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- ItemMitigating poverty: The patterns of multiple carbon tax and recycling regimes for Peru(Amsterdam [u.a.] : Elsevier Science, 2021) Malerba, Daniele; Gaentzsch, Anja; Ward, HaukeCarbon 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.
- ItemBalancing Health, Economy and Climate Risk in a Multi-Crisis(Basel : MDPI, 2021) Nathwani, Jatin; Lind, Niels; Renn, Ortwin; Schellnhuber, Hans JoachimIn the presence of a global pandemic (COVID-19), the relentless pressure on global decision-makers is to ensure a balancing of health (reduce mortality impacts), economic goals (income for livelihood sustenance), and environmental sustainability (stabilize GHG emissions long term). The global energy supply system is a dominant contributor to the GHG burden and deeply embedded in the economy with its current share of 85%, use of fossil fuels has remained unchanged over 3 decades. A unique approach is presented to harmonizing the goals of human safety, economic development, and climate risk, respectively, through an operational tool that provides clear guidance to decision-makers in support of policy interventions for decarbonization. Improving climate change performance as an integral part of meeting human development goals allows the achievement of a country’s environmental, social, and economic well-being to be tracked and monitored. A primary contribution of this paper is to allow a transparent accounting of national performance highlighting the goals of enhancing human safety in concert with mitigation of climate risks. A measure of a country’s overall performance, combined as the Development and Climate Change Performance Index (DCI), is derived from two standardized indexes, the development index H and the Climate Change Performance Index CCPI. Data are analyzed for 55 countries comprising 65 percent of the world’s population. Through active management and monitoring, the proposed DCI can illustrate national performance to highlight a country’s current standing, rates of improvement over time, and a historical profile of progress of nations by bringing climate risk mitigation and economic well-being into better alignment.
- ItemAnalysing Interlinked Frequency Dynamics of the Urban Acoustic Environment(Basel : MDPI AG, 2022) Haselhoff, Timo; Braun, Tobias; Hornberg, Jonas; Lawrence, Bryce T.; Ahmed, Salman; Gruehn, Dietwald; Moebus, SusanneAs sustainable metropolitan regions require more densely built-up areas, a comprehensive understanding of the urban acoustic environment (AE) is needed. However, comprehensive datasets of the urban AE and well-established research methods for the AE are scarce. Datasets of audio recordings tend to be large and require a lot of storage space as well as computationally expensive analyses. Thus, knowledge about the long-term urban AE is limited. In recent years, however, these limitations have been steadily overcome, allowing a more comprehensive analysis of the urban AE. In this respect, the objective of this work is to contribute to a better understanding of the time-frequency domain of the urban AE, analysing automatic audio recordings from nine urban settings over ten months. We compute median power spectra as well as normalised spectrograms for all settings. Additionally, we demonstrate the use of frequency correlation matrices (FCMs) as a novel approach to access large audio datasets. Our results show site-dependent patterns in frequency dynamics. Normalised spectrograms reveal that frequency bins with low power hold relevant information and that the AE changes considerably over a year. We demonstrate that this information can be captured by using FCMs, which also unravel communities of interlinked frequency dynamics for all settings.
- ItemAwareness, Experience, and Knowledge of Farming Households in Rural Bangladesh Regarding Mold Contamination of Food Crops: A Cross-Sectional Study(Basel : MDPI AG, 2021) Kyei, Nicholas N. A.; Waid, Jillian L; Ali, Nurshad; Gabrysch, SabineAside from specific environmental conditions, poor agricultural practices contribute to mold and thus the mycotoxin contamination of crops. This study investigated Bangladeshi farming households’ (i) awareness of and experience with mold contamination of food crops; (ii) knowledge and awareness of the timing, causes, and consequences of mold and mycotoxin contamination; and (iii) knowledge of the recommended agricultural practices for controlling and preventing mold contamination of food crops. A survey was conducted with 1280 households in rural areas of Habiganj district, Bangladesh. Basic descriptive statistics were calculated, and mixed-effects linear regression analyses were performed to examine associations between household characteristics and overall knowledge scores. The awareness of mold contamination of food crops was very high (99%; 95% CI: 98–100%) and a shared experience among households (85%; 95% CI: 80–88%). Yet, the majority (80%; 95% CI: 76–84%) demonstrated a low level of knowledge of the timing, causes, and preventive practices regarding mold contamination of crops. Knowledge scores were similar over demographic groups and better for households with more arable land. The findings suggest a generally insufficient knowledge of the conditions that favor mold contamination and the measures for preventing mold contamination of food crops. These findings underline the need for tailored interventions to promote good agricultural practices and reduce mold contamination of food crops.
