ALBERT

Description: Sustainability projects are being promoted around the world with a large dose of spectacle, including those in the Arabian Peninsula where governments have invested heavily in large greening projects and events. This article examines these spectacular projects in the United Arab Emirates (UAE), which are typically dismissed by Western observers as mere PR and ‘greenwashing.’ Moving past this simplistic critique, I contextualize ‘sustainability spectacle’ as a broad cultural phenomenon, with deep roots in Western countries. Based on ethnographic research on sustainability events, sites, and initiatives in the UAE, I show how ‘post-oil’ greening initiatives use sustainability spectacle to promote a positive narrative about the ‘modern’ national self, and reflect the growing international imperative to be green.

Description: We study the impact of California’s cap-and-trade system on carbon emissions in the electricity and industrial sectors. We use US state-level panel data covering the period 2005–2019 and apply the synthetic control method to construct an optimal counterfactual for per capita emissions in each sector. In our experiment, emissions in the power sector fall below counterfactual emissions by 48%. In the industrial sector, the state’s emissions are 6% higher than those of the synthetic control unit by the end of the observation period. Thus, cap-and-trade failed to deliver decarbonization across both sectors. While the abatement in the power sector was facilitated by complementary policies and driven by a switch from natural gas to renewables, California’s policy mix has disincentivized emission reductions in the industrial sector.

Description: Concentrating Solar Power (CSP) offers flexible and decarbonized power generation and is one of the few dispatchable renewable technologies able to generate renewable electricity on demand. Today (2018) CSP contributes only 5TWh to the European power generation, but it has the potential to become one of the key pillars for European decarbonization pathways. In this paper we investigate how factors and pivotal policy decisions leading to different futures and associated CSP deployment in Europe in the years up to 2050. In a second step we characterize the scenarios with their associated system cost and the costs of support policies. We show that the role of CSP in Europe critically depends on political developments and the success or failure of policies outside renewable power. In particular, the uptake of CSP depends on the overall decarbonization ambition, the degree of cross border trade of renewable electricity and is enabled by the presence of strong grid interconnection between Southern and Norther European Member States as well as by future electricity demand growth. The presence of other baseload technologies, prominently nuclear power in France, reduce the role and need for CSP. Assuming favorable technological development, we find a strong role for CSP in Europe in all modeled scenarios: contributing between 100TWh to 300TWh of electricity to a future European power system. This would require increasing the current European CSP fleet by a factor of 20 to 60 in the next 30 years. To achieve this financial support between € 0.4-2 billion per year into CSP would be needed, representing only a small share of overall support needs for power-system transformation. Cooperation of Member States could further help to reduce this cost.

Description: Simulating the ozone variability at regional scales using chemistry transport models (CTMs) remains a challenge. We designed a multi-model intercomparison to evaluate, for the first time, four regional CTMs on a national scale for Germany. Simulations were conducted with LOTOS-EUROS, REM-CALGRID, COSMO-MUSCAT and WRF-Chem for January 1st to December 31st, 2019, using prescribed emission information. In general, all models show good performance in the operational evaluation with average temporal correlations of MDA8 O3 in the range of 0.77-0.87 and RMSE values between 16.3 mu g m3 and 20.6 mu g m- 3. On average, better models' skill has been observed for rural background stations than for the urban background stations as well as for springtime compared to summertime. Our study confirms that the ensemble mean provides a better model-measurement agreement than individual models. All models capture the larger local photochemical production in summer compared to springtime and observed differences between the urban and the rural background. We introduce a new indicator to evaluate the dynamic response of ozone to temperature. During summertime a large ensemble spread in the ozone sensitivities to temperature is found with (on average) an underestimation of the ozone sensitivity to temperature, which can be linked to a systematic underestimation of mid-level ozone concentrations. During springtime we observed an ozone episode that is not covered by the models which is likely due to deficiencies in the representation of background ozone in the models. We recommend to focus on a diagnostic evaluation aimed at the model descriptions for biogenic emissions and dry deposition as a follow up and to repeat the operational and dynamic analysis for longer timeframes.

Description: Why do exercises in collaborative governance often witness more impasse than advantage? This paper suggests putting power at center stage and focusing the analysis on the micro level. It is by looking at the daily ‘minutiae’ of collaboration, and at the dynamics (here called flows of power) that they set off, that we can gain insights into failures of collaborative arrangements. To enable a power-sensitive and process-oriented analysis of collaborative governance, the paper develops an analytical framework for the empirical exploration of collaborative governance at the micro level. The framework examines how design choices at the outset of collaboration are re-interpreted, challenged, and transformed by micro-dynamics taking place over the course of the arrangement. The article argues that a process-oriented investigation of how collaboration evolves and unfolds over time elucidates the subtleties of power, which may be overlooked if we only consider outcomes rather than the processes that engender these outcomes. The work is based on an abductive research approach and illustrates the analytical possibilities of the framework by zooming in on an exemplar of a collaborative arrangement for planning the route of a high-voltage electricity line in Germany.

