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Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.AerChemMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MPI-ESM1.2-HAM climate model, released in 2017, includes the following components: aerosol: HAM2.3, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), atmosChem: sulfur chemistry (unnamed), land: JSBACH 3.20, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the ETH Zurich, Switzerland; Max Planck Institut fur Meteorologie, Germany; Forschungszentrum Julich, Germany; University of Oxford, UK; Finnish Meteorological Institute, Finland; Leibniz Institute for Tropospheric Research, Germany; Center for Climate Systems Modeling (C2SM) at ETH Zurich, Switzerland (HAMMOZ-Consortium) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 km.

Earth’s rapidly changing climate is particularly evident in the Arctic. Outside of the Arctic, the emergence of large-sample catchment databases has transformed science from an emphasis on local case-studies towards more systematic insights into drivers of watershed functioning. Here we present an integrated pan-ARctic CAtchments summary DatabasE (ARCADE) of >40,000 catchments, including small and medium-sized watersheds, draining into the Arctic Ocean. These watersheds, delineated at a high-resolution (90 m), are provided with 103 geospatial, environmental, climatic, and physiographic catchment properties. ARCADE is the first aggregated database of pan-Arctic river catchments that includes small watersheds at a high resolution. These small catchments are experiencing the greatest climatic warming while also storing large quantities of soil carbon in landscapes that are especially prone to degradation of permafrost (i.e., ice wedge polygon terrain) and associated hydrological regime shifts. The publication of this database is a necessary step toward more integrated monitoring of the pan-Arctic watershed.

We designed a controlled laboratory experiment to investigate the responses of a subarctic liverwort-based (Anthelia juratzkana) BSC from the south of Iceland to different levels of temperature, moisture and light. We studied how these environmental factors affect the capacity of subarctic BSC to fix N, and whether these responses were linked to changes in the abundance of N fixers and/or to structural changes in the BSC microbial communities. 1. Sample collection In September 2018 we collected BSC from a site adjacent to the Climate Research Unit at Subarctic Temperatures (CRUST) experiment (Salazar et al., in progress), near Landmannahellir, Iceland (64°02' N, 19°13' W; 590 m.a.s.l.). Mean annual temperature and precipitation at the site are ca. 5 °C and 1500 mm, respectively. Surface cover in this area is primarily liverwort-based BSC (ca. 50%), followed by mosses (ca. 30%) and Salix herbacea dwarf willow (ca. 20%), on an andosol/vitrisol substratum. We randomly collected eight BSC blocks (i.e. replicates) of 13x16 cm2 and ca. 5 cm deep (Figure S1a in article). Blocks were separated by at least 10 meters. Since the focus of this study is on BSC, patches of moss or vascular plants were avoided. We transported (approx. 5 h) the BSC blocks in coolers with ice packs and stored them in a dark room at 5 °C for 2 to 5 weeks while we performed the analyses described below. We kept wet paper towels inside the coolers to prevent desiccation. We subsampled BSC disks of 5 cm diameter and 1.5 cm depth out of the 13x16x5 cm3 BSC blocks (Figure S1c) for N fixation analyses (section 3). Then, we subsampled BSC disks of 1.5 cm diameter, 1.5 cm depth from each 5 cm diameter BSC disk, for Chl a (section 4) and cyanobacteria and liverwort cover (section 5) analyses and for DNA extractions (section 6). 2. Experimental design and environmental treatments We studied the effects of temperature, moisture and light on N fixation and the microbial community structure. For this, we conducted a factorial experiment (4 x 2 x 2) with four levels of temperature: 10, 15, 20 and 25 °C; two levels of moisture: ca. 75% (close to moisture at the moment of sampling) and 100% (saturated); and two levels of light ca. 2 μmol m-2 s-1 (low intensity) and ca. 90 μmol m-2 s-1 (high intensity; Figure S2 in article). Light was available all the time (i.e. we did not set day/night cycles), to simulate conditions similar to those in the sampling site during the summer. Temperature and