A software engineering team is developing a complex simulation software for environmental studies. The software is designed to simulate various environmental impacts based on multiple factors such as air pollution levels, water quality, and deforestation rates$--$ all requiring different computation. The team plans to implement parallel processing to enhance the efficiency of the simulation. Which of the following approach is better for processing the data?

Question options:

A$.$ Although the scenario involves computation on different sets of data $($air pollution, water quality, deforestation$),$ same computation can be applied there. Thus the given data can be sliced and the data parallelism technique can be applied to process the data.

B$.$ None of the approach is a good choice.

C$.$ In the given scenario, as each environmental factor $($air pollution, water quality, deforestation$)$ requires distinct computational algorithms and models, task parallelism would likely be more effective. This approach would allow each unique environmental simulation to be processed in parallel, maximizing efficiency and potentially reducing overall computation time.