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PurposeIn prospective life cycle assessment (pLCA), inventory models represent a future state of a production system and therefore contain assumptions about future developments. Scientific quality should be ensured by using foresight methods for handling these future assumptions during inventory modelling. We present a stepwise approach for integrating future scenario development into inventory modelling for pLCA studies. MethodsA transdisciplinary research method was used to develop the SIMPL approach for scenario-based inventory modelling for pLCA. Our interdisciplinary team of LCA and future scenario experts developed a first draft of the approach. Afterwards, 112 LCA practitioners tested the approach on prospective case studies in group work projects in three courses on pLCA. Lessons learned from application difficulties, misunderstandings and feedback were used to adapt the approach after each course. After the third course, reflection, discussion and in-depth application to case studies were used to solve the remaining problems of the approach. Ongoing courses and this article are intended to bring the approach into a broader application.Results and discussionThe SIMPL approach comprises adaptations and additions to the LCA goal and scope phase necessary for prospective inventory modelling, particularly the prospective definition of scope items in reference to a time horizon. Moreover, three iterative steps for combined inventory modelling and scenario development are incorporated into the inventory phase. Step A covers the identification of relevant inventory parameters and key factors, as well as their interrelations. In step B, future assumptions are made, by either adopting them from existing scenarios or deriving them from the available information, in particular by integrating expert and stakeholder knowledge. Step C addresses the combination of assumptions into consistent scenarios using cross-consistency assessment and distinctness-based selection. Several iterations of steps A–C deliver the final inventory models.ConclusionThe presented approach enables pLCA practitioners to systematically integrate future scenario development into inventory modelling. It helps organize possible future developments of a technology, product or service system, also with regard to future developments in the social, economic and technical environment of the technology. Its application helps to overcome implicit bias and ensures that the resulting assessments are consistent, transparently documented and useful for drawing practically relevant conclusions. The approach is also readily applicable by LCA practitioners and covers all steps of prospective inventory modelling.

Both full-fledged Earth system models (ESMs) and simple climate models (SCMs) have been used to investigate climate change for future representative CO2 concentration pathways under the sixth phase of the Coupled Model Intercomparison Project. Here, we explore to what extent complex and simple models are consistent in their carbon cycle response in concentration-driven simulations. Although ESMs and SCMs exhibit similar compatible fossil fuel CO2 emissions, ESMs systematically estimate a lower ocean carbon uptake than SCMs in the historical period and future scenarios. The ESM and SCM differences are especially large under low-concentration and overshoot scenarios. Furthermore, ESMs and SCMs deviate in their land carbon uptake estimates, but the differences are scenario-dependent. These differences are partly driven by a few model outliers (ESMs and SCMs) and the procedure of observational constraining that is present in the majority of SCMs but not applied in ESMs. The differences in land uptake arise from the difference in the way land-use change (LUC) emissions are calculated and different assumptions on how the carbon cycle feedbacks are defined, possibly reflecting the treatment of nitrogen limitation of biomass growth and historical calibration of SCMs. The differences in ocean uptake, which are especially large in overshoot scenarios, may arise from the faster mixing of carbon from the surface to the deep ocean in SCMs than in ESMs. We also discuss the inconsistencies that arise when converting CO2 emissions from integrated assessment models (IAMs) to CO2 concentrations inputs for ESMs, which typically rely on a single SCM. We further highlight the discrepancies in LUC emission estimates between models of different complexity, particularly ESMs and IAMs, and encourage climate modeling groups to address these potential areas for model improvement.

