Integrated Indicators for the Estimation of Vulnerability to Land Degradation

In this chapter we approach the assessment of the vulnerability to land degradation of a typical Mediterranean environment using a modified version of the ESA model. This approach combines analyses of the socio-economic component with analyses of the vegetation trends. According to the standard ESA strategy, different indicators representing the impact of agricultural and grazing activities are used. The main feature of these indicators is that they are census-based and consequently suitable only for the analysis at municipal scale. Therefore we have also elaborated a mechanization index (proxy for soil compaction induced by agricultural machineries) that uses land cover and morphological data [36], enabling high spatial resolution and faster rate of update. The indicators related to the anthropic impact are integrated into an overall Land Management Index (LMI) and in each area it is possible to enhance the main contributing factors to highlight the prevailing forces that drive human-induced degradation processes. In order to include vegetation in the vulnerability map we analyze satellite vegetation index NDVI (Normalized Difference Vegetation Index) which is recognized as ideal tool for monitoring long term trends of degradation phenomena and assessing different values of severity of the concerned processes [37,38]. The final result of our analyses is an integrated vulnerability map of the investigated region, accounting for management and vegetation factors, which allows us to identify priority sites where restoration/rehabilitation interventions are urgent. The adopted procedure can be easily applied to geographic contexts characterized by high complexity in terms of land cover type and economic vocation (intensive agriculture, grazing, industrial activities) thus enabling an early detection of the areas most vulnerable to land degradation

A Statistical Procedure for Analyzing the Behavior of Air Pollutants during Temperature Extreme Events: The Case Study of Emilia-Romagna Region (Northern Italy)

Meteorological conditions play a crucial role in air pollution by affecting both directly and indirectly the emissions, transport, formation, and deposition of air pollutants. Extreme weather events can strongly affect surface air quality. Understanding relations between air pollutant concentrations and extreme weather events is a fundamental step toward improving the knowledge of how excessive heat impacts on air quality. In this work, we developed a statistical procedure for investigating the variations in the correlation structure of four air pollutants (NOx, O3, PM10, PM2.5) during extreme temperature events measured in monitoring sites located of Emilia Romagna region, Northern Italy, in summer (June–August) from 2015 to 2017. For the selected stations, Hot Days (HDs) and Heat Waves (HWs) were identified with respect to historical series of maximum temperature measured for a 30-year period (1971–2000). This method, based on multivariate techniques, allowed us to highlight the variations in air quality of study area due to the occurrence of HWs. The examined data, including PM concentrations, show higher values, whereas NOx and O3 concentrations seem to be not influenced by HWs. This operative procedure can be easily exported in other geographical areas for studying effects of climate change on a local scale

Analysis of Air Quality during the COVID-19 Pandemic Lockdown in Naples (Italy)

Lockdown measures applied in the aftermath of the COVID-19 pandemic spread to Italy in the period March 13th–May 4th strongly limited the social and industrial activities with consequent effects on the air pollution. Here we report a study on the influence of the lockdown measures on the air quality in the city of Naples (Italy). The comparison of the levels of various gaseous pollutants (C6H6, CO, NO2 and SO2) and particulate matter (PM10, PM2.5, PM1) at ground level as well as of atmospheric aerosol properties registered by remote sensing techniques during the lockdown period with the values observed in the earlier months and during the same period of the previous year is used to gain interesting information on the environmental impact of the human activities. Our findings show a rather significant reduction of the pollution due to NO2 (49–62%) in urban as well as in green suburban area, while CO and SO2 showed a more important reduction in urban or industrial districts of the city (50–58% and 70%, respectively). Particulate matter at ground level is also affected but to a more limited extent (29–49%). Nevertheless, characterization of atmospheric aerosol columnar properties suggests an interesting variation of its composition. The observed features have been associated to the strong meteorological interference from Saharan Dust in the Mediterranean area also affecting the city of Naples

