Key Data Set Information | |
Location | QD-SD-CN |
Geographical representativeness description | A questionnaire survey was conducted on dairy farms in Qingdao, Shandong Province from July to August 2020. |
Reference year | 2016 |
Name |
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Use advice for data set | Data users should take note of the distinctive characteristics of the non-IPBS dairy farming system when utilizing this LCA data. It is crucial to differentiate between the non-IPBS and IPBS models, particularly regarding silage corn feed source, feed transportation distance, feed cost, and the utilization pathways of organic and liquid fertilizers. Ensure correct application of the provided values by taking into account that all inputs and outputs are calculated based on FPCM per ton, along with average input per hectare for comparison with relevant studies. Reference to specific research (indicated by [20]) is required when addressing areas of uncertainty, such as diesel consumption for farm tillage operations. |
Technical purpose of product or process | The milk production process described is utilized in dairy farming, specifically within non-integrated maize silage planting and dairy cow breeding systems (non-IPBS). This method focuses on raising dairy cattle and managing manure, with a distinctive practice of sourcing all feed through purchasing, and the manure composted is then fully sold to fruit and vegetable farmers. It stands in contrast to the IPBS model where farms cultivate their own silage corn and primarily use the produced organic and liquid fertilizers on their own farmland, selling the surplus to local farmers. |
Classification |
Class name
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Hierarchy level
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General comment on data set | In dairy farming, the difference between the two models is the source of silage corn feed. |
Copyright | No |
Owner of data set | |
Quantitative reference | |
Reference flow(s) |
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Functional Unit | The 1t FPCM corrected for protein and fat content was selected as the evaluation unit |
Time representativeness | |
Time representativeness description | From 2016, Shandong began to implement the silage corn planting subsidy policy, is one of the earliest provinces to implement the subsidy policy, the subsidy standard is 20~50 yuan /t. In 2019, Shandong Province silage corn planting area reached 14,100 hm2, accounting for 7.3% of the country. |
Technological representativeness | |
Technology description including background system | In the study area, there are mainly two milk production modes :IPBS and non-IPBS. In non-IPBS, the farms only have feeding links and manure treatment links, all the feed is purchased, and the manure pile fertilizer is made into organic fertilizer and sold to fruit and vegetable farmers. In IPBS, the silage corn planting process is increased in the farm, organic fertilizer and liquid fertilizer are mainly applied to the farm field, and the remaining part is sold to fruit farmers and vegetable farmers, etc. The differences between the two models are as follows :1) the sources of silage corn in the farm are different, resulting in different feed transportation distances and feed costs; 2) The use of organic fertilizer and liquid fertilizer is different, and the transportation distance is different. A total of 109 dairy farms were investigated in this study, and 83 valid questionnaires were obtained after excluding non-conforming questionnaires, among which 38 were non-IPBS and 45 were IPBS. |
Flow diagram(s) or picture(s) |
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 | ||||
Data treatment and extrapolations principles | The values in the table are the total input and output of each farm evenly distributed to FPCM per ton, and then the average value of each farm is taken. All input-output list data are calculated according to this method. The value in "()" is the average input per hectare, for the convenience of comparison with relevant studies; "a" Because the mechanical operation of farm tillage is mainly substitute tillage operation, the farmer is not clear about the diesel consumption in this link, and this data is based on relevant research [20]. "b" This value is the output of the process and is ultimately used entirely inside the system. | ||||
Deviation from data treatment and extrapolations principles / explanations | None | ||||
Data source(s) used for this data set | |||||
Sampling procedure | 研究地区主要有 2 种牛奶生产模式:IPBS 和 non-IPBS,具体见图 1.non-IPBS 中,养殖场只有饲养 环节和粪污处理环节,饲料全部来源于购买,粪便堆 肥制成有机肥后全销售给果农和菜农.IPBS 中,养殖 场增加青贮玉米种植环节,有机肥、液体肥主要施用 于场内农田,剩余部分销售给果农和菜农等.2 种模 式的区别:1)养殖场青贮玉米的来源不同,导致饲料 运输距离和饲料成本不同;2)有机肥、液体肥的利用 途径不同,运输距离不同.本研究共调研奶牛场 109 家,剔除不符合研究问卷后,得 83 份有效问卷,其中 non-IPBS 为 38 家,IPBS 为 45 家. | ||||
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) | 2024-03-19T15:52:00+08:00 |
Publication and ownership | |
UUID | 58728f65-3400-4484-bb22-79aaa7d37e89 |
Date of last revision | 2024-05-13T14:47:32.514235+08:00 |
Data set version | 01.00.005 |
Permanent data set URI | https://lcadata.tiangong.world/showProcess.xhtml?uuid=58728f65-3400-4484-bb22-79aaa7d37e89&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 | ||
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Product flow | Materials production / Food and renewable raw materials | 0.113 kg | 0.113 kg | ||||||
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Product flow | Materials production / Food and renewable raw materials | 0.03 kg | 0.03 kg | ||||||
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Product flow | Materials production / Food and renewable raw materials | 0.072 kg | 0.072 kg | ||||||
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Product flow | Materials production / Food and renewable raw materials | 0.033 kg | 0.033 kg | ||||||
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Product flow | Materials production / Food and renewable raw materials | 235.0 kg | 235.0 kg | ||||||
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Product flow | Materials production / Food and renewable raw materials | 115.0 kg | 115.0 kg | ||||||
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Waste flow | Wastes / Other waste | 53.0 kg | 53.0 kg | ||||||
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Product flow | Materials production / Food and renewable raw materials | 44.0 kg | 44.0 kg | ||||||
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Product flow | Materials production / Food and renewable raw materials | 1030.0 kg | 1030.0 kg | ||||||
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Product flow | Materials production / Food and renewable raw materials | 113.0 kg | 113.0 kg | ||||||
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Product flow | Materials production / Food and renewable raw materials | 124.0 kg | 124.0 kg | ||||||
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Product flow | Materials production / Raw materials | 305.0 kg | 305.0 kg | ||||||
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Product flow | Materials production / Raw materials | 39.0 kg | 39.0 kg | ||||||
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Product flow | Energy carriers and technologies / Electricity | 372.45599999999996 MJ | 372.45599999999996 MJ | ||||||
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Product flow | Energy carriers and technologies / Crude oil based fuels | 0.002265 kg | 0.002265 kg | ||||||
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Elementary flow | Resources / Resources from water / Renewable material resources from water | 10.647 m3 | 10.647 m3 | ||||||
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Elementary flow | Land use / Land occupation | 15.695 m2*a | 15.695 m2*a | ||||||
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Outputs
Type of flow | Classification | Flow | Location | Mean amount | Resulting amount | Minimum amount | Maximum amount | ||
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Product flow | Materials production / Food and renewable raw materials | 1000.0 kg | 1000.0 kg | ||||||
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Product flow | Materials production / Food and renewable raw materials | 0.92 kg | 0.92 kg | ||||||
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Product flow | Materials production / Food and renewable raw materials | 13.977 kg | 13.977 kg | ||||||
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Product flow | Materials production / Food and renewable raw materials | 1.185 kg | 1.185 kg | ||||||
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