Recent ucb_erg items

Generating adversarial inputs for a graph neural network model of AC power flow

Fri, 11 Sep 2026 00:00:00 +0000

This work formulates and solves optimization prob- lems to generate input points that yield high errors between a neural network’s predicted AC power flow solution and solutions to the AC power flow equations. We demonstrate this capability on an instance of the CANOS-PF graph neural network model, as implemented by the PF∆ benchmark library, operating on a 14-bus test grid. Generated adversarial points yield errors as large as 3.7 per-unit in reactive power and 0.08 per-unit in voltage magnitude. When minimizing the perturbation from a training point necessary to satisfy adversarial constraints, we find that the constraints can be met with as little as an 0.04 per-unit perturbation in voltage magnitude on a single bus. This work motivates the development of rigorous verification and robust training methods for neural network surrogate models of AC power flow.

GPU-to-Grid: Voltage Regulation via GPU Utilization Control

Fri, 11 Sep 2026 00:00:00 +0000

While the rapid expansion of data centers poses challenges for power grids, it also offers new opportunities as flexible loads. Existing power system research often abstracts data centers as aggregate resources, while computer system research focuses on GPU energy efficiency and largely ignores grid impacts. To bridge this gap, we develop a GPU-to-Grid framework that couples device-level GPU control with power system objectives. We study distribution-level voltage regulation enabled by LLM inference flexibility, using batch size as a data- center-side control knob that trades off GPU power consumption, inference latency, and token throughput. We first formulate the problem as an optimization problem and then realize it as an online feedback optimization controller, implemented by the data center operator using its own empirical GPU power-performance model and real-time measurements from both the GPU and grid systems. Our key insight is that reducing GPU power alleviates lower-voltage...

Hybrid GFL-GFM Control for Converter-Dominated Power Systems: A Systematic Survey and Open-Source Implementation

Fri, 11 Sep 2026 00:00:00 +0000

With the large-scale grid integration of inverter- based resources (IBRs), power systems are rapidly transitioning toward a converter-dominated paradigm. This trend motivates hybrid grid-following (GFL) and grid-forming (GFM) control to combine fast power regulation with improved voltage and frequency support. This paper reviews classical GFL-GFM foun- dations and provides a structured taxonomy of hybrid GFL-GFM strategies for both converters and systems, including switching- type, dual-source, loop-augmented, and system-level categories. A parallel-branch hybrid architecture, which was recently ap- proved by the Western Electricity Coordinating Council, is then introduced. In this model, the GFL and GFM branches operate concurrently under a coordinating plant controller. Both the REGFM C1 converter control model and the REPCGFM C1 plant control model have been implemented and made available in the open-source ANDES simulator. Case studies on Single- Machine Infinite-Bus system...

Climate Impact on Residential Load: the Tale of 100K GAMs

Fri, 11 Sep 2026 00:00:00 +0000

We design statistical methodology to project the impact of climate change on residential load at the level of substations. To achieve high-resolution load projections, we combine the outputs of downscaled global climate models (GCMs) with a statistical additive regression model. To this end we design a bespoke Generalized Additive Model (GAM) that links cooling/heating loads at given substation and hour of day to daily meteorological covariates. Our models are trained on the ResStock outputs for a realistic building mix and illustrated on the entire 1898 substations in the CATS synthetic grid. The results visualize feature relevance and aggregate climate impacts on California residential loads.

Online Electricity Pricing from Frequency Measurements

Fri, 11 Sep 2026 00:00:00 +0000

Frequency dynamics in power systems reflect active power imbalance in real time, thereby providing an instantaneous signal to inform electricity pricing. However, existing real-time markets operate on much slower timescales and fail to exploit this signal. In this letter, we develop integrated market–frequency dynamics that enable online pricing directly from frequency measurements. Representing the real-time market as a dynamic price-discovery process, and integrating this process with the grid frequency dynamics, we derive an explicit price formation mech- anism from frequency measurements. This mechanism manifests as a distributed PID-like controller for each generator, where frequency response is driven and remunerated by electricity prices derived solely from local frequency measurements.

Physics-Informed Non-Dimensionalisation for Neural Solvers

Fri, 11 Sep 2026 00:00:00 +0000

The ability to assess and control approximation errors is key to the success of numerical methods. In contrast, learned approximations must ensure during training that error requirements are met, typically relying on statistical loss func- tions that do not account for the underlying physics. In this work, we argue that the assessment of learning errors in neural solvers should be aligned with numerical methods by evaluating errors in the residual norm of the governing equations. We show how this residual-based error measure can be integrated into the learning process through a physics-informed non-dimensionalisation of inputs and outputs, yielding a training objective that reflects physical sensitivities. The proposed construction reduces reliance on dataset-dependent statistics, improves robustness for limited training data, and provides an interpretable connection between training loss and engineering error measures. We demonstrate the approach on learning power flow solutions...

DC Link Capacitor Ripple Constraints Limit the Benefits of Utility-Owned Four-Wire Power Converters

Fri, 11 Sep 2026 00:00:00 +0000

Utilities are increasingly interested in power con- verters to increase the headroom of their assets by actively controlling power flows on their network. In this work we demonstrate that thermal limits of dc link capacitors can result in substantially diminished benefits of these converters under unbalanced operation, due to constraints on neutral current and double-line frequency power ripple. Considering nine voltage source converter topologies with varying ripple capabilities, the upper bound (in terms of additional headroom released) increases by more than 80% compared to a no-ripple case for the application of phase current unbalance mitigation.

Incentive-Based Load Curtailment with Limited Information: A Bilevel Zeroth-Order Learning Approach

Fri, 11 Sep 2026 00:00:00 +0000

Incentive-based load curtailment unlocks critical demand-side flexibility but is hindered by the limited knowledge of private user parameters and the inherent nonsmoothness of responses due to physical device constraints. We address this via a constrained bilevel optimization framework and propose the Bi-ZOL (Bilevel Zeroth-Order Learning) algorithm. Unlike conventional black-box methods, Bi-ZOL exploits the bilevel structure to decompose the hypergradient, integrating the exact analytical information of the SO’s objective with a zeroth-order estimate of the unknown response sensitivity. This structural decomposition-based learning method mathematically smoothes the nonsmooth response landscape and reduces hypergradient estimation error. We provide theoretical convergence guarantees to an approximate stationary point and demonstrate through simulations that Bi-ZOL achieves near-optimal performance.

Embedding Neural Surrogates into Established Dynamic Power System Simulators

Fri, 11 Sep 2026 00:00:00 +0000

The evolving landscape of power systems is leading to larger and more complex systems. Future power systems comprise more diverse components, exhibit faster dynamics, and are, in general, less predictable. As a result, time-domain simulations are becoming increasingly necessary for both offline studies and real-time stability assessment. This evolution renders dynamic simulations computationally more demanding, calling for improved simulation speed. Although classical solvers are reliable, their computational performance is limited by the need for iterative solution schemes. We present a modular method that allows Neural Network (NN) based surrogates of any power system component to be embedded within the decoupled Newton iterations of a time-domain solver. A case study integrates Physics-Informed Neural Networks (PINNs) into a solver and demonstrates the general applicability of the proposed approach. The results reveal specific challenges regarding PINN accuracy but highlight...

Modeling Joint Optimal Transmission Switching and Bus Splitting via Reduced Bus–Branch and Bus–Breaker Representations

Fri, 11 Sep 2026 00:00:00 +0000

Transmission network reconfiguration is essential for congestion management, yet substation reconfiguration (bus splitting) is often overlooked due to its modeling complexity. This paper proposes a unified framework to jointly optimize line switching and bus splitting. To maintain computational tractabil- ity, we employ two complementary representations: a bus-branch representation that models bus splitting as a line outage and power transfer; and a more detailed bus-breaker representa- tion that captures flexibility from substation reconfigurations beyond the bus-branch representation. We demonstrate that the bus-branch optimal solutions effectively guide the modeling of branch-to-busbar assignment policies of the bus-breaker repre- sentation, further enhancing performance under high loading levels with tight switching budgets. Numerical experiments on IEEE test systems confirm that this joint approach provides significant flexibility compared to line switching alone.

Admittance Matrix Concentration Inequalities for Understanding Uncertain Power Networks

Fri, 11 Sep 2026 00:00:00 +0000

This paper presents conservative probabilistic bounds for the spectrum of the admittance matrix and classical linear power flow models under uncertain network parameters; for example, probabilistic line contingencies. Our proposed approach imports tools from probability theory, such as concentration inequalities for random matrices. This provides a theoretical framework for understanding error bounds of common ap- proximations of the AC power flow equations under parameter uncertainty, including the DC and LinDistFlow approximations. Additionally, we show that the upper bounds scale as functions of nodal criticality. This network-theoretic quantity captures how uncertainty concentrates at critical nodes for use in contingency analysis. We validate these bounds on IEEE test networks, demonstrating that they correctly capture the scaling behavior of spectral perturbations up to conservative constants.

A Hybrid Mean Field Framework for Aggregators Participating in Wholesale Electricity Markets

Fri, 11 Sep 2026 00:00:00 +0000

The rapid growth of distributed energy resources (DERs) is reshaping wholesale electricity markets, where aggre- gators coordinate large populations of prosumers, end users who own DERs and can both consume and produce electricity, to participate at scale. Existing models typically either optimize a single aggregator under exogenous prices or analyze a small number of strategic agents; neither captures the scale, structure, and price feedback that arise when large DER populations interact through wholesale market clearing. We address this gap with a hybrid mean field framework in which each aggregator coordinates a large prosumer population through its infinite agent limit, while a finite number of aggrega- tors participate in wholesale markets. Each aggregator maximizes the collective payoff of its prosumers, a cooperative structure rep- resented by mean field control. Across aggregators, interactions are non-cooperative; as a starting point, we model aggregators as non-strategic,...

Structural Misalignment in Financial Transmission Rights

Fri, 11 Sep 2026 00:00:00 +0000

Financial Transmission Rights (FTRs) enable elec- tricity market participants to hedge congestion risk in Day Ahead Market (DAM) operations, but for the market to be solvent, Independent System Operators (ISOs) must ensure that FTR payouts do not exceed the collected DAM merchandising surplus that funds them. We show that FTR underfunding (or conversely, hedging efficiency) can arise structurally from misalignment between the network models used in the FTR auction and the DAM, independent of bidding behavior. We develop a geometric framework in which both DAM mer- chandising surplus and the maximum supportable FTR payout are expressed as support functions of network-feasible injection polytopes. The resulting dual representation assigns nonneg- ative weights to transmission element-contingency constraints, enabling constraint-level attribution of model misalignment. Using this framework, we derive sharp implications for canon- ical FTR network modeling choices like uniform...

