NOTE: For the New York City Science and Engineering Fair (NYCSEF), not all projects are accepted, so even entry in the preliminary round indicates that a project has already passed a screening process.
The color of the materials used to construct roofs influence the environment significantly. Urban heat islands are small areas
that have different climates than its surrounding areas. Urban environments such as New York and Manhattan are considered
to be urban heat islands because the temperature between these urban areas is much greater than the temperatures in a
rural or suburban location. This experiment aimed to find the difference between three different colored surface materials.
The three colors are white, black, and green. The goal was to find the effects that these colored materials have on an
urban society, whether the effects are positive or negative. Based upon educated guesswork, the experiment hypothesized
that the green colored surface would have the greatest positive impact on an urban environment because it simulated
vegetated surface which ameliorates the effects of urban heat islands. The experiment utilized an apparatus that
measured the albedo of a surface. The apparatus was deployed for one week on top of the experimental site. The
results concluded that the white rooftop will have the greatest positive impact on the climate of an urban environment.
Pollution is becoming a big problem in the world today; atmospheric visibility can determine the amount of pollution
is in a given area. Our purpose for our experiment is to find out which season (summer or fall) would have poor
visibility. Our project mainly focuses on the differences of visibility in the summer and the fall. Picking any
week in the summer (best average temperature of the season) every day for one week, we will go to Queens College
which is located in Flushing. Going to the roof of the science building, we are able to see the horizon line from
a great angle. With the camera, we will take a photo at the same spot and be precise and accurate with the times
and scene. We will be observing our location on the day we take pictures. In addition, we will us air quality
index databases to determine temperatures, humidity, precipitation, and wind speed because they are all factors
in visibility. Materials needed are camera (Samsung SL 420), Image J software and Air Quality Index databases.
After collecting our pictures, we upload them and place it on the ImageJ software, where it calculates and
displays a histogram of the distribution of gray values in the active selection. The x-axis represents the
possible gray values and the y-axis shows the number of pixels found for each gray value. The graphs showed
there are lower gray values in summer and the number of pixels appears to be higher in fall. Our summer pictures
shows a pattern of decreasing gray value in contrast the fall pictures show that the intensity stays relatively
high until the distance reaches 1400 pixels. Our hypothesis was correct; results concluded visibility is better
in fall than summer.
We began our project with the goal of determining whether or not the length of the growing season has changed over the first decade of the 21st century in United States. To answer our question, we analyzed Leaf Area Index (LAI) data for every state except Alaska and Hawaii collected from a satellite named MODIS every eight days for each year between 2001-2010. LAI is the amount of leaf surface area per unit ground area. Once the data was collected, we made graphs for each state in the contiguous U.S. of the leaf area index for each year (except 2006, due to insufficient data) by plotting every eight-day data point over a whole year for each year from 2001-2010. We then used those graphs to determine the length of the growing season for each year by observing significant short-term changes in the shape of the graph trends. Next we split up the country into two regions, the area above forty degrees latitude and the area below, so that we could see how the latitude of a site could affect its growing season length. Following our data collection, we concluded that the length of the growing season in the U.S. has been increasing over the course of the first decade of the 21st century. The length of the growing seasons in the contiguous U.S. states above forty degrees latitude increased on average significantly more than those states below forty degrees latitude.
One of the issues of climate change is the relationship between insolation and the overall temperature of an area. This is the phenomenon of “Heat Islands”. We chose four sites to represent the “color” aspect of the built environment, urban environment is represented as white, the water’s edge as blue, the wetlands as green and residential areas is yellow. We hypothesized that the waters’ edge/blue environment will have the greatest temperature change of all the sites/color. We used a Hobo logger and probes to continuously measure insolation, thermal radiation, temperature and reflective radiation. Using this data we were able to determine the relationship between insolation and temperature from each site for 5 weeks. Our conclusion demonstrated that the water’s edge/ blue had the highest overall temperature and the most incoming solar radiation of any of the sites, thus supporting our hypothesis. This demonstrates that areas with water or large amounts of vegetation do not contain “heat” and do not create this “Heat Islands” that are developing in the built environments of man.
