Papers

Construction materials generate nearly one-third of global carbon emissions, yet conventional accounting captures only a fraction of this impact. Using EXIOBASE data spanning 25 years, we tracked emissions across construction supply chains for cement, steel, metals, and plastics. While global construction demand nearly tripled, regional patterns diverged significantly. The EU reduced emissions despite increased demand through renewable energy adoption and emissions trading, while China’s construction boom—driving most global growth—significantly increased domestic emissions. Manufacturing contributes most to embodied emissions compared to resource extraction and waste treatment. Increased reliance on offshore production undermines domestic emission control strategies, highlighting the need for expanded carbon border adjustment mechanisms. Without policies addressing full supply chain emissions, even aggressive climate initiatives will be compromised by carbon leakage, creating an emissions trajectory incompatible with global climate targets.

Deterministic energy transition planning risks uninformed decisions. Yet, the challenge of high-dimensional uncertainty–encompassing various technological, economic, social, and climatic factors–often leads to a deterministic treatment or simplification of uncertainties in planning. Here, we propose a computationally efficient framework that leverages surrogate-based sensitivity analysis to identify the key uncertainty sources driving the cost of different energy transition scenarios. We applied the proposed approach to Puerto Rico as a hurricane-prone power system that lacks efficient management. We find that changes in the frequency of hurricanes and organizational inefficiency are the two primary sources of uncertainty determining the system’s total expected cost. When examining operational costs, different transition scenarios demonstrate unique key uncertainty sources. For example, the price of biofuel would mainly drive the operational cost when transitioning to a fully renewable power system. These findings can help planners by allowing them to focus on a narrower set of uncertainties in planning.

In The Type V City, Jeana Ripple examines the social and spatial history of building codes and material patterns in five cities—New York, Tampa, Chicago, Philadelphia, and Seattle—to reframe the stories of America’s building priorities, methods, negotiations, and assumptions. By examining the development of building materials and codes alongside the environmental, social, economic, and political context of each city’s development, Ripple reveals previously overlooked connections between the power structures underpinning regulatory evolution and the impacts that lay just beyond the frame of city builders’ priorities. Handsomely illustrated and informed by both archival research and insights enabled by contemporary data analysis, The Type V City critiques the homogenous construction practices underlying US urbanization and raises pointed questions for future generations of data-driven city planners and architects.

Seagrass habitats support biodiversity, improve water quality, protect coastlines, and sequester carbon, among other essential ecosystem functions, yet they are declining worldwide due to human activity. Seagrass restoration and conservation can act as nature-based solutions for climate change, garnering growing interest from a diversity of stakeholders globally. Despite this interest, no seagrass projects have yet received carbon credits under international voluntary carbon standards. There is a clear need to better understand potential carbon mitigation outcomes of seagrass conservation and restoration practices. Here, we developed a mechanistic model based on a temperate meadow of Zostera marina to estimate carbon benefits (including net carbon dioxide removals, reductions, and methane and nitrous oxide fluxes) over 10 years as a result of four theoretical seagrass management scenarios, selected for their prevalence and potential—(1) restoration via seeding, (2) restoration via transplanting, (3) conserving a meadow and associated sediment from loss (e.g., from dredging), and (4) infilling an area with sediment prior to transplanting. We found significant differences and high variability in carbon benefits between these management scenarios. Restoration via transplant led to higher carbon gains than restoration via seeding, driven by more rapid areal bed expansion in transplanted meadows. However, the infill (adding 1 m of sediment) and conservation (preventing loss of 1 m of sediment) scenarios had total carbon benefits roughly 13–33 times (respectively) higher than the seeding and transplanting scenarios in which no sediment was mobilized. Within the model presented here, the minimum estimated revenue shows a 6 Ha seeding project generating as little as $1189 over 10 years (39.6 ± 6.2 T CO2eq), while a 100 Ha conservation project could generate a maximum of $1.53 million over this same time period (21,910 ± 2196 T CO2eq), excluding costs for project implementation and MRV (monitoring, reporting and verification). Voluntary carbon credit revenue variability (ranging from $198 to $15,337 per Ha) is driven by project size, project approach, and carbon price, among other factors. This work highlights the need for careful, context-specific consideration for if and how carbon finance might support seagrass recovery goals. Seascape-level approaches that pair strategic sediment management and avoided emissions with habitat restoration may lead to the highest climate mitigation benefits, while simultaneously supporting biodiversity and other ecosystem functions.

