State of the Lehigh Valley

Transcription

1 State of the Lehigh Valley 2012 Community Trends at a Glance LEHIGH VALLEY RESEARCH CONSORTIUM

2 Table of Contents Letter from the Director... 1 Reference Maps... 2 Economic Growth... 4 Unemployment... 4 Employment and Recovery... 5 Inclusion and Inequality... 9 Median Household Income... 9 Poverty Housing Affordability Post-Secondary Education Plans Government Affairs Political Participation Public Safety Special Focus: Environmental Quality Overview Air Quality Water Quality Recycling Land Use and Environmental Impact of Waste Contributors & Acknowledgements...Inside Back Cover The Lehigh Valley Research Consortium (LVRC) operates within the Lehigh Valley Association of Independent Colleges (LVAIC), a collaboration of Cedar Crest College, DeSales University, Lafayette College, Lehigh University, Moravian College and Muhlenberg College. Lehigh Carbon Community College and Northampton Community College are affiliate members of LVAIC. We are grateful for the continued support and encouragement from our administrators and colleagues at these institutions. We also owe thanks to members of the LVRC Advisory Board for their support of our goals and their expert advice, which has helped to shape our organization and our research. A final note of appreciation goes to organizations and individuals that have provided financial and other support during the last year, in particular PPL, Renew LV, LVAIC, and our LVAIC institutions. The information and views presented in this report do not necessarily reflect those of the trustees, administration, faculty, or staff of LVAIC institutions or our sponsors.

3 State of the Lehigh Valley 2012 Letter from the Director Dear Community Members of the Lehigh Valley, The State of the Lehigh Valley 2012, Community Trends at a Glance examines challenges and changes to our region at a time when we are digging out from the Great Recession and poised for economic recovery but hampered by social, economic, and environmental conditions that hinder a faster recovery. To be sure, there are bright signs of improvement in our region economic development projects are transforming our urban cores while most of our public high school graduates plan to enroll in higher education. However, the recovery has not had a beneficial impact on our poverty and unemployment rates, which remain stubbornly high, nor on our average housing costs, suggesting that some are faring better in this recovery than others. Our special focus section this year explores environmental indicators for the Lehigh Valley and the many factors that influence the quality of our air, water, and land. These indicators underscore connections from the natural environment to our health and vitality as we highlight key areas of concern and future study. In addition to our focus on Lehigh and Northampton counties and their municipalities and school districts, this report examines changes to our region over time as well as state and national measures. For some of the economic and inclusion indicators, we also compare our larger ABE PA-NJ Metropolitan Statistical Area (MSA) to similar MSAs in the northeastern part of the United States as a generalizable peer group. These MSAs were selected because they are similar in size and scope to our metro area. This report is intended to be used as an information resource for residents of the Lehigh Valley, to inform the community of emerging issues, and to provide useful information that enhances informed policy choices. The Lehigh Valley Research Consortium (LVRC) draws upon expert faculty from our six local private higher education institutions and community colleges to examine community issues, disseminate information about the community to its citizens, engage in collective dialogue, and augment the classroom learning of our six local college communities. This collaboration fosters new insights into regional challenges that can enhance our understanding of complex issues and facilitate our search for viable solutions that improve the quality of life of area residents. In our efforts to collaborate across campuses and across the community, we provide research support for our public, private, and non-profit organizations in order to improve our region s prosperity. I invite you to view the complete set of community indicators, reports, and other information about the LVRC on our website Sincerely, Michele Moser Deegan, Ph.D. Director, Lehigh Valley Research Consortium Chair and Associate Professor of Political Science Muhlenberg College LEHIGH VALLEY RESEARCH CONSORTIUM State of the Valley

4 Reference Maps Municipalities in the Lehigh Valley and the Greater Metro Area The Lehigh Valley includes Northampton County and Lehigh County, shown in bold outline in Figure 1. Together with Carbon County and Warren (NJ) County, also shown in Figure 1, they make up the Allentown-Bethlehem-Easton (ABE PA-NJ) Metropolitan Statistical Area (MSA). Municipalities within these four counties are also delineated and colored to represent changes in population from the 2000 to 2010 Censuses. The largest population growth over those ten years occurred in townships around Easton, the southern extent of Lehigh County, and the northern extent of Carbon County. Some areas have seen population decreases, but most areas, cities included, witnessed population growth. Comparable Metro areas Many statistics are collected at the level of the Metropolitan Statistical Area (MSA), some at the county level, and some at both levels of aggregation. Where possible and appropriate in this report, we compare our metro area to other comparable metro areas. MSAs are defined by the U.S. Office of Management and Budget as regions with at least one urbanized area of 50,000 or more population, plus adjacent territory that has a high degree of social and economic integration with the core as measured by commuting ties. The boundaries usually correspond to counties boundaries, except in New England where the town takes on more central importance than the county. Fig. 1: Municipalities in the Lehigh Valley and the Greater Metro Area Nesquehoning Hackettstown Washington Easton Upper Macungie Township Allentown Bethlehem Population Change, % or More Decrease 6% to 10% Decrease 1% to 5% Decrease 1:400,000 ± Miles 0% Change 1% to 5% Increase 6% to 10% Increase 11% to 20% Increase Sources: United States Census Bureau, Lehigh Valley Planning Commission, Pennsylvania Department of Transportation, New Jersey Office of Information Technology 21% or More Increase 2 Lehigh Valley Research Consortium

5 Our region s MSA includes Carbon, Lehigh, and Northampton counties in Pennsylvania and Warren County in New Jersey, as shown in Figure 1. Beginning with the 2011 report, we chose for comparison a peer group of MSAs in the Northeast whose population size is similar to the ABE PA-NJ metro area. This definition produced the sixteen areas shown in Figure 2. Using simple definition of population size allows us to explore dimensions in which the areas are similar to or different from the Lehigh Valley. In some cases we also include indicators for New Jersey, which has many regions that can be considered competitors or complementary to the health of the Lehigh Valley. National and Pennsylvania state averages are also provided for some comparisons. For more information, see and Fig. 2: Comparable Metropolitan Areas Comparison Group MSAs Albany - Schenectady - Troy, NY Bridgeport - Stamford - Norwalk, CT Harrisburg - Carlisle, PA Hartford - West Hartford - East Hartford, CT Lancaster, PA Manchester - Nashua, NH New Haven - Milford, CT Portland - South Portland - Biddeford, ME Poughkeepsie - Newburgh - Middletown, NY Reading, PA Rochester, NY Scranton - Wilkes Barre, PA Springfield, MA Syracuse, NY Worcester, MA York, PA Portland-South Portland-Biddeford, ME Rochester, NY Syracuse, NY Manchester-Nashua, NH Albany-Schenectady-Troy, NY Springfield, MA Worcester, MA Hartford, CT Scranton--Wilkes-Barre, PA Poughkeepsie-Newburgh- Middletown, NY Bridgeport-Stamford- Norwalk, CT New Haven- Milford, CT Allentown-Bethlehem-Easton, PA-NJ Reading, PA Harrisburg-Carlisle, PA Lancaster, PA York-Hanover, PA ± Miles Sources: United States Department of Commerce, United States Census Bureau State of the Valley

6 Economic Growth Unemployment Methodology and meaning: The rate of unemployment is a widely used measure of economic well-being that indicates the interplay between workers ability to find jobs and employers willingness to take on new hires. Through a random sample of 60,000 households each month, the Bureau of Labor Statistics collects data on about 110,000 individuals age 16 and older, asking them if they had a job during the previous week. If so, they are employed; if not, and if during the previous week they looked for a job, they are unemployed. All others are not in the labor force and thus are not part of the calculated unemployment rate. The unemployment rate is not an accurate measure of all dimensions of social distress, particularly during a downturn as significant as the recent recession. Other measures of underemployment capture the increased uncertainty and less-desirable employment that may be available, taking into account definitions of marginally attached and discouraged workers, for example, but such statistics are only available at the state and national level. Thus, we do not report them here. For more details, see How the Government Measures Unemployment. Figure 3 graphs unemployment during the month of September for four years: 2006, before the recession began; 2008, nine months into the 18-month recession; 2010, Fig. 3: Unemployment in Comparable Metropolitan Areas Allentown-Bethlehem-Easton, PA-NJ Harrisburg-Carlisle, PA Portland-South Portland-Biddeford, ME Manchester, NH York-Hanover, PA Albany-Schenectady-Troy, NY Reading, PA Bridgeport-Stamford-Norwalk, CT Poughkeepsie-Newburgh-Middletown, NY Rochester, NY Syracuse, NY Hartford-West Hartford-East Hartford, CT New Haven, CT Worcester, MA-CT Springfield, MA-CT Pennsylvania New Jersey United States average average average average 7.5 averages across all MSAs Unemployment Rate Source: U.S. Bureau of Labor Statistics, Current Population Survey, unemployment rates for September of each year. Data are not seasonally adjusted, to be consistent across the geographic areas. Authors: Christopher Ruebeck and Sabrina Terrizzi shortly after the recession ended; and 2012, about two years into the recovery. Looking first at the general trends in our comparison Metropolitan Statistical Areas (MSAs), it is clear that unemployment is a lagging indicator : it has remained high even as the productive capacity of the economy has improved. This feature of a slow recovery to full employment has become of more concern in the United States during the past two decades. Recent discussions of this slow recovery attempt to discern whether its slowness is due primarily to underlying structural factors (a mismatch between skills and the available jobs) or demand-based reasons (a lack of sufficient need for workers). Countrylevel data are generally found to point to a lack of sufficient demand; we do not have data at the MSA level to answer this question for our region. Unemployment statistics are available at the county level, so we could calculate unemployment for the Lehigh Valley counties (Northampton and Lehigh) alone. To facilitate comparison to other similar regions, we instead include the other two counties (Carbon, PA and Warren, NJ) that make up the ABE PA-NJ statistical area. In Figure 3 s comparison to similarly-sized MSAs in our region and at the state and national level, differing rates of recovery are evident. The dashed lines in the figure are averages taken across the comparison MSAs. Looking first at the data for 2006, we see that the four ABE PA-NJ counties had unemployment equal to that average, and slightly above Pennsylvania as a whole, but below both New Jersey and the country s level of unemployment. These comparisons held true as the recession began (in 2008), but our region s unemployment statistics then worsened more than average, and have since recovered more slowly than either the average of our comparison group, Pennsylvania as a whole, or the national average. New Jersey s unemployment, on the other hand, is worse (on average across the state) than that in any of the comparison MSAs. Comparing across the group of MSAs in Figure 3, those areas with the lowest rates of unemployment before the recession (in 2006) have generally also had lower rates of unemployment during and after the recession in particular for the two comparison MSAs farthest north, in Maine and New Hampshire. The converse is true for those that had higher rates of unemployment before the recession, although the two MSAs that cross the Connecticut-Massachusetts border (Worcester and Springfield) appear to have unemployment rates that are recovering relatively more quickly. Within our comparison group, there is also much greater variation in recent unemployment rates during 2010 and 2012 than prior to the recession and immediately after it began (captured by the data from 2006 and 2008). Thus, different regions may need to craft region-specific strategies as recovery efforts continue. 4 Lehigh Valley Research Consortium

