scholarly journals Does Size Matter? Scaling of CO2 Emissions and U.S. Urban Areas

2017 ◽  
pp. 79-98
Author(s):  
Michail Fragkias ◽  
José Lobo ◽  
Deborah Strumsky ◽  
Karen C. Seto
Keyword(s):  
Co2 Emissions ◽  
Urban Areas ◽  
Size Matter

scholarly journals Does Size Matter? Scaling of CO2 Emissions and U.S. Urban Areas

PLoS ONE ◽  
2013 ◽  
Vol 8 (6) ◽  
pp. e64727 ◽  
Author(s):  
Michail Fragkias ◽  
José Lobo ◽  
Deborah Strumsky ◽  
Karen C. Seto
Keyword(s):  
Co2 Emissions ◽  
Urban Areas ◽  
Size Matter

scholarly journals Diurnal, weekly, seasonal and spatial variabilities in carbon dioxide flux in different urban landscapes in Sakai, Japan

2016 ◽  
Author(s):  
Masahito Ueyama ◽  
Tomoya Ando
Keyword(s):  
Rural Area ◽  
Eddy Covariance ◽  
Co2 Emissions ◽  
Air Temperature ◽  
Urban Areas ◽  
Suburban Area ◽  
Urban Park ◽  
Urban Landscapes ◽  
Co2 Fluxes ◽  
Urban Center

Abstract. To evaluate CO2 emissions in urban areas and their temporal and spatial variabilities, continuous measurements of CO2 fluxes were conducted using the eddy covariance method at three locations in Sakai, Osaka, Japan. Based on the flux footprint at the measurement sites, CO2 fluxes from the three sites were partitioned into five datasets representing a dense urban center, a moderately urban area, a suburb, an urban park, and a rural area. Distinct biological uptake of CO2 was observed in the suburb, urban park, and rural areas in the daytime, whereas high emissions were observed at dense and moderate urban areas in daytime. Weekday CO2 emissions in the dense urban center and suburban area were approximately 50 % greater than during weekend and holidays, but the other landscapes did not exhibit a clear weekly cycle. Seasonal variations in the urban park, rural area, and suburban area were influenced by vegetation activities, exhibiting the lowest daily emissions or even uptakes during summer months. In contrast, the dense and moderately urban areas exhibited higher emissions in winter and summer months, when emissions significantly increased as air temperature increased in summer and air temperature decreased in winter. Irrespective of the landcover type, all urban landscapes measured in this study acted as net annual CO2 sources, with emissions ranging from 0.5 to 4.9 kg C m−2 yr−1. The magnitude of the annual CO2 emissions was negatively correlated with green fraction; areas with a smaller green fraction had higher annual CO2 emissions. Upscaled flux estimates based on the green fraction indicated that the emissions for the entire city were 3.3 kg C m−2 yr−1, which is equivalent to 0.5 Tg C yr−1 or 1.8 Mt CO2 yr−1 based on the area of the city (149.81 km2). A network of eddy covariance measurements is a powerful tool to evaluate CO2 emissions from urban areas.

scholarly journals Analysis of the Reduction of CO2 Emissions in Urban Environments by Replacing Conventional City Buses by Electric Bus Fleets: Spain Case Study

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 525 ◽  
Author(s):  
Edwin R. Grijalva ◽  
José María López Martínez
Keyword(s):  
Co2 Emissions ◽  
Urban Areas ◽  
Energy Demand ◽  
Vital Role ◽  
Urban Environments ◽  
Urban Transport ◽  
Transport Sector ◽  
Cost Of Energy ◽  
Electric Bus

The emissions of CO2 gas caused by transport in urban areas are increasingly serious, and the public transport sector plays a vital role in society, especially when considering the increased demands for mobility. New energy technologies in urban mobility are being introduced, as evidenced by the electric vehicle. We evaluated the positive environmental effects in terms of CO2 emissions that would be produced by the replacement of conventional urban transport bus fleets by electric buses. The simulation of an electric urban bus conceptual model is presented as a case study. The model is validated using the speed and height profiles of the most representative route within the city of Madrid—the C1 line. We assumed that the vehicle fleet is charged using the electric grid at night, when energy demand is low, the cost of energy is low, and energy is produced with a large provision of renewable energy, principally wind power. For the results, we considered the percentage of fleet replacement and the Spanish electricity mix. The analysis shows that by gradually replacing the current fleet of buses by electric buses over 10 years (2020 to 2030), CO2 emissions would be reduced by up to 92.6% compared to 2018 levels.

