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1.
J Chem Inf Model ; 2024 Jul 15.
Artículo en Inglés | MEDLINE | ID: mdl-39009039

RESUMEN

Chemical information disseminated in scientific documents offers an untapped potential for deep learning-assisted insights and breakthroughs. Automated extraction efforts have shifted from resource-intensive manual extraction toward applying machine learning methods to streamline chemical data extraction. While current extraction models and pipelines have ushered in notable efficiency improvements, they often exhibit modest performance, compromising the accuracy of predictive models trained on extracted data. Further, current chemical pipelines lack both transferability─where a model trained on one task can be adapted to another relevant task with limited examples─and extensibility, which enables seamless adaptability for new extraction tasks. Addressing these gaps, we present ChemREL, a versatile chemical data extraction pipeline emphasizing performance, transferability, and extensibility. ChemREL utilizes a custom, diverse data set of chemical documents, labeled through an active learning strategy to extract two properties: normal melting point and lethal dose 50 (LD50). The normal melting point is selected for its prevalence in diverse contexts and wider literature, serving as the foundation for pipeline training. In contrast, LD50 evaluates the pipeline's transferability to an unrelated property, underscoring variance in its biological nature, toxicological context, and units, among other differences. With pretraining and fine-tuning, our pipeline outperforms existing methods and GPT-4, achieving F1-scores of 96.1% for entity identification and 97.0% for relation mapping, culminating in an overall F1-score of 95.4%. More importantly, ChemREL displays high transferability, effectively transitioning from melting point extraction to LD50 extraction with 10 randomly selected training documents. Released as an open-source package, ChemREL aims to broaden access to chemical data extraction, enabling the construction of expansive relational data sets that propel discovery.

2.
Environ Sci Technol ; 58(26): 11492-11503, 2024 Jul 02.
Artículo en Inglés | MEDLINE | ID: mdl-38904357

RESUMEN

Soil organic carbon (SOC) plays a vital role in global carbon cycling and sequestration, underpinning the need for a comprehensive understanding of its distribution and controls. This study explores the importance of various covariates on SOC spatial distribution at both local (up to 1.25 km) and continental (USA) scales using a deep learning approach. Our findings highlight the significant role of terrain attributes in predicting SOC concentration distribution with terrain, contributing approximately one-third of the overall prediction at the local scale. At the continental scale, climate is only 1.2 times more important than terrain in predicting SOC distribution, whereas at the local scale, the structural pattern of terrain is 14 and 2 times more important than climate and vegetation, respectively. We underscore that terrain attributes, while being integral to the SOC distribution at all scales, are stronger predictors at the local scale with explicit spatial arrangement information. While this observational study does not assess causal mechanisms, our analysis nonetheless presents a nuanced perspective about SOC spatial distribution, which suggests disparate predictors of SOC at local and continental scales. The insights gained from this study have implications for improved SOC mapping, decision support tools, and land management strategies, aiding in the development of effective carbon sequestration initiatives and enhancing climate mitigation efforts.


Asunto(s)
Carbono , Clima , Suelo , Suelo/química , Ciclo del Carbono , Secuestro de Carbono
3.
Environ Sci Technol ; 58(20): 8709-8723, 2024 May 21.
Artículo en Inglés | MEDLINE | ID: mdl-38656828

