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Silicon nanowires entail significant potential as sensors in nanoelectromechanical systems. Despite its crucial impact in such applications, inconsistent trends in mechanical behavior reported in computational and experimental studies remain unexplained. Hence, scale effect in even the most fundamental elastic properties requires clarification. This work introduces a multiscale model to bridge the existing gap between atomistic simulations and experimental observations encountered around a critical dimension of 10 nm. The combined approach of this work is based on molecular dynamics and modified core–shell model and captures the scale effect over a substantial size range. The evolution of the modulus of elasticity is thus studied and linked to nanowire critical dimension through the parameterization of surface inhomogeneity. The developed method is also validated through an analysis of native oxide revealing an average modulus of elasticity of 75 GPa. The method’s applicability can be extended to similar one-dimensional structures with unique surface states.

A nanocomposite consisting of iron disilicide nanocrystals embedded in a Si matrix was prepared from industry-grade ferrosilicon by ball milling and subsequent heat treatment. By tailoring the heat treatment temperature either the metallic α -FeSi _2 or the semiconducting β -FeSi _2 phase could be made the dominant one, as indicated by x-ray diffraction. Magnetization curve and zero-field cooled/field cooled measurements revealed that ferromagnetic and superparamagnetic centers are present in the nanocomposites, which could be attributed to Fe-rich defective regions at the surface of the iron disilicide nanocrystals. For both nanocomposites, containing either mainly the α or β phase, we could show that the magnetization can be varied by about 40% by electrochemical lithiation and delithiation of the surrounding Si matrix, with up to 6.5% of the magnetization change being reversible. These variations could be attributed to the formation of additional Fe-rich magnetic regions, induced by a local change of the Fe/Si fraction at the FeSi _2 /Si interfaces, and their subsequent partial elimination. Thus, this work demonstrates a new concept for how an ‘indirect magneto-ionic effect’ can be obtained in composite materials consisting of a phase prone to the electrochemical ion uptake (i.e. the Si matrix) and a magnetic phase (i.e. the FeSi _2 nanocrystals).

Therapeutic ultrasound for brain stimulation has increased in the last years. This energy has shown promising results for treating Alzheimer’s disease, Parkinson’s disease and traumatic brain injury, among other conditions. However, the application of ultrasound in the brain should trespass a natural but highly attenuating and distorting barrier, the cranium. Implantable ceramic materials can be used to replace part of the cranium as an alternate method to enhance ultrasound transmission. In this work, it is presented the acoustic characterization of alumina ceramic disks that can be employed as cranial implants for acoustic windows-to-the-brain. Alumina samples were prepared using current-activated pressure-assisted densification and were acoustically characterized. Acoustic impedance and attenuation of the samples were determined for different porosities. Additionally, measured and modeled acoustic fields are presented and analyzed in terms of the total ultrasound transmitted through the ceramics. Results indicate a resonant behavior in the alumina disks when the thickness corresponds to a half-wavelength of ultrasound; this resonance permits a total of 95.4% of ultrasound transmission; for thicknesses out of the resonant zone, transmission is 53.0%. Alumina proves to be an excellent medium for ultrasound transmission that, in conjunction with its mechanical and optical properties, can be useful for cranium replacement in mixed opto-acoustic applications.

Borogermanate glasses containing terbium ions are interesting materials due to their luminescent and magnetic properties. Terbium can present two different oxidation states and the thermal poling technique can be a pertinent way to modulate spatially the oxidation state of these ions. In this work, we demonstrate using a thermo-electrical imprinting process the transfer of micro scaled motifs on the surface of a borogermanate glass containing Tb ^3+ resulting in a micrometric structuring of the oxidation state of Tb ^3+ /Tb ^4+ ions. A large change in absorption and luminescence optical properties is observed, arising from the distinct properties of trivalent and tetravalent terbium ions. Correlative micro luminescence, Raman and second harmonic generation measurements were carried out on the patterned poled glass surface. This has demonstrated an accurate concomitant modification of the glass structure accompanying large luminescence changes and the appearance of a second order optical response which could be attributed to a localized space charge implantation. These original results demonstrate how a simple electrical process allows managing multi optical properties but also paves the way to induce static electrical functionalities in a magnetic optical glassy system.

‘Compartmental models’ of epidemics are widely used to forecast the effects of communicable diseases such as COVID-19 and to guide policy. Although it has long been known that such processes take place on social networks, the assumption of ‘random mixing’ is usually made, which ignores network structure. However, ‘super-spreading events’ have been found to be power-law distributed, suggesting that the underlying networks may be scale free or at least highly heterogeneous. The random-mixing assumption would then produce an overestimation of the herd-immunity threshold for given R _0 ; and a (more significant) overestimation of R _0 itself. These two errors compound each other, and can lead to forecasts greatly overestimating the number of infections. Moreover, if networks are heterogeneous and change in time, multiple waves of infection can occur, which are not predicted by random mixing. A simple SIR model simulated on both Erdős–Rényi and scale-free networks shows that details of the network structure can be more important than the intrinsic transmissibility of a disease. It is therefore crucial to incorporate network information into standard models of epidemics.

Prolonged and recurrent droughts seriously threaten Africa’s food and water security. This threat frequently coexists with human-induced calamities, such as domestic and international conflicts and civil unrest, which could exacerbate the socio-economic instability already present in the region. Using a novel data-driven approach, we evaluated how drought risk in Africa affects the security of various crucial sectors of sustainable development, such as agriculture, water, and food nutrition/health (referred here as ‘nutritional’). Our findings show that different sectors and geographical areas exhibit distinct risk footprints. In Central African countries, for instance, we found that social instability linked to higher nutritional risk is more prevalent than that resulting from the agriculture and water sectors. Socio-economic volatility rather than uncertainty in the climate is the primary driver of this elevated nutritional risk. However, most Northern African countries are at risk of considerable agriculture and water insecurity because of extreme water stress and unstable climate trends. We indicate that the risk is majorly driven by recurrent drought events in Southern Africa, which significantly affect inclusive sectoral securities. The cause of higher risks in Eastern and Western Africa has been found to be an unfavorable interaction of all the risk components—vulnerability, exposure, and hazard. Notably, basic amenities, climate stability, and access to sustainable and renewable water sources are often missing from Africa’s sectoral risk hotspots. Our results emphasize the necessity of maximizing the efficacy of bottom-up initiatives to achieve sustainable food and water security, by integrating socio-economic policies and climate change at the granular level through observation.

