Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
«(Big) Data for
Env. Monitoring, Public Health and Verifiable
Risk Assessments-
New technologies with innovative handling
...
Mapping example of near (real)-time process
• Cartography identified the origins of the cholera during the London
Broad St...
Long-term temporal Hazards
Short-term acute events
Pre and Post tsunami image 26 Dec 2004 at
the Malacca village.
Dr RAMESH C DHIMAN
National Institu...
Short-term very acute events
Pre and Post Fukushima tsunami images 11 Mar 2011
http://wn.com/fukushima_before_and_after_ex...
Future needs involve Several Disciplines
(health)
2d AutoOil Programme
1. Select modelling periods for annual mean and episodes;
2. Input data on land use, topography, mete...
Actual measurements in 2010
BIG Data analysed 91,980,000 hourly records
(2years*365days*24hours*5species*1050geo-locations)
Environmental Monitoring …
• Satellite and UAVs for
covered areas:
 High resolution of
affected areas.
 High revisit per...
Climate advancements
Examples …
1. GISS ModelE2.
2. Ron L. Miller et.al. measurements since 1850 AGU at the
J. of Advances...
Big data for regulatory applications
• Real-time 10min met data
Examples …
1. Eliminate the use/uncertainity of questionna...
Population density maps from mob telephones
Francesco Pantisano EUR Report 27361 and
http://opencellid.org
… sensors and underwater robots
•…divers collect and sending samples back to the lab to
be tested,
•This FP7 robot makes t...
… sensors for citizen needs TrackR
• …ideal for practical applications but,
• Essential for real-time security and
vital i...
Final remarks Areas and Specific Efforts
• Environmental monitoring per sec has
consequences for proliferation of data and...
Thank you …
andreas.skouloudis@jrc.ec.europa.eu
skoulan@gmail.com
Upcoming SlideShare
Loading in …5
×

(Big) data for env. monitoring, public health and verifiable risk assessment-new technologies with innovative handling with data gaps

522 views

Published on

Presented by Andreas N. Skouloudis (JRC) during the 2nd BDE SC5 workshop, 11 October 2016, in Brussels, Belgium

Published in: Technology
  • Be the first to comment

  • Be the first to like this

(Big) data for env. monitoring, public health and verifiable risk assessment-new technologies with innovative handling with data gaps

  1. 1. «(Big) Data for Env. Monitoring, Public Health and Verifiable Risk Assessments- New technologies with innovative handling with data gaps» 1. Five Cases of big handling in the past (1854), 2. State-of-the-art uses, 3. The prospects ahead. Andreas N. Skouloudis andreas.skouloudis@jrc.ec.europa.eu
  2. 2. Mapping example of near (real)-time process • Cartography identified the origins of the cholera during the London Broad Street epidemic in 1854. • The containment of the epidemic was effective when the water pump was sealed at the Soho Broad Street.
  3. 3. Long-term temporal Hazards
  4. 4. Short-term acute events Pre and Post tsunami image 26 Dec 2004 at the Malacca village. Dr RAMESH C DHIMAN National Institute of Malaria Research
  5. 5. Short-term very acute events Pre and Post Fukushima tsunami images 11 Mar 2011 http://wn.com/fukushima_before_and_after_explosions_satellite_photos
  6. 6. Future needs involve Several Disciplines (health)
  7. 7. 2d AutoOil Programme 1. Select modelling periods for annual mean and episodes; 2. Input data on land use, topography, meteorology (multi-layer), and emissions (PiG) in order to characterise each modelling domain; 3. Definition of three dimensional wind patterns using meteorological models with two-way nesting; 4. Calculation of concentrations of different pollutants using full photochemistry; 5. Validation of the modelling results; 6. Adjustment of 1995 emission inventories to 2010; 7. Simulation runs for 2010 and comparison with objectives; 8. Development of emission reduction targets and simplified emission/air quality relationships (source apportionment); 9. Investigation of alternative emission scenarios (sensitivity tests); 10. Generalisation for all cities in the 10 domains (1065 towns, or 46% of EU15 urban population or 27% of all EU25 pop).
  8. 8. Actual measurements in 2010 BIG Data analysed 91,980,000 hourly records (2years*365days*24hours*5species*1050geo-locations)
  9. 9. Environmental Monitoring … • Satellite and UAVs for covered areas:  High resolution of affected areas.  High revisit periods are essential. • In-situ climate sensors:  Real-time datasets compact (weather) stations.  Not rely only on synoptic observations.
  10. 10. Climate advancements Examples … 1. GISS ModelE2. 2. Ron L. Miller et.al. measurements since 1850 AGU at the J. of Advances in Modelling Earth Systems.
  11. 11. Big data for regulatory applications • Real-time 10min met data Examples … 1. Eliminate the use/uncertainity of questionnaires. 2. Harmonize highly heterogeneous data, fill data gaps and verification of population effects. 3. Deal with questions of society and ethics. • Personal activity data
  12. 12. Population density maps from mob telephones Francesco Pantisano EUR Report 27361 and http://opencellid.org
  13. 13. … sensors and underwater robots •…divers collect and sending samples back to the lab to be tested, •This FP7 robot makes this process real-time with chemical sensors that makes these tests in-situ. •…3000 buoys deployed at seas for conventional data (GEOSS)
  14. 14. … sensors for citizen needs TrackR • …ideal for practical applications but, • Essential for real-time security and vital intervention in emergencies in- situ (earthquakes).
  15. 15. Final remarks Areas and Specific Efforts • Environmental monitoring per sec has consequences for proliferation of data and for pushing research to a new generation of tools; • There is always a temporal lag in integrating layers of information for environmental monitoring & health and this can effect cumulative population exposure; • Regulatory applications can significantly advance in combination with new monitoring tools (telematic use, citizens, traffic counts, RS etc); • Big data are already available for several areas applications and for assessing specific occupational hazards. It is the handling that redressing. • Big data are useless if not aiming to resolve problems that remain unsolved until now.
  16. 16. Thank you … andreas.skouloudis@jrc.ec.europa.eu skoulan@gmail.com

×