An approach for modelling CO2 emissions from road traffic in urban areas

2008 ◽  
Vol 406 (1-2) ◽  
pp. 269-278 ◽  
Author(s):  
Farhad Nejadkoorki ◽  
Ken Nicholson ◽  
Iain Lake ◽  
Trevor Davies
Keyword(s):  
Co2 Emissions ◽  
Urban Areas ◽  
Road Traffic

scholarly journals The climate change mitigation effects of active travel

2020 ◽  
Author(s):  
Christian Brand ◽  
Evi Dons ◽  
Esther Anaya-Boig ◽  
Ione Avila-Palencia ◽  
Anna Clark ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Urban Areas ◽  
Active Travel ◽  
Urban Life ◽  
Activity Data ◽  
Net Zero ◽  
Quality Of Urban Life ◽  
Zero Carbon ◽  
Car Travel ◽  
Daily Travel

Abstract Active travel (walking or cycling for transport) is considered the most sustainable form of getting from A to B. Yet the net effects of active travel on mobility-related CO2 emissions are complex and under-researched. Here we collected travel activity data in seven European cities and derived lifecycle CO2 emissions from daily travel activity. Daily mobility-related lifecycle CO2 emissions were 3.2 kgCO2 per person, with car travel contributing 70% and cycling 1%. Cyclists had 84% lower lifecycle CO2 emissions from all daily travel than non-cyclists. Lifecycle CO2 emissions decreased by -14% (95%CI -12% to -16%) per additional cycling trip and decreased by -62% (95%CI -61% to -63%) for each avoided car trip. An average person who ‘shifted travel modes’ from car to bike decreased lifecycle CO2 emissions by 3.2 (95%CI 2.0 to 5.2) kgCO2/day, and using a bike as the ‘main method of travel’ gave 7.1 (95%CI 4.8 to 10.4) kgCO2/day lower lifecycle CO2 emissions than mainly using a car or van. Investing in and promoting active travel should be a cornerstone of strategies to meet net zero carbon targets, particularly in urban areas, while also improving public health and quality of urban life.

scholarly journals Traces of urban forest in temperature and CO<sub>2</sub> signals in monsoon East Asia

2021 ◽  
Author(s):  
Keunmin Lee ◽  
Je-Woo Hong ◽  
Jeongwon Kim ◽  
Jinkyu Hong
Keyword(s):  
Co2 Emissions ◽  
Urban Areas ◽  
Urban Forest ◽  
Urban Forests ◽  
Forest Canopies ◽  
Area Index ◽  
Drought Period ◽  
Vegetation Activity ◽  
Urban Heat ◽  
The Impact

Abstract. Cities represent a key space for our sustainable trajectory in a changing environment, and our society is steadily embracing urban green space for its role in mitigating heatwaves and anthropogenic CO2 emissions. This study reports two-year surface fluxes of energy and CO2 measured via the eddy covariance method in an artificially constructed urban forest to examine the impact of urban forests on air temperature and net CO2 exchange. The urban forest site shows typical seasonal patterns of forest canopies with the seasonal march of the East Asian summer monsoon. Our analysis indicates that the urban forest reduces both the warming trend and urban heat island intensity compared to the adjacent high-rise urban areas and that photosynthetic carbon uptake is large despite relatively small tree density and leaf area index. During the significant drought period in the second year, gross primary production and evapotranspiration decreased, but their reduction was not as significant as those in natural forest canopies. We speculate that forest management practices, such as artificial irrigation and fertilization, enhance vegetation activity. We also stipulate that ecosystem respiration in urban forests is more pronounced than typical natural forests in a similar climate zone. This can be attributed to the substantial amount of soil organic carbon available due to intensive historical soil use and soil transplantation during forest construction, as well as relatively warmer temperatures in urban heat domes. Our observational study also indicates the need for caution in soil management for less CO2 emissions in urban areas.