Energy storage resource adequacy contributions considering state of charge deviations

Fri, 11 Sep 2026 00:00:00 +0000

Resource adequacy (RA) studies commonly repre- sent energy storage via economic dispatch, with the real-time state of charge (SOC) of storage units implicitly assumed to follow a predetermined schedule until scarcity conditions arise. This paper explores the implications of this assumption, by documenting how downward deviations in energy storage SOC in real-time operations affect reliability outcomes. Applying a probabilistic RA model to an ERCOT-like system with 5 GW of energy storage, we quantify the sensitivity of normalized expected unserved energy (NEUE) and marginal effective load carrying capability (ELCC) to SOC deviations across two-, four-, and eight-hour storage durations. We find that a downward SOC adjustment equal to 25% of maximum storage energy capacity increases system NEUE by a factor of 1.6–2.3 and reduces the marginal storage ELCC by 11–13 percentage points, both of which represent significant differences compared to reference cases. Metrics for shorter-duration...

Decentralized Stability Certificates in IBR-Dominated Grids: The Role of the Network State

Fri, 11 Sep 2026 00:00:00 +0000

Small-signal instabilities, such as unforced sub- synchronous oscillations (SSOs), are increasingly observed in inverter-based resource (IBR) dominated grids. While decentral- ized stability certificates offer a scalable means to avoid instability onset, they are typically derived under restrictive network-state assumptions–such as small angle differences or negligible voltage drops–that cannot capture how departures from these conditions affect system stability. In this paper, we develop a network model and a decentralized analysis framework that explicitly characterizes how reactive power mismatches, line loading, and inverter control parameters jointly determine small-signal stability. We show that increased steady-state reactive power mismatches and line loading lead to more stringent conditions on admissible inverter droop gains. These results make decentralized stability certificates explicitly network-state dependent, showing how network stress shrinks the set of stabilizing...

Zero-Shot Transfer Learning Across Reconfigurations for Three-Phase Unbalanced Power Distribution Systems

Fri, 11 Sep 2026 00:00:00 +0000

Distribution utilities increasingly rely on data-driven methods for state estimation and forecasting as large-scale renewable energy integration causes rapid state changes, yet most learning-based approaches remain tied to specific feeder topologies and require retraining when networks are reconfig- ured. In practice, retraining models for every feeder and opera- tional configuration is infeasible due to limited data availability, modeling effort, and computational costs. This paper presents a physics-aware graph learning framework for three-phase un- balanced distribution networks that enables zero-shot transfer across unseen feeder reconfigurations, with potential extension to feeders sharing similar electrical and topological statistics. By combining scalar-weight graph convolutions grounded in power flow physics with adaptive graph pooling, the proposed model learns topology-invariant representations while accommodating variable network sizes. Case studies on the IEEE 123-bus...

Dynamic Storage Operation Under Uncertainty and the Reliability Externality: Implications for Capacity Investments

Fri, 11 Sep 2026 00:00:00 +0000

Energy storage is increasingly relied upon to meet short-term demand uncertainties from renewable variability and electrification. Unlike conventional generators, storage’s contri- bution to reliability is policy-dependent and balances near-term arbitrage against future scarcity risk. We study how demand uncertainty alters such dynamic storage operation and how these operating decisions propagate into long-run investment outcomes. We formulate storage operation as an average-cost Markov decision process and embed the resulting stationary policies into a stylized capacity expansion framework. Demand uncertainty induces a precautionary storage policy which hedges against stochastic scarcity, leading to materially different post-storage demand distributions relative to perfect-foresight benchmarks. We additionally demonstrate that the reliability externality char- acteristic of electricity markets interacts with uncertainty in a manner that uniquely distorts both storage operation...

Trust-Region Benders for Scalable Multiperiod Expansion Planning for Transmission and Storage

Fri, 11 Sep 2026 00:00:00 +0000

Transmission expansion planning (TEP) seeks to identify cost-effective investment strategies that enable power systems to reliably meet future demand, while accounting for the location, timing, and operational impacts of infrastructure upgrades. As demand grows and renewable penetration increases, there is growing interest in jointly modeling energy storage investments to enhance operational flexibility. This work presents a multiperiod formulation that co-optimizes transmission reconductoring and energy storage installation across multiple planning periods. To solve the resulting large-scale problem efficiently, a Benders decomposition with per-period trust-region stabilization and a relaxation-based warm-start procedure is proposed. The approach is demonstrated on a 2,000-bus Texas system, producing an investment plan spanning 2030–2045 with optimality gap below 1.0%, and is compared against a rolling- horizon approach to highlight the benefits of multiperiod coor- dination

Locational Marginal Prices Obey DC Circuit Laws

Fri, 11 Sep 2026 00:00:00 +0000

Electricity markets often utilize the DC approxi- mation of the AC power flow equations to facilitate solving an otherwise complex nonconvex optimization problem. These DC power flow equations have analogies to DC circuit laws such as Kirchhoff’s Laws, resulting in an intuitive understanding of power flows under this model. Variables derived from the Lagrangian dual of the DC optimal power flow problem, such as locational marginal prices (LMPs) and congestion cost, are less intuitive without an understanding of optimization theory. Even with this understanding, LMP behavior, such as the conditions in which negative prices occur or the impact of individual congested lines on network-wide LMPs, remains somewhat mysterious. In this paper, we show that prices also obey DC circuit laws, which can help facilitate an intuitive understanding of their behav- ior and relationships throughout a network without explicitly understanding duality. In particular, prices can be modeled as voltages,...

Next-Generation Grid Codes: Toward a New Paradigm for Dynamic Ancillary Services

Fri, 11 Sep 2026 00:00:00 +0000

This paper presents preliminary results toward a conceptual foundation for Next-Generation Grid Codes (NGGCs) based on decentralized stability and performance certification for dynamic ancillary services. The proposed NGGC framework targets two core outcomes: (i) guaranteed closed-loop stability and (ii) explicit performance assurances for power-system frequency and voltage dynamics. Stability is addressed using loop-shifting and passivity-based methods that yield local frequency-domain certificates for individual devices, enabling fully decentralized verification of the interconnected system. Performance is char- acterized by deriving quantitative bounds on key time-domain metrics (e.g., nadirs, rate-of-change-of-frequency (RoCoF), steady- state deviations, and oscillation damping) through frequency- domain constraints on local device behavior. The framework is non-parametric and model-agnostic, accommodating a broad class of device dynamics under mild assumptions, and provides...

Productive Curtailment in Agrivoltaic Systems under Flexible Interconnection Agreements

Fri, 11 Sep 2026 00:00:00 +0000

Flexible interconnection agreements are increasingly used to streamline the distributed generation interconnection process by limiting real power exports and avoiding costly grid upgrades. Agrivoltaic systems–solar photovoltaic (PV) panels installed over agricultural land–can provide added value under these agreements by adjusting the PV panels away from sun tracking while increasing the sunlight available to crops. This technical note investigates the operation of agrivoltaics under flexible interconnection limits and evaluates their impact on both PV energy production and crop outcomes. We formulate an optimization problem that determines the time-varying tilt of a single-axis tracking agrivoltaic system to maximize energy production subject to a real power export limit over an entire growing season. The resulting PV operating schedules are then used to evaluate PV energy production and crop yield. In a case study, we demonstrate that agrivoltaic systems can comply with flexible...

Strategic Spatial Load Shifting and Market Efficiency

Fri, 11 Sep 2026 00:00:00 +0000

Large, spatially flexible electricity consumers such as data centers can reallocate demand across locations, influenc- ing dispatch and prices in wholesale electricity markets. While flexible load is often assumed to improve system efficiency, this intuition typically relies on price-taking behavior. We study price-anticipatory spatial load shifting by modeling a large flexible consumer as a Stackelberg leader interacting with DC optimal power flow (DC-OPF) based market clearing. We show that decentralized, cost-minimizing load shifting need not align with system operating cost minimization, and that misalignment arises at boundaries between DC-OPF operating regimes, where small changes in load can induce discrete changes in marginal generators or congestion patterns. We evaluate strategic load shifting on the 73-bus RTS-GMLC test system, where findings indicate reductions in system operating cost in most hours, but misalignment in a subset of cases that are driven by redispatch...

On the Concept of an Optimal Portfolio of Uncertain Flexible Loads

Fri, 11 Sep 2026 00:00:00 +0000

Flexible loads can enhance power system stability by providing reserves, but their limited energy capacity and uncer- tain availability distinguish them from conventional generators. To accommodate these characteristics, the Danish Transmission System Operator (TSO) recently introduced new reserve market rules that incorporate energy constraints and relax reliability requirements. In this context, the optimal reserve quantification becomes a joint chance-constrained reserve quantification prob- lem, which is difficult to solve. In this paper, we derive two analytical reformulations of this problem: an exact one when a reserve direction dominates and an approximate one, otherwise. Furthermore, when flexible loads must collectively satisfy a reliability requirement, we introduce the concept of an optimal portfolio of flexible loads: adding loads with similar expected values but different stochastic behaviors to an existing portfolio may change the total portfolio’s reserves....

Optimal Solar Investment and Operation under Asymmetric Net Metering

Fri, 11 Sep 2026 00:00:00 +0000

We examine the joint investment and operational decisions of a prosumer, a customer who both consumes and generates electricity, under net energy metering (NEM) tariffs. Traditional NEM schemes provide temporally flat compensation at the retail price for net energy exports over a billing period. However, ongoing reforms in several U.S. states are introducing time-varying prices and asymmetric import/export compensation to better align incentives with grid costs. While prior studies treat PV capacity as exogenous and focus primarily on consumption behavior, this work endogenizes PV investment and derives the marginal value of solar capacity for a flexible prosumer under asymmetric NEM tariffs. We characterize optimal investment and show how optimal investment changes with prices and PV costs. Through this analysis, we identify a PV effect: changes in NEM pricing in one period can influence net demand and consumption in generating periods with unchanged prices through adjustments...

