the process of having configurations with a larger distance between the pillars and that longer pillars facilitate earlier jumping as compared to that on surfaces with shorter pillars. We also look at the transition between Cassie-Baxter and Wenzel states (determining whether jumping of the particle-droplet system will take place at all) as a function of wetting properties of the surfaces. Our results contribute to optimization of superhydrophobic surfaces aiming to achieve an enhanced self-cleaning efficiency. • DNS of particle-droplet coalescence and jumping from pillared surfaces. • Delayed jumping from pillared compared to planar surfaces. • The pitch between pillars has a limited effect on the jumping energy. • Short pillars cause a reduced jumping velocity as compared to long ones.

<strong class="journal-contentHeaderColor">Abstract.</strong> Scenarios represent a critical tool in climate change analysis, enabling the exploration of future evolution of the climate system, climate impacts, and the human system (including mitigation and adaptation actions). This paper describes the scenario framework for ScenarioMIP as part of CMIP7. The design process, initiated in June 2023, has involved various rounds of interaction with the research community and user groups at large. The proposal covers a set of scenarios exploring high levels of climate change (to explore high-end climate risks), medium levels of climate change (anchored to current policy action), and low levels of climate change (aligned with current international agreements). These scenarios follow very different trajectories in terms of emissions, with some likely to experience peaks and subsequent declines in greenhouse gas concentrations. An important innovation is that most scenarios are intended to be run, if possible, in emission-driven mode, providing a better representation of the earth system uncertainty space. The proposal also includes plans for long-term extensions (up to 2500 AD) to study slow climate change-related processes, and (ir)reversibility. This proposal forms the basis for further implementation of the framework in terms of the derivation of climate forcing pathways for use by earth system models and additional variants for adaptation and mitigation studies.

<strong class="journal-contentHeaderColor">Abstract.</strong> Scenarios represent a critical tool in climate change analysis, enabling the exploration of future evolution of the climate system, climate impacts, and the human system (including mitigation and adaptation actions). This paper describes the scenario framework for ScenarioMIP as part of CMIP7. The design process, initiated in June 2023, has involved various rounds of interaction with the research community and user groups at large. The proposal covers a set of scenarios exploring high levels of climate change (to explore high-end climate risks), medium levels of climate change (anchored to current policy action), and low levels of climate change (aligned with current international agreements). These scenarios follow very different trajectories in terms of emissions, with some likely to experience peaks and subsequent declines in greenhouse gas concentrations. An important innovation is that most scenarios are intended to be run, if possible, in emission-driven mode, providing a better representation of the earth system uncertainty space. The proposal also includes plans for long-term extensions (up to 2500 AD) to study slow climate change-related processes, and (ir)reversibility. This proposal forms the basis for further implementation of the framework in terms of the derivation of climate forcing pathways for use by earth system models and additional variants for adaptation and mitigation studies.

<strong class="journal-contentHeaderColor">Abstract.</strong> Scenarios represent a critical tool in climate change analysis, enabling the exploration of future evolution of the climate system, climate impacts, and the human system (including mitigation and adaptation actions). This paper describes the scenario framework for ScenarioMIP as part of CMIP7. The design process, initiated in June 2023, has involved various rounds of interaction with the research community and user groups at large. The proposal covers a set of scenarios exploring high levels of climate change (to explore high-end climate risks), medium levels of climate change (anchored to current policy action), and low levels of climate change (aligned with current international agreements). These scenarios follow very different trajectories in terms of emissions, with some likely to experience peaks and subsequent declines in greenhouse gas concentrations. An important innovation is that most scenarios are intended to be run, if possible, in emission-driven mode, providing a better representation of the earth system uncertainty space. The proposal also includes plans for long-term extensions (up to 2500 AD) to study slow climate change-related processes, and (ir)reversibility. This proposal forms the basis for further implementation of the framework in terms of the derivation of climate forcing pathways for use by earth system models and additional variants for adaptation and mitigation studies.