Editing IPCC:AR6/WGIII/Chapter-12 (section)

== 12.4 Food systems ==

<div id="12.4.1" class="h2-container"></div>

<span id="introduction-2"></span>
=== 12.4.1 Introduction ===

<div id="h2-13-siblings" class="h2-siblings"></div>

This section complements [[IPCC:Wg3:Chapter:Chapter-7|Chapter 7]] by reviewing recent estimates of food system emissions and assessing options beyond the agriculture, forestry and land use sectors to mitigate food systems GHG emissions. A food system approach enables identification of cross-sectoral mitigation opportunities including both technological and behavioural options. Further, a system approach permits evaluation of policies that do not necessarily directly target primary producers or consumers, but other food system actors, with possibly higher mitigation efficiency. A food system approach was introduced in the IPCC Special Report on Climate Change and Land (SRCCL) ( [[#Mbow--2019|Mbow et al. 2019]] ). Besides major knowledge gaps in the quantification of food system GHG emissions ( [[#12.4.2|Section 12.4.2]] ), the SRCCL authors identified as major knowledge gaps the understanding of the dynamics of dietary change (including behavioural patterns, the adoption of plant-based dietary patterns, and interaction with human health and nutrition of sustainable healthy diets and associated feedbacks); and instruments and mechanisms to accelerate transitions towards sustainable and healthy food systems.

Sufficient food and adequate nutrition are fundamental human needs ( [[#HLPE--2020|HLPE 2020]] ; [[#Ingram--2020|Ingram 2020]] ). Food needs to be grown and processed, transported and distributed, and finally prepared and consumed. Food systems range from traditional, involving only few people and short supply chains, to modern food systems, comprising complex webs involving large numbers of stakeholders and processes that grow and transform food commodities into food products and distribute them globally ( [[#Gómez--2013|Gómez and Ricketts 2013]] ; [[#HLPE--2017|HLPE 2017]] ). A ‘food system’ includes all food chain activities (production, processing, distribution, preparation, consumption of food) and the management of food loss and wastes. It also includes institutions and infrastructures influencing any of these activities, as well as people and systems impacted ( [[#HLPE--2017|HLPE 2017]] ; [[#FAO--2018a|FAO 2018a]] ). Food choices are determined by the food environment, consisting of the ‘physical, economic, political and socio-cultural context in which consumers engage with the food system to acquire, prepare and consume food’ ( [[#HLPE--2017|HLPE 2017]] ). Food system outcomes encompass food and nutrition, productivity, profit and livelihood of food producers and other actors in food value chains, but also social outcomes and the impact on the environment ( [[#Zurek--2018|Zurek et al. 2018]] ). ‘Sustainable healthy diets’ have been defined by FAO and WHO (FAO and [[#WHO--2019|WHO 2019]] ) as ‘dietary patterns that promote all dimensions of individuals’ health and wellbeing; have low environmental pressure and impact; are accessible, affordable, safe and equitable; and are culturally acceptable’.

The SRCCL estimated overall global anthropogenic emissions from food systems to range between 10.8 and 19.1 GtCO 2 -eq yr –1 , equivalent to 21–37% of total anthropogenic emissions ( [[#Mbow--2019|Mbow et al. 2019]] ; [[#Rosenzweig--2020a|Rosenzweig et al. 2020a]] ). The authors identified major knowledge gaps for the GHG emissions inventories of food systems, particularly in providing disaggregated emissions from the food industry and transportation. The food system approach taken in the SRCCL ( [[#Mbow--2019|Mbow et al. 2019]] ) evaluates the synergies and trade-offs of food system response options and their implications for food security, climate change adaptation and mitigation. This integrated framework allows the identification of fundamental attributes of responses to maximise co-benefits, while avoiding maladaptation measures and adverse side effects. A food system approach supports the design of interconnected climate policy responses to tackle climate change, incorporating perspectives of producers and consumers. The SRCCL ( [[#Mbow--2019|Mbow et al. 2019]] ) found that the technical mitigation potential by 2050 of demand-side responses at 0.7–8.0 GtCO 2 -eq yr –1 is comparable to supply-side options at 2.3–9.6 GtCO 2 -eq yr –1 . This shows that mitigation actions need to go beyond food producers and suppliers to incorporate dietary changes and consumers’ behavioural patterns and reveals that producers and consumers need to work together to reduce GHG emissions.

Though total production of calories is sufficient for the world population ( [[#Wood--2018|Wood et al. 2018]] ; [[#Benton--2019|Benton et al. 2019]] ), availability and access to food is unequally distributed, and there is a lack of nutrient-dense foods, fruit and vegetables ( [[#Berners-Lee--2018|Berners-Lee et al. 2018]] ; KC et al. 2018). In 2019, close to 750 million people were food insecure. An estimated 2 billion people lacked adequate access to safe and nutritious food in both quality and quantity ( [[#FAO--2020|FAO et al. 2020]] ). Two billion adults are overweight or obese through inadequate nutrition, with an upward trend globally ( [[#FAO--2019|FAO et al. 2019]] ). Low intake of fruit and vegetables is further aggravated by high intake rates of refined grains, sugar and sodium, together leading to a high risk of non-communicable diseases such as cardiovascular disease and type 2 diabetes ( [[#Springmann--2016|Springmann et al. 2016]] ; [[#Clark--2018|Clark et al. 2018]] ; [[#Clark--2019|Clark et al. 2019]] ; GBD 2017 Diet Collaborators et al. 2019; [[#Willett--2019|Willett et al. 2019]] ) ( ''robust evidence, high agreement'' ). At least 340 million children under five years of age experience lack of vitamins or other essential bio-available nutrients, including almost 200 million suffering from stunting, wasting or overweight ( [[#UNICEF--2019|UNICEF 2019]] ).

[[#Bodirsky--2020|Bodirsky et al. (2020)]] find that the global prevalence of overweight will increase to 39–52% of world population in 2050 (from 29% in 2010; range across the Shared Socio-economic Pathways studied), and the prevalence of obesity to 13–20% (9% in 2010). The prevalence of underweight people was predicted to approximately halve, with absolute numbers stagnating at 0.4–0.7 billion. Although many studies represent future pathways of diets and food systems, there are few holistic and consistent narratives and quantification of the future pathways of diets and food systems ( [[#Mitter--2020|Mitter et al. 2020]] ; [[#Mora--2020|Mora et al. 2020]] ). Alternative pathways for improved diets and food systems have been developed, emphasising climate, environmental and health co-benefits ( [[#Bajželj--2014|Bajželj et al. 2014]] ; [[#Hedenus--2014|Hedenus et al. 2014]] ; [[#Damerau--2016|Damerau et al. 2016]] ; [[#Weindl--2017a|Weindl et al. 2017a]] ; [[#Weindl--2017b|Weindl et al. 2017b]] ; [[#Springmann--2018a|Springmann et al. 2018a]] ; [[#Bodirsky--2020|Bodirsky et al. 2020]] ; [[#Prudhomme--2020|Prudhomme et al. 2020]] ; [[#Hamilton--2021|Hamilton et al. 2021]] ), reduced food waste and closing yield gaps ( [[#Bajželj--2014|Bajželj et al. 2014]] ; [[#Pradhan--2014|Pradhan et al. 2014]] ), nitrogen management ( [[#Bodirsky--2014|Bodirsky et al. 2014]] ), urban and peri-urban agriculture ( [[#Kriewald--2019|Kriewald et al. 2019]] ) and different sustainability targets ( [[#Henry--2018b|Henry et al. 2018b]] ). The UN Food and Agriculture Organization (FAO) has examined three alternative food system scenarios: ‘business as usual’, ‘towards sustainability’, and ‘stratified societies’ ( [[#FAO--2018b|FAO 2018b]] ). Others have identified research priorities or changes in legislation needed to support adoption of improved food systems ( [[#Mylona--2018|Mylona et al. 2018]] ).

Malnutrition aggravates susceptibility of children to various infectious diseases ( [[#França--2009|França et al. 2009]] ; [[#Farhadi--2018|Farhadi and Ovchinnikov 2018]] ), and infectious diseases can also decrease nutrient uptake, thereby promoting malnutrition ( [[#Farhadi--2018|Farhadi and Ovchinnikov 2018]] ). Contamination of food with bacteria, viruses, parasites and microbial toxins can cause foodborne illnesses ( [[#Ricci--2017|Ricci et al. 2017]] ; [[#Abebe--2020|Abebe et al. 2020]] ; [[#Gallo--2020|Gallo et al. 2020]] ), foodborne substances such as food additives and specific proteins can cause adverse reactions, and contamination with toxic chemical substances used in agriculture and food processing can lead to poisoning or chronic diseases ( [[#Gallo--2020|Gallo et al. 2020]] ). Further, health risks from food systems may originate from the use of antibiotics in livestock production and the occurrence of anti-microbial resistance in pathogens (ECDC et al. 2015; [[#Bennani--2020|Bennani et al. 2020]] ), or zoonotic diseases such as COVID-19 ( [[#Gan--2020|Gan et al. 2020]] ; [[#Patterson--2020|Patterson et al. 2020]] ; [[#Vågsholm--2020|Vågsholm et al. 2020]] ).

Modern food systems are highly consolidated, through vertical and horizontal integration ( [[#Swinnen--2007|Swinnen and Maertens 2007]] ; [[#Folke--2019|Folke et al. 2019]] ). This consolidation has led to uneven distribution of power across the food value chain, with influence concentrated among a few actors in the post-farmgate food supply chain (e.g., large food processors and retailers), and has contributed to a loss of indigenous agriculture and food systems, for example on Pacific Islands ( [[#Vogliano--2020|Vogliano et al. 2020]] ). While agricultural producers contribute a higher proportion of GHG emissions compared with other actors in the supply chain, they have relatively little power to change the system ( [[#Clapp--2019|Clapp 2019]] ; [[#Group%20of%20Chief%20Scientific%20Advisors--2020|Group of Chief Scientific Advisors 2020]] ; [[#Leip--2021|Leip et al. 2021]] ).

In 2016, the agriculture, fisheries, and forestry sectors employed 29% of working people; employment within these sectors was 4% in developed countries, down from 9% in 1995, and 57% in least developed countries, down from 71% in 1995 ( [[#World%20Bank--2021|World Bank 2021]] ). Employment in other (non-agriculture) food system sectors, such as the food processing industry and service sectors, differs between food systems. The share of total non-farm food system employment ranges from 10% in traditional food systems (e.g., sub-Saharan Africa), to over 50% in food systems in transition (e.g., Brazil), to high shares (80%) in modern food systems (e.g., US) ( [[#Townsend--2017|Townsend et al. 2017]] ). The share of the food expenditures that farmers receive is decreasing; at the global level, this share has been estimated at 27% in 2015 ( [[#Yi--2021|Yi et al. 2021]] ).

<div id="12.4.2" class="h2-container"></div>

<span id="ghg-emissions-from-food-systems"></span>
=== 12.4.2 GHG Emissions from Food Systems ===

<div id="h2-14-siblings" class="h2-siblings"></div>

<div id="12.4.2.1" class="h3-container"></div>

<span id="sectoral-contribution-of-ghg-emissions-from-food-systems"></span>
==== 12.4.2.1 Sectoral Contribution of GHG Emissions from Food Systems ====

<div id="h3-5-siblings" class="h3-siblings"></div>

New calculations using the EDGAR v6.0 ( [[#Crippa--2021a|Crippa et al. 2021a]] ) and FAOSTAT ( [[#FAO--2021|FAO 2021]] ) databases provide territorial-based food system GHG emissions by country globally for the period 1990 to 2018 ( [[#Crippa--2021b|Crippa et al. 2021b]] ). The data are calculated based on a combination of country-specific data and aggregated information as described by [[#Crippa--2021b|Crippa et al. (2021b)]] and [[#Tubiello--2021|Tubiello et al. (2021)]] . The data show that, in 2018, 17 GtCO 2 -eq yr –1 (95% confidence range 13–23 GtCO 2 -eq yr –1 , calculated according to [[#Solazzo--2020|Solazzo et al. (2020)]] ) were associated with the production, processing, distribution, consumption of food and management of food system residues. This corresponded to 31% (range 23–42%) of total anthropogenic GHG emissions of 54 GtCO 2 -eq yr –1 . Based on the IPCC sectoral classification (Table 12.7 and Figure 12.5), the largest contribution of food systems GHG emissions in 2018 was from agriculture, that is, livestock and crop production systems (6.3 GtCO 2 -eq yr –1 , range 2.6–11.9) and land use, land use change and forestry (LULUCF) (4.0 GtCO 2 -eq yr –1 , range 2.1–5.9) (Figure 12.5). Emissions from energy use were 3.9 GtCO 2 -eq yr –1 (3.6–4.4 ''')''' , waste management 1.7 GtCO 2 -eq yr –1 (0.9–2.6), and industrial processes and product use 0.9 GtCO 2 -eq yr –1 (0.6–1.1). The share of GHG emissions from food systems generated outside the AFOLU (agriculture and LULUCF) sectors has increased over recent decades, from 28% in 1990 to 39% in 2018.

'''Table 12.7''' '''| GHG emissions from food systems by sector according to IPCC classification in Mt gas y''' '''r''' –1 '''and food systems’ share of total anthropogenic GHG emissions in''' '''1990 and 2015.'''