A Coalitional Stable and Fair Reward Allocation for Dynamic Virtual Power Plants

Fri, 11 Sep 2026 00:00:00 +0000

This paper establishes crucial cooperation criteria for the operation of Dynamic Virtual Power Plants (DVPPs). We propose a control design and reward allocation mechanism to enable and incentivize Distributed Energy Resources (DERs) to provide dynamic ancillary services (DAS). Our results illustrate how the cooperative aggregation of heterogeneous DERs lever- ages technical complementarities to outperform standalone DAS provision. The proposed reward allocation fulfills critical game- theoretic criteria, including individual rationality, coalitional stability, incentive compatibility, optimality, fairness and ex- post consistency. The control design and reward allocation are validated using a case study based on the Finnish power grid.

Outage Identification from Electricity Market Data: Quickest Change Detection Approach

Fri, 11 Sep 2026 00:00:00 +0000

Power system outages expose market participants to significant financial risk unless promptly detected and hedged. We develop an outage identification method from public market signals grounded in the parametric quickest change detection (QCD) theory. Parametric QCD operates on stochastic data streams, distinguishing pre- and post-change regimes using the ratio of their respective probability density functions. To derive the density functions for normal and post-outage market signals, we exploit multi-parametric programming to decompose complex market signals into parametric random variables with a known density. These densities are then used to construct a QCD-based statistic that triggers an alarm as soon as the statistic exceeds an appropriate threshold. Numerical experiments on a stylized PJM testbed demonstrate rapid line outage identification from public streams of electricity demand and price data.

Bifurcation Analysis of Sub-Synchronous Oscillations Related to Grid-Forming Converter Inner Controllers

Fri, 11 Sep 2026 00:00:00 +0000

To ensure power system stability and security, it is vital to understand the complex nonlinear power system dy- namics related to converter-interfaced generators. For example, grid-forming (GFM) converters are expected to be a key asset for maintaining a strong and stable power system, but might cause wide-bandwidth stability issues with underlying mechanisms heretofore unseen or understudied, including sub-synchronous oscillations (SSOs). This paper details a continuation-based bi- furcation analysis of a GFM converter, revealing stability bounds with respect to operational conditions in addition to the time constant of the cascaded inner voltage and current controllers. We focus our analysis on the strong grid instability caused by an inner controller-related SSO, including continuation of the limit cycle past the Hopf bifurcation point, revealing rapid onset of unacceptably large oscillations. Furthermore, we investigate the impact of the circular current limiter, revealing...

Unlocking the Informational Value of Marginal Costs for Exact Time Series Aggregation in Generation Expansion Planning

Fri, 11 Sep 2026 00:00:00 +0000

This paper addresses the generation expansion plan- ning (GEP) problem, formulated as a mixed-integer linear programming model with intertemporal storage constraints. Be- ing generally NP-hard, the problem’s computational complexity grows sharply with the planning horizon and the number of binary variables. While previous research has tackled this challenge using heuristic time series aggregation (TSA) methods, we propose a theoretically grounded marginal-cost-based TSA, designed to construct an aggregated model that preserves the active constraints of its full-scale counterpart, thereby explic- itly targeting exact temporal aggregation. This TSA method is embedded within solution algorithms that iteratively refine theoretically validated bounds on the maximum error introduced by the temporal aggregation relative to conventional full-scale optimization, thus offering a formal performance guarantee to the decision-maker. Numerical results highlight the computational advantages...

A Sparsification Method for Security-Constrained Optimal Power Flow

Fri, 11 Sep 2026 00:00:00 +0000

To ensure the security of power systems, operators solve security-constrained optimal power flow (SCOPF) problems to determine setpoints that satisfy operational constraints under credible contingencies. As the size of the contingency increases, the problem becomes computationally expensive, especially for very large systems with thousands of buses and lines. Solving SCOPF problems with large systems using the typical B-θ model can become intractable. Instead, a more tractable approach is to use a sensitivity-based model based on Power Transfer Distri- bution Factors (PTDFs). Sensitivity-based models solve SCOPF problems more efficiently when a subset of the constraints is active at optimal solutions. Although solving SCOPF with the PTDF has many advantages over the B-θ model, the PTDF matrix is very dense in real-world systems, resulting in slow computational performance. This paper presents a method for sparsifying the PTDF matrix without compromising solution quality. The...

Safe Reconnection Time for Large-Scale Data Center Loads: An Analytical Framework for Transient Stability Assessment

Fri, 11 Sep 2026 00:00:00 +0000

The rapid growth of large, power electronics-rich data center loads (DCLs) is creating new operational challenges for bulk power systems. A key risk arises when a DCLs unin- terruptible power supply (UPS) disconnects the facility during voltage/frequency disturbances and then reconnects it while the bulk grid is still dynamically settling to a new equilibrium point. Poorly timed reconnection can amplify electromechanical oscillations, deepen frequency deviations, and lead to repeated connect-disconnect flapping. In this paper, we develop an an- alytical framework to characterize the safe reconnection time for large DCL after a disturbance-induced disconnection that avoids flapping. Using a model in the spirit of the classical single-machine infinite-bus system, we capture (i) swing dynamics during the disconnection interval and (ii) voltage-angle coupling at the load bus, which determines the electrical power step at re- connection under constant-power load assumptions. Using...

Self-Certifying Primal-Dual Optimization Proxies for Large-Scale Batch Economic Dispatch

Fri, 11 Sep 2026 00:00:00 +0000

Recent research has shown that optimization proxies can be trained to high fidelity, achieving average optimality gaps under 1% for large-scale problems. However, worst-case analyses show that there exist in-distribution queries that result in orders of magnitude higher optimality gap, making it difficult to trust the predictions in practice. This paper aims at striking a balance between classical solvers and optimization proxies in order to enable trustworthy deployments with interpretable speed-optimality tradeoffs based on a user-defined optimality threshold. To this end, the paper proposes a hybrid solver that leverages duality theory to efficiently bound the optimality gap of predictions, falling back to a classical solver for queries where optimality cannot be certified. To improve the achieved speedup of the hybrid solver, the paper proposes an alternative training procedure that combines the primal and dual proxy training. Experiments on large-scale transmission systems...

A Welfarist Perspective on Fair Generation Curtailment

Fri, 11 Sep 2026 00:00:00 +0000

This paper presents a welfarist approach to fair active power curtailment in distribution grids with distributed photovoltaics. We address the lack of consistent axiomatic foun- dations in existing ad-hoc curtailment rules by modeling the decision as a social choice problem over feasible operating points and by deriving curtailment objectives from a set of foundational axioms that express principled stances on fairness and grid access rights. Rather than relying on the typically assumed full comparability of utilities, which can lead to undesirable outcomes in heterogeneous residential systems, we adopt a cardinal non- comparability stance on utilities. This approach requires far fewer assumptions about prosumers’ private preferences while providing a rigorous basis for fair social ranking. We then present a unified framework that demonstrates that existing curtailment schemes represent specific instances of the Kalai- Smorodinsky rule applied to different normative reference...

Integrated Investment and Policy Planning for Power Systems via Differentiable Scenario Generation

Fri, 11 Sep 2026 00:00:00 +0000

We formulate a method to co-optimize power system capacity planning decisions and policy investments that shape electricity load patterns. To this end, we leverage a gradient- based solution technique that enables the efficient solution of operation-aware planning models. To compute gradients with respect to the conditions that define daily electricity demand profiles, we introduce and formalize the concept of differentiable scenario generation and show that generative machine learning models satisfy the mathematical requirements needed to compute consistent gradients. We demonstrate the feasibility of the pro- posed approach through numerical experiments using a diffusion model–based scenario generator and a stylized generation and capacity expansion planning model.

Risk-Hedging Market Clearing for Flexible Ramping Products with Price-Maker Virtual Batteries

Fri, 11 Sep 2026 00:00:00 +0000

Current Flexible Ramping Product (FRP) procure- ment relies heavily on gas-fired generators, which incur signifi- cant inefficiencies due to the “over-commitment” problem caused by minimum generation constraints. While HVAC-based Virtual Batteries (VBs) offer a flexible alternative, their large-scale aggregation transforms them from price-takers to price-makers, creating a unique financial risk: the HVAC load increasing phase may coincide with self-induced price spikes, eroding ramping revenues. To address this, this paper proposes a two-stage stochastic market clearing framework that co-optimizes energy and ramping services. We explicitly model the distinct “Up- Down” and “Down-Up” load shifting of VBs to provide ramping capacities. Crucially, a financial risk management mechanism is integrated into the optimization to hedge against the price volatility caused by the VBs’ own load-shifting behavior. Nu- merical results demonstrate that the proposed method effectively mitigates...

Generalized Vector Locus Transformation for Unbalanced Three-Phase Systems

Fri, 11 Sep 2026 00:00:00 +0000

Coordinate transformations significantly simplify power systems computations. Most notably, the classical Clarke and dq0 transformations are widely used in three-phase systems, as together they transform balanced abc quantities into constant- valued signals. However, during unbalanced operation, the utility of these transformations diminishes, since a null 0-coordinate cannot be ensured and oscillating signals emerge. While recently proposed transformations ensure a null 0-coordinate, they either do not lead to constant-valued signals in the dq0 domain or fail under various unbalanced scenarios. In this paper, we propose a Generalized Vector Locus (GVL) transformation that ensures both a null 0-coordinate and constant-valued signals. Moreover, we show that, in the balanced case, the classical amplitude- invariant Clarke transformation is an instance of the proposed GVL transformation.

Next-Generation Grid Codes: Toward a New Paradigm for Dynamic Ancillary Services

Thu, 10 Sep 2026 00:00:00 +0000

Decentralized Stability Certificates in IBR-Dominated Grids: The Role of the Network State

Thu, 10 Sep 2026 00:00:00 +0000

Zero-Shot Transfer Learning for Three-Phase Unbalanced Power Distribution Systems

Thu, 10 Sep 2026 00:00:00 +0000

Snow-eater heat waves of the western United States

Thu, 20 Aug 2026 00:00:00 +0000

Abrupt snowmelt, triggered by rain-on-snow events or "snow-eater heat waves," can cause flooding, initiate or accelerate snow drought, and affect water availability. However, the characteristics (e.g., area, duration, and frequency), impacts, and trends of snow-eater heat waves have received little attention. To address this gap, we developed a method to identify snow-eater heat waves and estimate their melt potential using 20th Century Reanalysis version 3 air temperature data, the TempestExtremes algorithm, and an operational snowmelt model (SNOW-17) across 1850-2015. Melt season snow-eater heat waves typically last 3 to 5 days, with three to five events, doubling snowmelt rates. Seven of 11 spring superfloods are shown to coincide with snow-eater heat waves. Since the 1850s, snow-eater heat waves have increased in area and frequency, decreased in duration, and shifted earlier in the melt season. Incorporating snow-eater heat-wave impacts into SNOW-17 enhances extreme melt estimates,...

