Light pollution : A problem for
humanity
Donald R. Davis
International Dark-sky
Association
8 June, 2004
International Dark-Sky Assocation
The Inspirational
“Mortal as I am, I know that I am born for a day. But when I follow at my
pleasure the serried multitude of the stars in their circular course, my feet
no longer touch the earth.”
-- Ptolemy, c.150 AD
"Can we see the whole of life or only know a hemisphere of it before death?
I've no idea of the answer myself. But the sight of stars always sets me
dreaming…"
-- Vincent Van Gogh
"At night make me one with the darkness; in the morning make me one with
the light."
-- Wendell Berry
Startling fact: For 80% of the US population, two-thirds
of the EU population and one-fourth for the world
population, night never
Internationalcomes.
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Startling fact:
Two thirds of the US
population cannot see the
Milky Way with the unaided
eye from their back yards.
Why not?
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International Dark-Sky Assocation
Light pollution has negative
effects on:
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Wildlife.
Environment.
Landscape.
Human Activities.
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The Earth is really bright!
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International Dark-Sky Assocation
International Dark-Sky Assocation
IDA’s Goals
• To preserve and protect the nighttime
environment and our heritage of darkskies through quality outdoor lighting.
• Membership based. Members, from all
50 states and 70 other countries. 414
organizations.
International Dark-Sky Assocation
IDA Statistics
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Total Members — nearly 11,000
Organizational Members — 569
Lifetime Members — 203
Newsletters Issued — 57
Information Sheets Published — 193
International Dark-Sky Assocation
International Dark-Sky Assocation
International Dark-Sky Assocation
Bottom Line:
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Environmentally responsible,
Economically sensible.
Good lighting has great value!
We all win!
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"Now I think we are small enough. Let's call it a night.“
-- Theodore Roosevelt, a comment after marveling at the enormity of the number of visible stars
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Sky Brightness Measurement
Examples of Existing Programs
1) The National Park Service Night Sky
Project.
2) Sky Brightness mined from an
automated search program.
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Dark Skies in National Parks:
Measuring Night Sky Quality with a Wide Angle CCD Camera
Dan Duriscoe
Death Valley National Park
Chad Moore
Bryce Canyon National Park
Christian Luginbuhl
U.S. Naval Observatory, Flagstaff, Arizona
International Dark-Sky Assocation
International Dark-Sky Assocation
International Dark-Sky Assocation
DATA MINING OF AUTOMATIC TELESCOPE ARCHIVES FOR
NIGHT SKY BRIGHTNESS MONITORING
Erin M. Craine
University of Arizona
and
Global Network of Astronomical Telescopes
Presented at the Meeting of the International Dark Sky Association
Tucson, AZ
March 2004
International Dark-Sky Assocation
GN
AT
MOTESS “3-Shooter” Prototype
• 36-cm Newtonian reflector
• f/5 focal ratio
• 50 arcmin FOV
• scan mode
• 12 sq deg of sky/hr
under construction ^
< operational
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GN
AT
System Images
• 1024^2 px
• 16 bit
• 50 arcmin
• 191 sec int
• FITS format
• clear channel
• standard
2x2-in filters
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Examples of night sky brightness
measures
70000
70000
B
60000
50000
50000
40000
Sunset
Sunrise
30000
40000
30000
Moonrise
Sunset
20000
20000
10000
10000
0
0:00:00
D
Sky Brightness 12/4/2002
60000
Brightness
Brightness
Sky Brightness 11/14/2001
Sunrise
0
2:24:00
4:48:00
7:12:00
9:36:00
12:00:00
14:24:00
16:48:00
0:00:00
2:24:00
U.T.
4:48:00
7:12:00
9:36:00
12:00:00
14:24:00
U.T.
Graphs B and D represent dark nights just over a year apart.
The later image is about 10% brighter than the earlier
image, which is consistent with normal night to night
variations, suggesting that the observatory site brightness
has not increased significantly during the intervening year.
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16:48:00
Sky Brightness Modeling
• Significant economic benefits from the
astronomy, optics, and tourism industries.
• A tool is needed to predict the impact of
growth on dark skies.
• Environmental preservation is of increasing
importance in many places.
• Quality data is key to designing good
policies.
IDA Sky Brightness
Modeling Project
• Modify the Garstang code to add detailed
models of cities and visualization capability.
• Validate the model: Compare predictions to
actual sky brightness measurements
• In association with local jurisdictions, model
the impact of future growth on sky
brightness under a variety of scenarios.
Code Improvements
and Future Work
• Update the integration algorithms.
• Allow each segment of a city to have its
own light intensity and distribution. Use
as many segments as needed to
represent the city.
• Validate the angular distribution
assumptions.
• Visualize the output of the model.
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IDA Sky Brightness
Modeling Project
• Funding secured from two counties in
Arizona.
• Code modifications to be completed by July,
2004.
• Validation phase completed by September,
2004.
• Modeling and final report by Jan. 2005.
Summary
• Several projects underway to measure sky
brightness for specific objectives.
• Ongoing sky brightness monitoring at major
observatories still needs to be implemented.
• Inexpensive sky brightness measurement
instrument still needs to be developed.
• Modeling project underway to generate a
general tool for sky brightness prediction.
Conclusions
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There is a problem.
It is still getting worse most places.
Why do we tolerate it?
Solutions exist.
Good lighting is the key. It has value!
