Tailings Impoundment Failure Rates: A New Look At The WISE & ICOLD Data

In the wake of the Mt. Polley tailings Impoundment failure on August 4, 2014, we have been working with the ICOLD/WISE data (see link at end for machine readable compilation) . Our aim initially was  to assess the feasibility of risk pooling to fund the huge unfunded and presently unfundable public and environmental liability in every TSF failure. This requires reasonable predictions of the number and average cost of TSF failures for a given  large group of TSF’s.  Most within industry researchers working with this data and publishing technical reports with reference to it have looked at frequency and at causes of failure, i.e. descriptions of what has already happened. Few have worked specifically with the cost consequence of public and environmental liabilities or with predicting future failures.

Only two presentations we found in the literature spoke to prospective consequence and consequence trends. Rico/Benito/Diego (2008)  used actual ICOLD/WISE data supplemented with additional research to create a complete uniform data base. They developed regressions to predict volume of spill for a TSF of a given height and capacity and for calculation of run out in distance (size of the area potentially impacted)

“simple estimations can be performed based on generic empirical relationships. In these equations, key hydrological parameters associated with dam failures (e.g. outflow volume, peak discharge, mine waste run-out distance) can be estimated from pre-failure  physical characteristics of the dam (dam height, reservoir volume, etc.), based on reported historic dam failures. This approach has been successfully applied to estimate  peak discharge (V)and outflow(DMax) resulting from water-dam failures [8,9,10].” .

V f=0.354*Vt1.008       r2=0.86 where Vf= spilled volume  vt=Total volume

Dmax=1.612*(H*Vf).0655     R2=.057  where h=height;Dmax-= run out flow in Km”

The above equation shows, that on average, one third of the tailings and water at the decant pond is released during dam failures”

http://www.academia.edu/6662478/Floods_from_tailings_dam_failures

Using an estimate of total volume at time of failure based on verified dimensions and stated freeboard( (59.6 million cubic meters) we did the failure volume (V) calculation for Mt. Polley)   It came out very close to actual: predicted failure volume  21.9  v  24.5 actual).  As more precise data on more failures becomes available the Rico/Benito/Diego can be reclaibrated, if necessary.

Doing the D max ( run out) using 45m ht ( from Piesold 2011..we know it was actually higher at failure as three raises occurred after that but wanted to use an authoritative figure) calculated failure outflow (Dmax) is 2.5 km..  By examination of the equation it is clear that for a given total capacity of a TSF, greater height  will result in greater runout ( and a large area of damage).  This suggests that TSF’s lie Mt. Polley’s rising at unplanned rates to meet determined production scheudlues may potentially create more envionmental damage in the even of failure than a newer facility with a much larger footprint and much lower height.
Rico et.al. began with a subset  from the ICOLD/WISE with the most complete profile of key variables and then did research on those dams to fill out what was missing.  They ended up with complete enough information for only 28 failed TSF’s.  If the actual standing inventory is 3500 as Morgenstrern(1998) has estimated and other researchers have widely used , that in itself is an important statistic.  That we have a complete data set for only .8% of he worlds TSF’s when they are historically one of the most consequential sources of massive non remediable environmental impacts, and the single largest source of presently unfundable public liability gives pause. 
That we don’t even have an accurate global inventory of TSF’s with basic descriptors like construction type, year built, original design height and volume, present design height and volume number says that producing mines and keeping them in production has a higher “public value” than the responsible risk management of these facilities. The issuers of permits globally have had this information always and it is long recognized that growing waste volumes from mines sites are a key issue in assessing environmental risk  and yet we have no government agency, other than  West Australia, that is systematically compiling  this critical environmental risk management information.
The second work we found looking at consequence in a resposble way ( or at all)  was A. Mac G Robertson (2011) who  transcended the limitations of the ICOLD/WISE data presenting a theoretical model on “potential risk” using maximum achieved height and maximum achieved total volume of TSF’s which we will describe further below.