Author Correction: Potential of artificial intelligence in reducing energy and carbon emissions of commercial buildings at scale

Tue, 11 Aug 2026 00:00:00 +0000

Correction to: Nature Communications; https://doi.org/10.1038/s41467-024-50088-4, published online 14 July 2024 In the version of the article initially published, Jessica Granderson (Energy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, CA, USA) was not included in the author list and now appears in the HTML and PDF versions of the article.

A U.S. Scientific Community Vision for Sustained Earth Observations of Greenhouse Gases to Support Local to Global Action

Thu, 30 Jul 2026 00:00:00 +0000

Abstract Managing carbon stocks in the land, ocean, and atmosphere under changing climate requires a globally‐integrated view of carbon cycle processes at local and regional scales. The growing Earth Observation (EO) record is the backbone of this multi‐scale system, providing local information with discrete coverage from surface measurements and regional information at global scale from satellites. Carbon flux information, anchored by inverse estimates from spaceborne Greenhouse Gas (GHG) concentrations, provides an important top‐down view of carbon emissions and sinks, but currently lacks global continuity at assessment and management scales (<100 km). Partial‐column data can help separate signals in the boundary layer from the overlying atmosphere, providing an opportunity to enhance surface sensitivity and bring flux resolution down from that of column‐integrated data (100–500 km). Based on a workshop held in September 2024, the carbon cycle community envisions...

Assessing Consistency in Fuel Consumed Between Activity‐Based Wildfire Emission Estimates

Thu, 30 Jul 2026 00:00:00 +0000

Abstract Wildfire emission inventories exhibit large variability that complicates assessments of smoke impacts. Here we compare fuel consumed (in mass per burned area units) from multiple burn area‐based and energy‐based approaches for fires in the western US during 2020. Average fuel consumed can vary by up to factors of 2–16 between approaches across burn severity classes and fuel types. Fuel consumed estimates typically increase with burn severity, except for the energy‐based approaches for forest land cover, where it decreases for high burn severity. Also, in contrast to other approaches, energy‐based estimates decrease for tree cover greater than 40% regardless of burn severity class. This implies that corrections to the energy‐based approach are likely needed across burn severity categories to account for canopy and smoke shading. The methodological recommendations provided would likely result in greater consistency between wildfire emission estimates and highlight the need...

A U.S. scientific community review of carbon cycle science gaps and opportunities to better support earth system science and carbon management

Thu, 30 Jul 2026 00:00:00 +0000

Greenhouse gas (GHG) emissions continue to grow, while natural carbon reservoirs are becoming increasingly vulnerable to anthropogenic pressures, climate extremes, and disturbance. These changes are impacting humans, ecosystems, and natural resources worldwide. Tracking and mitigating GHG emissions require a pivot to operational monitoring of regional carbon flux and stock changes. The current GHG observing system is addressing needs at two distinct scales: 1) Local scale (< 1 km), related to anthropogenic point source emissions, and 2) global scales (> 1000 km), related to land and ocean carbon sinks. More focus on intermediate (10–1000 km) scales is needed to more effectively monitor progress in reducing carbon emissions, enhancing removals, and maintaining sinks.Representatives from carbon cycle biomass and flux communities across United States government agencies and academic institutions met in September 2024 to discuss the rationale and scientific context...

Utilizing Noncoincident Needs to Site Data Centers with Solar+Storage at Existing Gas Plants

Mon, 20 Jul 2026 00:00:00 +0000

Data centers and large electricity loads are power hungry, raising concerns about higher electricity costs, increased emissions, and reliability risks. We show that co-locating solar+storage systems with underutilized natural gas plants offers a practical, near-term pathway for reliable, low-cost industrial power. Using eight years of hourly weather data, we co-optimize load and hybrid solar+storage+gas configurations at 68 existing plants near data center developments, meeting over 95% of demand with solar+storage. Across these sites, levelized costs range from $60-138/MWh, competitive with data centers’ recent contract prices for 24/7 clean power. Conflict analysis indicates minimal overlap between solar+storage backup needs and grid stress across most regions of the United States today, allowing gas units to provide dual roles: facilitating large load integration while supporting grid reliability. By optimizing existing infrastructure, this approach offers a scalable pathway...

Dynamic Grid Management Technologies Reduce Wildfire Adaptation Costs in the Electric Power Sector

Mon, 20 Jul 2026 00:00:00 +0000

Wildfire is among the fastest-growing economic risks of climate change, yet strategies to adapt cost-effectively remain under-explored. In the electric power sector, where ignitions have triggered some of the most destructive wildfires on record, utilities are investing heavily to mitigate risk. This study evaluates the cost, reliability, and risk reduction benefits of the largest utility wildfire mitigation program in the U.S. Using detailed weather and vegetation data for 25,000 miles of high-risk powerlines, we develop a prediction model to estimate ignition risk and compare outcomes across locations with similar risk that received different interventions. With this quasi experimental design, we find that a new strategy that dynamically adjusts protective device sensitivity during elevated wildfire conditions reduces risk more cost-effectively than conventional measures such as burying powerlines underground or trimming vegetation. By combining models of wildfire risk, costs,...

Does Regulation Distort Exit Decisions? Evidence from U.S. Power Plants

Mon, 20 Jul 2026 00:00:00 +0000

Hundreds of power plants have closed in the United States since 2010, including 130+ gigawatts of coal and 50+ gigawatts of natural gas. In this paper, we highlight the potential for regulation to distort this type of exit decision. Using generator-level data from 2010–2023, we show that regulated units have been 45% less likely to exit than unregulated units. For unregulated units, exit decisions are made based on wholesale electricity prices, ongoing capital costs, and other traditional economic factors. In contrast, owners of regulated units are largely insulated from these factors and, in some cases, have a strong incentive to continue operating capital-intensive equipment. Previous work documents how this regulatory distortion affects investment decisions. Our paper emphasizes that these same incentives affect exit decisions as well.

The Environmental Costs and Geography of U.S. Data Center Expansion

Mon, 20 Jul 2026 00:00:00 +0000

Data centers powering artificial intelligence are growing rapidly across the United States, raising concerns among policymakers and local communities about their environmental and social costs. These costs depend on where data centers locate, and strategic siting has been proposed as a way to limit them. Using a comprehensive facility-level dataset of past, operational, and announced U.S. data centers, we characterize how the environmental and community characteristics of data center locations evolve over 2010–2030. We quantify how much of the projected growth in environmental damages can be attributed to changes in data center locations versus growth in power requirements. Decomposing projected carbon emissions and monetized local air pollution damages into scale and location-driven composition effects, we find that over 2010–2025, composition changes reduced carbon and local air pollution damages by 4 and 12%, respectively. Over 2024–2030, scale accounts for approximately 97%...

Benefits, Costs, and Distributional Outcomes in an Environmental Market

Mon, 20 Jul 2026 00:00:00 +0000

We study the benefits, abatement costs, and distributional outcomes of the EPA’s NOx Budget Program, a seasonal cap-and-trade market for NOx emissions. Using a new empirical approach, we recover source-specific marginal abatement cost curves and combine them with source-specific air pollution damages to quantify market outcomes. We find that abatement costs under the market are roughly one-sixth those of an abatement-equivalent non-market policy. Despite these large differences in aggregate costs, the market and the non-market policy yield similar air quality benefits, both in overall magnitude and across demographic groups. We show that these results reflect the weak correlation between source-specific marginal damages and abatement behavior.

Improving energy efficiency while reducing anthropogenic heat from buildings: how retrofits influence the building stock and urban microclimate in Los Angeles

Thu, 16 Jul 2026 00:00:00 +0000

Anthropogenic heat (AH) from buildings contributes to urban overheating, especially during heat waves, yet building retrofit studies usually evaluate energy savings without assessing impacts on AH. This study quantifies how common building retrofit measures affect both building energy use and AH emissions across the City of Los Angeles. Using a bottom-up urban building energy modeling framework coupled with high-resolution local weather from the Weather Research and Forecasting model with Building Effect Parameterization (WRF-BEP), we evaluate eleven retrofit measures and two multi-measure retrofit packages. HVAC and LED lighting retrofits provide the largest city-wide annual site energy savings, while roof coating is most effective for reducing AH. A package optimized for energy savings reduces summer site energy use by about 32% (2.3 TWh), while a package incorporating AH-focused measures reduces the total AH by over 50% (137 PJ) with minimal difference in energy savings. The...

Can Distribution Grid Infrastructure Accommodate Residential Electrification and Electric Vehicle Adoption in Northern California?

Wed, 15 Jul 2026 00:00:00 +0000

In this paper we ask: in what ways will utilities need to upgrade the electric distribution grid to accommodate electrified loads, and what will those upgrades cost? Our study focuses on the PG&E service area in Northern California, which serves 4.8 million electricity customers and is subject to aggressive targets for both EV adoption and electrification of residential space and water heating. We create spatio-temporally detailed electricity demand forecasts, and compare that demand to distribution infrastructure limits across a range of technology adoption scenarios. We find that electrification of residential space and water heating will lead to fewer impacts on distribution feeder capacity than EV charging, but that both transitions will require an acceleration of the current pace of upgrades. We also find that timing and location have a strong influence on total capacity additions in important ways: for example, scenarios that favor daytime EV charging have similar...

Accelerating Transmission Expansion by Using Advanced Conductors in Existing Right-of-Way

Wed, 15 Jul 2026 00:00:00 +0000

As countries pursue decarbonization goals, the rapid expansion of transmission capacity for renewable energy (RE) integration poses a significant challenge due to hurdles such as permitting and cost allocation. However, we find that large-scale reconductoring with advanced composite-core conductors can cost-effectively double transmission capacity within existing right-of-way (ROW), with limited additional permitting. This strategy unlocks a high availability of increasingly economically-viable RE resources in close proximity to the existing network. We implement reconductoring in a model of the United States power system, showing that reconductoring can help meet over 80% of the new interzonal transmission needed to reach over 90% clean electricity by 2035 given restrictions on greenfield transmission build-out. With $180 billion in system cost savings by 2050, reconductoring presents a cost-effective and time-efficient, yet underutilized, opportunity to accelerate global...