Urbanization is causing an increase in air pollution leading to serious health issues. However, even though the necessity of its regulation is acknowledged, there are relatively few monitoring sites in the capital metropolitan city of the Republic of Korea. Furthermore, a significant relationship between air pollution and climate variables is expected, thus the prediction of air pollution under climate change should be carefully attended. This study aims to predict and spatialize present and future NO2 distribution by using existing monitoring sites to overcome deficiency in monitoring. Prediction was conducted through seasonal Land use regression modeling using variables correlated with NO2 concentration. Variables were selected through two correlation analyses and future pollution was predicted under HadGEM-AO RCP scenarios 4.5 and 8.5. Our results showed a relatively high NO2 concentration in winter in both present and future predictions, resulting from elevated use of fossil fuels in boilers, and also showed increments of NO2 pollution due to climate change. The results of this study could strengthen existing air pollution management strategies and mitigation measures for planning concerning future climate change, supporting proper management and control of air pollution.

Bio-based fertilizers (BBFs) can be a solution for converting agricultural waste into new products useful for increasing organic matter in the soil, thus reducing the consumption of mineral fertilizers. This can contribute to the ecological transition launched by the European Commission for the coming decades. Scenario analysis is an effective tool to assess the factors that can affect the development of the agri-food supply chain, evaluating the effects of their possible evolutions. The aim of this work is to draw plausible future scenarios for the BBF supply chain and to strengthen the consistency evaluation process of these scenarios. We built the scenarios considering both the literature and findings from stakeholder consultations. We then verified their consistency by adopting the Cross-Impact Balances (CIB) method, along with other techniques to better evaluate the consistency and plausibility of the narratives. The analysis provides stakeholders with information to evaluate possible future trends in the BBF supply chain. Monitoring the evolution of the identified drivers and maintaining constant and periodic discussions among stakeholders constitute the prerequisites for supporting the desirable future development of BBFs.

The Baltic Sea is a shallow, semi-enclosed brackish sea suffering like many other coastal seas from eutrophication caused by human impact. Hence, nutrient load abatement strategies are intensively discussed. With the help of a high-resolution, coupled physical-biogeochemical circulation model we investigate the combined impact of changing nutrient loads from land and changing climate during the 21st century as projected from a global climate model regionalized to the Baltic Sea region. Novel compared to previous studies are an extraordinary spin-up based upon historical reconstructions of atmospheric, nutrient load and runoff forcing, revised nutrient load scenarios and a comparison of nutrient load scenario simulations with and without changing climate. We found in almost all scenario simulations, with differing nutrient inputs, reduced eutrophication and improved ecological state compared to the reference period 1976–2005. This result is a long-lasting consequence of ongoing nutrient load reductions since the 1980s. Only in case of combined high-end nutrient load and climate scenarios, eutrophication is reinforced. Differences compared to earlier studies are explained by the experimental setup including nutrient loads during the historical period and by the projected nutrient loads. We found that the impact of warming climate may amplify the effects of eutrophication and primary production. However, effects of changing climate, within the range of considered greenhouse gas emission scenarios, are smaller than effects of considered nutrient load changes, in particular under low nutrient conditions. Hence, nutrient load reductions following the Baltic Sea Action Plan will lead to improved environmental conditions independently of future climate change.

PurposeTo evaluate some of the current discussion about the possible impacts of the COVID-19 pandemic on wildlife tourism destinations. There could be either positive and/or negative impacts and this viewpoint provides some reflection on what the future might hold for some if not many wildlife tourism destinations when the global tourism industry resumes.Design/methodology/approachA combination of tourism and environmental impact research studies and online resources are used to demonstrate the wildlife tourism-conservation nexus and provide a commentary regarding the impact of COVID-19 on the wildlife tourism system.FindingsThis paper provides a context and viewpoint on the possible implications of post COVID-19 reflection for wildlife tourism operations in the future.Research limitations/implicationsThis viewpoint paper captures only a snapshot of rapidly emerging online perspectives but at the same time draws together relevant research that emphasises the importance of wildlife tourism.Practical implicationsThis paper enables an appreciation of the implications of not reflecting on the way that tourism and the environment are currently/recently managed and funded. One possibility is that we could arrive at a different baseline that reflects degraded wildlife tourism conditions. If, in a post COVID-19 world, a new awareness of the vulnerability of species and the tourism upon which it is dependent arises, this could open the door for improved tourism management and conservation of species that are of high tourism value.Social implicationsThis paper offers a synthesis of views that fosters understanding of the possibility of damage to wildlife tourism resources due to the social and economic impacts of COVID-19 on the global nature-based tourism sector.Originality/valueThe viewpoint proffered in this paper provides scope for a rapid evaluation of the current status of wildlife tourism, its vulnerability and the need to reflect on the industry in a post COVID-19 world.

