Operation Healthy Air— Southern California A Community Science Field Study Operation Healthy Air—Southern California A Community Science Field Study 2019

Earthwatch Institute is a -based international nonprofit organization that connects citizens with scientists to improve the health and of the planet. Since its founding in 1971, Earthwatch has empowered more than 100,000 volunteers from all walks of life to join leading scientists on field research expeditions that tackle critical environmental challenges around the globe—from climate change to ocean health to human-wildlife conflict. In 2018 alone Earthwatch sent over 1,700 volunteers into the field, who contributed over 98,000 hours of research, resulting in 33 peer reviewed publications. contact info Mark Chandler Director of Research Initiatives 1380 Soldiers Field Road [email protected] Suite 2700 Tel: 1-978-844-0884 Boston, MA 02135 facebook.com/earthwatch earthwatch.org twitter.com/earthwatch_org Contents 1 | Summary 2 2 | The OHA Program Overview 4 2.1 | Problem Statement and Context 3 3 | Study Design 5 3.1 | Objectives 6 3.2 | Selection of Study Regions 6 3.3 | Study Data Parameters 8 3.4 | OHA Project Partners 9 3.4.1 | Participants 9 3.4.2 | Socio-demographics of participants 10 3.4.3 | Participation by educational institutions 11 3.4.4 | Trainings 12 4 | Habitat Mapping 10 4.1 | Differences across cities in amount of green habitat, trees and pavement 13 5 | Air Temperature 16 5.1 | Home Temperature and Human Comfort 20 5.1.1 | How do people sense increasing temperature? 22 5.1.2 | At what temperatures are participants most comfortable? 23 5.1.3 | How do communities differ from one another in managing 24 indoor temperature? 5.2 | Community iButton Temperature Sensors 25 5.2.1 | iButton temperature results 26 5.3 | Exploring the air temperature data yourself! 27 6 | Ozone 31 6.1 | Explore ozone data using interactive viewer 34 6.2 | How does ozone vary across Southern California 34 6.3 | How does ozone vary with wind speed and direction? 35 6.4 | Ozone and Temperature 36 7 | Actions 38

OPERATION HEALTHY AIR FIELD STUDY | 1 1 | Summary Poor air quality and extreme heat are ubiquitous issues in cities globally impacting human health and well-being for hundreds of millions of people worldwide. Climate change will exacerbate the effects of pollution by increasing temperature extremes presenting severe health risks for those most vulnerable in society (e.g. those with respiratory illnesses such as asthma, the young and the elderly). Understanding where the impacts of air pollution and extreme heat are worse will help direct how cities adapt to the effects of heat and pollution.

A team of community members, scientists and local organizations came together in 2017 to assess how local air temperature and ozone changes from yard to yard, and from neighborhood to neighborhood in Southern California to help inform how best to adapt to dangerous levels of pollution and severe heat. The program called Operation Healthy Air (OHA) engaged over 1,000 community members who contributed their time, energy and insights to collect data at over 230 sites. We have started to analyze the data and are presenting some preliminary results in this report.

Using home temperature sensors we have been able to better understand the temperatures at which people become uncomfortable (~ 82°F), after which discomfort increases rapidly up to 92°F after which most people are universally uncomfortable. The temperature range can help set targets for managing home temperatures as well as outdoor activities. While many people kept their indoor temperature around 75–77 degrees using various control measures (e.g. air conditioning, passive cooling), indoor temperature at several homes were close to the start of the discomfort threshold. Often these homes were associated with lower income neighborhoods.

Our analysis of air temperature using the iButton sensors found that tree size does matter in helping to cool local air—even significantly—but only during the day time. At night, the amount of pavement—especially asphalt (i.e. roads)— influences night time temperature. Surprisingly, streets are slightly cooler during the day time than front or back yards perhaps because cooler air from the sea can more easily penetrate streets during the afternoons when winds pick up.

We found ozone levels to vary a lot from neighborhood to neighborhood—and was often driven by air temperature and wind direction. This will help design better monitoring programs as well as which activities are most appropriate for those who suffer from cardio and respiratory problems which ozone can exacerbate. While we did observe some high ozone levels during the 5 week periods of the study—the time frame was not long enough to make specific recommendations to those where the ozone sensors were located.

Overall, the OHA partnership including Earthwatch Institute, academic research institutions (e.g. University of California Riverside, University of Iowa), local partners (e.g. Aquarium of the Pacific, Chino Basin Water Conservation District, Riverside Country Resource Conservation District among others), managed to collect enough data to keep our science partners busy for years to come—and we expect several publications to come out over the next couple years. We have posted the data on air temperature and ozone for any to view and use as you see fit. Please visit the University of Iowa site to see and access the data http://esmc.uiowa.edu:3838/iButtons_data_working/.

We would like to thank the hundreds of community scientists who contributed their time and ideas, as well as the dozens of partners who made OHA possible—including Chino Basin Water Conservation District, Aquarium of the Pacific, Riverside Corona Resource Conservation District and Masters Gardeners. The study was funded by an NASA Earth Observation grant among others.

2 | OPERATION HEALTHY AIR FIELD STUDY 2 | The OHA Program Overview Operation Healthy Air (OHA) is a community science program that enlisted community members to assess fluctuations in ozone and air temperature around their homes and test whether local landscaping influences the well-being of their community. OHA launched its pilot program during 2017 in residential communities in the Long Beach and the Inland Empire regions of Southern California, specifically in Long Beach, Claremont, Ontario, Riverside and San Bernardino.

OHA was developed as a partnership including a community science organization (Earthwatch Institute), academic research institutions (e.g. University of California Riverside, University of Iowa), local partners (e.g. Aquarium of the Pacific, Chino Basin Water Conservation District, Riverside Country Resource Conservation District among others), and community scientists. OHA was supported by grants from NASA and other donors, and the generosity of over 1,000 community members who contributed their time, energy and insights.

2.1 | PROBLEM STATEMENT AND CONTEXT Everyone benefits from healthy air quality. Unfortunately in urban areas, poor air quality is a ubiquitous issue posing great threats to human health. Air pollutants, such as particulates and ozone are some of the greatest culprits. Poor air quality is exacerbated by extreme heat days (i.e., days above 105°), which are increasingly common in urban areas due to climate change. Extreme heat days and exposure to air pollutants present severe health risks especially to those most vulnerable in society including those with respiratory illnesses such as asthma, the young and the elderly.