Economic Effects of Distributed PV Generation on California's Distribution System

Tue, 14 Jul 2026 00:00:00 +0000

The economic value of distributed photovoltaic (PV) electricity is affected both by its correlation with transmission level energy prices and by a host of effects it may have on distribution systems. In this study we combine detailed physical simulation of distribution circuits with budgetary information provided by Pacific Gas & Electric (PG&E) to estimate PV’s value with respect avoided transmission-level energy expenditures, avoided distribution system capacity upgrades, and increased expenditures to manage voltage magnitudes. We find that favorable timing of generation and the potential to defer capacity investments both increase PV’s value on average by a small amount. We use circuit-level loading and load growth data to show that distribution circuit capacity value is very heterogeneous: PV shows very little capacity value on most circuits but substantial (over $60/kW-yr, nearly half of the near-term targets for the cost of distributed PV) on a limited number of...

Location, Location, Location: The Variable Value of Renewable Energy and Demand-side Efficiency Resources

Tue, 14 Jul 2026 00:00:00 +0000

Greenhouse gas mitigation efforts in the electricity sector emphasize accelerated deployment of energy efficiency measures and renewable energy resources. We evaluate renewable energy (RE) and energy efficiency (EE) technologies across regional power systems in the United States in terms of carbon dioxide emissions displaced, operating costs avoided, and capacity value generated. We estimate that external, emissions-related benefits account for between one quarter and one half of the total value generated per MWh over our study period. Regional variation in these emissions benefits gives rise to economically significant, regional differences in second-best production subsidies. This variation is not reflected in the prevailing policy incentives that currently guide new investments.

Global Carbon Budget 2025

Wed, 1 Jul 2026 00:00:00 +0000

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesise datasets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy and cement production data. Emissions from land-use change (ELUC) are estimated by bookkeeping models based on land-use data. The global atmospheric CO2 growth rate (GATM) is computed from changes in concentration measured at surface stations. The global net uptake of CO2 by the ocean (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based fCO2-products. The global net uptake of CO2 by the land (SLAND) is estimated with dynamic global vegetation...

Multi‐Decadal Dynamics of Wetland Methane Emissions Revealed by Knowledge‐Guided Machine Learning

Thu, 11 Jun 2026 00:00:00 +0000

Measurement of methane fluxes (FCH₄) from natural systems, such as wetlands, has lagged far behind carbon dioxide fluxes. Short and fragmented wetland FCH₄ data limit our ability to assess its long-term dynamics and potential climate feedbacks. Extrapolating short-term FCH₄ records to recent decades remains challenging for both process-based models and data-driven machine learning (ML) approaches. Here, we develop a knowledge-guided ML framework that integrates eddy covariance (EC) FCH₄ observations, field warming experiments, and biogeochemical knowledge to reconstruct the long-term FCH₄ budgets and trends. Focusing on the 11 longest EC monitoring sites in the AmeriFlux network, we found considerable variability in multi-decadal trends of wetland FCH₄, with increases up to 14% per decade from 2000 to 2024. We also found that the strength of these increasing trends declines from high to low latitudes, highlighting...

Forest aboveground biomass estimation through integration of sentinel-2 and PALSAR-2 time series: assessing models trained on GEDI and field inventory benchmarks

Wed, 10 Jun 2026 00:00:00 +0000

Accurate and spatially explicit forest Aboveground Biomass (AGB) mapping through remote sensing is critical for quantifying terrestrial carbon stocks and informing effective forest management strategies. However, AGB estimation in dense forests with complex terrain remains challenging due to satellite sensor signal saturation problem (saturation issue occurs in high biomass forests), structural complexity, and limited ground truth for calibration. This study presents a novel framework that integrates multi-temporal Sentinel-2 optical imagery, ALOS PALSAR-2 Synthetic Aperture Radar (SAR) data, and topographic variables with explainable Machine Learning to map AGB across mountainous forests within subtropical and temperate oceanic climate zones of Mexico. We evaluate the effects of temporal granularity and sensor synergy by comparing multiple temporal inputs and sensor configurations (Sentinel-2, PALSAR-2, and their fusion), and assess model performance using two reference datasets:...

CMIP7 data request: Earth system priorities and opportunities

Thu, 14 May 2026 00:00:00 +0000

Abstract. This paper presents a comprehensive overview of the Coupled Model Intercomparison Project Phase 7 (CMIP7) request for data pertaining to Earth systems science, and provides justification for the resources needed to produce this data. Topics within the CMIP7 Earth System (CMIP7-ES) theme centre around tracking of flows of energy, carbon, water and other fluxes across domains, and constraining feedbacks between these cycles and the climate system. These topics are summarized in this paper as scientific “opportunities” describing specific model intercomparison experiments and use cases for next-generation Earth System Model (ESM) output. These opportunities were submitted by modelling groups and scientific consortia following an extended public consultation process. Contained within each opportunity are requests for groups of Climate & Forecasting (CF) variables, which are bundled into variable groups representing all data required to address...

Contrasting Parametric Sensitivities in Two Global Vegetation Models Using Parameter Perturbation Ensembles

Wed, 15 Apr 2026 00:00:00 +0000

Abstract Uncertainty in land model projections remains high and the roles of parametric and structural uncertainty are difficult to disentangle. To compare parametric sensitivity across model structures we present two parameter perturbation ensembles using the Community Land Model (CLM) operating in satellite phenology mode. The ensembles contrast two vegetation modules: (a) the default CLM vegetation module and (b) the Functionally Assembled Terrestrial Ecosystem Simulator (CLM‐FATES). We perturbed over 300 parameters and quantified their effects on biophysical fluxes globally and across biomes. Most parameters have minimal impact on biophysical fluxes, with only a few substantially influencing results. While both models exhibit similar parameter sensitivity for some fluxes, CLM‐FATES shows larger spread in gross primary productivity (GPP), driven by strong sensitivity to carboxylation rate. CLM‐FATES also shows a weaker GPP response to soil hydrology parameters and exhibits...

Methodological Design Choices Can Affect Air Pollution Exposure Disparity Estimates: A Case Study on California’s Agricultural Sector

Mon, 30 Mar 2026 00:00:00 +0000

People of color in the United States are disproportionately and unfairly exposed to air pollution. Equity-oriented scientific evaluations quantifying these disparities often use population-average exposure metrics to capture the overall inequality within a system. Utilizing these metrics involves choices about the exposure input for assessing disparity, the study geography, and the reference population, which are critical to understanding disparities and effectively designing interventions. Here, we use a case study of exposure to fine particulate matter (PM_2.5) from California's agricultural sector to dissect the implications of these decisions. Using a reduced-complexity model and emissions of PM_2.5 and precursors, we compare estimates of racial and ethnic disparities in exposure resulting from different combinations of these methodological choices. The full population distributions highlight differences between disparities at the extremes (e.g., 90th percentile)...

Acceleration of Power System Dynamic Simulations Using a Deep Equilibrium Layer and Neural ODE Surrogate

Mon, 23 Mar 2026 00:00:00 +0000

The dominant paradigm for power system dynamic simulation is to build system-level simulations by combining physics-based models of individual components. The sheer size of the system along with the rapid integration of inverter-based resources exacerbates the computational burden of running time domain simulations. In this paper, we propose a data-driven surrogate model based on implicit machine learningspecifically deep equilibrium layers and neural ordinary differential equationsto learn a reduced order model of a portion of the full underlying system. The data-driven surrogate achieves similar accuracy and reduction in simulation time compared to a physics-based surrogate, without the constraint of requiring detailed knowledge of the underlying dynamic models. This work also establishes key requirements needed to integrate the surrogate into existing simulation workflows; the proposed surrogate is initialized to a steady state operating point that matches the power flow solution...

Large CO2 removal potential of woody debris preservation in managed forests

Mon, 9 Mar 2026 00:00:00 +0000

Limiting climate warming to 1.5 °C requires reductions in greenhouse gas emissions and CO2 removal. While various CO2 removal strategies have been explored to achieve global net-zero greenhouse gas emissions and account for legacy emissions, additional exploration is warranted to examine more durable, scalable and sustainable approaches to achieve climate targets. Here we show that preserving woody debris in managed forests can remove gigatonnes of CO2 from the atmosphere sustainably based on a carbon cycle analysis using three Earth system models. Woody debris is produced from logging, sawmill wastes and abandoned woody products, and can be preserved in deep soil to lengthen its residence time (a measure of durability) by thousands of years. Preserving annual woody debris production in managed forests has the capacity to remove 769–937 GtCO2 from the atmosphere cumulatively (10.1–12.4 GtCO2 yr−1 on average) from 2025 to 2100, if its residence time is lengthened for 100–2,000...

Subsets of geostationary satellite data over international observing network sites for studying the diurnal dynamics of energy, carbon, and water cycles

Tue, 17 Feb 2026 00:00:00 +0000

Abstract. The latest generation of geostationary satellites provide Earth observations similar to widely used polar-orbiting sensors but at intervals as frequently as every 5–10 min, making them ideal for studying the diurnal dynamics of land–atmosphere interactions. The NASA Earth Exchange (NEX) group created the GeoNEX datasets by collating data from several geostationary platforms, including GOES-16/17/18, Himawari-8/9, and GK-2A, and placing them on a common grid to facilitate use by the Earth science community. Here, we document the GeoNEX Coincident Ground Observations (GeCGO) dataset for terrestrial ecosystem studies and provide examples for its use. Currently, GeCGO provides GOES-16 Advanced Baseline Imager (ABI) data over a 10 km × 10 km area surrounding 1586 network sites across the Americas. GeCGO makes it easy to compare the time series of geostationary data with the diurnal ground observations, including carbon/water fluxes and aerosol optical depth, and is extensible...

The DREAM approach to demand-side emissions reductions in Indonesia, 2020–2060

Tue, 10 Feb 2026 00:00:00 +0000

The DREAM approach to demand-side emissions reductions in Indonesia, 2020–2060

Representing Soil Microbial Dynamics and Organo‐Mineral Interactions in the E3SM Land Model (ELM‐ReSOM)

Thu, 22 Jan 2026 00:00:00 +0000

Abstract Explicit representation of soil microbial processes and interactions with biotic and abiotic processes in Earth System Models (ESMs) remains limited, despite their importance in biogeochemical cycles. To address this gap, which hinders prediction of global biogeochemial cycling and responses to atmospheric conditions, we integrated a microbe‐ and mineral‐surface‐explicit model, the Reaction‐network‐based model of soil organic matter and Microbes (ReSOM), into the Energy Exascale ESM (E3SM) land model (ELM). Here, we describe ELM‐ReSOM and show a case study at a conifer forest in California. ELM‐ReSOM accurately simulated surface CO 2 fluxes and SOM stocks, demonstrating improved representations of microbial and mineral interactions compared to the default ELM. We examined ELM‐ReSOM sensitivity to microbial traits, enzyme properties, and organo‐mineral interactions. Microbial traits such as the maximum mortality rate, transporter‐density scaling factor, and maximum monomer...

