Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Non-Hispanic population of Long Island town by race. It includes the distribution of the Non-Hispanic population of Long Island town across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Long Island town across relevant racial categories.
Key observations
Of the Non-Hispanic population in Long Island town, the largest racial group is White alone with a population of 263 (92.28% of the total Non-Hispanic population).
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Long Island town Population by Race & Ethnicity. You can refer the same here
Note: Data elements were retired from HERDS on 10/6/23 and this dataset was archived.
This dataset includes the cumulative number and percent of healthcare facility-reported fatalities for patients with lab-confirmed COVID-19 disease by reporting date and age group. This dataset does not include fatalities related to COVID-19 disease that did not occur at a hospital, nursing home, or adult care facility. The primary goal of publishing this dataset is to provide users with information about healthcare facility fatalities among patients with lab-confirmed COVID-19 disease.
The information in this dataset is also updated daily on the NYS COVID-19 Tracker at https://www.ny.gov/covid-19tracker.
The data source for this dataset is the daily COVID-19 survey through the New York State Department of Health (NYSDOH) Health Electronic Response Data System (HERDS). Hospitals, nursing homes, and adult care facilities are required to complete this survey daily. The information from the survey is used for statewide surveillance, planning, resource allocation, and emergency response activities. Hospitals began reporting for the HERDS COVID-19 survey in March 2020, while Nursing Homes and Adult Care Facilities began reporting in April 2020. It is important to note that fatalities related to COVID-19 disease that occurred prior to the first publication dates are also included.
The fatality numbers in this dataset are calculated by assigning age groups to each patient based on the patient age, then summing the patient fatalities within each age group, as of each reporting date. The statewide total fatality numbers are calculated by summing the number of fatalities across all age groups, by reporting date. The fatality percentages are calculated by dividing the number of fatalities in each age group by the statewide total number of fatalities, by reporting date. The fatality numbers represent the cumulative number of fatalities that have been reported as of each reporting date.
https://www.newyork-demographics.com/terms_and_conditionshttps://www.newyork-demographics.com/terms_and_conditions
A dataset listing New York counties by population for 2024.
This dataset provides information about the number of properties, residents, and average property values for Long Island Drive cross streets in Hot Springs National Park, AR.
Onsite wastewater disposal systems (OWDS) in coastal regions of Long Island, New York, contribute bacteria, nutrients, and organic wastewater-associated compounds (including pharmaceuticals, personal care and domestic use products referred to here as contaminants of emerging concern (CECs)) to downgradient shallow groundwater in nearshore settings. Many of the densely populated areas along the East Coast (i.e. Long Island, New York) are served by OWDS. Approximately 75 percent of Suffolk County, New York, residents rely on simple OWDS such as a series of cesspools (ground pits lined with cement blocks or rings without a sealed bottom) and septic systems. Cesspools provide minimal wastewater treatment, typically relying on bacteria to breakdown the solid waste while untreated water percolates into the sandy surficial aquifer. The high hydraulic conductivity of the sandy surficial aquifer of the New York coastal region makes these areas particularly vulnerable to organic wastewater contamination. Groundwater samples were collected from the shallow groundwater flow system along the shoreline of (1) a barrier island summer community and (2) the mainland of Long Island. Both locations are distinctive coastal communities in Suffolk County, NY, and typically rely on a simple OWDS system. The coastal communities selected are in areas inundated by the storm tide brought on by Hurricane Sandy and are considered vulnerable to extreme storms (i.e. hurricanes and nor’easters), flooding events, and sea-level rise; all of which can damage wastewater infrastructure and lead to biogeochemical changes that disrupt the level of onsite treatment and result in increased discharge of contaminants to estuaries through groundwater seepage. Specific locations were selected in areas along the shore that are within 180 m downgradient from OWDS and just above the reaches of the spring high-tide mark along the shoreline. For our study, beach areas without bulkheads (a retaining wall built for shoreline protection) were targeted due to the need to access areas downgradient of OWDS. Twenty-nine of the 103 pharmaceuticals measured were detected at least once at the NY sample locations. Other detected CECs include PCDUs (caffeine, nicotine, and metabolites), methyl-1H-benzotrizole (a corrosion inhibitor), and piperonyl butoxide (a pesticide synergist). Lidocaine, an over-the-counter topical anesthetic, was the most commonly detected pharmaceutical (35% of samples). Other commonly detected pharmaceuticals included fexofenadine (an over-the-counter antihistamine detected in 30% of samples), and carbamazepine (an anticonvulsant), desvenlafaxine (antidepressant), meprobamate (an anxiolytic), metformin (an antidiabetic), and tramadol (an opioid) each detected in 25% of the samples.
