# Introduction | Grid and Regions methodology
Source: https://greenpixie.com/docs/methodology/grid/introduction

Purpose, audience, and context of the methodology.

This document describes Greenpixie's methodology for producing the region-specific factors that determine the carbon and water impact of running a workload in one cloud region rather than another, being hourly grid carbon intensity, data centre energy overhead, and the water stress of each cloud region's location. It is intended for customers, partners, procurement teams, auditors, regulators, and technically literate readers who require a clear understanding of how Greenpixie derives the carbon intensity applied to cloud and AI workloads.

The intensity of a grid varies by geography and by hour, as the mix of generation serving that grid changes. Organisations reporting electricity emissions under the GHG Protocol location-based method need a factor matched both to the grid that served the consumption and to the period in which the consumption occurred.

Greenpixie collects generation and intensity data published by grid operators, market bodies, national inventories and modelled national datasets. The methodology converts that data into an hourly emissions intensity for each electricity grid area. It then matches each grid area to the cloud regions that area serves. The [*Greenpixie Methodology for Cloud Emission Measurement*](/methodology/cloud) and the [*Greenpixie Methodology for Cloud AI Token Inference Energy, Carbon, and Water Measurement*](/methodology/ai) apply the factors produced this way. Those documents describe how the factors combine with energy figures to produce emissions.

The sections that follow describe the scope, inputs, calculation process, quality controls, governance, and outputs of this methodology.