Accounting for herbaceous communities in process‐based models will advance our understanding of “grassy” ecosystems

Mon, 5 Jan 2026 00:00:00 +0000

Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process-based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous...

Atmospheric Feedbacks Reverse the Sensitivity of Modeled Photosynthesis to Stomatal Function

Wed, 17 Dec 2025 00:00:00 +0000

Abstract Stomata mediate fluxes of carbon and water between terrestrial plants and the atmosphere. These fluxes are governed by stomatal function and can be modulated in many Earth system models by an empirical parameter within the calculation of stomatal conductance, the stomatal slope . Intuitively, represents the marginal water cost of carbon, relating it to the emergent plant property of water use efficiency. Observations show that can range widely across and within plant types in varying environments, and this distribution of is not captured within Earth system models which represent each plant type with a single value. Here we examine how influences photosynthesis using coupled Earth system model simulations by perturbing to observed and percentiles for each plant type. We find that high reduces photosynthesis nearly everywhere, while low has regionally dependent responses. Under fixed atmospheric conditions, low increases photosynthesis in the Amazon and central North America...

Modeling the mechanisms of coastal vegetation dynamics and ecosystem responses to changing water levels

Wed, 17 Dec 2025 00:00:00 +0000

Abstract. Coastal forests are increasingly experiencing mortality due to inundation by fresh- and seawater, leading to their replacement by marshes. These shifts alter vegetation composition, biogeochemical cycling, carbon storage, and hydrology. Using a hydraulically enabled ecosystem demography model (FATES-Hydro), we conducted numerical experiments to investigate the mechanisms behind inundation-driven forest loss and the ecosystem-scale consequences of forest-to-marsh transitions. We compared mortality processes and their effects across broadleaf and conifer trees at two coastal sites – Lake Erie (freshwater) and Chesapeake Bay (saline). Our simulations show that hydraulic failure, driven by root loss under prolonged flooding, is the primary mortality mechanism across both tree types and sites. Forest replacement by marsh reduced ecosystem-scale leaf area index (LAI), gross primary production (GPP), transpiration, and deep soil water uptake in conifer forests, while broadleaf...

On a simplified solution of climate-carbon dynamics in idealized flat10MIP simulations

Wed, 17 Dec 2025 00:00:00 +0000

Abstract. Idealized experiments with coupled climate-carbon Earth system models (ESMs) provide a basis for understanding the response of the carbon cycle to external forcing and for quantifying climate-carbon feedbacks. Here, we analyze globally-averaged results from idealized esm-flat10 experiments and show that most models exhibit a quasi-linear relationship between cumulative carbon uptake on land and in the ocean during a period of constant fossil fuel emissions of 10 Pg C yr−1. We hypothesize that this relationship does not depend on emission pathways. Further, as a simplification, we quantify the relationship between cumulative ocean carbon uptake and changes in ocean heat content using a linear approximation. In this way, changes in oceanic heat content and atmospheric CO2 concentration become interdependent variables, reducing the coupled temperature-CO2 system to just one differential equation. The equation can be solved analytically or numerically for the atmospheric...

Pervasive over-crediting from cookstove offset methodologies

Thu, 4 Dec 2025 00:00:00 +0000

Cookstove carbon offset projects can progress multiple Sustainable Development Goals (SDGs), including climate, energy, health, gender, poverty and deforestation. However, project emission reductions must be accurately or conservatively estimated to avoid undermining climate action and long-term SDG financing. Here we conduct a comprehensive, quantitative, quality assessment of offsets by comparing five cookstove methodologies with published literature and our own analysis. We find misalignment, in order of importance, with fraction of non-renewable biomass, firewood–charcoal conversion, stove adoption, stove usage, fuel consumption, stacking (using multiple stoves), rebound and emission factors. Additionality, leakage, permanence and overlapping claims require more research. We estimate that our project sample is over-credited 9.2 times. Gold Standard’s metered methodology, which directly monitors fuel use, is most aligned with our estimates (1.5 times over-credited) and has...

Demography, dynamics and data: building confidence for simulating changes in the world's forests

Thu, 4 Dec 2025 00:00:00 +0000

Vegetation demographic models (VDMs) are advanced tools for simulating forest responses to climate and land-use changes, and are essential for projecting carbon cycling and large-scale forest management strategies. Despite their increasing incorporation into Earth System Models, VDMs differ in their demographic assumptions, with no prior quantitative comparison of their performance. We benchmarked nine VDMs against observational data from boreal, temperate and tropical sites, assessing their accuracy in predicting tree growth, carbon turnover, biomass stocks and size distributions. Models were simulated under consistent climate conditions with postdisturbance recovery monitored for at least 420 yr. Postdisturbance carbon recovery trajectories showed significant variability while remaining within observational ranges. Initial regrowth rates varied substantially (0.03-0.60, 0.18-0.70 and 0.35-1.10 kgCm^-2 yr^-1 for boreal, temperate and tropical sites, respectively),...

A provincial cost analysis of electric vehicle operation in China

Fri, 21 Nov 2025 00:00:00 +0000

The transition to all-electric driving is essential for achieving carbon reduction goals in China's transportation sector, which is significantly influenced by economic costs and emission reduction benefits. In this study, a comprehensive provincial assessment method is developed to quantify the levelized cost of operation (LCOO) for four electric vehicle (EV) types in China, revealing a complex interaction between geographical, economic, and technological factors. We find that the LCOO of EVs ranges from $1.36/100 km for private light-duty vehicles in the northwest region to $26.09/100 km for heavy-duty trucks in the northeast region. The results emphasize the significant disparities in the LCOO of EVs across vehicle types and regions while underscoring the relative importance of various cost components. With the widespread electrification of transportation, there is an urgent requirement for a comprehensive model to disaggregate and estimate the LCOO considering multiple factors,...

The Role of Wind‐Moisture Characteristics in Shaping Atmospheric River Flood Hazards

Tue, 18 Nov 2025 00:00:00 +0000

Abstract Atmospheric rivers (ARs) are key drivers of extreme precipitation in the Western U.S. Using regionally downscaled thermodynamic global warming (TGW) simulations, we examine how ARs with varying wind and moisture characteristics respond to warming. We classified 812 historical AR events into Gusty‐Wet, Gusty‐Dry, Calm‐Wet, and Calm‐Dry groups to evaluate differences in precipitation behavior. ARs with stronger winds and higher moisture content exhibit higher precipitation efficiency (PE) and greater integrated water vapor (IWV). Regionally, Calm ARs show higher IWV accumulation due to slower inland transport and reduced PE. Projections indicate increases in storm‐total (sub‐Clausius‐Clapeyron (CC) scaling) and maximum 3‐hourly precipitation (super‐CC scaling) across all groups, with the most pronounced changes in Gusty‐Wet and Calm‐Wet ARs. Spatial differences in surface runoff, PE, and inland reach highlight the importance of AR subtype in shaping future flood hazards....

AmeriFlux BADM: Implementing lessons from 12 years of long-tail data management into next generation earth science systems

Fri, 31 Oct 2025 00:00:00 +0000

AmeriFlux is a community of scientists measuring ecosystem carbon, water, and energy fluxes across the Americas with eddy covariance techniques. The network’s data team collects flux data for quality assessment and provides standardized data products to the earth science research community. Critical for scientists’ use of the flux data are the supporting Biological, Ancillary, Disturbance and Metadata (BADM) that provide context, such as measurement heights, instrument operations, and disturbance events. Managing and collating BADM into standardized data products are challenging due to their inherent long-tail data characteristics, i.e., they are diverse, free-formed, and infrequently measured. Over the past 12 years, we have worked with the community to standardize and then manage BADM using a SQL database with strong data quality criteria. BADM’s inherent nature demands rigorous quality checks of submitted data. Some of these checks provide feedback to data providers for correction,...

Investigating the Global Biogeophysical Impact of Area and Mass Based Wood Harvest in a Vegetation Demography Model

Tue, 21 Oct 2025 00:00:00 +0000

Abstract Wood harvesting alters land surface properties and energy redistribution, but there is a lack of studies estimating these changes on a global scale. We coupled a vegetation demographic model, the Functionally Assembled Terrestrial Ecosystem Simulator, with the E3SM land model to perform offline model simulation to investigate the land biogeophysical responses, including canopy coverage, leaf area index, albedo, surface roughness length, and energy fluxes, to historical wood harvest on the global scale. In this study, we found 50% less harvested carbon (C) when choosing the area‐based harvest rate as driving data that has not been spatially harmonized, compared to reharmonized mass‐based harvesting. By considering the uncertainty from reconstruction of historical wood harvest time series and the choice of wood harvest approach in the model, continuous wood harvest (1850–2015) results in 5%–10% of canopy coverage loss, contributing 0.5%–1% increase of albedo over disturbed...

flat10MIP: an emissions-driven experiment to diagnose the climate response to positive, zero and negative CO2 emissions

Wed, 8 Oct 2025 00:00:00 +0000

Abstract. The proportionality between global mean temperature and cumulative emissions of CO2 predicted in Earth system models (ESMs) is the foundation of carbon budgeting frameworks. Deviations from this behavior could impact estimates of required net-zero timings and negative emissions requirements to meet the Paris Agreement climate targets. However, existing ESM diagnostic experiments do not allow for direct estimation of these deviations as a function of defined emissions pathways. Here, we perform a set of climate model diagnostic experiments for the assessment of transient climate response to cumulative CO2 emissions (TCRE), the Zero Emissions Commitment (ZEC), and climate reversibility metrics in an emissions-driven framework. The emissions-driven experiments provide consistent independent variables simplifying simulation, analysis and interpretation, with emissions rates more comparable to recent levels than existing protocols using model-specific compatible emissions...

