1 NR149 LOD/ /LOQ Clarificatin Required frequency Annually an MDL study must be perfrmed fr each cmbinatin f the fllwing: Matrix (if the slid and aqueus matrix methds are identical, extraplatin frm the water MDL is allwable) Preparatry Methd Analysis Methd Analyte (where an MDL study is apprpriate) Matrix Prep Methd Analysis Methd Analyte (r grup) MDL studies can be cmpleted by preparing and analyzing at least tw MDL study replicates each quarter. Annually, these quarterly replicate resultss culd then be used fr the LOD determinatin. NR (2) (d) includes a prvisin fr verifying the cntinued applicability f a previusly determined limit f detectin by an established and defensible prtcl. Hwever, the prgram has reviewed a number f prtcls and nne f them has been deemed t be defensible. We cntinue t explre different prtcls fr verifying that an established LOD remains valid, but at this time the lgical cnclusin is that the nly defensiblee apprach is t simply repeat the determinatin. The MDL study passes if bth the lw and high spike criteria are satisfied: LOD < spike cncentratin, and LOD is nt less than 10% f spike cncentratin If bth MDL studies were cnducted prperly and the resultant MDL still des nt pass r the lab feels the passing MDL is nt realistic prtcl is prvided n hw t establish a realistic, determinative LOD (MDL). Reprting Many parameters used in cvered prgrams under NR 149 require that sample results be reprted t the LOD. When reprting results t the LOD,, the LOQ must als be reprted. The LOD and LOQ shuld be belw the regulatry limitss established by cvered prgrams and prject plans, where it is achievable. In sme cases a mre sensitive methd may be required in rder t meet these limits. Why des WI require LOD/LOQ reprting? This requirement cmes frm the cvered prgrams. The cvered prgrams use data t make envirnmental impact assessments. The determinatin f whether r nt an actin level has beenn exceeded r whether additinal mnitring is required is based n the sample results relative t the LOD and LOQ.
2 NR149 LOD/ /LOQ Clarificatin MDL (LOD) determinatin Begin with establishing a valid calibratin. Befre yu attempt the MDL study it is in yur best interest t take the time t review the 40 CFR Appendix B MDL prcedures fr hw t determine a gd estimated LOD. Mst MDL study failures can be attributed t spiking at the wrng cncentratin and analyzing the replicates back t back in a single analytical run. The better yu d estimating the spike cncentratinn the better yur chances are that yu pass the MDL study the first time. The MDL prcedure requires that a spike cncentratin be used in the MDL study that will be clse t the estimated MDL (the prcedure referss t 1x 5x yur current LOD). Fr example, using 2-3 times yur current MDL cncentratin wuld be a gd idea. If there is nt a current MDL, r yu suspect yur MDL is n lnger valid, there are tw appraches yu can use t determine a gd estimated LOD: 40 CFR Appendix B MDL prcedures prvidee instructin n hw t estimate a MDL. Use yur knwledge n instrument limitatins, r the knwledge prvided by ther surces, such as the instrument vendr r ann authritative referencee methd. Perfrm the minimum 7 (but we encurage 8) replicate MDL study in 40 CFR Part, Appendix B. Replicates shuld be analyzed ver multiple days (run ~2 MDL spike samples each time). This is critical t incrprate day-t-dayy variability int the determinatin. Running all replicates simultaneusly will frequently resultt in a failed MDL determinatin. It advisable t analyze the replicates distributed amng rutine samples, nt directly after a blank. As previusly discussed, the MDL study passes if it meets bth f the fllwing criteria: LOD < spike cncentratin, and LOD is nt less than 10% f spike cncentratin
