Food security among dryland pastoralists and agropastoralists: The climate, land-use change, and population dynamics nexus

During the last decades, pastoralist, and agropastoralist populations of the world’s drylands have become exceedingly vulnerable to regional and global changes. Specifically, exacerbated stressors imposed on these populations have adversely affected their food security status, causing humanitarian emergencies and catastrophes. Of these stressors, climate variability and change, land-use and management practices, and dynamics of human demography are of a special importance. These factors affect all four pillars of food security, namely, food availability, access to food, food utilization, and food stability. The objective of this study was to critically review relevant literature to assess the complex web of interrelations and feedbacks that affect these factors. The increasing pressures on the world’s drylands necessitate a comprehensive analysis to advise policy makers regarding the complexity and linkages among factors, and to improve global action. The acquired insights may be the basis for alleviating food insecurity of vulnerable dryland populations.info:eu-repo/semantics/acceptedVersio

Cooling degree models and future energy demand in the residential sector. A seven-country case study

The intensity and duration of hot weather and the number of extreme weather events, such as heatwaves, are increasing, leading to a growing need for space cooling energy demand. Together with the building stock’s low energy performance, this phenomenon may also increase households’ energy consumption. On the other hand, the low level of ownership of cooling equipment can cause low energy consumption, leading to a lack of indoor thermal comfort and several health-related problems, yet increasing the risk of energy poverty in summer. Understanding future temperature variations and the associated impacts on building cooling demand will allow mitigating future issues related to a warmer climate. In this respect, this paper analyses the effects of change in temperatures in the residential sector cooling demand in 2050 for a case study of nineteen cities across seven countries: Cyprus, Finland, Greece, Israel, Portugal, Slovakia, and Spain, by estimating cooling degree days and hours (CDD and CDH). CDD and CDH are calculated using both fixed and adaptive thermal comfort temperature thresholds for 2020 and 2050, understanding their strengths and weaknesses to assess the effects of warmer temperatures. Results suggest a noticeable average increase in CDD and CDH values, up to double, by using both thresholds for 2050, with a particular interest in northern countries where structural modifications in the building stock and occupants’ behavior should be anticipated. Furthermore, the use of the adaptive thermal comfort threshold shows that the projected temperature increases for 2050 might affect people’s capability to adapt their comfort band (i.e., indoor habitability) as temperatures would be higher than the maximum admissible values for people’s comfort and health.The paper stems from collaborative work within COST Action ‘European Energy Poverty: Agenda Co-Creation and Knowledge Innovation’ (ENGAGER 2017–2021, CA16232) funded by European Cooperation in Science and Technology—www.cost.eu (5 December 2020). João Pedro Gouveia and Pedro Palma acknowledge and are thankful for the support provided to CENSE by the Portuguese Foundation for Science and Technology (FCT) through the strategic project UIDB/04085/2020 and through the scholarship SFRH/BD/146732/2019 provided to Pedro). Ricardo Barbosa acknowledges the support for this work, which was partly financed by FCT/MCTES through national funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Structural Engineering (ISISE), under reference UIDB/04029/2020

Clustering and forecasting of dissolved oxygen concentration on a river basin

The aim of this contribution is to combine statistical methodologies to geographically classify homogeneous groups of water quality monitoring sites based on similarities in the temporal dynamics of the dissolved oxygen (DO) concentration, in order to obtain accurate forecasts of this quality variable. Our methodology intends to classify the water quality monitoring sites into spatial homogeneous groups, based on the DO concentration, which has been selected and considered relevant to characterize the water quality. We apply clustering techniques based on Kullback Information, measures that are obtained in the state space modelling process. For each homogeneous group of water quality monitoring sites we model the DO concentration using linear and state space models, which incorporate tendency and seasonality components in different ways. Both approaches are compared by the mean squared error (MSE) of forecasts

Estimation of PM10-bound As, Cd, Ni and Pb levels by means of statistical modelling: PLSR and ANN approaches

Air quality assessment regarding metals and metalloids using experimental measurements is expensive and time consuming due to the cost and time required for the analytical determination of the levels of these pollutants. According to the European Union (EU) Air Quality Framework Directive (Directive 2008/50/EC), other alternatives, such as objective estimation techniques, can be considered for ambient air quality assessment in zones and agglomerations where the level of pollutants is below a certain concentration value known as the lower assessment threshold. These conditions occur in urban areas in Cantabria (northern Spain). This work aims to estimate the levels of As, Cd, Ni and Pb in airborne PM10 at two urban sites in the Cantabria region (Castro Urdiales and Reinosa) using statistical models as objective estimation techniques. These models were developed based on three different approaches: partial least squares regression (PLSR), artificial neural networks (ANNs) and an alternative approach consisting of principal component analysis (PCA) coupled with ANNs (PCA-ANN). Additionally, these models were externally validated using previously unseen data. The results show that the models developed in this work based on PLSR and ANNs fulfil the EU uncertainty requirements for objective estimation techniques and provide an acceptable estimation of the mean values. As a consequence, they could be considered as an alternative to experimental measurements for air quality assessment regarding the aforementioned pollutants in the study areas while saving time and resources.The authors gratefully acknowledge the financial support from the Spanish Ministry of Economy and Competitiveness through the Project CMT2010-16068. The authors also thank the Regional Environment Ministry of the Cantabria Government for providing the PM10 samples at the Castro Urdiales and Reinosa sites