Green spaces (i.e. trees, shrubbery, yards and parks) provide many benefits and services to human health. This includes cooling ambient temperature and improving our cognitive and emotional well-being. However, the availability and accessibility to green spaces and their benefits depend on one’s socioeconomic status due to the “luxury effect”— where wealthier neighborhoods include more green space than poorer areas. The same holds true for air quality and extreme heat in cities. Affluent communities experience health issues related to air quality far less than poorer communities. This is particularly true in southern California which frequently fails to attain minimum air quality standards set by US EPA. The widely disproportionate effects of poor air quality on environmental justice communities has recently been demonstrated (Tessum et al, 2019 PNAS 2019). For instance, the latter inhabit areas near highways at a much higher rate; meaning people (often Hispanic and African-American communities) in poor neighborhoods breathe more hazardous particles (including vanadium, nitrates, and zinc), putting them at higher risk of experiencing respiratory illnesses. Stress and economic conditions can further exacerbate the effects of pollution.

Climate change is predicted to exacerbate health challenges in cities, especially the conditions that impact poor communities most. Generally, attention and funding are drawn to the catastrophic events associated with climate change, such as coastal storms and areas with high risk for financial losses. However, urban and heavily developed suburban communities are subjected on a daily basis to the effects of climate change in the form of high temperatures which when combined with reduced air quality promote chronic health problems.

Vulnerable populations are typically most impacted by climate change because they often live in areas of environmental degradation. Moreover, these communities do not receive the same level of attention, and, the support for climate change vulnerability assessment and adaptation often do not meet their needs. In these communities, individuals and families may not have sufficient time outside work and family to voice their concerns and advocate for increased investment in climate change issues.

Policies including monitoring and enforcement of emission standards have helped improve air quality nationally resulting in improved health for many. Yet significant numbers, and especially those most vulnerable, remain impacted by unhealthy living conditions—notably in areas such as southern California where repeated non-attainment of air quality standards is common. More targeted interventions that can identify specific pollution or “stress” hotspots and solutions are now needed requiring more refined monitoring and mitigation programs.

OPERATION HEALTHY AIR FIELD STUDY | 3 3 | Study Design To better understand the conditions in urban/suburban communities living with intense heat days and overall increased temperatures, a partnership of organizations (e.g. Earthwatch, University of California Riverside, University of Iowa and other local partners) developed and implemented OHA as a pilot project focused on climate-related air quality vulnerabilities. This pilot project was heavily focused on engaging community members in thinking about current and future climate-related air quality vulnerabilities, and how community members can work with scientists to understand community concerns, address vulnerabilities and develop specific actions to support the community. As depicted in Figure 1, the OHA study was undertaken to collect focused data, which together with input and participation from the community would lead to actionable results.

FIGURE 1A: OHA Study Approach

FIGURE 1B: Operation Healthy Air project design conceptual design

4 | OPERATION HEALTHY AIR FIELD STUDY 3.1 | OBJECTIVES The study was designed to collect data to help OHA OHA Study Data Parameters research partners to understand critical conditions • Air Temperature increases associated with in communities vulnerable to increasingly hot weather climate change can result in increased rates of resulting from global warming. In addition to adding death and disease to our understanding of these conditions, the study • Ozone is an urban air pollutant with significant is also focused on developing actions that individuals can health effects that may increase with higher take on a personal level to become more resilient temperatures to changing climate. • Vegetated Habitat has an overall cooling effect by The study objectives include: reducing “urban heat island” effects and moderating high heat conditions • Collect temperature, ozone, and vegetative cover/habitat data from urban/suburban residential areas to better understand the extent to which these vary from neighborhood to neighborhood, from yard to yard where people are living, and how temperature and ozone concentrations varied across these habitats • Collect data on the comfort levels of individuals residing at these locations • Involve and train community members to collect this data • Collect socioeconomic survey data of individuals across the communities to understand their experience under changing climatic conditions • Evaluate the data set to better understand how the socio-economic groups in the study area differ in their interests and motivations concerning local climate and pollution.

In addition to these community-based goals, the data were also collected to provide ground-truthing for NASA’s satellite-based data collection systems. NASA is currently updating their imaging systems and sensors and increased understanding of the scale of local variation in air quality and ozone will inform the design of future instruments and data gathering efforts. The community-based data can be used to evaluate small-scale variability in micro- environments across landscapes, which may not be fully detected by satellites.

OPERATION HEALTHY AIR FIELD STUDY | 5 3.2 | SELECTION OF STUDY REGIONS Two regions in southern California, Long Beach and Inland Empire, were selected for this study (Figure 2). These areas are listed by the US Agency (US EPA) for poor air quality and high levels of toxins, and they are experiencing rapidly increasing extreme heat days (see Figure 3). These conditions result in higher current occurrences and future vulnerability to serious heat and air quality-induced health issues. The communities are demographically diverse, with significant low socioeconomic and immigrant populations.

FIGURE 2: Operation Healthy Air Study Regions and Field Data Collection

Data were collected from six study areas within two regions—the Long Beach Region and the Inland Empire Region. The six study areas were 4km2 to match the size of NASA’s satellite data pixel areas

FIGURE 3: Projected increase in extreme heat days due to climate change in study region

Study Regions represent urban residential areas with increasing numbers of extreme heat days and high levels of air pollution.

200

Average number of days between 1981 and 2000

Number of days by 2050

Number of days by 2100 150

100

50

0 Palm Springs Riverside San Gabriel Los Angeles Long Beach San Gabriel Santa Monica Valley Mountains

6 | OPERATION HEALTHY AIR FIELD STUDY 3.3 | STUDY DATA PARAMETERS Data is needed to evaluate the health effects of OHA data collection was focused on better understanding climate change on vulnerable urban residential heat and air quality conditions within urban residential areas communities. Community Scientists collected the data from their houses, yards and neighborhoods. • Urban and heavily developed suburban communities are subjected on a daily basis to the AIR TEMPERATURE was selected as the key study effects of climate change in the form of high parameter because it is directly associated with climate temperatures and poor air quality that promote change and negative human health effects, and it chronic health conditions. supports formation of the air contaminant ozone in urban areas. Temperature was measured directly using automatic sensors (e.g. iButtons and home thermometer monitoring devices). Temperature was also evaluated in terms of individuals’ self-described comfort levels as an indicator of potential physiological stress. Air humidity, which affects comfort level and respiratory health was also measured.