RESUMEN

Microplastics (MPs), plastic particles smaller than 5 mm, are now a growing environmental and public health issue, as they are detected pervasively in freshwater and marine environments, ingested by organisms, and then enter the human body. Industrial development drives this environmental burden caused by MP formation and human uptake by elevating plastic pollution levels and shaping the domestic dietary structure. We map the MP human uptake across 109 global countries on five continents from 1990 to 2018, focusing on the world's major coastlines that are affected by plastic pollution that affects the United Nations' Sustainable Development Goals (SDGs): SDG 6 (Clean Water and Sanitation), SDG 14 (Life Below Water), and SDG 15 (Life on Land). Amid rapid industrial growth, Indonesia tops the global per capita MP dietary intake at 15 g monthly. In Asian, African, and American countries, including China and the United States, airborne and dietary MP uptake increased over 6-fold from 1990 to 2018. Eradicating 90% of global aquatic plastic debris can help decrease MP uptake by more than 48% in Southeast Asian countries that peak MP uptake. To reduce MP uptake and potential public health risks, governments in developing and industrialized countries in Asia, Europe, Africa, and North and South America should incentivize the removal of free plastic debris from freshwater and saltwater environments through advanced water treatment and effective solid waste management practices.


Asunto(s)
Microplásticos , Plásticos , Humanos , Países en Desarrollo , Desarrollo Industrial
4.
Proc Natl Acad Sci U S A ; 121(14): e2313911121, 2024 Apr 02.
Artículo en Inglés | MEDLINE | ID: mdl-38527203

RESUMEN

Climate change persists as a pressing global issue due to high greenhouse gas emissions from fossil fuel-based energy sources. A transition to a greener energy matrix combined with carbon offsetting is imperative to mitigate the rate at which global temperature ascends. While countries have deployed faith in green hydrogen to accelerate worldwide decarbonization efforts, the concurrent rise of blockchain-operated crypto-applications, such as bitcoin, has exacerbated climate change concerns. In this study, we propose technological solutions that combine the green hydrogen infrastructure with bitcoin mining operations to catalyze environmental and socioeconomic sustainability in climate change mitigation strategies. Since the present state of crypto-operations undeniably contributes to worldwide carbon emissions, it becomes vital to explore opportunities for harnessing the widespread enthusiasm for bitcoin as an aid toward a sustainable and climate-friendly future. Our findings reveal that green hydrogen production, paired with crypto-operations, can accelerate the deployment of solar and wind power capacities to boost conventional mitigation frameworks. Specifically, leveraging the economic potential derived from green hydrogen and bitcoin for incremental investment in renewable energy penetration, this dynamic duo can enable capacity expansions of up to 25.5% and 73.2% for solar and wind power installations. Therefore, the proposed technological solutions that leverage green hydrogen and bitcoin mining, bolstered with appropriate policy interventions, can not only strengthen renewable power generation and carbon offsetting capacities but also contribute significantly to achieving climate sustainability.

5.
Proc Natl Acad Sci U S A ; 120(39): e2304099120, 2023 09 26.
Artículo en Inglés | MEDLINE | ID: mdl-37722045

RESUMEN

The growth in remote and hybrid work catalyzed by the COVID-19 pandemic could have significant environmental implications. We assess the greenhouse gas emissions of this transition, considering factors including information and communication technology, commuting, noncommute travel, and office and residential energy use. We find that, in the United States, switching from working onsite to working from home can reduce up to 58% of work's carbon footprint, and the impacts of IT usage are negligible, while office energy use and noncommute travel impacts are important. Our study also suggests that achieving the environmental benefits of remote work requires proper setup of people's lifestyle, including their vehicle choice, travel behavior, and the configuration of home and work environment.


Asunto(s)
COVID-19 , Teletrabajo , Humanos , Pandemias/prevención & control , COVID-19/epidemiología , COVID-19/prevención & control , Lugar de Trabajo , Estilo de Vida
6.
Proc Natl Acad Sci U S A ; 120(29): e2303109120, 2023 Jul 18.
Artículo en Inglés | MEDLINE | ID: mdl-37428917

