Relative concentration of the estimated number of people in the Sierra Nevada region that live in a household defined as "low income." There are multiple ways to define low income. These data apply the most common standard: low income population consists of all members of households that collectively have income less than twice the federal poverty threshold that applies to their household type. Household type refers to the household's resident composition: the number of independent adults plus dependents that can be of any age, from children to elderly. For example, a household with four people ' one working adult parent and three dependent children ' has a different poverty threshold than a household comprised of four unrelated independent adults.

Due to high estimate uncertainty for many block group estimates of the number of people living in low income households, some records cannot be reliably assigned a class and class code comparable to those assigned to race/ethnicity data from the decennial Census.

"Relative concentration" is a measure that compares the proportion of population within each Census block group data unit to the proportion of all people that live within the 775 block groups in the Sierra Nevada RRK region. See the "Data Units" description below for how these relative concentrations are broken into categories in this "low income" metric.

Relative concentration of the estimated number of people in the Southern California region that live in a household defined as "low income." There are multiple ways to define low income. These data apply the most common standard: low income population consists of all members of households that collectively have income less than twice the federal poverty threshold that applies to their household type. Household type refers to the household's resident composition: the number of independent adults plus dependents that can be of any age, from children to elderly. For example, a household with four people ' one working adult parent and three dependent children ' has a different poverty threshold than a household comprised of four unrelated independent adults.

Due to high estimate uncertainty for many block group estimates of the number of people living in low income households, some records cannot be reliably assigned a class and class code comparable to those assigned to race/ethnicity data from the decennial Census.

"Relative concentration" is a measure that compares the proportion of population within each Census block group data unit to the proportion of all people that live within the 13,312 block groups in the Southern California RRK region. See the "Data Units" description below for how these relative concentrations are broken into categories in this "low income" metric.

Time series data for the statistic Population_Exposed_To_Polluted_Air_In_Percent and country Djibouti. Indicator Definition:Percent of population exposed to ambient concentrations of PM2.5 that exceed the WHO guideline value is defined as the portion of a country’s population living in places where mean annual concentrations of PM2.5 are greater than 10 micrograms per cubic meter, the guideline value recommended by the World Health Organization as the lower end of the range of concentrations over which adverse health effects due to PM2.5 exposure have been observed.

This dataset contains information about annual estimates of fine particulate matter (PM2.5) concentrations and trends beginning in 1998. PM2.5 refers to airborne particulate matter less than 2.5 µm in diameter; comprises several chemical and particulate constituents, including nitrate, ammonium, elemental carbons, organic carbons, silicon and sodium ions and dust, and originates from a variety of sources, including vehicle exhaust, forest fires, and industrial processes. Exposure to PM2.5 is a leading environmental risk factor for mortality and the global burden of disease.

Global and regional PM2.5 concentrations are estimated using a combination of satellite observations, chemical transport modeling, and ground-based monitoring. Annual and coarse-resolution averages correspond to a simple mean of within-grid values. Gridded datasets are provided to allow users to agglomerate data as best meets their particular needs.

Annual and monthly datasets are provided in NetCDF [.nc] format, with naming convention V6GL02.02.CNNPM25.REGION.YYYYMM_START-YYYYMM_END.nc. REGION refers to the file region (e.g. ‘Global’). YYYYMM_START and YYYYMM_END refer to the numeric start and end date of the file (e.g. for annual mean PM2.5 for 2015, YYYYMM_START is 201501 and YYYYMM_END is 201512). Gridded files use the WGS84 projection.

Variable names within these files include "lat" (latitude coordinate centers of the PM2.5 grid, "lon" (longitude coordinates centers of the PM2.5 grid), and "PM25" (gridded mean PM2.5 concentrations).

Processed summary files are available for annual global country-level means, Canada provincial-level means, China and India regional-level means, and US state-level means. Population-weighted estimates and total population describe only those people covered by the V6.GL.02.02 dataset and are provided by Gridded Population of the World, version 4 (GPWv4). Country borders are defined following the Database of Global Administrative Areas, version 3.6 (GAD3.6).

Time series data for the statistic Population_Exposed_To_Polluted_Air_In_Percent and country West Bank and Gaza. Indicator Definition:Percent of population exposed to ambient concentrations of PM2.5 that exceed the WHO guideline value is defined as the portion of a country’s population living in places where mean annual concentrations of PM2.5 are greater than 10 micrograms per cubic meter, the guideline value recommended by the World Health Organization as the lower end of the range of concentrations over which adverse health effects due to PM2.5 exposure have been observed.

