20253 research outputs found
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CoSWAT Model v1: A high-resolution global SWAT+ hydrological model
No full textGlobal hydrological models are essential tools for understanding water resources and assessing Climate Change (CC) impacts at planetary scales, supporting water management, flood risk assessment, and sustainable development initiatives worldwide. The Soil and Water Assessment Tool (SWAT+) has demonstrated robust performance across various environments and scales, from local to continental applications. However, despite its widespread use, a global implementation of SWAT+ is currently lacking due to computational demands and data management challenges, while existing global models often lack the detailed process representation and high spatial resolution needed for comprehensive hydrological analysis. A global SWAT+ model would offer unique advantages through its integrated simulation of water quantity, quality, and land management processes, while supporting multiple UN Sustainable Development Goals and enhancing research opportunities in global hydrology. This study aimed to develop a High-resolution Global SWAT+ Model and establish a reproducible framework for large-scale SWAT+ applications. We developed the Community SWAT (CoSWAT) modeling framework, an open-source solution that automates data retrieval, preprocessing, and model configuration using Python, while maximizing parallel processing for computational efficiency. The global model was then set up using the framework at 2 km resolution using ASTER DEM, ESA land use data, FAO soil data, and ISIMIP climate data, with performance evaluated against GRDC flow data and GLEAM evapotranspiration dataset. Results without calibration showed reasonable spatial patterns in evapotranspiration simulation with 78.54 % of sampled points showing differences within +/- 100 mm compared to GLEAM data, though river discharge performance was limited due to lack of reservoir implementation with 23.02 % of stations showing positive Kling-Gupta Efficiency values. The development of this first global SWAT+ model demonstrates the feasibility of high-resolution global hydrological modeling using SWAT+, while the CoSWAT framework provides a robust foundation for reproducible large-scale modeling. These advances enable more detailed analysis of global water resources and CC impacts, though future work should focus on incorporating water management practices, improving process representation with calibration, and enhancing computational efficiency
Heart failure in China: a macroeconomic modelling study of intervention strategies
No full textBackground and Aims
Heart failure (HF) imposes a growing public health and macroeconomic burden in low- and middle-income countries (LMICs), yet its long-term economic impact remains unquantified. China, characterized by rapid ageing and escalating cardiovascular risks, provides a critical setting to model HF economic implications.
Methods
Using data from the Global Burden of Disease Study 2021, China Cardiovascular Association Registry, and national insurance databases, HF macroeconomic burden (2025–35) was projected via a health-augmented macroeconomic model. Three interventions were evaluated: B-type natriuretic peptide (BNP) screening (adults ≥40 years), intensive blood pressure (BP) control (hypertensive patients), and guideline-directed medical therapy (GDMT) optimization for HF with reduced ejection fraction. Costs are reported in 2017 international dollars (INT1001.1 billion (95% UI: 733.4–1365.6 billion), representing 0.26% of gross domestic product (95% UI: 0.19%–0.34%), driven by labour force attrition (72.1%; 95% UI: 64.4%–74.8%). Interventions reduced the total burden by 12.5% (95% UI: 10.4%–14.5%): BNP screening (25% coverage) saved INT27.5 billion (95% UI: 25.1–29.9 billion; 2.74% reduction; ratio 0.22), GDMT optimization saved INT$17.0 billion (95% UI: 12.8–22.4 billion; 1.70% reduction; ratio 0.48).