RESUMEN

The world is facing a formidable climate predicament due to elevated greenhouse gas (GHG) emissions from fossil fuels. The preceding decade has also witnessed a dramatic surge in blockchain-based applications, constituting yet another substantial energy consumer. Nonfungible tokens (NFTs) are one such application traded on Ethereum (ETH) marketplaces that have raised concerns about their climate impacts. The transition of ETH from proof of work (PoW) to proof of stake (PoS) is a step toward reducing the carbon footprint of the NFT sector. However, this alone will not address the climate impacts of the growing blockchain industry. Our analysis indicates that NFTs can cause yearly GHG emissions of up to 18% of the peak under the energy-intensive PoW algorithm. This results in a significant carbon debt of 4.56 Mt CO2-eq by the end of this decade, equivalent to CO2 emissions from a 600-MW coal-fired power plant in 1 y which would meet residential power demand in North Dakota. To mitigate the climate impact, we propose technological solutions to sustainably power the NFT sector using unutilized renewable energy sources in the United States. We find that 15% utilization of curtailed solar and wind power in Texas or 50 MW of potential hydropower from existing nonpowered dams can support the exponential growth of NFT transactions. In summary, the NFT sector has the potential to generate significant GHG emissions, and measures are necessary to mitigate its climate impact. The proposed technological solutions and policy support can help promote climate-friendly development in the blockchain industry.

7.
Sci Adv ; 9(24): eadg6740, 2023 Jun 16.
Artículo en Inglés | MEDLINE | ID: mdl-37315136

RESUMEN

Recent global logistics and geopolitical challenges draw attention to the potential raw material shortages for electric vehicle (EV) batteries. Here, we analyze the long-term energy and sustainability prospects to ensure a secure and resilient midstream and downstream value chain for the U.S. EV battery market amid uncertain market expansion and evolving battery technologies. With current battery technologies, reshoring and ally-shoring the midstream and downstream EV battery manufacturing will reduce the carbon footprint by 15% and energy use by 5 to 7%. While next-generation cobalt-free battery technologies will achieve up to 27% carbon emission reduction, transitioning to 54% less carbon-intensive blade lithium iron phosphate may diminish the mitigation benefits of supply chain restructuring. Our findings underscore the importance of adopting nickel from secondary sources and nickel-rich ores. However, the advantages of restructuring the U.S. EV battery supply chain depend on projected battery technology advancements.

8.
Nat Commun ; 14(1): 1616, 2023 Apr 11.
Artículo en Inglés | MEDLINE | ID: mdl-37041146

RESUMEN

Automotive electrification holds the promise of mitigating transportation-related greenhouse gas (GHG) emissions, yet at the expense of growing demand for critical metals. Here, we analyze the trade-off between the decarbonization potential of the road transportation sector and its critical metal requirement from the demand-side perspective in 48 major countries committing to decarbonize their road transportation sectors aided by electric vehicles (EVs). Our results demonstrate that deploying EVs with 40-100% penetration by 2050 can increase lithium, nickel, cobalt, and manganese demands by 2909-7513%, 2127-5426%, 1039-2684%, and 1099-2838%, respectively, and grow platinum group metal requirement by 131-179% in the 48 investigated countries, relative to 2020. Higher EV penetration reduces GHG emissions from fuel use regardless of the transportation energy transition, while those from fuel production are more sensitive to energy-sector decarbonization and could reach nearly "net zero" by 2040.

9.
Environ Sci Technol ; 57(16): 6506-6519, 2023 04 25.
Artículo en Inglés | MEDLINE | ID: mdl-37058399

RESUMEN

Plastic pollution caused by material losses and their subsequent chemical emissions is pervasive in the natural environment and varies with age. Cascading the life cycles of plastic losses with solid waste reclamation via re-manufacturing virgin polymers or producing fuels and energy may extend resource availability while minimizing waste generation and environmental exposure. Here, we systematically investigate this cascaded plastic waste processing over other waste end-of-life management pathways by analyzing the environmental consequences of plastic losses across the entire life cycle. Plastic losses can form volatile organic chemicals via photo-degradation and pose non-negligible global warming, ecotoxicity, and air pollution effects that worsen by at least 189% in the long run. These environmental burdens increase by above 9.96% under high ultraviolet radiation levels and participation rates, which facilitate plastic particulate compartment transport and degradation. Cascaded plastic waste processing aided by fast pyrolysis upcycling technologies can effectively cut environmental losses and outperform landfills and incineration in reducing 23.35% ozone formation and 19.91% air pollution by offsetting the external monomer manufacturing and fuels and energy production while saving at least 25.75% fossil fuels.


