March Map of the Month

By Grace Parker

Source: Federal Communications Commission

In today’s interconnected world, broadband is not a luxury; it is a necessity. Broadband influences many facets of life, from access to education to employment opportunities and even health. Access to broadband is also critical to monitoring and reducing residential energy use. Many energy technologies, such as smart thermostats and smart meters, require broadband connectivity to function, while most energy assistance programs rely on online applications for aid. Households that have limited access to broadband can find it more difficult to make use of energy efficiency assistance and have fewer tools to monitor and reduce home energy use. 

Drawing on data from the Federal Communications Commission (FCC) this month’s map shows the population in Arkansas without high-speed broadband access. Arkansas has about 251,000 households who lack adequate broadband access. At 14.3% of the state’s households, it’s one of the highest rates in the United States. That number increases to 17.4% when you account for those who have access to broadband infrastructure but do not have a subscription, likely because of affordability challenges. This problem extends across the South, with a 2009 report finding that the South had the lowest rate of broadband use and the greatest urban-rural divide.  

The FCC defines high-speed broadband as 100/20 megabits per second (Mbps), or 100 Mbps of download speed and 20 Mbps of upload speed. The FCC also set a nationwide goal of 1 Gbps/500 Mbps, which is currently only available in urban parts of Arkansas. This map likely underrepresents the population unserved by high-speed broadband since all the residents of a census block are considered served if anyone within it has access.  

The map highlights the difficulty broadband providers face in reaching rural areas, showing how, across the state, there are small, dispersed groups lacking broadband that will require significant investments in infrastructure by providers. Meanwhile, there are larger groups in more populated areas that still lack broadband access, which are more likely to be economical investments for providers. 

The lack of high-speed broadband and the energy efficiency measures it enables contribute to a concentrated disadvantage. Nationally, rural energy burdens are 40% higher than those in urban areas. Since most smart energy-saving devices communicate through the home’s broadband, these households have fewer opportunities to monitor and reduce their energy use. Energy assistance information and applications for programs such as the Weatherization Assistance Program (WAP) and utility offerings are often online, making it more challenging for these households to pursue energy efficiency upgrades. 

The Department of Commerce is investing over $1 billion in Arkansas and $12.8 billion in the Southeast as part of the “Internet for All” initiative, but some stakeholders and experts have expressed skepticism that this will be sufficient for making broadband universal. Electricity-broadband partnerships are one way to make the funding go further. These partnerships are expanding broadband coverage in the Southeast by sharing infrastructure, making it more cost-effective for broadband providers to reach dispersed populations. These partnerships include investor-owned utilities like Entergy and Alabama Power and many electric cooperatives. Electricity access – which is nearly universal in the United States from an infrastructure standpoint – far outpaces that of broadband, in part due to the work of electric cooperatives created to expand service into rural areas. These intersectional partnerships will be crucial to reaching the rural Southeast. 

Map of the Month – February

Laura Diaz-Villaquiran

Hover over the map to click through the slideshow. Click on image to view full image.

  • Redlining and Tree Canopy in Memphis, Tennessee

Data Source: Mapping Inequality: Redlining in New Deal America Dataset;  U.S. Forest Service Tree Canopy Cover (TCC) Dataset; Maps: SEEA.

Few things have impacted cities today as much as the suite of policies and practices that segregated neighborhoods on the basis of race over more than a century. Housing segregation had existed in practice for decades before the 1910s when white policymakers enacted the first racial zoning laws. Although these laws were declared unconstitutional by the United States Supreme Court in 1917, white city officials throughout the South still found ways to advance racial residential segregation.

In the 1920s and 1930s, segregation was taken up by the federal government in the form of “redlining,” the practice of denying financial lending – particularly for home purchases or improvements – to people based on their race or ethnicity and what neighborhood they lived in. For instance, the federal Home Owners’ Loan Corporation (HOLC) developed a series of maps that used the racial makeup of city neighborhoods to guide mortgage lending practices based on their assessment of the risk of lending. HOLC devised a four-tiered system that characterized neighborhoods in more than two hundred cities as A – best, B – still desirable, C – declining, and D – hazardous. These ratings were largely based on the racial makeup of a neighborhood, with C and D ratings typically having a larger share of racial and ethnic minorities than neighborhoods that rated A and B.

HOLC maps had less of an impact on private markets than often suggested, but they guided Federal Housing Administration (FHA) lending decisions for decades. Beyond that, they are also a spatial reflection of generations of policies and programs that segregated American cities, with far-reaching consequences that still shape cities today.