OZONE was selected as a study parameter because it is closely linked to temperature and is a significant health threat. Ozone is formed within a specific range of relatively high air temperature and air contaminant concentrations. Ozone is a significant health hazard that is expected to become increasingly problematic as global warming progresses, and is of particular concern in urban areas. Ozone data was collected to evaluate potential trends with temperature variations across urban residential areas.

HABITAT MAPPING data was collected as a description of land cover type. Land cover­­—whether impervious hard surfaces such as concrete or asphalt, or previous surfaces with vegetation—has significant effects on local air temperature and wind patterns. Vegetation has a cooling effect in terms of shade and can also act as a buffer to wide air temperature fluctuations. Hard, dark ground surfaces promote urban heat islands that store heat.

Activities that community scientists helped with

OPERATION HEALTHY AIR FIELD STUDY | 7 3.4 | OHA PROJECT PARTNERS

3.4.1 | Participants This OHA Project involved a variety of community stakeholders: local organizations, schools, governmental agencies, and residents. Overall, 200 community members and 750 students from Long Beach, Claremont, Ontario, San Bernardino, and Riverside cumulatively deployed over 250 temperature sensors and 18 ozone sensors. In addition, 150+ habitat maps were created with the help of more than 100 community members who collected vegetation cover information.

Participants were recruited from members of partner organizations, general outreach using social media (e.g. Facebook) and newspaper stories.

Partner Organizations

3.4.2 | Socio-demographics of participants The social and economic diversity of participants is represented in Table 1. In the table we differentiate averages for the city as a whole compared to those specific neighborhoods (i.e. census blocks) where the OHA participants lived. The California Environmental Screen score (https://oehha.ca.gov/calenviroscreen/report/calenviroscreen-30) represents a composite index that integrates 20 different indicators that together represent the degree to which people living in that “block” are thought to be vulnerable to an unhealthy environment. It includes both elements of exposure to threats such as pollutants and the capacity of a population to withstand unhealthy conditions. For example, wealth is considered a measure of the capacity.

The higher the score, the more vulnerable a community is to unhealthy conditions. Lower scores represent populations that are less likely to be vulnerable. In our study area, the city of Claremont had the highest proportion of whites (51.7%), the highest median income ($42.861) and the lowest Cal Enviro Score (CES percentile score 49.49). In contrast, Ontario and San Bernardino were the least wealthy (median incomes of $ 21,069 and $ 16.025 respectively), had the least percentage of whites (15.5% and 13.2%) and had the highest CES scores (i.e. most vulnerable). Looking at the specific neighborhoods where OHA participants live, we can see that OHA participants tended to come from much more white neighborhoods (i.e. census blocks) and wealthier neighborhoods. This difference was less apparent for CalEviroScreen scores where differences between the cities became more apparent.

In summary, OHA was located across a range of cities with differing socio-demographics—including some of the most diverse, least wealthy and most vulnerable in California. The actual participants in OHA tended to be from specific neighborhoods within those cities that were more white and wealthier than average. The neighborhoods studied though had similar CalEnviroScreen scores suggesting at least that the project findings are representative of the environmental vulnerability within those cities. These findings are consistent with other studies that find that poor (and often racially diverse) neighborhoods participate much less frequently in community science projects.

8 | OPERATION HEALTHY AIR FIELD STUDY TABLE 1: The socio-economics of participants in Operation Healthy Air. Data for Operation Healthy Air participants was derived from their census block data 2010.

Cal Enviro Score1 Race Median Income mean percentile % white Average Median earnings City OHA project City OHA project City OHA project City Claremont 56.2 49.49 65.80% 51.70% $35,751 $42,861 Long Beach 46.38 66.81 63.00% 26.10% $39,548 $29,096 Ontario 81.57 86.77 53.00% 15.50% $29,871 $21,069 Riverside 76.1 73.1 74.70% 33.00% $29,089 $24,152 San Bernardino 86.36 83.13 68.20% 13.20% $21,512 $16,025 Outside 49.75 55.10% $42,673 1. 1.California Environmental Screen Score : https://oehha.ca.gov/calenviroscreen/report/calenviroscreen-30

3.4.3 | Participation by educational institutions Participation of schools was extremely important as it provided data coverage throughout the study regions and a learning experience students and faculty. Some of the OHA school partners are listed in Table 2

TABLE 2: School District Participation—Students, Teachers and Administrators

Actively Involved in OHA Teachers/ Students Potentially Name of school School District Activities Administrators Students Impacted by OHA Norton Elementary San Bernardino Ozone City Unified 6 207 531 School District Juanita Jones Elementary San Bernardino Temp-iButton City Unified 1 Not known yet 430 School District Richardson Prep High San Bernardino Temp-iButton City Unified 2 Not known yet 617 School District Arroyo Elementary Ontario- Temp-iButton Montclair 3 80 393 School District Vineyard STEM Academy Ontario- Temp-iButton Montclair 2 164 761 School District Wiltsey Middle School Ontario- Temp-iButton Montclair 3 200 1063 School District Chaffey High School Chaffey Joint Temp-iButton Union High 1 15 3482 School District Webb School Claremont Temp-iButton 1 10 20 St. Anthony’s Catholic School Long Beach Habitat Mapping 1 50 60 CSU Los Angeles Los Angeles Temp-iButton 1 20 20 Hope International University Fullerton Temp-iButton 1 7 7 CSU Long Beach Long Beach Habitat-Mapping 1 2 2 Claremont McKenna College Claremont Habitat Mapping 1 4 4 Totals 24 759 7390

OPERATION HEALTHY AIR FIELD STUDY | 9 3.4.4 | Trainings Participants had the option of attending one of multiple trainings conducted by representatives from partner organizations, including Earthwatch and project scientists. These were held at partner organization locations. A list of training programs can be found on the Earthwatch Urban Resiliency project website http://earthwatch. urbanresiliency.org/training-materials/.

4 | Habitat Mapping The Urban Heat Island effect is a well-known phenomenon that affects most of the world’s FIGURE 4: The Benefits of Trees cities. When cities replace vegetation (which reflects and/or absorbs little solar heat) with pavement and other heat absorbing surfaces, cities become 3° to 7°F warmer as the new “dark” surfaces re-radiate the sun’s energy. Cities are now embarking on major re-greening efforts to redress the historic loss of nature in cities—with increased numbers of trees seen as providing many benefits (see Figure 4). However, it remains unclear how much residents can affect their own local temperature (and amount of air pollution) by planting trees of different sizes around their property.

