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In Cameroon, as in other countries of the Congo basin region, policy processes and activities related to climate change have been hitherto geared mostly towards mitigation and related questions, with limited concern about adaptation issues. However, the increasing vulnerability of Cameroon to climate variability and change makes adaptation significant to its national climate-change policy. Nonetheless, it remains a challenge to make both adaptation and mitigation occupy the same policy space in Cameroon. This paper builds partly on studies carried out in two community forest carbon initiatives in the southern rainforest of Cameroon. It also argues, supported by existing literature on adaptation and mitigation, that mitigation activities have the potential to produce adaptation outcomes; a situation which avoids duplication of efforts and waste of financial and technical resources, if synergetic options are anticipated and planned. However, whether such integrated approaches succeed and are subsequently reflected in national-level climate policy depends on how actors across different sectors and at different levels engage and carry out their roles. The paper discusses these roles and how they can support each other in pursuing integrated initiatives – a context which is vital for Cameroon.

AbstractShipbuilding is an energy-intensive industrial sector that produces a significant amount of waste, pollution and air emissions. However, the International Maritime Organization concentrates only on reducing emissions during the operational phase. In order to completely phase out emissions from the shipping industry, a life-cycle approach must be taken. The study implemented the proposed transdisciplinary energy management framework in a Bangladeshi shipyard. The framework aims to support shipyard decision makers in making rational and optimized decisions to make shipyards sustainable, while maintaining good product quality and reducing relative cost. This is achieved by applying the Fuzzy Analytical Hierarchy Process and Fuzzy Order of Preference by Similarity to Ideal Solution methods to identify optimal solutions. In addition to making shipyards more sustainable, the framework can enhance both the business and socio-economic prospects of the shipyard and promote the reputation of the shipyard and improve its competitiveness and, in line with this, lead to the promotion of nationally determined contributions under the Paris Agreement for States. The implementation of the framework shows that the political and legal discipline, the social criteria and the implementation of ISO 14001 and cyber security were the most important criteria and options for the yard's decision makers.

Agricultural adaptation to climate change is critical for ensuring future food security. Social capital is important for climate change adaptation, but institutions and social networks at multiple scales (e.g., household, community, and institution) have been overlooked in studying agricultural climate change adaptation. We combine data from 13 sites in 11 low-income countries in East Africa, West Africa, and South Asia to explore how multiple scales of social capital relate to household food security outcomes among smallholder farmers. Using social network theory, we define three community organizational social network types (fragmented defined by lack of coordination, brokered defined as having a strong central actor, or shared defined by high coordination) and examine household social capital through group memberships. We find community and household social capital are positively related, with higher household group membership more likely in brokered and shared networks. Household group membership is associated with more than a 10% reduction in average months of food insecurity, an effect moderated by community social network type. In communities with fragmented and shared organizational networks, additional household group memberships is associated with consistent decreases in food insecurity, in some cases up to two months; whereas in brokered networks, reductions in food insecurity are only associated with membership in credit groups. These effects are confirmed by hierarchical random effects models, which control for demographic factors. This suggests that multiple scales of social capital—both within and outside the household—are correlated with household food security. This social capital may both be bridging (across groups) and bonding (within groups) with different implications for how social capital structure affects food security. Efforts to improve food security could recognize the potential for both household and community level social networks and collaboration, which further research can capture by analyzing multiple scales of social capital data.

