“引洮工程”引发的受水区污染治理研究

[目的]为了解决甘肃中部安定区、陇西县、渭源县、临洮县、榆中县和会宁县的人畜饮水、工业用水、生态用水及农业灌溉用水问题,引洮工程通过九甸峡水利枢纽抬高水位将黄河上游洮河支流水资源引入受水区。在受水区,在调水增加本区供水总量的同时,相应增加了增量水资源使用后带来的废污水,客观上对污染治理工作水平提出了更高要求,轻视排污问题将加剧受水区乃至下游的水系污染程度,影响受水区经济社会的可持续发展。[方法]文章采用文献研究法从理论上探讨了环境容量、排污权及其关系。采用定额计量法计算了调水带来的COD和氨氮增量。[结果]调水使得受水区COD和氨氮每年分别增加6 914. 30t和1 440. 48t。就COD而言,受水区平均排放量占该区环境容量的51. 12%,似有较多的容量结余,但区内排放极不平衡,榆中和会宁已经超排。就氨氮而言,受水区平均排放量将占该区环境容量的151. 55%,总体超排很严重。区内除临洮以外,其余5县区均超排,其中,榆中和会宁超排1倍以上。[结论]排污量是假定增量污水符合二级排放标准的前提下计算的,如果处理率低、排放达标率低,则超排现象会更为严重。对此,要从宏观上进行综合治理,诸如完善政府、社会与市场共同治污机制、排污权配置的过渡性制度安排、污水处理企业改革及引导受水区进行产业结构调整等。     

广东湖北碳排放权市场动态相依性分析与风险测度

选择具有代表性的湖北和广东碳排放权交易市场为研究对象,利用GARCH-POT-Copula模型对这两个市场的动态相依性与组合风险度量进行分析。研究结果表明:广东和湖北碳排放权市场之间的相依度较小,两个碳排放权市场价格波动不能给对方市场带来较大的影响,两市场近似于独立存在。提出了要从配额指标、基础设施建设、报送系统、市场交易主体等方面建立健全和完善全国统一的碳排放权交易市场的建议。     

关键驱动力作用下的新疆生态系统服务时空格局分析

[目的]恶劣的生态环境和有限的资源驱动着新疆特殊生态系统服务的形成,人类又通过对生态系统服务的消费来满足和提高自身福祉,需要研究其时空变化并辨识主要驱动因素,支持区域可持续发展。[方法]文章构建了融合不同土地利用类型生态系统服务的价值量排序及服务功能强度矩阵的生态系统服务评估体系,并耦合3种关键驱动因子以评估各个因子的驱动强度,实现对生态系统服务热点与冷点变化的驱动及迁移分析。[结果]2000—2010年全疆生态系统服务总体增加,这一时期生态系统服务的热点区大部分转变为2010—2015年的冷点区,且15年来生态系统服务总体呈现小幅下降趋势。3个时期北疆和南疆人为干扰强度均呈增加趋势,由其驱动的生态系统服务则相应减小;南疆地区植被覆盖范围极其有限,故对生态系统服务驱动强度低;降水在北疆和南疆都能够产生高生态系统服务,但降水量的不稳定性能够使生态系统服务产生较大波动。相比于南疆地区,北疆生态系统在外界干扰下能够体现出更强的抗性和整体性,从而实现相对高效的生态系统服务输出。[结论]对关键驱动因子作用下的生态系统服务进行时空变化分析,有助于理解当地生态系统产生变化的原因,从而为当地生态环境保护提供参考。     

Cox Point Processes: Why One Realisation Is Not Enough

We review a rich class of point process models, Cox point processes, and illustrate the necessity of more than one observation (point patterns) in performing parameter estimation. Furthermore, we introduce a new Cox point process model by treating the intensity function of the underlying Poisson point process as a random mixture of normal components. The behaviour and performance of the new model are compared with those of popular Cox point process models. The new model is exemplified with an application that involves a single point pattern corresponding to earthquake events in California, USA.     

Beyond symbolic and substantive: Strategic disclosure of corporate environmental information in China

Under increasing regulatory pressure to disclose environmental impacts, corporate environmental information disclosure (EID) is becoming more prevalent. However, the motives for EID and disclosure approaches (i.e., symbolic or substantive) remain controversial. Using a sample of data for 742 listed manufacturing firms in China across 3 years, we provide evidence to show that the level of EID is significantly positively associated with a firm's advertising intensity and that firms in moderately competitive industries have a higher propensity for adopting an EID‐based differentiated strategy than firms in stronger or weaker competitive industries. We also find that firms that are more sensitive to environmental issues strategically understate their environmental impact when directly facing consumers. Our results suggest that the implementation of corporate EID is strategic and that firms have strong market motives, even under regulatory pressure to demonstrate legitimacy. We discuss this study's contributions to research on EID theory and implications for strategic EID management.     