Exploring the impact of particulate matter on mortality in coastal Mediterranean environments

Air pollution is one of the most important problems the world is facing nowadays, adversely affecting public health and causing millions of deaths every year. Particulate matter is a criteria pollutant that has been linked to increased morbidity, as well as all-cause and cause-specific mortality. However, this association remains under-investigated in smaller-size cities in the Eastern Mediterranean, which are also frequently affected by heat waves and dust storms. This study explores the impact of particulate matter with an aerodynamic diameter ≤ 10 μm (PM10) and ≤ 2.5 μm (PM2.5) on mortality (all-cause, cardiovascular, respiratory) in two coastal cities in the Eastern Mediterranean; Thessaloniki, Greece and Limassol, Cyprus. Generalized additive Poisson models were used to explore overall and gender-specific associations, controlling for long- and short-term patterns, day of week and the effect of weather variables. Moreover, the effect of different lags, season, co-pollutants and dust storms on primary associations was investigated. A 10 μg/m3 increase in PM2.5 resulted in 1.10 % (95 % CI: -0.13, 2.34) increase in cardiovascular mortality in Thessaloniki, and in 3.07 % (95 % CI: -0.90, 7.20) increase in all-cause mortality in Limassol on the same day. Additionally, significant positive associations were observed between PM2.5 as well as PM10 and mortality at different lags up to seven days. Interestingly, an association with dust storms was observed only in Thessaloniki, having a protective effect, while the gender-specific analysis revealed significant associations only for the males in both cities. The outcome of this study highlights the need of city- or county-specific public health interventions to address the impact of climate, population lifestyle behaviour and other socioeconomic factors that affect the exposure to air pollution and other synergistic effects that alter the effect of PM on population health

Extreme weather and air pollution effects on cardiovascular and respiratory hospital admissions in Cyprus.

In many regions of the world, climatic change is associated with increased extreme temperatures, which can have severe effects on mortality and morbidity. In this study, we examine the effect of extreme weather on hospital admissions in Cyprus, for inland and coastal areas, through the use of synoptic weather classifications (air mass types). In addition, the effect of particulate air pollution (PM10) on morbidity is examined. Our results show that two air mass types, namely (a) warm, rainy days with increased levels of water vapour in the atmosphere and (b) cold, cloudy days with increased levels of precipitation, were associated with increased morbidity in the form of hospital admissions. This was true both for cardiovascular and respiratory conditions, for all age groups, but particularly for the elderly, aged over 65. Particulate air pollution was also associated with increased morbidity in Cyprus, where the effect was more pronounced for cardiovascular diseases

Cooling degree models and future energy demand in the residential sector. A seven-country case study

The intensity and duration of hot weather and the number of extreme weather events, such as heatwaves, are increasing, leading to a growing need for space cooling energy demand. Together with the building stock's low energy performance, this phenomenon may also increase households' energy consumption. On the other hand, the low level of ownership of cooling equip-ment can cause low energy consumption, leading to a lack of indoor thermal comfort and several health-related problems, yet increasing the risk of energy poverty in summer. Understanding future temperature variations and the associated impacts on building cooling demand will allow mitigat-ing future issues related to a warmer climate. In this respect, this paper analyses the effects of change in temperatures in the residential sector cooling demand in 2050 for a case study of nineteen cities across seven countries: Cyprus, Finland, Greece, Israel, Portugal, Slovakia, and Spain, by estimating cooling degree days and hours (CDD and CDH). CDD and CDH are calculated using both fixed and adaptive thermal comfort temperature thresholds for 2020 and 2050, understanding their strengths and weaknesses to assess the effects of warmer temperatures. Results suggest a noticeable average increase in CDD and CDH values, up to double, by using both thresholds for 2050, with a particular interest in northern countries where structural modifications in the building stock and occupants' behavior should be anticipated. Furthermore, the use of the adaptive thermal comfort threshold shows that the projected temperature increases for 2050 might affect people's capability to adapt their comfort band (i.e., indoor habitability) as temperatures would be higher than the maximum admissible values for people's comfort and health. © 2021 by the authors. Licensee MDPI, Basel, Switzerland