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Climate change and human activities are two major drivers of grasslands degradation. Understanding the vulnerability of grasslands to both drives is of great importance for grassland conservation. This research established a vulnerability assessment model with historical and future the Normalized Difference Vegetation Index (NDVI), which was predicted by an optimized spatiotemporal NDVI prediction model, and then examined the vulnerability of grasslands under climate change and human activities in Gannan Prefecture on the north-eastern Qinghai-Tibet Plateau. Our results show that Gannan grasslands would show a vulnerability pattern of higher in the west and lower in the east under climate change and human activities. More than 46 % and 17 % of the region will become highly and medium vulnerable areas in the future, mainly concentrated in Maqu, Luqu and Xiahe counties in the west, southwest and northwest of Gannan. Specifically, the vulnerability is the lowest under the future climate scenario of moderate carbon emissions (i.e. RCP 4.5). Land use types such as forest land, unutilized land and cultivated land conversion to grassland could partially offset the vulnerability mainly caused climate change, while the conversion of grassland to unutilized land, forest land and cultivated land would increase the vulnerability of grassland. Our results would help to deepen the understanding of the patterns and main drivers of Gannan grasslands vulnerability under the impacts of climate change and human activities, and provide theoretical basis for the development of corresponding grassland management policies.

Livestock manure is a major source of the greenhouse gases (GHGs) methane (CH4) and nitrous oxide (N2O). The emissions can be mitigated by production of biogas through anaerobic digestion (AD) of manure, mostly together with other biowastes, which can substitute fossil energy and thereby reduce CO2 emissions and postdigestion GHG emissions. This paper presents GHG balances for manure and biowaste management as affected by AD for five Danish biogas scenarios in which pig and cattle slurry were codigested with one or more of the following biomasses: deep litter, straw, energy crops, slaughterhouse waste, grass–clover green manure, and household waste. The calculated effects of AD on the GHG balance of each scenario included fossil fuel substitution, energy use for transport, leakage of CH4 from biogas production plants, CH4 emissions during storage of animal manure and biowaste, N2O emissions from stored and field applied biomass, N2O emissions related to nitrate (NO3−) leaching and ammonia (NH3) losses, N2O emissions from cultivation of energy crops, and soil C sequestration. All scenarios caused significant reductions in GHG emissions. Most of the reductions resulted from fossil fuel substitution and reduced emissions of CH4 during storage of codigestates. The total reductions in GHG emissions ranged from 65 to 105 kg CO2-eq ton−1 biomass. This wide range showed the importance of biomass composition. Reductions were highest when straw and grass–clover were used as codigestates, whereas reductions per unit energy produced were highest when deep litter or deep litter plus energy crops were used. Potential effects of iLUC were ignored but may have a negative impact on the GHG balance when using energy crops, and this may potentially exceed the calculated positive climate impacts of biogas production. The ammonia emission potential of digestate applied in the field is higher than that from cattle slurry and pig slurry because of the higher pH of the digestate. This effect, and the higher content of TAN in digestate, resulted in increasing ammonia emissions at 0.14 to 0.3 kg NH3-N ton−1 biomass. Nitrate leaching was reduced in all scenarios and ranged from 0.04 to 0.45 kg NO3-N ton−1 biomass. In the scenario in which maize silage was introduced, the maize production increased leaching and almost negated the effect of AD. Methane leakage caused a 7% reduction in the positive climate impact for each percentage point of leakage in a manure-based biogas scenario.

Abstract. The impact of air pollution on human health and the associated external costs in Europe and the United States (U.S.) for the year 2010 is modelled by a multi-model ensemble of regional models in the frame of the third phase of the Air Quality Modelling Evaluation International Initiative (AQMEII3). This is the first study known to use a common health assessment approach across the two continents. The modelled surface concentrations of O3, CO, SO2 and PM2.5 from each model are used as input to the Economic Valuation of Air Pollution (EVA) system to calculate the resulting health impacts and the associated external costs. Along with a base case simulation, additional runs were performed introducing 20 % emission reductions both globally and regionally in Europe, North America and East Asia. Health impacts estimated by different models can vary up to a factor of three in Europe (twelve models) and the United States (three models). In Europe, the multi-model mean number of premature deaths is calculated to be 414 000 while in the U.S., it is estimated to be 160 000, in agreement with previous global and regional studies. In order to estimate the impact of biases coming from each model, two multi-model ensembles were produced, the first attributing an equal weight to each member of the ensemble, and the second where the subset of models that produce the smallest error compared to the surface observations at each time step. The latter results in increase of health impacts by up to 30 % in Europe, thus giving significantly higher mortality estimates compared to available literature. This is mostly due to a 27 % increase in the domain mean PM2.5 levels, along with a slight increase in O3 by ~ 1 %. Over the U.S., the mean PM2.5 and O3 levels decrease by 11 % and 2 %, respectively, when the optimal ensemble mean is used, leading to a decrease in the calculated health impacts by ~ 11 %. These differences encourage the use of optimal-reduced multi-model ensembles over traditional all model-mean ensembles, in particular for policy applications. Finally, the role of domestic versus foreign emission sources on the related health impacts is investigated using the 20 % emission reduction scenarios applied over the source regions as defined in the frame of HTAP2. The differences are calculated based on the models that are common in the basic multi-model ensemble and the perturbation scenarios, resulting in five models in Europe and all three models in the U.S. A 20 % reduction of global anthropogenic emissions avoids 54 000 and 27 500 premature deaths in Europe and the U.S., respectively. A 20 % reduction of North American emissions foreign emissions avoids ~ 1000 premature deaths in Europe and 25 000 premature deaths in the U.S. A 20 % decrease of emissions within the European source region avoids 47 000 premature deaths in Europe. Reducing the East Asian emission by 20 % avoids ~ 2000 premature deaths in the U.S. These results show that the domestic emissions make the largest impacts on premature death, while foreign sources make a minor contributing to adverse impacts of air pollution.