Asunto(s)
Compuestos Orgánicos Volátiles , Administración de Residuos , Animales , Plásticos , Polímeros , Rayos Ultravioleta , Estadios del Ciclo de Vida
10.
Nat Commun ; 14(1): 1274, 2023 Mar 08.
Artículo en Inglés | MEDLINE | ID: mdl-36890141

RESUMEN

The globalized supply chain for crystalline silicon (c-Si) photovoltaic (PV) panels is increasingly fragile, as the now-mundane freight crisis and other geopolitical risks threaten to postpone major PV projects. Here, we study and report the results of climate change implications of reshoring solar panel manufacturing as a robust and resilient strategy to reduce reliance on foreign PV panel supplies. We project that if the U.S. could fully bring c-Si PV panel manufacturing back home by 2035, the estimated greenhouse gas emissions and energy consumption would be 30% and 13% lower, respectively, than having relied on global imports in 2020, as solar power emerges as a major renewable energy source. If the reshored manufacturing target is achieved by 2050, the climate change and energy impacts would be further reduced by 33% and 17%, compared to the 2020 level. The reshored manufacturing demonstrates significant progress in domestic competitiveness and toward decarbonization goals, and the positive reductions in climate change impacts align with the climate target.

11.
Small ; 19(23): e2207802, 2023 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-36892170

RESUMEN

Identifying and removing microplastics (MPs) from the environment is a global challenge. This study explores how the colloidal fraction of MPs assemble into distinct 2D patterns at aqueous interfaces of liquid crystal (LC) films with the goal of developing surface-sensitive methods for identifying MPs. Polyethylene (PE) and polystyrene (PS) microparticles are measured to exhibit distinct aggregation patterns, with addition of anionic surfactant amplifying differences in PS/PE aggregation patterns: PS changes from a linear chain-like morphology to a singly dispersed state with increasing surfactant concentration whereas PE forms dense clusters at all surfactant concentrations. Statistical analysis of assembly patterns using deep learning image recognition models yields accurate classification, with feature importance analysis confirming that dense, multibranched assemblies are unique features of PE relative to PS. Microscopic characterization of LC ordering at the microparticle surfaces leads to predict LC-mediated interactions (due to elastic strain) with a dipolar symmetry, a prediction consistent with the interfacial organization of PS but not PE. Further analysis leads to conclude that PE microparticles, due to their polycrystalline nature, possess rough surfaces that lead to weak LC elastic interactions and enhanced capillary forces. Overall, the results highlight the potential utility of LC interfaces for rapid identification of colloidal MPs based on their surface properties.

12.
Fundam Res ; 3(6): 951-959, 2023 Nov.
Artículo en Inglés | MEDLINE | ID: mdl-38933002

RESUMEN

Providing accurate crop yield estimations at large spatial scales and understanding yield losses under extreme climate stress is an urgent challenge for sustaining global food security. While the data-driven deep learning approach has shown great capacity in predicting yield patterns, its capacity to detect and attribute the impacts of climatic extremes on yields remains unknown. In this study, we developed a deep neural network based multi-task learning framework to estimate variations of maize yield at the county level over the US Corn Belt from 2006 to 2018, with a special focus on the extreme yield loss in 2012. We found that our deep learning model hindcasted the yield variations with good accuracy for 2006-2018 (R2 = 0.81) and well reproduced the extreme yield anomalies in 2012 (R2 = 0.79). Further attribution analysis indicated that extreme heat stress was the major cause for yield loss, contributing to 72.5% of the yield loss, followed by anomalies of vapor pressure deficit (17.6%) and precipitation (10.8%). Our deep learning model was also able to estimate the accumulated impact of climatic factors on maize yield and identify that the silking phase was the most critical stage shaping the yield response to extreme climate stress in 2012. Our results provide a new framework of spatio-temporal deep learning to assess and attribute the crop yield response to climate variations in the data rich era.