Satellite images are often used to assess the amount of green in cities and are a cost- effective way to develop datasets that cover an entire city. However, most of this data is only accurate to a scale of 90 to 100 feet—and the OHA project needed to get habitat data that was accurate to about 3 to 8 feet. So, we turned to our community scientists to interpret aerial imagery and create a more detailed habitat map in part ground-truthed by community scientists.

We used Habitat Network (habitatnetwork. org)—a publicly available habitat mapping tool cultivated by the Cornell Lab of Ornithology and The Nature Conservancy. It allowed anyone to map a location and add detailed land cover information about that location. The data are maintained by the Cornell Lab of Ornithology Citizen Science Team in an Oracle Spatial database. (The project is currently in transition).

We trained those Operation Healthy Air participants who showed interest in the mapping of land cover (e.g. vegetation, pavement, grass, housing). Typically, there were three kinds of information recorded (see figure below). The goal of the habitat mapping portion of OHA was to assess the influence of different habitat features (such as trees, green space, buildings, pavement) on air temperature and air quality. Does having more trees, or cool roofs, or pavement lead to higher or lower air temperature or healthier air?

10 | OPERATION HEALTHY AIR FIELD STUDY Anatomy of a Habitat Map

The three steps taken by OHA participants to map the habitat around sensor. Step 1—draw a site line; step 2—draw a set of habitat polygons (grass lawns, buildings, roads, pools, other impervious surfaces, etc.) and step 3, draw in “objects—in our case these were primarily trees and bushes.

The Locations Where OHA Community Scientists Collected Habitat Information

The locations where OHA Community Scientists collected habitat information are shown below. Habitat was recorded within approximately 25 meters of an air sensor (e.g. temperature or ozone sensor). We were able to double check all maps, and ultimately created estimates of habitat features near each of the sensors to test for effects of habitat on local air temperature.

OPERATION HEALTHY AIR FIELD STUDY | 11 An Example Habitat Map for a Location with Vegetated Ground Cover

LEGEND: Ground Cover: brown Buildings : light gray Pavement: darker gray Shrubbery: purple Circular trees all mapped

12 | OPERATION HEALTHY AIR FIELD STUDY 4.1 | DIFFERENCES ACROSS CITIES IN AMOUNT OF GREEN HABITAT, TREES AND PAVEMENT We found variation in the amount of green (measured as size of trees, % of tree cover near the sensors and % landscape that had vegetation (i.e. trees, grass, bushes) around the sensors depending on the cities we examined (see Table 3 below). We found Claremont and Riverside to have larger trees (average diameter ~ 21-23 ft.) in contrast to Long beach which had the smallest trees (with sensors) where the average was only ~ 15 ft. in diameter.

We also used the habitat mapping to calculate the percentage of each habitat category within ~ 67 feet (10 meters) around the temperature sensors. Claremont was the greenest with 35% of the area covered by trees and a total of 49% covered by vegetation of some sort (inc. grasses). Riverside was next greenest. Long beach and San Bernardino were least green with only 14.7% and 15.1% covered in trees respectively, and, 39.9 and 32.7% respectively covered in vegetation. Not surprisingly Claremont and Riverside had the lowest fraction covered in pavement and asphalt. As we shall see later on in Section 4.2.1—these differences in habitats may play a role in influencing local temperature.

TABLE 3: Differences across cities in amount of different habitats surrounding each sensor. Percent cover was calculated as proportion of each habitat cover within 67 feet of a sensor. Tree canopy diameter % Vegetation % Pavement % Asphalt City (ft.) (with sensor) % Tree Cover Cover Cover Cover Claremont 21.8 35.2 49.2 31.4 26.9 Long Beach 14.7 14.7 39.9 45.7 33.7 Ontario 18.4 20.8 42.6 41.3 35.4 Riverside 23.6 29.9 49.9 35.4 29.5 San Bernardino 16.6 15.1 32.7 41.3 38.3

5 | Air Temperature IN A NUTSHELL Air temperature is one of the most influential environmental factors, with a wide variety of effects • 55 Participants measured their indoor and outdoor on humans. Extreme heat or cold conditions put stress temperature and human comfort levels on humans and can result in serious health effects (Day • Typically discomfort started at 82°F et al 2019). As an example, recent heat waves have led • Trees cool air in people’s yards during the day, and to hundreds and even thousands of deaths globally. paved roads/driveways increase heat at night. Extreme temperatures affect physiological (e.g. heart, lung, kidneys, etc.) and cognitive (brain processing, ACTION: Increasing awareness of thermal comfort productivity,) functioning and increases overall stress can help us to identify strategies that increase our levels. People have more “bad” days with even modest comfort and save energy increases in air temperature– with increases in violence, accidents, domestic abuse and even dog bites when temperatures increase. With a projected rise in global temperature including the number of extreme heat days, there is concern about its effect on how well we as humans can function.

A recent issue of the research journal Science of the Total Environment compiled 18 articles published in the journal between 2012 and 2019 on this topic (available ). The research studies looked at the effects of both hot and cold temperatures, and all of the studies found that temperature had significant effects on human health. Both mortality and morbidity (disease) were associated with exposure to increased heat. These compound other known issues associated with discomfort due to extreme temperatures including stress and decreased ability of the brain to function and make decisions. Indirect effects of discomfort associated with hotter temperatures include increases in crime, domestic violence, accidents and a decreased productivity.

A recent global survey of the impact of ambient air temperature on work productivity found that there was only a modest decrease in productivity between 20° and 25°C (see Figure 5)—as measured across many different fields (e.g. less output, more mistakes, more absences, etc.). Each line represents a different case study. Then there is a rapid increase in productivity loss starting around ~ 27°C (~ 77°F) up until 33°C (~ 91°F) at which point productivity is very significantly affected.

OPERATION HEALTHY AIR FIELD STUDY | 13 FIGURE 5. The effect of increasing temperature on labor productivity

Air temperature data were collected to understand how temperature varies over microclimates within communities, and also for community scientist participants to gain a better understanding of the range of temperature where they felt comfortable. In terms of personal comfort, participants recorded both the temperature sensation they felt (very hot, slightly warm, neutral, etc. and their comfort level (very comfortable to very uncomfortable). Individuals vary in how their bodies react physiologically, and their comfort level. Two people can feel the same high heat sensation, but have different levels of comfort. Also, the body’s experience of sensation and comfort can change over time or acclimate to changing conditions.

