North America registered the highest mobile data consumption per connection in 2023, with the average connection consuming ** gigabytes per month. This figure is set to triple by 2030, driven by the adoption of data intensive activities such as 4K streaming.

In 2022, the average data used per smartphone per month worldwide amounted to ** gigabytes (GB). The source forecasts that this will increase almost four times reaching ** GB per smartphone per month globally in 2028.

A line chart that shows % of U.S. adults who say they use the internet

A line chart that shows % of U.S. adults who say they use the internet, by age

As of February 2025, the average daily social media usage of internet users worldwide amounted to 141 minutes per day, down from 143 minutes in the previous year. Currently, the country with the most time spent on social media per day is Brazil, with online users spending an average of 3 hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in the U.S. was just 2 hours and 16 minutes. Global social media usage Currently, the global social network penetration rate is 62.3 percent. Northern Europe had an 81.7 percent social media penetration rate, topping the ranking of global social media usage by region. Eastern and Middle Africa closed the ranking with 10.1 and 9.6 percent usage reach, respectively. People access social media for a variety of reasons. Users like to find funny or entertaining content and enjoy sharing photos and videos with friends, but mainly use social media to stay in touch with current events and friends. Global impact of social media Social media has a wide-reaching and significant impact on not only online activities but also offline behavior and life in general. During a global online user survey in February 2019, a significant share of respondents stated that social media had increased their access to information, ease of communication, and freedom of expression. On the flip side, respondents also felt that social media had worsened their personal privacy, increased polarization in politics, and heightened everyday distractions.

Files contain 5000 samples of AWARE characterization factors, as well as sampled independent data used in their calculations and selected intermediate results.

AWARE is a consensus-based method development to assess water use in LCA. It was developed by the WULCA UNEP/SETAC working group. Its characterization factors represent the relative Available WAter REmaining per area in a watershed, after the demand of humans and aquatic ecosystems has been met. It assesses the potential of water deprivation, to either humans or ecosystems, building on the assumption that the less water remaining available per area, the more likely another user will be deprived.

The code used to generate the samples can be found here: https://github.com/PascalLesage/aware_cf_calculator/

Samples were updated from v1.0 in 2020 to include model uncertainty associated with the choice of WaterGap as the global hydrological model (GHM).

The following datasets are supplied:

1) AWARE_characterization_factor_samples.zip

Actual characterization factors resulting from the Monte Carlo Simulation. Contains 4 zip files:

* monthly_cf.zip: contains 116,484 arrays of 5000 monthly characterization factor samples for each of 9707 watershed and for each month, in csv format. Names are cf_.csv, where is the watershed id and is the first three letters of the month ('jan', 'feb', etc.).


* average_agri_cf.zip: contains 9707 arrays of 5000 annual average, agricultural use, characterization factor samples for each watershed, in csv format. Names are cf_average_agri_.csv.


* average_non_agri_cf.zip: contains 9707 arrays of 5000 annual average, non-agricultural use, characterization factor samples for each watershed, in csv format. Names are cf_average_non_agri_.csv.


* average_unknown_cf.zip: contains 9707 arrays of 5000 annual average, unspecified use, characterization factor samples for each watershed, in csv format. Names are cf_average_unknown_.csv..

2) AWARE_base_data.xlsx

Excel file with the deterministic data, per watershed and per month, for each of the independent variables used in the calculation of AWARE characterization factors. Specifically, it includes:

  Monthly irrigation
    Description: irrigation water, per month, per basin
    Unit: m3/month
    Location in Excel doc: Irrigation
    File name once imported: irrigation.pickle
    table shape: (11050, 12)


  Non-irrigation hwc: electricity, domestic, livestock, manufacturing
    Description: non-irrigation uses of water
    Unit: m3/year
    Location in Excel doc: hwc_non_irrigation
    File name once imported: electricity.pickle, domestic.pickle,
      livestock.pickle, manufacturing.pickle
    table shape: 3 x (11050,)


  avail_delta
    Description: Difference between "pristine" natural availability
      reported in PastorXNatAvail and natural availability calculated
      from "Actual availability as received from WaterGap - after
      human consumption" (Avail!W:AH) plus HWC.
      This should be added to calculated water availability to
      get the water availability used for the calculation of EWR
    Unit: m3/month
    Location in Excel doc: avail_delta
    File name once imported: avail_delta.pickle
    table shape: (11050, 12)


  avail_net
    Description: Actual availability as received from WaterGap - after human consumption
    Unit: m3/month
    Location in Excel doc: avail_net
    File name once imported: avail_net.pickle
    table shape: (11050, 12)


  pastor
    Description: fraction of PRISTINE water availability that should be reserved for environment
    Unit: unitless
    Location in Excel doc: pastor
    File name once imported: pastor.pickle
    table shape: (11050, 12)


  area
    Description: area
    Unit: m2
    Location in Excel doc: area
    File name once imported: area.pickle
    table shape: (11050,)

