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This paper gives an overview of the development of Fair Trade in six European countries: Austria, France, Germany, the Netherlands, Switzerland and the United Kingdom. After the description of the food retail industry and its market structures in these countries, the main European Fair Trade organizations are analyzed regarding their role within the Fair Trade system. The following part deals with the development of Fair Trade sales in general and with respect to the products coffee, tea, bananas, fruit juice and sugar. An overview of the main activities of national Fair Trade organizations, e.g. public relation activities, completes the analysis. This study shows the enormous upswing of Fair Trade during the last decade and the reasons for this development. Nevertheless, it comes to the conclusion that Fair Trade is still far away from being an essential part of the food retail industry in Europe.
Adoption of Modern Maize Varieties in India: Insights Based on Expert Elicitation Methodology
(2018)
The clear-sky radiative effect of aerosol-radiation interactions is of relevance for our understanding of the climate system. The influence of aerosol on the surface energy budget is of high interest for the renewable energy sector. In this study, the radiative effect is investigated in particular with respect to seasonal and regional variations for the region of Germany and the year 2015 at the surface and top of atmosphere using two complementary approaches.
First, an ensemble of clear-sky models which explicitly consider aerosols is utilized to retrieve the aerosol optical depth and the surface direct radiative effect of aerosols by means of a clear sky fitting technique. For this, short-wave broadband irradiance measurements in the absence of clouds are used as a basis. A clear sky detection algorithm is used to identify cloud free observations. Considered are measurements of the shortwave broadband global and diffuse horizontal irradiance with shaded and unshaded pyranometers at 25 stations across Germany within the observational network of the German Weather Service (DWD). Clear sky models used are MMAC, MRMv6.1, METSTAT, ESRA, Heliosat-1, CEM and the simplified Solis model. The definition of aerosol and atmospheric characteristics of the models are examined in detail for their suitability for this approach.
Second, the radiative effect is estimated using explicit radiative transfer simulations with inputs on the meteorological state of the atmosphere, trace-gases and aerosol from CAMS reanalysis. The aerosol optical properties (aerosol optical depth, Ångström exponent, single scattering albedo and assymetrie parameter) are first evaluated with AERONET direct sun and inversion products. The largest inconsistency is found for the aerosol absorption, which is overestimated by about 0.03 or about 30 % by the CAMS reanalysis. Compared to the DWD observational network, the simulated global, direct and diffuse irradiances show reasonable agreement within the measurement uncertainty. The radiative kernel method is used to estimate the resulting uncertainty and bias of the simulated direct radiative effect. The uncertainty is estimated to −1.5 ± 7.7 and 0.6 ± 3.5 W m−2 at the surface and top of atmosphere, respectively, while the annual-mean biases at the surface, top of atmosphere and total atmosphere are −10.6, −6.5 and 4.1 W m−2, respectively.
The retrieval of the aerosol radiative effect with the clear sky models shows a high level of agreement with the radiative transfer simulations, with an RMSE of 5.8 W m−2 and a correlation of 0.75. The annual mean of the REari at the surface for the 25 DWD stations shows a value of −12.8 ± 5 W m−2 as average over the clear sky models, compared to −11 W m−2 from the radiative transfer simulations. Since all models assume a fixed aerosol characterisation, the annual cycle of the aerosol radiation effect cannot be reproduced. Out of this set of clear sky models, the largest level of agreement is shown by the ESRA and MRMv6.1 models.
The clear-sky radiative effect of aerosol–radiation interactions is of relevance for our understanding of the climate system. The influence of aerosol on the surface energy budget is of high interest for the renewable energy sector. In this study, the radiative effect is investigated in particular with respect to seasonal and regional variations for the region of Germany and the year 2015 at the surface and top of atmosphere using two complementary approaches.
First, an ensemble of clear-sky models which explicitly consider aerosols is utilized to retrieve the aerosol optical depth and the surface direct radiative effect of aerosols by means of a clear-sky fitting technique. For this, short-wave broadband irradiance measurements in the absence of clouds are used as a basis. A clear-sky detection algorithm is used to identify cloud-free observations. Considered are measurements of the short-wave broadband global and diffuse horizontal irradiance with shaded and unshaded pyranometers at 25 stations across Germany within the observational network of the German Weather Service (DWD). The clear-sky models used are the Modified MAC model (MMAC), the Meteorological Radiation Model (MRM) v6.1, the Meteorological–Statistical solar radiation model (METSTAT), the European Solar Radiation Atlas (ESRA), Heliosat-1, the Center for Environment and Man solar radiation model (CEM), and the simplified Solis model. The definition of aerosol and atmospheric characteristics of the models are examined in detail for their suitability for this approach.