LIMITATIONS ON THE ICOLD/WISE DATA AND FAULTY PAST USE OF IT

Our search for what is needed to evaluate the feasibility of risk pools for public and environmental liabilities, which are now largely both unfunded and unfundable, lead us to some insights that also have a bearing on descriptive interpretations of the failure data.  Our findings mainly affect the interpretation of the failures per decade and the popular claim that the data show improved performance in the last two decades attributable to better knowledge and better practice.  These claims have been based on frequency data alone which is not a complete or even best indicator of potential liability   Further both the numerator and denominator of those numbers are fuzzy and frail.  The denominator “3500” is really just  an informed best guess by Morgenstern in 1998 that has been used by virtually all other users of the ICOLD/WISE data as “gospel”  even though China had more tha 12,000 TSF’s by 2008 . The numerator, # of failures per decade is not a complete inventory even post 60’s but again  its the best number available so  it too is treated as “gospel”.  In the world of the statistics that we need to rely on to give some realistic shape to public liability exposure these are very “soft and fuzzy” numbers.  Coupled with the irresponsibility of citing only frequency it’s  not much to “stake a claim” of improved industry performance on.  

Also a close examination of the ICOLD ISE Itself  refutes the industry claim of improved modern performance attributable to better practices and better regulatory system of permitting and oversight.  As our restatement below shows the trend in fact is to an increasing number of major and large failures.

 

TSF Failures Increasingly Major  and large

Of those 39 incidents cited as proof of improved environmental performance by the mining industry, 1990-2010 , 25 (64%) were major failures, 12 of those , (31%) of all  the incidents last two decades were at the scale of catastrophic. The total costs for just 6 of the 12  large failures 1990-2010 totaled $2.4 billion , an average cost of $400 million per failure.  These losses, according to dam committee reports and government accounts are almost all the result of miner failure to follow known best practice

LOOKING TO RISK PREDICTORS IN INDUSTRY WIDE DATA

Taking Dr. Robertsons lead and going beyond the limitations of the ICOLD/ WISE data to the actual numbers the industry and its investors and analysts rely on it is very clear that public liability loss exposure is  shaped by two numbers:  ore grade and production volume  which have been spreading from each other in opposite directions since about 1950.  These two numbers in turn are what is driving the characteristics of risk in the TSF’s themselves:  Height and more importantly TSF total capacity.  As dropping ore grades force more and more volume of ore production for essentially a flat line production of refined product , more waste is generated and larger TSF’s are created mostly we assume, as at Mt. Polley  through expansion of existing TSF’s..

Correlation Matrix of Key TSF Failure DescrIptors/indicators

Variables tfail lrgfail Mxpri decpro oregrd pricyc
tfail 1 0.651 -0.137 0.503 -0.675 -0.14
lrgfail 0.651 1 -0.239 0.835 -0.789 -0.496
Mxpri -0.137 -0.239 1 0.020 0.130 0.666
decpro 0.503 0.835 0.020 1 -0.907 -0.222
oregrd -0.675 -0.789 0.130 -0.907 1 0.288
pricyc -0.149 -0.496 0.666 -0.222 0.288 1

Bowker Associates Science & Research In The Public Interest  October 2014

The two variables MXPRIC and PRICYC were an exploration of price as a predictor and    our data element PRICYC does have a strong correlation, -0.496, with the number of large failures. We coded PRICYC to try and capture the character of the price climate over the decade L 0=no change, 1= 1 decade of upward price, 2 =2 decades f upward price,3 = 3 decades of upward price and -1, -2,-3 for downward trends.  MAXPRIC was the highest price per ton for ore attained in the decade. MAXPRIC had very low correlations with the non price variables explained by a line almost parallel   with downward grade of downward cost per ton for production(3) essentially nullifying  price as a factor in predicting decade trends for all TSFS’s. ( Although of course on an individual mine basis price often makes a particular mine infeasible and results in either going on standby as at Mt Polley or not going forward with a mine application.)

We were interested to see how this “maps” for the whole of failures as the price of copper ( in constant$2010) maps exactly to the failure histogram. We believe on further analysis it will prove a useful indicator of operating stage of TSF life.  Specifically, we hypothesize that the combination of price/price trend and production will define periods of intense active use of TSF’s where a higher failure rate with  higher consequence are most likely to occur. and for identifying “at risk ” TSF’s.  The 0.496 correlation of PRICYC with consequence ( LRGFAIL=# of failures gt 1 million cubic meters)suggests that as well.