Using tree canopy cover data from the U.S. Forest Service, this month’s map explores the relationship between redlining and urban tree canopy. In three cities (Columbia, Jackson, and Memphis), we find that formerly redlined neighborhoods have about half the level of tree canopy today than historically white neighborhoods.

In Memphis, Tennessee, formerly redlined neighborhoods have an average tree canopy covering 20% of the neighborhood, while neighborhoods rated “A” have canopies that cover about 43% of their land area. In Jackson, Mississippi, formerly redlined neighborhoods had an average tree canopy of 24%, while neighborhoods rated “A” have 50% canopy cover. In Columbia, South Carolina, formerly redlined neighborhoods had 15% tree canopy, compared to 32% for non-redlined neighborhoods.

These findings are consistent with national studies, which demonstrate how the legacies of residential segregation continue to impact people of color. This results in uneven access to public greenspace, less shade from trees, hotter temperatures, and poor air quality which can lead to more heat-related illness and asthma rates. Increased temperatures can place higher energy demands and financial burdens on people living in these areas, which will further strain health and household budgets as extreme heat becomes more common in the next few decades.

These implications underscore the need for comprehensive energy efficiency, clean energy, and urban planning strategies to mitigate adverse impacts. They also show that energy efficiency is an intersectional issue that must be advanced through collaborative efforts across sectors, including energy, public health, urban planning, and development.

Map of the Month – January

Grace Parker

Data Source: EIA Annual Electric Power Industry Report Form EIA-861 Dataset; Graph: SEEA

Accessing household energy data is critical to developing effective and evaluating efficiency programs, deploying energy assistance, and managing home energy use. Yet the accessibility of this data varies widely. One way to explore the accessibility of energy data is through Advanced Metering Infrastructure (AMI), a technology that monitors household energy usage, sends the encrypted data to the utility, and can communicate information back to the customer. A previous technology, Automated Meter Readings (AMR), allowed utilities to access real-time energy usage data but did not allow two-way communication with customers. The potential benefits of AMI include real-time energy adjustments by customers to lower bills, usage and outage notifications, and time-of-use pricing that encourages customers to shift energy use to times with lower energy prices. Because AMI provides granular data on energy usage, it can also be used to target and evaluate programs or policies for maximum impact and customer benefit.

This month’s map shows the percentage of residential energy sales (in MW) in each state that are monitored by AMI, as reported by electric utilities to the Energy Information Administration (EIA). The transparency of the map corresponds to how representative the data reported is of the state’s residential energy sales; states in which utilities report sufficient data for a high percentage of their energy sales appear opaque, while states in which utilities did not appear transparent. Both the percentage of energy tracked by AMI and the completeness of the data reported by utilities vary dramatically. The Southeast overall has a high rate of adoption with six states exceeding 90 percent of energy monitored by AMI, and the Southeast has some of the most complete data in the United States. In areas with low AMI adoption rates, its cost may be a barrier. AMI is more expensive than AMR, so ratepayers would first have to pay for the upgrade before realizing energy savings.

Even in areas that appear to have high adoption of AMI, there may still be barriers to accessing the data. A report by Mission: data national coalition of technology companies that works on energy data access—found that of the more than 17 million advanced meters funded by the American Recovery and Reinvestment Act in 2009, less than 3% have real-time data features enabled.

Some customers may even be unaware that they have AMI. According to the Residential Energy Consumption Survey, only 28% of households in the U.S. reported having an electricity “smart meter” in 2020, despite utilities reporting that about 65% of residential customers had one.

The data used in this map, which is reported unevenly to EIA and only covers around 70% of residential energy sales in the United States, underscores additional barriers to energy and data accessibility. As regulators and researchers continue to address data access issues, they must work with utilities to ensure the full benefits of AMI are realized and to understand the challenges to obtaining and reporting complete, high-quality data.

To this end, SEEA is launching a working group, as part of our Southeast Energy Insecurity Project (SEIP), to explore pathways to build data transparency around energy and housing data so that this data can be leveraged to address energy insecurity through policies and programs. If you, or your organization, are interested in digging into this issue as a member of a SEIP working group, please reach out to Will Bryan, SEEA’s Director of Research, at [email protected].