In this study, the Seebeck coefficient of a single-walled carbon nanotube (SWCNT) was evaluated using a nitrogen vacancy center in nanodiamonds as a thermometer. A temperature gradient was established across the SWCNT, and the temperatures of the nanodiamonds on the electrodes, along with the electromotive force between these electrodes, were measured. The Seebeck coefficient for a metallic SWCNT was determined to be 14.0 ± 1.1 μV K ^−1 , which is consistent with results reported in previous studies. This methodology offers a promising approach for evaluating the thermoelectric properties of various nanomaterials.

Quantum time transfer has emerged as a powerful technique, offering sub-picosecond precision and inherent security through the nonlocal temporal correlation property of energy-time entangled biphoton sources. In this paper, we demonstrate the inherent security advantage of quantum time transfer, and the utilization in detecting potential intercept-resend attacks. By investigating the impact of these attacks on the nonlocality identifier associated with nonlocal dispersion cancellation of energy-time entanglement, we establish a security threshold model for detecting intercept-resend attacks. Experimental verification on a 102 km fiber-optic link confirms that even a malicious delay as small as 25 ps can be identified. This investigation serves as a compelling illustration of secure two-way time transfer, safeguarding against intercept-resend attacks, and showcasing its potential applications in fields reliant on authentic time distribution between remote parties.

Forecasting the Indian Ocean Dipole (IOD) is crucial because of its significant impact on regional and global climates. While traditional dynamic and empirical models suffer from systematic errors due to nonlinear processes, convolutional neural networks (CNN) are nonlinear in nature and have demonstrated remarkable El Niño Southern Oscillation (ENSO) and IOD forecasting skills based on oceanic predictors, particularly sea surface temperature and heat content. However, it is difficult to measure heat content and easily introduces uncertainties, prompting the need to explore atmospheric predictors for IOD forecasts. Based on sensitivity prediction experiments, we identified the sea level pressure (SLP) signal as a crucial predictor, which forecasts IOD at a 7 month lead. In addition, the CNN model improves monthly forecasting accuracy while reducing errors by 13.43%. Utilizing the heatmap analysis, we elucidated that the multi-seasonal predictability of the IOD primarily originates from mid-latitude climate variability. Besides ENSO signals in the Pacific Ocean, our study highlights the significant impact of remote climate forcing in the South Indian Ocean, tropical North Indian Ocean, and Northwest Pacific Ocean on IOD forecasts. By introducing the SLP precursor and extratropical zones into IOD forecasts, our study offers fresh insights into the underlying dynamics of IOD evolution.

Climate change and most climate policies affect and reinforce different forms of inequalities. For instance, climate change policies that aim to change consumer behavior by increasing the price tag of goods and services that cause carbon emissions often carry a disproportionately higher burden (in terms of financial cost) to those with lower incomes. They can thereby either exacerbate existing income inequalities or contribute to generating new ones. Meanwhile, refraining from engaging with climate mitigation policies will incur other detrimental societal costs: the financial burden and the harmful consequences of climate change that future generations will have to bear if nothing is done. In this paper, we examine how the immediate economic inequality citizens face from climate mitigation policies (regarding carbon taxation) weighs against the long-term generational inequalities future generations will experience. We study how both types of inequality relate to policy support for climate change mitigation policies in the context of Germany. The German case is of special interest because a recent court ruling of the Federal Constitutional Court allows us to test whether making people aware of a new legal reality can bridge the gap between the economic and generational inequality. Our findings using a between-subjects survey experiment fielded among German citizens ( N = 6,319) in 2022 show that immediate economic concerns trump future generational concerns, generally making citizens less supportive of the policy. This negative support is however somewhat mitigated by the supportive signal from the court ruling.

Large amounts of plastic waste from non-local sources (>200 tonnes) wash up on Christmas Island and the Cocos Keeling Islands, two remote Indian Ocean islands, every year. Local communities on these islands organize beach clean-ups regularly to tackle this problem and, because their waste systems cannot handle the enormous amounts of plastic, predominantly incinerate the collected waste. However, as long as plastic waste keeps entering the ocean, beach clean-ups alone cannot be sustained. The first crucial step to solving this problem is to determine the main sources of plastic waste to the islands. In this study, we simulate the transport of floating plastic waste to determine the main riverine sources of plastic reaching the islands. We find that the majority of simulated plastic waste comes from just 4 Indonesian rivers: the Solo, Brantas, Ci Tanduy, and Wai Sekampung. We suggest that further numerical and field studies, as well as potential river clean-up efforts focus on these rivers to stop plastic waste inundating Christmas Island and the Cocos Keeling Islands.

Climate warming poses complex challenges for alpine ecosystems on the Qinghai–Tibetan Plateau (QTP), further exacerbated by permafrost degradation. Quantifying the specific ecological impacts of permafrost thaw remains elusive, as ecological variations are also influenced by external climate factors. This study tackles this gap by employing the Noah-MP model to simultaneously simulate permafrost thermal–hydrological dynamics and net primary production (NPP) across the Three River Headwaters Region from 1989 to 2018. Model results were validated against observations. To isolate the ecological effects of permafrost thaw, we implemented a novel relative time transformation on the simulation results. Our analysis reveals a 7.5 × 10 ^4 km ^2 reduction in permafrost coverage during the study period, coinciding with a 1.09 g C m ^−2 yr ^−2 increase in NPP. While precipitation is the primary driver of NPP changes in most years, soil moisture emerges as a crucial factor during permafrost disappearance, when the ground transitions to seasonally frozen ground. Surprisingly, the NPP response to permafrost disappearance exhibited a transient effect, diminishing to negligible levels within five years post-thaw. These findings enhance our understanding of the intricate and dynamic responses of the QTP ecosystem to permafrost degradation under a warming climate.

The ability of pollen to enable the glaciation of supercooled liquid water has been demonstrated in laboratory studies; however, the potential large-scale effect of plants and pollen on clouds, precipitation and climate is pressing knowledge to better understand and project clouds in the current and future climate. Combining ground-based measurements of pollen concentrations and satellite observations of cloud properties within the United States, we show that enhanced pollen concentrations during springtime lead to an increase in cloud ice fraction of up to 0.1 in the temperature regime where pollen are considered to act as INP (−15 $\,^\circ$ C and −25 $\,^\circ$ C ). We further establish the link from the pollen-induced increase in cloud ice to a higher precipitation frequency. In light of anthropogenic climate change, the extended and strengthened pollen season and future alterations in biodiversity can introduce a localized climate forcing and a modification of the precipitation frequency and intensity.