Sensation

14 | OPERATION HEALTHY AIR FIELD STUDY HOW INCREASINGLY HOT WEATHER COULD AFFECT YOUR HEALTH • Temperatures which go beyond our human “comfort zone” can often compound health challenges such as exposure to pollutants and stress—increasing health impacts. • Temperature affects biological functions and results in physiological stress (Day et al 2019) • People can acclimate, so those in Chicago don’t physiologically react the same to high temperature as those in Los Angeles

Review of this information developed by participants was used to develop actions that residents could take to better deal with increasing heat. These suggested actions are typically changes in home cooling approaches that can result in significant savings in both cost and carbon footprint.

Temperature, humidity and personal sensation and comfort data were collected by two methods: 1. Home temperature and humidity sensors (i.e. AcuRite) maintained by Community Scientists—with data being recorded manually in a spreadsheet. Participants typically also recorded their thermal sensation (e.g. neutral, warm, hot, etc.) along a graded scale, as well as their perceived thermal e.g. comfort (comfortable, uncomfortable, very uncomfortable) when they were recording the temperature. 2. Automatically recording “iButton” sensors which measured air temperature and humidity data that were placed at a consistent height (~ 7 feet or 2 m) in shaded spots (e.g. outside of participants’ homes),

These programs are discussed separately in the following sections.

IN A NUTSHELL

• Most participants maintained their homes temperatures between 75°F and 82°F. • Participants also reported being comfortable up until 82°F—at which point discomfort increased rapidly. • Communities varied with respect to the extent to which they “controlled” their indoor temperature—with some keeping it constant irrespective of outdoor temperature—and others allowing some moderation

ACTION: Opportunities exist in some households to allow indoor temperatures to rise above 75°F and still be comfortable—saving both energy, money and likely reducing carbon emissions!

OPERATION HEALTHY AIR FIELD STUDY | 15 5.1 | HOME TEMPERATURE AND HUMAN COMFORT Fifty-five community participants (or partners) manually recorded temperature and personal comfort and sensation, including four schools across the study area. The following types of data were collected over the course of the day by community scientists: • Time of day temperature recorded • Indoor and outdoor air temperature • Indoor and outdoor humidity • Comfort level at temperature (comfortable or uncomfortable) • Heat level they felt (sensation of cool, neutral or hot)

Home Temperature Monitoring

All the data collected were compiled into a database and reviewed. Data points that appeared to be “outliers”— data points that seemed unusual and inconsistent with what others recorded—were removed from the analysis. The remaining data were reviewed for patterns using standard statistical and visual analytical techniques. Patterns observed in the data are discussed in the following sections and graphics.

16 | OPERATION HEALTHY AIR FIELD STUDY EXAMPLE: Data Collected by Community Scientists–Claremont Household

The graphs show plot the temperature, humidity and personal comfort levels recorded by one community member in Claremont, California. Each dot on the first two graphs is a data point representing the temperature recorded at that time on one of the days over the data collection period. Some community scientists collected data twice a day just for one week—while others collected it many times during a day—and over the course of the entire 5-week study period.

For this specific community member, the data collected shows the following:

• Indoor temperature remained steady throughout the day at approximately 76°F, while outdoor temperature increased during the afternoons to an average of 92°F. The fact that the indoor temperature remained fairly constant suggests that a cooling device such as an air conditioner was likely in use. The outdoor temperature dips below the indoor temperature during the night. • Looking at the Total Thermal Comfort data, the household reported being comfortable between 60° and 80°F, and most comfortable in the 70’s. • This household is comfortable over a wide range of temperature, and is only uncomfortable inside the house when the temperature goes above 80°F. • Suggested Action: Turning the air conditioner off and opening the windows to bring the cooler outdoor temperature inside the house during the night could save cost on the electricity bill and reduce the carbon footprint of the household.

OPERATION HEALTHY AIR FIELD STUDY | 17 5.1.1 | How do people sense increasing temperature? When community scientists recorded indoor and outdoor temperature, they also recorded the “sensation” they felt — was it neutral, warm or cool? A summary of the average temperatures for each category of sensation is provided in Table 4. The color bands in the table represent categories which participants were able to differentiate to a statistically significant degree. As we can see, participants sensed outdoor heat differently than indoors. Generally, participants sensed that it felt “hot” at an average of 90.8° F outdoors, but instead participants felt hot indoors only at 83.5°F.

The data also suggest that participants are able to differentiate even small (~1 to 2 degrees F) cooler or warmer differences in ambient temperature—when it the temperature is around their “neutral” sensation, especially indoors. A “warm” and “slightly warm” sensation was experienced at average temperatures 1 to 3 degrees above neutral when indoors, and 5 to 6 degrees above neutral when outdoors.

TABLE 4: Sensation Felt by Participants Over a Range of Temperatures

Indoor temperature (F) Outdoor temperature (F) mean sd mean sd Cool 75.1 3.3 70.3 5.7 Neutral 76.3 3.5 74.1 6.7 Warm-slightly 77.3 3.8 79.2 5.6 Warm 79.6 4.5 80.8 7.3 Hot 83.5 6.5 90.8 9.2 Hot-Very 85.8 6.8 93.4 9.9

18 | OPERATION HEALTHY AIR FIELD STUDY 5.1.2 | At what temperatures are participants most comfortable? The temperature range at which people are comfortable depends on many factors such as their level of clothing, activity, age and time of day. Generally, studies have found that people tend to be most comfortable between 68 and 75 degrees Fahrenheit (i.e. 20 and 25 degrees Celsius).

For our study region, the percentage of participants who reported feeling uncomfortable both indoors and outdoors is presented in Figure 6. Overall, discomfort starts to occur at lower temperatures outdoors. Participants began to experience discomfort as the temperature went above 75°F outdoors, but indoors, discomfort didn’t start to increase until outside temperature reached the low-80’s. Discomfort then rises rapidly indoors to equal discomfort outdoors in the mid 80s. There are many reasons why participants may be more comfortable indoors than outdoors. People indoors may be less active or wear closes that are “cooler”. (it is not cumulative—it represents the proportion of respondents that report discomfort at that temperature.

FIGURE 6: Temperature and Comfort Levels

FINDING AND ACTION: INDOOR TEMPERATURE CONTROL Data indicate that most people tolerate higher temperatures indoors than outdoors. This finding leads us to wonder if residents with air cooling systems could acclimate to warmer indoor temperatures by raising their thermostats in small increments of one to two degrees over a period of time. This could result in reducing costs for cooling, reducing carbon footprint, and increasing overall resilience to warming trends.