{| class="wikitable"
|-
! '''Sector'''

! '''CO''' 2

! '''CH''' 4

! '''N''' 2 '''O'''

! '''F-gases'''

! '''GHG'''

! '''CO''' 2

! '''CH''' 4

! '''N''' 2 '''O'''

! '''F-gases'''

! '''GHG'''

|-
!
! colspan="5"| '''Emissions (Mt gas y''' '''r''' –1 ''')'''

! colspan="5"| '''Share of total sectoral emissions (%)'''

|-
|
| colspan="10"| '''1990'''

|-
| 1 Energy

| 2212

| 10

| 0

| –

| 2583

| 10.5

| 10.2

| 26.7

| –

| 10.7

|-
| 2 Industrial processes

| 190

| 0

| 0

| 0

| 263

| 14.5

| 0

| 38

| 4.8

| 16.2

|-
| 3 Solvent and Other Product Use

| 0

| –

| –

| –

| 0

| 0.2

| –

| –

| –

| 0.2

|-
| 4 Agriculture

| 102

| 142

| 5

| –

| 5370

| 100

| 100

| 99.2

| –

| 99.8

|-
| 5 LULUCF

| 4946

| –

| 0

| –

| 5080

| 181

| –

| 194

| –

| 182

|-
| 6 Waste

| 3

| 40

| 0

| –

| 1155

| 29

| 72.4

| 99.1

| –

| 73.2

|-
| '''Total'''

| '''7453'''

| '''192'''

| '''6'''

| '''0'''

| '''14452'''

| '''29.3'''

| '''65.2'''

| '''84.5'''

| '''4.8'''

| '''40.3'''

|-
| '''Total (MtCO''' 2 '''-eq y''' '''r''' –1 ''')'''

| '''7453'''

| '''5243'''

| '''1755'''

| '''0'''

| '''14452'''

| '''29.3'''

| '''63.9'''

| '''84.5'''

| '''0.3'''

| '''40.3'''

|-
|
| colspan="10"| '''2015'''

|-
| 1 Energy

| 3449

| 13

| 0

| –

| 3927

| 10.1

| 9.5

| 24.1

| –

| 10.2

|-
| 2 Industrial processes

| 242

| 0

| 0

| 0

| 881

| 7.9

| 0

| 28.6

| 58

| 20.1

|-
| 3 Solvent and Other Product Use

| 7

| –

| –

| –

| 7

| 4.1

| –

| –

| –

| 3.6

|-
| 4 Agriculture

| 140

| 161

| 7

| –

| 6326

| 100

| 100

| 99.1

| –

| 99.7

|-
| 5 LULUCF

| 3823

| –

| 1

| –

| 3982

| 190

| –

| 229

| –

| 191

|-
| 6 Waste

| 5

| 58

| 0

| –

| 1699

| 30.6

| 71.8

| 99.1

| –

| 72.9

|-
| '''Total'''

| '''7666'''

| '''231'''

| '''8'''

| '''0'''

| '''16821'''

| '''19.3'''

| '''61.6'''

| '''83.7'''

| '''58'''

| '''31.1'''

|-
| '''Total (MtCO''' 2 '''-eq y''' '''r''' – 1 ''')'''

| '''7666'''

| '''6317'''

| '''2256'''

| '''581'''

| '''16821'''

| '''19.3'''

| '''60.2'''

| '''83.7'''

| '''53.6'''

| '''31.1'''

|}

Notes: Agricultural emissions include the emissions from the whole sector; biomass production for non-food use currently not differentiated. Non-food system AFOLU emissions are negative (that is, a net carbon sink), therefore the share of AFOLU food system emissions is &gt;100. Source: EDGARv6 ( [[#Crippa--2019|Crippa et al. 2019]] ; [[#Crippa--2021b|Crippa et al. 2021b]] ), and FAOSTAT ( [[#FAO--2021|FAO 2021]] ). LULUCF: land use, land-use change and forestry.

<div id="_idContainer105" class="_idGenObjectStyleOverride-1"></div>

[[File:bcbd3fbc20b5d7f8776af6a4ab091011 IPCC_AR6_WGIII_Figure_12_5.png]]

'''Figure 12.5 | Food system GHG emissions from the agriculture, LULUCF, waste, and energy &amp; industry sectors.''' Source: [[#Crippa--2021b|Crippa et al. (2021b)]] .

'''Energy:''' Emissions from energy use occur throughout the food supply chain. In 2018, the main contributions came from energy industries supplying electricity and heat (970 MtCO 2 -eq yr –1 ), manufacturing and construction (920 MtCO 2 -eq yr –1 , of which 29% was attributable to the food, beverage, and tobacco industry), and transport (760 MtCO 2 -eq yr –1 ). These emissions were almost entirely as CO 2 . Energy emissions from forestry and fisheries amounted to 480 MtCO 2 -eq yr –1 , with 91% of emissions as CO 2 . Emissions from residential and commercial fuel combustion contributed 250 MtCO 2 -eq yr –1 (79% of emissions as CO 2 , and with emissions of 1.7 MtCH 4 yr –1 ) and 130 MtCO 2 -eq yr –1 (with 98% of emissions as CO 2 ), respectively.

Refrigeration uses an estimated 43% of energy in the retail sector ( [[#Behfar--2018|Behfar et al. 2018]] ) and significantly increases fuel consumption during distribution. Besides being energy intensive, supermarket refrigeration also contributes to GHG emissions through leakage of refrigerants (fluorinated gases, or F-gases), although their contribution to food system GHG emissions is estimated to be minor ( [[#Crippa--2021b|Crippa et al. 2021b]] ). The cold chain accounts for approximately 1% of global GHG emissions, but as the volume of refrigerators per capita in developing countries is reported to be one order of magnitude lower than in developed countries (19 m 3 versus 200 m 3 refrigerated storage capacity per 1000 inhabitants), the importance of refrigeration to total GHG emissions is expected to increase ( [[#James--2010|James and James 2010]] ). Although refrigeration gives rise to GHG emissions, both household refrigeration and effective cold chains could contribute to a substantial reduction in losses of perishable food and thus in emissions associated with food provision ( [[#University%20of%20Birmingham--2018|University of Birmingham 2018]] ; [[#James--2010|James and James 2010]] ). A trade-off exists between reducing food waste and increased refrigeration emissions, with the benefits depending on type of produce, location and technologies used (Sustainable Cooling for All 2018; [[#Wu--2019|Wu et al. 2019]] ).

Transport has overall a minor importance for food system GHG emissions, with a share of 5% to 6% (Poore and Nemecek 2018; [[#Crippa--2021b|Crippa et al. 2021b]] ). The largest contributor to food system transport GHG emissions was road transport (92%), followed by marine shipping (4%), rail (3%), and aviation (1%). Only looking at energy needs, air or road transport consumes one order of magnitude higher energy (road: 70–80 MJ t –1 km –1 ; aviation: 100–200 MJ t –1 km –1 ) than marine shipping (10–20 MJ t –1 km –1 ) or rail (8–10 MJ t –1 km –1 ) ( [[#FAO--2011|FAO 2011]] ). For specific food products with high water content, relatively low agricultural emissions and high average transport distances, the share of transport in total GHG emissions can be over 40% (e.g., bananas, with total global average GHG emissions of 0.7 kgCO 2 -eq kg –1 ) (Poore and Nemecek 2018), but transport is a minor source of GHG emissions for most food products (Poore and Nemecek 2018).

'''Industry:''' Direct industrial emissions associated with food systems are generated by the refrigerants industry (580 MtCO 2 -eq yr –1 as F-gases) and the fertiliser industry for ammonia production (280 MtCO 2 -eq yr –1 as CO 2 ) and nitric acid (60 MtCO 2 -eq yr –1 as N 2 O). The industry sector data account for CO 2 stored in urea (–50 MtCO 2 -eq yr –1 ). Packaging contributed about 6% of total food system emissions (0.98 GtCO 2 -eq yr –1 , 91% as CO 2 , with CH 4 emissions of 2.8 Mt CH 4 yr –1 ). Major emissions sources are pulp and paper (60 MtCO 2 -eq yr –1 ) and aluminium (30 MtCO 2 -eq yr –1 ), with ferrous metals, glass, and plastics making a smaller contribution. High shares of emissions from packaging are found for beverages and some fruit and vegetables (Poore and Nemecek 2018).

'''Waste:''' Management of waste generated in the food system (including food waste, wastewater, packaging waste, etc.) leads to biogenic GHG emissions, and contributed 1.7 GtCO 2 -eq yr –1 to food systems’ GHG emissions in 2018. Of these emissions, 55% were from domestic and commercial wastewater (30 MtCH 4 yr –1 and 310 ktN 2 O yr –1 ), 36% from solid waste management (20 MtCH 4 yr –1 and 310 ktN 2 O yr –1 ), and 8% from industrial wastewater (4 MtCH 4 yr –1 and 80 ktN 2 O yr –1 ). Emissions from waste incineration and other waste management systems contributed 1%.

<div id="12.4.2.2" class="h3-container"></div>

<span id="ghg-intensities-of-food-commodities"></span>
==== 12.4.2.2 GHG Intensities of Food Commodities ====

<div id="h3-6-siblings" class="h3-siblings"></div>

There is high variability in the GHG emissions of different food products and production systems (Figure 12.6). GHG emissions intensities – measured using attributional lifecycle assessment, considering the full supply chain, expressed as CO 2 -eq per kg of product or per kg of protein – are generally highest for ruminant meat, cheese, and certain crustacean species (e.g., farmed shrimp and prawns, trawled lobster) ( [[#Nijdam--2012|Nijdam et al. 2012]] ; [[#Clark--2017|Clark and Tilman 2017]] ; [[#Clune--2017|Clune et al. 2017]] ; [[#Hilborn--2018|Hilborn et al. 2018]] ; Poore and Nemecek 2018) ( ''robust evidence, high agreement'' ) ''.'' Generally, beef from dairy systems has a lower footprint (8–23 kgCO 2 -eq per 100 g protein than beef from beef herds (17–94 kgCO 2 -eq per 100 g protein (Figure 12.6, re-calculated from Poore and Nemecek (2018) using AR6 GWPs based on a 100year horizon) ( ''medium evidence'' , ''high agreement'' ). The wide variation in emissions from beef reflects differences in production systems, which range from intensive feedlots with stock raised largely on grains through to rangeland and transhumance production systems. Dairy systems are generally more intensive production systems, with higher digestibility feed than beef systems. Further, emissions from dairy systems are shared between milk and meat, which brings GHG footprints of beef from dairy herds closer to those of meat from monogastric animals, with emissions intensities of pork (4.4–13 kgCO 2 -eq per 100 g protein) and poultry meat (2.3–11 kgCO 2 -eq per 100 g protein) (Poore and Nemecek 2018).

<div id="_idContainer107" class="_idGenObjectStyleOverride-1"></div>

[[File:67e8f8e10f0276f12a17395f54ec004f IPCC_AR6_WGIII_Figure_12_6.png]]

'''Figure 12.6 | Ranges of GHG intensities [kgCO''' 2 '''-eq per 100 g protein,''' '''10–90''' th '''percentile] in protein-rich foods, quantified via a meta-analysis of attributional lifecycle assessment studies using economic allocation.''' Aggregation of CO 2 , CH 4 , and N 2 O emissions in Poore and Nemecek (2018) updated to use AR6 100-year GWP. Data for capture fish, crustaceans, and cephalopods from [[#Parker--2018|Parker et al. (2018)]] , with post-farm data from Poore and Nemecek (2018), where the ranges represent differences across species groups. CH 4 emissions include emissions from manure management, enteric fermentation, and flooded rice only. a Grains are not generally classed as protein-rich, but they provide about 41% of global protein intake. Here grains are a weighted average of wheat, maize, oats, and rice by global protein intake. b Conversion of annual to perennial crops can lead to carbon sequestration in woody biomass and soil, shown as negative emissions intensity. Source: data from Poore and Nemecek (2018); [[#Parker--2018|Parker et al. (2018)]] .

Emissions intensities for farmed fish ranged from 2.4–11 kgCO 2 -eq per 100 g protein (Poore and Nemecek 2018). For Norwegian seafood, large differences have been found ranging from 1.1 kgCO 2 -eq kg –1 edible product for herring to more than 8 kgCO 2 -eq kg –1 edible product for salmon shipped by road and ferry from Oslo to Paris ( [[#Winther--2020|Winther et al. 2020]] ). For capture fish, large differences in emissions have been found, ranging from 0.2–7.9 kgCO 2 -eq kg –1 landed fish ( [[#Parker--2018|Parker et al. 2018]] ), although an environmental comparison of capture fish to farmed foods should include other indicators such as overfishing. Plant-based foods generally have lower GHG emissions (–2.2 to +4.5 kgCO 2 -eq per 100 g protein) than farmed animal-based foods ( [[#Nijdam--2012|Nijdam et al. 2012]] ; [[#Clark--2017|Clark and Tilman 2017]] ; [[#Clune--2017|Clune et al. 2017]] ; [[#Hilborn--2018|Hilborn et al. 2018]] ; Poore and Nemecek 2018) ( ''robust evidence, high agreement'' ). Several plant-based foods are associated with emissions from land use change, for example, palm oil, soy and coffee (Poore and Nemecek 2018), although emissions intensities are context specific ( [[#Meijaard--2020|Meijaard et al. 2020]] ) and for plant-based proteins, GHG footprints per serving remain lower than those of animal source proteins ( [[#Kim--2019|Kim et al. 2019]] ) ''.''

In traditional production systems, especially in developing countries, livestock serve multiple functions, providing draught power, fertiliser, investment and social status, besides constituting an important source of nutrients ( [[#Weiler--2014|Weiler et al. 2014]] ). In landscapes dominated by forests or cropland, semi-natural pastures grazed by ruminants provide heterogeneity that supports biodiversity ( [[#Röös--2016|Röös et al. 2016]] ). Grazing on marginal land and the use of crop residues and food waste can provide human-edible food with lower demands for cropland ( [[#Röös--2016|Röös et al. 2016]] ; [[#Van%20Zanten--2018|Van Zanten et al. 2018]] ; Van Hal et al. 2019). Animal protein requires more land than vegetable protein, so switching consumption from animal to vegetable proteins could reduce the pressure on land resources and potentially enable additional mitigation through expansion of natural ecosystems, storing carbon while supporting biodiversity, or reforestation to sequester carbon and enhance wood supply capacity for the production of bio-based products substituting fossil fuels, plastics, cement, etc. ( [[#Schmidinger--2012|Schmidinger and Stehfest 2012]] ; [[#Searchinger--2018b|Searchinger et al. 2018b]] ; [[#Hayek--2021|Hayek et al. 2021]] ). At the same time, alternatives to animal-based meat and other livestock products are being developed (Figure 12.6). Their increasing visibility in supermarkets and catering services, as well as falling production prices, could make meat substitutes competitive in one to two decades ( [[#Gerhardt--2019|Gerhardt et al. 2019]] ). However, uncertainty around their uptake creates uncertainty around their effect on future GHG emissions.

<div id="12.4.2.3" class="h3-container"></div>

<span id="territorial-national-per-capita-ghg-emissions-from-food-systems"></span>
==== 12.4.2.3 Territorial National Per Capita GHG Emissions from Food Systems ====

<div id="h3-7-siblings" class="h3-siblings"></div>

Food systems are connected to other societal systems, such as the energy system, financial system, and transport system ( [[#Leip--2021|Leip et al. 2021]] ). Also, food systems are dynamic and continuously changing and adapting to existing and anticipated future conditions. Food production systems are very diverse and vary by farm size, intensity level, farm specialisation, technological level, production methods (e.g., organic, conventional, etc.), with differing environmental and social consequences ( [[#Václavík--2013|Václavík et al. 2013]] ; [[#Fanzo--2017|Fanzo 2017]] ; [[#Herrero--2017|Herrero et al. 2017]] ; [[#Herrero--2021|Herrero et al. 2021]] ).

Various frameworks have been proposed to assess sustainability of food systems, including metrics and indicators on environmental, health, economic and equity issues, pointing to the importance of recognising the multi-dimensionality of food system outcomes ( [[#Gustafson--2016|Gustafson et al. 2016]] ; [[#Chaudhary--2018|Chaudhary et al. 2018]] ; [[#Hallström--2018|Hallström et al. 2018]] ; [[#Zurek--2018|Zurek et al. 2018]] ; [[#Eme--2019|Eme et al. 2019]] ; [[#Béné--2020|Béné et al. 2020]] ; [[#Hebinck--2021|Hebinck et al. 2021]] ). Data platforms are being developed, but so far comprehensive data for evidence-based food system policy are lacking ( [[#Fanzo--2020|Fanzo et al. 2020]] ).