Exploring offshore wind’s potential to enhance energy security in nations with limited land and fuel resources

Tue, 23 Sep 2025 00:00:00 +0000

Offshore wind (OSW) power is critical to addressing energy security issues in nations with limited land and fuel resources. This study aims to assess the quality of OSW resources with high temporal and spatial resolution and to elucidate the economically feasible deployment of OSW using advanced power system models with Japan as a case study. First, comprehensive evaluations of OSW resources were performed by integrating a geographic information system (GIS)-based resource assessment with simulated data for hourly resource availability and renewable power plant operation. Then, using the ‘SWITCH-Japan’ model developed in our previous study, four key policy scenarios (‘pathways’) were analyzed. Each scenario incorporated three technology cost sensitivities and was assessed on multiple criteria including affordability, energy security, and land-use change. Finally, the potential for hydrogen production in other sectors was explored. We found that the Least-Cost scenario, which accelerates...

A Review of Abrupt Permafrost Thaw: Definitions, Usage, and a Proposed Conceptual Framework

Tue, 9 Sep 2025 00:00:00 +0000

Purpose of ReviewWe review how ‘abrupt thaw’ has been used in published studies, compare these definitions to abrupt processes in other Earth science disciplines, and provide a definitive framework for how abrupt thaw should be used in the context of permafrost science.Recent FindingsWe address several aspects of permafrost systems necessary for abrupt thaw to occur and propose a framework for classifying permafrost processes as abrupt thaw in the future. Based on a literature review and our collective expertise, we propose that abrupt thaw refers to thaw processes that lead to a substantial persistent environmental change within a few decades. Abrupt thaw typically occurs in ice-rich permafrost but may be initiated in ice-poor permafrost by external factors such as hydrologic change (i.e., increased streamflow, soil moisture fluctuations, altered groundwater recharge) or wildfire.SummaryPermafrost thaw alters greenhouse gas emissions, soil and vegetation properties, and hydrologic...

One‐at‐a‐Time Parameter Perturbation Ensemble of the Community Land Model, Version 5.1

Mon, 8 Sep 2025 00:00:00 +0000

Abstract Comprehensive land models are subject to significant parametric uncertainty, which can be hard to quantify due to the large number of parameters and high model computational costs. We constructed a large parameter perturbation ensemble (PPE) for the Community Land Model version 5.1 with biogeochemistry configuration (CLM5.1‐BGC). We performed more than 2,000 simulations perturbing 211 parameters across six forcing scenarios. This provides an expansive data set, which can be used to identify the most influential parameters on a wide range of output variables globally, by biome, or by plant functional type. We found that parameter effects can exceed scenario effects and that a small number of parameters explains a large fraction of variance across our ensemble. The most important parameters can differ regionally and also based on the forcing scenario. The software infrastructure developed for this experiment has greatly reduced the human and computer time needed for CLM...

Real-Time Partitioning of Diurnal Stem CO2 Efflux into Local Stem Respiration and Xylem Transport Processes

Tue, 26 Aug 2025 00:00:00 +0000

The apparent respiratory quotient (ARQ) of tree stems, defined as the ratio of net stem CO2 efflux (ES_CO2) to net stem O2 influx (ES_O2), offers insights into the balance between local respiratory CO2 production and CO2 transported via the xylem. Traditional static chamber methods for measuring ARQ can introduce artifacts and obscure natural diurnal variations. Here, we employed an open flow-through stem chamber with ambient air coupled with cavity ring-down spectrometry, which uses the molecular properties of CO2 and O2 molecules to continuously measure ES_CO2, ES_O2, and ARQ, at the base of a California cherry tree (Prunus ilicifolia) during the 2024 growing season. Measurements across three stem chambers over 3–11-day periods revealed strong correlations between ES_CO2 and ES_O2 and mean ARQ values ranging from 1.3 to 2.9, far exceeding previous reports. Two distinct diurnal ARQ patterns were observed: daytime suppression with nighttime recovery, and a morning peak followed...

India's residential space cooling transition: Decarbonization ambitions since the turn of millennium

Tue, 19 Aug 2025 00:00:00 +0000

As an emerging emitter poised for significant growth in space cooling demand, India requires comprehensive insights into historical emission trends and decarbonization performance to shape future low-carbon cooling strategies. By integrating a bottom-up demand resource energy analysis model and a top-down decomposition method, this study is the first to conduct a state-level analysis of carbon emission trends and the corresponding decarbonization efforts for residential space cooling in urban and rural India from 2000 to 2022. The results indicate that (1) the carbon intensity of residential space cooling in India increased by 292.4 % from 2000 to 2022, reaching 513.8 kg of carbon dioxide per household. The net state domestic product per capita, representing income, emerged as the primary positive contributor. (2) The increase in carbon emissions from space cooling can be primarily attributed to the use of fans. While fan-based space cooling has nearly saturated Indian...

Evaluating How Climate Adaptation Measures Affect the Interconnected Water‐Energy Resource Systems of the Western United States

Thu, 14 Aug 2025 00:00:00 +0000

Abstract The Western US faces increasing water stress from the impacts of climate change, making it difficult to meet water demands for the region's cities, agriculture, and hydropower generators. Existing literature suggests that climate adaptation measures such as water conservation, cropland retirement, wastewater recycling, and managed aquifer recharge can alleviate some of these challenges. Few analyses, however, compare the relative efficacy and system‐wide effects of these adaptations under different climate projections across the entire Western United States. Here we use a Western US‐wide water systems model to evaluate, by sector and sub‐region, how the widespread implementation of these adaptive measures impacts water demands, water deliveries, and electricity use related to the water system for three different climate projections. We find that wastewater recycling has greater potential to lower unmet indoor water demands than urban indoor water conservation measures....

Assessing Simulations of Forest Hurricane Disturbance and Recovery in Puerto Rico by ELM‐FATES Using Field Measurements

Tue, 22 Jul 2025 00:00:00 +0000

Abstract In the past three decades, Puerto Rico (PR) experienced five hurricanes that met or exceeded category three, and they caused severe forest structural damage and elevated tree mortality. To improve our mechanistic understanding of hurricane impacts on tropical forests and assess hurricane‐affected forest dynamics in Earth system models, we use in situ forest measurements at the Bisley Experimental Watersheds in Northeast PR to evaluate the Functionally Assembled Terrestrial Ecosystem Simulator coupled with the Energy Exascale Earth System Model Land Model (ELM‐FATES). The observations show that before Hurricane Hugo, 77.3% of the aboveground biomass (AGB) is from the shade‐tolerant plant function type (PFT). The Hugo‐induced mortality rates are over ∼50%, and they induce a ∼39% AGB reduction, which recovers to a level like the pre‐Hugo condition in 2014, following a second, lower intensity hurricane, Georges. We perform numerical experiments that simulate damage from Hugo...

Analysis and Assessment of the Existing Landscape and Opportunities for Building Energy Efficiency in Selected Countries in Asia

Wed, 16 Jul 2025 00:00:00 +0000

Executive Summary This report examines ASEAN’s building sector and the many opportunities that it offers for increased energy efficiency. The ten countries that make up ASEAN are diverse: the region contains some of the largest countries in the world by population, small highly developed city states, and a number of fast-growing economies with rapidly emerging middle classes. The report focuses mostly on the largest five of these markets: Indonesia, Malaysia, the Philippines, Thailand and Vietnam. While their energy circumstances vary, the countries of ASEAN have one thing in common: increasing pressures on their energy systems, from ongoing economic and industrial growth, infrastructure and capacity constraints, a reliance on energy imports, and rising incomes leading to increasing demand for energy using appliances. Taken together, and with ASEAN countries expected to add building floor space of as much as 22 billion m2 by 2060, optimizing energy use in buildings is therefore...

Fine‐root dynamics in deeper soils: a critical but overlooked component of ecosystem responses to climate warming

Tue, 1 Jul 2025 00:00:00 +0000

Climate warming is predicted to strongly affect the functioning of terrestrial ecosystems. The plant root system is a critical component of these ecosystems, with fine roots, in particular, playing a key role in plant water and nutrient uptake and transport. In addition, root litter and exudation represent the dominant plant carbon inputs into soil. Consequently, understanding fine-root responses to warming is essential for predicting how the growth, resilience, and carbon storage of terrestrial ecosystems will respond to future climate change. Despite the growing literature on fine-root responses to warming, most studies have focused on topsoil (0-30 cm). However, a significant portion of the fine-root mass occurs below this depth. For instance, c. 40% of fine-root mass is found below 30 cm in temperate and tropical ecosystems. Due to the importance of fine roots for plants and belowground carbon cycling, focusing solely on surface soils overlooks the critical need for insights...

Calcium is associated with specific soil organic carbon decomposition products

Wed, 25 Jun 2025 00:00:00 +0000

Abstract. Calcium (Ca) may contribute to the preservation of soil organic carbon (SOC) in more ecosystems than previously thought. Here, we provide evidence that Ca is co-located with SOC compounds that are enriched in aromatic and phenolic groups, across different acidic soil types and locations with different ecosystem properties, differing in terms of climate, parent material, soil type, and vegetation. In turn, this co-localised fraction of Ca–SOC is removed through cation exchange, and the association is then only re-established during decomposition in the presence of Ca (Ca addition incubation). Thus, this highlights a causative link between decomposition and the co-location of Ca with a characteristic fraction of SOC. Decomposition increases the relative proportion of negatively charged functional groups, which can increase the propensity for the association between SOC and Ca; in turn, this association can inhibit dissolved organic carbon export or further decomposition....

Balancing renewable energy and river resources by moving from individual assessments of hydropower projects to energy system planning

Wed, 4 Jun 2025 00:00:00 +0000

As governments and non-state actors strive to minimize global warming, a primary strategy is the decarbonization of power systems which will require a massive increase in renewable electricity generation. Leading energy agencies forecast a doubling of global hydropower capacity as part of that necessary expansion of renewables. While hydropower provides generally low-carbon generation and can integrate variable renewables, such as wind and solar, into electrical grids, hydropower dams are one of the primary reasons that only one-third of the world’s major rivers remain free-flowing. This loss of free-flowing rivers has contributed to dramatic declines of migratory fish and sediment delivery to agriculturally productive deltas. Further, the reservoirs behind dams have displaced tens of millions of people. Thus, hydropower challenges the world’s efforts to meet climate targets while simultaneously achieving other Sustainable Development Goals. In this paper, we explore strategies...