13.
Environ Sci Technol ; 56(16): 11780-11797, 2022 08 16.
Artículo en Inglés | MEDLINE | ID: mdl-35920730

RESUMEN

Concern about microplastic pollution sourced from mismanaged plastic waste losses to drainage basins is growing but lacks relevant environmental impact analyses. Here, we reveal and compare the environmental hazards of aquatic macro- and microplastic debris through a holistic life cycle assessment approach. Compared to polymeric debris, microplastics, especially smaller than 10 µm, exhibit higher freshwater ecotoxicity enhanced by watersheds' high average depth and low water temperature. High microplastic concentration within drainage basins can also cause air pollution regarding particulate matter formation and photochemical ozone formation. The environmental drawbacks of plastic mismanagement are then demonstrated by showing that the microplastic formulation and removal in drinking water treatment plants can pose more than 7.44% of the total ecotoxicity effect from plastic wastes' (microplastics') whole life cycle. Specifically, these two life cycle stages can also cause more than 50% of the plastic wastes' life cycle ecotoxicity effect related to organic chemical emissions. Therefore, reducing environmentally harmful plastic losses through advanced plastic waste recycling, collection, and effective microplastic removal technologies needs future investigation.


Asunto(s)
Microplásticos , Contaminantes Químicos del Agua , Animales , Monitoreo del Ambiente , Estadios del Ciclo de Vida , Plásticos/análisis , Polímeros , Contaminantes Químicos del Agua/análisis , Contaminantes Químicos del Agua/toxicidad
14.
J Dairy Sci ; 105(3): 2180-2189, 2022 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-34998551

RESUMEN

The objective of this study was to compare the application of iterative linear programming (iteLP), sequential quadratic programming (SQP), and mixed-integer nonlinear programming-based deterministic global optimization (MINLP_DGO) on ration formulation for dairy cattle based on Nutrient Requirements of Dairy Cattle (NRC, 2001). Least-cost diets were formulated for lactating cows, dry cows, and heifers. Nutrient requirements including energy, protein, and minerals, along with other limitations on dry matter intake, neutral detergent fiber, and fat were considered as constraints. Five hundred simulations were conducted, with each simulation randomly selecting 3 roughages and 5 concentrates from the feed table in NRC (2001) as the feed resource for each of 3 animal groups. Among the 500 simulations for lactating cows, 57, 45, and 21 simulations did not yield a feasible solution when using iteLP, SQP, and MINLP_DGO, respectively. All the simulations for dry cows and heifers were feasible when using SQP and MINLP_DGO, but 49 and 11 infeasible simulations occurred when using iteLP for dry cows and heifers, respectively. The average ration costs per animal per day of the feasible solutions obtained by iteLP, SQP, and MINLP_DGO were $4.78 (±0.71), $4.45 (±0.65), and $4.44 (±0.65) for lactating cows; $2.39 (±0.52), $1.48 (±0.26), and $1.48 (±0.26) for dry cows; and $0.98 (±0.72), $0.97 (±0.15), and $0.91 (±0.14) for heifers, respectively. The average computation time of iteLP, SQP, and MINLP_DGO were 0.59 (±1.87) s, 1.15 (±0.62) s, and 58.69 (±68.45) s for lactating cows; 0.041 (±0.070) s, 0.76 (±0.37) s, and 14.84 (±39.09) s for dry cows; and 1.60 (±2.90) s, 0.51 (±0.19) s, and 16.45 (±45.56) s for heifers, respectively. In conclusion, iteLP had limited capability of formulating least-cost diets when nonlinearity existed in the constraints. Both SQP and MINLP_DGO handled the nonlinear constraints well, with SQP being faster, whereas MINLP_DGO was able to return a feasible solution under some situations where SQP could not.