# Data from: Blue Carbon Benefits from Global Saltmarsh Restoration [https://doi.org/10.5061/dryad.pc866t1vp](https://doi.org/10.5061/dryad.pc866t1vp) This README file was generated on 12th September 2023 by Victoria Mason. **Title of Dataset:** Blue carbon benefits from global saltmarsh restoration. **Author information:** * Victoria G. Mason, Bangor University/Royal Netherlands Institute for Sea Research (NIOZ), victoria.mason@nioz.nl (*Corresponding author*) * Annette Burden, UK Centre for Ecology & Hydrology * Graham Epstein, University of Exeter/University of Victoria * Lucy L. Jupe, Wildfowl & Wetlands Trust * Kevin A. Wood, Wildfowl & Wetlands Trust * Martin W. Skov, Bangor University **Summary of dataset:** These data include all data which were extracted or derived from relevant studies on global saltmarsh carbon storage and greenhouse gas flux. Data were obtained following screening of 29,182 peer reviewed published studies for relevant data, which were then extracted from 431 studies via text, tables and figures. We then used a meta-analysis to assess drivers of variation in global saltmarsh and greenhouse gas flux. * Date of literature search: 21st January 2022. * Date of data extraction: February - March 2022 * Literature search conducted via: Scopus + Web of Science ## Description of the data and file structure The contents of these data include: * **Full dataset (Aug2023\_GlobalCarbonReview\_FullDataset.xls):** All data extracted from 431 relevant studies and used in analysis. This includes a title page, metadata (with descriptions of column headers) and the full dataset. Response variables included: * Carbon stock * Percentage organic carbon * Bulk density * Sediment accretion rate * Carbon accumulation rate * Carbon dioxide flux * Methane flux * Nitrous oxide flux **\- Data on each included study \(Aug2023\_GlobalCarbonReview\_IncludedStudies\.xls\):** List of each study included in the final analysis, and its metadata. This includes a title page, metadata (with descriptions of column headers) and the dataset. All data include standard deviation (SD) and n (number of replicates) where provided by the original study, which were used to calculate Hedge's *g* effect sizes reported in the subsequent study. | Frequently used abbreviations: | | | ------------------------------ | --- | | C | carbon | | OC | organic carbon | | GHG | greenhouse gas | | bd | bulk density (g cm-3 dry sediment) | | Y/N | yes/no | | ref | reference | | lat | latitude | | long | longitude | | rest | restoration | | prec | precipitation | | sal | salinity | | acc | accretion | | resp | respiration | | SR | soil respiration (appears for CO2 flux) | | ER | ecosystem respiration (appears for CO2 flux) | | n | number of samples included in mean/standard deviation | | sd | standard deviation | All abbreviations used are outlined in the ‘Metadata’ worksheet of .xls files. **Data specific information for Aug2023\_GlobalCarbonReview\_FullDataset.xls:** Number of variables: 88 Number of cases/rows: 2055 Variables included: See 'Metadata' sheet **Data specific information for** **Aug2023\_GlobalCarbonReview\_IncludedStudies.xls:** Number of variables: 47 Number of cases/rows: 431 Variables included: See 'Metadata' sheet **Empty cells:** Cells are empty where data on that variable were not provided by the original study from which they were extracted. For example, where a study provided data on carbon stock variables, but not greenhouse gas flux. For further details, see the 'Metadata' sheets of each file. ## Sharing/Access information These data are available via Dryad, and described in ‘Blue Carbon Benefits from Global Saltmarsh Restoration’, in Global Change Biology. **DOI:** 10.1111/gcb.16943 Data were extracted from 431 published peer reviewed articles, the details of which can be found in the attached datasheets. Coastal saltmarshes are found globally, yet are 25–50% reduced compared to their historical cover. Restoration is incentivised by the promise that marshes are efficient storers of ‘blue’ carbon, although the claim lacks substantiation across global contexts. We synthesised data from 431 studies to quantify the benefits of saltmarsh restoration to carbon accumulation and greenhouse gas uptake. The results showed global marshes store approximately 1.41–2.44 Pg carbon. Restored marshes had very low greenhouse gas (GHG) fluxes and rapid carbon accumulation, resulting in a mean net accumulation rate of 64.70 t CO2e ha-1 y-1. Using this estimate and potential restoration rates, we find saltmarsh regeneration could result in 12.93–207.03 Mt CO2e accumulation per year, offsetting the equivalent of up to 0.51% global-energy-related CO2 emissions – a substantial amount, considering marshes represent <1% of Earth’s surface. Carbon accumulation rates and GHG fluxes varied contextually with temperature, rainfall and dominant vegetation, with the eastern costs of the USA and Australia being particular hotspots for carbon storage. Whilst the study reveals paucity of data for some variables and continents, suggesting a need for further research, the potential for saltmarsh restoration to offset carbon emissions is clear. The ability to facilitate natural carbon accumulation by saltmarshes now rests principally on the action of the management-policy community and on financial opportunities for supporting restoration.

