Abstract. Urban surfaces are usually net sources of CO2. Vegetation can potentially have an important role in reducing the CO2 emitted by anthropogenic activities in cities, particularly when vegetation is extensive and/or evergreen. A direct and accurate estimation of carbon uptake by urban vegetation is difficult due to the particular characteristics of the urban ecosystem and high variability in tree distribution and species. Here, we investigate the role of urban vegetation in the CO2 flux from a residential neighbourhood in Singapore using two different approaches. CO2 fluxes measured directly by eddy covariance are compared with emissions estimated from emissions factors and activity data. The latter includes contributions from vehicular traffic, household combustion, soil respiration and human breathing. The difference between estimated emissions and measured fluxes should approximate the flux associated with the aboveground vegetation. In addition, a tree survey was conducted to estimate the annual CO2 sequestration using allometric equations and an alternative model of the metabolic theory of ecology for tropical forests. Palm trees, banana plants and turfgrass were also included in the survey with their annual CO2 uptake obtained from published growth rates. Both approaches agree within 2% and suggest that vegetation sequesters 8% of the total emitted CO2 in the residential neighbourhood studied. An uptake of 1.4 ton km−2 day−1 (510 ton km−2 yr−1) was estimated as the difference between assimilation by photosynthesis minus the aboveground biomass respiration during daytime (4.0 ton km−2 day−1) and release by plant respiration at night (2.6 ton km−2 day−1). However, when soil respiration is added to the daily aboveground flux, the biogenic component becomes a net source amounting to 4% of the total CO2 flux and represents the total contribution of urban vegetation to the carbon flux to the atmosphere.
Abstract. The number of deaths from landslides in Nepal has been increasing dramatically due to a complex combination of earthquakes, climate change, and an explosion of informal road construction that destabilizes slopes during the rainy season. This trend will likely rise as development continues, especially as China's Belt and Road Initiative seeks to construct three major trunk roads through the Nepali Himalaya that adjacent communities will seek to tie in to with poorly constructed roads. To determine the effect of these informal roads on generating landslides, we compare the distance between roads and landslides triggered by the 2015 Gorkha earthquake with those triggered by monsoon rainfalls, as well as a set of randomly located landslides to determine if the spatial correlation is strong enough to further imply causation. If roads are indeed causing landslides, we should see a clustering of rainfall-triggered landslides closer to the roads that accumulate and focus the water that facilitates failure. We find that in addition to a concentration of landslides in landscapes with more developed, agriculturally viable soils, that the rainfall-triggered landslides are more than twice as likely to occur within 100 m of a road than the landslides generated by the earthquake. The oversteepened slopes, poor water drainage and debris management provide the necessary conditions for failure during heavy monsoonal rains. Based on these findings, geoscientists, planners and policymakers must consider how road development affects the physical (and ecological), socio-political and economic factors that increase risk in exposed communities, alongside ecologically and financially sustainable solutions such as green roads.
Urban surfaces are usually net sources of CO2. Vegetation can potentially have an important role in reducing the CO2 emitted by anthropogenic activities in cities, particularly when vegetation is extensive and/or evergreen. Negative daytime CO2 fluxes, for example have been observed during the growing season at suburban sites characterized by abundant vegetation and low population density. A direct and accurate estimation of carbon uptake by urban vegetation is difficult due to the particular characteristics of the urban ecosystem and high variability in tree distribution and species. Here, we investigate the role of urban vegetation in the CO2 flux from a residential neighbourhood in Singapore using two different approaches. CO2 fluxes measured directly by eddy covariance are compared with emissions estimated from emissions factors and activity data. The latter includes contributions from vehicular traffic, household combustion, soil respiration and human breathing. The difference between estimated emissions and measured fluxes should approximate the biogenic flux. In addition, a tree survey was conducted to estimate the annual CO2 sequestration using allometric equations and an alternative model of the metabolic theory of ecology for tropical forests. Palm trees, banana plants and turfgrass were also included in the survey with their annual CO2 uptake obtained from published growth rates. Both approaches agree within 2% and suggest that vegetation captures 8% of the total emitted CO2 in the residential neighbourhood studied. A net uptake of 1.4 ton km−2 day−1 (510 ton km−2 yr−1 ) was estimated from the difference between the daily CO2 uptake by photosynthesis (3.95 ton km−2 ) and release by respiration (2.55 ton km−2). The study shows the importance of urban vegetation at the local scale for climate change mitigation in the tropics
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.