Access Across America: Auto 2019 Final Report Prepared by: Andrew Owen Brendan Murphy Accessibility Observatory Center for Transportation Studies University of Minnesota CTS 21-01 Technical Report Documentation Page 1. Report No. 2. 3. Recipients Accession No. CTS 21-01 4. Title and Subtitle 5. Report Date Access Across America: Auto 2019 February 2021 6. 7. Author(s) 8. Performing Organization Report No. Andrew Owen and Brendan Murphy 9. Performing Organization Name and Address 10. Project/Task/Work Unit No. Accessibility Observatory University of Minnesota Minneapolis, MN 55455 United States CTS 2016016 11. Contract (C) or Grant (G) No. 12. Sponsoring Organization Name and Address 13. Type of Report and Period Covered Center for Transportation Studies University of Minnesota University Office Plaza, Suite 440 2221 University Avenue SE Minneapolis, MN 55414 Final Report 14. Sponsoring Agency Code 15. Supplementary Notes http://ao.umn.edu/publications/ http://www.cts.umn.edu/publications/researchreports/ 16. Abstract (Limit: 250 words) Accessibility is the ease and feasibility of reaching valued destinations. It can be measured for a wide array of transportation modes, to different types of destinations, and at different times of day. There are a variety of ways to define accessibility, but the number of destinations reachable within a given travel time is the most comprehensible and transparent as well as the most directly comparable across cities. This study estimates the accessibility to jobs by auto for each of the 11 million U.S. census blocks and analyzes these data in the 50 largest (by population) metropolitan areas. Travel times are calculated using a detailed road network and speed data that reflect typical conditions for an 8 a.m. Wednesday morning departure. Additionally, the accessibility results for 8 a.m. are compared with accessibility results for 4 a.m. to estimate the impact of road and highway congestion on job accessibility. Rankings are determined by a weighted average of accessibility, with a higher weight given to closer, easier-to- access jobs. Jobs reachable within 10 minutes are weighted most heavily, and jobs are given decreasing weights as travel time increases up to 60 minutes. This report presents detailed accessibility values for each metropolitan area, as well as block-level maps which illustrate the spatial patterns of accessibility within each area. A separate publication, Access Across America: Auto 2019 Methodology, describes the data and methodology used in this evaluation. 17. Document Analysis/Descriptors 18. Availability Statement accessibility, bicycling, commuting, work trips, land use, travel time, travel behavior, urban transportation No restrictions. Document available from: National Technical Information Services, Alexandria, Virginia 22312 19. Security Class (this report) 20. Security Class (this page) 21. No. of Pages 22. Price Unclassified Unclassified 230 Access Across America: Auto 2019 Final Report Prepared by: Andrew Owen Brendan Murphy Accessibility Observatory Center for Transportation Studies University of Minnesota February 2021 Published by: Center for Transportation Studies University of Minnesota University Office Plaza, Suite 440 2221 University Avenue SE Minneapolis, MN 55414 This report represents the results of research conducted by the authors and does not necessarily reflect the official views or policy of the Center for Transportation Studies or the University of Minnesota. Authors Andrew Owen Director, Accessibility Observatory University of Minnesota Brendan Murphy Research Fellow, Accessibility Observatory University of Minnesota Acknowledgements The development of this report was made possible by sponsorship from: • Arkansas State Highway and Transportation Department • California Department of Transportation • District Department of Transportation • Federal Highway Administration • Florida Department of Transportation • Illinois Department of Transportation • Iowa Department of Transportation • Maryland Department of Transportation • Massachusetts Department of Transportation • Minnesota Department of Transportation • North Carolina Department of Transportation • Tennessee Department of Transportation • Virginia Department of Transportation • Washington Department of Transportation This report was created using TomTom’s MultiNet and Speed Proʮle Products. TomTom shall have no liability regarding the information contained in these reports and the information provided by TomTom is on an “AS IS BASIS” and “WITH ALL FAULTS”. Executive Summary Accessibility is the ease and feasibility of reaching valuable destinations. Accessibility can be measured for a wide array of transportation modes, to different types of destinations, and at different times of day. There are a variety of ways to deʮne accessibility, but the number of destinations reachable within a given travel time is the most comprehensible and transparent—as well as the most directly comparable between cities, and other geographic areas. This report focuses on accessibility to jobs by auto. Jobs are the most signiʮcant non-home destination, and job accessibility is an important consideration in the attractiveness and usefulness of a place or area. This study estimates the accessibility to jobs by auto for each of the United States’ 11 million census blocks, and analyzes these data in the 50 largest (by population) metropolitan areas. Travel times by auto are calculated using a detailed road network and speed data that reʯect typical conditions for an 8 AM Wednesday morning departure. Additionally, the accessibility results for 8 AM are compared with the maximum accessibility results across the 24-hour period to estimate the impact of road and highway congestion on job accessibility. Rankings are determined by a weighted average of accessibility, with a higher weight given to closer, easier to access jobs. Jobs reachable within ten minutes are weighted most heavily, and jobs are given decreasing weights as travel time increases up to 60minutes. Based on this measure, the 10metropolitan areas with the greatest accessibility to jobs by auto in 2019 are: 1. Los Angeles 2. New York 3. Dallas 4. San Jose 5. Chicago 6. Minneapolis 7. Houston 8. Detroit 9. Phoenix 10. Denver A similar weighting approach is applied to calculate an average congestion impact for eachmetropoli- tan area. Based on this measure, the 10 metropolitan areas where congestion causes the greatest per- centage reduction in job accessibility are: 1. Los Angeles 2. Riverside 3. New York 4. San Francisco 5. Boston 6. Atlanta 7. Washington 8. San Jose 9. Chicago 10. Miami Additionally, rankings based on 1-year changes in both weighted average accessibility, and weighted average congestion impact, are also provided, comparing the results of Access Across America: Auto 2018 with the results of the 2019 study. The 10 metropolitan areas with the greatest 1-year relative gains in accessibility to jobs by auto are: 1. San Antonio 2. Miami 3. Jacksonville 4. Phoenix 5. Detroit 6. Salt Lake City 7. Las Vegas 8. Dallas 9. Seattle 10. Houston 4 The 10 metropolitan areas with the greatest 1-year relative increase in congestion impact are: 1. Charlotte 2. Baltimore 3. St. Louis 4. Kansas City 5. Pittsburgh 6. Tampa 7. Cincinnati 8. Sacramento 9. Philadelphia 10. Riverside This report presents detailed accessibility and congestion impact values for each metropolitan area, as well as block-level maps that illustrate the spatial patterns of accessibility within each area, and a census tract-level map that shows accessibility patterns at a national scale. A separate publication, Access Across America: Auto 2019 Methodology, describes the data and methodology used in this evaluation. 5 Contents 1 Introduction 1 2 Accessibility to Jobs by Auto 3 2.1 National Accessibility by Auto . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.2 Metropolitan Area Accessibility Evaluation Results . . . . . . . . . . . . . . 5 2.3 Metropolitan Area Accessibility Rankings . . . . . . . . . . . . . . . . . . . 5 3 Congestion Impacts 10 3.1 National Congestion Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.2 Metropolitan Area Congestion Impact Results . . . . . . . . . . . . . . . . 12 3.3 Metropolitan Area Congestion Rankings . . . . . . . . . . . . . . . . . . . . 12 4 Data Sources and Methodology 17 4.1 Travel Times by Auto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 4.2 Geography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 4.3 Population and Job Distribution . . . . . . . . . . . . . . . . . . . . . . . . 17 4.4 Accessibility Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 5 Comparisons With Previous Years 18 6 Discussion 18 6.1 Land-Use Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 6.2 Congestion Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 6.3 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 7 Metropolitan Area Data and Maps 21 1 Introduction Accessibility is the ease and feasibility of reaching valuable destinations. It combines the simpler metric of mobility with the understanding that travel is driven by a desire to reach destinations. Accessibility can be measured for a wide range of transportation modes, to different types of destinations, and at different times of day. There are a variety of ways to deʮne accessibility, but the number of destinations reachable within a given travel time is the most comprehensible and transparent—as well as the most directly comparable across cities. This report focuses on accessibility to jobs by auto. Jobs are the most signiʮcant non-home destination, and job accessibility is an important consideration in the attractive- ness and usefulness of a place or area. Cars, trucks, and other private motor vehicles are used for an estimated 86% of commuting trips in the United States, making it the most widely used commute mode1. Accessibility is not a new idea.2 Historically, however, implementations of accessibility evaluation have typically focused on individual cities or metropolitan areas. Recent work has demonstrated the feasibility and value of systematically evaluating accessibility across multiple metropolitan areas by auto3 and by transit.4 This study estimates the accessibility to jobs by auto for each of the United States’ 11 million census blocks, and analyzes these data in the 50 largest (by population) metropolitan areas. Table 1 lists the included metropolitan areas, ordered by the total employment within each. Travel times by auto are calculated using a detailed road network and speed data that reʯect typical conditions for an 8 AM Wednesday morning departure. Additionally, the accessibility results for 8 AM are compared with 24-hour maximum accessibility results to estimate the impact of road and highway congestion on job accessibility. Section 2 presents the accessibility values for the included metropolitan areas and ranks metropoli- tan areas by accessibility, as well as a look at accessibility to jobs nationally in Section 2.1. Section 3 presents the congestion impact analysis results. Section 6 discusses these results and their implications, and Section 7 provides data and maps describing patterns of accessibility in individual metropolitan areas. A separate document, Access Across America: Auto 2019 Methodology, describes the data and detailed methodology used in the evaluation. 