Search Results
Aerial river management by smart cross-border reforestation
In the face of increasing socio-economic and climatic pressures in growing cities, it is rational for managers to consider multiple approaches for securing water availability. One often disregarded option is the promotion of reforestation in source regions supplying important quantities of atmospheric moisture transported over long distances through aerial rivers, affecting water resources of a city via precipitation and runoff (‘smart reforestation’). Here we present a case demonstrating smart reforestation's potential as a water management option. Using numerical moisture back-tracking models, we identify important upwind regions contributing to the aerial river of Santa Cruz de la Sierra (Bolivia). Simulating the effect of reforestation in the identified regions, annual precipitation and runoff reception in the city was found to increase by 1.25% and 2.30% respectively, while runoff gain during the dry season reached 26.93%. Given the city's population growth scenarios, the increase of the renewable water resource by smart reforestation could cover 22–59% of the additional demand by 2030. Building on the findings, we argue for a more systematic consideration of aerial river connections between regions in reforestation and land planning for future challenges. © 2019 The Authors
Reviewing the Market Stability Reserve in light of more ambitious EU ETS emission targets
The stringency of the EU's Emission Trading System (ETS) is bound to be ratcheted-up to deliver on more ambitious goals as formulated in the EU's Green Deal. Tightening the cap needs to consider the interactions with the Market Stability Reserve (MSR), which will be reviewed in 2021. We analyse these issues using the model LIMES-EU. First, we examine how revising MSR parameters impacts allowance cancellations. We find that varying key design parameters leads to cancellations in the range of 2.6–7.9 Gt – compared to 5.1 Gt under current regulation. Overall, the bank thresholds, which define when there is intake to/outtake from the MSR, have the highest impact. Intake rates above 12% only have a limited effect, and cause oscillatory intake behaviour. Second, we analyse how more ambitious climate 2030 targets can be achieved by adjusting the linear reduction factor (LRF). We find that the LRF increases MSR cancellations substantially up to 10.0 Gt. This implies that increasing its value from currently 2.2% to only 2.6% could be consistent with an EU-wide target of −55% by 2030. However, MSR cancellations are subject to large uncertainty, which increases the complexity of the market and induces high price uncertainty.
Web technologies for environmental Big Data
Recent evolutions in computing science and web technology provide the environmental community with continuously expanding resources for data collection and analysis that pose unprecedented challenges to the design of analysis methods, workflows, and interaction with data sets. In the light of the recent UK Research Council funded Environmental Virtual Observatory pilot project, this paper gives an overview of currently available implementations related to web-based technologies for processing large and heterogeneous datasets and discuss their relevance within the context of environmental data processing, simulation and prediction. We found that, the processing of the simple datasets used in the pilot proved to be relatively straightforward using a combination of R, RPy2, PyWPS and PostgreSQL. However, the use of NoSQL databases and more versatile frameworks such as OGC standard based implementations may provide a wider and more flexible set of features that particularly facilitate working with larger volumes and more heterogeneous data sources.
How global climate policy could affect competitiveness
A global uniform carbon price would be economically efficient and at the same time avoid ‘carbon-leakage’. Still, it will affect the competitiveness of specific industries, economic activity and employment across countries. This paper assesses short-term economic shocks following the introduction of a global carbon price that would be in line with the Paris Agreement. Based on the World Input-Output Database (WIOD), we trace the carbon content of final output through global supply chains. This allows us to estimate how prices of the final output would react to the introduction of a global carbon price. We find that impacts on industrial competitiveness are highly heterogeneous across regions and economic sectors. The competitive position of Brazil, Japan, the USA and advanced economies of the EU is likely to improve, whereas industries and labor markets in newly industrializing Asian economies as well as Eastern Europe are likely to experience substantial adverse impacts. © 2019 The Author(s)
Mitigating poverty: The patterns of multiple carbon tax and recycling regimes for Peru
Carbon taxes are an economically effective and efficient policy measure to address climate change mitigation. However, they can have severe adverse distributional effects. Recycling parts of the fiscal revenues to vulnerable, lower income households through cash transfers (social assistance) is an option to also overcome associated political difficulties. This paper simulates the distributional impacts of such a combined policy reform in Peru. In a first step, we assess the distributional impacts of varying carbon tax rates. In a second step, we evaluate different scenarios of recycling revenues through existing or expanded transfer schemes towards vulnerable households. The results indicate that a national carbon tax, without compensation, would increase poverty but have no significant impact on inequality. When tax revenues are recycled through transfer schemes, however, poverty would actually decrease. Depending on the amount to be redistributed and the design of the cash transfer scheme, our simulations show a proportional reduction in the poverty headcount of up to around 17%. In addition, the paper underlines how crucial it is to go beyond aggregate measures of poverty to better identify losers from such reform; and assure that the “leave no one behind” principle of the Sustainable Development Goals (SDGs) is addressed.