3 Example 1: MDL (LOD) determinatin meets criteria EXAMPLE 1: A valid MDL determinatin NR149 LOD/ /LOQ Clarificatin In Example 1, a valid LOD is btained. Unless yu havee dcumentatin t substantiate therwise, this wuld becme yur determinative LOD. What d i d if the first mdl study attempt fails? If the initial MDL study des nt pass then adjust the spike cncentratin based n the study results and re-perfrm the study ne mre time. Befre yu make yur 2 nd attempt at the MDLL study it is in yur best interest t take the time t review the MDL prcedure fr hw t determine a gd estimated LOD. It is a very gd idea t determinee at what cncentratin a standard can be seen that can be distinguished frm a blank. This is dne by analyzing lwer and lwer cncentratin standards ( serial dilutins) Once yu find the cncentratin where a result is detectable (3x 5x greater than the signal/nise r 3x the standard deviatin f a set f blanks) yu have determined an estimated LOD. Then take this estimated LOD value and red the MDL study using standards at 3x the LOD, r if the instrument is highly precisee it may be preferable t lwer the MDL
4 NR149 LOD/ /LOQ Clarificatin study t standards that are at, r just abve, this detected level. Again yu will achieve the best chance f passing yur MDLL study by making sure variability is accunted fr by running different study samples ver a number f days. EXAMPLE 2: Initial determinatin fails criteria; 2 nd attempt passes In Example 2, n the secnd attempt a valid LOD is btained. This is ften the case when the initial spiking cncentratin was justt t high. Remember that ur target is t spike clser t the LOD, where quantitatin is less accurate, and the standard deviatin f replicates increases. Unless yu have dcumentatin t substantiate therwise, this wuld becme yur determinative LOD. But what if, after tw attempts at perfrming the LOD determinatin,, yu still dn t meet criteria r the nminal LOD is unrealistically lw?
5 NR149 LOD/ /LOQ Clarificatin An alternatee apprach t determining a realistic, determinative LOD If the lab has addressed the issues in the first MDL study by re-determining a gd estimatee f the LOD and by spreading ut replicate analyses t accunt fr additinal variability and the 2 nd MDL study still fails criteria r results inn an unrealistically lw LOD then it is time t use an alternate apprach t establish a realistic,, determinedd LOD. This is usually nly applicable fr high precisin instruments (and typically fr thse in whichh there are n sample preparatin steps), such as fr in chrmatgraphy and flw injectin analysis. Step 1: Demnstrat te that the nminal LOD is unrealistic The first step in using a value ther than that btained using the apprved EPA prtcl, as yur determinative LOD, is t demnstrate that the nminal LOD determined is nt realistic. One way t d this is t analyze a prcessed LCS prepared at a cncentratin equal t the nminal LOD and demnstrate that either there is n signal r the quantitative result is belw the nminal LOD. Anther way t d this is t demnstrate that the nminal LOD respnse is nt significantly greater (three times r higher) than the respnse fund in rutine methd blanks. Step 2: Rule ut blank cntaminatin r pr lw end characterizatin f the calibratin Answer the questins, Hw d yu knw that yu d nt have lw level cntaminatin? Are yur blanks negative? Hw d yu knw the calibratin levels and algrithm are nt cntributing t blank cncerns? Step 3: Analyze several LCS samples spiked at levels abve the nminal LOD Once certain that blank levels are nt adversely affectedd by cntaminatin r calibratin issues, ne can analyze several LCS samples at increasing cncentratins,, starting at the LOD cncentratin. Each LCS is evaluated fr the instrument s ability t detect it at its cncentratin based n instrument respnse. Be certain that the result LCS respnse can be distinguished frm blank respnses (i.e. nt a false psitive). Remember that quantitative recvery is difficult t reliably achieve between the LOD and the LOQ. Yur determinative LOD is the lwest cncentratin at which yu can reliably detect a signal that is nt a false psitive. If yu get gd recvery, that s even better. Make sure that the LCS cncentratins used are nt significantly higher than the nminal LOD. cncentratin. Be sure that yu can answer the questin, Hw are yuu certain that the determinative LOD is nt lwer? Step 4: Establish the LOQ The LOQ can be calculated as 10/3 x the LOD.
