Nitrogen budget and statistical entropy analysis of the Tiber River catchment, a highly anthropized environment

Modern farming causes a decline in the recycling of the soil's inorganic matter due to losses by leaching, runoff, or infiltration into the groundwater. The Soil System Budget approach was applied to evaluate the net N budget at the catchment and sub-catchment levels of the Tiber River (central Italy) in order to establish the causes for different N budgets among the sub-catchments. Statistical Entropy Analysis (SEA) was used to evaluate the N efficiency of the Tiber River and its sub-catchments, providing information on the dispersion of different N forms in the environment. The total N inputs exceeded the total outputs, showing a low N retention (15.8%) at the catchment level, although some sub-catchments showed higher N retention values. The Utilized Agricultural Area was important in the determination of the N balance, as it was linked to zoo- and agricultural activities, although the Random Forest analysis showed that the importance ranking changed with the land use. The low N retention of the Tiber catchment was due to the soil characteristics (Cambisols and Leptosols), loads from atmospheric deposition, biological fixation, and the livestock industry. The SEA simulations showed a reduction of the N released into the atmosphere and groundwater compartments from 34% to 6% through a reduction of the N loads by 50%

The high frequency of manic symptoms in fibromyalgia does influence the choice of treatment?

BACKGROUND: Mood disorders were found associated with fibromyalgia (FM) and clinical studies have revealed the efficacy of antidepressant drugs in the treatment of FM. However no specific instruments to identify manic symptoms were used. OBJECTIVES: To assess the frequency of anxiety and mood disorders (particularly bipolar disorders and manic symptoms) in a consecutive sample of women affected by FM using standardized diagnostic tools and to compare the prevalence of these disorders with that observed in a sample of healthy controls from the general population. METHODS: Cases: consecutive series of women (N = 37, mean age 50.1 ± 21.0) attending a Rheumatology outpatient Unit at the University of Cagliari. Controls: 148 women, drawn from the data bank of an epidemiological study matched for sex and age with controls according to a randomisation "after blocks" method. The Italian version of the Composite International Diagnostic Interview Simplified were carried out by physicians. Psychiatric diagnosis was formulated according to DSM-IV criteria. The Italian version of the Mood Disorder Questionnaire (MDQ) was administered to identify manic symptoms and bipolar disorders. Diagnosis of FM were carried out by rheumatologist according to the criteria of American College of Rheumatology. RESULTS: Subjects with FM showed a higher comorbidity with Generalised Anxiety Disorder, Panic Disorder and Major Depressive Disorder than controls. The study showed a high frequency of manic symptoms (MDQ positive) in the sample of fibromyalgic patients (59%), approximately double that found in the control sample (P < 0.001). DISCUSSION: Clinical studies have shown the efficacy of antidepressants, especially tricyclic antidepressants, in the treatment of FM. The clinical difficulty in identifying hypomanic episodes is well known particularly where previous and not present episodes are concerned as in depressive patients. These data would suggest further studies on the subject are needed and more caution also in prescribing antidepressants in a population apparently at high risk for bipolar disorders

Economic losses due to ozone impacts on human health, forest productivity and crop yield across China

China's economic growth has significantly increased emissions of tropospheric ozone (O3) precursors, resulting in increased regional O3 pollution. We analyzed data from >1400 monitoring stations and estimated the exposure of population and vegetation (crops and forests) to O3 pollution across China in 2015. Based on WHO metrics for human health protection, the current O3 level leads to +0.9% premature mortality (59,844 additional cases a year) with 96% of populated areas showing O3–induced premature death. For vegetation, O3 reduces annual forest tree biomass growth by 11–13% and yield of rice and wheat by 8% and 6%, respectively, relative to conditions below the respective AOT40 critical levels (CL). These CLs are exceeded over 98%, 75% and 83% of the areas of forests, rice and wheat, respectively. Using O3 exposure–response functions, we evaluated the costs of O3-induced losses in rice (7.5 billion US$), wheat (11.1 billion US$) and forest production (52.2 billion US$) and SOMO35–based morbidity for respiratory diseases (690.9 billion US$) and non–accidental mortality (7.5 billion US$), i.e. a total O3-related cost representing 7% of the China Gross Domestic Product in 2015. Keywords: Surface ozone, Human health, Wheat, Rice, Forests, Crops, Risk assessment, Impacts, Economic valuatio

