Teaching Environmental Assessment (EA) in higher education is both challenging and essential, given its applied, interdisciplinary nature and close connection to evolving practice. While previous studies highlight recurring challenges in EA teaching, such as dispersed course structures, weak links to research, and ambiguities in how EA is positioned within academic programmes, they tend to address these aspects separately rather than as interrelated conditions. Drawing on literature analysis and qualitative interviews with teachers in Sweden and Germany, the study examines what teachers aim to convey, how they teach, and the factors that shape their pedagogical choices. Conceptually, it proposes an analytical framework that integrates teacherrelated, subject-related, student-related, and contextual dimensions, emphasising how teachers perceive and navigate them. In this sense, EA teaching is understood as a navigated practice shaped by how teachers respond to the conditions within which they work. The findings show that EA teaching shares a number of common aims and understandings across countries. Nevertheless, the teaching is also diverse and at times fragile. Teachers' responses to constraints, including limited resources, uneven access to EA knowledge and networks, and context-specific demands, play a central role in shaping what is taught. At the same time, the interdisciplinary nature of EA offers significant opportunities for integrating theory and practice. The study highlights the need to move beyond prescriptive accounts of EA education towards supporting teachers' situated practices and their capacity to make informed pedagogical choices under varying conditions.
PET circularity is often evaluated by recovery volumes, although performance ultimately depends on whether recovered material can be converted into quality-assured outputs and absorbed by viable end markets. Yet the mechanisms connecting policy, markets, technology, and stakeholder behavior remain dispersed across heterogeneous evidence. We developed a source-attributed, time-stamped causal-network approach using 750 Australian government, industry and NGO, corporate, and media documents published during 2010–2025. Causal extraction, semantic normalization, sentiment assignment, and graph construction yielded 2794 factor nodes and 1588 unique causal edges. The network was strongly externalized: policy, market, and social factors were more numerous and highly connected than internal technical and operational factors. Persistent barriers combined cost and price volatility, inconsistent recyclate quality, infrastructure gaps, and weak policy implementation. Positive mechanisms clustered around standards and measurement, design for recyclability, operational capacity, and end-market development; their circular value depended on retained material quality and the end use reached. Source attribution revealed systematic framing differences, with media coverage concentrating negative implementation narratives. Temporal and regional analyses indicated a shift from limited attention to rapid expansion and subsequent consolidation, alongside national structural hubs and differentiated state pathways. A full-text academic shadow corpus preserved the broad problem domains but changed their hierarchy: academic evidence foregrounded material and processing mechanisms, whereas the primary corpus foregrounded institutional coordination and market implementation. The contribution is therefore not a universal ranking of Australian interventions, but an auditable framework for identifying how technical feasibility becomes, or fails to become, operational circularity under different institutional conditions.
Under urbanization and multiple global crises, translating the sustainable development goals (SDGs) from global visions into local practices has become a central challenge of urban transformation. Sustainable neighborhood regeneration (SNR) has been widely regarded as an important spatial practice for advancing SDG localization. However, existing studies have largely focused on intervention performance, sustainability assessment, or SDG mapping, while paying less attention to the sequential process through which SDG-related goals enter SNR decision-making, are translated into specific intervention actions, and generate multidimensional effects under different conditions. To address this gap, this study conceptualizes SNR as a process mechanism for SDG localization and develops an analytical framework integrating goal translation, intervention actions, impact identification, and implementation conditions. A systematic review of 341 publications from 55 countries was conducted, using content analysis, SDG relationship coding, and structured narrative synthesis. The results show that: (a) knowledge production remains geographically uneven, and evidence from the Global South beyond China is still relatively limited; (b) multiple types of relationships are formed between SNR intervention actions and the SDGs, including direct positive contributions, indirect positive contributions, and negative effects; (c) SDG-related goals are selectively translated into local indicators, planning criteria, and negotiation agendas mainly through potential and performance assessment, modeling simulation and objective optimization, and participatory decision-making, while the translation of goals related to social equity and local context continues to be constrained by limitations in data, modeling, and participation conditions; and (d) financial, institutional, technical, data-related, and stakeholder conditions further shape both goal translation and action implementation. This study advances the understanding of SNR-SDG relationships from static goal correspondence toward a process-oriented, relational, and conditional explanatory framework for SDG localization, offering insights for risk-sensitive neighborhood regeneration decision-making.