Conclusions
HF imposes a substantial and increasing macroeconomic burden in China, largely through workforce productivity losses. Scalable, cost-effective strategies, including primary care-based BNP screening, subsidized hypertension control, and enhanced GDMT adherence, are essential to curb economic losses. These findings inform policy priorities for China and other LMICs confronting demographic transitions
Global Environment Outlook 7: A future we choose – Why investing in Earth now can lead to a trillion-dollar benefit for all
No full textThe Global Environment Outlook, Seventh Edition: A Future We Choose, the product of 287 multi-disciplinary scientists from 82 countries, is the most comprehensive scientific assessment of the global environment ever carried out. The report calls on all actors to acknowledge the urgency of the global environmental crises, build on progress made in recent decades, and collaborate in the co-design and implementation of integrated policies, strategies and actions to deliver a better future for all
Integrating NLP and Scenario Analysis for the Future of Space Security: A Structured Examination of Online Expert Discourse
No full textThis study conducts a scenario-based analysis of space security by integrating diverse perspectives from online media through advanced Natural Language Processing (NLP). Transcripts from 44 YouTube videos on space security are analysed including expert discussions, current news updates, and a diverse range of opinions to identify 14 key factors having an impact on the development of space security including international security environment, technological dependency, anti-satellite weaponry, space debris, governance, transparency, international cooperation, military organisation, commercial roles, cybersecurity, attack forms, commercial resilience, regulatory compliance, and space weather. Based on these factors, three scenarios of the future are developed: a Cooperative and Resilient Space Environment; a Fragmented and Vulnerable Space Domain; and a Chaotic and Hostile Space Environment. The stable future foresees strong international norms, robust cybersecurity, unified military organisation, and high commercial resilience, while the quasi-stable future reflects weakening international relations and governance. The unstable future is shaped by escalating geopolitical tensions, aggressive weaponisation, extreme debris, and severe space weather, leading to widespread disruption. This innovative methodology transforms unstructured online opinions into structured insights to guide policy and strategic decision-making
COVID-19 impacts and post-pandemic rebound in Pakistan’s sectoral greenhouse gas emissions (2018–2023)
No full textThis study presents the first multi-year, sectorally disaggregated greenhouse gas (GHG) inventory for Pakistan covering 2018–2023, capturing pre-pandemic, pandemic, and post-pandemic dynamics. Using the 2006 IPCC Guidelines and national activity data by sector, emissions were quantified across energy, industrial processes and product use (IPPU), agriculture, forestry, and other land use (AFOLU), and waste sectors. Total GHG emissions declined by 7% during 2019–2020, with energy sector emissions falling 16% from 217 Mt CO2-eq in 2018 to 184 Mt CO2-eq in 2020, before rebounding 7% in 2021. A further 18% reduction in 2023, driven by lower industrial and transport energy use, brought emissions to 363 Mt CO2-eq. IPPU emissions tracked economic fluctuations, rising 21% in 2021 and falling 12% in 2023, while AFOLU and waste emissions increased steadily by 2–3% annually, reflecting structural drivers. These findings indicate that pandemic-related reductions were temporary and economically driven, underscoring the need for structural decarbonization. Sustained mitigation requires renewable energy expansion, energy efficiency improvements, low-carbon industrial technologies, and climate-smart practices in agriculture and waste management. The study provides a robust evidence base to guide Pakistan’s mitigation strategies, supporting alignment with Nationally Determined Contribution (NDC) targets and long-term climate and sustainable development goals
Evaluierung von Maßnahmen zur Förderung des Kunststoffrecyclings mittels eines wirtschaftsmathematischen Modells (Evaluation of measures to promote plastics recycling using an economic mathematical model)
No full textDie COVID-19-Pandemie hat zu erheblichen Spannungen im Recyclingsektor geführt. Besonders betroffen war das Recycling von Kunststoffverpackungen, da der Preisverfall von Rohöl zu erheblich günstigeren Primärkunststoffen führte. Infolgedessen konnten Rezyklate nur schwer abgesetzt werden, und es kam teilweise zu problematischen Lagerbeständen bei den Recyclern. Daher wurde von vielen Branchenvertretern eine verpflichtende Mindesteinsatzquote von Rezyklaten in der Kunststoffverpackungsproduktion gefordert. Diese soll helfen, die Nachfrage nach Rezyklaten langfristig zu stabilisieren.
Um die Einführung einer solchen Quote zu untersuchen, wurde das Kunststoffverpackungssystem basierend auf einer Materialflussanalyse als vereinfachtes Stoffstrommodell abgebildet und mit einem ökonomischen Gleichgewichtsmodell verknüpft. In verschiedenen Szenarien wurde analysiert, wie das System auf stark sinkende Primärkunststoffpreise reagiert. Die Ergebnisse zeigen, dass das Modell die beobachtbaren realen Effekte qualitativ gut abbildet. Gleichzeitig wird deutlich, dass eine Mindestrezyklateinsatzquote als alleinige Maßnahme nicht ausreicht, um die gewünschten ökologischen und ökonomischen Ziele zu erreichen.