It also includes:

• information (k values) on the distributions used for each variable (uncertainty tab)

• information (k values) on the model uncertainty (model uncertainty tab)

• two filters used to exclude watersheds that are either in Greenland (polar filter) or without data from the Pastor et al. (2014) method (122 cells), representing small coastal cells with no direct overlap (pastor filter). (filters tab)

3) independent_variable_samples.zip

Samples for each of the independent variables used in the calculation of characterization factors. Only random variables are contained. For all watershed or watershed-months without samples, the Monte Carlo simulation used the deterministic values found in the AWARE_base_data.xlsx file.

The files are in csv format. The first column contains the watershed id (BAS34S_ID) if the data is annual or the (BAS34S_ID, month) for data with a monthly resolution. the other 5000 columns contain the sampled data.

The names of the files are .

4) intermediate_variables.zip

Contains results of intermediate calculations, used in the calculation of characterization factors. The zip file contains 3 zip files:

* AMD_world_over_AMD_i.zip: contains 116,484 arrays (for each watershed-month) of 5000 calculated values of the ratio between the AMD (Availability Minus Demand) for the watershed-month and AMD_glo, the world weighted AMD average. Format is csv.
* AMD_world.zip: contains one array of 5000 calculated values of the world average AMD. Format is csv.


* HWC.zip: contains 116,484 arrays (for each watershed-month) of 5000 calculated values of the total Human Water Consumption. Format is csv.

5) watershedBAS34S_ID.zip

Contains the GIS files to link the watershed ids (BAS34S_ID) to actual spatial data.

A line chart that shows % of U.S. adults who say they use the internet, by annual household income

Source

https://ourworldindata.org/grapher/per-capita-electricity-consumption

Key information about Russia Household Income per Capita

• Russia Annual Household Income per Capita reached 10,736.434 USD in Dec 2025, compared with the previous value of 8,292.703 USD in Dec 2024.
• Russia Annual Household Income per Capita data is updated yearly, available from Dec 1992 to Dec 2025, with an averaged value of 7,177.112 USD.
• The data reached an all-time high of 10,736.434 USD in Dec 2025 and a record low of 183.584 USD in Dec 1992.
• In the latest reports, Retail Sales of Russia grew 3.900 % YoY in Dec 2025.

CEIC calculates Annual Household Income per Capita from Monthly Average Household Income per Capita multiplied by 12 and converts it into USD. Federal State Statistics Service provides Average Household Income per Capita in local currency. The Bank of Russia average market exchange rate is used for currency conversions.

🌊 Global Water Consumption Dataset - Column Description 💧

📌 About the Dataset:

This dataset provides insights into global water consumption trends, focusing on agriculture, industrial, and household water usage across different countries over multiple years. 🌎

It helps in analyzing water scarcity levels, groundwater depletion rates, and the impact of rainfall on water availability. ☔💦

🗂️ Column Description:

Column Name	Description
🌍 Country	Name of the country.
📅 Year	Year of data collection.
💧 Total Water Consumption (Billion Cubic Meters)	Total volume of water consumed in the country in a given year.
🚰 Per Capita Water Use (Liters per Day)	Average water usage per person per day in liters.
🚨 Water Scarcity Level	The level of water scarcity (e.g., Low, Moderate, High).
🌾 Agricultural Water Use (%)	Percentage of total water consumption used for agricultural purposes.
🏭 Industrial Water Use (%)	Percentage of total water consumption used for industrial purposes.
🏠 Household Water Use (%)	Percentage of total water consumption used for household purposes.
☔ Rainfall Impact (Annual Precipitation in mm)	Annual precipitation in millimeters and its impact on water availability.
🛑 Groundwater Depletion Rate (%)	The rate at which groundwater is being depleted.