1American Community Survey 2014 5-year estimates 2See Hansen (1959) for its origins, and Geurs and Van Eck (2001) and Handy and Niemeier (1997) for reviews. 3Levinson (2013), Levine et al. (2012) 4Ramsey and Bell (2014), Tomer et al. (2011) 1 Table 1: Metropolitan Areas Ranked by Total Employment Rank Area Total Employment 1 New York 8,946,175 2 Los Angeles 5,825,012 3 Chicago 4,448,938 4 Dallas 3,366,285 5 Houston 2,894,863 6 Philadelphia 2,862,819 7 Washington 2,683,930 8 Atlanta 2,534,711 9 Miami 2,503,411 10 Boston 2,464,508 11 San Francisco 2,241,034 12 Phoenix 1,958,550 13 Detroit 1,915,549 14 Minneapolis 1,847,804 15 Seattle 1,798,352 16 Riverside 1,749,931 17 San Diego 1,419,381 18 Denver 1,395,732 19 St. Louis 1,344,165 20 Tampa 1,293,226 21 Baltimore 1,277,911 22 Portland 1,140,463 23 Orlando 1,135,710 24 Pittsburgh 1,105,247 25 Cincinnati 1,045,101 26 Kansas City 1,036,878 27 San Antonio 1,019,742 28 Austin 967,584 29 Sacramento 964,523 30 Cleveland 961,969 31 San Jose 947,987 32 Columbus 946,698 33 Las Vegas 941,812 34 Charlotte 930,190 35 Indianapolis 919,836 36 Nashville 843,428 37 Milwaukee 779,865 38 Providence 775,615 39 Virginia Beach 715,637 40 Jacksonville 662,664 41 Louisville 645,505 42 Richmond 640,682 43 Raleigh 615,937 44 Salt Lake City 605,393 45 Hartford 595,341 46 Memphis 589,984 47 Oklahoma City 565,695 48 Buffalo 525,947 49 New Orleans 505,876 50 Birmingham 479,837 Employment totals are based on LEHD estimates and may not match other sources. 2 2 Accessibility to Jobs by Auto 2.1 National Accessibility by Auto The scope of this report is national, following previous reports in the Access Across America: Auto series. Calculations were performed for every census block in the country, providing a complete, connected picture of accessibility to jobs by auto in every state, metropolitan area, or rural community. A national map of accessibility to jobs by auto follows, and utilizes the same scale and color intensities as the maps contained in Section 7. 3 Figure 1: National U.S. map of accessibility to jobs by auto in 30 minutes. 4 2.2 Metropolitan Area Accessibility Evaluation Results Table 2 gives the accessibility values for each metropolitan area, in alphabetical order. The columns indicate the number of jobs that a typical worker residing in the city can reach within 10, 20, 30, 40, 50, and 60 minutes of travel, departing at 8 AM on a typical Wednesday. 2.3 Metropolitan Area Accessibility Rankings The rankings of accessibility across U.S. cities for 2019 are shown in Table 3. The ʮrst column provides a weighted average, where the jobs reachable within each threshold are given a decreasing weight as travel time increases. A job reachable within 10 minutes counts more toward the ranking than a job reachable within 20, and so on. The 10 metro areas where workers can, on average, reach the most jobs are listed below. Within the speciʮc time thresholds, the rankings vary. 1. Los Angeles 2. New York 3. Dallas 4. San Jose 5. Chicago 6. Minneapolis 7. Houston 8. Detroit 9. Phoenix 10. Denver 5 Table 2: Number of Jobs Reachable by Travel Time Area 10 min 20 min 30 min 40 min 50 min 60 min Atlanta 31,187 187,161 484,464 883,595 1,349,658 1,852,199 Austin 50,160 244,925 494,183 731,502 938,597 1,106,297 Baltimore 38,909 220,238 539,136 915,199 1,320,280 1,803,526 Birmingham 24,105 130,535 266,839 374,229 482,502 597,293 Boston 44,386 233,219 582,975 1,063,205 1,622,819 2,245,988 Buffalo 43,697 209,641 386,918 488,763 544,381 593,060 Charlotte 35,291 188,297 454,198 770,678 1,024,155 1,224,185 Chicago 60,334 306,379 781,933 1,451,087 2,259,834 3,098,658 Cincinnati 35,052 211,722 504,322 805,607 1,055,313 1,249,533 Cleveland 34,441 209,087 516,984 867,340 1,169,079 1,410,739 Columbus 49,625 301,604 615,025 825,938 990,123 1,140,390 Dallas 65,805 418,056 1,079,330 1,893,807 2,659,576 3,151,871 Denver 62,272 341,662 797,919 1,249,511 1,528,240 1,711,466 Detroit 57,058 346,508 813,942 1,307,016 1,726,422 2,064,581 Hartford 38,271 216,432 494,557 825,316 1,166,832 1,493,350 Houston 50,898 309,443 790,245 1,429,365 2,057,094 2,503,954 Indianapolis 42,334 248,464 570,795 840,424 1,013,913 1,165,886 Jacksonville 28,473 161,182 344,451 489,403 601,372 686,489 Kansas City 49,787 287,412 617,423 871,347 1,009,014 1,126,852 Las Vegas 67,274 450,370 831,538 888,493 893,252 896,922 Los Angeles 96,746 525,411 1,275,161 2,251,284 3,386,696 4,566,776 Louisville 41,381 233,733 438,152 558,419 662,564 758,047 Memphis 43,593 226,382 421,163 521,071 574,055 620,819 Miami 46,669 258,264 619,669 1,020,851 1,419,419 1,802,729 Milwaukee 75,388 345,562 621,764 829,295 1,004,691 1,236,470 Minneapolis 62,834 392,836 893,707 1,342,099 1,634,236 1,826,877 Nashville 27,400 143,203 317,994 537,410 750,041 906,806 New Orleans 38,244 171,995 301,856 385,105 495,768 626,527 New York 85,112 456,819 1,184,927 2,252,821 3,615,924 5,145,437 Oklahoma City 39,531 209,701 384,053 493,861 561,821 609,473 Orlando 31,684 201,753 536,084 892,612 1,185,288 1,450,711 Philadelphia 42,652 238,279 617,757 1,179,390 1,873,317 2,633,691 Phoenix 64,911 345,459 773,754 1,217,889 1,575,685 1,791,768 Pittsburgh 23,475 128,607 314,545 554,539 799,820 1,030,880 Portland 49,874 241,178 524,725 822,162 1,048,680 1,193,970 Providence 34,490 164,294 358,636 615,417 934,341 1,285,696 Raleigh 42,402 231,029 497,633 735,547 944,776 1,129,214 Richmond 39,574 204,535 403,256 531,653 623,146 732,256 Riverside 36,260 189,858 442,803 749,962 1,128,388 1,707,424 Sacramento 45,015 231,429 489,816 756,394 956,128 1,123,578 Salt Lake City 83,595 419,677 684,399 910,142 1,061,572 1,119,352 San Antonio 50,099 301,711 585,172 774,898 899,837 987,194 San Diego 55,533 306,625 637,936 928,528 1,224,200 1,534,269 San Francisco 71,448 287,801 651,253 1,167,143 1,786,229 2,460,882 San Jose 79,839 442,549 831,681 1,223,992 1,674,326 2,222,606 Seattle 51,792 238,503 548,802 863,561 1,170,946 1,445,102 St. Louis 43,481 264,709 608,035 916,197 1,119,824 1,247,304 Tampa 40,825 188,708 427,946 767,245 1,098,359 1,385,646 Virginia Beach 36,116 186,823 344,400 480,745 585,212 672,289 Washington 43,170 226,747 564,270 1,062,673 1,699,171 2,392,428 6 The 10 metropolitan areas with the greatest 1-year relative gains in accessibility to jobs by auto are: 1. San Antonio 2. Miami 3. Jacksonville 4. Phoenix 5. Detroit 6. Salt Lake City 7. Las Vegas 8. Dallas 9. Seattle 10. Houston Additional details about each metropolitan area, including block-level maps of accessibility, are presented in Section 7. 7 Table 3: Metropolitan Areas Ranked by Job Accessibility Rank Weighted Average 10 min 20 min 30 min 40 min 50 min 60 min 1 Los Angeles Los Angeles Los Angeles Los Angeles New York New York New York 2 New York New York New York New York Los Angeles Los Angeles Los Angeles 3 Dallas Salt Lake City Las Vegas Dallas Dallas Dallas Dallas 4 San Jose San Jose San Jose Minneapolis Chicago Chicago Chicago 5 Chicago Milwaukee Salt Lake City San Jose Houston Houston Philadelphia 6 Minneapolis San Francisco Dallas Las Vegas Minneapolis Philadelphia Houston 7 Houston Las Vegas Minneapolis Detroit Detroit San Francisco San Francisco 8 Detroit Dallas Detroit Denver Denver Detroit Washington 9 Phoenix Phoenix Milwaukee Houston San Jose Washington Boston 10 Denver Minneapolis Phoenix Chicago Phoenix San Jose San Jose 11 San Francisco Denver Denver Phoenix Philadelphia Minneapolis Detroit 12 Las Vegas Chicago Houston Salt Lake City San Francisco Boston Atlanta 13 Salt Lake City Detroit San Diego San Francisco Boston Phoenix Minneapolis 14 Philadelphia San Diego Chicago San Diego Washington Denver Baltimore 15 Milwaukee Seattle San Antonio Milwaukee Miami Miami Miami 16 San Diego Houston Columbus Miami San Diego Atlanta Phoenix 17 Washington Austin San Francisco Philadelphia St. Louis Baltimore Denver 18 Boston San Antonio Kansas City Kansas City Baltimore San Diego Riverside 19 Miami Portland St. Louis Columbus Salt Lake City Orlando San Diego 20 Columbus Kansas City Miami St. Louis Orlando Seattle Hartford 21 Kansas City Columbus Indianapolis San Antonio Las Vegas Cleveland Orlando 22 St. Louis Miami Austin Boston Atlanta Hartford Seattle 23 Seattle Sacramento Portland Indianapolis Kansas City Riverside Cleveland 24 San Antonio Boston Seattle Washington Cleveland St. Louis Tampa 25 Baltimore Buffalo Philadelphia Seattle Seattle Tampa Providence 26 Indianapolis Memphis Louisville Baltimore Indianapolis Salt Lake City Cincinnati 27 Portland St. Louis Boston Orlando Milwaukee Cincinnati St. Louis 28 Atlanta Washington Sacramento Portland Columbus Portland Milwaukee 29 Orlando Philadelphia Raleigh Cleveland Hartford Charlotte Charlotte 30 Hartford Raleigh Washington Cincinnati Portland Indianapolis Portland 31 Cleveland Indianapolis Memphis Raleigh Cincinnati Kansas City Indianapolis 32 Austin Louisville Baltimore Hartford San Antonio Milwaukee Columbus 33 Sacramento Tampa Hartford Austin Charlotte Columbus Raleigh 34 Cincinnati Richmond Cincinnati Sacramento Tampa Sacramento Kansas City 35 Raleigh Oklahoma City Oklahoma City Atlanta Sacramento Raleigh Sacramento 36 Riverside Baltimore Buffalo Charlotte Riverside Austin Salt Lake City 37 Tampa Hartford Cleveland Riverside Raleigh Providence Austin 38 Charlotte New Orleans Richmond Louisville Austin San Antonio Pittsburgh 39 Louisville Riverside Orlando Tampa Providence Las Vegas San Antonio 40 Memphis Virginia Beach Riverside Memphis Louisville Pittsburgh Nashville 41 Providence Charlotte Tampa Richmond Pittsburgh Nashville Las Vegas 42 Richmond Cincinnati Charlotte Buffalo Nashville Louisville Louisville 43 Buffalo Providence Atlanta Oklahoma City Richmond Richmond Richmond 44 Oklahoma City Cleveland Virginia Beach Providence Memphis Jacksonville Jacksonville 45 Virginia Beach Orlando New Orleans Jacksonville Oklahoma City Virginia Beach Virginia Beach 46 Nashville Atlanta Providence Virginia Beach Jacksonville Memphis New Orleans 47 Jacksonville Jacksonville Jacksonville Nashville Buffalo Oklahoma City Memphis 48 Pittsburgh Nashville Nashville Pittsburgh Virginia Beach Buffalo Oklahoma City 49 New Orleans Birmingham Birmingham New Orleans New Orleans New Orleans Birmingham 50 Birmingham Pittsburgh Pittsburgh Birmingham Birmingham Birmingham Buffalo 8 Table 4: 1-Year Change in Weighted Accessibility Rank Area 1-Year Change in Weighted Accessibility 1 San Antonio +16.92% 2 Miami +8.43% 3 Jacksonville +7.01% 4 Phoenix +6.63% 5 Detroit +6.50% 6 Salt Lake City +6.34% 7 Las Vegas +6.23% 8 Dallas +5.38% 9 Seattle +4.94% 10 Houston +4.73% 11 Austin +4.07% 12 Portland +3.98% 13 Nashville +3.93% 14 Columbus +3.81% 15 Minneapolis +3.40% 16 Atlanta +3.26% 17 San Jose +3.10% 18 Orlando +2.93% 19 Raleigh +2.87% 20 San Diego +2.78% 21 Richmond +2.31% 22 Los Angeles +2.11% 23 Virginia Beach +2.09% 24 Denver +2.08% 25 Chicago +2.07% 26 Providence +1.91% 27 Memphis +1.90% 28 Hartford +1.89% 29 Sacramento +1.68% 30 San Francisco +1.44% 31 Charlotte +1.44% 32 New York +1.30% 33 Birmingham +1.06% 34 Indianapolis +1.04% 35 Buffalo +0.98% 36 Tampa +0.62% 37 Louisville +0.61% 38 Cincinnati +0.52% 39 Riverside +0.37% 40 Boston -0.06% 41 Philadelphia -0.13% 42 Oklahoma City -0.18% 43 Milwaukee -0.19% 44 Washington -0.37% 45 Cleveland -0.62% 46 New Orleans -0.95% 47 Kansas City -0.98% 48 St. Louis -1.11% 49 Pittsburgh -1.36% 50 Baltimore -3.97% 9 3 Congestion Impacts To estimate the impact that congestion has on job accessibility, accessibility calculations are performed for hourly departure times from midnight to 11 PM; accessibility results representing the morning commute peak (8 AM) are then compared to the maximum accessibility achieved across the 24-hour period. The difference in job accessibility between these two times is interpreted as the number of jobs that a traveler could reach (within a given travel time threshold) in free-ʯow conditions, but could not reach in congested conditions due to lower speeds. This can be expressed both as an absolute number of jobs and as a percentage change in accessibility. Expressing this metric as a percentage allows the degree of congestion impact to be compared across regions that have different absolute levels of accessibility. For example, a congestion impact of 9% at the 30 minutes travel time threshold indicates that the average worker can reach 9% fewer jobs during congested periods than during free-ʯow periods. The following sections present the results of this analysis for the top 50 US metropolitan areas. 