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The potential impacts of climate-induced changes in air pollution levels and its impacts on population health were investigated. The IPCC scenario (SRES A2) was used to analyse the effects of climate on future PM10 concentrations over Portugal and their impact on short-term population exposure and mortality. The air quality modelling system has been applied with high spatial resolution looking on climate changes at regional scale. To quantify health impacts related to air pollution changes, the WHO methodology for health impact assessment was implemented. The results point to 8% increase of premature mortality attributed to future PM10 levels in Portugal. The pollution episodes with daily average PM10 concentration above the current legislated value (50 μg·m−3) would be responsible for 81% of attributable cases. The absolute number of deaths attributable to PM10 under future climate emphasizes the importance of indirect effects of climate change on human health.

AbstractThe widespread use of petroleum products in modern times has led to a search for alternative resources. Biofuel is a promising alternative to petroleum fuel, but biodiesel has a lower calorific value and is slightly more denser than diesel. To address this, a novel combination of GNA emulsified MME20 fuel is being investigated. This study aims to analyze the impact of a novel Nano additive blended biodiesel on engine performance and optimize the best compression ratio for the selected blend. The novelty of the study lies in the production of novel GNA emulsified MME fuel and its influence on a conventional CI engine. To achieve the objectives of the study, MME was produced using a two-phase transesterification method, and GNA was added to the MME20 at concentrations of 30, 60, and 90 ppm using the ultrasonication method. Engine experiments were then conducted using the prepared samples at CRs of 16, 17.5, and 19, and the results were compared with the standard diesel and MME20 blend. The results showed that the CP of the MME20 + GNA30 fuel at a CR 19 revealed a 14% increase compared to diesel. The ID of the fuel decreased by 20% compared to diesel at CR19, and there was a 23.5% increase in the CD for the MME20 + GNA30 blend compared to diesel at CR19. The BTHE for the MME20 + GNA30 fuel showed increases of 2.64% and BSFC and EGT decreases of 3.6% and 3.9%, respectively, at CR19 compared to the other blends. In summary, the study found that MME20 with GNA30, along with VCR, significantly enhanced the engine attributes compared to the pure diesel-operated standard CI engine conditions.

It is increasingly acknowledged that climate change is influencing terrestrial ecosystems by increased drought and rainfall intensities. Soil microbes are key drivers of many processes in terrestrial systems and rely on water in soil pores to fulfill their life cycles and functions. However, little is known on how drought and rainfall fluctuations, which affect the composition and structure of microbial communities, persist once original moisture conditions have been restored. Here, we study how simulated short-term drying and re-wetting events shape the community composition of soil fungi and prokaryotes. In a mesocosm experiment, soil was exposed to an extreme drought, then re-wetted to optimal moisture (50% WHC, water holding capacity) or to saturation level (100% WHC). Composition, community structure and diversity of microbes were measured by sequencing ITS and 16S rRNA gene amplicons 3 weeks after original moisture content had been restored. Drying and extreme re-wetting decreased richness of microbial communities, but not evenness. Abundance changes were observed in only 8% of prokaryote OTUs, and 25% of fungal OTUs, whereas all other OTUs did not differ between drying and re-wetting treatments. Two specific legacy response groups (LRGs) were observed for both prokaryotes and fungi. OTUs belonging to the first LRG decreased in relative abundance in soil with a history of drought, whereas OTUs that increased in soil with a history of drought formed a second LRG. These microbial responses were spread among different phyla. Drought appeared to be more important for the microbial community composition than the following extreme re-wetting. 16S profiles were correlated with both inorganic N concentration and basal respiration and ITS profiles correlated with fungal biomass. We conclude that a drying and/or an extreme re-wetting history can persist in soil microbial communities via specific response groups composed of members with broad phylogenetic origins, with possible functional consequences on soil processes and plant species. As a large fraction of OTUs responding to drying and re-wetting belonged to the rare biosphere, our results suggest that low abundant microbial species are potentially important for ecosystem responses to extreme weather events.

Abstract The growth and development of maize (Zea mays L.) largely depends on its nutrient uptake through the root. Hence, studying its growth, response, and associated metabolic reprogramming to stress conditions is becoming an important research direction. A genome-scale metabolic model (GSM) for the maize root was developed to study its metabolic reprogramming under nitrogen stress conditions. The model was reconstructed based on the available information from KEGG, UniProt, and MaizeCyc. Transcriptomics data derived from the roots of hydroponically grown maize plants were used to incorporate regulatory constraints in the model and simulate nitrogen-non-limiting (N+) and nitrogen-deficient (N−) condition. Model-predicted flux-sum variability analysis achieved 70% accuracy compared with the experimental change of metabolite levels. In addition to predicting important metabolic reprogramming in central carbon, fatty acid, amino acid, and other secondary metabolism, maize root GSM predicted several metabolites (l-methionine, l-asparagine, l-lysine, cholesterol, and l-pipecolate) playing a regulatory role in the root biomass growth. Furthermore, this study revealed eight phosphatidylcholine and phosphatidylglycerol metabolites which, even though not coupled with biomass production, played a key role in the increased biomass production under N-deficient conditions. Overall, the omics-integrated GSM provides a promising tool to facilitate stress condition analysis for maize root and engineer better stress-tolerant maize genotypes.

