NOVEMBER 13, 2007 

REVISED FINAL REPORT 

ON 

CHARACTERIZATION OF DUST LEAD LEVELS AFTER RENOVATION, REPAIR, AND 

PAINTING ACTIVITIES 

Prepared By 

BATTELLE 

505 King Avenue 

Columbus, Ohio 43201 

EPA Contract No. EP-W-04-021 

Prepared For 

Sineta Wooten, Project Officer 

Ronald Morony, Work Assignment Manager 

Samuel Brown, Deputy Work Assignment Manager 

Program Assessment and Outreach Branch 

National Program Chemicals Division 

Office of Pollution Prevention and Toxics 

U.S. Environmental Protection Agency 

1200 Pennsylvania Avenue NW (7404T) 

Washington, D.C. 20460
Acknowledgements

Many people contributed to the completion of this study. At EPA, Mr. John Schwemberger 

served as the EPA Work Assignment Manager assisted by Mr. Samuel Brown. At Battelle, 

Mr. Tim Pivetz served as the project manager supported by a large team of people. In 

alphabetical order, those who contributed significantly include Mr. Wesley Baxter, 

Ms. Rona Boehm, Mr. Peter Bujnak, Dr. Cynthia Cooper, Mr. Steven Gomori, Mr. Brad 

Goodwin, Mr. Pernell Horton, Ms. Nicole-Iroz Elardo, Mr. Darrell Joseph, Ms. Michelle 

Lobdell, Ms. Kathya Mahadevan, Mr. Ian MacGregor, Mr. Mark Misita, Ms. Susan Morriss, 

Ms. Jyothi Nagaraja, Mr. Henry Pham, Ms. Cyndi Reese, Mr. Adam Ridenbaugh, Dr. Jessica 

Sanford, Dr. Ketra Schmitt, Ms. Elizabeth Slone, Mr. Warren Strauss, Mr. Joseph Tabor, 

Ms. Rena Thomas, Ms. Stephanie Weber, Mr. Zachary Willenberg, and Ms. Jennifer Zewatsky. 

The study team expresses sincere thanks to the many property owners who made their houses 

available for renovation work under this study, as well as to Columbus Public Schools who 

provided access to one of their vacant buildings. The study team also thanks the many 

subcontractors who supported the study including police officers in Columbus and Pittsburgh, 

renovation firms and the renovation workers who implemented the study protocols, abatement 

cleaning firms, environmental testing firms who provided XRF testing and clearance testing 

services, the analytical laboratory, and staff at Healthy Housing Solutions, Inc. who supported 

the search for potential units. The study also thanks those staff at the Ohio Department of 

Health, Columbus Health Department, Pennsylvania Department of Health, and Allegheny 

County Health Department who provided guidance and assistance along the way. 

Thanks also to other staff and subcontractors who provided support to the study but are not 

named above. The study could not have been completed without the full effort of everyone on 

the team.
i

TABLE OF CONTENTS

Page

GLOSSARY OF TERMS............................................................................................................. ................vii 

1.0 INTRODUCTION...........................................................................................................................1-1 

1.1 BACKGROUND AND PURPOSE OF STUDY.................................................................1-1 

1.2 PROPOSED RULE SUMMARY.......................................................................................1-1 

1.3 STUDY OBJECTIVES......................................................................................................1-2 

2.0 SUMMARY OF CONCLUSIONS AND PEER REVIEWS.............................................................2-1 

2.1 CONCLUSIONS SUMMARY ...........................................................................................2-1 

2.2 PEER REVIEWS OF STUDY DESIGN............................................................................2-2 

2.3 HUMAN SUBJECTS REVIEW.........................................................................................2-3 

3.0 STUDY DESIGN ...........................................................................................................................3-1 

 3.1 SITE SELECTION PROCESS AND REQUIREMENTS ..................................................3-1 

 3.2 SAMPLING METHODS ...................................................................................................3-2 

 3.3 LABORATORY ANALYSIS METHODS...........................................................................3-3 

 3.4 FIELD SAMPLING PROTOCOLS....................................................................................3-4 

 3.4.1 Interior Jobs ........................................................................................................3-4 

 3.4.2 Exterior Jobs .......................................................................................................3-9

 3.5 PARTICIPATING CONTRACTORS (RRP WORKERS, CLEANING, 

 CLEARANCE TECHNICIANS) ......................................................................................3-10 

 3.6 ENVIRONMENTAL SAFETY AND HEALTH PLAN.......................................................3-10 

4.0 FIELD WORK SUMMARY ............................................................................................................4-1 

4.1 OVERVIEW OF SITE SELECTION/SCREENING PROCESS........................................4-1 

4.2 NUMBER AND TYPE OF EXPERIMENTS COMPLETED..............................................4-3 

4.3 PROTECTION AND CLEANING ROUTINES..................................................................4-4 

4.4 ENVIRONMENTAL SAMPLES COLLECTED .................................................................4-6 

4.5 PROTOCOL/SAMPLING ISSUES AND RESOLUTIONS ...............................................4-7 

4.6 ADHERENCE TO ENVIRONMENTAL SAFETY AND HEALTH PROTOCOLS............4-10 

4.7 RECORDKEEPING........................................................................................................4-11 

5.0 STATISTICAL ANALYSIS PLAN ..................................................................................................5-1 

5.1 DATA ORGANIZATION ...................................................................................................5-1 

5.2 DESCRIPTIVE ANALYSES .............................................................................................5-1 

5.3 STATISTICAL MODELS..................................................................................................5-2 

6.0 DESCRIPTIVE ANALYSES ..........................................................................................................6-1 

6.1 HOUSING UNIT/EXPERIMENT SUMMARY INFORMATION.........................................6-1 

6.2 PAINT LEAD LEVELS .....................................................................................................6-5 

6.3 PRE-WORK CLEARANCE LEVELS................................................................................6-6 

6.4 BULK DEBRIS SAMPLES .............................................................................................6-10 

6.5 INTERIOR DUST SAMPLES .........................................................................................6-11 

 6.5.1 Interior Floor Samples.......................................................................................6-11 

 6.5.2 Interior Sill Samples ..........................................................................................6-17 

 6.5.3 Hallway/Exit Samples .......................................................................................6-22 

 6.5.4 Exterior Post-Work Tray Samples during Window Replacements ...................6-23 

6.6 INTERIOR AIR SAMPLES.............................................................................................6-24 

6.7 EXTERIOR DUST SAMPLES........................................................................................6-25 
ii

Page

6.8 SOIL SAMPLES.............................................................................................................6-29 

 6.8.1 Soil Sampling for Interior Jobs..........................................................................6-29 

 6.8.2 Soil Sampling for Exterior Jobs.........................................................................6-32 

6.9 LENGTH OF ACTIVITY DATA.......................................................................................6-34 

 6.9.1 Duration of Post-work Cleaning ........................................................................6-34 

 6.9.2 Duration of Cleaning Verification ......................................................................6-35 

 6.9.3 Duration of Pre-Work Set Up ............................................................................6-36 

 6.9.4 Duration of Interior RRP Work ..........................................................................6-37 

6.10 CLEANING VERIFICATION DATA................................................................................6-38 

 6.10.1 Verification of Floor Zones................................................................................6-38 

 6.10.2 Verification of Window Sills...............................................................................6-47 

7.0 STATISTICAL MODELING RESULTS .........................................................................................7-1 

7.1 POST-WORK DUST LEAD LEVELS...............................................................................7-2 

 7.1.1 Post-Work Work Room Dust Lead Levels ..........................................................7-2 

 7.1.2 Post-Work Tool Room Dust Lead Levels............................................................7-4 

 7.1.3 Post-Work Observation Room Dust Lead Levels ...............................................7-6 

7.2 POST CLEANING STAGE – DUST LEAD LEVELS........................................................7-7 

 7.2.1 Post-Cleaning Work Room Dust Lead Levels ....................................................7-7 

 7.2.2 Post-Cleaning Tool Room Dust Lead Levels....................................................7-10 

 7.2.3 Post-Cleaning Observation Room Dust Lead Levels .......................................7-13 

7.3 POST-VERIFICATION STAGE DUST LEAD LEVELS..................................................7-16 

 7.3.1. Post-Verification Work Room Dust Lead Levels...............................................7-16 

 7.3.2. Post-Verification Tool Room Dust Lead Levels ................................................7-18 

 7.3.3. Post-Verification Observation Room Dust Lead Levels....................................7-20 

7.4 COMPARISON OF RULE PRACTICES AND BASELINE PRACTICES-POST-JOB 

 DUST LEAD LEVELS ....................................................................................................7-22 

 7.4.1. Post-Job Work Room Dust Lead Levels...........................................................7-22 

 7.4.2. Post-Job Tool Room Dust Lead Levels ............................................................7-23 

 7.4,3. Post-Job Observation Room Dust Lead Levels................................................7-24 

7.5 EXTERIOR DUST LEAD LEVELS.................................................................................7-26 

7.6 POST-VERIFICATION PREDICTORS OF CLEARANCE FAILURE.............................7-28 

 7.6.1 Single Covariate Modeling Results...................................................................7-29 

 7.6.2 Multivariate Modeling Results...........................................................................7-45 

 7.6.3 Summary of Results..........................................................................................7-47 

8.0 QUALITY ASSURANCE AND QUALITY CONTROL RESULTS..................................................8-1 

8.1 FIELD AUDIT RESULTS .................................................................................................8-1 

 8.1.1 Site Selection Audit.............................................................................................8-1 

 8.1.2 Field Implementation...........................................................................................8-1 

 8.1.3 EPA Site Visits ....................................................................................................8-2 

8.2 LABORATORY AUDIT RESULTS...................................................................................8-2 

8.3 QC SAMPLE RESULTS, ISSUES, AND RESOLUTIONS...............................................8-2 

8.4 DATA AUDIT PROCESS AND RESULTS.......................................................................8-4 

8.5 SOFTWARE REVIEWS ...................................................................................................8-4 

9.0 CONCLUSIONS............................................................................................................................9-1 

9.1 OBJECTIVE 1: EFFECT OF INTENSITY LEVEL ON DUST-LEAD LEVELS .................9-1 

9.2 OBJECTIVE 2: EFFECT OF USE OF INTERIOR PLASTIC ...........................................9-1 

9.3 OBJECTIVE 3: EFFECT OF USE OF PROPOSED RULE CLEANING METHOD .........9-2 

9.4 OBJECTIVE 4: ANALYSIS OF DUST MIGRATION .......................................................9-2 
iii

9.5 OBJECTIVE 5: EFFECT OF PLASTIC GROUND COVERING DURING EXTERIOR 

WORK ............................................................................................................................9-3 

9.6 OBJECTIVE 6: EFFECTS OF CLEANING VERIFICATION PROCESS.........................9-3 

9.7 OBJECTIVE 7: COMPARISON OF RULE PRACTICES AND BASELINE PRACTICES 9-6 

APPENDIX A: EXPERIMENT-SPECIFIC REPORTS .............................................................................A-1 

APPENDIX B: DETAILED DESCRIPTIVE ANALYSES OF EXTERIOR DUST LEAD LOADINGS 

(INCLUDING BULK DEBRIS SAMPLES)........................................................................B-1 

APPENDIX C: DETAILED DESCRIPTIVE ANALYSES OF INTERIOR FLOOR DUST 

 LEAD LOADINGS........................................................................................................... C-1 

APPENDIX D: DETAILED DESCRIPTIVE ANALYSES OF INTERIOR WINDOW SILL DUST 

 LEAD LOADINGS .......................................................................................................... D-1 

APPENDIX E: DETAILED DESCRIPTIVE ANALYSES OF EXTERIOR DUST LEAD LOADINGS 

(WITHOUT BULK DEBRIS SAMPLES)...........................................................................E-1 

APPENDIX F: DETAILED DESCRIPTIVE ANALYSES OF INTERIOR AIR 

 LEAD CONCENTRATIONS.............................................................................................F-1 

APPENDIX G: DETAILED DESCRIPTIVE ANALYSES OF AVERAGE POST-WORK WORK ROOM 

FLOOR DUST LEAD LOADING, AVERAGE PAINT LEAD LOADING, AND AREA 

DISTURBED ................................................................................................................... G-1

APPENDIX H: DETAILED DESCRIPTIVE ANALYSES OF INTERIOR HALLWAY 

 DUST LEAD LOADINGS ................................................................................................ H-1 

APPENDIX I: DETAILED STATISTICAL MODELING RESULTS OF RESIDENTIAL FLOOR 

 LEAD LEVELS ..................................................................................................................I-1 

APPENDIX J: DETAILED STATISTICAL MODELING RESULTS OF RESIDENTIAL WINDOW 

 SILL LEAD LEVELS......................................................................................................... J-1 

APPENDIX K: DETAILED STATISTICAL MODELING RESULTS OF COF FLOOR 

 LEAD LEVELS .................................................................................................................K-1 

APPENDIX L: DETAILED STATISTICAL MODELING RESULTS OF COMBINED HOUSING 

 UNIT/COF FLOOR LEAD LEVELS..................................................................................L-1 

APPENDIX M: DETAILED STATISTICAL MODELING RESULTS OF COMBINED HOUSING 

 UNIT/COF WINDOW SILL LEAD LEVELS.....................................................................M-1 

APPENDIX N: DETAILED STATISTICAL MODELING RESULTS OF EXTERIOR DUST LEAD LEVELS 

FOR COMBINED RESIDENTIAL AND COF DATA ....................................................... N-1 

APPENDIX O: HISTOGRAMS OF RESIDUALS OF BEST FITTING MODELS .................................... O-1 

LIST OF TABLES 

Table 4-1. Housing Unit Distribution by City .....................................................................................4-1 

Table 4-2. Interior RRP Jobs Across Three Levels of RRP Work.....................................................4-3 

Table 4-3. Exterior RRP Jobs Across Three Levels of RRP Work ...................................................4-4 
iv

Table 4-4. Interior Jobs and Associated Approaches for Conducting Experiment ...........................4-5 

Table 4-5. Exterior Jobs Conducted in Each City .............................................................................4-6

Table 4-6. Total Number of Environmental Samples Collected .......................................................4-7 

Table 6-1 Housing Unit Information .................................................................................................6-1 

Table 6-2 Interior Experiment Summary Table ................................................................................6-2 

Table 6-3 Exterior Experiment Summary Table...............................................................................6-4 

Table 6-4 Summary of the Pre-work Clearance Information............................................................6-8 

Table 6-5 Interior Bulk Samples by Job Type ................................................................................6-10

Table 6-6 Exterior Bulk Samples by Job Type...............................................................................6-10 

Table 6-7 Exterior Dust Wipe Samples During Window Replacement ..........................................6-24 

Table 6-8 Number (and Percentage) of Interior Air Dust Lead Concentration Measurements 

 (μg/m3) Below Detection Limit Measurements by Room and Stage..............................6-24 

Table 6-9 Distance of Exterior Trays from Work............................................................................6-26 

Table 6-10 Average Background Dust Loading for Exterior Experiments, by Job Type..................6-29 

Table 6-11 Pre- and Post-Work Soil Sample Results (μg/g) by Interior Experiment .......................6-30 

Table 6-12 Average Post-work/Pre-work Ratios for Interior Work Soil Samples by Job Type ........6-32 

Table 6-13 Pre- and Post-Work Soil Sample Results (μg/g) for Exterior Experiments....................6-33 

Table 6-14 Ratio of Post-work to Pre-work Soil Lead Level in Exterior Soil Samples 

 by Job Type....................................................................................................................6-34 

Table 6-15 Summary of Post-work Cleaning Times, by Phase (in minutes) ...................................6-34 

Table 6-16 Summary of Post-work Cleaning Times, by Job (in minutes)........................................6-35 

Table 6-17 Summary of Post-work Cleaning Times, by Contractor (in minutes).............................6-35 

Table 6-18 Duration of Post-work Cleaning Verification Stages, by Phase (in minutes).................6-35 

Table 6-19 Duration of Post-work Cleaning Verification Stages, by Job (in minutes) .....................6-36 

Table 6-20 Duration of Post-work Cleaning Verification Stages, by Contractor (in minutes) ..........6-36 

Table 6-21 Duration of Interior Pre-work Set-up (in minutes) ..........................................................6-36 

Table 6-22 Duration of Interior Pre-work Set-up, by Contractor ......................................................6-36 

Table 6-23 Duration of Interior Pre-work Set-up, by Building Type (in minutes) .............................6-37 

Table 6-24 Duration of Interior Work, by Job (in minutes) ...............................................................6-37 

Table 6-25 Duration of Exterior Work, by Job (in minutes) ..............................................................6-38 

Table 6-26 Floor Verification Information by Phase.........................................................................6-40

Table 6-27 Post-cleaning and Post-verification Floor Lead Levels for Experiments with 

 Zero and ≥1 Verification Failures by Phase...................................................................6-40 

Table 6-28 Floor Verification Information by Job Type ....................................................................6-41 

Table 6-29 Floor Verification Information by Contractor ..................................................................6-42 

Table 6-30 Floor Verification Information by Floor Type..................................................................6-42 

Table 6-31 Floor Verification Information by Floor Condition...........................................................6-42 

Table 6-32 Floor Verification Information by Job Type, Floor Type, and Floor Condition ...............6-43 

Table 6-33 Floor Zones That Failed Second Wet Cloth Verification................................................6-43 

Table 6-34 Verification Information for Interior Experiments............................................................6-45 

Table 6-35 Window Sill Verification Information by Phase ..............................................................6-47 

Table 6-36 Window Sill Verification Information by Intensity Level..................................................6-47 

Table 6-37 Verification Information for Interior Experiments............................................................6-47 

Table 6-38 Post-cleaning and Post-verification Sill Lead Levels for Experiments with 

 Zero and ≥1 Verification Failures by Phase...................................................................6-48 

Table 6-39 Window Sill Verification Information for Interior Experiments........................................6-49 

Table 7-1 Post-Work Work Room Modeling Results........................................................................7-4 

Table 7-2 Post-Work Tool Room Modeling Results.........................................................................7-5 

Table 7-3 Post-Work Observation Room Modeling Results ............................................................7-7 

Table 7-4 Post-cleaning Work Room Modeling Results ..................................................................7-9 

Table 7-5 Post-cleaning Tool Room Modeling Results..................................................................7-12 

Table 7-6 Post-cleaning Observation Room Modeling Results .....................................................7-14 

Table 7-7 Post-verification Work Room Modeling Results.............................................................7-17 

Table 7-8 Post-verification Tool Room Modeling Results ..............................................................7-19 

Table 7-9 Post-verification Observation Room Modeling Results..................................................7-21 

Table 7-10 Post-job Work Room Rule vs. Non-Rule Modeling Results...........................................7-23 
v

Table 7-11 Post-job Tool Room Rule vs. Non-Rule Modeling Results ............................................7-24 

Table 7-12 Post-job Observation Room Rule vs. Non-Rule Modeling Results................................7-25 

Table 7-13 Comparison Exterior Dust Pan Levels Within Each Job with Bulk Debris Samples 

 Included (Model Based Estimate Differences and Ratios) ............................................7-26 

Table 7-14 Comparison Exterior Dust Pan Levels Within Each Job Excluding Bulk Debris 

 Samples (Model Based Estimate Differences and Ratios)............................................7-27 

Table 7-15 Single Covariate Logistic Regression Modeling Estimates for Proportion of Failed 

 Post-verification Floor Wipe Samples............................................................................7-32 

Table 7-16 Single Covariate Model Results for Proportion of Failed Post-verification Floor Wipe 

 Samples across All Jobs................................................................................................7-33 

Table 7-17 Single Covariate Model Results for Proportion of Failed Post-verification Floor 

 Wipe Samples across Non-restricted Jobs....................................................................7-34 

Table 7-18 Single Covariate Model Results for Proportion of Failed Post-verification Floor 

 Wipe Samples across Non-restricted Jobs Using Rule Cleaning..................................7-35 

Table 7-19 Single Covariate Logistic Regression Modeling Results for Probability of Failed 

 Post-verification Floor Wipe ...........................................................................................7-38 

Table 7-20 Single Covariate Model Results for Probability of Failed Post-verification Floor 

 Wipe ..........................................................................................................................7-39 

Table 7-21 Single Covariate Model Results for Probability of Failed Post-verification Floor 

 Wipe across Non-restricted Jobs...................................................................................7-40 

Table 7-22 Single Covariate Model Results for Probability of Failed Post-verification Floor 

 Wipe across Non-restricted Jobs Using Rule Cleaning.................................................7-41 

Table 7-23 Single Covariate Logistic Regression Modeling Results for Probability of Failed 

 Window Sill Cleaning Verification ..................................................................................7-43 

Table 7-24 Single Covariate Model Results for Probability of Failing a Single Post-verification 

 Window Sill Wipe Sample ..............................................................................................7-44 

Table 7-25 Single Covariate Model Results for Probability of Failing a Single Post-verification 

 Window Sill Wipe Sample across Non-restricted Jobs ..................................................7-44 

Table 7-26 Single Covariate Model Results for Probability of Failing a Single Post-verification 

 Window Sill Wipe Sample across Non-restricted Jobs Using Rule Cleaning................7-45 

Table 7-27 Multivariate Model Results for Proportion of Failed Post-verification Floor Wipe 

 Samples across all Experiments....................................................................................7-45 

Table 7-28 Multivariate Model Results for Proportion of Failed Post-verification Floor Wipe 

 Samples across Non-restricted Jobs .............................................................................7-46 

Table 7-29 Multivariate Model Results for Probability of Failed Post-verification Floor Wipe 

 across all Experiments...................................................................................................7-46

Table 7-30 Multivariate Model Results for Probability of Failed Post-verification Floor Wipe 

 across Non-restricted Jobs ............................................................................................7-47 

Table 8-1 Summary of External QC Results....................................................................................8-3

Table 8-2 Schneider Laboratories Quality Control Data ..................................................................8-3 

Table 9-1 Post-Job Floor Lead Levels and Number Of Samples Failing Clearance in the Work 

 Room ............................................................................................................................9-4 

Table 9-2 Post-Job Floor Lead Levels And Number Of Samples Failing Clearance (Excluding Door 

Planing And High Heat Gun Jobs)...................................................................................9-4 

Table 9-3 Post-Job Floor Lead Levels and Number of Samples Failing Clearance 

 (Door Planing and High Heath Gun Jobs Only) in the Work Room.................................9-5 

Table 9-4 Post-job Window Sill Lead Levels and Number of Samples Failing Clearance ..............9-5 

Table 9-5 Post-job Window Sill Lead Levels and Number of Samples Failing Clearance 

 For Sampled Window Sills ...............................................................................................9-6 

Table 9-6 Post-job Window Sill Lead Levels and Number of Samples Failing Clearance 

 Sampled Dust Collection Trays........................................................................................9-6 

Table 9-7 Post-Job Average Floor Lead Levels and Failed Samples by Job Type.........................9-9 

Table 9-8 Post-job Window Sill Average Lead Levels and Failed Samples by Job Type .............9-10 
vi

LIST OF FIGURES 

Figure 3-1 Flowchart of Interior Field Sampling Activities .................................................................3-8 

Figure 6-1 Scatter Plot of Area Disturbed vs. Average Post-work Work Room Floor 

 Lead Loading ...................................................................................................................6-6 

Figure 6-2 Post-work Work Room Floor Lead Levels, by Job.........................................................6-11 

Figure 6-3 Post-Cleaning Work Room Floor Lead Levels, by Job and Plastic Use........................6-12 

Figure 6-4 Post-Cleaning Work Room Floor Lead Levels, by Job and Cleaning Method...............6-13 

Figure 6-5 Post-Job Work Room Floor Lead Levels, by Job and Phase ........................................6-14 

Figure 6-6 Post-Job Tool Room Floor Lead Levels, by Job and Phase..........................................6-16 

Figure 6-7 Post-Job Observation Room Floor Lead Levels, by Job and Phase.............................6-16 

Figure 6-8 Post-Cleaning Work Room Sill Lead Levels, by Job and Plastic Use ...........................6-18 

Figure 6-9 Post-Cleaning Work Room Sill Lead Levels, by Job and Cleaning Method..................6-19 

Figure 6-10 Post-Job Work Room Sill Lead Levels, by Job and Rule Use.......................................6-20 

Figure 6-11 Post-Job Work Room Sill Lead Levels, by Job and Phase............................................6-20 

Figure 6-12 Post-Job Tool Room Sill Lead Levels, by Job and Rule Use ........................................6-21 

Figure 6-13 Post-Job Observation Room Sill Lead Levels, by Job and Rule Use............................6-22 

Figure 6-14 Post-work Air Lead Concentrations in the Work Room, by Job.....................................6-25 

Figure 6-15 Exterior Dust Lead Levels on and Under Rule Plastic, by Job 

 (w/bulk samples) ............................................................................................................6-28 

Figure 6-16 Exterior Dust Lead Levels on and Under Rule Plastic, by Job 

 (w/bulk samples) ............................................................................................................6-28 

Figure 6-17 Time Series of Soil Samples Near the Front Porch at H09 ...........................................6-31 

Figure 6-18 Post-verification Floor Lead Loadings by Phase ...........................................................6-39 

Figure 6-19 Post-verification Floor Lead Loadings by Job Type.......................................................6-41 

Figure 6-20 Number of Experiments by Post-cleaning and Post-verification Floor Lead Loadings..6-44 

Figure 6-21 Number of Experiments by Post-cleaning and Post-verification Sill Lead Loadings .....6-48 

Figure 9-1 Post-Job Work Room Floor Lead Levels, by Job and Rule Use .....................................9-7 

Figure 9-2 Post-Job Work Room Sill Lead Levels, by Job and Rule Use.........................................9-7 
vii

Glossary of Terms 

for the 

Field Study to Characterize Dust Lead Levels 

After Renovation, Repair, and Painting 

Baseline Cleaning – a series of steps to remove dust that are representative of standard cleaning 

practices used by RRP contractors without a final EPA rule for Renovation, Repair, and Painting. 

These include sweeping and vacuuming with a non-HEPA vacuum. 

Baseline Practices – the set of protection and clean-up practices (no use of protective plastic 

during work and use of baseline cleaning following work) representing typical work practices 

utilized for a renovation job without a final EPA rule for Renovation, Repair, and Painting. 

Child-Occupied Facility (COF) – a building, or portion of a vacant building, constructed 

before 1978 that could be used by children under six years old, such as a daycare center or 

early year kindergarten at a school, and that could conceivably meet the formal definition of a 

Child-Occupied Facility in 40 CFR part 745.223. 

Dust Lead Loading – the amount of lead obtained from in a given sample area. For this report, 

dust lead loading is presented in μg/ft2

. 

Experiment – full implementation of a single occurrence of a renovation job using one set of 

protection and clean-up methods; includes all work, cleaning, and environmental sampling. 

Housing Unit – a structure or portion of a structure that is typically occupied by one or more 

persons as living quarters. 

Job – a specific renovation, repair, or painting activity that is of interest for the risk assessment 

and economic cost-benefit analysis, such as installing a new window. 

Lead-based paint – paint or other coating with lead content at or above 1.0 mg/cm2

 or at or 

above 0.5% by weight (5,000 μg/g). 

Level or Intensity-level – one of three job categories (low, medium, or high), determined based 

on pre-study expectations of the amount of dust expected to be generated by each activity; 

because analysis of post-work lead levels indicated that these pre-assigned levels were not 

entirely consistent with actual dust generated, the primary analyses presented in the report 

summarize the renovation activities by individual job. 

Observation Room – an interior room adjacent to the Tool Room but not the Work Room that 

represents other areas of a house impacted by interior RRP work. 

Phase – one of four iterations of a job specified by the use or non-use of containment and a 

particular cleaning method (Phase I=plastic sheeting with specialized cleaning, Phase II=plastic 

sheeting with baseline cleaning, Phase III=no plastic sheeting with specialized cleaning, and 
viii

Phase IV=no plastic sheeting with baseline cleaning), each implemented under comparable 

conditions so the effect of containment and cleaning method can each be assessed. 

Replicate – a repetition of a specific job, including all four phases or iterations associated with 

the job (e.g., a second set of window replacements). 

RRP – an acronym that stands for Renovation, Repair, and Painting. 

Rule Practices – the set of protection and clean-up methods (use protective plastic during work, 

specialized cleaning following work, and cleaning verification) representing work practices 

under EPA’s Proposed Rule for Renovation, Repair, and Painting. 

Sites - housing units or COFs where one or more study experiments were conducted. 

Specialized (Rule) Cleaning – cleaning required by the EPA Proposed Rule for Renovation, 

Repair, and Painting; comprised of HEPA vacuuming and wet-mopping with two-bucket 

method. Note that neither phosphate nor ethylenediamine tetraacetic acid (EDTA) was used in 

the wash waters. 

Stage (of Sampling) – the four different points of time within an experiment at which 

environmental samples were collected (after completion of the RRP job, after completion of 

cleaning, after completion of the last wet cloth in the cleaning verification, and after completion 

of the last dry cloth in the cleaning verification). 

Study Location – a city or other geographic area participating in the study through 

identification, recruitment, and participation of housing units and COFs. 

Tool Room – an interior room immediately adjacent to the work room where workers might 

place equipment and materials needed for a job. 

Work Area – the location within the work room or on the exterior perimeter where the actual 

RRP work was performed. Note that the interior work area could cross the boundaries of the 

work room, e.g. if a window was being replaced from the inside, the work area might have 

included portions of the exterior. 

Work Room – the room in the housing unit or COF where the RRP work was to be performed. 
 

1-1 

1. Introduction 

1.1. Background and Purpose of Study 

Many residences built prior to 1978 contain lead-based paint that, if disturbed, is likely to create 

lead hazards for residents of the home. Data from the National Survey of Lead and Allergens in 

Housing indicate that lead-based paint was used in 24% of the housing constructed between 1960 

and 1978, in 69% of housing constructed between 1940 and 1959, and in 87% of housing 

constructed prior to 1940.1 Because of formulation changes, not only was lead more common 

among older homes but the lead content was higher as well. Actions that involve the disturbance 

or removal of lead-based paint, including many renovation and repair activities, can result in 

high localized concentrations of lead dust in the air and on exposed surfaces within the home, as 

well as in surrounding soils.2 

In support of the Federal government’s goal of eliminating childhood lead poisoning by 2010, 

EPA proposed a rule establishing requirements to protect residents of pre-1978 housing units 

from lead hazards due to Renovation, Repair, and Painting (RRP) activities. The proposed rule, 

issued under the authority of §402(c)(3) of the Toxic Substances Control Act (TSCA), was 

published in the Federal Register on January 10, 2006.3

 

In an effort to support a thorough risk assessment and cost-benefit analysis of the proposed rule, 

a field study was designed and conducted to characterize dust lead levels during various stages of 

RRP activities. Results of that field study are presented in this report. 

1.2. Proposed Rule Summary 

EPA’s proposed rule establishes training, certification, and accreditation requirements, as well as 

work practice standards, for contractors performing RRP work in housing built prior to 1978. 

Specifically, the proposal would establish requirements for training renovators and dust sampling 

technicians; certifying renovators, dust sampling technicians, and renovation firms; and 

accrediting providers of renovation and dust sampling technician training. The proposal would 

also require renovation professionals to follow certain lead-safe work practice standards. EPA 

developed these requirements, in part, based on conclusions drawn from a previous renovation 

and remodeling field study that identified relationships between certain renovation activities and 

elevated blood-lead levels.4

 The requirements address EPA’s concern that RRP work conducted 

by untrained and uncertified contractors may create new lead hazards, increasing the risk of lead 

exposure to the residents of homes containing lead-based paint. 

EPA has proposed a phased approach for implementation of this rule. Initially, the rule would 

apply only to RRP work performed in target housing built before 1960 – both rental and 

 

1

 U.S. Department of Housing and Urban Development (HUD). 2002. National Survey of Lead and Allergens in 

Housing, Volume I: Analysis of Lead Hazards, Final Report, Revision 7.1. 

2

 U.S. EPA. 2006. Air Quality Criteria for Lead (Second External Review Draft), Volume I of II. EPA/600/R-5/144aB. 3

 U.S. EPA. 40 CFR 745, Lead; Renovation, Repair, and Painting Program; Proposed Rule. Federal Register 

(71 FR 1588, January 10, 2006). 

4

 U.S. EPA. 1999. Lead Exposure Associated with Renovation and Remodeling Activities: Phase III, Wisconsin 

Childhood Blood-Lead Study. EPA 747-R-99-002. 
 

1-2 

owner-occupied – where a child with an elevated blood-lead level resides, unless, with respect to 

owner-occupied target housing, the renovation professional obtains a signed statement from the 

owner-occupant indicating that the renovation will occur in the owner’s residence and that no 

child under age 6 resides there. By the end of the phase-in period, the applicability of the rule 

would be expanded to include all rental and owner-occupied target housing built between 1960 

and 1977 and occupied by a child under age six. “Target housing” is defined in §401 of TSCA 

as “any housing constructed before 1978, except housing for the elderly or persons with 

disabilities (unless any child under age 6 resides or is expected to reside in such housing) or any 

0-bedroom dwelling.” EPA is also proposing to authorize interested states, U.S. Territories, and 

Indian Tribes to administer and enforce all elements of the new renovation provisions. 

1.3. Study Objectives 

The study was designed to compare environmental lead levels at appropriate stages after various 

types of RRP activities were conducted on the interior and exterior of residential housing units 

and child-occupied facilities (COFs). All jobs disturbed more than 2 square feet of lead based 

paint, which is the de minimus amount of disturbed area, to which the proposed rule applies. Of 

particular interest was the impact of using specific work practices that renovation contractors 

would be required to follow under the proposed rule (e.g., the use of plastic containment in the 

work area and a multi-step cleaning protocol). The RRP activities conducted represented the 

range of activities permitted under the proposed rule, including work practices that are restricted 

or prohibited under 40 CFR part 745.227(e)(6). These restricted or prohibited work practices 

included: 

• Open-flame burning or torching of lead-based paint; 

• Machine sanding or grinding or abrasive blasting or sandblasting of lead-based paint 

without a High Efficiency Particulate Air (HEPA) exhaust control; 

• Dry scraping of more than 2 square feet of interior lead-based paint in any one room 

and dry scraping totaling more than 20 square feet on exterior surfaces; and 

• Operating a heat gun on lead-based paint at temperatures above 1100 degrees 

Fahrenheit. 

 

The study design was tailored to generate data that would permit evaluation of the following 

seven study objectives: 

Objective 1: What is the effect of low-, medium-, and high-level RRP work on post-work, 

post-cleaning, and post-verification dust-lead levels (interior and exterior)? 

Objective 2: Are there significant differences in lead levels at the post-cleaning and/or 

post-verification phases from the use of heavy-duty polyethylene plastic sheeting during the 

work activity? Is there an interaction between level of RRP work and the use of plastic? 

Objective 3: Are there significant differences in post-cleaning and/or post-verification lead levels 

between surfaces cleaned with the proposed rule cleaning method and surfaces cleaned with 

baseline cleaning methods? Is there an interaction between level of RRP work and cleaning 

method used? 
 

1-3 

Objective 4: Are there differences in the amount of lead dust migration from the Work Room to 

adjacent rooms between different levels of RRP work, use and non-use of plastic, and use and 

non-use of proposed rule cleaning methods? 

Objective 5: Does the use of plastic ground coverings during exterior work reduce the amount of 

dust lead falling onto the ground? 

Objective 6: Are there significant differences in the lead levels remaining after the two steps of 

the cleaning verification process, i.e., the wet cloth step and the dry cloth step? 

Objective 7: Are there significant differences in post-job lead levels between jobs conducted 

using proposed rule practices (use of plastic, specialized cleaning, and cleaning verification) and 

those conducted using baseline practices (no plastic and baseline cleaning)? 
 

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2. Summary of Conclusions and Peer Reviews 

2.1. Conclusions Summary 

Objective 1 – Effect of Job Intensity and Job Type on Lead Levels Generated 

The results indicated that both initial intensity level and job type impacted post-work, postcleaning, and post-verification floor and sill lead levels. Data collected by the study indicated 

significant variability in the lead levels generated across the different jobs conducted. Using a 

power planer to remove paint from doors without exhaust controls generated significantly more 

lead than other interior jobs. On the other hand, cutting into walls to allow electrical, plumbing, 

or other work, generated significantly less lead than other jobs. On the exterior, jobs such as 

power sanding paint from walls generated large amounts of lead while dry scraping paint from a 

wall generated relatively less; however, these findings differed depending on whether the bulk 

debris and excessive dust generated by a job was included in the sample results. Removal of 

paint by torch burning left large amounts of lead in the dust collection trays as big chunks of 

paint were scraped from porch ceilings following heating with the torch; however, only one 

percent of the lead created by this work activity was measured by a dust wipe with the rest being 

work debris picked up by hand. 

Objective 2 – Effects of Use of Interior Plastic Protective Sheeting 

The results indicated that use of plastic resulted in somewhat lower average lead levels in the 

Work room; however, this effect was not statistically significant. Use of plastic did not 

consistently result in lower work room floor lead levels across job types at the post-cleaning 

phase. The use of plastic sheeting resulted in lower geometric mean lead levels for door planing 

and high heat gun jobs than when plastic was not used, as measured at the post-cleaning stage. 

Consistently lower geometric mean floor lead levels were found in the Tool and Observation 

rooms, respectively, with the use of plastic across all three sampling stages although the 

differences were relatively small. Hypothesis testing of differences in floor and sill lead levels 

based on use of plastic had mixed results with some statistically significant differences and some 

not statistically significant. 

Objective 3 – Effect of Use of Proposed Rule Cleaning Method 

The results indicated that the proposed Rule cleaning method led to much lower geometric mean 

lead levels remaining in the Work room following post-work cleaning, which was confirmed by 

statistical modeling. Little impact of cleaning method was observed in either of the two nonwork rooms. 

Objective 4 – Analysis of Dust Migration 

The results indicated that measurably lower levels of lead were measured in the Tool and 

Observation rooms when plastic was used during the work, however, mixed results were 

obtained in regards to the statistical significance of those differences. The cleaning method used 

in the work room did not have a significant impact on lead levels in the non-study rooms. 

Objective 5 – Effects of Plastic Ground Covering During Exterior Work 

The use of plastic ground coverings captured large amounts of lead which were considerably 

larger than the lead that was below the plastic coverings. When considering all the dust and 
 

2-2 

debris that was captured on top of the Rule plastic, predicted ratios of lead measured on top of 

the Rule plastic to lead measured under the Rule plastic ranged from 66:1 to 2,291:1 across 

exterior jobs. The lowest lower 95% confidence interval bounds on those ratios were 12:1 and 

6:1, respectively, for the power sanding and the torch burning jobs. Some jobs resulted in high 

lead levels measured in areas just outside the Rule plastic. 

Objective 6 – Effects of Cleaning Verification Process 

The cleaning verification process as stated in the proposed rule resulted in decreases in lead 

levels, but under the conditions of the study was not always accurate in identifying the presence 

of levels above EPA standards for floors and sills. Factors such as floor condition, contractor 

performance, job type, and dust particle characteristics impacted the cleaning verification 

process in the study; however, floor condition of post-work and post-cleaning lead levels were 

found to best explain cleaning verification failures. All interior experiments did result in final 

passed cleaning cloths for all floor zones and for all window sills, but nearly half of the 

experiments ended with average Work room floor lead levels above 40 μg/ft2 on floors. Lead 

levels for the cases above the floor standard were distributed as follows: 10 between 40 and 69, 

6 between 70 and 99, 5 between 100 and 199, 3 between 200 and 499, and 5 greater than 500. 

The eight highest levels were associated with high heat gun or door planing jobs and floors in 

poor condition. Of the 29 experiments where final lead levels were above 40 μg/ft2 on floors, 20 

were on floors in poor condition. Excluding the door planing and high heat gun jobs, which had 

higher post-job lead levels than the others and which appeared to generate fine particle size dust 

and, in the case of the door planing, a white dust that was hard to detect on a white cloth, postjob averages when the proposed rule cleaning was used were below clearance levels. For 

window sills, approximately 20 percent of the experiments ended with lead levels above 250 

μg/ft2. Almost all of the high levels, well above the standard, were associated with door plane 

and high temperature heat gun jobs. The study did not yield much evidence to evaluate 

differences in lead levels after the wet and dry cleaning verification steps because the dry 

cleaning verification was only required in three experiments. 

Objective 7 – Comparison of Rule Practices and Baseline Practices 

The results indicated that the proposed rule practices resulted in lower geometric mean floor and 

window sill lead levels in the work room at the completion of a job, and these results were 

confirmed by statistical modeling. There was evidence of proposed rule practices resulting in 

lower lead levels in the non-work rooms; however, these differences were not consistently 

statistically significant. 

2.2. Peer Reviews of Study Design 

The design and quality assurance project plan of this study were peer reviewed. The peer review 

was conducted from May 24, 2006 to June 11, 2006. Experts in fields related to the study 

reviewed the design and quality assurance plan independently and provided written comments to 

EPA. The major comments of the reviewers as a group are summarized below. 

Overall, most reviewers commented favorably on the study design. In response to a charge 

question asking for recommendations for alternative approaches, most reviewers indicated the 

design as proposed was satisfactory. Nevertheless, a number of reviewers recommended that 
 

2-3 

more samples be collected. In response, more dust samples were added in the Work Room, more 

exterior soil samples were included for both interior and exterior renovation jobs, and 

background samples for exterior dust collection tray sampling were added. 

Some reviewers suggested adding more intensive jobs to the study, and some reviewers 

questioned whether the less intensive jobs in the study would result in a sufficient amount of lead 

dust. In response, more intensive jobs, such as power sanding without a HEPA attachment and 

open flame burning, were added to the study. Less intensive jobs remained in the study, 

however, because the goal of the study was to examine the range of activities expected to be 

covered by the EPA rule. Approximate square footage of lead-based paint disturbed by each job 

was measured in each experiment, and all jobs in the study disturbed more than the de minimus 2 

square feet in the proposed Renovation, Repair, and Painting rule. 

A number of reviewers commented that the impact of “real world” renovation conditions, such 

as the presence of furniture, occupants, pets, pre-existing lead dust, and so on, would not be 

captured by the study. For health and safety reasons, the study was conducted in vacant housing 

units and other vacant units. The study results may underestimate the levels of dust that would 

result from a renovation job due to the absence of these “real world” factors, but the study will 

achieve its goal of providing comparative data on the difference in lead dust levels when leadbased paint is disturbed under proposed rule versus baseline work practices. 

A reviewer questioned the use of the phrase “normal cleaning” in the design documentation to 

describe dry broom sweeping and shop vacuuming. Dry broom sweeping and shop vacuuming 

were included in the study for comparative purposes as the cleaning that would likely be done if 

there were no EPA rule for Renovation, Repair, and Painting. The phrase “normal cleaning” was 

changed to “baseline cleaning.” 

Some reviewers recommended the use of ASTM standards. ASTM standards were adopted for 

dust and soil sampling. An ASTM standard for paint chip collection was included in the design 

at the time of the peer review. 

EPA has established an electronic record of the peer review of the study design. This record 

includes the comments from the reviewers and EPA’s responses to those comments. The peer 

review record for the review of the study design can be found in the public docket for the final 

rule. 

2.3. Human Subjects Review 

The study was assessed by EPA as to whether it met the definition of a Human Subjects study as 

defined by 40 CFR Part 26 – Protection of Human Subjects. EPA made the determination that 

the study was not a Human Subjects study because; (1) the only human subjects monitoring in 

the study, via the collection of personal air monitoring samples and the collection of blood 

samples from the RRP workers, was conducted solely to ensure compliance with all OSHA 

requirements in 29 CFR Part 1926.62 – Lead Exposure in Construction, and (2) the ensuing 

personal air monitoring data and blood lead data were not to be analyzed or generalized as part 
 

2-4 

of the study analysis. The personal air monitoring data and blood lead data were reported to 

appropriate parties as required by 29 CFR Part 1926.62. 

Representatives of the Battelle Institutional Review Board (IRB) reviewed the study design and 

data collection plans early in the design stage and again once the study protocols were fully 

established. From both reviews, they determined that the study did not meet the regulatory 

definition of “human subjects research” according to the definitions at 45 CFR 102 (f)(2) 

(Common Rule) and 40 CFR 26.102 (f)(2) (EPA specific regulation). As such, the study was not 

subject to the Human Subjects Protections regulations. 

Personal exposure monitoring was performed in accordance with health and safety requirements 

and was not used for purposes of research, but rather to determine the amount of airborne lead 

dust, if any, to which workers might be exposed and to confirm that the appropriate personal 

protective equipment (PPE) was used for the RRP workers. Thus, the IRB’s opinion was that the 

personal exposure monitoring was not related to the research objectives and, therefore, did not 

invoke human subjects protections, but, rather, was a personnel protection activity. In addition, 

the IRB did not determine the RPP field study to be an “intentional exposure” study in 

accordance with the provisions of 40 CFR Part 26.1102(1), “Research involving intentional 

exposure of a human subject means a study of a substance in which the exposure to the 

substance experienced by a human subject participating in the study would not have occurred 

but for the human subject's participation in the study.”. 
 

3-1 

3. Study Design 

3.1. Site Selection Process and Requirements 

As noted previously, the project was conducted to characterize the dust lead levels after various 

types and intensity of renovation, repair, or painting jobs in vacant housing units and vacant 

child-occupied facilities with lead-based paint (LBP). Both interior and exterior jobs were 

considered when evaluating sites for selection. 

Potential sites were evaluated for the 60 interior experiments (48 at housing units and 12 at 

COFs) and 15 exterior experiments (12 at housing units and 3 at COFs) for a total of 75 

experiments. Since multiple experiments could be performed at a single site, 75 individual sites 

were not required. To allow for multiple experiments at a site, however, there needed to be 

lead-based paint in sufficient quantities on the desired building components, ability to conduct 

the experiments in the available timeframe, and ability to avoid cross-contamination through 

cleaning and verification between experiments conducted at the same site. 

The following characteristics summarize the requirements of potential sites for inclusion in the 

study: 

• Built before 1978; 

• Cleanable before work began, in between, and at the completion of all study 

activities; 

• Vacant and accessible during the study data collection period and available to 

schedule work according to the study’s needs; 

• Presence of lead based paint at the required levels (defined as dried paint film that has 

a lead content at or exceeding 1.0 mg/cm2

 or 0.5 percent by weight) and of sufficient 

size [2 square feet (ft2) or more] within a single room or on specific desired 

components of the prospective site; 

• Ability of potential interior sites to meet the desired three room study layout by 

containing three sequentially adjacent rooms to allow sampling in a Work Room, a 

Tool Room, and an Observation Room; and 

• Adequate space at potential exterior sites in the yard or around the exterior of the 

building to allow desired sample collection and containment of dust and debris. 

Additional characteristics were also desirable but not required in potential sites, including: 

• Availability of electricity; 

• Selection of a cross section of building ages (e.g., 2 pre-1920, 2 built between 1920 

and 1950, and 2 built between 1950-1978) was ideal, but this desire was balanced by 

other study considerations; and 

• Sites within close proximity to each other so as to maximize site coordination efforts. 
3-2 

3.2. Sampling Methods 

For interior work, the study-impacted areas of participating housing units or COFs were defined 

as a set of three rooms – one undergoing the RRP activity, an adjacent room for tool storage, and 

an observation room adjacent to the tool storage room. In addition, post-experiment samples 

were obtained from a hallway running between these areas and the entrance of the unit used for 

conducting and exiting the job. 

Paint Chip Samples – Following initial identification of lead-based paint using an X-ray 

fluorescence instrument, paint chip samples were collected from prospective components for 

laboratory analysis in order to obtain an accurate measurement of the lead in the paint that was 

potentially going to be disturbed by the RRP work. The method used to collect paint samples 

was the cold-scraping method described in ASTM E1729, “Standard Practice for Field 

Collection of Dried Paint Samples for Subsequent Lead Determination.” The size of the samples 

obtained was approximately two square inches and included all paint down to the substrate, 

minimizing the amount of substrate material in the sample. Lead-based paint is defined by EPA 

as paint or other surface coatings that contain lead greater than or equal to 0.5 percent by weight 

or greater than or equal to 1.0 mg/cm2

. 