Second, the radiative effect is estimated using explicit radiative transfer simulations with inputs on the meteorological state of the atmosphere, trace gases and aerosol from the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis. The aerosol optical properties (aerosol optical depth, Ångström exponent, single scattering albedo and asymmetry parameter) are first evaluated with AERONET direct sun and inversion products. The largest inconsistency is found for the aerosol absorption, which is overestimated by about 0.03 or about 30 % by the CAMS reanalysis. Compared to the DWD observational network, the simulated global, direct and diffuse irradiances show reasonable agreement within the measurement uncertainty. The radiative kernel method is used to estimate the resulting uncertainty and bias of the simulated direct radiative effect. The uncertainty is estimated to −1.5 ± 7.7 and 0.6 ± 3.5 W m−2 at the surface and top of atmosphere, respectively, while the annual-mean biases at the surface, top of atmosphere and total atmosphere are −10.6, −6.5 and 4.1 W m−2, respectively.
The retrieval of the aerosol radiative effect with the clear-sky models shows a high level of agreement with the radiative transfer simulations, with an RMSE of 5.8 W m−2 and a correlation of 0.75. The annual mean of the REari at the surface for the 25 DWD stations shows a value of −12.8 ± 5 W m−2 as the average over the clear-sky models, compared to −11 W m−2 from the radiative transfer simulations. Since all models assume a fixed aerosol characterization, the annual cycle of the aerosol radiation effect cannot be reproduced. Out of this set of clear-sky models, the largest level of agreement is shown by the ESRA and MRM v6.1 models.
Recent findings in South Africa have once again underlined the fact that the oldest people in the world obviously came from Africa. Thus, historically, this continent has a very special significance. However, its history in more recent times, especially from the mid-19th century onwards, was strongly influenced by colonisation by European states. Many deep wounds from that time still have an impact on society as a whole today. However, the continent is currently also confronted with a greater number of challenges of a different nature.
On the one hand, Africa is trying to strengthen internal cohesion by means of a number of regional organisations and the African Union as a globally active institution; on the other hand, the continent has been marked by political and military conflicts between neighbouring states over the past decades until the recent present. In addition, there are regular internal social upheavals in individual countries due to violent or manipulated political change.
Yet the continent could well be on a good development path, since it has a large number of important raw materials - also in comparison to other continents. However, the individual African states - and especially their citizens - often do not benefit from this to an adequate extent. This results in a social imbalance in large parts of the continent (data collection until the end of June 2023), which leads to considerable internal tensions. To make matters worse, Africa is the continent most affected by climate change.
A closer look at the partly very different economic, political and social situations of the large continent leads to an overall predominantly critical assessment of Africa's further development, which is explained in more detail in the final chapter with regard to the foreseeable consequences for the continent.
Current global challenges such as climate change, lack of resources, desertification, land degradation as well as loss of biodiversity can ultimately be due to human actions. Reasons are excessive production and consumption of goods and services, along with using and consuming natural resources, causing emissions and waste products. Demand in the form of consumption and supply in the form of production are closely intertwined.
The implementation of the Sustainable Development Goals (SDGs) and the conservation and protection of nature are among the greatest challenges facing urban regions. There are few approaches so far that link the SDGs to natural diversity and related ecosystem services at the local level and track them in terms of increasing sustainable development at the local level. We want to close this gap by developing a set of indicators that capture ecosystem services in the sense of the SDGs and which are based on data that are freely available throughout Germany and Europe. Based on 10 SDGs and 35 SDG indicators, we are developing an ecosystem service and biodiversity-related indicator set for the evaluation of sustainable development in urban areas. We further show that it is possible to close many of the data gaps between SDGs and locally collected data mentioned in the literature and to translate the universal SDGs to the local level. Our example develops this set of indicators for the Bonn/Rhein-Sieg metropolitan area in North Rhine-Westphalia, Germany, which comprises both rural and densely populated settlements. This set of indicators can also help improve communication and plan sustainable development by increasing transparency in local sustainability, implementing a visible sustainability monitoring system, and strengthening the collaboration between local stakeholders.
