Comparison and Analysis of CO_2 Emissions Data for China

This paper reviews the CO2emissions data for China provided by various international organizations and databases(namely IEA,BP,EDGAR/PBL/JRC,CDIAC,EIA and CAIT)and compares them with China’s official data and estimation.The difference among these data is due to different scopes,methods and underlying data,and particularly the difference in fossil fuel consumption.Compared with data from other databases,IEA and CAIT data have the best comparability with China’s official data.The paper recommends that China enhance its coal statistics,raise the frequency of official data publication and improve the inventory completeness.

A compatible carbon efficiency information service framework based on the industrial internet identification

Green and low-carbon is a new development model that seeks balance between environmental sustainability and high economic growth.If explainable and available carbon emission data can be accurately obtained,it will help policy regulators and enterprise managers to more accurately implement this development strategy.A lot of research has been carried out,but it is still a difficult problem that how to accommodate and adapt the complex carbon emission data computing models and factor libraries developed by different regions,different industries and different enterprises.Meanwhile,with the rapid development of the Industrial Internet,it has not only been used for the supply chain optimization and intelligent scheduling of the manufacturing industry,but also been used by more and more industries as an important way of digital transformation.Especially in China,the Industrial Internet identification and resolution system is becoming an important digital infrastructure to uniquely identify objects and share data.Hence,a compatible carbon efficiency information service framework based on the Industrial Internet Identification is proposed in this paper to address the problem of computing and querying multi-source heterogeneous carbon emission data.We have defined a multi cooperation carbon emission data interaction model consisting of three roles and three basic operations.Further,the implementation of the framework includes carbon emission data identification,modeling,calculation,query and sharing.The practice results show that its capability and effectiveness in improving the responsiveness,accuracy,and credibility of compatible carbon efficiency data query and sharing services.

Steps Towards a Fully Automated Classification and Redshiftmeasurement Pipeline for LAMOST Spectra. I.Continuum level and wavelength estimation for galaxies

The Large Sky-Area Multi-Object Spectroscopic Telescope (LAMOST) under construction by the National Astronomical Observatories will yield up to four thousand multi-fiber spectra of stars and galaxies per field. The present series of papers describes the automated data-reduction pipeline currently being designed in order to cope with the anticipated flood of spectrographic data. In this preliminary paper, we present an automated method for estimating the continuum level, the positions of strong lines and the 4000 A break in galaxy spectra. In order to obtain detailed information on the continuum, we use a wavelet filter bank. After continuum fitting, our software searches for a 4000 A break and distinguishes between emission-line galaxies (ELGs) and non-ELGs according to whether the break is small or large. It then searches for strong lines and measures the intensities of emission lines and the equivalent widths of absorption lines. For non-ELGs, the absorption lines are identified automatically yielding redshift measurements.

Regional inequality, spatial spillover effects, and the factors influencing city-level energy-related carbon emissions in China

Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.

REMOTE SENSING OF AIR TEMPERATURE PROFILE AND SURFACE EMISSIVITY FROM HIRS2 DATA

A physical method,based on the simplification of surface radiation terms in remote sensing equations, has been suggested to retrieve the surface temperature,vertical temperature profile and surface emissivity from the first eight channel observations of TIROS-N/HIRS2.Analyses of several examples indicate that this method can obtain much more accurate temperatures in the lower atmosphere than a statistical technique, and that the surface temperature and emissivity retrieved are also reasonable.

Development and case study of a science-based software platform to support policy making on air quality

This article describes the development and implementations of a novel software platform that supports real-time, science-based policy making on air quality through a user-friendly interface. The software, RSM-VAT, uses a response surface modeling（RSM） methodology and serves as a visualization and analysis tool（VAT） for three-dimensional air quality data obtained by atmospheric models. The software features a number of powerful and intuitive data visualization functions for illustrating the complex nonlinear relationship between emission reductions and air quality benefits. The case study of contiguous U.S.demonstrates that the enhanced RSM-VAT is capable of reproducing the air quality model results with Normalized Mean Bias 〈 2% and assisting in air quality policy making in near real time.