3.1 National Congestion Impacts 10 Figure 2: National U.S. map of congestion impact. 11 3.2 Metropolitan Area Congestion Impact Results Table 5 gives the congestion impact values for each metropolitan area, in alphabetical order. The columns indicate the percentage reduction in job access that is caused by road and highway conges- tion, relative to free-ʯow speeds. For example, a congestion impact of 9% at the 30 minutes travel time threshold indicates that the average worker can reach 9% fewer jobs within 30 minutes during the AM peak period compared to free-ʯow periods. 3.3 Metropolitan Area Congestion Rankings The rankings of congestion impacts across U.S. metropolitan areas for 2019 are shown in Table 6. The ʮrst column provides a weighted average, where the congestion impacts for each threshold are given a decreasing weight as travel time increases. Congestion effects at 10 minutes count more toward the ranking than congestion effects at 20minutes, and so on. The 10metro areas where workers experience, on average, the greatest reduction in job access due to congestion in 2019 are listed below. Within the speciʮc time thresholds, the rankings vary. 1. Los Angeles 2. Riverside 3. New York 4. San Francisco 5. Boston 6. Atlanta 7. Washington 8. San Jose 9. Chicago 10. Miami 12 Table 5: Congestion Impact by Travel Time Area 10 min 20 min 30 min 40 min 50 min 60 min Atlanta 57.01% 60.82% 57.38% 49.94% 39.45% 27.19% Austin 54.84% 49.37% 35.45% 20.77% 11.83% 10.78% Baltimore 46.59% 49.69% 43.45% 43.17% 46.34% 46.64% Birmingham 43.93% 34.03% 18.79% 11.95% 10.25% 8.36% Boston 64.07% 64.32% 58.12% 50.82% 42.66% 32.69% Buffalo 35.00% 26.12% 12.11% 5.14% 2.58% 4.69% Charlotte 46.92% 47.91% 37.85% 21.79% 11.52% 8.98% Chicago 53.61% 59.27% 54.96% 48.05% 37.47% 25.58% Cincinnati 39.63% 37.19% 27.58% 16.52% 10.15% 7.63% Cleveland 41.12% 36.96% 25.07% 15.62% 8.79% 5.86% Columbus 47.06% 37.60% 16.96% 9.83% 6.19% 6.66% Dallas 53.62% 55.25% 45.75% 32.02% 17.21% 7.69% Denver 53.86% 54.90% 38.59% 17.49% 8.23% 7.95% Detroit 40.39% 39.05% 31.56% 21.64% 13.72% 9.74% Hartford 45.64% 35.78% 25.14% 18.70% 15.31% 13.75% Houston 58.74% 59.13% 51.12% 35.91% 20.83% 10.58% Indianapolis 38.72% 34.75% 21.59% 9.82% 6.02% 6.89% Jacksonville 48.46% 40.12% 24.39% 15.29% 8.87% 5.53% Kansas City 35.65% 29.40% 17.28% 6.57% 3.42% 3.09% Las Vegas 43.61% 32.89% 5.43% 0.28% 0.14% 0.18% Los Angeles 65.71% 69.18% 65.73% 58.00% 46.78% 34.54% Louisville 38.31% 27.83% 11.59% 6.43% 5.10% 5.80% Memphis 30.40% 23.60% 10.21% 3.78% 2.54% 2.96% Miami 61.31% 59.89% 50.36% 40.45% 30.16% 20.91% Milwaukee 38.54% 26.05% 13.19% 7.42% 6.88% 10.83% Minneapolis 48.73% 43.37% 29.11% 15.03% 7.95% 4.65% Nashville 50.17% 44.72% 36.30% 25.37% 13.23% 7.85% New Orleans 50.37% 34.49% 14.11% 13.57% 12.11% 13.81% New York 55.32% 64.61% 63.83% 56.46% 46.30% 35.80% Oklahoma City 33.18% 24.32% 12.05% 5.81% 2.83% 2.09% Orlando 53.78% 50.69% 35.63% 20.49% 13.31% 11.76% Philadelphia 50.81% 53.90% 50.42% 43.13% 33.78% 26.39% Phoenix 48.92% 51.49% 42.39% 27.92% 14.31% 5.72% Pittsburgh 54.71% 47.95% 37.86% 26.35% 18.10% 11.63% Portland 53.60% 54.26% 40.72% 23.37% 13.13% 8.43% Providence 35.47% 29.08% 31.36% 41.60% 49.33% 51.97% Raleigh 44.76% 40.10% 28.35% 17.57% 10.94% 8.98% Richmond 35.94% 25.87% 11.87% 5.62% 4.32% 6.12% Riverside 46.82% 51.26% 55.39% 63.09% 67.83% 64.90% Sacramento 55.37% 49.41% 34.33% 19.18% 14.44% 17.26% Salt Lake City 42.86% 24.74% 11.66% 8.32% 3.29% 1.24% San Antonio 46.75% 37.99% 19.46% 10.78% 8.36% 11.80% San Diego 59.02% 52.11% 38.19% 28.66% 20.23% 21.10% San Francisco 56.09% 61.15% 61.61% 56.38% 46.84% 35.27% San Jose 67.64% 54.46% 42.61% 43.29% 45.38% 36.65% Seattle 56.60% 58.57% 49.15% 41.39% 33.11% 24.41% St. Louis 38.82% 34.53% 22.50% 11.52% 5.92% 2.95% Tampa 50.37% 49.30% 46.08% 33.51% 23.74% 17.96% Virginia Beach 36.71% 24.84% 17.86% 12.32% 7.23% 5.87% Washington 55.69% 58.97% 57.84% 50.95% 40.69% 30.32% 13 The 10 metropolitan areas with the greatest 1-year relative increase in congestion impact are: 1. Charlotte 2. Baltimore 3. St. Louis 4. Kansas City 5. Pittsburgh 6. Tampa 7. Cincinnati 8. Sacramento 9. Philadelphia 10. Riverside Additional details about each metropolitan area, including block-level maps of congestion impacts, are presented in Section 7. 14 Table 6: Metropolitan Areas Ranked by Congestion Impact Rank Weighted Average 10 min 20 min 30 min 40 min 50 min 60 min 1 Los Angeles San Jose Los Angeles Los Angeles Riverside Riverside Riverside 2 Riverside Los Angeles New York New York Los Angeles Providence Providence 3 New York Boston Boston San Francisco New York San Francisco Baltimore 4 San Francisco Miami San Francisco Boston San Francisco Los Angeles San Jose 5 Boston San Diego Atlanta Washington Washington Baltimore New York 6 Atlanta Houston Miami Atlanta Boston New York San Francisco 7 Washington Atlanta Chicago Riverside Atlanta San Jose Los Angeles 8 San Jose Seattle Houston Chicago Chicago Boston Boston 9 Chicago San Francisco Washington Houston San Jose Washington Washington 10 Miami Washington Seattle Philadelphia Baltimore Atlanta Atlanta 11 Seattle Sacramento Dallas Miami Philadelphia Chicago Philadelphia 12 Baltimore New York Denver Seattle Providence Philadelphia Chicago 13 Houston Austin San Jose Tampa Seattle Seattle Seattle 14 Philadelphia Pittsburgh Portland Dallas Miami Miami San Diego 15 San Diego Denver Philadelphia Baltimore Houston Tampa Miami 16 Dallas Orlando San Diego San Jose Tampa Houston Tampa 17 Portland Dallas Phoenix Phoenix Dallas San Diego Sacramento 18 Tampa Chicago Riverside Portland San Diego Pittsburgh New Orleans 19 Phoenix Portland Orlando Denver Phoenix Dallas Hartford 20 Denver Philadelphia Baltimore San Diego Pittsburgh Hartford San Antonio 21 Providence New Orleans Sacramento Pittsburgh Nashville Sacramento Orlando 22 Austin Tampa Austin Charlotte Portland Phoenix Pittsburgh 23 Sacramento Nashville Tampa Nashville Charlotte Detroit Milwaukee 24 Pittsburgh Phoenix Pittsburgh Orlando Detroit Orlando Austin 25 Orlando Minneapolis Charlotte Austin Austin Nashville Houston 26 Charlotte Jacksonville Nashville Sacramento Orlando Portland Detroit 27 Nashville Columbus Minneapolis Detroit Sacramento New Orleans Charlotte 28 Minneapolis Charlotte Jacksonville Providence Hartford Austin Raleigh 29 Raleigh Riverside Raleigh Minneapolis Raleigh Charlotte Portland 30 Detroit San Antonio Detroit Raleigh Denver Raleigh Birmingham 31 Jacksonville Baltimore San Antonio Cincinnati Cincinnati Birmingham Denver 32 New Orleans Hartford Columbus Hartford Cleveland Cincinnati Nashville 33 San Antonio Raleigh Cincinnati Cleveland Jacksonville Jacksonville Dallas 34 Hartford Birmingham Cleveland Jacksonville Minneapolis Cleveland Cincinnati 35 Cincinnati Las Vegas Hartford St. Louis New Orleans San Antonio Indianapolis 36 Columbus Salt Lake City Indianapolis Indianapolis Virginia Beach Denver Columbus 37 Cleveland Cleveland St. Louis San Antonio Birmingham Minneapolis Richmond 38 Birmingham Detroit New Orleans Birmingham St. Louis Virginia Beach Virginia Beach 39 Indianapolis Cincinnati Birmingham Virginia Beach San Antonio Milwaukee Cleveland 40 St. Louis St. Louis Las Vegas Kansas City Columbus Columbus Louisville 41 Las Vegas Indianapolis Kansas City Columbus Indianapolis Indianapolis Phoenix 42 Salt Lake City Milwaukee Providence New Orleans Salt Lake City St. Louis Jacksonville 43 Milwaukee Louisville Louisville Milwaukee Milwaukee Louisville Buffalo 44 Virginia Beach Virginia Beach Buffalo Buffalo Kansas City Richmond Minneapolis 45 Kansas City Richmond Milwaukee Oklahoma City Louisville Kansas City Kansas City 46 Louisville Kansas City Richmond Richmond Oklahoma City Salt Lake City Memphis 47 Buffalo Providence Virginia Beach Salt Lake City Richmond Oklahoma City St. Louis 48 Richmond Buffalo Salt Lake City Louisville Buffalo Buffalo Oklahoma City 49 Oklahoma City Oklahoma City Oklahoma City Memphis Memphis Memphis Salt Lake City 50 Memphis Memphis Memphis Las Vegas Las Vegas Las Vegas Las Vegas 15 Table 7: 1-Year Change in Weighted Congestion Impact Rank Area 1-Year Change in Congestion Impact 1 Charlotte +3.24 2 Baltimore +2.64 3 St. Louis +2.08 4 Kansas City +1.88 5 Pittsburgh +1.76 6 Tampa +1.61 7 Cincinnati +1.48 8 Sacramento +1.25 9 Philadelphia +1.08 10 Riverside +1.02 11 Boston +0.98 12 Washington +0.96 13 Orlando +0.85 14 Atlanta +0.75 15 Indianapolis +0.75 16 Cleveland +0.74 17 Louisville +0.74 18 Richmond +0.71 19 New York +0.69 20 San Francisco +0.69 21 New Orleans +0.59 22 Oklahoma City +0.57 23 Chicago +0.56 24 Virginia Beach +0.47 25 Birmingham +0.43 26 Raleigh +0.40 27 San Jose +0.18 28 Dallas +0.16 29 Buffalo +0.13 30 Denver +0.12 31 Providence +0.06 32 Los Angeles -0.18 33 Memphis -0.24 34 Portland -0.32 35 Hartford -0.34 36 San Diego -0.38 37 Seattle -0.49 38 Columbus -0.65 39 Nashville -0.79 40 Las Vegas -1.02 41 Jacksonville -1.22 42 Minneapolis -1.29 43 Houston -1.30 44 Austin -1.40 45 Salt Lake City -1.42 46 Miami -1.91 47 Detroit -1.97 48 Phoenix -2.05 49 Milwaukee -4.13 50 San Antonio -8.94 16 4 Data Sources and Methodology The following sections provide a brief overview of the data sources andmethodology used to prepare this report. For a detailed description, please consult the Accessibility Observatory’s Access Across America: Auto 2019 Methodology report. 