The aim of this paper is to assess the objectives of farmers’ challenges in enhancing biodiversity. The so-called “trilemma” (WBGU 2021) of land use stems from the multiple demands made on land for the benefit of mitigating climate change, securing food and maintaining biodiversity. The agricultural sector is accused of maladministration: it is blamed for causing soil contamination, animal cruelty, bee mortality and climate change. That is why farmers are seen as key actors at all levels. They are, however, also key players when it comes to overcoming the problems of the future. Their supportive role is urgently needed, but farmers find themselves caught between a “rock” and a ”hard place”. Consumers are calling for sustainable, environmentally friendly production and inexpensive food products that do not contain pesticide residues, demanding enough food for all. Farmers are restricted by the wants and needs of consumers who are influenced by interest groups and are exposed to direct and indirect influencing factors and their interdependencies. They are also tasked with balancing the scrutiny of the critical public on the one hand, and the control exercised by eager authorities on the other.
As part of the DINA (Diversity of Insects in Nature protected Areas) project, a trans- and interdisciplinary research study, we collected and surveyed the data of farmers who are farming within or close to the 21 selected nature protected areas included in the DINA project. Data was collected as part of a mixed method approach using a semi-structured questionnaire. The methodological and strategic approach and interdependencies of issues demonstrate the complexity of today’s problems. To investigate this, we first used the data collection method using questionnaires with closed and open questions. The conflicts and obstacles farmers face were evaluated, and the results show farmers’ willingness and the importance of appreciation shown to farmers for implementation of biodiversity measures. The paper proposes some follow-up activities (quantitative study) to verify the objectives. The results will later lead to recommendations for policymakers and farmers in all German nature protected areas.
Hydrogen is a versatile energy carrier. When produced with renewable energy by water splitting, it is a carbon neutral alternative to fossil fuels. The industrialization process of this technology is currently dominated by electrolyzers powered by solar or wind energy. For small scale applications, however, more integrated device designs for water splitting using solar energy might optimize hydrogen production due to lower balance of system costs and a smarter thermal management. Such devices offer the opportunity to thermally couple the solar cell and the electrochemical compartment. In this way, heat losses in the absorber can be turned into an efficiency boost for the device via simultaneously enhancing the catalytic performance of the water splitting reactions, cooling the absorber, and decreasing the ohmic losses.[1,2] However,integrated devices (sometimes also referred to as “artificial leaves”), currently suffer from a lower technology readiness level (TRL) than the completely decoupled approach.
Large sections of the German society are able to buy and consume meat on a daily basis due to progress in the agri-food sector. However, the way meat is produced, traded and consumed increasingly has become an issue that is controversially discussed by the media, non-governmental organisations (NGOs), lobbyists, the industry itself and consumers – often with a negative connotation. The meat industry reacts to this. By creating information campaigns and animal welfare initiatives it aims to stress that it is going to take its corporate social responsibilities (CSR) for consumers and animal welfare seriously. But, the industry’s actions are still criticised as being not sufficient to improve animal welfare levels significantly. Much of this criticism can be observed in online news portals, where articles about the issue get published and commented by readers. This makes online portals a valuable source for information that is to be tapped in this study. It aims to better understand the multifaceted discussions concerning animal welfare initiatives in online portals. By applying qualitative content analysis and web mining techniques to a sample of documents taken from three major German news sites it can be shown that online discussions refer to various aspects of sustainability and corporate social responsibility. Findings also indicate that the discussions are framed by financial aspects.
Ghana suffers from frequent power outages, which can be compensated by off-grid energy solutions. Photovoltaic-hybrid systems become more and more important for rural electrification due to their potential to offer a clean and cost-effective energy supply. However, uncertainties related to the prediction of electrical loads and solar irradiance result in inefficient system control and can lead to an unstable electricity supply, which is vital for the high reliability required for applications within the health sector. Model predictive control (MPC) algorithms present a viable option to tackle those uncertainties compared to rule-based methods, but strongly rely on the quality of the forecasts. This study tests and evaluates (a) a seasonal autoregressive integrated moving average (SARIMA) algorithm, (b) an incremental linear regression (ILR) algorithm, (c) a long short-term memory (LSTM) model, and (d) a customized statistical approach for electrical load forecasting on real load data of a Ghanaian health facility, considering initially limited knowledge of load and pattern changes through the implementation of incremental learning. The correlation of the electrical load with exogenous variables was determined to map out possible enhancements within the algorithms. Results show that all algorithms show high accuracies with a median normalized root mean square error (nRMSE) <0.1 and differing robustness towards load-shifting events, gradients, and noise. While the SARIMA algorithm and the linear regression model show extreme error outliers of nRMSE >1, methods via the LSTM model and the customized statistical approaches perform better with a median nRMSE of 0.061 and stable error distribution with a maximum nRMSE of <0.255. The conclusion of this study is a favoring towards the LSTM model and the statistical approach, with regard to MPC applications within photovoltaic-hybrid system solutions in the Ghanaian health sector.
