scholarly journals A black carbon emission data base for atmospheric chemistry and climate studies

10.2172/28275 ◽  
1994 ◽  
Author(s):  
J. Dignon ◽  
H.E. Eddleman ◽  
J.E. Penner
Keyword(s):  
Data Base ◽  
Black Carbon ◽  
Atmospheric Chemistry ◽  
Carbon Emission ◽  
Emission Data ◽  
Climate Studies

Study on Carbon Emission Calculation Method of Concrete

2018 ◽  
Vol 768 ◽  
pp. 293-305 ◽  
Author(s):  
Chun Zhi Zhao ◽  
Yi Liu ◽  
Shi Wei Ren ◽  
Jiang Quan
Keyword(s):  
Energy Consumption ◽  
Calculation Method ◽  
Carbon Emission ◽  
Rapid Development ◽  
Reference Value ◽  
Calculation Model ◽  
Emission Data ◽  
Continuous Growth ◽  
Boundary Definition ◽  
Concrete Production

along with the rapid development of commercial concrete industry and the continuous growth of concrete demand, the commercial concrete production has brought large energy consumption and mineral resource consumption; cement calcination and direct/indirect energy consumption within the boundary of ready-mixed concrete system have become the main source of concrete greenhouse gas. This paper mainly settles key problems such as boundary definition, data collection, calculation model, data acceptance/rejection and data calculation method concerned with concrete carbon emission calculation, establishes the national uniform concrete carbon emission calculation method and emission factor within the same cultural boundary, and provides theoretical and data calculation basis for determining the reference value and grade of concrete carbon emission. As for other products, the carbon emission of unit product may also be calculated by reference to this paper; therefore, inherent carbon emission data of buildings are accumulated, providing quantized data support for taking measures to reduce the carbon emission intensity.

scholarly journals Sensitivity of aerosol radiative effects to different mixing assumptions in the AEROPT 1.0 submodel of the EMAC atmospheric-chemistry–climate model

2014 ◽  
Vol 7 (5) ◽  
pp. 2503-2516 ◽  
Author(s):  
K. Klingmüller ◽  
B. Steil ◽  
C. Brühl ◽  
H. Tost ◽  
J. Lelieveld
Keyword(s):  
Optical Properties ◽  
Radiative Transfer ◽  
Black Carbon ◽  
Atmospheric Chemistry ◽  
Radiative Forcing ◽  
Climate Model ◽  
Mixing Rule ◽  
Aerosol Optical Properties ◽  
Internal Mixing ◽  
Aerosol Radiative

Abstract. The modelling of aerosol radiative forcing is a major cause of uncertainty in the assessment of global and regional atmospheric energy budgets and climate change. One reason is the strong dependence of the aerosol optical properties on the mixing state of aerosol components, such as absorbing black carbon and, predominantly scattering sulfates. Using a new column version of the aerosol optical properties and radiative-transfer code of the ECHAM/MESSy atmospheric-chemistry–climate model (EMAC), we study the radiative transfer applying various mixing states. The aerosol optics code builds on the AEROPT (AERosol OPTical properties) submodel, which assumes homogeneous internal mixing utilising the volume average refractive index mixing rule. We have extended the submodel to additionally account for external mixing, partial external mixing and multilayered particles. Furthermore, we have implemented the volume average dielectric constant and Maxwell Garnett mixing rule. We performed regional case studies considering columns over China, India and Africa, corroborating much stronger absorption by internal than external mixtures. Well-mixed aerosol is a good approximation for particles with a black-carbon core, whereas particles with black carbon at the surface absorb significantly less. Based on a model simulation for the year 2005, we calculate that the global aerosol direct radiative forcing for homogeneous internal mixing differs from that for external mixing by about 0.5 W m−2.

