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AbstractBACKGROUND: Inappropriate utilisation of biosolids may adversely impact agrosystem productivity. Here, we address the response of wheat (Triticum durum) to different doses (0, 40, 100, 200 and 300 t ha−1) of either municipal solid waste (MSW) compost or sewage sludge in a greenhouse pot experiment. Plant growth, heavy metal uptake, and antioxidant activity were considered.RESULTS: Biomass production of treated plants was significantly enhanced at 40 t ha−1 and 100 t ha−1 of MSW compost (+48% and +78% relative to the control, respectively). At the same doses of sewage sludge, the increase was only 18%. Higher doses of both biosolids restricted significantly the plant growth, in concomitance with the significant accumulation of heavy metals (Ni2+, Pb2+, Cu2+ and Zn2+), especially in leaves. Leaf activities of antioxidant enzymes (ascorbate peroxidase, glutathione reductase, catalase and superoxide dismutase) were unchanged at 40 t ha−1 MSW compost or sewage sludge, but were significantly stimulated at higher doses (200–300 t ha−1), together with higher leaf concentration of reduced glutathione.CONCLUSION: This preliminary study suggests that a MSW supply at moderate doses (100 t ha−1) could be highly beneficial for wheat productivity. Copyright © 2010 Society of Chemical Industry

Sustainability is commonly assessed along environmental, societal, economic and technological dimensions. A crucial aspect of sustainability is that inter-generational equality must be ensured. This requires that sustainability is attained in the here and now as well as into the future. Therefore, what is perceived as 'sustainable' changes as a function of societal opinion and technological and scientific progress. A concept that describes the ability of systems to change is adaptive capacity. Literature suggests that the ability of systems to adapt is an integral part of sustainable development. This paper demonstrates that indicators measuring adaptive capacity are underrepresented in current urban water sustainability studies. Furthermore, it is discussed under which sustainability dimensions adaptive capacity indicators are lacking and why. Of the >90 indicators analysed, only nine are adaptive capacity indicators, of which six are socio-cultural, two technological, one economical and none environmental. This infrequent use of adaptive capacity indicators in sustainability assessments led to the conclusion that the challenge of dynamic and uncertain urban water systems is, with the exception of the socio-cultural dimension, not yet sufficiently reflected in the application of urban water sustainability indicators. This raises concerns about the progress towards urban water systems that can transform as a response variation and change. Therefore, research should focus on developing methods and indicators that can define, evaluate and quantify adaptive capacity under the economic, environmental and technical dimension of sustainability. Furthermore, it should be evaluated whether sustainability frameworks that focus on the control processes of urban water systems are more suitable for measuring adaptive capacity, than the assessments along environmental, economic, socio-cultural and technological dimensions.

The aim of this report is to demonstrate and evaluate the potential of tall wheatgrass (Elytrigia elongata) to avoid GHG emissions and obtain lower economic costs in marginal areas of Spain. Our research built scenarios based on experimental plots (2 and 3 years growth) in 3 locations of Spain with completely different climate conditions (provinces of Girona, Soria and Palencia). In our experiences, we achieved an adequate establishment and biomass production, and assumed a rank of biomass yields until the end of the life cycle that is usually accepted to be about 15 years in many other studies in United States, Argentina and Eastern Europe where tall wheatgrass is extensively cultivated in marginal areas for sheep livestock production. Using our experimental plots and statistical information for economic inputs costs, we built 5 different scenarios per region considering a large range of biomass yields of tall wheatgrass. The analysis included a comparison with annual grasses economic costs calculated for a wide range of biomass yields of a previous study. We estimated GHG emissions savings for tall wheatgrasses and used our previous study (which had GHG emissions savings as well). Savings were calculated replacing natural gas electricity with electricity from biomass combustion in real power plants in Spain. In a wide range of yields, the results suggest that marginal areas might present a better performance with tall wheatgrass compared to annual winter grasses (cereals whole plant cuttings), thus producing biomass yields with higher GHG savings and lower economic costs at the farm level. Proceedings of the 20th European Biomass Conference and Exhibition, 18-22 June 2012, Milan, Italy, pp. 217-229