The bottom line is that when both frequency & consequence are taken into account the modern era performance is lower than at any other time in history and continuing in that direction.

Data on mine production is more solid and established over the entire 100 year period whereas exact data on inventory of TSF’s is not and probably never will be historically.  More importantly there is no comparison between a typically small  pre 1950 TSF and a modern TSF like Mt. Polley. On a per TSF basis adjusted for the smaller number of TSF’s pre 1950 the frequency is actually greater in the two most recent decades.005 as compared with .001 pre-1940. Consequence has been constantly escalating since 1960 therefore overall performance either way is significantly lower.

 

BY WHATEVER MEASURE ONE CHOOSES FOR FREQUENCY ALL ARE TOO HIGH TO BE ATTRIBUTABLE TO CHANCE:ALL DESCRINE 100 YEARS OF HUMAN ERROR

By definition, by the way, failure rates over this entire history as at least one other researcher  has recognized, are well above what is considered reasonably attributable to chance.  Rates this high over the entire history of mining by definition indicate human error at work ( ie an established pattern of  failure to take reasonable precautions to control off site damages with increasingly grave consequences).  Even the overall failure rate for water dams, .0001 ,is just barely in the range of what could be considered attributable to chance.

Azam/Li (2010) arrayed the ICOLD/WISE data into this histogram  of incidents per decade from 1900 to 2000 for a total of  218 failure incidents . http://www.infomine.com/library/publications/docs/Azam2010.pdf

azamLi2010icoldwisebydecade

The stat most frequently cited is that the overall failure rate for the century is 1.2% expressed with reference to the total number of mine sites, 18401.( What that is and who chose that number 18401 is a mystery we have not yet unraveled)

By  custom the pre 1960 decades are not usually included in analysis. rates. According to TailSafe 1136 TSF’s were built before 1950 and had failure rate of .0220.  That number is probably every bit as “solid” as the “3500 and any comparisons on a per TSF basis should use 1136 as the basis. We think it is important to understand TSF failures in the context of the entire century. 1960  in fact is key.It marks the beginning of the “modern mining metric” where demand  for metals is met with ever increasing production volumes relative to final output of  refined metals. It also marks the beginning of the ever increasing spread between ore grade and total production. and a dramatic change in the profile of mines generating production from a very few large mines pre 1960 to many more mine sites of widely varying size.  We are looking to use as much reliable data over the longest term possible.

The rates (2) cited as evidence of improved performace by the industry(failures/3500) are .01467/decade for the 60’s 70’s and 80’s and .0052/decade for the two most recent decades shown on the chart  This interpretation seemed  to warrant a closer examination  First, because frequency alone does not measure outcome.  Frequency and severity together measure outcome.   ICOLD/WISE have no data on  cost of failures  and only spotty data  on the size of the failure which most agree is a good surrogate for severity of TSF failures. There is general consensus within  the industry  that pursuit of profit at ever decreasing average ore grades results in larger and larger volumes of waste and therefore larger and larger TSF’s with a greater consequence in the event of failure. It is universally recognized that impoundment size is a principal  driver/ indicator of potential consequence..

In a keynote address at a 2011 Tailings & Waste conference, A.MacG. Robertson ( 2011 )http://www.infomine.com/library/publications/docs/Robertson2011c.pdf   looked at the entire century beyond the failure incident data just in terms of changes in “potential risk” over time  as indicated in the upper limits of height and volume achieved  per decade He estimated that the volume of “potential waste” per 1/3 century had increased  10 fold accomodated by a 2 fold increase in achieved maximum  height and a 5 fold increase in achieved maximum volume of TSFs per 1/3 century.   While pointing in the right direction and framing an excellent theoretical model for looking at “consequence of failure”over the entire century, it is not useable as an actual measure of consequence over the century nor did he intend that it be used that way.

This is the formula for “expected loss” (size of group,* frequency of loss* average loss for group). So with more data on both the standing inventory of TSF’s and on failed dams  this is exactly the formula for estimating total liability in any group of dams.  We hope to be able to explore development of a Risk score for TSF’s based on that and other data not yet compiled by any known source.  We are hoping to “round out” information on at least 28 more of already failed dams and develop a data base of at least 50 dams representative of the standing inventory.

