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

Proximity Proximity AnalysisAnalysis

Sector Compliance Branch, Ontario Ministry of EnvironmentNational Environmental Partnership Summit

May 8, 2007

OutlineOutline

• Some Notes About Us

• Geographical Information Systems

• What is Proximity Analysis

• Things to Consider

• Breakout Sessions

• Closing Remarks

Some Notes Some Notes About UsAbout Us

Some Notes About UsSome Notes About Us

• 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


• 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


• 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

GeographicaGeographical l

Information Information SystemsSystems

(GIS)(GIS)

GISGIS

• 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

GISGIS

• 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

GISGIS

• 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

What is What is Proximity Proximity Analysis?Analysis?

Proximity AnalysisProximity 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


• 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


• 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


• 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



Facility Closest River Closet School Closest Hosp. Closest Res.ABCD

Facility River School Hospital ResidentialA 48 1992 3876 177BCD

Calculating DistanceFacility River School Hospital Residential

A 48 1992 3876 177B 115 2745 6134 1867C 591 2812 4530 2054D 98 1280 1778 671


• 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

Distance PIA

Ris

k

Facility River River Risk School School Risk Hospital Hosp. Risk Residential Res. Risk. Risk ScoreA 48 9.68 1992 0.00 3876 0.00 177 8.82 18.50D 98 9.35 1280 1.47 1778 0.00 671 5.53 16.34B 115 9.23 2745 0.00 6134 0.00 1867 0.00 9.23C 591 6.06 2812 0.00 4530 0.00 2054 0.00 6.06

Ris

k

Distance


• 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

Proximity AnalysisProximity Analysis• Are some receptors more important than others?

– Consider an industrial sector that dispels airborne chemicals that are particularly problematic for children

Weighting


• 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

Facility River River Risk School School Risk Hospital Hosp. Risk Residential Res. Risk. Risk ScoreA 48 9.68 1992 0.00 3876 0.00 177 8.82 18.50D 98 9.35 1280 1.47 1778 0.00 671 5.53 16.34B 115 9.23 2745 0.00 6134 0.00 1867 0.00 9.23C 591 6.06 2812 0.00 4530 0.00 2054 0.00 6.06

Weighting

Facility River River Risk School School Risk Hospital Hosp. Risk Residential Res. Risk. Risk ScoreD 98 9.35 1280 4.40 1778 0.00 671 5.53 19.27A 48 9.68 1992 0.00 3876 0.00 177 8.82 18.50B 115 9.23 2745 0.00 6134 0.00 1867 0.00 9.23C 591 6.06 2812 0.00 4530 0.00 2054 0.00 6.06

Proximity AnalysisProximity AnalysisConcentration

• We could also analyse the density or concentration of receptors in an area

0

12

34

5 6 7 8 9

10


• 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

Facility River River Risk School School Risk Schl. Dens. Hospital Hosp. Risk Residential Res. Risk. Risk ScoreD 98 9.35 1280 4.40 5.00 1778 0.00 671 5.53 24.27A 48 9.68 1992 0.00 1.00 3876 0.00 177 8.82 19.50B 115 9.23 2745 0.00 0.00 6134 0.00 1867 0.00 9.23C 591 6.06 2812 0.00 0.00 4530 0.00 2054 0.00 6.06

Proximity AnalysisProximity AnalysisFlow Chart

Facility LIst

Geo-code or use coordinate data to place facilities on a

map

Determine the types of receptors

that should be used

Locate the data

Find distances between each facility and the

receptors

Use the formulas and distances to

calculate Proximity Scores

Facility List with Proximity Scores

Facility lists with distance data

Determine how far a facility has to be for it to have no

impact on a receptor

Determine formulas for each

receptor

End

Start


• 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

Things to Things to ConsiderConsider

Things to ConsiderThings to Consider

• 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


• 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


• 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


• 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

Ris

k

Distance

Break OutBreak OutSessionsSessions

Break Out SessionsBreak Out Sessions

• Groups will be given scenarios where they have torank 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


• 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

Break Out SessionsBreak Out SessionsYour Tools


• 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


• 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


• Two years later, a new drinking water facility was completed and is located in the vicinity of many of these facilities

Scenario 3

Closing Closing RemarksRemarks

Closing RemarksClosing Remarks

• 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

Contact InformationContact Information

Franco Simone [email protected] Butson-Lewis [email protected] Burt [email protected]

http://www.ene.gov.on.ca/envision/scb/

mailto:[email protected]



http://www.ene.gov.on.ca/envision/scb/

Documents

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