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EASY DANUBE

EASY DANUBE. Environmental Assessment SYstem. EASY DANUBE. Assessment of environmental quality of the Danube area by an integrated approach using remote sensing, laboratory analyses and in-field monitoring and surveys. Study area. REMOTE SENSING. ENVIRONMENT. AIR. SOIL AND VEGETATION.

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EASY DANUBE

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  1. EASY DANUBE Environmental Assessment SYstem

  2. EASY DANUBE Assessment of environmental quality of the Danube area by an integrated approach using remote sensing, laboratory analyses and in-field monitoring and surveys Study area

  3. REMOTE SENSING ENVIRONMENT AIR SOIL AND VEGETATION ENVIRONMENTAL INFORMATION SYSTEM WATER ENVIRONMENTAL QUALITY Project architecture

  4. Chimere model Satellite PM10, PM2.5 (NO3-, SO42-, NH4+, OC, EC), O3, NOx, CO, SO2, Meterological parameters (T,P, RH%, wind, radiation)

  5. PMchemical-physicalcharacterization

  6. MODIS (Moderate Resolution Imaging Spectroradiometer) On board Earth Observing System (EOS) Terra and Aqua satellites; 36 channels (0.4 – 14.4 mm) 7 channels (0.47, 0.55, 0.66, 0.87, 1.24, 1.64, 2.1 mm) provides the spectral information of Aerosol Optical Properties Near global coverage (95%) everyday North-Italy crossing time: ~ 9-13 UTC Sun-Synchronous satellites Reflectance 0.47, 0.66, 2.1 mm (500 m res.) AOD 550 nm 10x10 km2 pixels

  7. PM and satellite MODIS AOD (550 nm) data in Milan: Model results • Mod_9 and Mod_10 were evaluated dividing the original dataset in 2 part: • 2/3 of data as Training set • 1/3 of data as Test set RMSE: 5.48 mg/m3 The division was made in order to mantain the variable seasonal pattern in the two dataset RMSE: 9.89 mg/m3

  8. Chimere The CHIMERE multi-scale model is primarily designed to produce daily forecasts of ozone, aerosols and other pollutants and make long-term simulations (entire seasons or years) for emission control scenarios. CHIMERE runs over a range of spatial scale from the regional scale (several thousand kilometers) to the urban scale (100-200 Km) with resolutions from 1-2 Km to 100 Km. CHIMERE is a parallel model that has been tested on machines ranging from desktop PCs running the GNU/Linux operating system, to massively parallel supercomputers (HPCD at ECMWF). MILANO-BICOCCA UNIVERSITY DEPARTMENT OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY

  9. Soil and Vegetation Why soil quality ? From European Environmental Agency: “Soil underpins 90% of all human food, fiber, and fuel and is essentialfor water and ecosystem health. It is second only to the oceans as a global carbon sink; holding an important role in the potential slowing of climate change” Soil quality assessment, maintenance and restoration

  10. 50 Km Soil and Vegetation Soil quality assessment: proposed study area Cross border area between Romania and Bulgaria: about 30000 Km2

  11. Environment degradation - Many important plant and animal species disappear - Decrease in crop production Soil and Vegetation Assessment of soil quality in relation to: soil contamination Human health: food chain

  12. Soil and Vegetation How to assess soil contamination? Analytical determinations of organic and inorganic pollutants + Biomonitoring strategies Soil effects on plant and animal biomonitors

  13. 18 Km 18 Km Grid: LUCAS EUROSTAT(Land Use/Cover Area from statistical Survey) Soil and Vegetation Soil sampling Systematic grid First monitoring level

  14. ML2 ML3 18 km 6 km Non systematic sampling Soil and Vegetation ML1 18 km Chemical and biological analyses 3 independent sampling for each station Comparison of results with remote sensing information (land use and pollution sources) ML2

  15. Soil and Vegetation Final monitoring results Development of thematic maps showing soil quality in the study area criticisms Correlation among soil quality, land use and possible sources of pollution

  16. Austrian pine woodland No cover land Hornbeam woodland Beech woodland Grass Turkey oak woodland Soil and Vegetation Vegetation plots • within each plot (12x12 mt): • species list • % of ground cover by each species • site parameters woodland shrubland Vegetation survey a) Plant diversity values b) Alien species frequency

  17. Soil and Vegetation Specific objective: the alien species Invasion caused by Habitat loss / degradation: industries and agriculture Tourism Genetic pollution (hybrids) Climatic changes Some danubian alien species Impatiens glandulifera Fallopia japonica Aster novi-belgii Solidago gigantea

  18. Soil and Vegetation Development of thematic maps showing vegetation quality in the monitored area Development of thematic maps showing soil quality in the monitored area criticisms restoration • Decision support system