Reading  the dam committee reports at WISE / ICOLDand surveying all the literature on TSF failures available online it was apparent  that the  greatest magnitude of loss for any given TSF failure  was in periods of active production of ore as at Mt. Polley.  Errors in the deposition of tailings and in the rate and size of raises were of  concern throughout the literature indentifying active operations as the most critical period in a TSF  where “best practices/best knowledge is most important in preventing TSF failures.  So we set about looking for some published and reliable data that might provide a more complete framing of these 218 TSF failure incidents against the periods in which TSF potential consequence is highest, in periods of actual production and in periods of price upswings.

APPRPROPRIATE STATEMENT OF FREQUNCY FOR TSF FAILURES

The first issue we considered is what basis to use for frequency. The table below compares three ways of looking at frequency.  Per TSF is customary in all literature we  have located via on line search and of course the most “normal” if we actually had “census” on TSF’s which we don’t.. So we wanted to explore other approaches. The table below, compares frequencees per TSF ( with a correction for the smaller number of mines pre 60’s) with frequency per mine site and frequencies based on production volume.     Per mine site is often used to cite century performance, 1.2% is the most frequently cited number.  However this is not as sensitive to the likely inventory of TSF’s over time so shouldn’t be used as a basis for stating overall performance either.  Overall performance should be stated on the same basis as per decade analysis.With the pre 1960 adjustment the failure rate per TSF is .015 pre-1960 v..055 60-s through 2010.  Much higher post 60.  Most researchers though only cite as “modern performance as  the 90’s and 2000’s and the failure rate 0.0057.

On an  ore production basis the failure rate over the century is an atsronomical .0449 mainly determined by the extremely high rates in the 60’s 70’s and 80’s.

Comparison Of TSF Failure  Frequencies Per TSF V.Per Mine siteV.Per Unit Production
 Decade TSFincidents Per/TSF*N1=1136   N2=3500 Per/SiteN=18401  Per/10 6 tons/10a CU mine production a to create closer    nominal scale
10’s 2* .0011 .0001 .0200.
20’s 2* .0011 .0001 .0200
30’s 4* .0030 .0002 .0220
40’s 8* .0070 .0004 .0381
50s 9* .0080 .0005 .0429
60’s 48 .0143 .0026 .1122
70’s 56 .0160 .0030 .0933
80’s 50 .0143 .0027 .0641
90’s 19 .0054 .0010 .0211
2000’s 20 .0057 .0011 .0153

Bowker Associates Science & Research In The Public Interest

October 2014

 

PRICE SWINGS  PRODUCTION COST TRENDS & THE  ENVIRONMENTAL RISK ENVELOPE

Knowing that the production at mines in operation is frequently interrupted by falling prices which can affect  most of a decade we first looked to data on copper prices over the entire century 1900 to 2000 and found that it mapped exactly into the shape of the historgram suggesting that  peaks in failure incidents  in the histogram in the 60s 70s 80s were in a period of price increase and that the two decades of the 90’s and 2000’s were in a period of general price decline  where it would be expected there would be a higher proportion of mines and TSFs in standby mode, ie not actively extracting.  This was the case at Mt. Polley which was reopened in 2005 after a 4 year period of no extraction due to falling market prices.

Copper Prices In $2010 dollars 1900 -2000

These periods of long upswings and long downswings in copper prices also presumably affect inventory of standing mines and inventory of standing TSF’s with the possibility of additions to both on long periods of upswing and the possibility of permanent shifts from “active” life phase to “closed” during long downward trends in price Here in Maine a long expensive history of exploring Bald Mountain, a small, low grade, high risk VMS deposit had reached a point in 1990 where Boliden was looking at the possibility of active extraction.  As the possible operation was too small and too uncertain they passed it off to a Denison subsidiary whose application was withdrawn in 1997 again citing falling metal prices. If that deposit had been a higher grade( and not had such extreme risk characteristics) it might have shifted into the “active life” phase with a small new “TSF” adding one new mine and one new TSF to inventory. On a down swing if a deposit is close to mined out it might just go into earlier than planned permanent closure of the mine site and of the TSF.