The Water-Energy Nexus (WEN) provides a comprehensive concept for the cooperative management of resources. Although the WEN system in cities is intricately connected to socioeconomic activities, relationship between WEN and economic systems remains understudied. This study introduces a tri-dimensional Nexus Pressure Index (NPI) to assess the pressure on WEN system. Gross Domestic Product (GDP) per capita and city tiers in the urban agglomeration were used to assess the relationship between the characteristics of WEN and economic system. We conducted a case study of 296 cities in China and 1330 counties in the United States from 2012 to 2019. During the 9 year study period, on average, pressure on WEN system have relieved by 22% in China and 27% in the United States, measured by NPI. Cities with most ideal characteristics (low pressure in all dimensions) rank merely in the middle of all eight classes, with GDP per capita 74% and 85% of the highest-GDP-per-capita class in China and the US respectively. Well-performing WEN system does not yield best economic outcomes. High water pressure correlates with better economic performance in the US, while high-energy-pressure cities had GDP per capita about 50% and 70% of the class with highest GDP per capita in China and the US, respectively, suggesting stronger economic constraints from energy stress. Urban agglomeration analysis revealed a negative relationship between WEN and economic performance. NPI in emerging cities is 0.6–1 lower than NPI in regionally-central cities in China, while 0.2–0.5 lower in the US. These results underscore the contradiction between preferred WEN characteristics and higher economic performance, and underpin the resource curse hypothesis at city-level in the two considered giants. A sustainable approach to harmonize WEN and economic system is in urgent need.

Marine carbon dioxide removal (mCDR) is gaining interest as a tool to meet global climate goals. Because the response of the ocean–atmosphere system to mCDR takes years to centuries, modeling is required to assess the impact of mCDR on atmospheric CO _2 reduction. Here, we use a coupled ocean–atmosphere model to quantify the atmospheric CO _2 reduction in response to a CDR perturbation. We define two metrics to characterize the atmospheric CO _2 response to both instantaneous ocean alkalinity enhancement (OAE) and direct air capture (DAC): the cumulative additionality ( α ) measures the reduction in atmospheric CO _2 relative to the magnitude of the CDR perturbation, while the relative efficiency ( ϵ ) quantifies the cumulative additionality of mCDR relative to that of DAC. For DAC, α is 100% immediately following CDR deployment, but declines to roughly 50% by 100 years post-deployment as the ocean degasses CO _2 in response to the removal of carbon from the atmosphere. For instantaneous OAE, α is zero initially and reaches a maximum of 40%–90% several years to decades later, depending on regional CO _2 equilibration rates and ocean circulation processes. The global mean ϵ approaches 100% after 40 years, showing that instantaneous OAE is nearly as effective as DAC after several decades. However, there are significant geographic variations, with ϵ approaching 100% most rapidly in the low latitudes while ϵ stays well under 100% for decades to centuries near deep and intermediate water formation sites. These metrics provide a quantitative framework for evaluating sequestration timescales and carbon market valuation that can be applied to any mCDR strategy.

Mitigating climate change (CC) and reversing biodiversity decline are urgent and interconnected global priorities. Strategies to address both crises must consider the relationships, synergies and trade-offs between key response measures, including sustainable production and consumption patterns, protected areas (PAs) and climate mitigation policy (CP). In this paper, we review a large set of scenarios ( n = 96) from the Integrated Model to Assess the Global Environment (IMAGE) describing future development of land use, greenhouse gas emissions and their impact on CC and biodiversity. We calculate the global mean temperature increase (GMTI) and the Mean Species Abundance (MSA) of plants, a metric indicative of local terrestrial biodiversity intactness. The set includes scenarios with and without specific CP to address CC, PA for biodiversity and demand and supply sustainability measures such as increased energy efficiency and reduced meat consumption. Our findings indicate that scenarios with integrated measures can prevent biodiversity loss at the global scale, yet with clear regional differences. By 2050, 15 out of 30 (50%) scenarios with at least 30% of global land as PAs show positive MSA changes in grasslands and tropical non-forests (Grass & TnF), but only 1 (3%) does so in tropical forests (TF). We demonstrate that pasture and food/feed crops are the main drivers of MSA loss in Grass & TnF and that scenarios with high levels of PAs prevent land conversion and increase biodiversity. By 2100, 28 out of 46 (60%) scenarios with mitigation measures to restrict CC to 2 °C or less in 2100 result in positive MSA changes in TF, but only 13 (28%) do so in Grass & TnF, reflecting the larger impacts of land use change in the latter region. These results underscore the importance of time and regionally-tailored approaches to address the biodiversity and CC crises.

The dynamics of lateral nutrient fluxes through hydrological movements are crucial for understanding ecological functions related to the flow of energy, materials, and organisms across various spatiotemporal scales. To investigate the connectivity of multiple spatial flow processes, we conducted a one-year field study to measure lateral hydrologic carbon (C) and nitrogen (N) fluxes across the continental shelf in the Yangtze estuary. We observed a significant correlation between the differences in remote sensing-based estimates of gross primary production (GPP) (ΔGPP _MODIS ) and the differences in eddy covariance (EC) tower-based GPP (ΔGPP _EC ) at both high-elevation and low-elevation sites. Our findings indicate that the saltmarsh acts as a net source of dissolved total C while serving as a net sink for dissolved total N. Furthermore, there was a significant correlation in the total dissolved stoichiometry of the C/N ratio between imports from and exports to adjacent aquatic systems. These findings highlight the importance of integrating ecological stoichiometric principles to improve our understanding of the complex relationships among physical, chemical, and ecological processes, particularly within the context of the meta-ecosystem framework. Additionally, when reciprocal hydrological lateral C and N flows are considered, a single ecosystem can function as both a source and sink within the meta-ecosystem framework.

Mode pairing quantum key distribution (MP-QKD) overcomes the repeaterless bound without requiring phase locking and phase tracking. However, MP-QKD still assumes that the light source is trusted, which can present challenges in practical deployments and potentially introduce security vulnerabilities. In this paper, we propose a light source monitoring (LSM) scheme that guarantees the security of MP-QKD with the untrusted light sources. The simulation results demonstrate that, when considering untrusted light sources, the performance of MP-QKD with the LSM scheme remains nearly identical to that of ideal MP-QKD, even in the presence of the source fluctuations. Furthermore, we simplify some of the complex integration calculations involved in simulating the observed quantities of MP-QKD, which reduces the running time of the parameter optimization procedure.