Map of the Month – December

Grace Parker

Source: Federal Financial Institutions Examination Council, Home Mortgage Disclosure Act Dataset; Graph: SEEA

Following last month’s map that explored home purchase mortgage denial rates by race, this month’s map shows home improvement mortgage denial rates by race in five Southeast cities: Atlanta, Birmingham, Miami, Nashville, and Richmond. Like mortgage loans for home purchases, we found wide disparities between racial groups in their ability to access lending for home improvements. Using data collected by the U.S. Consumer Financial Protection Bureau to ensure compliance with the Home Mortgage Disclosure Act, we discovered that the denial rate for home improvement loans in each city is highest for Black and Hispanic applicants, followed by Asian applicants, with white applicants experiencing the lowest rates. In Birmingham, the denial rate for Black applicants is twice that of white applicants. 

In each of these cities, denial rates for home improvement mortgages are generally higher than those for home purchase mortgages. Home Mortgage Disclosure Act regulations consider home improvement loans as those that are “for the purpose, in whole or in part, of repairing, rehabilitating, remodeling, or improving a dwelling or the real property on which the dwelling is located.” This includes home improvement spending built into mortgages for home purchases or lines of credit opened for home improvement if the home itself is used as collateral on the loan. 

According to the U.S. Census Bureau’s American Housing Survey, about a third of home improvements in the Southeast are for energy efficiency measures. Limited access to capital for home improvement hinders the ability of homeowners, particularly Black, Hispanic, and Asian homeowners, to make energy efficiency upgrades. This further contributes to racial disparities in energy costs and burdens and makes it more difficult for people of color to access healthy, efficient and affordable housing. 

Map of the Month – November

Grace Parker

hover over the map to click through the slideshow

  • Mortgage denials for white households.

Source: Dynamic National Loan-Level Dataset, U.S. Consumer Financial Protection Bureau; Maps: SEEA

Redlining and other forms of housing segregation officially ended in 1968 with the Fair Housing Act, but access to lending still differs depending on a person’s race. People of color are still more likely to be denied access to mortgage lending than white people. Homeownership is the most common pathway to building generational wealth in the United States and limiting access to capital for buying a home not only prevents people from healthy, safe, and affordable housing and inhibits social mobility. 

This month’s map tracks disparities in mortgage lending throughout the Southeast using data collected from federally- backed lenders as part of the Home Mortgage Disclosure Act (HMDA). It shows the mortgage denial rate by race among counties in the Southeast between 2018 and 2022. As housing costs and high- interest rates raised monthly mortgage payments, lenders denied around 12 percent of home purchase mortgage applications in the Southeast. However, the applicants are not denied evenly. Between 2018 and 2022, about 10 percent of non-Hispanic white applicants, 8 percent of Asian applicants, 14 percent of Hispanic applicants, and 21 percent of Black applicants in the Southeast were denied mortgage loans.  

In 2022, the most common reason for mortgage application denials was insufficient income. Income also varies by race. The median non-Hispanic, white household income in 2022 was $81,000; Asian household income was $109,000, Hispanic household income was $63,000, and Black household income was $53,000. Inequities in income, lending, and the ability to build wealth impact a household’s ability to access safe and healthy housing. A lack of mortgage capital also makes it difficult for people to access the benefits energy efficiency, whether through housing choice or home retrofits. Stay tuned for a forthcoming map on lending for home improvements, which will shed light on the ability of households to achieve energy efficiency savings through home improvement capital.  

Map of the Month – October

Grace Parker

Source: Lawrence Berkeley National Laboratory; Map: SEEA

The Inflation Reduction Act (IRA) and other recent federal developments provide unprecedented opportunities to hasten the energy transition through the development of renewable energy resources. Yet this progress is being hindered by the backlog of energy projects waiting in the interconnection queue, a phase in which energy developers request to connect to the power grid and complete studies about the impact of these connections. The number of projects waiting in the nation’s interconnection queue grew by 40 percent in 2022 as more renewable energy projects were greenlit. The amount of time each project spends in the queue is also growing. Projects completed in 2022 spent an average of five years in the queue, compared to less than two years for projects completed in 2008.

These delays threaten project feasibility, potentially undermining the transition to renewable energy.  During waiting periods, project terms, including how much consumers will pay for electricity and the availability and costs of proposed real estate, are likely to change, which leads to projects being abandoned. Less than a quarter of the projects in the queue are expected to be completed.