Rationale:Air pollution consists of many pollutants, among other particulate matter. These particles are able to penetrate deeply into the respiratory tract and therefore constitute a risk for health by increasing mortality from respiratory infections and diseases, lung cancer, and selected cardiovascular diseases. Definition: The mean annual concentration of fine suspended particles of less than 2.5 microns in diameters is a common measure of air pollution. The mean is a population-weighted average for urban population in a country. Method of measurement: Concentration of PM2.5 are regularly measured from fixed-site,
population-oriented monitors located within the metropolitan areas. High-quality measurements of PM concentration from all the monitors in the metropolitan area can be averaged to develop a single estimate. Method of estimation: Although PM is measured at many thousands of locations throughout the world, the amount of monitors in different geographical areas vary, with some areas having little or no monitoring. In order to produce global estimates at high resolution (0.1◦ grid‐cells), additional data is required. Annual urban mean concentration of PM2.5 is estimated with improved modelling using data integration from satellite remote sensing, population estimates, topography and ground measurements.

Time series data for the statistic Population_Exposed_To_Polluted_Air_In_Percent and country Kenya. Indicator Definition:Percent of population exposed to ambient concentrations of PM2.5 that exceed the WHO guideline value is defined as the portion of a country’s population living in places where mean annual concentrations of PM2.5 are greater than 10 micrograms per cubic meter, the guideline value recommended by the World Health Organization as the lower end of the range of concentrations over which adverse health effects due to PM2.5 exposure have been observed.

A new component of fair housing studies is an analysis of the opportunities residents are afforded in “racially or ethnically concentrated areas of poverty,” also called RCAPs or ECAPs. An RCAP or ECAP is a neighborhood with significant concentrations of extreme poverty and minority populations. HUD’s definition of an RCAP/ECAP is: • A Census tract that has a non‐white population of 50 percent or more AND a poverty rate of 40 percent or more; OR • A Census tract that has a non‐white population of 50 percent or more AND the poverty rate is three times the average tract poverty rate for the metro/micro area, whichever is lower.

Why the 40 percent threshold? The RCAP/ECAP definition is not meant to suggest that a slightly‐lower‐than‐40 percent poverty rate is ideal or acceptable. The threshold was borne out of research that concluded a 40 percent poverty rate was the point at which a neighborhood became significantly socially and economically challenged. Conversely, research has shown that areas with up to 14 percent of poverty have no noticeable effect on community opportunity. (See Section II in City of Austin’s 2015 Analysis of Impediments to Fair Housing Choice: http://www.austintexas.gov/sites/default/files/files/NHCD/Reports_Publications/1Analysis_Impediments_for_web.pdf)

This dataset provides socioeconomic data on protected classes from the 2008-2012 American Community Survey on census tracts in Austin’s city limits and designates which of those tracts are considered RCAPs or ECAPs based on these socioeconomic characteristics. A map of the census tracts designated as RCAPs or ECAPs is attached to this dataset and downloadable as a pdf (see below).

To assist communities in identifying racially/ethnically-concentrated areas of poverty (R/ECAPs), HUD has developed a census tract-based definition of R/ECAPs. The definition involves a racial/ethnic concentration threshold and a poverty test. The racial/ethnic concentration threshold is straightforward: R/ECAPs must have a non-white population of 50 percent or more. Regarding the poverty threshold, Wilson (1980) defines neighborhoods of extreme poverty as census tracts with 40 percent or more of individuals living at or below the poverty line. Because overall poverty levels are substantially lower in many parts of the country, HUD supplements this with an alternate criterion. Thus, a neighborhood can be a R/ECAP if it has a poverty rate that exceeds 40% or is three or more times the average tract poverty rate for the metropolitan/micropolitan area, whichever threshold is lower. Census tracts with this extreme poverty that satisfy the racial/ethnic concentration threshold are deemed R/ECAPs. This translates into the following equation: Where i represents census tracts, () is the metropolitan/micropolitan (CBSA) mean tract poverty rate, is the ith tract poverty rate, () is the non-Hispanic white population in tract i, and Pop is the population in tract i.While this definition of R/ECAP works well for tracts in CBSAs, place outside of these geographies are unlikely to have racial or ethnic concentrations as high as 50 percent. In these areas, the racial/ethnic concentration threshold is set at 20 percent.

Data Source: American Community Survey (ACS), 2009-2013; Decennial Census (2010); Brown Longitudinal Tract Database (LTDB) based on decennial census data, 1990, 2000 & 2010.

Related AFFH-T Local Government, PHA Tables/Maps: Table 4, 7; Maps 1-17. Related AFFH-T State Tables/Maps: Table 4, 7; Maps 1-15, 18.

References:Wilson, William J. (1980). The Declining Significance of Race: Blacks and Changing American Institutions. Chicago: University of Chicago Press.

