基于变更平衡表的土地利用演化信息提取与预测方法研究——以苏州市为例

变更平衡表为国土资源管理部门历年实地调查、汇总所得,精度高,目前的研究中对其深入的应用较少,基于变更平衡表的应用方法研究可为区域土地利用演变信息提取与预测提供帮助。推导了由连续年份的年度变更平衡表求多年周期的平衡表的方法,提出了基于土地利用综合动态度分析土地利用有序程度的思路,探讨了利用连续年份的变更平衡表预测任意年份土地利用结构的方法,并基于传统方法进行了改进,提出了利用矩阵开方法求预测概率矩阵。应用苏州市一定时期的连续年份的年度变更平衡表对上述方法进行了验证,结果表明:提出的信息提取方法有效,预测结果可信;在分析期内(1998~2008年),苏州市耕地大量减少的去向是各类建设用地增加的来源,区域土地利用有序程度较高;预测显示至2020年土地利用结构变化仍将维持农用地、耕地不断减少和建设用地总量不断增加的趋势,但转化的速率将有所放缓;对变更平衡表的深入应用有一定的借鉴意义。     

武汉城市群夏季热岛特征及演变

利用2000~2010年共11期MODIS地表温度资料和多源多时相的遥感影像分类结果揭示武汉城市群的夏季热岛效应,反演并计算出10 a间武汉城市群日间和夜间的热岛强度变化、土地覆盖类型和城镇用地面积。在对不同时相的地表温度数据进行热岛指数归一化处理的基础上,分析了武汉城市群热岛的分布特征及年代演变,定量分析了武汉城市群以及中心城市武汉市不同热状况区面积的变化和热场的变迁。结果表明,武汉城市群夏季热岛效应较为明显,其中武汉市是主要热源和热中心;自2000年起,武汉城市群城乡温度差异逐步减小,热中心分布向外扩散,城市热岛区域急速扩张,整体热环境趋于恶化;新兴城区的开发增加了武汉市的热源分布,人工表面的增加以及自然表面的减少导致城市热岛效应不断加剧。     

Research on whole life cycle carbon emission model of typical buildings

Based on the theory of life cycle assessment (LCA), this article analyzes the influence factors on carbon emissions from residential buildings. In the article, the life cycle of residential buildings has been divided into five stages: building materials production period, construction period, operation and maintenance period, demolition period, and solid waste recycle and disposal period. Based on this definition, the authors provide a theoretical model to calculate carbon emissions of residential building life cycle. In particular, the factor of human activities was introduced in the calculation of carbon emissions from the buildings. Furthermore, the authors put forward a model for calculation with the unit of carbon emissions for per-capita living space.     

Energy and economic impacts of an international multi-regional carbon market

The establishment of a global multi-regional carbon market is considered to be a cost effective approach to facilitate global emission abatement and has been widely concerned.The ongoing planned linkage between the European Union’s carbon market and a new emission trading system in Australia in 2015 would be an important attempt to the practice of building up an international carbon market across different regions.To understand the abatement effect of such a global carbon market and to study its energy and economic impact on different market participants,this article adopts a global dynamic computable general equilibrium model with a detailed representation of the interactions between energy and economic systems.Our model includes 20 economic sectors and 19 regions,and describes in detail 17 energy technologies.Bundled with fossil fuel consumptions,the emission permits are considered to be essential inputs in each of the production and consumption activities in the economic system to simulate global carbon market policies.Carbon emission permits are endogenously set in the model,and can be traded between sectors and regions.Considering the current development of the global carbon market,this study takes 2020 as the study period.Four scenarios(reference scenario,independent carbon market scenario,Europe Union（EUh-Australia scenario,and China-EU-Australia scenario） are designed to evaluate the impact of the global carbon market involving China,the EU,and Australia.We find that the carbon price in the three countries varies a lot,from $32/tCO₂ in Australia,to $17.5/tCO₂ in the EU,and to $10/tCO₂ in China.Though the relative emission reduction（3%） in China is lower than that in the EU（9%） and Australia（18%）,the absolute emission reduction in China is far greater than that in the EU and Australia.When China is included in the carbon market,which already includes the EU and Australia,the prevailing global carbon price falls from $22 per ton carbon dioxide（CO₂） to $12/tCO₂,due to the relatively lower abatement cost in China.Seventy-one percent of the EU’s and eighty-one percent of Australia’s domestic reduction burden would be transferred to China,increasing 0.03%of the EU’s and 0.06%of Australia’s welfare.The emission constraint improves the energy efficiency of China’s industry sector by 1.4%,reduces coal consumption by3.3%,and increases clean energy by 3.5%.     