7 Employment and Recovery by Occupational Categories Methodology and meaning: We use the Standard Occupational Classification (SOC) system to assess employment and recovery trends within the Lehigh Valley and comparable geographic areas. The Bureau of Labor Statistics maintains the SOC system, which classifies workers and jobs into occupational categories. To determine how the Lehigh Valley experienced job losses and growth within occupations before and after The Great Recession (which lasted from January 2008 to June 2009), Figures 4 and 5 display employment levels and changes in employment during 2007, 2009, and 2011, both by SOC category and across our comparison group of Metropolitan Statistical Areas (MSAs). There are 23 major categories encompassing all occupations within the United States; we focus on those with the largest percentage of employment opportunities in our MSA. Figures 6, 7, and 8 compare employment changes in Education and Healthcare occupations among our comparison group of MSAs. For more details, see We first consider the total contribution all of the 23 Bureau of Labor Statistics job categories to the ABE PA-NJ area s employment for 2007, 2009, and The length of the bars on the left-side panel of Figure 4 indicate those occupations that are most important to our area. Most jobs are in Office and Administrative support (18%), with Sales (11%) next, closely followed by Food Preparation and Serving (8%), Production (8%), Transportation (8%), Education (7%), and Healthcare Practitioners (7%). These occupations account for just over 65% of the jobs in the area; the ten largest contributing sectors contain over three-quarters of the area s jobs. The right-hand panel of Figure 4 uses a location quotient to compare these occupations share of our MSA s employment to all other MSAs across the country; this is represented with the green bars labeled ABE PA-NJ. The orange bars indicate the average of our comparison MSAs location quotients. The location quotient is a comparative measure calculated as the ratio of an occupation s share of employment in a given area to that occupation s share of employment in the U.S. as a whole. Values greater than one indicate a larger proportion of occupationspecific jobs within a given MSA than in the country overall. Relative to the country as a whole, the bars with location quotients above 1.0 include not only some of the previously mentioned categories with large shares of employment in the area, but also include Healthcare Support (1.18), Community Service (1.09), Installation and Maintenance (1.07), Personal Care (1.06), and Education (1.04). Of the categories mentioned above that have a larger share of jobs in our MSA, both Sales (0.99) and Food Fig. 4: Employment Levels and Comparisons Healthcare Support Production 2007 Healthcare Practitioners and Technical 2009 Transportation and Material Moving 2011 Community and Social Service Office and Administrative Support Installation, Maintenance, and Repair Personal Care and Service Education, Training, and Library Building and Grounds Cleaning and Maintenance Architecture and Engineering Sales and Related Food Preparation and Serving Related Construction and Extraction Business and Financial Operations Management Arts, Design, Entertainment, Sports, and Media Life, Physical, and Social Science Computer and Mathematical Protective Service Legal Farming, Fishing, and Forestry 0 20,000 40,000 60,000 Number of Jobs Location Quotient ABE PA-NJ MSA avg Nat'l Avg 1.0 Source: U.S. Bureau of Labor Statistics, Occupational Employment Statistics. In the right-hand graph, the value of 1.0 indicates the national average across all Metropolitan Statistical Areas. The location quotient for our MSA (green bars) are compared to that national average and to the average location quotients of our comparison MSAs (orange bars). State of the Valley

8 Preparation (0.91) are less represented in our area than they are nationally. The top occupation employment sectors that we have chosen to show in Figure 5 comprise 90% of the employment opportunities within our area, and they are ordered by this market-share percentage shown in the right-hand panel. Figure 5 s left-hand panel shows the growth (or decline) in these employment areas during the recession (2007 to 2009) and during the following recovery (2009 to 2011). The categories that employ a large proportion of our local population shrank or only grew slightly during the recession (red bars) and most have continued to shrink during the recovery (blue bars). Note that these data are only through the end of 2011, as the 2012 data have not yet been reported. We see the strongest total growth over these four years in the two categories of Healthcare Practitioners and Management, as well as in two of the smaller categories: Building and Grounds, and Personal Care. There was somewhat weaker growth in the three categories of Office Support, Education, and Business Operations. The last of those three categories, Business and Financial Operations, saw the largest swing as it both contracted significantly and is now recovering strongly. All other categories shrank over that four year period, with unsurprisingly the largest losses in Construction and Extraction. In the remainder of this section, we consider healthcare and education, two areas that are often described as Fig. 5: Employment Change and Share of Workforce Office and Administrative Support Sales and Related Food Preparation and Serving Related Production Transportation and Material Moving Education, Training, and Library Healthcare Practitioners and Technical Installation, Maintenance, and Repair Business and Financial Operations Management Healthcare Support Construction and Extraction Building and Grounds Cleaning and Maintenance Personal Care and Service % -10% -5% 0% 5% 10% 15% 0% 5% 10% 15% 20% Two-Year Change in Jobs Share of 2011 ABE PA-NJ workforce Source: U.S. Bureau of Labor Statistics, Occupational Employment Statistics. important for the Lehigh Valley economy. When focusing on employment levels shown in the left-hand panel of Figure 4 and the shares of the workforce shown in the right-hand panel of Figure 5, it is apparent that five other occupations employ more workers in the Lehigh Valley than healthcare and education. The Education, Training, and Library Occupations and Healthcare Practitioners and Technical Occupations are the sixth and seventh largest occupation categories, each accounting for approximately 7% of jobs within the area. The Healthcare Support Occupation is eleventh, representing approximately 3.5% of the area s jobs. The importance of healthcare and education to our area can be better understood through the location quotient, shown in the right-hand panel of Figure 4 (in comparison to other ABE PA-NJ employment categories) and of Figures 6, 7, and 8 (shown for each of our comparison MSAs). The top three occupations in which ABE PA-NJ employs a larger than average proportion of the population (see Figure 4 s right-hand panel) include Healthcare Support, Production Operations, and Healthcare Practitioners. As compared to the rest of the country, we employ a larger than average percent of the population in the two healthcare occupation categories. Based on average location quotients across our comparison MSAs, the comparison group employs a slightly smaller fraction of their work force in these occupation categories, but they are also above the national average. Our MSA s location quotient for Education, Training, and Library Occupations is slightly above both the national average and the average of our comparison MSAs. Comparing employment in education across MSAs, Figure 6 s right-hand panel, shows that ten of the comparison metro areas have higher location quotients within the Education, Training, and Library Occupations, with New Haven-Milford, CT having the largest. All similar MSAs in New York and Connecticut, in addition to Reading, have higher location quotients for Education, Training, and Library Occupations than does our area. Figure 6 s left-hand panel also shows that most of our comparison MSAs experienced employment growth in the Education category dur- 6 Lehigh Valley Research Consortium

9 ing the recession, and a slight contraction on average in the recovery that followed. Our area saw only small changes but, interestingly, in the opposite direction compared to the group s average for both time periods. We thus find education to be a relatively smaller component of the workforce in our MSA than in similarly-sized areas in the Northeast, but this employment is also less volatile than in that comparison group. Turning back to the healthcare professions, the location quotients displayed in the right-hand panels of Figures 7 and 8 show that almost all of the MSAs in our comparison group, like the ABE area, are above the national average in employment of both categories of the healthcare workforce. The Healthcare Practitioner category includes the many health diagnosing and treating practitioner fields, as well as technologists and technicians. The jobs in this category (Figure 7) grew on average only marginally more slowly in the recession than during the following two years of expansion. Our area s jobs in this occupation group grew more slowly over the four years shown than did the average of the comparison MSAs. The Health Support category includes occupations such as nursing, occupational therapy, dental and medical assistants, transcriptionists, and pharmacy aides. In this group (Figure 8), most of the comparison MSAs job markets shrank during the recession, as did our area s. During the economic expansion, some had strong growth, but in most cases they experienced weaker Fig. 6: Education, Training, and Library Occupations New Haven-Milford, CT Poughkeepsie-Newburge-Middletown, NY Rochester, NY Syracuse, NY Albany-Schenectady-Troy, NY Springfield, MA Worcester, MA-CT Hartford-West Hartford-East Hartford, CT Bridgeport-Stamford-Norwalk, CT Reading, PA Allentown, Bethlehem, Easton, PA-NJ Portland-South Portland-Biddeford, ME Manchester-Nashua, NH York, PA Harrisburg-Carlisle, PA Lancaster, PA median median % -5% 0% 5% 10% 15% Two-Year Change in Jobs Nat'l Avg Location Quotient Source: U.S. Bureau of Labor Statistics, Occupational Employment Statistics. Fig. 7: Health Practitioners and Technical Occupations Albany-Schenectady-Troy, NY Harrisburg-Carlisle, PA Allentown-Bethlehem-Easton, PA-NJ Bridgeport-Stamford-Norwalk, CT Worcester, MA-CT Portland-South Portland-Biddeford, ME Hartford-West Hartford-East Hartford, CT Poughkeepsie-Newburgh-Middletown, NY Rochester, NY Reading, PA Lancaster, PA York-Hanover, PA Syracuse, NY Springfield, MA-CT New Haven, CT median median 4.6 Manchester, NH -5% 0% 5% 10% 15% Two-Year Change in Jobs Location Quotient Source: U.S. Bureau of Labor Statistics, Occupational Employment Statistics. Nat'l Avg 1.0 State of the Valley

10 growth. Some MSAs like the ABE PA-NJ area continued to contract. Although our area has particularly strong employment in the healthcare sector (its location quotient is relatively high for both occupation groups), job growth is sluggish by comparison (Figure 7) or continuing to shrink (Figure 8). Considering the Education, Training, and Library Occupations along with both healthcare occupation groups, we see a sobering trend. Our metropolitan area s recovery in all three of these important sectors, as measured by job growth, has been below the average of our comparison metropolitan areas. Additionally, our area has experienced negative growth in Healthcare Support Occupations, which has been on a continual decline since The decline in Healthcare Support Occupations may be offset by the increases in Healthcare Practitioners and Technical Occupations, but growth in this area is still not as large as growth seen by comparable MSAs. Fig. 8: Healthcare Support Occupations Portland-South Portland-Biddeford, ME Albany-Schenectady-Troy, NY Springfield, MA York, PA Worcester, MA-CT Allentown, Bethlehem, Easton, PA-NJ Hartford-West Hartford-East Hartford, CT New Haven-Milford, CT Reading, PA Bridgeport-Stamford-Norwalk, CT Lancaster, PA Poughkeepsie-Newburge-Middletown, NY Manchester-Nashua, NH Harrisburg-Carlisle, PA Rochester, NY Syracuse, NY median median % 0% 10% 20% 30% Two-Year Change in Jobs Nat'l Avg Location Quotient Source: U.S. Bureau of Labor Statistics, Occupational Employment Statistics. Data Collection Challenges Economic measures are gathered widely across the country, so there is perhaps less need for improved data here than will be seen in later sections of this report. Nonetheless, it would be helpful to gain a clearer picture of the structure of local conditions with more measures of unemployment at the MSA and county levels. Marginally attached workers, those who have been discouraged and dropped out of the labor force, are counted only at the national and state levels, not at the MSA and county levels. These are unemployment measures that have been particularly important as the slow recovery from the Great Recession continues its return to levels of employment like those we saw before the housing crisis. Longer-term unemployment continues to pose a problem nationally, but we have an incomplete picture of the local recovery. Additionally, accessing county-level data for all of the statistics reported in this section would allow us to make more definitive statements about the two-county Lehigh Valley. 8 Lehigh Valley Research Consortium

11 Inequality and inclusion Median Household Income by Race and Ethnicity Authors: Debra Wetcher-Hendricks and Michele Moser Deegan Methodology and meaning: The physical and social conditions of an area can be affected by its residents incomes. Differences in median household income over time and across social groups, accordingly, can explain differences in quality of life. Further, comparing median household incomes in the Lehigh Valley to similar regions puts our residents recent economic struggles into perspective $60,000 $55,000 $50,000 In the Lehigh Valley, the size of the population classified as lower income $45,000 has grown since 2008, when the economic recession began to affect income levels. Layoffs, salary freezes, and other cost-cutting measures by businesses help $40,000 to explain the recent downward trend in median household income among Lehigh Valley residents. As shown in Figure 9, median household income has decreased in the Lehigh Valley between 2008 and 2011, at a rate greater than that seen in the overall state and nation during the same time period. Even with these decreased income levels, the Lehigh Valley median household income exceeds those of both Pennsylvania and the United States, as it did before the recession began. Should the changes in income remain on their current path, however, the median income in the Lehigh Valley could fall below those of the state and nation. Examination of specific economic conditions in the Lehigh Valley Fig. 9: Median Household Income Lehigh Valley Pennsylvania United States Source: can help identify those populations whose median incomes are falling at a faster rate than others. Additionally, the likelihood that individuals can improve their economic circumstances depends, in part, on their levels of educational attainment. The remainder of this section compares poverty and housing affordability as well as high school seniors post-graduation plans across various segments of the Lehigh Valley population. Several of the analyses use federal standards for measuring poverty and housing affordability to distinguish those who are financially stable from those who are not. State of the Valley