OPERATION HEALTHY AIR FIELD STUDY | 19 5.1.3 | How do communities differ from one another in managing indoor temperature? A comparison of the mean indoor and outdoor temperatures across each of the studied communities is depicted in Figure 7. As expected, the general trend between outdoor and indoor temperatures is positive; as temperature outdoors goes up—the temperature indoors (i.e. homes and schools) also goes up—but this trend varies a lot depending on the community you live in.

At the lower outdoor temperatures (between 50°F and 70°F), indoor and outdoor temperatures across all communities are within approximately 10oF of each other. As outdoor temperature rise (into the 80’s, 90’s and over 100°F), some communities do not show an equal increase in indoor temperature and instead indoor temperature remains fairly constant or increases only slightly in some communities (e.g. the schools Rancho Cucamonga, Redlands, Colton). These can be thought of communities where indoor temperature that are resilient to changes in outdoor temperature. In others communities, indoor temperature rises much more in step with increases in outdoor temperature (e.g. Ontario, Montclair, Jurupa Valley among others)—presumably because they do not or cannot manage their indoor temperature (within levels that are more comfortable—and thus are not resilient to extreme heat.

FIGURE 7: Home Indoor vs. Outdoor Temperatures

As heat increases with climate change, the ability to keep your indoor environment at a comfortable temperature is a form of climate change resilience. In many cases, this resilience results from the use of air conditioning systems— whether this be by choice or economic hardship. However, there are other ways to improve indoor heat resilience, including avoiding heat islands with ground vegetation, house insulation, or altering lifestyle behaviors. These will be discussed further in the “Action” section.

20 | OPERATION HEALTHY AIR FIELD STUDY 5.2 | COMMUNITY IBUTTON TEMPERATURE SENSORS Automated sensors (i.e. iButtons) were placed outdoors throughout the each of the study communities in addition to home sensors. These automated sensors were placed beneath trees at a consistent height of ~ 7 feet and collected data continuously every half hour over the study period. Data was downloaded, compiled into a central database and is available for viewing at http://earthwatch.urbanresiliency.org/news-blog/use-esmc-ibutton-data-explorer/.

IN A NUTSHELL

• Cities varied in their average temperature—with both distance form ocean and season influencing temperature • Streets were slightly cooler during the day than either front or back yards—but streets were ~ 1.5°F hotter at night

ACTION: an interactive daily viewer of air temperature allows participants to test how local temperature varies across places

Map of locations of all ibutton temperature sensors (orange) at community science locations

OPERATION HEALTHY AIR FIELD STUDY | 21 5.2.1 | iButton temperature results The results of average air temperature across cities and landscapes is presented in Table 5. The table includes not only average temperature but also 25 % hottest temperatures during the 5 week study period (~ 8 hottest days out of the 35 days when temperatures were measured). We can see that Long Beach is typically much cooler during the day and night—which is not surprising given the moderating influence of the ocean compared to the Inland Empire. Claremont and Riverside which were studied in the peak of summer (July) had the highest temperatures—with Riverside hotter than Claremont. Ontario and San Bernardino were studied in later summer (August-September) and were cooler than Claremont and Riverside—with a small West to East gradient detected—westerly cities (i.e. Claremont and Ontario) being cooler than the more easterly cities for the time periods studied.

TABLE 5: iButton Air Temperature Across the Sturdy Cities and Landscapes for Operation Healthy Air.

Between 20 and 60 iButtons were placed in each city at 7 feet high under a tree with temperature readings taken every 30 minutes.

DAY NIGHT Mean daily temperature (F) City average backyard frontyard street average backyard frontyard street Long Beach 76.47 75.88 77.86 75.67 64.09 63.57 64.13 64.58 Claremont 90.96 90.93 90.70 91.24 70.06 69.26 69.82 71.11 Riverside 93.12 93.76 92.86 92.75 72.34 71.83 71.92 73.27 Ontario 88.56 87.89 90.12 87.66 68.58 68.14 68.36 69.24 San 90.84 92.21 90.64 89.67 70.52 69.98 69.51 72.07 Bernardino landscape 88.13 88.44 87.40 69.80 69.90 71.42 average 25 % percentile hottest temperature City average backyard frontyard street average backyard frontyard street Long Beach 80.54 79.7 82.76 79.16 65.54 64.76 65.48 66.38 Claremont 95.3 95.9 95 95 73.1 72.5 72.5 74.3 Riverside 98.3 99.5 97.7 97.7 75.5 75.2 75.2 76.1 Ontario 96.56 95.9 98.6 95.18 72.8 72.5 72.5 73.4 San 99.32 100.58 98.78 98.6 75.14 74.66 73.76 77 Bernardino landscape 94.316 94.568 93.128 73.715 73.49 75.2 average

When comparing landscapes—streets were between 1 degree F cooler than front and 0.5 cooler than back yards during the day—but 1.5 degree F hotter at night. While it is intuitive that streets are hotter at night due the large amounts of “black top” or asphalt that absorb heat during the day and reradiate it out at night. However, that streets are slightly cooler during the day may be due to a phenomenon called the “street canyon” effect where wind can more easily bring cooler air from elsewhere (maritime air—cool air from the mountains…) into to cool streets. Yards have more 3 dimensional structure (walls, buildings, trees) that slow down air flow which restricts air flow and keeps warmer air present.

Preliminary analyses on the effect of trees on local air cooling suggests that bigger trees do in fact provide a small but significant cooling benefits to their immediate surroundings—but just during the day.

22 | OPERATION HEALTHY AIR FIELD STUDY 5.3 | EXPLORING THE AIR TEMPERATURE DATA YOURSELF! An interactive data viewer (http://esmc.uiowa.edu:3838/iButtons_data_working/) was developed by Dr Jun Wang and Dr Lorena Castro at University of Iowa as part of their effort to make accessible networks of environmental sensors to community members and researchers (see http://esmc.uiowa.edu:3838/uiowa_sc_working/).

The front page of the data explorer website is shown below. The data explorer includes simple directions for selecting data to review and allows you to generate simple graphics to help understand single household results or compare different households. Data from all three campaigns Inland Empire and Long Beach regions is included on the website. You can find a place you are curious about and see how temperature varies across our study period. You can also compare multiple sensors against each other to see how temperature varies from place to place. Note that some sensors are placed close to one another e.g. one in front yard and another in a backyard—and you will need to zoom in to see them. There is also a slide button which allow you to choose longer time scales (e.g. weeks) or shorter ones (e.g. a day)—depending on what kind of questions you are interested in exploring.