In recent years, residential wood combustion (RWC) has become a major source of ambient particulate matter (PM) in many developed countries, and in some of these countries even the largest source of primary particle emissions. While other sources of PM have been regulated intensively during the past decades, RWC has been subject to only minor regulation despite of its impact on climate and health. This review covers recent research publications on RWC contributions to ambient PM in different regions of Europe, North America and Australasia, and on key species associated with RWC. Furthermore, factors governing emissions from wood stoves (as the typical appliance used in residential heating) are evaluated. State-of-the-art methods for estimating RWC as a source of ambient PM are discussed. We conclude by highlighting important areas for future research and policies.

Abstract Model-based control schemes such as model predictive control (MPC) can assist smart-energy systems in achieving higher efficiency and utilization of renewable energy sources. A practical barrier for deploying such control schemes for space heating of residential buildings is the costs related to obtaining the weather data measurements needed for identifying a model that describes the dynamic behaviour of the building. Therefore, this paper reports on a simulation-based study investigating whether there is a significant impact on the performance of MPC schemes when substituting these weather measurements with data from meteorological weather services. Since access to weather forecasts is necessary during the operation of the MPC scheme, this implementation approach draws on data already available to remove the need for weather measurements. The results indicated that this approach only led to a minor performance impact in that heating savings were reduced by 4% while comfort violations increased by less than 0.1 Kh per day on average. The results thereby suggest that the use of data from meteorological forecast services for model identification may constitute a cost-efficient alternative to on-site or near-by weather measurements.

The utilisation of typological concepts of participation-based research on the community of practice (CoP) examines Uganda’s public sector in relation to environmental impact assessment (EIA) of national projects. The re-assessment of participatory knowledge is analysed and incorporated into EIA project planning, design and implementation. A case study within the five divisions of the Kampala District used 250 semi-structured and open-ended survey questionnaires and 20 key informants by way of piecewise random sampling. The findings suggest that the majority of respondents were non-informed, on components of CoP, within the selected EIA projects. The CoP revealed concerns regarding Uganda’s security and corruption which intertwined on how the CoP was conducted. We provide original data on the CoP in relation to EIA projects with the intention of facilitating public sector entities a suitable level of knowledge in aiding affected communities.

Several global developments (e.g. diminishing production resources, growing demand for bio-energy) and numerous sector-wide crises (e.g. BSE, swine fever, dioxin) have led to a changing attitude of society towards the consequences of the food systems activities for social, economic and environmental issues, captured in the term of sustainability. Consumers in their role as final customers, and as a consequence also enterprises within agri-food supply chains, show increasing interest in the characteristics of food, and in turn, on the availability of related information and guarantees. Enterprises in agri-food supply chains are facing new expectations and are seeking to communicate social, economic and environmental performance of their business to customers within their supply chain and to consumers. New solutions for determination and communication of sustainability are needed for the agri-food sector, covering single aspects of sustainability as well as sustainability in a broader sense, including social, economic and environmental issues. Integrated, computer-based information services, since they are mainly building on existing systems, provide flexible solutions for enterprises to measure and evaluate sustainability of products throughout agri-food supply chains. Gained information on product characteristics might be used for decision support within enterprises as well as for communication of sustainable practices to customers and consumers, resulting in increased competitiveness of enterprises, supply chains and the sector by satisfying customers’ and consumers’ demands for information on the sustainability of a product. The present paper introduces a framework for developing information services for European pork chains using the three selected information domains food safety (representing social sustainability), quality (representing economic sustainability) and global warming potential (representing environmental sustainability). Resulting information models give an aggregated overview on information availability and exchange in European pork chains, additional information demands of possible service users and deficiencies in the existing information infrastructures. The paper supports different stakeholders involved in agri-food production, such as service developers, enterprise decision makers and management consultants, in developing enterprise- and chain-specific solutions which meet customers’ and consumers’ demands by providing appropriate sustainability information and guarantees.