In the research project "MetPVNet", both, the forecast-based operation management in distribution grids and as well as the forecasts of the feed-in of PV-power from decentralized plants could be improved on the basis of satellite data and numerical weather forecasts. Based on a detailed network analyses for a real medium-voltage grid area, it was shown that both – the integration of forecast data based on satellite and weather data and the improvement of subsequent day forecasts based on numerical weather models – have a significant added value for forecast-based congestion management or redispatch and reactive power management in the distribution grid. Furthermore, forecast improvements for the forecast model of the German Weather Service were achieved by assimilating visible satellite imagery, and cloud and radiation products from satellites were improved, thus improving the database for short-term forecasting as well as for assimilation. In addition, several methods have been developed that will enable forecast improvement in the future, especially for weather situations with high cloud induced variability and high forecast errors. This article summarizes the most important project results.
Diversity of Insects in Nature protected Areas (DINA): an interdisciplinary German research project
(2021)
Insect declines and biodiversity loss have attracted much attention in recent years, but lack of comprehensive data, conflicting interests among stakeholders and insufficient policy guidance hinder progress in preserving biodiversity. The project DINA (Diversity of Insects in Nature protected Areas) investigates insect communities in 21 nature reserves in Germany. All selected conservation sites border arable land, with agricultural practices assumed to influence insect populations. We taught citizen scientists how to manage Malaise traps for insect collection, and subsequently used a DNA metabarcoding approach for species identification. Vegetation surveys, plant metabarcoding as well as geospatial and ecotoxicological analyses will help to unravel contributing factors for the deterioration of insect communities. As a pioneering research project in this field, DINA includes a transdisciplinary dialogue involving relevant stakeholders such as local authorities, policymakers, and farmers, which aims at a shared understanding of conservation goals and action pathways. Stakeholder engagement combined with scientific results will support the development of sound policy recommendations to improve legal frameworks, landscape planning, land use, and conservation strategies. With this transdisciplinary approach, we aim to provide the background knowledge to implement policy strategies that will halt further decline of insects in German protected areas.
The temperature of photovoltaic modules is modelled as a dynamic function of ambient temperature, shortwave and longwave irradiance and wind speed, in order to allow for a more accurate characterisation of their efficiency. A simple dynamic thermal model is developed by extending an existing parametric steady-state model using an exponential smoothing kernel to include the effect of the heat capacity of the system. The four parameters of the model are fitted to measured data from three photovoltaic systems in the Allgäu region in Germany using non-linear optimisation. The dynamic model reduces the root-mean-square error between measured and modelled module temperature to 1.58 K on average, compared to 3.03 K for the steady-state model, whereas the maximum instantaneous error is reduced from 20.02 to 6.58 K.
Education for Sustainable Development (ESD, SDG 4) and human well-being (SDG 3) are among the central subjects of the Sustainable Development Goals (SDGs). In this article, based on the Questionnaire for Eudaimonic Well-Being (QEWB), we investigate to what extent (a) there is a connection between EWB and practical commitment to the SDGs and whether (b) there is a deficit in EWB among young people in general. We also want to use the article to draw attention to the need for further research on the links between human well-being and commitment for sustainable development. A total of 114 students between the ages of 18 and 34, who are either engaged in (extra)curricular activities of sustainable development (28 students) or not (86 students), completed the QEWB. The students were interviewed twice: once regarding their current and their aspired EWB. Our results show that students who are actively engaged in activities for sustainable development report a higher EWB than non-active students. Furthermore, we show that students generally report deficits in EWB and wish for an improvement in their well-being. This especially applies to aspects of EWB related to self-discovery and the sense of meaning in life. Our study suggests that a practice-oriented ESD in particular can have a positive effect on the quality of life of young students and can support them in working on deficits in EWB.
For several decades, farmers have been mixing rock powders with livestock slurry to reduce its NH3 emissions and increase its nutrient content. However, mixing rock powders with slurry is controversial, and there is currently no scientific evidence for its effects on NH3 and greenhouse gas (GHG) emissions or on changes in its nutrient content due to element release from rock powders. The major aim of this study was therefore to analyse the effects of mixing two commercially established rock powders with cattle slurry on NH3, CO2, N2O and CH4 emissions, and on nutrient release over a course of 46 days. We found that rock powders did not significantly affect CO2 emission rates. NH3 and N2O emission rates did not differ significantly up until the end of the trial, when the emission rates of the rock powder treatments significantly increased for NH3 and significantly decreased for N2O, respectively, which coincided with a reduction of the slurry crust. Cumulative NH3 emissions did not, however, differ significantly between treatments. Unexpected and significant increases in CH4 emission rates occurred for the rock powder treatments. Rock powders increased the macro- and micronutrient content of the slurry. The conflicting results are discussed and future research directions are proposed.