Web interface of the ESMC data exploration tool

On the left is the map of the area of interest(e.g. Long Beach) and on the left is the temperature data across the dates of interest for a sensor selected (in this case sensor # 5).

One example of how the data visualization tool can be used is illustrated in the highlight story below.

Blog on Earthwatch Urban resiliency web site on how to use iButton data explorer

OPERATION HEALTHY AIR FIELD STUDY | 23 Highlight Story: Variation in Temperature across Residential Community Microclimates

RESEARCH QUESTION: Does air temperature differ when comparing a backyard, front yard, and neighboring park? To examine this, we looked at three air temperature sensors (i.e. iButtons) in Montclair. Each sensor was located about 2 meters (~ 7 feet) high in a tree. • Sensor # 37: in a backyard. Tree species: Tangelo, 8 feet average tree canopy radius and about 15 feet high. • Sensor # 45: in a park (cemetery). Tree species: Plum/cheery tree, 8.6 feet average tree canopy radius and about 16 feet high. • Sensor # 47: in the front yard/street. Tree species: Coast live oak, 24 feet average tree canopy radius and about 35 feet high.

24 | OPERATION HEALTHY AIR FIELD STUDY In Figure 8, we have chosen to show variation between these three sensors over a 4 day period. Over these four days, there was a general decrease in maximum temperature from a high over 100 in the first couple days to below 100 in the last couple days. Focusing on how temperature changes over the course of a day, temperature peaked between 1 and 4 pm, and dropped through the night with the coolest time around 5am.

Comparing temperatures during the mid-day heat peak (e.g. noon to 4:00 p.m.) across each of the three sites we can see that air temperature beneath the trees in the front yard of the house (#47) and at the cemetery (#45) were cooler than the tree in the backyard of the residence (#35). The front yard tree had a larger canopy radius (35-feet), and would have more shade, than the backyard tree (8-foot radius). The cemetery tree has an 8-foot canopy radius, but is surrounded by vegetation, which has an overall cooling effect.

The coolest location at nighttime is the cemetery park (by 2 to 6 degrees F). One possible reason may be that the park is surrounded by trees and vegetation, compared to the pavement and buildings surrounded by trees and vegetation, compared to the pavement and buildings at the house, which tend to absorb heat during the day and radiate heat out at night.

This seems to be a general trend we also found elsewhere—bigger trees help cool during the day—and at night, area with lots of asphalt pavement tend to be hottest!

You can continue to explore the data changing which sensors you view or the timescale you focus on. For example, you could explore whether park trees provide more or less benefit during heat waves (in contrast to cooler days)!

Figure 8: Four Days of Temperature Data

OPERATION HEALTHY AIR FIELD STUDY | 25 6 | Ozone IN A NUTSHELL We chose ozone as the key focal pollutant because it can seriously compromise the health of people including • Ozone can vary extensively over short distances (< those with respiratory illness such as asthma. Ground level 2.5 miles) ozone (O3) is formed when the right mix of precursor air • Ozone varies with air temperature and tends to peak pollutants (Nitrogen dioxide (NO2) and volatile organic in mid-afternoon compounds (VOCs)) comes together with sunlight and • Current forecasts tend to underestimate some daily heat. These conditions occur in proximity to sources of maximum amounts of ozone. these precursors (such as ports, highways, energy generation facilities) as well as places where these ACTION: Vulnerable populations should avoide precursors collect (due to the prevailing wind directions) outdoors during high heat days to minimize exposure to hazardous ozone levels and are concentrated far away from the original sources. This is why some national parks (e.g. Joshua Tree National Park, and, Acadia National Park in Maine) can have terrible air pollution problems despite not producing any pollution themselves. Similarly, while the ports of Long Beach and San Pedro are large producers of pollutants, the downstream effects are often worst along the foothills and Riverside. We focused the project in both Long Beach—source of many of the precursors - as well as downwind along the Inland Empire (e.g. Claremont, Ontario, Riverside, and San Bernardino; see Figure 2).

Despite major improvement in Southern California air quality over the past 30 years, it remains one of the country’s major ozone problem areas with many days failing air quality standards (and hazardous for healthy adults). Moreover, given the high variability across the key ingredients (known as precursors) to the formation of ozone across both time and location, knowing more precisely how ozone varies at small scales will help target interventions and monitoring programs more precisely. In particular, it is important to test whether ozone varied predictably at scales smaller than most existing monitoring programs currently assume it does. We chose to test variability of 4 km by 4 km as this represents the spatial resolution of the current NASA imagery. To get at this question of local variability in ozone, we needed to work with local community members to access homes and yards to create a neighborhood scale understand of variability in ozone.

Ozone stations consisted of the new high-end O3 analyzer (106-L, 2B Technologies, Boulder, CO). The 106-L instrument has been designated by the EPA as a Federal Equivalent Method (FEM) for monitoring for compliance with the US Clean Air Act (EQOA– 0914–218). In addition, the stations were equipped with anemometers, relative humidity, and air temperature sensors. For all sensors, we conducted a series of calibration and validation studies in both a controlled atmospheric chamber and field conditions. We ran five to six ozone stations at each of the three campaigns (Long Beach and Inland Empire) within the 4 km x 4 km square sampling areas. Many of these were in people’s backyards! These allowed us to gather information for 5-week periods at small scales in these different communities.

26 | OPERATION HEALTHY AIR FIELD STUDY Surface ozone: when bad air and sunlight mix Photo credit:Photo Al Pavangkanan

Smog (i.e. ozone pollution) over los Angeles

How Does Ozone Form? Ozone Health Effects Ozone is formed when the right ratios of Deaths per year due to high Ozone levels: specific types of air pollutants (NO2, VOC) • 3,255 for Los Angeles-Long Beach-Glendale are exposed to sunlight and heat. • 1,416 for Riverside-San Bernardino-Ontario area, Ozone is a toxic pollutant that irritates and damages lungs and other tissues. Number of times people called in sick, missed school, etc. because of air pollution. • 2.9 million days in Los Angeles-Long Beach- Glendale area, •1.3 million in the Inland area

OPERATION HEALTHY AIR FIELD STUDY | 27 6.1 | EXPLORE OZONE DATA USING INTERACTIVE VIEWER The ozone data is available to community members and the general public at the same website as the iButton temperature data discussed in the previous section of this report. (http://earthwatch.urbanresiliency.org/news-blog/ use-esmc-ibutton-data-explorer/).