4.1 Travel Times by Auto Travel times by car were calculated using the June 2019 version of TomTom North America, Inc.’s MultiNet and Speed Proʮle data products. The road network dataset includes roadways of all functional classiʮcations, including local streets throughmajor highways. Speed data for each roadway segment are based on measurements collected by GPS devices during the June 2017 – June 2019 period. For road segments where speed data are provided separately for different days of the week, data for Wednesday is used. 4.2 Geography Census blocks are the fundamental unit for travel time and accessibility calculation, and block-level accessibility results are aggregated over larger areas for analysis. When calculating accessibility for an individual origin, all potential destinations within 74.6 miles (120 km) are included, even if those destinations are located in a different state. Only locations within the United States are included. 4.3 Population and Job Distribution Data describing the distribution of labor and employment in the region are drawn from the U.S. Cen- sus Bureau’s Longitudinal Employer-Household Dynamics program (LEHD)5. The LEHD Origin- Destination Employment Statistics (LODES) dataset, which is updated annually, provides Census block-level estimates of employee home and work locations. This analysis uses LODES data from 2016, the most recent available as of this writing. 4.4 Accessibility Calculation The accessibility metrics presented in this analysis are cumulative opportunity metrics — they reʯect the total amount of opportunities (in this case, jobs) reachable within given travel time thresholds from an origin location. To calculate these metrics, the travel time calculations described above are performed ʮrst to identify the travel time from one origin to all surrounding destinations. Next, the number of jobs at each destination is summed for all destinations that can be reached within a given travel time threshold, providing the accessibility value for a single origin at a single departure time. This process provides accessibility values for individual Census blocks. To summarize this block- level data to larger areas, the accessibility values for the relevant blocks are weighted by the number 5http://lehd.ces.census.gov/data/ 17 of workers living in each block and then averaged. This person-weighted approach allows the sum- mary metric to reʯect the distribution of residents within the area. For example, a person-weighted accessibility value of 134,173 indicates that a typical resident within the area can reach 134,173 jobs. Road and highways speeds vary throughout the day. The accessibility data presented in this report assume a departure time of 8 AM in order to represent job accessibility during the AM peak period. 5 Comparisons With Previous Years This analysis uses the same tools and techniques asAccess Across America: Auto 2018, at the same national scale. It also uses the same datasets, updated to more recent versions as detailed in Access Across America: Auto 2019 Methodology. Beginning in data year 2018, federal jobs and federal workers are not included due to changes in underlying datasets from the U.S. Census Bureau. As a result, comparisons between 2018 and 2019 accessibility results are possible, and provide a way to monitor changes in accessibility over time. 6 Discussion This research provides a new methodology and dataset to enable inter-metropolitan comparisons of accessibility to jobs by auto in a way that is clearly understood and explainable, track with our experience and the available evidence, and incorporates highly detailed data describing the structure and speed of the entire US road and highway network. Not all jobs are the same. Some jobs are higher paying, some are lower skilled, and they exist in a variety of industries. Given suʪcient data, one could differentiate accessibility by breaking down jobs by type and get different results. Accessibility to non-work locations (shopping, health care, education, etc.) is also important. Regardless of trip purpose, people who experience higher accessibility tend to travel shorter distances because origins and destinations are closer together. But accessibility to jobs is not the only thing that people care about. If it were, cities would be situated on a minimum amount of space so people could live immediately adjacent to their jobs, or everyone would work from home. Measuring (and then valuing) accessibility to other opportunities and considering the trade-off between accessibility and living space are central problems of urban economics, regional science, and transportation and land-use planning. While being more accessible is generally better, there are costs as well as beneʮts associated with accessibility. If land is more valuable, its price is higher, and purchasers can afford less. Streets in places with more activities are inherently more crowded, and trips are less peaceful. Accessibility is a function of both transportation and land-use decisions, which has important policy implications. There are two broad avenues to increasing accessibility: improving transportation systems and altering land-use patterns. Neither of these things can be easily shifted overnight, but over time they do change—through direct plans and action as well as through market forces. 18 6.1 Land-Use Effects Land-use-based approaches to improving auto accessibility revolve around proximity and density for both origins and destinations. Density is the manifestation of the increasing value of more accessible locations. As residential areas become denser, more residents experience the local accessibility; as em- ployment areas become denser, more jobs can be accessed through the same road and highway network. Density is not determined solely by accessibility, however: land-use policies can restrict density where it would otherwise be high or encourage density where it might otherwise be low. Among the most famous examples of such policies are Oregon’s urban growth boundary laws, which encourage density by restricting the amount of land available for urban development, and the Height of Buildings Act of 1910, which restricts density in the District of Columbia by limiting building heights. A range of density-focused urban policies, often embedded in zoning codes, are implemented across the country and contribute to each city’s accessibility performance. Finally, it is important to note that the job and employment data used in this analysis does not include jobs outside of the United States. While international commuting is rare, it does occur in cities close to national borders. Including these jobs would indicate higher accessibility values for border cities, especially those which are near large foreign cities. 6.2 Congestion Effects Congestion is a widely-discussed aspect of urban road and highway systems. Typical investigations of congestion measure its costs in terms of “extra” time spent commuting, or relative increases in commute times compared to free-ʯow travel. These approaches implicitly focus on the experience of individual travelers. This report takes a different approach to evaluating congestion by measuring access to destinations. Congestion is reʯected by the decrease in the number of jobs that can be reached at congested times of day relative to free-ʯow times. Rather than focusing on the experiences of individual travelers, this approach seeks to quantify the overall impact that congestion has on the potential for interaction within urban areas. Larger, denser cities typically experience greater congestion than smaller cities. But within this over- arching trend, variation in the arrangement of land uses, road network structure, traʪc management practices, and the provision of alternate transportation modes allows individual cities to experience greater or lesser congestion impacts than their size would predict. For example, Boston ranks 18th by job accessibility by auto but 5th by congestion impact, indicat- ing that congestion may play a relatively larger role in limiting local access to jobs than in other cities. Geography likely plays a role here: access to Boston’s CBD is signiʮcantly dependent on bridges and tunnels with limited capacity. Conversely, Dallas ranks 3rd by job accessibility but 16th by congestion impact, suggesting that job accessibility is inʯuenced less by congestion there than in other cities. This is not to suggest that drivers in Dallas do not experience congestion—only that other factors, such as zoning, highway capacity, and other land use issues, play a relatively larger role in determining job accessibility. The geography of congestion and how it relates to land-use patterns is evident within the spatial congestionmaps in Section 7. In general, most cities exhibit a “ring of congestion” effect, where workers 19 departing from Census blocks closer to a city center or central business district experience smaller losses in accessibility than those departing from Census blocks some distance out from the city center. However, within cities characterized by a less concentrated central business district and more uniform density across a wider area of the city, such as Los Angeles, this effect of reduced loss of accessibility due to congestion within the city center is mitigated, and congestion impacts appear more evenly distributed throughout the city core and surrounding area. 6.3 Conclusions This report uses an approach to accessibility evaluation which can be applied consistently across different transportation modes. The metrics presented here, as in all of the Access Across America reports, indicate the number of jobs that can be reached in a given travel times— a simple concept that can be understood equally well in the context of travel by auto, transit, walking, or biking. This provides new opportunities for comparisons across transportation modes. Transportation and land-use systems are both dynamic, and this report presents only a single snap- shot in time. In constantly-evolving systems like these, it is also critical to monitor changes over time. A city that adopts a goal of increasing accessibility by auto should be evaluated based on how effectively it advanced that goal relative to a baseline. The data presented in the Access Across America report series can show how accessibility in these metropolitan areas evolves in response to transportation investments and land-use decisions. 20 7 Metropolitan Area Data and Maps The following pages present summary accessibility data andmaps for each of the 50 includedmetropoli- tan areas. Metropolitan areas are presented in alphabetical order. The maps show 30-minute accessi- bility values and congestion impact values at the Census block level. On the data summary pages, two separate chart scales, and a third for New York City, are used to allow simple comparison of accessibility values across metropolitan areas while accounting for readability. All charts using the same scale are plotted in the same color. 