✅ Cleaned Data:

• Duplicate entries for the same Country-Year combination have been removed. 🗑️
• Aggregation was done by taking the mean of numeric values for consistency. 📊

Graph and download economic data for Average Hours of Work Per Week, Total, Household Survey for United States (M08354USM310NNBR) from Jan 1947 to Jan 1970 about hours, household survey, labor, and USA.

Humans need food, shelter, and water to survive. Our planet provides the resources to help fulfill these needs and many more. But exactly how much of an impact are we making on our planet? And will we reach a point at which the Earth can no longer support our growing population?Just like a bank account tracks money spent and earned, the relationship between human consumption of resources and the number of resources the Earth can supply—our human footprint—can be measured. Our human footprint can be calculated for an individual, town, or country, and quantifies the intensity of human pressures on the environment. The Human Footprint map layer is designed to do this by deriving a value representing the magnitude of the human footprint per one square kilometer (0.39 square miles) for every biome.This map layer was created by scientists with data from NASA's Socioeconomic Data and Applications Center to highlight where human pressures are most extreme in hopes to reduce environmental damage. The Human Footprint map asks the question, where are the least influenced, most “wild” parts of the world?The Human Footprint map was produced by combining thirteen global data layers that spatially visualize what is presumed to be the most prominent ways humans influence the environment. These layers include human population pressure (population density), human land use and infrastructure (built-up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). Based on the amount of overlap between layers, each square kilometer value is scaled between zero and one for each biome. Meaning that if an area in a Moist Tropical Forest biome scored a value of one, that square kilometer of land is part of the one percent least influenced/most wild area in its biome. Knowing this, we can help preserve the more wild areas in every biome, while also highlighting where to start mitigating human pressures in areas with high human footprints.So how can you reduce your individual human footprint? Here are just a few ways:Recycle: Recycling helps conserve resources, reduces water and air pollution, and helps save space in overcrowded landfills.Use less water: The average American uses 310 liters (82 gallons) of water a day. Reduce water consumption by taking shorter showers, turning off the water when brushing your teeth, avoiding pouring excess drinking water down the sink, and washing fruits and vegetables in a bowl of water rather than under the tap.Reduce driving: When you can, walk, bike, or take a bus instead of driving. Even 3 kilometers (2 miles) in a car puts about two pounds of carbon dioxide (CO2) into the atmosphere. If you must drive, try to carpool to reduce pollution. Lastly, skip the drive-through. You pollute more when you sit in a line while your car is emitting pollutant gases.Know how much you’re consuming: Most people are unaware of how much they are consuming every day. Calculate your individual ecological footprint to see how you can reduce your consumption here.Systemic implications: Individually, we are a rounding error. Take some time to understand how our individual actions can inform more systemic changes that may ultimately have a bigger impact on reducing humanity's overarching footprint.

Discover key Google usage statistics, including search volume, user demographics, popular services, mobile trends, and global reach!

The average person has 8-9 social media accounts. This has doubled since 2013, when the average person just had 4-5 accounts.

Potable water use by sector and average daily use for Canada, provinces and territories.

A line chart that shows % of U.S. adults who say they subscribe to home broadband, by community type

Key information about United States Monthly Earnings

• United States Monthly Earnings stood at 5,120 USD in Feb 2026, compared with the previous figure of 5,100 USD in Jan 2026
• US Monthly Earnings data is updated monthly, available from Mar 2006 to Feb 2026, with an average number of 3,492 USD
• The data reached the an all-time high of 5,120 USD in Feb 2026 and a record low of 2,741 USD in Mar 2006

CEIC calculates Monthly Earnings from Average Weekly Earnings multiplied by 4. U.S. Bureau of Labor Statistics provides Average Weekly Earnings in USD. Monthly Earnings include Private Non Agricultural sector only.