6 NR149 LOD/ /LOQ Clarificatin Example 3: A valid alternative LOD determinat tin In Example, 3, the lab perfrmed an LOD that failed criteria. The study was repeated at a lwer level, which met criteria. Unfrtunatel ly, the resultant LOD falls belw typical levels bserved in blanks. An LCS prepared at the nminal LOD was undetectablee demnstrating that the nminal LOD was unrealistic. A secnd LCS, at ppb, was within the nrmal variance fr blanks. Therefre ppb wuld nt meet the definitin f an LOD which is designed t avid false psitives. Finally, an LCS at 0.05 ppb was assciated with a respnse well abve that bserved in blanks. In additin, 0.05 ppb is still well belw relevant regulatry limits. Therefre, this prtcl established a valid determinative LOD at 0.05 ppb.
7 NR149 LOD/ /LOQ Clarificatin Example 4: Insufficient alternative LOD impacted by calibratin. In example 4, the initial nminal LOD (0.4 ppb) was rejected due t failed criteria. The secnd attempt met criteria and yielded a nminal LOD (0.5 ppb) very clse t that btained initially. That wuld seem t crrbrate a determinative LOD f abut 0.5 ppb. Hwever, the lab rejected the secnd nminal LOD as unrealistic and pted t emply an alternative apprach t establishing its determinative LOD. The lab subsequently prepared an LOD verificatin standard at 1.0 ppb and an LOQ verificatin at 3.2 ppb. Since gd recveries were bserved fr bth standards, the lab established its LOD at 1 and LOQ at 3.2. The decisin t start at 1.0 ug/l as the determinative LOD may have been related t the fact that the required SDWA LOD fr arsenic is 1 ug/ /L r less. The ratinale fr ignring the acceptable 2 nd LOD determinatin was based n its histrical experience that methd blanks averaged a cncentratinn f -0.5 ppb with a standard deviatin f 0.6. That wuld be an apprpriate ratinale as lng as the lab culd demnstrate that their calibratin is nt adversely impacting blank values.
8 The questin unanswered is: Hw d we knw that the determinative LOD desn t fall between 0.5 and 1.0? N analysis was perfrmed in this regin. And why are blanks rutinely negative with significant variance? What s wrng with this picture? Subsequently, the surce f the negativee blank biass was investigated. On clser examinatin, the lab was calibrating with standard levels f 0, 10, 20, and 40 ppb. Clearly, this is an inapprpriate calibratin, even frr an LOD ff 1.0. Remember, the first calibratin standardd needs t be near the LOQ. Furthermre, hw ften wuld ne expect t find arsenic in drinking water abve even 10 ppb? Sure, it happens in sme areas, but calibratins must be designedd t cver the nrmal range f anticipated sample cncentratins and must include adequate definitin f the range near the LOQ. With an ppb. NR149 LOD/ /LOQ Clarificatin LOD f 0.5 ppb, a mre apprpriate calibratin wuld be 0, 2, 5, 10, and 20
9 NR149 LOD/ /LOQ Clarificatin LOQ determina tin The LOQ must be mathematically related t the LOD (just indicating that the LOQ is greaterr than the LOD is nt a mathematical relatinship). The traditinally accepted statistical definitin f the LOQ is 10/3 the LOD. The lwest calibratin standardd NR (6)(e) equires that, Labratries reprting results at levels at r near the limit f detectin f an analysis shall include in initial calibratins a standard at a cncentratin near the limit f quantitatin f the analysis. Mst analyses perfrmed fr cvered prgrams ff the agency will require results t be reprted dwn t the LOD. Therefre, calibratins need t include a standard near the LOQ. The further the standard cncentratin is frm the actual LOD, the mre significant the ptential impact n achieving a realistic, determinative LOD. Additinal infrmatin and examples fr MDL studies aree included in a dcument called Analytica Detectin Limit Guidance n ur website:
