Editing IPCC:AR6/WGIII/Chapter-8 (section)

=== Box 8.2: Urban Carbon Storage: An Example from New York City ===

<div id="h2-19-siblings" class="h2-siblings"></div>

The structure, composition, extent, and growing conditions of vegetation in cities has an influence on their potential for mitigating climate change ( [[#Pregitzer--2021|Pregitzer et al. 2021]] ). Urban natural areas, particularly forested natural areas, grow in patches and contain many of the same components as non-urban forests, such as high tree density, down woody material, and regenerating trees (Box 8.2, Figure 1).

<div id="_idContainer00e"></div>

[[File:be07ee82a2555dd5d2b39e1f2e66fe58 IPCC_AR6_WGIII_Box_8_1_Figure_1.png]]

'''Box 8.2, Figure 1: Estimates for carbon storage in natural area forests in New York City.''' '''(a)''' Mean estimated carbon stock per hectare in natural area forests ( [[#Pregitzer--2019a|Pregitzer et al. 2019a]] , 2021); '''(b)''' estimates for carbon stocks vary based on vegetation types; and '''(c)''' estimates of the amount of carbon stock in different forest pools per hectare. The proportion of the total estimated carbon stock per pool is out of the total estimated for the entire city (1.86 TgC). Source: adapted from [[#Pregitzer--2021|Pregitzer et al. (2021)]] .

Urban forested natural areas have unique benefits as they can provide habitat for native plants and animals, protecting local biodiversity in a fragmented landscape ( [[#Di%20Giulio--2009|Di Giulio et al. 2009]] ). Forests can have a greater cooling effect on cities than designed greenspaces, and the bigger the forest the greater the effect ( [[#Jaganmohan--2016|Jaganmohan et al. 2016]] ). In New York City, urban forested natural areas have been found to account for the majority of trees estimated in the city (69%), but are a minority of the total tree canopy (25%, or 5.5% of the total city land area) ( [[#Pregitzer--2019a|Pregitzer et al. 2019a]] ). In New York City, natural areas are estimated to store a mean of 263.5 MgC ha –1 (megagram carbon per hectare), adding up to 1.86 TgC (teragram carbon) across the city, with the majority of carbon (86%) being stored in the trees and soils ( [[#Pregitzer--2021|Pregitzer et al. 2021]] ). These estimates are similar to per-hectare estimates of carbon storage across different pools in non-urban forest types (Table 1), and 1.5 times greater than estimates for carbon stored in just trees across the entire city ( [[#Pregitzer--2021|Pregitzer et al. 2021]] ).

Within urban natural areas, the amount of carbon stored varies widely based on vegetation type, tree density, and the species composition (Box 8.2, Figure 1). The oak-hardwood forest type is one of the most abundant in New York City’s natural areas and is characterised by large and long-lived native hardwood tree species, with relatively dense wood. These forests store an estimated 311.5 MgC ha –1 . However, non-native exotic invasive species can be prevalent in the understory vegetation layer (&lt;1m height), and account for about 50% of cover in New York City ( [[#Pregitzer--2019b|Pregitzer et al. 2019b]] ).

This could lead to a trajectory where exotic understory species, which are often herbaceous, out-compete regenerating trees in the understory layer, alter the soil ( [[#Ward--2020|Ward et al. 2020]] ), and alter the forest canopy ( [[#Matthews--2016|Matthews et al. 2016]] ). A change in New York City’s vegetation structure and composition to a more open vegetation type could reduce the carbon storage by over half (open grassland 120.1 MgC ha –1 ).

When compared to estimates of carbon storage presented in other studies, the components (pools) of the natural area forests in New York City store carbon in similar proportions to other non-urban forests (see Table 1). This might suggest that in other geographies, similar adjacent non-urban forest types may store similar carbon stocks per unit area ( ''medium confidence'' ). However, despite similarities to non-urban forests, the urban context can lead to altered forest function and carbon cycling that should be considered. For example, trees growing in urban areas have been observed to grow at much higher rates due to higher access to light, nutrients, and increased temperatures ( [[#Gregg--2003|Gregg et al. 2003]] ; [[#Reinmann--2020|Reinmann et al. 2020]] ).

Higher growth rates coupled with the UHI effect have also been suggested to yield greater evaporative cooling by urban canopies relative to rural forests ( [[#Winbourne--2020|Winbourne et al. 2020]] ). Based on estimates in New York City, it is likely that the majority of tree biomass, and carbon in trees in cities, could be found in urban natural area forest patches ( ''medium agreement'' , ''limited evidence'' ). More research is needed to map urban natural areas, assess vegetation, and differentiate tree canopy types (natural versus non-natural) at fine scales within many cities and geographies. Accurate maps, as well as greater understanding of definitions of urban canopies and vegetation, could lead to better accounts for carbon stocks and the many other unique benefits they provide ( [[#Raciti--2012|Raciti et al. 2012]] ; [[#Pregitzer--2019a|Pregitzer et al. 2019a]] ).