There is strong interest in sustainable aviation fuels (SAF) to decarbonize aviation; however, local decision-makers will need to consider what additional incentives could stimulate SAF commercialization within their own jurisdictions. This study analyzed SAF production in Virginia, evaluating two biomass-to-energy platforms (gasification Fischer Tropsch [GFT] and pyrolysis) and two regionally abundant feedstocks (woody wastes and municipal solid wastes). A suite of open-access modeling tools were applied to possible SAF supply chains encompassing feedstock collection and transportation, conversion, and fuel upgrading and transport. Key modeling outputs were minimum product selling price (MPSP) ($/gallon) and life-cycle global warming potential (GWP) (g CO2eq/MJ). Results suggest that early SAF production via GFT will require local incentives of approximately $3.61 per gallon compared to $0.75 per gallon for pilot-scale pyrolysis. Location of production facility (by county) influences economic and environmental metrics but is not nearly as important as facility size (tonnes/year). Different formats of financial incentives (i.e., tax credits, loan forgiveness, etc.) offer markedly different reductions in SAF MPSP. Finally, under current federal incentives in the US, it is still more economically efficient to use pyrolysis (with higher GWP) than GFT (with lower GWP). Therefore, regional stakeholders will need to navigate the tradeoff between economic and environmental performances of these platforms. Though Virginia was used as a case study, the methodology is replicable for other jurisdictions, insofar it can be adapted for use in other locations without decision-makers having to completely build their own TEA models.

To achieve net zero carbon emissions by mid-century, the United States may need to rely on carbon dioxide removal (CDR) to offset emissions from difficult-to-decarbonize sectors and/or shortfalls in near-term mitigation efforts. CDR can be delivered using many approaches with different requirements for land, water, geologic carbon storage capacity, energy, and other resources. The availability of these resources varies by region in the U.S. suggesting that CDR deployment will be uneven across the country. Using the global change analysis model for the United States (GCAM-USA), we modeled six classes of CDR and explored their potential using four scenarios: a scenario where all the CDR pathways are available (Full Portfolio), a scenario with restricted carbon capture and storage (Low CCS), a scenario where the availability of bio-based CDR options is limited (Low Bio), and a scenario with constraints on enhanced rock weathering (ERW) capabilities (Low ERW). We find that by employing a diverse set of CDR approaches, the U.S. could remove between 1 and 1.9 GtCO2/yr by midcentury. In the Full Portfolio scenario, direct air carbon capture and storage (DACCS) predominates, delivering approximately 50% of CO2 removal, with bioenergy with carbon capture and storage contributing 25%, and ERW delivering 11.5%. Texas and the agricultural Midwest lead in CDR deployment due to their abundant agricultural land and geological storage availability. In the Low CCS scenario, reliance on DACCS decreases, easing pressure on energy systems but increasing pressure on the land. In all cases CDR deployment was found to drive important impacts on energy, land, or materials supply chains (to supply ERW, for example) and these effects were generally more pronounced when fewer CDR technologies were available.

Direct Air Carbon Capture and Storage (DACCS) is an emerging technology with significant potential to mitigate climate change by removing carbon dioxide directly from the atmosphere. While past studies have evaluated environmental impacts and economic feasibility of DACCS using Life Cycle Assessment and Techno-Economic Assessment, there is a significant gap in localized assessments of DACCS suitability to better inform and facilitate its implementation in geographic areas where it will be deployed. In this study, we developed a framework that combines geospatial analysis with Multi-Criteria Decision Analysis (MCDA) to facilitate a detailed, localized suitability analysis for DACCS implementation, considering economic, environmental, and social factors. Additionally, we created a web-based decision support tool to streamline the evaluation process for potential DACCS implementation, enhancing engagement with decision-makers and stakeholders. Focusing on Virginia as our case study, our findings indicate that most counties’ suitability was significantly affected by changes in criteria prioritization, indicating the substantial impact of economic, environmental, and social factors. This variability highlights the importance of the decision support tool in enhancing decision-making by illustrating how differing criteria and stakeholder perspectives impact site assessments. This study underscores the necessity of a comprehensive and inclusive approach, particularly crucial for emerging carbon removal technology projects.