Efficient agricultural water management (AWM) practices enhance crop water productivity and promote climate change adaptation and resilience initiatives, particularly in smallholder farming systems. Approximately 90% of sub-Saharan Africa’s (SSA) agriculture is rainfed under smallholder farmers who constitute about 60% of the continent’s population and depend on agriculture for their livelihoods. While AWM is central to the African agenda, knowledge of AWM is fragmented, making it challenging to operationalize regional initiatives at country levels. Therefore, this study sought to review the status of AWM practices and technologies in Africa and provide guidelines, scenarios, and investment plans to guide the prioritization and operationalization of the African Union’s irrigation development and AWM (AU-IDAWM) initiative. The initiative proposes four developmental pathways; 1—improved water control and watershed management in rain-fed farming, 2—farmer-led irrigation, 3—irrigation scheme development and modernization, and 4—unconventional water use for irrigation. The preferred reporting items for systematic reviews and meta-analyses approach guided the systematic literature review. The study indicates that most agricultural production systems are mainly under pathways 1 and 2, which dictate the subsequent AWM practices. Pathway 4 had isolated adoption in North Africa. SSA exhibited overlaps in opportunities for AWM, whereas North Africa had green energy and strong extension services. The challenges were unique to each geopolitical region. Policy-related issues affected North Africa, whilst low investment in AWM dominated West Africa. Poor institutional coordination plagued East Africa, whilst low access to extension services affected Southern Africa. The Central African region was undermined by poor management practices that culminated in soil salinity in the agricultural lands. Targeted and scalable investments across interventions are necessary topotentially improve AWM uptake and subsequent food security in the continent. Also, institutional setups are essential in coordinating efforts towards achieving AWM. Extension services are essential information dissemination platforms for adopting effective climate-smart agriculture.

To answer the question of whether the growth of digital inputs can be beneficial for carbon neutrality, we thoroughly explore the impacts of digital inputs on carbon emission reduction in this work. We propose a combined framework of panel regression model and multi-objective optimization model to identify the key digital sectors and obtain their optimal total outputs. First, the results show that digital inputs continue to increase in most countries (regions) from 2000 to 2021, especially in the USA, EU countries and China. Digital equipment inputs in China are the most significant, while digital service inputs in the USA and EU countries are relatively important. Second, the regression results show that digital service inputs have significantly negative influence on carbon emissions, which means that the growth of digital service inputs will decrease carbon emissions. This result indicates that the key point of industrial digitalization for carbon emission reduction may be increasing the digital service inputs. Third, the optimization results show that the digital-input-oriented optimization model, which encourages an increase in digital service inputs, could achieve greater targets of economic growth and carbon emission reduction. The total outputs of Telecommunication Services and Computer Services should increase globally by 10.24% and 8.89%, respectively.

Wheat’s nutritional value is critical for human nutrition and food security. However, more attention is needed, particularly regarding the content and concentration of iron (Fe) and zinc (Zn), especially in the context of climate change (CC) impacts. To address this, various controlled field experiments were conducted, involving the cultivation of three wheat cultivars over three growing seasons at multiple locations with different soil and climate conditions under varying Fe and Zn treatments. The yield and yield attributes, including nutritional values such as nitrogen (N), Fe and Zn, from these experiments were integrated with national yield statistics from other locations to train and test different machine learning (ML) algorithms. Automated ML leveraging a large number of models, outperformed traditional ML models, enabling the training and testing of numerous models, and achieving robust predictions of grain yield (GY) ( R ^2 > 0.78), N ( R ^2 > 0.75), Fe ( R ^2 > 0.71) and Zn ( R ^2 > 0.71) through a stacked ensemble of all models. The ensemble model predicted GY, N, Fe, and Zn at spatial explicit in the mid-century (2020–2050) using three Global Circulation Models (GCMs): GFDL-ESM4, HadGEM3-GC31-MM, and MRI-ESM2-0 under two shared socioeconomic pathways (SSPs) specifically SSP2-45 and SSP5-85, from the downscaled NEX-GDDP-CMIP6. Averaged across different GCMs and SSPs, CC is projected to increase wheat yield by 4.5%, and protein concentration by 0.8% with high variability. However, it is expected to decrease Fe concentration by 5.5%, and Zn concentration by 4.5% in the mid-century (2020–2050) relative to the historical period (1980–2010). Positive impacts of CC on wheat yield encountered by negative impacts on nutritional concentrations, further exacerbating challenges related to food security and nutrition.

Given that the vegetation over mid-high latitude Asia (MHA) has been more variable in recent years, it is necessary to better understand the physical causes of vegetation variations in this region. Based on the normalized difference vegetation index (NDVI), this study reveals a close linkage of the variability of spring (April–May) vegetation in MHA to the winter (December–January–February) Pacific-North American (PNA) pattern. When the winter PNA pattern lies in the positive phase, the NDVI tends to decrease in most parts of the MHA region during the following spring. Further analysis suggests that the lagged influence of winter PNA on spring atmospheric circulations and hence the vegetation in MHA is accomplished by the stratospheric pathway. The positive PNA phase can enhance the upward transport of wave energy into the stratosphere over the high latitudes in winter through the linear constructive interference of zonal wavenumber 1 (WN1), consequently leading to a weaker polar vortex in the stratosphere during February-March. Subsequently, the weakened polar vortex signal propagates downward from the stratosphere to the troposphere, inducing the negative Arctic Oscillation-like circulation with an anomalous cyclonic circulation dominating the MHA region in spring. The anomalous cyclonic circulation further cools the surface air temperature in MHA via modulating downward solar radiation and temperature advection, resulting in a decrease of spring NDVI in situ .

Despite their apparent utility in mitigating climate change, technologies for removing methane from air are in early stages of development. Here we evaluate the limiting physical constraints, for three types of systems: two- and three-dimensional infrastructure and atmospheric oxidation enhancement, focusing on removing low ( $x_\textrm{CH4} \lt $ 1000 ppm) and ambient ( $x_\textrm{CH4} \lt $ 2 ppm) methane from air. With the space velocities and removal efficiencies of current three-dimensional technologies, volumes of 7–350 km ^3 are required to remove 1 Tg CH _4 yr ^−1 . Two-dimensional solutions are limited by the transport rate of methane to a surface. If every molecule of methane that collides with the surface is removed, an area of 1130 km ^2 is needed to remove 1 Tg CH _4 yr ^−1 at ambient concentration. However, research shows that per-collision reaction probabilities are $ \lt $ 10 ^−8 requiring a surface area of 10 ^10 –10 ^15 km ^2 . Finally, we examine atmospheric oxidation enhancement, where 4.8 Tg yr ^−1 of Cl $^\cdot$ or 8.8 Tg yr ^−1 of OH $^\cdot$ is required to remove 1 Tg CH _4 yr ^−1 , with precursors such as H _2 O _2 or O _3 . However, limitations arise concerning multiple environmental impacts. We conclude that the physical and practical constraints are considerable, and identify the main barriers that must be addressed.

