To solve this optimization problem, we need to define variables and constraints that capture the snow removal process in both cities. Let's denote:

- $x_n$ as the kilograms of snow removed from the northern city,
- $x_s$ as the kilograms of snow removed from the southern city.

The objective is to maximize profit, which can be calculated based on the net revenue per kilogram of snow removed in each city.

The constraints are based on the available time for each piece of equipment. For each item (snow plow, truck, shovel), we cannot exceed 500 minutes per day.

### Objective Function

Maximize: $2x_n + 1.5x_s$

This represents the total profit from removing $x_n$ kilograms of snow from the northern city and $x_s$ kilograms from the southern city.

### Constraints

1. **Snow Plow Time Constraint**: 
   - Northern city: $2x_n$
   - Southern city: $x_s$
   - Total time cannot exceed 500 minutes: $2x_n + x_s \leq 500$

2. **Truck Time Constraint**:
   - Northern city: $x_n$
   - Southern city: $3x_s$
   - Total time cannot exceed 500 minutes: $x_n + 3x_s \leq 500$

3. **Shovel Time Constraint**:
   - Northern city: $5x_n$
   - Southern city: $2x_s$
   - Total time cannot exceed 500 minutes: $5x_n + 2x_s \leq 500$

4. **Non-Negativity Constraints**: 
   - $x_n \geq 0$ (cannot remove a negative amount of snow)
   - $x_s \geq 0$ (cannot remove a negative amount of snow)

Now, let's translate this into Gurobi code in Python:

```python
from gurobipy import *

# Create a new model
m = Model("Snow Removal Optimization")

# Define variables
x_n = m.addVar(lb=0, name="northern_city")  # Kilograms of snow removed from the northern city
x_s = m.addVar(lb=0, name="southern_city")  # Kilograms of snow removed from the southern city

# Set objective function: Maximize profit
m.setObjective(2*x_n + 1.5*x_s, GRB.MAXIMIZE)

# Add constraints
m.addConstr(2*x_n + x_s <= 500, name="snow_plow_time")
m.addConstr(x_n + 3*x_s <= 500, name="truck_time")
m.addConstr(5*x_n + 2*x_s <= 500, name="shovel_time")

# Optimize model
m.optimize()

# Print solution
if m.status == GRB.OPTIMAL:
    print(f"Optimal solution: Remove {x_n.x} kilograms from the northern city and {x_s.x} kilograms from the southern city.")
else:
    print("No optimal solution found")
```