We are now in  a period of continued sustained upswing in copper prices and as a result of that we would expect both a higher frequency of failure, exceeding those of the middle three decades (60’s,70s, 80s) and significantly greater magnitude as grade has continued to decline over the past 1/3 century and the size of the standing inventory of TSF’s has pushed to greater heights and greater volume as compared to the size of these same facilities in the middle decade.(3)

This is very much the case at Mt. Polley and in the exit letter the designer of the original TSF who had continuously served as  consulting engineer to  the mine owner expressed concern about the size of the facility.   Further specific details about their concerns were found in the recently released 2009 annual inspection report submitted by the consulting engineer to the mine owner/operator.

What this all means is that degree of risk in any given standing TSF has a tendency to increase over time if it remains in active use because as production continues,  the TSF grows in both height and total volume.

 

ENVIRONMENTAL RISK ENVEOPE IS THE SPREAD BETWWEN ORE GRADE & PRODUCTION

Looking at TSF failures against global copper production 1900-2010 yields perhaps better data and more insight on actual trends in TSF failures and consequence implications especially when taken in conjunction with the world bank graph of copper production, ore grade and ore production over this same period.  All Failures has very weak correlations with everything except major failures because it includes mostly small incidents ( rather than failures) or very minor actual spills.  Both major failures and large failures have extremely high correlations with ore grade, mine production ( whether of copper only or of all metals), dam height at failure

Variables allmetals millions copper millions tons Mxpri pricyc $us2009 mxht oregrd tfail majfail lrgfail
allmetals millions 1.000 0.586 0.064 0.029 -0.212 0.524 -0.741 0.501 0.518 0.492
copper millions tons 0.586 1.000 0.092 -0.226 -0.769 0.967 -0.956 0.447 0.900 0.969
Mxpri 0.064 0.092 1.000 0.642 0.194 0.033 -0.023 -0.061 -0.014 0.018
pricyc 0.029 -0.226 0.642 1.000 0.517 -0.396 0.234 -0.149 -0.393 -0.325
$us2009 -0.212 -0.769 0.194 0.517 1.000 -0.795 0.694 -0.164 -0.736 -0.797
mxht 0.524 0.967 0.033 -0.396 -0.795 1.000 -0.922 0.346 0.860 0.950
oregrd -0.741 -0.956 -0.023 0.234 0.694 -0.922 1.000 -0.551 -0.889 -0.904
tfail 0.501 0.447 -0.061 -0.149 -0.164 0.346 -0.551 1.000 0.725 0.382
majfail 0.518 0.900 -0.014 -0.393 -0.736 0.860 -0.889 0.725 1.000 0.882
lrgfail 0.492 0.969 0.018 -0.325 -0.797 0.950 -0.904 0.382 0.882 1.000

Looking  at the world bank graph below we see that the spread between the blue line ( ore extracted (=waste volume)) compared with the flat refined ​copper line (red line) continually increases after 1960. The blue line ( total production of ore to produce the same level of ​refined copper), in effect is the same as the magnitude of consequence and more or less graphs what Dr. Robertson was conveying in his 2011 key note tailings conference address.

worldbankgraphgradeoreproduction

​Mapping the histogram of 218 TSF failure events ​(Azam/Li (2010) onto this graph​, ex​press​ing it on an incident per ​million tonnes of production basis​, shows that the two decades pre 1960 had a failure rate of .002 per ​million tonnes produced  ( adjusted for​ China which is not reflected in the TSF failure incident data) . and almost the same for the two most recent decades.( see table above)

Given the difference in magnitude of co​nsequence over the post ’60 period ( larger and higher im​poundments to handle more and more waste ​per unit ​of final metal) this is obviously a considerably worse​ risk management performance by the industry as a whole as compared with the pre- 1960 era ( looking only at TSF’s).

The middle period​ (60s, 70s, 80s) , of maximum TSF failure incidents was at a time of frenzy chasing an almost continuous upward trend in copper prices ( in constant $2010) and as ex​pected during such a big push on production the pressure on safety of TSF’s shows in much higher failures rate of .00878 per​ million tonnes(scaled by 100).

