Begin by exporting the data from Airtable. Open your Airtable base, navigate to the table you want to export, and use the "Download CSV" option. This will save your table as a CSV file on your local machine, which can be used for further processing.

Open the downloaded CSV file in a spreadsheet editor or text editor to ensure the data is correctly formatted. Check for any special characters, empty values, or formatting issues that need correction. This step ensures a smooth import into PostgreSQL.

If you haven't already, install PostgreSQL on your machine or server. Create a new database or use an existing one. You can do this using the PostgreSQL command line (`psql`) or a graphical interface like pgAdmin. Ensure you have the necessary privileges to create tables and insert data.

Define a table schema in PostgreSQL that corresponds to the structure of your Airtable data. Use the `CREATE TABLE` SQL statement to match the columns and data types of the CSV data. For example:
```sql
CREATE TABLE my_table (
id SERIAL PRIMARY KEY,
column1 VARCHAR(255),
column2 INTEGER,
column3 DATE
);
```

Use the `COPY` command in PostgreSQL to import the CSV data into the newly created table. This command is executed in the PostgreSQL command line or through a tool like pgAdmin. The syntax is:
```sql
COPY my_table(column1, column2, column3)
FROM '/path/to/your/file.csv'
DELIMITER ','
CSV HEADER;
```
Ensure the file path is accessible to the PostgreSQL server.

After loading the data, verify that the data in PostgreSQL matches the data in Airtable. Run `SELECT` queries to check the number of records and spot-check some entries. Look for any discrepancies or data conversion issues that may have arisen during the import process.

If this data transfer is a recurring task, consider writing a script to automate the process. Use a scripting language like Python or Bash to automate the steps of exporting the CSV, preparing the data, and importing it into PostgreSQL. This will save time and reduce errors in the long run.