Das entwickelte Modell erweist sich somit als geeignetes Instrument, um politische Maßnahmen zur Stabilisierung und Förderung des Kunststoffrecyclings zu entwerfen und zu bewerten. Es ermöglicht ein besseres Verständnis für die Wechselwirkungen zwischen Marktmechanismen und politischen Maßnahmen und kann damit zur Entwicklung wirksamer Strategien für eine nachhaltigere Kreislaufwirtschaft beitragen.
The COVID-19 pandemic has led to significant distortions in the recycling sector. The recycling of plastic packaging was particularly affected, as the sharp decline in crude oil prices resulted in much cheaper virgin plastics. Consequently, recyclers had difficulties getting their recyclates into the market and the storages filled up. To stabilize the long-term demand for recyclates, the introduction of a mandatory minimum recyclate utilization rate in plastic packaging production was proposed.
To examine the implications of such a measure, the plastic packaging system was modeled as a simplified material flow system and linked to an economic equilibrium model. Various scenarios were used to analyze how the system responds to sharply declining virgin plastic prices and the implementation of a minimum utilization rate. The results indicate that the model accurately reproduces the qualitative effects observed. At the same time, it becomes clear that a minimum utilization rate alone is insufficient to achieve the desired environmental and economic objectives.
Nevertheless, the developed model proves to be a suitable tool for designing and evaluating policy measures aimed at stabilizing and promoting plastic recycling. It enhances the understanding of the interactions between market mechanisms and policy interventions and thus contributes to the development of effective strategies for a more sustainable circular economy
How moral philosophers can help society
No full textThis paper argues that moral philosophers can have a special role in helping members of society come to choose which moral theories to believe. Importantly, the argument does not depend on the idea that moral philosophers (more) reliably have true moral beliefs (or are “Strong Moral Experts”). Instead, the argument is that moral philosophers are well-placed to develop understanding of moral theories by drawing out valid implications (they are “Weak Moral Experts”). By developing valid moral arguments, and by making the relevant implications accessible to society, moral philosophers can help people understand the costs and benefits of various moral theories, allowing them to make more informed choices. This does not imply that everyone will agree; there is room for disagreement about the weight to put on various theoretical costs and benefits. But it does give a metaphilosophical picture of the role of moral philosophers, justify certain kinds of public philosophy, and explain the value that moral philosophers can add to society at the philosophy-public interface
Global Pasture Watch - Annual grassland class and extent maps at 30-m spatial resolution (2000—2024) V2-beta
No full textSub-dataset: Dominant grassland class, 2012-2014
Description
Global annual grassland class and extent for 2000—2024 produced by Parente et al. (2024) within the scope of the Global Pasture Watch initiative. The mapped grassland extent includes any land cover type, which contains at least 30% of dry or wet low vegetation, dominated by grasses and forbs (less than 3 meters) and a:
maximum of 50% tree canopy cover (greater than 5 meters),
maximum of 70% of other woody vegetation (scrubs and open shrubland), and
maximum of 50% active cropland cover in mosaic landscapes of cropland & other vegetation.
The grassland extent is classified into two classes:
Cultivated grassland: Areas where grasses and other forage plants have been intentionally planted and managed, as well as areas of native grassland-type vegetation where they clearly exhibit active and 'heavy' management for specific human-directed uses, such as directed grazing of livestock.
Natural/semi-natural grassland: Relatively undisturbed native grasslands/short-height vegetation, such as steppes and tundra, as well as areas that have experienced varying degrees of human activity in the past, which may contain a mix of native and introduced species due to historical land use and natural processes. In general, they exhibit natural-looking patterns of varied vegetation and clearly ordered hydrological relationships throughout the landscape.
Open shrubland (v2-beta): Land on which the vegetation is dominated by low-growing woody plants, characterized by a sparse distribution of shrubs and dominated by woody perennials. Typically covers 50—75% of the area, with significant open ground (with or without herbaceous understory) between them, where shrub canopies are less than 10 meters in diameter, and tree cover is below 10%, meaning they do not form a continuous or semi-continuous canopy.