To visualise several food systems dimensions in a GHG context, Figure 12.7 shows GHG emissions per capita and year for regional country aggregates ( [[#Crippa--2021a|Crippa et al. 2021a]] ; [[#Crippa--2021b|Crippa et al. 2021b]] ), indicated by the size of the bubbles. The GHG emissions presented here are based on territorial accounting similar to the UNFCCC GHG inventories: emissions are assigned to the country where they occur, not where food is consumed ( [[#Crippa--2021a|Crippa et al. 2021a]] ; [[#Crippa--2021b|Crippa et al. 2021b]] ) ( [[#12.4.2.1|Section 12.4.2.1]] ). The colours of the bubbles indicate the relative contribution of the following risk factors to deaths, according to the classification used in the Global Burden of Disease Study: child and maternal malnutrition (red, deficiencies of iron, zinc or Vitamin A, or low birth weight or child growth failure), dietary risks (yellow, for example diets low in vegetables, legumes, whole grains or diets high in red and processed meat and sugar-sweetened beverages) or high body mass index (blue). The combined contribution of these three risk factors to total deaths varies strongly and is between 28% and 88% of total deaths. Figure 12.7 shows that dietary risk factors are prevalent throughout all regions. Though not a complete measure of the health impact of food, these were selected as a proxy for nutritional adequacy and balance of diets, avoidance of food insecurity, over- or mal-nutrition and associated non-communicable diseases ( [[#GBD%202017%20Diet%20Collaborators--2018|GBD 2017 Diet Collaborators 2018]] ; GBD 2017 Diet Collaborators et al. 2019).

<div id="_idContainer109" class="_idGenObjectStyleOverride-1"></div>

[[File:f5aff741bb98c5989996a74bd340024c IPCC_AR6_WGIII_Figure_12_7.png]]

'''Figure 12.7 | Regional differences in health outcomes, territorial per capita GHG emissions from national food systems, and share of food system GHG emissions from energy use.''' GHG emissions are calculated according to the IPCC Tier 1 approach and are assigned to the country where they occur, not necessarily where the food is consumed. Health outcome is expressed as relative contribution of each of the following risk factors to their combined risk for deaths: child and maternal malnutrition (red), dietary risks (yellow) or high body mass index (blue). Sources: wholesale cost of food per capita: [[#Springmann--2021|Springmann et al. 2021]] ); territorial food system GHG emissions: EDGAR v.6, [[#Crippa--2021a|Crippa et al. (2021a)]] , recalculated according to [[#Crippa--2021b|Crippa et al. (2021b)]] using AR6 GWPs; deaths attributed to dietary factors: [[#IHME--2018|IHME (2018)]] ; GBD 2017 Diet Collaborators et al. (2019).

The share of GHG emissions from energy use is taken as a proxy for the structure of food supply in a region ( [[#12.4.1|Section 12.4.1]] ), and the cost for food as a proxy for the structure of the demand side and the access to (healthy) food ( [[#Chen--2016|Chen et al. 2016]] ; [[#Finaret--2019|Finaret and Masters 2019]] ; [[#Hirvonen--2019|Hirvonen et al. 2019]] ; [[#HLPE--2020|HLPE 2020]] ; [[#Springmann--2021|Springmann et al. 2021]] ), though acknowledging the limitations of such a simplification.

While total food system emissions in 2018 range between 0.9 and 8.5 tCO 2 -eq per capita per year between regions, the share of energy emissions relative to energy and land-based (agriculture and food system land-use change) emissions ranges between 3% and 78%. Regional expenditures for food range from USD3.0–8.8 per capita per day (Figure 12.7), though there is high variability within countries and the costs of nutrient-adequate diets often exceeds those of diets delivering adequate energy ( [[#Hirvonen--2019|Hirvonen et al. 2019]] ; Bai et al. 2020; [[#FAO--2020|FAO et al. 2020]] ). Thus, low-income households in industrialised countries can also be affected by food insecurity ( [[#Penne--2020|Penne and Goedemé 2020]] ).

<div id="12.4.3" class="h2-container"></div>

<span id="mitigation-opportunities"></span>
=== 12.4.3 Mitigation Opportunities ===

<div id="h2-15-siblings" class="h2-siblings"></div>

GHG emissions from food systems can be reduced by targeting direct or indirect GHG emissions in the supply chain including enhanced carbon sequestration, by introducing sustainable production methods such as agroecological approaches which can reduce system-level GHG emissions of conventional food production and also enhance resilience ( [[#HLPE--2019|HLPE 2019]] ), by substituting food products with high GHG intensities with others of lower GHG intensities, by reducing food over-consumption, and/or by reducing food loss and waste. The substitution of food products with others that are more sustainable and/or healthier is often called ‘dietary shift’.

Clark et al. (2020) showed that even if fossil fuel emissions were eliminated immediately, food system emissions alone would jeopardise the achievement of the 1.5ºC target and threaten the 2ºC target. They concluded that both demand-side and supply-side strategies are needed, including a shift to a diet with lower GHG intensity and rich in plant-based ‘conventional’ foods (e.g., pulses, nuts), or new food products that could support dietary shift. Such dietary shift needs to overcome socio-cultural, knowledge, and economic barriers to significantly achieve GHG mitigation ( [[#12.4.5|Section 12.4.5]] ).

Food losses occur at the farm, post-harvest and during the food processing/wholesale stages of a food supply chain, while in the final retail and consumption stages the term food waste is used ( [[#HLPE--2014|HLPE 2014]] ). Typically, food losses are linked to technical issues such as lack of infrastructure and storage, while food waste is often caused by socio-economic and behavioural factors. Mitigation opportunities through reducing food waste and loss exist in all food supply chain stages and are described in the sub-sections below.

Food system mitigation opportunities are divided into five categories as given in Table 12.8:

• Food production from agriculture, aquaculture, and fisheries (Chapter 7.4 and [[#12.4.3.1|Section 12.4.3.1]] )

'''•''' Controlled-environment agriculture ( [[#12.4.3.2|Section 12.4.3.2]] )

'''•''' Emerging food production technologies ( [[#12.4.3.3|Section 12.4.3.3]] )

'''•''' Food processing industries ( [[#12.4.3.4|Section 12.4.3.4]] )

• Storage and distribution ( [[#12.4.3|Section 12.4.3]] .5)

Food system mitigation opportunities can be either incremental or transformative ( [[#Kugelberg--2021|Kugelberg et al. 2021]] ). Incremental options are based on mature technologies, for which processes and causalities are understood, and their implementation is generally accepted by society. They do not require a substantial change in the way food is produced, processed, or consumed and might lead to a (slight) shift in production systems or preferences. Transformative mitigation opportunities have wider food system implications and usually coincide with a significant change in food choices. They are based on technologies that are not yet mature and are expected to require further innovation ( [[#Klerkx--2020|Klerkx and Rose 2020]] ), and/or mature technologies that might already be part of some food systems but are not yet widely accepted and have transformative potential if applied at large scale, for example consumption of insects ( [[#Raheem--2019a|Raheem et al. 2019a]] ). Many emerging technologies might be seen as a further step in agronomic development where land-intensive production methods relying on the availability of naturally-available nutrients and water are successively replaced with crop variants and cultivation practices reducing these dependencies at the cost of larger energy input ( [[#Winiwarter--2014|Winiwarter et al. 2014]] ). Others suggest a shift to agroecological approaches combining new scientific insights with local knowledge and cultural values ( [[#HLPE--2019|HLPE 2019]] ). Food system transformation can lead to regime shifts or (fast) disruptions ( [[#Pereira--2020|Pereira et al. 2020]] ) if driven by events that are out of control of private or public measures and have a ‘crisis’ character (e.g., BSE) ( [[#Skuce--2013|Skuce et al. 2013]] ).

Table 12.8 summarises the main characteristics of food system mitigation opportunities, their effect on GHG emissions, and associated co-benefits and adverse effects.

'''Table 12.8 | Food system mitigation''' '''opportunities.'''

{| class="wikitable"
|-
! colspan="2"| '''Food system mit''' '''igation options'''

''I: incremental; T: transformative''

! '''Direct and indirect effect on GHG mitigation'''

''D: direct emissions except emissions from energy use; E: energy demand; M: material demand; FL: food losses; FW:'' ''food waste''

''Direction of effect on GHG mitigation:'' ''+'' ''increased mitigation;'' ''0'' ''neutral;'' ''–'' ''decreased mitigation''

! '''Co-benefits/adverse effects'''

''H: health aspects; A: animal welfare; R: resource use; L: land demand; E: ecosystem services; 0: neutral''

''+'' ''co-benefits;'' ''–'' ''adverse effects''

! '''Source'''

|-
| rowspan="5"| Food from agriculture, aquaculture and fisheries

| (I) Dietary shift, in particular increased share of plant-based protein sources

| D+ ↓ GHG footprint

| A+ Animal welfare

L+ Land sparing

H+ Good nutritional properties, potentially ↓ risk from zoonotic diseases, pesticides and antibiotics

| 1–5

|-
| (I/T) Digital agriculture

| D+ ↑ Logistics

| L+ Land sparing

R+ ↑ Resource use efficiencies

| 6–7

|-
| (T) Gene technology

| D+ ↑ Productivity or efficiency

| H+ ↑ Nutritional quality

E0 ↓ Use of agrochemicals; ↑ probability of off-target impacts

| 7–11

|-
| (I) Sustainable intensification, Land-use optimisation

| D+ ↓ GHG footprint

E0 Mixed effects

| L+ Land sparing

R– Might ↑ pollution/biodiversity loss

| 7, 12

|-
| (I) Agroecology

| D+ ↓ GHG/area, positive micro-climatic effects E+ ↓ Energy, possibly ↓ transport FL+ Circular approaches

| E+ Focus on co-benefits/ecosystem services

R+ Circular, ↑ nutrient and water use efficiencies

| 13–17

|-
| Controlled-environment agriculture

| (T) Soilless agriculture

| D+ ↑ productivity, weather independent

FL+ harvest on demand

E- Currently ↑ energy demand, but ↓ transport, building spaces can be used for renewable energy

| R+ Controlled loops ↑ nutrient and water use efficiency

L+ Land sparing

H+ Crop breeding can be optimised for taste and/or nutritional quality

| 18–24

|-
| rowspan="4"| Emerging food production technologies

| (T) Insects

| D0 Good feed conversion efficiency

FW+ Can be fed on food waste

| H0 Good nutritional qualities but attention to allergies and food safety issues required

| 25–28

|-
| (I/T) Algae and bivalves

| D+ ↓ GHG footprints

| A+ Animal welfare

L+ Land sparing

H+ Good nutritional qualities; risk of heavy metal and pathogen contamination

R+ Biofiltration of nutrient-polluted waters

| 29–32

|-
| (I/T) Plant-based alternatives to animal-based food products

| D+ No emissions from animals, ↓ inputs for feed

| A+ Animal welfare

L+ Land sparing

H+ Potentially ↓ risk from zoonotic diseases, pesticides and antibiotics; but ↑ processing demand

| 31–33

|-
| (T) Cellular agriculture (including cultured meat, microbial protein)

| D+ No emissions from animals, high protein conversion efficiency

E– ↑ Energy need

FLW+ ↓ Food loss and waste

| A+ Animal welfare

R+ ↓ Emissions of reactive nitrogen or other pollutants

H0 Potentially ↓ risk from zoonotic diseases, pesticides and antibiotics; ↑ research on safety aspects needed

| 3, 24

34–42

|-
| rowspan="4"| Food processing and packaging

| (I) Valorisation of by-products, food loss and waste logistics and management

| M+ Substitution of bio-based materials

FL+ ↓ of food losses

|
| 43–44

|-
| (I) Food conservation

| FW+ ↓ Food waste

E0 ↑ energy demand but also energy savings possible (e.g., refrigeration, transport)

