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Исследование ландшафтов всегда было традиционным научным направлением географии. В России подобная направленность исследований остаётся актуальной, несмотря на то, что термины «геоэкология» и «ландшафтная экология» сегодня более распространены в англоязычном научном сообществе. Наш краткий обзор показывает значительное ускорение антропогенных ландшафтных изменений в Европе, Центральной Азии и азиатской части России за последние пять десятилетий. Ландшафтные исследования в антропоцене должны быть направлены на достижение и сохранение устойчивости ландшафта при его высокой производительности, что включает в себя прекращение деградации ландшафтов, развитие культурных и сохранение природных ландшафтов. Чистая вода и чистый воздух, плодородные и здоровые почвы для производства продуктов питания и других экосистемных услуг, а также биологически разнообразная зеленая среда являются атрибутами ландшафтов, обеспечивающих выживание и благополучие населения. Дисциплинарные и междисциплинарные исследования должны генерировать знания, инновации и правила принятия действенных решений. Генерация знаний в глобализованном мире основана на сборе больших массивов данных и моделировании сценариев. Международные длительные полевые опыты и системы агроэкологического мониторинга будут предоставлять данные для экосистемных моделей и систем поддержки принимаемых решений. Landscape research has been a traditional scientific discipline of geography. This is still the case in Russia, whilst the terms geo-ecology and landscape ecology have become established in the English speaking scientific community. Our short review reveals huge and accelerating anthropogenic landscape transformations in Europe, Central Asia and Asian Russia since the end the 1960s. Landscape research in the Anthropocene has to focus on achieving landscape sustainability at high productivity. This includes halting landscape degradation, developing cultural landscapes, and maintaining semi-natural landscapes. Clean water and air, fertile and healthy soils for food and other ecosystem services and a green and bio-diverse environment are attributes of landscapes for the survival and well-being of humans. Research has to generate knowledge, innovations and decision rules by disciplinary, interdisciplinary and trans-disciplinary work. Knowledge generation in a globalized world is based on big data gathering and scenario modelling. International long-term experiments and agri-environmental monitoring systems will deliver data for ecosystem models and decision support systems.

Global fossil fuel reserves are declining due to differential uses, especially for power generation. Everybody can help to do their bit for the environment by using solar energy. Geographically, Bangladesh is a potential zone for harnessing solar energy. In March 2021, the renewable generation capacity in Bangladesh amounted to 722.592 MW, including 67.6% from solar, 31.84% from hydro, and 0.55% from other energy sources, including wind, biogas, and biomass, where 488.662 MW of power originated from over 6 million installed solar power systems. Concurrently, over 42% of rural people still suffer from a lack of electricity, where solar energy can play a vital role. This paper highlights the present status of various forms of solar energy progress in Bangladesh, such as solar parks, solar rooftops, solar irrigation, solar charging stations, solar home systems, solar-powered telecoms, solar street lights, and solar drinking water, which can be viable alternative sources of energy. This review will help decision-makers and investors realize Bangladesh’s up-to-date solar energy scenario and plan better for the development of a sustainable society.

Abstract The Renewable energy power generation capacity has been rapidly increasing in China recently. Meanwhile, the contradiction between power supply and demand is becoming increasingly more prominent due to the intermittence of renewable energies. On the other hand, on the mitigation of carbon dioxide (CO2) emissions in China needs immediate attention. Power-to-Gas (PtG), a chemical energy storage technology, can convert surplus electricity into combustible gases. Subsurface energy storage can meet the requirements of long term storage with its large capacity. This paper provides a discussion of the entire PtG energy storage technology process and the current research progress. Based on the comparative study of different geological storage schemes for synthetic methane, their respective research progress and limitations are noted. In addition, a full investigation of the distribution and implementation of global PtG and CO2 capture and storage (CCS) demonstration projects is performed. Subsequently, the opportunities and challenges of the development of this technology in China are discussed based on techno-economic and ecological effects analysis. While PtG is expected to be a revolutionary technology that will replace traditional power systems, the main issues of site selection, energy efficiency and the economy still need to be adequately addressed. Additionally, based on the comprehensive discussion of the results of the analysis, power-to-gas and subsurface energy storage implementation strategies, as well as outlook in China are presented.

