Climate change mitigation scenarios and policies and measures: the case of Kazakhstan

This article illustrates the main difficulties encountered in the preparation of GHG emission projections and climate change mitigation policies and measures (P&M) for Kazakhstan. Difficulties in representing the system with an economic model have been overcome by representing the energy system with a technical-economic growth model (MARKAL-TIMES) based on the stock of existing plants, transformation processes, and end-use devices. GHG emission scenarios depend mainly on the pace of transition in Kazakhstan from a planned economy to a market economy. Three scenarios are portrayed: an incomplete transition, a fast and successful one, and even more advanced participation in global climate change mitigation, including participation in some emission trading schemes. If the transition to a market economy is completed by 2020, P&M already adopted may reduce emissions of CO₂ from combustion by about 85 MtCO₂ by 2030 – 17% of the emissions in the baseline (WOM) scenario. One-third of these reductions are likely to be obtained from the demand sectors, and two-thirds from the supply sectors. If every tonne of CO₂ not emitted is valued up to US$10 in 2020 and $20 in 2030, additional P&M may further reduce emissions by 110 MtCO₂ by 2030.     

Trend and Interannual Variability of Chinese Air Pollution since 2000 in Association with Socioeconomic Development: A brief Overview

air pollution, trend and variability, socioeconomic development, satellite measurements, bottom-up emission inventories, top-down constraints     

Top-down and bottom-up modelling to support low-carbon scenarios: climate policy implications

Bottom-up and top-down models are used to support climate policies, to identify the options required to meet GHG abatement targets and to evaluate their economic impact. Some studies have shown that the GHG mitigation options provided by economic top-down and technological bottom-up models tend to vary. One reason for this is that these models tend to use different baseline scenarios. The bottom-up TIMES_PT and the top-down computable general equilibrium GEM-E3_PT models are examined using a common baseline scenario to calibrate them, and the extend of their different mitigation options and its relevant to domestic policy making are assessed. Three low-carbon scenarios for Portugal until 2050 are generated, each with different GHG reduction targets. Both models suggest close mitigation options and locate the largest mitigation potential to energy supply. However, the models suggest different mitigation options for the end-use sectors: GEM-E3_PT focuses more on energy efficiency, while TIMES_PT relies on decrease carbon intensity due to a shift to electricity. Although a common baseline scenario cannot be ignored, the models’ inherent characteristics are the main factor for the different outcomes, thereby highlighting different mitigation options.

Policy relevance

The relevance of modelling tools used to support the design of domestic climate policies is assessed by evaluating the mitigation options suggested by a bottom-up and a top-down model. The different outcomes of each model are significant for climate policy design since each suggest different mitigation options like end-use energy efficiency and the promotion of low-carbon technologies. Policy makers should carefully select the modelling tool used to support their policies. The specific modelling structures of each model make them more appropriate to address certain policy questions than others. Using both modelling approaches for policy support can therefore bring added value and result in more robust climate policy design. Although the results are specific for Portugal, the insights provided by the analysis of both models can be extended to, and used in the climate policy decisions of, other countries.     

遥感图谱认知理论与计算

近年来,随着对地观测技术的迅猛发展,卫星遥感领域逐渐进入了大数据时代。针对当前遥感应用的需求和特点,开展与视觉认知相结合的高分辨率遥感认知理论与方法研究是可行且必要的。在此背景下,受地学信息图谱思想启发,本文对遥感认知领域的图谱问题进行了研究,系统地提出了遥感图谱认知理论与计算方法论,旨在规范高分辨率遥感信息提取流程,构建精细化、定量化、智能化、综合化相结合的遥感信息解译模型。整套方法体系由横向“自底向上的分层抽象”和纵向“自顶向下的知识迁移”2个方向上的认知计算组成,分别对应了“由谱聚图”、“图谱协同”和“认图知谱”3大图谱转化过程。论文对涉及的概念、基本思想、关键技术及难点问题进行了重点分析,强调综合利用大数据、逐步融入知识来实现不同层次的遥感认知,以期为数据源极大丰富条件下的遥感信息解译提供新的视角。     

Integrating agriculture and energy to assess GHG emissions reduction: a methodological approach

