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Bioenergy crops are well known for their ability to reduce greenhouse gas emissions and increase the soil carbon stock. Although such crops are often held to be in competition with food crops and thus raise the question of current and future food security, at the same time mitigation measures are required to tackle climate change and sustain local farming communities and crop production. However, in some cases the actions envisaged for specific pedo-climatic conditions are not always economically sustainable by farmers. In this frame, energy crops with high environmental adaptability and yields, such as giant reed (Arundo donax L.), may represent an opportunity to improve farm incomes, making marginal areas not suitable for food production once again productive. In so doing, three of the 17 Sustainable Development Goals (SDGs) of the United Nations would be met, namely SDG 2 on food security and sustainable agriculture, SDG 7 on reliable, sustainable and modern energy, and SDG 13 on action to combat climate change and its impacts. In this work, the response of giant reed in the marginal areas of an agricultural district of southern Italy (Destra Sele) and expected farm incomes under climate change (2021-2050) are evaluated. The normalized water productivity index of giant reed was determined (WP; 30.1gm-2) by means of a SWAP agro-hydrological model, calibrated and validated on two years of a long-term field experiment. The model was used to estimate giant reed response (biomass yield) in marginal areas under climate change, and economic evaluation was performed to determine expected farm incomes (woodchips and chopped forage). The results show that woodchip production represents the most profitable option for farmers, yielding a gross margin 50% lower than ordinary high-input maize cultivation across the study area.

Giant Reed (Arundo Donax L.) is one of the most interesting crop for energy production due to the high productivity in less-fertile environments too. Among all the technological options, anaerobic fermentation with oleaginous yeasts for the synthesis of lipids rep- resents the last frontier of biological conversion of ligno-cellulosic biomasses to fuels or to bio-polymers. The chemical composition of biomass (i.e. cellulose, lignin and emicellulose) is a key factor of this process.

Using recycled rubber crumbs as drainage layer in extensive green roofs have high potential to reduce the heating and cooling loads in buildings over traditional materials used as drainage layer, such as pozzolana gravel. However, the environmental impact due to the life cycle should be analyzed to assess its environmental benefit. This paper evaluates the environmental performance of green roofs in which the drainage layer is made of rubber crumbs, a recycled material the use of which is still experimental for this purpose. In this paper Life Cycle Assessment (LCA) is applied to compare the environmental impact of four constructive systems, two extensive green roofs without insulation layer and with different drainage materials, e a recycled material, rubber crumbs, and a conventional one, pozzolana gravel -, in front of two conventional flat roofs, with and without thermal insulation (polyurethane), built in an experimental set-up consisting of four monitored house-like cubicles, located in Mediterranean continental climate (Lleida, Spain). The LCA considered the production, construction, operational, and disposal phases of the roofs, according to UNE-EN 15643-2. The operational phase was carried out using data measured in the experimental set-up, considering heating and cooling energy consumptions in the winter and summer period, respectively.

Recent empirical research indicates that certain types of emissions follow an inverted-U or environmental Kuznets curve (EKC) as income grows. This regularity has been interpreted as a possible de-linking of economic growth and patterns of certain pollutants for developed economies. In this paper the empirical basis of this result is investigated by considering some statistical particularities of the various EKC studies performed. It is argued that the inverted-U relationship between income and emissions estimated from panel data need not hold for specific individual countries over time. Based on insights from 'intensity-of-use' analysis in resource economics, an alternative growth model is specified and estimated for three types of emissions (CO

Species distribution models (SDMs) provide realistic scenarios to explain the influence of bioclimatic variables on plant pathogen distribution. Diplodia sapinea is most harmful to plantations of both exotic and native pine species in Italy, causing economic consequences expecially to edible seed production. In this study, we developed maximum entropy models for D. sapinea in Italy to reach the following goals: (i) to carry out the pathogen's first geographical distribution analysis in Italy and determine which ecogeographical variables (EGVs) may influence its outbreaks; (ii) to detect the effect of climate change on the potential occurrence of disease outbreaks by 2050 and 2070. We used Maxent ver. 3.4.0 to develop SDMs. We used six global climate models (BCC-CSM1-1, CCSM4, GISS-E2-R, MIROC5, HadGEM2-ES and MPI-ESM-LR) for two representative concentration pathways (4.5 and 8.5) and two time projections (2050 and 2070) to detect future climate projections of D. sapinea. The most important EGVs influencing outbreaks were land cover, altitude, mean temperature of driest and wettest quarter, precipitation of wettest quarter, precipitation seasonality and minimum temperature of coldest month. The distribution of D. sapinea mostly expanded in central and southern Italy and shifted in altitude upwards on average by ca. 93m a.s.l. Moreover the fungus expanded the range where disease outbreaks may be recorded in response to an increase in the mean temperature of wettest and driest quarter by ca. 1.9 C and 5.8 C, respectively in all climate change scenarios. Precipitation of wettest quarter did not differ between current and any of future models. Under different climate change scenarios D. sapinea's disease outbreaks will be likely to affect larger areas of pine forests in the country, probably causing heavy effects on the dynamics and evolution of these stands or perhaps constraining their survival.

Depleted hydrocarbon reservoirs and deep saline aquifers are key targets for geological storage of CO

Abstract In this paper a model is presented with the aim of studying the long-term relationship between an economy and its natural environment. The approach is based on two main elements: reciprocal interactions between on the one hand population growth, investment, allocation of inputs and outputs, technology and productivity, and on the other hand declining environmental quality, pollution and resource exhaustion; and a more realistic and consistent representation of the interdependence between various environmental effects, from extraction to emission, by using a materials balance perspective on economic processes. In order to develop the model attention is devoted to production functions that are consistent with materials balance. The model is multisectoral, including economic processes of extraction, production of commodities and investment goods, waste abatement and recycling. Environmental processes of resource regeneration and waste assimilation are linked through the economic and environmental sphere, and the model allows for endogenous development of resource-efficient technology.

Polychlorodibenzo-p-dioxins, polychlorodibenzo-furans (PCDD/Fs) and dioxin-like polychlorobiphenyls (DL-PCBs) enter the food chain from the environment. In this study, we report the 2008-2018 time-trends in the PCDD/F and DL-PCB contamination of milk from buffaloes fed on local forage in rural areas of the Campania region. Validated according to QA/QC criteria, the dataset (N = 808 on a total of 2068 samples, after excluding follow-up results and outliers) was computed on the upper-bound value pg WHO-TEQ2005 g-1fat. We assessed time-trends and assayed baseline contamination levels, which displayed log-normal distribution. A significant decreasing trend (p < 0.01) was observed from 2008 to 2009 and 2010; the P50-P95 range fell from 2.37-8.48 pg WHO-TEQ2005 g-1fat (N = 393) in 2008 to 1.73-4.61 in 2009 (N = 86) and to 0.67-1.46 in 2010 (N = 42). From 2010 to 2018 (N = 329), no significant variation was found among years and the related dataset fitted a log-normal distribution (p < 0.05). Occurrence descriptors indicated that the baseline contamination of dairy products (mean = 0.54; P50-P95 = 0.47-1.24) in the Campania Region was well below the EU regulatory limit in force (5.5 pg WHO-TEQ2005 g-1fat). Given the Tolerable Weekly Intake of 2 pg WHO-TEQ kg-1 body weight (bw) proposed by the EFSA for PCDD/Fs and DL-PCBs, this level of baseline contamination is discussed with regard to the orientation of food safety and food security risk connected with buffalo mozzarella cheese production.