12 Poverty Methodology and meaning: The U.S. Government uses a formula based upon the number of adults and children living in a household to determine the upper threshold of incomes for those considered to be living in poverty. An area s poverty rate serves as an indicator of community stability as well as a predictor of community need. The distribution of funds for public necessities such as education, social services, and community health depend, in part, upon poverty rates. The United States government defines a minimum subsistence level, the amount of income needed to provide basic needs for a household, to evaluate poverty status. This level varies according to the number of people in the household and their ages. An individual who lives in a household with an income below the household s designated minimum subsistence value is in poverty. It is important to understand that households with incomes just above this level also struggle economically, yet do not receive formal governmental recognition of or assistance for their financial distress. Governmental poverty status applies to 11.8% of the Lehigh Valley population. Figure 10 shows how this value compares to poverty levels in comparable metropolitan areas. The Lehigh Valley s place near the center of this range does not paint a dismal picture, but certainly leaves room for improvement. Efforts to reduce poverty levels can begin with the identification of the subgroups most affected. In particular, the possible effects of the recent recession, as generally seen in the declining household income depicted in Figure 9, deserve attention. Figures 11, 12, and 13 display poverty percentages in 2008 and 2011 stratified by sex, race/ethnicity, and age categories for the Lehigh Valley, Pennsylvania, and the US. Fig. 10: 2011 Poverty Percentages in Comparable Metropolitan Areas* Percent in Poverty 20% 15% 10% 5% 0% Bridgeport-Stamford-Norwalk, CT Harrisburg-Carlisle, PA Lancaster, PA Hartford-West Hartford-East Hartford, CT Albany-Schenectady-Troy, NY Portland-South Portland-Biddeford, ME Worcester, MA Allentown-Bethlehem-Easton, PA-NJ Poughkeepsie-Newburgh-Middletown, NY New Haven-Milford, CT Scranton--Wilkes-Barre, PA Rochester, NY Springfield, MA Syracuse, NY Manchester-Nashua, NH Reading, PA York-Hanover, PA Source: Source: Fig. 11: 2008 & 2011 Poverty Percentages by Sex Lehigh Valley Pennsylvania United States 0% 5% 10% 15% 20% Percent in Poverty male female male female national average 12.6% * 2011 data unavailable for Manchester-Nashua, NH, Reading, PA and York, PA 10 Lehigh Valley Research Consortium

13 These graphs identify three Lehigh Valley demographic groups in more need of poverty relief than their counterparts in other areas of both the state and nation. More women in the Lehigh Valley live in poverty compared to men and, while this pattern reflects that seen in Pennsylvania at large and the nation in general, the level of poverty among women in the Lehigh Valley is closer to the higher statewide and national levels than are the rates for men. The aged also face higher poverty: 19.6% of those over age 64 in the Lehigh Valley are in poverty, a rate that is higher than that seen among children or those between the ages of 18 and 64. Neither the state nor the nation has a percentage this high among those over the age of 64. The same situation exists for Hispanics and Latinos as well as for those of multiple races or ethnicities. Their respective poverty rates of 35.5% and 27.1% in the Lehigh Valley exceed the comparable rates statewide and nationwide. Race and ethnicity thus emerge as demographic factors strongly associated with poverty in the Lehigh Valley. It is true that those over age 64 years saw an increase in poverty by 2011, which may be a result of decreased levels of employment of this age group during the recession as businesses focused hiring on younger employees. However, only two racial and ethnic groups, Whites and Asians, have lower poverty rates in the Lehigh Valley compared to both the state and the nation. Poverty rates for all other racial and ethnic groups exceed the corresponding rates in Pennsylvania, the nation, or both. To target those Lehigh Valley residents in poverty, therefore, public assistance, including job training programs and healthcare to support employment, should be directed towards these diverse groups in particular. Percent in Poverty Percent in Poverty Fig. 12: 2008 & 2011 Poverty Percentages by Race/Ethnicity 40% 30% 20% 10% 0% 30% 20% 10% 0% Lehigh Valley Pennsylvania United States White Black Asian Hispanic other more than White Black Asian Hispanic other more than and African and Latino one race/ and African and Latino one race/ American ethnicity American ethnicity Source: Fig. 13: 2008 & 2011 Poverty Percentages by Age Lehigh Valley Pennsylvania United States under over 64 under over Source: State of the Valley

14 Housing Affordability Methodology and meaning: In addition to income, living conditions are identified by the U.S. Census Bureau as an important determinant of well-being. Living conditions address quality of life in a way that income alone cannot. Those who can afford suitable housing have physical, psychological, and social advantages over those who cannot afford suitable housing. Thus, housing affordability helps to indicate the strength of the overall community. Although an analysis of housing affordability among various demographic groups would prove useful for this analysis, the U.S. Census Bureau only provides information about housing affordability with relation to income levels. Measures of housing affordability allow for additional analyses of financial distress. Although the amount of income per household indicates who does and does not fall into poverty, household finances depend on more than just income. Living expenses, most prominently housing costs, severely diminish a household s discretionary income. According to the Department of Housing and Urban Development, housing costs (including rent or mortgage payments, utilities, and other related costs) should consume no more than 30% of household income. The percentage of the Lehigh Valley population with unaffordable housing (that requiring more than 30% of household income) is rather high within the group of comparable metropolitan areas, as shown in Figure 14. The Lehigh Valley s percentage of 38.4% puts it in the top third of the group, meaning that the Lehigh Fig. 14: 2011 Percentages of Unaffordable Housing in Comparable Metropolitan Areas Harrisburg-Carlisle, PA Syracuse, NY Scranton--Wilkes-Barre, PA Albany-Schenectady-Troy, NY York-Hanover, PA Rochester, NY Reading, PA Lancaster, PA Worcester, MA Portland-South Portland-Biddeford, ME Springfield, MA Hartford-West Hartford-East Hartford, CT Allentown-Bethlehem-Easton, PA-NJ Manchester-Nashua, NH New Haven-Milford, CT Poughkeepsie-Newburgh-Middletown, NY Bridgeport-Stamford-Norwalk, CT 0% 12.5% 25% 37.5% 50% Percent of Unaffordable Housing Source: national average 36.7% 12 Lehigh Valley Research Consortium

15 Valley area has less affordable housing than most of the other comparable metropolitan areas. Further, the area has the highest percentage of unaffordable housing among all of the Pennsylvania metropolitan areas examined. As with the issue of poverty, this situation demands consideration of the subpopulations of the Lehigh Valley who must cope with unaffordable housing the most. Data indicate that the percentage of individuals with unaffordable housing consistently decreases as income increases. At opposite extremes are those earning less than $20,000 per year, 86.10% of whom have unaffordable housing, and those earning at least $75,000 per year, 10.26% of whom have unaffordable housing. Although this trend comes as no surprise, it helps to identify the demographic groups most prone to unaffordable housing. The fact that Lehigh Valley residents over the age of 65, Hispanics and Latinos, and those of more than one race or ethnicity have higher poverty rates than others do (as explained in the Poverty section of this report) implies that these individuals are strongly represented in the lower income categories. So the unaffordable housing issues that affect people with low incomes likely affect people in these demographic groups. Programs for low-cost housing can, thus, be directed especially toward these groups. The type of housing unit in which people reside can also help to predict the affordability of housing in the Lehigh Valley. Percentages of income devoted to housing expenses differ for those in rental units, units with mortgages, and units without rental or mortgage payments. Figure 15 shows percentages of unaffordable housing based upon type of housing unit in the Lehigh Valley, along with comparable data on Pennsylvania and the United States. Housing affordability in the Lehigh Valley follows the same trend that it does in the state and the nation. Percentages of unaffordable housing are highest in rental units and lowest in units without mortgage or rent. The comparatively small percentage of those living in units without mortgage or rent who have unaffordable housing reflects the lack of overall housing costs. Most of these individuals have paid their mortgages in full, thus substantially lowering the percentage of their incomes spent on housing costs. The need for housing assistance increases sharply for those still paying mortgages and, especially, for those paying rent. Perhaps more disturbing than this general trend, though, is the percentage of unaffordable housing in the Lehigh Valley compared to national and state percentages. Other areas of Pennsylvania and the U.S. do not have as high a percentage of unaffordable housing as the Lehigh Valley does, regardless of the type of housing unit considered. In addition to adverse effects of the recession in the Lehigh Valley, possible explanations for this situation include the diminishing availability of jobs in industries (for example, steel production) that have historically provided income for Lehigh Valley residents and the increase in housing costs that has accompanied the recent urbanization of the area. Additional research into the Lehigh Valley s comparably high percentage of unaffordable housing could focus upon these issues as well as further investigate whether the demographic groups identified as those with high poverty percentages are also those with greater unaffordable housing costs. Fig. 15: 2011 Housing Affordability by Type of Housing Unit 50% Lehigh Valley Pennsylvania United States Percent with Unaffordable Housing 40% 30% 20% 10% 0% rental units units with mortgage units without mortgage or rent Type of Housing Unit Source: State of the Valley

16 Post-Secondary Education Plans Methodology and meaning: An individual s level of education is linked to employment, health, and overall quality of life. The education level of residents in a region impacts economic development and the mix of jobs available as businesses seek to locate in areas with the mix of skills and education that they need. This, in turn, impacts employment rates and overall regional quality of life. Each spring, the Pennsylvania Department of Education surveys graduating seniors of public schools regarding their plans after graduation. Here we report the responses of high school seniors in 2011 in our 17 public school districts, recognizing that this is a measure of individuals plans, not what may actually occur post-graduation. 50% 40% 30% 20% 10% 0% Fig. 16: Post-secondary Plans of Lehigh Valley High School Graduates Two Four Other Post Blue Military Unknown Other Year Year Secondary Collar Source: PA Department of Education Expected Post Graduation Activity Report Note: For privacy purposes, data by gender and race/ethnicity were only reported when the number of students in each category exceeded 10. If those planning to enroll in college actually complete their degrees and move back to the region, there is an opportunity to increase regional economic vitality; as the education level of our regional population increases, so too should jobs that require college degrees. As shown in Figure 16, in 2011 about 76% of graduating public school seniors in our 17 school districts were collegebound, which is the same as the state overall percentage of college-bound seniors at 76.5%; about equal percentages of students planned to enroll in a 4-year versus a 2-year degree program. Data obtained for our three urban school districts suggest that, overall, a similar percentage of seniors planned to enroll in college than the state average. While in the Allentown School District 67% of high school seniors planned to enroll in college, 82% in the Easton Area School District and 80% in the Bethlehem Area School District planned to enroll. However, in the urban school districts there appears to be a higher percentage of seniors unsure (14%) about their plans post-high school, than the average across all school districts (11%). Looking more closely at the data stratified by gender and race/ethnicity, there are some differences worth noting in seniors plans following graduation from high school. As Figure 17 shows, females were more likely than males to plan to enroll in post-secondary education in 2011 (about 20 percentage points more likely), while more male students than female planned to enter the blue-collar work force (about 10 percentage points more likely) and the military (almost 10 percentage points more likely). Statewide, there is a somewhat smaller difference in female to male percentage of college-bound seniors (little more than 10 percentage points) in These data follow national trends of actual enrollment, as more females are enrolled in post-secondary education in general. The most recent national data from the US National Center for Education Statistics on college enrollment of recent high school graduates (2009) indicate that about 74% of year old females are enrolled in college compared to 66% of males who enroll. Plans to enroll in college depend, in part, on a family s ability to pay for higher education. Higher education costs typically rise faster than the rate of inflation, and in this economy it is becoming increasingly difficult for families to afford college. As shown in Figure 18, of the three largest race/ethnic groups in the Lehigh Valley, African American students were most likely to say that they planned to attend some form of post-secondary school (81%), followed by White Non-Hispanic (77%), and Hispanic students of any race (69%). However, minority students are more likely 14 Lehigh Valley Research Consortium