长江源区基于坡面尺度的土壤水热过程模拟研究

长江源多年冻土区土壤水热传输过程机理与模拟,是广泛关系到高原生态环境保护恢复和区域水文过程的关键科学问题。因此,以GEOtop模型为研究平台,以长江源不同植被盖度下（裸地、30%、65%和92%）高寒草甸的观测数据为基础,检验模型对土壤水热迁移过程的描述与模拟精度。总体而言,GEOtop模型需要率定的参数较少,从而减少模型模拟的不确定性,提高了模拟精度。对不同植被盖度下土壤温度、水分和实际蒸散发模拟的NSE 系数基本达到08,表明模型能准确模拟高寒生态系统土壤的水热传输过程,可以作为长江源区土壤水热过程的有效模拟工具     

Environmental policy and macroeconomic dynamics in a new Keynesian model

This paper studies the dynamic behavior of an economy under different environmental policy regimes in a New Keynesian model with nominal and real uncertainty. We find the following results: (i) an emissions cap policy is likely to dampen macroeconomic fluctuations; (ii) staggered price adjustment alters significantly the performance of the environmental policy regime put in place; (iii) the optimal environmental policy response to shocks is strongly influenced by the degree to which prices adjust and by the monetary policy reaction.     

SMART-SREC: A stochastic model of the New Jersey solar renewable energy certificate market

Markets for solar renewable energy certificates (SRECs) are gaining in prominence in many states, stimulating growth of the US solar industry. However, SREC market prices have been extremely volatile, causing high risk to participants and potentially less investment in solar power generation. Such concerns necessitate the development of realistic, flexible and tractable models of SREC prices that capture the behavior of participants given the rules that govern the market. We propose an original stochastic model called SMART-SREC to fill this role, building on established ideas from the carbon pricing literature, and including a feedback mechanism for generation response to prices. We calibrate the model to the New Jersey market and backtest it, analyzing parameter sensitivity and demonstrating its ability to reproduce historical dynamics. Finally, we run simulations to investigate the role and impact of regulatory parameters, thus providing insight into the crucial role played by market design.     

Physiologically based pharmacokinetic modeling of perfluoroalkyl substances in the human body

Currently, there are limited data on the levels of perfluoroalkyl substances other than perfluorooctane sulfonic acid and perfluorooctanoic acid in the human body. Most of this information has been extracted from biological monitoring of plasma while the occurrence of perfluoroalkyl substances in other human tissues is rarely studied. The objective of the present study was to develop a physiologically based pharmacokinetic model to assess the concentration of perfluoroalkyl substances in human tissues, based on an existing model previously validated for perfluorooctane sulfonic acid and perfluorooctanoic acid. Experimental data on concentrations of perfluoroalkyl substances in human tissues from individuals in Tarragona County (Catalonia, Spain) were used to estimate the values of some distribution and elimination parameters needed for the simulation. No significant correlations were found between these parameters and the chain lengths. The model was finally validated for five perfluoroalkyl substances.     

Cybersecurity and dynamic operation in practice: Equipment impacts and safety guarantees

Though dynamic operation of chemical processes has been extensively explored theoretically in contexts such as economic model predictive control or even considering the potential for cyberattacks on control systems creating non-standard operating policies, important practical questions remain regarding dynamic operation. In this work, we look at two of these with particular relevance to process safety: (1) evaluating dynamic operating policies with respect to process equipment fidelity and (2) evaluating procedures for determining the parameters of an advanced control law that can promote both dynamic operation as well as safety if appropriately designed. Regarding the first topic, we utilize computational fluid dynamics and finite element analysis simulations to analyze how cyberattacks on control systems could impact a metric for stress in equipment (maximum Von Mises stress) over time. Subsequently, we develop reduced-order models showing how both a process variable and maximum Von Mises stress vary over time in response to temperature variations at the boundary of the equipment, to use in evaluating how advanced control frameworks might impact and consider the stress. We close by investigating options for obtaining parameters of an economic model predictive control design that would need to meet a variety of theoretical requirements for safety guarantees to hold. This provides insights on practical safety aspects of control theory, and also indicates relationships between control and design from a safety perspective that highlight further relationships between design and control under dynamic operation to deepen perspectives from the computational fluid dynamics and finite element analysis discussions.     

基于缓冲区重采样的LSTM林火预测模型*

为提高林火风险预测精度,挖掘地图上隐含的空间信息、时间序列上隐含的长期趋势和循环波动,提出1种基于缓冲区重采样的长短期记忆（LSTM）林火预测模型,选取15个与林火相关的影响因素,以方差膨胀因子为评价指标对其进行多重共线性检验,方差膨胀因子大于10的因素具有共线性,并采用信息增益率验证筛选结果的合理性。考虑到火灾的空间聚集特性,采用缓冲区分析与过采样相结合方法减少样本不均衡现象的影响,最终得到176 732条样本。对12个影响因素和研究时间段的火点建立LSTM预测模型,对森林火灾发生风险进行预测。研究结果表明:基于缓冲区重采样的LSTM林火预测模型有效考虑时空上隐含的信息,预测模型准确率为87.06%,特异性为97.99%,敏感度为76.12%,阳性预测率为97.43%,阴性预测率为80.41%,ROC曲线与AUC值均优于随机森林（RF）和支持向量机（SVM）这2种基准算法。维尔克松秩和检验发现,本文提出的模型与基准算法结果具有显著性差异。研究结果可为提高林火风险预测精度提供参考。