- ItemTightening EU ETS targets in line with the European Green Deal: Impacts on the decarbonization of the EU power sector(Amsterdam : Elsevier Science, 2021) Pietzcker, Robert C.; Osorio, Sebastian; Rodrigues, RenatoThe EU Green Deal calls for climate neutrality by 2050 and emission reductions of 50–55% in 2030 in comparison to 1990. Achieving these reductions requires a substantial tightening of the regulations of the EU emissions trading system (EU ETS). This paper explores how the power sector would have to change in reaction to a tighter EU ETS target, and analyses the technological and economic implications. To cover the major ETS sectors, we combine a detailed power sector model with a marginal-abatement cost curve representation of industry emission abatement. We find that tightening the target would speed up the transformation by 3–17 years for different parts of the electricity system, with renewables contributing 74% of the electricity in 2030, EU-wide coal use almost completely phased-out by 2030 instead of 2045, and zero electricity generation emissions reached by 2040. Carbon prices within the EU ETS would more than triple to 129€/tCO2 in 2030, reducing cumulated power sector emissions from 2017 to 2057 by 54% compared to a scenario with the current target. This transformation would come at limited costs: total discounted power system costs would only increase by 5%. We test our findings against a number of sensitivities: an increased electricity demand, which might arise from sector coupling, increases deployment of wind and solar and prolongs gas usage. Not allowing transmission expansion beyond 2020 levels shifts investments from wind to PV, hydrogen and batteries, and increases total system costs by 3%. Finally, the unavailability of fossil carbon capture and storage (CCS) or further nuclear investments does not impact results. Unavailability of bioenergy-based CCS (BECCS) has a visible impact (18% increase) on cumulated power sector emissions, thus shifting more of the mitigation burden to the industry sector, but does not increase electricity prices or total system costs (<1% increase). © 2021 The Authors
- ItemReviewing the Market Stability Reserve in light of more ambitious EU ETS emission targets(Amsterdam [u.a.] : Elsevier Science, 2021) Osorio, Sebastian; Tietjen, Oliver; Pahle, Michael; Pietzcker, Robert C.; Edenhofer, OttmarThe 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.
- ItemFuture changes in consumption: The income effect on greenhouse gas emissions(Amsterdam [u.a.] : Elsevier Science, 2021) Bjelle, Eivind Lekve; Wiebe, Kirsten S.; Többen, Johannes; Tisserant, Alexandre; Ivanova, Diana; Vita, Gibran; Wood, RichardThe scale and patterns of household consumption are important determinants of environmental impacts. Whilst affluence has been shown to have a strong correlation with environmental impact, they do not necessarily grow at the same rate. Given the apparent contradiction between the sustainable development goals of economic growth and environmental protection, it is important to understand the effect of rising affluence and concurrent changing consumption patterns on future environmental impacts. Here we develop an econometric demand model based on the data available from a global multiregional input-output dataset. We model future household consumption following scenarios of population and GDP growth for 49 individual regions. The greenhouse gas (GHG) emissions resulting from the future household demand is then explored both with and without consideration of the change in expenditure over time on different consumption categories. Compared to a baseline scenario where final demand grows in line with the 2011 average consumption pattern up until 2030, we find that changing consumer preferences with increasing affluence has a small negative effect on global cumulative GHG emissions. The differences are more profound on both a regional and a product level. For the demand model scenario, we find the largest decrease in GHG emissions for the BRICS and other developing countries, while emissions in North America and the EU remain unchanged. Decreased spending and resulting emissions on food are cancelled out by increased spending and emissions on transportation. Despite relatively small global differences between the scenarios, the regional and sectoral wedges indicate that there is a large untapped potential in environmental policies and lifestyle changes that can complement the technological transition towards a low-emitting society.
- ItemRemote Sensing Based Yield Estimation of Rice (Oryza Sativa L.) Using Gradient Boosted Regression in India(Basel : MDPI, 2021) Arumugam, Ponraj; Chemura, Abel; Schauberger, Bernhard; Gornott, ChristophAccurate and spatially explicit yield information is required to ensure farmers’ income and food security at local and national levels. Current approaches based on crop cutting experiments are expensive and usually too late for timely income stabilization measures like crop insurances. We, therefore, utilized a Gradient Boosted Regression (GBR), a machine learning technique, to estimate rice yields at ~500 m spatial resolution for rice-producing areas in India with potential application for near real-time estimates. We used resampled intermediate resolution (~5 km) images of the Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) and observed yields at the district level in India for calibrating GBR models. These GBRs were then used to downscale district yields to 500 m resolution. Downscaled yields were re-aggregated for validation against out-of-sample district yields not used for model training and an additional independent data set of block-level (below district-level) yields. Our downscaled and re-aggregated yields agree well with reported district-level observations from 2003 to 2015 (r = 0.85 & MAE = 0.15 t/ha). The model performance improved further when estimating separate models for different rice cropping densities (up to r = 0.93). An additional out-of-sample validation for the years 2016 and 2017, proved successful with r = 0.84 and r = 0.77, respectively. Simulated yield accuracy was higher in water-limited, rainfed agricultural systems. We conclude that this downscaling approach of rice yield estimation using GBR is feasible across India and may complement current approaches for timely rice yield estimation required by insurance companies and government agencies.