Interior Dust Wipe Samples – The interior sampling protocol involved collecting four floor dust 

wipe samples and one window sill dust wipe sample from the Work Room and two floor dust 

wipe samples and one window sill dust wipe sample from the other two study rooms (Tool and 

Observation rooms) at each stage of the experiment – post-work, post-cleaning, and postcleaning verification. In addition, if a floor verification zone in the Work Room failed two wet 

cloth verifications, an additional post-wet cloth verification sample was collected for that floor 

zone before proceeding with the dry verification process. All dust wipes were collected in 

accordance with ASTM 1728, “Standard Practice for Collection of Settled Dust Samples Using 

Wipe Sampling Methods for Subsequent Lead Determination.” 

The locations of the floor and window sill dust wipe samples in all three study rooms were 

randomly selected prior to the experiment and specified in experiment-specific sampling plans. 

This ensured that the locations of the samples were not biased by the field technician, and that no 

two samples were collected from the same area. The randomized sample selection in each room 

was stratified as necessary, to ensure samples were obtained from different sections of a room. If 

window sills were badly damaged, inadequately sized, or missing, a dust collection tray was 

placed in the study room, and all window sill samples were collected from the tray. Dust 

collection trays also replaced actual window sills when sills could not be cleaned below 250 

μg/ft2

. For the window replacement experiments, a dust collection tray was placed on the 

horizontal surface directly below the outside of the window and sampled after the work was 

completed. 

Note that total dust loadings were not obtained as part of this study. Total dust loading would 

have enabled calculation of concentration of lead per unit of total dust. 
3-3 

Exterior Dust Wipe Samples – For exterior work, nine dust collection trays were set up prior to 

the RRP work – three on top of the Rule plastic coverings, three in corresponding positions 

underneath the Rule plastic coverings, and three near the Rule plastic and on top of the 

protection plastic. Dust wipe samples were taken from each tray following completion of the 

work. Background lead levels in the air at exterior job sites were measured by setting out a dust 

collection tray for a number of hours and subsequently taking a dust wipe of the tray. 

Bulk Debris Samples – Where necessary, field technicians were instructed to collect excess 

debris that could not be collected with a dust wipe from each sampling location during the postwork sampling stage. The debris was collected by glove-covered hands and tools such as chisels 

that could scoop up material and placed in a plastic bag or centrifuge tube for further processing 

and laboratory analysis. For jobs that generated such large amounts of dust that it could not all 

be picked up using a dust wipe (such as the door planing job), technicians also used glovecovered hands to collect and place the excessive dust in a plastic bag. 

Ambient Air Samples – Air samples were collected as part of this study following NIOSH 

Method 7082. For interior work, air samplers were placed in all three study rooms on tripods 

approximately five feet off the ground, so as to approximate levels of dust lead available to be 

inhaled. A flow rate of 3 L/min was used and kept relatively constant (within the limits of the 

calibrator) for consistency throughout the study. 

Soil Samples – Soil samples were collected according to ASTM E1727-05, “Standard Practice 

for Field Collection of Soil Samples for Subsequent Lead Determination,” before and after both 

interior and exterior work. The soil samples served to measure potential track-in contamination 

during work (interior) and background lead contamination of the property (exterior), as well as 

potential contamination of the property by study activities. 

3.3. Laboratory Analysis Methods 

Paint Chip Samples – Laboratory sample preparation was performed according to EPA Method 

3050B, and the subsequent atomic absorption analysis of the determination of lead followed EPA 

Method 7420. The analysis provided measurements of lead concentrations in μg/g, with a 

minimum detection limit of 20 μg total lead per sample. 

Dust Wipe Samples – All interior and exterior dust wipe samples were prepared according to 

EPA Method 3050B and analyzed for lead content using EPA Method 7420 (atomic absorption). 

The analysis provided measurements of lead concentrations in μg/ft2

, with a minimum detection 

limit of 10 μg total lead per sample, which was requested to provide more specificity at lower 

levels of lead. 

Bulk Debris Samples –Battelle technicians recorded the total mass of each bulk debris sample. 

Subsequently, any non-paint chip/dust debris was removed (screws, nails, pieces of wood, etc.), 

the samples were homogenized (paint, dust, and other material crushed and mixed with a clean 

mortar and pestle), and two subsamples of at least 1 g each were obtained. Each was labeled 

appropriately and sent to the laboratory for analysis as paint chip samples. The laboratory 

reported percentage of lead by mass in each of the two subsamples. The mean lead mass percent 
3-4 

was calculated; this mean multiplied by the total bulk mass gives the total lead in the bulk 

sample. The total lead mass in the bulk sample is added to the total lead mass measured in the 

associated dust wipe sample to obtain total mass per square foot (μg/ft2) in the sampled area. 

Ambient Air Samples – Air filter samples were analyzed using NIOSH Method 7082 (flame 

atomic absorption spectrophotometry). The analysis provided measurements of lead 

concentrations in μg/m3, with a minimum detection limit of 2 μg total lead per filter. 

Soil Samples – EPA Method 3050B was used to prepare the soil samples for analysis. EPA 

Method 7420 (atomic absorption) was used to analyze the samples for lead. The analysis of soil 

lead concentrations was reported in μg/g, with a minimum detection limit of 20 μg total lead per 

sample. 

3.4. Field Sampling Protocols 

3.4.1. Interior Jobs 

Prior to the start of an experiment, paint chip samples were collected from building components 

that would potentially be disturbed during RRP activities to evaluate the lead concentrations in 

the paint. In addition, three composite soil samples were collected, where applicable, from bare 

soil nearest to (1) the entryway to the building used by the workers, (2) the walkway from the 

entryway to the street, and (3) a window closest to the work area. If the unit was used for 

multiple interior experiments, the post-experiment soil samples of the previous experiment were 

used as the pre-experiment soil samples for the next interior experiment, where appropriate. 

All areas of the unit not being used in the study were barricaded using plastic coverings. All air 

vents in floors, walls, and ceilings in any of the areas impacted by the study were also covered 

with plastic. A thorough cleaning was conducted by a lead abatement firm with experience 

cleaning after lead abatement activities in accordance with the U.S. Department of Housing and 

Urban Development (HUD) Guidelines on abatement cleaning and clearance. An independent 

licensed clearance technician then collected five dust wipes (4 floor, 1 sill) from the Work Room 

and three dust wipes (2 floor and 1 sill) each from the Tool and Observation Rooms, plus up to 

three additional samples in hallways or other areas impacted by the study. If the lead loading on 

the clearance wipes was no greater than 40 μg/ft2

 on floors and 250 μg/ft2 on window sills, the 

unit was declared clean. If one or more samples failed to meet these clearance standards, then 

the room in which that sample was collected was re-cleaned and re-sampled. 

Deviations from this plan did occur in order to maintain progress. There were some cases where 

one or more samples in a room were measured above 40 μg/ft2, but because the room average 

was below 40, the decision was made to proceed with work. There were a few cases where the 

room average was above 40 μg/ft2

, but work occurred because of schedule constraints. When 

floors in Tool and Observations were unable to achieve clearance, they were covered with clean 

plastic, which provided a clean surface with which to start the experiment. When window sills 

were in poor condition and/or could not be cleaned below 250 μg/ft2

, clean dust collection trays 

were used in place of the actual window sill in almost all cases. 
3-5 

If the interior protection/clean-up (P/CU) phase to be implemented involved containment, plastic 

coverings were set up in the Work Room by the RRP contractor according to the proposed rule. 

This included closing and sealing all doors into the Work Room; covering all doors within the 

work area that had to be used while the job was being performed with plastic sheeting in a 

manner that allowed workers to pass through, while confining dust and debris to the work area; 

covering the entire floor surface with taped-down plastic sheeting in the Work Room; and taping 

plastic to the outside of the window frame, if a window was being replaced as part of the job, so 

that no debris could fall to the ground outside the window. 

An area just outside of the Work Room (either in the hallway or the Tool Room) was identified 

to serve as the primary decontamination area where workers removed all dust and debris from 

their person, their equipment, and the exterior of any waste containers using a HEPA vacuum. 

The floor of the primary decontamination area was securely covered with plastic. 

A secondary decontamination area was set up just inside or outside of the main entrance to the 

unit. This area was used to remove and dispose of the Tyvek suits and booties worn for worker 

protection while inside the unit. Respirators were also removed in the secondary 

decontamination area. Personnel also cleaned off any debris remaining on equipment, clothing, 

or the exterior of waste containers prior to leaving the study site. A tack pad was set up to 

remove any remaining dust from street shoes before leaving the property. 

The hired RRP contractors conducted their job as they normally would, within the specifications 

of the study. Following job completion, study personnel waited for one hour before collecting 

post-work dust wipe and air samples. According to Choe et al. 20005

, about 90 percent of 

airborne lead mass settled within one hour of lead abatement work. Thus, one hour wait times 

were utilized by the study protocol as it would allow settling of most if the lead dust but also be 

short enough to allow completion of an experiment in a single day. In instances where 

significant debris covered the pre-designated sampling location, the debris was collected in a 

plastic bag prior to wiping the area with a dust wipe. The bulk samples were sent separately to 

the lab for analysis. 

Once post-work environmental samples were collected, the RRP contractor misted and picked up 

the plastic sheeting covering the floor, if present. The sheeting isolating the Work Room from 

the other areas of the unit remained in place until all cleaning activities were completed. 

RRP contractors were instructed to follow one of two cleaning methods – a baseline cleaning or 

the proposed rule cleaning. For a baseline cleaning effort, the RRP contractor swept the entire 

Work Room with a broom and dustpan to collect large amounts of debris. Subsequently, the 

RRP contractor vacuumed the work area with a Shop Vac-type vacuum. For the rule cleaning, 

the RRP contractor followed the guidelines detailed in the proposed rule to clean the entire Work 

Room. Large pieces of debris were collected and disposed of prior to cleaning. All walls were 

vacuumed with a HEPA vacuum starting from the ceiling and working down to the floor. The 

remaining surfaces and objects in the work area, including floors and any fixtures, were then 

vacuumed with a HEPA vacuum. The floors were then thoroughly mopped using a 2-bucket 

 

5

 Choe, KT, Trunov, M, Grinshpun, SA, Willeke, K, Harney, J, Trakumas, S, Mainelis, G, Bornschein, R, Clark, S, 

and Friedman, W. Particle Settling after Lead Based Paint Abatement Work and Clearance Waiting Period. AIHAJ 

61:798-807. November/December 2000. 
3-6 

mopping method. Simple Green detergent was used as the cleaning solution in all experiments. 

Neither phosphate nor ethylenediaminetetraacetic acid (EDTA) were used for cleaning purposes. 

If containment was used in the experiment, after completion of all appropriate cleaning activities 

the plastic covering the door separating the Work Room from the other areas of the unit was 

taken down. This was performed by first misting and, then removing the plastic carefully 

folding it up, and placing it in a heavy duty garbage bag. 

After the cleaning was complete, all study personnel waited for one hour before collecting 

post-cleaning dust wipe and air samples. Once all post-cleaning samples were collected, the 

RRP contractor began the cleaning verification process described in detail in the proposed rule. 

For both the window sills and floor zones, each area was wiped with a wet cleaning verification 

cloth and compared to photographic standards contained on the verification card provided as 

guidance for determining the cleanliness of the cloth. If the RRP contractor determined that the 

cloth used was dirtier than the photographic standard for a clean cloth, then the component was 

re-cleaned following the proposed rule cleaning method (i.e., using a HEPA vacuum and wet 

mop) and wiped again with a new wet cloth. Any re-cleanings were done with the proposed rule 

cleaning method in order to get more information regarding the cleaning cloth performance 

under proposed rule methods. 

If the second wet cloth failed verification, then the component was re-cleaned and allowed to 

dry. The component was then wiped with a dry, white verification cloth, which was compared to 

the dry cloth photographic standard on the verification card provided. If the first dry cloth failed, 

i.e. was dirtier than the photographic standard of a clean, dry cloth, then the component was 

wiped with a second dry verification cloth. The process was repeated for a maximum of four dry 

verification cloths. All windowsills were verified as clean before moving on to the floor 

verification. The floor was separated into zones approximately 40 ft2

 in area for the verification 

process. In the cases where a window sill or floor zone failed two wet verification tests, a postwet verification sample was collected from that zone before proceeding with re-cleaning the 

component and dry cloth verification. The collection of post-verification dust wipe and air 

samples took place immediately following the cleaning verification. 

After collection of the cleaning verification samples from the three study rooms, up to three 

additional 1 ft2 floor dust wipe samples from a hallway connecting the study rooms to the unit’s 

entrance were collected. In addition, three composite soil samples were collected in locations 

near those taken during pre-experiment sampling. 

Following completion of an experiment, the areas of the unit impacted by the study were 

re-cleaned. If the unit was to be used in a subsequent experiment, the plastic sheeting protecting 

the parts of a housing unit not impacted by the study were left in place. A licensed clearance 

technician then collected five dust wipes (4 floor, 1 sill) from the Work Room and three dust 

wipes (2 floor and 1 sill) from the Tool and Observation Rooms, plus up to three additional 

samples in hallways or other areas impacted by the study. If the lead in the clearance wipes met 

the study’s clearance standards, the unit was declared clean. If not, then each room that failed 

was re-cleaned and re-sampled. 
3-7 

If all interior work at the unit was complete, the plastic sheeting protecting the parts of the 

housing unit not impacted by the study was taken down, and the entire unit underwent an 

abatement style cleaning. A certified inspector/risk assessor or clearance technician then 

collected samples from one floor, one window sill, and one window trough, where accessible, 

from four rooms in the unit, in accordance with state procedures for clearance testing after lead 

abatement. If one or more samples were measured with dust lead levels over the clearance level, 

the area from which that sample was taken underwent re-cleaning. Following re-cleaning, 

another clearance sample was obtained and re-analyzed. Clearance levels were achieved in all 

study housing units, with the exception of some window troughs. Some window troughs did not 

get below 400 μg/ft2, but these were either unimpacted by study activities or were in a 

deteriorated condition pointed out to the property owner. Final clearance results were provided 

to all property owners. 

Figure 3-1 presents a flowcharts of the steps involved with conducting the interior experiments 

including all related sampling activities. 
3-8 

Figure 3-1. Flowchart of Interior Field Sampling Activities 
3-9 

3.4.2. Exterior Jobs

Prior to the start of an experiment, paint chip samples were collected from building components 

that were potentially going to be disturbed during RRP activities to evaluate the lead 

concentrations in the paint. In addition, three composite soil samples were collected, where 

applicable, from bare soil (1) near the foundation of the housing unit/COF and within the area to 

be covered by the Rule plastic, (2) at the back edge (farthest from the housing unit/COF) of the 

Rule plastic, and (3) at the back edge (farthest from the housing unit/COF) of the containment 

plastic. If the unit was used in multiple exterior experiments, the post-experiment soil samples 

from the previous experiment were used as the pre-experiment soil samples for the next interior 

experiment, where appropriate. One or more dust collection trays were set out prior to work 

commencing to evaluate the background level of dust lead in the air at a housing unit. 

The approximate size and location of the “Rule containment” was estimated in advance by the 

study team in order to identify pre-work soil sample locations. The exact size and location of the 

“Rule containment’ was determined by the site supervisor in consultation with the RRP 

contractor, taking into account any physical constraints such as property lines, fences, nearby 

houses and the placement of the vertical containment structure. Before exterior work began, the 

RRP contractor set up “protection containment,” which included a large area of plastic covering 

the ground and vertical containment spanning the entire distance between ground level and the 

maximum height of the component undergoing RRP work. 

The Rule containment was set up subsequently by the RRP contractor in accordance with the 

proposed rule. This included lying securely taped- or weighed-down plastic on top of the 

containment plastic extending out from the edge of the building a reasonable distance to collect 

falling paint debris. All doors and windows within 20 feet of and below the work area were 

closed. Dust collection pans were placed by study technicians under, on top of, and near the 

Rule plastic covering. 

A decontamination area was set up immediately outside of the work area, where all study 

personnel removed and disposed of their protective suits and booties, and removed all dust and 

debris from tools and supplies. 

The hired RRP contractors conducted their job as they normally would, within the specifications 

of the study. Following an up to one-hour wait after job completion, field technicians obtained 

dust-wipe samples from the dust collection pans on top of the Rule plastic sheeting. 

Subsequently, the RRP contractor misted and folded the plastic sheeting inward to trap dust and 

debris inside. The dust wipe samples from the pans under the Rule plastic were sampled after 

the plastic was removed. The trays placed near the rule plastic were also sampled at this time. 

Technicians collected three composite soil samples, consisting of three sub-samples each, in 

locations similar to those used for the pre-experiment soil sampling. Once all study-related 

activities were complete, the RRP contractor removed the vertical containment. 
3-10 

3.5. Participating Contractors (RRP Workers, Cleaning, Clearance Technicians) 

Study implementation required the participation of multiple contractors in both Columbus, Ohio, 

and Pittsburgh, Pennsylvania. In Columbus, the study utilized two licensed firms to conduct 

initial cleanings, recleanings, and final cleanings of the Columbus housing units and 

child-occupied facility. All XRF inspections and dust lead clearance tests were performed by 

ATC Associates, Inc. (ATC), also licensed by the state of Ohio to conduct these activities. Three 

separate contractors provided the renovation work support for the field operations at the 

Columbus housing units and school. All had at least one person who had received training in the 

EPA/HUD course in Lead Safety for Remodeling, Repair, and Painting. In some cases, property 

owners worked with study personnel to identify preferred contractors who would conduct the 

renovation work on their properties. 

In Pittsburgh, the study utilized services of one abatement cleaning firm, one certified 

environmental firm to conduct XRF inspections and dust lead clearance tests, and one renovation 

contractor. The renovation workers in Pittsburgh received training in the EPA/HUD course in 

Lead Safety for Remodeling, Repair, and Painting prior to starting work. 

All participating renovation workers underwent study-specific training that reviewed the study 

health and safety plan, reviewed study protocols, and introduced and demonstrated the cleaning 

verification process. In addition, the study arranged for respirator training and fit testing for 

those renovation workers who were not equipped with the necessary respirator protection. 

Site security during working hours was provided by special-duty police officers in Pittsburgh and 

off-duty police officers in Columbus. 

3.6. Environmental Safety and Health Plan 

The health and safety requirements for the study were applicable to all RRP workers and study 

personnel. A Health and Safety Plan was drafted to specify the precautions required to comply 

with the OSHA Lead in Construction standard (29 CFR 1926.62); to prevent study personnel 

from injuring themselves, their families, or neighbors; and to protect the study property and 

surrounding properties. During study activities, standard safe work practices were followed to 

avoid falls, burns, lacerations, and other injuries. 

All RRP contractors were trained in accordance with the Lead in Construction standard, as well 

as the HAZCOM standard (29 CFR 1910.1200) with regard to lead. In addition, at least one 

member of the RRP work crew present on site was required to have Lead Safe Renovation 

training. Half- or full-face respirators were worn during all work activities in accordance with 

the observed personal exposure results for each type of study-related activity performed. To 

ensure that workers had adequate respiratory protection prior to job-specific data being available, 

the study conservatively assigned respirator types to each job at the beginning of the study so 

that for many jobs a higher degree of protection was utilized beyond what might typically be 

used. For the experiments where paint was removed by open-flame torching, the RRP workers 

and study personnel wore supplied air respirators for increased protection against lead inhalation. 
3-11 

A blood lead surveillance program was implemented to monitor the pre- and post- study blood 

lead content of all RRP workers and study personnel. 

For both interior and exterior work, personal air samples were collected to ensure compliance 

with OSHA requirements; however, the results are not analyzed as part of the study. Personal air 

sampling results were monitored closely to ensure that respirators used for each job were 

adequate to provide sufficient protection. All personal air monitoring and blood lead results 

were provided to the workers.

Great effort was taken to limit the potential for lead contamination outside of the study area. 

Workers and study personnel were required to wear hooded protective clothing made of Tyvek, 

or another appropriate material, while performing study activities. Upon exiting the work area, 

all protective clothing and equipment were cleaned with a HEPA vacuum, and, in some cases, a 

wet cloth. Protective booties were worn to protect against contamination of the study areas from 

the outside, as well as to protect the property from contamination due to the work-generated dust. 

Before exiting the property, the protective clothing was vacuumed, again, and discarded. A tack 

pad was used to remove any residual dust from the bottoms of shoes. Workers and study 

personnel were required to wash exposed skin with soap and water immediately after exiting the 

property. All waste generated during study activities was removed from the properties and 

transported to a municipal or construction landfill to be disposed of as household waste. 
4-1 

4. Field Work Summary 

4.1. Overview of Site Selection/Screening Process 

The study team developed a list of potential locations and contacts for identifying prospective 

housing units and COFs to enroll in the study. Initially, the study sought to identify locations in 

or around Columbus, Ohio because of their proximity to Battelle and because Columbus is home 

to a large scale effort by various housing agencies, neighborhood associations, non-profit 

agencies, and private developers to rehabilitate older, low-income housing. The study team 

thought such organizations would likely have vacant housing and would be open to collaborating 

on the study to have work done that is beneficial to their ongoing efforts in housing renovation 

and remodeling activities. Leads identified through various sources in other cities were explored 

including Milwaukee, Detroit, Los Angeles, Birmingham, Philadelphia, Chicago, Baltimore, 

Arlington (VA), and Washington, DC. 

The site selection process involved contacting organizations thought to have information on 

ongoing RRP activities. During the initial contact, study representatives explained the study to 

the contact, offered to provide them with a Fact Sheet summarizing the study, and asked whether 

they knew of RRP activities planned for housing in their area or of housing fitting the study 

requirements that would be a good candidate for participation in the study. If they were 

interested in supporting the study, detailed discussions about potential candidate housing units 

were held. If phone conversations concerning potential sites seemed to satisfy all the necessary 

study requirements and the owner was amenable to working within the study requirements for 

available experiments and study schedule, then a site visit was scheduled to inspect the property. 

Permission to inspect and test units or buildings was obtained from site owners or managers prior 

to any inspection or testing taking place. The permission included an agreement as to whether 

and how the results of the inspection and testing would be transmitted to the site owner or 

manager. The required study form was used to obtain formal permission of the property owner 

to conduct the XRF inspection and visual assessment of a property. Each prospective housing 

unit or COF underwent a visual inspection to ensure that it met the study requirements beyond 

the presence of LBP – three sequential rooms, vacant, cleanable, etc. If the visual inspection 

confirmed that a prospective housing unit met the study requirements, a full lead screening 

inspection was scheduled with a portable XRF device to measure lead content of various painted 

components in the house – walls, window sills, trim, doors, etc. Inspectors obtained a large 

number of XRF measurements throughout a house, which were recorded by the field operations 

coordinator for the area, or their representative, on the appropriate data collection forms. As the 

study progressed and experiments were assigned to prospective units to begin work, subsequent 

site inspections were targeted to the components for experiments that still needed to be assigned. 

Following review of the XRF measurements at a prospective housing unit, study planners 

determined whether there were one or more rooms that could serve as the Work Room for an 

interior job or whether there was more than one exterior side of the house that could serve as the 

work area for an exterior job. Permission to collect paint chip samples was obtained from the 

property owner using the proper form. Paint samples were then collected from components in 

prospective rooms and exterior sides for laboratory analysis, as necessary. Based on 
4-2 

confirmation of sufficient levels of lead based paint in the prospective housing site components, 

matching experiments were assigned and the housing owners were informed of their inclusion in 

the study and of the intended schedule of renovation activities to be performed at their housing 

unit. 

In Columbus, Ohio and Pittsburgh, Pennsylvania, the study was able to conduct experiments in 

vacant housing owned by local non-profit agencies that own older housing needing renovation. 

Additionally, private citizens in Columbus who owned vacant housing containing lead-based 

paint also made their homes available to the study. A suitable COF was identified through the 

Columbus Public Schools system. A vacant school that contained sufficient amounts of 

lead-based paint was utilized for all COF experiments. Therefore, the study was able to use 

housing units in both Columbus and Pittsburgh and a COF in Columbus to provide some 

measure of geographic diversity while still being able to allow economy of site coordination 

efforts. 

A total of 35 housing units were sufficient candidates to warrant a visual inspection of the 

properties. Of these 35 units, 27 properties were in good enough condition and satisfied the 

study requirements to warrant having an XRF screening performed. A number of the housing 

units that were excluded from the study posed safety hazards to study personnel such as missing 

stairwells and caved-in ceilings. Units were not excluded based solely on floor condition and 

many experiments were performed using floors in poor condition. 

Based on the XRF measurements, the subsequent paint chip sampling, and a matching of the 

units to the study experiments, the study ultimately identified 15 housing units that met the 

selection criteria for use in the characterization of environmental lead levels associated with low, 

medium, and high levels of interior and exterior RRP activity. Table 4-1 summarizes the 

distribution of housing units among the two cities and interior/exterior experiments. As 

mentioned above, in addition to the housing units, one school was utilized to conduct 12 interior 

and 3 exterior experiments. 

 

Table 4-1. Housing Unit Distribution by City. 

Columbus Pittsburgh 

Interior Only 3 4 

Exterior Only 3 1 

Interior/Exterior 1 3 

TOTAL 7 8 

The buildings studied do not represent a statistically-representative sample of housing on a 

national basis, as this was not an objective of this research study. However, although most of the 

housing used in the study was built pre-1930, the distribution of paint lead levels on components 

worked on covered a broad range - from 0.8% to 10.2% lead by weight for interior jobs and from 

1.3% to 16.8% lead by weight for exterior jobs. These ranges of paint lead levels are consistent 

with the types of distributions reported in the National Survey of Lead and Allergens in Housing 

for components with lead-based paint. 
4-3 

4.2. Number and Type of Experiments Completed 

The study conducted 12 interior jobs at housing units and 3 interior jobs at a COF and, similarly, 

12 exterior jobs at housing units and 3 exterior jobs at a COF. Table 4-2 identifies each of the 

interior and exterior jobs performed at housing units across three work intensity levels specified 

prior to work taking place, while Table 4-3 lists the interior and exterior work performed at the 

COF. In parentheses at the end of each job description is the number of times each job was 

conducted. For interior jobs, each replicate of a job was to be done four times under each phase 

of plastic protection and cleaning method. Thus, interior housing unit jobs actually were 

conducted eight times to achieve the two full job replicates. As noted in Section 1.3, practices 

restricted by 40 CFR 745.227(e)(6) were included among the jobs conducted as part of the study. 

These are noted with roman numerals within the table corresponding to the four prohibited 

activities specified in 40 CFR 745.227(e)(6). 

Table 4-2. Interior RRP Jobs across Three Levels of RRP Work. 

Type Low Level Work Medium Level Work High Level Work HOUSING UNITS 

Make up to three cut-outs, each 

of a 2 foot or more section of 

wall with LBP disturbing 

approximately 6 ft2

 of LBP. (2) 

Replace window from inside 

unit, disturbing at least 2 ft2 of 

LBP. (2) 

Scrape deteriorating LBP from 

interior walls, scraping 50-75 

ft2

 of painted surfaces [iii]. (2) 

Plane 20-40 ft2

 of LBP from an 

interior door [ii]. (2) 

Remove paint from 75-100 ft2

 of 

lead-based painted components by 

using a heat gun over 1100° Fahrenheit 

held at one inch or the distance 

specified from paint [iv]. (2) 

Gut out a kitchen, disturbing 100 ft2

 or 

more of LBP. (2) 

COF 

Make three cut-outs, each of a 2 

foot or more section of wall 

with LBP disturbing 

approximately 6 ft2

 of leadbased paint. (1) 

Remove paint from 50 ft2

 of 

lead-based painted components 

by using a heat gun UNDER

1100° Fahrenheit held at one 

inch or the distance specified 

from paint. (1) 

Remove paint from 75 ft2

 of lead-based 

painted components by using a heat 

gun OVER 1100° Fahrenheit held at 

one inch or the distance specified from 

paint [iv]. (1) 
4-4 

Table 4-3. Exterior RRP Jobs across Three Levels of RRP Work. 

Type Low Level Work Medium Level Work High Level Work HOUSING UNITS 

Replace an exterior door and 

doorway, disturbing 25-50 ft2

of lead-based paint. (2) 

Replace fascia boards, soffits, 

and other exterior trim on one 

side of the structure, 

disturbing approximately 50 

ft2

 of lead-based paint. (2) 

Remove lead-based paint from 

exterior components by dry 

scraping, disturbing 

approximately 100 ft2

 of leadbased paint [iii]. (4) 

Remove paint by power sanding or 

grinding at least 100 ft2

 of lead-based 

paint on exterior wood components on 

one side of the structure [ii]. (2) 

Remove lead-based paint by torching 

or open-flame burning on at least 100 

ft2

 of lead-based paint from wood 

porch ceilings [i]. (2) 

COF 

Remove approximately 50 ft2

of LBP from an exterior 

component using a needle 

gun. (1) 

Remove paint from 50-75 ft2 of 

lead-based painted components by 

using a heat gun UNDER 1100° 

Fahrenheit held at one inch or the 

distance specified from paint. (1) 

Remove paint from 75-100 ft2

 of 

lead-based painted components by 

using a heat gun OVER 1100° 

Fahrenheit held at one inch or the 

distance specified from paint [iv]. (1) 

4.3. Protection and Cleaning Routines 

Interior Jobs – For each interior job, the study evaluated four work area protection/clean-up 

(P/CU) routines or phases – the four combinations of (1) use of plastic coverings/no use of 

plastic coverings and (2) baseline cleaning after work completion/cleaning per the proposed rule 

after work completion. Thus, the four P/CU routines were:

• Phase I - Use of plastic coverings on floor and doorways during work combined with rule 

cleaning after work completion; 

• Phase II - Use of plastic coverings on floor and doorways during work combined with 

baseline cleaning after work completion; 

• Phase III - No plastic coverings on floor or doorways during work combined with rule 

cleaning after work completion; and 

• Phase IV - No plastic coverings on floor or doorways during work combined with 

baseline cleaning after work completion. 

Within each job, the study attempted to characterize the amount and spread of dust under each of 

the four P/CU routines. The preferred method for achieving this was to split the job into four 

phases of equal activity to be performed in one room – the 1 Unit/1 Room Approach – and 

conduct the experiment independently four times so that each experiment corresponded to one of 

the four P/CU routines. In the instances where the job was unable to be replicated four times in 

the same room, the next alternative was to conduct the work across two rooms – applying two of 

the four P/CU routines in one room and the other two routines in another room. For jobs that 

could not be replicated in one or two rooms, such as the kitchen gutting job, the study used a 

4 Room approach where each P/CU routine was conducted in a different room. These rooms 

could be in the same unit or different units. The approaches requiring multiple rooms or units to 

complete a full job produced data for which comparability depends on the degree to which 

similar room layouts with lead-based paint on the same components could be found. Table 4-4 

lists the jobs performed with the approach used to complete that job. 
4-5 

Table 4-4. Interior Jobs and Associated Approaches for Conducting Experiment. 

Activity 

Level Job Job # Columbus Pittsburgh 

1 2 Units, 2 Rooms Cut outs 2 2 Units, 2 Rooms 

1 2 Units, 2 Rooms Low 

Replace window from inside house 2 1 Unit, 3 Rooms 

1 1 Unit, 1 Room Scrape deteriorating lead-based paint 

from a flat interior component 2 1 Unit, 1 Room 

1 2 Units, 3 Rooms 

Medium 

Scrape or plane 20-40 ft2

 of lead-based 

paint from an interior door 2 2 Units, 2 Rooms 

Remove paint from 75-100 ft 1 1 Unit, 1 Room 2 of leadbased painted components in a room by 

using a heat gun at or over 1100 

degrees Fahrenheit 

2 1 Unit, 4 Rooms 

1 4 Units, 4 Rooms

High 

Gut out a kitchen 

2 2 Units, 2 Rooms 2 Units, 2 Rooms

The window replacement job in Columbus was conducted in one housing unit, but the windows 

were spread across three rooms with one room having two windows replaced. The other job that 

required three rooms, one door planing job, used two doors from a room in one house and two 

doors from another house, but the doors in the second house were in different rooms. 

At the school, the three jobs were conducted in two separate classrooms, with six experiments 

conducted in each classroom. All four Cut-out experiments were conducted in one room, while 

the four low heat gun jobs were conducted in the second classroom. The high heat gun job was 

split between the two classrooms with two experiments conducted in each room. These 

assignments were made based on wall space available to have paint removed. 
4-6 

Exterior Jobs – For exterior jobs, the primary protection technique under evaluation was the use 

of plastic ground covering. To investigate this, plastic coverings were set up under an exterior 

job, as required by the proposed rule, with dust collection trays under, on top of, and near the 

plastic coverings. After completion of the exterior work, dust wipe samples were obtained from 

the dust collection trays. Thus, the exterior work and associated sampling were performed in one 

phase. Table 4-5 shows the distribution of the exterior jobs across city and the number of 

housing units required. The three exterior jobs at the COF were all conducted at the school in 

Columbus.

Table 4-5. Exterior Jobs Conducted in Each City. 

Activity 

Level Job (# Jobs) Columbus Pittsburgh 

Replace exterior door (2) 2 Units Low 

Replace soffit, fascia and trim (2) 1 Unit 1 Unit 

Medium Scrape deteriorating lead-based paint from a flat 

exterior component (4) 3 Units

Remove paint from 100 ft2 of lead-based painted 

components by power sanding (2) 1 Unit

High 

Remove paint from 100 ft2

 of lead-based painted 

components by open flame burning (2) 2 Units

4.4. Environmental Samples Collected 

Dust wipe and air samples were collected during each stage of the interior experiments. In 

addition, dust clearance samples were gathered following the pre-experiment (initial clearance) 

and post-experiment (final clearance) cleanings for interior jobs to ensure (1) that each phase of 

work began in a clean environment and (2) that housing units and buildings did not contain any 

residual lead hazards when work was completed. Table 4-6 summarizes the total number of 

environmental samples that were collected, including those collected for clearance purposes. 

The quality control samples included in the table include field spike and field blank samples 

inserted into the sample stream for quality assurance purposes. 
4-7 

Table 4-6. Total Number of Environmental Samples Collected 

Experiment Housing Units (12) COF (3) 

Type Sample Type 

# of Samples # of Samples 

TOTAL 

Dust Lead 

Clearance Wipe 806 132 938 

Dust Wipe 1,699 469 2,168 

Air 576 146 722 

Bulk 120 37 157 

Soil 170 0 170 

Interior 

Paint Chip 187 22 209 

Dust Wipe 137 28 165 

Air 13 4 17 

Bulk 24 11 35 

Soil 72 0 72 

Exterior 

Paint Chip 29 4 33 

Quality Wipe QC 201 51 252 

Control Air QC 96 25 121 

TOTAL 4,130 929 5,059 

4.5. Protocol/Sampling Issues and Resolutions 

Throughout the duration of field work, various circumstances impacted the performance of study 

protocols. Such circumstances generally resulted in minor adaptations to field activities or 

sampling procedures. Any adaptations were planned by field personnel, in consultation with 

study organizers whenever possible, to preserve the validity of each experiment. Summarized 

below are various protocol variations and sampling issues noted by field personnel over the 

course of the field study. 

Protocol Variations 

Obstructed floor samples – All sampling plans were prepared prior to sampling without access 

to detailed photographs of the study rooms. As a result, sampling plans sometimes included 

floor samples in areas occupied by air vents and other obstructions. When this occurred, field 

technicians moved the affected floor sample to an adjacent location not already used or 

designated for sampling. 

Reduced wait times – The study design called for field personnel to wait for one hour following 

completion of the RRP work and cleaning stages before collecting dust wipe and air samples 

from the study rooms. Some RRP jobs took significantly longer than anticipated to complete, 

pushing the first one-hour wait period well into the afternoon. On several such occasions, site 
4-8 

supervisors opted to reduce the post-cleaning wait time in an effort to finish the experiment 

before dark or before site security personnel left for the day (typically at 5:00 pm). No postwork wait times were reduced. When post-cleaning wait times were reduced, which only 

occurred on approximately five occasions, wait times ranged from zero (once) to 50 minutes. 

During exterior work, one hour post-work wait times also were planned to allow dust to settle 

before sampling. In two cases, anticipated bad weather or increasing winds led site supervisors 

to shorten wait times in order to collect samples before weather conditions might lead to loss of 

samples. 

Extreme weather conditions (during interior experiments) – In general, field personnel used a 

front porch or other non-study area of a housing unit to set up a staging area for all study-related 

equipment and supplies. Several experiments were conducted in Columbus on extremely cold or 

rainy days at housing units with no available interior space, aside from the study rooms, to set up 

a staging area. To protect study equipment and personnel from the elements, field technicians 

used a portion of the housing unit’s Observation Room to hold study equipment. In these cases, 

which are noted in the experiment-level reports (see Appendix A), technicians first ensured that 

adequate space was available in the Observation Room to serve as a staging area and satisfy 

sampling requirements for that room. All equipment and cleaning supplies were protected under 

plastic whenever necessary to prevent contamination from RRP work and other study-related 

activities. Floor samples were moved, when necessary, to the open area nearest the planned 

sampling location to avoid sampling from areas partially or fully covered by study equipment. 

Vacuuming protocol (Baseline cleaning) – Early in the study, field personnel in Pittsburgh were 

confused as to whether contractors should be using the Shop-Vac to vacuum the Work Room 

walls during baseline cleaning. In some experiments the walls had been vacuumed, and in others 

they had not. Field personnel consulted with study organizers in Columbus and determined that 

the walls should not be vacuumed during baseline cleaning, since the baseline scenario was 

intended to represent a less intensive cleaning effort than Rule cleaning. For all subsequent 

experiments, contractors were directed to vacuum the walls only during Rule cleaning. 

 

Mopping protocol (Rule cleaning) – The application of the two bucket mopping method differed 

across the RRP contractors. Some contractors preferred to mop the entire Work Room with 

soapy water first, then remove the soapy bucket from the room and mop the entire floor again 

with the rinse water. Other contractors used both buckets simultaneously – mopping several 

square feet with soapy water and then going over the same area with rinse water. Since both 

approaches are consistent with the text in the proposed rule and as RRP contractors were 

expected to perform the job as they would under normal conditions, both approaches were 

represented in the study. 

Sampling Issues

Use of sampling trays in place of window sills – During many experiments, sampling trays were 

used in place of actual window sills. This was done for a number of reasons including 

insufficient sill surface area for repeated sampling, poor condition of a sill, and inability to clean 

a sill so it would pass clearance. Out of 60 interior experiments, sampling trays were used in 

approximately 30 Work Rooms, 39 Tool Rooms (which often were hallways with at most one 
4-9 

available window), and 26 Observation Rooms. Use of trays as a stand-in for actual window 

sills allowed the study to determine the amount of lead generated by the RRP activity and how 

much of that remained behind afterward, without confounding the results with background levels 

or deteriorated sill conditions. On a small number of occasions in Pittsburgh, sampling trays 

were not put into position before RRP work began, when they were supposed to be used. In 

these instances, field technicians taped off a rectangular section of floor in an area where no floor 

samples were supposed to be taken and sampled directly from the floor instead of the tray. On 

several other occasions when sampling trays should have been used in place of the unit’s original 

window sills, field technicians inadvertently sampled from the sills instead of sampling trays. 

All such instances are noted in the experiment-level reports (see Appendix A). 

Soil sample locations – Soil samples were intended to be taken from the same general locations 

before and after each experiment to facilitate a comparative analysis of soil-lead levels. In 

practice, field technicians occasionally took post-work samples from areas that were not sampled 

prior to work. A variety of field personnel was used in Columbus, and the same individuals did 

not always work at the same housing units. As a result, the individuals collecting the samples 

were occasionally uncertain about the location of pre-work samples and/or the most appropriate 

location of post-work samples. 

Use of Plastic to cover tool and observation floors – The design of the study called for sampling 

to occur on actual floor surfaces, which had been cleaned prior to a renovation job occurring. 

Because of floors that were in poor condition and proved difficult to clean to a level at which 

they would pass clearance testing, during approximately 11 of the 60 interior experiments plastic 

sheeting was used to cover tool and observation room floors in order to provide a clean surface at 

the beginning of the experiment. As floors in the tool and observation rooms were not cleaned as 

part of the study protocol, this should not impact the results. All sampling in the work room was 

performed on actual floor surfaces (excluding the post-work sampling when plastic containment 

was used). 

Cleaning Verification - Some RRP contractors appeared more likely than others to consider 

discolored wet verification cloths to be “clean,” attributing discolorations to factors other than 

residual paint dust (with no apparent basis for such conclusions). The impact of this on the study 

is that there may have been fewer cleaning verifications than there should have been, and 

potentially higher post-verification lead levels than would have been achieved if re-cleaning was 

performed and additional verification cloths used. 

Field personnel also observed that the use of Simple Green detergent could contribute to 

discoloration of the verification cloths, as on multiple occasions verification cloths used on zones 

that were re-cleaned with Simple Green appeared progressively more soiled after each recleaning. Field personnel eventually concluded that the cleaning solution itself was causing the 

grayish discoloration. Subsequent analysis of floor samples taken from these zones confirmed 

that the discoloration was not caused by lead-based paint particulates. 
4-10 

4.6. Adherence to Environmental Safety and Health Protocols 

As described in Section 3, a site-specific health and safety plan was prepared for each housing 

unit and COF used for field work. The field work crews in Columbus and Pittsburgh kept copies 

of these plans on-site at all times. Each plan contained detailed health and safety protocols to be 

followed by contractors and field technicians. The site supervisor at each job site was 

responsible for ensuring that all crew members adhered to these guidelines, which could be 

grouped into the general categories described below. 

Study unit containment (to prevent lead contamination of non-study areas) – Contractors were 

directed to seal off non-study areas of each housing unit/COF with plastic sheeting and tape prior 

to beginning work. If cuts, holes, or gaps were observed in the containment at any time, 

contractors or field technicians quickly took action to re-tape or otherwise re-seal the plastic so 

that non-study areas would continue to be protected from lead dust and other potential hazards. 

Personal safety during all stages of field work and sampling – On each day of field work, prior 

to beginning the RRP activity, the site supervisor held a safety meeting to communicate potential 

hazards associated with the job (e.g., lead exposure, physical hazards) and remind the crew 

members about the personal protective equipment that would be required for the day’s work. 

During work, contractors were routinely reminded to inform the site supervisor if they needed a 

break. Field crews had access to a fire extinguisher, first-aid kid, and emergency air horn at all 

times during the study. 

Respiratory protection and monitoring – All crew members were required to wear 

NIOSH/MSHA-approved respirators when inside the work areas. The type of respirator initially 

required for each job was based on the OSHA requirements and an assessment of the air 

monitoring data available for the jobs in the study. Half-mask, air-purifying respirators were 

required for activities expected to generate relatively small amounts of leaded dust. Full-mask, 

air-purifying respirators or half-mask, supplied-air respirators were required for activities 

expected to generate significant dust or lead vapors. Air sampling for personal exposure to lead 

was performed during each of the three stages of the study – renovation work, post-work 

cleaning, and cleaning verification. Personal air sampling results were reviewed after each job 

and used to modify respirator requirements for subsequent jobs. For example, personal air 

samples collected during the cleaning verification stage were consistently below the analyzing 

laboratory’s detection limits; therefore, contractors and field technicians in Pittsburgh and 

Columbus were not required to wear respiratory protection during the cleaning verification stage 

after the first two weeks of field work. 

Hygiene – Site-specific health and safety plans called for handwashing facilities to include hot 

water, soap, and towels. Contractors in Columbus in Pittsburgh were responsible for providing 

these facilities, which typically consisted of two handheld pressure sprayers (one filled with 

soapy water, one with clear water) and a bucket to collect used water. Workers in the COF had 

access to a sink with running water and often elected to use hand soap at the sink instead of the 

pressure sprayers. Because much of the field work was conducted in cold weather, it was not 

always possible to use hot water for the handwashing stations set up at the housing units. 
4-11 

Contractors had no way of heating the water or maintaining its temperature in the field. On days 

when outdoor temperatures were below freezing, some crew members elected to use baby wipes 

to clean their hands and faces in lieu of the cold water in the pressure sprayers. 

Medical Surveillance – Medical surveillance was conducted on all field personnel and 

renovation workers. Each worker’s blood lead level was measured before field work began and 

was or will be measured again following completion of work on the study. 

4.7. Recordkeeping 

Detailed records were kept of all field data collection activities. The information recorded by 

site supervisors and field technicians on data collection forms included: 

• Clearance sampling locations and chain of custody records; 

• Site wind speed and direction data for each day of exterior work; 

• Precipitation activity during exterior work; 

• P/CU phase of each experiment; 

• Description of RRP work and duration of all RRP activities, including setting up 

plastic coverings, conducting cleaning, and conducting cleaning verification; 

• Unit ID, location of study rooms or exterior work area, and specific location of 

samples obtained; 

• Surface type and size of dust wipe samples; 

• Air sampling locations and air flow rates for each sampler; 

• Soil sample locations and associated sample IDs 

• Location of the decontamination area where booties and other protective gear were 

removed upon exiting the work area; 

• Paint lead levels on components undergoing work activity; 

• Regular sample and QC sample identification information; 

• Chain-of-custody records; and 

• Signatures and initials of sample collectors. 

When data collectors made or discovered errors on their data collection forms, they crossed out 

the incorrect information, inserted the correct information, and added their initials and the date 

next to the change. 

In addition to written records, site supervisors obtained digital photographs and video recordings 

of various activities during the study across a subset of the housing units and experiments 

performed. Activities photographed or recorded include: 

• initial inspection of the properties, 

• RRP contractors conducting the work, 

• plastic coverings being set up as containment, 

• post-work cleaning, 

• collection of environmental samples, and 

• cleaning verification. 
4-12 

All digital photographs and video recordings were downloaded to computers for electronic 

storage. 

Laboratory results were returned from the laboratory in electronic spreadsheet and Portable 

Document Format (PDF) files. All laboratory results were entered into a Microsoft (MS) Access 

2003 database and exported into MS Excel 2003 and SAS v9.1 for statistical analyses. Data 

collection forms were archived for use in verifying the results entered in the database and in 

checking the electronic files received from the laboratory. These forms are not included in this 

final report in order to maintain the privacy of individual property owners. 
5-1 

5. Statistical Analysis Plan 

5.1. Data Organization 

A MS Access database was developed to manage the various types of data generated by the 

study. Throughout the study, paint chip, initial and final soil, initial and final dust clearance, 

dust wipe, air and bulk samples were collected, with respective collection information recorded 

on data collection forms (see Section 4). In addition to the environmental samples, property 

information, room designations and XRF results were recorded. The information recorded on 

the forms was entered by a data entry specialist or other professional into a customized interface 

that mirrored the look of the actual forms so that the information could be entered exactly as it 

was seen on the individual forms, thus reducing the potential for data entry errors. Laboratory 

analysis results were submitted electronically by the laboratory in MS Excel format. After 

review, they were directly uploaded into the database. The two sources of information could be 

linked by the unique sample ID. The information from the data collection sheets provided 

supplemental information to the lab results, including the collection date, location of the sample, 

and any issues encountered when collecting the sample. 

5.2. Descriptive Analyses 

The descriptive analysis section presents summary results for each type of data collected in the 

order listed below: 

• Housing unit/experiment summary data, 

• Paint lead levels, 

• Pre-work clearance levels, 

• Bulk debris samples, 

• Interior dust samples, 

• Interior air samples, 

• Exterior dust samples with and without bulk debris samples included, 

• Soil samples, 

• Activity duration data, and 

• Cleaning verification information. 

For the environmental sample data, exploratory descriptive analyses were generated to 

summarize sampling results summarized by a variety of covariates of interest. The study was 

performed in multiple housing units in two different cities by four different renovation 

contractors, providing multiple sources of variance; thus, results are summarized by Unit, City, 

and Contractor. Results are also presented with respect to the type of job performed and the 

expected intensity level of the work. Jobs are further aggregated into those that did and did not 

use restricted practices. For interior experiments, the effect of the P/CU phase used during the 

experiment is investigated. The P/CU analysis is further broken down into the use or non-use of 

plastic coverings and whether the RRP contractors followed the rule cleaning or baseline 

cleaning guidelines. Additionally, floor and sill wipe results are summarized by work room floor 

type and condition. 
5-2 

For the various categorical variables investigated, detailed descriptive analyses in 

Appendices B-E contain box plots and summary tables, which illustrate and summarize the 

distribution of the data across the various factors. A box plot displays the median (represented 

by the center horizontal line), the 25th percentile (represented by the bottom of the box), and the 

75th percentile (represented by the top of the box). The vertical lines, or whiskers, are drawn 

from the box to the most extreme point within 1.5 * interquartile range. (An interquartile range 

is the distance between the 25th and the 75th percentiles.) Any value more extreme than this, is 

identified individually with stars. The data are plotted using a log-base 10 scale. The summary 

statistics provided in the tables are sample size, arithmetic average, geometric average, 

minimum, 25th percentile, median, 75th percentile, maximum, and, for interior wipe data, the 

percentage of measurements exceeding the federal clearance standard. 