https://www.newyork-demographics.com/terms_and_conditionshttps://www.newyork-demographics.com/terms_and_conditions
A dataset listing New York cities by population for 2024.
This deprecated dataset provides systemwide ridership and traffic estimates for subways (including the Staten Island Railway), buses, Long Island Rail Road, Metro-North Railroad, Access-A-Ride, and Bridges and Tunnels, beginning 3/1/2020, and provides a percentage comparison against a comparable pre-pandemic date.
Next-day estimates for daily ridership, without the pre-pandemic comparison, are now provided at https://data.ny.gov/d/sayj-mze2
This dataset provides information about the number of properties, residents, and average property values for Long Island Drive cross streets in Atlanta, GA.
VITAL SIGNS INDICATOR Life Expectancy (EQ6)
FULL MEASURE NAME Life Expectancy
LAST UPDATED April 2017
DESCRIPTION Life expectancy refers to the average number of years a newborn is expected to live if mortality patterns remain the same. The measure reflects the mortality rate across a population for a point in time.
DATA SOURCE State of California, Department of Health: Death Records (1990-2013) No link
California Department of Finance: Population Estimates Annual Intercensal Population Estimates (1990-2010) Table P-2: County Population by Age (2010-2013) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/
U.S. Census Bureau: Decennial Census ZCTA Population (2000-2010) http://factfinder.census.gov
U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2013) http://factfinder.census.gov
CONTACT INFORMATION vitalsigns.info@mtc.ca.gov
METHODOLOGY NOTES (across all datasets for this indicator) Life expectancy is commonly used as a measure of the health of a population. Life expectancy does not reflect how long any given individual is expected to live; rather, it is an artificial measure that captures an aspect of the mortality rates across a population that can be compared across time and populations. More information about the determinants of life expectancy that may lead to differences in life expectancy between neighborhoods can be found in the Bay Area Regional Health Inequities Initiative (BARHII) Health Inequities in the Bay Area report at http://www.barhii.org/wp-content/uploads/2015/09/barhii_hiba.pdf. Vital Signs measures life expectancy at birth (as opposed to cohort life expectancy). A statistical model was used to estimate life expectancy for Bay Area counties and ZIP Codes based on current life tables which require both age and mortality data. A life table is a table which shows, for each age, the survivorship of a people from a certain population.
Current life tables were created using death records and population estimates by age. The California Department of Public Health provided death records based on the California death certificate information. Records include age at death and residential ZIP Code. Single-year age population estimates at the regional- and county-level comes from the California Department of Finance population estimates and projections for ages 0-100+. Population estimates for ages 100 and over are aggregated to a single age interval. Using this data, death rates in a population within age groups for a given year are computed to form unabridged life tables (as opposed to abridged life tables). To calculate life expectancy, the probability of dying between the jth and (j+1)st birthday is assumed uniform after age 1. Special consideration is taken to account for infant mortality.
For the ZIP Code-level life expectancy calculation, it is assumed that postal ZIP Codes share the same boundaries as ZIP Code Census Tabulation Areas (ZCTAs). More information on the relationship between ZIP Codes and ZCTAs can be found at http://www.census.gov/geo/reference/zctas.html. ZIP Code-level data uses three years of mortality data to make robust estimates due to small sample size. Year 2013 ZIP Code life expectancy estimates reflects death records from 2011 through 2013. 2013 is the last year with available mortality data. Death records for ZIP Codes with zero population (like those associated with P.O. Boxes) were assigned to the nearest ZIP Code with population. ZIP Code population for 2000 estimates comes from the Decennial Census. ZIP Code population for 2013 estimates are from the American Community Survey (5-Year Average). ACS estimates are adjusted using Decennial Census data for more accurate population estimates. An adjustment factor was calculated using the ratio between the 2010 Decennial Census population estimates and the 2012 ACS 5-Year (with middle year 2010) population estimates. This adjustment factor is particularly important for ZCTAs with high homeless population (not living in group quarters) where the ACS may underestimate the ZCTA population and therefore underestimate the life expectancy. The ACS provides ZIP Code population by age in five-year age intervals. Single-year age population estimates were calculated by distributing population within an age interval to single-year ages using the county distribution. Counties were assigned to ZIP Codes based on majority land-area.