Further information about United States Monthly Earnings

• In the latest reports, US Population reached 342 million people in Dec 2025
• Unemployment Rate of US increased to 4 % in Feb 2026
• The country's Labour Force Participation Rate increased to 62 % in Feb 2026

There is more to housing affordability than the rent or mortgage you pay. Transportation costs are the second-biggest budget item for most families, but it can be difficult for people to fully factor transportation costs into decisions about where to live and work. The Location Affordability Index (LAI) is a user-friendly source of standardized data at the neighborhood (census tract) level on combined housing and transportation costs to help consumers, policymakers, and developers make more informed decisions about where to live, work, and invest. Compare eight household profiles (see table below) —which vary by household income, size, and number of commuters—and see the impact of the built environment on affordability in a given location while holding household demographics constant.*$11,880 for a single person household in 2016 according to US Dept. of Health and Human Services: https://aspe.hhs.gov/computations-2016-poverty-guidelinesThis layer is symbolized by the percentage of housing and transportation costs as a percentage of income for the Median-Income Family profile, but the costs as a percentage of income for all household profiles are listed in the pop-up:Also available is a gallery of 8 web maps (one for each household profile) all symbolized the same way for easy comparison: Median-Income Family, Very Low-Income Individual, Working Individual, Single Professional, Retired Couple, Single-Parent Family, Moderate-Income Family, and Dual-Professional Family.An accompanying story map provides side-by-side comparisons and additional context.--Variables used in HUD's calculations include 24 measures such as people per household, average number of rooms per housing unit, monthly housing costs (mortgage/rent as well as utility and maintenance expenses), average number of cars per household, median commute distance, vehicle miles traveled per year, percent of trips taken on transit, street connectivity and walkability (measured by block density), and many more.To learn more about the Location Affordability Index (v.3) visit: https://www.hudexchange.info/programs/location-affordability-index/. There you will find some background and an FAQ page, which includes the question:"Manhattan, San Francisco, and downtown Boston are some of the most expensive places to live in the country, yet the LAI shows them as affordable for the typical regional household. Why?" These areas have some of the lowest transportation costs in the country, which helps offset the high cost of housing. The area median income (AMI) in these regions is also high, so when costs are shown as a percent of income for the typical regional household these neighborhoods appear affordable; however, they are generally unaffordable to households earning less than the AMI.Date of Coverage: 2012-2016 Date Released: March 2019Date Downloaded from HUD Open Data: 4/18/19Further Documentation:LAI Version 3 Data and MethodologyLAI Version 3 Technical Documentation_**The documentation below is in reference to this items placement in the NM Supply Chain Data Hub. The documentation is of use to understanding the source of this item, and how to reproduce it for updates**

Title: Location Affordability Index - NMCDC Copy

Summary: This layer contains the Location Affordability Index from U.S. Dept. of Housing and Urban Development (HUD) - standardized household, housing, and transportation cost estimates by census tract for 8 household profiles.

Notes: This map is copied from source map: https://nmcdc.maps.arcgis.com/home/item.html?id=de341c1338c5447da400c4e8c51ae1f6, created by dianaclavery_uo, and identified in Living Atlas.

Prepared by: dianaclavery_uo, copied by EMcRae_NMCDC

Source: This map is copied from source map: https://nmcdc.maps.arcgis.com/home/item.html?id=de341c1338c5447da400c4e8c51ae1f6, created by dianaclavery_uo, and identified in Living Atlas. Check the source documentation or other details above for more information about data sources.

Feature Service: https://nmcdc.maps.arcgis.com/home/item.html?id=447a461f048845979f30a2478b9e65bb

UID: 73

Data Requested: Family income spent on basic need

Method of Acquisition: Search for Location Affordability Index in the Living Atlas. Make a copy of most recent map available. To update this map, copy the most recent map available. In a new tab, open the AGOL Assistant Portal tool and use the functions in the portal to copy the new maps JSON, and paste it over the old map (this map with item id

Date Acquired: Map copied on May 10, 2022

Priority rank as Identified in 2022 (scale of 1 being the highest priority, to 11 being the lowest priority): 6

Tags: PENDING

This database automatically captures metadata sourced from the GOVERNMENT OF THE REPUBLIC OF SLOVENIA STATISTICAL OFFICE OF THE REPUBLIC OF SLOVENIA and corresponds to the source database entitled 'Average monthly labour costs per person employed (EUR) by sectors of activity (NACE Rev. 2), Slovenia, annually, provisional data'.

The actual data is available in PC-Axis (.px) format. Among the additional links, you can access the page of the source portal for insight and selection of data, and there is also the PX-Win program, which can be downloaded for free. Both allow you to select data for display, change the printout format and store it in different formats, as well as view and print tables of unlimited size and some basic statistical analyses and graphical representations.

Graph and download economic data for Average Weekly Hours of All Employees, Total Private (AWHAETP) from Mar 2006 to Feb 2026 about establishment survey, hours, private, employment, and USA.