To learn more about R/ECAPs visit:https://www.hud.gov/program_offices/fair_housing_equal_opp/affh ; https://www.hud.gov/sites/dfiles/FHEO/documents/AFFH-T-Data-Documentation-AFFHT0006-July-2020.pdf, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Date of Coverage: 11/2017

Based on the background of urbanization in China, we used the dynamic spatial panel Durbin model to study the driving mechanism of ozone pollution empirically. We also analyzed the spatial distribution of ozone driving factors using the GTWR. The results show that: i) The average annual increase of ozone concentration in ambient air in China from 2015 to 2019 was 1.68μg/m3, and 8.39μg/m3 elevated the year 2019 compared with 2015. ii) The Moran’s I value of ozone in ambient air was 0.027 in 2015 and 0.209 in 2019, showing the spatial distribution characteristics of "east heavy and west light" and "south low and north high". iii) Per capita GDP industrial structure, population density, land expansion, and urbanization rate have significant spillover effects on ozone concentration, and the regional spillover effect is greater than the local effect. R&D intensity and education level have a significant negative impact on ozone concentration. iv) There is a decreasing trend in the inhibitory effect of educational attainment and R&D intensity on ozone concentration, and an increasing trend in the promotional effect of population urbanization rate, land expansion, and economic development on ozone concentration. Empirical results suggest a twofold policy meaning: i) to explore the causes behind the distribution of ozone from the new perspective of urbanization, and to further the atmospheric environmental protection system and ii) to eliminate the adverse impacts of ozone pollution on nature and harmonious social development.

Time series data for the statistic Population_Exposed_To_Polluted_Air_In_Percent and country Cuba. Indicator Definition:Percent of population exposed to ambient concentrations of PM2.5 that exceed the WHO guideline value is defined as the portion of a country’s population living in places where mean annual concentrations of PM2.5 are greater than 10 micrograms per cubic meter, the guideline value recommended by the World Health Organization as the lower end of the range of concentrations over which adverse health effects due to PM2.5 exposure have been observed.The statistic "Population Exposed To Polluted Air In Percent" stands at 100.00 percent as of 12/31/2017, the lowest value since 12/31/2012. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -1E-13 percentage points compared to the value the year prior.The 1 year change in percentage points is -1E-13.The 3 year change in percentage points is 0.0.The 5 year change in percentage points is 0.0.

Time series data for the statistic Population_Exposed_To_Polluted_Air_In_Percent and country Slovak Republic. Indicator Definition:Percent of population exposed to ambient concentrations of PM2.5 that exceed the WHO guideline value is defined as the portion of a country’s population living in places where mean annual concentrations of PM2.5 are greater than 10 micrograms per cubic meter, the guideline value recommended by the World Health Organization as the lower end of the range of concentrations over which adverse health effects due to PM2.5 exposure have been observed.

Time series data for the statistic Population_Exposed_To_Polluted_Air_In_Percent and country Eritrea. Indicator Definition:Percent of population exposed to ambient concentrations of PM2.5 that exceed the WHO guideline value is defined as the portion of a country’s population living in places where mean annual concentrations of PM2.5 are greater than 10 micrograms per cubic meter, the guideline value recommended by the World Health Organization as the lower end of the range of concentrations over which adverse health effects due to PM2.5 exposure have been observed.

Time series data for the statistic Population_Exposed_To_Polluted_Air_In_Percent and country Costa Rica. Indicator Definition:Percent of population exposed to ambient concentrations of PM2.5 that exceed the WHO guideline value is defined as the portion of a country’s population living in places where mean annual concentrations of PM2.5 are greater than 10 micrograms per cubic meter, the guideline value recommended by the World Health Organization as the lower end of the range of concentrations over which adverse health effects due to PM2.5 exposure have been observed.The statistic "Population Exposed To Polluted Air In Percent" stands at 99.69 percent as of 12/31/2017, the lowest value at least since 12/31/1991, the period currently displayed. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -0.0283 percentage points compared to the value the year prior.The 1 year change in percentage points is -0.0283.The 3 year change in percentage points is -0.3112.The 5 year change in percentage points is -0.3112.The Serie's long term average value is 99.95 percent. It's latest available value, on 12/31/2017, is 0.26 percentage points lower, compared to it's long term average value.The Serie's change in percentage points from it's minimum value, on 12/31/2017, to it's latest available value, on 12/31/2017, is +0.0.The Serie's change in percentage points from it's maximum value, on 12/31/2011, to it's latest available value, on 12/31/2017, is -0.311.