​The big price push over this period was driven mainly by demand from China who were both stockpiling and using at very high levels and by electrical infrastructure demands in developing/modernizing nations.. By 2010 China was a significant producer  of refined  metal in its own right with 25% of the global refining production and 10% of global production through mining.(after a very bad record of TSF failures not reflected in the ICOLD/WISE data)

This preliminary analysis  does not factor in the growing trade in copper concentrate solutions(secondary refining) at about 16% of total mine production in 2009  or the increasing role .and the increasing role of SW/Ex which was almost 20% of all production in 2009. Both of these changes in the profile of “mine production” have implications for TSF utilization and expansion

********************

End Notes & Links

(1)Here is a link to Tailing.Info’s excellent codification of the ICOLD/WSE data.  It is not current with that data. ICOLD/WISE  is immediately updated and revised as each new failure occurs so does not include Mt. Polley.Its consistent codification though does significantly improve the possibilities of using the ICOLD/WISE for systematic analysis.

https://drive.google.com/file/d/0Bw0jCpuVRzgEXzdZTHp3OGJtaGM/view?usp=sharing

Thank you Eric A. Tuttle for volunteering to transfer the Tailings.Info codification into useable spread sheet form.

(2) Number of Standing TSF’s .The industry seems to have  adopted “3500” as the “semi official” inventory of TSF’s and it seems, as far as we can see to originate form this paper by Davies et. al. citing a 1998 paper by Morgenstern.

http://www.infomine.com/library/publications/docs/Davies2002d.pdf

We have not yet checked the Morgenstern to see what he intended/believed the number represents.  It is not clear whether they intend their created number  of “3500 TSF’s globally” to mean all TSF’s between “Put in service” and ” closure” or also closed TSF’s. .  Everyone cites Azam/LI (2010) as the source who in turn cite this paper.

(3)Schodde, Richard “100 Years of Resource Growth For Copper Impacts Of Cost. Grade and Technology” ( http://www.minexconsulting.com/publications/Growth%20Factors%20for%20Copper%20SME-MEMS%20March%202010.pdf) has some fascinating insights on  HOW miners continued production as grades fell and prices varied.  His main point is that costs of production went steadily down making it possible to profitably mine lower and lower grades.and that a 6 fold lowering ore grades  allowed a 3 fold output  in refined copper.  He says “price is input” . We don’t believe this is a relevant predictor of TSF failures but his analysis is compelling. His slide presentation also has fascinating  bar graph showing that pre 1960 almost all copper production was out of  a few very large mines where as post1960 there is a greater number of mines and more diversity in the size of the mines.

(4)  technically it is not correct to say copper is “post peak” as reserves have not approached 50% reduction . Nor have they reached a point where continued extraction is not economically viable,  Extraction at current low grades of about .3 are still economically viable and we have reached nowhere need 50% .  Environmentally though it is post peak.  Because as that spread increase, the public side of the risk equation grows exponentially large and we hope soon to name that.  We know it is far greater than the 3% ( the rate of production increase in copper.)  We know that is what brings us mine proposals like Pebble & Northmet and Freeport McMorans plans for 2 billion cubic meter TSF.