In this experiment, we wanted to find out if you could power a South Florida home entirely out of solar panels. We got the idea
from our local weather, which brought plenty of incoming sunlight, yet only a few people in the area took advantage
of it as a source of energy. There is the big issue of global warming happening, and a lot of people are "going green". THis
would be another, efficient way, of helping slow down air pollution, since power plans would be in less use. Also, for
those who do use solar panels, we wanted to know if those same solar panels could power not only a portion of the home, but
the entire home. We wanted to test if Florida "The Sunshine State" had enough Sunshine to power our homes. Our goal was to
find out if solar panels are as efficient as they are portrayed. We expected that over the 24 hours of a day, there would
in total be at least 5 hours of pure sunlight. We hypothesized that there would be enough incoming sunlight over the course of
one day to power a home over the same period of time. Through various background sources, we clculated that, per day, a
south Florida home needs 32kWh Iilowatt-hours). For data collection, a Hobo Data Logger with sensors (temperature,
insolation, and reflection, thermal radiations were measured) is set up in two locations. South Miami Middle School
(suburban) and in the Fairchild AWetlands (closer to water). The school site is in the middle of the south Miami suburban
neighborhood, and is surrounded by greenery and plants. This site represents the average suburban neighborhood. The
Fairchild wetlands are very green and very plant-filled. This sunlight, when calculated into kilowat-hours (kWh), was concluded
to be enough to power an expected amount of solar panels, which would convert it to electricity to power the home. Our
major findings were that there was more than enough sunlight to power a home with 7 solar panels, and that you could
get by without using power plant electricity as long as the incoming sunlight is constant.
The research we conducted showed us how cloud cover relates to global warming. Our research attempted to solve if cloud cover will act as a shield to sun insolation, allowing less sun insolation to reach Earth’s surface, allowing the Earth to cool. We did this by researching the relation of cloud cover and sun insolation. We felt that the sun insolation would reduce as the cloud cover increased, which we proved by calculating sun insolation and cloud cover using a pyranometer and a time lapse camera, and then relating them with each other. Our data showed that our hypothesis was correct. As cloud cover increased, the sun insolation decreased. Clouds block out sun insolation so solar radiation in not warming our Earth but could
be keeping reflective radiation from escaping.
Does climate change have any effects on seaweed growth? Some of the climate change factors that affect seaweed are water pollution in the water, amount of sun light, water height, carbon monoxide, and humane interaction nutrition in soil, carbon in the water, water temperature. I want to investigate the effects of water temperature on seaweed beds in the Atlantic Ocean, Gulf of Mexico and the Caribbean. If the temperature rises it will be harder for the see grass beds to grow since seagrass beds require a specific temperature to grow in. I believe, like most living things on earth, the seagrass beds were evolved to live in very specific living conditions, and when they are changed quickly the sea weed does not evolve fast enough and dies out. I want to first explore the overall effects of sea surface temperature on a global scale. With this in mind I began with viewing satellite images over time. I used NASA’s Near Earth Observation website (neo.sci.gsfc.nasa.gov) which has a collection of satellite images over time. I chose to view sea surface temperature, chlorophyll concentration and air borne carbon monoxide. As seen in many of the areas, sea grass beds do well in warmer temperatures. In most of the world the hotter it is, the more plant life you are likely to have, than colder places. There is no difference, however, among water plants. When evaluating the satellite images of water temperature and chlorophyll in the water (plant life). Plant life and sea temperature rise together, however, this is under the assumption that they are the only variables, which is not the case.
Our research consisted of figuring out which human areas affect absorption and reflection of heat, and which has the heat island effect. The scientific gap now being filled is the question how much insolation is being reflected, and absorbed. In the end our hypothesis that that the urban area would absorb then reflect light was not supported. The urban areas since, have covered the natural environment would appear to absorb then reflect more heat into the atmosphere. Thus, creating a “heat island”. Comparing are two researched sites the UM parking lot, and the Fairchild Gardens pond, The Fairchild Gardens absorbed then reflected more heat. We made this conclusion by collecting data in these two sites with a hobologger that was attached to a pyranometer that measured insolation, a reflectometer which measured reflected light, and a thermopile that measures thermal energy. Now, it is evident that the Fairchild Gardens has the heat island effect
One of the issues of climate change is the relationship between insolation and the overall temperature of an area. This is the phenomenon of “Heat Islands”. We chose four sites to represent the “color” aspect of the built environment, urban environment is represented as white, the water’s edge as blue, the wetlands as green and residential areas is yellow. We hypothesized that the waters’ edge/blue environment will have the greatest temperature change of all the sites/color. We used a Hobo logger and probes to continuously measure insolation, thermal radiation, temperature and reflective radiation. Using this data we were able to determine the relationship between insolation and temperature from each site for 5 weeks. Our conclusion demonstrated that the water’s edge/ blue had the highest overall temperature and the most incoming solar radiation of any of the sites, thus supporting our hypothesis. This demonstrates that areas with water or large amounts of vegetation do not contain “heat” and do not create this “Heat Islands” that are developing in the built environments of man.