21 Atlanta Atlanta-Sandy Springs-Marietta, GA Rank by Weighted Accessibility 28 Rank by Weighted Congestion Impact 6 Rank by Total Employment 8 Rank by 1-Year Change in Weighted Accessibility 16 Rank by 1-Year Change in Weighted Congestion Impact 14 1-Year Change in Weighted Accessibility +3.26% 1-Year Change in Weighted Congestion Impact +0.8% Total Jobs 2,637,483 Average Job Density (per mi2) 316 Total Workers 2,534,711 Average Worker Density (per mi2) 303 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 31,187 187,161 484,464 883,595 1,349,658 1,852,199 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +1,824 +7,654 +13,126 +20,363 +34,229 +53,225 22 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 57.0% 60.8% 57.4% 49.9% 39.5% 27.2% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.6% +0.6% +0.9% +0.8% +0.4% +0.0% 23 24 25 Austin Austin-Round Rock-San Marcos, TX Rank by Weighted Accessibility 32 Rank by Weighted Congestion Impact 22 Rank by Total Employment 28 Rank by 1-Year Change in Weighted Accessibility 11 Rank by 1-Year Change in Weighted Congestion Impact 44 1-Year Change in Weighted Accessibility +4.07% 1-Year Change in Weighted Congestion Impact -1.4% Total Jobs 1,004,341 Average Job Density (per mi2) 238 Total Workers 967,584 Average Worker Density (per mi2) 229 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 50,160 244,925 494,183 731,502 938,597 1,106,297 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 -1,084 +9,083 +26,704 +37,149 +46,960 +61,128 26 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 54.8% 49.4% 35.5% 20.8% 11.8% 10.8% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.3% -1.0% -1.9% -1.9% -1.9% -2.5% 27 28 29 Baltimore Baltimore-Towson, MD Rank by Weighted Accessibility 25 Rank by Weighted Congestion Impact 12 Rank by Total Employment 21 Rank by 1-Year Change in Weighted Accessibility 50 Rank by 1-Year Change in Weighted Congestion Impact 2 1-Year Change in Weighted Accessibility -3.97% 1-Year Change in Weighted Congestion Impact +2.6% Total Jobs 1,316,328 Average Job Density (per mi2) 505 Total Workers 1,277,911 Average Worker Density (per mi2) 491 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 38,909 220,238 539,136 915,199 1,320,280 1,803,526 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 -880 -11,715 -28,611 -38,060 -35,079 -46,519 30 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 46.6% 49.7% 43.5% 43.2% 46.3% 46.6% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +1.3% +2.9% +3.4% +2.9% +1.9% +2.1% 31 32 33 Birmingham Birmingham-Hoover, AL Rank by Weighted Accessibility 50 Rank by Weighted Congestion Impact 38 Rank by Total Employment 50 Rank by 1-Year Change in Weighted Accessibility 33 Rank by 1-Year Change in Weighted Congestion Impact 25 1-Year Change in Weighted Accessibility +1.06% 1-Year Change in Weighted Congestion Impact +0.4% Total Jobs 510,537 Average Job Density (per mi2) 96 Total Workers 479,837 Average Worker Density (per mi2) 90 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 250,000 500,000 750,000 1,000,000 24,105 130,535 266,839 374,229 482,502 597,293 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +880 +2,774 +1,433 -1,079 -2,279 -557 34 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 43.9% 34.0% 18.8% 11.9% 10.3% 8.4% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 -0.0% -0.1% +0.2% +0.9% +1.2% +0.8% 35 36 37 Boston Boston-Cambridge-Quincy, MA-NH Rank by Weighted Accessibility 18 Rank by Weighted Congestion Impact 5 Rank by Total Employment 10 Rank by 1-Year Change in Weighted Accessibility 40 Rank by 1-Year Change in Weighted Congestion Impact 11 1-Year Change in Weighted Accessibility -0.06% 1-Year Change in Weighted Congestion Impact +1.0% Total Jobs 2,682,278 Average Job Density (per mi2) 769 Total Workers 2,464,508 Average Worker Density (per mi2) 706 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 44,386 233,219 582,975 1,063,205 1,622,819 2,245,988 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 -417 -2,075 -123 +5,968 +10,146 +3,970 38 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 64.1% 64.3% 58.1% 50.8% 42.7% 32.7% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.8% +1.1% +1.0% +0.8% +0.8% +1.1% 39 40 41 Buffalo Buffalo-Niagara Falls, NY Rank by Weighted Accessibility 43 Rank by Weighted Congestion Impact 47 Rank by Total Employment 48 Rank by 1-Year Change in Weighted Accessibility 35 Rank by 1-Year Change in Weighted Congestion Impact 29 1-Year Change in Weighted Accessibility +0.98% 1-Year Change in Weighted Congestion Impact +0.1% Total Jobs 546,694 Average Job Density (per mi2) 349 Total Workers 525,947 Average Worker Density (per mi2) 336 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 250,000 500,000 750,000 1,000,000 43,697 209,641 386,918 488,763 544,381 593,060 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +1,392 +3,480 +1,445 -1,614 -3,223 -802 42 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 35.0% 26.1% 12.1% 5.1% 2.6% 4.7% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.1% -0.1% -0.1% -0.0% +0.1% +0.8% 43 44 45 Charlotte Charlotte-Gastonia-Rock Hill, NC-SC Rank by Weighted Accessibility 38 Rank by Weighted Congestion Impact 26 Rank by Total Employment 34 Rank by 1-Year Change in Weighted Accessibility 31 Rank by 1-Year Change in Weighted Congestion Impact 1 1-Year Change in Weighted Accessibility +1.44% 1-Year Change in Weighted Congestion Impact +3.2% Total Jobs 1,037,014 Average Job Density (per mi2) 336 Total Workers 930,190 Average Worker Density (per mi2) 301 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 35,291 188,297 454,198 770,678 1,024,155 1,224,185 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +1,069 +2,563 +3,497 +10,688 +14,371 +20,352 46 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 46.9% 47.9% 37.8% 21.8% 11.5% 9.0% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +5.0% +3.8% +2.9% +1.7% +1.4% +0.9% 47 48 49 Chicago Chicago-Joliet-Naperville, IL-IN-WI Rank by Weighted Accessibility 5 Rank by Weighted Congestion Impact 9 Rank by Total Employment 3 Rank by 1-Year Change in Weighted Accessibility 25 Rank by 1-Year Change in Weighted Congestion Impact 23 1-Year Change in Weighted Accessibility +2.07% 1-Year Change in Weighted Congestion Impact +0.6% Total Jobs 4,559,884 Average Job Density (per mi2) 633 Total Workers 4,448,938 Average Worker Density (per mi2) 618 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 60,334 306,379 781,933 1,451,087 2,259,834 3,098,658 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +2,181 +6,523 +12,678 +26,910 +40,483 +62,920 50 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 53.6% 59.3% 55.0% 48.1% 37.5% 25.6% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.3% +0.8% +0.9% +0.4% +0.1% -0.7% 51 52 53 Cincinnati Cincinnati-Middletown, OH-KY-IN Rank by Weighted Accessibility 34 Rank by Weighted Congestion Impact 35 Rank by Total Employment 25 Rank by 1-Year Change in Weighted Accessibility 38 Rank by 1-Year Change in Weighted Congestion Impact 7 1-Year Change in Weighted Accessibility +0.52% 1-Year Change in Weighted Congestion Impact +1.5% Total Jobs 1,051,395 Average Job Density (per mi2) 239 Total Workers 1,045,101 Average Worker Density (per mi2) 237 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 35,052 211,722 504,322 805,607 1,055,313 1,249,533 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +532 -370 +1,032 +6,799 +10,079 +12,605 54 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 39.6% 37.2% 27.6% 16.5% 10.1% 7.6% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +1.6% +2.0% +1.5% +0.9% +0.7% +0.6% 55 56 57 Cleveland Cleveland-Elyria-Mentor, OH Rank by Weighted Accessibility 31 Rank by Weighted Congestion Impact 37 Rank by Total Employment 30 Rank by 1-Year Change in Weighted Accessibility 45 Rank by 1-Year Change in Weighted Congestion Impact 16 1-Year Change in Weighted Accessibility -0.62% 1-Year Change in Weighted Congestion Impact +0.7% Total Jobs 1,023,177 Average Job Density (per mi2) 512 Total Workers 961,969 Average Worker Density (per mi2) 481 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 34,441 209,087 516,984 867,340 1,169,079 1,410,739 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 -217 -3,058 -2,618 -3,125 -1,495 -2,023 58 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 41.1% 37.0% 25.1% 15.6% 8.8% 5.9% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +1.0% +1.2% +0.6% +0.5% +0.3% +0.2% 59 60 61 Columbus Columbus, OH Rank by Weighted Accessibility 20 Rank by Weighted Congestion Impact 36 Rank by Total Employment 32 Rank by 1-Year Change in Weighted Accessibility 14 Rank by 1-Year Change in Weighted Congestion Impact 38 1-Year Change in Weighted Accessibility +3.81% 1-Year Change in Weighted Congestion Impact -0.6% Total Jobs 1,025,982 Average Job Density (per mi2) 258 Total Workers 946,698 Average Worker Density (per mi2) 238 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 49,625 301,604 615,025 825,938 990,123 1,140,390 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +1,485 +14,040 +24,467 +25,476 +26,471 +25,215 62 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 47.1% 37.6% 17.0% 9.8% 6.2% 6.7% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.1% -1.1% -1.0% -0.4% -0.2% +0.1% 63 64 65 Dallas Dallas-Fort Worth-Arlington, TX Rank by Weighted Accessibility 3 Rank by Weighted Congestion Impact 16 Rank by Total Employment 4 Rank by 1-Year Change in Weighted Accessibility 8 Rank by 1-Year Change in Weighted Congestion Impact 28 1-Year Change in Weighted Accessibility +5.38% 1-Year Change in Weighted Congestion Impact +0.2% Total Jobs 3,546,551 Average Job Density (per mi2) 397 Total Workers 3,366,285 Average Worker Density (per mi2) 377 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 65,805 418,056 1,079,330 1,893,807 2,659,576 3,151,871 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -400,000 -200,000 0 200,000 400,000 +1,398 +24,935 +60,668 +105,363 +132,157 +119,312 66 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 53.6% 55.2% 45.8% 32.0% 17.2% 7.7% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +2.0% +0.4% +0.0% -0.9% -1.4% -0.8% 67 68 69 Denver Denver-Aurora-Broomfield, CO Rank by Weighted Accessibility 10 Rank by Weighted Congestion Impact 20 Rank by Total Employment 18 Rank by 1-Year Change in Weighted Accessibility 24 Rank by 1-Year Change in Weighted Congestion Impact 30 1-Year Change in Weighted Accessibility +2.08% 1-Year Change in Weighted Congestion Impact +0.1% Total Jobs 1,450,715 Average Job Density (per mi2) 173 Total Workers 1,395,732 Average Worker Density (per mi2) 167 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 62,272 341,662 797,919 1,249,511 1,528,240 1,711,466 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +632 +7,152 +17,868 +27,371 +31,958 +35,935 70 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 53.9% 54.9% 38.6% 17.5% 8.2% 7.9% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.7% +0.1% -0.0% +0.0% -0.0% -0.1% 71 72 73 Detroit Detroit-Warren-Livonia, MI Rank by Weighted Accessibility 8 Rank by Weighted Congestion Impact 30 Rank by Total Employment 13 Rank by 1-Year Change in Weighted Accessibility 5 Rank by 1-Year Change in Weighted Congestion Impact 47 1-Year Change in Weighted Accessibility +6.50% 1-Year Change in Weighted Congestion Impact -2.0% Total Jobs 1,934,459 Average Job Density (per mi2) 497 Total Workers 1,915,549 Average Worker Density (per mi2) 492 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 57,058 346,508 813,942 1,307,016 1,726,422 2,064,581 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +3,008 +25,547 +56,914 +79,040 +76,846 +74,477 74 