The accurate forecasting of solar radiation plays an important role for predictive control applications for energy systems with a high share of photovoltaic (PV) energy. Especially off-grid microgrid applications using predictive control applications can benefit from forecasts with a high temporal resolution to address sudden fluctuations of PV-power. However, cloud formation processes and movements are subject to ongoing research. For now-casting applications, all-sky-imagers (ASI) are used to offer an appropriate forecasting for aforementioned application. Recent research aims to achieve these forecasts via deep learning approaches, either as an image segmentation task to generate a DNI forecast through a cloud vectoring approach to translate the DNI to a GHI with ground-based measurement (Fabel et al., 2022; Nouri et al., 2021), or as an end-to-end regression task to generate a GHI forecast directly from the images (Paletta et al., 2021; Yang et al., 2021). While end-to-end regression might be the more attractive approach for off-grid scenarios, literature reports increased performance compared to smart-persistence but do not show satisfactory forecasting patterns (Paletta et al., 2021). This work takes a step back and investigates the possibility to translate ASI-images to current GHI to deploy the neural network as a feature extractor. An ImageNet pre-trained deep learning model is used to achieve such translation on an openly available dataset by the University of California San Diego (Pedro et al., 2019). The images and measurements were collected in Folsom, California. Results show that the neural network can successfully translate ASI-images to GHI for a variety of cloud situations without the need of any external variables. Extending the neural network to a forecasting task also shows promising forecasting patterns, which shows that the neural network extracts both temporal and momentarily features within the images to generate GHI forecasts.
Solar energy is one option to serve the rising global energy demand with low environmental Impact [1]. Building an energy system with a considerable share of solar power requires long-term investment and a careful investigation of potential sites. Therefore, understanding the impacts from varying regionally and locally determined meteorological conditions on solar energy production will influence energy yield projections. Clouds are moving on a short term timescale and have a high influence on the available solar radiation, as they absorb, reflect and scatter parts of the incoming light [2]. However, modeling photovoltaic (PV) power yields with a spectral resolution and local cloud information gives new insights on the atmospheric impact on solar energy.
Accurate forecasting of solar irradiance is crucial for the integration of solar energy into the power grid, power system planning, and the operation of solar power plants. The Weather Research and Forecasting (WRF) model, with its solar radiation (WRF-Solar) extension, has been used to forecast solar irradiance in various regions worldwide. However, the application of the WRF-Solar model for global horizontal irradiance (GHI) forecasting in West Africa, specifically in Ghana, has not been studied. This study aims to evaluate the performance of the WRF-Solar model for GHI forecasting in Ghana, focusing on 3 health centers (Kologo, Kumasi and Akwatia) for the year 2021. We applied a two one-way nested domain (D1=15 km and D2=3 km) to investigate the ability of the WRF solar model to forecast GHI up to 72 hours in advance under different atmospheric conditions. The initial and lateral boundary conditions were taken from the ECMWF operational forecasts. In addition, the optical aerosol depth (AOD) data at 550 nm from the Copernicus Atmosphere Monitoring Service (CAMS) were considered. The study uses statistical metrics such as mean bias error (MBE), root mean square error (RMSE), to evaluate the performance of the WRF-Solar model with the observational data obtained from automatic weather stations in the three health centers in Ghana. The results of this study will contribute to the understanding of the capabilities and limitations of the WRF-Solar model for forecasting GHI in West Africa, particularly in Ghana, and provide valuable information for stakeholders involved in solar energy generation and grid integration towards optimized management of in the region.
Accurate global horizontal irradiance (GHI) forecasting is critical for integrating solar energy into the power grid and operating solar power plants. The Weather Research and Forecasting model with its solar radiation extension (WRF-Solar) has been used to forecast solar irradiance in different regions around the world. However, the application of the WRF-Solar model to the prediction of GHI in West Africa, particularly Ghana, has not yet been investigated. The aim of this study is to evaluate the performance of the WRF-Solar model for predicting GHI in Ghana, focusing on three automatic weather stations (Akwatia, Kumasi and Kologo) for the year 2021. We used two one-way nested domains (D1 = 15 km and D2 = 3 km) to investigate the ability of the fully coupled WRF-Solar model to forecast GHI up to 72-hour ahead under different atmospheric conditions. The initial and lateral boundary conditions were taken from the ECMWF high-resolution operational forecasts. Our findings reveal that the WRF-Solar model performs better under clear skies than cloudy skies. Under clear skies, Kologo performed best in predicting 72-hour GHI, with a first day nRMSE of 9.62 %. However, forecasting GHI under cloudy skies at all three sites had significant uncertainties. Additionally, WRF-Solar model is able to reproduce the observed GHI diurnal cycle under high AOD conditions in most of the selected days. This study enhances the understanding of the WRF-Solar model’s capabilities and limitations for GHI forecasting in West Africa, particularly in Ghana. The findings provide valuable information for stakeholders involved in solar energy generation and grid integration towards optimized management in the region.