Natural climate phenomena like El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) influence the Indian monsoon and thereby the region’s agricultural systems. Understanding their influence can provide seasonal predictability of agricultural production metrics to inform decision-making and mitigate potential food security challenges. Here, we analyze the effects of ENSO and IOD on four agricultural production metrics (production, harvested area, irrigated area, and yields) for rice, maize, sorghum, pearl millet, and finger millet across India from 1968 to 2015. El Niños and positive-IODs are associated with simultaneous reductions in the production and yields of multiple crops. Impacts vary considerably by crop and geography. Maize and pearl millet experience large declines in both production and yields when compared to other grains in districts located in the northwest and southern peninsular regions. Associated with warmer and drier conditions during El Niño, >70% of all crop districts experience lower production and yields. Impacts of positive-IODs exhibit relatively more spatial variability. La Niña and negative-IODs are associated with simultaneous increases in all production metrics across the crops, particularly benefiting traditional grains. Variations in impacts of ENSO and IOD on different cereals depend on where they are grown and differences in their sensitivity to climate conditions. We compare production metrics for each crop relative to rice in overlapping rainfed districts to isolate the influence of climate conditions. Maize production and yields experience larger reductions relative to rice, while pearl millet production and yields also experience reductions relative to rice during El Niños and positive-IODs. However, sorghum experiences enhanced production and harvested areas, and finger millet experiences enhanced production and yields. These findings suggest that transitioning from maize and rice to these traditional cereals could lower interannual production variability associated with natural climate variations.

In this paper, we study the exotic Landau problem at the classical level where two conserved quantities are derived. At the quantum level, the corresponding quantum operators of the conserved quantities provide two oscillator representations from which we derive two Boson Fock spaces. Using the normalized coherent states which are the minimum uncertainty states on noncommutative configuration space isomorphic to each of the boson Fock space, we form entangled coherent states which are Bell- like states labeled quasi-Bell states. The effect of non-maximality of a quasi-Bell state based quantum channel is investigated in the context of a teleportation of a qubit.

The degradation of an n ^++ GaN regrown ohmic contact in a MIS-HEMT device induced by ion beam etching (IBE) damages and relevant mechanisms have been studied. Abnormal I–V behaviors of the etched n ^++ GaN were observed by the transfer length method using a Ti/Al/Ni/Au stack as the contact metal, and it can be recovered with the assistance of post-metallization rapid thermal annealing. According to further analysis, we speculate that the degradation of the ohmic contact originates from the preferential loss of nitrogen by IBE, which boosts the oxygen incorporation and formation of an oxide layer isolating the contact metal from the n ^++ GaN.

Saline brines currently being brought to the surface to produce geothermal energy in the Salton Sea region of California contain high concentrations of lithium that could potentially be extracted before the brine is reinjected back into the geothermal reservoir. This would create a new supply chain of domestically sourced lithium for the United States to produce lithium-based batteries that will help drive the transition to a renewable-based energy grid. Plans to expand geothermal production along with lithium extraction are being considered in the Salton Sea known geothermal resource area. We discuss water availability and quality issues and potential concerns about water pollution associated with this geothermal expansion and lithium production in the context of potential future restrictions on water extractions from the Colorado River Basin. We estimate that water demand for currently proposed geothermal production and lithium extraction facilities only accounts for ∼4% of the historical water supply in the region. Regional water allocation will be more impacted by the proposed cuts to the region’s water allocation from the Colorado River between now and 2050 than by expansion of geothermal production with associated lithium extraction. Accurately planning for water needs in the future will require more specific information about water demands of the lithium extraction and refining processes.

An intense global research effort on carbon dioxide removal (CDR) technologies is generating a rapidly expanding scientific literature. These contributions stem from various disciplines and investigate various CDR concepts and their potential implications. This study conducts an updated analysis of the international research effort on CDR from 2012 to 2023, examining 7893 publications using bibliometric techniques. We focus on the geographic distribution of technology-specific research and the funding driving this research. Significant publication growth is observed post-2015, particularly after 2018 and in 2023, driven primarily by the EU, China, and the US. Notably, biochar, afforestation/reforestation, and soil carbon sequestration are among the most researched CDR options, with direct air carbon capture and storage, bioenergy carbon capture and storage, and blue carbon also receiving substantial attention, especially in 2023. Analysis of scientific funding patterns aligns with these trends. Based on these findings, the study proposes a knowledge roadmap to elucidate emerging trends in CDR literature, offering insights for future research and policy development.

It is well-known that climate warming increases air temperature and reduces cold extremes in the long-term. But internal variability strongly modulates the variability of temperature at mid- and- high latitudes, for example, causing the remarkable cooling and severe winter weather over Eurasia from the 1990s to the early 2010s. It remains unclear whether the occurrence of Eurasian cooling and cold extremes will be offset by climate warming or stimulated by internal variability in the future. Based on the Sixth phase of the Coupled Model Intercomparison Project multi-model projections for 2015–2100, this study shows that the projected probability of Eurasian cooling trend decreases with increasing greenhouse gas concentration in the long-term (i.e. 2070–2099) from 14.8% under SSP126 to 0.9% under SSP585. In the near-term (i.e. 2021–2050), however, Eurasian cooling occurrences are less influenced by different emission scenarios. Coinciding with deep Arctic warming throughout the troposphere, the projected significant Eurasian cooling exhibits similar pattern and intensity among different scenarios. The similar trend towards tropospheric anticyclone over the Arctic among different scenarios in the near-term promotes the deep Arctic warming-Eurasian cooling trend through transporting warm (cold) air into the Arctic (mid-latitudes). Moreover, winter extreme cold anomalies (i.e. −3.0–−2.0 °C) and extreme cold days (i.e. 4–6 d) over the Eurasian continent are not sensitive to emission scenarios in the near-term. In the long-term, the accelerating climate warming under high-emission scenarios significantly reduces the frequency and intensity of Eurasian cold extremes compared to low-emission scenarios. Therefore, the occurrence of Eurasian cooling trend and cold extremes in the near-term will be dominated by internal influences (e.g. Ural blocking) and will rely more on the internal variability after the mid-century if carbon neutrality goal is achieved.