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 40.4% 39.1% 31.6% 21.6% 13.7% 9.7% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.3% -1.9% -2.7% -3.1% -2.2% -1.5% 75 76 77 Hartford Hartford-West Hartford-East Hartford, CT Rank by Weighted Accessibility 30 Rank by Weighted Congestion Impact 34 Rank by Total Employment 45 Rank by 1-Year Change in Weighted Accessibility 28 Rank by 1-Year Change in Weighted Congestion Impact 35 1-Year Change in Weighted Accessibility +1.89% 1-Year Change in Weighted Congestion Impact -0.3% Total Jobs 637,565 Average Job Density (per mi2) 420 Total Workers 595,341 Average Worker Density (per mi2) 393 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 38,271 216,432 494,557 825,316 1,166,832 1,493,350 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +147 +2,847 +9,613 +20,271 +30,183 +33,411 78 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 45.6% 35.8% 25.1% 18.7% 15.3% 13.8% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.2% -0.4% -0.5% -0.2% -0.3% -0.3% 79 80 81 Houston Houston-Sugar Land-Baytown, TX Rank by Weighted Accessibility 7 Rank by Weighted Congestion Impact 13 Rank by Total Employment 5 Rank by 1-Year Change in Weighted Accessibility 10 Rank by 1-Year Change in Weighted Congestion Impact 43 1-Year Change in Weighted Accessibility +4.73% 1-Year Change in Weighted Congestion Impact -1.3% Total Jobs 2,977,082 Average Job Density (per mi2) 337 Total Workers 2,894,863 Average Worker Density (per mi2) 327 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 50,898 309,443 790,245 1,429,365 2,057,094 2,503,954 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -400,000 -200,000 0 200,000 400,000 -1,596 +6,431 +47,137 +114,733 +128,615 +82,794 82 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 58.7% 59.1% 51.1% 35.9% 20.8% 10.6% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +2.5% +0.6% -1.9% -4.4% -4.4% -2.6% 83 84 85 Indianapolis Indianapolis-Carmel, IN Rank by Weighted Accessibility 26 Rank by Weighted Congestion Impact 39 Rank by Total Employment 35 Rank by 1-Year Change in Weighted Accessibility 34 Rank by 1-Year Change in Weighted Congestion Impact 15 1-Year Change in Weighted Accessibility +1.04% 1-Year Change in Weighted Congestion Impact +0.7% Total Jobs 1,012,511 Average Job Density (per mi2) 262 Total Workers 919,836 Average Worker Density (per mi2) 238 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 42,334 248,464 570,795 840,424 1,013,913 1,165,886 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +382 +1,873 +6,139 +10,515 +12,572 +13,291 86 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 38.7% 34.8% 21.6% 9.8% 6.0% 6.9% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +1.1% +0.9% +0.6% +0.4% +0.4% +0.5% 87 88 89 Jacksonville Jacksonville, FL Rank by Weighted Accessibility 47 Rank by Weighted Congestion Impact 31 Rank by Total Employment 40 Rank by 1-Year Change in Weighted Accessibility 3 Rank by 1-Year Change in Weighted Congestion Impact 41 1-Year Change in Weighted Accessibility +7.01% 1-Year Change in Weighted Congestion Impact -1.2% Total Jobs 694,925 Average Job Density (per mi2) 217 Total Workers 662,664 Average Worker Density (per mi2) 207 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 250,000 500,000 750,000 1,000,000 28,473 161,182 344,451 489,403 601,372 686,489 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +2,292 +12,481 +24,056 +25,208 +27,356 +30,360 90 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 48.5% 40.1% 24.4% 15.3% 8.9% 5.5% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 -1.0% -1.7% -2.0% -0.6% -0.2% +0.0% 91 92 93 Kansas City Kansas City, MO-KS Rank by Weighted Accessibility 21 Rank by Weighted Congestion Impact 45 Rank by Total Employment 26 Rank by 1-Year Change in Weighted Accessibility 47 Rank by 1-Year Change in Weighted Congestion Impact 4 1-Year Change in Weighted Accessibility -0.98% 1-Year Change in Weighted Congestion Impact +1.9% Total Jobs 1,059,744 Average Job Density (per mi2) 135 Total Workers 1,036,878 Average Worker Density (per mi2) 132 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 49,787 287,412 617,423 871,347 1,009,014 1,126,852 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 -751 -7,301 -8,165 +3,936 +10,400 +10,728 94 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 35.6% 29.4% 17.3% 6.6% 3.4% 3.1% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +2.5% +2.7% +2.1% +0.7% +0.1% -0.0% 95 96 97 Las Vegas Las Vegas-Paradise, NV Rank by Weighted Accessibility 12 Rank by Weighted Congestion Impact 41 Rank by Total Employment 33 Rank by 1-Year Change in Weighted Accessibility 7 Rank by 1-Year Change in Weighted Congestion Impact 40 1-Year Change in Weighted Accessibility +6.23% 1-Year Change in Weighted Congestion Impact -1.0% Total Jobs 956,530 Average Job Density (per mi2) 121 Total Workers 941,812 Average Worker Density (per mi2) 119 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 250,000 500,000 750,000 1,000,000 67,274 450,370 831,538 888,493 893,252 896,922 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +5,277 +40,258 +37,335 +21,031 +20,138 +19,735 98 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 43.6% 32.9% 5.4% 0.3% 0.1% 0.2% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +1.8% -3.0% -2.0% -0.1% -0.0% -0.0% 99 100 101 Los Angeles Los Angeles-Long Beach-Santa Ana, CA Rank by Weighted Accessibility 1 Rank by Weighted Congestion Impact 1 Rank by Total Employment 2 Rank by 1-Year Change in Weighted Accessibility 22 Rank by 1-Year Change in Weighted Congestion Impact 32 1-Year Change in Weighted Accessibility +2.11% 1-Year Change in Weighted Congestion Impact -0.2% Total Jobs 6,249,699 Average Job Density (per mi2) 1,289 Total Workers 5,825,012 Average Worker Density (per mi2) 1,201 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 2,000,000 4,000,000 6,000,000 8,000,000 96,746 525,411 1,275,161 2,251,284 3,386,696 4,566,776 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +2,384 +12,380 +29,045 +42,317 +55,828 +75,995 102 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 65.7% 69.2% 65.7% 58.0% 46.8% 34.5% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.1% -0.1% -0.3% -0.3% -0.3% -0.3% 103 104 105 Louisville Louisville/Jefferson County, KY-IN Rank by Weighted Accessibility 39 Rank by Weighted Congestion Impact 46 Rank by Total Employment 41 Rank by 1-Year Change in Weighted Accessibility 37 Rank by 1-Year Change in Weighted Congestion Impact 17 1-Year Change in Weighted Accessibility +0.61% 1-Year Change in Weighted Congestion Impact +0.7% Total Jobs 668,246 Average Job Density (per mi2) 162 Total Workers 645,505 Average Worker Density (per mi2) 157 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 250,000 500,000 750,000 1,000,000 41,381 233,733 438,152 558,419 662,564 758,047 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +709 +328 +1,750 +4,485 +5,510 +6,567 106 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 38.3% 27.8% 11.6% 6.4% 5.1% 5.8% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +1.1% +0.9% +0.6% +0.2% +0.1% +0.2% 107 108 109 Memphis Memphis, TN-MS-AR Rank by Weighted Accessibility 40 Rank by Weighted Congestion Impact 50 Rank by Total Employment 46 Rank by 1-Year Change in Weighted Accessibility 27 Rank by 1-Year Change in Weighted Congestion Impact 33 1-Year Change in Weighted Accessibility +1.90% 1-Year Change in Weighted Congestion Impact -0.2% Total Jobs 615,157 Average Job Density (per mi2) 134 Total Workers 589,984 Average Worker Density (per mi2) 128 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 250,000 500,000 750,000 1,000,000 43,593 226,382 421,163 521,071 574,055 620,819 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +527 +4,432 +9,931 +9,052 +8,571 +8,890 110 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 30.4% 23.6% 10.2% 3.8% 2.5% 3.0% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.7% -0.4% -0.8% -0.3% -0.1% +0.1% 111 112 113 Miami Miami-Fort Lauderdale-Pompano Beach, FL Rank by Weighted Accessibility 19 Rank by Weighted Congestion Impact 10 Rank by Total Employment 9 Rank by 1-Year Change in Weighted Accessibility 2 Rank by 1-Year Change in Weighted Congestion Impact 46 1-Year Change in Weighted Accessibility +8.43% 1-Year Change in Weighted Congestion Impact -1.9% Total Jobs 2,560,082 Average Job Density (per mi2) 504 Total Workers 2,503,411 Average Worker Density (per mi2) 493 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 46,669 258,264 619,669 1,020,851 1,419,419 1,802,729 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -400,000 -200,000 0 200,000 400,000 +3,376 +19,499 +50,050 +80,597 +115,835 +133,660 114 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 61.3% 59.9% 50.4% 40.5% 30.2% 20.9% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 -0.2% -1.0% -2.1% -3.1% -4.1% -4.2% 115 116 117 Milwaukee Milwaukee-Waukesha-West Allis, WI Rank by Weighted Accessibility 15 Rank by Weighted Congestion Impact 43 Rank by Total Employment 37 Rank by 1-Year Change in Weighted Accessibility 43 Rank by 1-Year Change in Weighted Congestion Impact 49 1-Year Change in Weighted Accessibility -0.19% 1-Year Change in Weighted Congestion Impact -4.1% Total Jobs 856,719 Average Job Density (per mi2) 588 Total Workers 779,865 Average Worker Density (per mi2) 536 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 75,388 345,562 621,764 829,295 1,004,691 1,236,470 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 -467 -44 +1,137 -878 -5,729 -12,001 118 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 38.5% 26.1% 13.2% 7.4% 6.9% 10.8% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 -6.8% -4.7% -2.5% -1.0% -1.0% -1.1% 119 120 121 Minneapolis Minneapolis-St. Paul-Bloomington, MN-WI Rank by Weighted Accessibility 6 Rank by Weighted Congestion Impact 28 Rank by Total Employment 14 Rank by 1-Year Change in Weighted Accessibility 15 Rank by 1-Year Change in Weighted Congestion Impact 42 1-Year Change in Weighted Accessibility +3.40% 1-Year Change in Weighted Congestion Impact -1.3% Total Jobs 1,901,603 Average Job Density (per mi2) 315 Total Workers 1,847,804 Average Worker Density (per mi2) 306 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 62,834 392,836 893,707 1,342,099 1,634,236 1,826,877 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +2,238 +17,621 +30,341 +35,184 +33,012 +34,982 122 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 48.7% 43.4% 29.1% 15.0% 7.9% 4.7% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 -0.9% -1.8% -1.6% -1.0% -0.3% -0.0% 123 124 125 Nashville Nashville-Davidson–Murfreesboro–Franklin, TN Rank by Weighted Accessibility 46 Rank by Weighted Congestion Impact 27 Rank by Total Employment 36 Rank by 1-Year Change in Weighted Accessibility 13 Rank by 1-Year Change in Weighted Congestion Impact 39 1-Year Change in Weighted Accessibility +3.93% 1-Year Change in Weighted Congestion Impact -0.8% Total Jobs 922,352 Average Job Density (per mi2) 162 Total Workers 843,428 Average Worker Density (per mi2) 148 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 250,000 500,000 750,000 1,000,000 27,400 143,203 317,994 537,410 750,041 906,806 