Impacts of air pollution on human and ecosystem health, and implications for the National Emission Ceilings Directive. Insights from Italy

Across the 28 EU member states there were nearly half a million premature deaths in 2015 as a result of exposure to PM2.5, O3 and NO2. To set the target for air quality levels and avoid negative impacts for human and ecosystems health, the National Emission Ceilings Directive (NECD, 2016/2284/EU) sets objectives for emission reduction for SO2, NOx, NMVOCs, NH3 and PM2.5 for each Member State as percentages of reduction to be reached in 2020 and 2030 compared to the emission levels into 2005. One of the innovations of NECD is Article 9, that mentions the issue of “monitoring air pollution impacts” on ecosystems. We provide a clear picture of what is available in term of monitoring network for air pollution impacts on Italian ecosystems, summarizing what has been done to control air pollution and its effects on different ecosystems in Italy. We provide an overview of the impacts of air pollution on health of the Italian population and evaluate opportunities and implementation of Article 9 in the Italian context, as a case study beneficial for all Member States. The results showed that SO42− deposition strongly decreased in all monitoring sites in Italy over the period 1999–2017, while NO3− and NH4+ decreased more slightly. As a consequence, most of the acid-sensitive sites which underwent acidification in the 1980s partially recovered. The O3 concentration at forest sites showed a decreasing trend. Consequently, AOT40 (the metric identified to protect vegetation from ozone pollution) showed a decrease, even if values were still above the limit for forest protection (5000 ppb h−1), while PODy (flux-based metric under discussion as new European legislative standard for forest protection) showed an increase. National scale studies pointed out that PM10 and NO2 induced about 58,000 premature deaths (year 2005), due to cardiovascular and respiratory diseases. The network identified for Italy contains a good number of monitoring sites (6 for terrestrial ecosystem monitoring, 4 for water bodies monitoring and 11 for ozone impact monitoring) distributed over the territory and will produce a high number of monitored parameters for the implementation of the NECD

Tuning graphene doping by carbon monoxide intercalation at the Ni(111) interface

Under near-ambient pressure conditions, carbon monoxide molecules intercalate underneath an epitaxial graphene monolayer grown on Ni(111), getting trapped into the confined region at the interface. On the basis of ab-initio density functional theory calculations, we provide here a full characterization of the intercalated CO pattern, highlighting the modifications induced on the graphene electronic structure. For CO coverages as low as 0.14 monolayer (ML), the graphene layer is spatially decoupled from the metallic substrate, with a significant C 1s core level shift towards lower binding energies. The most relevant signature of the CO intercalation is a clear switching of the graphene doping state, which changes from n-type, when strongly interacting with the metal surface, to p-type. The shift of the Dirac cone linearly depends on the CO coverage, reaching about 0.9 eV for the saturation value of 0.57 ML. Theoretical predictions are compared with the results of scanning tunnelling microscopy, low-energy electron diffraction and photoemission spectroscopy experiments, which confirm the proposed scenario for the nearly saturated intercalated CO system. This result opens the way to the application of the Graphene/Ni(111) interface as gas sensor to easily detect and quantify the presence of carbon monoxide

Modelling study of soil C, N and pH response to air pollution and climate change using European LTER site observations