Continuous variables investigated in the exploratory analyses include the paint lead 

concentration and size of the disturbed area for both interior and exterior work; pre- and postwork soil lead concentrations for both interior and exterior work; and floor dust lead loadings at 

clearance and average post-work work room floor lead level for interior work. For these 

variables, scatter plots of dust lead loadings are presented to illustrate the distribution of the data 

as a function of the various characteristics. Fitted linear regression lines are included on those 

scatter plots with associated r-square values to provide information on the correlation between 

the data and the characteristic of interest. 

The detailed descriptive analyses (Appendices B-E) also present analysis of the distribution of 

the various types of data before and after transformation. 

Due to laboratory limitations, some environmental samples were reported as having levels below 

the detection limit, which were 10 μg for dust wipes and 2 μg for air samples. In order to include 

these values in summary analyses, the lead level for all sample types was set to one half of the 

reporting limit of the laboratory. Appendices B-E contains summaries of the amount of data 

reported below the detection limit. None of the exterior dust wipes fell below the detection limit. 

The dust wipes in the descriptive analyses are presented as both wipe only and wipe plus bulk 

results. The wipe only results represent the amount of lead dust remaining on the floor after RRP 

work was performed and larger pieces of debris and excessive amounts of dust were picked up; a 

probable scenario for real-world RRP work. The inclusion of bulk samples provides a value of 

the total lead in the dust and debris, and thus total lead contamination, resulting from the work. 

5.3. Statistical Models 

Effectiveness of the proposed cleaning and interior plastic and exterior plastic protocols was 

analyzed using general linear models with mixed (fixed and random) effects. The response 

(loge-concentrations) was modeled to be linearly related to combinations of categorical and 

continuous covariates. The lead concentrations were loge-transformed prior to modeling so that 

residuals were approximately normally-distributed. Prior to analyzing the lead dust loadings, the 

underlying distribution of the response data was examined for normality using Shapiro-Wilks 

tests, a standard test for normality. Pre- and post-transformed data were reviewed. To a large 
5-3 

extent, the log transformations yielded data that were approximately normal; however, in all 

cases the log-transformed data were used in the analyses. 

Key fixed effects included indicators for rule- or baseline cleaning and use of containment plastic 

on interior jobs. On exterior jobs, the key fixed effects included tray position on, under or near a 

sheet of plastic. A random effect was included for experiment number (grouped by Work-room 

number nested within housing unit) in order to model covariance among the multiple subsamples to correctly assess significance and confidence limits. That is, floor-wipes within an 

experiment are treated as sub-samples (exchangeable repeated measures) on the experimental 

unit. Dustpan loadings in each exterior experiment are also treated as sub-samples on the 

experimental unit. 

 

Besides key fixed effects, other covariates (both categorical and continuous) were analyzed to 

assess the extent that different factors explain differences in loge lead concentrations in the 

samples. More detailed descriptions follow. Detailed model results across all objectives is 

available in Appendices I through N. 

The first objective is assessed using only Work-room wipes at the Post-work (PW) stages. The 

effects of plastic and cleaning (the second and third objectives) on reduction of loge lead levels 

subsequent to cleaning are assessed using Work-room wipes from Post-cleaning (PC) and 

Post-verification (PV) stages. The effects of plastic and cleaning on migration (the fourth 

objective) are assessed on wipes from Post-cleaning (PC) and Post-verification (PV) stages from 

the Observation and Tool rooms. Objective 5 addresses exterior plastic and involves only the 

exterior dust pan loge loadings. 

Additional statistical modeling of the study data was pursued to determine what factors were 

predictive of post-verification clearance failure in the Work Room. Attention was focused on 

post-verification clearance failures on floor and window sill surfaces, in which post-verification 

dust-wipe samples were compared to the standards of 40 μg/ft2 and 250 μg/ft2, respectively. 

Logistic regression models were used to assess the predictive ability of various candidate 

predictor variables in single covariate models, and to build a multivariate statistical model. 

Likelihood statistics from the single covariate models were used to assess the predictive ability 

of each potential variable, and the multivariate model was built by sequentially adding variables 

to the model in order of predictive ability. Interaction terms were explored to the degree that 

they made physical sense. Since multiple (floor) dust-wipe samples were collected in the postverification phase within each experiment, logistic regression models were developed 

corresponding to two different response variables: 

1. The proportion of post-verification dust-wipe samples that exceed the clearance standard 

– in which the response becomes a binomial proportion (number exceeding standard / 

number of dust samples collected); and 

2. The probability that any one post-verification dust-wipe sample will exceed the clearance 

standard – in which the response becomes a binary outcome. Note that dust wipes failing 

clearance are analogous to obtaining a false negative response from a cleaning 

verification cloth, as each cleaning verification zone had to pass visual inspection before 

post-verification dust wipe testing could commence. 
5-4 

Since only one post-verification window-sill dust-lead loading measure was obtained from the 

workroom in each experiment, the logistic regression analysis defaulted to a single binary 

response.
6-1 

6. Descriptive Analyses 

6.1. Housing Unit/Experiment Summary Information 

Table 6-1 summarizes the 15 housing units and one COF utilized to complete the 75 

experiments. The four apartments (H31-H33, H35) were located in two attached buildings and 

the two duplex units (H16-H17) were both halves of the same building. Thus, 12 separate 

buildings were used for the study, with most of the buildings built between approximately 1900 

and 1925. The only exception was the COF school building, which was built in 1967. 

Table 6-1. Housing Unit Information 

Unit ID City Year Built Building Type Approximate Interior 

Square Footage 

H01 Columbus, Ohio 1918 Single Family Exterior Only 

H02 Columbus, Ohio OLD* (Pre-1920) Single Family Exterior Only 

H03 Columbus, Ohio OLD* (Pre-1920) Single Family 1,500 

H08 Columbus, Ohio 1910 Single Family 1,744 

H09 Columbus, Ohio OLD* (Pre-1920) Single Family 2,404 

H10 Pittsburgh, Pennsylvania 1920 Single Family 2,508 

H13 Pittsburgh, Pennsylvania 1900 Single Family Exterior Only 

H16 Pittsburgh, Pennsylvania 1925 Duplex 1,472 

H17 Pittsburgh, Pennsylvania 1925 Duplex 1,472 

H19 Columbus, Ohio 1920 Garage Exterior Only 

H31 Pittsburgh, Pennsylvania 1925 Apartment 550 

H32 Pittsburgh, Pennsylvania 1925 Apartment 550 

H33 Pittsburgh, Pennsylvania 1925 Apartment 550 

H35 Columbus, Ohio 1900 Single Family 1,538 

H36 Pittsburgh, Pennsylvania 1925 Apartment 550 

C01 Columbus, Ohio 1967 School Not available 

* Only information on Year Built from tax assessor records is “OLD.” Nearby properties indicate that these houses 

were likely built between 1900 and 1920. 

Tables 6-2 and 6-3 summarize various characteristics of the interior and exterior experiments, 

respectively. For the interior experiments, Table 6-2 contains the average paint lead, amount of 

surface disturbed and type of surface disturbed. Average paint lead ranged from 0.8 to 13.0 

percent by weight across the 60 interior experiments. For the work room, floor type and 

condition and size are presented. The size of the tool and observation rooms is also included, as 

well as the distance from the observation room to the work room. This was calculated as the 

distance from the observation room entrance to the work room entrance. In some cases, these 

distances are relatively small, such as four and five feet. In those cases, the work room was a 

second floor bedroom and the observation room was another second floor bedroom. The 

hallway separating the bedrooms served as the tool room. 
6-2 

Table 6-2. Interior Experiment Summary Table 

Job-Related Information Work Room Tool Room 

Exp. 

# 

Unit 

ID Job Phase 

Avg. Paint 

Lead 

(% by wt.)

Disturbed 

Paint (ft2) 

Substrate 

Behind Paint

Room 

# 

Floor 

Type 

Floor 

Condition

Size 

(ft2)

Room 

# 

Size 

(ft2)

5 H03 Dry Scrape I 1.6 90 Plaster 201 Wood Poor 160 205 70 6 H03 Dry Scrape II 2.7 90 Plaster 201 Wood Poor 160 205 70 7 H03 Dry Scrape IV 1.7 70 Plaster 201 Wood Poor 160 205 70 8 H03 Dry Scrape III 1.7 110 Plaster 201 Wood Poor 160 205 70 9 H09 Window Repl. III 7.3 9 Wood 201 Wood Poor 180 204 100 

10 H09 Window Repl. IV 3.3 9 Wood 201 Wood Poor 180 204 100 11 H09 Window Repl. II 10.1 18 Wood 203 Wood Poor 200 204 100 12 H09 Window Repl. I 7.2 11 Wood 206 Wood Poor 150 204 100 13 H09 Heat Gun II 8.1 53 Wood/Stone 201 Wood Poor 180 204 100 14 H09 Heat Gun III 2.0 75 Wood 202 Wood Poor 140 204 100 15 H09 Heat Gun IV 10.2 75 Wood/Stone 203 Wood Poor 200 204 100 16 H09 Heat Gun I 4.0 75 Wood 206 Wood Poor 150 204 100 22 H16 Cut-outs IV 3.6 13 Plaster 103 Vinyl Tile Good 190 102 215 23 H16 Cut-outs I 3.6 14 Plaster 103 Vinyl Tile Good 190 102 215 24 H17 Cut-outs III 5.0 40 Plaster 103 Vinyl Tile Good 190 102 215 25 H16 Cut-outs II 3.6 14 Plaster 103 Vinyl Tile Good 190 102 215 26 H17 Dry Scrape III 2.1 60 Plaster 103 Vinyl Tile Good 190 102 215 27 H17 Dry Scrape IV 2.5 64 Plaster 103 Vinyl Tile Good 190 102 215 28 H17 Dry Scrape I 2.5 65 Plaster 103 Vinyl Tile Good 190 102 215 29 H17 Dry Scrape II 2.6 72 Plaster 103 Vinyl Tile Good 190 102 215 30 H10 Heat Gun IV 10 65 Wood 201 Wood Poor 150 206 50 31 H10 Heat Gun II 5.1 65 Wood 201 Wood Poor 150 206 50 32 H10 Heat Gun III 8.5 69 Wood 201 Wood Poor 150 206 50 33 H10 Heat Gun I 3.5 60 Wood 201 Wood Poor 150 206 50 41 H16 Window Repl. I 0.9 10 Wood 101 Wood Poor 230 102 215 42 H16 Window Repl. II 1.9 10 Wood 101 Wood Poor 230 102 215 43 H17 Window Repl. IV 1.9 10 Wood 101 Wood Fair 230 102 215 44 H17 Window Repl. III 4.1 10 Wood 101 Wood Fair 230 102 215 45 H08 Cut-outs IV 1.8 6 Plaster 103 Vinyl Tile Poor 180 102 220 46 H08 Cut-outs III 1.8 7 Plaster 103 Vinyl Tile Poor 180 102 220 47 H08 Door Plane IV 3.9 40 Wood 103 Vinyl Tile Poor 180 102 220 48 H08 Door Plane I 7.8 40 Wood 103 Vinyl Tile Poor 180 102 220 49 H31 Kitchen Gut II 1.7 55 Plaster 101 Vinyl Tile Fair 80 106 80 50 H32 Kitchen Gut IV 2.3 40 Plaster 101 Vinyl Tile Fair 80 106 80 
6-3 

Table 6-2. (continued) Interior Experiment Summary Table 

Job-Related Information Work Room Tool Room 

Exp. 

# 

Unit 

ID Job Phase 

Avg. Paint 

Lead 

(% by wt.)

Disturbed 

Paint (ft2) 

Substrate 

Behind Paint

Room 

# 

Floor 

Type 

Floor 

Condition

Size 

(ft2)

Room 

# 

Size 

(ft2)

51 H33 Kitchen Gut I 3.5 66 Plaster 101 Vinyl Tile Fair 80 106 80 52 C01 Cut-outs III 9.5 6 Plaster 102 Tile Good 120 112 560 53 C01 Cut-outs II 7.4 6 Plaster 102 Tile Good 120 112 560 54 C01 Cut-outs IV 7.4 6 Plaster 102 Tile Good 120 112 560 55 C01 Cut-outs I 7.4 6 Plaster 102 Tile Good 120 112 560 56 C01 Low Heat Gun II 2.2 50 Plaster 105 Tile Good 190 115 550 57 C01 Low Heat Gun IV 2.4 50 Plaster 105 Tile Good 190 115 550 58 C01 Low Heat Gun III 2.8 50 Plaster 105 Tile Good 145 115 600 59 C01 Low Heat Gun I 13.0 50 Plaster 105 Tile Good 240 115 500 60 C01 Heat Gun II 2.9 75 Plaster 105 Tile Good 160 115 580 61 C01 Heat Gun III 2.2 75 Plaster 105 Tile Good 160 115 580 62 C01 Heat Gun IV 2.2 73 Plaster 102 Tile Good 160 112 520 63 C01 Heat Gun I 2.6 75 Plaster 102 Tile Good 160 112 520 67 H16 Kitchen Gut I 1.2 40 Plaster 103 Vinyl Tile Good 190 102 215 68 H17 Kitchen Gut III 2.5 34 Plaster 103 Vinyl Tile Good 190 102 215 69 H08 Kitchen Gut IV 5.2 69 Plaster 103 Vinyl Tile Poor 180 102 220 70 H35 Kitchen Gut II 0.8 61 Plaster 101 Tile Fair 115 110 50 71 H35 Cut-outs II 0.8 6 Plaster 101 Tile Fair 115 110 50 72 H35 Cut-outs I 1.0 7 Plaster 101 Tile Fair 115 110 50 73 H35 Door Plane II 1.2 31 Wood 101 Tile Fair 115 110 50 74 H35 Door Plane III 3.2 26 Wood 101 Tile Fair 115 110 50 76 H36 Kitchen Gut III 1.6 60 Plaster 101 Vinyl Tile Fair 80 106 80 77 H08 Door Plane II 1.7 26 Wood 103 Vinyl Tile Poor 180 102 220 78 H08 Door Plane IV 2.0 25 Wood 103 Vinyl Tile Poor 180 102 220 79 H09 Door Plane I 2.1 32 Wood 202 Wood Poor 140 204 100 80 H09 Door Plane III 5.9 40 Wood 201 Wood Poor 180 204 100 
6-4 

Table 6-3. Exterior Experiment Summary Table 

Exp. # Job Unit ID Work Location Painted Material Average Paint Lead (% by wt.) Disturbed Paint (ft2) Length of Rule Plastic from Work Location (ft) Width of Rule Plastic (ft) Len

P

1 Dry Scrape H01 North Wall Wood 13.5 90 7 12 2 Power Sanding H01 North Wall Wood 11.7 100 12 35 3 Power Sanding H01 North Wall Wood 13.1 100 12 25 4 Trim Replacement H02 Rear Porch Wood 15.3 40 5 20 

21 Dry Scrape H09 North Wall Wood 1.3 150 12 25 34 Replace Exterior Door H16 South Wall Wood 10.5 25 4 8 35 Replace Exterior Door H17 North Wall Wood 11.2 25 4 8 36 Trim Replacement H10 Front Porch Wood 16.8 60 13 24 37 Torching H10 Porch Ceiling Wood 2.7 98 13 20 38 Torching H13 Porch Ceiling Wood 11.4 80 10 15 40 Dry Scrape H19 North Wall Wood 15.7 250 6 20 64 Low Heat Gun C01 Door Trim in Courtyard Wood 31.5 75 5 10 65 Needle Gun C01 Railing in Courtyard Metal 5.3 30 5 30 66 High Heat Gun C01 Awning in Courtyard Metal 18.3 30 8 12 75 Dry Scrape H09 North Wall Wood 1.3 100 6 25 

* The containment plastic did not extend an identical amount in all directions around the railing. The railing was bordered on one side by a 

which limited the size of the rule and containment plastic on that side. 
6-5 

6.2. Paint Lead Levels 

Once the presence of lead-based paint was established based on XRF measurements, paint chips 

were obtained from each building component that would be disturbed by the renovation work. In 

all cases, the laboratory reported lead levels in the paint chips consistent with the definition of 

LBP. In general, higher levels of lead were found on exterior surfaces with average paint lead 

levels ranging from 1 percent to 32 percent by weight across the 15 exterior experiments with an 

overall average of approximately 12 percent. Across the 60 interior experiments, overall average 

paint lead levels ranged from 1 to 13 percent with an average of approximately 4 percent. As 

noted in Section 4.1, the distribution of paint lead levels on components undergoing work 

covered a broad range and were consistent with the types of distributions reported in the National 

Survey of Lead and Allergens in Housing for components with lead-based paint. 

The lead content of the paint in a particular experiment could affect the resulting dust lead levels. 

To investigate this within Appendix G, Section G2 contains detailed summaries of the average 

paint lead levels by intensity level, city, job, use of plastic and cleaning method, and other 

experimental characteristics. The bullets below summarize some findings of interest from those 

analyses: 

• Average paint lead levels were similar across the three intensity levels for both interior 

and exterior work. Average interior levels were 3 or 4 percent across the three levels for 

interior work and 11 to 13 percent across the three levels for exterior work (see 

Figure/Table G2.1a). 

• Average paint lead levels differed a bit across jobs (see Figure/Table G2.3a). Average 

paint lead levels ranged from 2 to 5 percent across different interior jobs with dry 

scraping and kitchen gut/cabinet replacement having the lowest average levels. Average 

paint lead levels ranged from 5 to 32 percent across different exterior jobs with the needle 

gun, torching, and dry scraping being the only jobs averaging less than 10 percent. The 

low heat gun job on an exterior door and doorway at the school was the job with a paint 

lead average of 32 percent lead, much higher than the next highest single job average of 

18 percent. 

• Average paint lead level did not differ based on plastic use, cleaning method, or phase 

(see Figures/Tables G2.5a-2.7a). 

• There appeared to be only a slight association between paint lead levels and average 

post-work floor lead loadings in the work room (see Figure G2.11). 

• Paint lead levels and post-work soil lead levels after interior work appeared to have some 

association with an r-square of 0.11 (see Figure G2.14). 

In addition to the average paint lead level, the amount of paint disturbed during the work was 

another factor that might influence the lead levels resulting from the job. Following work, field 

technicians recorded the approximate number of square feet that were disturbed by each job. 

Area disturbed ranged from 25 to 250 ft2

 across exterior jobs and 6 to 110 ft2 across interior jobs. 

Appendix G, Section G3 explores the association of square footage disturbed with the various 

other study characteristics of interest. Findings of interest are listed below: 
6-6 

• Low level interior and exterior jobs disturbed significantly less area than the medium and 

high intensity jobs, which is consistent with the study design (see Figure/Table G3.1a) 

• Of the interior jobs, the cut outs and window replacement jobs disturbed the least amount 

of paint (see Figure/Table G3.2a). 

• Average area disturbed did not differ much based on plastic use, cleaning method, or 

phase (see Figures/Tables G3.5a-2.7a). 

• For interior restricted jobs, average area disturbed was 61 ft2 compared to 26 ft2 for 

non-restricted jobs (see Figure/Table G3.8a). 

• As seen in Figure 6-1 below, average area disturbed did appear to be associated with 

average post-work floor lead levels in the work room with an r-square of 0.28 (see also 

Figure G3.11). Average area disturbed may be associated with job intensity, since the 

disturbed area increased as the (initial) job intensity increased. 

Disturbed Area (Sq. Ft)

0

10

20

30

40

50

60

70

80

90

100

110

Floor - Avg. Post-Work Workroom Floor Lead Loading (w/ Bulk) (R-Square = 27.73%)

10 100 1000 10000 100000 1000000 10000000

o

oo

o

o

o

o

o

o

o

oo

o

oo oo

o

o

o

o

o o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

o

Figure 6-1. Scatter Plot of Area Disturbed Versus Average Post-work Work Room 

Floor Lead Loading 

6.3. Pre-work Clearance Levels 

The goal at the beginning of each experiment was to obtain values of <10 μg/ft2 for all pre-work 

floor clearance samples and <62.5 μg/ft2

 for all pre-work window sill clearance samples. After 

reviewing the dust lead results from the initial cleanings and subsequent re-cleanings of 

candidate properties, it became clear that such stringent clearance levels were going to be 

difficult to achieve and could seriously hinder the progress of the study. Due to the initial 

difficulties in achieving the proposed clearance levels, the pre-work clearance standards were 

changed to target an average of <40 μg/ft2

 for floors and < 250 μg/ft2 for sills, the current EPA 

clearance levels for lead in dust. For most experiments these targets were achieved; however, 

there were a few cases where they were not. 
6-7 

As seen in Table 6-4, which presents the average clearance levels for all experiments, there were 

three experiments that started with average work room floor lead levels above 40 μg/ft2

, ranging 

from 44 to 151 μg/ft2. Tool room and observation room floor lead levels started above 40 μg/ft2

once in each room type. Additionally, exit hallways started above 40 μg/ft2

 four times. There 

were also a handful of cases where a window sill was used for sampling after failing to get below 

clearance levels. For most experiments, dust collection trays replaced window sills when they 

were in poor condition or could not pass clearance. 

Pre-work clearance levels did not appear to be associated with other endpoints. Within 

Appendix G, pre-work clearance levels are compared to average post-work lead levels and little 

or no correlation is evident with an r-square of 0.03 (see Figure G1.12). Figures C3.2a-c within 

Appendix C explore the correlation between pre-work clearance levels and post-work, 

post-cleaning, and post-verification floor lead levels. No correlation was apparent in any of the 

three rooms at any of the three sampling stages. Figures D3.2a-c within Appendix D present 

these analyses for sill lead levels with similar results. 
6-8 

Table 6-4. Summary of Pre-Work Clearance Information 

Final Pre-work Floor Lead Levels Final Pre-work 

Work Room Tool Room Observ. Room Hallway Work Room To

Exp. # Job Phase Avg. (μg/ft2) # of Cleans^ Avg. (μg/ft2) # of Cleans Avg. (μg/ft2) # of Cleans Avg. (μg/ft2) # of Cleans Avg. (μg/ft2) # of Cleans Avg

(μg/f

5 Dry Scrape I 28.4 1 29.8 1 25.7 1 <10 1 323.1T 1 n/a 6 Dry Scrape II 27.4 2 15.3 1 22.1 1 <10 1 - - - 7 Dry Scrape IV 35.0 1 32.3 1 17.8 1 <10 1 - - - 8 Dry Scrape III 7.1 2 8.3 1 < 10 1 <10 1 - - - 9 Window Repl. III 30.0 2 10.5 1 19.6 1 20.6 1 120.8 2 < 10 

10 Window Repl. IV < 10 1 55.8* 1 44.7* 1 8.4 1 30.9 1 756.911 Window Repl. II 6.8 3 < 10 1 < 10 2 4.1 1 46.3 1 7,73712 Window Repl. I 43.9 2 < 10 1 < 10 1 <10 1 346.9T 2 172.013 Heat Gun II 10.4 1 < 10 1 8.7 1 57.6 1 18.3T 1 481.314 Heat Gun III < 10 2 28.2 1 32.5 1 9.9 1 1684.4T 1 1096.15 Heat Gun IV < 10 1 < 10 1 < 10 1 45.7 1 89.7T 1 453.316 Heat Gun I < 10 1 < 10 1 < 10 1 6.0 1 374.3T 1 1,82822 Cut-outs IV < 10 1 < 10 1 < 10 1 - - 61.1 1 960.623 Cut-outs I < 10 1 < 10 1 < 10 1 - - <15.9 1 73.3 24 Cut-outs III < 10 2 12.7 1 21.4 1 - - <76.9 1 88.3 25 Cut-outs II < 10 1 < 10 1 < 10 1 - - <15.9 1 63.2 26 Dry Scrape III < 10 1 < 10 1 8.7 1 - - < 20 1 143.27 Dry Scrape IV < 10 1 < 10 1 < 10 1 - - 25.9 1 78.8 28 Dry Scrape I < 10 1 < 10 1 < 10 1 - - < 20 1 18.9 29 Dry Scrape II < 10 1 < 10 1 < 10 1 - - < 20 1 < 20 30 Heat Gun IV 11.0 2 < 10 2 < 10 2 29.3 2 - - - 31 Heat Gun II 17.8 2 < 10 2 < 10 2 <10 2 - - - 32 Heat Gun III 18.3 1 < 10 1 < 10 1 12.0 1 - - - 33 Heat Gun I < 10 1 < 10 1 < 10 1 10.0 1 - - - 41 Window Repl. I < 10 1 < 10 1 < 10 1 - - < 16.1 1 45.4 42 Window Repl. II < 10 1 < 10 1 < 10 1 - - < 16.1 1 < 1643 Window Repl. IV < 10 1 < 10 1 < 10 1 - - 20.2 1 65.3 44 Window Repl. III < 10 1 < 10 1 < 10 1 - - 18.3 1 < 1645 Cut-outs IV 95.0 2 20.7 2 18.8 2 - - 1,217.50 2 29.6 46 Cut-outs III 19.0 2 39.3* 1 146.1* 1 - - 336.8T 2 45.047 Door Plane IV < 10 1 < 10 1 < 10 1 - - 107.1 1 <10.
6-9 

Table 6-4. (continued) Summary of Pre-Work Clearance Information 

Final Pre-work Floor Lead Levels Final Pre-work 

Work Room Tool Room Observ. Room Hallway Work Room To

Exp. # Job Phase Avg. (μg/ft2) # of Cleans^ Avg. (μg/ft2) # of Cleans Avg. (μg/ft2) # of Cleans Avg. (μg/ft2) # of Cleans Avg. (μg/ft2) # of Cleans Avg

(μg/f

48 Door Plane I 150.7 1 708.7* 1 250.3* 1 - - 516.8 1 599.49 Kitchen Gut II < 10 1 < 10 1 < 10 1 - - <30.3 1 - 50 Kitchen Gut IV < 10 1 < 10 1 < 10 1 - - <30.3 1 - 51 Kitchen Gut I < 10 1 < 10 1 < 10 1 - - <30.3 1 - 52 Cut-outs III < 10 1 < 10 1 19.3 1 < 10 1 - - - 53 Cut-outs II < 10 1 < 10 1 < 10 1 8.9 1 - - - 54 Cut-outs IV < 10 1 < 10 1 < 10 1 < 10 1 - - - 55 Cut-outs I 6.8 1 < 10 1 < 10 1 < 10 1 - - - 56 Low Heat Gun II 7.9 1 10.8 1 < 10 1 < 10 1 - - - 57 Low Heat Gun IV 6.8 1 8.6 1 8.6 1 12.3 1 - - - 58 Low Heat Gun III 18.4 1 12.5 1 9.1 1 < 10 1 - - - 59 Low Heat Gun I 9.4 1 14.4 1 < 10 1 < 10 1 - - - 60 Heat Gun II 14.1 1 82.0 1 < 10 1 < 10 1 - - - 61 Heat Gun III 12.5 1 11.2 1 < 10 1 < 10 1 - - - 62 Heat Gun IV < 10 1 < 10 1 < 10 1 < 10 1 - - - 63 Heat Gun I < 10 1 < 10 1 < 10 1 < 10 1 - - - 67 Kitchen Gut I < 10 1 < 10 1 < 10 1 - - < 16.1 1 131.68 Kitchen Gut III < 10 1 < 10 1 <10 1 - - 152.1 1 19.2 69 Kitchen Gut IV < 10 1 < 10 1 <10 1 - - 264.8 1 55.1 70 Kitchen Gut II 8.4 1 < 10 1 <10 1 69.2 1 < 30.3 1 - 71 Cut-outs II < 10 1 8.0 1 < 10 1 141.1 1 22.4 1 - 72 Cut-outs I < 10 1 < 10 1 < 10 1 17.2 1 < 18.5 1 - 73 Door Plane II < 10 1 < 10 1 < 10 1 <10 1 <18.9 1 - 74 Door Plane III < 10 1 < 10 1 < 10 1 <10 1 <14.5 1 - 76 Kitchen Gut III < 10 1 < 10 1 < 10 1 - - <30.3 1 - 77 Door Plane II 7.5 1 < 10 1 < 10 1 - - 3,304.9T 1 25.4 78 Door Plane IV 18.0 1 < 10 1 < 10 1 - - 1,161.1T 1 90.5 79 Door Plane I < 10 1 < 10 1 48.9 1 8.2 1 1,691.9T 1 1,07880 Door Plane III 9.6 1 < 10 1 38.6 1 37.0 1 417.9T 1 7.8 

 * Clean plastic was put over the floor prior to the start of work  ** Where the window sill clearance sample is missing ( - ), or has a ' T ' ( T ), a dust collection tray was used instead of the window ^ # of Cleans represents the number of times that a unit was cleaned prior to an experiment. If one or more rooms did not pass cle

additional clearance testing was required. 
6-10 

6.4. Bulk Debris Samples 

Many of the intensive renovation jobs generated large amounts of debris and dust. When larger 

pieces of debris and/or excessive dust were present, technicians collected it in a sample bag or 

container prior to collecting the dust wipe. For interior work, all these samples were taken in the 

work room during the post-work stage. For exterior work, all bulk samples were taken on top of 

the rule plastic. In later analyses, the bulk sample results are largely excluded from interior data 

analyses based on the concept that renovators would typically pick up larger debris and excessive 

dust. Table 6-5 contains a summary of the bulk debris samples collected on each interior job. 

Each bulk sample was collected from a specific sampling area, and the average lead in the wipes 

that correspond to those sampling areas is presented, as well. For the exterior analyses, 

descriptive analyses of the exterior dust results are presented both with and without the bulk 

debris samples. Table 6-6 contains summary data by job for the exterior jobs. Similar to the 

interior experiments, the average lead in the wipes represents the trays from which the bulk 

samples were collected. 

Table 6-5. Interior Bulk Samples by Job Type 

Interior Job # of Bulk 

Samples 

Average Lead in 

Corresponding 

Wipes (μg/ft2) 

Average Lead in 

Bulk Sample (μg/ft2) 

Average Total Lead in 

Sample Area (μg/ft2) 

Cut-outs 17 1,810 255,734 257,544 

Window Replacement 8 10,771 84,976 95,748 

Dry Scrape 19 7,659 1,946,558 1,954,217 

Door Plane 19 59,802 1,685,460 1,745,262 

Low Heat Gun 8 20,510 630,304 650,814 

Kitchen Gut 9 3,363 74,610 77,973 

Heat Gun 34 32,780 1,558,268 1,591,049 

TOTAL 114 23,751 1,164,304 1,188,055 

Table 6-6. Exterior Bulk Samples by Job Type 

Exterior Job # Bulk 

Samples 

Average Lead in 

Corresponding 

Wipes (μg/ft2) 

Average Lead in 

Bulk Sample (μg/ft2) 

Average Total Lead in 

Sample Area (μg/ft2) 

Replace Exterior Door 1 5,286 212,025 217,311 

Trim Replacement 3 58,424 2,087,562 2,145,986 

Needle Gun 2 21,466 613,410 634,876 

Dry Scrape 5 58,975 5,479,144 5,538,119 

Low Heat Gun 4 65,884 34,193,431 34,259,314 

Power Sanding 2 46,608 6,431,386 6,477,994 

High Heat Gun 3 17,384 490,164 507,548 

Torching 5 25,297 6,827,905 6,853,202 

TOTAL 25 42,150 8,813,751 8,855,901 
6-11 

6.5. Interior Dust Samples 

The exploratory analyses of the interior dust samples include data for both the housing units and 

COF combined. The bulk debris samples, which all were in the work room at the post-work 

stage, are not included in these analyses. 

6.5.1. Interior Floor Samples

Appendix C contains numerous box plots, summary tables, and scatter plots of the interior floor 

dust lead loadings across the three study rooms. The bullets below list highlights of those 

analyses separately for the Work room and the Tool/Observation rooms. 

Work Room 

• Figure and Table C2.1a summarize the work room data by intensity level. The geometric 

means (GM) and medians for the medium intensity job are higher than the high intensity 

jobs at all three sampling stages. The low intensity jobs do have lower GMs and median 

floor lead levels compared to the other two intensity levels. 

• Floor lead levels are similar between the work in Columbus and Pittsburgh, as seen in 

Figures and Tables C2.2a to C2.2c. 

• The door planing and heat gun >1100 degrees Fahrenheit jobs generated the highest 

amounts of post-work lead dust in the work room, as seen in Table C2.3.a and Figure 6-2 

below. 

Post-Work Work Room Floor Lead Levelsby Job Type

422

3,993 2,686

7,737

958

2,080

32,644

1

10

100

1,000

10,000

100,000

Cut-outs Window

Repl.

Kitchen

Gut

Heat Gun

<1100

Door

Planing

Dry

Scraping

Heat Gun

>1100

Interior Jobs

GM Floor Lead Level 

(μg/ft2

)

Figure 6-2. Post-work Floor Lead Levels in the Work Room, by Job The error bars 

represent the 95% confidence interval computed using the geometric 

standard deviation. The values presented on the graph are the geometric 

mean floor lead levels. 
6-12 

• There are differences in work room floor lead levels across the three contractors that 

performed interior work with post-cleaning GMs ranging from 27 μg/ft2

 to 90 μg/ft2 and 

post-verification GMs ranging 18 μg/ft2 to 53 μg/ft2. (Figure/Table C2.4a) 

• When plastic protective sheeting was used as required in the proposed EPA rule, GM 

post-cleaning floor lead levels in the work room are 41 μg/ft2 compared to 62 μg/ft2 when 

plastic was not used. Figure 6-3 compares work room post-cleaning floor lead levels by 

use of plastic and by job. Use of plastic did not lead to lower post-cleaning floor lead 

levels in the Work Room for all jobs. 

Post-Cleaning Work Room Floor Lead Levelsby Job Type and Plastic Use

123

44

25

77 78 66

7

411

25 18

85

18

31

220

1

10

100

1,000

Cut-outs Window

Repl.

Kitchen

Gut

Heat Gun

<1100

Door

Planing

Dry

Scraping

Heat Gun

>1100

GM Floor Lead Level 

(μg/ft2

)

Plastic No Plastic

 Figure 6-3. Post-Cleaning Work Room Floor Lead Levels, By Job and Plastic Use. The 

error bars represent the 95% confidence interval computed using the 

geometric standard deviation. The values presented on the graph are the 

geometric mean floor lead levels. 

• When rule cleaning was performed following work, post-cleaning GM and median floor 

lead levels in the work room were lower (see Figure/Table C2.7a), at less than half the 

levels as when baseline cleaning was used. Across all jobs, the GM post-cleaning lead 

level was 34 μg/ft2

 with rule cleaning and 75 μg/ft2 with baseline cleaning. There is 

variability in this difference by job, as seen in Figure 6-4, but except for the door planing 

job, rule cleaning consistently achieved lower post-cleaning levels. 
6-13 

Post-Cleaning Work Room Floor Lead Levels - 

by Job and Cleaning Method

122 59

28

236

26 54

12

10

245

86

214

30

51

13

1

10

100

1000

Cut-outs Window

Repl.

Kitchen Gut Heat Gun

<1100

Door Planing Dry

Scraping

Heat Gun

>1100

GM Floor Lead Level 

(μg/ft2

)

Proposed Rule Cleaning Baseline Cleaning

Figure 6-4. Post-Cleaning Work Room Floor Lead Levels, By Job and 

Cleaning Method. The error bars represent the 95% confidence interval 

computed using the geometric standard deviation. The values presented 

on the graph are the geometric mean floor lead levels. 

• Table C2.8a reports that the phases using rule cleaning (I and III) led to lower GM floor 

lead levels in the work room following post-work cleaning, with Phase IV (no plastic and 

baseline cleaning) having a GM nearly twice that of the nearest phase – 105 μg/ft2

compared to 54 μg/ft2 for baseline cleaning with plastic. When analyzing how the four 

phases compare, it is appropriate to use post-cleaning data for the baseline cleaning 

phases and post-verification data for the rule cleaning phases, since under the proposed 

rule the rule cleaning would be followed by the cleaning verification process. These data 

are referred to as “post-job” levels throughout this and subsequent analyses. Figure 6-5 

compares those data for each job, illustrating the consistently lower levels achieved by 

the proposed rule practices compared to the baseline practices. Regarding the phases that 

combined rule and baseline practices, in five of seven jobs no plastic/rule cleaning 

achieved noticeably lower GM floor lead levels than plastic/baseline cleaning, indicating 

that rule cleaning may be more important than the use of plastic sheeting for lowering 

lead levels on floors in the Work Room. Large differences are evident for a few jobs 

such as heat gun over 1100 degrees with GM post-job floor lead levels of 36 μg/ft2

 using 

proposed rule methods and 445 μg/ft2 using baseline methods. 
6-14 

Post-job Work Room Floor Lead Levels, by Job and 

Phase

5

33

12

24

148

30 36

22

135

58

41

450

66

445

8

110

45

23

102 113 135

8

70

15

7

353

11

89

1

10

100

1,000

Cut-outs Window

Repl.

Kitchen

Gut

Heat Gun

<1100

Door

Planing

Dry

Scraping

Heat Gun

>1100

GM Floor Lead Level (

μg/ft 2

)

Proposed Rule Practices Baseline Practices

Plastic/Baseline Clean No Plastic/Rule Clean

Figure 6-5. Post-Job Work Room Floor Lead Levels, By Job and Phase 

• When grouping jobs together by whether a restricted practice was used, the non-restricted 

practice jobs achieved significantly lower GM and median work room floor lead levels at 

each of the post-work, post-cleaning, and post-verification phases (see Figure/Table 

C2.9a). 

• Higher lead levels were measured on wood floors compared to tile floors (see 

Figure/Table C2.10a); however, because the post-work levels are measurably higher on 

wood floors, this may be correlated with the types of jobs done on wood floors and the 

paint lead level and square footage disturbed in those rooms. 

• Similarly, floor in poor condition also had higher floor lead levels across the three 

sampling stages; however, because post-work levels are measurably higher, the 

differences at the subsequent two stages may be caused by higher intensity work (see 

Figure/Table C2.11a). 

• There is some correlation between the average paint lead concentration of the 

components worked on and the work room floor lead levels measured at the three main 

sampling stages (see Figure C3.1a). R-square values range from 0.10 to 0.15 across the 

post-work to post-verification stages. Work room floor lead levels also appear to be 

correlated with average post-work work room floor lead levels (including bulk debris 

samples) with r-square values of 0.24 at post-cleaning and 0.16 at post-verification (see 

Figure C3.6a). 

• Work room floor lead levels do not appear to be correlated with pre-work clearance 

levels, initial and final soil lead levels, and area disturbed. 
6-15 

Tool/Observation Rooms 

• Similar to the Work room, the Medium intensity jobs led to a higher GM floor lead level 

in both the Tool and Observation rooms at all three sampling stages – post-work, postcleaning, and post-verification (see Figure/Table C2.1b-c). 

• Tool and Observation room floor lead levels vary by job performed, with the jobs leading 

to higher work room levels (Door planing and high heat gun) also having higher levels in 

the non-work rooms (see Figure/Table C2.3b-c). 

• Lower GM floor lead levels were achieved with plastic than without plastic across the 

three sampling stages (see Figures/Tables C2.6b-c). On the other hand, the levels 

measured in the non-work rooms did not vary much based on cleaning method used (see 

Figures/Tables C2.7b-c). Thus, for Tool and Observation rooms, use of plastic sheeting 

for the Work Room as required by the Proposed Rule appears to be more important than 

the cleaning method used in the Work Room. 

• Comparing proposed rule practices to baseline practices in the Tool room, post-job 

(post-cleaning for baseline cleaning phases and post-verification for rule cleaning phases) 

GM floor lead levels are 36 μg/ft2

 using proposed rule practices and 66 μg/ft2 using 

baseline practices (see Table C2.8b). In the Observation room, post-job floor lead levels 

are 20 μg/ft2 using proposed rule practices and 34 μg/ft2 using baseline practices (see 

Table C2.8c). 

• Figures 6-6 and 6-7 plot the post-job (post-cleaning for baseline cleaning phases and 

post-verification for rule cleaning phases) floor lead levels for Phase I and Phase IV by 

job. The differences in the non-work rooms become more pronounced in the higher 

intensity jobs. Further evidence of this is seen when comparing restricted practice jobs to 

non-restricted practice jobs (see Figure/Table C2.9b-c). The restricted practice jobs have 

higher GM floor lead levels across the three sampling stages in both non-work rooms, 

although the difference is larger in the Tool room. 
6-16 

Post-Job Tool Room Floor Lead Levelsby Job Type and Phase

32

39

33

228

11

64

10

39

32

76

1,379

19

95

11

1

10

100

1,000

10,000

100,000

Cut-outs Window

Repl.

Kitchen

Gut

Heat Gun

<1100

Door

Planing

Dry

Scraping

Heat Gun

>1100

GM Floor Lead Levels 

(μg/ft2

)

Phase I-PV Phase IV-PC

 Figure 6-6. Post-Job Tool Room Floor Lead Levels, By Job and Phase. The error bars 

represent the 95% confidence interval computed using the geometric 

standard deviation. The values presented on the graph are the geometric 

mean floor lead levels. 

Post-Job Observation Room Floor Lead Levels-

 by Job Type and Phase

24 20

138

20

6

10 10

26

58

420

14 26

10 10

1

10

100

1,000

10,000

100,000

Cut-outs Window

Repl.

Kitchen

Gut

Heat Gun

<1100

Door

Planing

Dry

Scraping

Heat Gun

>1100

GM Floor Lead Levels 

(μg/ft2

)

Phase I Phase IV

Figure 6-7. Post-Job Observation Room Floor Lead Levels, By Job and Phase. The 

error bars represent the 95% confidence interval computed using the 

geometric standard deviation. The values presented on the graph are the 

geometric mean floor lead levels. 

• Tool and Observation room floor lead levels are not correlated with most of the 

continuous covariates considered (soil lead levels, paint lead levels, square footage); 
6-17 

however they do appear to be correlated with post-work work room floor lead levels, i.e., 

the more lead dust stirred up by the work, the more lead dust escapes to nearby rooms 

(see Figures C3.6b-c). 

6.5.2. Interior Sill Samples

Appendix D contains an identical set of exploratory analyses to that generated for the floor dust 

data. As seen in Table D1.1, a higher percentage of non-detect measurements was obtained for 

the window sill data. For example, over 70 percent of Observation Room samples were below 

the detection limit at the post-cleaning and post-observation stages. Note that the sample sizes 

for most of the window sill samples were less than 1 square foot. With less surface area to work 

with on actual window sills and dust collection trays serving as window sills, the size of some 

sill samples is around 0.25-0.35 ft2. With a reporting limit of 10 μg of lead and a sample size of 

.2 ft2

, the reported measurement would be <50 μg/ft2. As noted earlier, half the detection limit 

was used for analysis purposes. Thus, a <50 μg/ft2

 sample was reported as 25 μg/ft2 for the 

following analyses. 

The bullets below contain selected results of interest from the detailed Appendix D analyses. 

• The window sill data are much closer to a normal distribution following the log 

transformation (see Figures D1.1a-D1.3b). The large number of non-detects still skews 

the distribution, but use of the log-transformed data should be acceptable. 

• The post-work sill samples in the Work room do not have a consistent relationship across 

sampling stages when analyzed by intensity level. At post-work, medium intensity jobs 

yielded higher sill levels; however at post-cleaning, the high level jobs yielded higher 

GM sill lead levels (see Figure/Table D2.1a). 

• Jobs in Pittsburgh appear to have yielded higher sill lead levels across the three study 

rooms and all sampling stages than jobs in Columbus (see Figures/Tables D2.2a-D2.2c). 

• The door planing job generated higher lead dust on window sills as measured at each 

sampling stage in all three study rooms (Figure/Tables D2.3a-D2.3c). Generally, the high 

heat gun job and window replacement job also led to somewhat higher levels than the 

other jobs. 

• Contractor C2’s jobs led to lower sill lead levels at all sampling stages across the three 

rooms (see Figure/Tables D2.4a-D2.4c). This may be correlated with the job types 

conducted by each contractor. 

• The sill lead levels are highly variable across housing units. Unit H10 yielded much 

higher post-cleaning and post-verification sill lead levels in the work room with GMs of 

4,067 μg/ft2

 and 1,367 μg/ft2 at the two stages, respectively (see Figure/Tables D2.5aD2.5c). The next highest GM at both stages in the Work room belonged to H08 at 367 

μg/ft2

 and 196 μg/ft2, respectively. 

• Use of plastic is associated with lower post-cleaning and post-verification GM and 

median sill lead levels across all three rooms (see Figure/Tables D2.6a-D2.6c). Sill lead 

levels in the Tool room are also lower when plastic was used with a post-cleaning GM of 
6-18 

67 μg/ft2 with plastic and 124 μg/ft2 without plastic. When focused on post-cleaning 

levels by job in the Work room, five of seven jobs yielded similar or lower sill lead levels 

when plastic was used, as illustrated in Figure 6-8. 

Post-cleaning Work Room Sill Lead Levels, By 

Job and Use of Plastic

37

134

30

198 209

47

238

52

139

282

72

682

39

351

0

100

200

300

400

500

600

700

800

Cut-outs Window

Repl.

Kitchen Gut Heat Gun

<1100

Door

Planing

Dry

Scraping

Heat Gun

>1100

GM Sill Lead Level (μg/ft 2) 

Plastic No Plastic

Figure 6-8. Post-Cleaning Work Room Sill Lead Levels, By Job and Plastic Use 

• Use of rule cleaning appears to be associated with lower post-cleaning and postverification sill lead levels in the Work room (see Figure/Tables D2.7a). Figure 6-9 

displays Work room sill lead levels by job and cleaning method. Similarly, lower sill 

lead levels were found in the Tool room at all three sampling stages with GMs of 74, 81, 

and 54 μg/ft2

 across the three stages using rule cleaning and 117, 103, and 125 μg/ft2

using baseline cleaning (see Figure/Tables D2.7b). Not much difference is observed in 

the Observation room by cleaning method (see Figure/Tables D2.7c). 
6-19 

Post-cleaning Work Room Sill Lead Levels, by Job and 

Cleaning Method

25 49 63 54

392

23

126

78

381

132

265

365

81

660

0

100

200

300

400

500

600

700

Cut-outs Window

Repl.

Kitchen

Gut

Heat Gun

<1100

Door

Planing

Dry

Scraping

Heat Gun

>1100

GM Sill Lead Level (

μg/ft 2) 

Proposed Rule Cleaning Baseline Cleaning

Figure 6-9. Post-Cleaning Work Room Sill Lead Levels, By Job and Cleaning Method 

Analyzing the work room sill lead levels by phase, the largest post-cleaning and postverification differences are between Phases I and IV, with the proposed rule practices having 

the lowest GM and the baseline practices having the highest GM (see Figure/Tables D2.8a). 

Figure 6-10 presents the work room data from these two phases by job, using postverification levels for Phase I and post-cleaning levels for Phase IV. Figure 6-11 presents the 

work room data for all four phases using post-verification levels for Phases I and III and 

post-cleaning levels for Phases II and IV. The largest differences are usually between the 

Proposed Rule Practices and the Baseline practices; however, in the dry scraping and high 

heat gun jobs, the plastic/baseline cleaning routine yielded higher GM sill lead levels than no 

plastic/baseline cleaning. [Note that there was only one Heat Gun < 1100°F experiment that 

used no plastic/rule cleaning and the corresponding post-verification window sill sample in 

the Work Room was not received by the laboratory, which explains the missing bar in 

Figure 6-11.] 
6-20 

Post-job Work Room Window Sill Lead Levels, by Job and 

Rule Use

28

63

21 21

197

17

72

120

568 429

247

707

61

601

1

10

100

1,000

Cut-outs Window

Repl.