Power systems are transitioning toward renewable sources and electrification, introducing significant uncertainties in generation and demand that optimal power flow (OPF) methods must manage. Traditional deterministic methods struggle with these variabilities. Additionally, addressing uncertainty in OPF calculations incurs computational burdens due to the need for multiple evaluations across various scenarios. This necessitates the use of advanced surrogate models. However, these models require significant data for training, and surrogate-based optimization can yield unreliable results due to inaccuracies in constraint handling. To overcome these issues, this paper proposes a novel surrogate-based hybrid chance-constrained optimal power flow (HCC-OPF) methodology employing enhanced multi-fidelity graph neural networks (EMF-GNN) as power flow solver surrogates. This model integrates low-fidelity and high-fidelity simulations to significantly reduce training cost while maintaining high accuracy. We further enhance the robustness and accuracy of OPF solutions through a hybrid methodology that selectively uses exact power flow solver to correct surrogate inaccuracies near critical thresholds. Extensive testing on multiple IEEE systems under high-dimensional correlated uncertainty of load and generation shows the EMF-GNN model outperforms existing single-fidelity and multi-fidelity models. Furthermore, the proposed HCC-OPF methodology accurately solves OPF problems across various system sizes and conditions, exhibiting scalability and efficiency. Additionally, it effectively manages N-1 security constraints to further exhibit its robustness under operational challenges.

California faces a dire housing crisis. California’s land-use regulatory system remains a key driver of this crisis. State law grants local governments broad power to craft their own regulations on how to review and approve housing development. Though state law may limit a locality’s ability to outright deny some types of housing development, local governments can and do use creative ways to stall approvals or functionally deny housing by making it infeasible to develop. One such strategy is to demand more intensive environmental review of new housing projects under the California Environmental Quality Act (CEQA) than what state law requires. More intensive environmental review can create substantial delay and uncertainty, increasing the costs for the construction of new housing. Although the state has made many efforts to streamline the process of both local land-use regulation and CEQA review, delays and uncertainty remain.
We propose that the state address this ongoing problem by (1) issuing an authoritative map of urban “infill priority areas” (IPAs) where new housing is expected to provide net social and environmental benefits, and (2) limiting the scope of environmental review, within the IPAs, to environmental impacts identified by the city or members of the public within a brief temporal window and demonstrated by the proponent of environmental review to be significant. In effect, the law would presume no impact from new housing within an IPA unless significant impacts are quickly and unambiguously identified. We also propose enforcement mechanisms. New infill housing reduces carbon emissions, exposure to wildfire risk, and threats to habitat. Environmental review should be calibrated accordingly.

Recent drought, wildfires and rising temperatures in the western US highlight the urgency of increasing resiliency in overstocked forests. However, limited valuation information hinders the broader participation of beneficiaries in forest management. We assessed how historical disturbances in California’s Central Sierra Nevada affected live biomass, forest water use and carbon uptake and estimated marginal values of these changes. On average, low-severity wildfire caused greater declines in forest evapotranspiration (ET), gross primary productivity (GPP) and live biomass than did commercial thinning. Low-severity wildfires represent proxies for prescribed burns and both function as biomass removal to alleviate overstocked conditions. Increases in potential runoff over 15 years post-disturbance were valued at $108,000/km2 for commercial thinning versus $234,000/km2 for low-severity wildfire, based on historical water prices. Respective declines in GPP were valued at −$305,000 and −$1,317,000/km2, based on an average social cost of carbon. Considering biomass levels created by commercial thinning and low-severity fire as more-sustainable management baselines for overstocked forests, carbon uptake over 15 years post-disturbance can be viewed as a benefit rather than loss. Realizing this benefit upon management re-entry may require sequestering thinned material. High-severity wildfire and clearcutting resulted in greater declines in ET and thus greater potential water benefits but also substantial declines in GPP and live carbon. These lessons from historical disturbances indicate what benefit ranges from fuels treatments can be expected from more-sustainable management of mixed-conifer forests and the importance of setting an appropriate baseline.

California’s legislature has passed several laws that intervene in local land-use regulation in order to increase desperately needed housing production—particularly affordable housing production. Some of these new laws expand local reporting requirements concerning zoning and planning laws, and the application of those laws apply to proposed housing development. This emphasis on measurement requires the state to develop a housing data strategy to support both enforcement of existing law and effective policymaking in the future. Our Comprehensive Assessment of Land Use Entitlements Study (CALES) predates, but aligns with and supports, this state-led effort to improve local reporting. For the cities that it covers, CALES provides verified and cleaned data indicating how cities apply local and state law. In this symposium contribution, we use the CALES data to illustrate the importance of collecting a range of precise objective data on how cities apply law, and then offer a simple but sufficiently comprehensive measurement of regulation that can help identify when a local land use regime may be operating to exclude affordable housing.