light treatments were set in a growth chamber (Termaks series 8000, Bergen, Norway), and monitored hourly with temperature/light loggers (HOBO Pendant® MX Temperature/Light Data Logger, MX2202, Onset, Bourne, MA, USA). Levels of these environmental variables were selected within ranges commonly experienced by BSC at the sampling site (between ca. >0 and 25°C; 0 and >100 μmol m-2 s-1; and between dryness for short periods of time during the summer, and saturation e.g. after the winter snow is melted; unpublished observations) and comparable ecosystems (e.g. a mesic-dry heath in Greenland; Rousk et al., 2018). We compared ambient vs. saturation moisture levels because mean annual precipitation in subarctic and arctic regions is projected to increase in the coming decades (IPCC, 2021). The maximum temperatures in our experimental design were selected based on peaks of warming (measured at the soil surface) recorded during previous growing seasons (unpublished data). In this sense, our high temperature treatment should simulate BSC responses to heat waves at the study site, under different moisture and light conditions. Average temperature and light intensity inside the jars were 11.1 ± 0.7, 16.5 ± 0.7, 21.5 ± 0.7 and 26.6 ± 0.9 °C (2 loggers x 2 light levels; n = 4) and 2.3 ± 0.04 and 88.0 ± 1.6 μmol m-2 s-1 (2 loggers x 4 temperature levels; n = 8) respectively (Figure S2a and b in article). Temperature levels inside the jars were slightly higher than temperatures set in the growing chamber due to a greenhouse effect. To create a saturation level in the moisture treatment, we wetted each sample with an excess of deionized water and waited for approximately one minute until it stopped dripping. Moisture was maintained between analyses by placing wet towels in the coolers stored in the cold, dark room. After environmental treatments and N fixation measurements (see following section), we oven dried (60 °C, 24 h) BSC disks to estimate the dried weight of the samples, and to prepare them for chlorophyll a analysis and DNA extraction. Average moisture content was 75.5 ± 2.4 and 107.2 ± 2.3 % (Figure S3c in article). 3. N fixation under controlled temperature, moisture and light conditions We estimated N fixation rates with the Acetylene Reduction Assay (ARA; Hardy et al., 1968). We used eight 5-cm subsampled disks (i.e. replicates) per combination of temperature and moisture treatments. Thus, each temperature-specific ARA analysis was composed of a total of 16 samples with two levels of moisture, eight saturated and eight unsaturated, plus controls with acetylene, ethylene and air. The BSC disks were weighed (for further water content analysis) and placed in 350 mL glass jars with rubber septa in the lids (Figure S1c in article). These jars were then placed in an environmental chamber (Termaks series 8000, Bergen, Norway) at fixed temperature and light conditions. We acclimated the samples to each combination of temperature and light for 24 h. We then manually aerated the jars for a few seconds, closed the jars tightly and replaced 10% of the headspace with acetylene (except in jars used as ethylene and air controls). We incubated the jars at the set temperature and light conditions for 24 h. Then, we collected 22 mL of gas from each jar and analyzed it using a Clarus 400 gas chromatograph (PerkinElmer Ltd., Beaconsfield, UK) equipped with an automatic split/splitless injector and a flame ionization detector (FID), and an Elite-Alumina column (30 m, 0.53 mm; PerkinElmer Ltd., Beaconsfield, UK). At the end of each 48 h acclimation-incubation period, we manually aerated the samples and started a new acclimation-incubation at a different light (but same temperature) condition. To control for a possible effect of the storing time in the cold room, we randomized the order of the temperatures for the incubations. We incubated first samples (8 replicates at ca. 75% and 8 at 100% moisture content) at 20°C, then at 10, 25 and 15 °C. Also, to control for a possible cumulative effect between light levels, we switched the order of the light levels for each temperature treatment. For example, for samples incubated at 20°C we measured ethylene production first at low light (48 h) and then at high light (48 h). For the next quarter of the samples, incubated at 10°C, we measured ethylene production first at high light (48 h) and then at low light (48 h), and so on, for the other two temperature treatments. Since ARA is a non-destructive method, we were able to estimate N fixation rates on the same sample at different light treatments. For the rest of the analysis, based on destructive methods (see details below), we measured BSC responses to moisture and temperature. 