Over the past decades, the Arctic-midlatitude linkage has been extensively explored. Recent studies have suggested that the characteristics of phasic evolutions in the relationship between the Arctic warming and midlatitudes remain elusive. Therefore, this study systematically investigates this issue by using running empirical orthogonal function and moving correlation, and the results show a phasic alternation process in the relationship between the tropospheric thickness over the Barents–Kara Seas (BKS) and East Asian temperature, characterized by a phasic weak (P1: 1979–2000)–strong (P2: 2001–2011)–weak (P3: 2012–2021) connection. Our results highlight that since the winter of 2010, despite the Arctic sea ice being in an exceptionally reduced phase and continuous Arctic warming, the Arctic-midlatitude connection has not exhibited sustained strengthening relative to P2 phase. Moreover, it is found that changes of the connection between the BKS warming and the East Asian winter Monsoon may contribute to this phasic evolution, and the Arctic Oscillation plays an important role in modulating their phasic evolutions. The conclusions of this study help to deepen our understanding of the evolution of the strength and weakness of the relationship between Arctic warming and climate variations in midlatitudes.

Marine CO _2 removal (CDR) using enhanced-alkalinity seawater discharge was simulated in the estuarine waters of the Salish Sea, Washington, US. The high-alkalinity seawater would be generated using bipolar membrane electrodialysis technology to remove acid and the alkaline stream returned to the sea. Response of the receiving waters was evaluated using a shoreline resolving hydrodynamic model with biogeochemistry, and carbonate chemistry. Two sites, and two deployment scales, each with enhanced TA of 2997 mmol m ^−3 and a pH of 9 were simulated. The effects on air-sea CO _2 flux and pH in the near-field as well as over the larger estuary wide domain were assessed. The large-scale deployment (addition of 164 Mmoles TA yr ^−1 ) in a small embayment (Sequim Bay, 12.5 km ^2 ) resulted in removal of 2066 T of CO _2 (45% of total simulated) at rate of 3756 mmol m ^−2 yr ^−1 , higher than the 63 mmol m ^−2 yr ^−1 required globally to remove 1.0 GT CO _2 yr ^−1 . It also reduced acidity in the bay, ΔpH ≈ +0.1 pH units, an amount comparable to the historic impacts of anthropogenic acidification in the Salish Sea. The mixing and dilution of added TA with distance from the source results in reduced CDR rates such that comparable amount 2176 T CO _2 yr ^−1 was removed over >1000 fold larger area of the rest of the model domain. There is the potential for more removal occurring beyond the region modeled. The CDR from reduction of outgassing between October and May accounts for as much as 90% of total CDR simulated. Of the total, only 375 T CO _2 yr ^−1 (8%) was from the open shelf portion of the model domain. With shallow depths limiting vertical mixing, nearshore estuarine waters may provide a more rapid removal of CO _2 using alkalinity enhancement relative to deeper oceanic sites.

Weather extremes can drive substantial crop losses. Farm-level management strategies play a critical role in mitigating the impacts of and consequences for farmer livelihoods and food security. While the impacts of extreme weather on crop yields are well documented in recent studies, these predominantly focused on expansive geographical scales and commonly overlooked the critical role of management practices in modulating the dynamics of weather-crop sensitivities. We fill this gap in the literature by using a unique dataset that explores the timely relationship between extreme weather and crop yields at farm level in the Netherlands. We cover 10 types of crops and elucidate the role of soil types, irrigation and nutrient application in modulating the relationship between extreme weather and crops, by estimating fixed-effects regression models. We show substantial impacts from drought during the growing- and harvesting period and excessive precipitation during the planting- and growing period. Severe droughts show significant ( $p\unicode{x2A7D}0.05$ ) reductions in yield for all crops, and lead to yield reductions up to 24 percent relative to average yields during the growing period. Meanwhile, eight crops show significant reductions in yield due to severe water excess during the planting period, with yield reductions up to 18 percent. Soils such as sand or loess amplify the negative impact of drought on crop yield, while softening the impact of excessive precipitation. Irrigation and to a lesser extent nutrient application are shown to moderately decrease the impact of extreme weather on crop yield. Our findings contribute valuable insights to guide local adaptation priorities which are critical given the projected increase in the intensity and frequency of extreme weather under climate change.

The impact of soil moisture (SM) and vapor pressure deficit (VPD) on gross primary productivity (GPP) variability in ecosystems is a topic of significant interest. Previous studies have predominantly focused on real-time associations between SM, VPD, and carbon uptake, attributing SM as the principal driver of GPP variability due to its direct and indirect effects through VPD. Using an information theory-based process network approach, we discovered that the influence of past VPD, mediated through its effects on SM, emerges as the primary driver of GPP variability across tropical regions. The past VPD conditions influence GPP directly and also affect SM in real-time alongside GPP, which subsequently impacts GPP variability. Examining land-atmosphere feedback using information theory reveals that past VPD conditions influence SM, but not the reverse. These causal structures explain the consistent decline in GPP with increasing VPD trends observed in tropical regions, which are not consistent with SM trends. Our findings emphasize the importance of considering the influence of past VPD mediated by SM when analyzing complex land-vegetation-atmosphere interactions.

Climate models project a weakening and expansion of the Hadley circulation (HC) under global warming but with considerable spread in the magnitude of these changes. Here, utilizing models from the latest Coupled Model Intercomparison Project Phase 6 (CMIP6), we illustrate how the variance in projected changes in the HC arises from equilibrium climate sensitivity (ECS) uncertainty across models. Models with higher ECS project a greater extent of static stability increase hence larger HC changes. Using the best estimate of ECS with value of 3 K (∼2.5–4.0 K) to constrain the HC projection, we reveal that the constrained projection yields a 15% (11%) decrease in the weakening (poleward shift) of the HC in the Northern (Southern) Hemisphere compared to the multimodel mean under the SSP5-8.5 scenario. The corresponding projection uncertainty is reduced by about 77.4% and 75.6%, respectively. Our results indicate a smaller-than-expected change in the HC in response to increased CO _2 concentrations.