Help build awareness. Get involved!
With good lighting, we all win.
International Dark-Sky Assocation
Flagstaff Lighting and Land Use
Project
Kevin Pick, Don Davis, Wes Lockwood, Chris Luginbuhl
Funded by Coconino County and IDA
IDA award: International Dark
Sky City
International Dark-Sky Assocation
Project Goals
 How much outdoor light is produced by different types
of users?
 What fraction of outdoor lighting goes up?
How effective has the Outdoor Lighting Code been?
 How do our results compare with standard numbers used
in computer models, e.g. the Garstang code?
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Data Collection: How?
1. Roadway and sports lighting information from the
City of Flagstaff and Arizona Dept of Transportation.
2. Inventory of large shopping centers
3. On-site surveys of a sample of commercial sites
4. Lighting inventory flyers distributed to single family
homes
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Data Collection: On-the-ground
survey
 45 sites targeted, including most shopping centers,
and smaller samples of other uses
 On site, fixtures counted, photographed, and marked
on maps
 Wattage and bulb type obtained for each fixture
 Total mean lamp lumens calculated for each site
surveyed
 An average CU and “dirt depreciation” for each
fixture type applied to the lumen count
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Data Collection: Residential
 500 survey forms distributed to five residential
neighborhoods – 115 were returned
 Total mean lamp lumens calculated for each home
 An average CU and “dirt depreciation” applied to
the lumen count
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Data Collection: Residential
survey form
International Dark-Sky Assocation
Results: How is lighting
used?
117 million lumens
Metal halide
sports
40 million
lumens
LPS
26 million
lumens
1.4 megawatts
LPS
HPS
MH
MV
QH+PAR
Incand
Fluor
Sports
LPS
185 kW
Metal Halide
sports
430 kW
HPS
350 kW
HPS
35 million
lumens
MH
Commercial
8 million
lumens
Other white light
8 million lumens
Other white
light 200
kW
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MH
Commercial
MV
130 kW
60 kW
Results: Where is Lighting
Used?
Lighting and sky glow proportions
100%
90%
80%
Municipal
Roadways
Residential
Commercial
70%
60%
50%
40%
30%
20%
10%
0%
Installed
Effective
Up (sports off)
International Dark-Sky Assocation
Up(sports on)
Results: Where does uplight come
from?
Sports lighting
off
Sports lighting on
Unshielded
direct uplight
Unshielded
direct uplight
Commercial
Commercial
Residential
Residential
Roadways
Roadways
Munic+sports
Munic
1/3 of Flagstaff’s sky glow comes from unshielded
sources
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THE CODE AND DARK-SKY
AWARENESS IS WORKING!
Measurements by Lockwood
show no increase in sky
brightness in Flagstaff in the past
25 years despite a doubling of the
population.
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Sky brightness changes since
1975
International Dark-Sky Assocation
CONSTANTS
Flagstaff Lighting and Land Use Project
Population
Effective Maintained Lumen Values (mean lumens * CU * LDD)
55,000
blue means linked to worksheets = update through worksheet, not here!
ON/OFF
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
eff lm 50k eff lm 100k
#NAME?
44,200
Summary
Numberunits surveyedunit type mean lm/unitfactional err mean frac up frac err
Shopping Centers
9
101.56
acre
83971
0.08
0.03
0.36
Auto Dealers
4
15.83
acre
39865
0.25
0.08
0.49
C-Stores
3
3.00
each
224145
0.14
0.00
0.31
Hotels
10
17.50
acre
83258
0.13
0.09
0.36
Banks
2
2.72
acre
143875
0.34
0.01
0.42
Restaurants
5
5.73
acre
164641
0.38
0.06
0.67
Industrial
1
2.00
acre
30704
0.15
Residential
115
115
each
541
0.08
0.38
Apartments
3
274.00
each
2459
0.44
0.18
Roadway Flagstaff 1
1.00
total
20,103,480
0.00
0.00
0.00
Roadway Private
1
1.00
total
55,235
0.00
0.15
0.00
Roadway ADOT
1
1.00
total
7,481,455
0.00
0.00
0.00
Flagstaff Sports
1
1.00
total
25,481,221
0.00
0.13
0.00
FUSD
1
1.00
total
0
0.00
#DIV/0!
0.00
FUSD Sports
1
1.00
total
8,478,750
0.00
0.13
0.00
Flagstaff Muni
1
1.00
total
2,521,734
0.00
0.00
0.00
Total
Total per capita
Total units
pre-89
172.64
25
100.4762118
34.89367309
13,000
3,368
1
1
1
1
1
1
1
ave LLD
0.8
ave LDD post-89 up fract
0.85
0.05
Total acres Total acres
50k
100k
Total lm surveyed
12.26
8,716,416
585,188
672,434
11.27
1,328,452
347,601
16.63
1.47
930,717
61,407
62,248
64.16
31.56
700,410
20,103,480
55,235
7,481,455
25,481,221
0
8,478,750
2,521,734
77,526,747
1409.577225
check these!
Examine canopy impacts using AGI32 models
Graph potential extrapolation methods
Extrapolate only unmeasured sites - directly enter measured sites
c-stores per unit, per acre and per pump
Re-do by using inventoried values then adding extrapolations…?
check various commercial types - perhaps they are not all statistically different
to add cars
gen comm
warehouses
ave CU
0.65
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