10 NR149 LOD/ /LOQ Clarificatin Definitins Methd blank = reagent water that is prcessed simultaneusly with and under the same cnditins as the assciated samples including all preparatry, cleanup, and analysis steps. LOD (Limit f detectin) = the lwest cncentratin r amunt f analyte that can be identified, measured, and reprted with cnfidence that the cncentratin is nt a false psitive value. Fr department purpses, the LOD apprximate s the EPA ss MDL (methd detectin limit) and is determined accrding t the prtcl established in 40 CFR Part 136, Appendix B. A quantitative recvery is nt expected at the LOD. The study must be well dne because the LOD is used t set the LOQ and fr sme parameters determining a true LOD is very imprtant t the prgrams using that data. Nminal LOD = the LOD calculated fllwing the accepted EPA prtcl (statistically derived). It remains the Nminal LOD until it has been prperly vetted r replaced with either a vetted 2 nd determinatin, r ne determined thrugh sme alternative prtcl, acceptable t the Department. Determinative LOD = the adpted LOD used fr reprting. The adpted LOD may be the LOD btained frm the initial MDL study, the 2 nd determinatin, r the ne determined frm an apprved alternate prtcl. Methd Detectin Limit (MDL) = the minimum cncentratin ff an analyte that can be measured and reprted with 99% cnfidence that thee stated cncentratin is greater than zer as determined frm analyses f a set f samples cntaining the analyte in reagent water. The methd detectin limit is generated accrding t the prtcl specified in 40 CFR 136, Appendix B. It is listed here because mst EPA methds refer t the MDL. LOQ (Limit f quantitatin) = the lwest cncentratin rr amunt f an analyte fr which quantitative results can be btained. A quantitative recvery is expected at the LOQ. NR 149 requires that there be a mathematical relatinship between the LOD and the LOQ. Traditinal statistics define the LOQ as 10/3 the LOD. Lwest cncentrati n standard in the calibratin curve = NR 149 requires that the lwest standard in the initial calibratin be near the LOQ. Near culd be defined as 2-5 times the LOQ fr multi-analyte methds. Nte hwever that the cmbinatinn f 5 times the LOQ and the LOQ being 10/3 f the LOD means that the lw calibratin standard culd be as much as 17 times the LOD. This situatin shuld be avided as much as pssible as it culd lead t bias at the lw end f the calibratin curve (see Example 4). NOTE: Calibratin is arguably the mst critical part f determining an LOD. The calibratin must be prperly established withut ver-extending the upper limit f the calibratin, while als prperly characterizing thee lw end f the calibratin. The predminance f negative blanks is a primary indicatr f a pr calibratin. Reminder: the calibratin levels and calibratin algrithm selected fr the LOD determinati n MUST be the same as that usedd fr analysis f samples and QC.
A Beginner s Guide t Successfully Securing Grant Funding Intrductin There is a wide range f supprt mechanisms ut there in the funding wrld, including grants, lans, equity investments, award schemes and
Hw t Write Prgram Objectives/Outcmes Objectives Gals and Objectives are similar in that they describe the intended purpses and expected results f teaching activities and establish the fundatin fr assessment.
