Introducing nature based solutions (NBS) into urban areas is a challenging task for climate change mitigation and adaptation. However, the impact and effectiveness of NBS contingent upon the social acceptability of implemented measures. This study uses a dynamic and adaptive social acceptance framework that shows how data-driven science can inform the integration of NBS into cities while also ensuring that the public embraces these solutions. We apply the framework to four different cases: METU Forest in Ankara, Tisza River Bank in Szeged, Forest Garden in Alcalá de Henares, and Quarries in Milan. The results indicate that the key factor affecting social acceptance are procedural and distributive fairness, perceived risks, costs and benefits, knowledge, experience, and personal norms. Perceived benefit is the single common driver that directly affects social acceptance across the four case studies. Understanding the risk and benefits of an NBS and developing personal norms related to the environment will contribute to the improvement of resilience.

In this study, we investigate the validity of the J-curve hypothesis based on the bilateral trade models between the UK and its 17 main trading partner countries over the period of 1981Q1-2015Q1, by applying Nonlinear Autoregressive Distributed Lag (NARDL) cointegration approach. The results of this study suggest no evidence supporting the J-curve hypothesis between the UK and any of its 17 trading partners. We also find that depreciations and appreciations in value of the GBP have asymmetric effects on the UK’s trade balances in the short-run. Therefore, the results of this study have potential to shed light on both short run and long run consequences of the recent fluctuations of the GBP with respect to the trade balances after the UK’s EU membership referendum in 2016.

Solar and wind generation are the primary tools to prevent climate change and high carbon emissions. Due to their intermittent generation characteristics, solar and wind power plants have a different impact on the market-clearing price formation compared to conventional generation sources. The paper investigates the solar and wind generation effect on the day ahead market-clearing price in Turkey between the 2016 and 2022. We used a 2nd order polynomial learner model to analyze the impact of solar and wind generation level on the market-clearing price level and volatility. We find that Dutch TTF increases market-clearing price with a coefficient of 0.24. An increase in wind and solar generation reduce the market-clearing price. Solar generation is ineffective on the market-clearing price below a certain demand level. Wind generation reduces market-clearing price with a 37.78 coefficient at low demand levels and a 6.55 coefficient at high demand levels. Solar generation has a price-reducing effect with 5.55 at high demand levels. Finally, Dutch TTF and wind generation increased volatility with coefficients of 0.04 and 0.69; solar generation reduced volatility with a coefficient of 0.83.

Over the last two decades, the current accounts in the European Union (EU) have diverged substantially. This divergence has raised concerns about the sustainability of the core countries' current account surpluses since the peripheral countries' financing of their significantly rising levels of current deficits depends on them. In this study, by applying both linear and nonlinear unit root tests and taking into account structural breaks in the datagenerating process, we examine the current account sustainability of the main core countries with large external surpluses. We find that the current accounts of Austria, Denmark and Germany are not on sustainable paths, which suggests that the core economies might not continue to run surpluses to finance the peripheral countries' external deficits. The results of this study imply that the policymakers in peripheral countries might take proactive measures against possible borrowing problems and capital outflow risk in the future.

The direct rebound effect for space heating targeting households in Ankara, Turkey, is calculated by using primary and socio-economic indicators related data for energy efficiency applications in buildings. The demographic, dwelling characteristics, and behavioral factors that affect gas consumption are included in the analyses and are found to be crucial to assuring the successful implementation of energy efficiency technology in space heating.

Examining the relation between oil price changes and the trade balance is important for oil-importing countries to formulate policy solutions. This study contributes to the literature by examining the asymmetric effects of changes in oil prices on the trade balance of China, the world’s largest crude oil importer. To this end, the Nonlinear Autoregressive Distributed Lag (NARDL) cointegration approach and Pesaran’s Generalized Variance Decompositions technique are adopted. The results reveal that the trade balance responds asymmetrically to oil price changes in the long run, while the responses are symmetric in the short run. The Generalized Variance Decompositions results indicate that the trade balance is more sensitive to the oil price increases than to decreases. These results indicate that China should support energy-efficient systems to reduce its dependency on imported oil.