“I am the one responsible”: The gendered reality of clean cooking fuel affordability in Shirati, Tanzania

Wed, 4 Jun 2025 00:00:00 +0000

Abstract: Affordability remains one of the most significant barriers to the exclusive use of clean cookstoves and fuels, a top global health, energy, and development priority. The measurement and discussion of clean fuel affordability is almost always based on the unitary, or single decision-maker, household as the unit of analysis, although the more realistic household disaggregated into its individual decision-makers is a well-established literature. The limited work on intra-household dynamics in clean cooking cannot reveal who is buying the stove or fuel and at what true cost. Following an experiment testing the effect of microsavings to increase clean fuel consumption in Shirati, a rural town in Mara region, Tanzania, we conducted 90 interviews and numerous focus groups/budget games with a stratified random sample of mostly female main cooks. Drawing on over two years of fieldwork, we investigate the range of household needs, the role of gender in household...

Degradation and deforestation increase the sensitivity of the Amazon Forest to climate extremes

Tue, 6 May 2025 00:00:00 +0000

About 40% of the Brazilian Amazon has been deforested or suffered changes in forest structure through degradation (selective logging, fires, and fragmentation). The impact of forest degradation on the forest’s sensitivity to climate extremes has not been fully explored because of a lack of data and the complex interplay of forest structure and climate drivers. Here, we combined forest structure data from 545 airborne lidar transects (375 ha each) across the Brazilian Amazon with the Ecosystem Demography Model (ED2). We explore the forest’s functional response to near-present (1981–2019) climate extremes under observed forest structure from lidar (Control) and two forest structure change scenarios: (1) forest recovery by excluding all future deforestation and degradation (Recovery) and (2) expansion of selective logging and deforestation (Degradation). Using the Control simulation, we found a close and positive association between local forest aboveground biomass and the predicted...

Cities Are Concentrators of Complex, MultiSectoral Interactions Within the Human‐Earth System

Tue, 6 May 2025 00:00:00 +0000

Cities are concentrators of complex, multi-sectoral interactions. As keystones in the interconnected human-Earth system, cities have an outsized impact on the Earth system. We describe a multi-lens framework for organizing our understanding of the complexity of urban systems and scientific research on urban systems, which may be useful for natural system scientists exploring the ways their work can be made more actionable. We then describe four critical dimensions along which improvements are needed to advance the urban research that addresses urgent climate challenges: (a) solutions-oriented research, (b) equity-centered assessments which rely on fine-scale human and ecological data, (c) co-production of knowledge, and (d) better integration of human and natural systems occurring through theory, observation, and modeling.

Grid connections and inequitable access to electricity in African cities

Fri, 18 Apr 2025 00:00:00 +0000

Grid connections and inequitable access to electricity in African cities

Coupling Remote Sensing With a Process Model for the Simulation of Rangeland Carbon Dynamics

Tue, 15 Apr 2025 00:00:00 +0000

Abstract Rangelands provide significant environmental benefits through many ecosystem services, which may include soil organic carbon (SOC) sequestration. However, quantifying SOC stocks and monitoring carbon (C) fluxes in rangelands are challenging due to the considerable spatial and temporal variability tied to rangeland C dynamics as well as limited data availability. We developed the Rangeland Carbon Tracking and Management (RCTM) system to track long‐term changes in SOC and ecosystem C fluxes by leveraging remote sensing inputs and environmental variable data sets with algorithms representing terrestrial C‐cycle processes. Bayesian calibration was conducted using quality‐controlled C flux data sets obtained from 61 Ameriflux and NEON flux tower sites from Western and Midwestern US rangelands to parameterize the model according to dominant vegetation classes (perennial and/or annual grass, grass‐shrub mixture, and grass‐tree mixture). The resulting RCTM system produced higher...

The interaction between population age structure and policy interventions on the spread of COVID-19

Wed, 9 Apr 2025 00:00:00 +0000

COVID-19 has triggered an unprecedented public health crisis and a global economic shock. As countries and cities have transitioned away from strict pandemic restrictions, the most effective reopening strategies may vary significantly based on their demographic characteristics and social contact patterns. In this study, we employed an extended age-specific compartment model that incorporates population mobility to investigate the interaction between population age structure and various containment interventions in New York, Los Angeles, Daegu, and Nairobi - four cities with distinct age distributions that served as local epicenters of the epidemic from January 2020 to March 2021. Our results demonstrated that individual social distancing or quarantine strategies alone cannot effectively curb the spread of infection over a one-year period. However, a combined strategy, including school closure, 50 % working from home, 50 % reduction in other mobility, 10 % quarantine rate, and...

GREENER IS CHEAPER: AN EXAMPLE FROM OFFSHORE WIND FARMS

Wed, 9 Apr 2025 00:00:00 +0000

Offshore wind farms (OWF) are now in operation and increasingly under construction as scalable, sustainable energy sources. In fact OWFs are currently the cheapest form of new energy projects in Europe. The levelized cost of energy (LCOE) for OWF has fallen drastically due to decades of innovation facilitated by both taxpayer and private sector funding. This emerging industry is experiencing massive worldwide growth with the potential to accelerate the decarbonization of regional and the global economy as well as bring a reliable source of green hydrogen into commercial use, all with minimal disruption to ecosystems and impacts on biodiversity. This paper provides a historical perspective of wind energy harnessing and shows that wind turbines are the oldest, largest and one of the smartest machines. We also highlight the potential of offshore wind energy to provide new solutions to (a) meet clean energy demand for a growing world population, (b) improve energy security of nations...

2 Kosovo’s conflict coal: regional stability through coordinated investments in sustainable energy infrastructure

Wed, 9 Apr 2025 00:00:00 +0000

2 Kosovo’s conflict coal: regional stability through coordinated investments in sustainable energy infrastructure

The Role of Leaf Area Changes Within Plant CO2 Physiological Impacts on the Global Hydrological Cycle

Tue, 18 Mar 2025 00:00:00 +0000

Abstract Rising atmospheric CO 2 concentrations enhance greenhouse warming and drive changes to plant physiology, leading to innumerable climate impacts. This study explores the impacts of plant responses on hydrological cycling at 2x preindustrial CO 2 concentrations by analyzing simulations that isolate plant physiological effects using the Community Earth System Model versions 1 and 2. We find that leaf area growth increases canopy evaporation, which offsets transpiration declines, and dampens changes in global mean evapotranspiration, precipitation, and runoff in a CESM2 experiment with dynamic leaf area. These leaf area impacts are also evident in the differences between CESM1 and CESM2, with CESM2 better capturing observed leaf area magnitudes but potentially overestimating leaf area‐CO 2 sensitivity, highlighting the importance of plant CO 2 physiology on hydrological cycle changes and the need to improve its representation in climate models. Plain Language Summary Atmospheric...

Vertical canopy gradients of respiration drive plant carbon budgets and leaf area index

Wed, 12 Mar 2025 00:00:00 +0000

Despite its importance for determining global carbon fluxes, leaf respiration remains poorly constrained in land surface models (LSMs). We tested the sensitivity of the Energy Exascale Earth System Model Land Model - Functionally Assembled Terrestrial Ecosystem Simulator (ELM-FATES) to variation in the canopy gradients of leaf maintenance respiration (R_dark). We ran global and point simulations varying the canopy gradient of R_dark to explore the impacts on forest structure, composition, and carbon cycling. In global simulations, steeper canopy gradients of R_dark lead to increased understory survival and leaf biomass. Leaf area index (LAI) increased up to 77% in tropical regions compared with the default parameterization, improving alignment with remotely sensed benchmarks. Global vegetation carbon varied from 308 Pg C to 449 Pg C across the ensemble. In tropical forest simulations, steeper gradients of R_dark had a large impact on successional...

California annual grass phenology and allometry influence ecosystem dynamics and fire regime in a vegetation demography model

Mon, 3 Mar 2025 00:00:00 +0000

Grass-dominated ecosystems cover wide areas of the land surface yet have received far less attention from the Earth System Model (ESM) community. This limits model projections of ecosystem dynamics in response to global change and coupled vegetation-climate dynamics. We used the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a dynamic vegetation demography model, to determine ecosystem sensitivity to alternate, observed grass allometries and biophysical traits, and evaluated model performance in capturing California C₃ annual grasslands structure and fire regimes. Grass allometry, leaf physiology, plant phenology, and plant mortality all drove the seasonal variation in matter and energy exchange and fire dynamics in California annual grasslands. Allometry influenced grassland structure and function mainly through canopy architecture-mediated space and light competition instead of through carbon partitioning strategy. Regional variation in grassland...

Energy efficiency and carbon savings via a body grid

Thu, 27 Feb 2025 00:00:00 +0000

The climate crisis necessitates decarbonization solutions that transform energy systems across all scales. While attention today focuses on utility-scale power systems, mini-or metro-scale grids, and at end-use device efficiency, the individual user scale remains underexplored. Just as with energy efficiency innovations tailored to micro-environments, body-scale energy savings offer new opportunities alongside technological and behavioral challenges. Here we propose a technique and a suite of potential innovations focused on the “body grid” in which devices, circuits, information network, human body and the environment interact within a universal framework to achieve energy savings, new functionality, and improved comfort. We present and test a prototype body grid supporting inter-device synergy and cooperation with external energy systems indoors and outdoors. This system yields substantial energy and economic savings, enhances personal control and comfort, and enables potential...

Agricultural fertilization significantly enhances amplitude of land-atmosphere CO2 exchange

Wed, 26 Feb 2025 00:00:00 +0000

Observations show an increase in the seasonal cycle amplitude of CO2 in northern latitudes over the past half century. Although multiple drivers contribute, observations and inversion models cannot quantitatively account for the factors contributing to the increased CO2 amplitude and older versions of Earth System Models (ESMs) do not simulate it. Here we show that several current generation ESMs are closer to the observed CO2 amplitude and highlight that in the Community Earth System Model (CESM) agricultural nitrogen (N) fertilization increases CO2 amplitude by 1-3 ppm throughout the Northern Hemisphere and up to 9 ppm in agricultural hotspots. While agricultural N fertilization is the largest contributor to the enhanced amplitude (45%) in Northern Hemisphere land-atmosphere carbon fluxes in CESM, higher CO2 concentrations and warmer temperatures also contribute, though to a lesser extent (40% and 18% respectively). Our results emphasize the fundamental role of agricultural...

Gender equality and quality of life must be central to the design and delivery of sanitation

Wed, 26 Feb 2025 00:00:00 +0000

Gender equality and quality of life must be central to the design and delivery of sanitation