Asunto(s)
Alimentación Animal , Lactancia , Alimentación Animal/análisis , Animales , Bovinos , Dieta/veterinaria , Fibras de la Dieta/metabolismo , Femenino , Leche/metabolismo , Rumen/metabolismo
15.
J Hazard Mater ; 424(Pt A): 127330, 2022 02 15.
Artículo en Inglés | MEDLINE | ID: mdl-34600379

RESUMEN

Plastic waste and its environmental hazards have been attracting public attention as a global sustainability issue. This study builds a neural network model to forecast plastic waste generation of the EU-27 in 2030 and evaluates how the interventions could mitigate the adverse impact of plastic waste on the environment. The black-box model is interpreted using SHapley Additive exPlanations (SHAP) for managerial insights. The dependence on predictors (i.e., energy consumption, circular material use rate, economic complexity index, population, and real gross domestic product) and their interactions are discussed. The projected plastic waste generation of the EU-27 is estimated to reach 17 Mt/y in 2030. With an EU targeted recycling rate (55%) in 2030, the environmental impacts would still be higher than in 2018, especially global warming potential and plastic marine pollution. This result highlights the importance of plastic waste reduction, especially for the clustering algorithm-based grouped countries with a high amount of untreated plastic waste per capita. Compared to the other assessed scenarios, Scenario 4 with waste reduction (50% recycling, 47.6% energy recovery, 2.4% landfill) shows the lowest impact in acidification, eutrophication, marine aquatic toxicity, plastic marine pollution, and abiotic depletion. However, the global warming potential (8.78 Gt CO2eq) is higher than that in 2018, while Scenario 3 (55% recycling, 42.6% energy recovery, 2.4% landfill) is better in this aspect than Scenario 4. This comprehensive analysis provides pertinent insights into policy interventions towards environmental hazard mitigation.


Asunto(s)
Eliminación de Residuos , Administración de Residuos , Contaminación Ambiental , Plásticos/toxicidad , Reciclaje , Residuos Sólidos , Instalaciones de Eliminación de Residuos
16.
Nat Commun ; 12(1): 7324, 2021 12 16.
Artículo en Inglés | MEDLINE | ID: mdl-34916499

RESUMEN

Since 2020, the COVID-19 pandemic has urged event holders to shift conferences online. Virtual and hybrid conferences are greener alternatives to in-person conferences, yet their environmental sustainability has not been fully assessed. Considering food, accommodation, preparation, execution, information and communication technology, and transportation, here we report comparative life cycle assessment results of in-person, virtual, and hybrid conferences and consider carbon footprint trade-offs between in-person participation and hybrid conferences. We find that transitioning from in-person to virtual conferencing can substantially reduce the carbon footprint by 94% and energy use by 90%. For the sake of maintaining more than 50% of in-person participation, carefully selected hubs for hybrid conferences have the potential to slash carbon footprint and energy use by two-thirds. Furthermore, switching the dietary type of future conferences to plant-based diets and improving energy efficiencies of the information and communication technology sector can further reduce the carbon footprint of virtual conferences.

17.
Sci Adv ; 7(45): eabi7633, 2021 Nov 05.
Artículo en Inglés | MEDLINE | ID: mdl-34739316

RESUMEN

Second life and recycling of retired automotive lithium-ion batteries (LIBs) have drawn growing attention, as large volumes of LIBs will retire in the coming decade. Here, we illustrate how battery chemistry, use, and recycling can influence the energy and environmental sustainability of LIBs. We find that LIBs with higher specific energy show better life cycle environmental performances, but their environmental benefits from second life application are less pronounced. Direct cathode recycling is found to be the most effective in reducing life cycle environmental impacts, while hydrometallurgical recycling provides limited sustainability benefits for high-performance LIBs. Battery design with less aluminum and alternative anode materials, such as silicon-based anode, could enable more sustainable LIB recycling. Compared to directly recycling LIBs after their electric vehicle use, carbon footprint and energy use of LIBs recycled after their second life can be reduced by 8 to 17% and 2 to 6%, respectively.