Heat stress is a global issue constraining pig productivity, and it is likely to intensify under future climate change. Technological advances in earth observation have made tools available that enable identification and mapping livestock species that are at risk of exposure to heat stress due to climate change. Here, we present a methodology to map the current and likely future heat stress risk in pigs using R software by combining the effects of temperature and relative humidity. We applied the method to growing-finishing pigs in Uganda. We mapped monthly heat stress risk and quantified the number of pigs exposed to heat stress using 18 global circulation models and projected impacts in the 2050s. Results show that more than 800 000 pigs in Uganda will be affected by heat stress in the future. The results can feed into evidence-based policy, planning and targeted resource allocation in the livestock sector.

Les systèmes agricoles sont intimement liés au changement climatique : ils sont d'une part affectés par la dérive de son état moyen et de sa variabilité, et sont d'autre part des contributeurs nets à l'évolution du climat par l'extension de leur surface et l'intensité de leur gestion. L'évolution du système climat-agriculture repose sur nombreux mécanismes qui s'étendent sur une large gamme d'échelles temporelles et spatiales, et sont interdépendants. Pour réduire l'incertitude associée à l'évolution de ce système et guider les choix collectifs pertinents, il est nécessaire d'intégrer ces processus sur cette gamme d'échelle temporelle et spatiale. Dans cette thèse, je me suis intéressé aux échelles spatiales allant de la plus petite unité décisionnelle des systèmes de production agricole (l'exploitation) à celle de la décision publique concernant ces interactions entre climat et agriculture (échelle nationale à supranationale). Je me suis d'autre part intéressé au court terme (quelques années) et à l'Europe. J'ai poursuivi le développement d'un outil de modélisation reposant sur le couplage du modèle d'offre agricole Européenne (AROPAj) et du modèle générique de culture (STICS), qui permet de prendre en compte les mécanismes adéquats à l'échelle du système de production, et leurs facteurs d'hétérogénéité à l'échelle de l'Europe. Cet outil m'a permis de mettre en valeur le rôle important à l'échelle Européenne des mécanismes de court-terme dans la réponse de l'offre agricole au changement climatique. En particulier, la prise en compte des adaptations de court terme des systèmes de production agricole modifie la vision habituellement retenue des impacts du changement climatique en Europe. J'ai de plus développé des méthodes alliant agronomie et statistique pour explorer l'hétérogénéité du comportement des principales cultures Européenne sous changement climatique entre régions, espèces et scénarios de changement climatique. Enfin, j'ai pu mettre en valeur la faible interaction en première analyse entre adaptation au changement climatique et réponse à la mise en place d'une politique réduction des émissions de gaz à effet de serre au niveau des systèmes de production agricole. Agriculture, and the climate system are closely linked: agricultural systems are driven by changes in mean climate and its variability, while their expansion and intensification contribute to the anthropogenic perturbation of the climate system. The evolution of the climate-agriculture system relies on numerous processes, which extend over a wide large range of temporal and spatial scale, and are intertwined. It is necessary to integrate these processes across scales in order to both reduce the uncertainty that overshadow the evolution of the system, and help clever decision making. In this work, I focused on that integration goal in the specific case of Europe for short-term time scales in a future horizon. I focused on typical spatial scales of decision making: from the smallest decision unit in agriculture (farm scale) to the one of policy making regarding agriculture-climate interactions (Europe). I continued the development of a modelling framework relying on the coupling of a microeconomic model of European agricultural supply (AROPAj) to a generic crop model (STICS), which account for adequate processes at farm scale, and for the factors that drive the heterogeneity in their net effects over Europe. This tool allowed me to highlight the specific role of farm-scale adaptations in the response of European agricultural supply to climate change. In particular, accounting for these processes alters the usual picture of climate change impacts over Europe. I further developed analytical methods building on agronomic and statistic knowledge to explore the heterogeneity in the response of major European crops, among geographical locations, species, and climate change scenarios. Finally, first results showed that at the farm scale, little interaction is expected between the adaptation to climate change and the implementation of a greenhouse gas mitigation policy targeting the agricultural sector.