4. Cyanobacteria and liverwort cover on BSC We estimated the cover of cyanobacteria and liverwort (Anthelia juratzkana; Figure S1b in article) on the BSC surface by epifluorescence microscopy (Figure S3 in article; similar to Lan et al., 2019). After ARA measurements, BSC samples were stored in a dark room at 5 °C for 1 to 4 days. Plant and cyanobacterial growth was assumed to be minimal under these conditions. From each 5 cm diameter BSC disk (Figure S1c), we subsampled a 1.5 cm diameter BSC disk and imaged the plant (liverwort) chlorophyll using a Leica DM6000B fluorescent microscope (Leica, Heerbrugg Switzerland) equipped with an I3 filter cube (Ex 450/90, Di 510, Em 515), and the cyanobacterial phycocyanin with a TX2 filter cube (Ex 560/40, Di 595, Em 630/30). Multiple fields of view were measured using both filter cubes and stitched together to form an image of 1x1 cm of BCS surface (Figure S3) using the Leica software. Images were analyzed in ImageJ/Fiji (Collins, 2007; Schindelin et al., 2012), and estimates of cyanobacterial and plant covers calculated as percentage of BSC surface cover. We did not subsample BSC disks between light levels, but rather used samples that were exposed to low light for 48 h (24 h acclimation plus 24 h ARA) and then to high light for another 48 h, or vice versa. Therefore, the treatments in this part of our analysis include temperature and moisture, but not light. 5. Chlorophyll a We estimated Chl a content as an indicator of net photosynthetic rate in BSC (Yan-Gui et al., 2011). Similar to our BSC cover analysis, we subsampled a 1.5 cm diameter, 1.5 cm depth BSC disk from each 5 cm diameter BSC disk (Figure S1c in article) used for ARA analysis. We dried subsamples at 60 °C for 24 h, extracted Chl a using DMSO (65 °C, 90 min) and then estimated Chl a content by spectrophotometry (665 and 750 nm; Genesys 20, Thermo Scientific, Waltham, MA), as in Caesar et al. (2018): Chl a µg = (11.9035 × (A665 − A750)) × S (1) Chl a [mg × m−2] = Chl a [µg] / (AR × 1000) (2) Where S is volume of solvent, AR is area (in m-2) and A665 and A750 are absorbances at 665 and 750 nm, respectively. As for BSC cover, treatments in this part of our analysis included temperature and moisture, but not light. 6. DNA extraction and analysis Immediately after the fluorescence microscopy measurements (section 4), we dried (60 °C, 24 h) and ground (1 min, Mini bead beater 16; Biospec products) the 1.5 cm diameter, 1.5 cm depth BSC disks used for the cyanobacteria/liverwort cover analysis and stored them at -80 °C for up to four months for DNA extraction. We pooled together replicates in pairs, combining them in equal weight parts (125 mg each for a total of 250 mg). We used the PowerSoil® DNA extraction kit (MOBIO/Qiagen), and shotgun sequencing approaches and analyses via the alignment-free fast taxonomic annotation tool Kraken2 (Wood and Langmead, 2019) with the Kraken2 Refseq Standard plus protozoa and fungi database and the web-based pipeline Kaiju (Menzel et al., 2016). We estimated relative abundance of microbial groups using Kraken2 and fungal:bacteria ratios based on Kaiju taxonomic assignments (see sections below). After quality filtering the raw reads using Trim Galore microbial metagenome functional profiling was performed using HUMAnN 3 (Beghiji et al., 2021). For the functional annotation, UniRef50 (Suzek et al., 2015), KEGG (Kanehisa and Goto, 2000), and BioCyc databases (Karp et al., 2019) were used. As for BSC cover and Chl a, treatments for this part of our analysis included temperature and moisture but not light. We characterized microbial communities only at two temperature levels: 10 and 20 °C, which showed significant differences in N fixation and cyanobacterial cover (see Results in article) 7. Fungal:bacterial ratios Fungi and bacteria decompose organic matter at different rates, which affects the N and C biogeochemistry of substrates like BSC. To study potential effects of the environment on the biogeochemistry of BSC via differential effects on fungi and bacteria, we estimated fungal:bacterial ratios. We calculated fungal:bacterial ratios based on numbers of gene copies assigned to each group by Kaiju. 