The failure to fully internalize externalities from production and consumption, including on future generations, is supposed to be at the core of the perceived failure to ensure (ecological) sustainability within the realm of antitrust enforcement. While some argue that sustainability should constitute a goal in itself that must be balanced against economic efficiency in antitrust analysis, we instead want to explore whether and how sustainability can be incorporated into a consumer welfare approach. We make a key distinction between what we term an individualistic and a collective consumer welfare analysis. Within an individualistic consumer welfare analysis, consumers’ willingness-to-pay is measured ceteris paribus, holding other consumers’ choices fixed. In a collective consumer welfare analysis, consumers may express their willingness-to-pay also for the choices of others and, thereby, also for the reduction of externalities on themselves. Borrowing from environmental and resource economics, we also discuss more indirect ways of incorporating such externalities. And we critically assess the possibility of ‘laundering’ consumers’ sustainability preferences in the light of supposed biases and cognitive limitations. Finally, we relate our analysis to the Draft Horizontal Guidelines of the European Commission, published in March 2022. antitrust, consumer welfare, conjoint analysis, contingent valuation, Draft EU Horizontal Guidelines, environmental economics, externalities, laundering preferences, sustainability, willingness-to-pay

Carbon capture and utilization (CCU) is a field of key emerging technologies. CCU can support the economy to decrease the dependency on fossil carbon raw materials, to stabilize electricity grids and markets with respect to a growing share of fluctuating renewable energy. Furthermore, it can contribute to mitigate anthropogenic CO2 emissions. The German Federal Ministry of Education and Research has provided substantial financial support for research and development projects, stimulating research, development, and innovations in the field of CO2 utilization. This review provides an overview over the most relevant funding measures in this field. Examples of successful projects demonstrate that CCU technologies are already economically viable or technologically ready for industrial application. CCU technologies as elements of a future "green economy" can contribute to reach the ambitious German sustainability targets with regard to climate protection as well as raw material productivity.

Cogeneration of heat and electricity is an important pillar of energy and climate policy. To plan the production and distribution system of combined heat and power (CHP) systems for residential heating, suitable methods for decision support are needed. For a comprehensive feasibility analysis, the integration of the location and capacity planning of the power plants, the choice of customers, and the network planning of the heating network into one optimization model are necessary. Thus, we develop an optimization model for electricity generation and heat supply. This mixed integer linear program (MILP) is based on graph theory for network flow problems. We apply the network location model for the optimization of district heating systems in the City of Osorno in Chile, which exhibits the “checkerboard layout” typically found in many South American cities. The network location model can support the strategic planning of investments in renewable energy projects because it permits the analysis of changing energy prices, calculation of break-even prices for heat and electricity, and estimation of greenhouse gas emission savings.

Sustainable development goals (SDGs) adopted in 2015 are geared toward sustainable development through various pathways, one being reducing inequality as covered in SDG 10. Inequalities are a threat to health and wellbeing of populations and a planet Earth in which we live. This rapid review aims to identify key issues that are likely to exacerbate inequalities around the six SDGs directly related to One Health, which are SDG 3, 6, 11, 13, 14 and 15, and suggest some actions that may help to address them using inclusive governance taking into account the coronavirus disease of 2019 (COVID-19) pandemic. Informed by the literature on SDGs and using the “inclusive development concept” by Gupta and Vegelin, literature search was done in Google Scholar, PubMed Central, as well as, searching of references in the relevant articles identified using search terms from the six SDGs that are directly related to One Health. In the context of the SDGs, in order to achieve One Health through inclusive governance, and tackle inequalities, the following needs to be considered and addressed: increasing number of armed conflicts; ongoing COVID-19 pandemic; ensuring availability of water and sanitation facilities; improving city and urban areas planning to cope with climate change; improving governance arrangements for addressing climate change factoring gender and human rights; multisectoral planning for conservation of oceans, seas, and marine resources; balancing trade regulation of wildlife trade with conservation efforts; need for a research collaborative involving experts from environmental sciences, wildlife, agriculture and human health to study and develop scientific evidence on contribution of changes in land use practices to occurrence of zoonotic diseases; and need of a legislation for promoting animal welfare to protect public health. Also, inclusion of people with disabilities in the use of digital technologies is critical.

In recent years, prices for photovoltaics have fallen steadily and the demand for sustainable energy has increased. Consequentially, the assessment of roof surfaces in terms of their suitability for PV (Photovoltaic) installations has continuously gained in importance. Several types of assessment approaches have been established, ranging from sampling to complete census or aerial image analysis methodologies. Assessments of rooftop photovoltaic potential are multi-stage processes. The sub-task of examining the photovoltaic potential of individual rooftops is crucial for exact case study results. However, this step is often time-consuming and requires lots of computational effort especially when some form of intelligent classification algorithm needs to be trained. This often leads to the use of sampled rooftop utilization factors when investigating large-scale areas of interest, as data-driven approaches usually are not well-scalable. In this paper, a novel neighbourhood-based filtering approach is introduced that can analyse large amounts of irradiation data in a vectorised manner. It is tested in an application to the city of Giessen, Germany, and its surrounding area. The results show that it outperforms state-of-the-art image filtering techniques. The algorithm is able to process high-resolution data covering 1 km2 within roughly 2.5 s. It successfully classifies rooftop segments which are feasible for PV installations while omitting small, obstructed or insufficiently exposed segments. Apart from minor shortcomings, the approach presented in this work is capable of generating per-rooftop PV potential assessments at low computational cost and is well scalable to large scale areas.