A critical knowledge pathway to low-carbon, sustainable futures: Integrated understanding of urbanization, urban areas, and carbon

Independent lines of research on urbanization, urban areas, and carbon have advanced our understanding of some of the processes through which energy and land uses affect carbon. This synthesis integrates some of these diverse viewpoints as a first step toward a coproduced, integrated framework for understanding urbanization, urban areas, and their relationships to carbon. It suggests the need for approaches that complement and combine the plethora of existing insights into interdisciplinary explorations of how different urbanization processes, and socio-ecological and technological components of urban areas, affect the spatial and temporal patterns of carbon emissions, differentially over time and within and across cities. It also calls for a more holistic approach to examining the carbon implications of urbanization and urban areas, based not only on demographics or income but also on other interconnected features of urban development pathways such as urban form, economic function, economic-growth policies, and other governance arrangements. It points to a wide array of uncertainties around the urbanization processes, their interactions with urban socio-institutional and built environment systems, and how these impact the exchange of carbon flows within and outside urban areas. We must also understand in turn how carbon feedbacks, including carbon impacts and potential impacts of climate change, can affect urbanization processes. Finally, the paper explores options, barriers, and limits to transitioning cities to low-carbon trajectories, and suggests the development of an end-to-end, coproduced and integrated scientific understanding that can more effectively inform the navigation of transitional journeys and the avoidance of obstacles along the way

Integrating Brain and Biomechanical Models—A New Paradigm for Understanding Neuro-muscular Control

To date, realistic models of how the central nervous system governs behavior have been restricted in scope to the brain, brainstem or spinal column, as if these existed as disembodied organs. Further, the model is often exercised in relation to an in vivo physiological experiment with input comprising an impulse, a periodic signal or constant activation, and output as a pattern of neural activity in one or more neural populations. Any link to behavior is inferred only indirectly via these activity patterns. We argue that to discover the principles of operation of neural systems, it is necessary to express their behavior in terms of physical movements of a realistic motor system, and to supply inputs that mimic sensory experience. To do this with confidence, we must connect our brain models to neuro-muscular models and provide relevant visual and proprioceptive feedback signals, thereby closing the loop of the simulation. This paper describes an effort to develop just such an integrated brain and biomechanical system using a number of pre-existing models. It describes a model of the saccadic oculomotor system incorporating a neuromuscular model of the eye and its six extraocular muscles. The position of the eye determines how illumination of a retinotopic input population projects information about the location of a saccade target into the system. A pre-existing saccadic burst generator model was incorporated into the system, which generated motoneuron activity patterns suitable for driving the biomechanical eye. The model was demonstrated to make accurate saccades to a target luminance under a set of environmental constraints. Challenges encountered in the development of this model showed the importance of this integrated modeling approach. Thus, we exposed shortcomings in individual model components which were only apparent when these were supplied with the more plausible inputs available in a closed loop design. Consequently we were able to suggest missing functionality which the system would require to reproduce more realistic behavior. The construction of such closed-loop animal models constitutes a new paradigm of computational neurobehavior and promises a more thoroughgoing approach to our understanding of the brain’s function as a controller for movement and behavior

Estimation of the Relationship Between Remotely Sensed Anthropogenic Heat Discharge and Building Energy Use

This paper examined the relationship between remotely sensed anthropogenic heat discharge and energy use from residential and commercial buildings across multiple scales in the city of Indianapolis, Indiana, USA. The anthropogenic heat discharge was estimated with a remote sensing-based surface energy balance model, which was parameterized using land cover, land surface temperature, albedo, and meteorological data. The building energy use was estimated using a GIS-based building energy simulation model in conjunction with Department of Energy/Energy Information Administration survey data, the Assessor's parcel data, GIS floor areas data, and remote sensing-derived building height data. The spatial patterns of anthropogenic heat discharge and energy use from residential and commercial buildings were analyzed and compared. Quantitative relationships were evaluated across multiple scales from pixel aggregation to census block. The results indicate that anthropogenic heat discharge is consistent with building energy use in terms of the spatial pattern, and that building energy use accounts for a significant fraction of anthropogenic heat discharge. The research also implies that the relationship between anthropogenic heat discharge and building energy use is scale-dependent. The simultaneous estimation of anthropogenic heat discharge and building energy use via two independent methods improves the understanding of the surface energy balance in an urban landscape. The anthropogenic heat discharge derived from remote sensing and meteorological data may be able to serve as a spatial distribution proxy for spatially-resolved building energy use, and even for fossil-fuel CO2 emissions if additional factors are considered

On the Impact of Granularity of Space-Based Urban CO2 Emissions in Urban Atmospheric Inversions: A Case Study for Indianapolis, IN

Quantifying greenhouse gas (GHG) emissions from cities is a key challenge towards effective emissions management. An inversion analysis from the INdianapolis FLUX experiment (INFLUX) project, as the first of its kind, has achieved a top-down emission estimate for a single city using CO2 data collected by the dense tower network deployed across the city. However, city-level emission data, used as a priori emissions, are also a key component in the atmospheric inversion framework. Currently, fine-grained emission inventories (EIs) able to resolve GHG city emissions at high spatial resolution, are only available for few major cities across the globe. Following the INFLUX inversion case with a global 1x1 km ODIAC fossil fuel CO2 emission dataset, we further improved the ODIAC emission field and examined its utility as a prior for the city scale inversion. We disaggregated the 1x1 km ODIAC non-point source emissions using geospatial datasets such as the global road network data and satellite-data driven surface imperviousness data to a 3030 m resolution. We assessed the impact of the improved emission field on the inversion result, relative to priors in previous studies (Hestia and ODIAC). The posterior total emission estimate (5.1 MtC/yr) remains statistically similar to the previous estimate with ODIAC (5.3 MtC/yr). However, the distribution of the flux corrections was very close to those of Hestia inversion and the model-observation mismatches were significantly reduced both in forward and inverse runs, even without hourly temporal changes in emissions. EIs reported by cities often do not have estimates of spatial extents. Thus, emission disaggregation is a required step when verifying those reported emissions using atmospheric models. Our approach offers gridded emission estimates for global cities that could serves as a prior for inversion, even without locally reported EIs in a systematic way to support city-level Measuring, Reporting and Verification (MRV) practice implementation