17 to plan to enroll in two-year colleges, particularly community colleges in Pennsylvania. Over 47% of Hispanic students of any race plan to enroll in two-year colleges. The closest comparison data at the national level is the percentage of students that are enrolled in college by race/ethnicity. Nationally, a higher percentage of White Non-Hispanic students aged are enrolled in college (about 70%), while only 59% of Hispanic students of any race are enrolled. On average in the U.S., the percentage of Hispanic students enrolled in college dropped from 64% to 59% from 2008 to 2009, perhaps signaling the difficulty of affording higher education during the recession, as the percentage for White Non-Hispanic students only dropped by 1%. The data on post-high school plans for Lehigh Valley high school seniors suggest that our region is faring well regarding college enrollment plans, particularly for African American students. It is important to recognize, however, that a larger percentage of students in urban school districts were unsure about their plans following high school. Additionally, students of Hispanic heritage lag behind other ethnic groups in certainty about their post-graduation plans. Given the growing Hispanic population in the entire region, attention should be paid to continuing the trend toward growing the college enrollment of this student population and the interdependent relationships between college unaffordability, low educational attainment, unemployment, and poverty. 50% 40% 30% 20% 10% 0% 60% 50% 40% 30% 20% 10% 0% Fig. 17: Post-secondary Plans Among Lehigh Valley Males & Females Two Four Other Blue Military Unknown Other Two Four Other Blue Military Unknown Other Year Year Post Collar Year Year Post Collar Secondary Secondary males females Fig. 18: Post-secondary Plans by Race/Ethnicity Two Four Other Blue Military Unknown Two Four Blue Unknown Two Four Blue Military Unknown Year Year Post Collar Year Year Collar Year Year Collar Secondary White African American Hispanic Non-Hispanic Non-hispanic of any race Source: PA Department of Education Expected Post-Graduation Activity Report Note: For privacy purposes, data by gender and race/ethnicity were only reported when the number of students in each category exceeded 10. Data Collection Challenges The data used in this section of the report are estimates from the U.S. Census Bureau and Pennsylvania Department of Education (PDE). A number of data points, particularly those referring to poverty percentages in specific municipalities, were unavailable. Further, to maintain confidentiality, the state Pennsylvania Department of Education does not provide raw data for subgroups with fewer than 10 students. Statistics regarding college plans of students in these districts is only reported at the aggregate level, making efforts to address intra-district inequalities difficult due to the possibility that the PDE s data may underrepresent the actual number of students with post-secondary plans. Additionally, the PDE would not release data at the school district level by race/ethnicity or gender because districts outside of the urban areas had many missing values for subgroups. It is important, therefore, to realize that the trends described in this section cannot be used to characterize any particular individual in those municipalities or school districts mentioned. State of the Valley

18 Government Affairs Percentage of Vote Percentage of Vote Voter Turnout 60% 40% 20% 0% 80% 60% 40% 20% 80% 60% 40% 20% 0% Political Participation Methodology and meaning: It is challenging to collect and interpret voter turnout data. Voter turnout can be measured in a variety of different ways. Not every voter votes on every race or issue on the ballot, so counting the total number of votes is more difficult than it may initially appear. In addition, voter turnout is measured relative to a variety of different standards, including the total adult population, the total eligible adult population, and the total registered voters. None of these different measures are any better or worse than the other, but the existence of so many makes it hard to be sure valid comparisons are being made when considering voter turnout statistics. Fig. 19: Percentage of Vote Obama Romney Fig. 20: Pennsylvania Voting by Income Fig. 21: Voter Turnout 2008 and Obama Lehigh Valley Pennsylvania United States Romney 0% under $30k $30-$50k more than more than $50k $100k Lehigh Valley Pennsylvania United States Author: Ziad Munson President Barack Obama s re-election is the most significant political event of 2012 for the Lehigh Valley. As in many previous years, election results in the Lehigh Valley closely mirrored those of the country as a whole. Obama received 52% of the area vote, compared to Romney s 46% a single point difference from the national results in which Obama won 51% and Romney 47% of the vote, broken down by precinct in Figure 22. Exit polls in Pennsylvania suggest that voting was strongly influenced by social class. Overall, 74% of state voters earning less than $30,000 a year reported voting for Obama, while only 45% of those earning more than $100,000 did. This relationship between income and voting was stronger in this election than it was in Such data help dispel myths about red states and blue states common in mass media coverage of presidential elections. In the Lehigh Valley, these data explain much of Obama s strong showing in the more urban precincts in Allentown, Bethlehem, and Easton, and Romney s stronger showing in wealthier suburban areas such as Lower Macungie Township. An important local political development in the last election cycle was the debate over Pennsylvania s new voter ID law requiring all voters to show government-issued photo identification at the polls before being allowed to vote. This law, which enjoys broad public support, was passed by the Republican-controlled state legislature and signed into law by the Republican governor in an attempt to reduce the number of Democratic-leaning votes in the state. As the Pennsylvania Republican House Leader Mike Turzai explained, the voter ID law was going to allow Governor Romney to win the state of Pennsylvania. Did the voter ID law affect the election? Most of the law was blocked by the courts just weeks before the election, but some observers predicted that confusion over the law could still depress voting turnout. Election returns, however, show little evidence that the law had such an impact. Overall voter turnout was indeed lower in 2012 than it was in 2008 in the Lehigh Valley (65% of registered voters in 2012 compared to 67% in 2008), but not in Pennsylvania as a whole. Moreover, many other regions around the country also experienced lower voter turnout, including those areas where new voter ID laws were not an issue. In addition to lower voter turnout, the total number of registered voters in the Lehigh Valley is down since 2008, from 432,549 to 425,289. The difference, however, is too small to draw any definitive conclusions about a trend in voter registration in the area. These figures remain important because they are used by political scientists as measures of civic engagement in the community. Sources: Lehigh County, Northampton County, Pennsylvania Department of State ( United States Elections Project at George Mason University ( The New York Times ( 16 Lehigh Valley Research Consortium

19 Fig. 22: Percentage of Vote for Obama by Precinct in Northampton and Lehigh Counties BANGOR EASTON -- LYNN ALLENTOWN BETHLEHEM ± 0 1:300,000 UPPER MACUNGIE Miles Sources: George Mason University, Pennsylvania Department of State, Lehigh Valley Planning Commission, Lehigh County Office of Information Technology UPPER SAUCON Percent of Vote for Barack Obama 39% and Below 40% to 44% 45% to 49% 50% to 54% 55% to 59% 60% and Above Data Collection Challenges Collecting accurate voting information is perhaps the most important data collection challenge in a democracy, because the results of elections depend on it. Many people are surprised to learn that not every vote is counted correctly in elections. The short video of the Pennsylvania voting machine that changed one person s Obama vote to a Romney vote (available at made national news precisely because it reminded people that not all voting data are collected accurately. Voting machines vary in their reliability and resistance to tampering, and because each county in Pennsylvania determines for itself which voting machines its citizens will use, the likelihood of votes being counted correctly can vary from place to place. Surveys by Muhlenberg College s Public Opinion Institute show that a large majority of Pennsylvanians support the adoption of common voting machines throughout the state, but there has thus far been little political will to enact such a change to how the state tallies votes. Collecting data on voting also faces more mundane challenges. In the Lehigh Valley, Lehigh and Northampton counties report voting results differently, using different systems, and providing different levels of detail. This makes voting data more difficult and expensive to analyze. In addition, we often want to know more than just the vote totals for different candidates; we want to know something about the people who cast votes their age, gender, race, education, and so forth. This kind of data is collected by exit polls, which are voluntary surveys conducted with voters immediately after they have exited a voting station. Because of their cost, however, exit polls are only conducted at a small sample of polling locations nationwide, making it difficult to apply the results to specific places, like the Lehigh Valley. Those who vote via absentee ballot and those who arrive early or late on Election Day may not be included in the results because exit pollsters can t interview absentee voters, may arrive after polls open, and will leave before the polls close. State of the Valley

20 Public Safety Methodology and meaning: We present data supplied by the Northampton County Department of Corrections, represented in two different forms. Daily population counts were aggregated to monthly counts and then again to yearly averages. The jail takes multiple counts during the course of any given day but relies on the same headcount event, in an attempt to provide consistency in data collection. In addition, the data have been represented as a percentage change from one year to the next. The 2010 and 2011 State of the Lehigh Valley reports evaluated crime trends in the Lehigh valley with respect to overall crime, property crime, and violent crime. In doing so, the authors suggested that one way to measure the health of a society is to evaluate crime trends over time. Increasing crime trends suggest that some thought needs to be given to why increases have been witnessed and how best to slow them. Decreasing patterns also warrant consideration in that they may cause one to evaluate whether changes in community responses to criminal behavior have assisted in diminishing perceived problems. Although continued evaluation of crime trends is important, this year the report will focus on incarceration trends in one of the two county jails operating in the Lehigh Valley. Incarceration rates and trends are important to consider when assessing the overall health of any community because high rates of incarceration have been demonstrated to have negative social effects in the communities in which they occur (Austin et al., 2007). Today, 1 in every 34 adults is under some type of correctional supervision (Glaze & Parks, 2012); as a result, some communities may struggle with the breakup of the family, civic disengagement, and Authors: Scott A. Hoke and Nicole Youells racial tension (Austin et al., 2007). With respect to jails in the United States, nearly 12 million people were admitted to these facilities in 2011 (Minton, 2012). By a wide margin, jails are the criminal justice agency with which members of any community are most likely to have some experience or to which they are likely to have some exposure. As a result, it is appropriate to evaluate the trends for this sector of the criminal justice system. Figure 23 compares the change in the average daily population for the nation s jails to that of Northampton County. (Lehigh County data were not included in the analysis because they were not readily available at the time of publication.) The patterns display unusually large increases during specific years in the average daily jail population in Northampton County as compared to both its own trend and that of the national average. Fortunately for Northampton County, however, there was a decrease in the average daily jail population in 5 of the 11 years evaluated. Figure 23 also demonstrates that the size of the jail population in Northampton County is projected to continue to decline in (The data on the national jail population trends for 2012 were not available at the time of publication and therefore are not included.) With an estimated decrease of 9% in 2012, Northampton County s average daily jail population will drop to a level last seen in 2006 (see Figure 24). This means that the jail appears to be recovering from the large increases in population seen in 2006 and This is important from an operational and managerial perspective because the overcrowding experienced during that two-year span ( ) challenges the resources of the county and facility. Change in Average Daily Inmate Population 20% 15% 10% 5% 0% -5% Fig. 23: Percentage Change in Average Daily Jail Populations United States Northampton County Sources: Bureau of Justice Statistics: Jail Inmates at Midyear 2011-Statistical Tables NCJ , Northampton County Prison -10% projected 18 Lehigh Valley Research Consortium