The investigation, Vegetation and its Effects on Radiation, measured and collected data from two different sites. The site at Fairchild Gardens was full of vegetation and South Miami Middle was the site with partial vegetation also the residential site. The equipment used contains a thermopile, two channel reflectometer, pyranometer, and thermometer collecting data which was used for comparing the amount of incoming and outgoing radiation at both sites. We hypothesized that total vegetation produces a cooler atmospheric environment, and our data supports the conclusion that the more vegetation present the cooler the air around it becomes. The experiment also supports the idea of Urban Heat Islands proving that vegetation prevents excessive climate change.
The purpose of this investigation was to figure out if black asphalt is hotter than white concrete in relation to its surface and air temperature. We think that black asphalt will be hotter than white concrete in surface temperature because of its absorption of sunlight. However, white concrete will be hotter in air temperature because of its reflectance of sunlight. Once we collected our data we found that between 12 to 7 pm there was a greater air temperature than surface temperature on the black asphalt. We also found that between 9 and 11 am, concrete had a greater air temperature than surface temperature. This means that during the day, asphalt was cooler in air temperature during the morning hours of the day, and most likely, during the evening hours it was releasing all the heat it absorbed during the day. During the morning hours concrete was reflecting most of the sunlight that hit its surface. This research could be implied to figure out which surface you would want to play on. This proves that white concrete is cooler, and therefore better to play on.
This project was done to determine the optimal angles for solar panels by using
pyranometers. We conducted an experiment to test different angles in order to determine
the ideal angle in which solar panels could be placed in. The most common angle placement for
solar panels is the latitude of the location with an addition of 15 degrees. Our location for the
experiment was at 40.678 latitude, but was rounded to 40 due to the lack of pinpoint accuracy.
Instead of using expensive solar panels, the experiment substituted solar panels with pyranometers.
Our control pyranometer was set at 0 degrees while the others were set up at 45 degrees, 50
degrees, and 55 degrees. The pyranometers were set at fixed angles from 11/26/11 on the rooftop of
a two story building. The roof of the building allowed the pyranometers to record solar radiation (volatge created)
without the interference of shadows caused by buildings. he pyranometers were connected to
a data logger which recorded the amount of solar radiation present and the amount of voltage generated
in a 10 minute interval. This experiment was performed to determine if there was a better angle
to place solar panels. The angle of a solar panel can greatly affect the amount of energy produced.
Renewable energy sources are very valuable due to the decreasing amount of nonrenewable fuels.
After the experiment and data recording, we noticed that our hypothesis was wrong, but found many
ways to improve our project.
Climate research is an important factor for the environment. It accounts for many of the occurrences in the world that relate to global warming. Understanding the climate may help in the efforts to reduce the amount of activities that add on to global warming. In this study, two landscapes have been tested: concrete and grass. For each of the landscapes, two bases were built that would hold the pyranometers and data loggers. The pyranometers measured the incoming solar radiation and the solar radiation that was reflected off the surfaces. Every week I checked the data that is retrieved from the data logger. The original hypothesis included the idea that the grass would absorb more sunlight, and the concrete would reflect more sunlight. The two different types of surfaces were observed to have different results. The grass had an overall approximate incoming radiation average of 0.004 V compared to the concrete, which had an overall approximate average of 0.003V. The overall average for the reflecting radiation for the grass over two weeks was 0.007875 V, whereas for the concrete, the reflecting radiation was 0.18568 V. The end results indicated that concrete has a better reflecting capability compared to grass. It also indicated that grass has a better capability of absorbing sunlight in comparison to concrete.