Two sets of ozone data are included in the web-based data viewer. One set is labeled as “in-situ”, meaning it is from measurements collected from the iButton sensors placed in the community. The second set of data is the results of a model called WRF-Chem used to estimate ozone concentrations across a broader region than that covered by the in-situ data points. The model data is labeled “fcst” because it forecasts ozone concentrations beyond the measured values.

The in-situ and model forecast ozone data from the three campaigns and all study areas can be viewed, graphed and compared. The ozone data can also be viewed alongside the temperature data to look for trends and relationships.

6.2 | HOW DOES OZONE VARY ACROSS SOUTHERN CALIFORNIA Ozone concentrations typically start to increase in the early afternoon and peak around 4:00 or 5:00 p.m. During the evening, both temperature and ozone concentrations decrease significantly and are low when people are waking up and starting their days.

Both ozone and temperature vary extensively within quadrat areas less than 4 km2. This is important because NASA maps ozone concentrations by 4 km2 quadrats, which means they could miss high and low concentrations within those areas, and either overestimate or underestimate ozone concentrations within the quadrats.

Ozone concentrations measured in the field were similar to model results, demonstrating that the WRF-Chem model is capable of estimating ozone distribution over a region. However, the model missed some of the daily variability in ozone concentration, such as the frequent nighttime low concentrations. In some cases, the model also did not show the increase in ozone at the highest temperatures. A regional overview of ozone is illustrated in Figure 9.

FIGURE 9: Ozone Distribution Based on WRF-Chem Model

The WRF-Chem model uses ozone concentration at set points, the location of known sources of ozone, and weather data (mostly wind direction) to estimate, or forecast, ozone concentrations over a region. This type of model is a set of mathematical equations developed to mimic how ozone is distributed.

The model results were compared to the actual concentrations of ozone measured during this study to check how well the model works.

28 | OPERATION HEALTHY AIR FIELD STUDY 6.3 | HOW DOES OZONE VARY WITH WIND SPEED AND DIRECTION? We know that ozone tends to form in mid to late-afternoon when air temperatures (an ozone precursor) tend to be highest. However, wind also tends to pick up in late afternoon—with unknown effects on the other precursors (such as nitrogen dioxide—a common source of pollution from trucks and power stations among other sources).

To better understand the effects of wind direction and strength on ozone formation we can use a type of visualization called a polar plot shown in Figure 10. Each dot represents the average amount of ozone for that wind direction and wind speed at one particular ozone station. The redder the color the higher the amount of ozone found (on average) for that wind direction and speed across the study. The further from the middle—the higher the wind speed; with the wind direction being indicated by the cardinal direction on the plot. For example, points on the top half represent wind heading north, and points on the right side represent wind heading towards the east.

In the figure presented below for an ozone station in Claremont CA, the highest amounts of ozone tend to occur when wind is blowing more strongly toward the South and/or South-East—with ozone being relatively low when there is little or no wind, or blowing to the North. This information can help identify sources of the precursors to forming ozone and when people who are sensitive to ozone (e.g. elderly people, babies and people with respiratory problems such as asthmatics) should avoid being outside.

FIGURE 10: Distribution of Ozone Concentrations

OPERATION HEALTHY AIR FIELD STUDY | 29 6.4 | OZONE AND TEMPERATURE Data shows a close correlation between ozone concentration levels and temperature over the course of a day. As an example, Figures 11 and 12 depict data at Station 6 in Ontario; both the field data measured by iButtons (in-situ) and the modeled results (fcst) are shown.

FIGURE 11: OHA Study—OHA Study—Relationship Between Ozone and Temperature — 4 Day Record -Ozone Station 2 in Ontario, CA —August 25 to 29, 2017

The measured temperature and ozone concentrations (labeled in-situ in the figure) clearly show a strong correlation, with ozone increasing with temperature with the afternoon heat. Ozone concentrations increase from zero to more than 100 ppb daily. The ozone peaks occur at approximately 5:00 p.m., slightly after the temperature daily maxima.

FIGURE 12: Relationship Between Ozone and Temperature— 12 Day Record Ozone Station2—August 26 to September 3, 2017

This 9-day record shows a close correlation between the measured in-situ data and the levels forecasted by the WRF-Chem model. However, the maxima and minima daily ozone concentrations reported by the model underestimate the amount of ozone detected by sensors.

30 | OPERATION HEALTHY AIR FIELD STUDY 7 | Actions REDUCING EXPOSURE TO OZONE With the improved understanding of heating and cooling trends in urban residential environments, we can Data indicate that ozone concentrations peak at develop ways that households can become more resilient approximately 5:00 p.m. Lowest ozone levels and to climate change and save money on our electric bill! temperature were recorded in the pre-dawn hours. Some easy changes that we can make are summarized in the Thermal Regulation snapshot at the end of this ACTION: Avoid being outdoors during the hottest section and described below. parts of the day to avoid the highest concentrations of ozone in the air. • Manage indoor air temperature to minimize carbon footprint and cost. This study has demonstrated that even small differences in temperature have an impact on our comfort so paying attention to local temperature can improve your health and ability to function well. Research has also shown that people can become acclimated and adjust their temperature comfort threshold—so it is possible to adapt to warmer temperatures within reason. Try to adjust indoor air conditioners down one or two degrees to see if you can become acclimated. If that works, try to adjust down again and see what happens. You may surprise yourself!

• Limit outside activity during the hottest part of the day when ozone levels could be highest. Ozone concentrations increase with heat over the afternoon and peak at approximately 5:00 p.m., just following the peak temperature. Making small adjustments in your daily routines and behavior can result in improved health. By limiting outside activity during the later afternoon and early evening, you can avoid both the intense heat and the highest ozone concentrations, both of which can affect respiratory function.

• Landscaping—Plant trees in your yard and minimize hard, dark ground surfaces such as asphalt wherever possible. Dark, hard ground surfaces such as asphalt absorb heat during the day and radiate the heat off at night when temperatures drop. Vegetated ground cover does not absorb heat to the same extent, and avoids this night time heat transfer, allowing the area to cool overnight. Also, tress can provide shade and a tree’s evapotranspiration process has an overall cooling effect on any given area.