21 The decline in Northampton County should prompt community leaders to examine the reasons for the trend. Typically, reasons for dramatic changes in jail populations, as was witnessed in Northampton County, are difficult to identify without detailed investigation. Because jails house a wide variety of offenders, determining the cause of any change requires a detailed study of societal conditions and enforcement practices. Declining jail populations benefit the community, and the internal or external factors that have influenced these patterns should be identified. Whether it be a stronger emphasis on proactive policing, a greater use of non-incarcerative programs by the courts, or a reduction in recidivism based on increases in jail programming, the potential causes of the declining trends in the Northampton prison population warrant identification. Average Daily Inmate Population Fig. 24: Average Daily Population Northampton County Prison projected Source: Northampton County Prison Resources: Austin, J., Clear, T., Dusler, T., Greenberg, D.F., Irwin, J., Mobley, A., Owen, B., & Page, J. (2007). Unlocking America: Why and how to reduce America s prison population. Washington DC: JFA Institute. Glaze, L.E., & Parks, E. (2012). Correctional populations in the United States, Washington DC: Department of Justice. Minton, T.D. (2012). Jail inmates at midyear 2011 statistical tables. Washington DC: Department of Justice. Pew Center on the States. (2009). One in 31: The long reach of American corrections. Washington DC: The Pew Charitable Trusts. Data Collection Challenges The analysis of criminal justice data, like much of the data collected for this report, has a number of associated challenges, which we present so the reader can understand the complexity of cross-jurisdiction comparisons and to assist authorities in attempts to change the way data are collected and reported both in this region and in the nation as a whole. The biggest challenge associated with the collection of crime data for the purpose of offering a cross-jurisdictional comparison is that such an effort ignores the social and environmental differences that exist between communities. People always want to know how their community compares to other similarly situated communities across a given region or the nation. Such a simple comparison ignores what is known about crime in the United Sates: it is influenced by a number of social and environmental factors that vary across communities. No two communities are the same and comparisons of the type that are often seen in newspaper and media outlets force such a comparison when the only appropriate comparison is within the same community over time. Comparisons between jurisdictions also ignore another common fact about crime, which is that it clusters geographically. Crime is not evenly distributed in any community; it clusters in certain areas. So when someone tries to assess the safety of a city, such as Allentown, the assessment should only be done at the level of small geographic areas. A city as large as Allentown can be expected to have some locations that have higher rates of crime and other areas that have virtually no crime. Thus, designating an entire city as safe or dangerous based on aggregate data is misleading. Knowing that crime clusters geographically also highlights another challenge associated with the collection of crime data. Often, crime data are only reported at an aggregate level. Most police departments and reporting agencies do not report crime for smaller land areas such as census tracts, block groups, or individual blocks. The only way those types of data can be evaluated is if the reporting agency agrees to release them. With an area as large and geographically diverse as the Lehigh Valley, crime trends are best viewed from much smaller aggregate areas than are currently available. Some agencies and municipalities are beginning to see the value in smaller reporting areas and are making such data available. The city of Bethlehem, as an example, maintains a public website that provides access to the exact location of individual crimes. This is a step in the right direction and recognizes the value of data presented in a more user-friendly format. In summary, it is important to remember that cross-jurisdictional comparisons with respect to crime have limited value. The more appropriate evaluation is to compare crime trends over time within the same community. In addition, crime data need to be more accessible at smaller geographic designations. Knowing neighborhood crime trends will provide much more data to community leaders than knowing the trends that exist in the city or community as a whole. State of the Valley

22 Special Focus: Environmental Quality Authors: Breena Holland, Eike Reichardt and Lauren Schneck The Lehigh Valley faces some particular challenges as our region is still failing to meet national air quality standards mandated by the 1990 Federal Clean Air Act. These standards seek to protect citizens from exposure to harmful levels of environmental pollutants in the ambient air. Failing to meet these standards can lead to significant health hazards for those living in, working in, and visiting the Lehigh Valley. Air quality is a particularly difficult problem to address because the natural geography of the Lehigh Valley functions to trap pollutants within the Valley s walls. The area s climate and moisture contribute to the prevalence of many natural allergens that work alongside human-created pollutants to exacerbate respiratory disorders. Like many other valley areas in the country, the Lehigh Valley is non-compliant with Clean Air Act standards for fine particulate pollution, and it has not yet attained the 2008 standards established for safe levels of ground level ozone (or smog). While the number of unhealthy air days for at least one sensitive group (such as children or people with lung disease) shows an overall decline since 2002, the biggest reductions in unhealthy air days for both Lehigh and Northampton counties (Figure 25) have occurred after 2007; that is, after the start of the recent economic recession. Although air quality is a function of many factors other than pollution associated with economic activity (including allergens and the Valley s topography), as the Lehigh Valley evolves in the 21st Century, its leaders will need to find new and innovative ways to reduce a growing population s exposure to vehicular sources of pollution and to meet increasingly stringent health-based The quality of our natural environment has many different impacts on residents of the Lehigh Valley. Features of the environment (or environmental media), such as air, water, and land, are the source of great pleasure and wealth as sites of recreation, aesthetic appreciation, and economic development. These natural systems, however, also can be the site for disposing and dispersing of human-produced pollution and waste. Sustaining environmental quality entails limiting the amount of pollution that natural systems must absorb, so these systems can continue to provide the environmental goods and services that protect and provide for citizens health and quality of life. Balancing opportunities for residential and economic development with the pressures that they put on environmental media is also crucial to the long-term success of our region as a growing metropolitan area. To the extent that regional planners, political leaders, non-profit organizations, and ordinary citizens wish to protect or improve environmental quality in the Lehigh Valley, their decisions must be informed by an understanding of the natural environment s present conditions and of the ways in which new activities and projects may improve or degrade those conditions. In this special focus on environmental quality we take a look at measures of the Lehigh Valley s current conditions in the areas of air quality, water quality, waste generation, recycling, and land use. A review of these indicators reveals some areas in which measures of aggregate adverse environmental impact are relatively low and other domains where significant progress is yet to be achieved. Number of Unhealthy Air Quality Days for at Least One "Sensitive" Group regulatory standards. For instance, black carbon particulate matter poses serious harms to younger and older populations, especially in high traffic areas such as south Bethlehem, where major pedestrian routes through the city are also used by heavy-duty diesel vehicles that emit especially large amounts of black carbon particles. Among the four watersheds extending into the Lehigh Valley, the number of stream miles per watershed with impaired water quality ranges from 7% to 34%. Each of these watersheds extends beyond the borders of the Lehigh Valley and each faces distinct kinds of pollution problems. Among the known sources of surface water pollution in the four watersheds, the problem of abandoned mine drainage poses the most significant threat, with runoff from urban areas, storm sewers, and agriculture also taking a large toll on surface waters. A review of the two most recent national water qual- Fig. 25: Number of Unhealthy Air Days by Year in the Lehigh Valley Source: Airnow.gov, County Comparisons, Number of Unhealthy Days Lehigh County Northampton County Lehigh Valley Research Consortium

23 ity assessments paints an overall picture of increased stress on all but one of these watersheds. In particular, within the Lehigh Valley (as shown below in Figure 34), the Middle Delaware Musconetcong watershed and the Lehigh watershed cover the largest geographical areas. While 22% of the stream miles in the Middle Delaware Musconetcong watershed are impaired, this watershed did not see an increase in the number of water bodies listed as impaired between the two most recent national water quality assessments, in 2004 and In contrast, during this same period, the Lehigh watershed saw the number of impaired water bodies more than double, while the Schuylkill watershed on the northwestern side of the Lehigh Valley saw the number of impaired water bodies increase from 100 to 259. The overall picture of waste and recycling is also one of mixed success. While total generation of waste in both Northampton and Lehigh counties has dropped since peaking in the years of 2005 and 2006, there has been an overall increase in total and per capita waste generation for both counties over the last two decades (Figure 26). Since 1990, Lehigh County has seen a larger increase than Northampton County in total tons of waste generated, but per capita waste generation rates in both counties have dropped significantly since Per capita recycling rates have seen an overall increase since 1990, but the counties have progressed in different ways (Figure 27). In Northampton County, many years with dramatic spikes in recycling rates were due to an unsustained increase in one particular category of recycled goods, such as leaf and yard waste. Lehigh County has seen a more steady increase in recycling rates across a number of categories of recycled goods, but in 2010, its per capita rates were lower than they have been in any year since 1995, showing that per-person recycling rates are on the decline. Tons of Waste Generated Annually Per Person Tons of Materials Recycled Annually Per Person Fig. 26: Lehigh Valley Waste Generation Per Capita by Year Lehigh County Northampton County Source: Pennsylvania Department of Environmental Protection, Bureau of Waste Mangagement, Division of Reporting and Fee Collection, Annual Municipal Waste Disposal Information Fig. 27: Regional Per Capita Recycling Rates By County By Year Lehigh Northampton Schuylkill Bucks Berks Carbon Source for all counties: Pennsylvania Department of Environmental Protection, Reporting and Fee Collection Department of Environmental Protection, Bureau of Waste Management State of the Valley

24 Air Quality Methodology and meaning: Like many highly populated valley areas across the country, the Lehigh Valley is prone to produce temperature inversions that lock polluted air into the lower atmosphere, where people live, work, and play. Increases in population, and therefore in the number of vehicle miles traveled in the Valley, contribute to high levels of certain air pollutants, such as ground level ozone (smog) and fine particulate matter (PM2.5). Currently there is debate about whether there is any safe level of exposure to these pollutants. Older adults, young children, and those who spend significant amounts of time working or playing in high traffic areas are especially vulnerable to respiratory disorders and other health effects of polluted air. Current monitoring of air quality in the Lehigh Valley is insufficient for conveying the threat posed by episodic lung-level exposure to harmful air pollutants and for determining the most effective ways in which citizens can avoid those exposures. Air quality has a significant impact on health and well-being. Poor air quality can create and worsen health problems such as asthma and heart disease, and good air quality can contribute to aesthetic values, such as visibility and the experience of scenic beauty. In the Lehigh Valley, air quality has and will continue to pose a set of important challenges. Although some industrial sources of air pollution such as the Bethlehem Steel Mill no longer contribute to the Valley s air pollution problems, growth in the broader metropolitan region has increased the number of vehicle miles traveled by both residents of and tourists to the Lehigh Valley. Without a widely accessible public transportation system, continued growth in suburban areas and the location of major traffic attractors (such as new malls, stadiums, and casinos) promise to keep air quality at the top of the region s environmental agenda. Here we take a detailed look at trends in ground-level ozone (smog) and fine particulate matter for the Lehigh Valley, both of which are federally regulated air pollutants that currently pose the biggest threats to our area s air quality. In 2009, the Lehigh Valley attained air quality standards for ground level ozone that were issued in 1997; however, our region has yet to meet the 2008 standards for ground-level ozone. The federal Environmental Protection Agency (EPA) has therefore designated the valley as a non-attainment area as of April The extent of our current non-attainment is categorized as marginal, rather than severe or extreme, but there are good reasons to believe that federal standards establishing the allowable amount of ground level ozone will become increasingly stringent over time, creating Average Annual PM2.5 Concentrations (µg/m 3 ) an on-going challenge for emissions-reduction efforts. Ground level ozone is not emitted directly into the air but is created by chemical reactions that occur when nitrogen oxides (NOx) and volatile organic compounds (VOCs) interact with sunlight. In Northampton and Lehigh counties, the majority of VOCs come from mobile sources, such as aircraft, locomotives, and diesel vehicles. An additional 30% comes from solvents used in commercial processes such as degreasing, dry cleaning, and industrial and nonindustrial surface coating. NOx emissions break down differently in these two counties. In Northampton County, the emissions are roughly equal among the following three sources: industrial processes, fuel combustion, and mobile sources. In Lehigh County, about 80% of NOx emissions Fig. 28: Lehigh Valley Average PM2.5 Concentrations Year Source: Pennsylvania Department of Environmental Protection, Ambient Air Monitoring Data Reports, Monthly Parameter Detail Report 22 Lehigh Valley Research Consortium

