Quantifying uncertainty in the biospheric carbon flux for England and Wales

Summary.  A crucial issue in the current global warming debate is the effect of vegetation and soils on carbon dioxide (CO₂) concentrations in the atmosphere. Vegetation can extract CO₂ through photosynthesis, but respiration, decay of soil organic matter and disturbance effects such as fire return it to the atmosphere. The balance of these processes is the net carbon flux. To estimate the biospheric carbon flux for England and Wales, we address the statistical problem of inference for the sum of multiple outputs from a complex deterministic computer code whose input parameters are uncertain. The code is a process model which simulates the carbon dynamics of vegetation and soils, including the amount of carbon that is stored as a result of photosynthesis and the amount that is returned to the atmosphere through respiration. The aggregation of outputs corresponding to multiple sites and types of vegetation in a region gives an estimate of the total carbon flux for that region over a period of time. Expert prior opinions are elicited for marginal uncertainty about the relevant input parameters and for correlations of inputs between sites. A Gaussian process model is used to build emulators of the multiple code outputs and Bayesian uncertainty analysis is then used to propagate uncertainty in the input parameters through to uncertainty on the aggregated output. Numerical results are presented for England and Wales in the year 2000. It is estimated that vegetation and soils in England and Wales constituted a net sink of 7.55 Mt C (1 Mt C = 10¹² g of carbon) in 2000, with standard deviation 0.56 Mt C resulting from the sources of uncertainty that are considered.     

Social network and content analysis of the North American Carbon Program as a scientific community of practice

The North American Carbon Program (NACP) was formed to further the scientific understanding of sources, sinks, and stocks of carbon in Earth's environment. Carbon cycle science integrates multidisciplinary research, providing decision-support information for managing climate and carbon-related change across multiple sectors of society. This investigation uses the conceptual framework of communities of practice (CoP) to explore the role that the NACP has played in connecting researchers into a carbon cycle knowledge network, and in enabling them to conduct physical science that includes ideas from social science. A CoP describes the communities formed when people consistently engage in shared communication and activities toward a common passion or learning goal. We apply the CoP model by using keyword analysis of abstracts from scientific publications to analyze the research outputs of the NACP in terms of its knowledge domain. We also construct a co-authorship network from the publications of core NACP members, describe the structure and social pathways within the community. Results of the content analysis indicate that the NACP community of practice has substantially expanded its research on human and social impacts on the carbon cycle, contributing to a better understanding of how human and physical processes interact with one another. Results of the co-authorship social network analysis demonstrate that the NACP has formed a tightly connected community with many social pathways through which knowledge may flow, and that it has also expanded its network of institutions involved in carbon cycle research over the past seven years.     

上海生态文明建设的激励和约束机制研究

生态文明建设是一项系统工程,需要通过整体推进,构筑规划、建设、管理、技术、产业、社会和合作协同发展的综合体系。未来上海应以建立和完善市场机制为核心,以法律机制为前提,以政府监管机制为保障,以能力建设机制为基础,以社会参与机制为监督,按照"引逼结合、多方合力、突出重点、先行先试"的原则,加快上海生态文明建设机制创新。主要途径有:完善碳排放交易试点,建立长效市场机制;推进分布式能源应用,提高清洁能源比重;加快新能源汽车推广,优化交通能源结构;培育发展再制造产业,推广先进制造理念。     

碳强度目标:演进、理由与实现

碳强度目标是关于未来要达到的温室气体排放强度的国家承诺。研究碳强度目标对于认识和实现中国气候承诺具有重要意义。严格性、约束力和覆盖范围是碳强度目标的关键要素。碳强度目标具有坚实的理论基础和深刻的现实背景,至少具有与温室气体数量目标同等重要的地位。降低碳强度需要降低温室气体的边际弹性或国民生产总值的边际碳强度,需要将国家碳强度目标分解到行业和企业,还要建立碳排放交易制度。     

Two-step estimation for inhomogeneous spatial point processes

Summary.  The paper is concerned with parameter estimation for inhomogeneous spatial point processes with a regression model for the intensity function and tractable second-order properties ( K -function). Regression parameters are estimated by using a Poisson likelihood score estimating function and in the second step minimum contrast estimation is applied for the residual clustering parameters. Asymptotic normality of parameter estimates is established under certain mixing conditions and we exemplify how the results may be applied in ecological studies of rainforests.     

中国碳排放库兹涅茨曲线存在性研究

经济增长与环境恶化之间的矛盾直接推动了碳排放库兹涅茨曲线的研究。本文基于1995-2009年中国省际碳排放面板数据,利用面板协整和误差修正模型对中国碳排放库兹涅茨曲线的存在性进行实证研究,结果发现：动态固定效应下的面板误差修正模型最优,碳排放与经济增长间存在长期稳定的倒U型关系,拐点为人均国内生产总值29847.29元,且存在短期误差修正机制;与权威机构时序数据回归结果比较,动态面板模型结果具有稳健性。     

Developing spatial inequalities in carbon appropriation: A sociological analysis of changing local emissions across the United States

This study examines an overlooked dynamic in sociological research on greenhouse gas emissions: how local areas appropriate the global carbon cycle for use and exchange purposes as they develop. Drawing on theories of place and space, we hypothesize that development differentially drives and spatially decouples use- and exchange-oriented emissions at the local level. To test our hypotheses, we integrate longitudinal, county-level data on residential and industrial emissions from the Vulcan Project with demographic, economic and environmental data from the U.S. Census Bureau and National Land Change Database. Results from spatial regression models with two-way fixed-effects indicate that alongside innovations and efficiencies capable of reducing environmentally harmful effects of development comes a spatial disarticulation between carbon-intensive production and consumption within as well as across societies. Implications for existing theory, methods and policy are discussed.     

A hybrid approach to configure eco-efficient supply chains under consideration of performance and risk aspects

Formal models that support multi-criteria decision making represent a strongly growing area in sustainable supply chain management research. However, uncertainties and risks are seldom considered in quantitative models for green supply chain (SC) design. The paper at hand suggests a hybrid approach to configure an eco-efficient SC for a new product under consideration of economic and environmental risks. Discrete-event simulation is applied to assess the financial, operational and environmental performance of different SC configuration options while the value-at-risk concept is adapted to evaluate related SC risks. The analytic hierarchy process is employed to solve the resulting multi-criteria decision problem of choosing the best option. The approach is illustrated at a case example of a fast moving consumer goods manufacturer.     

Proportional Trapping-Removal Model with a Known Ratio

ABSTRACT

Population size estimator is derived for a proportional trapping-removal model with a known ratio between two sub-population sizes, and the corresponding asymptotic properties is obtained. The performance of the proposed estimator is checked via simulation studies and an example.     

Spillover Effects of Carbon Footprint Labelling on Less Developed Countries: The Example of the East Asia Summit Region

The spillover effects of carbon footprint (CFP) labelling are particularly significant in the East Asia Summit (EAS) region which has closely integrated production networks, wide development gaps and predominantly small and medium‐sized enterprises. Poor management of the effects would undermine not only the effectiveness of CFP labelling, but also EAS efforts towards economic integration and the narrowing of development gaps. Well‐designed labelling schemes, accessible and affordable data and transparent certification processes are essential, as well as capacity‐building and engagement of non‐labelling countries, in particular LDCs.