Despite this potential, natural areas are inherently a minority land-use type in cities and should be viewed along with other types of urban tree canopy that occur in more designed environments that might out-perform natural areas in other ecosystem services. The mosaic of vegetation characteristics and growing conditions will yield different ecosystem services across cities ( [[#Pataki--2011|Pataki et al. 2011]] ) and should be an important consideration in planning, management, and policy in the future.

'''Box 8.2, Table 1: A selection of benchmark reference estimates of different carbon pools sampled and the related urban considerations to contextualise the results from New York City (NYC), United States (USA) natural area carbon stocks.''' The benchmark estimates are intended to provide a point of reference to help contextualise the calculations for carbon pools in NYC’s forests. Forest carbon is highly variable and dependent on microclimatic conditions such as moisture, microbial communities, and nutrient availability, all of which can be impacted by human activity in urban or altered environments. Standard errors and 95% confidence intervals can be found in [[#Pregitzer--2021|Pregitzer et al. (2021)]] . DBH: diameter at breast height; DWM: down woody material; CWM: coarse woody material and FWM: fine woody material. Source: [[#Pregitzer--2021|Pregitzer et al. (2021)]] .

{| class="wikitable"
|-
! Pool considered in NYC natural area

! Published estimates of carbon stock (MgC ha –1 )

! NYC estimated carbon stock (MgC ha –1 )

! Urban considerations

|-
| Live trees: all trees (&gt;2 cm DBH) including above and below ground

| 87.1: northeastern USA ( [[#Smith--2013|Smith et al. 2013]] )

73.3: NYC assuming 100% cover ( [[#Nowak--2013|Nowak et al. 2013]] )

| 135.4

| Lower ozone levels, higher CO 2 , warmer temperatures, and higher nutrient deposition could lead to increased growth rates and annual carbon sequestration. However, pollutants in soil (e.g., heavy metals), increased pests, and GHGs in the atmosphere (e.g., NO X and SO 2 ) could decrease annual tree growth and carbon sequestration ( [[#Gregg--2003|Gregg et al. 2003]] )

|-
| Groundcover: all vegetation growing &lt;1 m height

| 1.8: northeastern USA ( [[#Smith--2013|Smith et al. 2013]] )

| 5.5

| Anthropogenic disturbance creates canopy gaps that accelerate herbaceous growth; invasive vines are prevalent in urban forests that can alter tree survival and growth and soils ( [[#Matthews--2016|Matthews et al. 2016]] ; [[#Ward--2020|Ward et al. 2020]] )

|-
| Standing dead trees

| 5.1: northeastern USA ( [[#Smith--2013|Smith et al. 2013]] )

2.59: Massachusetts ( [[#Liu--2006|Liu et al. 2006]] )

| 5.8

| Removal may occur due to safety considerations

|-
| CWM: coarse (&gt;10 cm) and FWM (&gt;0.1 cm)

| 9.18: CWM – New York state

2.52: CWM – Massachusetts ( [[#Liu--2006|Liu et al. 2006]] )

6.37: FWM – New York ( [[#Woodall--2013|Woodall et al. 2013]] )

3.67: FWM northern hardwood; 0 to 227.94: Northern USA ( [[#Domke--2016|Domke et al. 2016]] )

| 15.25 (added together DWM and FWM)

| Removal may occur due to safety considerations

|-
| Litter and duff: depth measured

| 12: NYC ( [[#Pouyat--2002|Pouyat et al. 2002]] )

9.36: northern hardwood;

0.04: northern USA ( [[#Domke--2016|Domke et al. 2016]] )

| 10.95

| Decomposition increases with temperature ( [[#Hanson--2003|Hanson et al. 2003]] ); decreased ozone levels facilitate litter decay ( [[#Carreiro--2009|Carreiro et al. 2009]] )

|-
| Mineral soil (organic 30 cm)

| 104: to 30 cm depth, NYC ( [[#Cambou--2018|Cambou et al. 2018]] )

50: to 10 cm depth, NYC ( [[#Pouyat--2002|Pouyat et al. 2002]] )

| 105.11(30 cm) and 77.78 (10 cm)

| UHI and pollution alter the litter chemistry, decomposer organisms, conditions, and resources, which all influence respiration rates ( [[#Carreiro--2009|Carreiro et al. 2009]] ); earthworms, prevalent in urban areas, accelerate decay, but some carbon is sequestered in passive pools ( [[#Pouyat--2002|Pouyat et al. 2002]] ). Soil could be compacted.

|}

<div id="8.4.4.2" class="h3-container"></div>

<span id="benefits-of-green-roofs-green-walls-and-greenways"></span>
==== 8.4.4.2 Benefits of Green Roofs, Green Walls, and Greenways ====

