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Among various bioreactors examined in anaerobic digestion and dark fermentation, UASB bioreactor has shown to be a promising alternative. However, mass transfer resistance and biomass washout have been the issues that reported as draw backs of the granular system in the literature. Another problem associated with such a system is its long start-up period as a result of biomass washout and long microbial granulation stage. In this paper, the results obtained from an UASFF bioreactor in methane (AD process) and hydrogen (DF process) production from POME, are presented to assess mass transfer of substrate into the granules and also study the role of internal packing used in the middle part of reactor in the process stability. The value of effectiveness factor, η, for AD and DF processes were calculated to be 0.96 and 0.94, respectively, indicating that there was no mass transfer resistance due to internal and/or external factors. The results showed that the packing material could retain biomass in the reactor and had outstanding contribution in the granulation enhancement. Its role as a supplementing treatment stage was more significant at low HRTs and up-flow velocities.

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Corruption has found very fertile ground in the health sector. Many studies demonstrate the negative relationship between sustainability and corruption. However, relatively little is known at this time about how to prevent corruption in healthcare organizations (HCOs), and thus to recover the important sustainability of the entire healthcare system. After noticing this gap in the literature, the authors’ aim in undertaking this study was twofold: first, to analyze the current state of knowledge about how Italian HCOs adopt corruption prevention plans in compliance with the National Plan issued by the National Anti-Corruption Authority; second, to identify some clusters of HCOs which represent different adoption patterns of corruption prevention interventions and to classify these HCOs. For these purposes, the authors studied 68 HCOs along 13 dimensions that characterized the corruption prevention plans. The empirical results showed that the HCOs were not fully compliant with the anti-corruption legislation. At the same time, the authors identified three clusters of HCOs with different patterns of anti-corruption prevention interventions. The clusters that adopted some specific interventions seemed to be more sustainable than others.

# 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.

Understanding the system of connections between societal contexts and policy outcomes in municipal governments provides important insights into how community sustainability happens, and why it happens differently in various communities. A growing body of research in recent years has focused on understanding the socio-economic characteristics of communities and cities that are recognized as policy leaders in sustainability. In this paper, we expand the focus beyond the leaders in sustainability as we apply a selection of socio-demographic influences of community sustainability to a large sample of U.S. communities using community classification analytics to identity a range of community types and levels of engagement with sustainability. Our typology presents an integrated and comprehensive perspective on the structure of community sustainability in the United States, highlighting key points of comparison between human capital factors such as population size and density, affluence, home ownership, and adoption of sustainability policy. The analysis provides new insights not only about community leaders in sustainability, but also communities with the civic and social capacity to do more, and the challenges that may inhibit sustainability efforts in others.

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).

The classical approach to load modeling is to divide the load by customer class and then identify and model the load components corresponding to each customer class. This work explores an alternative way to break down the load using readily available data. Namely, using historical usage data and historical weather data the load can be first divided into temperature-dependent and temperature-independent portions. A simple thermal model of the structure(s) served by the electrical circuit forms the theoretical and mathematical basis of this separation. During summer peaking conditions, the temperature-dependent load is generally composed of air conditioners, which must be modeled properly in order to analyze delayed voltage recovery or other dynamic phenomenon. Once the temperature-dependent fraction of the load has been characterized, the size of compressor, fan, and pump motors can be inferred by the customer class.

The hydraulic balance of heating network is considered as a pre-condition for the implementation of low temperature district heating (LTDH). Its imbalance result into high energy consumption and heat-losses in the network. In this study, a novel hydraulic model is presented which investigates hydraulic imbalance in the LTDH network, using real weather and hourly monitored operational heating data from an existing boiler based building. Analysis of delta t in space-heating system shows that the delta t is maximum when the outside air temperature is lowest and it decreases with increase in outside air temperature. Furthermore, the hydraulic imbalance is analysed for four different control scenarios with the aim to find an optimum scenario with minimum pumping power, energy consumption and heat-losses in the LTDH network. Results show that the hydraulic imbalance is due to the absence of flow-limiters and balancing valves on the return pipe and thermostatic radiator valves (TRVs) alone are unable to maintain hydraulic balance in the space-heating system of buildings. Moreover, the control scenario with variable flow-rate and fixed supply water temperature from the sub-station is found to be optimum. Compared to the constant flow-rate scenario, the pumping power, energy consumption and heat-losses in the LTDH network are reduced by approximately 2%, 63% and 14%, respectively.