Nano Banana 2 Image-to-Image: Crafting Realistic Industrial Smoke Plumes

Creating convincing atmospheric effects is often the difference between a flat image and a scene that feels alive. When working with Nano Banana 2, specifically within its image-to-image workflow, adding realistic smoke plumes to industrial environments requires a precise approach. The goal is not merely to overlay a texture but to generate volumetric smoke that interacts correctly with existing light sources and appears to originate from the specific machinery or vents in your reference image.

This guide focuses on the structural elements of your prompt to achieve this effect. It is important to remember that Nano Banana refers to the AI image generation tool described here, distinct from any physical cosmetic products or skincare brands. By understanding how to direct the model, you can control the density, direction, and lighting of the smoke without altering the core identity of your industrial subject.

Structuring Your Prompt for Origin Accuracy

The most common challenge when adding smoke is ensuring it emerges from the correct source point rather than floating randomly across the frame. In an industrial setting, smoke should logically exit a chimney, a valve, or a cooling tower. To achieve this, your prompt must explicitly define the spatial relationship between the smoke and the machinery.

Start by describing the scene's context clearly. Instead of simply asking for "smoke," specify the source. For example, use phrases like "thick gray smoke billowing directly from the rusted exhaust pipe" or "volumetric steam rising vertically from the cooling vent." This directional language helps the model anchor the new element to the existing geometry of the image.

When constructing your instruction, place the description of the smoke immediately after the description of the source object. This proximity reinforces the causal link in the model's processing. Avoid vague terms like "somewhere near the factory" as they can lead to ambiguous placement. If the reference image has multiple potential sources, be specific about which one you intend to modify. Remember that prompt instructions describe desired outcomes; they do not guarantee perfect preservation of every label or object detail, so clarity is paramount.

Controlling Light Interaction and Volume

Realism in smoke generation relies heavily on how the plume interacts with the environment's lighting. Industrial scenes often feature harsh sunlight, overcast skies, or artificial floodlights. The smoke must react to these conditions to look authentic. A plume that ignores the sun's angle will appear pasted on rather than integrated.

In your prompt, include descriptors regarding the lighting conditions affecting the smoke. Phrases such as "backlit by the setting sun," "illuminated by overhead industrial floodlights," or "diffused under an overcast sky" provide crucial context. You might also specify the color temperature, noting if the smoke should carry a warm orange glow from nearby flames or remain cool blue-gray in a shaded area.

To enhance the volumetric feel, use adjectives that suggest depth and density. Words like "translucent," "billowing," "dense," or "wispy" help the model understand the opacity and movement of the gas. Combining these with lighting cues ensures the smoke casts subtle shadows or catches highlights consistent with the rest of the scene. This technique creates a cohesive visual narrative where the atmosphere feels physically present.

Testing and Refining Your Results

Since AI generation involves probabilistic outcomes, achieving the perfect plume may require iteration. Start with a clear base prompt that defines the source and lighting. If the initial result shows smoke appearing too solid or disconnected from the light, refine the wording to emphasize transparency and flow. For instance, if the smoke looks like a static cloud, add "dynamic motion" or "rising currents" to the prompt.

It is essential to note that while the prompt library offers example prompts that users can copy, these are examples and not guaranteed templates. Different images may yield different results based on their unique composition. If the smoke does not appear to originate from the intended point, try rephrasing the location constraint more strictly. Additionally, be aware that the specific model version being used influences the output. Google documents Nano Banana 2 as Gemini 3.1 Flash Image, which handles complex edits well, whereas other versions like Nano Banana 2 Lite focus on speed and cost and may have limitations with multi-turn editing or complex reference inputs.

For those looking to experiment further, Try Nano Banana to access the full capabilities of the image-to-image workflow. Always review the generated images against your original intent. If the smoke obscures critical details of the machinery, adjust the prompt to reduce density or increase the distance from the focal point. Continuous refinement of your descriptive language is the key to mastering this effect.

By focusing on the origin point, lighting interaction, and iterative testing, you can effectively use Nano Banana 2 to add professional-grade smoke effects to your industrial imagery. This structured approach ensures that the final output enhances the realism of the scene rather than detracting from it.