Background:
Access to electricity is one of the enabling factors for healthcare service provision. From the sustainable development perspective, an essential requirement for improving health and caring for our environment is to assure that health facilities have sufficient and reliable access to the supply of clean and sustainable energy. The objective of this work is to investigate the users’ perceptions of electricity needs and electricity sources and the way those influence different attributes and their relevance for the diffusion of renewable electricity systems in healthcare facilities.
Methods:
To identify preferences and choices, Stated Choice modelling was applied as the use of solar PV systems in health facilities is not widespread in Ghana. This method allows to present the respondents with hypothetical options, which have attributes close to the real world. Four attributes were considered, namely electricity system configuration, initial investment cost, monthly costs, and improvements to the reliability of the electricity supply.
Results:
The largest share of the 200 health facilities interviewed reported services provision as outpatient treatment, provision of maternity services and family planning, which are relatively low electricity-intensive services. However, there was a general perception that increased reliability on the electricity supply can improve the health service provision and operation of the facilities. Moreover, despite that preferences towards the solar systems, the initial investment costs of the solar systems is still perceived as preventing the adoption of this technology
Conclusion:
From this study we can conclude that health facilities in Ghana rely greatly on the national supply which has issues with reliability, compromising the delivery of healthcare services. However, the adoption of alternative electricity technologies based on renewable sources is not likely to occur at the facility level without the engagement of other actors that can help bridging the barriers for adoption, as initial investment costs.
This paper aims to assess farmers’ challenges in enhancing biodiversity. The so-called “trilemma” (WBGU 2021) of land use stems from the multiple demands made on land for the benefit of mitigating climate change, securing food, and maintaining biodiversity. Agriculture is accused of maladministration, causing soil contamination, animal cruelty, bee mortality, and climate change. However, farmers play a key role in overcoming upcoming sustainability challenges. While their supportive role is urgently needed, farmers find themselves caught between a “rock” and a ”hard place”. Consumers call for sustainable production and affordable food products without pesticide residues, demanding enough for all. Farmers are restricted by the wants and needs of consumers who are influenced by interest groups and exposed to interdependent direct and indirect influencing factors. They need to balance the scrutiny of the critical public as well as the regulatory control. In this paper, we collected and surveyed the data of farmers within or close to the 21 selected nature protected areas of the DINA (Diversity of Insects in Nature protected Areas) Project, using a mixed methods approach with a semi-structured questionnaire considering issues’ interdependencies and the complexity of today´s problems. The conflicts and obstacles faced by farmers were assessed. The results reflect the farmers’ willingness and the importance of receiving appreciation for implementing biodiversity measures. These results, complemented by a following quantitative study, are the basis for recommendations for policymakers and farmers in all German nature protected areas.
Food losses occur for many reasons at all stages of supply chains for fruits, vegetables and potatoes. They cause immense economic, environmental and social costs – not only in developing countries but also in developed countries. According to the European Commission, about 90 million tonnes of food are wasted annually in Europe alone. However, particularly for the early stages of supply chains for fruits, vegetables and potatoes there is still a lack of reliable data. Thus, one objective of this study is to contribute to the quantification of food losses between field and retail, where the main focus is set on potatoes, apples, carrots, strawberries and asparagus. Furthermore, neither reasons why products are removed from the supply chains nor their alternative uses are fully examined yet. This is why, the study takes a look on those issues, too. Results are based on data from an online survey among producers of fruits, vegetables and potatoes in North-Rhine Westphalia, Germany and on interviews with producers and other supply chain experts. Findings suggest that the products’ size and form, their storage capabilities and food safety issues have big impacts on food losses. Despite a small sample size, these findings are in line with recent studies.