ZIP Codes in the Bay Area vary in population from over 10,000 residents to less than 20 residents. Traditional life expectancy estimation (like the one used for the regional- and county-level Vital Signs estimates) cannot be used because they are highly inaccurate for small populations and may result in over/underestimation of life expectancy. To avoid inaccurate estimates, ZIP Codes with populations of less than 5,000 were aggregated with neighboring ZIP Codes until the merged areas had a population of more than 5,000. ZIP Code 94103, representing Treasure Island, was dropped from the dataset due to its small population and having no bordering ZIP Codes. In this way, the original 305 Bay Area ZIP Codes were reduced to 217 ZIP Code areas for 2013 estimates. Next, a form of Bayesian random-effects analysis was used which established a prior distribution of the probability of death at each age using the regional distribution. This prior is used to shore up the life expectancy calculations where data were sparse.
LISTOS_Ground_OuterIsland_Data is the Long Island Sound Tropospheric Ozone Study (LISTOS) ground site data collected at the Outer Island ground site during the LISTOS field campaign. This product is a result of a joint effort across multiple agencies, including NASA, NOAA, the EPA Northeast States for Coordinated Air Use Management (NESCAUM), Maine Department of Environmental Protection, New Jersey Department of Environmental Protection, New York State Department of Environmental Conservation, and several research groups at universities. Data collection is complete.The New York City (NYC) metropolitan area (comprised of portions of New Jersey, New York, and Connecticut in and around NYC) is home to over 20 million people, but also millions of people living downwind in neighboring states. This area continues to persistently have challenges meeting past and recently revised federal health-based air quality standards for ground-level ozone, which impacts the health and well-being of residents living in the area. A unique feature of this chronic ozone problem is the pollution transported in a northeast direction out of NYC over Long Island Sound. The relatively cool waters of the Long Island Sound confine the pollutants in a shallow and stable marine boundary layer. Afternoon heating over coastal land creates a sea breeze that carries the air pollution inland from the confined marine layer, resulting in high ozone concentrations in Connecticut and, at times, farther east into Rhode Island and Massachusetts. To investigate the evolving nature of ozone formation and transport in the NYC region and downwind, Northeast States for Coordinated Air Use Management (NESCAUM) launched the Long Island Sound Tropospheric Ozone Study (LISTOS). LISTOS was a multi-agency collaborative study focusing on Long Island Sound and the surrounding coastlines that continually suffer from poor air quality exacerbated by land/water circulation. The primary measurement observations took place between June-September 2018 and include in-situ and remote sensing instrumentation that were integrated aboard three aircraft, a network of ground sites, mobile vehicles, boat measurements, and ozonesondes. The goal of LISTOS was to improve the understanding of ozone chemistry and sea breeze transported pollution over Long Island Sound and its coastlines. LISTOS also provided NASA the opportunity to test air quality remote sensing retrievals with the use of its airborne simulators (GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS), and Geostationary Trace gas and Aerosol Sensory Optimization (GeoTASO)) for the preparation of the Tropospheric Emissions; Monitoring of Pollution (TEMPO) observations for monitoring air quality from space. LISTOS also helped collaborators in the validation of Tropospheric Monitoring Instrument (TROPOMI) science products, with use of airborne- and ground-based measurements of ozone, NO2, and HCHO.