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About lindsaynewlandbowker

Bowker Associates, Science & Research In The Public Interest, is an independent non profit providing self initiated pro bono analysis on key issues with a potential for massive adverse environmental impact . Bowker Associates has been an internationally recognized and cited voice in analysis of the Samarco failure, its consequence, and the possibilties for recovery. In 2015 Bowker Associates collaborated with globally respected geophysicist David M. Chambers to recompile global authoritative accounts of significant TSF failures in recorded history and to analyze these data in the context of gloal mining economics 1910-2010 ( Risk, Economics and Public Liability of TSF Failures, Bowker/Chambers July 2015) In 2014 Bowker Associates commissioned globally respected geophysicist and hydrogeologist Dr. David Chambers to undertake two technical works: (1) development of technical go no go criteria for vetting mine applications tp://lindsaynewlandbowker.wordpress.com/2014/01/05/a-new-statutory-regulatory-framework-for-responble-sulfide-mining-should-this-mine-be-built/ and (2) a case study of Maine's Bald Mountain, an un mined low grade high risk VMS deposit demonstrating the efficacy and accuracy of two risk assessment tools in vetting mine proposals https://lindsaynewlandbowker.wordpress.com/2014/02/28/mountain-x-would-you-issue-a-permit-to-this-mine/ In Maine, Bowker Associates has deeply engaged and been a public voice in the Searsport DCP LPG Tank, The Cianbro proposal for a Private East West Toll Road, JD Irvings rolling pipeline of Bakken crude to its plant in St. John and review of Phase II plans at The Callahan Superfund site in Brooksville, Maine, and Maine's revisitation of mining in statute and regulation... Our only “client”: is always “the pubic interest”. Our model is to focus on only one or two issues at a time so that we have a substantive command of the relevant field as our foundation for ongoing engagement. Our core work is in envirommental risk management, science and technology as well as bringing any available “best practices” models to the fore. The legal and regulatory history/best models are also a major thrust of our work in building and evaluating public policy. Director/Principal Lindsay Newland Bowker, CPCU, ARM is a recognized expert in Environmental Risk Management., Heavy Construction Risk Management and Marine and Transit Risks and has more than 3 decades of engagement in buiding public policy. Appointed by Governor Mario Cuomo to New York State Banking Board (served 1986-1996); President New York Chapter Chartered Property and Casualty Insurers; Environmental Committee, Risk and Insurance Management Society; Director, Convenor/Co-Chair Bermuda Market Briefing "From Captive to Cats" Hamilton Bermuda. Published Articles of Significance The Risk Economics and Public Liability of Tailings Facility Failures, co-authored with David M. Chambers, July 2015 Beyond. Polarization: Superfund Reform in Perspective, Risk & Insurance Managing Risk For Loss Prevention & Cost Control (Jan. 24, 1997). Lead Hazards and Abatement Technologies in Construction: A Risk Management Approach CPCU Journal 1997 Employee Leasing: Liability in Limbo Risk Management June 1 1997 Environmental Audit Privilege and the Public interest Risk & Insurance Managing Risk For Loss Prevention & Cost Control, April 1997 Asbestos:Holes In Abatement Policies Need To Be Plugged, Lloyd’s Environmental Risk International, May 1993 Editor Published Letters Evironmental Risk Management Beware of Facile Policies Like Fetal Protection Business Insurance 1995(?) High Court Review May Increase Sale of Bank Annuities Business Insurances August 8, 1995 Professional Profiles Protecting the Big Apple’s Core Managing Risk For Loss Prevention & Control December 1996 Major Career Highlights First rigorous analysis showing Relationship Between declining ore grades and TSF Failures of increasing consequence ( July 2015) FIrst Documentation that Gentrification Has Same Impacts as Unassisted Displacement from Urban Renewal Sites Direted Court Ordered EIS of FHA Mortgage Scandal Created Nation's First Homeownership Program for Low Income People (SHIP) Created Earliest Geographic Information Systems Using Defense Technology Developed By IBM Designed and Conducted Parallel Census Count to Show Systematic undercount in minority neighborhoods Documented Bias in ISO Territory Rating Plans for Private Passenger Auto Insurance Using ISO's own Rating Techniques Demonstrated Inherent Bias in Mortgage Policies of Banks With Inner City Branches Demonstrated that NY Telephones Plan for Area Code Split To accommodate anticipated cell phone demand was not efficient and would exhaust in 5 years ( which it did) Undertook First Systematic Evaluation of Child Protective Services Caseload Using Multi Variate Analyic Techniques Developed Child Protective Caseload Management and Tracking System (CANTS) and directed implementation in 4 client states including Illinois, Florida and New York Created and Ran Office of Risk Management for NYC DEP the Nations largest Water & Sewer Authority . Designed, Created and Administered Nation's First Owner Controlled Insurance Program (OCIP)for High Risk Tunneling Education Masters NYU Graduate School of Public Administration BSC New School For Social Research Maine Public Schools Deering High School
This entry was posted in Analysis TSF Failures, Bowker Associates Science & Research In The Public Interest, Copper Mine Production 1900-1999, Copper Prices 1900-2000, Frequency of TSF Failures BY Decade, ICOLD, Measuring Magnitude of Consequence TSF Failures, Tailings Failure Rates, Tailings.Info, TailSafe, TSF Failure Incidets 1900-2000, TSF Risk Management, Universe of Mine Sites, Universe of Standing TSF, WISE. Bookmark the permalink.

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