The optimization process and recommendations:

1. Avoid Calling Functions With Indexed Columns (query line: 11): When a function is used directly on an indexed column, the database's optimizer won’t be able to use the index. For example, if the column `latitude` is indexed, the index won’t be used as it’s wrapped with the function `ACOS`. If you can’t find an alternative condition that won’t use a function call, a possible solution is to store the required value in a new indexed column.
2. Avoid Calling Functions With Indexed Columns (query line: 11): When a function is used directly on an indexed column, the database's optimizer won’t be able to use the index. For example, if the column `longitude` is indexed, the index won’t be used as it’s wrapped with the function `ACOS`. If you can’t find an alternative condition that won’t use a function call, a possible solution is to store the required value in a new indexed column.
3. Avoid Selecting Unnecessary Columns (query line: 2): Avoid selecting all columns with the '*' wildcard, unless you intend to use them all. Selecting redundant columns may result in unnecessary performance degradation.
4. Create Optimal Indexes (modified query below): The recommended indexes are an integral part of this optimization effort and should be created before testing the execution duration of the optimized query.
5. Use Equality Operator Over LIKE (modified query below): Equality operators (such as '\u003d') are usually better optimized and more readable. Prefer the equality operator when searching for a constant value such as `A`.
6. Use Equality Operator Over LIKE (modified query below): Equality operators (such as '\u003d') are usually better optimized and more readable. Prefer the equality operator when searching for a constant value such as `X`.
7. Use Equality Operator Over LIKE (modified query below): Equality operators (such as '\u003d') are usually better optimized and more readable. Prefer the equality operator when searching for a constant value such as `X-Y`.
8. Use Numeric Column Types For Numeric Values (query line: 12): Referencing a numeric value (e.g. 1) as a string in a WHERE clause might result in poor performance. Possible impacts of storing numbers as varchars: more space will be used, you won't be able to perform arithmetic operations, the data won't be self-validated, aggregation functions like SUM won't work, the output may sort incorrectly and more. If the column is numeric, remove the quotes from the constant value, to make sure a numeric comparison is done.

Optimal indexes for this query:

ALTER TABLE `Table1` ADD INDEX `table1_idx_col2_col3_col1` (`col2`,`col3`,`col1`);

The optimized query:

SELECT
        table1.*,
        table2.* 
    FROM
        Table1 AS table1 
    LEFT JOIN
        Table2 AS table2 USING (col1) 
    LEFT JOIN
        Table3 AS table3 USING (col1) 
    WHERE
        3963.191 * ACOS((SIN(PI() * $usersLatitude / 180) * SIN(PI() * table3.latitude / 180)) + (COS(PI() * $usersLatitude / 180) * COS(PI() * table3.latitude / 180) * COS(PI() * table3.longitude / 180 - PI() * 37.1092162 / 180))) <= 10 
        AND table1.col1 != '1' 
        AND table1.col2 = 'A' 
        AND (
            table1.col3 = 'X' 
            OR table1.col3 = 'X-Y'
        ) 
        AND (
            table2.col4 = 'Y' 
            OR table2.col5 = 'Y'
        )