Description: The Tibetan Plateau is a global hotspot of stratospheric intrusion, and elevated surface ozone was observed at ground monitoring sites. Still, links between the variability of surface ozone and stratospheric intrusion at the regional scale remain unclear. This study synthesized ground measurements of surface ozone over the Tibetan Plateau and analyzed their seasonal variations. The monthly mean surface ozone concentrations over the Tibetan Plateau peaked earlier in the south in April and May and later in the north in June and July. The migration of monthly surface ozone peaks was coupled with the synchronous movement of tropopause folds and the westerly jet that created conditions conducive to stratospheric ozone intrusion. Stratospheric ozone intrusion significantly contributed to surface ozone across the Tibetan Plateau, especially in the areas with high surface ozone concentrations during their peak-value month. We demonstrated that monthly variation of surface ozone over the Tibetan Plateau is mainly controlled by stratospheric intrusion, which warrants proper consideration in understanding the atmospheric chemistry and the impacts of ozone over this highland region and beyond.

Description: Transdisciplinary processes deal with transdisciplinary problems that are (i) complex, (ii) societally relevant, (iii) ill-defined, and (iv) real-world problems which often show a high degree of ambiguity resulting in contested perceptions and evaluations among and between scientists and practitioners. Therefore, they are susceptible to multiple trade-offs. Transdisciplinary processes construct socially robust orientations (SoROs) particularly for sustainable transitioning. The integration of science and practice knowledge on equal footing (1) is considered the core of transdisciplinary processes. Yet other forms of knowledge integration contribute essentially to construct SoROs. Individuals may (2) use different modes of thought; (3) refer to various cultures with diverse value and belief systems; and (4) problems are perceived and prioritized based on roles and interests. Coping with transdisciplinary problems, (5) purposeful differentiation and integration and (6) an integration of evolutionary evolving codes of representing knowledge are necessary. Finally, (7) what systems to integrate requires consensus-building among participating scientists and practitioners. This paper is Part I of a two-part publication. It provides a conceptualization of the different types of knowledge integration. Part II analyzes tasks, challenges, and barriers related to different types of knowledge integration in five transdisciplinary processes which developed SoROs for sensitive subsystems of Germany affected by the irresponsible use of digital data.

Description: Millions of people are exposed to enhanced levels of nitrogen dioxide in urbanized areas, leading to severe health effects. Moreover, nitrogen oxides contribute to the formation of ozone and particulate matter, and as such have wider health related impacts. A substantial reduction of nitrogen oxides may offer considerable health benefits for the human society. As a first step, this requires a detailed understanding of source sector contributions to nitrogen oxide levels. Whereas many regions have information on the local (traffic) contributions, the source contributions to the rural and urban background levels are commonly not available. In this study we compared and evaluated the results of two source attribution techniques to quantify the contribution of 5 source sectors to background nitrogen oxide levels across Germany. The results of a labelling technique were compared to brute force simulations with variable emission reduction percentages. The labelled NO2 source contributions of the main sectors averaged for all urban background stations are road transport (45 ± 5%), non-road transport (24 ± 6%), energy & industry (20 ± 3%), households (10 ± 6%), and the remaining source sectors (1 ± 1%). For the brute force technique, the explained mass differs from the unperturbed baseline concentration after scaling the impact of each sensitivity simulation to 100%. The attributed concentration of NO2 is lower in urban background areas (−3 ± 5%) and larger in the rural background (4 ± 6%) than that of the labelling. Largest deviations up to −15% are calculated for the major cities along the Rhine and Main. The annual average overestimation for NO is about 53 ± 24% for urban and 40 ± 26% for rural background sites based on a 20% reduction of emissions. On shorter time scales the differences are larger. These deviations are caused by (the lack of) regime changes in the titration of ozone, most notably present at ozone-limiting conditions during nocturnal winter periods. As a consequence, the differences between the methodologies are larger for smaller emission reduction percentages applied in the brute force technique. Similarly, for small-sized emission source sectors larger deviations were found compared to large-sized sector categories. Hence, applying the brute force technique for the source attribution for a single sector should be avoided as there is no way to verify for consistency and quantify the error for the sector and total explained contribution. We recommend applying the labelling approach to estimate sector contributions in forthcoming studies for nitrogen oxides.

Description: The focus of the paper is to use a single weibo from a user to predict whether the user account is verified, referred to as verified account prediction, on Sina Weibo. To the best of our knowledge, verified account prediction on Sina Weibo has not been studied. For better understanding of the prediction problem, a comprehensive data analysis of weibos related to verified accounts is conducted first. Then, verified account prediction is formulated as a sequence learning problem. Specifically, a weibo from a user is represented as a sequence of feature values by feature hashing and whether the user account is verified is the corresponding label to predict. A deep learning approach is proposed for solving verified account prediction in this formulation. The proposed approach significantly outperforms the shallow learning methods in the comparisons in terms of accuracy and F1 by large margins in the experiments.