Kitchen

Gut

Heat Gun

<1100

Door

Planing

Dry

Scraping

Heat Gun

>1100

GM Sill Lead Level (μg/ft 2

)

Proposed Rule Practices Baseline Practices

Figure 6-10. Post-Job Work Room Sill Lead Levels, By Job and Rule Use 

Post-job Work Room Sill Lead Levels, by Job and Phase

28

63

21 21

197

17

72

120

568 429

247

707

61

601

51

256

41

285

188

108

726

43

75 60

411

24

108

1

10

100

1,000

Cut-outs Window

Repl.

Kitchen

Gut

Heat Gun

<1100

Door

Planing

Dry

Scraping

Heat Gun

>1100

GM Sill Lead Level (

μg/ft 2

)

Proposed Rule Practices Baseline Practices

Plastic/Baseline Clean No Plastic/Rule Clean

Figure 6-11. Post-Job Work Room Sill Lead Levels, By Job and Phase 

• GM Tool room sill lead levels are also lower across the three sampling stages under the 

Proposed Rule Practices (Phase I) compared to the Baseline Practices (Phase IV) – 57 

μg/ft2

 vs. 127 μg/ft2 at post-work, 55 μg/ft2 vs. 131 μg/ft2 at post-cleaning, and 41 μg/ft2

vs. 150 μg/ft2

 at post-verification. Figure 6-12 displays the post-work Tool room lead 

levels by job for these two phases. 
6-21 

Post-job Tool Room Sill Lead Levels, by Job and Rule 

Use

21

40 43

21

265

11

65 66

23

143

57

1,986

84

222

1

10

100

1,000

10,000

Cut-outs Window

Repl.

Kitchen

Gut

Heat Gun

<1100

Door

Planing

Dry

Scraping

Heat Gun

>1100

GM Sill Lead Level (

μg/ft 2

)

Proposed Rule Practices Baseline Practices

Figure 6-12. Post-Job Tool Room Sill Lead Levels, By Job and Rule Use 

• There is not as much difference between GM Observation room sill lead levels under the 

Proposed Rule Practices (Phase I) compared to the Baseline Practices (Phase IV) – 53 

μg/ft2

 vs. 58 μg/ft2 at post-work, 35 μg/ft2 vs. 52 μg/ft2 at post-cleaning, and 35 μg/ft2 vs. 

49 μg/ft2

 at post-verification (see Figure/Table D2.8c). Figure 6-13 displays the post-job 

Observation room lead levels by job for these two phases. There are mostly minor 

differences in the non-restricted practice jobs, whereas the Proposed Rule Practices 

appear to have led to lower post-job lead levels from the restricted practice jobs. 
6-22 

Post-job Observation Room Sill Lead Levels, by Job and Rule 

Use

22 21

58

21

142

11

56

23

40 33

19

306

26

127

1

10

100

1,000

Cut-outs Window

Repl.

Kitchen Gut Heat Gun

<1100

Door

Planing

Dry

Scraping

Heat Gun

>1100

GM Sill Lead Level (μg/ft 2

)

Proposed Rule Practices Baseline Practices

Figure 6-13. Post-Job Observation Room Sill Lead Levels, By Job and Rule Use 

• Use of restricted practices is associated with higher GM sill lead levels in each of the 

three study rooms. Note that the window sills in the Observation and Tool rooms are not 

cleaned between each stage of the experiment, indicating that the higher post-work sill 

lead levels observed after restricted practices translates to higher post-cleaning and postverification levels, as well (see Figure/Tables D2.9a-D2.9c). 

6.5.3. Hallway/Exit Samples

The study design specified collection of three samples at the end of each experiment along the 

path from the work room to the entrance used by workers. These samples provide data on both 

the track-in of lead dust from the outside and tracking of lead dust from the work room through 

the house as workers enter and exit. The location of the samples was not pre-specified in 

sampling plans. Technicians were instructed to obtain one sample near the entrance of the 

house, one from an area closer to the work room, and one in between. In houses where work was 

done on the second floor, the hallway samples were generally taken from the bottom of the steps, 

near the entrance, and in between these two areas. The samples were taken following the 

collection of all post-verification samples in the three main study rooms. At this point, the 

workers would have removed most if not all of their job-related equipment, and remaining traffic 

through the house mainly involved removal of study-related equipment. 

Appendix H contains a set of exploratory analyses similar to those generated for the other data 

types. As with the other dust wipe data, the data were log-transformed to get closer to a normal 

distribution. The bullets below present some key results seen in Appendix H. 

• Higher lead levels are seen in exit samples taken after medium intensity jobs with a GM 

of 507 μg/ft2

 for medium intensity jobs compared to 212 μg/ft2 for high intensity and 

73 μg/ft2

 for low intensity (see Figure/Table H2.1a). 
6-23 

• The GM exit sample lead level for Door Planing jobs was 500 μg/ft2

, much higher than 

all other jobs (see Figure/Table H2.3a). GMs of the other six jobs range from 21 to 

83 μg/ft2, with the high heat gun job having the next highest level below the door 

planning job. 

• As seen in Figure/Table H2.6a, there is little difference in GM lead levels between jobs 

that used plastic in the Work room during the work (67 μg/ft2) and those that did not 

(69 μg/ft2). 

• The difference in GM lead levels is relatively small between jobs using rule cleaning 

(59 μg/ft2) compared to jobs using baseline cleaning (78 μg/ft2). 

• The baseline practices (no plastic/baseline cleaning) yielded higher GM exit levels of 

88 μg/ft2 compared to a range of 55 μg/ft2

 to 69 μg/ft2 for the other three P/CU routines 

(see Figure/Table H2.8a). 

• Higher hallway lead levels were measured following restricted practice jobs compared to 

non-restricted jobs with GM of 136 μg/ft2

 versus 34 μg/ft2 (see Figure/Table H2.9a). 

• When the work room floors were in poor condition, hallway lead levels were higher than 

when work room floors were in good condition with GMs of 143 μg/ft2

 for poor 

condition floors and 18 μg/ft2 for floors in good condition (see Figure/Table H2.11a). 

• Hallway/exit lead levels were not associated with pre-work or post-work soil lead levels 

(see Figures H3.4 and H3.5). 

• Hallway/exit lead levels do appear to be correlated with average post-work work room 

floor lead levels with an r-square value of 0.11 (see Figure H3.7). 

6.5.4. Exterior Post-Work Tray Samples During Window Replacements

For the experiments where a window was replaced from the interior of a housing unit, one dust 

collection tray was placed for sampling on top of plastic sheeting on the exterior of the unit, 

directly below the window. This sampling was done to evaluate potential exterior contamination 

when performing a window replacement from the inside of the house. Prior to conducting the 

window replacements, the RRP workers covered the window with plastic from the outside to 

prevent falling debris from contaminating the ground below. After the replacement was finished, 

the RRP workers carefully removed the exterior plastic sheeting. The dust collection tray was 

sampled immediately after the work was completed and the plastic removed. The results of 

those exterior dust collection tray samples are shown in Table 6-7. The results are not consistent, 

even when considering variability due to contractor, housing unit, and tray location. For 

experiments 11 and 42, a significant amount of debris was observed falling from a pocket at the 

bottom of the external plastic sheeting when the RRP workers were removing it. The debris fell 

onto the ground covering and into the dust collection tray. For some of the other experiments, 

small paint chips were present in the tray when sampled, but no significant debris was observed 

falling out of the protective plastic. 
6-24 

Table 6-7. Exterior Dust Wipe Samples During Window Replacement 

Experiment Concentration 

(μg/ft2) Location 

9 291 Porch roof under second story window 

10 232 Porch roof under second story window 

11 31,715 Ground under second story window 

12 12 Ground under second story window 

41 17.0 Porch floor under first story window 

42 20,591 Porch floor under first story window 

43 44 Porch floor under first story window 

44 338 Porch floor under first story window 

6.6. Interior Air Samples 

Indoor air samplers collected samples during each work stage (work, cleaning, and cleaning 

verification) in each of the three study rooms. The work and cleaning stages included a one-hour 

wait time following completion of activity to allow settling of airborne dust. The air monitors 

operated from the beginning of the activity until the end of the one-hour wait time. Field 

technicians recorded information on flow rate at the beginning and end of the sampling period in 

order to calculate a mean flow rate. In a few cases, multiple air filters were needed during a 

single sampling stage because of a filter getting clogged with dust. In these cases, the 

concentrations obtained for the two samples were averaged and that value used in subsequent 

analyses. 

Appendix F contains detailed exploratory analyses of the indoor air filter samples. Laboratory 

analysis of the air filter samples had a 2 μg detection limit. With many of the filters not running 

for long, e.g. during the cleaning verification stage that sometimes only lasted 10-15 minutes, 

this made it more challenging to measure enough lead to be over the detection limit. 

Additionally, with only small amounts of air monitored, laboratory measurements are relatively 

variable. The air sampling time could not have been increased, as it then would not have been 

representative of the length of time and exposure for each stage of the experimental protocol. 

Reported levels range anywhere from <2.7 to <20 to <666 μg/m3

. Table 6-8 (also Table F1.1) 

presents the number and percentage of samples that contained lead below the detection limit. 

Appendix F presents analyses using the half the reporting limit for each sample that was below 

the detection limit; thus, the three example values listed above are included as 1.35, 10, and 333 

μg/m3 in the analyses. 

Table 6-8. Number (and Percentage) of Interior Air Dust Lead Concentration 

Measurements (μg/m3

) Below Detection Limit Measurements by 

Room and Stage 

Room 

Stage Work Tool Observation 

Post-Work 29 (48.3%) 43 (71.7%) 45 (75.0%) 

Post-Cleaning 50 (82.0%) 53 (88.3%) 54 (90.0%) 

Post-Verification 59 (98.3%) 59 (98.3%) 58 (96.7%) 
6-25 

Below are a few findings from the air lead analyses. Since the Tool and Observation rooms have 

at most 28% reported values in any given stage, no results from those analyses are presented. 

Similarly, because the post-cleaning and post-verification data in the Work room have no more 

than 18 percent reported measurements, no results from those analyses are discussed. Because 

the post-work stage in the work room is the only set of data with more than half of its values 

actually being reported measurements, only those data are discussed. 

• Air lead concentrations in the work room during Medium intensity jobs were higher than 

the High and Low intensity jobs. 

• The finding regarding intensity level is driven largely by the door planing job, which has 

a GM air lead concentration far greater than any other job – 300 μg/m3 compared to the 

next highest job, heat gun above 1100 degrees, with 13 μg/m3 (see Figure/Table F2.3a). 

• The GM work room air lead level when plastic was used is higher than when plastic was 

not used - 12 μg/m3 compared to 8 μg/m3 (see Figure/Table F2.6a). During phases with 

protective plastic used, plastic sheeting covered floors and the doorway into the Work 

Room. Presence of the airlock that did not allow airborne lead to escape the Work Room 

likely contributed to higher Work Room air lead levels in these cases. 

• The GM work room air lead level was higher during restricted practice jobs than other 

jobs, which is not surprising since the door planing is defined as a restricted practice job 

(see Figure/Table F2.9a). Figure 6-14 plots air lead concentrations for each job. 

Post-work Air Lead Concentration in Work Room, by Job

5 6

3

10

300

2

13

1

10

100

1,000

Cut-outs Window

Repl.

Kitchen

Gut

Heat Gun

<1100

Door

Planing

Dry

Scraping

Heat Gun

>1100

GM Air Lead Level (

μg/m 3

)

Air Lead Level

Figure 6-14. Post-work Air Lead Concentration in the Work Room, by Job 

6.7. Exterior Dust Samples 

The exterior study design specified collection of three types of dust collection tray samples – on 

the Rule plastic, under-the-Rule plastic, and near-the-Rule plastic. Three samples were obtained 

from each location during each experiment. The size of the Rule plastic varied from job to job. 

The proposed rule does not identify specific areas of ground to be covered during exterior work, 
6-26 

so the size of the rule plastic was determined for each experiment within the constraints of the 

dimensions of the property being worked on and the need to collect samples near the Rule plastic 

as well. For this study, vertical containment and additional ground plastic were set up as a 

precaution to capture dust and debris that might not be captured on the Rule plastic. Table 6-9 

contains distances from the work location for all on and near Rule plastic samples, as well as 

associated results. The under Rule plastic samples were obtained from similar locations to those 

used for the on Rule plastic samples. 

Table 6-9. Distance of Exterior Trays from Work. 

On top of Rule Plastic Near Rule Plastic 

Exp. 

# Job Type Unit ID 

Sample 

# 

Loading* 

(μg/ft2) 

Dist. From 

Work (ft) 

Loading* 

(μg/ft2) 

Dist. From 

Work (ft)** 

1 12,516,131 1 4,178 8 

1 Dry Scrape H01 2 50,819 5 953 12 

3 8,556 7 929 17 

1 4,666,776 1 58,718 15 

2 Power Sanding H01 2 341,492 5 85,985 14 

3 106,383 11 65,719 12 

1 8,289,211 3 18,002 14 

3 Power Sanding H01 2 234,877 8 9,865 17 

3 129,738 12 16,905 15 

1 4,109 2 61,388 5 

4 2 1,652,382 1 27,082 6 Trim 

Replacement H02 

3 115,207 2 54,851 5 

1 1,463,974 1 274 13 

21 Dry Scrape H09 2 2,357 7 172 18 

3 417 11 574 15 

1 217,311 1 31,708 6 

34 2 79,163 3 84,290 6 Replace Exterior 

Door H16 

3 14,441 3 1,129 6 

1 30,060 1 3,793 5 

35 2 43,976 1 30,426 5.5 Replace Exterior 

Door H17 

3 151,734 1 17,590 5.5 

1 161,018 3 19,278 7 

36 2 2,991,198 2 133,690 7 Trim 

Replacement H10 

3 1,794,377 2 217,900 7 

1 1,134,829 4.5 150 15 

37 Torching H10 2 956 12 198 15 

3 349,644 10 151 15 

1 29,401,680 2 658 16.5 

38 Torching H13 2 1,560,303 10.5 1,836 16.5 

3 1,819,556 9 1,093 16.5 

1 14,348.0 6 7,596 11 

40 Dry Scrape H19 2 11,480,352 2 12,169 9 

3 268,359 4 16,597 10 
6-27 

Table 6-9. (continued) Distance of Exterior Trays from Work. 

On top of Rule Plastic Near Rule Plastic 

Exp. 

# Job Type Unit ID 

Sample 

# 

Loading* 

(μg/ft2) 

Dist. From 

Work (ft) 

Loading* 

(μg/ft2) 

Dist. From 

Work (ft)** 

1 130,674,045 1 2,692,069 7 

64 Low Heat Gun C01 2 1,133,090 5 27,650 8 

3 2,538,052 3 16,884 7 

1 381,586 3 21,158 6 

65 Needle Gun C01 2 22,004 1 8,768 6 

3 888,167 2 1,380 12 

1 196,760 7 14,689 11 

66 High Heat Gun C01 2 494,822 5 331 16 

3 831,062 3 363 13 

1 1,961,779 1 1,205 8 

75 Dry Scrape H09 2 14,345 4 190 15 

3 1,845 7 488 12 

* Where applicable, the loading represents the sum of the dust wipe plus the bulk sample. 

** Distance from work represents the perpendicular distance from the work wall/area to the collection tray 

Appendix B contains detailed exploratory analyses of the exterior tray samples by location 

summarized by intensity level, city, job, contractor, and housing unit. The bulk debris samples 

are included in these analyses. Appendix E contains the same analyses, but excludes the bulk 

debris samples. Figures B1.1a-1.3b and Figures E1.1a-1.3b display histograms of the raw and 

log-transformed data collected for each location – on, under, and near Rule plastic. The logtransformation does lead to a data more closely approximating normality. The following bullets 

describe selected findings observed from Appendices B and E: 

• The GM and median lead levels measured on the Rule plastic across all jobs is much 

higher than the other two locations with GM of 241,977 μg/ft2

 and median 268,359 

μg/ft2

, compared to GM of 479 μg/ft2 and median of 322 μg/ft2 under-the-Rule plastic 

and GM of 5,771 μg/ft2 and median of 9,865 μg/ft2 near-the-Rule plastic. Excluding the 

bulk debris samples reduced the top of Rule plastic GM to 21,292 μg/ft2

 and median 

to 22,004 μg/ft2. No bulk debris samples were collected near or under rule plastic. 

• The high intensity jobs resulted in higher GM lead levels on and under-the-Rule plastic, 

when the bulk samples are included, but the high and low level jobs have similar GMs 

when bulk samples are excluded. The low level jobs yielded higher levels near-the-Rule 

plastic (see Figure/Tables B2.1a-c). A possible explanation for this is that the Rule 

plastic covered less area in the low-level jobs (trim/soffit and door replacements and 

needle gun) because of space constraints. 

• The low heat gun job yielded the bulk samples with the most amount of lead, which 

gave this job a much higher GM on the Rule plastic than all other jobs. With bulk 

samples excluded, the power sanding job yielded a much higher GM on the Rule plastic. 

Figures 6-15 and 6-16 present the on and under Rule plastic samples both with and 

without the bulk debris samples, respectively, by each job. All jobs yielded much higher 

lead levels on the plastic than under the plastic regardless of whether the bulk samples 

are included, except the torch burning job. The torching job has a GM on the Rule 

plastic of 562,462 μg/ft2 with the bulk samples included and only 5,447 μg/ft2 with the 
6-28 

bulk samples excluded. The GM of the under Rule plastic samples for the torching jobs 

is 8,565 μg/ft2

. 

Exterior Lead Measured on Top of and Under Rule Plastic, 

by Job (w/ bulk debris samples)

32

648

270

3,149

89

4,896 8,565

388

60,662

296,251 195,372

7,216,358

71,540

591,491 562,462 432,520

1

10

100

1,000

10,000

100,000

1,000,000

10,000,000

Door Repl. Trim/Soffit

Repl.

Needle

Gun

Heat gun

<1100

Dry

Scrape

Pow er

Sanding

Torching Heat gun

>1100

GM Lead Levels (ug/ft 2

)

Under Rule Plastic Top of Rule Plastic

Figure 6-15. Exterior Dust Lead Levels On and Under Rule Plastic, by Job (w/ Bulk Samples) 

Exterior Lead Levels on Top of and Under Rule Plastic, by 

Job (excluding debris samples)

32

648

270

3149

89

4896 8565

388

32,653 44,474

7,713

37,431

12,004

111,388

5,447

18,000

1

10

100

1,000

10,000

100,000

1,000,000

E1-Door

Repl.

E2-

Trim/Soffit

Repl.

E3-Needle

Gun

E4-Heat

gun <1100

E5-Dry

Scrape

E6-Pow er

Sanding

E7-

Torching

E8-Heat

gun >1100

GM Lead Levels (ug/ft 2) 

Under Rule Plastic Top of Rule Plastic

Figure 6-16. Exterior Dust Lead Levels On and Under Rule Plastic, by Job (excl. bulk samples) 

• There does appear to be an association between paint lead levels and lead levels 

measured on and near-the-Rule plastic with r-square values of 0.16 and 0.17, respectively 
6-29 

(see Figure B3.1). No association between paint lead level and under Rule plastic 

samples was found. 

• No association is observed between initial soil lead levels and lead measured in any of 

the three exterior tray locations (see Figure B3.2). While no association is observed 

between post-work soil lead levels and lead measured on or under Rule plastic, there does 

appear to be some correlation between post-work soil levels and lead levels measured in 

trays near-the-Rule plastic (see Figure B3.3). 

• There does not appear to be an association between amount of area disturbed by the RRP 

work and lead measured at any of the three locations (see Figure B3.4). 

Prior to performing exterior experiments, one or more dust collection trays were set out in the 

area of the rule plastic to measure the background concentration of lead at the property. Trays 

were exposed for periods ranging from two and a quarter hours to 10 hours, with two-thirds 

exposed between four and five hours. Exposure was less than four hours for only one 

experiment, caused by theft of the initial set of sampling trays at the location. The number of 

samples collected for each job type and associated lead levels and sampling times are presented 

in Table 6-10. In the instances where more than one experiment was performed at the same unit 

(e.g. the trim replacement and torching at H10), the results of the background tray(s) are included 

for both experiments. 

Table 6-10. Average Background Dust Loading for Exterior Experiments, by Job Type 

Exterior Job # Samples Average Background 

Lead Level (μg/ft2) 

Exposure Time 

(hr) 

Trim Replacement 6 13.9 4.0, 5.8 

Door Replacement 6 < 9.6 9.0 

Dry Scrape 5 16.4 2.25, 4.25 

Power Sanding 2 51.2 4.25 

Torching 6 32.8 4.0, 10.0 

6.8. Soil Samples 

6.8.1. Soil Sampling for Interior Jobs

For interior experiments, soil samples were collected before work began and again after work 

was completed at three sampling locations: near the main entrance to the unit used during the 

experiment, near the path traveled by the workers and study personnel from their vehicles to the 

unit, and from the ground immediately below a window that led into the Work Room. See Table 

6-11 for the all soil lead measurements for each interior experiment. The soil samples were 

collected to evaluate the possible contamination of the soil by study activities, as well as to get 

an idea of the potential track-in from the outside. There was no soil or dirt at any of the 

sampling locations for H31, H32, H33, H36 and C01, thus no soil samples were collected for 

experiments performed at those units. 
6-30 

Table 6-11. Pre- and Post-Work Soil Sample Results (μg/g) by Interior Experiment 

05 - H03 06 - H03 07 - H03 08 - H03 09 - H09 

Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-W

Near Entrance 903 1,635 1,635 737 737 856 856 709 679 39Near Path 96 125 125 129 129 86 86 74 401 273 Under Window 141 385 385 288 288 44 44 105 705 700 

11 - H09 12 - H09 13 - H09 14 - H09 15 - H09 

Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-W

Near Entrance 5,551 2,245 3,460 2,508 5,006 2,074 4,540 3,348 3,026 5,35Near Path 276 229 343 291 241 289 367 288 323 230 Under Window 10,361 11,226 1,746 2,117 2,411 2,845 10,097 8,643 5,672 15,1

22 - H16 23 - H16 24 - H17 25 - H16 26 - H17 

Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-W

Near Entrance 1,213 910 910 485 752 677 485 575 616 57Near Path 408 429 429 286 334 204 286 274 213 272 Under Window 1,136 1,410 1,410 1,772 622 564 1,772 2,355 644 91

28 - H17 29 - H17 30 - H10 31 - H10 32 - H10 

Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-W

Near Entrance 685 286 286 1,105 1,230 929 2,258 1,033 1,033 957 Near Path 287 652 652 329 773 940 700 426 426 877 Under Window 613 541 541 879 n/a 1,441 n/a 4,031 4,031 1,50

41 - H16 42 - H16 43 - H17 44 - H17 45 - H08 

Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-W

Near Entrance 8,120 8,167 8,167 2,921 529 622 622 1,138 359 308 Near Path 457 399 399 473 278 203 203 542 133 146 Under Window n/a 386 386 444 n/a 521 521 346 367 336 

47 - H08 48 - H08 67 - H16 68 - H17 69 - H08 

Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-W

Near Entrance 450 390 390 359 575 1,178 677 616 940 347 Near Path 218 170 170 133 274 344 204 213 121 118 Under Window 482 204 204 367 2,355 3,650 564 644 519 416 

71 - H35 72 - H35 73 - H35 74 - H35 77 - H08 

Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-W

Near Entrance 471 413 413 772 383 476 476 471 347 395 Near Path 481 500 500 502 355 337 337 481 118 175 Under Window 554 567 567 1,260 478 426 426 554 416 n/a 

79 - H09 80 - H09 

Pre-Work Post-Work Pre-Work Post-Work

Near Entrance 684 1,659 1,659 3,098 Near Path 35 49 49 308 Under Window 11,121 16,547 n/a 1,387 
6-31 

If work was performed in the same unit within the same Work Room, the post-work soil samples 

from the previous experiment were used as the pre-work soil samples for the next experiment. 

For two experiments performed at H09 and one experiment each at H16 and H17, the Work 

Room changed from experiment to experiment and pre-soil samples were not collected to 

correspond to the correct Work Room window. At H10, exterior experiments were performed 

alternately with interior experiments, resulting in two experiments where there were no pre-work 

soil samples collected under the Work Room window, and the post-work sample of the previous 

experiment could not be used due to possible contamination by the exterior experiment. 

The samples collected near the main entrance and under the Work Room window were typically 

higher than the near path samples, due to their proximity to the foundation of the house. Large 

variations in the lead content of the soil were observed when samples were collected within the 

same general area. When examining an increase from pre-work soil lead to post-work soil lead, 

the variability became evident as subsequent samples collected in the same location were 

consistent with the lower, pre-work samples. An example of this for samples collected near the 

front porch of H09 is given in Figure 6-17. In cases where post-work samples were collected in 

the same general area but different locations than the pre-work samples, it is difficult to discern 

the change due to natural variability and change due to study activities. 

Figure 6-17. Time series of soil samples near the front porch at H09. These samples correspond to 

the near entrance samples and some under the Work Room window samples. Where more than one 

sample is collected on the same day, the plot shows whether the sample was pre-work or post-work. 
6-32 

Table 6-12 lists the number of collected samples and average post-work to pre-work soil lead 

level ratio. Instances where the two samples were collected from inconsistent locations are not 

included in this table. The job type, job intensity, and sample location do not appear to play a 

significant role in determining the change in soil lead level. This table also depicts the effect of 

variability as some locations across the study experienced an overall decrease in soil lead levels. 

Table 6-12. Average Post-work/Pre-work Ratios for Interior Work Soil Samples, 

by Job Type 

Near Main 

Entrance Near Path Under Work Room Window 

Interior Job # Ratio # Ratio # Ratio

Cut-outs 8 1.25 8 0.91 8 1.30 

Window Replacement 8 0.89 8 1.12 6 1.35 

Dry Scrape 8 1.33 8 1.12 8 1.33 

Door Plane 8 1.28 8 1.74 5 1.18 

Kitchen Gut 4 1.02 4 1.03 4 1.03 

Heat Gun 8 1.15 8 1.02 6 1.17 

Figures C3.3a-c and C3.4a-c within Appendix C plot pre-work and post-work soil lead levels, 

respectively, against floor dust lead loadings in the work, tool, and observation rooms. Little if 

any association is evidenced from these plots between soil lead levels and interior floor lead 

levels. The highest r-square value (.06) is seen in Figure C3.4a showing slight association 

between post-work soil lead level and post-cleaning floor lead levels in the work room. Identical 

analyses are presented in Figures D3.3a-c and D3.4a-c for sill lead levels and no correlation 

between sill lead levels and soil lead levels is indicated. 

There is some evidence of correlation between paint lead levels in the work room and soil lead 

levels. Within Appendix G, Figures G2.13 and G2.14 plot pre-work and post-work soil lead 

levels, respectively, by average paint lead levels. The association between pre-work soil lead 

and average paint lead yielded an r-square of .08 while the association between post-work soil 

lead and average paint lead yielded an r-square of 0.11. 

6.8.2. Soil Sampling for Exterior Jobs

Similar to the interior experiments, soil samples were collected for all exterior experiments at 

three distinct locations: near the foundation of the house, near the back edge of the rule 

containment plastic, and near the back edge of the plastic used for property containment 

purposes. See Table 6-13 for the actual soil lead levels for each exterior experiment. These soil 

samples were collected to evaluate the possible contamination of the soil resulting from study 

activities. The samples collected near the foundation of the house were generally higher than the 

other locations, as the deteriorating paint from house components are more likely to collect there. 

For H02, H16 and H17, there were no soil samples collected near the foundation due to a 

concrete sidewalk resting against the house. 
6-33 

Table 6-13. Pre- and Post-Work Soil Sample Results (μg/g) for Exterior Experiments 

01 - H01 02 – H01 03 – H01 04 - H02 

Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work 

Near Foundation 2,347 2,880 2,733 16,540 4,590 1,782 n/a n/a Near Edge of Rule Plastic 371 853 111 279 422 480 218 253 Near Edge of Containment Plastic 299 480 178 97 258 336 194 147 

34 – H16 35 – H17 36 – H10 37 – H10 

Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work Pre-Work Post-Work 

Near Foundation n/a n/a n/a n/a 1,075 1,230 181 2,258 Near Edge of Rule Plastic 2,953 8,120 562 529 944 773 548 700 Near Edge of Containment Plastic 438 457 294 278 316 358 213 335 

40 - H19 75 – H09 

Pre-Work Post-Work Pre-Work Post-Work 

Near Foundation 3,164 4,522 373 382 Near Edge of Rule Plastic 306 371 1,882 1,592 Near Edge of Containment Plastic 146 226 467 434 
6-34 

Variability in the soil lead levels also played a role in the change in pre-work to post-work soil 

samples for exterior experiments. Samples were sometimes not collected at the same location, 

making it more difficult to determine the study effect. The number of collected samples and 

average post-work to pre-work exterior soil lead level ratio for each sampling location, by job, 

are contained in Table 6-14. Note that the exterior experiments were only performed two or four 

times, so the averages include a small number (1-2) of values. The largest change is observed 

near the foundation, while the medium and high level jobs appear to have a larger change in soil 

lead than the low intensity jobs. 

Table 6-14. Ratio of Post-work to Pre-work Soil Lead Level in Exterior Soil Samples, by 

Job Type 

Near 

Foundation 

Near Edge of 

Rule Plastic 

Near Edge of 

Containment Plastic

Trim Replacement 1.144 .990 .945 

Door Replacement n/a 1.846 .994 

Dry Scrape 2.124 4.852 2.466 

Power Sanding 3.220 1.825 .924 

Torching 6.918 1.263 1.260 

6.9. Length of Activity Data 

Field technicians recorded the length of time required to perform various activities throughout 

each experiment including pre-work set up, renovation work, post-work cleaning, and cleaning 

verification. The tables included below present summary data on cleaning and cleaning 

verification activities. 

6.9.1. Duration of Post-work Cleaning

The summary data on post-work cleaning times does indicate a small difference in the length of 

time required to conduct Rule and baseline cleaning – an average of 45 minutes for rule cleaning 

and 36 minutes for baseline cleaning. Table 6-15 indicates that there is not a difference in 

cleaning time based on the use of plastic. Some differences are evident across jobs, with higher 

dust producing jobs (door planing, heat gun) resulting in higher clean-up times, as seen in Table 

6-16. Table 6-17 reports that one contractor took approximately 8 minutes longer on average to 

conduct post-work cleaning than the other two. 

Table 6-15. Summary of Post-work Cleaning Times, by Phase (in Minutes) 

P/CU Phase # Obs. Avg. Std. Dev. Min Max 

Phase I - Plastic/Rule cleaning 15 44.7 18.0 20.0 80.0 

Phase II - Plastic/Baseline cleaning 14 35.6 12.3 18.0 60.0 

Phase III - No Plastic/Rule cleaning 15 45.3 12.9 30.0 70.0 

Phase IV - No Plastic/Baseline cleaning 15 36.1 12.3 19.0 60.0 

Total 59 40.5 14.5 18.0 80.0 
6-35 

Table 6-16. Summary of Post-work Cleaning Times, by Job (in Minutes) 

Job # Obs. Avg. Std. Dev. Min Max 

Cut-outs 12 38.8 12.7 18.0 62.0

Door Plane 7 45.3 20.1 25.0 80.0

Dry Scrape 8 40.1 19.9 20.0 80.0

High Heat Gun 12 44.9 12.6 29.0 70.0

Kitchen Gut 8 35.9 11.1 22.0 55.0

Low Heat Gun 4 42.5 12.6 30.0 60.0

Window Replacement 8 36.4 14.1 19.0 65.0

Total 59 40.5 14.5 18.0 80.0

Table 6-17. Summary of Post-work Cleaning Times, by Contractor (in Minutes) 

Job # Obs. Avg. Std. Dev. Min Max 

Contractor 2 20 45.9 13.8 25.0 80.0

Contractor 3 17 38.1 16.5 18.0 80.0

Contractor 4 22 37.5 12.6 20.0 65.0

Total 59 40.5 14.5 18.0 80.0

6.9.2. Duration of Cleaning Verification

The length of the cleaning verification process was measured from its start to when the last floor 

verification zone was declared clean. This included time spent recleaning zones if any failed and 

performing both the wet cloth verification and dry cloth verification, if any were necessary. 

Across all experiments, the cleaning verification process averaged 21 minutes with a range from 

5 minutes to 135 minutes. As seen in Table 6-18, the average cleaning verification length was 

longer when baseline cleaning was used following work as opposed to Rule cleaning. 

Summarizing the cleaning verification durations by job, as reported in Table 6-19, the jobs 

taking longest on average to pass cleaning verification were the kitchen gut (35.5. minutes) and 

cut out (24.5 minutes) jobs, which were relatively low intensity in terms of dust production. On 

average, Contractor 3 took longer to conduct the cleaning verifications, as seen in Table 6-20. 

Table 6-18. Duration of Cleaning Verification Stages, by Phase (in Minutes) 

Phase # Obs. Avg. Std. Dev. Min Max 

Phase I - Plastic/Rule cleaning 15 12.9 5.3 7.0 25.0 

Phase II - Plastic/Baseline cleaning 14 21.8 33.4 5.0 135.0 

Phase III - No Plastic/Rule cleaning 15 15.5 10.6 6.0 45.0 

Phase IV - No Plastic/Baseline cleaning 15 35.0 28.0 10.0 95.0 

Total 59 21.3 23.4 5.0 135.0 
6-36 

Table 6-19. Duration of Cleaning Verification Stages, by Job (in Minutes)

Job # Obs. Avg. Std. Dev. Min Max 

Cut-outs 12 24.5 24.4 5.0 95.0 

Door Plane 7 21.0 20.8 6.0 60.0 

Dry Scrape 8 22.9 29.4 8.0 95.0 

Heat Gun 12 11.1 4.9 5.0 25.0 

Kitchen Gut 8 35.5 41.4 10.0 135.0 

Low Heat Gun 4 16.3 7.5 10.0 25.0 

Window Replacement 8 18.8 12.5 10.0 45.0 

Total 59 21.3 23.4 5.0 135.0 

Table 6-20. Duration of Cleaning Verification Stages, by Job (in Minutes)

Job # Obs. Avg. Std. Dev. Min Max 

Contractor 2 20 18.7 19.5 5.0 95.0 

Contractor 3 17 31.2 35.7 6.0 135.0 

Contractor 4 22 16.0 9.2 8.0 40.0 

Total 59 21.3 23.4 5.0 135.0 

6.9.3. Duration of Pre-work Set Up

Before work could begin prior to a job, renovation workers had to prepare for the work by 

unloading tools and equipment, setting up generators, setting up plastic containment if it was 

necessary, etc. Table 6-21 reports that experiments that required plastic containment took more 

time on average to prepare for. There was little difference by contractor, as seen in Table 6-22, 

or by type of building as seen in Table 6-23. 

Table 6-21. Duration of Interior Pre-work Set Up, by Phase (in Minutes)

Phase # Obs. Avg. Std. Dev. Min Max 

Phase I - Plastic/Rule cleaning 15 96.2 27.3 60.0 140.0

Phase II - Plastic/Baseline cleaning 14 96.6 24.8 65.0 140.0

Phase III - No Plastic/Rule cleaning 15 75.6 25.1 30.0 135.0

Phase IV - No Plastic/Baseline cleaning 15 64.3 13.6 45.0 95.0

Total 59 83.0 26.6 30.0 140.0

Table 6-22. Duration of Interior Pre-work Set Up, by Contractor (in Minutes)

Contractor # Obs. Avg. Std. Dev. Min Max 

C2 20 87.0 27.3 45.0 140.0

C3 17 81.6 24.9 40.0 135.0

C4 22 80.3 28.0 30.0 135.0
6-37 

Table 6-23. Duration of Interior Pre-work Set Up, by Building Type (in Minutes)

Unit Type # Obs. Avg. Std. Dev. Min Max 

Housing Unit 47 83.8 27.4 30.0 140.0

COF 12 79.6 24.1 45.0 120.0

The pre-work set up times for exterior work encompassed a significant amount of study-required 

set up including vertical containment set up and laying out containment plastic on the ground. 

Thus, the exterior pre-work set up times are not indicative of set up required by the proposed 

rule, which would primarily be laying out the rule plastic, and are not presented. 

6.9.4. Duration of Interior RRP Work

The length of time that it took to conduct each job for the study varied significantly. A 

summary of interior work duration times is reported in Table 6-24. The heat gun jobs took the 

longest averaging three hours for the heat gun <1100 degrees job and about three and half hours 

for the heat gun >1100 degrees job. On the other hand, the jobs averaging the shortest amount 

of time were the cut outs and kitchen gut jobs. There is high variability among the cut out jobs 

as some experiments only involved the cutting of the holes in the wall, but not any electrical or 

plumbing work, while others included actual installation of wiring, outlets, or lights. 

Table 6-24. Duration of Interior Work, by Job (in Minutes)

Job # Obs. Avg. Std. Dev. Min Max 

Cut-outs 12 49.8 48.7 7.0 170.0

Window Replacement 8 90.9 46.6 45.0 188.0

Dry Scrape 8 95.4 44.0 65.0 201.0

Door Plane 7 60.4 31.0 30.0 125.0

Heat Gun < 1100 degrees 4 180.0 24.8 145.0 200.0

Kitchen Gut 8 50.0 23.5 25.0 90.0

Heat Gun > 1100 degrees 12 214.8 44.4 145.0 300.0

Total 59 105.2 75.7 7.0 300.0

A summary of exterior work duration times is reported in Table 6-25. The paint removal jobs 

conducted at the COF took the longest, while the door replacement and dry scraping jobs took 

less time on average than the others. 
6-38 

Table 6-25. Duration of Exterior Work, by Job (in Minutes)

Job # Obs. Avg. Std. Dev. Min Max 

Replace Exterior Door 2 47.5 10.6 40.0 55.0 

Trim Replacement 2 115.0 134.4 20.0 210.0 

Needle Gun 1 239.0 n/a 239.0 239.0 

Dry Scrape 4 70.0 63.5 35.0 165.0 

Heat Gun <1100 degrees 1 245.0 n/a 245.0 245.0 

Power Sanding 2 112.5 10.6 105.0 120.0 

Heat Gun > 1100 degrees 1 305.0 n/a 305.0 305.0 

Torching 2 152.5 31.8 130.0 175.0 

Total 15 128.3 91.5 20.0 305.0 

6.10. Cleaning Verification Data 

The analyses contained in this section explore the impact of the cleaning verification process on 

lead levels remaining in the Work room at the completion of an RRP job. The analyses explore 

the association of different factors with post-verification floor and sill lead levels, including 

phase, job type, contractor, floor type and condition. Of interest were the relation of 

post-verification levels to EPA clearance standards. 

6.10.1. Verification Of Floor Zones

As detailed in Section 3, each interior experiment contained a cleaning verification stage, where 

the RRP workers performed cleaning verification in accordance with the proposed rule. In an 

effort to keep the cleaning verification process as close as possible to what the RRP workers 

would do if the rule was enacted, they were given training on how to do the cleaning verification, 

and minimal guidance was provided by study personnel during the execution. The decision to 

pass or fail a verification cloth was left solely up to the RRP workers, although the study field 

supervisors were instructed to overrule any clearly unwarranted determinations. Information on 

the cleaning verification for all interior experiments is seen in Table 6-34. All average values 

presented in this section refer to the Work Room only. 

Floor Cleaning Verification by Phase 

Figure 6-18 displays the post-verification (PV) floor lead levels for all interior experiments by 

Phase. Note that the sample results below the detection limit of the laboratory are set to 5 μg/ft2

, 

one half of the detection limit, for plotting and analysis purposes. 
6-39 

Figure 6-18. Post-verification Floor Lead Loadings by Phase. The reference line is set at the EPA 

clearance standard of 40 μg/ft2

 for floor surfaces. 

When considering the percentage of floor zones that failed cleaning verification on the first wet 

verification cloth, Table 6-26 reports that 48.6% of floor zones that were tested after Phase IV 

(no plastic and baseline cleaning) failed. The two phases which involved no use of plastic had 

the highest average post-verification floor lead levels (313.5 and 192.7 μg/ft2). When plastic was 

used and the rule cleaning method performed, the average post-verification floor lead level was 

the closest to the EPA clearance standard of 40 μg/ft2

. One problem that arose during the study 

was that after the use of insufficiently diluted Simple Green solution during the rule cleaning and 

all cleanings after the first wet verification failure, the verification cloths had a gray color to 

them, making them visibly darker than the verification card. This led to the failure of some floor 

zones, although the post-cleaning (PC) and post-verification (PV) floor lead levels were below 

clearance standards. This was especially true for the experiments performed at C01-the school. 
6-40 

Table 6-26. Floor Verification Information by Phase 

 Phase 

Avg. PC Floor 

Lead Level 

(μg/ft2) 

% 1st Wet 

Cloth 

Failure 

% 2nd Wet 

Cloth 

Failure 

Avg. PV Floor 

Lead Level 

(μg/ft2) 

I – Plastic/Rule Cleaning 69.0 9.4% 0.0% 55.1 

II – Plastic/Baseline Cleaning 172.8 10.9% 4.7% 121.2 

III – No plastic/Rule Cleaning 305.9 4.5% 0.0% 313.5 

IV – No plastic/Baseline Cleaning 476.8 48.6% 2.9% 192.7 

As seen in Table 6-27, the average percent change (PV versus PC) in floor lead level for 

Phase III is positive due to an unusual value for experiment 76 where the average post-cleaning 

floor lead level was less than 10 μg/ft2

 and the average post-verification lead level was 89.6 

μg/ft2

. If this experiment is excluded, the overall average percent change in floor lead level 

across all experiments between the post-cleaning and post-verification stages results in a 

decrease of 29.1%. A greater decrease in the floor lead levels is observed when one or more of 

the floor zones failed and were re-cleaned at least once. For phases involving baseline cleaning, 

this meant that the floor was cleaned according to the rule method following the first failure and 

any subsequent failures, as called for by the design. This shift in cleaning methods for cleaning 

verification should be considered in interpreting the data from the cleaning verification portion 

of the experiments. 

Table 6-27. Post-cleaning and Post-verification Floor Lead Levels for Experiments with 

Zero and ≥1 Verification Failures by Phase 

Phase 

I II III IV 

# of Verification 

Failures 0 ≥1 0 ≥1 0* ≥1 0 ≥1 

Average PC Floor 

Lead Level (μg/ft2) 79.1 41.3 204.1 47.6 369.442 75.4 752.8 235.3 

Average PV Floor 

Lead Level (μg/ft2) 69.0 17.0 145.7 23.0 374.192 61.6 328.2 74.2 

Avg. % Change per 

Experiment -18.6% -27.2% -19.5% -50.7% -17.4% -41.5% -35.1% -60.2%

Overall Avg. Change -12.7% -58.9% -28.6% -51.6% 3.2% -18.3% -56.4% -68.4%

* excludes one experiment with <10 at post-cleaning and 89.6 at post-verification 

Floor Cleaning Verification by Job 

Figure 6-19 and Table 6-28 display the post-verification floor lead levels for all interior 

experiments by job type. The jobs with the highest average floor lead level after cleaning 

verification were the door planing and the high heat gun jobs. The door plane job resulted in a 

significant amount of fine dust distributed around the entire Work Room, while the other jobs 

resulted in larger paint chips and pieces of debris. This could be the cause of the high postverification lead levels, as the fine dust was difficult to clean, especially when the floor surface 

was not in good condition. The fine dust was also more difficult to see on the verification cloths 

than any dark, soot-like residue. 
6-41 

Figure 6-19. Post-verification Floor Lead Loadings by Job Type. The reference line is 

set at the EPA clearance standard of 40 μg/ft2

 for floor surfaces. 

Table 6-28. Floor Verification Information by Job Type

Job Type Average PC Floor 

Lead Level (μg/ft2)

% 1st Wet 

Cloth Failure 

% 2nd Wet 

Cloth Failure 

Average PV Floor 

Lead Level (μg/ft2)

Cut-outs 19.2 33.3% 2.1% 12.1 

Window Replacement 109.1 11.9% 0.0% 65.0 

Dry Scrape 81.3 15.0% 0.0% 38.6 

Door Plane 431.7 28.6% 2.9% 284.0 

Heat Gun <1100 degrees 50.4 20.0% 0.0% 26.2 

Kitchen Gut 45.2 20.0% 10.0% 37.0 

Heat Gun >1100 degrees 799.8 6.1% 0.0% 549.4 

Floor Cleaning Verification by Contractor 

Across the study, the cleaning verification was performed variably by the RRP workers. Some 

of the observed differences included the amount of force applied to the verification cloth, the 

speed of wiping the verification zones, the cleaning performed if a particular zone or zones failed 
6-42 

verification, and the determination of whether a zone passed or failed. Table 6-29 reports that 

RRP workers in Pittsburgh were less likely to fail a floor zone, and had an average PV floor lead 

level of more than double that of Columbus contractors. 

Table 6-29. Floor Verification Information by Contractor 

City Contractor # of 

Exp. 

Avg. PC Floor 

Lead Level 

(μg/ft2) 

% 1st Wet 

Cloth 

Failure 

% 2nd Wet 

Cloth 

Failure 

Avg. PV Floor 

Lead Level 

(μg/ft2) 

C2 20 175.5 28.6% 6.5% 65.9 Columbus C3 18 220.0 22.4% 0.0% 147.7 

Pittsburgh C4 22 365.6 8.8% 0.0% 291.1 

Floor Cleaning Verification by Floor Type and Condition 

Tables 6-30 and 6-31 report the floor verification summary data by floor type and floor 

condition, respectively. Table 6-30 reports that the first verification cloths taken on floors were 

more likely to fail on vinyl tile and tile floors even though the post-cleaning levels on average 

are lower on the tile floors as opposed to the wood floors. The vinyl and tile floors were located 

in residential kitchens and in the classrooms at the COF. Table 6-31 reports that the floors in 

poor condition had significantly higher post-verification floor lead levels. Note that nearly all of 

the wood floors (20 of 22 experiments) were in poor condition. 

Table 6-30. Floor Verification Information by Floor Type 

Floor Type # of Exp 

Avg. PC Floor 

Lead Level 

(μg/ft2) 

% 1st Wet 

Cloth Failure 

% 2nd Wet 

Cloth Failure 

Avg. PV Floor 

Lead Level 

(μg/ft2) 

Wood 22 543.5 10.6% 0.0% 384.5 

Vinyl 21 123.8 23.7% 2.1% 61.4 

Tile 17 47.7 25.4% 4.8% 28.8 

Table 6-31. Floor Verification Information by Floor Condition 

Floor Type # of Exp 

Avg. PC Floor 

Lead Level 

(μg/ft2) 

% 1st Wet 

Cloth Failure 

% 2nd Wet 

Cloth Failure 

Avg. PV Floor 

Lead Level 

(μg/ft2) 

Good 22 35.8 19.4% 0.0% 16.8 

Fair 11 76.5 15.4% 7.7% 58.8 

Poor 27 508.9 15.4% 1.6% 341.5 

Table 6-32 provides information regarding how the interaction between job type and floor type 

and condition impacts cloth failures and post-verification floor lead levels. Certain jobs occurred 

only in rooms with certain floor types and conditions, which highlights some differences 

between and within jobs. While door planing resulted in relatively high post-verification floor 

lead levels as seen in Table 6-28, the two jobs that occurred on wood floors in poor condition 

performed significantly worse with a post-verification average of 619 μg/ft2

 than the other six 

jobs that occurred in rooms with vinyl or tile floors. Within the cut out and kitchen jobs, 

although relatively low post-verification lead levels were found across all jobs, higher levels 

were found for the jobs performed in rooms with poor floor condition. 
6-43 

Table 6-32. Floor Verification Information by Job Type, Floor Type, and Floor Condition 

Job Type Floor Type/ 

Condition 

# of 

Exp 

Avg. PC 

Floor Lead 

Level (μg/ft2) 

% 1st 

Wet Cloth 

Failure 

% 2nd Wet 

Cloth 

Failure 

Avg. PV 

Floor Lead 

Level (μg/ft2) 

Tile-Good 4 10.5 50.0% 0.0% 5.0 

Vinyl-Good 4 16.4 30.0% 0.0% 7.2 

Tile-Fair 2 11.6 0.0% 0.0% 12.4 

Cut-Outs 

Vinyl-Poor 2 49.9 40.0% 10.0% 36.1 

Window Wood-Fair 2 96.4 0.0% 0.0% 82.2 

Replacement Wood-Poor 6 113.4 16.7% 0.0% 59.2 

Vinyl-Good 4 92.3 0.0% 0.0% 42.6 Dry Scrape Wood-Poor 4 70.2 30.0% 0.0% 34.6 

Tile-Fair 2 196.6 0.0% 0.0% 134.5 

Door Plane Vinyl-Poor 4 443.8 50.0% 5.0% 191.2 

Wood-Poor 2 642.4 0.0% 0.0% 619.2 

Heat Gun 

<1100 degrees Tile-Good 4 50.4 20.0% 0.0% 26.2 

Vinyl-Good 2 14.8 0.0% 0.0% 8.6 

Tile-Fair 1 71.5 100.0% 100.0% 41.4 

Vinyl-Fair 4 40.2 25.0% 0.0% 36.9 Kitchen Gut 

Vinyl-Poor 1 99.7 0.0% 0.0% 89.6 

Heat Gun Tile-Good 4 19.8 18.8% 0.0% 7.3 

>1100 degrees Wood-Poor 8 1,189.8 0.0% 0.0% 820.4 

Impact of Dry Cloth Verification 

Table 6-33 shows the corresponding average post-cleaning, post-wet verification and postverification floor lead levels for each of the five floor zones that failed the second wet 

verification cloth. For each experiment, the number of dry verification cloths used is also listed. 