scholarly journals Comparative study of retaining walls aiming to optimize carbon footprint

2020 ◽  
Vol 11 (1) ◽  
pp. 460-467
Author(s):  
João Vitor de Almeida Bezerra ◽  
Tiago Gripp Mota ◽  
Horasa Maria Lima da Silva Andrade ◽  
Luciano Pires de Andrade ◽  
Ricardo Brauer Vigoderis
Keyword(s):  
Reinforced Concrete ◽  
Co2 Emissions ◽  
Carbon Footprint ◽  
Urban Areas ◽  
Retaining Wall ◽  
Reinforced Soil ◽  
Reinforced Concrete Structure ◽  
Vegetation Growth ◽  
Soil Structures ◽  
Increasing Demand

Urban areas are commonly developed with inadequate planning, which can lead to communities settling in unstable locations, creating a need to either relocate these settlements to more appropriate places, or to stabilize the terrain. These actions must be combined with practices focused on reduction of environmental impacts, such as CO2 emissions. Therefore, this research aimed to compare the carbon footprint of reinforced soil structures to a conventional method. Two types of retaining wall using geogrid reinforcements were designed as an alternative to a cantilever wall made of reinforced concrete. After the design process, the volume of necessary material was estimated for each structure as well as the amount of CO2 emissions related to their production. The designed reinforced soil structures obtained a much smaller carbon footprint when compared to the reinforced concrete structure. Due to the increasing demand for terrain stabilization in urban areas, structures that are less impactful to the environment should be prioritized especially when they can also be used to promote vegetation growth. Thus, reinforced soil structures are a great alternative to common methods because of their smaller carbon footprint and they can also bring several benefits to the landscape, such as an increase in vegetated area.

scholarly journals A global map of emission clumps for future monitoring of fossil fuel CO<sub>2</sub> emissions from space

2019 ◽  
Vol 11 (2) ◽  
pp. 687-703 ◽  
Author(s):  
Yilong Wang ◽  
Philippe Ciais ◽  
Grégoire Broquet ◽  
François-Marie Bréon ◽  
Tomohiro Oda ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Land Surface ◽  
Urban Areas ◽  
Power Plants ◽  
Fossil Fuel ◽  
Large Fraction ◽  
Point Sources ◽  
Bottom Up ◽  
Large Power ◽  
Data Product