Generation of an Emission Data Base for TRACT

2000 ◽  
pp. 269-278 ◽  
Author(s):  
J. Seier ◽  
P. Berner ◽  
R. Friedrich ◽  
C. John ◽  
A. Obermeier
Keyword(s):  
Data Base ◽  
Emission Data

scholarly journals The Spatial Network Structure of China’s Regional Carbon Emissions and Its Network Effect

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2706 ◽  
Author(s):  
Feng Wang ◽  
Mengnan Gao ◽  
Juan Liu ◽  
Wenna Fan
Keyword(s):  
Network Structure ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Geographical Location ◽  
Network Effect ◽  
Quadratic Assignment ◽  
Spatial Correlations ◽  
Emission Data ◽  
Correlation Relationship ◽  
Four Blocks

Under the “new normal”, China is facing more severe carbon emissions reduction targets. This paper estimates the carbon emission data of various provinces in China from 2008 to 2014, constructs a revised gravity model, and analyzes the network structure and effects of carbon emissions in various provinces by using social network analysis (SNA) and quadratic assignment procedure (QAP) analysis methods. The conclusions show that there are obvious spatial correlations between China’s provinces and regions in terms of carbon emissions: Tianjin, Shanghai, Zhejiang, Jiangsu and Guangdong are in the center of the carbon emission network, and play the role of “bridges”. Carbon emissions can be divided into four blocks: “bidirectional spillover block”, “net beneficial block”, “net spillover block” and “broker block”. The differences in the energy consumption, economic level and geographical location of the provinces have a significant impact on the spatial correlation relationship of carbon emissions. Finally, the improvement of the robustness of the overall network structure and the promotion of individual network centrality can significantly reduce the intensity of carbon emissions.

scholarly journals Chemodiversity of a Scots pine stand and implications for terpene air concentrations

2012 ◽  
Vol 9 (2) ◽  
pp. 689-702 ◽  
Author(s):  
J. Bäck ◽  
J. Aalto ◽  
M. Henriksson ◽  
H. Hakola ◽  
Q. He ◽  
...  
Keyword(s):  
Scots Pine ◽  
Atmospheric Chemistry ◽  
Bimodal Distribution ◽  
Atmospheric Modeling ◽  
Emission Data ◽  
Intermediate Group ◽  
Pine Trees ◽  
Seed Origin ◽  
Atmospheric Concentrations ◽  
Air Concentrations

Abstract. Atmospheric chemistry in background areas is strongly influenced by natural vegetation. Coniferous forests are known to produce large quantities of volatile vapors, especially terpenes. These compounds are reactive in the atmosphere, and contribute to the formation and growth of atmospheric new particles. Our aim was to analyze the variability of mono- and sesquiterpene emissions between Scots pine trees, in order to clarify the potential errors caused by using emission data obtained from only a few trees in atmospheric chemistry models. We also aimed at testing if stand history and seed origin has an influence on the chemotypic diversity. The inherited, chemotypic variability in mono- and sesquiterpene emission was studied in a seemingly homogeneous 48 yr-old stand in Southern Finland, where two areas differing in their stand regeneration history could be distinguished. Sampling was conducted in August 2009. Terpene concentrations in the air had been measured at the same site for seven years prior to branch sampling for chemotypes. Two main compounds, α-pinene and Δ3-carene formed together 40–97% of the monoterpene proportions in both the branch emissions and in the air concentrations. The data showed a bimodal distribution in emission composition, in particular in Δ3-carene emission within the studied population. 10% of the trees emitted mainly α-pinene and no Δ3-carene at all, whereas 20% of the trees where characterized as high Δ3-carene emitters (Δ3-carene forming >80% of total emitted monoterpene spectrum). An intermediate group of trees emitted equal amounts of both α-pinene and Δ3-carene. The emission pattern of trees at the area established using seeding as the artificial regeneration method differed from the naturally regenerated or planted trees, being mainly high Δ3-carene emitters. Some differences were also seen in e.g. camphene and limonene emissions between chemotypes, but sesquiterpene emissions did not differ significantly between trees. The atmospheric concentrations at the site were found to reflect the species and/or chemodiversity rather than the emissions measured from any single tree, and were strongly dominated by α-pinene. We also tested the effect of chemodiversity on modeled monoterpene concentrations at the site and found out that since it significantly influences the distributions and hence the chemical reactions in the atmosphere, it should be taken into account in atmospheric modeling.

scholarly journals Inverse modeling of black carbon emissions over China using ensemble data assimilation