The subjective assessment of cognitive health follows the international consensus in the field of subjective cognitive decline research, and a subjective cognitive decline scale (SCD-10) with multiple cognitive domains and assisted by life examples is developed for evaluation. The cognitive domains evaluated by the subjective cognitive decline scale include four main dimensions: memory, attention, executive function, and speech function. 1) Memory: It includes three sub cognitive domains: delayed recall, immediate recall, and prospective memory. The specific operational definitions are as follows. Delayed recall: able to recall details of recent daily events (shopping, socializing, eating, taking medication). Immediate memory: Being able to remember what just happened and what has just been learned. Prospective memory: refers to the memory of completing an activity at an appropriate time in the future, which can be based on time or events. Emphasize the ability to remember and execute this activity at the appropriate time or event. 2) Attention: It includes two sub cognitive domains: attention concentration and attention allocation, with specific operational definitions as follows. Attention concentration: When focusing on a daily cognitive activity, attention can be maintained on the task for a certain period of time, and is not easily disturbed by external things, thus achieving good performance in cognitive activities. Attention allocation: Being able to pay attention to two or more stimuli at the same time, or allocate attention to different tasks. 3) Executive function: It includes three sub cognitive domains: plan organization, task initiation, and cognitive flexibility. The specific operational definitions are as follows. Planning organization: able to predict, arrange, and handle daily cognitive activities such as travel, meal preparation, financial management, and socializing, ensuring that these tasks can be completed smoothly. Task initiation: Start doing a difficult task according to the predetermined plan. Cognitive flexibility: In the process of problem-solving, one can be aware of the controllability of difficult situations and the selectivity of behavior. 4) Speech function: It includes two sub cognitive domains: delayed recall, immediate recall, and prospective memory. The specific operational definitions are as follows. Language understanding: In the process of language perception, one can accurately understand the meaning of words and texts. Verbal expression: In the process of speech generation, the ability to express oneself with accurate vocabulary and smooth grammar and syntax. This dataset is sourced from a cognitive health survey conducted on the elderly population in February 2022. This survey was published online by Questionnaire Star. A total of 611 cases of data were collected during the survey. The content of this dataset includes demographic information (such as age, gender, education level, etc.) and subjective cognitive decline.

Ozone concentration and urbanization level in China, 2015–2019.

Time series data for the statistic Population_Exposed_To_Polluted_Air_In_Percent and country Burundi. Indicator Definition:Percent of population exposed to ambient concentrations of PM2.5 that exceed the WHO guideline value is defined as the portion of a country’s population living in places where mean annual concentrations of PM2.5 are greater than 10 micrograms per cubic meter, the guideline value recommended by the World Health Organization as the lower end of the range of concentrations over which adverse health effects due to PM2.5 exposure have been observed.

The file contains three files in comma separated values (.csv) format. “Reyes_EHP_Phthalates_US_metabolites.csv” contains information about the National Health and Nutrition Examination Survey (NHANES) metabolite code names along with Tolerable Daily Intake (TDI), molecular weight of the parent phthalate, molecular weight of the metabolite, and names and abbreviations of the corresponding metabolites and phthalates. “Reyes_EHP_Phthalates_US_MCR.csv” contains the following information: • Data on the surveyed individuals from the original NHANES data files that includes • Identifying information for individual; • Demographic information used in defining the creatinine levels and in investigating sub populations based on age, gender, ethnicity; • Concentration of phthalate metabolites and creatinine in urine. • Calculated values for each individual; • Daily intake of each of the six phthalate; • Hazard Quotients associated with each phthalate’s daily intake; • Values of Hazard Index and the Maximum Cumulative Ratio. “Reyes_EHP_Phthalates_US_MCR_definitions.csv” and the definitions and units of the fields in “Reyes_EHP_Phthalates_US_MCR.csv”. This dataset is associated with the following publication: Reyes, J., and P. Price. An analysis of cumulative risks based on biomonitoring data for six phthalates using the Maximum Cumulative Ratio. ENVIRONMENT INTERNATIONAL. Elsevier B.V., Amsterdam, NETHERLANDS, 112: 77-84, (2018).

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) System (MTS). The MTS represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The TIGER/Line shapefiles include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state but may extend across county and county subdivision boundaries. An incorporated place is usually a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs are often defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The boundaries of most incorporated places in this shapefile are as of January 1, 2024, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CDPs were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census, but some CDPs were added or updated through the 2024 BAS as well.

Time series data for the statistic Population_Exposed_To_Polluted_Air_In_Percent and country Cabo Verde. Indicator Definition:Percent of population exposed to ambient concentrations of PM2.5 that exceed the WHO guideline value is defined as the portion of a country’s population living in places where mean annual concentrations of PM2.5 are greater than 10 micrograms per cubic meter, the guideline value recommended by the World Health Organization as the lower end of the range of concentrations over which adverse health effects due to PM2.5 exposure have been observed.