PurposeFuture scenarios and life cycle assessment (LCA) are powerful tools that can provide early sustainability assessments of novel products, technologies and systems. The combination of the two methods involves practical and conceptual challenges, but formal guidance and consensus on a rigorous approach are currently missing. This study provides a comprehensive overview of how different topic areas use future scenarios and LCA in order to identify useful methods and approaches, and to provide overall recommendations.MethodsThis study carried out a systematic literature review that involved searching for peer-reviewed articles on Web of Science, Scopus and Science Direct, utilising a rigorous set of keywords for future scenarios and for LCA. We identified 514 suitable peer-reviewed articles that were systematically analysed according to pre-defined sets of characteristics for the combined modelling of future scenarios and LCA.Results and discussionThe numbers of studies combining future scenarios and LCA increase every year and in all of the 15 topic areas identified. This combination is highly complex, due to different sequences in the modelling between future scenarios and LCA, the use of additional models and topic area-specific challenges. We identify and classify studies according to three archetypal modelling sequences: input, output and hybrid. More than 100 studies provide methods and approaches for combining future scenarios and LCA, but existing recommendations are specific to topic areas and for modelling sequences, and consensus is still missing. The efficacy of many studies is hampered by lack of quality. Only half of the articles complied with the LCA ISO standards, and only one quarter demonstrated consistent knowledge of future scenario theory. We observed inconsistent use of terminology and a considerable lack of clarity in the descriptions of methodological choices, assumptions and time frames.Conclusions and RecommendationsThe combined use of future scenarios and LCA requires formal guidance, in order to increase clarity and communicability. Guidance should provide unambiguous definitions, identify minimum quality requirements and produce mandatory descriptions of modelling choices. The goal and scope of future scenarios and LCA should be in accordance, and quality should be ensured both for the future scenarios and the LCA. In particular, future scenarios should always be developed contextually, to ensure effective assessment of the problem at hand. Guidance should also allow for maintaining current modelling complexity and topic area differences. We provide recommendations from the reference literature on terminology, future scenario development and the combined use of future scenarios and LCA that may already constitute preliminary guidance in the field. Information collected and recommendations provided will assist in a more balanced development of the combined use of future scenarios and LCA in view of the urgent challenges of sustainable development.

Adaptation strategies to climate change need information about present and future climatic conditions. However, next to scenarios about the future climate, scenarios about future vulnerability are essential, since also changing societal conditions fundamentally determine adaptation needs. At the international and national level, first initiatives for developing vulnerability scenarios and so-called shared socioeconomic pathways (SSPs) have been undertaken. Most of these scenarios, however, do not provide sufficient information for local scenarios and local climate risk management. There is an urgent need to develop scenarios for vulnerability at the local scale in order to complement climate change scenarios. Heat stress is seen as a key challenge in cities in the context of climate change and further urban growth. Based on the research project ZURES (ZURES 2020 website), the paper presents a new method for human vulnerability scenarios to heat stress at the very local scale for growing medium-sized cities. In contrast to global models that outline future scenarios mostly with a country-level resolution, we show a new method on how to develop spatially specific scenario information for different districts within cities, starting from the planned urban development and expansion. The method provides a new opportunity to explore how different urban development strategies and housing policies influence future human exposure and vulnerability. Opportunities and constraints of the approach are revealed. Finally, we discuss how these scenarios can inform future urban development and risk management strategies and how these could complement more global or national approaches.