N Unsafe Lift Wrkbk Cver and Sectin Break image prvided curtesy f Arj Canada Inc. Table Of Cntents Purpse f this wrkbk... 2 Hw t use this wrkbk...3 SECTION ONE A Brief Review f the Literature...5 SECTION
Click4it Wiki - Tlkit Mst Significant Change Step by Step Step 1: Starting and raising interest A. It may help t use ne f the fllwing metaphrs t explain the MSC: Newspaper: Newspapers are structured int
Springer Texts in Statistics Gareth James Daniela Witten Trevr Hastie Rbert Tibshirani An Intrductin t Statistical Learning with Applicatins in R Springer Texts in Statistics 103 Series Editrs: G. Casella
The Synchrnizatin f Peridic Ruting Messages Sally Flyd and Van Jacbsn, Lawrence Berkeley Labratry, One Cycltrn Rad, Berkeley CA 9470, flyd@eelblgv, van@eelblgv T appear in the April 994 IEEE/ACM Transactins
Cmparisn f cmpsitin (nutrients and ther substances) f rganically and cnventinally prduced fdstuffs: a systematic review f the available literature Reprt fr the Fd Standards Agency Nutritin and Public Health
Frm Data Mining t Knwledge Discvery in Databases Usama Fayyad, Gregry Piatetsky-Shapir, and Padhraic Smyth Data mining and knwledge discvery in databases have been attracting a significant amunt f research,
Teacher s Manual fr the wrld s mst ppular LMS Jaswinder Singh Hw t Use Mdle 2.7 2 Hw t use Mdle 2.7, 1 st Editin Teacher s Manual fr the wrld s mst ppular LMS Jaswinder Singh 3 This bk is dedicated t my
SECURITY GUIDANCE FOR CRITICAL AREAS OF FOCUS IN CLOUD COMPUTING V3.0 INTRODUCTION The guidance prvided herein is the third versin f the Clud Security Alliance dcument, Security Guidance fr Critical Areas
Hw t Cnvert yur Paper int a Presentatin During yur cllege career, yu may be asked t present yur academic wrk in the classrm, at cnferences, r at special events. Tw types f talks are cmmn in academia: presentatins
Building Yur Bk fr Kindle We are excited yu ve decided t design, frmat, and prepare yur bk fr Kindle! We ll walk yu thrugh the necessary steps in creating a prfessinal digital file f yur bk fr quick uplad
Nt in Cully: Anti-Displacement Strategies fr the Cully Neighbrhd Prepared fr Living Cully: A Cully Ecdistrict June 2013 Nt in Cully: Anti-Displacement Strategies fr the Cully Neighbrhd June 2013 Acknwledgements
The Data Center Management Elephant By David Cle DATA CENTER SOLUTIONS Fr Mre Infrmatin: (866) 787-3271 Sales@PTSdcs.cm 2010 N Limits Sftware. All rights reserved. N part f this publicatin may be used,
Springer Series in Statistics Trevr Hastie Rbert Tibshirani Jerme Friedman The Elements f Statistical Learning Data Mining, Inference, and Predictin Secnd Editin This is page v Printer: paque this T ur
HOW TO OVERCOME PERFECTIONISM Mst peple wuld cnsider having high standards a gd thing. Striving fr excellence can shw that yu have a gd wrk ethic and strength f character. High standards can als push yu
Please cite this paper as: Mickleit, A. (2014), Scial Media Use by Gvernments: A Plicy Primer t Discuss Trends, Identify Plicy Opprtunities and Guide Decisin Makers, OECD Wrking Papers n Public Gvernance,
1 IS THERE A CONTRACT? MANIFESTATION OF MUTUAL ASSENT: There must be an bjective manifestatin f mutual assent t a K. Judged by what a reasnable persn wuld understand the parties actins t mean. - At stake
Anim. Behav., 1991,41, 103 ll0 Grey squirrels remember the lcatins f buried nuts LUCIA F. JACOBS+ & EMILY R. LIMANT Deprtnrent f Bilgv, Princetn University, Princetn, NJ 08544, U.S.A. ( Received 2 January
R fr Beginners Emmanuel Paradis Institut des Sciences de l Évlutin Université Mntpellier II F-34095 Mntpellier cédex 05 France E-mail: email@example.com I thank Julien Claude, Christphe Declercq,
FACING YOUR FEARS: EXPOSURE An imprtant step in managing anxiety invlves facing feared situatins, places r bjects. It is nrmal t want t avid the things yu fear. Hwever, avidance prevents yu frm learning
Revised August 2014 fr Applicatin Perid Fall 2015 Frequently Asked Questins LPN - RN Prgram LPN s interested in the LPN-RN transitin have the same pre-admissin & general educatin requirements as generic
RISING TO THE CHALLENGE Re-Envisining Public Libraries RISING TO THE CHALLENGE Re-Envisining Public Libraries A reprt f the Aspen Institute Dialgue n Public Libraries by Amy K. Garmer Directr Aspen Institute