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +794 +5,734 +12,212 +21,575 +30,858 +29,682 126 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 50.2% 44.7% 36.3% 25.4% 13.2% 7.8% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.1% -1.1% -0.8% -0.9% -1.0% -0.2% 127 128 129 New Orleans New Orleans-Metairie-Kenner, LA Rank by Weighted Accessibility 49 Rank by Weighted Congestion Impact 32 Rank by Total Employment 49 Rank by 1-Year Change in Weighted Accessibility 46 Rank by 1-Year Change in Weighted Congestion Impact 21 1-Year Change in Weighted Accessibility -0.95% 1-Year Change in Weighted Congestion Impact +0.6% Total Jobs 534,498 Average Job Density (per mi2) 180 Total Workers 505,876 Average Worker Density (per mi2) 170 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 250,000 500,000 750,000 1,000,000 38,244 171,995 301,856 385,105 495,768 626,527 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 -469 -1,602 -2,252 -3,620 -5,562 -6,916 130 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 50.4% 34.5% 14.1% 13.6% 12.1% 13.8% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +1.1% +0.2% +0.1% +0.5% +0.9% +1.2% 131 132 133 New York New York-Northern New Jersey-Long Island, NY-NJ-PA Rank by Weighted Accessibility 2 Rank by Weighted Congestion Impact 3 Rank by Total Employment 1 Rank by 1-Year Change in Weighted Accessibility 32 Rank by 1-Year Change in Weighted Congestion Impact 19 1-Year Change in Weighted Accessibility +1.30% 1-Year Change in Weighted Congestion Impact +0.7% Total Jobs 9,159,786 Average Job Density (per mi2) 1,369 Total Workers 8,946,175 Average Worker Density (per mi2) 1,337 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 2,000,000 4,000,000 6,000,000 8,000,000 85,112 456,819 1,184,927 2,252,821 3,615,924 5,145,437 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +976 +6,878 +17,470 +35,960 +26,451 +48,268 The plot scales have been changed to accommodate the much larger number of jobs within New York City. 134 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 55.3% 64.6% 63.8% 56.5% 46.3% 35.8% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.9% +0.8% +0.6% +0.4% +0.7% +0.6% 135 136 137 Oklahoma City Oklahoma City, OK Rank by Weighted Accessibility 44 Rank by Weighted Congestion Impact 49 Rank by Total Employment 47 Rank by 1-Year Change in Weighted Accessibility 42 Rank by 1-Year Change in Weighted Congestion Impact 22 1-Year Change in Weighted Accessibility -0.18% 1-Year Change in Weighted Congestion Impact +0.6% Total Jobs 595,050 Average Job Density (per mi2) 107 Total Workers 565,695 Average Worker Density (per mi2) 102 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 250,000 500,000 750,000 1,000,000 39,531 209,701 384,053 493,861 561,821 609,473 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +629 -966 -2,465 -1,862 -1,591 -102 138 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 33.2% 24.3% 12.1% 5.8% 2.8% 2.1% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.4% +0.8% +0.5% +0.1% +0.1% +0.0% 139 140 141 Orlando Orlando-Kissimmee-Sanford, FL Rank by Weighted Accessibility 29 Rank by Weighted Congestion Impact 25 Rank by Total Employment 23 Rank by 1-Year Change in Weighted Accessibility 18 Rank by 1-Year Change in Weighted Congestion Impact 13 1-Year Change in Weighted Accessibility +2.93% 1-Year Change in Weighted Congestion Impact +0.8% Total Jobs 1,262,313 Average Job Density (per mi2) 362 Total Workers 1,135,710 Average Worker Density (per mi2) 326 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 31,684 201,753 536,084 892,612 1,185,288 1,450,711 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +949 +5,213 +12,945 +27,439 +40,120 +48,051 142 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 53.8% 50.7% 35.6% 20.5% 13.3% 11.8% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +1.0% +1.0% +1.0% +0.3% +0.2% +0.3% 143 144 145 Philadelphia Philadelphia-Camden-Wilmington, PA-NJ-DE-MD Rank by Weighted Accessibility 14 Rank by Weighted Congestion Impact 14 Rank by Total Employment 6 Rank by 1-Year Change in Weighted Accessibility 41 Rank by 1-Year Change in Weighted Congestion Impact 9 1-Year Change in Weighted Accessibility -0.13% 1-Year Change in Weighted Congestion Impact +1.1% Total Jobs 2,853,154 Average Job Density (per mi2) 619 Total Workers 2,862,819 Average Worker Density (per mi2) 622 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 42,652 238,279 617,757 1,179,390 1,873,317 2,633,691 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +203 -703 -2,394 -5,554 -2,961 +15,343 146 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 50.8% 53.9% 50.4% 43.1% 33.8% 26.4% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.6% +1.0% +1.1% +1.3% +1.3% +1.1% 147 148 149 Phoenix Phoenix-Mesa-Glendale, AZ Rank by Weighted Accessibility 9 Rank by Weighted Congestion Impact 19 Rank by Total Employment 12 Rank by 1-Year Change in Weighted Accessibility 4 Rank by 1-Year Change in Weighted Congestion Impact 48 1-Year Change in Weighted Accessibility +6.63% 1-Year Change in Weighted Congestion Impact -2.1% Total Jobs 2,007,240 Average Job Density (per mi2) 137 Total Workers 1,958,550 Average Worker Density (per mi2) 134 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 64,911 345,459 773,754 1,217,889 1,575,685 1,791,768 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -400,000 -200,000 0 200,000 400,000 +83 +19,346 +66,980 +95,317 +102,491 +86,060 150 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 48.9% 51.5% 42.4% 27.9% 14.3% 5.7% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.9% -1.2% -3.3% -3.6% -3.2% -1.9% 151 152 153 Pittsburgh Pittsburgh, PA Rank by Weighted Accessibility 48 Rank by Weighted Congestion Impact 24 Rank by Total Employment 24 Rank by 1-Year Change in Weighted Accessibility 49 Rank by 1-Year Change in Weighted Congestion Impact 5 1-Year Change in Weighted Accessibility -1.36% 1-Year Change in Weighted Congestion Impact +1.8% Total Jobs 1,138,726 Average Job Density (per mi2) 215 Total Workers 1,105,247 Average Worker Density (per mi2) 209 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 23,475 128,607 314,545 554,539 799,820 1,030,880 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 -547 -2,695 -4,728 -5,731 -5,534 -4,949 154 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 54.7% 47.9% 37.9% 26.3% 18.1% 11.6% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +2.0% +2.0% +1.7% +1.5% +1.3% +1.0% 155 156 157 Portland Portland-Vancouver-Hillsboro, OR-WA Rank by Weighted Accessibility 27 Rank by Weighted Congestion Impact 17 Rank by Total Employment 22 Rank by 1-Year Change in Weighted Accessibility 12 Rank by 1-Year Change in Weighted Congestion Impact 34 1-Year Change in Weighted Accessibility +3.98% 1-Year Change in Weighted Congestion Impact -0.3% Total Jobs 1,165,042 Average Job Density (per mi2) 174 Total Workers 1,140,463 Average Worker Density (per mi2) 170 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 49,874 241,178 524,725 822,162 1,048,680 1,193,970 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +1,687 +8,621 +22,437 +34,692 +39,085 +38,399 158 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 53.6% 54.3% 40.7% 23.4% 13.1% 8.4% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.3% -0.0% -0.7% -1.0% -0.9% -0.6% 159 160 161 Providence Providence-New Bedford-Fall River, RI-MA Rank by Weighted Accessibility 41 Rank by Weighted Congestion Impact 21 Rank by Total Employment 38 Rank by 1-Year Change in Weighted Accessibility 26 Rank by 1-Year Change in Weighted Congestion Impact 31 1-Year Change in Weighted Accessibility +1.91% 1-Year Change in Weighted Congestion Impact +0.1% Total Jobs 689,902 Average Job Density (per mi2) 434 Total Workers 775,615 Average Worker Density (per mi2) 488 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 34,490 164,294 358,636 615,417 934,341 1,285,696 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +383 +3,046 +7,014 +12,775 +20,035 +23,836 162 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 35.5% 29.1% 31.4% 41.6% 49.3% 52.0% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.8% -0.1% -0.1% +0.1% +0.0% +0.0% 163 164 165 Raleigh Raleigh-Cary, NC Rank by Weighted Accessibility 35 Rank by Weighted Congestion Impact 29 Rank by Total Employment 43 Rank by 1-Year Change in Weighted Accessibility 19 Rank by 1-Year Change in Weighted Congestion Impact 26 1-Year Change in Weighted Accessibility +2.87% 1-Year Change in Weighted Congestion Impact +0.4% Total Jobs 677,938 Average Job Density (per mi2) 320 Total Workers 615,937 Average Worker Density (per mi2) 290 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 42,402 231,029 497,633 735,547 944,776 1,129,214 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +1,614 +6,615 +14,046 +18,225 +22,952 +25,435 166 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 44.8% 40.1% 28.4% 17.6% 10.9% 9.0% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.1% +0.7% +0.3% +0.1% +0.1% +0.1% 167 168 169 Richmond Richmond, VA Rank by Weighted Accessibility 42 Rank by Weighted Congestion Impact 48 Rank by Total Employment 42 Rank by 1-Year Change in Weighted Accessibility 21 Rank by 1-Year Change in Weighted Congestion Impact 18 1-Year Change in Weighted Accessibility +2.31% 1-Year Change in Weighted Congestion Impact +0.7% Total Jobs 659,862 Average Job Density (per mi2) 116 Total Workers 640,682 Average Worker Density (per mi2) 112 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 250,000 500,000 750,000 1,000,000 39,574 204,535 403,256 531,653 623,146 732,256 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +1,126 +5,685 +8,539 +8,542 +10,070 +13,116 170 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 35.9% 25.9% 11.9% 5.6% 4.3% 6.1% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +2.0% +0.6% +0.0% +0.1% +0.2% +0.2% 171 172 173 Riverside Riverside-San Bernardino-Ontario, CA Rank by Weighted Accessibility 36 Rank by Weighted Congestion Impact 2 Rank by Total Employment 16 Rank by 1-Year Change in Weighted Accessibility 39 Rank by 1-Year Change in Weighted Congestion Impact 10 1-Year Change in Weighted Accessibility +0.37% 1-Year Change in Weighted Congestion Impact +1.0% Total Jobs 1,439,654 Average Job Density (per mi2) 52 Total Workers 1,749,931 Average Worker Density (per mi2) 64 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 36,260 189,858 442,803 749,962 1,128,388 1,707,424 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +1,381 +2,674 -532 +4,984 -8,326 -35,805 174 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 46.8% 51.3% 55.4% 63.1% 67.8% 64.9% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.4% +1.1% +1.5% +0.7% +0.9% +1.4% 175 176 177 Sacramento Sacramento–Arden-Arcade–Roseville, CA Rank by Weighted Accessibility 33 Rank by Weighted Congestion Impact 23 Rank by Total Employment 29 Rank by 1-Year Change in Weighted Accessibility 29 Rank by 1-Year Change in Weighted Congestion Impact 8 1-Year Change in Weighted Accessibility +1.68% 1-Year Change in Weighted Congestion Impact +1.3% Total Jobs 951,760 Average Job Density (per mi2) 186 Total Workers 964,523 Average Worker Density (per mi2) 189 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 