Dark Mode
Worldwide Atmospheric Conditions
Data Science and Analytics
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
The World Air Quality Data 2024 (Updated) dataset offers an in-depth look into air quality measurements from various global locations. It contains over 50,000 records, each providing key air quality parameters vital for environmental analysis, public health studies, and policy development. This dataset tracks a wide range of pollutants, including PM2.5, NO2, SO2, CO, and O3, giving insights into atmospheric conditions in cities worldwide. With data points collected up to March 2024, it serves as an important tool for understanding current global air quality status and trends.
Columns
- Country Code: A short code identifying the country where air quality data was recorded. (Observed: 100% valid with 13,975 unique country codes in the sample.)
- City: The name of the city where the measurement was taken. (Observed: 51,013 unique cities, with 70 records missing in the sample.)
- Location: Specific location details within a city. (Observed: 91% of records are missing for this column, with 3,835 unique locations where data is present.)
- Coordinates: Geographic coordinates (latitude and longitude) of the measurement location. (Observed: This column is 100% missing for 54,100 records in the sample, with only 170 unique coordinate sets present in the few valid entries.)
- Pollutant: The type of air pollutant measured (e.g., PM2.5, NO2). (Observed: This column is 100% missing for 54,300 records in the sample, with only 3 unique pollutant types listed where data is present.)
- Source Name: The name of the entity or sensor from which the data was sourced. (Observed: This column is 100% missing for all records in the sample.)
- Unit: The unit of measurement for the pollutant value. (Observed: This column is 100% missing for all records in the sample.)
- Value: The measured concentration or level of the pollutant. (Observed: This column is 100% missing for all records in the sample.)
- Last Updated: The timestamp indicating when the measurement was last updated. (Observed: This column is 100% missing for all records in the sample.)
- Country Label: A full name or label for the country. (Observed: This column is 100% missing for all records in the sample.)
Distribution
The dataset is provided in CSV format and includes over 50,000 records. The sample file size is 6.47 MB, structured with 10 columns. Specific numbers for records are indicated as 'over 50,000'.
Usage
This dataset is ideal for:
- Predictive Modelling: Forecasting future pollution levels based on historical air quality data, considering environmental and human-influenced factors.
- Trend Analysis: Identifying long-term patterns and shifts in air quality across different times and geographical areas to understand impacts of seasonal changes and policy implementations.
- Environmental Risk Assessment: Evaluating areas susceptible to high pollution levels and assessing potential effects on health, ecosystems, and climate, aiding in targeted intervention strategies.
- Air Quality Improvement Strategies: Informing the creation of effective air quality management plans by analysing correlations between pollutants and various contributing factors.
- Machine Learning Projects: Enhancing projects focused on understanding intricate relationships between air quality indicators and external variables like traffic density, industrial activities, and weather patterns.
Coverage
The dataset covers air quality measurements from numerous locations globally, specifically focusing on cities worldwide. The data points extend up to March 2024, providing recent insights into atmospheric conditions. The data is broadly applicable geographically, but observations from the sample indicate a significant amount of missing data for several key columns, which may affect detailed geographic or time-range analyses for certain attributes.
License
Attribution 4.0 International (CC BY 4.0)
Who Can Use It
This dataset is intended for a variety of users, including:
- Researchers: For detailed environmental analysis, health studies, and machine learning projects aimed at understanding air quality indicators.
- Policymakers: To inform the development of environmental policies and air quality improvement strategies.
- The Public: To gain a broader understanding of air quality issues and their implications for public health and environmental well-being.
Dataset Name Suggestions
- Global Air Quality Metrics 2024
- Worldwide Atmospheric Conditions
- Urban Air Quality Measurements
- Current Pollution Levels Dataset
- Environmental Air Quality Insights
Attributes
Original Data Source: Worldwide Atmospheric Conditions
QUALITY