Each of these three experiments occurred with a tile floor using the kitchen as the work room. 

Table 6-33. Floor Zones That Failed Second Wet Cloth Verification 

Exp # - Job Floor 

Zone 

PC Floor Lead 

Level (μg/ft2) 

WV Floor Lead 

Level (μg/ft2) 

# of Dry 

Cloths 

PV Floor Lead 

Level (μg/ft2) 

45 – Cut outs 2 91.5 61.5 2 37.3 

47 – Door planing 2 1,292.1 550.8 1 643.6 

1 n/a 150.7 1 77.9 

70 – Kitchen gut 2 46.2 < 10 2 < 10 

3 147.1 < 10 1 n/a 

 
6-44 

Comparison of Post-cleaning and Post-verification Lead Levels 

Figure 6-20 plots the number of experiments in various categories of floor lead levels at the postcleaning and post-verification stages. With floors, over 50 percent of the experiments ended 

with average post-verification levels less than 40 μg/ft2. The number of experiments with 

average levels over 100 μg/ft2 dropped from 20 at the post-cleaning stage to 13 at postverification. 

Figure 6-20. Number of Experiments by Post-cleaning and Post-verification Floor Lead 

Loadings
6-45 

Table 6-34. Verification Information for Interior Experiments 

Exp. 

# 

Unit 

ID Job Phase Floor Type Floor Cond. Cont. # of Floor Zones Avg. PC Floor Lead Level (μg/ft2) # Failed 1st Wet Cloths # Failed 2nd Wet Cloths Post-Wet Verif. (μg/ft2) # Failed Dry Cloths Avg. PV Floor Lead Level (μg/ft2) # P

Sam

>40 μ

23 H16 Cut-outs I Vinyl Good C4 5 6.6 1 0 - 0 < 10 0 55 C01 Cut-outs I Tile Good C2 3 < 10 1 0 - 0 < 10 0 72 H35 Cut-outs I Tile Fair C3 3 14.8 0 0 - 0 < 10 0 25 H16 Cut-outs II Vinyl Good C4 5 11 0 0 - 0 8.7 0 53 C01 Cut-outs II Tile Good C2 3 7.8 0 0 - 0 < 10 0 71 H35 Cut-outs II Tile Fair C3 3 8.5 0 0 - 0 19.8 0 24 H17 Cut-outs III Vinyl Good C4 5 31.1 0 0 - 0 9.9 0 46 H08 Cut-outs III Vinyl Poor C3 5 15.9 0 0 - 0 14.9 0 52 C01 Cut-outs III Tile Good C2 3 17.8 2 0 - 0 < 10 0 22 H16 Cut-outs IV Vinyl Good C4 5 16.7 5 0 - 0 < 10 0 45 H08 Cut-outs IV Vinyl Poor C3 5 84 4 1 61.5 1 57.2 1 54 C01 Cut-outs IV Tile Good C2 3 11.3 3 0 - 0 < 10 0 48 H08 Door Plane I Vinyl Poor C3 5 180.9 0 0 - 0 290.4 4 79 H09 Door Plane I Wood Poor C3 4 139.1 0 0 - 0 87.4 4 73 H35 Door Plane II Tile Fair C3 3 233.9 0 0 - 0 116.3 3 77 H08 Door Plane II Vinyl Poor C3 5 50.7 0 0 - 0 31.4 1 74 H35 Door Plane III Tile Fair C3 3 159.4 0 0 - 0 152.6 4 80 H09 Door Plane III Wood Poor C3 5 1,145.8 0 0 - 0 1,150.9 4 47 H08 Door Plane IV Vinyl Poor C3 5 1,372.7 5 1 550.8 0 395.5 4 78 H08 Door Plane IV Vinyl Poor C3 5 171 5 0 - 0 47.6 2 

5 H03 Dry Scrape I Wood Poor C2 5 31.6 1 0 - 0 28.9 2 

28 H17 Dry Scrape I Vinyl Good C4 5 104.4 0 0 - 0 39.5 1 

6 H03 Dry Scrape II Wood Poor C2 5 180.5 0 0 - 0 58.7 4 

29 H17 Dry Scrape II Vinyl Good C4 5 156.1 0 0 - 0 38.1 1 

8 H03 Dry Scrape III Wood Poor C2 5 12.9 0 0 - 0 9.4 0 

26 H17 Dry Scrape III Vinyl Good C4 5 23.2 0 0 - 0 19.3 0 

7 H03 Dry Scrape IV Wood Poor C2 5 55.9 5 0 - 0 41.2 3 

27 H17 Dry Scrape IV Vinyl Good C4 5 85.5 0 0 - 0 73.6 3 16 H09 Heat Gun>1100 I Wood Poor C2 3 54 0 0 - 0 65.5 4 33 H10 Heat Gun>1100 I Wood Poor C4 4 191.8 0 0 - 0 147.5 4 
6-46 

Table 6-34. (continued) Verification Information for Interior Experiments 

Exp. 

# 

Unit 

ID Job Phase Floor Type Floor Cond. Cont. # of Floor Zones Avg. PC Floor Lead Level (μg/ft2) # Failed 1st Wet Cloths # Failed 2nd Wet Cloths Post-Wet Verif. (μg/ft2) # Failed Dry Cloths Avg. PV Floor Lead Level (μg/ft2) # P

Sam

>40 μ

63 C01 Heat Gun>1100 I Tile Good C2 4 < 10 0 0 - 0 < 10 0 13 H09 Heat Gun>1100 II Wood Poor C2 5 97.2 0 0 - 0 205.3 3 31 H10 Heat Gun>1100 II Wood Poor C4 4 1,393.0 0 0 - 0 1,122.9 4 60 C01 Heat Gun>1100 II Tile Good C2 4 30.2 0 0 - 0 12.9 0 14 H09 Heat Gun>1100 III Wood Poor C2 4 84.9 0 0 - 0 76.4 3 32 H10 Heat Gun>1100 III Wood Poor C4 4 2,876.6 0 0 - 0 2,976.1 4 61 C01 Heat Gun>1100 III Tile Good C2 4 11.3 0 0 - 0 < 10 0 15 H09 Heat Gun>1100 IV Wood Poor C2 5 2,669.6 0 0 - 0 678.9 4 30 H10 Heat Gun>1100 IV Wood Poor C4 4 2,151.0 0 0 - 0 1,290.7 4 62 C01 Heat Gun>1100 IV Tile Good C2 4 32.7 3 0 - 0 6.4 0 51 H33 Kitchen Gut I Vinyl Fair C4 3 45.4 0 0 - 0 42.3 2 67 H16 Kitchen Gut I Vinyl Good C4 5 < 10 0 0 - 0 < 10 0 49 H31 Kitchen Gut II Vinyl Fair C4 3 45.8 3 0 - 0 10.5 0 68 H17 Kitchen Gut III Vinyl Good C4 5 24.6 0 0 - 0 12.2 0 76 H36 Kitchen Gut III Vinyl Fair C4 3 < 10 0 0 - 0 89.6 1 50 H32 Kitchen Gut IV Vinyl Fair C4 3 64.7 0 0 - 0 < 10 0 70 H35 Kitchen Gut II Tile Fair C3 3 71.5 3 3 

150.7 

<10 <10 1 41.4 1 

69 H08 Kitchen Gut IV Vinyl Poor C3 5 99.7 0 0 - 0 89.6 3 59 C01 Low Heat Gun I Tile Good C2 6 122.2 3 0 - 0 29.1 2 56 C01 Low Heat Gun II Tile Good C2 5 25.6 1 0 - 0 17.2 0 58 C01 Low Heat Gun III Tile Good C2 4 9.5 0 0 - 0 7.5 0 57 C01 Low Heat Gun IV Tile Good C2 5 44.2 0 0 - 0 51 2 12 H09 Window Repl. I Wood Poor C3 3 60.5 0 0 - 0 29.9 1 41 H16 Window Repl. I Wood Poor C4 6 69 0 0 - 0 41.4 3 11 H09 Window Repl. II Wood Poor C3 5 96.9 0 0 - 0 33.5 1 42 H16 Window Repl. II Wood Poor C4 6 183.4 0 0 - 0 96.2 4 

9 H09 Window Repl. III Wood Poor C3 5 133 1 0 - 0 118.2 4 

44 H17 Window Repl. III Wood Fair C4 6 38.1 0 0 - 0 56.1 2 10 H09 Window Repl. IV Wood Poor C3 5 137.8 4 0 - 0 36 1 43 H17 Window Repl. IV Wood Fair C4 6 154.7 0 0 - 0 108.3 3 

* Verification time includes window sill and floor verification, re-cleaning, and wait times.
6-47 

6.10.2. Verification of Window Sills

Along with the floor zones, each window sill in the Work Room was subject to cleaning 

verification. As stated previously, all window sills had to pass clearance before the RRP workers 

moved on to the cleaning verification of the floor. Overall, only three window sills failed the 

first wet cloth verification, despite the fact that nineteen window sills had post-cleaning lead 

levels of greater than 250 μg/ft2. Tables 6-35, 6-36, and 6-37 list the post-cleaning and postverification average sill lead levels by phase, job intensity level, and contractor respectively. 

Table 6-39 reports window sill cleaning verification information across all experiments. 

Table 6-35. Window Sill Verification Information by Phase 

Phase PC Sill Lead 

Level (μg/ft2) 

PV Sill Lead 

Level (μg/ft2) 

# 1st Wet Cloth 

Failures 

I – Plastic/Rule Cleaning 151.8 198.7 1 

II – Plastic/Baseline Cleaning 761.6 119.6 0 

III – No plastic/Rule Cleaning 1439.0 490.5 1 

IV – No plastic/Baseline Cleaning 601.4 467.4 1 

Table 6-36. Window Sill Verification Information by Intensity Level 

Intensity Level PC Sill Lead 

Level (μg/ft2) 

PV Sill Lead 

Level (μg/ft2) 

# 1st Wet Cloth 

Failures 

Low 159.9 155.7 2 

Medium 366.1 451.9 1 

High 1689.3 347.6 0 

Table 6-37. Window Sill Verification Information by Contractor 

City Contractor # of 

Exp 

Avg. PC Sill 

Lead Level 

(μg/ft2) 

% 1st Wet 

Cloth 

Failure 

% 2nd 

Wet Cloth 

Failure 

Avg. PV Sill 

Lead Level 

(μg/ft2) 

C2 20 142.0 0.0% 0.0% 39.3 Columbus 

C3 18 469.2 7.7% 0.0% 526.8 

Pittsburgh C4 22 1,500.9 3.1% 0.0% 381.1 

No window sills failed a second wet cloth verification. For two of the three window sills that 

failed the first wet verification cloth, there are no corresponding post-cleaning or postverification samples. This is because the sampling protocol called for one window sill sample at 

each sampling stage for interior experiments, while the cleaning verification protocol requires 

the testing of all window sills within the Work Room. For the one window sill that does 

correspond to the window used in the three-stage sampling, the post-cleaning lead level was 

44.5 μg/ft2

 and the post-verification level was 20 μg/ft2. 

Comparison of Post-cleaning and Post-verification Lead Levels 

Figure 6-21 plots the number of experiments in various categories of sill lead levels at the 

post-cleaning and post-verification stages. The number of experiments with sill lead levels 

below the clearance standard of 250 μg/ft2 increased from 41 to 48 between post-cleaning and 

post-verification. Table 6-38 presents the percent change in window sill lead levels from 
6-48 

post-cleaning to post-verification by phase and whether a cloth failure was identified. It is worth 

noting that lead levels from 24 experiments were below the detection limit at post-cleaning and 

34 experiments are post-verification, with 21 being below the detection limit at both stages (9 

from Phase I). 

Figure 6-21. Number of Experiments by Post-cleaning and Post-verification Sill Lead 

Loadings

Table 6-38. Post-cleaning and Post-verification Sill Lead Levels for Experiments with 

Zero and ≥1 Verification Failures by Phase. 

Phase 

I II III IV 

# of Verification 

Failures 0 ≥1 0 ≥1 0 ≥1 0 ≥1 

Average PC Sill 

Lead Level (μg/ft2) 156.5 85.8 761.6 n/a 1,538.6 44.5 614.9 411.5 

Average PV Sill 

Lead Level (μg/ft2) 208.8 57.5 118.8 n/a 526.7 20.0 438.4 873.3 

Avg. % Change per 

Experiment 1.7% -33.0% -52.5% n/a 106.1%* -55.1% -44.2% 112.2%

Overall Avg. 

Change 33.4% -33.0% -84.4% n/a -65.8% -55.1% -28.7% 112.2%

* with exclusion of 2 experiments that changed from below detection limit to 166 and 282 μg/ft2, average percent 

change would be -14.2% 
6-49 

Table 6-39. Window Sill Verification Information for Interior Experiments 

Exp. 

# 

Unit 

ID Job Phase Sill Type Cont. # of Sills 

PC Sill Lead 

Level (μg/ft2)

# Failed 1st 

Wet Cloths 

PV Sill Lead 

Level (μg/ft2) 

# PV Samples 

>250 μg/ft2

23 H16 Cut-outs I SILL C4 2 < 40 0 < 40 0 

55 C01 Cut-outs I TRAY C2 1 < 41.6 0 < 41.6 0 

72 H35 Cut-outs I SILL C3 2 < 100 0 < 100 0 

25 H16 Cut-outs II SILL C4 2 < 52.6 0 < 52.6 0 

53 C01 Cut-outs II TRAY C2 1 48.7 0 < 45.5 0 

71 H35 Cut-outs II SILL C3 2 101.1 0 < 62.5 0 

24 H17 Cut-outs III SILL C4 2 < 50 0 166.4 0 

46 H08 Cut-outs III TRAY C3 1 < 41.6 0 < 41.6 0 

52 C01 Cut-outs III TRAY C2 1 < 45.5 0 < 45.5 0 

22 H16 Cut-outs IV SILL C4 2 198.2 0 < 40 0 

45 H08 Cut-outs IV SILL C3 1 416.9 0 276.6 1 

54 C01 Cut-outs IV TRAY C2 1 < 41.6 0 < 41.6 0 

48 H08 Door Plane I SILL C3 1 521.3 0 1,707.9 1 

79 H09 Door Plane I TRAY C3 1 104.2 0 < 45.5 0 

73 H35 Door Plane II SILL C3 3 127.1 0 115.7 0 

77 H08 Door Plane II TRAY C3 1 278.6 0 61.7 0 

74 H35 Door Plane III SILL C3 2 170.4 0 < 100 0 

80 H09 Door Plane III TRAY C3 1 2,546.1 0 3,378.2 1 

47 H08 Door Plane IV SILL C3 1 1,798.7 0 2,625.3 1 

78 H08 Door Plane IV TRAY C3 1 277.9 0 96.5 0 

5 H03 Dry Scrape I TRAY C2 1 < 10 0 < 10 0 

28 H17 Dry Scrape I SILL C4 2 85.8 1* 57.5 0 

6 H03 Dry Scrape II TRAY C2 1 < 50 0 < 25 0 

29 H17 Dry Scrape II SILL C4 2 467 0 115 0 

8 H03 Dry Scrape III TRAY C2 1 < 45.5 0 < 45.5 0 

26 H17 Dry Scrape III SILL C4 2 < 52.6 0 < 52.6 0 

7 H03 Dry Scrape IV TRAY C2 1 < 50 0 < 50 0 

27 H17 Dry Scrape IV SILL C4 2 150.8 0 < 52.6 0 

16 H09 Heat Gun I TRAY C2 1 < 41.6 0 < 41.6 0 

33 H10 Heat Gun I TRAY C4 1 1005.3 0 790.2 1 

63 C01 Heat Gun I TRAY C2 1 < 45.5 0 < 45.5 0 

13 H09 Heat Gun II TRAY C2 1 253.7 0 81.4 0 

31 H10 Heat Gun II TRAY C4 1 8,838.8 0 927.2 1 

60 C01 Heat Gun II TRAY C2 1 170.4 0 < 45.5 0 

14 H09 Heat Gun III TRAY C2 1 < 45.5 0 < 45.5 0 

32 H10 Heat Gun III TRAY C4 1 18,132.8 0 2,669.6 1 

61 C01 Heat Gun III TRAY C2 1 < 41.6 0 < 41.6 0 

15 H09 Heat Gun IV TRAY C2 1 1,352.4 0 182.7 0 

30 H10 Heat Gun IV TRAY C4 1 1,697.6 0 1,784.5 1 
6-50 

Table 6-39. (continued) Window Sill Verification Information for Interior Experiments 

Exp. 

# 

Unit 

ID Job Phase Sill Type Cont. # of Sills 

PC Sill Lead 

Level (μg/ft2)

# Failed 1st 

Wet Cloths 

PV Sill Lead 

Level (μg/ft2) 

# PV Samples 

>250 μg/ft2

62 C01 Heat Gun IV TRAY C2 1 94.4 0 < 45.5 0 

51 H33 Kitchen Gut I SILL C4 1 < 45.5 0 < 45.5 0 

67 H16 Kitchen Gut I SILL C4 2 < 40 0 < 40 0 

49 H31 Kitchen Gut II SILL C4 1 < 100 0 < 100 0 

70 H35 Kitchen Gut II SILL C3 2 < 66.6 0 < 66.6 0 

68 H17 Kitchen Gut III SILL C4 2 396.5 0 < 52.6 0 

76 H36 Kitchen Gut III SILL C4 1 86.2 0 138.3 0 

50 H32 Kitchen Gut IV SILL C4 1 130.3 0 < 41.6 0 

69 H08 Kitchen Gut IV SILL C3 1 1,414.2 0 73.5 0 

59 C01 Low Heat Gun I TRAY C2 1 137.7 0 < 41.6 0 

56 C01 Low Heat Gun II TRAY C2 1 285.1 0 133.1 0 

58 C01 Low Heat Gun III TRAY C2 1 < 41.6 0 n/a 1 

57 C01 Low Heat Gun IV TRAY C2 1 246.8 0 70.4 0 

12 H09 Window Repl. I TRAY C3 1 < 45.5 0 < 45.5 0 

41 H16 Window Repl. I SILL C4 1 218.1 0 176 0 

11 H09 Window Repl. II SILL C3 1 106.9 0 < 45.5 0 

42 H16 Window Repl. II SILL C4 1 611.9 0 126.2 0 

9 H09 Window Repl. III SILL C3 2 44.5 1 < 40 0 

44 H17 Window Repl. III SILL C4 1 < 52.6 0 281.5 1 

10 H09 Window Repl. IV SILL C3 2 411.5 1* 873.3 1 

43 H17 Window Repl. IV SILL C4 1 784.9 0 892.5 1 

* The failed verification cloth does not correspond to the sill from which the samples were collected. 
7-1 

7. Statistical Modeling Results 

The following sections provide the results of statistical models applied to floor and window sill 

dust-lead results from the RRP Field Study. The results are organized by Stage (Post Work, Post 

Cleaning, and Post Verification) and Room (Work, Tool, and Observation) – with separate 

statistical models being specified within each Stage-by-Room combination to address the 

multiple inferential objectives mentioned earlier in Section 1. Section 7.1 corresponds to all 

results obtained in the Post Work Stage of field data collection, with subsections 7.1.1 – 7.1.3 

corresponding to results in the Work Room, Tool Room and Observation Room, respectively. 

Similarly, Sections 7.2 and 7.3 (and their associated sub-sections) correspond to the Post 

Cleaning and Post Verification Stages. Section 7.4 corresponds to a cross-stage analysis that 

compares full rule implementation (use of plastic sheeting and RRP rule cleaning in the Postverification Stage) to baseline activities or no rule implementation (no use of plastic sheeting and 

baseline cleaning in the Post-cleaning Stage). 

The results summarized in the following sections provide an overview of the statistical modeling 

results for floor and window sill dust-lead loadings from interior RRP jobs for two subsets of 

study data: (1) data limited to residential units only, and (2) Combined data for all interior RRP 

jobs (both residential and COFs). All analyses that were conducted on the second subset of data 

include a term in the model that adjusts for differences between residential units and COFs. 

Thus, a COF variable appears in all models of the Combined data. 

The rationale for presenting the analysis results for each Stage-by-Room combination is that the 

series of statistical models that are fit to a subset of data (e.g. post-cleaning floor dust-lead 

loadings in the Observation room) are directly comparable using a likelihood ratio test statistic. 

Differences in reported likelihood fit statistics (-2 Log-Likelihood) between two models applied 

to the same dataset can be assessed by comparing to the Chi-Squared (χ

2

) distribution with 

degrees of freedom matching the difference in the number of fixed effects included in the two 

models. Generally, the lower likelihood ratio statistic indicates the better fitting model. Within 

each subset of data, a potential best model is identified based on evaluation of the likelihood 

ratio along with the number of variables included and the significance of additional variables. 

A mixed models analysis of variance approach including both fixed and random effects was used 

to fit the statistical models presented in this section and test the various study hypotheses, using 

Proc Mixed in SAS®. Each of the models explained dust-lead loadings on floors or window sills 

as a function of one or more fixed effects variables (intensity-level, job-type, use of plastic 

sheeting, post-work cleaning method, average paint-lead loading on disrupted component(s), 

square feet of lead-based paint disturbed, etc.) – with some models investigating interactions 

between some of these fixed effect variables to address specific analysis objectives. 

Adjustments were made in the model to account for the data not being independent. There is 

anticipated positive correlation between the multiple samples of each type taken within the same 

room during the same experiment, within the same room across experiments, and within the 

same housing unit across experiments. To account for this, the models applied to floor dust-lead 

loadings included random effect terms that adjusted for anticipated positive correlation among 

multiple results observed from within the same unit, among multiple results observed from 
7-2 

within the same room (within a unit), and among multiple results observed from within the same 

RRP experiment. The models applied to window sill dust-lead loadings included a random 

effect for the anticipated positive correlation among multiple results observed from within the 

same room within a unit (a random effect for experiment was unnecessary because there was 

only one window sill sample obtained from each Stage-by-Room combination within an 

experiment). 

Because the statistical models assume the data are normally distributed and because the dust lead 

loading data were non-normal (as indicated by various figures in Appedices B-E), all floor and 

sill data underwent log-transformation to more closely approximate normality, which generally is 

done with environmental lead data. Although most sets of transformed data still differ 

significantly enough from normality to be identified as non-normal by the test statistic presented 

in the appendices, the statistical models utilized are robust enough to account for this level of 

non-normality. Plots of residuals from each set of data are presented within the section to 

illustrate the suitability of the models used. 

In the sections that follow, we provide summary tables for the models fit for each 

Stage-by-Room combination of data. The summary tables provide an overview of the p-value 

associated with each explanatory factor and the likelihood fit statistic for model fit to that 

particular subset of data. The p-values for categorical variables are based on an F-test for the 

combined effect across multiple levels. Statistical significance is generally attributed to p-values 

less than 0.05. P-values between .05 and about .10 are referred to as borderline significant. 

Additional detail on the specific parameter estimates and standard errors from each model can be 

found in Appendices I through N. Residential floor and sill results are in Appendices I and J; 

COF floor results are in Appendix K; combined interior results are in Appendices L and M; and 

detailed exterior model results are in Appendix N. Residual plots for the best fitting models are 

contained in Appendix O. In a few places in this section, we compare the specific parameter 

estimates for a variable of interest and calculate the model-predicted difference in geometric 

mean levels based on those estimates. This is done using the formula 100*(1-ex

), with “x” being 

the difference in parameter estimates.

7.1. Post-Work Dust Lead Levels 

The following three subsections provide an overview of statistical modeling results for floor and 

window sill dust lead loading results in the post work stage of the field study, in the Work room 

(subsection 7.1.1), Tool room (subsection 7.1.2), and Observation room (subsection 7.1.3). 

7.1.1. Post-Work Work Room Dust Lead Levels 

Table 7-1 provides an overview of results from statistical models developed to describe postwork floor and window sill dust-lead loadings in the Work room across the two subsets of data 

described earlier (residential units only and all units combined). The results are repeated using 

the wipe-only dust-lead results, as well as the results that also integrated the bulk samples. 
7-3 

Objective 1-Model 1 assesses the total effect of Intensity-Level (High, Medium, and Low) on 

floor and window sill dust lead loadings, which was shown to be statistically significant in all 

models. Objective 1-Model 2 assesses the total effect of Job-Type (a 6-level variable in the 

residential unit dataset, and a 7-level variable in the all units combined dataset), which explained 

additional variability in floor and window sill dust-lead loadings as anticipated. Job-type is 

nested within intensity level by design. 

In addition to the models assessing the total effect of intensity level and job type, Objective 1-

Models 3 and 4 investigate whether these two variables are still statistically significant predictors 

of floor and window sill dust lead loadings after adjusting for the paint-lead loading on the 

surface being disturbed and a measure of the square feet of lead-based paint disturbed during the 

RRP activity. The summary of results provided in Table 7-1 demonstrate that both IntensityLevel and Job-Type are statistically significant predictors of post-work floor and window sill 

dust-lead loadings in the work room after adjusting for the effects of paint-lead loading and 

square footage disturbed, and the addition of these two variables does not always improve the 

predictive ability of these models. This suggests that these two additional terms may compete 

for explanatory power with intensity-level and job-type. A comparison of the wipe-only dustlead loadings with the measures that integrate the bulk samples did not yield any meaningful 

differences in interpretation of the data. 

The highlighted rows in Table 7-1 indicate the models that appear to fit the data best. Objective 

1-Model 2, which accounted only for job type and COF, performs best for the residential floor 

data and both sets of window sill data. Within the combined floor data, the inclusion of area 

disturbed and average paint lead level improved the model fit slightly with average paint lead 

significantly impacting the floor lead levels. Section O1 of Appendix O contains the residual 

plots from these four best fitting models. The floor model residuals appear to be approximately 

normally distributed. The residuals from the sill models appear to contain some skewness. 
7-4 

Table 7-1: Post-work Work Room Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

Variables 

Included in 

Model p-value 

-2 Log 

Likelihood p-value

-2 Log 

Likelihood p-value

-2 Log 

Likelihood p-value

-2 Log 

Likelihood

Objective 1: Model 1 COF . 756.3 0.20 945.5 . 214.8 0.28 263.8 

Objective 1: Model 1 Intensity level <.01 <.01 <.01 <.01 

Objective 1: Model 2 COF . 726.7 0.05 921.3 . 192.5 0.35 231.3 

Job type <.01 <.01 <.01 <.01 

Objective 1: Model 3 COF . 755.5 0.05 943.2 . 215.2 0.16 269.4 

Objective 1: Model 3 Square feet disturbed 0.34 0.76 0.35 0.95 

Objective 1: Model 3 Avg. paint lead <.01 <.01 <.01 0.10 

Objective 1: Model 3 Intensity level <.01 <.01 <.01 <.01 

Objective 1: Model 4 COF . 731.7 0.03 915.4 . 197.2 0.34 236.1 

Square feet disturbed 0.58 0.82 0.33 0.21 

Avg. paint lead 0.04 <.01 0.35 0.19 

Job type <.01 <.01 <.01 <.01 

Objective 1: Model 1, COF . 954.5 0.67 1222.9 . 228.4 0.28 278.4 

with bulkw Intensity level <.01 <.01 <.01 <.01 

Objective 1: Model 2, COF . 931.0 0.29 1195.3 . 205.9 0.34 247.1 

with bulkwodel 2 Job type <.01 <.01 <.01 <.01 

COF . 952.1 0.20 1222.3 . 228.1 0.15 283.1 

Square feet disturbed 0.57 0.20 0.34 0.89 

Objective 1: Model 3, 

with bulk 

Avg. paint lead <.01 <.01 <.01 0.07 

Objective 1: Model 3 Intensity level <.01 <.01 <.01 0.01 

Objective 1: Model 4, COF . 934.7 0.18 1193.7 . 209.8 0.33 251.1 

with bulk: Model 4 Square feet disturbed 0.55 0.94 0.32 0.22 

Objective 1: Model 4 Avg. paint lead 0.03 <.01 0.33 0.16 

Objective 1: Model 4 Job type <.01 <.01 <.01 <.01 

7.1.2. Post-work Tool Room Dust Lead Levels 

Table 7-2 provides an overview of results from statistical models developed to describe postwork floor and window sill dust-lead loadings in the Tool room across the two subsets of data 

described earlier (residential units only and all units combined). The results are provided for the 

wipe samples only (as there were no bulk samples found in the Tool room). 

Objective 1-Model 5 assesses the total effect of Intensity-Level on floor and window sill dust 

lead loadings, which was shown to be statistically significant in all models. Model 6 assesses the 

total effect of Job-Type, which explained additional variability in floor and window sill dust-lead 

loadings as anticipated. In addition to the models assessing the total effect of intensity level and 

job type, Objective 1-Models 7 and 8 investigate whether these two variables are still statistically 

significant predictors of floor and window sill dust lead loadings after adjusting for the paint-lead 

loading on the surface being disturbed and a measure of the square feet of lead-based paint 

disturbed during the RRP activity. 

The summary of results provided in Table 7-2 demonstrate that both Intensity-Level and JobType are statistically significant predictors of post-work floor and window sill dust-lead loadings 
7-5 

in the Tool room after adjusting for the effects of paint-lead loading and square footage 

disturbed. The addition of these two variables does not always improve the predictive ability of 

these models, which suggests that these two additional terms may compete for explanatory 

power with intensity-level and job-type. 

Models were also developed to assess whether the use of plastic sheeting reduced post-work 

dust-lead loadings observed in the Tool room. Objective 1–Models 9 and 10 provide the results 

of these analyses. Although the use of plastic sheeting did not always result in statistically 

significant reductions in post-work dust lead loadings in the Tool room – inspection of the 

parameter estimates of these models (found in Appendices I through M) reveals that the effect of 

using plastic sheeting results in lower estimated post-work dust lead loadings for the Tool Room 

across all models. The effects of Job-Type and Intensity-Level were found to be statistically 

significant, after adjusting for the use of plastic sheeting in all models applied to dust lead 

loadings in the Tool room at the post-work stage. 

Objective 1–Model 6, which accounts for job type and the differences between residential units 

and the COF, is highlighted in Table 7-2 as the best fitting model for all four data sets. Although 

the log-likelihoods are slightly lower for Objective 1–Model 10, that model also included an 

additional variable, which did not lead to much gain in the likelihood statistic and was not 

significant. Although use of plastic was not statistically significant, the detailed results of this 

model in Table L2 report that combined floor lead levels are 0.32 units lower on the log scale 

when plastic was used, which equates to geometric means predicted to be 27% lower when 

plastic was used than when it was not used. Section O2 of Appendix O contains the residual 

plots from these best fitting models, which all indicate reasonable normal distributions. 

Table 7-2: Post-Work Tool Room Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

Variables Included in 

Model p-value

-2 Log 

Likelihood p-value

-2 Log 

Likelihood p-value 

-2 Log 

Likelihood p-value

-2 Log 

Likelihood

Objective 1: Model 5 COF . 328.1 0.36 436.3 . 176.4 0.32 212.0 

Objective 1: Model 5 Intensity level <.01 <.01 0.03 0.01 

Objective 1: Model 6 COF . 306.5 0.31 413.4 . 164.0 0.21 198.2 

Job type <.01 <.01 0.02 0.02 

Objective 1: Model 7 COF . 334.6 0.21 441.9 . 172.0 0.07 211.1 

Objective 1: Model 7 Square feet disturbed 0.78 0.78 0.09 0.18 

Objective 1: Model 7 Avg. paint lead 0.06 0.02 <.01 <.01 

Objective 1: Model 7 Intensity level <.01 <.01 <.01 0.01 

Objective 1: Model 8 COF . 311.7 0.25 417.2 . 164.9 0.12 199.6 

Objective 1: Model 8 Square feet disturbed 0.07 0.32 0.50 0.72 

Objective 1: Model 8 Avg. paint lead 0.49 0.01 <.01 <.01 

Objective 1: Model 8 Job type <.01 <.01 0.04 0.03 

Objective 1: Model 9 COF . 326.0 0.36 435.2 . 175.2 0.32 212.0 

Objective 1: Model 9 Plastic 0.12 0.19 0.32 0.60 

Objective 1: Model 9 Intensity level <.01 <.01 0.02 0.01 

Objective 1: Model 10 COF . 305.0 0.31 412.7 . 163.1 0.22 198.3 

Objective 1: Model 10 Plastic 0.16 0.20 0.37 0.66 

Objective 1: Model 10 Job type <.01 <.01 0.02 0.02 
7-6 

7.1.3. Post-Work Observation Room Dust Lead Levels 

Table 7-3 provides an overview of results from statistical models developed to describe postwork floor and window sill dust-lead loadings in the Observation room across both residential 

units only and all units combined. The results are provided for the wipe samples only as there 

were no bulk samples found in the Observation room. 

As in the other two rooms, both intensity level and job type are statistically significant when 

assessed by themselves – in Objective 1-Model 11, and Objective 1-Model 12, respectively. 

Again Job Type performs better than intensity level in explaining more variability in the floor 

and window sill dust-lead loadings as anticipated, achieving lower log-likelihood ratios. 

Objective 1-Models 13 and 14 investigate whether intensity level and job type were still 

statistically significant predictors of floor and window sill dust lead loadings after adjusting for 

the paint-lead loading on the surface being disturbed and area disturbed during the RRP activity. 

The summary of results provided in Table 7-3 demonstrate that both Intensity-Level and JobType are statistically significant predictors of post-work floor and window sill dust-lead loadings 

in the work room after adjusting for the effects of paint-lead loading and square footage 

disturbed. The addition of these two variables improved the predictive ability for floors, but not 

for window sills. Furthermore, average paint-lead loading on components disrupted by the RRP 

activity was a statistically significant predictor of dust-lead levels found in the Observation room 

in the post-work stage in most of the models. 

Models were also developed to assess whether the use of plastic sheeting reduced dust-lead 

loadings found in the Observation room in the post work stage. Objective 1–Models 15 and 16 

provide the results of theses analyses. The use of plastic sheeting resulted in statistically 

significant reductions in post-work floor lead loadings in the Observation room for residential 

units only. This effect was only borderline significant in the combined data (p-value=.10), which 

included the COFs. 

The detailed results in Table L3 of Appendix L report floor lead levels from the combined model 

0.46 units less when plastic was used, which equates to a predicted GM 36.9% lower than when 

plastic was not used. The use of plastic sheeting did not significantly lower window sill dust 

lead loadings in the Observation room at the post-work stage. The effects of Job-Type and 

Intensity-Level were found to be statistically significant, after adjusting for the use of plastic 

sheeting in all models applied to dust lead loadings in the observation room at the post-work 

stage. 

The best-fitting models differed across data sets for the post-work Observation room data. As 

highlighted in Table 7-3, the model adjusting for plastic use in addition to job type performed 

best for residential floors, while in the combined data the model adjusting for paint lead level and 

area disturbed performed better. For window sills, the model adjusting only for job type 

performed best. Section O3 of Appendix O contains the residual plots from these best fitting 

models, which indicate reasonable normal distributions for floors and some skewness for sills. If 

additional analyses are performed, these can be investigated further to determine impact of 

outliers in the window sill data. 
7-7 

Table 7-3: Post-Work Observation Room Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

Variables Included 

in Model p-value 

-2 Log 

Likelihood

pvalue-2 Log 

Likelihood p-value 

-2 Log 

Likelihood p-value

-2 Log 

Likelihood

Objective 1: Model 11 COF . 304.3 0.78 368.6 . 161.7 0.23 191.3 

Objective 1: Model 11 Intensity level <.01 <.01 0.02 0.01 

Objective 1: Model 12 COF . 285.8 0.85 350.1 . 151.9 0.35 179.0 

Job type <.01 <.01 0.04 0.02 

Objective 1: Model 13 COF . 300.6 0.24 362.9 . 165.3 0.09 197.5 

Objective 1: Model 13 Square feet disturbed 0.53 0.58 0.24 0.64 

Objective 1: Model 13 Avg. paint lead <.01 <.01 <.01 0.02 

Objective 1: Model 13 Intensity level <.01 <.01 0.03 0.03 

Objective 1: Model 14 COF . 285.3 0.54 344.5 . 158.1 0.23 184.5 

Square feet disturbed 0.18 0.50 0.97 0.79 

Avg. paint lead <.01 <.01 0.09 0.03 

Job type <.01 <.01 0.09 0.03 

Objective 1: Model 15 COF . 298.8 0.78 366.1 . 161.9 0.24 191.9 

Objective 1: Model 15 Plastic 0.02 0.09 0.83 0.79 

Objective 1: Model 15 Intensity level <.01 <.01 0.02 0.02 

Objective 1: Model 16 COF . 280.4 0.86 348.1 . 152.1 0.35 179.6 

Plastic 0.02 0.10 0.80 0.81 

Job type <.01 <.01 0.04 0.03 

7.2. Post Cleaning Stage - Dust Lead Levels 

The following three subsections provide an overview of statistical modeling results for floor and 

window sill dust lead loadings in the post-cleaning stage of the field study, in the Work room 

(subsection 7.2.1), Tool room (subsection 7.2.2), and Observation room (subsection 7.2.3). 

7.2.1. Post-Cleaning Work Room Dust Lead Levels 

Table 7-4 provides an overview of results from statistical models developed to describe postcleaning floor and window sill dust lead loadings in the work room for residential units only and 

all units combined. The results are provided for the wipe samples only (as there were no bulk 

samples after the post-work stage). Below are some highlights of some of the models run for 

these data. 

• Objective 1-Models 17 and 18 assess the total effects of Intensity-Level and Job-Type, 

respectively, on floor and window sill dust lead loadings in the Work room during the 

post-cleaning stage. Intensity-Level and Job-Type were shown to be statistically 

significant in all models. 

• Objective 1-Models 19 and 20 investigate whether intensity level and job type are still 

statistically significant predictors of floor and window sill dust lead loadings after 

adjusting for the paint lead loading on the surface being disturbed and a measure of the 

square feet of lead-based paint disturbed during the RRP activity. The results in Table 7-

4 demonstrate that both Intensity-Level and Job-Type remain statistically significant 

predictors of post-cleaning floor dust lead loadings in the Work room after adjusting for 

the effects of paint lead loading and square footage disturbed. While average paint lead 

loading was found to be a significant predictor of post-cleaning floor dust lead loadings 
7-8 

in the Work room – Models 19 and 20 did not improve the prediction over Models 17 and 

18, as evidenced by a comparison of the log-likelihoods. Models 19 and 20 applied to the 

window sill dust lead loadings demonstrate that the addition of these two variables 

(average paint-lead loading and square footage disturbed) competes with intensity-level 

and job-type for predictive power, without improving the model fit. 

• Objective 2–Model 1 assesses the total effect of using plastic sheeting on post-cleaning 

dust lead levels in the work room, which was not a statistically significant predictor (on 

its own) in any of the models applied to floor and window sill dust lead levels. 

Inspection of the parameter estimates from these models in Appendices I through M, 

however, demonstrates that use of plastic sheeting was consistently associated with lower 

predicted post-cleaning dust lead levels in the Work room. 

• Objective 2–Models 2 through 5 assess whether the use of plastic is significant after 

adjusting for intensity-level or job-type, and whether there is any significant interaction 

between the use of plastic and either intensity-level or job-type when predicting floor and 

window sill dust lead loadings following cleaning in the work room. These results follow 

the same general trend as observed in Objective 2–Model 1, in which the use of plastic 

sheeting was not statistically significant, but inspection of the parameter estimates is 

suggestive of a modest protective effect. 

• Objective 3–Model 1 assesses the total effect of using RRP rule cleaning on postcleaning dust-lead levels in the Work room, which was highly statistically significant in 

lowering dust lead loadings in all of the models. 

• Objective 3–Models 2 through 5 assess whether the use of RRP rule cleaning is 

significant after adjusting for intensity-level or job-type, and whether there is any 

significant interaction between the use of RRP rule cleaning and either intensity-level or 

job-type when predicting floor and window sill dust lead loadings following cleaning in 

the Work room. The use of RRP rule cleaning was highly significant in all models, even 

after adjusting for intensity-level or job-type. The addition of the interaction term 

between RRP rule cleaning and either intensity-level or job-type did not significantly 

improve the prediction of the model – suggesting that the effectiveness of RRP rule 

cleaning does not change as a function of intensity level or job type. 

• The remaining models fit to the post-cleaning stage in the Work room investigate the 

simultaneous effects of using plastic sheeting and RRP rule cleaning by adding both of 

these terms and their interaction to the model. Objective 1 – Models 21 and 22 explore 

the interactive effects of plastic sheeting and RRP rule cleaning on dust lead loadings 

after adjusting for the effects of intensity-level (21) and job-type (22). Objective Y – 

Models 1 and 2 build further on these models by also adjusting for average paint lead 

loading, which was found to be a significant predictor in previously described models. 

The results suggest that Model 22, which explains floor dust lead loading as a function of jobtype, plastic sheeting, RRP rule cleaning, and the interaction between plastic sheeting and RRP 

rule cleaning, provides the best fit for the floor data. In this model, post-cleaning work room 

floor dust lead loadings were lowest in the experiments that combined both proposed rule 

cleaning and the use of plastic sheeting, next lowest for experiments that just the proposed RRP 

rule cleaning but not plastic, followed by experiments that only employed the use of plastic. 

Each of these three combinations resulted in significantly lower floor dust lead loadings than 
7-9 

found in experiments that had baseline cleaning and no use of plastic, as seen in the detailed 

parameter estimates found in Table I4 of Appendix I and Table L4 of Appendix L. 

For window sills, the results suggest that Objective 3–Model 5 provides the best fit by adjusting 

for job type, cleaning method, and their interaction. It makes sense that use of plastic would 

have less impact on window sills, as the plastic did not cover the sills as it did floors. Table J4 of 

Appendix J and Table M4 of Appendix M contain the detailed parameter estimates for this 

model. Looking at some of the models that explores the differences between phases, such as 

Objective Y-Model 2, the results indicate that the window sill dust lead loadings were only found 

to be significantly lower for the experiments that employed proposed rule cleaning and use of 

plastic on its own did not yield statistically significant lower window sill dust lead loadings. 

Section O4 of Appendix O contains the residual plots from some of the best-fitting models, 

which indicate reasonably normal distributions for floors and some skewness for sills. If 

additional analyses are performed, these can be investigated further to determine potential causes 

of normality in these residuals. 

Table 7-4: Post-Cleaning Work Room Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

 

Variables Included in 

Model p-value

-2 Log 

Likelihood

pvalue-2 Log 

Likelihood p-value 

-2 Log 

Likelihood p-value

-2 Log 

Likelihood

Objective 1: Model 17 COF . 529.6 0.16 646.6 . 173.6 0.45 208.5 

Objective 1: Model 17 Intensity level <.01 <.01 0.14 0.07 

Objective 1: Model 18 COF . 513.4 <.01 634.4 . 164.1 0.21 197.8 

Objective 1: Model 18 Job type <.01 <.01 0.14 0.15 

Objective 1: Model 19 COF . 529.2 0.02 646.5 . 178.8 0.33 216.1 

Objective 1: Model 19 Square feet disturbed 0.60 0.90 0.18 0.32 

Objective 1: Model 19 Avg. paint lead <.01 <.01 0.05 0.16 

Objective 1: Model 19 Intensity level <.01 <.01 0.10 0.08 

Objective 1: Model 20 COF . 516.8 <.01 630.5 . 171.2 0.15 205.7 

Objective 1: Model 20 Square feet disturbed 0.89 0.65 0.54 0.55 

Objective 1: Model 20 Avg. paint lead <.01 <.01 0.26 0.21 

Objective 1: Model 20 Job type <.01 <.01 0.25 0.17 

Objective 1: Model 21 COF . 510.2 0.01 623.0 . 162.8 0.29 195.6 

Objective 1: Model 21 Avg. paint lead <.01 <.01 0.09 0.06 

Objective 1: Model 21 Clean*Plastic <.01 <.01 0.02 <.01 

Objective 1: Model 21 Intensity level <.01 <.01 0.11 0.03 

Objective 1: Model 22 COF . 499.0 <.01 607.4 . 153.4 0.15 184.1 

Avg. paint lead <.01 <.01 0.29 0.10 

Clean*Plastic <.01 <.01 0.02 <.01 

Job type <.01 <.01 0.12 0.05 

Objective 2: Model 1 COF . 542.7 0.19 661.6 . 176.8 0.43 213.8 

Objective 2: Model 1 Plastic 0.38 0.37 0.22 0.48 

Objective 2: Model 2 COF . 527.2 0.17 644.9 . 171.4 0.44 208.0 

Objective 2: Model 2 Intensity level <.01 <.01 0.10 0.06 

Objective 2: Model 2 Plastic 0.08 0.11 0.15 0.37 

Objective 2: Model 3 COF . 521.6 0.18 639.2 . 165.3 0.45 202.9 

Objective 2: Model 3 Intensity level <.01 <.01 0.08 0.05 

Plastic 0.03 0.05 0.15 0.37 

Intensity level*Plastic 0.15 0.10 0.25 0.28 
7-10 

Table 7-4: (continued) Post-Cleaning Work Room Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

Variables Included in 

Model p-value

-2 Log 

Likelihood

pvalue-2 Log 

Likelihood p-value 

-2 Log 

Likelihood p-value

-2 Log 

Likelihood

Objective 2: Model 4 COF . 511.7 0.01 633.4 . 162.1 0.21 197.5 

Objective 2: Model 4 Job type <.01 <.01 0.12 0.15 

Objective 2: Model 4 Plastic 0.14 0.18 0.17 0.41 

Objective 2: Model 5 COF . 495.2 0.01 614.8 . 147.1 0.23 179.5 

Job type <.01 <.01 0.14 0.16 

Plastic 0.15 0.52 0.16 0.44 

Job type*Plastic 0.10 0.13 0.56 0.46 

Objective 3: Model 1 COF . 538.1 0.21 656.1 . 171.8 0.41 203.5 

Objective 3: Model 1 Clean 0.02 <.01 0.01 <.01 

Objective 3: Model 2 COF . 523.5 0.20 639.5 . 167.0 0.42 197.5 

Objective 3: Model 2 Intensity level <.01 <.01 0.12 0.04 

Objective 3: Model 2 Clean <.01 <.01 0.01 <.01 

Objective 3: Model 3 COF . 521.2 0.21 636.6 . 161.6 0.42 194.3 

Objective 3: Model 3 Intensity level <.01 <.01 0.14 0.05 

Objective 3: Model 3 Clean <.01 <.01 0.01 <.01 

Objective 3: Model 3 Intensity level*Clean 0.76 0.41 0.27 0.54 

Objective 3: Model 4 COF . 506.1 <.01 627.0 . 156.1 0.19 185.2 

Objective 3: Model 4 Job type <.01 <.01 0.07 0.05 

Objective 3: Model 4 Clean <.01 <.01 <.01 <.01 

Objective 3: Model 5 COF . 494.9 <.01 614.0 . 140.9 0.19 169.5 

Job type <.01 <.01 0.08 0.08 

Clean <.01 <.01 <.01 <.01 

Job type*Clean 0.57 0.58 0.36 0.47 

Objective Y: Model 1 COF . 509.9 0.11 621.8 . 155.4 0.72 186.3 

Objective Y: Model 1 Intensity level 0.74 0.75 0.49 0.61 

Objective Y: Model 1 

Avg. PostWork Work 

Floor Lead <.01 <.01 <.01 <.01 

Objective Y: Model 1 Clean*Plastic 0.01 <.01 0.03 <.01 

Objective Y: Model 2 COF . 500.4 0.02 615.6 . 148.4 0.37 177.4 

Objective Y: Model 2 Job type 0.08 0.64 0.55 0.57 

Objective Y: Model 2 

Avg. PostWork Work 

Floor Lead 0.04 <.01 0.03 <.01 

Objective Y: Model 2 Clean*Plastic 0.01 <.01 0.02 <.01 

7.2.2. Post-Cleaning Tool Room Dust Lead Levels 

Table 7-5 provides an overview of results from statistical models developed to describe postcleaning floor and window sill dust-lead loadings in the Tool room across residential units only 

and all units combined. The results provided are for wipe samples only as there were no bulk 

samples found in the Tool room. The bullets below summarize the various models tested. 