|
| 45–46

|-
| (I) Smart packaging and other technologies

| FW+ ↓ Food waste

M0 ↑ Material demand and ↑ material-efficiency

E0 ↑ Energy demand; energy savings possible

| H+ Possibly ↑ freshness/reduced food safety risks

| 46–49

|-
| (I) Energy efficiency

| E+ ↓ Energy

|
| 50

|-
| rowspan="5"| Storage and distribution

| (I) Improved logistics

| D+ ↓ Transport emissions

FL+ ↓ Losses in transport

FW– Easier access to food could ↑ food waste

|
| 46–47

51–53

|-
| (I) Specific measures to reduce food waste in retail and food catering

| FW+ ↓ Food waste

E+ ↓ Downstream energy demand

M+ ↓ Downstream material demand

|
| 54–56

|-
| (I) Alternative fuels/ transport modes

| D+ ↓ Emissions from transport

|
|-
| (I) Energy efficiency

| E+ ↓ Energy in refrigeration, lightening, climatisation

|
| 57–58

|-
| (I) Replacing refrigerants

| D+ ↓ Emissions from the cold chain

|
| 50

59–60

|}

Sources: [1] [[#McDermott--2017|McDermott and Wyatt (2017)]] ; [2] [[#Foyer--2016|Foyer et al. (2016)]] ; [3] [[#Semba--2021|Semba et al. (2021)]] ; [4] [[#Weindl--2020|Weindl et al. (2020)]] ; [5] [[#Hertzler--2020|Hertzler et al. (2020)]] ; [6] [[#Finger--2019|Finger et al. (2019)]] ; [7] [[#Herrero--2020|Herrero et al. (2020)]] ; [8] [[#Steinwand--2020|Steinwand and Ronald (2020)]] ; [9] [[#Zhang--2020a|Zhang et al. (2020a)]] ; [10] [[#Ansari--2020|Ansari et al. (2020)]] ; [11] [[#Eckerstorfer--2021|Eckerstorfer et al. (2021)]] ; [12] [[#Folberth--2020|Folberth et al. (2020)]] ; [13] [[#HLPE--2019|HLPE (2019)]] ; [14] [[#Wezel--2009|Wezel et al. (2009)]] ; [15] [[#Van%20Zanten--2018|Van Zanten et al. (2018)]] ; [16] [[#Van%20Zanten--2019|Van Zanten et al. (2019)]] ; [17] [[#van%20Hal--2019|van Hal et al. (2019)]] ; [18] [[#Beacham--2019|Beacham et al. (2019)]] ; [19] [[#Benke--2017|Benke and Tomkins (2017)]] ; [20] [[#Gómez--2018|Gómez and Gennaro Izzo (2018)]] ; [21] [[#Maucieri--2018|Maucieri et al. (2018)]] ; [22] [[#Rufí-Salís--2020|Rufí-Salís et al. (2020)]] ; [23] [[#Shamshiri--2018|Shamshiri et al. (2018)]] ; [24] [[#Graamans--2018|Graamans et al. (2018)]] ; [25] [[#Fasolin--2019|Fasolin et al. (2019)]] ; [26] [[#Garofalo--2019|Garofalo et al. (2019)]] ; [27] [[#Parodi--2018|Parodi et al. (2018)]] ; [28] [[#Varelas--2019|Varelas (2019)]] ; [29] [[#Gentry--2020|Gentry et al. (2020)]] ; [30] [[#Peñalver--2020|Peñalver et al. (2020)]] ; [31] [[#Torres-Tiji--2020|Torres-Tiji et al. (2020)]] ; [32] [[#Willer--2020|Willer and Aldridge (2020)]] ; [33] [[#Fresán--2019|Fresán et al. (2019)]] ; [34] [[#Mejia--2019|Mejia et al. (2019)]] ; [35] [[#Tuomisto--2019|Tuomisto (2019)]] ; [36] [[#Thorrez--2019|Thorrez and Vandenburgh (2019)]] ; [37] [[#Tuomisto--2011|Tuomisto and Teixeira de Mattos (2011)]] ; [38] [[#Mattick--2015|Mattick et al. (2015)]] ; [39] [[#Mattick--2018|Mattick (2018)]] ; [40] [[#Souza%20Filho--2019|Souza Filho et al. (2019)]] ; [41] [[#Chriki--2020|Chriki and Hocquette (2020)]] ; [42] [[#Hadi--2021|Hadi and Brightwell (2021)]] ; [43] [[#Göbel--2015|Göbel et al. (2015)]] ; [44] [[#Caldeira--2020|Caldeira et al. (2020)]] ; [45] [[#Silva--2019|Silva and Sanjuán (2019)]] ; [46] [[#FAO--2019a|FAO (2019a)]] ; [47] [[#Molina-Besch--2019|Molina-Besch et al. (2019)]] ; [48] [[#Poyatos-Racionero--2018|Poyatos-Racionero et al. (2018)]] ; [49] [[#Müller--2019|Müller and Schmid (2019)]] ; [50] [[#Niles--2018|Niles et al. (2018)]] ; [51] [[#Lindh--2016|Lindh et al. (2016)]] ; [52] [[#Wohner--2019|Wohner et al. (2019)]] ; [53] [[#Bajželj--2020|Bajželj et al. (2020)]] ; [54] [[#Buisman--2019|Buisman et al. (2019)]] ; [55] [[#Albizzati--2019|Albizzati et al. (2019)]] ; [56] [[#Liu--2016|Liu et al. (2016)]] ; [57] [[#Chaomuang--2017|Chaomuang et al. (2017)]] ; [58] [[#Lemma--2014|Lemma et al. (2014)]] ; [59] [[#McLinden--2017|McLinden et al. (2017)]] ; [60] [[#Gullo--2017|Gullo et al. (2017)]] . Food from Agriculture, Aquaculture, and Fisheries.

Agricultural food production systems range from smallholder subsistence farms to large animal production factories, in open spaces, greenhouses, rural areas or urban settings.

'''Dietary shift:''' Studies demonstrate that a shift to diets rich in plant-based foods, particularly pulses, nuts, fruits and vegetables, such as vegetarian, pescatarian or vegan diets, could lead to substantial reduction of greenhouse gas emissions as compared to current dietary patterns in most industrialised countries, while also providing health benefits and reducing mortality from diet-related non-communicable diseases ( [[#Springmann--2018a|Springmann et al. 2018a]] ; [[#Chen--2019|Chen et al. 2019]] ; [[#Willett--2019|Willett et al. 2019]] ; [[#Bodirsky--2020|Bodirsky et al. 2020]] ; [[#Costa%20Leite--2020|Costa Leite et al. 2020]] ; [[#Ernstoff--2020|Ernstoff et al. 2020]] ; [[#Jarmul--2020|Jarmul et al. 2020]] ; [[#Semba--2020|Semba et al. 2020]] ; [[#Theurl--2020|Theurl et al. 2020]] ; [[#Hamilton--2021|Hamilton et al. 2021]] ).

Pulses such as beans, chickpeas, or lentils, have a protein composition complementary to cereals, providing together all essential amino acids ( [[#Foyer--2016|Foyer et al. 2016]] ; [[#McDermott--2017|McDermott and Wyatt 2017]] ). Bio-availability of proteins in foods is influenced by several factors, including amino acid composition, presence of anti-nutritional factors, and preparation method ( [[#Hertzler--2020|Hertzler et al. 2020]] ; [[#Weindl--2020|Weindl et al. 2020]] ; [[#Semba--2021|Semba et al. 2021]] ). Soy beans, in particular, have a well-balanced amino acid profile with high bio-availability ( [[#Leinonen--2019|Leinonen et al. 2019]] ). Pulses are part of most traditional diets ( [[#Semba--2021|Semba et al. 2021]] ) and supply up to 10–35% of protein in low-income countries, but consumption decreases with increasing income and they are globally only a minor share of the diet ( [[#McDermott--2017|McDermott and Wyatt 2017]] ). Pulses play a key role in crop rotations, fixing nitrogen and breaking disease cycles, but yields of pulses are relatively low and have seen small yield increases relative to those of cereals ( [[#Foyer--2016|Foyer et al. 2016]] ; [[#McDermott--2017|McDermott and Wyatt 2017]] ; [[#Barbieri--2021|Barbieri et al. 2021]] ; [[#Semba--2021|Semba et al. 2021]] ).

'''Technological innovations:''' have made food production more efficient since the onset of agriculture ( [[#Winiwarter--2014|Winiwarter et al. 2014]] ; [[#Herrero--2020|Herrero et al. 2020]] ). Emerging technologies include digital agriculture (using advanced sensors, big data), gene technology (crop bio-fortification, genome editing, crop innovations), sustainable intensification (automation of processes, improved inputs, precision agriculture) ( [[#Herrero--2020|Herrero et al. 2020]] ), or multi-trophic aquaculture approaches ( [[#Knowler--2020|Knowler et al. 2020]] ; [[#Sanz-Lazaro--2020|Sanz-Lazaro and Sanchez-Jerez 2020]] ), though literature on aquaculture and fisheries in the context of GHG mitigation is limited.

Such technologies may contribute to a reduction of GHG emissions at the food system level, enhanced provision of food, better consideration of ecosystem services, and/or contribute to nutrition-sensitive agriculture, for example, by increasing the nutritional quality of staple crops, increasing the palatability of leguminous crops such as lupines, or increasing the agronomic efficiency or resilience of crops with good nutritional characteristics.

For details on agricultural mitigation opportunities refer to [[IPCC:Wg3:Chapter:Chapter-7#7.4|Section 7.4]] .

<div id="12.4.3.1" class="h3-container"></div>

<span id="controlled-environment-agriculture"></span>
==== 12.4.3.1 Controlled-environment Agriculture ====

<div id="h3-8-siblings" class="h3-siblings"></div>

Controlled-environment agriculture is mainly based on hydroponic or aquaponic cultivation systems that do not require soil. Aquaponics combine hydroponics with a re-circulating aquaculture compartment for integrated production of plants and fish ( [[#Junge--2017|Junge et al. 2017]] ; [[#Maucieri--2018|Maucieri et al. 2018]] ), while aeroponics is a further development of hydroponics that replaces water as a growing medium with a mist of nutrient solution ( [[#Al-Kodmany--2018|Al-Kodmany 2018]] ). Aquaponics could potentially produce proteins in urban farms, but the technology is not yet mature and its economic and environmental performance is unclear ( [[#Love--2015|Love et al. 2015]] ; [[#O’Sullivan--2019|O’Sullivan et al. 2019]] ).

Controlled-environment agriculture is often undertaken in urban environments to take advantage of short supply chains ( [[#O’Sullivan--2019|O’Sullivan et al. 2019]] ), and might use abandoned buildings or be integrated in supermarkets, producing for example herbs ‘on demand’.

Optimising growing conditions, hydroponic systems achieve higher yields than un-conditioned agriculture ( [[#O’Sullivan--2019|O’Sullivan et al. 2019]] ); and yields can be further enhanced in CO 2 -enriched atmospheres ( [[#Shamshiri--2018|Shamshiri et al. 2018]] ; [[#Armanda--2019|Armanda et al. 2019]] ). By using existing spaces or modular systems that can be vertically stacked, this technology minimises land demand, however it is energy intensive and requires large financial investments. So far, only a few crops are commercially produced in vertical farms, including lettuce and other leafy greens, herbs and some vegetables, due to their short growth period and high value ( [[#Benke--2017|Benke and Tomkins 2017]] ; [[#Armanda--2019|Armanda et al. 2019]] ; [[#Beacham--2019|Beacham et al. 2019]] ; [[#O’Sullivan--2019|O’Sullivan et al. 2019]] ). Through breeding, other crops could reach commercial feasibility, or crops with improved taste or nutritional characteristics can be grown ( [[#O’Sullivan--2019|O’Sullivan et al. 2019]] ).

In controlled-environment agriculture, photosynthesis is fuelled by artificial light through LEDs or a combination of natural light with LEDs. Control of the wave band and light cycle of the LEDs and micro-climate can be used to optimise photosynthetic activity, yield and crop quality ( [[#Gómez--2018|Gómez and Gennaro Izzo 2018]] ; [[#Shamshiri--2018|Shamshiri et al. 2018]] ).

Co-benefits of controlled-environment agriculture include minimising water and nutrient losses as well as agro-chemical use ( [[#Al-Kodmany--2018|Al-Kodmany 2018]] ; [[#Shamshiri--2018|Shamshiri et al. 2018]] ; [[#Armanda--2019|Armanda et al. 2019]] ; [[#Farfan--2019|Farfan et al. 2019]] ; [[#O’Sullivan--2019|O’Sullivan et al. 2019]] ; [[#Rufí-Salís--2020|Rufí-Salís et al. 2020]] ) ( ''robust evidence, high agreement'' ). Water is recycled in a closed system and additionally some plants generate fresh water by evaporation from grey or black water, and high nutrient use efficiencies are possible. Food production from controlled-environment agriculture is independent of weather conditions and able to satisfy some consumer demand for locally-produced fresh and diverse produce throughout the year ( [[#Benke--2017|Benke and Tomkins 2017]] ; [[#Al-Kodmany--2018|Al-Kodmany 2018]] ; [[#O’Sullivan--2019|O’Sullivan et al. 2019]] ).

Controlled-environment agriculture is a very energy intensive technology (mainly for cooling) and its GHG intensity depends therefore crucially on the source of the energy. Options for reducing GHG intensity include reducing energy use through improved lighting and cooling efficiency or by employing low-carbon energy sources, potentially integrated into the building structure ( [[#Benke--2017|Benke and Tomkins 2017]] ).

Comprehensive studies assessing the GHG balance of controlled-environment agriculture are lacking. The overall GHG emissions from controlled-environment agriculture is therefore uncertain and depends on the balance of reduced GHG emissions from production and distribution and reduced land requirements, versus increased external energy needs.

<div id="12.4.3.2" class="h3-container"></div>

<span id="emerging-foods-and-production-technologies"></span>
==== 12.4.3.2 Emerging Foods and Production Technologies ====

<div id="h3-9-siblings" class="h3-siblings"></div>

A diverse range of novel food products and production systems are emerging, that are proposed to reduce GHG emissions from food production, mainly by replacing conventional animal-source food with alternative protein sources. Assessments of the potential of dietary changes are given in Sections 5.3 and 7.4. Here, we assess the GHG intensities of emerging food production technologies. This includes products such as insects, algae, mussels and products from bio-refineries, some of which have been consumed in certain societies and/or in smaller quantities ( [[#Pikaar--2018|Pikaar et al. 2018]] ; [[#Jönsson--2019|Jönsson et al. 2019]] ; [[#Govorushko--2019|Govorushko 2019]] ; [[#Raheem--2019a|Raheem et al. 2019a]] ; [[#Souza%20Filho--2019|Souza Filho et al. 2019]] ). The novel aspect considered here is the scale at which they are proposed to replace conventional food with the aim to reduce both negative health and environmental impacts. To fully realise the health benefits, dietary shifts should also encompass a reduction in consumption of added sugars, salt, saturated fats, and potentially harmful additives ( [[#Curtain--2019|Curtain and Grafenauer 2019]] ; [[#Fardet--2019|Fardet and Rock 2019]] ; [[#Petersen--2021|Petersen et al. 2021]] ).

Meat analogues have attracted substantial venture capital, and production costs have dropped considerably in the last decade, with some reaching market maturity ( [[#Mouat--2018|Mouat and Prince 2018]] ; [[#Santo--2020|Santo et al. 2020]] ), but there is uncertainty whether they will ‘disrupt’ the food market or remain niche products. According to [[#Kumar--2017|Kumar et al. (2017)]] , the demand for plant-based meat analogues is expected to increase as their production is relatively cheap and they satisfy consumer demands with regard to health and environmental concerns as well as ethical and religious requirements. Consumer acceptance is still low for some options, especially insects ( [[#Aiking--2019|Aiking and de Boer 2019]] ) and cultured meat ( [[#Chriki--2020|Chriki and Hocquette 2020]] ; [[#Siegrist--2020|Siegrist and Hartmann 2020]] ).

'''Insects:''' Farmed edible insects have a higher feed conversion ratio than other animals farmed for food, and have short reproduction periods with high biomass production rates ( [[#Halloran--2016|Halloran et al. 2016]] ). Insects have good nutritional qualities ( [[#Parodi--2018|Parodi et al. 2018]] ). They are suited as a protein source for both humans and livestock, with high protein content and favourable fatty acid composition ( [[#Fasolin--2019|Fasolin et al. 2019]] ; [[#Raheem--2019b|Raheem et al. 2019b]] ). If used as feed, they can grow on food waste and manure; if used as food, food safety concerns and regulations can restrict the use of manure ( [[#Raheem--2019b|Raheem et al. 2019b]] ) or food waste ( [[#Varelas--2019|Varelas 2019]] ) as growing substrates, and the dangers of pathogenic or toxigenic microorganisms and incidences of anti-microbial resistance need to be managed ( [[#Garofalo--2019|Garofalo et al. 2019]] ).

'''Algae and bivalves''' have a high protein content and a favourable nutrient profile and can play a role in providing sustainable food. Bivalves are high in omega-3 fatty acids and vitamin B12 and therefore well suited as replacement of conventional meats, and have a lower GHG footprint ( [[#Parodi--2018|Parodi et al. 2018]] ; [[#Willer--2020|Willer and Aldridge 2020]] ). Micro- and macro algae are rich in omega-3 and omega-6 fatty acids, anti-oxidants and vitamins ( [[#Parodi--2018|Parodi et al. 2018]] ; [[#Peñalver--2020|Peñalver et al. 2020]] ; [[#Torres-Tiji--2020|Torres-Tiji et al. 2020]] ). [[#Kim--2019|Kim et al. (2019)]] show that diets with modest amounts of animals low on the food chain such as forage fish, bivalves, or insects have similar GHG intensities to vegan diets. Algae and bi-valves can be used to filter nutrients from waters, though care is required to avoid accumulation of hazardous substances ( [[#Gentry--2020|Gentry et al. 2020]] ; [[#Willer--2020|Willer and Aldridge 2020]] ).