Going Conservative or Conventional? Investigating Farm Management Strategies in between Economic and Environmental Sustainability in Southern Italy

The European “Green Deal” strategy is aimed at making Europe the first climate-neutral continent by 2050 through integrated actions relying on healthier agricultural systems grounded in (environmental and economic) sustainable practices, including soil carbon management and biodiversity enhancement. In this vein, the present study contrasts the economic-environmental performances of conventional (deep tillage) and conservative (no-tillage and soil ripping) practices for two varieties of durum wheat (Triticum turgidum spp. durum), namely a modern (Anco Marzio) and an ancient landrace (Saragolla Lucana) variety in the Basilicata region (Southern Italy). Field and laboratory analysis (granulometry, mineralogy, and geochemistry) as well as satellite data (RapidEye) were used to characterize the soil and vegetation patterns. The empirical results indicate a higher biomass production and vegetative potential together with higher grain yields in soils managed with conventional deep tillage compared with soil managed with conservative practices. Similarly, the modern wheat variety exhibited better performance with respect to the old landrace. The soils managed with conventional practices had a distribution of exchangeable macro-nutrients characterized by a reduction in Ca+ and an increase in Mg2+ and K+ between pre-sowing and post-harvesting. Such a distribution was also genotype-dependent, with a higher variability for Saragolla Lucana than Anco Marzio, showing a diverging adsorption of macro-elements between the modern and ancient landrace varieties

Going Conservative or Conventional? Investigating Farm Management Strategies in between Economic and Environmental Sustainability in Southern Italy

The European “Green Deal” strategy is aimed at making Europe the first climate-neutral continent by 2050 through integrated actions relying on healthier agricultural systems grounded in (environmental and economic) sustainable practices, including soil carbon management and biodiversity enhancement. In this vein, the present study contrasts the economic-environmental performances of conventional (deep tillage) and conservative (no-tillage and soil ripping) practices for two varieties of durum wheat (Triticum turgidum spp. durum), namely a modern (Anco Marzio) and an ancient landrace (Saragolla Lucana) variety in the Basilicata region (Southern Italy). Field and laboratory analysis (granulometry, mineralogy, and geochemistry) as well as satellite data (RapidEye) were used to characterize the soil and vegetation patterns. The empirical results indicate a higher biomass production and vegetative potential together with higher grain yields in soils managed with conventional deep tillage compared with soil managed with conservative practices. Similarly, the modern wheat variety exhibited better performance with respect to the old landrace. The soils managed with conventional practices had a distribution of exchangeable macro-nutrients characterized by a reduction in Ca+ and an increase in Mg2+ and K+ between pre-sowing and post-harvesting. Such a distribution was also genotype-dependent, with a higher variability for Saragolla Lucana than Anco Marzio, showing a diverging adsorption of macro-elements between the modern and ancient landrace varieties

MULTIVARIATE DATA ANALYSIS PROCEDURE FOR CHARACTERIZING CORRELATION STRUCTURE OF AIR CONTAMINANTS IN OPERATING ROOMS

Operating Rooms (ORs), collected under different conditions, were analyzed. In 18 ORs of general surgery, concentrations of particles with aerodynamic diameter higher than 5μm and 10μm, microbial charge, air change numbers and differential pressure were measured. To quantify the influence of the surgical environment on the Surgical Site Infections (SSIs) so to minimize the risk in hospitalized patients the data were collected under different conditions. The correlation pattern analysis, based on factorial multivariate techniques, put in evidence the indoor environmental conditions in which parameters characterizing air quality show a strong correlation. Moreover, this analysis allowed to define which staff behaviors introduced the greatest variations in the correlation pattern. Moreover, a clustering procedure allows defining different typologies of ORs, based on their characteristics. The multivariate approach allows to identify the role of each air quality parameter in the correlation structure of the data and to evaluate how their role plays when the condition of the surgical environment changes