• Objective 1-Models 23 and 24 assess the total effects of Intensity-Level and Job-Type, 

respectively, on floor and window sill dust lead loadings in the Tool room during the 

post-cleaning stage. Intensity-Level and Job-Type were shown to be statistically 

significant in all models. 

• Regarding Objective 1-Models 25 and 26, the results provided in Table 7-5 demonstrate 

that both Intensity-Level and Job-Type remain statistically significant predictors of post 
7-11 

cleaning floor dust-lead loadings in the Tool room after adjusting for the effects of paint 

lead loading and square footage disturbed. While average paint-lead loading was found 

to be a significant predictor of post-cleaning floor and window sill dust lead loadings in 

the Tool room for most of the models – Models 25 and 26 did not improve the prediction 

over Models 23 and 24, as evidenced by a comparison of the log-likelihoods. 

• Objective 2–Model 6 assesses the total effect of using plastic sheeting on post-cleaning 

dust lead levels in the tool room, which was not a statistically significant predictor (on its 

own) in any of the models applied to floor and window sill dust lead levels. Inspection of 

the parameter estimates from these models in Appendices I through M, however, 

demonstrates that use of plastic sheeting is consistently associated with lower predicted 

post-cleaning dust-lead levels in the Tool room. 

• Objective 2–Models 7 through 10 assess whether the use of plastic is significant after 

adjusting for intensity-level or job-type, and whether there is any significant interaction 

between the use of plastic and either intensity-level or job-type when predicting floor and 

window sill dust lead loadings following cleaning in the Work room. The results of these 

analyses suggest that there may be a significant interaction between the use of plastic and 

job-type when explaining both floor and window sill dust-lead loadings in the tool room 

following cleaning – and that these models provided the best fit of the data compared to 

any of the remaining models described below. 

• Objective 3–Model 6 assesses the total effect of using the proposed Rule cleaning on 

post-cleaning dust lead levels in the Tool room, and Objective 3–Models 7 through 10 

assess this effect after adjusting for intensity and job-type and their interaction with 

cleaning method. As anticipated, the method of cleaning applied in the Work room did 

not influence floor or window sill dust lead levels in the Tool room. 

• The remaining models fit to the post-cleaning stage in the Tool room investigate the 

simultaneous effects of using plastic sheeting and proposed rule cleaning by adding both 

of these terms and their interaction to the model. These models did not improve upon the 

models that simply adjusted for the interaction between use of plastic and job-type. 

As noted above, Objective2-Model 10 provided the best fit for all four data sets – residential 

floors and sills and combined floors and sills. Although use of plastic is not found to be 

significant by this model, there are significant or borderline significant interactions between job 

type and use of plastic for the floor data. Section O5 in Appendix O contains residual plots for 

these models, which all are reasonably normally distributed. 
7-12 

Table 7-5: Post-Cleaning Tool Room Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

Variables Included in 

Model p-value

-2 Log 

Likelihood

pvalue-2 Log 

Likelihood p-value 

-2 Log 

Likelihood p-value

-2 Log 

Likelihood

Objective 1: Model 23 COF . 315.6 0.40 411.6 . 171.4 0.25 204.9 

Objective 1: Model 23 Intensity level <.01 <.01 0.05 0.04 

Objective 1: Model 24 COF . 297.9 0.39 392.8 . 157.9 0.24 189.8 

Objective 1: Model 24 Job type <.01 <.01 0.02 0.02 

Objective 1: Model 25 COF . 319.0 0.08 415.4 . 168.7 0.05 205.8 

Objective 1: Model 25 Square feet disturbed 0.91 0.97 0.06 0.10 

Objective 1: Model 25 Avg. paint lead <.01 <.01 <.01 <.01 

Objective 1: Model 25 Intensity level <.01 <.01 <.01 0.01 

Objective 1: Model 26 COF . 300.2 0.26 392.2 . 160.8 0.15 194.0 

Objective 1: Model 26 Square feet disturbed 0.08 0.20 0.97 0.83 

Objective 1: Model 26 Avg. paint lead 0.11 <.01 0.02 0.02 

Objective 1: Model 26 Job type <.01 <.01 0.03 0.03 

Objective 1: Model 27 COF . 309.2 0.21 405.9 . 161.0 0.08 197.5 

Objective 1: Model 27 Avg. paint lead 0.01 <.01 <.01 <.01 

Objective 1: Model 27 Clean*Plastic 0.54 0.52 0.36 0.31 

Objective 1: Model 27 Intensity level <.01 <.01 0.02 0.01 

Objective 1: Model 28 COF . 294.3 0.27 385.5 . 151.1 0.12 184.3 

Objective 1: Model 28 Avg. paint lead 0.05 <.01 0.02 0.01 

Objective 1: Model 28 Clean*Plastic 0.53 0.40 0.44 0.32 

Objective 1: Model 28 Job type <.01 <.01 0.03 0.02 

Objective 2: Model 6 COF . 328.0 0.41 424.5 . 176.4 0.23 210.3 

Objective 2: Model 6 Plastic 0.34 0.42 0.20 0.20 

Objective 2: Model 7 COF . 312.5 0.40 410.3 . 168.7 0.24 202.7 

Objective 2: Model 7 Intensity level <.01 <.01 0.03 0.02 

Objective 2: Model 7 Plastic 0.07 0.18 0.11 0.12 

Objective 2: Model 8 COF . 305.6 0.41 404.3 . 160.7 0.25 198.2 

Objective 2: Model 8 Intensity level <.01 <.01 0.04 0.03 

Objective 2: Model 8 Plastic 0.16 0.29 0.24 0.18 

Objective 2: Model 8 Intensity level*Plastic 0.14 0.15 0.10 0.36 

Objective 2: Model 9 COF . 295.5 0.39 391.9 . 155.5 0.24 187.9 

Objective 2: Model 9 Job type <.01 <.01 0.01 0.02 

Objective 2: Model 9 Plastic 0.10 0.20 0.12 0.13 

Objective 2: Model 10 COF . 277.4 0.42 370.5 . 137.8 0.27 168.7 

Job type <.01 <.01 0.01 0.02 

Plastic 0.30 0.52 0.40 0.44 

Job type*Plastic 0.06 0.04 0.16 0.21 

Objective 3: Model 6 COF . 329.0 0.42 425.2 . 178.1 0.25 212.0 

Objective 3: Model 6 Clean 0.96 0.77 0.77 0.97 

Objective 3: Model 7 COF . 315.8 0.41 412.1 . 171.2 0.25 205.3 

Objective 3: Model 7 Intensity level <.01 <.01 0.05 0.04 

Objective 3: Model 7 Clean 0.91 0.72 0.61 0.90 

Objective 3: Model 8 COF . 311.7 0.41 408.2 . 168.0 0.26 202.9 

Objective 3: Model 8 Intensity level <.01 <.01 0.07 0.05 

Objective 3: Model 8 Clean 0.83 0.73 0.68 0.91 

Objective 3: Model 8 Intensity level*Clean 0.57 0.43 0.97 0.98 
7-13 

Table 7-5: (continued) Post-Cleaning Tool Room Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

Variables Included in 

Model p-value

-2 Log 

Likelihood

pvalue-2 Log 

Likelihood p-value 

-2 Log 

Likelihood p-value

-2 Log 

Likelihood

Objective 3: Model 9 COF . 298.1 0.41 392.9 . 158.0 0.24 190.2 

Objective 3: Model 9 Job type <.01 <.01 0.02 0.02 

Objective 3: Model 9 Clean 0.81 0.40 0.89 0.79 

Objective 3: Model 10 COF . 285.6 0.41 379.3 . 146.5 0.24 176.7 

Objective 3: Model 10 Job type <.01 <.01 0.03 0.03 

Objective 3: Model 10 Clean 0.97 0.70 0.97 0.68 

Objective 3: Model 10 Job type*Clean 0.62 0.69 0.92 0.85 

Objective Y: Model 3 COF . 308.5 0.51 402.0 . 165.0 0.43 197.5 

Objective Y: Model 3 Intensity level 0.25 0.12 0.80 0.92 

Objective Y: Model 3 

Avg. PostWork Work 

Floor Lead <.01 <.01 0.01 <.01 

Objective Y: Model 3 Plastic 0.23 0.22 0.19 0.12 

Objective Y: Model 4 COF . 296.9 0.48 391.2 . 155.5 0.36 186.1 

Objective Y: Model 4 Job type 0.04 0.06 0.39 0.43 

Objective Y: Model 4 

Avg. PostWork Work 

Floor Lead 0.62 0.08 0.21 0.05 

Objective Y: Model 4 Plastic 0.14 0.24 0.18 0.14 

7.2.3. Post-Cleaning Observation Room Dust Lead Levels 

Table 7-6 provides an overview of statistical modeling results post-cleaning floor and window 

sill dust-lead loadings in the Observation room across the residential units only and all units 

combined data sets. The results are provided for wipe samples only as there were no bulk 

samples found in the Observation room. The bullets below summarize findings from the various 

models. 

• Objective 1-Models 29 and 30 assess the total effects of Intensity-Level and Job-Type, 

respectively, on floor and window sill dust lead loadings in the work room during the 

post-cleaning stage. Intensity-Level and Job-Type were shown to be statistically 

significant in all models. 

• Objective 1-Models 31 and 32 investigate whether intensity level and job type are still 

statistically significant predictors of floor and window sill dust lead loadings after 

adjusting for the paint lead loading on the surface being disturbed and a measure of the 

square feet of lead-based paint disturbed during the RRP activity. The summary of 

results provided in Table 7-6 demonstrates that both Intensity-Level and Job-Type remain 

statistically significant predictors of post-cleaning floor dust-lead loadings in the 

Observation room after adjusting for the effects of paint lead loading and square footage 

disturbed. While average paint-lead loading was found to be a significant predictor of 

post-cleaning floor and window sill dust lead loadings in the Observation room in all of 

the models – these more complex models did not always improve the prediction over 

Models 29 and 30, suggesting that these terms may compete with intensity-level and jobtype for explanatory power. 

• Objective 2–Model 11 assesses the total effect of using plastic sheeting on post-cleaning 

dust-lead levels in the observation room, which a statistically significant predictor for 

floors in residential units (p-value = 0.03, estimate of -0.97) and nearly significant for all 
7-14 

units (p-value = 0.06). The total effect of plastic on lowering window sill dust lead levels 

in the Observation room was borderline significant (p-value of 0.10 in residential units 

and 0.12 in all units combined). 

• Objective 2–Models 12 through 15 assess whether the use of plastic was significant after 

adjusting for intensity-level or job-type, and whether there was any significant interaction 

between the use of plastic and either intensity-level or job-type when predicting floor and 

window sill dust lead loadings following cleaning in the work room. Although the F-test 

associated with the interaction term was not statistically significant across any of these 

models, Objective 2 – Model 15 provided the best fit of the data across floors and 

window sills within both subsets of data explored. 

• Objective 3–Model 11 assesses the total effect of using the proposed Rule cleaning 

method on post-cleaning dust-lead levels in the Observation room, and Objective 3–

Models 12 through 15 assess this effect after adjusting for intensity and job-type and their 

interaction with cleaning method. As in the Tool room, the method of cleaning applied in 

the Work room did not influence floor or window sill dust lead levels in the Observation 

room. 

• The remaining models fit to the post-cleaning stage in the Observation room investigate 

the simultaneous effects of using plastic sheeting and RRP rule cleaning by adding both 

of these terms and their interaction to the model. These models did not significantly 

improve upon the models that simply adjusted for the interaction between use of plastic 

and job-type. 

As noted above, Objective2-Model 15 provided the best fit for all four data sets – residential 

floors and sills and combined floors and sills. Although use of plastic is not found to be 

significant by this model, there are significant or borderline significant interactions between job 

type and use of plastic for the floor data. Section O6 in Appendix O contains residual plots for 

these models, which all are reasonably normally distributed. 

Table 7-6: Post-Cleaning Observation Room Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

Variables Included in 

Model p-value

-2 Log 

Likelihood p-value

-2 Log 

Likelihood

pvalue -2 Log 

Likelihood p-value

-2 Log 

Likelihood

Objective 1: Model 29 COF . 298.7 0.61 363.3 . 154.6 0.22 179.5 

Objective 1: Model 29 Intensity level <.01 <.01 0.08 0.07 

Objective 1: Model 30 COF . 281.6 0.50 349.0 . 137.5 0.33 157.1 

Objective 1: Model 30 Job type <.01 <.01 <.01 <.01 

Objective 1: Model 31 COF . 294.3 0.26 356.8 . 154.2 0.07 185.1 

Objective 1: Model 31 Square feet disturbed 0.28 0.23 0.19 0.43 

Objective 1: Model 31 Avg. paint lead <.01 <.01 <.01 0.01 

Objective 1: Model 31 Intensity level <.01 <.01 0.04 0.09 

Objective 1: Model 32 COF . 283.6 0.36 344.6 . 138.5 0.28 160.0 

Objective 1: Model 32 Square feet disturbed 0.79 0.80 0.15 0.03 

Objective 1: Model 32 Avg. paint lead <.01 <.01 0.04 0.09 

Objective 1: Model 32 Job type <.01 <.01 <.01 <.01 

Objective 1: Model 33 COF . 277.9 0.24 343.1 . 145.0 0.09 175.5 

Objective 1: Model 33 Avg. paint lead <.01 <.01 <.01 0.02 

Clean*Plastic 0.01 0.03 0.26 0.25 

Intensity level <.01 <.01 0.03 0.04 
7-15 

Table 7-6: (continued) Post-Cleaning Observation Room Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

Variables Included in 

Model p-value

-2 Log 

Likelihood p-value

-2 Log 

Likelihood

pvalue -2 Log 

Likelihood p-value

-2 Log 

Likelihood

Objective 1: Model 34 COF . 265.7 0.37 330.4 . 130.9 0.25 155.8 

Avg. paint lead <.01 <.01 0.02 0.05 

Clean*Plastic <.01 0.03 0.26 0.22 

Job type <.01 <.01 <.01 <.01 

Objective 2: Model 11 COF . 311.1 0.69 376.7 . 156.8 0.19 182.2 

Plastic 0.03 0.06 0.10 0.12 

Objective 2: Model 12 COF . 288.9 0.59 358.1 . 150.5 0.22 176.7 

Objective 2: Model 12 Intensity level <.01 <.01 0.02 0.03 

Objective 2: Model 12 Plastic <.01 0.02 0.03 0.06 

Objective 2: Model 13 COF . 286.3 0.60 355.1 . 147.2 0.22 174.1 

Objective 2: Model 13 Intensity level <.01 <.01 0.05 0.05 

Objective 2: Model 13 Plastic <.01 0.03 0.07 0.09 

Objective 2: Model 13 Intensity level*Plastic 0.75 0.63 0.61 0.55 

Objective 2: Model 14 COF . 270.8 0.72 343.4 . 133.4 0.34 154.0 

Objective 2: Model 14 Job type <.01 <.01 <.01 <.01 

Objective 2: Model 14 Plastic <.01 0.01 0.03 0.04 

Objective 2: Model 15 COF . 259.7 0.74 326.6 . 120.9 0.35 139.4 

Job type <.01 <.01 <.01 <.01 

Plastic <.01 0.06 0.14 0.20 

Job type*Plastic 0.62 0.27 0.36 0.22 

Objective 3: Model 11 COF . 316.1 0.72 380.2 . 159.3 0.21 184.4 

Objective 3: Model 11 Clean 0.75 0.81 0.60 0.60 

Objective 3: Model 12 COF . 298.5 0.62 363.6 . 154.7 0.22 180.1 

Objective 3: Model 12 Intensity level <.01 <.01 0.08 0.07 

Objective 3: Model 12 Clean 0.49 0.61 0.54 0.55 

Objective 3: Model 13 COF . 294.2 0.62 360.7 . 151.6 0.22 178.1 

Objective 3: Model 13 Intensity level <.01 <.01 0.11 0.09 

Objective 3: Model 13 Clean 0.50 0.61 0.49 0.51 

Objective 3: Model 13 Intensity level*Clean 0.44 0.66 0.66 0.69 

Objective 3: Model 14 COF . 281.9 0.50 349.6 . 138.3 0.33 158.3 

Objective 3: Model 14 Job type <.01 <.01 <.01 <.01 

Objective 3: Model 14 Clean 0.66 0.84 0.92 0.95 

Objective 3: Model 15 COF . 269.3 0.51 335.9 . 127.8 0.30 147.9 

Objective 3: Model 15 Job type <.01 <.01 0.02 <.01 

Objective 3: Model 15 Clean 0.63 0.76 0.77 0.85 

Objective 3: Model 15 Job type*Clean 0.55 0.71 0.65 0.68 

Objective Y: Model 5 COF . 284.4 0.92 351.4 . 148.5 0.36 173.1 

Objective Y: Model 5 Intensity level 0.02 0.04 0.81 0.84 

Objective Y: Model 5 

Avg. PostWork Work 

Floor Lead <.01 <.01 0.03 0.01 

Objective Y: Model 5 Plastic <.01 0.01 0.08 0.06 

Objective Y: Model 6 COF . 272.4 0.99 340.2 . 134.6 0.44 155.1 

Objective Y: Model 6 Job type <.01 0.02 0.04 0.01 

Objective Y: Model 6 

Avg. PostWork Work 

Floor Lead 0.51 0.02 0.32 0.23 

Objective Y: Model 6 Plastic <.01 0.01 0.05 0.04 
7-16 

7.3. Post-Verification Stage Dust Lead Levels 

The following three subsections provide an overview of statistical modeling results for floor and 

window sill dust lead loading results in the post-verification stage of the field study, in the Work 

room (subsection 7.3.1), Tool room (subsection 7.3.2), and Observation room (subsection 7.3.3). 

7.3.1. Post-Verification Work Room Dust Lead Levels 

Table 7-7 provides an overview of results from statistical models developed to describe postverification floor and window sill dust lead loadings in the work room across the two subsets of 

data described earlier (residential units only and all units combined). Detailed floor and sill 

modeling results are contained in Appendices I through M. It is important to keep in mind when 

considering the Work room data at the post-verification stage that zones of the work room that 

failed a cleaning verification step underwent recleaning using the proposed Rule cleaning 

method, regardless of which cleaning method was used at the post-cleaning stage. The bullets 

below summarize the various models run to explore the post-verification Work room data. 

• Objective 1-Models 35 and 36 indicate that Intensity-Level and Job-Type were shown to 

be statistically significant predictors of post-verification floor dust lead loadings – but not 

significant predictors of window sill dust-lead loadings. 

• Objective 1-Models 37 and 38 demonstrate that intensity-level and job-type are still 

statistically significant predictors of floor dust lead loadings after adjusting for the paintlead loading on the surface being disturbed and a measure of the square feet of lead-based 

paint disturbed during the RRP activity. Average paint-lead loading was found to be a 

significant predictor of post-verification floor dust lead loadings in the Work room. None 

of the variables in Models 37 and 38 appeared significantly predictive of window sill 

dust-lead loadings in the Work room following verification. 

• The remaining models fit to the post-verification dust lead loadings in the Work room 

were largely unremarkable – with the remaining variables (use of plastic, cleaning 

method, etc.) failing to explain a major portion of variability in post-verification dust lead 

results. This result suggests that the verification step acts as an equalizer – removing the 

factors that previously explained elevated dust lead levels in earlier phases of the 

experiment. 

• The fact that intensity-level, job-type, and average paint lead loading are still predictive 

of post-verification floor dust-lead levels may be a concern. On the other hand, over half 

of all experiments ended with the average post-verification floor lead levels below 40 

μg/ft2

 indicating that the various cleaning techniques utilized were able to return floor 

levels to a clean condition in the majority of experiments. 

Objective 3-Model 20 provided the best fit for three of the four data sets – residential floors and 

residential and combined sills. This model adjusted for cleaning method, job type, and their 

interaction. This model performed well for the combined floor data set as well, but Objective 1-

Model 40, which adjusted for phase (Clean*Plastic) and average paint lead, may have performed 

slightly better. Cleaning method was no longer significant at the post-verification stage. Section 

O7 in Appendix O contains residual plots for these models. The residuals from the floor models 

are normally distributed, although there does appear to be an outlier on the upper end of the 

distribution. The sill models appear to contain some skewness in the residuals. 
7-17 

Table 7-7: Post-Verification Work Room Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

Variables Included in 

Model p-value

-2 Log 

Likelihood p-value

-2 Log 

Likelihood p-value 

-2 Log 

Likelihood

pvalue-2 Log 

Likelihood

Objective 1: Model 35 COF . 542.0 0.16 640.6 . 167.9 0.33 194.3 

Objective 1: Model 35 Intensity level <.01 <.01 0.27 0.10 

Objective 1: Model 36 COF . 520.1 <.01 627.8 . 155.6 0.12 180.5 

Objective 1: Model 36 Job type <.01 <.01 0.08 0.06 

Objective 1: Model 37 COF . 536.3 0.02 639.8 . 174.5 0.30 204.3 

Objective 1: Model 37 Square feet disturbed 0.92 0.53 0.94 0.70 

Objective 1: Model 37 Avg. paint lead <.01 <.01 0.09 0.50 

Objective 1: Model 37 Intensity level <.01 <.01 0.28 0.13 

Objective 1: Model 38 COF . 522.4 <.01 623.8 . 161.5 0.17 187.8 

Objective 1: Model 38 Square feet disturbed 0.81 0.91 0.12 0.09 

Objective 1: Model 38 Avg. paint lead <.01 <.01 0.69 0.90 

Objective 1: Model 38 Job type <.01 <.01 0.08 0.03 

Objective 1: Model 39 COF . 526.9 0.02 629.3 . 164.4 0.27 195.1 

Objective 1: Model 39 Avg. paint lead <.01 <.01 0.09 0.40 

Objective 1: Model 39 Clean*Plastic 0.27 0.10 0.48 0.44 

Objective 1: Model 39 Intensity level <.01 <.01 0.24 0.14 

Objective 1: Model 40 COF . 514.3 <.01 614.3 . 153.5 0.12 181.1 

Avg. paint lead <.01 <.01 0.40 0.59 

Clean*Plastic 0.42 0.17 0.37 0.35 

Job type <.01 <.01 0.13 0.07 

Objective 2: Model 16 COF . 556.5 0.19 658.9 . 170.0 0.30 198.0 

Objective 2: Model 16 Plastic 0.40 0.51 0.29 0.34 

Objective 2: Model 17 COF . 539.9 0.17 639.9 . 166.5 0.33 193.4 

Objective 2: Model 17 Intensity level <.01 <.01 0.22 0.08 

Objective 2: Model 17 Plastic 0.09 0.18 0.22 0.23 

Objective 2: Model 18 COF . 535.4 0.17 637.4 . 163.1 0.33 191.1 

Objective 2: Model 18 Intensity level <.01 <.01 0.22 0.09 

Objective 2: Model 18 Plastic 0.06 0.16 0.22 0.24 

Objective 2: Model 18 Intensity level*Plastic 0.24 0.47 0.89 0.93 

Objective 2: Model 19 COF . 518.0 <.01 627.5 . 154.3 0.12 179.8 

Objective 2: Model 19 Job type <.01 <.01 0.07 0.06 

Objective 2: Model 19 Plastic 0.08 0.26 0.22 0.26 

Objective 2: Model 20 COF . 508.2 <.01 617.0 . 142.2 0.12 166.8 

Objective 2: Model 20 Job type <.01 <.01 0.10 0.08 

Objective 2: Model 20 Plastic 0.10 0.39 0.27 0.33 

Objective 2: Model 20 Job type*Plastic 0.69 0.89 0.86 0.92 

Objective 3: Model 16 COF . 556.6 0.21 658.2 . 170.8 0.30 198.2 

Objective 3: Model 16 Clean 0.42 0.26 0.56 0.38 

Objective 3: Model 17 COF . 542.1 0.19 640.2 . 167.8 0.32 194.2 

Objective 3: Model 17 Intensity level <.01 <.01 0.28 0.11 

Objective 3: Model 17 Clean 0.41 0.20 0.58 0.41 
7-18 

Table 7-7: (continued) Post-Verification Work Room Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

Variables Included in 

Model p-value

-2 Log 

Likelihood p-value

-2 Log 

Likelihood p-value 

-2 Log 

Likelihood

pvalue-2 Log 

Likelihood

Objective 3: Model 18 COF . 540.2 0.20 639.2 . 164.3 0.32 191.8 

Objective 3: Model 18 Intensity level <.01 <.01 0.33 0.13 

Objective 3: Model 18 Clean 0.41 0.20 0.62 0.45 

Objective 3: Model 18 Intensity level*Clean 0.92 0.92 0.73 0.81 

Objective 3: Model 19 COF . 520.2 <.01 627.5 . 155.0 0.12 179.7 

Objective 3: Model 19 Job type <.01 <.01 0.07 0.05 

Objective 3: Model 19 Clean 0.39 0.25 0.39 0.24 

Objective 3: Model 20 COF . 505.6 <.01 612.7 . 142.8 0.13 165.5 

Job type <.01 <.01 0.10 0.09 

Clean 0.49 0.39 0.45 0.18 

Job type*Clean 0.11 0.27 0.76 0.68 

Objective 7: Model 7 COF . 534.9 0.31 632.9 . 156.5 0.48 185.3 

Objective Y: Model 7 Intensity level 0.90 0.59 0.39 0.45 

Objective Y: Model 7 

Avg. PostWork Work Floor 

Lead <.01 <.01 <.01 <.01 

Objective Y: Model 7 Clean*Plastic 0.67 0.35 0.64 0.47 

Objective 7: Model 8 COF . 517.6 <.01 623.9 . 148.8 0.21 175.4 

Objective Y: Model 8 Job type <.01 0.01 0.42 0.43 

Objective Y: Model 8 

Avg. PostWork Work Floor 

Lead 0.17 <.01 0.04 0.04 

Objective Y: Model 8 Clean*Plastic 0.42 0.48 0.54 0.41 

7.3.2. Post-Verification Tool Room Dust Lead Levels 

Table 7-8 provides an overview of results from models developed to describe post-verification 

floor and window sill dust lead loadings in the Tool room. The bullets below summarize the 

various models run. 

• Objective 1-Models 41 and 42 assess the total effects of Intensity-Level and Job-Type, 

respectively, on floor and window sill dust lead loadings in the Tool room during the 

post-verification stage. Job-Type was shown to still be a statistically significant 

predictor of post-verification floor dust lead loadings – but not a significant predictor of 

window sill dust lead loadings. Intensity-level was not a significant predictor of postverification floor or window sill post-verification dust lead levels in the Tool room. 

• In the remaining models fit to the data, average paint lead loading appeared to be 

predictive of window sill dust lead levels – and models that accounted for the combined 

effects of job type and cleaning method appeared to be most predictive of window sill 

dust-lead loadings. Similarly, average paint lead levels appeared only marginally 

predictive of floor dust-lead loadings, and models that accounted for the combined 

effects of job-type and use of plastic provided the best fit for the post-verification floor 

dust lead models for the Tool room. 

Objective 2-Model 25, which adjusted for job type, plastic, and their interaction, appeared to be 

the best-fitting model for the floor lead data. Use of plastic was significant in residential units, 

but not significant when including the COF data in the analysis. Note that the COF variable was 
7-19 

significant indicating differences between the residential units and the school. In the school, the 

classroom being worked on was separated into both the Work room and Tool room whereas in 

houses the Tool room was an adjacent room usually accessed through a doorway. This 

difference may impact the Tool room results. Interestingly, Objective3-Model 25 fits the sill 

data best and found a borderline significance for cleaning method in the combined data set. 

Section O8 in Appendix O contains residual plots for these models. As with most of the other 

analyses, the residuals from the floor models appear normally distributed while the residuals 

from the sill models are somewhat skewed. 

Table 7-8: Post-Verification Tool Room Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

Variables Included in 

Model p-value

-2 Log 

Likelihood p-value

-2 Log 

Likelihood p-value 

-2 Log 

Likelihood

pvalue-2 Log 

Likelihood

Objective 1: Model 41 COF . 351.2 0.42 452.6 . 181.6 0.29 217.2 

Objective 1: Model 41 Intensity level 0.08 0.03 0.25 0.13 

Objective 1: Model 42 COF . 334.5 0.06 436.8 . 172.7 0.43 206.4 

Objective 1: Model 42 Job type <.01 <.01 0.28 0.23 

Objective 1: Model 43 COF . 357.7 0.14 461.2 . 179.8 0.09 222.2 

Objective 1: Model 43 Square feet disturbed 0.96 0.90 0.19 0.33 

Objective 1: Model 43 Avg. paint lead 0.09 0.10 <.01 0.02 

Objective 1: Model 43 Intensity level 0.10 0.06 0.08 0.12 

Objective 1: Model 44 COF . 342.5 0.04 444.5 . 173.0 0.32 212.5 

Objective 1: Model 44 Square feet disturbed 0.67 0.98 0.89 0.64 

Objective 1: Model 44 Avg. paint lead 0.74 0.16 <.01 0.08 

Objective 1: Model 44 Job type 0.02 0.02 0.28 0.32 

Objective 1: Model 45 COF . 342.7 0.13 447.3 . 170.2 0.04 209.9 

Objective 1: Model 45 Avg. paint lead 0.14 0.10 <.01 <.01 

Objective 1: Model 45 Clean*Plastic 0.08 0.09 0.41 0.13 

Objective 1: Model 45 Intensity level 0.03 0.02 0.17 0.14 

Objective 1: Model 46 COF . 328.0 0.03 431.7 . 162.4 0.19 200.3 

Objective 1: Model 46 Avg. paint lead 0.79 0.15 <.01 0.02 

Objective 1: Model 46 Clean*Plastic 0.07 0.10 0.40 0.13 

Objective 1: Model 46 Job type <.01 <.01 0.25 0.28 

Objective 2: Model 21 COF . 354.7 0.37 457.8 . 185.1 0.25 221.3 

Objective 2: Model 21 Plastic 0.12 0.16 0.65 0.49 

Objective 2: Model 22 COF . 347.4 0.39 450.0 . 181.0 0.28 216.7 

Objective 2: Model 22 Intensity level 0.04 0.02 0.24 0.12 

Objective 2: Model 22 Plastic 0.06 0.09 0.56 0.41 

Objective 2: Model 23 COF . 341.9 0.40 445.7 . 176.4 0.28 213.4 

Objective 2: Model 23 Intensity level 0.04 0.02 0.29 0.15 

Objective 2: Model 23 Plastic 0.06 0.10 0.66 0.47 

Objective 2: Model 23 Intensity level*Plastic 0.41 0.46 0.71 0.88 

Objective 2: Model 24 COF . 330.3 0.05 434.2 . 172.1 0.43 206.0 

Objective 2: Model 24 Job type <.01 <.01 0.28 0.23 

Objective 2: Model 24 Plastic 0.04 0.09 0.60 0.45 

Objective 2: Model 25 COF . 313.3 0.05 417.3 . 158.0 0.42 191.0 

Job type <.01 <.01 0.38 0.34 

Plastic 0.03 0.16 0.81 0.70 

Job type*Plastic 0.29 0.59 0.89 0.95 
7-20 

Table 7-8: (continued) Post-Verification Tool Room Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

Variables Included in 

Model p-value

-2 Log 

Likelihood p-value

-2 Log 

Likelihood p-value 

-2 Log 

Likelihood

pvalue-2 Log 

Likelihood

Objective 3: Model 21 COF . 355.6 0.39 458.7 . 184.2 0.22 219.2 

Objective 3: Model 21 Clean 0.20 0.29 0.26 0.10 

Objective 3: Model 22 COF . 349.2 0.41 451.7 . 180.4 0.25 215.1 

Objective 3: Model 22 Intensity level 0.08 0.03 0.29 0.15 

Objective 3: Model 22 Clean 0.16 0.27 0.31 0.13 

Objective 3: Model 23 COF . 344.4 0.42 447.1 . 176.5 0.26 211.7 

Objective 3: Model 23 Intensity level 0.07 0.03 0.31 0.15 

Objective 3: Model 23 Clean 0.18 0.31 0.30 0.14 

Objective 3: Model 23 Intensity level*Clean 0.55 0.38 0.88 0.74 

Objective 3: Model 24 COF . 332.6 0.06 435.9 . 171.1 0.38 203.6 

Objective 3: Model 24 Job type <.01 0.01 0.27 0.19 

Objective 3: Model 24 Clean 0.17 0.28 0.24 0.09 

Objective 3: Model 25 COF . 318.2 0.06 420.3 . 155.9 0.41 185.6 

Job type <.01 0.02 0.24 0.16 

Clean 0.18 0.38 0.27 0.06 

Job type*Clean 0.66 0.71 0.62 0.45 

Objective Y: Model 9 COF . 346.6 0.45 448.7 . 180.9 0.35 217.4 

Objective Y: Model 9 Intensity level 0.57 0.27 0.94 0.62 

Objective Y: Model 9 

Avg. PostWork Work Floor 

Lead 0.03 0.04 0.12 0.21 

Objective Y: Model 9 Plastic 0.11 0.10 0.64 0.42 

Objective Y: Model 10 COF . 331.5 0.07 435.0 . 173.1 0.46 207.4 

Objective Y: Model 10 Job type 0.05 0.10 0.74 0.58 

Objective Y: Model 10 

Avg. PostWork Work Floor 

Lead 0.82 0.31 0.75 0.80 

Objective Y: Model 10 Plastic 0.05 0.09 0.64 0.45 

7.3.3. Post-Verification Observation Room Dust Lead Levels 

Table 7-9 provides the results from the statistical models developed to describe post-verification 

floor and window sill dust-lead loadings in the Observation room. Objective 1-Models 47 and 

48 assess the total effects of Intensity-Level and Job-Type, respectively, on post-verification 

floor and window sill dust lead loadings. Both were shown to still be statistically significant 

predictors of post-verification floor and window sill dust lead loadings in the Observation room. 

In the remaining models fit to the post-verification Observation room data, average paint lead 

loading appeared to be predictive of both floor and window sill dust-lead levels, and models that 

accounted for the combined effects of job type and use of plastic provided the best fit. 

Objective 2-Model 30 is highlighted in Table 7-9 as providing the best fit for each of the four 

data sets; however, the results for these data are not as clear. Use of plastic is found to be 

borderline significant in the residential data but not is significant in the combined data. When 

the job type by plastic use interaction is not included, the effect of plastic use is significant for 

the residential data and for window sills in the combined data. The residual plots in Section O9 

of Appendix O appear approximately normal for floors and window sills. 
7-21 

Table 7-9: Post-Verification Observation Room Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

Variables Included in 

Model p-value

-2 Log 

Likelihood p-value

-2 Log 

Likelihood p-value 

-2 Log 

Likelihood

pvalue-2 Log 

Likelihood

Objective 1: Model 47 COF . 273.0 0.84 346.8 . 151.4 0.25 176.2 

Objective 1: Model 47 Intensity level <.01 <.01 0.07 0.05 

Objective 1: Model 48 COF . 249.1 0.80 325.7 . 138.6 0.35 159.7 

Objective 1: Model 48 Job type <.01 <.01 0.02 <.01 

Objective 1: Model 49 COF . 267.1 0.38 348.5 . 145.9 0.03 179.2 

Objective 1: Model 49 Square feet disturbed 0.82 0.56 0.10 0.25 

Objective 1: Model 49 Avg. paint lead <.01 <.01 <.01 <.01 

Objective 1: Model 49 Intensity level <.01 <.01 0.02 0.05 

Objective 1: Model 50 COF . 244.6 0.48 323.0 . 135.2 0.24 161.8 

Objective 1: Model 50 Square feet disturbed 0.03 0.10 0.46 0.10 

Objective 1: Model 50 Avg. paint lead <.01 <.01 <.01 0.01 

Objective 1: Model 50 Job type <.01 <.01 <.01 <.01 

Objective 1: Model 51 COF . 253.9 0.37 339.0 . 134.6 0.08 168.4 

Objective 1: Model 51 Avg. paint lead <.01 <.01 <.01 <.01 

Objective 1: Model 51 Clean*Plastic 0.08 0.31 0.06 0.12 

Objective 1: Model 51 Intensity level <.01 <.01 <.01 0.02 

Objective 1: Model 52 COF . 235.5 0.48 317.4 . 123.8 0.18 153.8 

Objective 1: Model 52 Avg. paint lead <.01 <.01 <.01 <.01 

Objective 1: Model 52 Clean*Plastic 0.04 0.39 0.10 0.14 

Objective 1: Model 52 Job type <.01 <.01 <.01 <.01 

Objective 2: Model 26 COF . 292.2 0.87 366.5 . 152.8 0.21 178.8 

Plastic 0.26 0.59 0.05 0.08 

Objective 2: Model 27 COF . 268.8 0.83 346.4 . 145.8 0.24 172.8 

Objective 2: Model 27 Intensity level <.01 <.01 0.01 0.02 

Objective 2: Model 27 Plastic 0.03 0.29 0.01 0.04 

Objective 2: Model 28 COF . 266.4 0.83 344.4 . 141.4 0.24 169.1 

Objective 2: Model 28 Intensity level <.01 <.01 0.03 0.03 

Objective 2: Model 28 Plastic 0.05 0.32 0.04 0.07 

Objective 2: Model 28 Intensity level*Plastic 0.95 0.99 0.32 0.32 

Objective 2: Model 29 COF . 244.7 0.80 325.6 . 133.4 0.37 156.2 

Objective 2: Model 29 Job type <.01 <.01 <.01 <.01 

Objective 2: Model 29 Plastic 0.03 0.32 0.02 0.03 

Objective 2: Model 30 COF . 230.8 0.83 306.3 . 118.9 0.38 140.3 

Job type <.01 <.01 <.01 <.01 

Plastic 0.06 0.85 0.08 0.13 

Job type*Plastic 0.17 0.07 0.21 0.18 

Objective 3: Model 26 COF . 293.0 0.88 366.7 . 155.6 0.24 180.6 

Objective 3: Model 26 Clean 0.44 0.65 0.30 0.25 

Objective 3: Model 27 COF . 272.5 0.84 347.3 . 150.4 0.26 175.5 

Objective 3: Model 27 Intensity level <.01 <.01 0.06 0.04 

Objective 3: Model 27 Clean 0.33 0.58 0.22 0.19 

Objective 3: Model 28 COF . 269.8 0.83 344.4 . 147.9 0.25 173.8 

Objective 3: Model 28 Intensity level <.01 <.01 0.08 0.06 

Objective 3: Model 28 Clean 0.37 0.60 0.22 0.19 

Objective 3: Model 28 Intensity level*Clean 0.86 0.59 0.85 0.81 
7-22 

Table 7-9: (continued) Post-Verification Observation Room Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

Variables Included in 

Model p-value

-2 Log 

Likelihood p-value

-2 Log 

Likelihood p-value 

-2 Log 

Likelihood

pvalue-2 Log 

Likelihood

Objective 3: Model 29 COF . 248.9 0.79 326.6 . 138.5 0.36 159.9 

Job type <.01 <.01 0.02 <.01 

Clean 0.33 0.84 0.40 0.33 

Objective 3: Model 30 COF . 239.3 0.77 313.6 . 126.9 0.35 147.6 

Objective 3: Model 30 Job type <.01 <.01 0.05 0.02 

Objective 3: Model 30 Clean 0.32 0.92 0.33 0.26 

Objective 3: Model 30 Job type*Clean 0.82 0.63 0.55 0.51 

Objective 4: Model Y COF . 266.3 0.96 342.3 . 143.9 0.39 168.9 

Objective Y: Model 11 Intensity level <.01 0.02 0.93 0.97 

Objective Y: Model 11 

Avg. PostWork Work Floor 

Lead 0.02 <.01 0.02 <.01 

Objective Y: Model 11 Plastic 0.08 0.34 0.05 0.05 

Objective 4: Model Y COF . 246.8 0.88 326.3 . 133.8 0.50 156.5 

Objective Y: Model 12 Job type <.01 <.01 0.19 0.16 

Objective Y: Model 12 

Avg. PostWork Work Floor 

Lead 0.79 0.20 0.19 0.11 

Objective Y: Model 12 Plastic 0.03 0.34 0.04 0.04 

7.4. Comparison of Rule Practices and Baseline Practices - Post-Job Dust Lead Levels 

The following three subsections provide an overview of statistical modeling results for floor and 

window sill dust lead loadings in a cross-stage analysis comparing full rule implementation (use 

of plastic sheeting and proposed Rule cleaning at the Post-Verification Stage) to no rule 

implementation (no use of plastic sheeting and baseline cleaning at the Post-Cleaning Stage). 

7.4.1. Post-Job Work Room Dust Lead Levels 

Table 7-10 provides an overview of results from the various statistical models applied across 

stages within the Work room - comparing full rule implementation to no rule implementation. 

Model 1 assesses the total effect of rule implementation, which was shown to be highly 

significant in both floors and window sills in the two subsets of data explored. Models 2 through 

5 assess the effect of full rule implementation in the Work room, after adjusting for intensitylevel or job type and their interaction with full rule implementation. In each of these adjusted 

models, full rule implementation was associated with significantly lower dust-lead loadings in 

the Work room. Model 5 appears to fit the data best for each of the four data sets. The residual 

plots from the floor models appear reasonable, while the residual plots from the sill models 

appear to be heavy-tailed. 
7-23 

Table 7-10: Post-Job Work Room, Rule vs. Non-Rule Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

Variables Included 

in Model p-value 

-2 Log 

Likelihood p-value

-2 Log 

Likelihood p-value 

-2 Log 

Likelihood p-value

-2 Log 

Likelihood

Objective 7: Model 1 COF . 245.1 0.22 293.4 . 78.1 0.31 92.8 

Objective X: Model 1 Rule 0.01 <.01 0.02 <.01 

Objective 7: Model 2 COF . 238.8 0.12 285.5 . 76.4 0.33 91.3 

Objective X: Model 2 Rule <.01 <.01 0.03 <.01 

Objective X: Model 2 Intensity level 0.06 0.01 0.93 0.77 

Objective 7: Model 3 COF . 234.3 0.11 280.9 . 71.4 0.33 87.8 

Objective X: Model 3 Rule <.01 <.01 0.04 <.01 

Objective X: Model 3 Intensity level 0.17 0.02 0.69 0.61 

Objective X: Model 3 Rule*Intensity level 0.49 0.23 0.58 0.74 

Objective 7: Model 4 COF . 215.9 <.01 268.0 . 64.7 0.19 76.7 

Objective X: Model 4 Rule <.01 <.01 0.02 <.01 

Objective X: Model 4 Job type <.01 <.01 0.35 0.34 

Objective 7: Model 5 COF . 202.7 <.01 253.2 . 49.6 0.33 59.4 

Rule <.01 <.01 0.10 0.02 

Job type <.01 <.01 0.61 0.52 

Rule*Job type 0.35 0.68 0.66 0.60 

7.4.2. Post-Job Tool Room Dust Lead Levels 

The model results from comparing full rule implementation to no rule implementation within the 

Tool room are presented in Table 7-11. Model 6 assesses the total effect of rule implementation, 

which was not a statistically significant predictor of dust lead loadings in the Tool room. Models 

7 through 10 assess the effect of full rule implementation in the Work room, after adjusting for 

intensity-level or job type and their interaction with full rule implementation. These models 

suggest that full rule implementation was associated with a marginally significant decrease in 

window sill dust lead levels, after adjusting for the effects of job-type (Model 9). Model 10 

appears to provide the best fit, although by adding the rule use by job type interaction the effect 

of the rule was no longer significant. Section O11 presents the residual plots for Model 10, 

which appear to be normally distributed except for the residential sill data. 
7-24 

Table 7-11: Post-Job Tool Room, Rule vs. Non-Rule Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

Variables Included 

in Model p-value 

-2 Log 

Likelihood p-value

-2 Log 

Likelihood p-value 

-2 Log 

Likelihood p-value

-2 Log 

Likelihood

Objective 7: Model 6 COF . 180.4 0.47 233.2 . 91.0 0.45 107.6 

Objective X: Model 6 Rule 0.46 0.46 0.24 0.13 

Objective 7: Model 7 COF . 171.5 0.33 224.8 . 83.4 0.40 102.1 

Objective X: Model 7 Rule 0.22 0.23 0.18 0.10 

Objective X: Model 7 Intensity level <.01 <.01 0.14 0.20 

Objective 7: Model 8 COF . 165.9 0.37 220.3 . 76.7 0.40 96.7 

Objective X: Model 8 Rule 0.35 0.31 0.23 0.13 

Objective X: Model 8 Intensity level 0.05 0.03 0.12 0.17 

Objective X: Model 8 Rule*Intensity level 0.78 0.84 0.45 0.59 

Objective 7: Model 9 COF . 144.2 0.23 205.1 . 69.2 0.54 85.8 

Rule 0.08 0.23 0.09 0.06 

Job type <.01 <.01 0.07 0.16 

Objective 7: Model 10 COF . 131.3 0.22 186.5 . 52.2 0.46 66.6 

Rule 0.17 0.36 0.19 0.14 

Job type <.01 0.10 0.30 0.36 

Rule*Job type 0.97 0.99 0.80 0.91 

7.4.3. Post-Job Observation Room Dust Lead Levels 

Table 7-12 contains the model results from comparing full rule implementation to no rule 

implementation across stages within the Observation room. Model 11 assesses the total effect of 

rule implementation, which was not a statistically significant predictor of dust lead loadings. 

Models 12 through 15 assess the effect of full rule implementation, after adjusting for intensitylevel or job-type and their interaction with full rule implementation. The effect of full rule 

implementation was not a significant predictor of dust-lead loadings in any of these adjusted 

models within the Observation room. 

Model 15 seems to provide the best fit to the data, but the variable added for the interaction 

between rule use and job type is not significant at all. The residuals plots for Model 15 

contained in Section O12 of Appendix O are approximately normal except for the residential 

floor data. 
7-25 

Table 7-12: Post-Job Observation Room, Rule vs. Non-Rule Modeling Results 

 Floors Sills 

 All Residential Combined All Residential Combined 

Model 

Variables Included 

in Model p-value 

-2 Log 

Likelihood p-value

-2 Log 

Likelihood p-value 

-2 Log 

Likelihood p-value

-2 Log 

Likelihood

Objective 7: Model 11 COF . 167.4 0.68 201.2 . 78.3 0.33 91.7 

Objective X: Model 11 Rule 0.43 0.66 0.43 0.56 

Objective 7: Model 12 COF . 154.4 0.49 191.5 . 74.0 0.29 88.0 

Objective X: Model 12 Rule 0.23 0.40 0.38 0.50 

Objective X: Model 12 Intensity level <.01 0.01 0.32 0.27 

Objective 7: Model 13 COF . 149.2 0.50 186.9 . 69.6 0.31 84.4 

Objective X: Model 13 Rule 0.23 0.41 0.43 0.54 

Objective X: Model 13 Intensity level 0.02 0.03 0.44 0.38 

Objective X: Model 13 Rule*Intensity level 0.77 0.79 0.90 0.85 

Objective 7: Model 14 COF . 135.1 0.49 174.9 . 58.9 0.34 70.7 

Objective X: Model 14 Rule 0.10 0.26 0.23 0.32 

Objective X: Model 14 Job type <.01 <.01 0.06 0.07 

Objective 7: Model 15 COF . 122.5 0.55 157.9 . 44.9 0.35 56.0 

Rule 0.14 0.35 0.35 0.47 

Job type <.01 0.12 0.33 0.32 

Rule*Job type 0.96 1.00 0.80 0.93 
7-26 

7.5. Exterior Dust Lead Levels 

The main comparisons of interest for the exterior experiments are (1) the levels of lead measured 

on top of the Rule plastic compared to levels measured under the Rule plastic, and (2) the levels 

of lead measured on top of the Rule plastic compared to levels measured near the Rule plastic. 

