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1000 Titel
  • The COVID-19 pandemic as a starting point to accelerate improvements in health in our cities through better urban and transport planning
1000 Autor/in
  1. Nieuwenhuijsen, Mark J. |
  2. Hahad, Omar |
  3. Münzel, Thomas |
1000 Erscheinungsjahr 2021
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-12-29
1000 Erschienen in
1000 Quellenangabe
  • 29(12):16783-16785
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1007/s11356-021-18364-8 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8714554/ |
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1000 Begutachtungsstatus
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1000 Abstract/Summary
  • PURPOSE: The inclusion of insect protein into the food system has been proposed as a promising solution to ensure future food security and mitigate negative environmental impacts related to food production. However, the market volume for edible insects in Europe is still small; consequently, producers need a decision-support system to ensure the sustainable upscaling of the sector. The study analyzed environmental and economic impacts of insect production to identify the most eco-efficient production scenarios. METHODS: A novel modular eco-efficiency assessment approach was developed to analyze the production of dried Hermetia illucens larvae. An exemplary, industrial-scale insect production system was disaggregated into a total of 29 module variants that can be combined into 4608 distinct production scenarios, which are characterized by different feeds, energy efficiencies, and processing technologies. Environmental life cycle and cost assessments were carried out for each module variant, and eco-efficiency assessment was used to jointly assess these two sustainability dimensions. Additionally, the influence of the insect feed on the production system performance and impact was investigated by employing feed-specific scaling factors. These were used to aggregate module results into production scenario results. RESULTS AND DISCUSSION: The most eco-efficient production scenarios include energy-efficient rearing facilities that rely on blanching and microwave drying for processing. The insect feed is the largest contributor to the environmental impacts and costs, but from an eco-efficiency standpoint, the choice of feed might not be crucial. Waste-type feeds (e.g., manure, fruit, and vegetable waste) have low environmental impacts and costs, but the production scenarios based on these feeds are less efficient. The low impacts of the feed are offset by higher impacts during the rearing and processing stages. Conversely, scenarios based on higher quality feeds (e.g., by-products like wheat middlings or distiller’s grains) require less resources, but the initial feed impacts and costs are higher. Moreover, of the feed types studied, only highly processed ones, such as compound chicken feed, should be avoided for insect rearing. CONCLUSIONS: The developed modular assessment approach is efficient in assessing multiple potential insect production scenarios. It can be adapted to incorporate additional variations of the production system via additional modules. Limitations include the potential for redundant module combinations and the up-front time investment needed. Finally, the results are sensitive to methodological choices: thus, these should be carefully considered and communicated during the design of the modular assessment system.
1000 Sacherschließung
gnd 1206347392 COVID-19
lokal City Planning [MeSH]
lokal Humans [MeSH]
lokal Environmental Chemistry
lokal Ecotoxicology
lokal Atmospheric Protection/Air Quality Control/Air Pollution
lokal Environment, general
lokal Pandemics [MeSH]
lokal Environmental Health
lokal Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution
lokal Trend Editorial
lokal COVID-19 [MeSH]
lokal Cities [MeSH]
lokal SARS-CoV-2 [MeSH]
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  1. https://frl.publisso.de/adhoc/uri/TmlldXdlbmh1aWpzZW4sIE1hcmsgSi4=|https://frl.publisso.de/adhoc/uri/SGFoYWQsIE9tYXI=|https://frl.publisso.de/adhoc/uri/TcO8bnplbCwgVGhvbWFz
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  • DeepGreen-ID: e282689c9c1d41c2a6eff0f8528e7d12 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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1000 Erstellt am 2023-04-27T13:50:50.632+0200
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1000 Zuletzt bearbeitet 2023-10-14T05:06:23.495+0200
1000 Objekt bearb. Sat Oct 14 05:06:23 CEST 2023
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