8. Microbial community and statistical analyses Microbial community analyses were performed using the microeco package in R (version 3.5.0). We first investigated the most important Orders for classifying samples into different treatments using a random forest approach. We then conducted an ANOVA test followed by a Tukey’s HSD test, α<0.05, as well as Pearson correlations and PERMANOVA analyses between the Bray–Curtis dissimilarity score and moisture content. Finally, we conducted a Distance-based redundancy analysis (dbRDA) to assess the effects of the abiotic treatments on the top most abundant bacterial orders. To identify distinctive molecular pathways between treatments, we performed a linear discriminant analysis (LDA) effect size (LEfSe) analysis as implemented in the microeco package, then we selected the functions with a LDA score ≥ 3.5. We used a mixed model (lmer function in R, version 3.6.1) to analyze the fixed effects of environmental manipulations on N fixation, while accounting for the random effect of measurements on the same sample at two light levels. For the other response variables, which varied in response to temperature and moisture but not light, we used fixed models (lm function in R, version 3.6.1). We compared models based on the Bayesian Information Criterion (BIC; Figure S4 in article). Together, Biological Soil Crust (BSC) and other cryptogamic groundcovers can contribute up to half of the global nitrogen (N) fixation. BSC also stabilizes the soil (reducing erosion and dust emissions), fixes carbon (C), retains moisture, and acts as a hotspot of microbial diversity and activity. Much of the knowledge about how climate change is affecting the composition and functioning of BSC comes from hot arid and semiarid regions. The comparatively smaller body of research on BSC from cold and mesic environments has been primarily observational, for example along chronosequences after a glacier retreat. Few studies have experimentally investigated the effects of the environment on BSC from high latitudes. Such experiments allow unraveling of relationships at a resolution that can only be achieved by controlling for confounding factors. We measured short-term (2-4 days) responses of a liverwort-based (Anthelia juratzkana) BSC from the south of Iceland to a range of temperature, moisture and light conditions. Warming increased N fixation rates, especially when moisture was at a saturation level, and only when light was not limiting. A correlation analysis suggests that increases in N fixation rates were linked to cyanobacterial abundance on the BSC surface and to the rates of their metabolic activity. Warming and moisture changes also induced compositional and structural modification of the bacterial community, with consequences at the functional level. In contrast to many observations on BSC from hot drylands, the BSC from our cold and mesic study site is more limited by low temperature and light than by moisture. Our findings show possible ways in which BSC from cold and mesic ecosystems can respond to short-term manifestations of climate change, such as increasingly frequent heat waves. We used phyloseq and metaphlan2 to open tsv files.Other options include: QIIME MG-RAST PICRUSt Mothur phyloseq MEGAN VAMPS metagenomeSeq Phinch RDP Classifier USEARCH PhyloToAST EBI Metagenomics GCModeller MetaPhlAn 2 More about this in https://biom-format.org/

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MPI-ESM1.2-HAM climate model, released in 2017, includes the following components: aerosol: HAM2.3, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), atmosChem: sulfur chemistry (unnamed), land: JSBACH 3.20, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the ETH Zurich, Switzerland; Max Planck Institut fur Meteorologie, Germany; Forschungszentrum Julich, Germany; University of Oxford, UK; Finnish Meteorological Institute, Finland; Leibniz Institute for Tropospheric Research, Germany; Center for Climate Systems Modeling (C2SM) at ETH Zurich, Switzerland (HAMMOZ-Consortium) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 km.

The EU has long pursued relatively ambitious climate and energy policies, often against the backdrop of what has been termed the EU ‘polycrisis’. This paper introduces a special issue which seeks t...