The dataset is organized in 69 global mosaics (25 years for each time series) in COG (Cloud Optimized GeoTIFF) format, WGS84 Coordinate Systems (EPSG:4326) and pixel size equal to 0.00025 degrees, including:
Probabilities of cultivated grassland (values range from 0–100),
Probabilities of natural/semi-natural grassland (values range from 0–100), and
Probabilities of open shrubland (values range from 0–100), and
Dominant class (0-other land cover, 1-cultivated grassland and 2-natural/semi-natural grassland, 3-open shrubland).
All raster files are in unsigned 8-bit integer format and use 255 as no-data value (pixels ignored by prediction), following an specific naming convention:
Project name: Global Pasture Watch (gpw)
Class name: cultivated grassland (cultiv.grassland), natural/semi-natural grassland (nat.semi.grassland), open shrubland (open.shrubland) and dominant grassland (grassland)
Procedure combination: Random Forest (rf), median filter (med.filt) and balanced threshold (bthr).
Variable type: probability (p) and factor class (c)
Spatial resolution: 30m
Begin of time reference: date of first Landsat composite used by the modeling (20240101)
End of time reference: date of last Landsat composite used by the modeling (20241231)
Spatial extent: global (go)
Coordinate system: World Geodetic System 1984, used in GPS (epsg.4326)
Version: v2
Related resources
Maps of dominant grassland:
2000-2002 2003-2005 2006-2008 2009-2011 2012-2014 2015-2017 2018-2020 2021-2023 2024
Probability maps of cultivated grassland:
2000-2024 (All URLs)
Probability maps of natural/semi-natural grassland:
2000-2024 (All URLs)
Grassland reference samples based on VHR imagery (2000–2024):
GeoPackage files
Global machine learning models (Random Forest):
Parquet and joblib python files
Reference sampling design derived by FSCV:
GeoPackage and raster files
Harmonized reference samples based on existing LULC dataset:
GeoPackage and raster files
Source code for reproducibility:
GitHub release
Mapping feedback tool:
GeoWiki
Data catalogues:
OpenLandMap STAC Google Earth Engine
Support
For questions of bugs/inconsistencies related to the dataset raise a GitHub issue in https://github.com/wri/global-pasture-watc
CMIP7 ScenarioMIP historical timeseries for harmonisation and simple climate model workflow
No full textThe files here are compiled historical experiment timeseries. They were compiled for use as part of the CMIP7 ScenarioMIP exercise and are primarily used for supporting emissions harmonisation. Here, 'harmonisation' means alignment of modelled emissions from IAMs with the emissions used for the CMIP7 historical experiment.
As a result, they are a key input for the process of 'gridding' emissions (i.e. taking raw emissions from IAMs and assigning them to a spatial grid, ready for use by Earth System Models (ESMs)) and for running the simple climate model based assessment of the scenarios to derive a first-order estimate of the warming associated with these scenarios (the ESMs will quantify the warming and other climate change associated with these scenarios as part of ScenarioMIP, and this quantification is underpinned by a deeper, more physically-based set of modelling assumptions.)
There are three different files, provided in three different formats each. The three files are:
gridding-history*: the history used for harmonisation at the 'gridding' level. The gridding requires emissions with regional and sectoral detail. It also has to support every IAMs' native regions. As a result, there are lots (of order 30 000) timeseries.
country-history*: same as above, but at the country level rather than in native IAM regions.
global-workflow-history*: the history used for harmonisation at the 'global' level. This only has global total emissions, except for CO2 which is split into fossil-based and land-based (i.e. originating from the land carbon pool) emissions. It includes a number of species that are not used in the gridding workflow but are relevant for climate projections e.g. all of the greenhouse gases covered by the Montreal Protocol. As a result, there are only 52 timeseries.
The files were derived using the code in this repository: https://github.com/iiasa/emissions_harmonization_historical. The filenames are composed of identifiers related to the processing of each of the different input data sources. To identify the exact meaning of these identifiers, please see the processing code in https://github.com/iiasa/emissions_harmonization_historical
Household air pollution health impact assessment for Nigeria
No full textThis dataset quantifies the household air pollution health impacts at the state level in Nigeria in 2018 to accompany the manuscript
An estimation of the health and climatic impacts of household biomass consumption across Nigeria in 2018
DOI 10.1088/2752-5309/adb87