Pumping energy is a key component of the groundwater governance challenge, yet it is largely missing in the discourse on agricultural use of groundwater. A sub-category of the literature studying groundwater-energy nexus tends to focus on groundwater depletion hotspots where entrenched interests and long-standing histories restrict the range of feasible energy pricing options. Using an agent-based model, we estimate the expected impact of expanding groundwater irrigation under five different energy provision models in Odisha, an Indian state with among the lowest irrigation coverage, and, therefore, is free of path-dependent policies. We find that aquifer properties play a crucial role in mediating the groundwater-energy nexus. In this study region, on average, the maximum volume of water that can be pumped from a well of a specific depth in an alluvial aquifer is approximately 150 times the volume that can be pumped from a well in a hard-rock aquifer. Therefore, the risk of over-consumption and aquifer depletion is a far greater challenge in alluvial than hard-rock aquifers. Risks of groundwater consumption and depletion can be limited in hard-rock aquifers provided the number and depths of wells can be controlled. Capital subsidies for well construction could be an effective policy to increase irrigated areas as long as economic incentives for digging deeper are not distorted. Our results imply that solar pumps are a relatively safe option for hard-rock regions where deep drawdowns naturally limit the extent of over-extraction. Solar pumps are also estimated to be among the most economical for expanding irrigation. Using a novel data set comprising biophysical and socioeconomic data, we find hard-rock regions to have limited irrigation coverage, high availability of annually replenishable groundwater, and high concentrations of marginalized farmers. Therefore, groundwater irrigation expansion in hard-rock areas could have dual benefits of ensuring future food security and targeting poverty reduction.

Studies have found that understanding forest management is critical in understanding the interaction between the carbon cycle and the integrated human-Earth system. This makes effectively representing forest management decisions such as planting and harvesting important. Here, we implement a novel dynamic forest harvest model in a global state of the art multi-sector dynamics model, namely the Global Change Analysis Model (GCAM). We implement an approach that explicitly tracks forest age and generates rotation ages for forest harvest that are responsive to changes in wood prices, changes in forest age and regional preferences for forest rotation. Furthermore, the forest sector in GCAM competes for investment with other land use types in the future years based on expected profit. Our baseline scenario results indicate that with the new forest harvest model, the current global wood product demand in GCAM can be met with minimal loss of old growth forest through the age-based harvest decisions. We find that economic pressure for deforestation and consequent loss of forest carbon is a bigger driver of global forest change than wood harvests, especially in developing regions. Under alternative scenarios where an economic value is placed on carbon across the terrestrial and energy systems, while there is an increase in forest plantations, there can be corresponding decreases in forest cover in some regions as forest land competes with land for bio-energy crops. When the carbon in forests is assigned a price, we find that the average rotation age for wood harvests can be reduced across regions to harvest forests in a more carbon efficient manner.

Coulomb excitation of hydrogen atoms by vortex protons is theoretically investigated within the framework of the non-relativistic first–Born approximation and the density matrix approach. Special attention is paid to the magnetic sublevel population of excited atoms and, consequently, to the angular distribution of the fluorescence radiation. We argue that both these properties are sensitive to the projection of the orbital angular momentum (OAM), carried by the projectile ions. In order to illustrate the OAM–effect, detailed calculations have been performed for the $1s \to 2p$ excitation and the subsequent $2p \to 1s$ radiative decay of a hydrogen target, interacting with incident Laguerre–Gaussian vortex protons. The calculation results suggest that Coulomb excitation can be employed for the diagnostics of vortex ion beam at accelerator and storage ring facilities.

We investigate the influence of quasiperiodic modulations on one-dimensional non-Hermitian diamond lattices with an artificial magnetic flux θ that possess flat bands. Our study shows that the symmetry of these modulations and the magnetic flux θ play a pivotal role in shaping the localization properties of the system. When θ = 0, the non-Hermitian lattice exhibits a single flat band in the crystalline case, and symmetric as well as antisymmetric modulations can induce accurate mobility edges. In contrast, when $\theta = \pi$ , the clean diamond lattice manifests three dispersionless bands referred to as an ‘all-band-flat’ (ABF) structure, irrespective of the non-Hermitian parameter. The ABF structure restricts the transition from delocalized to localized states, as all states remain localized for any finite symmetric modulation. Our numerical calculations further unveil that the ABF system subjected to antisymmetric modulations exhibits multifractal-to-localized edges. Multifractal states are predominantly concentrated in the internal region of the spectrum. Additionally, we explore the case where θ lies within the range of $(0, \pi)$ , revealing a diverse array of complex localization features. Finally, we propose a classical electrical circuit scheme to realize the non-Hermitian flat-band chain with quasiperiodic modulations.

The interplay between superconductivity and magnetism is an important subject in condensed matter physics. EuFe _2 As _2 -based iron pnictides could offer an interesting plateau to study their relationship that has attracted considerable attention. So far, two magnetic phase transitions were observed in EuFe _2 As _2 -based crystal, which were deemed to originate from the itinerant Fe moments (~190 K) and the localized Eu ^2+ moments (~19 K), respectively. Here, we systematically studied the heat capacity for the EuFe _2 (As $ _{1-x}$ P _x ) _2 crystals with x = 0.21 (optimally doped) and x = 0.29 (overdoped). We have found two new magnetic orders in the superconducting state (ranging from 0.4 to 1.2 K) in the optimally doped crystal. As more P was introduced into the As site, one of the magnetic orders becomes absent in the overdoped crystal. Additionally, we observed strong field and orientation dependence in heat capacity. The present findings in EuFe _2 (As $ _{1-x}$ P _x ) _2 have detected the new low-temperature magnetic orders, which may originate from the localized Eu ^2+ spins order or the spin reorientation.

We present a superquantization rule which indicates the possible robust stationary states of a generic driven-dissipative quantum system. Multistability in a driven cavity mode interacting with a qudit is revealed hence within a simple intuitive picture. The accuracy of the superquantization approach is confirmed by numerical simulations of the underlying quantum model. In the case when the qudit is composed of several two-level emitters coupled homogeneously to the cavity, we demonstrate the robustness of the superquantized steady states to single-emitter decay.

Accurate streamflow prediction is crucial to understand climate impacts on water resources and develop effective adaption strategies. A global long short-term memory (LSTM) model, using data from multiple basins, can enhance streamflow prediction, yet acquiring detailed basin attributes remains a challenge. To overcome this, we introduce the Geo-vision transformer (ViT)-LSTM model, a novel approach that enriches LSTM predictions by integrating basin attributes derived from remote sensing with a ViT architecture. Applied to 531 basins across the Contiguous United States, our method demonstrated superior prediction accuracy in both temporal and spatiotemporal extrapolation scenarios. Geo-ViT-LSTM marks a significant advancement in land surface modeling, providing a more comprehensive and effective tool for better understanding the environment responses to climate change.