Housing costs in major coastal metropolitan areas nationwide have skyrocketed, impacting people, the economy, and the environment. Landuse regulation, controlled primarily at the local level, plays a major role in determining housing production. In response to this mounting housing crisis, scholars, policymakers, and commentators are debating whether greater state involvement in local land-use decision-making is the best path forward.
We argue here that there are good reasons to believe that continuing on the current path—with local control of land-use regulation as it is— will lead to persistent underproduction of housing. The benefits of housing production are primarily regional, including improved job markets, increased socioeconomic mobility, and reduced greenhouse gas emissions. But the costs associated with producing more housing are often local, felt at the neighborhood level. Local governments whose voters are impacted by the local negative impacts of housing and will usually have less incentive to consider those regional, and national, benefits and approve housing. Recent political science, planning, economics, and legal research shows that smaller local jurisdictions tend to produce less housing, and when political institutions decentralize control over housing to the sublocal (e.g., neighborhood) scale, less housing is approved.
A central theory in academic research in land-use regulation and local government law has been the idea that competition among highly fragmented local governments can produce more efficient outcomes in public services and land-use regulation, even if there may be significant inequities across local jurisdictions in outcomes. Our analysis shows that this theory no longer accurately describes how fragmented local governance affects economic efficiency. Indeed, our analysis makes clear that fragmented local governance is both inequitable and inefficient, at least in the context of land-use regulation. Our analysis also raises questions about local government law scholarship contending that increased local governmental power can effectively address the dysfunctions of metropolitan areas in the United States.
We present a range of policy proposals to address the problems we identify. First, greater state intervention in local land-use regulation is necessary. While a greater state role need not (and probably should not) entirely displace local control, it is essential to ensure that the larger-scale benefits of housing are appropriately considered. Second, we note that the highly fragmented local land-use regulatory system imposes challenges for housing production, in part, because variation among local regulatory practices creates barriers to entry for new housing across jurisdictions. Accordingly, we advocate for a state role to increase the standardization of local land-use regulatory tools as a key step to help advance greater housing production, even where local control is maintained.

California has endured devastating fire seasons over the past few years, with billions of dollars of damages, thousands of homes lost, and dozens dead. A key driver of the state’s fire crisis is the increase in development of housing in the wildland-urban interface, where ecosystems and landscapes are more likely to burn. Wildland-urban interface development can put people and property in harm’s way and can increase the risk of ignitions of fires. Wildland-urban interface development can also make it harder to restore fire to the landscape, a critical step to reducing fire hazards in California. But current law in California appears to do little to deter development in these high fire hazard areas. Direct regulation of land-use is generally undertaken by local governments that may have incentives to allow greater wildland-urban interface development. The California Environmental Quality Act (CEQA), which requires review and mitigation of the environmental impacts of new development projects, may not provide an adequate response to wildland-urban interface development. In particular, a recent California Supreme Court case limited the scope of CEQA review to the impacts caused by a project on the environment, rather than the impacts of the environment on a project––much of the potential harm posed by fire to wildland-urban interface development falls in the latter category. To understand how well CEQA is addressing wildland-urban interface development, we analyzed data on environmental review for housing projects in three large exurban counties and additional cities with substantial wildland-urban interface areas. We found that in San Diego County, significant amounts of development are being approved using streamlined CEQA review processes, and that most of the housing development in the County is occurring in the wildland-urban interface. Our results indicate that CEQA and local land-use regulation may not be adequately addressing wildland-urban interface development in California. However, any policy response must also recognize the dire housing shortage in the state. Balancing the goals of reducing fire risk and increasing housing production suggests that increased housing development in low fire hazard urban infill areas, and a regional-level planning structure to properly plan for fire hazards, may be appropriate policy responses.

California has committed to reducing greenhouse gas emissions (GHG) to address climate change. But in California, the sector that produces the largest share of greenhouse gas emissions is transportation, and reducing those emissions depends on reducing total vehicle miles traveled (VMT). And that, in turn requires rebuilding urban and suburban areas in California to become less car-centered and more oriented around mass-transit and walkable neighborhoods: transit-oriented infill development (TOD). Critiques of the transition from sprawl to TOD raise concerns that TOD is pushing low-income communities out of our urban core and into to exurban areas. A key question is the role of local versus state control over land use in addressing the dual challenges of climate change and the state’s housing crisis. To address this debate, we built a first-of-its-kind data set that examines entitlement, or the local approval process to obtain a building permit, in relationship to present day zoning as well as historical discriminatory land use policy. We find that local government choices about zoning reflect past racial discrimination around land use, directing dense TOD almost entirely into neighborhoods that were subject to those discriminatory practices.