Agriculture is responsible for approximately 25% of anthropogenic global GHG emissions. This significant share highlights the fundamental importance of the agricultural sector in the global GHG emissions reduction challenge. This article develops and tests a methodology for the integration of agricultural and energy systems modelling. The goal of the research is to extend an energy systems modelling approach to agriculture in order to provide richer insights into the dynamics and interactions between the two (e.g. in competition for land-use). We build Agri-TIMES, an agricultural systems module using the TIMES energy systems modelling framework, to model the effect of livestock emissions and explore emissions reduction options. The research focuses on Ireland, which is an interesting test case for two reasons: first, agriculture currently accounts for about 30% of Ireland's GHG emissions, significantly higher than other industrialized countries yet comparable with global levels (here including emissions associated with other land-use change and forestation); second, Ireland is both a complete and reasonably sized agricultural system to act as a test case for this new approach. This article describes the methodology used, the data requirements, and technical assumptions made to facilitate the modelling. It also presents results to illustrate the approach and provide associated initial insights.

Policy relevance

Most of the policy focus with regard to climate mitigation targets has been on reducing energy-related CO₂ emissions, which is understandable as they represent by far the largest source of emissions. Non-energy-related GHG emissions – largely from agriculture, industrial processes, and waste – have received significantly less attention in policy discourse. Going forward, however, if significant cuts are made in energy-related CO₂ emissions, the role of non-energy-related GHG emissions will grow in importance. It is therefore crucial that climate mitigation analyses and strategies are not limited to the energy system. This article shows the value of using integrated energy and agriculture techno-economic modelling techniques to draw evidence for new comprehensive climate policy strategies able to discern between the full range of technical solutions available. It enables the production of economy-wide least-cost climate mitigation pathways.     

Adaptation of water resources systems to changing society and environment: a statement by the International Association of Hydrological Sciences

ABSTRACT

We explore how to address the challenges of adaptation of water resources systems under changing conditions by supporting flexible, resilient and low-regret solutions, coupled with on-going monitoring and evaluation. This will require improved understanding of the linkages between biophysical and social aspects in order to better anticipate the possible future co-evolution of water systems and society. We also present a call to enhance the dialogue and foster the actions of governments, the international scientific community, research funding agencies and additional stakeholders in order to develop effective solutions to support water resources systems adaptation. Finally, we call the scientific community to a renewed and unified effort to deliver an innovative message to stakeholders. Water science is essential to resolve the water crisis, but the effectiveness of solutions depends, inter alia, on the capability of scientists to deliver a new, coherent and technical vision for the future development of water systems.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR not assigned     

鲫(Carassius auratus)对浅水湖泊水体浊度、营养水平和浮游生物生物量的影响——基于中宇宙模拟实验

鲫(Carassius auratus)是我国各类淡水水体的优势鱼类之一.作为底栖杂食性鱼类,一方面,鲫可以通过排泄和扰动沉积物影响湖泊营养和光照水平,通过"上行效应"促进浮游植物生长;另一方面,鲫也可以捕食浮游动物,通过"下行控制"影响藻类生长以及营养盐循环.对于浅水湖泊,两种途径对于生态系统影响的相对重要性仍有待研究.本研究设计了一个两因素户外中宇宙实验,通过在沉积物表面添加隔网的方式,比较两种情况下(能、否接触沉积物),鲫对水体浊度、营养盐和浮游生物生物量的影响.实验在16个大型钢化玻璃桶(400 L)中进行,持续36 d(2019年8月6日—9月11日).研究结果表明:1)在能接触沉积物的条件下,鲫显著促进了沉积物再悬浮,表现为水体的总悬浮物(TSS)和无机悬浮物(ISS)浓度大幅升高;水体的光衰减系数(Kd)增加,总氮(TN)和总磷(TP)浓度明显升高; 2)在不能接触沉积物的条件下,鲫对水体悬浮物(TSS和ISS)浓度和Kd的影响不明显,但是显著降低了水体TN和TP浓度; 3)在两种情况下,鲫对浮游植物叶绿素a浓度以及浮游动物生物量的影响均不显著.本研究表明鲫只有在能够接触沉积物的条件下,才会显著提高水体浊度和营养水平.因此,在缺乏沉水植被的浅水湖泊中,鲫扰动沉积物产生的"上行效应"可能是其对生态系统产生负面影响的主要途径.