The U.S. Census Bureau conducts the Island Areas Censuses in partnership with the governments of American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the U.S. Virgin Islands to comply with the legal requirements set forth in Title 13 of the United States Code and to meet the specific data needs of the Island Areas. The 2020 Island Areas Censuses counted people living in the U.S. Island Areas using a long-form questionnaire to meet the Island Areas' data needs for demographic, social, economic, and housing unit information. This long-form questionnaire was similar to the American Community Survey questionnaire used in the 50 states, the District of Columbia, and Puerto Rico. With the release of the 2020 IAC Demographic Profile, the Census Bureau provides summary statistics for the Island Areas, including selected demographic and housing characteristics for places and minor civil divisions (MCDs).
This dataset provides information about the number of properties, residents, and average property values for Long Island Drive cross streets in Eatonton, GA.
LISTOS_Ground_YaleCoastal_Data is the Long Island Sound Tropospheric Ozone Study (LISTOS) ground site data collected at the Yale Coastal ground site during the LISTOS field campaign. This product is a result of a joint effort across multiple agencies, including NASA, NOAA, the EPA Northeast States for Coordinated Air Use Management (NESCAUM), Maine Department of Environmental Protection, New Jersey Department of Environmental Protection, New York State Department of Environmental Conservation and several research groups at universities. Data collection is complete.The New York City (NYC) metropolitan area (comprised of portions of New Jersey, New York, and Connecticut in and around NYC) is home to over 20 million people, but also millions of people living downwind in neighboring states. This area continues to persistently have challenges meeting past and recently revised federal health-based air quality standards for ground-level ozone, which impacts the health and well-being of residents living in the area. A unique feature of this chronic ozone problem is the pollution transported in a northeast direction out of NYC over Long Island Sound. The relatively cool waters of Long Island Sound confine the pollutants in a shallow and stable marine boundary layer. Afternoon heating over coastal land creates a sea breeze that carries the air pollution inland from the confined marine layer, resulting in high ozone concentrations in Connecticut and, at times, farther east into Rhode Island and Massachusetts. To investigate the evolving nature of ozone formation and transport in the NYC region and downwind, Northeast States for Coordinated Air Use Management (NESCAUM) launched the Long Island Sound Tropospheric Ozone Study (LISTOS). LISTOS was a multi-agency collaborative study focusing on Long Island Sound and the surrounding coastlines that continually suffer from poor air quality exacerbated by land/water circulation. The primary measurement observations took place between June-September 2018 and include in-situ and remote sensing instrumentation that were integrated aboard three aircraft, a network of ground sites, mobile vehicles, boat measurements, and ozonesondes. The goal of LISTOS was to improve the understanding of ozone chemistry and sea breeze transported pollution over Long Island Sound and its coastlines. LISTOS also provided NASA the opportunity to test air quality remote sensing retrievals with the use of its airborne simulators (GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS), and Geostationary Trace gas and Aerosol Sensory Optimization (GeoTASO)) for the preparation of the Tropospheric Emissions; Monitoring of Pollution (TEMPO) observations for monitoring air quality from space. LISTOS also helped collaborators in the validation of Tropospheric Monitoring Instrument (TROPOMI) science products, with use of airborne- and ground-based measurements of ozone, NO2, and HCHO.
This dataset provides information about the number of properties, residents, and average property values for Buffalo Road cross streets in Long Island, VA.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Understanding population structure and areas of demographic persistence and transients is critical for effective species management. However, direct observational evidence to address the geographic scale and delineation of ephemeral or persistent populations for many marine fishes is limited. The Lined seahorse (Hippocampus erectus) can be commonly found in three western Atlantic zoogeographic provinces, though inhabitants of the temperate northern Virginia Province are often considered tropical vagrants that only arrive during warm seasons from the southern provinces and perish as temperatures decline. Although genetics can locate regions of historical population persistence and isolation, previous evidence of Virginia Province persistence is only provisional due to limited genetic sampling (i.e., mitochondrial DNA and five nuclear loci). To test alternative hypotheses of historical persistence versus the ephemerality of a northern Virginia Province population we used a RADseq generated dataset consisting of 11,708 single nucleotide polymorphisms (SNP) sampled from individuals collected from the eastern Gulf of Mexico to Long Island, NY. Concordant results from genomic analyses all infer three genetically divergent subpopulations, and strongly support Virginia Province inhabitants as a genetically diverged and a historically persistent ancestral gene pool. These results suggest that individuals that emerge in coastal areas during the warm season can be considered “local” and supports offshore migration during the colder months. This research demonstrates how a large number of genes sampled across a geographical range can capture the diversity of coalescent histories (across loci) while inferring population history. Moreover, these results clearly demonstrate the utility of population genomic data to infer peripheral subpopulation persistence in difficult-to-observe species.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset contains measurements from a laboratory mesocosm experiment (Oct 2022 to Apr 2023) with adult Black Sea Bass (Centropristis striata) collected in Long Island Sound. Fish in this experiment were collected concurrently with fish sampled for a related wild-caught dataset (see 'Related Datasets' section).
