ALBERT

Description: This study aimed to describe the degree of annoyance among pregnant women in a Spanish cohort and to examine associations with proximity to traffic, NO2 and benzene exposure. We included 2457 participants from the Spanish Childhood and Environment study. Individual exposures to outdoor NO2 and benzene were estimated, temporally adjusted for pregnancy. Interviews about sociodemographic variables, noise and air pollution were carried out. Levels of annoyance were assessed using a scale from 0 (none) to 10 (strong and unbearable); a level of 8 to 10 was considered high. The reported prevalence of high annoyance levels from air pollution was 11.2% and 15.0% from noise; the two variables were moderately correlated (0.606). Significant correlations between NO2 and annoyance from air pollution (0.154) and that from noise (0.181) were observed. Annoyance owing to noise and air pollution had a low prevalence in our Spanish population compared with other European populations. Both factors were associated with proximity to traffic. In multivariate models, annoyance from air pollution was related to NO2, building age, and country of birth; annoyance from noise was only related to the first two. The health burden of these exposures can be increased by stress caused by the perception of pollution sources.

Description: Time series of remotely sensed data are an important source of information for understanding land cover dynamics. In particular, the fraction of absorbed photosynthetic active radiation (fAPAR) is a key variable in the assessment of vegetation primary production over time. However, the fAPAR series derived from polar orbit satellites are not continuous and consistent in space and time. Filtering methods are thus required to fill in gaps and produce high-quality time series. This study proposes an adapted (iteratively reweighted) local regression filter (LOESS) and performs a benchmarking intercomparison with four popular and generally applicable smoothing methods: Double Logistic (DLOG), smoothing spline (SSP), Interpolation for Data Reconstruction (IDR) and adaptive Savitzky-Golay (ASG). This paper evaluates the main advantages and drawbacks of the considered techniques. The results have shown that ASG and the adapted LOESS perform better in recovering fAPAR time series over multiple controlled noisy scenarios. Both methods can robustly reconstruct the fAPAR trajectories, reducing the noise up to 80% in the worst simulation scenario, which might be attributed to the quality control (QC) MODIS information incorporated into these filtering algorithms, their flexibility and adaptation to the upper envelope. The adapted LOESS is particularly resistant to outliers. This method clearly outperforms the other considered methods to deal with the high presence of gaps and noise in satellite data records. The low RMSE and biases obtained with the LOESS method (|rMBE| 〈 8%; rRMSE 〈 20%) reveals an optimal reconstruction even in most extreme situations with long seasonal gaps. An example of application of the LOESS method to fill in invalid values in real MODIS images presenting persistent cloud and snow coverage is also shown. The LOESS approach is recommended in most remote sensing applications, such as gap-filling, cloud-replacement, and observing temporal dynamics in situ where rapid seasonal changes are produced.

Description: Sensors, Vol. 18, Pages 2188: Real-Time Vehicle Roll Angle Estimation Based on Neural Networks in IoT Low-Cost Devices Sensors doi: 10.3390/s18072188 Authors: Javier García Guzmán Lisardo Prieto González Jonatan Pajares Redondo Mat Max Montalvo Martínez María Jesús L. Boada The high rate of vehicle-crash victims has a fatal economic and social impact in today’s societies. In particular, road crashes where heavy vehicles are involved cause more severe damage because they are prone to rollover. For this reason, many researches are focused on developing RSC Roll Stability Control (RSC) systems. Concerning the design of RSC systems with an adequate performance, it is mandatory to know the dynamics of the vehicle. The main problem arises from the lack of ability to directly capture several required dynamic vehicle variables, such as roll angle, from low-cost sensors. Previous studies demonstrate that low-cost sensors can provide data in real-time with the required precision and reliability. Even more, other research works indicate that neural networks are efficient mechanisms to estimate roll angle. Nevertheless, it is necessary to assess that the fusion of data coming from low-cost devices and estimations provided by neural networks can fulfill hard real-time processing constraints, achieving high level of accuracy during circulation of a vehicle in real situations. In order to address this issue, this study has two main goals: (1) Design and develop an IoT based architecture, integrating ANN in low cost kits with different hardware architectures in order to estimate under real-time constraints the vehicle roll angle. This architecture is able to work under high dynamic conditions, by following specific best practices and considerations during its design; (2) assess that the IoT architecture deployed in low-cost experimental kits achieve the hard real-time performance constraints estimating the roll angle with the required calculation accuracy. To fulfil these objectives, an experimental environment was set up, composed of a van with two set of low-cost kits, one including a Raspberry Pi 3 Model Band the other having an Intel Edison System on Chip linked to a SparkFun 9 Degrees of Freedom module. This experimental environment be tested in different maneuvers for comparison purposes. Neural networks embedded in low-cost sensor kits provide roll angle estimations highly approximated to real values. Even more, Intel Edison and Raspberry Pi 3 Model B have enough computing capabilities to successfully run roll angle estimation based on neural networks to determine rollover risk situations, fulfilling real-time operation restrictions stated for this problem.