'''Plant-based meat, milk and egg analogues:''' Demand for plant-based proteins is increasing and incentivising the development of protein crop varieties with improved agronomic performance and/or nutritional quality ( [[#Santo--2020|Santo et al. 2020]] ). There is also an emerging market for meat replacements based on plant proteins, such as pulses, cereals, soya, algae and other ingredients mainly used to imitate the taste, texture and nutritional profiles of animal-source food ( [[#Kumar--2017|Kumar et al. 2017]] ; [[#Boukid--2021|Boukid 2021]] ). Currently, the majority of plant-based meat analogues is based on soy ( [[#Semba--2021|Semba et al. 2021]] ). While other products still serve a niche market, their share is growing rapidly and some studies project a sizeable share within a decade ( [[#Kumar--2017|Kumar et al. 2017]] ; [[#Jönsson--2019|Jönsson et al. 2019]] ). In particular, plant-based milk alternatives have seen large increases in market share ( [[#Jönsson--2019|Jönsson et al. 2019]] ). A LCA of 56 plant-based meat analogues showed mean GHG intensities (farm to factory) of 0.21–0.23 kgCO 2 -eq per 100 g of product or 20 g of protein for all assessed protein sources ( [[#Fresán--2019|Fresán et al. 2019]] ). Higher footprints were found in the meta-review by [[#Santo--2020|Santo et al. (2020)]] . Including preparation, Meija et al. (2019) found higher emissions for burgers and sausages as compared to minced products.

'''Cellular agriculture:''' The use of fungi, algae and bacteria is an old process (beer, bread, yoghurt) and serves, among others, for the preservation of products. The concept of cellular agriculture ( [[#Mattick--2018|Mattick 2018]] ) covers bio-technological processes that use micro-organisms to produce acellular (fermentation-based cellular agriculture) or cellular products. Yeasts, fungi or bacteria can synthesise acellular products such as haem, milk and egg proteins, or protein-rich animal feed, other food ingredients, and pharmaceutical and material products ( [[#Rischer--2020|Rischer et al. 2020]] ; [[#Mendly-Zambo--2021|Mendly-Zambo et al. 2021]] ). Cellular products include cell tissues such as muscle cells to grow cultured meat, fish or other cells ( [[#Post--2012|Post 2012]] ; [[#Rischer--2020|Rischer et al. 2020]] ) and products where the micro-organisms will be eaten themselves ( [[#Pikaar--2018|Pikaar et al. 2018]] ; [[#Sillman--2019|Sillman et al. 2019]] ; [[#Schade--2020|Schade et al. 2020]] ). Single cell proteins, combined with photovoltaic electricity generation and direct air capture of carbon dioxide, are proposed as highly land- and energy-efficient alternatives to plant-based protein ( [[#Leger--2021|Leger et al. 2021]] ). Some microbial proteins are produced in a ‘bioreactor’ and use Haber-Bosch nitrogen and vegetable sugars or atmospheric CO 2 as source of nitrogen and carbon ( [[#Pikaar--2018|Pikaar et al. 2018]] ; [[#Simsa--2019|Simsa et al. 2019]] ). Cultured meat is currently at the research stage and some challenges remain, such as the need for animal-based ingredients to ensure fast and effective growth of muscle cells; tissue engineering to create different meat products; production at scale and at competitive costs; and regulatory barriers ( [[#Post--2012|Post 2012]] ; [[#Stephens--2018|Stephens et al. 2018]] ; [[#Rubio--2019|Rubio et al. 2019]] ; [[#Tuomisto--2019|Tuomisto 2019]] ; [[#Post--2020|Post et al. 2020]] ). Only a few studies to date have quantified the GHG emissions of microbial proteins or cultured meat, suggesting GHG emissions at the level of poultry meat ( [[#Tuomisto--2011|Tuomisto and Teixeira de Mattos 2011]] ; [[#Mattick--2015|Mattick et al. 2015]] ; [[#Souza%20Filho--2019|Souza Filho et al. 2019]] ; [[#Tuomisto--2019|Tuomisto 2019]] ).

A review of LCA studies on different plant-based, animal source and nine ‘future food’ protein sources ( [[#Parodi--2018|Parodi et al. 2018]] ) concluded that insects, macro-algae, mussels, mycoproteins and cultured meat show similar GHG intensities per unit of protein (mean values ranging 0.3–3.1 kgCO 2 -eq per 100 g protein), comparable to milk, eggs, and tuna (mean values ranging 1.2–5.4 kgCO 2 -eq per 100 g protein); while ''chlorella'' and ''spirulina'' consume more energy per unit of protein and were associated with higher GHG emissions (mean values ranging 11–13 kgCO 2 -eq per 100 g protein). As the main source of GHG emissions from insects and cellular agriculture foods is energy consumption, their GHG intensity improves with increased use of low-carbon energy ( [[#Smetana--2015|Smetana et al. 2015]] ; [[#Parodi--2018|Parodi et al. 2018]] ; [[#Pikaar--2018|Pikaar et al. 2018]] ).

Future foods offer other benefits such as lower land requirements, controlled systems with reduced losses of water and nutrients, increased resilience, and possibly reduced hazards from pesticide and antibiotics use and zoonotic diseases, although more research is needed including on allergenic and other safety aspects, and possibly reduced protein bioavailability ( [[#Alexander--2017|Alexander et al. 2017]] ; [[#Parodi--2018|Parodi et al. 2018]] ; [[#Stephens--2018|Stephens et al. 2018]] ; [[#Fasolin--2019|Fasolin et al. 2019]] ; [[#Chriki--2020|Chriki and Hocquette 2020]] ; [[#Santo--2020|Santo et al. 2020]] ; [[#Hadi--2021|Hadi and Brightwell 2021]] ; [[#Tzachor--2021|Tzachor et al. 2021]] ) ( ''medium evidence, high agreement'' ). Research is needed also on the effect of processing ( [[#Wickramasinghe--2021|Wickramasinghe et al. 2021]] ), though a randomised crossover trial comparing appetising plant foods with meat alternatives found several beneficial and no adverse effects from the consumption of the plant-based meats (Crimarco et al. 2020).

<div id="12.4.3.3" class="h3-container"></div>

<span id="food-processing-and-packaging"></span>
==== 12.4.3.3 Food Processing and Packaging ====

<div id="h3-10-siblings" class="h3-siblings"></div>

Food processing includes preparation and preservation of fresh commodities (fruit and vegetables, meat, seafood and dairy products), grain milling, production of baked goods, and manufacture of pre-prepared foods and meals. Food processors range from small local operations to large multinational food producers, producing food for local to global markets. The importance of food processing and preservation is particularly evident in developing countries which lack cold chains for the preservation and distribution of fresh perishable products such as fresh fish ( [[#Adeyeye--2016|Adeyeye and Oyewole 2016]] ; [[#Adeyeye--2017|Adeyeye 2017]] ).

Mitigation in food processing largely focuses on reducing food waste and fossil energy usage during the processing itself, as well as in the transport, packaging and storage of food products for distribution and sale ( [[#Silva--2019|Silva and Sanjuán 2019]] ). Reducing food waste provides emissions savings by reducing wastage of primary inputs required for food production. Another mitigation route, contributing to the circular bioeconomy ( [[#12.6.1.2|Section 12.6.1.2]] and Cross-Working Group Box 3 in this chapter), is by valorisation of food processing by-products through recovery of nutrients and/or energy. No global analyses of the emissions savings potential from the processing step in the value chain could be found.

Reduced food waste during food processing can be achieved by seeking alternative processing routes ( [[#Atuonwu--2018|Atuonwu et al. 2018]] ), improved communication along the food value chain ( [[#Göbel--2015|Göbel et al. 2015]] ), optimisation of food processing facilities, reducing contamination, and limiting damages and spillage ( [[#HLPE--2014|HLPE 2014]] ). Optimisation of food packaging also plays an important role in reducing food waste, in that it can extend product shelf life; protect against damage during transport and handling; prevent spoilage; facilitate easy opening and emptying; and communicate storage and preparation information to consumers ( [[#Molina-Besch--2019|Molina-Besch et al. 2019]] ).

Developments in smart packaging are increasingly contributing to reducing food waste along the food value chain. Strategies for reducing the environmental impact of packaging include using less, and more sustainable, materials and a shift to reusable packaging ( [[#Coelho--2020|Coelho et al. 2020]] ). Active packaging increases shelf life through regulating the environment inside the packaging, including levels of oxygen, moisture and chemicals released as the food ages ( [[#Emanuel--2019|Emanuel and Sandhu 2019]] ). Intelligent packaging communicates information on the freshness of the food through indicator labels ( [[#Poyatos-Racionero--2018|Poyatos-Racionero et al. 2018]] ), and data carriers can store information on conditions such as temperature along the entire food chain ( [[#Müller--2019|Müller and Schmid 2019]] ).

LCA can be used to evaluate the benefits and trade-offs associated with different processing or packaging types ( [[#Silva--2019|Silva and Sanjuán 2019]] ). Some options, such as aluminium, steel and glass, require high energy investment in manufacture when produced from primary materials, with significant savings in energy through recycling being possible ( [[#Camaratta--2020|Camaratta et al. 2020]] ). However, these materials are inert in landfill. Other packaging options, such as paper and biodegradable packaging, may require a lower energy investment during manufacture, but may require larger land area and can release methane when consigned to anaerobic landfill where there is no methane recovery. Nevertheless, packaging accounts for only 1–12% (typically around 5%) of the GHG emissions in the lifecycle of a food system ( [[#Wohner--2019|Wohner et al. 2019]] ; [[#Crippa--2021b|Crippa et al. 2021b]] ), suggesting that its benefits can often outweigh the emissions associated with the packaging itself.

The second component of mitigation in food processing relates to reduction in fossil energy use. Opportunities include energy efficiency in processes (also discussed in [[IPCC:Wg3:Chapter:Chapter-11#11.3|Section 11.3]] ), the use of heat and electricity from low-carbon energy sources in processing (Chapter 6), through off-grid thermal processing (sun drying, food smoking) and improving logistics efficiencies. Energy-intensive processes with energy-saving potential include milling and refining (oil seeds, corn, sugar), drying, and food safety practices such as sterilisation and pasteurisation ( [[#Niles--2018|Niles et al. 2018]] ). Packaging also plays a role: reduced transport energy can be achieved through reducing the mass of goods transported and improving packing densities in transport vehicles ( [[#Lindh--2016|Lindh et al. 2016]] ; [[#Molina-Besch--2019|Molina-Besch et al. 2019]] ; [[#Wohner--2019|Wohner et al. 2019]] ). Choice of packaging also influences refrigeration energy requirements during transport and storage.

<div id="12.4.3.4" class="h3-container"></div>

<span id="storage-and-distribution"></span>
==== 12.4.3.4 Storage and Distribution ====

<div id="h3-11-siblings" class="h3-siblings"></div>

Transport mitigation options along the supply chain include improved logistics, the use of alternative fuels and transport modes, and reduced transport distances. Logistics and alternative fuels and transport modes are discussed in Chapter 10. Transport emissions might increase with increasing demand for a diversity of foods as developing countries become more affluent. New technologies that enable food on demand or online food shopping systems might further increase emissions from food transport; however, the consequences are uncertain and might also entail a shift from individual traffic to bulk transport. The impact on food waste is also uncertain as more targeted delivery options could reduce food waste, but easier access to a wider range of food could also foster over-supply and increase food waste. Mitigation opportunities in food transport are inherently linked to decarbonisation of the transport sector (Chapter 10).

Retail and the food service industry are the main factors shaping the external food environment or ‘food entry points’; they are the ‘physical spaces where food is obtained; the built environment that allows consumers to access these spaces’ ( [[#HLPE--2017|HLPE 2017]] ). These industries have significant influence on consumers’ choices and can play a role in reducing GHG emissions from food systems. Opportunities are available for optimisation of inventories in response to consumer demands through advanced IT systems ( [[#Niles--2018|Niles et al. 2018]] ), and for discounting foods close to sell-by dates, which can serve to reduce both food spoilage and wastage ( [[#Buisman--2019|Buisman et al. 2019]] ).

As one of the highest contributors to energy demand at this stage in the food value chain, refrigeration has received a strong focus in mitigation. Efficient refrigeration options include advanced refrigeration temperature control systems, and installation of more efficient refrigerators, air curtains and closed display fridges ( [[#Chaomuang--2017|Chaomuang et al. 2017]] ). Also related to reducing emissions from cooling and refrigeration is the replacement of hydrofluorocarbons which have very high GWPs with lower GWP alternatives ( [[#Niles--2018|Niles et al. 2018]] ). The use of propane, isobutane, ammonia, hydrofluoroolefins and CO 2 (refrigerant R744) are among those that are being explored, with varying success ( [[#McLinden--2017|McLinden et al. 2017]] ). In recent years, due to restrictions on high GWP-refrigerants, a considerable growth in the market availability of appliances and systems with non-fluorinated refrigerants has been seen ( [[#Eckert--2021|Eckert et al. 2021]] ).

Energy efficiency alternatives generic to buildings more broadly are also relevant here, including efficient lighting, heating, ventilation, and air conditioning systems and building management, with ventilation being a particularly high energy user in retail, that warrants attention ( [[#Kolokotroni--2015|Kolokotroni et al. 2015]] ).

In developing countries particularly, better infrastructure for transportation and expansion of processing and manufacturing industries can significantly reduce food losses, particularly of highly perishable food ( [[#Niles--2018|Niles et al. 2018]] ; [[#FAO--2019a|]] [[#FAO--2019|FAO 2019]] a ).

<div id="12.4.4" class="h2-container"></div>

<span id="enabling-food-system-transformation"></span>
=== 12.4.4 Enabling Food System Transformation ===

<div id="h2-16-siblings" class="h2-siblings"></div>

Food system mitigation potentials in AFOLU are assessed in [[IPCC:Wg3:Chapter:Chapter-7#7.4|Section 7.4]] , and food system mitigation potentials linked to demand-side measures are assessed in Chapter 5. Studies suggest that implementing supply- and demand-side policies in combination makes ambitious mitigation targets easier to achieve ( [[#Clark--2020|Clark et al. 2020]] ; [[#Global%20Panel%20on%20Agriculture%20and%20Food%20Systems%20for%20Nutrition--2020|Global Panel on Agriculture and Food Systems for Nutrition 2020]] ; [[#Temme--2020|Temme et al. 2020]] ; [[#Latka--2021|Latka et al. 2021]] a) ( ''high agreement'' , ''lim'' ''ited evidence'' ) ''.''