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

Green roofs and green walls have potential to mitigate air and surface temperature, improve thermal comfort, and mitigate UHI effects ( [[#Jamei--2021|Jamei et al. 2021]] ; [[#Wong--2021|Wong et al. 2021]] ), while lowering the energy demand of buildings ( [[#Susca--2019|Susca 2019]] ) (Figure 8.18). Green roofs have the highest median cooling effect in dry climates (3°C) and the lowest cooling effect in hot, humid climates (1°C) ( [[#Jamei--2021|Jamei et al. 2021]] ). These mitigation potentials depend on numerous factors and the scale of implementation. The temperature reduction potential for green roofs when compared to conventional roofs can be about 4°C in winter and about 12°C during summer conditions ( [[#Bevilacqua--2016|Bevilacqua et al. 2016]] ). Green roofs can reduce building heating demands by about 10–30% compared to conventional roofs ( [[#Besir--2018|Besir and Cuce 2018]] ), 60–70% compared to black roofs, and 45–60% compared to white roofs ( [[#Silva--2016|Silva et al. 2016]] ). Green walls or facades can provide a temperature difference between air temperature outside and behind a green wall of up to 10°C, with an average difference of 5°C in Mediterranean contexts in Europe ( [[#Perini--2017|Perini et al. 2017]] ). The potential of saving energy for air conditioning by green facades can be around 26% in summer months. Considerations of the spatial context are essential given their dependence on climatic conditions ( [[#Susca--2019|Susca 2019]] ). Cities are diverse and emissions savings potentials depend on several factors, while the implementation of green roofs or facades may be prevented in heritage structures.

Green roofs have been shown to have beneficial effects in stormwater reduction ( [[#Andrés-Doménech--2018|Andrés-Doménech et al. 2018]] ). A global meta-analysis of 75 international studies on the potential of green roofs to mitigate runoff indicate that the runoff retention rate was on average 62% but with a wide range (0–100%) depending on a number of interdependent factors ( [[#Zheng--2021|Zheng et al. 2021]] ). These factors relate to the characteristics of the rainfall event (e.g., intensity) and characteristics of the green roof (e.g., substrate, vegetation type, and size), and of the climate and season type. A hydrologic modelling approach applied to an Italian case demonstrated that implementing green roofs may reduce peak runoff rates and water volumes by up to 35% in a 100% green roof conversion scenario ( [[#Masseroni--2016|Masseroni and Cislaghi 2016]] ).

Greenways support stormwater management to mitigate water runoff and urban floods by reducing the water volume (e.g., through infiltration) and by an attenuation or temporal shift of water discharge ( [[#Fiori--2020|Fiori and Volpi 2020]] ; [[#Pour--2020|Pour et al. 2020]] ). Using green infrastructure delays the time to runoff and reduces water volume but depends on the magnitude of floods ( [[#Qin--2013|Qin et al. 2013]] ). Measures are most effective for flood mitigation at a local scale; however, as the size of the catchment increases, the effectiveness of reducing peak discharge decreases ( [[#Fiori--2020|Fiori and Volpi 2020]] ). Reduction of water volume through infiltration can be more effective with rainfall events on a lower return rate. Overall, the required capacity for piped engineered systems for water runoff attenuation and mitigation can be reduced while lowering flow rates, controlling pollution transport, and increasing the capacity to store stormwater ( [[#Srishantha--2017|Srishantha and Rathnayake 2017]] ). Benefits for flood mitigation require a careful consideration of the spatial context of the urban area, the heterogeneity of the rainfall events, and characteristics of implementation ( [[#Qiu--2021|Qiu et al. 2021]] ). Maintenance costs and stakeholder coordination are other aspects requiring attention ( [[#Mguni--2016|Mguni et al. 2016]] ).

Providing a connected system of greenspace throughout the urban area may promote active transportation ( [[#Nieuwenhuijsen--2016|Nieuwenhuijsen and Khreis 2016]] ), thereby reducing GHG emissions. Soft solutions for improving green infrastructure connectivity for cycling is an urban NBS mitigation measure, although there is ''low evidence'' for emissions reductions. In the city of Lisbon, Portugal, improvements in cycling infrastructure and bike-sharing system resulted in 3.5 times more cyclists within two years ( [[#Félix--2020|Félix et al. 2020]] ). In Copenhagen, the cost of cycling (0.08 EUR km -1 ) is declining and is about six times lower than car driving (Euro 0.50/km) ( [[#Vedel--2017|Vedel et al. 2017]] ). In addition, participants were willing to cycle 1.84 km longer if the route has a designated cycle track and 0.8 km more if there are also green surroundings. Changes in urban landscapes, including through the integration of green infrastructure in sustainable urban and transport planning, can support the transition from private motorised transportation to public and physically active transportation in carbon-neutral, more liveable and healthier cities ( [[#Nieuwenhuijsen--2016|Nieuwenhuijsen and Khreis 2016]] ; [[#Nieuwenhuijsen--2020|Nieuwenhuijsen 2020]] ). Car infrastructure can be also transferred into public open and green space, such as in the Superblock model in Barcelona’s neighbourhoods ( [[#Rueda--2019|Rueda 2019]] ). Health impact assessment models estimated that 681 premature deaths may be prevented annually with this implementation ( [[#Mueller--2020|Mueller et al. 2020]] ) and the creation of greenways in Maanshan, China has stimulated interest in walking or cycling ( [[#Zhang--2020|Zhang et al. 2020]] ).

<div id="8.4.5" class="h2-container"></div>

<span id="socio-behavioural-aspects"></span>