45,015 231,429 489,816 756,394 956,128 1,123,578 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +1,083 +3,745 +4,730 +11,718 +20,438 +26,135 178 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 55.4% 49.4% 34.3% 19.2% 14.4% 17.3% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +1.4% +1.1% +1.4% +1.2% +0.7% +0.4% 179 180 181 Salt Lake City Salt Lake City, UT Rank by Weighted Accessibility 13 Rank by Weighted Congestion Impact 42 Rank by Total Employment 44 Rank by 1-Year Change in Weighted Accessibility 6 Rank by 1-Year Change in Weighted Congestion Impact 45 1-Year Change in Weighted Accessibility +6.34% 1-Year Change in Weighted Congestion Impact -1.4% Total Jobs 716,561 Average Job Density (per mi2) 74 Total Workers 605,393 Average Worker Density (per mi2) 63 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 83,595 419,677 684,399 910,142 1,061,572 1,119,352 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +7,930 +31,822 +30,862 +34,759 +36,358 +33,091 182 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 42.9% 24.7% 11.7% 8.3% 3.3% 1.2% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 -1.4% -2.9% -1.2% -0.5% -0.5% -0.1% 183 184 185 San Antonio San Antonio-New Braunfels, TX Rank by Weighted Accessibility 24 Rank by Weighted Congestion Impact 33 Rank by Total Employment 27 Rank by 1-Year Change in Weighted Accessibility 1 Rank by 1-Year Change in Weighted Congestion Impact 50 1-Year Change in Weighted Accessibility +16.92% 1-Year Change in Weighted Congestion Impact -8.9% Total Jobs 979,988 Average Job Density (per mi2) 134 Total Workers 1,019,742 Average Worker Density (per mi2) 139 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 250,000 500,000 750,000 1,000,000 50,099 301,711 585,172 774,898 899,837 987,194 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +6,756 +61,915 +90,681 +77,522 +63,301 +51,238 186 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 46.7% 38.0% 19.5% 10.8% 8.4% 11.8% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -20 -10 0 10 20 -6.5% -11.5% -10.7% -6.8% -4.1% -2.3% 187 188 189 San Diego San Diego-Carlsbad-San Marcos, CA Rank by Weighted Accessibility 16 Rank by Weighted Congestion Impact 15 Rank by Total Employment 17 Rank by 1-Year Change in Weighted Accessibility 20 Rank by 1-Year Change in Weighted Congestion Impact 36 1-Year Change in Weighted Accessibility +2.78% 1-Year Change in Weighted Congestion Impact -0.4% Total Jobs 1,403,191 Average Job Density (per mi2) 333 Total Workers 1,419,381 Average Worker Density (per mi2) 337 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 55,533 306,625 637,936 928,528 1,224,200 1,534,269 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +1,101 +7,140 +20,072 +27,052 +36,789 +41,744 190 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 59.0% 52.1% 38.2% 28.7% 20.2% 21.1% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.2% -0.2% -0.8% -0.8% -0.6% +0.0% 191 192 193 San Francisco San Francisco-Oakland-Fremont, CA Rank by Weighted Accessibility 11 Rank by Weighted Congestion Impact 4 Rank by Total Employment 11 Rank by 1-Year Change in Weighted Accessibility 30 Rank by 1-Year Change in Weighted Congestion Impact 20 1-Year Change in Weighted Accessibility +1.44% 1-Year Change in Weighted Congestion Impact +0.7% Total Jobs 2,400,290 Average Job Density (per mi2) 971 Total Workers 2,241,034 Average Worker Density (per mi2) 907 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 71,448 287,801 651,253 1,167,143 1,786,229 2,460,882 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +1,017 +4,417 +5,707 +18,544 +28,047 +43,885 194 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 56.1% 61.1% 61.6% 56.4% 46.8% 35.3% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +1.5% +0.8% +0.7% +0.3% +0.2% +0.1% 195 196 197 San Jose San Jose-Sunnyvale-Santa Clara, CA Rank by Weighted Accessibility 4 Rank by Weighted Congestion Impact 8 Rank by Total Employment 31 Rank by 1-Year Change in Weighted Accessibility 17 Rank by 1-Year Change in Weighted Congestion Impact 27 1-Year Change in Weighted Accessibility +3.10% 1-Year Change in Weighted Congestion Impact +0.2% Total Jobs 1,077,279 Average Job Density (per mi2) 402 Total Workers 947,987 Average Worker Density (per mi2) 353 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 79,839 442,549 831,681 1,223,992 1,674,326 2,222,606 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +3,476 +17,666 +23,423 +27,922 +33,352 +29,580 198 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 67.6% 54.5% 42.6% 43.3% 45.4% 36.6% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.6% -0.4% +0.0% +0.3% +0.3% +0.3% 199 200 201 Seattle Seattle-Tacoma-Bellevue, WA Rank by Weighted Accessibility 23 Rank by Weighted Congestion Impact 11 Rank by Total Employment 15 Rank by 1-Year Change in Weighted Accessibility 9 Rank by 1-Year Change in Weighted Congestion Impact 37 1-Year Change in Weighted Accessibility +4.94% 1-Year Change in Weighted Congestion Impact -0.5% Total Jobs 1,919,635 Average Job Density (per mi2) 326 Total Workers 1,798,352 Average Worker Density (per mi2) 306 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 51,792 238,503 548,802 863,561 1,170,946 1,445,102 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +2,437 +13,542 +26,380 +36,669 +48,058 +53,271 202 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 56.6% 58.6% 49.2% 41.4% 33.1% 24.4% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.1% -0.7% -0.7% -0.5% -0.7% -0.7% 203 204 205 St. Louis St. Louis, MO-IL Rank by Weighted Accessibility 22 Rank by Weighted Congestion Impact 40 Rank by Total Employment 19 Rank by 1-Year Change in Weighted Accessibility 48 Rank by 1-Year Change in Weighted Congestion Impact 3 1-Year Change in Weighted Accessibility -1.11% 1-Year Change in Weighted Congestion Impact +2.1% Total Jobs 1,363,165 Average Job Density (per mi2) 158 Total Workers 1,344,165 Average Worker Density (per mi2) 155 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 43,481 264,709 608,035 916,197 1,119,824 1,247,304 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +387 -6,473 -10,997 -7,179 +1,754 +5,806 206 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 38.8% 34.5% 22.5% 11.5% 5.9% 3.0% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +1.3% +2.9% +2.4% +1.6% +0.8% +0.4% 207 208 209 Tampa Tampa-St. Petersburg-Clearwater, FL Rank by Weighted Accessibility 37 Rank by Weighted Congestion Impact 18 Rank by Total Employment 20 Rank by 1-Year Change in Weighted Accessibility 36 Rank by 1-Year Change in Weighted Congestion Impact 6 1-Year Change in Weighted Accessibility +0.62% 1-Year Change in Weighted Congestion Impact +1.6% Total Jobs 1,307,910 Average Job Density (per mi2) 520 Total Workers 1,293,226 Average Worker Density (per mi2) 514 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 40,825 188,708 427,946 767,245 1,098,359 1,385,646 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +571 +1,151 -1,749 +4,288 +13,679 +17,949 210 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 50.4% 49.3% 46.1% 33.5% 23.7% 18.0% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +1.7% +1.5% +2.0% +1.4% +0.9% +1.0% 211 212 213 Virginia Beach Virginia Beach-Norfolk-Newport News, VA-NC Rank by Weighted Accessibility 45 Rank by Weighted Congestion Impact 44 Rank by Total Employment 39 Rank by 1-Year Change in Weighted Accessibility 23 Rank by 1-Year Change in Weighted Congestion Impact 24 1-Year Change in Weighted Accessibility +2.09% 1-Year Change in Weighted Congestion Impact +0.5% Total Jobs 711,408 Average Job Density (per mi2) 270 Total Workers 715,637 Average Worker Density (per mi2) 272 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 250,000 500,000 750,000 1,000,000 36,116 186,823 344,400 480,745 585,212 672,289 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +1,234 +5,072 +5,281 +6,077 +7,084 +8,702 214 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 36.7% 24.8% 17.9% 12.3% 7.2% 5.9% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.3% +0.1% +0.8% +0.7% +0.5% +0.2% 215 216 217 Washington Washington-Arlington-Alexandria, DC-VA-MD-WV Rank by Weighted Accessibility 17 Rank by Weighted Congestion Impact 7 Rank by Total Employment 7 Rank by 1-Year Change in Weighted Accessibility 44 Rank by 1-Year Change in Weighted Congestion Impact 12 1-Year Change in Weighted Accessibility -0.37% 1-Year Change in Weighted Congestion Impact +1.0% Total Jobs 2,830,896 Average Job Density (per mi2) 505 Total Workers 2,683,930 Average Worker Density (per mi2) 479 Job and worker totals are based on LEHD estimates and may not match other sources. Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min 1,000,000 2,000,000 3,000,000 4,000,000 43,170 226,747 564,270 1,062,673 1,699,171 2,392,428 1-Year Change in Average Job Accessibility by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -100,000 -50,000 0 50,000 100,000 +538 -37 -2,976 -10,577 -13,348 -9,431 218 Average Congestion Impact by Travel Time Threshold (worker-weighted) Higher numbers indicate greater job access loss due to congestion 10 min 20 min 30 min 40 min 50 min 60 min 0% 25% 50% 75% 100% 55.7% 59.0% 57.8% 51.0% 40.7% 30.3% 1-Year Change in Average Congestion Impact by Travel Time Threshold (worker-weighted) 10 min 20 min 30 min 40 min 50 min 60 min -10 -5 0 5 10 +0.8% +0.8% +0.7% +1.1% +1.3% +1.3% 219 220 221 References Geurs, K. and Van Eck, J. (2001). Accessibility measures: Review and applications. Technical Report 408505 006, National Institute of Public Health and the Environment. Handy, S. L. and Niemeier, D. A. (1997). Measuring accessibility: An exploration of issues and alter- natives. Environment and planning A, 29(7):1175–1194. Hansen, W. (1959). How accessibility shapes land use. Journal of the American Institute of Planners, 25(2):73–76. Levine, J., Grengs, J., Shen, Q., and Shen, Q. (2012). Does accessibility require density or speed? A comparison of fast versus close in getting where you want to go in U.S. metropolitan regions. Journal of the American Planning Association, 78(2):157–172. Levinson, D. M. (2013). Access across America. Technical Report CTS 13-20, Univer- sity of Minnesota Center for Transportation Studies, http://www.cts.umn.edu/Publications/ ResearchReports/pdfdownload.pl?id=2334. Owen, A. and Murphy, B. (2018). Access Across America: Auto 2017. Technical Report CTS 18-13, University of Minnesota Center for Transportation Studies. Owen, Andrew, Murphy, B. (2016). Access Across America: Auto 2015. Technical Report CTS 16-07, University of Minnesota Center for Transportation Studies. Ramsey, K. and Bell, A. (2014). The smart location database: A nationwide data resource characterizing the built environment and destination accessibility at the neighborhood scalement and destination accessibility at the neighborhood scale. Cityscape: A Journal of Policy Development and Research, 16(2). Tomer, A., Kneebone, E., Puentes, R., and Berube, A. (2011). Missed opportunity: Transit and jobs in metropolitan america. Technical report, Brookings Institution, http://www.brookings.edu/~/media/research/files/reports/2011/5/12%20jobs%20and% 20transit/0512_jobs_transit.pdf. 222