25 come from mobile sources, with another 15% coming from fuel combustion and industrial processes. Thus, reducing mobile source emissions promises to deliver the largest gains to ground level ozone in Lehigh County. High levels of fine particulate matter (PM2.5) also pose a significant threat to air quality and human health in the Lehigh Valley (Figure 28). This form of pollution is composed of fine microscopic particles in the air, which are often invisible to the naked eye as they measure 2.5 micrometers or less in diameter. These particles are so small they bypass the body s normal air filtration system and enter deep into the chest and lungs, triggering or contributing to serious respiratory problems such as asthma and lung disease. In the Lehigh Valley, the primary sources of PM2.5 pollution are industrial processes, dust, mobile sources, and fuel combustion; fuel combustion and industrial processes produce the largest quantity of particle pollution in Lehigh County and Northampton County, respectively. We will characterize the threat posed by this form of pollution by explaining exposures occurring at increasingly smaller time scales. There are two standards regulating fine particulate pollution one regulating the concentration of PM2.5 over a 24-hour period, and the other regulating the concentration of PM2.5 as an annual average measured over a three-year time period. Although the Lehigh Valley is currently meeting the annual average of allowable PM2.5 in the ambient air, it is important to note that the EPA has just issued more stringent annual standards. Current air quality data suggests that the region will fail to meet these new standards. Specifically, the previous annual standard requires that annual average concentrations of PM2.5 not exceed 15 micrograms per cubic meter of air (µg/m3) averaged over a three-year period. Between 2004 and 2011, the Lehigh Valley recorded annual averages just under this annual standard (Figure 28). However, the EPA has now dropped the annual standard for allowable PM2.5 concentration from 15 µg/m3 to 12 µg/m3; the Lehigh Valley currently fails to meet this revised standard. In contrast to the average annual standard for allowable PM2.5 concentration, the daily standard requires that the average concentration of PM2.5 over a 24-hour period not exceed 35 µg/m3. Because the Lehigh Valley also currently fails to meet the daily standard for PM2.5, this poses an added problem for our area. In June of 2011, for Fig. 29: Lehigh Valley Daily Average PM2.5 Concentrations, June Hour Average PM2.5 Concentrations (µg/m 3 ) Day of Month, June 2011 Source: Pennsylvania Department of Environmental Protection, Ambient Air Monitoring Data Reports, Monthly Parameter Detail Report example, the Lehigh Valley s PM2.5 concentration violated the 24-hour standard several times (Figure 29). Although daily average concentrations have changed little in the Lehigh Valley since 2004, hourly concentrations of PM2.5 vary significantly (Figure 30). Rather than an overall drop in total PM2.5 emissions as a response to more stringent regulatory standards, we find that the Lehigh Valley has displayed a shift from relatively stable hourly emissions to emissions that vary more dramatically by hour. Thus, in recent years there are more spikes in PM2.5 levels, demonstrated by a pattern of peaks and valleys in PM2.5 concentrations. For example, taking one recent 6-month period between June and December of 2011, Figure 30 shows each instance of an excessive spike in the concentration of PM2.5 in the ambient air, defined here as the occurrence of a concentration of 70 µg/m3 of PM2.5 (which is more than double the national daily standard of 35 µg/m3). The spikes in Figure 30 are colored by hour of occurrence in order to demonstrate the prevalence of excessive PM2.5 concentrations recorded overnight, between 9:00 p.m. and 6:00 a.m. (in red). PM2.5 concentrations recorded during this time period account for 83% of all excessive concentrations between June and December of Although there are several excessive PM2.5 concentrations recorded during daytime hours (in blue), the concentrations are not nearly as high as most that occur overnight. The spikes in PM2.5 during the overnight time period suggest that the Valley s high PM2.5 levels do not correspond to traffic patterns, which are presumably lighter during overnight hours. However, as Figure 31 demonstrates, State of the Valley

26 Hourly PM2.5 Concentrations (µg/m 3 ) Hourly PM2.5 Concentrations (µg/m 3 ) during some daytime hours, PM2.5 levels do appear to track rush hour traffic patterns; but these daytime concentrations occur at much lower overall concentrations than the overnight spikes identified in Figure 30. For example, hourly PM2.5 concentrations recorded on June 7, 2011 show PM2.5 levels peaking between 7:00 a.m. and 9:00 a.m. and between 3:00 p.m. and 6:00 p.m. While the 24-hour Fig. 30: Lehigh Valley Time Comparison of Hourly PM2.5 Concentrations Greater Than 70 µg/m 3 0 June July August September October November December 2011 Source: Pennsylvania Department of Environmental Protection, Ambient Air Monitoring Data Reports, Monthly Parameter Detail Report 24 Lehigh Valley Research Consortium 7am - 8pm 9pm - 6am Fig. 31: Lehigh Valley Hourly PM2.5 Concentrations, June :00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 June 7, 2011 Source: Pennsylvania Department of Environmental Protection, Ambient Air Monitoring Data Reports, Monthly Parameter Detail Report average concentration did not exceed the daily standard of 35 µg/m3 for this particular day, the air quality during rush hour periods is certainly poorer than in the immediately preceding and succeeding hours. Looking at local air quality through the lens of federal standards provides some understanding of the broader trends in air quality in the Lehigh Valley. This perspective is limited, however, because federal air quality standards are defined in terms of daily and yearly averages. This compromises our understanding of non-average exposures, such PM 2.5 EPA Standard as those faced by people who spend significant time outdoors in especially polluted areas. Even the hourly PM2.5 concentration dataset is poorly suited to study these types of nonaverage exposure because the data are collected from only one air monitor in the Lehigh Valley, located in Freemansburg. Additionally, because PM2.5 is composed of such small particles, it dissipates quickly into the air. This means that the hourly concentrations in Freemansburg are capturing levels of PM2.5 that are likely to be very different than the exposure levels occurring near the sources of particulate pollution. To assess these more localized and episodic exposures, personal exposure to black carbon particulate concentrations were monitored (Figure 32). Black carbon is a type of particulate matter that usually makes up about 10-20% of the total PM2.5 in the ambient air. Diesel vehicles, such as trucks, buses, and heavy equipment are a primary source of black carbon pollution in the region. Diesel vehicle traffic may be especially high in South Bethlehem, where Highway 378 and Route 412 run directly through highly populated areas of the city. A look at episodic exposure to black carbon on the south side of Bethlehem shows that traffic emissions are indeed a significant source of localized air pollution, posing threats to citizens health. Figure 32 shows black carbon emissions at the Five Points intersection in south Bethlehem, where Highway 378 crosses Broadway Street. Measurements taken in October 2010 during rush-hour traffic at this intersection showed concentrations of black carbon exceeding 1,000 µg/m3. Even if citizens are only exposed to such extreme episodes of black carbon concentrations for short periods of time, these are exceptionally high and potentially dangerous levels.

27 In an effort to develop a more thorough understanding of episodic black carbon exposure, black carbon concentrations were simultaneously recorded along Broughal Middle School students primary and alternative walking routes home from school. In Figure 33, the primary route represents the path a student commonly takes. As these data demonstrate, planning walking routes that avoid high-traffic areas has the potential to significantly lower black carbon exposure levels, which were found to be substantially lower along the alternative route. Black carbon concentration peaks along the primary route corresponded to pollution events occurring at intersections where the student came into contact with cross-traffic and idling vehicles, as well as emissions coming from buses and heavy-duty vehicles travelling along Broadway Street. These black carbon measurements reveal that episodic exposures to particulate pollution can pose a significant threat in highly trafficked areas of the Lehigh Valley. Given our region s high levels of asthma among children and the large population of elderly adults who have retired in the Lehigh Valley, reducing the quantity and/or improving the emissions-capture capabilities of vehicles entering urban areas can do much to avert potential respiratory problems related to particulate pollution exposure. Similarly, encouraging pedestrians to avoid high-traffic areas by making low-traffic routes safe and accessible to those who regularly traverse the city streets on foot can do much to help citizens avoid the worst exposures to black carbon particulate matter. Black Carbon PM2.5 Concentrations (µg/m 3 ) Fig. 32: Bethlehem Black Carbon PM2.5 Concentrations 0 3:00 3:15 3:30 3:45 4:00 4:15 4:30 4:45 5:00 October 22, 2010 Source: Lehigh University, Breena Holland, Undergraduate Air Monitoring Project Fig. 33: Black Carbon PM2.5 Concentrations along Primary & Alternative Walking Routes Home from Broughal Middle School Black Carbon PM2.5 Concentrations (µg/m 3 ) Primary Route Alternative Route 0 2:45 3:00 3:15 3:30 3:45 4:00 Time of Day on October 11, 2011 Source: Lehigh University, Breena Holland, Undergraduate Air Monitoring Project Data Collection Challenges The Lehigh Valley has three air monitors located within its borders that record hourly and/or daily ambient air quality for criteria pollutants regulated under the Federal Clean Air Act. However, each monitor records a different set of pollutants, so comparisons are not possible across all categories for the three sites; instead the distinct pollutant measured at each site is treated as representative for the entire valley. Periodic repairs of monitors require that they be shut down for weeks or months at a time. This can produce significant gaps in the air quality data. The monitoring sites are located in somewhat rural areas in order to record ambient open air conditions. Additional monitoring locations would be necessary in order to evaluate urban exposure in finer detail; however, this presents formidable infrastructure and data management costs. State of the Valley

28 Water Quality Methodology and meaning: While growth in residential and commercial development in the Lehigh Valley has brought many economic advantages, it can have negative consequences for waterways, such as damaging buffer zones that protect the ecological health of streams and mobilizing pollutants otherwise latent in previously damaged soil. Careful planning can minimize damage to waterways resulting from development in the Valley s remaining open space. The Lehigh Valley s industrial legacy poses a more challenging problem when it comes to preventing the mobilization of pollutants found in redeveloping urban areas or otherwise contaminated lands on the urban periphery. The Lehigh Valley s surface waters flow within four distinct watersheds (Figure 34) that all extend beyond the Valley s borders. Each of these watersheds has a number of streams or rivers with pollutant levels that make them unable to support one or more of their designated uses, such as swimming, protecting and propagating aquatic life, or drinking. While most of the particular types of pollutants (e.g. metals, mercury, sedimentation, etc.) impairing these watersheds are known, in some areas the sources of these pollutants remain unknown. For example, although mercury pollutes the most stream miles in the Middle Delaware Musconetcong watershed, the source of the pollution remains unknown for 40% of the watershed s impaired stream miles. Overall levels of impairment vary among the four watersheds extending into the Lehigh Valley. The watersheds that cover both the smallest and the largest amount of area within the Valley have relatively low levels of overall Fig. 34: Lehigh Valley Watersheds impairment. The Middle Delaware Mongaup Broadhead watershed, which covers the smallest area, has the smallest percentage of impaired stream miles. The Lehigh watershed, which covers the largest area, has a percentage of impaired stream miles that is only marginally higher than the Middle Delaware Mongaup Broadhead watershed. In contrast, the Middle Delaware Musconetcong watershed, which also has a significant presence in the Lehigh Valley, has a percentage of impaired stream miles that is approximately three times as high as these other two watersheds. Overall, the Schuylkill watershed has the highest percentage of stream miles impaired; however, this watershed does not cover as much area within the Lehigh Valley as either the Lehigh or Middle Delaware Musconetcong watersheds. The nature of the Schuylkill watershed s impairment also is of less environmental concern because a large portion of its impairment is due to problems of sedimentation and water flow variability rather than to toxic pollutants such as mercury and metals. Among the known sources of surface water pollution in the four watersheds (see Figures 35-38), abandoned mine drainage poses the largest problem, with urban runoff, storm sewers, and agriculture also leading to significant impairment in the two largest watersheds in the Lehigh Valley, the Lehigh and Middle Delaware Musconetcong watersheds. Abandoned mine drainage is a long-term and on-going problem in the Lehigh watershed, accounting for nearly half of the pollution problems leading to impairment. A combination of stressors stemming from urban and sewer runoff, removal of vegetation, and agriculture account for 35% of the impairment within the Middle Delaware Musconetcong watershed and 33% of the impairment within the Lehigh watershed. While abandoned mine drainage results from our state s legacy of past extraction processes, runoff and vegetation removal that mobilize contaminated soils into our surface waters can be reduced by adopting various strategies. These include careful land use planning, adopting natural storm water retention systems, decreasing impervious surfaces, and preventing further pressures on 26 Lehigh Valley Research Consortium