Bioenergy with carbon capture and storage (BECCS) based electricity generation is one possible approach for delivering large-scale carbon dioxide removal from the atmosphere. This study evaluates the environmental impacts of leveraging existing power plants for BECCS. We performed a life cycle meta-analysis of eight carbon capture technologies, including five previously simulated only for coal and natural gas, for both steam cycle and integrated gasification combined cycle (IGCC) power plants. We found that IGCC plants offer the best balance of negative emissions, energy return on investment (EROI) and low water use irrespective of capture technologies. Planned IGCC plants tend to be large whereas biomass-fired power plants are often small and distributed in the landscape because of the distributed nature of the fuel. Steam cycle plants had larger negative emissions, but also lower EROI, and so blending with coal may be necessary to achieve a suitable EROI. Steam cycles were sensitive to capture technology type, and results found membrane and calcium looping capture technologies offer a balance between negative emissions, EROI and water use when fired using coal-biomass blends. These results suggest that steam cycle power plants may be the most desirable candidates to support early-stage deployment of BECCS.

The socio-hydrology community has been very successful in promoting the need for taking the human factor into account in the mainstream hydrology literature since 2012. However, the interest in studying and modeling human-water systems is not new and pre-existed the post-2012 socio-hydrology. So, it is critical to ask what socio-hydrology has been able to offer that would have been unachievable using the existing methods, tools, and analysis frameworks. Thus far, the socio-hydrology studies show a strong overlap with what has already been in the literature, especially in the water resources systems and coupled human and natural systems (CHANS) areas. Nevertheless, the work in these areas has been generally dismissed by the socio-hydrology literature. This paper overviews some of the general concerns about originality, practicality, and contributions of socio-hydrology. It is argued that while in theory, a common sense about the need for considering humans as an integral component of water resources systems models can strengthen our coupled human-water systems research, the current approaches and trends in socio-hydrology can make this interest area less inclusive and interdisciplinary.

Scenarios for meeting ambitious climate targets rely on large-scale deployment of negative emissions technologies (NETs), including direct air capture (DAC). However, the tradeoffs between food, water and energy created by deploying different NETs are unclear. Here we show that DAC could provide up to 3 GtCO2 yr−1 of negative emissions by 2035—equivalent to 7% of 2019 global CO2 emissions—based on current-day assumptions regarding price and performance. DAC in particular could exacerbate demand for energy and water, yet it would avoid the most severe market-mediated effects of land-use competition from bioenergy with carbon capture and storage and afforestation. This could result in staple food crop prices rising by approximately fivefold relative to 2010 levels in many parts of the Global South, raising equity concerns about the deployment of NETs. These results highlight that delays in aggressive global mitigation action greatly increase the requirement for DAC to meet climate targets, and correspondingly, energy and water impacts.

Climate change mitigation strategies informed by Integrated Assessment Models (IAMs) increasingly rely on major deployments of negative emissions technologies (NETs) to achieve global climate targets. Although NETs can strongly complement emissions mitigation efforts, this dependence on the presumed future ability to deploy NETs at scale raises questions about the structural elements of IAMs that are influencing our understanding of mitigation efforts. Model inter-comparison results underpinning the IPCC’s special report on Global Warming of 1.5°C were used to explore the role that current assumptions are having on projections and the way in which emerging technologies, economic factors, innovation, and tradeoffs between negative emissions objectives and UN Sustainable Development Goals might have on future deployment of NETs. Current generation IAM scenarios widely assume we are capable of scaling up NETs over the coming 30 years to achieve negative emissions of the same order of magnitude as current global emissions (tens of gigatons of CO2/year) predominantly relying on highly land intensive NETs. While the technological potential of some of these approaches (e.g., direct air capture) is much greater than for the land-based technologies, these are seldom included in the scenarios. Alternative NETs (e.g., accelerated weathering) are generally excluded because of connections with industrial sectors or earth system processes that are not yet included in many models. In all cases, modeling results suggest that significant NET activity will be conducted in developing regions, raising concerns about tradeoffs with UN Sustainable Development Goals. These findings provide insight into how to improve treatment of NETs in IAMs to better inform international climate policy discussions. We emphasize the need to better understand relative strength and weaknesses of full suite of NETs that can help inform the decision making for policy makers and stakeholders.