The first comparison focuses on the effectiveness of the Rule plastic at preventing dust from 

spreading to the ground underneath it, while the second focuses on whether the Rule plastic was 

adequate to prevent contamination of the ground a bit further away from the work area. 

Appendix N contains the detailed model results for the mixed models run on both sets of exterior 

data. Table 7-13 presents the ratios of the model-predicted lead levels measured at each of the 

three locations: near (N) Rule plastic vs. on (O) Rule plastic; near (N) Rule plastic vs. Under (U) 

Rule plastic; and on (O) Rule plastic vs. Under (U) Rule plastic. Bulk debris samples are 

included in Table 7-13; however, the same statistics are presented in Table 7-14 without the bulk 

debris samples. 

Table 7-13. Comparison Exterior Dust Pan Levels within Each Job with Bulk Debris 

Samples Included (Model Based Estimate Differences and Ratios) 

95% Confidence 

Job Type Interval on the Ratio Location 

1 

Location 

2 

Estimate 

(Log. 

Scale) 

StdErr of 

Estimate 

(Log. Scale) 

Ratio 

Lower Upper 

Near On -1.50 1.19 0.2 0.0 2.4

Door Replacement Near Under 6.03 1.19 417.0 39.6 4,386.7

On Under 7.53 1.19 1,869.9 177.7 19,672.5

Near On -1.58 1.19 0.2 0.0 2.2

Near Under 4.54 1.19 94.0 8.9 989.3 Trim/Soffit 

Replacement On Under 6.13 1.19 457.1 43.5 4,809.4

Near On -3.43 1.68 0.0 0.0 0.9

Needle Gun Near Under 3.16 1.68 23.6 0.8 657.0

On Under 6.59 1.68 724.9 26.0 20,213.6

Near On -4.20 1.68 0.0 0.0 0.4

Near Under 3.53 1.68 34.3 1.2 955.5 Heat gun under 1100 

degrees On Under 7.74 1.68 2,291.3 82.2 63,895.1

Near On -4.03 0.84 0.0 0.0 0.1

Dry Scrape Near Under 2.65 0.84 14.2 2.7 75.0

On Under 6.69 0.84 802.0 151.9 4,235.4

Near On -2.93 1.19 0.1 0.0 0.6

Power Sanding Near Under 1.86 1.19 6.5 0.6 67.9

On Under 4.79 1.19 120.8 11.5 1,271.1

Near On -7.19 1.19 0.0 0.0 0.0

Torching Near Under -3.00 1.19 0.1 0.0 0.5

On Under 4.18 1.19 65.7 6.2 690.9

Near On -5.88 1.68 0.0 0.0 0.1

Near Under 1.14 1.68 3.1 0.1 86.8 Heat gun over 1100 

degrees On Under 7.02 1.68 1,113.8 39.9 31,058.6
7-27 

The Estimate column within tables 7-13 and 7-14 provides the predicted difference from the 

model for Location 1 – Location 2. Thus, the predicted difference of On-Under for the door 

replacement job (including bulk debris samples) is 6.9 units on the log scale. This translated to a 

ratio of 1,870:1 with a lower bound on a 95% confidence interval of 178:1. For the O:U 

comparison, a ratio greater than one indicates significantly higher levels on the plastic than 

under, which was expected. For the N:O comparison, a ratio less than one indicates that the lead 

levels measured near the Rule plastic are lower than those on the Rule plastic. 

Table 7-14. Comparison Exterior Dust Pan Levels within Each Job Excluding Bulk 

Debris Samples (Model Based Estimate Differences and Ratios) 

95% Confidence 

Job Type Interval on the Ratio Location 

1 

Location 

2 

Estimate 

(Log. 

Scale) 

StdErr of 

Estimate 

(Log. Scale) 

Ratio 

Lower Upper 

Near On -0.88 0.92 0.41 0.07 2.58

Door Replacement Near Under 6.03 0.92 416.95 66.92 2598.06

On Under 6.91 0.92 1006.52 161.53 6271.66

Near On 0.32 0.92 1.37 0.22 8.54

Near Under 4.54 0.92 94.03 15.09 585.93

Trim Soffit 

Replacement 

 On Under 4.23 0.92 68.63 11.01 427.62

Near On -0.19 1.30 0.82 0.06 10.94

Needle Gun Near Under 3.16 1.30 23.56 1.77 313.20

On Under 3.35 1.30 28.62 2.15 380.44

Near On 0.01 1.30 1.01 0.08 13.48

Near Under 2.49 1.30 12.05 0.91 160.24 Heat gun under 1100 

degrees On Under 2.48 1.30 11.88 0.89 158.01

Near On -2.25 0.65 0.11 0.03 0.38

Dry Scrape Near Under 2.65 0.65 14.21 3.90 51.80

On Under 4.90 0.65 134.58 36.91 490.70

Near On -1.26 0.92 0.28 0.05 1.77

Power Sanding Near Under 1.86 0.92 6.46 1.04 40.22

On Under 3.12 0.92 22.75 3.65 141.77

Near On -2.55 0.92 0.08 0.01 0.49

Torching Near Under -3.00 0.92 0.05 0.01 0.31

On Under -0.45 0.92 0.64 0.10 3.96

Near On -2.70 1.30 0.07 0.01 0.89

Near Under 1.14 1.30 3.11 0.23 41.37

Heat gun over 1100 

degrees 

 On Under 3.84 1.30 46.35 3.49 616.23

The results in Table 7-13, which include the bulk debris samples, report that O:U ratios range 

from 66:1 to 2,291:1 with the power sanding the torch burning jobs having the lowest lower 

confidence interval bounds at 12:1 and 6:1, respectively. Generally, this indicates that only a 

small percentage of the lead levels that landed on top of the Rule plastic were measured 

underneath the plastic. Note that the 95% confidence bounds are very wide because of the 

relatively small number of samples available for each job. The N:O ratios are less than 0.2:1 

across all jobs, although the upper confidence bound on the door replacement and trim/soffit 

replacement jobs exceeded 1:1. 
7-28 

Because the impact of excluding the bulk debris samples was to significantly lower the amounts 

of lead measured on top of the Rule plastic, the results in Table 7-14 differ somewhat from those 

in Table 7-13. The estimated O:U ratio of the torch burning job is below 1:1, as over 99 percent 

of the on Rule plastic samples were comprised of the bulk debris. The O:U ratios for the other 

jobs declined, but the lowest predicted ratio other than the torch burning was 12:1 for the heat 

gun job below 1100 degrees. Similarly, the lower 95% confidence bounds decreased with the 

torch burning and heat gun <1100 degrees below 1:1. The N:O ratios increased with the decline 

in the lead levels on the Rule plastic causing two jobs exceed 1:1 – the trim/soffit replacement 

and the heat gun under 1100 degrees. The upper confidence bounds on five jobs exceeds 1:1 

with the exclusion of the bulk debris samples. 

Note that the lead levels measured near the Rule plastic are somewhat impacted by the amount of 

Rule plastic that could be used for a job given the property constraints. Both door replacement 

jobs only had seven or eight feet of space between the door being worked on and a fence, which 

limited the size of the Rule plastic that could be used. Similarly, one of the trim/soffit 

replacement jobs had about the same distance between the porch being worked on and a 

neighboring fence. For that job especially, which occurred on components about 10 feet off the 

ground, in a real-world situation more rule plastic would be used than was used in the 

experiment. 

7.6. Post-verification Predictors of Clearance Failure 

As discussed in Section 5.3, statistical modeling was performed to investigate causes of postverification lead levels above the clearance standards on floors and sills. The following predictor 

variables were explored in these analyses: 

• Job Type 

• Cleaning Method 

• Use of Plastic 

• Phase - interaction of cleaning method and plastic use 

• Restricted job - groups jobs by restricted and non-restricted status (28 of 60 experiments 

were done using restricted practices) 

• Intensity level – based on initial assignment 

• Building type - Housing vs. COF 

• Contractor – 3 different contractors performed interior work 

• Floor type – Vinyl, Tile, and Wood 

• Floor condition – rated as Good, Fair, Poor 

• Paint-Lead Levels 

• Area of Painted Surface Disturbed 

• Post-Work Dust Lead Loading in the Work Room – analyzed both arithmetic average and 

geometric mean 

• Post-Cleaning Dust Lead Loading in the Work Room - analyzed both arithmetic average 

and geometric mean 

We planned to conduct the analyses two ways to consider cleaning method differently. The 

initial analyses used data from all experiments whether they used the Baseline or Rule cleaning 

method. In these models, Cleaning Method was considered as a variable. Once the data set was 
7-29 

reduced to only non-restricted jobs, we also created a subset of experiments in which Rule 

Cleaning was used to specifically focus on factors influencing cleaning verification success when 

the proposed rule cleaning methods were used. The first set of analyses provides results on 

whether the cleaning method was a factor in whether the subsequent cleaning verification 

process was a success. 

Generalized Estimating Equations were used to account for the potential positive correlation 

among the dust-lead loading outcomes that are assessed from within the same housing unit or 

COF and within the same room. 

7.6.1. Single Covariate Modeling Results

Two sets of models were run to analyze cleaning verification failure on floors. Model Set 1 used 

proportion of dust wipes > 40 μg/ft2

 as the outcome measure, while Model Set 2 used probability 

of a single post-verification dust wipe failing clearance. Within each model set, three groups of 

data were analyzed – data from all jobs, data from non-restricted jobs only, and data from nonrestricted jobs at which the Rule Cleaning method was used. Cleaning verification failure on 

window sills were analyzed using the probability of a post-verification dust wipe sample > 250 

μg/ft2

. Thus, the nine sets of output are listed below: 

• Model Set 1a – proportion of failing floor wipes, data from all jobs 

• Model Set 1b - proportion of failing floor wipes, data from non-restricted jobs only 

• Model Set 1c - proportion of failing floor wipes, data from non-restricted jobs that used 

Rule Cleaning 

• Model Set 2a – probability of one or more post-verification floor wipes failing, data from 

all jobs 

• Model Set 2b - probability of one or more post-verification floor wipes failing, data from 

non-restricted jobs only 

• Model Set 2c - probability of one or more post-verification floor wipes failing, data from 

non-restricted jobs that used Rule Cleaning 

• Model Set 3a - probability of a post-verification sill wipe failing, data from all jobs 

• Model Set 3b - probability of a post-verification sill wipe failing, data from non-restricted 

jobs only 

• Model Set 3c - probability of a post-verification sill wipe failing, data from non-restricted 

jobs that used Rule Cleaning 

Model Set 1a – Proportion of Failing Floor Dust Wipes, All Jobs 

Each variable being considered was included in a single covariate logistic regression model to 

assess its predictive ability on proportion of dust wipes failing clearance. From review of Table 

7-15 that presents p-values indicating the overall statistical significance of each variable 

considered, the variables that were predictive of proportion of dust wipes failing clearance (at a 

.05 significance level) were: 

• Job type 

• Restricted status 

• Floor type 

• Floor condition 

• Post-work average and GM floor lead levels 

• Post-cleaning average floor lead levels (although GM floor 

lead levels had a p-value of .065) 
7-30 

Table 7-16 presents the comparisons between the different responses or levels within each of the 

variables considered. Within the Restricted Job model, the estimate of 1.69 for restricted jobs 

indicates a higher proportion of floor dust wipes failing clearance compared to non-restricted 

jobs. Within Floor Type, Tile and Vinyl have estimates of -2.64 and -2.07, respectively, with pvalues <.001 indicating that proportion of floor dust wipes failing clearance on those surfaces is 

significantly lower compared to wood floors. Within Floor Condition, floors in Good condition 

have a parameter estimate of -2.94 and floors in Fair condition have a parameter estimate of -

1.52 compared to those in Poor condition with p-values of .001 and <.0001, respectively. 

Model Set 1b – Proportion of Failing Floor Dust Wipes, Non-restricted Jobs 

Subsetting the data set to only the 32 experiments that used non-restricted jobs eliminates about 

47 percent of the data. As a result, the only variables in Table 7-15 indicated as statistically 

significant predictors of proportion of floor dust wipes failing clearance are Post-work Average 

and GM Floor Lead Levels and Post-cleaning Average and GM Floor Lead Levels. Job Type is 

borderline significant with a p-value of .06. Floor Type and Floor Condition are borderline 

significant as well with p-values of .09. Note that the Restricted Job model was not run as only 

non-restricted jobs were included in the data set. 

Although the overall significance of Job Type, Floor Type, and Floor Condition did not reach the 

.05 level, Table 7-17 indicates that there were significant differences between levels of these 

variables. 

• Within Job Type, the estimate of -2.38 for Cut Outs indicates a significantly lower 

proportion of floor wipe failures compared to the Kitchen Gut job (p-value of .0001) 

while the estimate of 1.85 for Window Replacement indicates a significantly higher 

proportion of failures compared to the Kitchen Gut job (p-value of .007). 

• Within Building Type, the estimate of -2.40 for COFs and a p-value of .004 indicates a 

significantly lower proportion of floor wipe failures compared to residential housing. 

• Within Floor Type, the estimate of -2.43 and -2.33 for Tile and Vinyl, respectively, with 

p-values of .001 indicate significantly lower proportion of floor wipe failures compared 

to Wood floors. 

• Within Floor Condition, the estimate of -2.48 for Good floors with an associated p-value 

of .01 indicates a significantly lower proportion of floor dust wipe failures compared to 

floors in Poor condition. 

Model Set 1c – Proportion of Failing Floor Dust Wipes, Non-restricted Jobs with Rule 

Cleaning 

Subsetting the data set of non-restricted jobs further to include only those done with Rule 

Cleaning reduces the data set to only 16 experiments or about 27 percent of the data used in 

Model Set 1a. Because of these changes, Job Type and Cleaning Method were not assessed. 

Table 7-15 indicates that using this limited data set no variables met the .05 level of significance. 

Post-work Average and GM Floor Lead Levels and Post-cleaning Average and GM Floor Lead 

Levels were all borderline significant with p-values ranging from .051 to .061. 

Similar to Model Set 1b, although the overall significance of Floor Type and Floor Condition did 

not reach the .05 level, Table 7-18 indicates that there were significant differences between 

levels of these variables. 
7-31 

• Within Floor Type, the estimate of -2.71 and -2.91 for Tile and Vinyl, respectively, with 

p-values <.01 indicate significantly lower proportion of floor wipe failures compared to 

Wood floors. 

• Within Floor Condition, the estimate of -2.56 for Good floors with an associated p-value 

of .03 indicates a significantly lower proportion of floor dust wipe failures compared to 

floors in Poor condition. 
7-32 

Table 7-15. Single Covariate Logistic Regression Modeling Estimates for Proportion of 

Failed Post-verification Floor Wipe Samples 

Model Source DF Chi Square 

Estimate p-value 

Job Type 6 66.83 <.0001 

Cleaning Method 1 0.14 0.7054 

Plastic Use 1 0.17 0.677 

Phase 3 1.2 0.7537 

Restricted 1 11.74 0.0006 

Intensity Level 2 3.68 0.1586 

Building type 1 8.27 0.004 

Contractor 2 1.77 0.4128 

Floor Type 2 20.12 <.0001 

Floor Condition 2 26.96 <.0001 

Disturbed Area 1 1.91 0.1675 

Paint Lead Level 1 2.17 0.1412 

Post-work Avg. Floor Lead 1 14.08 0.0002 

Post-work GM Floor Lead 1 11.26 0.0008 

Post-cleaning Avg. Floor Lead 1 64.19 <.0001 

Set 1a: All Jobs 

Post-cleaning GM Floor Lead 1 51.82 <.0001 

Job Type 3 29.83 <.0001 

Cleaning Method 1 0.16 0.6893 

Plastic Use 1 0.26 0.6086 

Phase 3 0.81 0.8464 

Intensity Level 2 0.43 0.8071 

Building type 1 1.07 0.3001 

Contractor 2 1.44 0.4868 

Floor Type 2 16.17 0.0003 

Floor Condition 2 7.45 0.0242 

Disturbed Area 1 0 0.9837 

Paint Lead Level 1 0.08 0.7811 

Post-work Avg. Floor Lead 1 2.39 0.1217 

Post-work GM Floor Lead 1 2.37 0.1237 

Post-cleaning Avg. Floor Lead 1 38.17 <.0001 

Set 1b: Restricted 

Jobs 

Post-cleaning GM Floor Lead 1 28.01 <.0001 

Plastic Use 1 0 1 

Phase 1 0.04 0.849 

Intensity Level 2 2.3 0.3161 

Building type 1 0.76 0.3845 

Contractor 2 1.04 0.5959 

Floor Type 2 12.68 0.0018 

Floor Condition 2 4.6 0.1001 

Disturbed Area 1 0.31 0.5804 

Paint Lead Level 1 0.95 0.3302 

Post-work Avg. Floor Lead 1 4.71 0.0299 

Post-work GM Floor Lead 1 4.39 0.0362 

Post-cleaning Avg. Floor Lead 1 10.74 0.001 

Set 1c: Restricted 

Jobs with Rule 

Cleanings 

Post-cleaning GM Floor Lead 1 15.74 <.0001 
7-33 

Table 7-16. Single Covariate Model Results for Proportion of Failed Post-verification 

Floor Wipe Samples across All Jobs 

Single Covariate Levels Estimate 

Standard 

Error Lower CL 

Upper 

CL Z p-value 

Intercept -1.47 0.56 -2.57 -0.37 -2.61 0.009

I1-Cut Outs -2.38 0.62 -3.60 -1.17 -3.85 0.0001

I2-Replace Windows 1.85 0.68 0.51 3.18 2.7 0.0069

I3-Scrape Surface 1.22 0.61 0.03 2.40 2.01 0.0447

I4-Scrape Door 2.93 0.95 1.06 4.80 3.07 0.0021

I5-Heat gun < 1100 degrees 0.37 0.56 -0.73 1.47 0.65 0.5127

I6-Heat gun > 1100 degrees 1.98 1.02 -0.02 3.97 1.94 0.0519

Job Type 

I7-Kitchen Gut 0.00 0.00 0.00 0.00 

Intercept -0.41 0.41 -1.21 0.40 -0.99 0.323

Cleaning Method 0=Baseline Method 0.14 0.36 -0.57 0.85 0.38 0.7054

1=Rule Method 0.00 0.00 0.00 0.00 

Intercept -0.41 0.39 -1.16 0.35 -1.05 0.2942

Plastic Use 0 – No plastic 0.14 0.33 -0.51 0.78 0.42 0.677

1 – Plastic 0.00 0.00 0.00 0.00 

Intercept 0.00 0.42 -0.83 0.83 0 1

I – Plastic/Rule Cleaning -0.14 0.35 -0.84 0.55 -0.4 0.6863

II – Plastic/Baseline Cleaning -0.55 0.50 -1.53 0.44 -1.09 0.2752

III – No Plastic/Rule Cleaning -0.55 0.77 -2.05 0.96 -0.71 0.4772

Phase 

IV – No Plastic/Baseline Cleaning 0.00 0.00 0.00 0.00 

Intercept -1.18 0.40 -1.97 -0.40 -2.97 0.003

Restricted Job 1-yes 1.69 0.49 0.73 2.66 3.43 0.0006

2-no 0.00 0.00 0.00 0.00 

Intercept -1.10 0.57 -2.22 0.03 -1.92 0.0554

1-High 0.90 0.70 -0.48 2.28 1.28 0.2013

2-Medium 1.30 0.68 -0.03 2.63 1.92 0.055

Intensity-level 

3-Low 0.00 0.00 0.00 0.00 

Intercept 0.00 0.32 -0.62 0.62 0 1

Building Type COF -2.40 0.83 -4.03 -0.76 -2.88 0.004

Residential Housing 0.00 0.00 0.00 0.00 

Intercept -0.34 0.62 -1.55 0.88 -0.54 0.5868

C2 -0.34 0.86 -2.03 1.35 -0.39 0.6948

C3 0.45 0.67 -0.86 1.75 0.67 0.5019

Contractor 

C4 0.00 0.00 0.00 0.00 

Intercept 1.10 0.33 0.45 1.75 3.31 0.0009

Tile -2.64 0.71 -4.02 -1.25 -3.74 0.0002

Vinyl -2.07 0.62 -3.28 -0.86 -3.35 0.0008

Floor Type 

Wood 0.00 0.00 0.00 0.00 

Intercept 0.87 0.33 0.22 1.51 2.63 0.0085

Fair -1.52 0.46 -2.44 -0.61 -3.28 0.001

Good -2.99 0.60 -4.16 -1.81 -4.98 <.0001

Floor Condition 

Poor 0.00 0.00 0.00 0.00 

Intercept -0.84 0.48 -1.78 0.11 -1.73 0.0834 Disturbed Area 

Disturbed Area 0.01 0.01 0.00 0.03 1.38 0.1675
7-34 

Single Covariate Levels Estimate 

Standard 

Error Lower CL 

Upper 

CL Z p-value 

Avg. Paint Lead Intercept -0.89 0.36 -1.59 -0.20 -2.52 0.0119

Level Avg. Paint Lead Level 0.14 0.10 -0.05 0.33 1.47 0.1412

Post-work Avg. Intercept -1.49 0.38 -2.23 -0.75 -3.93 <.0001

Floor Lead Post-work Avg. Floor Lead 0.00 0.00 0.00 0.00 3.75 0.0002

Post-work GM Intercept -1.31 0.36 -2.02 -0.60 -3.62 0.0003

Floor Lead Post-work GM Floor Lead 0.00 0.00 0.00 0.00 3.36 0.0008

Post-cleaning Intercept -2.56 0.37 -3.28 -1.83 -6.93 <.0001

Avg. Floor Lead Post-cleaning Avg. Floor Lead 0.03 0.00 0.02 0.03 8.01 <.0001

Post-cleaning Intercept -2.54 0.38 -3.29 -1.80 -6.67 <.0001

GM Floor Lead Post-cleaning GM Floor Lead 0.03 0.00 0.02 0.04 7.2 <.0001

Table 7-17. Single Covariate Model Results for Proportion of Failed Post-verification 

Floor Wipe Samples across Non-restricted Jobs 

Single Covariate Levels Estimate 

Standard 

Error Lower CL 

Upper 

CL Z p-value 

Intercept -1.47 0.56 -2.57 -0.37 -2.61 0.009

I1-Cut Outs -2.38 0.62 -3.60 -1.17 -3.85 0.0001

I2-Replace Windows 1.85 0.68 0.51 3.18 2.7 0.0069

I5-Heat gun < 1100 degrees 0.37 0.56 -0.73 1.47 0.65 0.5127

Job Type 

I7-Kitchen Gut 0.00 0.00 0.00 0.00 

Intercept -1.27 0.47 -2.19 -0.35 -2.71 0.0067

Cleaning Method 0=Baseline Method 0.17 0.44 -0.68 1.03 0.4 0.6893

1=Rule Method 0.00 0.00 0.00 0.00 

Intercept -1.37 0.61 -2.57 -0.16 -2.23 0.026

Plastic Use 0 – No plastic 0.35 0.68 -0.99 1.69 0.51 0.6086

1 – Plastic 0.00 0.00 0.00 0.00 

Intercept -0.79 0.47 -1.72 0.14 -1.66 0.0963

I – Plastic/Rule Cleaning -0.31 0.58 -1.44 0.82 -0.54 0.592

II – Plastic/Baseline Cleaning -0.68 0.84 -2.32 0.96 -0.81 0.4174

III – No Plastic/Rule Cleaning -0.48 0.87 -2.19 1.22 -0.56 0.5776

Phase 

IV – No Plastic/Baseline Cleaning 0.00 0.00 0.00 0.00 

Intercept -1.10 0.57 -2.22 0.03 -1.92 0.0554

1-High -0.37 0.80 -1.93 1.20 -0.46 0.6452

2-Medium 0.00 0.57 -1.12 1.12 0 1 Intensity-level 

3-Low 0.00 0.00 0.00 0.00 

Intercept -0.99 0.44 -1.86 -0.12 -2.23 0.0257

Building Type COF -0.96 0.92 -2.76 0.85 -1.04 0.3001

Residential Housing 0.00 0.00 0.00 0.00 

Intercept -1.00 0.68 -2.34 0.34 -1.46 0.1444

C2 -0.95 1.06 -3.02 1.13 -0.89 0.3709

C3 0.15 0.81 -1.44 1.75 0.19 0.8527

Contractor 

C4 0.00 0.00 0.00 0.00 

Intercept 0.38 0.39 -0.38 1.14 0.98 0.328

Tile -2.43 0.75 -3.91 -0.96 -3.23 0.0012

Vinyl -2.33 0.73 -3.75 -0.90 -3.19 0.0014

Floor Type 

Wood 0.00 0.00 0.00 0.00 
7-35 

Single Covariate Levels Estimate 

Standard 

Error Lower CL 

Upper 

CL Z p-value 

Intercept 0.00 0.44 -0.87 0.87 0 1

Fair -1.25 0.76 -2.74 0.24 -1.65 0.0997

Good -2.48 0.98 -4.41 -0.56 -2.53 0.0113

Floor Condition 

Poor 0.00 0.00 0.00 0.00 

Intercept -1.19 0.75 -2.67 0.28 -1.58 0.1131 Disturbed Area 

Disturbed Area 0.00 0.02 -0.03 0.03 0.02 0.9837

Avg. Paint Lead Intercept -1.32 0.66 -2.61 -0.02 -1.99 0.0463

Level Avg. Paint Lead Level 0.03 0.12 -0.20 0.26 0.28 0.7811

Post-work Avg. Intercept -1.93 0.53 -2.97 -0.89 -3.65 0.0003

Floor Lead Post-work Avg. Floor Lead 0.00 0.00 0.00 0.00 1.55 0.1217

Post-work GM Intercept -1.86 0.51 -2.86 -0.86 -3.65 0.0003

Floor Lead Post-work GM Floor Lead 0.00 0.00 0.00 0.00 1.54 0.1237

Post-cleaning Intercept -3.19 0.50 -4.16 -2.22 -6.44 <.0001

Avg. Floor Lead Post-cleaning Avg. Floor Lead 0.03 0.00 0.02 0.04 6.18 <.0001

Post-cleaning Intercept -3.03 0.50 -4.01 -2.05 -6.07 <.0001

GM Floor Lead Post-cleaning GM Floor Lead 0.03 0.01 0.02 0.05 5.29 <.0001

Table 7-18.. Single Covariate Model Results for Proportion of Failed Post-verification 

Floor Wipe Samples across Non-restricted Jobs Using Rule Cleaning 

Single Covariate Levels Estimate 

Standard 

Error Lower CL 

Upper 

CL Z p-value 

Intercept -1.27 0.59 -2.43 -0.12 -2.16 0.0309

Plastic Use 0 – No plastic 0.00 0.95 -1.87 1.87 0 1

1 – Plastic 0.00 0.00 0.00 0.00 

Intercept -1.27 0.74 -2.72 0.18 -1.72 0.0857

Phase I – Plastic/Rule Cleaning 0.17 0.92 -1.62 1.97 0.19 0.849

III – No Plastic/Rule Cleaning 0.00 0.00 0.00 0.00 

Intercept -1.10 0.63 -2.32 0.13 -1.76 0.079

1-High -0.85 0.75 -2.32 0.63 -1.13 0.2598

2-Medium 0.00 0.63 -1.23 1.23 0 1 Intensity-level 

3-Low 0.00 0.00 0.00 0.00 

Intercept -1.10 0.54 -2.17 -0.03 -2.02 0.0436

Building Type COF -0.85 0.97 -2.76 1.06 -0.87 0.3845

Residential Housing 0.00 0.00 0.00 0.00 

Intercept -1.10 0.60 -2.28 0.08 -1.82 0.0682

C2 -0.85 1.01 -2.82 1.13 -0.84 0.4005

C3 0.31 1.13 -1.90 2.52 0.27 0.7834

Contractor 

C4 0.00 0.00 0.00 0.00 

Intercept 0.51 0.60 -0.66 1.68 0.86 0.3916

Tile -2.71 1.02 -4.71 -0.70 -2.65 0.0081

Vinyl -2.91 0.90 -4.68 -1.14 -3.22 0.0013

Floor Type 

Wood 0.00 0.00 0.00 0.00 

Intercept 0.00 0.79 -1.55 1.55 0 1

Fair -1.10 0.92 -2.90 0.71 -1.19 0.2326

Good -2.56 1.20 -4.91 -0.22 -2.15 0.0319

Floor Condition 

Poor 0.00 0.00 0.00 0.00 
7-36 

Single Covariate Levels Estimate 

Standard 

Error Lower CL 

Upper 

CL Z p-value 

Intercept -1.03 0.81 -2.61 0.55 -1.28 0.2001 Disturbed Area 

Disturbed Area -0.01 0.02 -0.04 0.02 -0.55 0.5804

Avg. Paint Lead Intercept -1.83 0.79 -3.38 -0.27 -2.3 0.0213

Level Avg. Paint Lead Level 0.11 0.12 -0.12 0.34 0.97 0.3302

Post-work Avg. Intercept -1.85 0.58 -2.99 -0.71 -3.18 0.0015

Floor Lead Post-work Avg. Floor Lead 0.00 0.00 0.00 0.00 2.17 0.0299

Post-work GM Intercept -1.86 0.60 -3.03 -0.69 -3.12 0.0018

Floor Lead Post-work GM Floor Lead 0.00 0.00 0.00 0.00 2.09 0.0362

Post-cleaning Intercept -3.14 0.63 -4.38 -1.90 -4.97 <.0001

Avg. Floor Lead Post-cleaning Avg. Floor Lead 0.04 0.01 0.02 0.06 3.28 0.001

Post-cleaning Intercept -3.40 0.70 -4.78 -2.03 -4.84 <.0001

GM Floor Lead Post-cleaning GM Floor Lead 0.06 0.01 0.03 0.08 3.97 <.0001

Model Set 2a – Probability of Single Floor Dust Wipe Failing Clearance, All Jobs 

The analyses presented for Model Sets 1a-1c were repeated using probability of one or more 

floor dust wipes failing clearance within the multiple post-verification floor samples collected 

from within the work room of each experiment. The previous models focused on the proportion 

of post-verification floor dust-wipe samples from the workroom that failed clearance (which is a 

slightly different response variable). As before, each variable being considered was included in a 

single covariate logistic regression model to assess its predictive ability on probability of a floor 

dust wipe failing clearance. Analyses by Job Type are not included in the results because there 

were too many categories for the amount of data available. From review of Table 7-19 that 

presents p-values indicating the overall statistical significance of each variable considered, the 

variables identified as statistically significant are similar to those identified in the first model set. 

Variables that were predictive of probability of a floor dust wipe failing clearance (at a .05 

significance level) were: 

• Restricted status (p-value=.01) 

• Building type (p-value<.01) 

• Floor type (p-value<.01) 

• Floor condition (p-value<.01) 

• Post-work average (p-value=.04) and GM (p-value<.01) floor lead levels 

• Post-cleaning average (p-value<.01) and GM (p-value<.01) floor lead levels 

Within Floor Type, there is evidence that both Tile and Vinyl floors had significantly lower 

probability of clearance floor wipe failure than Wood floors with estimates of -3.92 and -2.84, 

respectively. Similarly, both Good and Fair floor conditions had significantly lower probability 

of failure than floors in Poor condition. Although the overall significance of Intensity Level did 

not reach the .05 level, Table 7-20 indicates that there were significant differences between 

levels of this variable. The estimate of 1.59 for Medium intensity indicates a significantly higher 

probability of floor wipe failure compared to the Low intensity jobs (p-value of .0493). 

Model Set 2b – Probability of Single Floor Dust Wipe Failing Clearance, Non-restricted Jobs 

As noted previously, limiting the analysis to only the 32 experiments that used non-restricted 

jobs eliminates about 47 percent of the data. Table 7-19 indicates that the statistically significant 
7-37 

predictors of probability of floor dust wipe clearance failure are Floor Condition, Post-work 

Average and GM Floor Lead Levels, and Post-cleaning Average and GM Floor Lead Levels. 

Within Floor Condition the estimate of -3.78 for Good floors has a significantly lower 

probability of failure than floors in Poor condition; however the comparison of Fair condition 

floors to Poor condition floors results in a p-value of .087, only borderline significant likely 

because of the limited data set. 

Model Set 2c – Probability of Single Floor Dust Wipe Failing Clearance, Non-restricted Jobs 

with Rule Cleaning 

Following narrowing of the data set further to include only those non-restricted jobs done with 

Rule Cleaning, only Post-work Average and GM Floor Lead Levels were left as statistically 

significant predictors of probability of floor wipe failure as Floor Condition and Post-cleaning 

Average and GM Floor Lead Levels were all borderline significant with p-values ranging from 

.064 to .075. 
7-38 

Table 7-19. Single Covariate Logistic Regression Modeling Results for Probability of 

Failed Post-verification Floor Wipe 

Model Source DF Chi Square 

Estimate p-value 

Cleaning Method 1 0.77 0.3812 

Plastic Use 1 0.09 0.7693 

Phase 3 1.36 0.714 

Restricted 1 6.29 0.0121 

Intensity Level 2 4.54 0.1033 

Building type 1 7.47 0.0063 

Contractor 2 5.71 0.0574 

Floor Type 2 11.98 0.0025 

Floor Condition 2 20.99 <.0001 

Disturbed Area 1 1.24 0.2651 

Paint Lead Level 1 0.85 0.3576 

Post-work Avg. Floor Lead 1 4.25 0.0392 

Post-work GM Floor Lead 1 19.19 <.0001 

Post-cleaning Avg. Floor Lead 1 7.5 0.0062 

Set 2a: All Jobs 

Post-cleaning GM Floor Lead 1 8.63 0.0033 

Cleaning Method 1 0.21 0.6484 

Plastic Use 1 0.14 0.7051 

Phase 3 1.59 0.6608 

Intensity Level 2 0.1 0.9528 

Building type 1 1.36 0.244 

Contractor 2 3.12 0.2096 

Floor Condition 2 8.84 0.0121 

Disturbed Area 1 0.64 0.4241 

Paint Lead Level 1 0.18 0.6711 

Post-work Avg. Floor Lead 1 10.78 0.001 

Post-work GM Floor Lead 1 7.61 0.0058 

Post-cleaning Avg. Floor Lead 1 6.41 0.0114 

Set 2b: Restricted 

Jobs 

Post-cleaning GM Floor Lead 1 6.21 0.0127 

Plastic Use 1 0.21 0.6462 

Phase 1 0.55 0.4591 

Intensity Level 2 0.37 0.8311 

Building type 1 0.91 0.3414 

Contractor 2 1.23 0.5403 

Floor Condition 2 5.19 0.0748 

Disturbed Area 1 0.77 0.3816 

Paint Lead Level 1 0.64 0.4245 

Post-work Avg. Floor Lead 1 6.45 0.0111 

Post-work GM Floor Lead 1 5.37 0.0205 

Post-cleaning Avg. Floor Lead 1 3.18 0.0746 

Set 2c: Restricted 

Jobs with Rule 

Cleanings 

Post-cleaning GM Floor Lead 1 3.44 0.0635 
7-39 

Table 7-20. Single Covariate Model Results for Probability of Failed Post-verification 

Floor Wipe 

Single Covariate Levels Estimate 

Standard 

Error Lower CL 

Upper 

CL Z p-value 

Intercept 0.27 0.43 -0.58 1.11 0.62 0.5336

Cleaning Method 0=Baseline Method 0.42 0.49 -0.53 1.38 0.88 0.3812

1=Rule Method 0.00 0.00 0.00 0.00 

Intercept 0.55 0.51 -0.45 1.54 1.08 0.2811

Plastic Use 0 – No plastic -0.14 0.48 -1.08 0.80 -0.29 0.7693

1 – Plastic 0.00 0.00 0.00 0.00 

Intercept 1.01 0.75 -0.46 2.48 1.35 0.1784

I – Plastic/Rule Cleaning -0.10 0.54 -1.15 0.96 -0.18 0.8594

II – Plastic/Baseline Cleaning -0.61 0.69 -1.96 0.75 -0.88 0.3806

III – No Plastic/Rule Cleaning -1.15 1.00 -3.10 0.81 -1.15 0.2515

Phase 

IV – No Plastic/Baseline Cleaning 0.00 0.00 0.00 0.00 

Intercept -0.13 0.46 -1.03 0.78 -0.27 0.7853

Restricted Job 1-yes 1.42 0.57 0.31 2.54 2.51 0.0121

2-no 0.00 0.00 0.00 0.00 

Intercept -0.20 0.65 -1.47 1.07 -0.31 0.7572

1-High 0.61 0.67 -0.72 1.93 0.9 0.3691

2-Medium 1.59 0.81 0.00 3.17 1.97 0.0493

Intensity-level 

3-Low 0.00 0.00 0.00 0.00 

Intercept 0.99 0.43 0.15 1.83 2.3 0.0214

Building Type COF -2.60 0.95 -4.46 -0.74 -2.73 0.0063

Residential Housing 0.00 0.00 0.00 0.00 

Intercept 0.49 0.59 -0.67 1.64 0.82 0.4095

C2 -0.69 0.88 -2.41 1.04 -0.78 0.4349

C3 1.12 0.79 -0.42 2.67 1.43 0.1542

Contractor 

C4 0.00 0.00 0.00 0.00 

Intercept 3.04 0.92 1.23 4.85 3.3 0.001

Tile -3.92 1.14 -6.15 -1.69 -3.44 0.0006

Vinyl -2.84 1.09 -4.99 -0.70 -2.6 0.0093

Floor Type 

Wood 0.00 0.00 0.00 0.00 

Intercept 2.53 0.54 1.47 3.58 4.7 <.0001

Fair -1.97 0.74 -3.41 -0.52 -2.67 0.0075

Good -3.69 0.81 -5.28 -2.10 -4.55 <.0001

Floor Condition 

Poor 0.00 0.00 0.00 0.00 

Intercept 0.01 0.65 -1.27 1.29 0.02 0.9863 Disturbed Area 

Disturbed Area 0.01 0.01 -0.01 0.03 1.11 0.2651

Avg. Paint Lead Intercept 0.00 0.46 -0.91 0.91 0 0.9977

Level Avg. Paint Lead Level 0.13 0.14 -0.14 0.40 0.92 0.3576

Post-work Avg. Intercept -1.18 0.68 -2.51 0.15 -1.74 0.0823

Floor Lead Post-work Avg. Floor Lead 0.00 0.00 0.00 0.00 2.06 0.0392

Post-work GM Intercept -1.82 0.57 -2.94 -0.70 -3.18 0.0015

Floor Lead Post-work GM Floor Lead 0.00 0.00 0.00 0.00 4.38 <.0001

Post-cleaning Intercept -3.70 1.30 -6.26 -1.15 -2.84 0.0045

Avg. Floor Lead Post-cleaning Avg. Floor Lead 0.09 0.03 0.03 0.16 2.74 0.0062

Post-cleaning Intercept -4.24 1.55 -7.28 -1.21 -2.74 0.0061

GM Floor Lead Post-cleaning GM Floor Lead 0.13 0.04 0.04 0.21 2.94 0.0033
7-40 

Table 7-21. Single Covariate Model Results for Probability of Failed Post-verification 

Floor Wipe across Non-restricted Jobs 

Single Covariate Levels Estimate 

Standard 

Error Lower CL 

Upper 

CL Z p-value 

Intercept -0.25 0.54 -1.32 0.82 -0.46 0.6443

Cleaning Method 0=Baseline Method 0.25 0.55 -0.83 1.33 0.46 0.6484

1=Rule Method 0.00 0.00 0.00 0.00 

Intercept -0.25 0.57 -1.37 0.86 -0.44 0.6583

Plastic Use 0 – No plastic 0.25 0.66 -1.05 1.55 0.38 0.7051

1 – Plastic 0.00 0.00 0.00 0.00 

Intercept 0.51 0.78 -1.02 2.05 0.65 0.5142

I – Plastic/Rule Cleaning -0.22 0.81 -1.81 1.36 -0.28 0.7823

II – Plastic/Baseline Cleaning -1.02 0.91 -2.80 0.76 -1.12 0.2612

III – No Plastic/Rule Cleaning -1.02 1.03 -3.05 1.00 -0.99 0.3226

Phase 

IV – No Plastic/Baseline Cleaning 0.00 0.00 0.00 0.00 

Intercept -0.20 0.65 -1.47 1.07 -0.31 0.7572

1-High 0.20 0.91 -1.57 1.98 0.22 0.8246

2-Medium 0.20 0.65 -1.07 1.47 0.31 0.7572

Intensity-level 

3-Low 0.00 0.00 0.00 0.00 

Intercept 0.17 0.54 -0.89 1.23 0.31 0.757

Building Type COF -1.27 1.09 -3.40 0.86 -1.16 0.244

Residential Housing 0.00 0.00 0.00 0.00 

Intercept -0.15 0.76 -1.65 1.34 -0.2 0.8401

C2 -0.94 1.21 -3.32 1.43 -0.78 0.4364

C3 1.00 0.99 -0.94 2.94 1.01 0.3125

Contractor 

C4 0.00 0.00 0.00 0.00 

Intercept 2.08 0.85 0.42 3.74 2.45 0.0142

Fair -1.86 1.08 -3.98 0.27 -1.71 0.0866

Good -3.78 1.28 -6.28 -1.28 -2.97 0.003

Floor Condition 

Poor 0.00 0.00 0.00 0.00 

Intercept -0.51 0.81 -2.10 1.08 -0.63 0.5316 Disturbed Area 

Disturbed Area 0.01 0.02 -0.02 0.05 0.8 0.4241

Avg. Paint Lead Intercept -0.38 0.65 -1.65 0.89 -0.58 0.5613

Level Avg. Paint Lead Level 0.06 0.15 -0.23 0.35 0.42 0.6711

Post-work Avg. Intercept -1.75 0.66 -3.04 -0.45 -2.65 0.0081

Floor Lead Post-work Avg. Floor Lead 0.00 0.00 0.00 0.00 3.28 0.001

Post-work GM Intercept -1.90 0.65 -3.17 -0.63 -2.93 0.0034

Floor Lead Post-work GM Floor Lead 0.00 0.00 0.00 0.00 2.76 0.0058

Post-cleaning Intercept -3.23 1.23 -5.65 -0.82 -2.62 0.0087

Avg. Floor Lead Post-cleaning Avg. Floor Lead 0.07 0.03 0.02 0.13 2.53 0.0114

Post-cleaning Intercept -3.61 1.48 -6.51 -0.72 -2.44 0.0145

GM Floor Lead Post-cleaning GM Floor Lead 0.11 0.04 0.02 0.19 2.49 0.0127
7-41 

Table 7-22. Single Covariate Model Results for Probability of Failed Post-verification 

Floor Wipe across Non-restricted Jobs Using Rule Cleaning 

Single Covariate Levels Estimate 

Standard 

Error Lower CL 

Upper 

CL Z p-value 

Intercept 0.00 0.79 -1.55 1.55 0 1

Plastic Use 0 – No plastic -0.51 1.11 -2.69 1.67 -0.46 0.6462

1 – Plastic 0.00 0.00 0.00 0.00 

Intercept -0.51 0.78 -2.05 1.02 -0.65 0.5142

Phase I – Plastic/Rule Cleaning 0.80 1.08 -1.32 2.91 0.74 0.4591

III – No Plastic/Rule Cleaning 0.00 0.00 0.00 0.00 

Intercept -0.41 0.69 -1.75 0.94 -0.59 0.5552

1-High 0.41 1.07 -1.69 2.50 0.38 0.704

2-Medium 0.41 0.69 -0.94 1.75 0.59 0.5552

Intensity-level 

3-Low 0.00 0.00 0.00 0.00 

Intercept 0.00 0.67 -1.31 1.31 0 1

Building Type COF -1.10 1.15 -3.36 1.16 -0.95 0.3414

Residential Housing 0.00 0.00 0.00 0.00 

Intercept 0.29 0.90 -1.47 2.05 0.32 0.7486

C2 -1.39 1.30 -3.94 1.17 -1.06 0.2869

C3 -0.29 1.34 -2.92 2.35 -0.21 0.8305

Contractor 

C4 0.00 0.00 0.00 0.00 

Intercept 1.10 1.15 -1.16 3.36 0.95 0.3414

Fair 0.00 1.63 -3.20 3.20 0 1

Good -2.89 1.51 -5.85 0.07 -1.92 0.0555

Floor Condition 

Poor 0.00 0.00 0.00 0.00 

Intercept -0.75 0.90 -2.51 1.01 -0.84 0.4025 Disturbed Area 

Disturbed Area 0.02 0.02 -0.02 0.06 0.87 0.3816

Avg. Paint Lead Intercept -0.88 0.97 -2.77 1.01 -0.91 0.3625

Level Avg. Paint Lead Level 0.14 0.17 -0.20 0.48 0.8 0.4245

Post-work Avg. Intercept -5.55 2.67 -10.79 -0.31 -2.07 0.038

Floor Lead Post-work Avg. Floor Lead 0.00 0.00 0.00 0.00 2.54 0.0111

Post-work GM Intercept -4.59 1.21 -6.97 -2.22 -3.79 0.0001

Floor Lead Post-work GM Floor Lead 0.00 0.00 0.00 0.01 2.32 0.0205

Post-cleaning Intercept -3.23 2.00 -7.15 0.69 -1.62 0.1063

Avg. Floor Lead Post-cleaning Avg. Floor Lead 0.10 0.06 -0.01 0.21 1.78 0.0746

Post-cleaning Intercept -3.40 1.98 -7.28 0.49 -1.71 0.0868

GM Floor Lead Post-cleaning GM Floor Lead 0.14 0.07 -0.01 0.28 1.86 0.0635
7-42 

Model Set 3a – Proportion of Failing Sill Dust Wipes, All Jobs 

Because only one post-verification window sill sample was obtained during the study, the 

analyses of cleaning verification effectiveness on window sills are limited to analyzing the 

probability of obtaining a post-verification wipe >250 μg/ft2

. Additionally, because fewer data 

points were available for analysis, a smaller number of the variables under consideration were 

able to be modeled. 

When the full set of interior experiments was analyzed, Table 7-23 reports that only Post-work 

Average and GM Floor Lead Levels and Post-cleaning Average and GM Floor Lead Level were 

found to be significant predictors of probability of window sill wipe failure based on the single 

covariate logistic regression modeling. Each of the four variables yielded p-values <.001. 

Unlike the floor modeling, Plastic Use and Phase were found to be borderline significant with pvalues of .05 and .07, respectively. As seen in Table 7-24, the probability of achieving a postverification sill sample above 250 μg/ft2

 was higher in No Plastic experiments as indicated by the 

parameter estimate of 1.19 compared to the experiments using Plastic. Within the Phase 

variable, there is evidence that both the Plastic/Rule Cleaning and Plastic/Baseline Cleaning 

options yielded lower probability of clearance sill wipe failure than the No Plastic/Baseline 

Cleaning option with estimates of -1.10 and -1.95, respectively and associated p-values of .059 

and .042. 

Model Set 3b – Proportion of Failing Sill Dust Wipes, Non-restricted Jobs 

When limiting the window sill data to non-restricted jobs only, none of the variables considered 

reach the .05 level of significance for predicting probability of a post-verification sill sample 

above 250 μg/ft2

. On the other hand, Disturbed Area (p-value=.076), Paint Lead Level (pvalue=.086), Post-cleaning average floor lead level (p-value=.099), and Post-cleaning GM floor 

lead level (p-value=.099) were all borderline significant. 