29 Fig. 35: Water Quality & Probable Sources of Quality impairment Lehigh Watershed Fig. 36: Water Quality & Probable Sources of Quality impairment Middle Delaware Mongaup Brodhead Watershed Total Miles Good Quality 92% Total Miles Impaired Quality 8% Abandoned Mine Drainage 46% Agriculture 19% Crop Related Agriculture 7% Municipal Point Source Discharge 2% Other 2% Source Unknown 6% Surface Mining 4% Urban Runoff/Storm Sewers 14% Total Miles Good Quality 93% Total Miles Impaired Quality 7% Construction 2% Hydromodification 2% Municipal Point Source Discharge 3% On Site Wastewater 2% Permitted Small Flow Discharges 3% Road Runoff 4% Source Unknown 77% Urban Runoff/Storm Sewers 7% Fig. 37: Water Quality & Probable Sources of Quality impairment Middle Delaware Musconetcong Watershed Fig. 38: Water Quality & Probable Sources of impairment Schuylkill Watershed Total Miles Good Quality 78% Total Miles Impaired Quality 22% Agriculture 12% Habitat Modification 3% Industrial Point Source Discharge 9% Municipal Point Source Discharge 11% Removal of Vegetation 12% Source Unknown 40% Surface Mining 3% Urban Runoff/Storm Sewers 11% Total Miles Good Quality 66% Total Miles Impaired Quality 34% Abandoned Mine Drainage 8% Agriculture 17% Channelization 9% Habitat Modification 9% Road Runoff 8% Small Residential Runoff 12% Source Unknown 14% Urban Runoff/Storm Sewers 24% Source for all watersheds: United States Environmental Protection Agency, Watershed Assessment, Tracking & Environmental Results, Pennsylvania Assessment Data for 2006, Assessed Waters of Pennsylvania by Watershed combined sewer systems that capture both sanitary and storm water runoff. Likewise, much can be done to improve the adverse impact of agricultural practices on stream and river impairment through the adoption of management practices that minimize agricultural runoff and create appropriate buffers for streams. Data Collection Challenges Due to shared connectivity and hydrologic conditions, data on surface water quality that are required for assessing compliance with the federal Clean Water Act are collected and organized by watershed rather than by municipality. Consider, for example, the impaired river miles within the Lehigh watershed. Since hydrologic systems do not recognize county lines, not all of these miles are necessarily located within the Lehigh Valley. This does not mean that impaired river miles flowing outside of county lines should be of no concern; for example, upstream contamination can easily flow downstream over time, just as downstream pollutants can extend upstream to disturb ecosystem function. However, some impaired stream miles may nonetheless fall outside the Valley s borders. The format of the National Water Quality Report prepared by the EPA has naturally evolved over time as data collection and analysis methods have changed. This makes comparisons over time difficult, and limits our ability to identify trends in surface water quality. The most recent data on surface water quality available for the entire Lehigh Valley is from Comprehensive assessments like the 2006 report are resource-intensive because more than 7,000 river miles had to be sampled in preparation for the 2006 National Water Quality Report on the Lehigh Valley s four watersheds alone. At present, the 2006 data are the most current data available for analysis. State of the Valley

30 Recycling Methodology and Meaning: Recycling can significantly reduce the quantity of waste that our area s land base must contain as well as the demand our citizens place on ecosystems that provide the raw materials that we use for our basic needs and for increasing quality of life. Much additional research is required to understand the various factors shaping trends in individual recycling rates and the sometimes dramatic changes in particular categories of recycled goods seen over time. While per capita recycling rates do show a general trend of increasing over time, total tons of recycled materials remains quite small in comparison to the total tons of materials that enter the Valley s municipal waste stream. Increased recycling as well as reducing and reusing products that enter the municipal waste stream would help reduce the increasing pressure that waste production puts on the Lehigh Valley s natural systems. Per capita recycling rates have varied a great deal in the Lehigh Valley, but the rates show a generally increasing trend since tracking of recycled materials began in the late 1980s (Figure 41). In both Lehigh and Northampton counties, growth in recycling has outpaced growth in population, with Lehigh County reaching a peak of total tons recycled in 2009 and Northampton County reaching a peak of total tons recycled in Even with significant drops in total tons recycled following these peak years, per capita recycling rates have increased by more than 500 pounds per person per year since 1989 in both counties. Between 2007 and 2010, both counties have seen a steady increase in single stream recycling, which allows for recycling of mixed materials (i.e. materials that are not pre-sorted). Although not shown in the figure, we know that the increase in single stream recycling in Northampton County has been somewhat offset by corresponding drops in the total amount of newsprint, commingled materials, and magazines that are recycled as pre-sorted materials. In Lehigh County, by comparison, continued recycling of these pre-sorted materials has held relatively steady. Northampton County per capita recycling rates have been rising steadily (Figure 41), with the exception of years 1998, 2001, and 2004, when there were sharp spikes in per capita recycling rates that were largely due to increases in particular categories of recycled goods (Figure 39). For instance, in 1998 and 2001, the total tons of materials recycled were more than double the amount recycled in both preceding and succeeding years. In these years recycled metals (not including steel cans, aluminum cans, and scrap) represented an especially large percentage of total tons recycled in Northampton County. Specifically, recycled metals made up 72% of total tons recycled in 1998 and 73% in 2001, compared to just 1% in 1997, 2% in 1999, and 3% in The contribution of recycled metals to total tons of recycled materials rose again to more than Total Recycled 100% 75% 50% 25% 0% Total Recycled Fig. 39: Percentage of Recycled Metals and Leaf/Yard Waste in Northampton County (tons) 100% 75% 50% 25% 0% Other Recycled Materials Recycled Leaf and Yard Waste Recycled Metals Source: Pennsylvania Department of Environmental Protection, Bureau of Waste Mangagement, Division of Reporting and Fee Collection, Annual Municipal Waste Disposal Information 40% during 2002 and 2003, but it then dropped to less than 1% of total recycled goods in However, in 2004, per capita recycling rates in Northampton County again spiked due to a large increase in leaf and yard waste. In this year nearly 190,000 tons of materials were recycled, Fig. 40: Shares of Recycled Materials in Lehigh County (tons) Other Recycled Materials Cardboard Used Oil* Metals Leaf/Yard Waste * The recorded numbers of this category of recycled materials did not begin until 2006, but this does not necessarily mean that no oil was recycled prior to that date; e.g. oil may have been recycled but not recorded Source: Pennsylvania Department of Environmental Protection, Bureau of Waste Mangagement, Division of Reporting and Fee Collection, Annual Municipal Waste Disposal Information 28 Lehigh Valley Research Consortium

31 compared to approximately 87,000 tons in 2003 and 97,000 tons in 2005, but leaf and yard waste comprised more than 80% of the total tons of materials recycled. In comparison, this category of waste was only 18% of the total recycled material during the preceding year of 2003, and 63% of total recycled material in In comparison to Northampton County, per capita recycling rates in Lehigh County have been less subject to extreme spikes and falls, with the exception of 2009, when Lehigh County recycled over 160,000 tons of cardboard (Figure 40). In this year, cardboard comprised 61% of the total tons of materials recycled in the county, making the total weight of recycled materials more than double the weight of materials recycled in either 2008 or 2010; in the latter two years, cardboard comprised 28% and 13% of the total tons of recycled materials, respectively. More generally, recycling of both cardboard and leaf and yard waste consistently represents a significant portion of the total tons of recycled materials in Lehigh County. Over the last two decades, just these two kinds of recycled materials have made up between one-third and well over half of the total tons of all materials recycled. Also notable in Lehigh County are occasional spikes in the quantity of specific recycled materials. For example, 40,452 tons of used oil were recycled in 2007 which made up nearly a quarter of the total weight of recycled materials in Lehigh County during that year. A spike also occurred in the amount of recycled metals (not including steel cans and aluminum cans and scrap) in Although these recycled metals comprised only 17% of the total tons Lehigh County recycled during 2003, it is nearly triple the quantity recycled in any preceding year and is between five to nine times as high as the amount of these metals normally recycled on an annual basis. As future research begins to explore the social, economic, and political forces shaping recycling trends in the Lehigh Valley, it is important to contextualize recycling in relation to municipal waste generation, since a primary goal of recycling is to reduce the municipal waste stream. Although per capita recycling rates have generally increased since record keeping began in 1989, the per capita tons of municipal waste generated remains several times the per capita tons of waste recycled (Figure 41). For example, in Lehigh County, with the exception of 2009 (when recycling rates were abnormally high due to the large amount of cardboard recycled, as seen in Figure 40), the per capita tons of waste generated have been between approximately 2 and 12 times as high as the per capita tons of materials re- cycled (Figure 41). Likewise, in Northampton County, with the exception of 1989 (when recycling rates were abnormally low), the per capita tons of waste generated have been between approximately 2 and 15 times as high as the per capita tons of materials recycled. Thus, in both counties, the total tons of municipal waste generated are far more than the total tons of materials recycled. Additionally, while Northampton County experienced three years during which its per capita recycling rates exceeded the more populous Lehigh County s per capita recycling rates, in nearly all years Northampton County had higher per capita municipal waste generation rates and lower per capita recycling rates. In short, Northampton County is producing more waste per person and recycling less compared to Lehigh County. Total Recycled Tons Fig. 41: Per Capita Waste Production and Recycling Rates in the Lehigh Valley (tons) Lehigh Waste Per Capita Northampton Waste Per Capita Lehigh Recycling Per Capita Northampton Recycling Per Capita Source: Pennsylvania Department of Environmental Protection, Reporting and Fee Collection Department of Environmental Protection, Bureau of Waste Management Data Collection Challenges Data collection on recycling only began in As collection techniques improve, single categories of recycled materials are broken down into multiple categories within the data set, making comparisons over time difficult. For example, the recorded categories of recycled metals include aluminum cans and steel cans in The categories expanded to include other metal, aluminum scrap, and drum steel in 2001, and then expanded further to also include mixed metals, brass, copper, nickel, aluminum scrap, ferrous metal, non-ferrous metal, and steel and bimetallic in The opposite occurs when multiple categories of recycled goods are merged. For instance, single stream materials do not require presorting of certain types of products, such as paper, aluminum and plastics; therefore, aggregate totals mask trends in quantities of these formerly distinct recycled materials. The data do show a general trend of increasing recycling rates, but some of this may be due to improved data collection techniques that account for a wider range of recycled materials in the annual reporting. Interviewing recycling facility managers who understand the evolution of data collection techniques and conducting historical research on changes in recycling laws and incentives is necessary for further analysis. State of the Valley

32 Land Use and Environmental Impact of Waste Patterns of land use in our region can be a proxy for measuring economic change. As the share of land for industrial and commercial use increases, the number of jobs tax revenues should also increase. However, increases in residential and commercial properties decrease open space, which is also valued by the community. Here, we present a few indicators of our region s land use for the 464,410 total acres of land in Lehigh and Northampton counties. From 2007 to 2010, land use trends have remained stable. For example, in 2010, 123,245 acres (26.5% of total acreage) in the Lehigh Valley were subject to residential use, an increase of only 0.5 percentage points from 2007 (121,041 acres or 26%). This is the lull in the residential building boom of the late 2000s that was linked to the recession. This slight increase in residential land use was accompanied by a slight decrease in agricultural or vacant land from 2007 (49%) to 2010 (48.4%). Trends in land use for parks and recreation and for public use diverged over this time, with slight increases in parks and recreation land (8.1% in Fig. 42: New Housing Unit Permits Source: LVPC 2012 report 30 Lehigh Valley Research Consortium 2010 and 8% in 2007) and a decrease in land for public use (2.7% in 2010 and 3% in 2007). See Figures 43 and 44. The municipal profile reports provide evidence of differing changes in land use across our region s cities, boroughs, and townships. Some townships and boroughs gained land use for residences, while cities decreased their land for public use and vacancies. For example, residential land use was unchanged in Lower Macungie Township in 2010, remaining at just over 32% of total land use, the same as in 2007 (see Figure 42). During the same period, however, agricultural and vacant land in Lower Macungie Township decreased from 39% in 2007 to 35% in In Alburtis Borough, residential land use continued to increase from 39% to over 40% between 2007 and 2010, compared to 34% in In the Lehigh Valley cities (Allentown, Bethlehem and Easton), the amount of vacant land declined on average over the 2007 to 2010 period (from 14% to 12.6%) as did land for public use (from 11% to 10%). Residential land use increased in these cities over the same period Allentown Lower Macungie Township Upper Saucon Township Lower Saucon Township Easton Bethlehem Alburtis Methodology and meaning: This section uses the Lehigh Valley Planning Commission s 2009 and 2012 municipal profiles reports as well as other data to describe recent land use trends in the Lehigh Valley. The data compare growth rates of select municipalities and also provide a preliminary look at waste generation within the Lehigh Valley, comparing the total tons of waste generated in Lehigh and Northampton counties across several kinds of waste. Some trends in waste production reflect recent changes in land use. However, when contextualized over a longer time period, trends in waste generation reveal the importance of exploring differences in the two counties municipal waste infrastructure and their relative production of industrial wastewater. (from 29% to 34%) and remained constant for commercial use at 37% based on combined land use for commercial and industrial purposes, transportation, communications, and utilities. This situation in land use could affect city tax revenues as the lack of growth in commercial use may mean that property tax revenues from commercial development are not growing as the necessary services for new residents grow. On a positive note, the increase in residential land use can have a beneficial impact on city tax revenues and invites further study. Conversely, our inner ring boroughs and townships such as Lower Macungie have experienced a slight increase in land for residential use (to 32.8%) and commercial/ industrial use (to 6.6%), with a decline of agriculture/vacant land (to 35.7%); however, the growth of commercial use is slightly higher than for residential use. This may be attributed to a trend towards an increasing density of residences in our newer subdivisions.