The trends in the global and national food systems towards a globalisation of food supply chains and increasing dominance of supermarkets and large corporate food processors ( [[#Dries--2004|Dries et al. 2004]] ; [[#Neven--2004|Neven and Reardon 2004]] ; [[#Baker--2016|Baker and Friel 2016]] ; [[#Andam--2018|Andam et al. 2018]] ; [[#Popkin--2018|Popkin and Reardon 2018]] ; [[#Reardon--2019|Reardon et al. 2019]] ; [[#Pereira--2020|Pereira et al. 2020]] ) have led to environmental, food insecurity and malnutrition problems. Studies therefore call for a transformation of current global and national food systems to solve these problems (Schösler and Boer 2018; [[#McBey--2019|McBey et al. 2019]] ; [[#Kugelberg--2021|Kugelberg et al. 2021]] ). This has not yet been successful, including due to insufficient coordination between relevant food system policies ( [[#Weber--2020|Weber et al. 2020]] ) ( ''medium evidence, h'' ''igh agreement'' ) ''.''

Different elements of food systems are currently governed by separate policy areas that in most countries scarcely interact or cooperate ( [[#Termeer--2018|Termeer et al. 2018]] ; [[#iPES%20Food--2019|iPES Food 2019]] ). This compartmentalisation makes the identification of synergetic and antagonistic effects difficult and faces the possibility of failure due to unintended and unanticipated negative impacts on other policy areas and consequently lack of agreement and social acceptance ( [[#Mylona--2018|Mylona et al. 2018]] ; [[#Brouwer--2020|Brouwer et al. 2020]] ; [[#Mausch--2020|Mausch et al. 2020]] ; [[#Hebinck--2021|Hebinck et al. 2021]] ) ( [[#12.4.5|Section 12.4.5]] ). This could be overcome through cooperation across several policy areas (Sections 12.6.2 and 13.7), in particular agriculture, nutrition, health, trade, climate and environment, and an inclusive and transparent governance structure ( [[#Termeer--2018|Termeer et al. 2018]] ; [[#Bhunnoo--2019|Bhunnoo 2019]] ; [[#Diercks--2019|Diercks et al. 2019]] ; [[#Herrero--2021|Herrero et al. 2021]] ; [[#iPES%20Food--2019|iPES Food 2019]] ; [[#Mausch--2020|Mausch et al. 2020]] ; [[#Kugelberg--2021|Kugelberg et al. 2021]] ), making use of potential spillover effects ( [[#Kanter--2020|Kanter et al. 2020]] ; [[#OECD--2021|OECD 2021]] ).

Transformation of food systems may come from technological, social or institutional innovations that start as niches but can potentially lead to rapid changes, including changes in social conventions ( [[#Centola--2018|Centola et al. 2018]] ; [[#Benton--2019|Benton et al. 2019]] ).

Where calories and ruminant animal-source food are consumed in excess of health guidelines, reduction of excess meat (and dairy) consumption is among the most effective measures to mitigate GHG emissions, with a high potential for environment, health, food security, biodiversity, and animal welfare co-benefits ( [[#Hedenus--2014|Hedenus et al. 2014]] ; [[#Springmann--2018a|Springmann et al. 2018a]] ; [[#Chai--2019|Chai et al. 2019]] ; [[#Chen--2019|Chen et al. 2019]] ; [[#Kim--2019|Kim et al. 2019]] ; [[#Willett--2019|Willett et al. 2019]] ; [[#Semba--2020|Semba et al. 2020]] ; [[#Theurl--2020|Theurl et al. 2020]] ; [[#Hamilton--2021|Hamilton et al. 2021]] ; [[#Stylianou--2021|Stylianou et al. 2021]] ) ( ''robust evidence,'' ''high agreement'' ) ''.'' Dietary changes are relevant for several SDGs, in addition to SDG 13 (climate action), including SDG 2 (zero hunger), SDG 3 (good health and well-being), SDG 6 (clean water and sanitation), SDG 12 (responsible consumption and production), SDG 14 (life below water) and SDG 15 (life on land) (Bruce M et al. 2018; [[#Mbow--2019|Mbow et al. 2019]] ; [[#Vanham--2019|Vanham et al. 2019]] ; [[#Herrero--2021|Herrero et al. 2021]] ) ( [[#12.6.1|Section 12.6.1]] ). However, behavioural change towards diets of lower environmental impact and higher nutritional qualities faces barriers both from agricultural producers and consumers ( [[#Apostolidis--2016|Apostolidis and McLeay 2016]] ; Aiking and de Boer 2018; [[#de%20Boer--2018|de Boer et al. 2018]] ; [[#Milford--2019|Milford et al. 2019]] ), and requires policy packages that combine informative instruments with behavioural, administrative and/or market-based instruments, and are attentive to the needs of, and engage, all food system stakeholders including civil society networks, and change the food environment ( [[#Cornelsen--2015|Cornelsen et al. 2015]] ; [[#Kraak--2017|Kraak et al. 2017]] ; [[#Stoll-Kleemann--2017|Stoll-Kleemann and Schmidt 2017]] ; [[#El%20Bilali--2019|El Bilali 2019]] ; [[#iPES%20Food--2019|iPES Food 2019]] ; [[#Milford--2019|Milford et al. 2019]] ; [[#Temme--2020|Temme et al. 2020]] ) ( [[#12.4.1|Section 12.4.1]] ) ( ''robust evidence, h'' ''igh agreement'' ).

Table 12.9 summarises the implications of a range of policy instruments discussed in more detail in the following sub-sections and highlights the benefits of integrated policy packages. Furthermore, Table 12.9 assesses transformative potential, environmental effectiveness, feasibility, distributional effect, cost, and cost-benefits and trade-offs of individual policy instruments, as well as their potential role as part of coherent policy packages. Table 12.9 shows that information and behavioural policy instruments can have significant but small effects in changing diets ( ''robust evidence'' '', medium agreement'' ), but are mutually enforcing and might be essential to lower barriers and increase acceptance of market-based and administrative instruments ( ''medium evidence, h'' ''igh agreement'' ).

'''Table 12.9 | Assessment of food system policies targeting (post-farm gate) food chain actors''' '''and consumers.'''

{| class="wikitable"
|-
!
! '''Level G: global/multinational; N: national; L: local'''

! '''Transformative potential'''

! '''Environmental effectiveness'''

! '''Feasibility'''

! '''Distributional effects'''

! '''Cost'''

! '''Co-benefits''' a '''and adverse side effect'''

! '''Implications for coordination, coherence and consistency in policy package''' b

|-
| '''Integrated food policy packages'''

| '''NL'''

|
| '''can be controlled'''

| '''cost efficient'''

| '''+ balanced, addresses multiple sustainability goals'''

| Reduces cost of uncoordinated interventions; increases acceptance across stakeholders and civil society ( ''robust evidence'' , ''high agreement'' )

|-
| Taxes on food products

| GN

|
| '''regressive'''

| low # 1

| '''– unintended substitution effects'''

| High enforcing effect on other food policies; higher acceptance if compensation or hypothecated taxes ( ''medium evidence'' , ''high agreement'' )

|-
| rowspan="2"| GHG taxes on food

| rowspan="2"| GN

| rowspan="2"|
| rowspan="2"| '''regressive'''

| rowspan="2"| low # 2

| '''– unintended substitution effects'''

| rowspan="2"| Supportive, enabling effect on other food policies, agricultural/fishery policies; requires changes in power distribution and trade agreements ( ''medium evidence'' , ''medium agreement'' )

|-
| + high spillover effect

|-
| rowspan="2"| Trade policies

| rowspan="2"| G

| rowspan="2"|
| rowspan="2"| impacts global distribution

| rowspan="2"| complex effects

| + counters leakage effects

| rowspan="2"| Requires changes in existing trade agreements ( ''medium evidence'' , ''high agreement'' )

|-
| +/– effects on market structure and jobs

|-
| Investment into research and innovation

| GN

|
| none

| medium

| + high spillover effect + converging with digital society

| Can fill targeted gaps for coordinated policy packages (e.g., monitoring methods) ( ''robust evidence'' , ''high agreement'' )

|-
| Food and marketing regulations

| N

|
| low

|
| Can be supportive; might be supportive to realise innovation; voluntary standards might be less effective ( ''medium evidence'' , ''medium agreement'' )

|-
| Organisational-level procurement policies

| NL

|
| low

| + can address multiple sustainability goals

| Enabling effect on other food policies; reaches large share of population ( ''medium evidence'' , ''high agreement'' )

|-
| Sustainable food-based dietary guidelines

| GNL

|
| none

| low

| + can address multiple sustainability goals

| Little attention so far on environmental aspects; can serve as benchmark for other policies (labels, food formulation standards, etc.) ( ''medium evidence'' , ''medium agreement'' )

|-
| Food labels/ information

| GNL

|
| education level relevant

| low

| + empowers citizens

+ increases awareness

+ multiple objectives

| Effective mainly as part of a policy package; incorporation of other objectives (e.g., animal welfare, fair trade); higher effect if mandatory ( ''medium evidence'' , ''medium agreement'' )

|-
| Nudges

| NL

|
| none

| low

| + possibly counteracting information deficits in population subgroups

| High enabling effect on other food policies ( ''medium evidence'' , ''high agreement'' )

|}

Effect of measures:   negative   none/unclear   slightly positive   positive 

Notes: #1 Minimum level to be effective 20% price increase; #2 Minimum level to be effective USD50–80 tCO 2 -eq. a In addition, all interventions are assumed to address health and climate change mitigation. b Requires coordination between policy areas, participation of stakeholders, transparent methods and indicators to manage trade-offs and prioritisation between possibly conflicting objectives; and suitable indicators for monitoring and evaluation against objectives.

The policy instruments are assessed in relation to shifting food consumption and production towards increased sustainability and health. This includes lowering GHG emissions, although not in all cases is this the primary focus of the instrument, and in some cases lowering GHG emissions may not even be explicitly mentioned.

<div id="12.4.4.1" class="h3-container"></div>

<span id="market-based-instruments"></span>
==== 12.4.4.1 Market-based Instruments ====

<div id="h3-12-siblings" class="h3-siblings"></div>

'''Taxes and subsidies:''' Food-based taxes have largely been implemented to reduce non-communicable diseases and sugar intake, particularly those targeting sugar-sweetened beverages ( [[#WHO--2019|WHO 2019]] ). Many health-related organisations recommend the introduction of such taxes to improve the nutritional quality of marketed products and consumers’ diets ( [[#Wright--2017|Wright et al. 2017]] ; [[#Park--2019|Park and Yu 2019]] ; [[#WHO--2019|WHO 2019]] ), even though the impacts of food taxes are complex due to cross-price and substitution effects and supplier reactions ( [[#Cornelsen--2015|Cornelsen et al. 2015]] ; [[#Gren--2019|Gren et al. 2019]] ; [[#Blakely--2020|Blakely et al. 2020]] ) and can have a regressive effect ( [[#WHO--2019|WHO 2019]] ). Subsidies and taxes are found to be effective in changing dietary behaviour at levels above 20% price increase ( [[#Cornelsen--2015|Cornelsen et al. 2015]] ; [[#Niebylski--2015|Niebylski et al. 2015]] ; [[#Nakhimovsky--2016|Nakhimovsky et al. 2016]] ; [[#Hagenaars--2017|Hagenaars et al. 2017]] ; [[#Mozaffarian--2018|Mozaffarian et al. 2018]] ), even though longer-term effects are scarcely studied ( [[#Cornelsen--2015|Cornelsen et al. 2015]] ) and effects of sugar tax with tax rates lower than 20% have been observed for low-income groups ( [[#Temme--2020|Temme et al. 2020]] ).

Modelling results show only small consumption shifts with moderate meat price increases; and high price increases are required to reach mitigation targets, even though model predictions become highly uncertain due to lack of observational data ( [[#Mazzocchi--2017|Mazzocchi 2017]] ; [[#Bonnet--2018|Bonnet et al. 2018]] ; [[#Fellmann--2018|Fellmann et al. 2018]] ; [[#Zech--2019|Zech and Schneider 2019]] ; [[#Latka--2021|Latka et al. 2021]] b). Taxes applied at the consumer level are found to be more effective than levying the taxes on the production side ( [[#Springmann--2017|Springmann et al. 2017]] ).

Unilateral taxes on food with high GHG intensities have been shown to induce increases in net export flows, which could reduce global prices and increase global demand. Indirect effects on GHG mitigation therefore could be reduced by up to 70–90% of national results ( [[#Fellmann--2018|Fellmann et al. 2018]] ; [[#Zech--2019|Zech and Schneider 2019]] ) ( ''limited evidence, high agreement'' ). The global mitigation potential for GHG taxation of food products at USD52 kgCO 2 -eq –1 has been estimated at 1 GtCO 2 -eq yr –1 ( [[#Springmann--2017|Springmann et al. 2017]] ).

Studies have shown that taxes can improve the nutritional quality of diets and reduce GHG emissions from the food system, particularly if accompanied by other policies that increase acceptance and elasticity, and reduce regressive and distributional problems ( [[#Niebylski--2015|Niebylski et al. 2015]] ; [[#Hagenaars--2017|Hagenaars et al. 2017]] ; [[#Mazzocchi--2017|Mazzocchi 2017]] ; [[#Springmann--2017|Springmann et al. 2017]] ; [[#Wright--2017|Wright et al. 2017]] ; [[#Henderson--2018|Henderson et al. 2018]] ; [[#Säll--2018|Säll 2018]] ; [[#FAO--2020|FAO et al. 2020]] ; [[#Penne--2020|Penne and Goedemé 2020]] ) ( ''robust evidence, h'' ''igh agreement'' ) ''.''

'''Trade:''' Since the middle of the last century, global trade in agricultural products has contributed to boosting productivity and reducing commodity prices, while also incentivising national subsidies for farmers to remain competitive in the global market ( [[#Benton--2019|Benton et al. 2019]] ). Trade liberalisation has been coined as an essential element of sustainable food systems, and as one element required to achieve sustainable development, that can shift pressure to regions where the resources are less scarce ( [[#Wood--2018|Wood et al. 2018]] ; Traverso and Schiavo 2020). However, [[#Clapp--2017|Clapp (2017)]] argues that the main economic benefit of trade liberalisation flows to large transnational firms. Benton and Bailey (2019) argue that low food prices in the second half of last century contributed to both yield and food waste increases, and to a focus on staple crops to the disadvantage of nutrient-dense foods. However, global trade can also contribute to economic benefits such as jobs and income, reduce food insecurity and facilitate access to nutrients ( [[#Wood--2018|Wood et al. 2018]] ; Hoff et al. 2019; Traverso and Schiavo 2020; [[#Geyik--2021|Geyik et al. 2021]] ) and has contributed to increased food supply diversity ( [[#Kummu--2020|Kummu et al. 2020]] ). The relevance of trade for food security, and adaptation and mitigation of agricultural production, has also been discussed in [[#Mbow--2019|Mbow et al. (2019)]] .

