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  # Ozone Training Data
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- ## Description
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- This dataset contains atmospheric and environmental data used for training machine learning models to predict ozone levels. It includes various meteorological and chemical measurements collected across different locations and time periods. The dataset is designed for applications in air quality monitoring, environmental studies, and predictive modeling.
 
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  ## Authors
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  - Ziheng Sun
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  - Yunyao Li
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- - Daniel Tong
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- - Siqi Ma
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  ## Year
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  2024
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  ## Columns
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- | Column Name | Unit | Data Type | Description |
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- |----------------------|--------------|-----------|-----------------------------------------------------------------------------|
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- | **Latitude** | Degrees | Float64 | Latitude of the observation location. |
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- | **Longitude** | Degrees | Float64 | Longitude of the observation location. |
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- | **YYYYMMDDHH** | - | Object | Date and time of the observation (formatted as year-month-day-hour). |
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- | **CMAQ12KM_O3(ppb)** | ppb | Float64 | Ozone concentration in parts per billion (CMAQ model data). |
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- | **CMAQ12KM_NO2(ppb)**| ppb | Float64 | Nitrogen dioxide concentration in parts per billion (CMAQ model data). |
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- | **CMAQ12KM_CO(ppm)** | ppm | Float64 | Carbon monoxide concentration in parts per million (CMAQ model data). |
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- | **CMAQ_OC(ug/m3)** | µg/m³ | Float64 | Organic carbon concentration in micrograms per cubic meter (CMAQ model data).|
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- | **CO(moles/s)** | Moles/second | Float64 | Carbon monoxide emission rate. |
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- | **PRSFC(Pa)** | Pascals | Float64 | Surface pressure. |
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- | **PBL(m)** | Meters | Float64 | Planetary boundary layer height. |
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- | **TEMP2(K)** | Kelvin | Float64 | Temperature at 2 meters above ground level. |
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- | **WSPD10(m/s)** | m/s | Float64 | Wind speed at 10 meters above ground level. |
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- | **WDIR10(degree)** | Degrees | Float64 | Wind direction at 10 meters above ground level. |
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- | **RGRND(W/m2)** | W/m² | Float64 | Ground solar radiation. |
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- | **CFRAC** | - | Float64 | Cloud fraction. |
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- | **month** | - | Integer | Month of the observation (1-12). |
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- | **day** | - | Integer | Day of the observation (1-31). |
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- | **hours** | - | Integer | Hour of the observation (0-23). |
 
 
 
 
 
 
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  ## License
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  CC-BY-4.0
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  ## Usage
 
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  The dataset can be used for:
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  - Training and testing machine learning models for air quality prediction.
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  - Conducting research in atmospheric and environmental sciences.
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  - Analyzing the relationship between meteorological factors and air pollutants.
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  ## Citation
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  If you use this dataset in your research or projects, please cite it as follows:
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  # Ozone Training Data
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+ ## Dataset Summary
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+
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+ The Ozone training dataset contains information about ozone levels, temperature, wind speed, pressure, and other related atmospheric variables across various geographic locations and time periods. It includes detailed daily observations from multiple data sources for comprehensive environmental and air quality analysis. Geographic coordinates (latitude and longitude) and timestamps (month, day, and hour) provide spatial and temporal context for the data.
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  ## Authors
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  - Ziheng Sun
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  - Yunyao Li
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+ - Daniel Tong
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+ - Siqi Ma
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  ## Year
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  2024
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  ## Columns
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+ | Key | Unit | Data Type | Description |
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+ |-----------------------|-----------|-----------|---------------------------------------------------|
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+ | StationID | - | Int64 | Unique identifier for the station |
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+ | Latitude_x | Degrees | Float64 | Latitude of the observation location |
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+ | Longitude_x | Degrees | Float64 | Longitude of the observation location |
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+ | AirNOW_O3 | ppb | Float64 | Ozone levels from AirNOW |
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+ | Lat_airnow | Degrees | Float64 | Latitude from AirNOW data |
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+ | Lon_airnow | Degrees | Float64 | Longitude from AirNOW data |
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+ | Lat_cmaq | Degrees | Float64 | Latitude from CMAQ model |
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+ | Lon_cmaq | Degrees | Float64 | Longitude from CMAQ model |
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+ | Latitude_y | Degrees | Float64 | Latitude from secondary data source |
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+ | Longitude_y | Degrees | Float64 | Longitude from secondary data source |
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+ | CMAQ12KM_O3(ppb) | ppb | Float64 | Ozone levels from CMAQ model |
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+ | CMAQ12KM_NO2(ppb) | ppb | Float64 | NO2 levels from CMAQ model |
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+ | CMAQ12KM_CO(ppm) | ppm | Float64 | CO levels from CMAQ model |
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+ | CMAQ_OC(ug/m3) | ug/m3 | Float64 | Organic carbon concentration from CMAQ model |
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+ | PRSFC(Pa) | Pa | Float64 | Surface pressure |
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+ | PBL(m) | m | Float64 | Planetary boundary layer height |
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+ | TEMP2(K) | K | Float64 | Temperature at 2 meters |
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+ | WSPD10(m/s) | m/s | Float64 | Wind speed at 10 meters |
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+ | WDIR10(degree) | degree | Float64 | Wind direction at 10 meters |
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+ | RGRND(W/m2) | W/m2 | Float64 | Ground radiation |
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+ | CFRAC | - | Float64 | Cloud fraction |
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+ | month | - | Int64 | Month of observation |
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+ | day | - | Int64 | Day of observation |
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+ | hours | - | Int64 | Hour of observation |
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  ## License
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  CC-BY-4.0
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  ## Usage
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+
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  The dataset can be used for:
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  - Training and testing machine learning models for air quality prediction.
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  - Conducting research in atmospheric and environmental sciences.
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  - Analyzing the relationship between meteorological factors and air pollutants.
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+
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  ## Citation
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  If you use this dataset in your research or projects, please cite it as follows:
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