Towards a new climate economics:research areas and prospects

International cooperation to address climate change now stands at a crossroads.With a new international regime for emissions reduction established by the Durban Platform, "New Climate Economics(NCE)" has become a research hotspot.The need for urgent action to combat climate change has prompted discussion on reforms of economic growth patterns and the energy system.The industrial civilization,therefore,now faces a transition towards a new pathway for ecological sustainability.NCE explores new economic concepts,theories,and analytical methods to design a balanced pathway for sustainable growth and emission reduction.Instead of getting trapped in discussions on allocation of emission reduction responsibilities and obligations among countries,NCE pays more attention to developing win-win multilateral cooperation mechanisms that facilitate collaborative RD and knowledge sharing.In addition,NCE studies incentives for low-carbon transition,turning carbon emission reduction into a domestic need for countries to increase their international competitiveness.To achieve the 2°C target,most countries around the world face challenges of insufficient emission allowances to cover expected emissions associated with their projected economic growth.As carbon emissions rights becomes an increasingly scarce resource,increasing the carbon productivity of the economy turns to be the critical path to address the dilemma of green or growth.NCE studies the historical evolution of carbon productivity for countries at different development stages as well as ways to enhance such carbon productivity.This type of study provides invaluable lessons for emerging economies to reach their own emission peaks without losing the momentum of growth.Replacing fossil fuels with new and renewable energy has proven to be an inevitable choice for reshaping the energy system and addressing climate change- it has already become a global trend.NCE studies incentives for new energy technology innovation and deployment provided by carbon pricing,and sheds light on the co-benefits of climate change mitigation,such as resource conservation,environmental protection,and energy security.The role of carbon pricing in promoting intemational RD cooperation and technical transfer will also be studied.The shift in consumption patterns is another key factor enabling a low-carbon transformation.Therefore,NCE also explores the theoretical work on new values of wealth,welfare and consumption,new lifestyles in the context of ecological civilization,concepts and implementation of low-carbon urban planning in developing countries,and the impacts of consumption pattern changes on social development,material production,and urban infrastructure construction.     

用含固定化微生物的曝气生物滤池处理炼油厂高浓度废水

采用含固定化微生物的曝气生物滤池(G-BAF)处理炼油厂高浓度废水。当G-BAF池进水COD为298～11 278 mg/L时,出水COD为33.0～94.3 mg/L,COD平均去除率为97%;当G-BAF池进水ρ(NH_3-N)为12.1～188.0 mg/L时,出水ρ(NH_3-N)为0.9～49.4 mg/L,NH_3-N平均去除率为83%。经G-BAF处理后出水水质完全达到GB8978—1996《污水综合排放标准》第二类污染物的二级排放标准。     

钢渣吸附Pb2+的动力学研究

采用批式振荡吸附法研究了钢渣吸附Pb^2＋的动力学。研究结果表明,钢渣吸附Pb^2＋的动力学控制步骤（简称动力学控制步骤）随实验条件的变化而变化：钢渣粒径大于120μm、振荡器转速小于150r/min或Pb^2＋初始质量浓度小于150mg/L时,孔扩散是动力学控制步骤;钢渣粒径小于120μm、振荡器转速大于150r/min或Pb^2＋初始质量浓度大于150mg/L时,表面扩散是动力学控制步骤;钢渣对Pb^2＋的吸附反应是二级反应,其吸附速率为13.26g/（mg.min）。     

用生物填料塔处理三甲胺废气

为解决废气中有机胺类物质的恶臭污染问题,采用自制生物填料塔处理三甲胺废气,考察了生物填料塔运行的主要影响因素及对三甲胺废气的净化效果。实验结果表明,在进气中三甲胺质量浓度为80.00mg/m3、气体流量为0.3m3/h(停留时间不小于30s)、循环液喷淋密度为0.5m3/(m2.h)的条件下,三甲胺去除率达99.9%,净化后气体能达到国家二级排放标准;生物填料塔对三甲胺的总去除量与容积负荷呈直线关系,相关系数达0.9949,表明三甲胺废气的生物净化效果显著。     

硫化法制备废水处理用光催化剂La3NbS2O5

采用高温硫化法制备了具有可见光活性的La3 NbS2 O5光催化剂,运用X射线衍射谱图、扫描电子显微镜照片、比表面积和紫外-可见漫反射光谱对La3 NbS2 O5的结构、物理性质和光吸收性能进行了表征.以亚甲基蓝为目标降解物,考察了硫化温度、催化剂加入量和制备方法对亚甲基蓝降解率的影响.实验结果表明,当硫化温度为800...     