In this study, air concentrations of BaP in two different seasons (winter 2015 and summer 2016) and BaP levels in ground vegetation from Tarragona County were used as control simulations performed with the WRF-CHIMERE air quality modelling system, in order to reproduce the incidence of that hazardous chemical in air and soils. The CTM was validated for the present climatology, showing a good ability to represent air and soil concentrations of BaP over the target domain (petrochemical, chemical, urban and background sites), particularly in the winter. Then, the variation of the BaP concentrations in air and soils were simulated for the time series 1996-2015 and for the climate change scenario RCP8.5 (2031-2050). While an increase is projected for the levels in air, particularly in chemical and remote sites where the variation can go up to 10%, in terms of soil deposition the findings are the opposite, with an evident decrease in soil BaP concentrations, particularly for background sites. Finally, a potential health effect of BaP for the local population (lung cancer) was assessed. Although according to the projections the EU threshold for BaP atmospheric incidence (1 ng m-3) will not be reached by 2050, there will be an increase in the life-time risk of lung cancer, particularly in the most populated areas within the simulation domain.

Landfill gas (LFG) tends to escape from the landfill surface even when LFG collecting systems are installed. Since LFG leaks are generally a noticeable percentage of the total production of LFG, the optimisation of the collection system is a fundamental step for both energy recovery and environmental impact mitigation. In this work, we suggest to take into account the results of direct measurements of gas fluxes at the air-cover interface to achieve this goal.During the last 5 years (2004-2009), 11 soil gas emission surveys have been carried out at the Municipal Solid Waste landfill of Legoli (Peccioli municipality, Pisa Province, Italy) by means of the accumulation chamber method. Direct and simultaneous measurements of CH(4) and CO(2) fluxes from the landfill cover (about 140,000 m(2)) have been performed to estimate the total output of both gases discharged into the atmosphere. Three different data processing have been applied and compared: Arithmetic mean of raw data (AMRD), sequential Gaussian conditional simulations (SGCS) and turning bands conditional simulations (TBCS). The total amount of LFG (captured and not captured) obtained from processing of direct measurements has been compared with the corresponding outcomes of three different numerical models (LandGEM, IPCC waste model and GasSim).Measured fluxes vary from undetectable values (<0.05 mol m(-2) day(-1) for CH(4) and <0.02 mol m(-2) day(-1) for CO(2)) to 246 mol m(-2) day(-1) for CH(4) and 275 mol m(-2) day(-1) for CO(2). The specific CH(4) and CO(2) fluxes (flux per surface unit) vary from 1.8 to 7.9 mol m(-2) day(-1) and from 2.4 to 7.8 mol m(-2) day(-1), respectively.The three different estimation methodologies (AMRD, SGCS and TBCS) used to evaluate the total output of diffused CO(2) and CH(4) fluxes from soil provide similar estimations, whereas there are some mismatches between these results and those of numerical LFG production models. Isoflux maps show a non-uniform spatial distribution, with high-flux zones not always corresponding with high-temperature areas shown by thermographic images.The average value estimated over the 5-year period for the Legoli landfill is 245 mol min(-1) for CH(4) and 379 mol min(-1) for CO(2), whereas the volume percentage of CH(4) in the total gas discharged into the atmosphere varies from 29% to 51%, with a mean value of 39%. The estimated yearly emissions from the landfill cover is about 1.29 x 10(8) mol annum(-1) (2,100 t year(-1)) of CH(4) and 1.99 x 10(8) mol annum(-1) (8,800 t year(-1)) of CO(2). Considering that the CH(4) global warming potential is 63 times greater than that of CO(2) (20 a time horizon, Lashof and Ahuja 1990), the emission of methane corresponds to 130,000 t annum(-1) of CO(2).The importance of these studies is to provide data for the worldwide inventory of CH(4) and CO(2) emissions from landfills, with the ultimate aim of determining the contribution of waste disposal to global warming. This kind of studies could be extended to other gas species, like the volatile organic compounds.