Ambitious international targets are being developed to protect and restore biodiversity under the Convention on Biological Diversity's post-2020 Global Biodiversity Framework and the European Union's Green Deal. Yet, the land system consequences of meeting such targets are unclear, as multiple pathways may be able to deliver on the set targets. This paper introduces a novel scenario approach assessing the plural implementations of these targets. The Nature Futures Framework (NFF) developed by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services aims to illustrate the different, positive ways in which society can value nature. It therefore offers a lens through which the spatial implementation of sustainability targets may be envisioned. We used CLUMondo, a spatially explicit model, to simulate plural land system scenarios for Europe for 2050. The model builds on current land system representations of Europe and explores how and where sustainability targets can be implemented under projected population trends and commodity demands. We created three different scenarios in which the sustainability targets are met, each representing an alternative, normative view on nature as represented by the NFF, favoring land systems providing strong climate regulation (Nature for Society), species conservation (Nature for Nature), or agricultural heritage features (Nature as Culture). Our results show that, irrespective of the NFF view, meeting sustainability targets will require European land systems to drastically change, as natural grasslands and forests are forecast to expand while productive areas are projected to undergo a dual intensification and diversification trajectory. Despite each NFF perspective showcasing a similar direction of change, 20% of Europe's land area will differ based on the adopted NFF perspective, with hotspots of disagreement identified in eastern and western Europe. These simulations go beyond existing scenario approaches by not only depicting broad societal developments for Europe, but also by quantifying the land system synergies and trade-offs associated with alternative, archetypal, interpretations and values of how nature may be managed for sustainability. This quantification exemplifies a means towards constructive dialogue, on the one hand by acknowledging areas of contention, and bringing such issues to the fore, and on the other by highlighting points of convergence in a vision for a sustainable Europe.

Abstract Coal energy landscapes have changed dramatically over the last decades, including geographic shifts in production and consumption, technological changes that have reduced labour demand and led to relatively new mining practices (e.g. invasive mountain-top approaches), changed economic footprints, a shutdown of capacities or a complete end of mining in many regions with massive impacts on regional and local economies, community well-being, social capital, et cetera. Then the Covid-19 pandemic and Russia´s invasion of Ukraine have fundamentally affected the global economy, disrupted energy markets, and shattered existing estimates about development trends, challenging the progress and speed of the low-carbon energy transition and coal phase-out. This article provides a brief reflection on the changing landscapes of coal and their possible futures, and serves as an introduction to the Special Issue of Moravian Geographical Reports on “The death of coal in the energy transition? Regional perspectives”.

Le changement d'utilisation des terres/de couverture est la principale cause de dégradation des écosystèmes terrestres. Cependant, ses impacts seront exacerbés en raison du changement climatique et de la croissance démographique, entraînant une expansion agricole en raison de la demande accrue de denrées alimentaires et de la baisse des rendements agricoles dans certaines zones tropicales. Les stratégies internationales visant à atténuer les impacts du changement climatique et du changement du couvert terrestre sont difficiles dans les régions en développement. Cette étude vise à évaluer des alternatives pour minimiser les impacts de ces menaces dans le cadre de trajectoires socio-économiques, dans l'une des régions les plus biologiquement riches du Guatemala et du Mexique. Cette étude est située dans le bassin versant d'Usumacinta, une région transfrontalière qui partage une histoire commune, avec des propriétés biophysiques et des contraintes économiques similaires qui ont conduit à d'importants changements dans l'utilisation/la couverture des terres. Pour comprendre les impacts