The increasing frequency and intensity of heat waves, and the projected rise in temperatures due to climate change, pose a significant challenge for the thermal adaptation of residential buildings. This research aims to evaluate the thermal resilience of existing social housing by assessing thermal comfort and overheating through six retrofit strategies generated using Phase Change Material (PCM) to roofs and thermal insulation. Using transient simulations, the scenarios were evaluated under three schemes: historical climate, the 2024 heat waves, and a future climate scenario (2050). The study focuses on three Mexican cities with different climates: Mexico City, Chihuahua, and Tuxtla Gutiérrez, for which the optimal melting temperature of the PCM was determined by evaluating its potential to improve thermal comfort in each one. Key findings include a decrease in average annual thermal comfort in the baseline case for temperate climates (Mexico City and Tuxtla Gutiérrez), while the more extreme climates with very cold winters and very hot summers (Chihuahua) show improvement, demonstrating the need for retrofitting in most cases. When only PCM was applied, an improvement in thermal comfort was observed in all cases by 2050, with Mexico City standing out with an 18% increase. When combining PCM and insulation, only Chihuahua showed an improvement, with a 13% increase by 2050. When the overheating is studied, dramatic results were observed, with temperatures exceeding 25°C and 28°C reaching 93% and 51%, respectively, for Chihuahua, and 97% and 59%, respectively, for Tuxtla Gutiérrez. These results indicate that implementing retrofit strategies increases thermal resilience in future climate scenarios by enhancing thermal comfort during a warmer year in the future, but does not guarantee a significant reduction in overheating during extreme heat waves over a short period (e.g. two weeks).

This paper presents the response to anthropogenic forcing in the GISS-E2.1 climate models for the 21st century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The experiments were performed using an updated and improved version of the NASA Goddard Institute for Space Studies (GISS) coupled general circulation model that includes two different versions for atmospheric composition: A non-interactive version (NINT) with prescribed composition and a tuned aerosol indirect effect and the One-Moment Aerosol model (OMA) version with fully interactive aerosols which includes a parameterized first indirect aerosol effect on clouds. The effective climate sensitivities are 3.0°C and 2.9°C for the NINT and OMA models, respectively. Each atmospheric version is coupled to two different ocean general circulation models: The GISS ocean model (E2.1-G) and HYCOM (E2.1-H). We describe the global mean responses for all future scenarios and spatial patterns of change for surface air temperature and precipitation for four of the marker scenarios: SSP1-2.6, SSP2-4.5, SSP4-6.0, and SSP5-8.5. By 2100, global mean warming ranges from 1.5°C to 5.2°C relative to 1,850–1,880 mean temperature. Two high-mitigation scenarios SSP1-1.9 and SSP1-2.6 limit the surface warming to below 2°C by the end of the 21st century, except for the NINT E2.1-H model that simulates 2.2°C of surface warming. For the high emission scenario SSP5-8.5, the range is 4.6–5.2°C at 2100. Due to about 15% larger effective climate sensitivity and stronger transient climate response in both NINT and OMA CMIP6 models compared to CMIP5 versions, there is a stronger warming by 2100 in the SSP emission scenarios than in the comparable Representative Concentration Pathway (RCP) scenarios in CMIP5. Changes in sea ice area are highly correlated to global mean surface air temperature anomalies and show steep declines in both hemispheres, with the largest sea ice area decreases occurring during September in the Northern Hemisphere in both E2.1-G (−1.21 × 106 km2/°C) and E2.1-H models (−0.94 × 106 km2/°C). Both coupled models project decreases in the Atlantic overturning stream function by 2100. The largest decrease of 56%–65% in the 21st century overturning stream function is produced in the warmest scenario SSP5-8.5 in the E2.1-G model, comparable to the reduction in the corresponding CMIP5 GISS-E2 RCP8.5 simulation. Both low-end scenarios SSP1-1.9 and SSP1-2.6 also simulate substantial reductions of the overturning (9%–37%) with slow recovery of about 10% by the end of the 21st century (relative to the maximum decrease at the middle of the 21st century).