  19. Quality – physico-chemical survey – microbiological analyses Quantity – hydrological data Habitat – Morphology & Ecology Dipartimento di Scienze dell’Ambiente e del Territorio Università degli Studi di Milano - Bicocca Water

  20. Active Monitoring Broad Operativity Fixed Sampling Stations Remote Control Dipartimento di Scienze dell’Ambiente e del Territorio Università degli Studi di Milano - Bicocca Water Quality Survey Sampling sites: upstream and downstream of the identified major stressors. Weighting reciprocal influences

  21. Dipartimento di Scienze dell’Ambiente e del Territorio Università degli Studi di Milano - Bicocca Water Quality Survey A range of about 40 physico-chemical parameters and 3 microbiological indicators (E.coli, S.faecalis, P.aeruginosa) A customized “check-up” for River Danube A reference frame for further assessment A complete survey and laboratory system, ready to go with trained Bulgarian and Romanian technicians.

  22. Dipartimento di Scienze dell’Ambiente e del Territorio Università degli Studi di Milano - Bicocca Microbiological Diversity Molecular Fingerprints of microbial water comunity Construction of 16S rRNA library and identification by sequences of the species present in the microbial comunity

  23. Flow rate Habitat Assessment Polluting Loads Dipartimento di Scienze dell’Ambiente e del Territorio Università degli Studi di Milano - Bicocca Hydrology Water Levels Models Decision-Making Support

  24. Dipartimento di Scienze dell’Ambiente e del Territorio Università degli Studi di Milano - Bicocca Morphology Satellite/Remote Survey River Functionality Assessment Habitat Identification

  25. Dipartimento di Scienze dell’Ambiente e del Territorio Università degli Studi di Milano - Bicocca Biomonitoring WFD 2000/60 Let the river ecosystem speak by itself

  26. Dipartimento di Scienze dell’Ambiente e del Territorio Università degli Studi di Milano - Bicocca Data Set Present River Conditions Understanding of River Dynamics Knowledge of River Habitat Suitability, Biotic Communities and Microbiological Diversity Support to Decision-Making in the Future Help for Sustainable Development Definition of Priorities in River Restoration

  27. ENVIRONMENTAL INFORMATION SYSTEM Hardware Infrastructure Raw data client Management and Analysis client Management and Analysis Environmental monitoring stations and ground data Raw data client Management and Analysis ComputerServer

  28. ENVIRONMENTAL INFORMATION SYSTEM Server Software Infrastructure Features of the infrastructure Databases PostgreSQL • Raw data import from: • - satellite • - environmental monitoring stations • - lab analyses • Data integration • Remote user interface for data management and analysis • Data Mining Algorithms Data Management and analysistools (python, scipy, matlab, chimere, home_madealghoritms ) Application server java (glassfish, tomcat), python (plone/zope) web interface

  29. E. I. S.: • Integration of the results • On-line data diffusion and website • Skilled technicians ENVIRONMENTAL QUALITY Expected results REMOTE SENSING • AIR: • estimate of the direct effect of aerosol on climate from LIDAR and AERONET sun photometer • behavioural assessment of air pollution in the atmosphere over the CB area using CHIMERE 3D simulation model and air pollution forecast • creation of air quality maps including PM10, PM2.5, O3, NO, NO2, CO, SO2 using a coupled system of models and satellite remote sensing • 4 Skilled technicians • SOIL AND VEGETATION: • thematic maps showingthe quality of the soils and the vegetation in the study area. • correlation between soil/vegetation quality and possible sources of pollution. • validation and integration of remote sensing results concerning land use and vegetation • 4 skilled technicians • WATER: • concentrations of the basic pollution indicators and of some potentially hazardous pollutants • hydromorphological state • habitat availability • health of biotic communities • potential toxicity • self-purifying potential • microbiological quality and diversity • Ongoing continuous monitoring • 4 skilled technicians

  30. 24 Stage 4: Data analysis and result integration; WP 1, 2, 3, 4, 5 18 Stage 3: Monitoring (in field and laboratory analyses; remote sensing); WP 1, 2, 3, 4, 5 Transfer of knowledge and technology; WP 5 Stage 2: Sampling logistic (choice of sampling stations, monitoring parameters, installation of automatic monitoring equipments, organization of in-field sampling and analyses); WP1, 2, 3, 5 6 4 Stage 1: Territory investigation (land use, pollutant sources, climate); WP1, 2, 3, 5 0 Project schedule and partners involved in each single stage UNIMIB + CNR + Bulgarian and Romanian Partners UNIMIB + Bulgarian and Romanian Partners Development of the environmental information system; WP 4 UNIMIB + Bulgarian and Romanian Partners + industrial suppliers of equipment and instruments UNIMIB + Bulgarian and Romanian Partners

  31. Thank you

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