Abstract. A large fraction of fossil fuel CO2 emissions emanate from “hotspots”, such as cities (where direct CO2 emissions related to fossil fuel combustion in transport, residential, commercial sectors, etc., excluding emissions from electricity-producing power plants, occur), isolated power plants, and manufacturing facilities, which cover a small fraction of the land surface. The coverage of all high-emitting cities and point sources across the globe by bottom-up inventories is far from complete, and for most of those covered, the uncertainties in CO2 emission estimates in bottom-up inventories are too large to allow continuous and rigorous assessment of emission changes (Gurney et al., 2019). Space-borne imagery of atmospheric CO2 has the potential to provide independent estimates of CO2 emissions from hotspots. But first, what a hotspot is needs to be defined for the purpose of satellite observations. The proposed space-borne imagers with global coverage planned for the coming decade have a pixel size on the order of a few square kilometers and a XCO2 accuracy and precision of <1 ppm for individual measurements of vertically integrated columns of dry-air mole fractions of CO2 (XCO2). This resolution and precision is insufficient to provide a cartography of emissions for each individual pixel. Rather, the integrated emission of diffuse emitting areas and intense point sources is sought. In this study, we characterize area and point fossil fuel CO2 emitting sources which generate coherent XCO2 plumes that may be observed from space. We characterize these emitting sources around the globe and they are referred to as “emission clumps” hereafter. An algorithm is proposed to identify emission clumps worldwide, based on the ODIAC global high-resolution 1 km fossil fuel emission data product. The clump algorithm selects the major urban areas from a GIS (geographic information system) file and two emission thresholds. The selected urban areas and a high emission threshold are used to identify clump cores such as inner city areas or large power plants. A low threshold and a random walker (RW) scheme are then used to aggregate all grid cells contiguous to cores in order to define a single clump. With our definition of the thresholds, which are appropriate for a space imagery with 0.5 ppm precision for a single XCO2 measurement, a total of 11 314 individual clumps, with 5088 area clumps, and 6226 point-source clumps (power plants) are identified. These clumps contribute 72 % of the global fossil fuel CO2 emissions according to the ODIAC inventory. The emission clumps is a new tool for comparing fossil fuel CO2 emissions from different inventories and objectively identifying emitting areas that have a potential to be detected by future global satellite imagery of XCO2. The emission clump data product is distributed from https://doi.org/10.6084/m9.figshare.7217726.v1.

Reduction of CO2 emissions in urban areas through optimal expansion of existing district heating networks

2018 ◽  
Vol 204 ◽  
pp. 117-129 ◽  
Author(s):  
Elisa Guelpa ◽  
Guglielmina Mutani ◽  
Valeria Todeschi ◽  
Vittorio Verda
Keyword(s):  
Co2 Emissions ◽  
Urban Areas ◽  
District Heating ◽  
Reduction Of Co2 ◽  
Heating Networks

scholarly journals Network design for quantifying urban CO<sub>2</sub> emissions: Assessing trade-offs between precision and network density

2016 ◽  
Author(s):  
Alexander J. Turner ◽  
Alexis A. Shusterman ◽  
Brian C. McDonald ◽  
Virginia Teige ◽  
Robert A Harley ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Urban Areas ◽  
Cost Effective ◽  
Point Sources ◽  
Urban Region ◽  
Dense Network ◽  
Industrial Facilities ◽  
Trade Offs ◽  
Combined Uncertainty ◽  
The City

Abstract. The majority of anthropogenic CO2 emissions are attributable to urban areas. While the emissions from urban electricity generation often occur in locations remote from consumption, many of the other emissions occur within the city limits. Evaluating the effectiveness of strategies for controlling these emissions depends on our ability to observe urban CO2 emissions and attribute them to specific activities. Cost effective strategies for doing so have yet to be described. Here we characterize the ability of a prototype measurement network, modeled after the BEACO2N network, in combination with an inverse model based on WRF-STILT to improve our understanding of urban emissions. The pseudo-measurement network includes 34 sites at roughly 2 km spacing covering an area of roughly 400 km2. The model uses an hourly 1 × 1 km2 emission inventory and 1 × 1 km2 meteorological calculations. We perform an ensemble of Bayesian atmospheric inversions to sample the combined effects of uncertainties of the pseudo-measurements and the model. We vary the estimates of the combined uncertainty of the pseudo-observations and model over a range of 20 ppm to 0.005 ppm and vary the number of sites from 1 to 34. We use these inversions to develop statistical models that estimate the efficacy of the combined model-observing system at reducing uncertainty in CO2 emissions. We examine uncertainty in estimated CO2 fluxes at the urban scale, as well as for sources embedded within the city such as a line source (e.g., a highway) or a point source (e.g., emissions from the stacks of small industrial facilities). We find that a dense network with moderate precision is the preferred setup for estimating area, line, and point sources from a combined uncertainty and cost perspective. The dense network considered here could estimate weekly CO2 emissions from an urban region with less than 5 % error, given our characterization of the combined observation and model uncertainty.

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