The presence of emerging contaminants (ECs) in the atmospheric environment is a growing and potential significant issue in environmental sciences. Environmental studies are mostly focused on the occurrence and fate of ECs in aqueous environments. In contrast, less attention is paid to the atmospheric compartment, which plays a significant role in the global cycling pollutants. It is now accepted that bioaerosols and particulate matter can be emitted to the air from common activated sludge processes (aeration tank) and during biosolid land spreading events. ECs may be adsorbed or trapped on airborne particles emitted from these sources and thus be transferred to the atmosphere. Hence, waste water treatment plants (WWTPs) could be an active source of ECs in the atmosphere through volatilization or aerosolization processes. WECARE main goals are (i) to provide valuable data on the occurrence of ECs in the atmosphere (ii) a better understanding of the impact of WWTPs and biosolid land spreading on the emissions of aerosols and ECs in the atmosphere (transfer processes) (ii) to also provide valuable data on key atmospheric parameters (gas-particle partitioning, particle size distribution of aerosols emitted, mass fluxes, …) which affect the deposition, chemical reactions, long-range transport and impact on human and ecosystem health of pollutants.

Reuse of treated wastewater is increasingly seen as one of the solutions to tackle the water scarcity problem and to limit the pollution load to surface water. Yet, using reclaimed water for non-potable purposes and particularly to irrigate food crops presents an exposure pathway for antibiotics and antibiotic resistant bacteria and genes (ARB&G) to enter the food chain. Wastewater reuse is currently of particular concern as potential source of selective pressure that elevates the levels of antibiotic resistance in native bacteria. There are also growing concerns that environmental concentrations of antibiotics exert a selective pressure on clinically relevant bacteria. These acute strains call for a major shift towards a more efficient monitoring strategies based on a limited number of indicators that would facilitate the assessment of the anthropogenic impact on the water cycle. This project aims at: i) establishing monitoring strategies based on the data-derived priorization of a set of indicator conatminants and pathogens for domestic wastewater, and ii) developping energy-efficient, cost-effective, and robust treatment systems for the decentralized production of treated wastewater mainly from domestic wastewater. Diagnostic indicators will be selected based on their regular occurrence, potential for mobility and toxicological relevance. The second major objective of this project is to design wastewater treatment technologies based on the combination of biology-based treatment systems using selected plants and microorganisms (e.g., fungi, endophytic bacteria and microalgae) and the use of low-cost engineered nanostructured materials for the catalytical activation of oxidants (persulfate and hydrogen peroxide). Such decentralized treatment systems using smart technologies will be tailored to remove key antibiotics and ARB&G. Thus, IDOUM project will help to protect our freshwater supply, reduce the risk of human exposure to toxic compounds and of antibioresistance spreading, and provide access to alternative sources of water.

Current Earth Observation systems provide operational tools to derive areal evapotranspiration (ET) for drought monitoring and sustainable management of agricultural water. But partitioning ET into transpiration T and evaporation E is also key for targeting plant water use efficiency and plant water stress conditions at landscape scale. T and E are estimated through land surface models (LSM) forced by visible/near infrared and thermal infrared (TIR) remote sensing (RS) data. However, water budget-based LSM face parameterization issues to constrain water limited T and E rates, while dual-source energy budget-based LSM forced by TIR observations provide separate estimates of T and E, but rely on specific assumptions to retrieve both components from a single composite surface temperature. Additional information is thus required, either specifically related to E (surface water content, cf. Sentinel-1 S1) or T (Shortwave infrared SWIR, cf. Sentinel-2). HiDRATE aims at determining how the existing and future (TRISHNA, LSTM) TIR observations can map T and E by synergistic use of RS observations of multiple wavelengths in conjunctions with LSMs of various complexities. This includes the directional RS signature in terms of soil and canopy cover fraction in the sensor field-of-view. The relevance of increasing modeling complexity or the number of RS constraints in inferring T and E will be assessed using in-situ experiments at local scale including independent ET, E/T, T and E estimates based on eddy covariance, lysimeters, sap flow and stable isotope measurements for several biomes and climates. Drone campaigns will be organized to mimic the revisit cycle of the future satellites. HiDRATE builds on the complementarity of two groups who share expertise in TIR ET retrieval: on the French side, experts in E+T measurements/modeling, as well as soil moisture mapping from S1; on the Luxembourg side, experts in airborne mapping as well as plant water stress assessment using SWIR.

