Selecting optimal hyperspectral bands to discriminate nitrogen status in durum wheat: a comparison of statistical approaches

Hyperspectral data can provide prediction of physical and chemical vegetation properties, but data handling, analysis, and interpretation still limit their use. In this study, different methods for selecting variables were compared for the analysis of on-the-ground hyperspectral signatures of wheat grown under a wide range of nitrogen supplies. Spectral signatures were recorded at the end of stem elongation, booting, and heading stages in 100 georeferenced locations, using a 512-channel portable spectroradiometer operating in the 325–1075-nm range. The following procedures were compared: (i) a heuristic combined approach including lambda-lambda R² (LL R²) model, principal component analysis (PCA), and stepwise discriminant analysis (SDA); (ii) variable importance for projection (VIP) statistics derived from partial least square (PLS) regression (PLS-VIP); and (iii) multiple linear regression (MLR) analysis through maximum R-square improvement (MAXR) and stepwise algorithms. The discriminating capability of selected wavelengths was evaluated by canonical discriminant analysis. Leaf-nitrogen concentration was quantified on samples collected at the same locations and dates and used as response variable in regressive methods. The different methods resulted in differences in the number and position of the selected wavebands. Bands extracted through regressive methods were mostly related to response variable, as shown by the importance of the visible region for PLS and stepwise. Band selection techniques can be extremely useful not only to improve the power of predictive models but also for data interpretation or sensor design.     

The impact of the electricity tariff reform on renewable energies and energy efficiency investments: The case of the Italian residential market

This article investigates the impact that the electricity tariff reform is likely to have on investments in renewable energies (i.e., photovoltaics) and the adoption of energy efficiency measures (i.e., installation of heat pumps and efficient home appliances) in the residential market in Italy. The study develops detailed cost comparisons and simulations considering two different investment scenarios (before and after the reform) to conclude that the reform will: (i) have a negative impact on investments in photovoltaic systems; (ii) favor the adoption of energy efficiency measures, such as efficient home appliances.     

A comparison of octanol-water partitioning between organic chemicals and their metabolites in mammals

Bioaccumulation models take various elimination and uptake processes into account, estimating rates from chemical lipophilicity, expressed as the octanol-water partition ratio (K_ow). Here, we focussed on metabolism, which transforms parent compounds into usually more polar metabolites, thus enhancing elimination. The aim of this study was to quantify the change in lipophilicity of relevant organic pollutants undergoing various biotransformation reactions in mammals. We considered oxidation reactions catalyzed by three enzyme groups: cytochrome P450 (CYP), alcohol dehydrogenase (ADH), and aldehyde dehydrogenase (ALDH). Estimated log K_ow values of a selected dataset of parent compounds were compared with the log K_ow of their first metabolites. The log K_ow decreased by a factor that varies between 0 and −2, depending on the metabolic pathway. For reactions mediated by CYP, the decrease in K_ow was one order of magnitude for hydroxylated and epoxidated compounds and two orders of magnitude for dihydroxylated and sulphoxidated xenobiotics. On the other hand, no significant change in lipophilicity was observed for compounds N-hydroxylated by CYP and for alcohols and aldehydes metabolized by ADH and ALDH. These trends could be anticipated by the calculus method of log K_ow. Yet, they were validated using experimental log K_ow values, when available. These relationships estimate the extent to which the elimination of pollutants is increased by biotransformation. Thus, the quantification of the K_ow reduction can be considered as a first necessary step in an alternative approach to anticipate biotransformation rates, which are hard to estimate with existing methods.     

The influence of light exposure,water quality and vegetation on the removal of sulfonamides and tetracyclines: A laboratory-scale study

The effect of aquatic vegetation (Spyrogira sp. and Zannichellia palustris), light exposure and water quality (secondary-treated wastewater vs. ultrapure water) on the removal efficiency of six antibiotics (sulfonamides and tetracyclines) is studied in laboratory-scale reactors. After 20 d of treatment, 3–59% of sulfonamides were eliminated in the reactors exposed to light. Removal was about 10% in unplanted reactors in darkness. The elimination of tetracycline (TC) and oxytetracycline (OTC) ranged between 83% and 97% in both planted and unplanted reactors. However, in dark unplanted reactors, OTC was largely removed (88%) while only 15% of TC was eliminated. These results suggest that TC was mainly removed by photodegradation whereas biodegradation or hydrolysis process seems to be significant processes for OTC. Sulfonamides were mainly eliminated by biodegradation or indirect photodegradation processes. Pseudo-first order kinetics removal rates ranged from 0.003 and 0.007 d^?1 for Sulfamethazine and TC in the covered control reactors to 0.13 and 0.21 d^?1 for TC and OTC in the uncovered control reactors, with half-lives from 3 to 350 d. A TC photodegradation product was tentatively identified in uncovered reactors. This study highlights the important role played by light exposure in the elimination of antibiotics in polishing ponds.     