Study description:
We experimentally examined overwintering potential of adult Black Sea Bass (Centropristis striata), an ecologically and economically important fish that seasonally migrates from offshore overwintering grounds to coastal feeding and nursery areas. We collected adults from Long Island Sound in September 2022 and reared them in a laboratory-mesocosm experiment under a contemporary seasonal temperature profile for Long Island Sound (LIS; October 2022 – April 2023) to assess their potential to survive and accumulate lipids throughout the winter. We also fed experimental adults two diet items (blue mussels and Atlantic herring), which are commonly found in Long Island Sound.
In addition, we sampled fish from the same reef in LIS at the start (October) and end (April) of the experiment to identify lipid dynamics in wild fish that migrate offshore (see "Related Datasets" section for wild fish data). Experimental C. striata growth throughout the winter was negligible with high mortality (> 50% observed).
While survivors fed herring had higher tissue lipid contents, mortality was 2x higher than for fish fed mussels. In contrast, to the experimental fish, wild-captured fish in the spring had higher gonadosmatic indices than that for survivors across both diet treatments, which was most similar to fall-captured fish. While some fish survived throughout the winter, current winter bottom temperatures still preclude a year-round C. striata presence within Long Island Sound. Overwintering inshore is still disadvantageous compared to seasonally migrating due to surviving experimental fish having lower gonadosomatic indices, suggesting that the offshore overwintering period is a time to build energy reserves. However, as coastal waters continue to warm, changing conditions could lead populations to become year-round residents of Long Island Sound, thus increasing C. striata abundance.
The U.S. Census Bureau conducts the Island Areas Censuses in partnership with the governments of American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the U.S. Virgin Islands to comply with the legal requirements set forth in Title 13 of the United States Code and to meet the specific data needs of the Island Areas. The 2020 Island Areas Censuses counted people living in the U.S. Island Areas using a long-form questionnaire to meet the Island Areas' data needs for demographic, social, economic, and housing unit information. This long-form questionnaire was similar to the American Community Survey questionnaire used in the 50 states, the District of Columbia, and Puerto Rico. With the release of the 2020 IAC Demographic Profile, the Census Bureau provides summary statistics for the Island Areas, including selected demographic and housing characteristics for places and minor civil divisions (MCDs).
LISTOS_Ground_Rutgers_Data is the Long Island Sound Tropospheric Ozone Study (LISTOS) Rutgers ground site data collected during the LISTOS field campaign. This product is a result of a joint effort across multiple agencies, including NASA, NOAA, the EPA Northeast States for Coordinated Air Use Management (NESCAUM), Maine Department of Environmental Protection, New Jersey Department of Environmental Protection, New York State Department of Environmental Conservation and several research groups at universities. Data collection is complete.The New York City (NYC) metropolitan area (comprised of portions of New Jersey, New York, and Connecticut in and around NYC) is home to over 20 million people, but also millions of people living downwind in neighboring states. This area continues to persistently have challenges meeting past and recently revised federal health-based air quality standards for ground-level ozone, which impacts the health and well-being of residents living in the area. A unique feature of this chronic ozone problem is the pollution transported in a northeast direction out of NYC over Long Island Sound. The relatively cool waters of Long Island Sound confine the pollutants in a shallow and stable marine boundary layer. Afternoon heating over coastal land creates a sea breeze that carries the air pollution inland from the confined marine layer, resulting in high ozone concentrations in Connecticut and, at times, farther east into Rhode Island and Massachusetts. To investigate the evolving nature of ozone formation and transport in the NYC region and downwind, Northeast States for Coordinated Air Use Management (NESCAUM) launched the Long Island Sound Tropospheric Ozone Study (LISTOS). LISTOS was a multi-agency collaborative study focusing on Long Island Sound and the surrounding coastlines that continually suffer from poor air quality exacerbated by land/water circulation. The primary measurement observations took place between June-September 2018 and include in-situ and remote sensing instrumentation that were integrated aboard three aircraft, a network of ground sites, mobile vehicles, boat measurements, and ozonesondes. The goal of LISTOS was to improve the understanding of ozone chemistry and sea breeze transported pollution over Long Island Sound and its coastlines. LISTOS also provided NASA the opportunity to test air quality remote sensing retrievals with the use of its airborne simulators (GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS), and Geostationary Trace gas and Aerosol Sensory Optimization (GeoTASO)) for the preparation of the Tropospheric Emissions; Monitoring of Pollution (TEMPO) observations for monitoring air quality from space. LISTOS also helped collaborators in the validation of Tropospheric Monitoring Instrument (TROPOMI) science products, with use of airborne- and ground-based measurements of ozone, NO2, and HCHO.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the median household income across different racial categories in Long Island town. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.