Producing Policy-relevant Science by Enhancing Robustness and Model Integration for the Assessment of Global Environmental Change
We use the flexible model coupling technology known as the bespoke framework generator to link established existing modules representing dynamics in the global economy (GEMINI_E3), the energy system (TIAM-WORLD), the global and regional climate system (MAGICC6, PLASIM-ENTS and ClimGEN), the agricultural system, the hydrological system and ecosystems (LPJmL), together in a single integrated assessment modelling (IAM) framework, building on the pre-existing framework of the Community Integrated Assessment System. Next, we demonstrate the application of the framework to produce policy-relevant scientific information. We use it to show that when using carbon price mechanisms to induce a transition from a high-carbon to a low-carbon economy, prices can be minimised if policy action is taken early, if burden sharing regimes are used, and if agriculture is intensified. Some of the coupled models have been made available for use at a secure and user-friendly web portal. © 2018 The Authors
Available and missing data to model impact of climate change on European forests
Climate change is expected to cause major changes in forest ecosystems during the 21st century and beyond. To assess forest impacts from climate change, the existing empirical information must be structured, harmonised and assimilated into a form suitable to develop and test state-of-the-art forest and ecosystem models. The combination of empirical data collected at large spatial and long temporal scales with suitable modelling approaches is key to understand forest dynamics under climate change. To facilitate data and model integration, we identified major climate change impacts observed on European forest functioning and summarised the data available for monitoring and predicting such impacts. Our analysis of c. 120 forest-related databases (including information from remote sensing, vegetation inventories, dendroecology, palaeoecology, eddy-flux sites, common garden experiments and genetic techniques) and 50 databases of environmental drivers highlights a substantial degree of data availability and accessibility. However, some critical variables relevant to predicting European forest responses to climate change are only available at relatively short time frames (up to 10-20 years), including intra-specific trait variability, defoliation patterns, tree mortality and recruitment. Moreover, we identified data gaps or lack of data integration particularly in variables related to local adaptation and phenotypic plasticity, dispersal capabilities and physiological responses. Overall, we conclude that forest data availability across Europe is improving, but further efforts are needed to integrate, harmonise and interpret this data (i.e. making data useable for non-experts). Continuation of existing monitoring and networks schemes together with the establishments of new networks to address data gaps is crucial to rigorously predict climate change impacts on European forests. © 2019 The Author(s)
Changing seasonal temperature offers a window of opportunity for stricter climate policy
Environmental catastrophes, including the increased severity and frequency of climate extremes, can act as “windows of opportunities” that challenge citizens’ mental models and motivate them to engage in reflective processes, challenging their pre-conceived ideas. Less well understood is whether experiencing changing weather conditions, common in mid-latitudes, can have a similar effect and increase the citizens’ concerns about climate change and their willingness to accept more stringent climate policies. In this paper, we investigate the effects of changing seasonal temperature on the perceived seriousness of climate change and willingness to mitigate climate change. We use data from four yearly waves of a spatially explicit representative population survey in Germany and weather records from the postal code areas in which they live. To our knowledge, this study is the first analysis to link individual perceptions towards climate change and different mitigation options with seasonal temperature changes at specific locations in Europe. The analyzed perceptions were strongly influenced by socio-demographic characteristics and broader societal changes, as well as individual experiences of seasonal temperatures. The results show that experienced seasonal temperature change influences personal climate change concerns as well as the willingness to mitigate climate change, although with a weaker effect. The results indicate that it is the absolute temperature variation experienced that is important, rather than whether it is getting colder or warmer than usual. Considering the influences identified in this study can offer a window of opportunity for more stringent and targeted climate change policy.
Evaluating the grassland NPP dynamics in response to climate change in Tanzania
Livestock is important for livelihoods of millions of people across the world and yet climate change risk and impacts assessments are predominantly on cropping systems. Climate change has significant impacts on Net Primary Production (NPP) which is a grassland dynamics indicator. This study aimed to analyze the spatio-temporal changes of NPP under climate scenario RCP2.6 and RCP8.5 in the grassland of Tanzania by 2050 and link this to potential for key livestock species. To this end, a regression model to estimate NPP was developed based on temperature (T), precipitation (P) and evapotranspiration (ET) during the period 2001–2019. NPP fluctuation maps under future scenarios were produced as difference maps of the current (2009–2019) and future (2050). The vulnerable areas whose NPP is mostly likely to get affected by climate change in 2050 were identified. The number of livestock units in grasslands was estimated according to NPP in grasslands of Tanzania at the Provincial levels. The results indicate the mean temperature and evapotranspiration are projected to increase under both emission scenarios while precipitation will decrease. NPP is significantly positively correlated with Tmax and ET and projected increases in these variables will be beneficial to NPP under climate change. Increases of 17% in 2050 under RCP8.5 scenario are projected, with the southern parts of the country projected to have the largest increase in NPP. The southwest areas showed a decreasing trend in mean NPP of 27.95% (RCP2.6) and 13.43% (RCP8.5). The highest decrease would occur in the RCP2.6 scenario in Ruvuma Province, by contrast, the mean NPP value in the western, eastern, and central parts would increase in 2050 under both Scenarios, the largest increase would observe in Kilimanjaro, Dar-Es-Salaam and Dodoma Provinces. It was found that the number of grazing livestock such as cattle, sheep, and goats will increase in the Tanzania grasslands under both climate scenarios. As the grassland ecosystems under intensive exploitation are fragile ecosystems, a combination of improving grassland productivity and grassland conservation under environmental pressures such as climate change should be considered for sustainable grassland management.
Looking under the hood: A comparison of techno-economic assumptions across national and global integrated assessment models
Integrated assessment models are extensively used in the analysis of climate change mitigation and are informing national decision makers as well as contribute to international scientific assessments. This paper conducts a comprehensive review of techno-economic assumptions in the electricity sector among fifteen different global and national integrated assessment models. Particular focus is given to six major economies in the world: Brazil, China, the EU, India, Japan and the US. The comparison reveals that techno-economic characteristics are quite different across integrated assessment models, both for the base year and future years. It is, however, important to recognize that techno-economic assessments from the literature exhibit an equally large range of parameters as the integrated assessment models reviewed. Beyond numerical differences, the representation of technologies also differs among models, which needs to be taken into account when comparing numerical parameters. While desirable, it seems difficult to fully harmonize techno-economic parameters across a broader range of models due to structural differences in the representation of technology. Therefore, making techno-economic parameters available in the future, together with of the technology representation as well as the exact definitions of the parameters should become the standard approach as it allows an open discussion of appropriate assumptions. © 2019 The Authors