Material and energy recovery from Automotive Shredded Residues (ASR) via sequential gasification and combustion

Shredding is the common end-of-life treatment in Europe for dismantled car wrecks. It produces the so-called Automotive Shredded Residue (ASR), usually disposed of in landfill. This paper summarizes the outcome of a study carried out by Politecnico di Milano and LEAP with the support of Actelios SpA on the prospects of a technology based on sequential gasification and combustion of this specific waste stream. Its application to the treatment of ASR allows the recovery of large fractions of metals as non-oxidized, easily marketable secondary raw materials, the vitrification of most of the ash content and the production of power via a steam cycle. Results show that despite the unfavourable characteristics of ASR, the proposed technology can reach appealing energy performances. Three of four environmental impact indicators and the cumulative energy demand index are favourable, the main positive contributes being electricity production and metal recovery (mainly aluminium and copper). The only unfavourable indicator is the global warming index because, since most of the carbon in ASR comes from fossil sources, the carbon dioxide emissions at the stack of the thermal treatment plant are mainly non-renewable and, at the same time, the avoided biogas production from the alternative disposal route of landfilling is minor.     

Study on the influence of various factors in the hydrometallurgical processing of waste printed circuit boards for copper and gold recovery

The present lab-scale experimental study presents the process of leaching waste printed circuit boards (WPCBs) in order to recover gold by thioureation. Preliminary tests have shown that copper adversely affects gold extraction; therefore an oxidative leaching pre-treatment was performed in order to remove base metals. The effects of sulfuric acid concentration, hydrogen peroxide volume and temperature on the metal extraction yield were studied by analysis of variance (ANOVA). The highest copper extraction yields were 76.12% for sample A and 18.29% for sample D, after leaching with 2 M H₂SO₄, 20 ml of 30% H₂O₂ at 30 °C for 3 h. In order to improve Cu removal, a second leaching was performed only on sample A, resulting in a Cu extraction yield of 90%. Other experiments have shown the negative effect of the stirring rate on copper dissolution. The conditions used for the process of gold extraction by thiourea were: 20 g/L thiourea, 6 g/L ferric ion, 10 g/L sulfuric acid, 600 rpm stirring rate. To study the influence of temperature and particle size, this process was tested on pins manually removed from computer central processing units (CPUs) and on waste CPU for 3½ h. A gold extraction yield of 69% was obtained after 75% of Cu was removed by a double oxidative leaching treatment of WPCBs with particle sizes smaller than 2 mm.     

Characterization of the bioaerosol in a natural thermal cave and assessment of the risk of transmission of SARS-CoV-2 virus

Environmental Geochemistry and Health - Thermal caves represent an environment characterized by unique chemical/physical properties, often used for treatment and care of musculoskeletal,...     

E-bikers’ braking behavior: Results from a naturalistic cycling study

Abstract

Objective: The number of e-bike users has increased significantly over the past few years and with it the associated safety concerns. Because e-bikes are faster than conventional bicycles and more prone to be in conflict with road users, e-bikers may need to perform avoidance maneuvers more frequently. Braking is the most common avoidance maneuver but is also a complex and critical task in emergency situations, because cyclists must reduce speed quickly without losing balance. The aim of this study is to understand the braking strategies of e-bikers in real-world traffic environments and to assess their road safety implications. This article investigates (1) how cyclists on e-bikes use front and rear brakes during routine cycling and (2) whether this behavior changes during unexpected conflicts with other road users.

Methods: Naturalistic data were collected from 6 regular bicycle riders who each rode e-bikes during a period of 2 weeks, for a total of 32.5?h of data. Braking events were identified and characterized through a combined analysis of brake pressure at each wheel, velocity, and longitudinal acceleration. Furthermore, the braking patterns obtained during unexpected events were compared with braking patterns during routine cycling.

Results: In the majority of braking events during routine cycling, cyclists used only one brake at a time, favoring one of the 2 brakes according to a personal pre-established pattern. However, the favored brake varied among cyclists: 66% favored the rear brake and 16% the front brake. Only 16% of the cyclists showed no clear preference, variously using rear brake, front brake, or combined braking (both brakes at the same time), suggesting that the selection of which brake to use depended on the characteristics of the specific scenario experienced by the cyclist rather than on a personal preference. In unexpected conflicts, generally requiring a larger deceleration, combined braking became more prevalent for most of the cyclists; still, when combined braking was not applied, cyclists continued to use the favored brake of routine cycling. Kinematic analysis revealed that, when larger decelerations were required, cyclists more frequently used combined braking instead of single braking.

Conclusions: The results provide new insights into the behavior of cyclists on e-bikes and may provide support in the development of safety measures including guidelines and best practices for optimal brake use. The results may also inform the design of braking systems intended to reduce the complexity of the braking operation.