Abstract. Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement. This study provides a consolidated synthesis of CH4 and N2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27+UK). We integrate recent emission inventory data, ecosystem process-based model results, and inverse modelling estimates over the period 1990–2018. BU and TD products are compared with European National GHG Inventories (NGHGI) reported to the UN climate convention secretariat UNFCCC in 2019. For uncertainties, we used for NGHGI the standard deviation obtained by varying parameters of inventory calculations, reported by the Member States following the IPCC guidelines recommendations. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model specific uncertainties when reported. In comparing NGHGI with other approaches, a key source of bias is the activities included, e.g. anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011–2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 Tg CH4 yr−1 (EDGAR v5.0) and 19.0 Tg CH4 yr−1 (GAINS), consistent with the NGHGI estimates of 18.9 ± 1.7 Tg CH4 yr−1. TD total inversions estimates give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher resolution atmospheric transport models give a mean emission of 28.8 Tg CH4 yr−1. Coarser resolution global TD inversions are consistent with regional TD inversions, for global inversions with GOSAT satellite data (23.3 Tg CH4yr−1) and surface network (24.4 Tg CH4 yr−1). The magnitude of natural peatland emissions from the JSBACH-HIMMELI model, natural rivers and lakes emissions and geological sources together account for the gap between NGHGI and inversions and account for 5.2 Tg CH4 yr−1. For N2O emissions, over the 2011–2015 period, both BU approaches (EDGAR v5.0 and GAINS) give a mean value of anthropogenic emissions of 0.8 and 0.9 Tg N2O yr−1 respectively, agreeing with the NGHGI data (0.9 ± 0.6 Tg N2O yr−1). Over the same period, the average of the three total TD global and regional inversions was 1.3 ± 0.4 and 1.3 ± 0.1 Tg N2O yr−1 respectively, compared to 0.9 Tg N2O yr−1 from the BU data. The TU and BU comparison method defined in this study can be operationalized for future yearly updates for the calculation of CH4 and N2O budgets both at EU+UK scale and at national scale. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4288969 (Petrescu et al., 2020).

Summary Past climatic fluctuations have played a major role in shaping the current plant biodiversity. Although harbouring an exceptional biota, oceanic islands have received little attention in studies on species demographic history and past vegetation patterns. We investigated the impact of past climatic changes on the effective population size of a tree (Coffea mauritiana) that is endemic to Reunion Island, located in the south‐western Indian Ocean (SWIO). Demographic changes were inferred using summary statistics calculated from genomic data. Using ecological niche modelling and the current distribution of genetic diversity, the paleodistribution of the species was also assessed. A reduction in the effective population size of C. mauritiana during the last glaciation maximum was inferred. The distribution of the species was reduced on the western side of the island, due to low rainfall. It appeared that a major reduction in rainfall and a slight temperature decrease prevailed in the SWIO. Our findings indicated that analyses on the current patterns of intraspecific genetic variations can efficiently contribute to past climatic changes characterisation in remote islands. Identifying area with higher resilience in oceanic islands could provide guidance in forest management and conservation faced to the global climate change.

As a relatively mature technology, biomass molded fuel (BMF) is widely used in distributed and centralized heating in China and has received considerable government attention. Although many BFM incentive policies have been developed, decreased domestic traditional fuel prices in China have caused BMF to lose its economic viability and new policy recommendations are needed to stimulate this industry. The present study built a regionalized net present value (NPV) model based on real production process simulation to test the impacts of each policy factor. The calculations showed that BMF production costs vary remarkably between regions, with the cost of agricultural briquette fuel (ABF) ranging from 86 US dollar per metric ton (USD/t) to 110 (USD/t), while that of woody pellet fuel (WPF) varies from 122 USD/t to 154 USD/t. The largest part of BMF’s cost composition is feedstock, which accounts for up 50%–60% of the total; accordingly a feedstock subsidy is the most effective policy factor, but in consideration of policy implementation, it would be better to use a production subsidy. For ABF, the optimal product subsidy varies from 26 USD/t to 57 USD/t among different regions of China, while for WPF, the range is 36 USD/t to 75 USD/t. Based on the data, a regional BMF development strategy is also proposed in this study.

Purpose This study aims to consider environmental sustainability, a global challenge under the preview of sustainable development goals, highlighting the significance of knowledge economy in attaining sustainable aggregate demand behavior globally. For this purpose, 155 countries that have data available from 1995 to 2021 were selected. The purpose of selecting these countries is to test the global responsibility of the knowledge economy to attain environmental sustainability. Design/methodology/approach Results are estimated with the help of panel quantile regression. The empirical existence of aggregate demand-based environmental Kuznets curve (EKC) was tested using non-linear tests. Moreover, principal component analysis has been incorporated to construct the knowledge economy index. Findings U-shaped aggregate demand-based EKC at global level is validated. However, environmental deterioration increases with an additional escalation after US$497.945m in aggregate demand. As a determinant, the knowledge economy is reducing CO2 emissions. The knowledge economy has played a significant role in global responsibility, shifting the EKC downward and extending the CO2 reduction phase for every selected country. Further, urbanization, energy intensity, financial development and trade openness significantly deteriorate the environmental quality. Originality/value This study contains the empirical existence of aggregate demand-based EKC. The role of the knowledge economy is examined through an index which is calculated by using four pillars of the knowledge economy (technology, innovations, education and institutions). This study is based on a combined panel of all the countries for which the data was available.