Public and private stakeholders of the wastewater and stormwater sectors are increasingly confronted with the analysis of massive heterogeneous data (imprecise and uncertain geographical data, digital/analogue maps, etc). Obtaining accurate and updated information on the underground wastewater networks is a cumbersome task especially in cities undergoing urban expansion. This multidisciplinary project CROQUIS, designed through four work packages, aims to create a framework where researchers from Water Sciences and Artificial Intelligence will join forces in order to offer novel solutions for representing, merging, archiving, classifying, integrating domain knowledge, repairing and querying heterogeneous data capturing the main characteristics of wastewater and stormwater networks. The consortium, composed of two partners from AI (CRIL and I3S) and a partner from Water Science (HSM), provides very complementary skills essential to achieving the objectives of the project.

Leptospirosis is a severe bacterial disease with highest impact in the Tropics. Recent data show a growing incidence in Europe (France, Belgium, Croatia, the Netherlands). Leptospirosis affects 1 million humans yearly, killing 58,900, but remains neglected and attracts insufficient attention. One century ago, Noguchi outlined its epidemiology and pointed the role of the survival of leptospires “in nature”. Leptospires chronically colonize the kidneys of mammals and are shed in the environment, where humans get infected. Animal-environment-human interactions determine patterns of disease; thus understanding the ecology of leptospires in ecosystems is critical. Yet, leptospirosis has mostly been studied as a zoonosis; environmental determinants of transmission have not been an active field of research. Early work identified conditions for Leptospira survival; however, recent work show that assumptions need be revisited. It is assumed that pathogens only survive in soil or freshwater; yet no resistance form was ever evidenced. The ability of the environment to support the survival of leptospires is a cornerstone of leptospirosis epidemiology. SpIRAL aims at filling the gaps in knowledge of Leptospira habitat outside a host. SpIRAL goals are to (1) identify the environmental abiotic factors that impact Leptospira survival in soils and freshwater, (2) characterize the microbiota that shelter Leptospira in the environment (3) model the dynamics of Leptospira dispersion upon rainfall and (4) generate a spatial map of leptospirosis risk integrating environmental, ecological and climatic parameters. This holistic approach of the environmental component of leptospirosis will yield new knowledge and avenues for a better control of the disease, also making the case for other environment-borne infections. SpIRAL will take benefit of the expertise developed in New Caledonia in the fields of leptospirosis and soil sciences. A full knowledge of Leptospira environmental habitats will be acquired, requiring a substantial amount of information on the ecosystems allowing or oppositely impairing their viability. First a collection of georeferenced soils and sediments will be collected and characterized (physical and chemical soil analysis, presence of virulent leptospires in situ, prokaryotic and eukaryotic microbiota). Their ability to support the survival of Leptospira will be assessed in vitro using microcosms. The interaction of pathogenic leptospires with soil particles, with Free-Living Ameoba or in natural biofilms will also be studied, providing further insight into their environmental lifestyle. Taking benefit of a site fully equipped for hydrology, we will also study and model the dispersion of Leptospira during rainfalls, known triggers of leptospirosis outbreaks. The model will be established in the pilot watershed then evaluated in other areas of high incidence. The information gained on Leptospira dynamics in water under the influence of rain will prove for prevention. Data of SpIRAL together with known leptospirosis risk factors will be analyzed spatially to establish and evaluate a spatial map of disease risk. This model will be used to study the relative weights of risk factors and to translate research findings into health benefits. SpIRAL aims to provide a comprehensive understanding of the ecosystem in the persistence of- and dynamics of exposure to- leptospirosis. It will address knowledge gaps on basic aspects of Leptospira lifestyle outside a host, key determinants of human disease, and will provide an integrated, data-rich and comprehensive and generalizable picture of Leptospira environmental habitat. Shifting the paradigm of leptospirosis epidemiology from a zoonosis to an environment-borne infection, SpIRAL aims to better understand epidemiology and infer risk management strategies for a better control of the disease.