Trade policies can be used to protect national food system measures, by requiring front-of-package labels, or to impose border taxes on unhealthy products ( [[#Thow--2019|Thow and Nisbett 2019]] ). For example, in the frame of the Pacific Obesity Prevention in Communities project, the Fijian government implemented three measures (out of seven proposed) that eliminated import duties on fruits and vegetables, and imposed 15% import duties on unhealthy oils ( [[#Latu--2018|Latu et al. 2018]] ). Trade agreements, however, have the potential to undermine national efforts to improve public health ( [[#Unar-Munguía--2019|Unar-Munguía et al. 2019]] ). GHG mitigation efforts in food supply chains can be counteracted by GHG leakage, with a general increase of environmental and social impact in developing countries exporting food products, and a decrease in the developed countries importing food products ( [[#Fellmann--2018|Fellmann et al. 2018]] ; [[#Sandström--2018|Sandström et al. 2018]] ; [[#Wiedmann--2018|Wiedmann and Lenzen 2018]] ). The demand for agricultural commodities has also been associated with tropical deforestation, though a robust estimate on the extent of embodied deforestation in food commodities is not available ( [[#Pendrill--2019|Pendrill et al. 2019]] ).

'''Investment into research and innovation:''' [[#El%20Bilali--2019|El Bilali (2019)]] assessed research gaps in the food system transition literature and found a need to develop comparative studies that enable the assessment of spatial variability and scalability of food system transitions. The author found also that the role of private industry and corporate business is scarcely researched, although they could play a major role in food system transitions.

The InterAcademy Partnership assessed how research can contribute to providing the required evidence and opportunities for food system transitions, with a focus on climate change impacts and mitigation ( [[#IAP--2018|IAP 2018]] ). The project builds on four regional assessments of opportunities and challenges on food and nutrition security in Africa ( [[#NASAC--2018|NASAC 2018]] ), the Americas ( [[#IANAS--2018|IANAS 2018]] ), Asia ( [[#AASSA--2018|AASSA 2018]] ), and Europe ( [[#EASAC--2017|EASAC 2017]] ). The Partnership concludes with a set of research questions around food systems, that need to be better understood: (i) how are sustainable food systems constituted in different contexts and at different scales? (ii) how can transition towards sustainable food systems be achieved? and (iii) how can success and failure be measured along sustainability dimensions including climate mitigation?

<div id="12.4.4.2" class="h3-container"></div>

<span id="regulatory-and-administrative-instruments"></span>
==== 12.4.4.2 Regulatory and Administrative Instruments ====

<div id="h3-13-siblings" class="h3-siblings"></div>

'''Marketing regulations:''' Currently, 16 countries regulate marketing of unhealthy food to children, mainly on television and in schools ( [[#Taillie--2019|Taillie et al. 2019]] ), and many other efforts are ongoing across the globe ( [[#European%20Commission--2019|European Commission 2019]] ). The aim to counter the increase in obesity in children and target products high in saturated fats, trans-fatty acids, free sugars and/or salt ( [[#WHO--2010|WHO 2010]] ) was endorsed by 192 countries ( [[#Kovic--2018|Kovic et al. 2018]] ). Nutrition and health claims for products are used by industry to increase sales, for example in the sport sector or for breakfast cereals. They can be informative, but can also be misleading if misused for promoting unhealthy food ( [[#Whalen--2018|Whalen et al. 2018]] ; [[#Ghosh--2019|Ghosh and Sen 2019]] ; [[#Sussman--2019|Sussman et al. 2019]] ).

Strong statutory marketing regulations can significantly reduce the exposure of children to, and sales of, unhealthy food compared with voluntary restrictions ( [[#Kovic--2018|Kovic et al. 2018]] ; [[#Temme--2020|Temme et al. 2020]] ). Data on effectiveness of marketing regulations with a broader food sustainability scope are not available. On the other hand, regulations that mobilise private investment into emerging food production technologies can be instrumental in curbing the cost and making them competitive ( [[#Bianchi--2018a|Bianchi et al. 2018a]] ).

'''Voluntary sustainability standards:''' Voluntary sustainability standards are developed either by a public entity or by private organisations to respond to consumers’ demands for social and environmental standards ( [[#Fiorini--2019|Fiorini et al. 2019]] ). For example, the Dutch Green Protein Alliance, an alliance of government, industry, NGOs and academia, formulated a goal to shift the ratio of protein consumption from 60% animal source proteins currently to 40% by 2050 ( [[#Aiking--2020|Aiking and de Boer 2020]] ), and Cool Food Pledge signatories (organisations that serve food, such as restaurants, hospitals and universities) committed to a 25% reduction in GHG emissions by 2030, compared with 2015 ( [[#Cool%20Food--2020|Cool Food 2020]] ). For firms, obtaining certification under such schemes can be costly, and costs are generally borne by the producers and/or supply chain stakeholders ( [[#Fiorini--2019|Fiorini et al. 2019]] ). The effectiveness of private voluntary sustainability standards is uncertain. [[#Cazzolla%20Gatti--2019|Cazzolla Gatti et al. (2019)]] have investigated the effectiveness of the Roundtable on Sustainable Palm Oil on halting forest loss and habitat degradation in Southeast Asia and concluded that production of certified palm oil continued to lead to deforestation.

'''Organisational procurement:''' Green public procurement is a policy that aims to create additional demand for sustainable products ( [[#Bergmann%20Madsen--2018|Bergmann Madsen 2018]] ; [[#Mazzocchi--2019|Mazzocchi and Marino 2019]] ) or decrease demand for less sustainable products (e.g., the introduction of ‘Meatless Monday’ by the Norwegian Armed Forces) ( [[#Cheng--2018|Cheng et al. 2018]] ; [[#Gava--2018|Gava et al. 2018]] ; [[#Milford--2019|Milford and Kildal 2019]] ; [[#Wilts--2019|Wilts et al. 2019]] ). To improve dietary choices, organisations can increase the price of unsustainable options while decreasing the price of sustainable ones, or employ information or choice architecture measures ( [[#Goggins--2016|Goggins and Rau 2016]] ; [[#Goggins--2018|Goggins 2018]] ). Procurement guidelines exist at global, national, organisational or local levels ( [[#Noonan--2013|Noonan et al. 2013]] ; [[#Neto--2018|Neto and Gama Caldas 2018]] ). Procurement rules in schools or public canteens increase the accessibility of healthy food and can improve dietary behaviour and decrease purchases of unhealthy food ( [[#Cheng--2018|Cheng et al. 2018]] ; [[#Temme--2020|Temme et al. 2020]] ).

'''Food regulations:''' Novel foods based on insects, microbial proteins or cellular agriculture must go through authorisation processes to ensure compliance with food safety standards before they can be sold to consumers. Several countries have ‘novel food’ regulations governing the approval of foods for human consumption. For example, the European Commission, in its update of the Novel Food Regulation in 2015, expanded its definition of novel food to include food from cell cultures, or that produced from animals by non-traditional breeding techniques ( [[#EU--2015|EU 2015]] ).

For animal product analogues, regulatory pathways and procedures ( [[#Stephens--2018|Stephens et al. 2018]] ) and terminology issues (defining equivalence questions) ( [[#Carrenõ--2018|Carrenõ and Dolle 2018]] ; [[#Pisanello--2018|Pisanello and Ferraris 2018]] ) need clarification, as does their relation to religious rules ( [[#Chriki--2020|Chriki and Hocquette 2020]] ).

Examples of legislation targeting food waste include the French ban on wasting food approaching best-before dates, requiring its donation to charity organisations ( [[#Global%20Alliance%20for%20the%20Future%20of%20Food--2020|Global Alliance for the Future of Food 2020]] ). In Japan, the Food Waste Recycling Law set targets for food waste recycling for industries in the food sector for 2020, ranging between 50% for restaurants and 95% for food manufacturers ( [[#Liu--2016|Liu et al. 2016]] ).

<div id="12.4.4.3" class="h3-container"></div>

<span id="informative-instruments."></span>
==== 12.4.4.3 Informative Instruments. ====

<div id="h3-14-siblings" class="h3-siblings"></div>

'''Sustainable food-based dietary guidelines:''' National food-based dietary guidelines (FBDGs) provide science-based recommendations on food group consumption quantities. They are available for 94, mostly upper- and middle-income, countries globally ( [[#Wijesinha-Bettoni--2021|Wijesinha-Bettoni et al. 2021]] ), are adapted to national cultural and socio-economic context, and can be used as a benchmark for food formulation standards for public and private food procurement, or to inform citizens ( [[#Bechthold--2018|Bechthold et al. 2018]] ; [[#Temme--2020|Temme et al. 2020]] ). Most FBDGs are based on health considerations and only a few mention environmental sustainability aspects ( [[#Bechthold--2018|Bechthold et al. 2018]] ; [[#Ritchie--2018|Ritchie et al. 2018]] ; [[#Ahmed--2019|Ahmed et al. 2019]] ; [[#Springmann--2020|Springmann et al. 2020]] ). Implementation of FBDGs so far focuses largely in the education and health sectors, with few countries also using their potential for guiding food system policies in other sectors ( [[#Wijesinha-Bettoni--2021|Wijesinha-Bettoni et al. 2021]] ).

Despite the fact that 1.5 billion people follow a vegetarian diet from choice or necessity, and that the position statements of various nutrition societies point out that vegetarian diets are adequate if well planned, few FBDGs give recommendations for vegetarian diets ( [[#Costa%20Leite--2020|Costa Leite et al. 2020]] ). An increase in consumption of plant-based food is a recurring recommendation in FBDGs, though an explicit reduction or limit of animal-source proteins is not often included, with the exception of red or processed meat ( [[#Temme--2020|Temme et al. 2020]] ). To account for changing dietary trends, however, FBDGs need to incorporate sustainability aspects ( [[#Herforth--2019|Herforth et al. 2019]] ). A healthy diet respecting planetary boundaries has been proposed by [[#Willett--2019|Willett et al. (2019)]] , though some authors have questioned the validity of the nutritional ( [[#Zagmutt--2019|Zagmutt et al. 2019]] ) or environmental implications, such as water use ( [[#Vanham--2020|Vanham et al. 2020]] ). In October 2019, 14 global cities pledged to adhere to this ‘planetary health diet’ ( [[#C40%20Cities--2019|C40 Cities 2019]] ).

'''Education on food/nutrition and environment:''' Some consumers are reluctant to adopt sustainable healthy dietary patterns because of a lack of awareness of the environmental and health consequences of what they eat, but also out of suspicion towards alternatives that are perceived as not ‘natural’ and that seem to be difficult to integrate into their daily dietary habits ( [[#Hartmann--2017|Hartmann and Siegrist 2017]] ; [[#Stephens--2018|Stephens et al. 2018]] ; [[#McBey--2019|McBey et al. 2019]] ; [[#Siegrist--2020|Siegrist and Hartmann 2020]] ) or simply lack of knowledge on how to prepare or eat unfamiliar foods ( [[#El%20Bilali--2019|El Bilali 2019]] ; [[#Aiking--2020|Aiking and de Boer 2020]] ; [[#Temme--2020|Temme et al. 2020]] ). Misconceptions may contribute, for example, to the belief that packaging or ‘food miles’ dominate the climate impact of food ( [[#Macdiarmid--2016|Macdiarmid et al. 2016]] ). However, spillover effects can induce sustainable behaviour from ‘entry points’ such as concerns about food waste ( [[#El%20Bilali--2019|El Bilali 2019]] ). Early-life experiences are crucial determinants for adopting healthy and sustainable lifestyles ( [[#Bascopé--2019|Bascopé et al. 2019]] ; [[#McBey--2019|McBey et al. 2019]] ), so improved understanding of sustainability aspects in the education of public health practitioners and in university education is proposed ( [[#Wegener--2018|Wegener et al. 2018]] ). Investment in education, particularly of women ( [[#Vermeulen--2020|Vermeulen et al. 2020]] ), might lower the barrier for stronger policies to be accepted and effective ( [[#McBey--2019|McBey et al. 2019]] ; [[#Temme--2020|Temme et al. 2020]] ) ( ''medium evidence, h'' ''igh agreement'' ) ''.''

'''Food labels:''' Instruments to improve transparency and information on food sustainability aspects are based on the assumption of the ‘rational’ consumer. Information gives the necessary freedom of choice, but also the responsibility to make the ‘right choice’ ( [[#Kersh--2015|Kersh 2015]] ; [[#Bucher--2016|Bucher et al. 2016]] ). Studies find a lack of consumer awareness about the link between own food choices and environmental effect ( [[#Grebitus--2016|Grebitus et al. 2016]] ; [[#Leach--2016|Leach et al. 2016]] ; [[#Hartmann--2017|Hartmann and Siegrist 2017]] ; [[#de%20Boer--2018|de Boer et al. 2018]] ) and so effective messaging is required to raise awareness and acceptance of potentially stricter food system policies.

Back-of-package labels usually provide detailed nutritional information ( [[#Temple--2019|Temple 2019]] ). Front-of-package labels simplify and interpret the information: for example, the traffic light system or the Nutri-Score label used in France ( [[#Kanter--2018b|Kanter et al. 2018b]] ) and the health star rating used in Australia and New Zealand ( [[#Shahid--2020|Shahid et al. 2020]] ) provide an aggregate rating based on product attributes such as energy, sugar, saturated fat and fibre content; other labels warn against frequent consumption (e.g., in the 1990s Finland introduced a mandatory warning for products high in salt; the keyhole label was introduced in Sweden in 1989 ( [[#Storcksdieck%20genannt%20Bonsmann--2020|Storcksdieck genannt Bonsmann et al. 2020]] ); and ‘high in’ (energy/saturated fat/sugar) labels were introduced in Chile in 2016 to reduce obesity ( [[#Corvalán--2019|Corvalán et al. 2019]] )). Front-of-package labels serve also as an incentive to industry to produce healthier or more sustainable products, or can serve as a marketing strategy ( [[#Van%20Loo--2014|Van Loo et al. 2014]] ; [[#Apostolidis--2016|Apostolidis and McLeay 2016]] ; [[#Kanter--2018b|Kanter et al. 2018b]] ). Carbon footprint labels can be difficult for consumers to understand ( [[#Hyland--2017|Hyland et al. 2017]] ), and simple, interpretative summary indicators used on front-of-package labels (e.g., traffic lights) are more effective than more complex ones ( [[#Bauer--2019|Bauer and Reisch 2019]] ; [[#Ikonen--2019|Ikonen et al. 2019]] ; [[#Temple--2019|Temple 2019]] ; [[#Tørris--2019|Tørris and Mobekk 2019]] ) ( ''robust evidence, high agreement'' ) ''.'' Reviews find mixed results but overall a positive effect of food labels in improving direct purchasing decisions ( [[#Hieke--2016|Hieke and Harris 2016]] ; [[#Sarink--2016|Sarink et al. 2016]] ; [[#Anastasiou--2019|Anastasiou et al. 2019]] ; [[#Shangguan--2019|Shangguan et al. 2019]] ; [[#Temple--2019|Temple 2019]] ), and in raising levels of awareness, thus possibly increasing success of other policy instruments ( [[#Apostolidis--2016|Apostolidis and McLeay 2016]] ; [[#Samant--2016|Samant and Seo 2016]] ; [[#Al-Khudairy--2019|Al-Khudairy et al. 2019]] ; [[#Miller--2019|Miller et al. 2019]] ; [[#Temple--2019|Temple 2019]] ) ( ''medium evidence'' , ''h'' ''igh agreement'' ).