Green infrastructure improves environmental health in cities, benefits human health, and provides habitat for wildlife. Increasing urbanization has demanded the expansion of urban areas and transformation of existing cities. The adoption of compact design in urban planning is a recommended strategy to minimize environmental impacts; however, it may undermine green infrastructure networks within cities as it sets a battleground for urban space. Under this scenario, multifunctionality of green spaces is highly desirable but reconciling human needs and biodiversity conservation in a limited space is still a challenge. Through a systematic review, we first compiled urban green space's characteristics that affect mental health and urban wildlife support, and then identified potential synergies and trade-offs between these dimensions. A framework based on the One Health approach is proposed, synthesizing the interlinkages between green space quality, mental health, and wildlife support; providing a new holistic perspective on the topic. Looking at the human-wildlife-environment relationships simultaneously may contribute to practical guidance on more effective green space design and management that benefit all dimensions.
Pursuant to Sustainable Development Goal (SDG) 15 of the 2030 Agenda for Sustainable Development of the United Nations, one pivotal target is to halt biodiversity loss. This paper’s objective is to analyze why and how German farmers hesitate to implement more than the prescriptive measures with regard to cross compliance and direct payments under the European Common Agricultural Policy (CAP) and what their aspirations are for possible incentives to bring biodiversity into focus. By applying a mixed methods approach, we investigate the experience of individual farmers by means of a qualitative approach followed by a quantitative study. This analysis sheds light on how farmers perceive indirect influencing factors and how these factors play a non-negligible role in farmers´ commitment to biodiversity. Economy, policy and society are intertwined and need to be considered from a multi-faceted perspective. In addition, an in-depth analysis is conducted based on online focus group discussions to determine whether farmers accept financial support, focusing on both action- and success-oriented payments. Our results highlight the importance of paying attention to the heterogeneity of farmers, their locations and, consequently, farmers’ different views on indirect drivers influencing agricultural processes, showing the complexity of the problem. Although farmers’ expectations can be met with financial allocations, other aspects must also be taken into account.
Reliable and regional differentiated power forecasts are required to guarantee an efficient and economic energy transition towards renewable energies. Amongst other renewable energy technologies, e.g. wind mills, photovoltaic systems are an essential component of this transition being cost-efficient and simply to install. Reliable power forecasts are however required for a grid integration of photovoltaic systems, which among other data requires high-resolution spatio-temporal global irradiance data. Hence the generation of robust reviewed global irradiance data is an essential contribution for the energy transition.
Reliable and regional differentiated power forecasts are required to guarantee an efficient and economic energy transition towards renewable energies. Amongst other renewable energy technologies, e.g. wind mills, photovoltaic (PV) systems are an essential component of this transition being cost-efficient and simply to install. Reliable power forecasts are however required for a grid integration of photovoltaic systems, which among other data requires high-resolution spatio-temporal global irradiance data.
Estimates of global horizontal irradiance (GHI) from reanalysis and satellite-based data are the most important information for the design and monitoring of PV systems in Africa, but their quality is unknown due to the lack of in situ measurements. In this study, we evaluate the performance of hourly GHI from state-of-the-art reanalysis and satellite-based products (ERA5, CAMS, MERRA-2, and SARAH-2) with 37 quality-controlled in situ measurements from novel meteorological networks established in Burkina Faso and Ghana under different weather conditions for the year 2020. The effects of clouds and aerosols are also considered in the analysis by using common performance measures for the main quality attributes and a new overall performance value for the joint assessment. The results show that satellite data performs better than reanalysis data under different atmospheric conditions. Nevertheless, both data sources exhibit significant bias of more than 150 W/m2 in terms of RMSE under cloudy skies compared to clear skies. The new measure of overall performance clearly shows that the hourly GHI derived from CAMS and SARAH-2 could serve as viable alternative data for assessing solar energy in the different climatic zones of West Africa.
In January 2015, German retail and industry jointly started a sector-wide initiative ("Initiative Tierwohl" - ITW) to improve animal welfare standards. The principle of the ITW is communicated mostly via the websites of ITW and its participating companies. However, uncertainty remained whether or not these websites provide the necessary information consumers need on the ITW products. Based on Schwartz's basic human values, different types of consumers were identified by a cluster analysis (ward-method, k-means). The results showed that depending on expressed meta‐values (Self-Transcendence/Openness to Change Self-Enhancement or Conservation), respondents had different specific information sources and needs. Online sources were rarely mentioned, the majority of consumers referred to brochures, flyers and interpersonal contacts.