Concerns exist about the viability of food security across Europe due to multiple, potentially adverse drivers. These include economic, political and climate forcing factors, all of which require quantification. Here, we focus on the climate forcing, and in particular, the soil moisture change component which crucially determines water availability for crop uptake. We estimate future soil moisture levels at 34 sites of the UK COsmic-ray Soil Moisture Observing System (COSMOS-UK) network. We do this by combining three platforms: the Joint UK Land Environment Simulator (JULES) land surface model, field-scale soil moisture observations from the COSMOS-UK stations and 2.2 km convection-permitting UK Climate Projections (UKCP18). We use COSMOS-UK data to optimise key soil moisture-related parameters in the JULES model, based on its performance in the contemporary period. We then force the calibrated model with UKCP18 data to produce future soil moisture estimates. We evaluate the modelled soil moisture for an average soil depth between 0 and 35 cm to match the depth of soil moisture observations. Our main conclusions concern future soil moisture droughts which we compare with equivalent events in the historical period, 1982–2000. We find that on average across all sites, there is an increase in the frequency of future extreme soil moisture drought events of duration above 90 days. In 2062–80, such frequency increase of between 0.1 and 0.6 events per year (equivalent to at least 2 and up to 12 additional events in a 20-year period) is expected. We also show that, in 2062–80, there is an increased risk of high or more intense soil moisture drought conditions in months between May and November, with months between June and October being at especially high risk. The UKCP18 data corresponds to a high-emissions future described by the RCP8.5 scenario.

The number of dams globally has increased dramatically over the past few decades, providing reliable water resources by regulating natural streamflow. However, assessing the impact of dams on natural streamflow at a large scale remains a challenge due to lack of dam storage variation data. Here we analyzed flow regulation by dams from 1985 to 2014 over 153 basins globally using satellite remote sensing data. Two-thirds of global basins are regulated below 10%, and the high degree of regulation is mainly distributed in underdeveloped regions such as Central Asia and East Asia. Only 27% of basins have an increasing regulation trend from 1985 to 2014 and no basins show a decreasing trend. The gross domestic production, climatic water deficit and runoff show significant correlations with the flow regulation. We provide a global scale assessment of flow regulation by dams to support global water resources management.

In theoretical research framework of acoustics or optics, how to provide stable and efficient experimental vortex sources with arbitrary orbital angular momentum (OAM) (especially with larger OAM) is a highly challenging research topic. Here, we propose and demonstrate the general principle of two different methods to generate vortex sources with arbitrary OAM, based on the point-sources array and acoustic metamaterials, respectively. Specifically, the general synthetic law is summarized from the analytical perspective behind generating two-dimensional vortex waves using different point sources with different phases, and the design flexibility of acoustic metamaterials is also utilized to provide an ideal solution for generating vortex sources with larger OAM. Besides, we qualitatively and quantitatively determine the OAM of generated vortex waves through simple formulas, and briefly discuss the applicability and stability of two different methods with complementary advantages. The principles of vortex sources generation revealed in this work provide direct theoretical support for the experimental exploration of interactions between multiphysics fields and complex media, with potential applications in vortex fields manipulation and OAM detection.

Since the ingenious discovery of zero-determinant (ZD) strategies by Press and Dyson, many efforts have been devoted to the evolutionary performance of ZD strategies. Recently, the effects of higher-order interactions on evolutionary games have attracted widespread interests, whereas it remains unknown how higher-order interactions affect the evolutionary performance of ZD strategies. This paper focuses on the role of higher-order interactions on evolutionary ZD strategies in iterated public goods game, where the baseline payoff is a key parameter to describe nodes’ extent of reciprocity in both first-order and second-order interactions. Through the adaptive-like dynamics, we found that there is a critical value of each network, above which the networked game will converge to a consensus state where all the nodes obtain the same payoff. This critical value is significantly affected by the relative strength of higher-order interactions with a U-shaped trend. Numerical simulations are carried out to explore how the network structures affect the dynamics. The results in networks with different sizes indicate that networks with higher average degree are more easily to converge to the consensus state. The simulations on a real-world network further support the theoretical conclusions.

Physical reservoir computing (PRC) with visible-light signals was demonstrated using dye-sensitized solar cells. The short-term memory required for PRC was confirmed using light pulse inputs. Waveform learning was demonstrated for nonlinear autoregressive moving-average time series level 2 (NARMA2) signals with normalized mean square error of 0.027. The relatively slow (milliseconds to seconds) and complex charge transfer dynamics in the TiO _2 porous layer with redox reactions in the solution phase provided the characteristics required for PRC.

The influence of mesoscale eddies on chlorophyll (Chl) has received significant attention due to Chl being a proxy for phytoplankton, which plays a crucial role in marine ecosystems. Solely relying on the analysis of satellite-observed Chl poses challenges in determining the phytoplankton response to mesoscale eddies. To address this, our study takes a collaborative approach, utilizing satellite-derived sea surface temperature anomalies (SSTA) and chlorophyll anomalies (CHLA) to comprehensively investigate the dynamical-biological processes associated with eddies in the subtropical and mid-latitude North Atlantic. In the subtropics, the patterns in CHLA and SSTA predominantly exhibit a dipole nature, with the dipole component providing more than 70% of the explained variance (EV). This suggests that eddy stirring is the dominant mechanism driving the observed anomaly patterns. Conversely, in the mid-latitudes, the monopole components ( T _M ) explain more than 60% of the EV, implying a more influential role for eddy trapping and vertical modulations. The signs of the T _M of eddy SSTA persist throughout their lifetime, being consistent with the lowering (raising) of isopycnals within AEs (CEs). However, the subtropical CHLA response is higher in AEs than CEs, indicating additional factors, such as eddy-induced Ekman pumping and/or mixing to a deeper level may be important. This finding is also corroborated by subsurface observations from Argo floats. At mid-latitudes, there is a clear inverse correspondence between the CHLA and mixed layer depth. In contrast, no significant correlation is observed in the subtropics, except during winter when a positive relationship emerges. These patterns suggest that phytoplankton exhibit highly diverse responses to the physical dynamics associated with eddies. Our work offers a method to estimate eddy dynamical-biological impacts on phytoplankton using satellite products, compensating for the limitations of in-situ observations. It also reveals potential contributions to marine primary production, global carbon cycles, and the development of biogeochemical models.