<div id="12.4.4.4" class="h3-container"></div>

<span id="behavioural-instruments"></span>
==== 12.4.4.4 Behavioural Instruments ====

<div id="h3-15-siblings" class="h3-siblings"></div>

Choice architecture: Information is more effective if accompanied by reinforcement through structural changes or by changing the food environment, such as through product placement in supermarkets, to overcome the intention–behaviour gap ( [[#Bucher--2016|Bucher et al. 2016]] ; [[#Broers--2017|Broers et al. 2017]] ; [[#Tørris--2019|Tørris and Mobekk 2019]] ). Behavioural change strategies have also been shown to improve efficiencies of school food programmes ( [[#Marcano-Olivier--2020|Marcano-Olivier et al. 2020]] ).

Environmental considerations rank behind financial, health, or sensory factors for determining citizens’ food choices ( [[#Leach--2016|Leach et al. 2016]] ; [[#Hartmann--2017|Hartmann and Siegrist 2017]] ; [[#Neff--2018|Neff et al. 2018]] ; [[#Rose--2018|Rose 2018]] ; [[#Gustafson--2019|Gustafson et al. 2019]] ). There is evidence that choice architecture (‘nudging’) can be effective in influencing purchase decisions, but regulators do not normally explore this option ( [[#Broers--2017|Broers et al. 2017]] ). Examples of green nudging include making the sustainable option the default option, enhancing visibility, accessibility of, or exposure to, sustainable products and reducing visibility and accessibility of unsustainable products, or increasing the salience of healthy sustainable choices through social norms or food labels ( [[#Bucher--2016|Bucher et al. 2016]] ; [[#Wilson--2016|Wilson et al. 2016]] ; [[#Broers--2017|Broers et al. 2017]] ; [[#Al-Khudairy--2019|Al-Khudairy et al. 2019]] ; [[#Bauer--2019|Bauer and Reisch 2019]] ; [[#Ferrari--2019|Ferrari et al. 2019]] ; [[#Weinrich--2019|Weinrich and Elshiewy 2019]] ; [[#Cialdini--2021|Cialdini and Jacobson 2021]] ). Available evidence suggests that choice architecture measures are relatively inexpensive and easy to implement ( [[#Ferrari--2019|Ferrari et al. 2019]] ; [[#Tørris--2019|Tørris and Mobekk 2019]] ), they are a preferred solution if a restriction of choices is to be avoided ( [[#Wilson--2016|Wilson et al. 2016]] ; [[#Kraak--2017|Kraak et al. 2017]] ; [[#Vecchio--2019|Vecchio and Cavallo 2019]] ), and can be effective ( [[#Arno--2016|Arno and Thomas 2016]] ; [[#Bucher--2016|Bucher et al. 2016]] ; [[#Bianchi--2018b|Bianchi et al. 2018b]] ; [[#Cadario--2018|Cadario and Chandon 2018]] ) if embedded in policy packages ( [[#Wilson--2016|Wilson et al. 2016]] ; [[#Tørris--2019|Tørris and Mobekk 2019]] ) ( ''medium evidence, h'' ''igh agreement'' ).

Choice architecture measures are also facilitated by growing market shares of animal-free protein sources taken up by discount chains and fast food companies, that enhance visibility of new products and ease integration into daily life for consumers, particularly if sustainable products are similar to the products they substitute (Slade 2018). This effect can be further increased by media and role models ( [[#Elgaaied-Gambier--2018|Elgaaied-Gambier et al. 2018]] ).

<div id="12.4.5" class="h2-container"></div>

<span id="food-systems-governance"></span>
=== 12.4.5 Food Systems Governance ===

<div id="h2-17-siblings" class="h2-siblings"></div>

To support the policies outlined in [[#12.4.4|Section 12.4.4]] , food system governance depends on the cooperation of actors across traditional sectors in several policy areas, in particular agriculture, nutrition, health, trade, climate, and environment ( [[#Termeer--2018|Termeer et al. 2018]] ; [[#Bhunnoo--2019|Bhunnoo 2019]] ; [[#Diercks--2019|Diercks et al. 2019]] ; [[#iPES%20Food--2019|iPES Food 2019]] ; [[#Rosenzweig--2020b|Rosenzweig et al. 2020b]] ). Top-down integration, mandatory mainstreaming, or boundary-spanning structures like public-private partnerships may be introduced to promote coordination ( [[#Termeer--2018|Termeer et al. 2018]] ). ‘Flow-centric’ rather than territory-centric governance combined with private governance mechanisms has enabled codes of conduct and certification schemes ( [[#Eakin--2017|Eakin et al. 2017]] ), for example the Roundtable on Sustainable Palm Oil (RSPO), as well as commodity chain transparency initiatives and platforms like Trase ( [[#Meijaard--2020|Meijaard et al. 2020]] ; [[#Pirard--2020|Pirard et al. 2020]] ). Trade agreements are an emerging arena of governance in which improving GHG performance may be an objective, and trade agreements can involve sustainability assessments.

Research on food system governance is mostly non-empirical or case study based, which means that there is limited understanding of which governance arrangements work in specific social and ecological contexts to produce particular food system outcomes ( [[#Delaney--2018|Delaney et al. 2018]] ). Research has identified a number of desirable attributes in food systems governance, including adaptive governance ( [[#Termeer--2018|Termeer et al. 2018]] ), a systems perspective ( [[#Whitfield--2018|Whitfield et al. 2018]] ), governance that considers food system resilience ( [[#Ericksen--2008|Ericksen 2008]] ; [[#Moragues-Faus--2017|Moragues-Faus et al. 2017]] ; [[#Meyer--2020|Meyer 2020]] ), transparency, participation of civil society ( [[#Candel--2014|Candel 2014]] ; [[#Duncan--2015|Duncan 2015]] ;), and cross-scale governance ( [[#Moragues-Faus--2017|Moragues-Faus et al. 2017]] ).

Food systems governance has multiple targets and objectives, not least contributing to the achievement of the SDGs. GHG emissions from food systems can be impacted by both interventions targeted at different parts of the food system and interventions in other systems, such as reducing deforestation or promoting reforestation ( [[#Lee--2019|Lee et al. 2019]] ). For example, policies targeting health can contribute to diet shifts away from red meat, while also influencing GHG emissions ( [[#Springmann--2018b|Springmann et al. 2018b]] ; [[#Semba--2020|Semba et al. 2020]] ); national and local food self-sufficiency policies may also have GHG impacts ( [[#Kriewald--2019|Kriewald et al. 2019]] ; [[#Loon--2019|Loon et al. 2019]] ). Cross-sectoral governance could enhance synergies between reduced GHG emissions from food systems and other goals; however, integrative paradigms for cross-sectoral governance between food and other sectors have faced implementation challenges ( [[#Delaney--2018|Delaney et al. 2018]] ). For example, in the late 2000s, the water-energy-food nexus emerged as a framework for cross-sectoral governance, but has not been well integrated into policy ( [[#Urbinatti--2020|Urbinatti et al. 2020]] ), perhaps because of perceptions that it is an academic concept, or that it takes a technical-administrative view of governance; simply adopting the paradigm is not sufficient to develop effective nexus governance ( [[#Cairns--2016|Cairns and Krzywoszynska 2016]] ; [[#Weitz--2017|Weitz et al. 2017]] ; [[#Pahl-Wostl--2018|Pahl-Wostl et al. 2018]] ). Other policy paradigms and theoretical frameworks that aim to integrate food systems governance include system transition, agroecology, multifunctionality in agriculture ( [[#Andrée--2018|Andrée et al. 2018]] ), climate-smart agriculture ( [[#Taylor--2018|Taylor 2018]] ) and the circular economy ( ). Cross-sectoral coordination on food systems and climate governance could be aided by internal recognition and ownership by agencies, dedicated budgets for cross-sectoral projects, and consistency in budgets ( [[#Pardoe--2018|Pardoe et al. 2018]] ) (Boxes 12.1 and 12.2).

Food systems governance is still fragmented at national levels, which means that there may be a proliferation of efforts that cannot be scaled and are ineffective ( [[#Candel--2014|Candel 2014]] ). National policies can be complemented or possibly pioneered by initiatives at the local level ( [[#de%20Boer--2018|de Boer et al. 2018]] ; [[#Rose--2018|Rose 2018]] ). The city-region has been proposed as a useful focus for food system governance ( [[#Vermeulen--2020|Vermeulen et al. 2020]] ); for example, the Milan Urban Food Policy Pact involves 180 global cities committed to integrative food system strategies ( [[#Candel--2019|Candel 2019]] ; [[#Moragues-Faus--2021|Moragues-Faus 2021]] ). Local food policy groups and councils that assemble stakeholders from government, civil society, and the private sector have formed trans-local networks of place-based local food policy groups, with over two hundred food policy councils worldwide ( [[#Andrée--2018|Andrée et al. 2018]] ). However, the fluidity and lack of clear agendas and membership structures may hinder their ability to confront fundamental structural issues like unsustainable diets or inequities in food access ( [[#Santo--2019|Santo and Moragues-Faus 2019]] ).

Early characterisations of food systems governance featured a binary distinction between global and local scales, but this has been replaced by a relational approach where the local governance is seen as a process that relies on the interconnections between scales ( [[#Lever--2019|Lever et al. 2019]] ). Cross-scalar governance is not simply an aggregation of local groups, but involves the telecoupling of distant systems; for example, transnational NGO networks have been able to link coffee retailers in the global North with producers in the global South via international NGOs concerned about deforestation and social justice ( [[#Eakin--2017|Eakin et al. 2017]] ). Global governance institutions like the Committee on World Food Security can promote policy coherence globally and reinforce accountability at all levels ( [[#McKeon--2015|McKeon 2015]] ), as can norm-setting efforts like the Voluntary Guidelines for the Responsible Governance of Tenure of Land, Fisheries and Forests ( [[#FAO--2012|FAO 2012]] ). Global multi-stakeholder processes like the UN Food Systems Summit can foster the development of principles for guiding further actions based on sound scientific evidence. The European Commission’s Farm to Fork strategy aims to promote policy coherence in food policy at EU and national levels, and could be the exemplar of a genuinely integrated food policy ( [[#Schebesta--2020|Schebesta and Candel 2020]] ).

<div id="Box 12" class="h2-container"></div>

<span id="box-12-.2-case-study-the-finnish-fo-od2030-strategy"></span>
=== Box 12.2 | Case Study: The Finnish Food2030 Strategy ===

<div id="h2-18-siblings" class="h2-siblings"></div>

Until 2016, the strategic goals of Finnish food policy were split between different programmes and ministries, resulting in fragmented national oversight of the Finnish food system. To enable policy coordination, a national food strategy was adopted in 2017 called Food2030 ( [[#Government%20of%20Finland--2017|Government of Finland 2017]] ). Food2030 embodies a holistic food system approach and addresses multiple outcomes of the food system, including the competitiveness of the food supply chain and the development of local, organic and climate-friendly food production, as well as responsible and sustainable consumption.

The specific policy mix covers a range of policy instruments to enable changes in agro-food supply, processing and societal norms ( [[#Kugelberg--2021|Kugelberg et al. 2021]] ). The government provides targeted funding and knowledge support to drive technological innovations on climate solutions to reduce emissions from food and in the agriculture, forestry and land use sectors. In addition, the Finnish government applies administrative means, such as legislation, advice, guidance on public procurement and support schemes to diversify and increase organic food production to 20% of arable land, which in turn improve the opportunities for small-scale food production and steer public bodies to purchase local and organic food. The Finnish government applies educational and informative instruments to enable a shift to healthy and sustainable dietary behaviours. The policy objective is to reduce consumption of meat and replace it with other sources of protein, aligned with nutrition recommendations and avoiding food waste. The Ministry of Agriculture and Forestry, in collaboration with the Finnish Farmer’s unions and the Union of Swedish-speaking Farmers and Forest Owners in Finland, ran a two-year multi-media campaign in 2018 with key messages on the sustainability, traceability and safety of locally-produced food ( [[#Ministry%20of%20Agriculture%20and%20Forestry--2021|Ministry of Agriculture and Forestry 2021]] ). A ’Food Facts’ website project ( [[#Luke--2021|Luke 2021]] ), funded by the Ministry of Agriculture and Forestry in collaboration with the Natural Resources Institute Finland and the Finnish Food Safety Authority, helps to raise knowledge about food, which could shape responsible individual food behaviour, for example choosing local and sustainable foods and reducing food waste.

A critical enabler for developing a shared food system strategy across sectors and political party boundaries was the implementation of a one-year inclusive, deliberative and consensual stakeholder engagement process. A wide range of stakeholders could exert real influence during the vision-building process, resulting in strong agreement on key policy objectives, and subsequently an important leverage point to policy change ( [[#Kugelberg--2021|Kugelberg et al. 2021]] ). Moreover, cross-sectoral coordination of Food2030 and the government’s wider climate action programmes are enabled by a number of institutional mechanisms and collaborative structures, for example the advisory board for the food chain, formally established during the agenda-setting stage of Food2030, inter-ministerial committees to guide and assess policy implementation, and Our Common Dining Table, a multi-stakeholder partnership that assembles 18 food system actors to engage in reflexive discussions about the Finnish food system.

Box 12.2

Critical barriers to strategy and policy formulation include a lack of attention to integrated impact assessments ( [[#Kugelberg--2021|Kugelberg et al. 2021]] ), which blurs a transparent overview of potential trade-offs and hidden conflicts. There were few policy evaluations from independent organisations to inform policymaking, reducing the opportunities for more progressive policy approaches. Monitoring and food policy evaluation is very close to the ministry in charge, which hampers critical thinking about policy measures ( [[#Hildén--2014|Hildén et al. 2014]] ). In addition, there is a lack of standardised indicators covering the whole food system, which hinders comprehensive oversight of progress towards a sustainable food system ( [[#Kanter--2018a|Kanter et al. 2018a]] ). Some of the problems related to monitoring, reporting and verification (MRV) are typical for countries in the EU. To improve, MRV will probably require structural changes, such as efforts to build up institutional capacity and application of new technology, development of standardised indicators covering the whole food system, regulations on transparency and verification, and mechanisms to enable reflexive discussions between business, farmers, public, NGOs and the government ( [[#Meadowcroft--2018|Meadowcroft and Steurer 2018]] ; [[#Kanter--2020|Kanter et al. 2020]] ).

<div id="12.5" class="h1-container"></div>

<span id="land-related-impacts-risks-and-opportunities-associated-with-mitigation-options"></span>