2016 ◽  
Vol 16 (2) ◽  
pp. 989-1002 ◽  
Author(s):  
P. Wang ◽  
H. Wang ◽  
Y. Q. Wang ◽  
X. Y. Zhang ◽  
S. L. Gong ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Black Carbon ◽  
Atmospheric Chemistry ◽  
Inverse Modeling ◽  
Optimal Interpolation ◽  
Top Down ◽  
Bottom Up ◽  
Error Matrix ◽  
Ensemble Data Assimilation ◽  
Ensemble Data

Abstract. Emissions inventories of black carbon (BC), which are traditionally constructed using a bottom-up approach based on activity data and emissions factors, are considered to contain a large level of uncertainty. In this paper, an ensemble optimal interpolation (EnOI) data assimilation technique is used to investigate the possibility of optimally recovering the spatially resolved emissions bias of BC. An inverse modeling system for emissions is established for an atmospheric chemistry aerosol model and two key problems related to ensemble data assimilation in the top-down emissions estimation are discussed: (1) how to obtain reasonable ensembles of prior emissions and (2) establishing a scheme to localize the background-error matrix. An experiment involving 1-year-long simulation cycle with EnOI inversion of BC emissions is performed for 2008. The bias of the BC emissions intensity in China at each grid point is corrected by this inverse system. The inverse emission over China in January is 240.1 Gg, and annual emission is about 2539.3 Gg, which is about 1.8 times of bottom-up emission inventory. The results show that, even though only monthly mean BC measurements are employed to inverse the emissions, the accuracy of the daily model simulation improves. Using top-down emissions, the average root mean square error of simulated daily BC is decreased by nearly 30 %. These results are valuable and promising for a better understanding of aerosol emissions and distributions, as well as aerosol forecasting.

scholarly journals Anthropogenic Black Carbon Emission Increase during the Last 150 Years at Coastal Jiangsu, China

PLoS ONE ◽  
2015 ◽  
Vol 10 (7) ◽  
pp. e0129680 ◽  
Author(s):  
Kunshan Bao ◽  
Ji Shen ◽  
Guoping Wang ◽  
Chuanyu Gao
Keyword(s):  
Black Carbon ◽  
Carbon Emission

scholarly journals Research on the Spatial Network Characteristics and Synergetic Abatement Effect of the Carbon Emissions in Beijing–Tianjin–Hebei Urban Agglomeration

2019 ◽  
Vol 11 (5) ◽  
pp. 1444 ◽  
Author(s):  
Xintao Li ◽  
Dong Feng ◽  
Jian Li ◽  
Zaisheng Zhang
Keyword(s):  
Carbon Emissions ◽  
Carbon Emission ◽  
Synergetic Effect ◽  
Urban Agglomeration ◽  
Network Density ◽  
Spatial Network ◽  
Network Efficiency ◽  
Emission Data ◽  
Network Characteristics ◽  
Network Hierarchy

Based on the carbon emission data in the Beijing–Tianjin–Hebei urban agglomeration from 2007 to 2016, this paper used the method of social network analysis (SNA) to investigate the spatial correlation network structure of the carbon emission. Then, by constructing the synergetic abatement effect model, we calculated the synergetic abatement effect in the cities and we empirically examined the influence of the spatial network characteristics on the synergetic abatement effect. The results show that the network density first increased from 0.205 in 2007 to 0.263 in 2014 and then decreased to 0.205 in 2016; the network hierarchy fluctuated around 0.710, and the minimum value of the network efficiency was 0.561, which indicates that the network hierarchy structure is stern and the network has good stability. Beijing and Tianjin are in the center of the carbon emission spatial network and play important “intermediary” and “bridge” roles that can have better control over other carbon emission spatial spillover relations between the cities, thus the spatial network of carbon emissions presents a typical “center–periphery” structure. The synergetic abatement effect increased from −2.449 in 2007 to 0.800 in 2011 and then decreased to −1.653 in 2016; the average synergetic effect was −0.550. This means that the overall synergetic level has a lot of room to grow. The carbon emission spatial network has a significant influence on the synergetic abatement effect, while increasing the network density and the network hierarchy. Decreasing the network efficiency will significantly enhance the synergetic abatement effect.

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