Current climate warming is expected to continue in coming decades, whereas high N deposition may stabilize, in contrast to the clear decrease in S deposition. These pressures have distinctive regional patterns and their resulting impact on soil conditions is modified by local site characteristics. We have applied the VSD+ soil dynamic model to study impacts of deposition and climate change on soil properties, using MetHyd and GrowUp as pre-processors to provide input to VSD+. The single-layer soil model VSD+ accounts for processes of organic C and N turnover, as well as charge and mass balances of elements, cation exchange and base cation weathering. We calibrated VSD+ at 26 ecosystem study sites throughout Europe using observed conditions, and simulated key soil properties: soil solution pH (pH), soil base saturation (BS) and soil organic carbon and nitrogen ratio (C:N) under projected deposition of N and S, and climate warming until 2100. The sites are forested, located in the Mediterranean, forested alpine, Atlantic, continental and boreal regions. They represent the long-term ecological research (LTER) Europe network, including sites of the ICP Forests and ICP Integrated Monitoring (IM) programmes under the UNECE Convention on Long-range Transboundary Air Pollution (LRTAP), providing high quality long-term data on ecosystem response. Simulated future soil conditions improved under projected decrease in deposition and current climate conditions: higher pH, BS and C:N at 21, 16 and 12 of the sites, respectively. When climate change was included in the scenario analysis, the variability of the results increased. Climate warming resulted in higher simulated pH in most cases, and higher BS and C:N in roughly half of the cases. Especially the increase in C:N was more marked with climate warming. The study illustrates the value of LTER sites for applying models to predict soil responses to multiple environmental changes

Currently legislated decreases in nitrogen deposition will yield only limited plant species recovery in European forests

Atmospheric nitrogen (N) pollution is considered responsible for a substantial decline in plant species richness and for altered community structures in terrestrial habitats worldwide. Nitrogen affects habitats through direct toxicity, soil acidification, and in particular by favoring fast-growing species. Pressure from N pollution is decreasing in some areas. In Europe (EU28), overall emissions of NO x declined by more than 50% while NH3 declined by less than 30% between the years 1990 and 2015, and further decreases may be achieved. The timescale over which these improvements will affect ecosystems is uncertain. Here we use 23 European forest research sites with high quality long-term data on deposition, climate, soil recovery, and understory vegetation to assess benefits of currently legislated N deposition reductions in forest understory vegetation. A dynamic soil model coupled to a statistical plant species niche model was applied with site-based climate and deposition. We use indicators of N deposition and climate warming effects such as the change in the occurrence of oligophilic, acidophilic, and cold-tolerant plant species to compare the present with projections for 2030 and 2050. The decrease in N deposition under current legislation emission (CLE) reduction targets until 2030 is not expected to result in a release from eutrophication. Albeit the model predictions show considerable uncertainty when compared with observations, they indicate that oligophilic forest understory plant species will further decrease. This result is partially due to confounding processes related to climate effects and to major decreases in sulphur deposition and consequent recovery from soil acidification, but shows that decreases in N deposition under CLE will most likely be insufficient to allow recovery from eutrophication

Adaptive iterative thresholding algorithms for magnetoencephalography

We provide fast and accurate adaptive algorithms for the spatial resolution of current densities in MEG. We assume that vector components of the current densities possess a sparse expansion with respect to preassigned wavelets. Additionally, different components may also exhibit common sparsity patterns. We model MEG as all inverse problem with joint sparsity constraints, promoting the coupling of non-vanishing components. We show how to compute solutions of the MEG linear inverse problem by iterative thresholded Landweber schemes. The resulting adaptive scheme is fast, robust, and significantly Outperforms the classical Tikhonov regularization in resolving sparse current densities. Numerical examples are included

Electric current density imaging via an accelerated iterative algorithm with joint sparsity constraints

International audienceMany problems in applied sciences require to spatially resolve an unknown electrical current distribution from its external magnetic field. Electric currents emit magnetic fields which can be measured by sophisticated superconducting devices in a noninvasive way. Applications of this technique arise in several fields, such as medical imaging and non-destructive testing, and they involve the solution of an inverse problem. Assuming that each component of the current density vector possesses the same sparse representation with respect to a preassigned multiscale basis, allows us to apply new regularization techniques to the magnetic inverse problem. The solution of linear inverse problems with sparsity constraints can be efficiently obtained by iterative algorithms based on gradient steps intertwined with thresholding operations. We test this algorithms to numerically solve the magnetic inverse problem with a joint sparsity constraint