The living environment and children's fears following the Indonesian tsunami

The tsunami that struck South-east Asia on 26 December 2004 left more than 500,000 people in Aceh, Indonesia, homeless and displaced to temporary barracks and other communities. This study examines the associations between prolonged habitation in barracks and the nature of fears reported by school-age children and adolescents. In mid-2007, 30 months after the tsunami, the authors interviewed 155 child and parent dyads. Logistic regression analysis was used to compare the fears reported by children and adolescents living in barracks with those reported by their peers who were living in villages. After adjusting for demographic factors and tsunami exposure, the data reveals that children and adolescents living in barracks were three times more likely than those living in villages to report tsunami-related fears. The study demonstrates that continued residence in barracks 30 months after the tsunami is associated with higher rates of reporting tsunami-related fears, suggesting that barracks habitation has had a significant impact on the psychological experience of children and adolescents since the tsunami.     

长株潭城市群核心区土地利用生态风险评价

随着长株潭城市群的快速发展,人类活动导致的土地利用结构及方式改变对生态环境构成了巨大压力。运用G IS和景观生态学方法的土地利用生态风险评价,以长株潭城市群核心区为研究区域,选择湘江岸线为典型样带,建立了基于源与汇景观功能的土地利用生态风险评价指标体系,并构建了评价模型,对生态风险进行了空间分析和综合评价。结果表明,长沙市建成区的土地利用生态风险指数整体最高,株洲和湘潭居次。其中,从城市群建成区向外,风险指数逐渐降低,长沙、株洲、湘潭三市交界处生态风险指数也较低。根据研究区域生态风险状况、变化和分布特征,提出了相应的风险调控策略和管理方法,为实现区域土地利用与生态、社会、经济的可持续发展提供决策依据。     

西南山地区域森林火险综合预报模型研究——以重庆市为例

森林火灾严重破坏森林生态系统的结构和功能,针对其风险预报开展研究具有重要的理论意义和应用价值。通过融合气象、地表覆盖和人类活动等要素的方式构建森林火险综合预报模型,是西南山地区域森林火险综合预报业务化应用的重要发展方向。基于《森林火险气象等级》国家标准(GB/T 36743-2018),本文研究首先构建了重庆市森林火险气象风险预报模型。然后通过融合可燃物因素和人为因素的方式,进一步构建重庆市森林火险综合预报模型。最后利用历史火点数据针对上述两类模型的精度进行对比和分析。研究结果表明:重庆市森林火灾发生次数较多,且呈现出季节性规律;重庆市森林火灾的发生不仅受到气象条件的影响,而且受到地表覆盖和人类活动等多种要素条件的共同影响;与森林火险气象风险预报结果相比,森林火险综合预报结果在空间分布上具有更高的精细程度;森林火险综合预报模型能有效提高森林火险等级预报精度。     

局域地形和林火数量对区划方法的影响规律研究

森林火灾等级区划不仅能为预防森林火灾提供宏观指导,并有利于防火人员的合理安排,从而达到对火灾的有效防范和控制。一个好的森林火灾的区划结果得益于适宜的区划方法,而区划方法的选择则受制于区划影响因子,因此探讨森林火灾区划的影响因子对区划结果至关重要。分析了重庆市森林火灾的空间分布特征,并在GIS支持下,利用2000-2010年中527例历史林火记录和DEM数据,分析了局域高度和林火数量对森林火灾区划的影响。最终,将局域高度及林火数量构建成火灾易发程度并空间化,从林火易发程度的角度出发给出了重庆市森林火灾区划结果。通过分析发现,所构建的林火易发程度可从地形和林火数量的角度反映某一地区的林火发生情况,因此局域地形和林火数量可分别作为重庆市森林火灾区划的指标之一。     

Estimating the variance in before-after studies

Problem

To simplify the computation of the variance in before-after studies, it is generally assumed that the observed crash data for each entity (or observation) are Poisson distributed. Given the characteristics of this distribution, the observed value (x_i) for each entity is implicitly made equal to its variance. However, the variance should be estimated using the conditional properties of this observed value (defined as a random variable), that is, f(x_i|μ_i), since the mean of the observed value is in fact unknown.

Method

Parametric and non-parametric bootstrap methods were investigated to evaluate the conditional assumption using simulated and observed data.

Results

The results of this study show that observed data should not be used as a substitute for the variance, even if the entities are assumed to be Poisson distributed. Consequently, the estimated variance for the parameters under study in traditional before-after studies is likely to be underestimated.

Conclusions

The proposed methods offer more accurate approaches for estimating the variance in before-after studies.