Urban food systems consist of many stakeholders with different perspectives, different interests and different governance tools. This study aimed at developing potential future scenarios for the food system of Cologne by analysing the system with a Delphi approach. In our research-design, the suitability of the Delphi-method was evaluated not only as a tool for future modelling and scenario design, but also as a communication tool among the group of participants on a multi-stakeholder-platform. As a case study, the Food Policy Council of Cologne, Germany was used. Cologne can be seen as a forerunner among German cities in the development of a new urban food policy. Some of the successful steps to re-envisioning food as an urban system include joining the Milan Urban Food Policy Pact, the decision of the City Council to become an edible city and the establishment of a Food Policy Council. For the study it was important to capture participants’ visions of a common goal regarding the governance of the urban food system and also to identify mental ‘silos’. It was obvious that the municipality of Cologne together with the Food Policy Council made great efforts towards participatory processes to build a vision for a sustainable and regional food supply. However, many stakeholder-groups in the process still work exclusively among themselves and do not actively practice the confrontation with the viewpoints of other relevant groups. This supports the maintenance of ‘silos’ and leaves little room for face-to-face discussions. Therefore, the primary aim of this study is to explore key components of food provisioning in the future for Cologne while confronting all stakeholders (municipal administration and politicians, farmers and food activists) with the perspectives of all group members. We used a multi-stakeholder Delphi approach with 19 panellists to find out essential components of the municipal regional food provisioning system in Cologne. Unique in this Delphi study is the bringing together of municipal administration, regional urban farmers and food activists. The research is still on-going, but preliminary results show that more communication among all relevant actors, especially horizontally among different city departments, in the urban food system is needed.
West Africa has a great potential for the application of solar energy systems, as it combines high levels of solar irradiance with a lack of energy production. Southern West Africa is a region with a very high aerosol load. Urbanization, uncontrolled fires, traffic as well as power plants and oil rigs lead to increasing anthropogenic emissions. The naturally circulating north winds bring mineral dust from the Sahel and Sahara and monsoons - sea salt and other oceanic compounds from the south. The EU-funded Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa (DACCIWA) project (2014–2018), dlivered the most complete dataset of the atmosphere over the region to date. In our study, we use in-situ measured optical properties of aerosols from the airborne campaign over the Gulf of Guinea and inland, and from ground measurements in coastal cities.
Solar energy is one option to serve the rising global energy demand with low environmental impact. Building an energy system with a considerable share of solar power requires long-term investment and a careful investigation of potential sites. Therefore, understanding the impacts from varying regionally and locally determined meteorological conditions on solar energy production will influence energy yield projections.
Impact of atmospheric aerosols on photovoltaic energy production - Scenario for the Sahel zone
(2017)
Photovoltaic (PV) energy is one option to serve the rising global energy need with low environmental impact. PV is of particular interest for local energy solutions in developing countries prone to high solar insolation. In order to assess the PV potential of prospective sites, combining knowledge of the atmospheric state modulating solar radiation and the PV performance is necessary. The present study discusses the PV power as function of atmospheric aerosols in the Sahel zone for clear-sky-days. Daily yields for a polycrystalline silicon PV module are reduced by up to 48 % depending on the climatologically-relevant aerosol abundances.
Solar energy plants are one of the key options to serve the rising global energy need with low environmental impact. Aerosols reduce global solar radiation due to absorption and scattering and therewith solar energy yields. Depending on the aerosol composition and size distribution they reduce the direct component of the solar radiation and modify the direction of the diffuse component compared to standard atmospheric conditions without aerosols.
Atmospheric aerosols affect the power production of solar energy systems. Their impact depends on both the atmospheric conditions and the solar technology employed. By being a region with a lack in power production and prone to high solar insolation, West Africa shows high potential for the application of solar power systems. However, dust outbreaks, containing high aerosol loads, occur especially in the Sahel, located between the Saharan desert in the north and the Sudanian Savanna in the south. They might affect the whole region for several days with significant effects on power generation. This study investigates the impact of atmospheric aerosols on solar energy production for the example year 2006 making use of six well instrumented sites in West Africa. Two different solar power technologies, a photovoltaic (PV) and a parabolic through (PT) power plant, are considered. The daily reduction of solar power due to aerosols is determined over mostly clear-sky days in 2006 with a model chain combining radiative transfer and technology specific power generation. For mostly clear days the local daily reduction of PV power (at alternating current) (PVAC) and PT power (PTP) due to the presence of aerosols lies between 13 % and 22 % and between 22 % and 37 %, respectively. In March 2006 a major dust outbreak occurred, which serves as an example to investigate the impact of an aerosol extreme event on solar power. During the dust outbreak, daily reduction of PVAC and PTP of up to 79 % and 100 % occur with a mean reduction of 20 % to 40 % for PVAC and of 32 % to 71 % for PTP during the 12 days of the event.
Due to the policy goals for sustainable energy production, renewable energy plants such as photovoltaics are increasingly in use. The energy production from solar radiation depends strongly on atmospheric conditions. As the weather mostly changes, electrical power generation fluctuates, making technical planning and control of power grids to a complex problem.