Description: Water, Vol. 10, Pages 664: The Water–Energy–Food Nexus: A Fuzzy-Cognitive Mapping Approach to Support Nexus-Compliant Policies in Andalusia (Spain) Water doi: 10.3390/w10050664 Authors: Pilar Martinez Maria Blanco Bente Castro-Campos Water, energy and food are essential resources for economic development and social well-being. Framing integrated policies that improve their efficient use requires understanding the interdependencies in the water–energy–food (WEF) nexus. Stakeholder involvement in this process is crucial to represent multiple perspectives, ensure political legitimacy and promote dialogue. In this research, we develop and apply a participatory modelling approach to identify the main interlinkages within the WEF nexus in Andalusia, as a starting point to developing a system dynamic model at a later stage. The application of fuzzy cognitive mapping enabled us to gain knowledge on the WEF nexus according to opinions from 14 decision-makers, as well as contributing to raising awareness and building consensus among stakeholders. Results show that climate change and water availability are key drivers in the WEF nexus in Andalusia. Other variables with significant interlinkages within the WEF nexus are food production, irrigated agriculture, energy cost, socio-economic factors, irrigation water use, environmental conservation, and farm performance indicators. The scenario analysis reveals the interdependencies among nexus sectors and the existence of unanticipated effects when changing variables in the system, which need to be considered to design integrated policies.

Description: Remote Sensing, Vol. 10, Pages 763: A Critical Comparison of Remote Sensing Leaf Area Index Estimates over Rice-Cultivated Areas: From Sentinel-2 and Landsat-7/8 to MODIS, GEOV1 and EUMETSAT Polar System Remote Sensing doi: 10.3390/rs10050763 Authors: Manuel Campos-Taberner Francisco García-Haro Lorenzo Busetto Luigi Ranghetti Beatriz Martínez María Amparo Gilabert Gustau Camps-Valls Fernando Camacho Mirco Boschetti Leaf area index (LAI) is a key biophysical variable fundamental in natural vegetation and agricultural land monitoring and modelling studies. This paper is aimed at comparing, validating and discussing different LAI satellite products from operational services and customized solution based on innovative Earth Observation (EO) data such as Landsat-7/8 and Sentinel-2A. The comparison was performed to assess overall quality of LAI estimates for rice, as a fundamental input of different scale (regional to local) operational crop monitoring systems such as the ones developed during the “An Earth obseRvation Model based RicE information Service” (ERMES) project. We adopted a multiscale approach following international recognized protocols of the Committee on Earth Observation Satellites (CEOS) Land Product Validation (LPV) guidelines in different steps: (1) acquisition of representative field sample measurements, (2) validation of decametric satellite product (10–30 m spatial resolution), and (3) exploitation of such data to assess quality of medium-resolution operational products (~1000 m). The study areas were located in the main European rice areas in Spain, Italy and Greece. Field campaigns were conducted during three entire rice seasons (2014, 2015 and 2016—from sowing to full-flowering) to acquire multi-temporal ground LAI measurements and to assess Landsat-7/8 LAI estimates. Results highlighted good correspondence between Landsat-7/8 LAI estimates and ground measurements revealing high correlations (R2 ≥ 0.89) and low root mean squared errors (RMSE ≤ 0.75) in all seasons. Landsat-7/8 as well as Sentinel-2A high-resolution LAI retrievals, were compared with satellite LAI products operationally derived from MODIS (MOD15A2), Copernicus PROBA-V (GEOV1), and the recent EUMETSAT Polar System (EPS) LAI product. Good agreement was observed between high- and medium-resolution LAI estimates. In particular, the EPS LAI product was the most correlated product with both Landsat/7-8 and Sentinel-2A estimates, revealing R2 ≥ 0.93 and RMSE ≤ 0.53 m2/m2. In addition, a comparison exercise of EPS, GEOV1 and MODIS revealed high correlations (R2 ≥ 0.90) and RMSE ≤ 0.80 m2/m2 in all cases and years. The temporal assessment shows that the three satellite products capture well the seasonality during the crop phenological cycle. Discrepancies are observed mainly in absolute values retrieved for the peak of rice season. This is the first study that provides a quantitative assessment on the quality of available operational LAI product for rice monitoring to both the scientific community and users of agro-monitoring operational services.

Description: Nitrogen is a main contaminant of wastewater worldwide. Novel processes for nitrogen removal have been developed over the last several decades. One of these is the partial nitritation process. This process includes the oxidation of ammonium to nitrite without the generation of nitrate. The partial nitritation process has several advantages over traditional nitrification-denitrification processes for nitrogen removal from wastewaters. In addition, partial nitritation is required for anammox elimination of nitrogen from wastewater. Partial nitritation is affected by operational conditions and substances present in the influent, such as quinolone antibiotics. In this review, the impact that several operational conditions, such as temperature, pH, dissolved oxygen concentration, hydraulic retention time and solids retention time, have over the partial nitritation process is covered. The effect of quinolone antibiotics and other emerging contaminants are discussed. Finally, future perspectives for the partial nitritation process are commented upon.