This month’s map shows the total capacity of energy projects in the queue for each state, and how much of each of this capacity is in renewable energy projects. The data, from Lawrence Berkeley National Laboratory, includes seven independent system operators and 35 utilities, representing about 85% of the U.S. electricity load.

Texas leads the country by far in total capacity in the queue with about 200 GW, followed by California and Arizona, with about 113 GW each. Interconnection queues are managed by regional transmission organizations and utilities, so the total capacity in the queue indicates both interest in building energy projects and the efficiency of queue managers.

The proportion of capacity that is renewable energy is high overall, with only seven states below 80 percent. The relatively large backlog of projects in the queue in other regions might be due in part to the lack of long-distance, high-capacity transmission lines on which renewable energy projects typically depend. Lacking this infrastructure, renewable projects are more challenging to connect to the grid, contributing to long periods in the queue.

The Federal Energy Regulatory Commission issued a rule reforming the interconnection process in July by streamlining permitting, instituting deadlines and fines for delayed assessments, and instituting financial requirements to cut down on speculative projects. But many experts still say that more system reform is needed to meet clean energy goals. While policymakers are working on additional changes to the interconnection process, energy efficiency upgrades are critical for preparing homes and commercial buildings to realize the maximum benefit of renewable energy supplies.

Map of the Month – September

Grace Parker

Source: U.S. EPA, Environmental Justice Screening and Mapping Tool
Map: Southeast Energy Efficiency Alliance
Source: U.S. Census Bureau, Small Area Income and Poverty Estimates
Map: Southeast Energy Efficiency Alliance

The EPA’s Clean School Bus Program aims to reduce greenhouse gas emissions and exposure to air pollution by replacing older school buses with low-emission and zero-emission models. Has that funding reached the communities most impacted by the harmful effects of diesel school buses? Diesel buses produce diesel particulate, which has been linked to an increased risk of asthma and cancer. A part of the Bipartisan Infrastructure Law, the Clean School Bus Program provides funding to school districts to purchase new low-emission and zero-emission buses. This funding supports a global reduction of greenhouse gas emissions, local air quality improvements, and health benefits to nearby communities.

This month’s maps show that the school districts that were awarded program funding in 2023 are generally more rural, have high student poverty rates and lower levels of diesel particulate, especially compared to more urban districts. The EPA prioritizes funding for rural school districts, high-need local education agencies, and schools that serve residents of Native American lands. High-need local education agencies include districts where 20 percent or more of students served are from low-income families. The student poverty map shows that most of the funding went to these districts. The Clean School Bus Program largely supports schools that have smaller budgets and serve students from lower-income communities.

This month’s maps reveal a tension between funding districts that have the most difficulty paying for clean school buses and funding districts with the highest diesel particulate pollution. However, we can target funding to areas that need support to overcome both of these challenges, like New Orleans. Although a district with similar needs in Birmingham received a $3.6 million grant, New Orleans districts did not. School districts seeking cleaner air and better health for their communities need additional outreach and technical assistance to support their funding applications to the Clean School Bus Program. By focusing on districts that face multiple obstacles to their achieving their goals, we can deepen the impact of this historic and critical funding.

Map of the Month – August

Grace Parker

Data: National Renewable Energy Laboratory. “Household Energy and Transportation Burden,” State and Local Planning for Energy and Feeding America. “Map the Meal Gap”, Southeast Energy Efficiency Alliance.

A household’s high energy bills are more than just a heating and cooling problem; they can force low-income households to choose between paying for utilities, groceries or medicine. Studies demonstrate that difficulty covering energy and food costs are often intertwined. Hardship paying energy bills, particularly during extreme heat or cold periods, often makes it more difficult for low-income households to purchase enough food, known as the “heat or eat” dilemma. According to the 2022 Residential Energy Consumption Survey from the U.S. Energy Information Administration (EIA), nearly 7 million households in the Southeast have cut back on food or medicine to pay their energy bills, most likely due to cooling costs rather than heating.

This month’s map compares energy costs with food insecurity in North Carolina, where counties with high energy burdens tend to have higher rates of food insecurity. In these counties, high energy burdens are not the only cause of food insecurity, but the people living here are likely choosing between paying energy bills and buying food.

Rural North Carolina counties have higher than average rates of energy burden and food insecurity. In contrast, metropolitan areas like the Research Triangle, Charlotte, Greensboro, and Asheville have lower rates of energy burden and food insecurity. Counties in northeast North Carolina near Kitty Hawk have the state’s highest energy burden and food insecurity rates. The correlation between places that struggle with high energy costs and food insecurity underlines the importance of energy efficiency and weatherization. These programs help households maintain a comfortable and safe temperature, resulting in lower energy costs and more money for other necessities like food.