Size and value effects in high-tech industries: The role of R&D investment

We use monthly US stock data over 55 years from 1962 to 2017 to show that the R&D intensity at firms adds another important dimension to the size and value effects in describing stock returns, especially for small high-tech firms. A trading strategy that double sorts on R&D intensity and size or book-to-market ratio outperforms a simple small-minus-big (SMB) or high-minus-low (HML) strategy in producing higher and more significant portfolio returns. The most profitable schemes involve triple sorts by size, BM, and R&D intensity: the payoffs of buying high-BM/R&D-Active portfolio and selling low-BM/R&D-Inactive portfolio in the small-size/high-tech group and that of buying high-tech/high-BM and selling low-tech/low-BM in the small-size/R&D-active group generate a return of more than 2% on a monthly basis. Our results are robust to alternative classification method of assigning stocks in portfolios.     

碳排放交易制度的节能减排路径：效率提升还是结构转型？——来自中国省级数据的准自然实验

以中国2013年以来实行的碳排放交易试点政策作为准自然实验事件，基于2000-2017年中国30个省市的面板数据，运用双重差分法实证检验碳排放交易制度的节能减排效应及影响机制。研究发现，碳排放交易制度有利于实现中国经济“节能”与“减排”的双重目标，并通过了一系列稳健性检验；作用机制检验表明，能源效率提升和能源结构转型都是碳排放交易制度实现节能减排目标的重要路径；能源效率提升在碳排放交易制度实现“节能”和“减排”中分别发挥了10.19%和5.93%的作用，而能源结构转型分别发挥了48.87%和52.95%的作用。这意味着中国碳排放交易制度实现节能减排的主要动力来自能源结构转型，而非能源效率提升。能源结构转型涉及问题更加宏观和深层，这为中国加快推进节能减排进程，特别是完成2030年碳达峰和2060年碳中和的国际承诺提供政策启示。     

老龄化与碳排放：消费效应还是生产效应？——基于2002-2017年中国省级面板数据的实证研究

人口老龄化是经济增长的一大阻碍,它对碳排放的影响是做出环境政策抉择的关键因素.以中国2002—2017年的省级面板数据为研究样本,从理论与实证两个层面分析人口老龄化与碳排放的关系及影响机制.一方面,构建包含碳排放的世代交叠模型(overlapping generations,OLG),发现老龄化主要通过消费效应和生产效应两个路径对碳排放产生影响;另一方面,从实证层面发现老龄化与碳排放之间存在倒"U"形关系,而且消费效应在人口老龄化与碳排放的关系中起到部分中介作用,生产效应的影响则不显著.     

基于神经网络的建筑业碳排放强度预测——以京津冀为例

通过统计分析得出影响建筑业碳排放强度的13个影响因素,基于收集的京津冀相关数据,运用逐步回归分析找出其中6个关键因素.借鉴五折交叉验证解决数据稀缺问题,采用神经网络对京津冀建筑业碳排放强度进行预测.利用敏感性分析简化模型,筛选出4个核心因素.结果表明,此模型预测精度高达99％,同时根据挖掘出的核心因素和关键因素,提出建筑业节能减排的建议.     

Estimating emissions based on the integration of microscopic traffic simulation and vehicle dynamics model

This study proposes an integrated simulation approach, which consists of a microscopic traffic simulation model, a vehicle dynamics model, and an emission estimation model, in order to estimate emissions based on more reliable vehicle performance measures. The vehicle performance measures such as engine power and engine speed significantly relate to the amount of emissions, and road curvatures and inclinations are the core inputs affecting these vehicle performance measures. Therefore, providing reliable vehicle performance measures reflecting the road geometric attributes is critical for a reliable emission estimation. This study proposes to use the microscopic traffic simulation model for generating vehicle trajectories, which is advantageous in modeling various traffic situations, and the vehicle dynamics model for producing the vehicle performance measures based on the vehicle trajectories. Finally, the outputs from the vehicle dynamics model are fed into the emission estimation model to compute emission measures. This study conducted a case-study using two road sections, one is a hypothesized road section, including various curvatures and inclinations with regular variations, and the other is a Kesselberg road section, which is an actual geometry in Bayern, Germany. The emission measures are estimated in these case-study road sections using both an existing simulation approach and the proposed integrated simulation approach. The difference between these two emission estimation approaches is discussed in terms of the emission measures, including fuel consumption, nitrogen oxides, and particulate matters.