Description: Sustainability, Vol. 10, Pages 90: Algerian Carob Tree Products: A Comprehensive Valorization Analysis and Future Prospects Sustainability doi: 10.3390/su10010090 Authors: Rosa Mahtout Víctor Ortiz-Martínez María Salar-García Isabel Gracia Francisco Hernández-Fernández Antonia Pérez de los Ríos Farid Zaidia Sergio Sanchez-Segado Luis Lozano-Blanco This research presents a thorough analysis of the nutrients and anti-nutrients contained in different products from Algerian carob tree, Ceratonia siliqua L. (pod, pulp, seeds and leaves). Other parameters such as moisture, ash content and calorific value were also determined. The main purpose was to characterize these products derived from carob tree and analyze their possible valorization in several fields such as chemical, energy or medical industries. The results show that these products contain low amount of crude lipids (2.4–4.5%), moderate amounts of protein (4–7.4%) and high levels of total sugar (up to 66.6%). The compositional analysis reveals high nutritional values but, at the same time, it is also worth underscoring their high content in anti-nutrients: (i) trypsin inhibitor (6.4–7.3 mg·g−1); and (ii) phytic acid (0.6–0.94 mg·g−1). This work quantifies these two secondary metabolites in carob tree products for the first time. Finally, based on the results obtained, a process scheme is proposed for the complete use of carob tree products, including the use of anti-nutrients (trypsin inhibitors and phytic acid) for bio-medical applications since many research studies support that these compounds have great potential in this field.

Description: Sustainability, Vol. 10, Pages 3008: Durability Studies of Solar Reflectors Used in Concentrating Solar Thermal Technologies under Corrosive Sulfurous Atmospheres Sustainability doi: 10.3390/su10093008 Authors: Alejandro García-Segura Aránzazu Fernández-García Francisco Buendía-Martínez María Jesús Ariza Florian Sutter Loreto Valenzuela Concentrating solar thermal (CST) technologies are a feasible and promising option to tackle worldwide energy problems. These solar facilities are sometimes located near industrial sites, where their main components—including concentrating solar reflectors—are prone to significant degradation caused by corrosive agents, especially in the presence of sulfurous atmospheres such as H2S and SO2. This paper focuses on analyzing the influence of sulfurous atmospheres on the durability of reflector materials used in CST technologies. To this end, accelerated aging tests were performed on the most commonly used materials found in solar reflectors (i.e., thick silvered glass and aluminum-based reflectors) by applying the same concentrations of H2S and SO2 under the same conditions of temperature and relative humidity. The results showed that the solar reflectors based on a silver reflective layer are significantly corroded by H2S atmospheres—several corrosion defects were found in the samples tested. However, those based on aluminum were barely affected by sulfurous environments in the conditions tested. Nonetheless, the study suggests that both reflector types are suitable candidates, depending on the purpose of the CST technology in question and the specific environmental conditions.

Description: In cities with problems of aridity and a shortage of drinking water supply, there is an urgent need to establish alternatives for an adequate water management program. This study proposes an estimation through which users can select a rainwater harvesting system for non-drinking water consumption. For the cities of Pachuca and Mineral de la Reforma, State of Hidalgo, Central Mexico, the historical record of rainfall analyzed covers a period of 33 years (1980–2013). We calculated the monthly volume of rainwater harvestable from roof areas (VR, m3) with household roof areas (Hra) of 45 m2, 50 m2, 100 m2 and 200 m2. It is proposed to replace in each single house the flush toilets and washing machine with ecological devices with consumptions of 4.8 L/flush and 70 L/load, respectively. Furthermore, a maximum and a minimum consumption of eight and six flushes/day/person (flush toilets) and five and four loads/week (washing machine), respectively, are proposed. From these considerations, our estimations of the harvestable rainwater showed that households with Hra of 45 m2 and 50 m2 would depend on the water supply system of the public network during part of the year. On the other hand, households with Hra of 100 m2 and 200 m2 might be able to store enough water to meet other needs besides toilet flushing and laundry.

Description: Symmetry, Vol. 10, Pages 24: Efficient Location of Resources in Cylindrical Networks Symmetry doi: 10.3390/sym10010024 Authors: José Carreño José Martínez María Puertas The location of resources in a network satisfying some optimization property is a classical combinatorial problem that can be modeled and solved by using graphs. Key tools in this problem are the domination-type properties, which have been defined and widely studied in different types of graph models, such as undirected and directed graphs, finite and infinite graphs, simple graphs and hypergraphs. When the required optimization property is that every node of the network must have access to exactly one node with the desired resource, the appropriate models are the efficient dominating sets. However, the existence of these vertex sets is not guaranteed in every graph, so relaxing some conditions is necessary to ensure the existence of some kind of dominating sets, as efficient as possible, in a larger number of graphs. In this paper, we study independent [ 1 , 2 ] -sets, a generalization of efficient dominating sets defined by Chellali et al., in the case of cylindrical networks. It is known that efficient dominating sets exist in very special cases of cylinders, but the particular symmetry of these graphs will allow us to provide regular patterns that guarantee the existence of independent [ 1 , 2 ] -sets in every cylinder, except in one single case, and to compute exact values of the optimal parameter, the independent [ 1 , 2 ] -number, in cylinders of selected sizes.