Since 2007, a range of new modeling approaches and tools have been developed for sustainability impact assessment (SIA), but a lack of universal acceptance of SIA tools in applied policy making is observed. The current article gives an overview of experiences from several European and international projects, critically reviews the selected SIA tools and then discusses a number of reasons for the observed disconnect of the tools with the potential users. Largely based on the experiences of the presented SIA tools focusing land use policy advice, a decision tree is designed, which may facilitate an adequate, region and developmental phase specific selection of tool-box components for the development of SIA tools in future. Elements to ensure end-user participation are also integrated in the decision tree in order to increase the likelihood of the tool in applied land use policy advice. In addition, the Challenges in SIA tool development and use are further discussed.

Several dairy farms in the Netherlands aim at reducing their environmental impact by improving the internal nutrient cycle (INC) at farm level. Practices to improve nutrient cycling at these INC farms, however, might not only reduce the environmental impact on-farm, but alter also the off-farm environmental impact associated with supply chain processes (production and transport) related to inputs entering the farm, such as purchased feed or fertilizer or the economic or societal performance of these farms. We compared, therefore, a set of sustainability indicators of nine INC farms with a group of benchmark farms, comparable in terms of farm size, intensity and site-specific circumstances. This benchmark group was composed using statistical matching to exclude the effect of these characteristics on economic, environmental and societal performance. Economic indicators used were: farm income per unpaid annual working unit and the costs to revenues ratio. Environmental indicators used were derived from a cradle-to-farm-gate life cycle assessment: land occupation (LO), non-renewable energy use (NREU), global warming potential (GWP), acidification potential (AP) and eutrophication potential (EP), expressed per kg fat-and-protein-corrected milk (FPCM). In addition, we quantified the soil content of organic carbon and phosphorus, and the soil nitrogen supply. Societal indicators used were: payments for agri-environmental measures, grazing hours and penalties for aberrant milk composition. Results showed that INC farms had a lower non-renewable energy use per kg FPCM, higher soil organic carbon content and received higher annual payments for agri-environmental measures, whereas economic and other environmental, societal indicators did not differed. Furthermore, we demonstrated the need for a sound benchmark to assess the effect of INC-farming on the economic, environmental and societal performance. Statistical matching enabled us to define, for each INC farm, a benchmark group with similar farm characteristics, which are known to affect sustainability indicators. Observed differences in sustainability indicators between both farm groups, therefore, truly resulted from aiming at internal nutrient cycling, and not from differences in other farm characteristics.

Abstract The Mediterranean region is one of the most vulnerable regions to climate change. The majority of climate models forecast a rise in temperatures and less rainfall, which have been observed in recent decades. These changes will affect several vegetation properties, especially phenological dynamics and traits, by increasing drought intensity and recurrence. In this climate change context, the present study aims to assess the evolution of vegetation state and its relation with the climate dynamics in the Mediterranean forest region of northeast Tunisia using Land Surface Phenology (LSP) metrics and the vegetation index (NDVI) analysis from 2000 to 2017. To conduct this work, we used precipitation and temperature data from the two closest weather stations and 16-day NDVI composite images from the MODIS satellite source, with 250-m spatial resolution. Three phenological metrics— start of season (SOS), end of season (EOS), and length of season (LOS) — were obtained and compared for different vegetation types. The LSP variation in response to climatic metrics was also analyzed. The results showed that the LSP in our study area changed significantly during the 2000–2017 period, which includes an average 7.8 days delay in the SOS, an average advance in the EOS by 5 days, and LOS shortened by an average 12.8 days. Autumn (Pr_9) and spring (Pr_3 and P3_4) precipitations, as well as maximum temperature (Tx9+10), represent the best climate parameters to explain the changes in LSP. Both the NDVI and SPEI showed a significant high correlation (p