Model Set 3c – Proportion of Failing Sill Dust Wipes, Non-restricted Jobs with Rule Cleaning 

After limiting the window sill data further to non-restricted jobs that used Rule Cleaning, three 

variables were found to be significant predictors of probability of a post-verification sill sample 

above 250 μg/ft2

 - Disturbed Area (p-value=.004), Post-cleaning average floor lead level (pvalue=.030), and Post-cleaning GM floor lead level (p-value=.030). 
7-43 

Table 7-23. Single Covariate Logistic Regression Modeling Results for Probability of 

Failed Window Sill CV 

Model Source DF Chi Square 

Estimate p-value 

Cleaning Method 1 1.14 0.2847 

Plastic Use 1 3.76 0.0525 

Phase 3 7.05 0.0704 

Restricted 1 1.05 0.3063 

Intensity Level 2 0.19 0.9085 

Disturbed Area 1 0.23 0.6333 

Paint Lead Level 1 2.24 0.1342 

Post-work Sill Lead 1 14.51 0.0001 

Set 3a: All Jobs 

Post-cleaning Sill Lead 1 12.05 0.0005 

Cleaning Method 1 2.01 0.1561 

Disturbed Area 1 3.15 0.0761 

Paint Lead Level 1 2.94 0.0864 

Post-work Sill Lead 1 0.44 0.5057 

Set 3b: Restricted 

Jobs 

Post-cleaning Sill Lead 1 2.72 0.0992 

Disturbed Area 1 8.15 0.0043 

Paint Lead Level 1 0.32 0.5724 

Set 3c: Restricted 

Jobs with Rule 

Cleanings Post-cleaning Sill Lead 1 4.7 0.0302 
7-44 

Table 7-24. Single Covariate Model Results for Probability of Failing a Single Postverification Window Sill Wipe Sample 

Single Covariate Levels Estimate 

Standard 

Error Lower CL 

Upper 

CL Z p-value 

Intercept -1.61 0.59 -2.76 -0.46 -2.75 0.006

Cleaning Method 0=Baseline Method 0.22 0.21 -0.19 0.63 1.07 0.2847

1=Rule Method 0.00 0.00 0.00 0.00 

Intercept -2.20 0.79 -3.74 -0.65 -2.79 0.0053

Plastic Use 0 – No plastic 1.19 0.61 -0.01 2.38 1.94 0.0525

1 – Plastic 0.00 0.00 0.00 0.00 

Intercept -0.69 0.51 -1.69 0.31 -1.36 0.174

I – Plastic/Rule Cleaning -1.10 0.58 -2.24 0.04 -1.89 0.0587

II – Plastic/Baseline Cleaning -1.95 0.96 -3.82 -0.07 -2.03 0.0419

III – No Plastic/Rule Cleaning -0.69 0.46 -1.59 0.21 -1.51 0.1304

Phase 

IV – No Plastic/Baseline Cleaning 0.00 0.00 0.00 0.00 

Intercept -1.95 0.65 -3.21 -0.68 -3.01 0.0026

Restricted Job 1-yes 0.85 0.83 -0.78 2.47 1.02 0.3063

2-no 0.00 0.00 0.00 0.00 

Intercept -1.39 0.68 -2.72 -0.06 -2.04 0.0412

1-High 0.00 1.21 -2.37 2.37 0 1

2-Medium -0.35 0.82 -1.95 1.25 -0.43 0.6698 Intensity-level 

3-Low 0.00 0.00 0.00 0.00 

Intercept -1.16 0.71 -2.56 0.24 -1.63 0.1037 Disturbed Area 

Disturbed Area -0.01 0.02 -0.04 0.03 -0.48 0.6333

Avg. Paint Lead Intercept -2.18 0.60 -3.35 -1.01 -3.66 0.0003

Level Avg. Paint Lead Level 0.16 0.11 -0.05 0.37 1.5 0.1342

Post-work Sill Intercept -2.01 0.58 -3.15 -0.87 -3.46 0.0005

Lead Post-work Sill Lead 0.00 0.00 0.00 0.00 3.81 0.0001

Post-cleaning Sill Intercept -2.94 0.63 -4.18 -1.70 -4.64 <.0001

Lead Post-cleaning Sill Lead 0.00 0.00 0.00 0.00 3.47 0.0005

Table 7-25. Single Covariate Model Results for Probability of Failing a Single Postverification Window Sill Wipe Sample across Non-restricted Jobs 

Single Covariate Levels Estimate 

Standard 

Error Lower CL 

Upper 

CL Z p-value 

Intercept -2.71 1.05 -4.77 -0.65 -2.58 0.0099

Cleaning Method 0=Baseline Method 1.24 0.88 -0.47 2.96 1.42 0.1561

1=Rule Method 0.00 0.00 0.00 0.00 

Intercept -0.25 1.01 -2.23 1.74 -0.24 0.8083 Disturbed Area 

Disturbed Area -0.12 0.07 -0.26 0.01 -1.77 0.0761

Avg. Paint Lead Intercept -1.21 0.81 -2.80 0.37 -1.5 0.1334

Level Avg. Paint Lead Level -0.22 0.13 -0.46 0.03 -1.71 0.0864

Post-work Sill Intercept -2.02 0.61 -3.21 -0.83 -3.33 0.0009

Lead Post-work Sill Lead 0.00 0.00 0.00 0.00 0.67 0.5057

Post-cleaning Sill Intercept -2.46 0.71 -3.86 -1.07 -3.46 0.0005

Lead Post-cleaning Sill Lead 0.00 0.00 0.00 0.00 1.65 0.0992
7-45 

Table 7-26. Single Covariate Model Results for Probability of Failing a Single Postverification Window Sill Wipe Sample across Non-restricted Jobs Using Rule Cleaning 

Single Covariate Levels Estimate 

Standard 

Error Lower CL 

Upper 

CL Z p-value 

Intercept -1.44 1.21 -3.81 0.93 -1.19 0.2333 Disturbed Area 

Disturbed Area -0.08 0.03 -0.13 -0.03 -2.85 0.0043

Avg. Paint Lead Intercept -2.51 1.11 -4.69 -0.33 -2.26 0.024

Level Avg. Paint Lead Level -0.05 0.08 -0.21 0.11 -0.56 0.5724

Post-cleaning Sill Intercept -1.76 1.19 -4.08 0.56 -1.49 0.1374

Lead Post-cleaning Sill Lead -0.03 0.01 -0.05 0.00 -2.17 0.0302

7.6.2. Multivariate Modeling Results

Based on the results of the single covariate logistic regression modeling, multivariate logistic 

regression models were built to assess the combined effect of the multiple factors influencing the 

post-verification clearance failures. Multivariate models were built for the full experiment and 

non-restricted jobs analyses, but not for the non-restricted jobs with Rule cleaning data because 

of the limited amount of data. The window sill, as well, did not support development of a 

multivariate model because of the limited amount of data. 

Model Set 1 - Proportion of Failed Post-verification Floor Wipe Samples

Table 7-27 presents the multivariate regression model develop for Model Set 1a for proportion of 

failed post-verification floor wipe samples using the full set of experiments. Job Type, Floor 

Condition, and Post-cleaning Average Floor Lead were the three variables included in the final 

model based on this data set. The Type III p-values for Floor Condition (p-value=.03) and Postcleaning Average Floor Lead (p-value=.01) indicate that these two variables are significant 

predictors of proportion of failed post-verification floor wipe samples. Job Type, although many 

of the jobs differ significantly from the Kitchen Gut job in terms of their predictive ability, did 

not reach the .05 level of significance overall within the model. Its inclusion in the model, 

however, provides a better fit. 

Table 7-27. Multivariate Model Results for Proportion of Failed Post-verification Floor 

Wipe Samples across all Experiments 

Covariate Levels Estimate 

Standard 

Error 

Lower 

CL 

Upper 

CL Z p-value 

Type III 

p-value 

Intercept Intercept -2.15 0.51 -3.14 -1.16 -4.24 <.0001

I1-Cut Outs -1.42 0.41 -2.21 -0.62 -3.48 0.0005

I2-Replace Windows 0.39 0.68 -0.93 1.72 0.58 0.5612

I3-Scrape Surface 1.55 0.63 0.31 2.78 2.46 0.014

I4-Scrape Door 0.31 0.91 -1.49 2.10 0.34 0.7373

I5-Heat gun < 1100 degrees 2.53 0.66 1.23 3.83 3.82 0.0001

I6-Heat gun > 1100 degrees 1.70 0.76 0.21 3.18 2.24 0.0252

Job Type 

I7-Kitchen Gut 0.00 0.00 0.00 0.00 

<.0001

Fair -0.29 0.44 -1.15 0.57 -0.66 0.5086

Floor Condition Good -2.72 0.48 -3.66 -1.78 -5.66 <.0001

Poor 0.00 0.00 0.00 0.00 

<.0001

Post-cleaning 

Floor Lead Post-cleaning Avg. Floor Lead 0.02 0.00 0.01 0.03 6.03 <.0001 <.0001
7-46 

Table 7-28 presents the multivariate regression model developed for Model Set 1b for proportion 

of failed post-verification floor wipe samples using experiments done with non-restricted 

practices. Floor Condition dropped out of this model leaving only Job Type and Post-cleaning 

GM Floor Lead as the two explanatory variables included in the final model. The Type III pvalues for Job Type and Post-cleaning GM Floor Lead were both at about .06 indicating 

borderline statistical significance. 

Table 7-28. Multivariate Model Results for Proportion of Failed Post-verification Floor 

Wipe Samples across Non-restricted Jobs 

Covariate Levels Estimate 

Standard 

Error 

Lower 

CL 

Upper 

CL Z p-value 

Type III 

p-value 

Intercept Intercept -2.48 0.51 -3.47 -1.48 -4.86 <.0001

I1-Cut Outs -1.88 0.60 -3.06 -0.70 -3.11 0.0019

I2-Replace Windows 0.71 0.77 -0.80 2.22 0.92 0.3555

I5-Heat gun < 1100 degrees 0.32 0.42 -0.50 1.14 0.76 0.4463 Job Type 

I7-Kitchen Gut 0.00 0.00 0.00 0.00 

.0482

Post-cleaning 

Floor Lead Post-cleaning GM Floor Lead 0.02 0.01 0.01 0.04 2.61 0.0091 .0091

Model Set 2 – Probability of a Post-verification Floor Wipe Sample Exceeding 40 μg/ft2

Table 7-29 presents the multivariate regression model developed for Model Set 2a for probability 

of a post-verification floor wipe sample failing clearance. Restricted Status, Floor Condition, 

and Post-work Average Floor Lead were the three variables included in the final model. The 

Type III p-value for Floor Condition (p-value=.03) indicated it as a significant predictors of 

probability of a post-verification floor wipe sample failing clearance, although the p-value for 

Post-work Floor Lead was just a bit over the .05 level. 

Table 7-29. Multivariate Model Results for Probability of Failed Post-verification Floor 

Wipe across all Experiments 

Covariate Levels Estimate 

Standard 

Error 

Lower 

CL 

Upper 

CL Z p-value 

Type III 

p-value 

Intercept Intercept 0.90 0.36 0.19 1.61 2.48 0.013

Fair -1.63 0.74 -3.09 -0.17 -2.19 0.0283

Floor Condition Good -2.96 0.71 -4.36 -1.56 -4.15 <.0001

Poor 0.00 0.00 0.00 0.00 

.0001

Post-work Floor 

Lead Post-work Avg. Floor Lead 0.00 0.00 0.00 0.00 1.94 0.0519 .0519

Table 7-30 presents the multivariate regression model developed for Model Set 2a for probability 

of a post-verification floor wipe sample failing clearance using only experiments done with nonrestricted practices. Floor Condition and Post-work Average Floor Lead were the two variables 

included in the final model. The Type III p-values for Floor Condition (p-value=.053) and Postwork Floor Lead (p-value=.07) were a bit over the .05 level, but these two covariates performed 

best at explaining the variability of the probability of a post-verification floor wipe sample 

failing clearance. 
7-47 

Table 7-30. Multivariate Model Results for Probability of Failed Post-verification Floor 

Wipe across Non-restricted Jobs 

Covariate Levels Estimate 

Standard 

Error 

Lower 

CL 

Upper 

CL Z p-value 

Type III 

p-value 

Intercept Intercept 0.68 0.52 -0.34 1.71 1.3 0.1929

Fair -2.19 0.87 -3.89 -0.49 -2.53 0.0116

Floor Condition Good -3.88 0.87 -5.58 -2.17 -4.46 <.0001

Poor 0.00 0.00 0.00 0.00 

<.0001

Post-work Floor 

Lead Post-work Avg. Floor Lead 0.00 0.00 0.00 0.00 3.38 0.0007 .0007

7.6.3. Summary of Results

Between the single covariate and multivariate modeling of post-verification floor wipes that 

exceed 40 μg/ft2, the primary variables found to be best predict these failures were Floor 

Condition and Post-work and Post-cleaning Lead Levels. Job Type and the Restricted Status of 

jobs also had some predictive ability within some of these models. Although other potential 

covariates such as Building Type, Floor Type, and Intensity Level were found to have some 

relationship to post-verification floor wipes exceeding 40 μg/ft2, they were not good predictors 

when considered together with the other covariates. Thus, it could be that covariates such as Job 

Type, Restricted Status, and Intensity Level were ultimately correlated with Post-work and Postcleaning lead levels, which is the best predictor of whether actual lead levels remaining on floors 

following the cleaning verification process were below the clearance level. 

The window sill post-verification clearance failure results were not as clear. Similar to the floor 

models, post-work and post-cleaning sill lead level appeared to be one of the best predictors of 

the probability of achieving a post-verification window sill value > 250 μg/ft2. A number of 

other potential covariates such as amount of area disturbed and paint lead level, indicated some 

predictive ability but did not reach a level of statistical significance. 

Development of multivariate models in order to identify factors that are predictive of postverification clearance failures in the Work Room was challenged by the relatively small number 

of experiments completed in the RRP Field Study (particularly when limiting the analyses to 

non-restricted work practices). The single covariate models, however, provide important insight 

into the factors that merit further investigation (as well as those factors that do not seem to be 

predictive, such as the use of rule cleaning or plastic). 
8-1 

8. Quality Assurance and Quality Control Results 

8.1. Field Audit Results 

8.1.1. Site Selection Audit

The Battelle Quality Assurance officer conducted audits of the X-ray fluorescence (XRF) 

measurement procedure and the methodology for collection of paint chip samples on September 

11, 2006, and October 24, 2006, respectively. Both audits were performed by observing actual 

work done in the field. The procedures as performed by the study technicians, including Battelle 

staff and subcontractors, followed those outlined in the Site Selection QAPP. Only minor 

suggestions, usually concerning documentation, were offered to the field staff, who immediately 

implemented the corrective actions as appropriate. 

8.1.2. Field Implementation

The Battelle Quality Assurance officer conducted three on-site field audits of renovation work 

and related environmental sampling. The first audit was of an exterior paint removal job in 

Columbus on October 19, 2006. Observed was the construction of the containment structure, use 

of personal protective equipment (PPE), manual paint removal, and sampling by collection of 

dust and paint chips accumulated on the dust collection trays, followed by subsequent take down 

of the containment structure. The procedures as performed by the field crew, including Battelle 

staff and subcontractors, followed those outlined in the Full Study QAPP. Personnel for the onsite RRP contractor were reminded that they must use the appropriate PPE, and they complied 

immediately; however, no major deficiencies were identified. 

An on-site audit of an interior window removal job (Phase III) in Columbus was performed on 

October 20, 2006. The Battelle auditor observed, among other tasks, removal and replacement 

of the window, personal and area air sampling, rule cleaning using HEPA vacuums followed by 

wet mopping, and cleaning verification. Specifically inspected was the method of dust wipe 

collection in the work, tool, and observation rooms. It was confirmed that the study technicians 

were following ASTM guidelines to properly collect wipe samples by using a proper “S” pattern 

and using as much of the wipe surface area as possible in order to maximize dust collection 

efficiency. The procedures as performed by the field crew, including Battelle staff and 

subcontractors, followed those outlined in the Full Study QAPP. 

A third on-site audit was conducted in Pittsburgh during an interior kitchen gutting (Phase II) on 

November 6, 2006. Essentially the same activities were observed as for the on-site field audit in 

Columbus on October 19, 2006, for the window removal job. Specifically inspected was the 

method of dust wipe collection in the work, tool, and observation rooms. It was confirmed that 

the study technicians were following ASTM guidelines to properly collect wipe samples. In 

general, the procedures as performed by the field crew, including Battelle staff and 

subcontractors, followed those outlined in the Full Study QAPP. 
8-2 

During all three field audits, no major deficiencies were identified; only minor suggestions, 

usually concerning documentation, were offered to the field staff, who immediately implemented 

corrective actions as appropriate. 

8.1.3. EPA Site Visits

EPA staff made four separate visits to observe the field work in the study, and provided written 

and oral reports to the Principal Investigator on their observations. The Principal Investigator 

reviewed the observations in these reports and responded promptly to any concerns. 

8.2. Laboratory Audit Results 

The Battelle Quality Assurance officer conducted an on-site, day-long inspection of the 

analytical laboratory, Schneider Laboratories, Incorporated (SLI), in Richmond, VA, on 

November 13, 2006. Reviewed were: all pertinent documentation, the lab’s organization and 

project staff responsibilities, elements of Quality Assurance and Quality Control, the staff 

training program, lab safety, document control, as well as a general review of the lab facilities, 

equipment, and software. In addition, a thorough review was performed of the procedures 

employed to prepare and analyze samples. During the course of the audit, no significant issues 

were identified that required follow-up by the Battelle Quality Assurance officer. A formal audit 

report was prepared and forwarded to Schneider staff and to project leaders. 

8.3. QC Sample Results, Issues, and Resolutions 

In general, the results of the analysis of the quality control (QC) samples revealed not only that 

field staff were handling samples appropriately, but also that the results from the contract 

analytical laboratory, Schneider Laboratories, Inc., (SLI) were accurate and reproducible. 

A number of different external QC samples were prepared. Blank wipes were prepared by field 

technicians who donned clean gloves, opened the wipe packet, and placed the unused wipe into a 

clean, prelabeled sample vial. Blank air cassettes were flow checked by passing a nominal 

amount of air through them (no more than approximately 6 L), then were capped and labeled. 

Spiked wipes and air cassettes were prepared by the Department of Environmental Services 

(DES) at the University of Cincinnati using National Institutes of Standards and Technology 

(NIST) Standard Reference Materials. The spikes were then inserted into the sample stream as 

blind performance evaluation samples to verify the integrity of the analytical results provided by 

SLI. 

Table 8-1 contains the results from analyzing the external quality control samples. 

As seen in Table 8-1, for both the spiked wipes and air cassette blanks, more than 95% of the 

external QC samples came back within the desired tolerance. Approximately 91% of the blank 

wipes showed values less than the laboratory’s reporting limit (10 μg lead), and over 95% of the 

blank wipes had lead amounts less than 20 μg. 
8-3 

Table 8-1. Summary of External QC Results 

Media QC 

Type 

Total 

Number 

Acceptable 

Tolerance 

Percent Within 

Tolerance 

Number Out 

Of Tolerance 

Percent Out 

Of Tolerance 

Wipe Spike 117 Bias < 20% 95.7 5 4.3 

Wipe Blank 113 Amount < RL† 91.2 10 8.8 

Air Spike 46 Bias < 20% 82.6 8 17.4 

Air Blank 66 Amount < RL 97.0 2 3.0 

†

RL = reporting limit; for wipes, 10 μg lead; for air cassettes, 2 μg lead

A total of eight of the spiked air cassettes were recovered beyond the acceptable bias range of 

20%; of these, four consecutively numbered samples (as labeled by UC DES) showed lead levels 

less than the reporting limit of 2 μg. DES was contacted and the most likely explanation was an 

error by the preparation laboratory - that blank cassettes were inadvertently mistaken for spiked 

cassettes. Excluding these four samples, 90% (42 of 46) of the external QC air cassettes 

demonstrated acceptable recoveries. 

In all cases in which the laboratory measured external QC samples outside the acceptable 

tolerance ranges, it was requested that samples be reanalyzed in order to confirm the original 

results. In all cases, the initial results were confirmed upon repeat analysis. 

An analysis of laboratory’s internal quality control data is shown in Table 8-2. These results 

indicate that the laboratory’s internal QC procedures were adequate and, except for the matrix 

spike, met the study’s QC requirements. 

Table 8-2. Schneider Laboratories Quality Control Data 

Schneider 

Laboratories QC Type 

Number of 

Samples 

QC Tolerance # Out of 

Tolerance 

% Out of 

Tolerance 

Reagent Blank 908 < RLa 0 0 

Wipe Blank 248 < RL 0 0 

Soil Blank 61 < RL 0 0 

Paint Blank 72 < RL 0 0 

Air Filter Blank 74 < RL 0 0 

Paint Control Sample 74 Bias < 20% 0 0 

Wipe Control Sample 248 Bias < 20% 0 0 

Soil Control Sample 61 Bias < 20% 0 0 

Air Filter Control Sample 148 Bias < 20% 0 0 

Calibration Verification 904 Bias < 15% 0 0 

Duplicates 133 RPDb < 25% 6 4.5% 

Replicates 454 RPDb < 25% 0 0 a

RL = Reporting Limit ; for most analyses, RL = 10 μg; for air, RL = 2 μg 

b

Relative percent deviation: RPD = |x1-x2|/[(x1+x2)/2]*100% 

Duplicate and replicate tolerances were calculated as relative percent deviation (RPD). A 

replicate analysis is one in which the sample extract is analyzed twice and is a measure of the 

repeatability of a measurement (instrument reproducibility). This is substantially different from 

a duplicate analysis in which a given sample is homogenized and split into two subsamples. 

Duplicate samples could only be prepared for matrices that could be subsampled, i.e., only for 
8-4 

paint chip and soil samples. Results from duplicate analyses provide a measure of the 

reproducibility of the sample handling and extraction procedures, superimposed onto any 

instrumental variability. Approximately 13% of the replicate analyses showed lead 

concentrations below the applicable reporting limit. In all cases, both sample and replicate 

values were below the applicable reporting limit; as such, all were within tolerance. 

Matrix spikes are prepared in a manner similar to a duplicate sample, with the exception that one 

of the subsamples was subsequently spiked with 200 μg of lead. In most cases, a sample to be 

prepared for duplicate analysis was also used for the matrix spike; thus a total of three 

subsamples were collected: one for the primary sample, one for the duplicate, and one for the 

matrix spike. The spike amount of 200 μg of lead, however, was generally only a small fraction 

of the total lead concentration in the samples. Thus, small variations in the amount of lead in the 

samples, due primarily to the heterogeneity of paint and soil samples, resulted in matrix spike 

recoveries generally outside of the specified tolerance. For example, one particular paint chip 

sample extract was found to contain 124,206 μg of lead and its duplicate sample showed 139,579 

μg lead (RPD = 11.7 %). The matrix spike should have had 124,406 μg of lead, but instead 

130,495 μg was found, which calculates to a spike recovery of (130,495 – 124,206 μg)/200 μg * 

100% = 3,144%. Given the relatively low spike amount, the ordinary variation between 

duplicate subsamples resulted in poor spike recoveries. 

8.4. Data Audit Process and Results 

Battelle’s Quality Assurance officer traced approximately 2% of the data (169 field and QC 

samples) acquired during the field study and subsequent laboratory analyses from the initial 

acquisition, through data reduction and statistical analysis to ensure the integrity of the results. 

All calculations performed on these data were verified as correct. Comments that stemmed from 

the data audit are listed below. 

• The need for recording actual batch IDs for environmental samples in the database was 

identified, in order to allow linking of QC results to samples in a given batch. If 

necessary, environmental data associated with out-of-tolerance QC samples could be 

flagged as potentially suspect. 

• Field blank and field spike samples were included in the database table containing all the 

environmental data. It seemed appropriate to move those data to the table containing 

QA/QC samples. 

8.5. Software Reviews 

EPA prepared test data sets of interior and exterior data that were processed using the descriptive 

and statistical summary programs used to summarize the study data. EPA reviewed the output 

resulting from the analysis of the test data sets and determined that the analytical programs 

performed as expected. 
9-1 

9.0 Conclusions 

Conclusions are presented in this section for each of the seven objectives specified in Section 

1.3. 

9.1 Objective 1: Effect of Intensity-level on Dust Lead Levels 

The results indicated that both initial intensity level and job type impacted post-work, postcleaning, and post-verification floor and sill lead levels. Data collected by the study indicated 

significant variability in the lead levels generated across the different jobs conducted. Using a 

power planer to remove paint from doors without exhaust controls generated significantly more 

lead than other interior jobs. On the other hand, cutting into walls to allow electrical, plumbing, 

or other work, generated significantly less lead than other jobs. On the exterior, jobs such as 

power sanding paint from walls generated large amounts of lead while dry scraping paint from a 

wall generated relatively less; however, these findings differed depending on whether the bulk 

debris and excessive dust generated by a job was included in the sample results. Removal of 

paint by torch burning left large amounts of lead in the dust collection trays as big chunks of 

paint were scraped from porch ceilings following heating with the torch; however, only one 

percent of the lead created by this work activity was measured by a dust wipe with the rest being 

work debris picked up by hand. 

9.2. Objective 2: Effect of Heavy Duty Polyethylene Plastic Sheeting on Interior Lead 

Levels 

Figure 6-3 indicates that use of plastic did not consistently result in lower geometric mean work 

room floor lead levels across job types at the post-cleaning phase. The use of plastic sheeting, 

however, did lower geometric means for door planing and high heat gun jobs as measured at the 

post-cleaning phase. Similar results are found with window sills, as seen in Figure 6-8. 

Modeling and hypothesis testing of the effect of plastic on lead levels on floors in the Work 

room was not statistically significant at either the post-cleaning (p-value = .15) or postverification stages (p-value = .10) for housing units when adjusted for job and interactions with 

job type. For window sills, statistical modeling and hypothesis testing also showed that the use 

of plastic was not statistically significant at either the post-cleaning or psot-verification stages for 

housing units. Using the combined housing unit and COF data, similar results were obtained. 

Conclusions about protective plastic are different when considering other parts of a house or 

building. Figure/Table C2.6b and C2.6c reported consistently lower geometric mean floor lead 

levels in the Tool and Observation rooms, respectively, with the use of plastic across all three 

sampling stages – although the differences were relatively small. For example, Tool room floor 

geometric mean lead levels were 41, 43, and 39 μg/ft2

 across post-work, post-cleaning, and postverification stages with plastic compared to 57, 61, and 79 μg/ft2

 without plastic; Observation 

room geometric mean levels were 18, 17, and 22 μg/ft2 with plastic compared to 30, 38, and 31 

μg/ft2

 without plastic. 

When modeling the Tool room floor levels, use of plastic was not significant at the post-work 

stage (p-value=.20, estimate=-0.32, combined data) adjusting for job type and was not significant 
9-2 

at the post-cleaning stage (p-value=.52, combined data) adjusting for job type and interactions 

with job type. At the post-verification stage, use of plastic was borderline significant using the 

combined data (p-value=.09, adjusted for job type) and significant (p-value=.03, adjusted for job 

type and post-work lead levels) using only the housing unit data. 

Findings for the Observation room floor levels differ somewhat depending on whether COF data 

are included in the analysis. For residential units only, modeling Observation room levels 

resulted in significantly lower levels when using plastic at all three stages with p-values of .02 at 

post-work (adjusted for job type) and <.01 at post-cleaning and post-verification (adjusted for job 

type and interactions with job type). When analyzing the combined data, the model predicts 

lower levels using plastic but the difference is borderline significant (p-value =.10, estimate= 

-0.46) at the post-work stage; significant at the post-cleaning stage (p-value=.01, estimate=-0.71) 

when adjusted for job type and average post-work work room floor lead; and not significant at 

post-verification (p-value=.34) using that same model. 

The statistical modeling did not find that the use of plastic significantly impacted sill lead levels 

in the Tool room at any of the three sampling stages. There is evidence, however, when 

analyzing the residential data of use of plastic leading to lower sill lead levels in the Observation 

room at post-cleaning (p-value =.03) and post-verification (p-value =.02) when adjusting for job 

type or post-work work room floor lead levels. 

9.3. Objective 3: Effect of Cleaning Method on Interior Lead Levels 

The data do provide evidence that the proposed rule cleaning method of HEPA vacuuming 

followed by wet mopping with a cleaning solution yielded lower lead levels than the baseline 

cleaning method. Analyzing differences in cleaning method is focused on the Work room, as 

little impact of cleaning method was observed in either of the two non-work rooms, which did 

not undergo any cleaning. Table C2.7a reports GM post-cleaning floor lead across all jobs of 34 

μg/ft2

 for the Rule cleaning and 75 μg/ft2 for the baseline cleaning. Figure 6-4, which plots postcleaning GM floor lead levels by job and cleaning method, reports lower levels across all job 

types except door planing. Figure 6-9 shows similar results for window sills. The statistical 

models verify these trends, reporting significantly lower post-cleaning floor lead levels after rule 

cleaning (p-value <.01). No significant difference is found between cleaning methods for floors 

at the post-verification stage. It should be noted that any cleaning verification failures after 

baseline cleaning led to recleanings by rule cleaning method in this study. Significantly lower 

work room window sill lead levels are also found at the post-cleaning (p-value<.01) stages 

following rule cleaning. Similar to floor lead levels, however, no significant difference based on 

cleaning method is found at the post-verification stage. Thus, it appears that the differences in 

lead levels between the two cleaning methods remaining after the initial cleaning stage were 

removed by the cleaning verification process conducted for all experiments regardless of 

cleaning method used. 

9.4. Objective 4: Migration of Lead Dust from Work Room to Adjacent Rooms 

The results indicated that lower levels of lead were measured in the Tool and Observation rooms 

when plastic was used during the work; however, mixed results were obtained in regards to the 
9-3 

statistical significance of those differences. The cleaning method used in the work room did not 

have a significant impact on lead levels in the non-study rooms. 

9.5. Objective 5: Effectiveness of Plastic Ground Coverings during Exterior Work 

The use of plastic ground coverings captured large amounts of lead which were considerably 

larger than the lead that was below the plastic coverings. When considering all the dust and 

debris that was captured on top of the Rule plastic, predicted ratios of lead measured on top of 

the Rule plastic to lead measured under the Rule plastic ranged from 66:1 to 2,291:1 across 

exterior jobs. The lowest lower 95% confidence interval bounds on those ratios were 12:1 and 

6:1, respectively, for the power sanding the torch burning jobs. Some jobs resulted in high lead 

levels measured in areas just outside the Rule plastic. 

9.6. Objective 6: Lead Levels Remaining Following Cleaning Verification Process 

The cleaning verification process as stated in the proposed rule resulted in decreases in lead 

levels, but under the conditions of the study was not always accurate in identifying the presence 

of levels above EPA standards for floors and sills. Factors such as floor condition, contractor 

performance, job type, and dust particle characteristics impacted the cleaning verification 

process in the study. As indicated in Section 7.6, the logistic regression modeling of postverification floor wipes that exceed 40 μg/ft2

 found that the primary variables found to be best 

predict these failures were Floor Condition and Post-work and Post-cleaning Lead Levels. All 

interior experiments did result in final passed cleaning cloths for all floor zones and for all 

window sills, but nearly half of the experiments ended with average Work room floor lead levels 

above 40 μg/ft2 on floors. Lead levels for the cases above the floor standard were distributed as 

follows: 10 between 40 and 69, 6 between 70 and 99, 5 between 100 and 199, 3 between 200 

and 499, and 5 greater than 500. The eight highest levels were associated with high heat gun or 

door planing jobs and floors in poor condition. Of the 29 experiments where final lead levels 

were above 40 μg/ft2 on floors, 20 were on floors in poor condition. Excluding the door planing 

and high heat gun jobs, which had higher post-job lead levels than the others and which appeared 

to generate fine particle size dust and, in the case of the door planing, a white dust that was hard 

to detect on a white cloth, post-job averages when the proposed rule cleaning was used were 

below clearance levels. For window sills, approximately 20 percent of the experiments ended 

with lead levels above 250 μg/ft2

. Almost all of the high levels, well above the standard, were 

associated with door plane and high temperature heat gun jobs. The study did not yield much 

evidence to evaluate differences in lead levels after the wet and dry cleaning verification steps 

because the dry cleaning verification was only required in three experiments. 

Table 9-1 summarizes the arithmetic average post-verification lead levels and number of samples 

> 40 μg/ft2

 for rule cleaning phases and post-cleaning lead levels and number of samples > 40 

μg/ft2 for baseline cleaning phases. Note that for Phases II and IV, which included baseline 

cleaning, any recleanings required were done by rule cleaning methods. Within the no 

plastic/rule cleaning phase, experiment 32 achieved an average post-verification floor lead level 

of 2,976 μg/ft2

. If that experiment were excluded, the average post-verification floor lead level 

for phase III would become 123.4 μg/ft2

. Factors such as contractor, floor condition, and floor 

type impacted the performance of the cleaning verification process. One contractor obtained 
9-4 

higher post-verification lead levels than the others due in part to this contractor being more 

willing to pass a verification cloth. 

Table 9-1. Post-job Floor Lead Levels and Number of Samples Failing Clearance in the 

Work Room 

RULE CLEANING - Post 

Verification 

BASELINE CLEANING - 

Post Cleaning 

Phase I - Plastic III - No plastic II - Plastic IV - No plastic 

Average Lead Level (μg/ft2) 55.1 313.5* 172.8 305.9 

Average # of Post-job Dust 

Wipes > 40 μg/ft2** 1.8 1.4 2.5 2.9 

* Excluding Experiment 32, which had a very high post-verification floor level, the average lead level is 123.4 

μg/ft2 

** 4 post-job floor dust wipes were obtained from the Work Room, thus for each experiment the minimum # of 

wipes ≥ 40 is 0 and maximum number of wipes ≥ 40 is 4 

The door planing and high heat gun jobs resulted in the highest post-job lead levels. Table 9-2 

summarizes post-job floor lead levels with these two jobs excluded. Significantly lower levels 

than those presented in Table 9-1 were achieved with these two jobs excluded. Without the two 

jobs, the post-verification averages for the rule cleaning phases are below clearance, while the 

baseline cleaning post-cleaning averages are between 75 and 80 μg/ft2

. For comparison, Table 9-

3 presents the summary data for the door planing and high heat gun jobs only, both of which 

generated a lot of fine dust. The distribution across the four P/CU phases is different for these 

two jobs, with the combination of use of plastic and baseline cleaning associated with lower 

post-job levels than no plastic and baseline cleaning. Again, one very high post-verification 

value (2,976.1) from a Phase III heat gun job impacts that average significantly. With that 

sample excluded, the post-verification average for phase III for door planes and heat guns 

becomes 346.2 μg/ft2. 

Table 9-2. Post-job Floor Lead Levels and Number of Samples Failing Clearance 

(excluding Door Planing and High Heat Gun) 

RULE CLEANING - Post 

Verification 

BASELINE CLEANING - 

Post Cleaning 

Phase I - Plastic III - No plastic II – Plastic IV - No plastic 

Average Lead Level (μg/ft2) 23.1 34.2 78.7 75.5 

Average # of Post-job Dust 

Wipes > 40 μg/ft2* 1.1 0.6 2.1 2.7 

* 4 post-job floor dust wipes were obtained from the Work Room, thus for each experiment the minimum # of 

wipes ≥ 40 is 0 and maximum number of wipes ≥ 40 is 4 
9-5 

Table 9-3. Post-job Floor Lead Levels and Number of Samples Failing Clearance 

(Door Planing and High Heat Gun Jobs Only) in the Work Room

RULE CLEANING – Post 

Verification 

BASELINE CLEANING - Post 

Cleaning 

Phase I - Plastic III - No plastic II – Plastic IV - No plastic 

Average Lead Level 

(μg/ft2) 119.2 872.2 361.0 1,279.4 

Average # of Post-job 

Dust Wipes > 40 μg/ft2* 3.2 3.0 3.2 3.4 

* 4 post-job dust wipes were obtained from the Work Room, thus for each experiment the minimum # of wipes ≥

40 is 0 and maximum number of wipes ≥ 40 is 4 

Similar to the post-job floor levels and number of samples above the clearance standard, Table 

9-4 summarizes the average post-job lead levels and number of samples > 250 μg/ft2 for rule and 

baseline cleaning phases. Again, post-job refers to the post-verification sampling stage for rule 

cleaning phases (I and III), and to the post-cleaning sampling stage for baseline cleaning phases 

(II and IV). Overall, the two phases involving rule cleaning resulted in lower post-job window 

sill lead levels than the two phases involving baseline cleaning. 

Table 9-4. Post-job Window Sill Lead Levels and Number of Samples Failing Clearance 

RULE CLEANING - Post 

Verification 

BASELINE CLEANING - Post 

Cleaning 

Phase I - Plastic III - No plastic II - Plastic IV - No plastic 

Average Lead Level 

(μg/ft2) 198.7 490.5 761.6 601.4 

Average # of Post-job 

Dust Wipes > 250 μg/ft2* 0.1 0.4 0.3 0.5 

* 1 post-job dust wipe was obtained from the Work Room window sill, thus for each experiment the minimum # 

of wipes ≥ 40 is 0 and maximum number of wipes ≥ 40 is 1 

Due to the configuration of the study rooms and above clearance pre-work lead levels, dust 

collection trays were substituted for window sills in the Work Room for half (30) of the interior 

experiments. Tables 9-5 and 9-6 show the comparison of post-job lead levels and number of 

failures by cleaning method for sampled window sills and dust collection trays, respectively. 

The average lead level across the phases appears to be lower when sills were sampled, however, 

16 out of 20 door plane and heat gun experiments, noted above as having the most dust 

generated, were completed with dust collection trays serving as window sills. 
9-6 

Table 9-5. Post-job Window Sill Lead Levels and Number of Samples Failing 

Clearance for Sampled Window Sills 

RULE CLEANING - Post 

Verification 

BASELINE CLEANING - Post 

Cleaning 

Phase I - Plastic III - No plastic II - Plastic IV - No plastic 

Average Lead Level 

(μg/ft2) 293.4 101.3 190.5 663.2 

Average # of Post-job 

Dust Wipes > 250 μg/ft2* 0.1 0.3 0.1 0.6 

* 1 post-job dust wipe was obtained from the Work Room window sill, thus for each experiment the minimum # 

of wipes ≥ 40 is 0 and maximum number of wipes ≥ 40 is 1 

Table 9-6. Post-job Window Sill Lead Levels and Number of Samples Failing 

Clearance for Sampled Dust Collection Trays 

RULE CLEANING - Post 

Verification 

BASELINE CLEANING - Post 

Cleaning 

Phase I - Plastic III - No plastic II - Plastic IV - No plastic 

Average Lead Level 

(μg/ft2) 115.7 879.7 1,414.3 530.7 

Average # of Post-job 

Dust Wipes > 250 μg/ft2* 0.1 0.6 0.4 0.4 

* 1 post-job dust wipe was obtained from the Work Room window sill, thus for each experiment the minimum # 

of wipes ≥ 40 is 0 and maximum number of wipes ≥ 40 is 1 

9.7 Objective 7: Comparing Post-job Levels between the Proposed Rule Package and 

the Baseline Package 

Interior 

Application of the package of plastic protective sheeting, HEPA vacuuming and wet mopping, 

and cleaning verification practices in EPA’s proposed rule did result in lower lead levels at the 

end of a job than were achieved using baseline practices (no plastic protective sheeting and 

cleaning with broom and a shop-vacuum vacuum). Descriptive analyses in Section 6 of this 

report display the lower geometric mean levels achieved consistently across jobs on work room 

floors and sills (see Figures 9-1 and 9-2). Statistical modeling presented in Section 7 confirms a 

statistically significant difference between proposed rule and baseline practices for work room 

floors. The associated hypothesis test had a p-value <.01 from models that compared proposed 

rule practices to baseline practices adjusting for job type and the interaction between job type 

and use of rule practices for housing units only and for all units combined. The difference 

between the proposed rule practices and baseline practices was significant (p-value=<.01) for 

window sills in the Work room, using the combined housing unit and COF data and adjusting for 

job type and COF. This comparison was also significant using only the residential data (p-value 

=.02) and adjusting for job type. 
9-7 

5

33

135

24 30

148

24

12

41

66

450

41

58

22

1

10

100

1,000

10,000

Cut-outs Window

Repl.

Kitchen Gut Heat Gun

<1100

Door

Planing

Dry

Scraping

Heat Gun

>1100

GM Floor Lead Levels 

(μg/ft2

)

Proposed Rule Practices Baseline Practices

Figure 9-1. Post-Job Work Room Floor Lead Levels, By Job and Rule Use 

28

63

21 21

197

17

72

120

568 429

247

707

61

601

1

10

100

1,000

Cut-outs Window

Repl.

Kitchen

Gut

Heat Gun

<1100

Door

Planing

Dry

Scraping

Heat Gun

>1100

GM Sill Lead Level (μg/ft 2

)

Proposed Rule Practices Baseline Practices

Figure 9-2. Post-Job Work Room Sill Lead Levels, By Job and Rule Use 

For the Tool and Observation room floors, differences between the rule package and baseline 

package were smaller, not consistent across all jobs, and not statistically significant. Figures 6-6 

and 6-7 display smaller and non-uniform differences between use of proposed rule practices and 

baseline practices in the two non-work rooms for floors, with the rule package being lower than 

the baseline package in five of seven jobs in each room. For some jobs, Tool and Observation 

room geometric mean floor lead levels at the end of a job were above the EPA standard, even 

when the rule package was followed. Application of the same statistical model applied to the 

Work room achieved a non-significant p-value of .17 in the Tool room and .14 in the 

Observation room for the difference between rule and baseline practices when looking just at 

housing units. These p-values were even higher with the combined housing unit and COF data. 

Figures 6-12 and 6-13 display post-job geometric mean lead levels on window sills in the Tool 

and Observation Rooms, respectively. The differences between rule and baseline practices were 

non-uniform. Rule practices had lower levels than baseline practices in five of the seven job 

types for the Tool room, and for four of the seven job types in the Observation room. In the Tool 

room, the difference between proposed rule practices and baseline practices was borderline 

significant for window sills (p-value=.06 combined, p-value=.09 housing units only) adjusting 

for job type and COF. In the Observation room, the difference between proposed rule practices 

and baseline practices was not significant for window sills (p-value=.32 combined, p-value=.23 

housing units only) in models accounting for job type and COF in the combined model and job 

type in the housing units only model. Tool and Observation room geometric mean sill lead 

levels were below the EPA standard for all job types except door planing. 
9-8 

While the rule package resulted in lower lead levels than the baseline package in the work room, 

the final lead levels measured under the rule package were not always lower than the EPA 

standards. Table 9-7 and Table 9-8, for floors and sills respectively, show the arithmetic mean 

post-job lead levels and average number of samples above the EPA standard by job type and 

study phase. The post-job results displayed include post-verification results for phases with rule 

cleaning and post-cleaning results for phases with baseline cleaning. The arithmetic average 

post-job floor lead level over all samples collected in the work room for Phase I (plastic and rule 

cleaning) is less than 40 μg/ft2 for all job types except Door Planing and Heat Gun >1100 

Degrees. The average number of samples above or equal to 40 μg/ft2 was two or less out of four 

in five of the seven job types. The arithmetic average post-job window sill lead level over all 

samples collected in the work room for Phase I is less than 250 μg/ft2

 for all job types except 

Door Planing and Heat Gun >1100 Degrees, with the latter job just beyond that clearance 

standard at 278 μg/ft2

. Consistent with this result is that no post-job sill samples above 250 

μg/ft2

 were collected in Phase I except in the Door Planing and High Heat Gun jobs. 
9-9 

Table 9-7. Post-job* Average Floor Lead Levels and Failed Samples by Job Type 

Job Type Phase # of 

Exp. 

Post-Job* Average 

Lead Level (μg/ft2) 

Post-Job* Average # of 

Samples > 40 (μg/ft2) 

I (plastic/rule) 3 5.0 0.0 

II (plastic/baseline) 3 9.1 0.0 

III (no plastic/rule) 3 9.9 0.0 

Cut-outs 

IV (no plastic/baseline) 3 37.3 1.3 

I (plastic/rule) 2 35.7 2.0 

II (plastic/baseline) 2 140.2 4.0 

III (no plastic/rule) 2 87.2 3.0 

Window 

Replacement 

IV (no plastic/baseline) 2 146.2 4.0 

I (plastic/rule) 2 34.2 1.5 

II (plastic/baseline) 2 168.3 3.5 

III (no plastic/rule) 2 14.4 0.0 Dry Scrape 

IV (no plastic/baseline) 2 70.7 3.5 

I (plastic/rule) 2 188.9 4.0 

II (plastic/baseline) 2 142.3 3.5 

III (no plastic/rule) 2 651.8 4.0 

Door Plane 

IV (no plastic/baseline) 2 771.9 4.0 

I (plastic/rule) 1 29.1 2.0 

II (plastic/baseline) 1 25.6 1.0 

III (no plastic/rule) 1 7.5 0.0 

Heat 

Gun<1100 

Degrees 

IV (no plastic/baseline) 1 44.2 2.0 

I (plastic/rule) 2 23.7 1.0 

II (plastic/baseline) 2 58.6 2.5 

III (no plastic/rule) 2 50.9 0.5 

Kitchen Gut 

IV (no plastic/baseline) 2 82.2 3.0 

I (plastic/rule) 3 72.7 2.7 

II (plastic/baseline) 3 506.8 3.0 

III (no plastic/rule) 3 1,019.2 2.3 

Heat 

Gun>1100 

Degrees 

IV (no plastic/baseline) 3 1,617.8 3.0 

* Post-job refers to the post-verification values for phases that involve the rule cleaning method (I and 

III) and the post-cleaning values for phases that involve the baseline cleaning method (II and IV). 
9-10 

Table 9-8. Post-job* Window Sill Average Lead Levels and Failed Samples by 

Job Type. 

Job Type Phase # of 

Exp.

Post-Job* Average 

Lead Level (μg/ft2)

Post-Job* Average # of 

Samples > 250 (μg/ft2)

I (plastic/rule) 3 30.3 0.0 

II (plastic/baseline) 3 58.7 0.0 

III (no plastic/rule) 3 70.0 0.0 

Cut-outs 

IV (no plastic/baseline) 3 212.0 0.3 

I (plastic/rule) 2 99.4 0.0 

II (plastic/baseline) 2 359.4 0.5 

III (no plastic/rule) 2 150.8 0.5 

Window 

Replacement 

IV (no plastic/baseline) 2 598.2 1.0 

I (plastic/rule) 2 31.3 0.0 

II (plastic/baseline) 2 246.0 0.5 

III (no plastic/rule) 2 24.5 0.0 Dry Scrape 

IV (no plastic/baseline) 2 87.9 0.0 

I (plastic/rule) 2 865.3 0.5 

II (plastic/baseline) 2 202.9 0.5 

III (no plastic/rule) 2 1,714.1 0.5 

Door Plane 

IV (no plastic/baseline) 2 1,038.3 1.0 

I (plastic/rule) 1 20.8 0.0 

II (plastic/baseline) 1 285.1 1.0 

III (no plastic/rule) 1 n/a 1.0 

Heat Gun <1100 

Degrees 

IV (no plastic/baseline) 1 246.8 0.0 

I (plastic/rule) 2 21.4 0.0 

II (plastic/baseline) 2 41.7 0.0 

III (no plastic/rule) 2 82.3 0.0 

Kitchen Gut 

IV (no plastic/baseline) 2 772.3 0.5 

I (plastic/rule) 3 277.9 0.3 

II (plastic/baseline) 3 3,087.6 0.7 

III (no plastic/rule) 3 904.4 0.3 

Heat Gun >1100 

Degrees 

IV (no plastic/baseline) 3 1,048.1 0.7 

* Post-job refers to the post-verification values for phases that involve the rule cleaning method (I and 

III) and the post-cleaning values for phases that involve the baseline cleaning method (II and IV). 

Exterior 

The use of plastic as a ground covering during exterior jobs captured large amounts of leaded 

dust. Figure 6-14 and Figure 6-15 compare the amount of lead on top of the rule plastic to the 

amount under the rule plastic, with Figure 6-14 including bulk debris samples and Figure 6-15 

excluding the bulk debris samples. For most job types, there is a substantial difference between 

the amount of lead captured by the rule plastic and the amount under the rule plastic. One 

notable special case is Torching. Without the bulk debris samples, the amount of lead under the 

plastic exceeds the amount on top. For all 8 job types, the ratio of the amount of lead on top of 

the rule plastic to the amount underneath was statistically significant when bulk debris samples 

were included. This changed to 6 out of the 8 job types when bulk debris samples were 

excluded. 
9-11 

For some job types, substantial amounts of lead were measured in collection trays just outside 

the rule plastic. The job types for which substantial amounts of lead were measured just outside 

the rule plastic were trim/soffit replacement, power sanding, and door replacement.