1. Proximity Analysis Sector Compliance Branch, Ontario Ministry of Environment National Environmental Partnership Summit May 8, 2007

2. Outline Some Notes About Us Geographical Information Systems What is Proximity Analysis Things to Consider Breakout Sessions Closing Remarks

3. Some Notes About Us

4. Ontario is a province just over 1 million square kilometres (400,000 sq mi) Ontario could cover as many as 13 states Ontario’s Area

5. Some Notes About Us Ontario has just over 12 million people –Almost half of Canada’s total population Toronto at 2.5 million, is the only city in Ontario with over 1 million people Ontario’s population is concentrated in the south Population

6. Some Notes About Us There are approximately 125,000 operations within the regulated community Since December 2000, SCB has conducted over 5000 sector inspections SCB has 42 Officers who conduct inspections SCB Inspections

7. Geographical Information Systems (GIS)

8. GIS GIS is made up of many elements: –Data –Software –Hardware –Personnel GIS is used to manipulate, analyse, and present spatial data As you will see, GIS is a major component in Proximity Analysis

9. GIS Multiple pieces of information can be brought together when they share the same geographical area GIS Data Landuse Postal Codes Land Ownership Census Tract Air Quality Imagery

10. GIS Vector –Points, lines, and polygons –Each feature has attributes/data associated with it GIS Data Raster (Grid) –A grid of cells/pixels/boxes –Each cell has a number that communicates something about the area that cell occupies GIS data comes in two types: Vector and Raster

11. What is Proximity Analysis?

12. Proximity Analysis Proximity Analysis is the process of risk ranking facilities in a specific industrial sector according to their distance to sensitive receptors 47 m 90 m

13. Proximity Analysis Sensitive receptors are those entities that if impacted by adverse effects, environmental or health impairment may occur An industrial sector can be defined as a group of companies that engage in similar processes in order to produce similar end products Some Definitions

14. Proximity Analysis The Challenge –We have a large list of facilities for potential inspections (i.e. 200 facilities) –We only have the resources to inspect 80 (40%) of them –How do we determine which facilities to inspect? Other Information –We do not have previous compliance history, or at least not for all of the facilities –All these facilities have similar processes (they are all part of the same industrial sector) –We know that these facilities: Have very high stacks Make excessive noise Have large containers with liquid hazardous materials The Challenge

15. Proximity Analysis

16. There are 200 facilities, do we visually inspect each of them on a map? –No, not feasible –We can calculate the distances between each facility and sensitive receptors using GIS –We can use these distance values to help determine the risk that facilities pose onto sensitive receptors Proximity Analysis

17. We can measure the distance between each facility and the closest receptor Calculating Distance

18. Proximity Analysis The Potential Influence Area (PIA) is the area in which adverse effects may be experienced by sensitive receptors –Receptors outside of this area are essentially unaffected by the facility and therefore will get very low or zero Risk Scores Separation Distance

19. Proximity Analysis By using a formula like the one below on each receptor, and then adding all the results, we get the following Risk Scores Risk Formula

20. Proximity Analysis Are some receptors more important than others? –Consider an industrial sector that dispels airborne chemicals that are particularly problematic for children Weighting

21. Proximity Analysis We should put more weight on the School Risk score –We decide that the distance to schools should have 3 times more weight –In the table below we multiplied all the School Risk scores by 3 –This is possible because we are using distance values instead of just looking at a map Weighting

22. Proximity Analysis Concentration We could also analyse the density or concentration of receptors in an area 0 1 2 3 4 5 6 7 8 9 10

23. Proximity Analysis You can define your density categories or ranges so that they range from 0 to your maximum Risk value Identify the Density Category the facilities are in, and use those values in the formula Concentration

24. Proximity Analysis Flow Chart

25. Proximity Analysis Proximity Analysis is the process of risk ranking facilities in a specific industrial sector according to their distance to sensitive receptors Distance values obtained through GIS are easier to deal with than large maps You can put weights on selected sensitive receptors You can use the density of receptors to help identify facilities that are in densely populated areas Summary

26. Things to Consider

27. Risk Scores are ultimately based on the distance that the facilities are from sensitive receptors Errors could arise from several sources –If the GIS layers representing the sensitive receptors are not accurate or are missing some features, then the resulting Risk Score may be skewed In order to limit these errors, you need to choose GIS layers that you have confidence in

28. Things to Consider Ensure that Risk Scores are not interpreted literally –If Facility A has a Risk Score of 8 and Facility B has 4, this does not mean that Facility A has twice as much risk

29. Things to Consider You may have to create some data based on other pieces of data –You can create a school density layer from a school point layer –You may not have residential areas, but schools are often located in residential areas, so you may decide to use schools as an indicator of residential communities

30. Things to Consider Today we looked at using a formula which took the distance to sensitive receptors as input, and outputted a risk score for that receptor We could use formulas that more closely approximate risk We could also use different formulas for different receptors

31. Break Out Sessions

32. Groups will be given scenarios where they have to rank six facilities using Proximity Analysis Three of these facilities will be selected for inspection Just by looking at the data, and before you begin your Proximity Analysis, indicate how you would rank all six facilities and be prepared to justify your choices Research indicates that all receptors beyond 3000 m (1.8 mi or 3280 yd) will not be effected by these types of facilities Conduct a Proximity Analysis and use it to rank the six facilities Be sure to indicate which data you used and any assumptions that were made You will need to assign a scribe and speaker for each group

33. Break Out Sessions You have the following data –Facilities –Schools –School Density –Hospitals –Hospital Density –Nursing Homes –Nursing Home Density –Residential Communities –Rivers –River Flow Direction –Municipal Water Intake Points Your Data

34. Break Out Sessions Your Tools

35. Break Out Sessions Air emissions from these facilities are a concern –The materials used and stored onsite are dry powders and other solids These facilities are particularly noisy These facilities are operational 24 hours a day, 7 days a week Scenario 1

36. Break Out Sessions Four years later, the business at these facilities has changed These facilities now dispel airborne chemicals that are particularly problematic for children Containers with liquid hazardous materials now exist onsite and spills have been recently reported Scenario 2

37. Break Out Sessions Two years later, a new drinking water facility was completed and is located in the vicinity of many of these facilities Scenario 3

38. Closing Remarks

39. The information gained from conducting the Proximity Analysis is valuable in that it allows our branch to rank the sector facilities based on impact to sensitive receptors This is important when the branch is planning the logistics for inspections in an industrial sector as it brings an additional element of risk assessment to the overall process

40. Contact Information Franco Simonefranco.simone@ontario.cafranco.simone@ontario.ca Susan Butson-Lewissusan.butsonlewis@ontario.casusan.butsonlewis@ontario.ca Amanda Burtamanda.burt@ontario.caamanda.burt@ontario.ca http://www.ene.gov.on.ca/envision/scb/