Key observations
Based on our analysis of the distribution of Long Island town population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 88.33% of the total residents in Long Island town. Notably, the median household income for White households is $88,125. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $88,125.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Long Island town median household income by race. You can refer the same here
LISTOS_Ground_Westport_Data is the Long Island Sound Tropospheric Ozone Study (LISTOS) Wesport ground site data collected during the LISTOS field campaign. This product is a result of a joint effort across multiple agencies, including NASA, NOAA, the EPA Northeast States for Coordinated Air Use Management (NESCAUM), Maine Department of Environmental Protection, New Jersey Department of Environmental Protection, New York State Department of Environmental Conservation and several research groups at universities. Data collection is complete.The New York City (NYC) metropolitan area (comprised of portions of New Jersey, New York, and Connecticut in and around NYC) is home to over 20 million people, but also millions of people living downwind in neighboring states. This area continues to persistently have challenges meeting past and recently revised federal health-based air quality standards for ground-level ozone, which impacts the health and well-being of residents living in the area. A unique feature of this chronic ozone problem is the pollution transported in a northeast direction out of NYC over Long Island Sound. The relatively cool waters of Long Island Sound confine the pollutants in a shallow and stable marine boundary layer. Afternoon heating over coastal land creates a sea breeze that carries the air pollution inland from the confined marine layer, resulting in high ozone concentrations in Connecticut and, at times, farther east into Rhode Island and Massachusetts. To investigate the evolving nature of ozone formation and transport in the NYC region and downwind, Northeast States for Coordinated Air Use Management (NESCAUM) launched the Long Island Sound Tropospheric Ozone Study (LISTOS). LISTOS was a multi-agency collaborative study focusing on Long Island Sound and the surrounding coastlines that continually suffer from poor air quality exacerbated by land/water circulation. The primary measurement observations took place between June-September 2018 and include in-situ and remote sensing instrumentation that were integrated aboard three aircraft, a network of ground sites, mobile vehicles, boat measurements, and ozonesondes. The goal of LISTOS was to improve the understanding of ozone chemistry and sea breeze transported pollution over Long Island Sound and its coastlines. LISTOS also provided NASA the opportunity to test air quality remote sensing retrievals with the use of its airborne simulators (GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS), and Geostationary Trace gas and Aerosol Sensory Optimization (GeoTASO)) for the preparation of the Tropospheric Emissions; Monitoring of Pollution (TEMPO) observations for monitoring air quality from space. LISTOS also helped collaborators in the validation of Tropospheric Monitoring Instrument (TROPOMI) science products, with use of airborne- and ground-based measurements of ozone, NO2, and HCHO.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Non-Hispanic population of Long Island town by race. It includes the distribution of the Non-Hispanic population of Long Island town across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Long Island town across relevant racial categories.
Key observations
Of the Non-Hispanic population in Long Island town, the largest racial group is White alone with a population of 263 (92.28% of the total Non-Hispanic population).
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Long Island town Population by Race & Ethnicity. You can refer the same here