Interannual variations in continental-scale net carbon exchange and sensitivity to observing networks estimated from atmospheric CO2 inversions for the period 1980 to 2005

Author Posting. © American Geophysical Union, 2008. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 22 (2008): GB3025, doi:10.1029/2007GB003082.Interannually varying net carbon exchange fluxes from the TransCom 3 Level 2 Atmospheric Inversion Intercomparison Experiment are presented for the 1980 to 2005 time period. The fluxes represent the model mean, net carbon exchange for 11 land and 11 ocean regions after subtraction of fossil fuel CO2 emissions. Both aggregated regional totals and the individual regional estimates are accompanied by a model uncertainty and model spread. We find that interannual variability is larger on the land than the ocean, with total land exchange correlated to the timing of both El Niño/Southern Oscillation (ENSO) as well as the eruption of Mt. Pinatubo. The post-Pinatubo negative flux anomaly is evident across much of the tropical and northern extratropical land regions. In the oceans, the tropics tend to exhibit the greatest level of interannual variability, while on land, the interannual variability is slightly greater in the tropics and northern extratropics. The interannual variation in carbon flux estimates aggregated by land and ocean across latitudinal bands remains consistent across eight different CO2 observing networks. The interannual variation in carbon flux estimates for individual flux regions remains mostly consistent across the individual observing networks. At all scales, there is considerable consistency in the interannual variations among the 13 participating model groups. Finally, consistent with other studies using different techniques, we find a considerable positive net carbon flux anomaly in the tropical land during the period of the large ENSO in 1997/1998 which is evident in the Tropical Asia, Temperate Asia, Northern African, and Southern Africa land regions. Negative anomalies are estimated for the East Pacific Ocean and South Pacific Ocean regions. Earlier ENSO events of the 1980s are most evident in southern land positive flux anomalies

Urbanization and the carbon cycle: Current capabilities and research outlook from the natural sciences perspective

This paper explores the urban carbon cycle from the natural sciences perspective, identifying key knowledge gaps and priority areas for future research. The combination of large, concentrated carbon fluxes and rapid change makes cities key elements of the carbon cycle and offers the potential for them to serve as “first responders” for climate action. Estimates of urban‐scale carbon fluxes are significantly more uncertain than at larger spatial scales, in part because past studies have mostly avoided local/urban scales where the mix of anthropogenic and natural fluxes is complex and difficult to observationally isolate. To develop effective emission reduction policies, we need to understand emission sources and how they may be changing. Such improved quantification and understanding of underlying processes at the urban scale will not only provide policy‐relevant information and improve the understanding of urban dynamics and future scenarios, but will also translate into better global‐scale anthropogenic flux estimates, and advance our understanding of carbon cycle and climate feedbacks across multiple scales. Understanding the relationship between urbanization and urban carbon flows requires intellectual integration with research communities beyond the natural sciences. Cities can serve as interdisciplinary process laboratories that are sufficiently constrained in both spatial and governance scale to support truly integrated research by the natural sciences, social sciences, and engineering. A thoughtfully crafted science research agenda that is grounded in sustained, dense observations relevant to estimating urban carbon fluxes and their controlling processes and is focused on a statistically significant sample of cities will advance our understanding of the carbon cycle. Key Points Large carbon fluxes and rapid change make cities key carbon cycle elements Cities represent ideal interdisciplinary carbon cycle process laboratories Sustained campaigns in representative cities will transform urban carbon sciencePeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109579/1/eft244.pd

Targeting deforestation rates in climate change policy: a "Preservation Pathway" approach

We present a new methodological approach to incorporating deforestation within the international climate change negotiating regime. The approach, called "Preservation Pathway" combines the desire for forest preservation with the need to reduce emissions associated with forest loss by focusing on the relative rate of change of forest cover as the criteria by which countries gain access to trading preserved forest carbon stocks. This approach avoids the technically challenging task of quantifying historical or future deforestation emission baselines. Rather, it places emphasis on improving quantification of contemporary stocks and the relative decline in deforestation rates necessary to preserve those stocks. This approach places emphasis on the complete emissions trajectory necessary to attain an agreed-upon preserved forest and as such, meets both forest conservation and climate goals simultaneously

Contrasting carbon cycle responses of the tropical continents to the 2015–2016 El Niño

The 2015–2016 El Niño led to historically high temperatures and low precipitation over the tropics, while the growth rate of atmospheric carbon dioxide (CO_2) was the largest on record. Here we quantify the response of tropical net biosphere exchange, gross primary production, biomass burning, and respiration to these climate anomalies by assimilating column CO_2, solar-induced chlorophyll fluorescence, and carbon monoxide observations from multiple satellites. Relative to the 2011 La Niña, the pantropical biosphere released 2.5 ± 0.34 gigatons more carbon into the atmosphere in 2015, consisting of approximately even contributions from three tropical continents but dominated by diverse carbon exchange processes. The heterogeneity of the carbon-exchange processes indicated here challenges previous studies that suggested that a single dominant process determines carbon cycle interannual variability