sur la déforestation et les émissions de carbone des différentes pratiques de gestion des terres, nous avons développé trois scénarios (1) : le statu quo (BAU), (2) un scénario de réduction des émissions visant à réduire la déforestation et la dégradation (REDD+) et (3) zéro déforestation à partir de 2030 sur la base des engagements internationaux. Nos résultats suggèrent que d'ici 2050, la couverture terrestre naturelle pourrait réduire de 22,3 et 12,2% son étendue dans les scénarios BAU et REDD +, respectivement par rapport à 2012. Cependant, le scénario zéro déforestation montre que d'ici 2050, il serait possible d'éviter de perdre 22,4 % du bassin versant boisé (1,7 million d'hectares) et d'en récupérer 5,9 % (0,4 million d'hectares). En termes de séquestration du carbone, les projets REDD + peuvent réduire les pertes de carbone dans la végétation naturelle, mais une politique de zéro déforestation peut doubler la séquestration du carbone produite par les projets REDD + uniquement. Cette étude montre que pour réduire les pressions sur les écosystèmes, en particulier dans les régions fortement marginalisées avec des migrations importantes, il est nécessaire de mettre en œuvre des politiques transfrontalières de gestion des terres qui intègrent également des stratégies de réduction de la pauvreté. El cambio en el uso/cobertura de la tierra es la principal causa de la degradación de los ecosistemas terrestres. Sin embargo, sus impactos se exacerbarán debido al cambio climático y al crecimiento de la población, impulsando la expansión agrícola debido a una mayor demanda de alimentos y menores rendimientos agrícolas en algunas áreas tropicales. Las estrategias internacionales destinadas a mitigar los impactos del cambio climático y el cambio en la cobertura del uso de la tierra son un desafío en las regiones en desarrollo. Este estudio tiene como objetivo evaluar alternativas para minimizar los impactos de estas amenazas bajo trayectorias socioeconómicas, en una de las regiones biológicamente más ricas de Guatemala y México. Este estudio se encuentra en la cuenca de Usumacinta, una región transfronteriza que comparte una historia común, con propiedades biofísicas y limitaciones económicas similares que han llevado a grandes cambios en el uso/cobertura de la tierra. Para comprender los impactos en la deforestación y las emisiones de carbono de las diferentes prácticas de gestión de la tierra, desarrollamos tres escenarios (1): negocios como siempre (BAU), (2) un escenario de reducción de emisiones destinado a reducir la deforestación y la degradación (REDD+) y (3) cero deforestación a partir de 2030 en función de los compromisos internacionales. Nuestros resultados sugieren que para 2050, la cobertura natural de la tierra podría reducir el 22.3 y el 12.2% de su extensión bajo los escenarios BAU y REDD +, respectivamente, en comparación con 2012. Sin embargo, el escenario de deforestación cero muestra que para 2050, sería posible evitar la pérdida del 22,4% de la cuenca forestal (1,7 millones de ha) y recuperar el 5,9% (0,4 millones de hectáreas) de la misma. En términos de secuestro de carbono, los proyectos REDD + pueden reducir las pérdidas de carbono en la vegetación natural, pero una política de deforestación cero puede duplicar el secuestro de carbono producido solo por los proyectos REDD +. Este estudio muestra que para reducir las presiones sobre los ecosistemas, particularmente en regiones altamente marginadas con una migración significativa, es necesario implementar políticas transfronterizas de gestión de la tierra que también integren estrategias de alivio de la pobreza. Land-use/cover change is the major cause of terrestrial ecosystem degradation. However, its impacts will be exacerbated due to climate change and population growth, driving agricultural expansion because of higher demand of food and lower agricultural yields in some tropical areas. International strategies aimed to mitigate impacts of climate change and land use-cover change are challenging in developing regions. This study aims to evaluate alternatives to minimize the impacts of these threats under socioeconomic trajectories, in one of the biologically richest regions in Guatemala and Mexico. This study is located at the Usumacinta watershed, a transboundary region that shares a common history, with similar biophysical properties and economic constraints which have led to large land use/cover changes. To understand the impacts on deforestation and carbon emissions of different land-management practices, we developed three scenarios (1): business as usual (BAU), (2) a reducing emissions scenario aimed to reduce deforestation and degradation (REDD+), and (3) zero-deforestation from 2030 onwards based on the international commitments. Our results suggest that by 2050, natural land cover might reduce 22.3 and 12.2% of its extent under the BAU and REDD + scenarios, respectively in comparison with 2012. However, the zero-deforestation scenario shows that by 2050, it would be possible to avoid losing 22.4% of the forested watershed (1.7 million ha) and recover 5.9% (0.4 million hectares) of it. In terms of carbon sequestration, REDD + projects can reduce the carbon losses in natural vegetation, but a zero-deforestation policy can double the carbon sequestration produced by REDD + projects only. This study shows that to reduce the pressures on ecosystems, particularly in regions highly marginalized with significant migration, it is necessary to implement transboundary land-management policies that also integrate poverty alleviation strategies. استخدام الأراضي/تغيير الغطاء هو السبب الرئيسي لتدهور النظام الإيكولوجي الأرضي. ومع ذلك، ستتفاقم آثاره بسبب تغير المناخ والنمو السكاني، مما يؤدي إلى التوسع الزراعي بسبب ارتفاع الطلب على الغذاء وانخفاض الغلة الزراعية في بعض المناطق الاستوائية. تشكل الاستراتيجيات الدولية الرامية إلى التخفيف من آثار تغير المناخ وتغير استخدام الأراضي تحدياً في المناطق النامية. تهدف هذه الدراسة إلى تقييم البدائل لتقليل آثار هذه التهديدات في إطار المسارات الاجتماعية والاقتصادية، في واحدة من أغنى المناطق بيولوجيًا في غواتيمالا والمكسيك. تقع هذه الدراسة في مستجمع مياه أوسوماسينتا، وهي منطقة عابرة للحدود تشترك في تاريخ مشترك، مع خصائص فيزيائية حيوية مماثلة وقيود اقتصادية أدت إلى تغييرات كبيرة في استخدام الأراضي/تغطيتها. لفهم تأثيرات ممارسات إدارة الأراضي المختلفة على إزالة الغابات وانبعاثات الكربون، وضعنا ثلاثة سيناريوهات (1): العمل كالمعتاد (BAU)، (2) سيناريو خفض الانبعاثات الذي يهدف إلى الحد من إزالة الغابات وتدهورها (REDD+)، و (3) إزالة الغابات الصفرية اعتبارًا من عام 2030 فصاعدًا بناءً على الالتزامات الدولية. تشير نتائجنا إلى أنه بحلول عام 2050، قد يقلل الغطاء الأرضي الطبيعي بنسبة 22.3 و 12.2 ٪ من مداه في إطار سيناريو العمل الاعتيادي وسيناريو خفض الانبعاثات الناجمة عن إزالة الغابات وتدهورها في البلدان النامية، على التوالي مقارنة بعام 2012. ومع ذلك، يُظهر سيناريو إزالة الغابات الصفرية أنه بحلول عام 2050، سيكون من الممكن تجنب فقدان 22.4 ٪ من مستجمعات المياه الحرجية (1.7 مليون هكتار) واستعادة 5.9 ٪ (0.4 مليون هكتار) منها. من حيث عزل الكربون، يمكن لمشاريع خفض الانبعاثات الناجمة عن إزالة الغابات وتدهورها في البلدان النامية أن تقلل من خسائر الكربون في الغطاء النباتي الطبيعي، ولكن سياسة إزالة الغابات الصفرية يمكن أن تضاعف عزل الكربون الناتج عن مشاريع خفض الانبعاثات الناجمة عن إزالة الغابات وتدهورها في البلدان النامية فقط. تُظهر هذه الدراسة أنه للحد من الضغوط على النظم الإيكولوجية، لا سيما في المناطق المهمشة للغاية مع الهجرة الكبيرة، من الضروري تنفيذ سياسات إدارة الأراضي العابرة للحدود التي تدمج أيضًا استراتيجيات التخفيف من حدة الفقر.

The increasing demand for energy and commodities has led to escalating greenhouse gas emissions, the chief of which is represented by carbon dioxide (CO2). Blue hydrogen (H2), a low-carbon hydrogen produced from natural gas with carbon capture technologies applied, has been suggested as a possible alternative to fossil fuels in processes with hard-to-abate emission sources, including refining, chemical, petrochemical and transport sectors. Due to the recent international directives aimed to combat climate change, even existing hydrogen plants should be retrofitted with carbon capture units. To optimize the process economics of such retrofit, it has been proposed to remove CO2 from the pressure swing adsorption (PSA) tail gas to exploit the relatively high CO2 concentration. This study aimed to design and numerically investigate a vacuum pressure swing adsorption (VPSA) process capable of capturing CO2 from the PSA tail gas of an industrial steam methane reforming (SMR)-based hydrogen plant using NaX zeolite adsorbent. The effect of operating conditions, such as purge-to-feed ratio and desorption pressure, were evaluated in relation to CO2 purity, CO2 recovery, bed productivity and specific energy consumption. We found that conventional cycle configurations, namely a 2-bed, 4-step Skarstrom cycle and a 2-bed, 6-step modified Skarstrom cycle with pressure equalization, were able to concentrate CO2 to a purity greater than 95% with a CO2 recovery of around 77% and 90%, respectively. Therefore, the latter configuration could serve as an efficient process to decarbonize existing hydrogen plants and produce blue H2.