18.
Appl Energy ; 304: 117848, 2021 Dec 15.
Artículo en Inglés | MEDLINE | ID: mdl-34539038

RESUMEN

The widespread COVID-19 pandemic led to a shortage in the supply of N95 respirators in the United States until May 2021. In this study, we address the energy, environmental, and economic benefits of the decontamination-and-reuse of the N95 masks. Two popular decontamination methods, including dry heat and vapor hydrogen peroxide (VHP), are investigated in this study for their effective pathogen inactivation and favorable performance in preserving filtration efficiency and structural integrity of respirators. Two multiple reuse cases, under which the N95 masks are disinfected and used five times with the dry heat method and 20 times using the VHP method, are considered and compared with a single-use case. Compared to the single-use case, the dry heat-based multiple-use case reduces carbon footprint by 50% and cumulative energy demand (CED) by 17%, while the VHP-based case decreases carbon footprint by 67% and CED by 58%. The dry-heat-based and VHP-based multiple reuse cases also present environmental benefits in most of the other impact categories, primarily due to substituting new N95 respirators with decontaminated ones. Decontaminating and reusing respirators costs 77% and 89% less than the case of single-use and disposal. The sensitivity analysis results show that the geographical variation in the power grid and the times of respirator use are the most influential factors for carbon footprint and CED, respectively. The result also reaffirms the energy, environmental, and economic favorability of the decontamination and reuse of N95 respirators.

19.
Appl Energy ; 283: 116129, 2021 Feb 01.
Artículo en Inglés | MEDLINE | ID: mdl-33519036

RESUMEN

The ongoing COVID-19 pandemic leads to a surge on consumption of respirators. This study proposes a novel and effective waste respirator processing system for protecting public health and mitigating climate change. Respirator sterilization and pre-processing technologies are included in the system to resist viral infection and facilitate unit processes for respirator pyrolysis, product separation, and downstream processing for greenhouse gas (GHG) emission reduction. We evaluate the system's environmental performance through high-fidelity process simulations and detailed life cycle assessment. Techno-economic analysis results show that the payback time of the waste respirator processing system is seven years with an internal rate of return of 21.5%. The tipping fee and discount rate are the most influential economic factors. Moreover, the unit life cycle GHG emissions from the waste respirator processing system are 12.93 kg CO2-eq per thousand waste respirators treated, which reduces GHG emissions by 59.08% compared to incineration-based system so as to mitigate climate change.

20.
Sci Adv ; 6(31): eabb0055, 2020 Jul.
Artículo en Inglés | MEDLINE | ID: mdl-32789177

RESUMEN

A promising route to widespread deployment of photovoltaics is to harness inexpensive, highly-efficient tandems. We perform holistic life cycle assessments on the energy payback time, carbon footprint, and environmental impact scores for perovskite-silicon and perovskite-perovskite tandems benchmarked against state-of-the-art commercial silicon cells. The scalability of processing steps and materials in the manufacture and operation of tandems is considered. The resulting energy payback time and greenhouse gas emission factor of the all-perovskite tandem configuration are 0.35 years and 10.7 g CO2-eq/kWh, respectively, compared to 1.52 years and 24.6 g CO2-eq/kWh for the silicon benchmark. Prolonging the lifetime provides a strong technological lever for reducing the carbon footprint such that the perovskite-silicon tandem can outcompete the current benchmark on energy and environmental performance. Perovskite-perovskite tandems with flexible and lightweight form factors further improve the energy and environmental performance by around 6% and thus enhance the potential for large-scale, sustainable deployment.

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