This paper evaluates the feasibility of hydrothermal treatment (HTT) with carbon capture and storage (CCS) as an energy producing negative emissions technology (NET) and compares such system with a conventional bioenergy with carbon capture and sequestration (BECCS) system. Machine learning models were developed to predict product yields and characteristics from HTT of various feedstocks. The model results were then integrated into a life cycle assessment (LCA) model to compute two metrics: energy return on investment (EROI) and net global warming potential (GWP). Results showed random forest models had better prediction accuracy than regression tree and multiple linear regression to model HTT of feedstocks (e.g., microalgae, crops/forest residues, energy crops, and biodegradable organic wastes) and predicted the mass yields of multiple products (biocrude, hydrochar, gas, and aqueous co product) as well as the energy and carbon contents of biocrude and hydrochar. LCA results revealed that the proposed HTT-CCS system constituted a net-energy producing NET for some combinations of feedstock characteristics and reaction conditions. Best overall energy and GWP performance was achieved for HTT-CCS of lignocellulosic biomass at low temperature. Compared with the conventional BECCS system, HTT-CCS generally exhibited higher EROI but higher net GWP, depending on processing conditions and the feedstock types.

Biofuel development to comply with the Renewable Fuel Standard (RFS) would alter conventional crop patterns in agricultural watersheds. As a result, the hydrologic response of the watersheds will exhibit different and often opposing effects on agrohydrological system variables such as riverine nitrate-N load and streamflow. Conventional modeling approaches treat those externalities as regulatory constraints, often fail to consider the hierarchical nature of the decision-making process, and end with unrealistic solutions. This study therefore proposes an alternative decision-modeling framework for biofuel development to optimize a water-quality objective under different levels of streamflow requirement in the watershed. A bilevel programming model is established to mimic the hierarchical decision-making process in environmental regulation. The model is applied to the Sangamon River basin, a typical agricultural watershed in central Illinois, to determine the optimal locations and type of ethanol biorefineries as policy instruments. The results show that the proposed instruments can effectively guide the decisions in biofuel development to meet the environmental objectives in the watershed, although adopting the proposed framework yields a lower profit than the conventional models, which is the price of a more realistic solution to the hierarchical decision problem. The results also highlight the importance of spatial heterogeneity and identifying an appropriate spatial scale to design effective environmental policies in biofuel development.

Studies on the food, energy, and water (FEW) nexus lay a shared foundation for researchers, policy makers, practitioners, and stakeholders to understand and manage linked production, utilization, and security of FEW systems. The FEW nexus paradigm provides the water community specific channels to move forward in interdisciplinary research where integrated water resources management (IWRM) has fallen short. Here, we help water researchers identify, articulate, utilize, and extend our disciplinary strengths within the broader FEW communities, while informing scientists in the food and energy domains about our unique skillset. This paper explores the relevance of existing and ongoing scholarship within the water community, as well as current research needs, for understanding FEW processes and systems and implementing FEW solutions through innovations in technologies, infrastructures, and policies. Following the historical efforts in IWRM, hydrologists, water resources engineers, economists, and policy analysts are provided opportunities for interdisciplinary studies among themselves and in collaboration with energy and food communities, united by a common path to achieve sustainability development goals.

Seagrass meadows are highly productive habitats that provide important ecosystem services in the coastal zone, including carbon and nutrient sequestration. Organic carbon in seagrass sediment, known as “blue carbon,” accumulates from both in situ production and sedimentation of particulate carbon from the water column. Using a large-scale restoration (>1700 ha) in the Virginia coastal bays as a model system, we evaluated the role of seagrass, Zostera marina, restoration in carbon storage in sediments of shallow coastal ecosystems. Sediments of replicate seagrass meadows representing different age treatments (as time since seeding: 0, 4, and 10 years), were analyzed for % carbon, % nitrogen, bulk density, organic matter content, and 210Pb for dating at 1-cm increments to a depth of 10 cm. Sediment nutrient and organic content, and carbon accumulation rates were higher in 10-year seagrass meadows relative to 4-year and bare sediment. These differences were consistent with higher shoot density in the older meadow. Carbon accumulation rates determined for the 10-year restored seagrass meadows were 36.68 g C m-2 yr-1. Within 12 years of seeding, the restored seagrass meadows are expected to accumulate carbon at a rate that is comparable to measured ranges in natural seagrass meadows. This the first study to provide evidence of the potential of seagrass habitat restoration to enhance carbon sequestration in the coastal zone.