| Key Data Set Information | |
| Location | GZ-CN |
| Reference year | 2019 |
| Name |
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| Use advice for data set | When employing this data set for life cycle assessment or carbon footprint calculations, users should consider the specific energy structure of the electricity mix in Guizhou. It is important to account for the regional differences in electricity generation sources when comparing with other regions or assessing product life cycles. The temporal relevance of the data should also be considered, as the energy mix can change over time. Users should update the dataset to reflect the most current energy mix if available and ensure the technological applicability to their specific case study. |
| Technical purpose of product or process | This dataset represents the mixed electricity generation in Guizhou, which can be utilized in various sectors requiring electricity. The electricity mix is composed of thermal (coal, gas, oil), hydro, wind, nuclear, and solar power generation processes. This mix is indicative of the energy used for residential, commercial, industrial, and transportation sectors within the region. |
| Classification |
Class name
:
Hierarchy level
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| General comment on data set | Electricity mix includes thermal, hydro, wind, nuclear and solar generation |
| Copyright | No |
| Owner of data set | |
| Quantitative reference | |
| Reference flow(s) |
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| Technological representativeness | |
| LCI method and allocation | |||||
| Type of data set | Unit process, single operation | ||||
| Deviation from LCI method principle / explanations | None | ||||
| Deviation from modelling constants / explanations | None | ||||
| Data sources, treatment and representativeness | |||||
| Deviation from data cut-off and completeness principles / explanations | None | ||||
| Deviation from data selection and combination principles / explanations | None | ||||
| Deviation from data treatment and extrapolations principles / explanations | None | ||||
| Data source(s) used for this data set | |||||
| Completeness | |||||
| Completeness of product model | No statement | ||||
| Validation | |||||
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| Data generator | |
| Data set generator / modeller | |
| Data entry by | |
| Time stamp (last saved) | 2024-04-06T10:18:11+08:00 |
| Publication and ownership | |
| UUID | 91135241-e3dc-4e8e-ad1c-39f3d5b274ca |
| Date of last revision | 2024-04-20T15:11:25.045336+08:00 |
| Data set version | 00.01.005 |
| Permanent data set URI | https://lcadata.tiangong.world/showProcess.xhtml?uuid=91135241-e3dc-4e8e-ad1c-39f3d5b274ca&version=01.00.000&stock=TianGong |
| Owner of data set | |
| Copyright | No |
| License type | Free of charge for all users and uses |
Inputs
| Type of flow | Classification | Flow | Location | Mean amount | Resulting amount | Minimum amount | Maximum amount | ||
|---|---|---|---|---|---|---|---|---|---|
| Product flow | Energy carriers and technologies / Electricity | 2.216862 MJ | 2.216862 MJ | ||||||
| |||||||||
| Product flow | Energy carriers and technologies / Electricity | 1.2267972 MJ | 1.2267972 MJ | ||||||
| |||||||||
| Product flow | Energy carriers and technologies / Electricity | 0.0 MJ | 0.0 MJ | ||||||
| |||||||||
| Product flow | Energy carriers and technologies / Electricity | 0.124434 MJ | 0.124434 MJ | ||||||
| |||||||||
| Product flow | Energy carriers and technologies / Electricity | 0.0319068 MJ | 0.0319068 MJ | ||||||
| |||||||||
Outputs
| Type of flow | Classification | Flow | Location | Mean amount | Resulting amount | Minimum amount | Maximum amount | ||
|---|---|---|---|---|---|---|---|---|---|
| Product flow | Energy carriers and technologies / Electricity | 3.6 MJ | 3.6 MJ | ||||||
| |||||||||