33 Fig. 43: 2007 Lehigh County Land Use Fig. 44: 2007 Northampton County Land Use 47.8% Agriculture and Vacant 25.7% Residential 8.8% Transportation, Communication, Utilities 8.6% Parks and Recreation 3.0% Industrial 2.9% Public and Quasi-Public 2.5% Commerical 0.7% Wholesale and Warehousing 50.2% Agriculture and Vacant 26.3% Residential 7.8% Transportation, Communication, Utilities 7.8% Parks and Recreation 3.4% Industrial 2.5% Public and Quasi-Public 1.7% Commerical 0.3% Wholesale and Warehousing Source: Lehigh Valley Planning Commission, Municipal Profiles, 2007 Data Collection Challenges Record-keeping for land use data is limited to several broad categories. Finer-grained data could include more detailed usage indicators of public land, the percentages for vacant housing units (habitable & uninhabitable), and vacant lots in need of pollution remediation, as well as the proportions of commercially farmed land vs. overall agricultural land use. As in any major metropolitan region, the production of waste is also a concern, especially in areas undergoing rapid population increases. In the Lehigh Valley, the total volume of municipal waste declined from 2007 to 2010 by 42,503 tons (from 527,133 tons to 484,630 tons), perhaps reflecting a decline in consumption due to the economic recession and the relatively modest growth of only 0.5 percentage points in the Lehigh Valley s residential land use. During this same period, sewage sludge in both Lehigh and Northampton counties also declined by about 15% (Figure 45). Sewage sludge is composed of the solid, semisolid, and liquid residues that are generated during the treatment of domestic sewage and industrial wastewater. Since 2000, the amount of sewage sludge produced by Lehigh County has remained relatively stable, after a significant drop in production that began in 1995; at that time, the amount of sewage sludge generated in Lehigh County was more than 15 times the amount generated in In Northampton County, the amount of sewage sludge generated also declined during the late nineties, but in contrast to Lehigh County, it then rose again, peaking in 2004 and in 2007, after which a more general decline in levels of sewage sludge has been sustained. In comparing the generation of sewage sludge in the Lehigh Valley s two counties, one notable conclusion is Total Tons 60,000 50,000 40,000 30,000 20,000 10,000 Northampton County s consistent generation of more sewage sludge than Lehigh County, despite its smaller population. Specifically, since 1989, in only one year has Lehigh County produced slightly more sewage sludge, Given that Lehigh County is more populous than Northampton County, this suggests that Northampton County either has many more residences connected to the municipal sewer system, or that it Fig. 45: Sewage Sludge Production in the Lehigh Valley Lehigh County Sewage Sludge Northampton County Sewage Sludge Lehigh Valley Sewage Sludge Source: Pennsylvania Department of Environmental Protection, Bureau of Waste Mangagement, Division of Reporting and Fee Collection, Annual Municipal Waste Disposal Information pt?open=514&objid=589667&mode=2 State of the Valley

34 Total Tons Total Tons Fig. 46: Residual, Infectious, and Construction Waste Production in Northampton County 130,000 97,500 65,000 32, ,000 97,500 65,000 32,500 Residual Waste Infectious Waste Construction Waste Fig. 47: Residual, Infectious, and Construction Waste Production in Lehigh County Residual Waste Infectious Waste Construction Waste Source: Pennsylvania Department of Environmental Protection, Bureau of Waste Mangagement, Division of Reporting and Fee Collection, Annual Municipal Waste Disposal Information treats comparatively high levels of industrial wastewater. Northampton County also tends to produce higher levels of residual waste (nonhazardous industrial waste) than Lehigh County (Figures 46 and 47, respectively). For instance, in all but three years since 1989, Northampton County has consistently produced more tons of residual waste than Lehigh County, and in the three years Lehigh County produced more, it did so only marginally. Between 2007 and 2011, as might be expected due to the housing market decline, the production of construction waste in both counties declined; however, the production of residual waste increased in both counties, from 36,133 tons to 55,737 tons, during this same period. The two counties also diverge in their production of infectious waste coming from the successful growth of the health care industry in the Lehigh Valley. While there has been a general trend toward increased production of infectious waste in recent years (from 2,418 tons to 2,952 tons between 2007 and 2011), Lehigh County has again tended to produce lower overall levels of infectious waste since Taken as a whole, Lehigh County s lower level of waste production across these several categories of waste invites further investigation. Given that waste disposal sinks have finite capacity, and that Pennsylvania s ecosystems are under increasing strain from waste generated by the natural gas boom, ongoing efforts to reduce the production of all forms of waste should be a top priority for our region. Data Collection Challenges Pennsylvania s Bureau of Land Recycling and Waste Management generates its annual waste report based on the data provided by counties, Source: NEED SOURCE but data collection may vary among counties, and each county may not monitor all categories. For example, infectious waste numbers are sometimes given as zero, which is a perplexing finding for some of Pennsylvania s larger counties that house major hospitals, such as Lehigh County. However, because a zero is also given to any category of waste that a county does not report, it is possible that Lehigh County simply did not report on this category of infectious waste in particular years, such as 1989 and Data collection for waste occurs at disposal facilities, where both the county of origin is tracked in order to report on county totals and the total disposal is tracked in order to report on facility totals. While this allows for waste disposed within the state to be tracked back to its county of origin, any waste shipped to out-of-state disposal facilities does not get included in the totals. Suppose that all of a county s infectious waste is disposed of out-of-state: the state s annual report would read zero for that category; however, this does not necessarily mean that a county is not generating infectious waste. 32 Lehigh Valley Research Consortium

35 Editors Jamila Bookwala, Ph.D. Professor, Department of Psychology Lafayette College Christopher Ruebeck, Ph.D. Associate Professor, Department of Economics Lafayette College Report Authors Scott Hoke, MPA Assistant Professor Department of Social Sciences Cedar Crest College Breena Holland, Ph.D. Associate Professor, Department of Political Science and the Environmental Initiative Lehigh University Michele Moser Deegan, Ph.D. Director, Lehigh Valley Research Consortium Associate Professor Department of Political Science Muhlenberg College Ziad Munson, Ph.D. Associate Professor, Department of Sociology Lehigh University Eike Reichardt, Ph.D. Assistant Professor, Department of Social Sciences Lehigh Carbon Community College Christopher Ruebeck, Ph.D. Associate Professor, Department of Economics Lafayette College Lauren Schneck, M.A. Graduate of Environmental Policy Design Program, Lehigh University Sabrina Terrizzi, Ph.D. Assistant Professor, Department of Economics Moravian College Debra Wetcher-Hendricks, Ph.D. Associate Professor, Department of Sociology Moravian College Nicole Youells Cedar Crest College Staff Mary Ann Williams, Financial Director Lehigh Valley Association of Independent Colleges Alessandra Bazo Vienrich, Lehigh University Executive Committee Brian Alnutt, Ph.D. Associate Professor, Department of History Northampton Community College Christopher Borick, Ph.D. Professor, Department of Political Science Muhlenberg College Scott Hoke, MPA Assistant Professor Department of Social Sciences Cedar Crest College Jeremy Littau, Ph.D. Assistant Professor, Department of Journalism and Communication Lehigh University Michele Moser Deegan, Ph.D. Director, Lehigh Valley Research Consortium Associate Professor Department of Political Science Muhlenberg College Ziad Munson, Ph.D. Associate Professor Department of Sociology Lehigh University Mae Ann Pasquale, Ph.D. Assistant Professor, Department of Nursing Cedar Crest College Eike Reichardt, Ph.D. Assistant Professor Department of Social Sciences Lehigh Carbon Community College Robert Root, Ph.D. Professor, Department of Mathematics Lafayette College Christopher Ruebeck, Ph.D. Associate Professor, Department of Economics Lafayette College Amy Saborsky, Ph.D. Assistant Professor, Department of Psychology DeSales University Sabrina Terrizzi, Ph.D. Assistant Professor, Department of Economics Moravian College Debra Wetcher-Hendricks, Ph.D. Associate Professor, Department of Sociology Moravian College Diane Dimitroff Executive Director, Lehigh Valley Association of Independent Colleges Advisory Board John Reynolds...Children s Coalition of the LV Alan Jennings...Community Action Committee of the LV Michael Stershic...Discover Lehigh Valley Cynthia Lambert...Good Shepherd Rehabilitation Network Charlene Brennan...Intermediate Unit 20 Robert Keegan...Intermediate Unit 21 Glynis Daniels...Lehigh Carbon Community College Cindy Feinberg...Lehigh County Randall Forte...LV Arts Council Michelle Young...LV Chamber of Commerce Jarrett Witt...LV Economic Development Corporation Geoff Reese...LV Planning Commission Robert Wendt...LV Workforce Investment Board Diane Elliott...New Bethany Ministries Jeffrey Focht...Northampton Community College Ross Marcus...Northampton County Donald Bernhard...PPL Rachel Bradshaw...Renew Lehigh Valley Bonnie Coyle...St. Luke s Hospital and Health Network Cori Rolon...United Way GLV Christopher Kocher...Wildlands Conservancy Design & Charts: Jeanne Stock & Barbara Field, Jeanne Stock Design Maps: John Wilson, MS, & Andrew O Brien, Lafayette College Photography: Cover: (clockwise from top left) Easton (Ang Caggiano), Allentown arena site (Morning Call), Church & New St.(Ang Caggiano), Lynn Twp. (Nicholas Tonelli). Inside Front Cover: (top to bottom) ArtsQuest at SteelStacks (Ang Caggiano), Weisenberg Twp. (Nicholas Tonelli), ArtsPark2 (Alan Salinger). Page 5: (clockwise from top) Lehigh Valley Mall (Ang Caggiano), Allentown Fairgrounds Farmers Market (Buy Fresh Buy Local), C.F. Martin (Discover Lehigh Valley). Page 9: Lehigh University Farmers Market (Community Action Development Corporation Bethlehem). Page 12: N. 7th Street Easton (Ang Caggiano). Page 14: Lafayette College Arts Plaza (Spillman Farmer Architects Halkin Photography). Page 20: Blue Mtn and farm in Northampton Twp (Kyle Miller). Page 22: Bethlehem (LVEDC). Page 26: Lehigh River Slatington near NorCo line (Nicholas Tonelli). Page 30: Banana Factory, Bethlehem (Community Action Development Corporation). Inside Back Cover: Coca-Cola Park baseball diamond (LVEDC), South Bethlehem (Discover Lehigh Valley) downtown Easton (Ang Caggiano) LEHIGH VALLEY RESEARCH CONSORTIUM