Map of the Month – April

Joy Ward and Bianca Acha-Morfaw

Data: 2001-2019 National Land Cover Data (NLCD) from the Multi-Resolution Land Characteristics (MRLC) consortium. Map: Southeast Energy Efficiency Alliance.

This month, our map is influenced by Earth Month, an initiative to raise awareness of global environmental challenges and to increase support for environmental protections and initiatives.

This map highlights the rapid increase of development in one of the fastest growing areas in the U.S., the Raleigh-Cary metropolitan area.

From 2000 to 2020, the population of Raleigh increased over 50%, according to U.S. Census Data. Surrounding towns, Cary and Morrisville experienced population booms of 94,536 to 174,721 and 5,208 to 29,630 respectively. The economic and cultural gains that coincide with an increased population can do wonders for an area but can also have environmental consequences.

A time lapse map of the Raleigh-Cary metropolitan area, using National Land Cover Data (NLCD) from the Multi-Resolution Land Characteristics (MRLC) consortium, contains satellite imagery of forestry and medium to high intensity development in Raleigh from 2001, 2011 and 2019.

From 2001 to 2019 the developed land cover (in tan hues) has replaced forestry (in green), specifically in the Research Triangle located between Raleigh and Durham. The increase of developed land over time aligns with the rise of urbanization and has resulted in an increase of impervious surfaces made of water-resistant materials like asphalt, concrete, brick, stone. Rooftops and compacted soils like sports fields are also impervious.  

As impervious surfaces increase, tree canopy decreases. This leads to the urban heat island effect, when natural land cover is replaced with impervious surfaces that absorb and retain heat, resulting urban areas that are a lot warmer than the rural areas surrounding it. This is particularly a problem for energy efficiency as increased temperatures lead to increased energy costs and extreme heat events.

Tree canopy helps reduce the impact of the urban heat island effect as they provide shade to buildings that reflect heat, can deflect radiation from the sun that provide cooler temperatures to entire communities without expelling additional energy.

Map of the Month – March

Joy Ward and Bianca Acha-Morfaw

Data: Solar Energy Industries Association, 2022 Solar State by State. Map: Southeast Energy Efficiency Alliance.

In honor of Women’s History Month, our March map pays tribute to Mária Telkes, a Hungarian-American scientist whose contributions to the field of solar energy research earned her the nickname “The Sun Queen.” Telkes is best remembered for her invention of the solar distiller, which was included in the military’s emergency medical kits in World War II. The solar distiller was also the first solar-powered heating system designed for residences. Telkes is remembered as one of the world’s foremost solar energy pioneers, with over 20 solar energy-focused patents.

This month’s map shows the percentage of electricity generated from solar by both small-scale and utility-scale facilities across the United States. The map was created using data from the Solar Energy Industries Association (SEIA), a national non-profit trade association that supports the U.S. solar-energy industry.

More solar electricity is generated on the east and west coasts compared to inland states. Indicated with a darker hue, California, Nevada, and Massachusetts, have the highest percentages of solar-generated electricity at 27.32%, 23.32%, and 19.33%, respectively. The highest-ranking southeastern state, North Carolina, generates 8.92% of its electricity from solar. While most states are increasing their use of solar, 40% of states currently generate less than 1% of their electricity using solar panels.

Solar energy is becoming more accessible. In 2022, the U.S. Department of Energy’s Berkeley Lab reported a record increase in utility-scale solar generation. New installations are predicted to triple by 2030 as costs have fallen more than 75 percent since 2010, with utility companies increasing commitments to renewable energy and creating resources to aid residents in their solar installation process. Decreased costs, along with the passage of the Inflation Reduction Act, which contains incentives and tax breaks, should expand the advantages of using solar.

While utilities are helping educate residents on the solar installation process, Solar and Energy Loan Fund (SELF), an affordable financing nonprofit, is providing communities with access to low-cost financing. SELF provides low-interest rate home improvement loans, with a credit-free application process. These loans can be used for solar installations along with other types of sustainable property improvements.

When coupled with other energy efficient designs and technologies, renewable energy can work in tandem to increase affordability and mitigate the impacts of climate change by advancing decarbonization and reducing greenhouse gas emissions.