Carbon sink services are essential for climate change mitigation, yet their benefits are unevenly distributed across space. High-emission regions often differ from areas with strong ecosystem carbon uptake, creating spatial mismatches among carbon demand, ecological supply, and compensation responsibility. Existing assessments commonly focus on static supply-demand balances or distance-based source-sink relationships, giving insufficient attention to atmospheric transport pathways and cross-regional benefit attribution. To address this gap, this study develops a forward trajectory-based framework for tracing carbon sink benefits and informing fair regional compensation. The framework integrates carbon sink supply-demand assessment, HYSPLIT-based atmospheric trajectory modeling, representative trajectory clustering, flow allocation, payment for ecosystem services, and financial sustainability assessment. Applied to the Qinghai–Tibet Plateau and surrounding regions from 2000 to 2022, the framework identifies the spatial structure, temporal dynamics, and compensation implications of atmosphere-mediated carbon sink service flows. Results show that carbon sink benefit pathways exhibit directional rigidity, extensive weak connectivity, and pronounced flow asymmetry. The regional carbon sink system has shifted from relative independence toward stronger cross-regional coordination, indicating growing interdependence between carbon-deficit and carbon-surplus areas. The estimated compensation structure shows spatial polarization but also signs of convergence over time, with payment scales generally increasing. Financial sustainability assessment suggests that the proposed payment scheme does not create systematic imbalance for either paying or receiving regions. The study provides a spatially explicit decision-support framework for carbon sink attribution, ecological compensation, and regional carbon governance.
Current assessment tools for streams and rivers focus on ecological functioning while ignoring the social dimension, which varies across rural and urban ecosystems. This study presents the rural–urban socioecological stream sustainability index (hereinafter, RU-SESSI) for assessing stream function across the rural–urban continuum. This index is based on the stream ecosystem services (ES) and biodiversity index (SESBI), which was developed in our previous study to assess stream health. The SESBI was extended into a sustainability subindex by adding two economic indicators, and the framework was complemented by a stream–society interaction subindex comprising accessibility, public safety, and community involvement. Together, these subindices capture stream function through both sustainability performance and human–stream interaction patterns. The framework was refined and validated using the Delphi method, revealing significant differences in the relative importance of most RU-SESSI indicators between rural and urban segments. Applied to the Yarkon Stream in central Israel, the index revealed higher biodiversity and regulating services scores in the rural reach, whereas economic, recreation, and accessibility scores were higher in the urban reach, while public safety and community involvement were comparable between reaches. The urban reach achieved a slightly higher RU-SEES score than the rural reach (6.22 vs. 5.76), with no significant difference in the distribution of weighted indicator scores. The RU-SESSI offers a context-sensitive framework that accounts for unique socioecological dynamics, providing policymakers with valuable insights for tailoring stream management to rural–urban settings and contributing to global water security and sustainability.
This study aimed to assess the water footprint of plastic tubular digesters to treat organic waste and recover bioenergy. Different scenarios in a small-scale dairy farm in Colombia were considered: i) scenario without the digester in which cow manure is piled up, and dairy wastewater is directly discharged into the environment, ii) scenario with a plastic tubular digester treating cow manure, and iii) scenario with a plastic tubular digester co-digesting cow manure with dairy wastewater. The ReCiPe 2016 – midpoint (H) method was used to assess the degradation of water bodies (i.e. eutrophication and ecotoxicity impact categories), while the AWARE 2.0 method was applied to evaluate the water scarcity impact category. Results showed that, in terms of water quality degradation, the co-digestion scenario exhibited impacts 10% to 45% lower than those of the other scenarios, depending on the impact category. In terms of water scarcity, the co-digestion scenario exhibited approximately 10% lower water scarcity than the other scenarios, which showed a similar water scarcity footprint. This indicates that implementing plastic tubular digesters, even under mono-digestion conditions, does not worsen water availability. These benefits are greater if co-digestion of different agri-food waste is applied, since it helps preserve water quality by valorising the intrinsic water content of food wastewater. It also decreases environmental impacts by reducing synthetic fertiliser use through the production of a higher-quality digestate. Overall, plastic tubular digesters provide a low-water footprint alternative to the direct discharge and uncontrolled storage of livestock waste and food-production wastewater in small-scale farms.
Heparin sodium, a widely used anticoagulant, is produced from swine intestinal mucosa. Its life-cycle carbon footprint remains unknown due to a methodological challenge, namely, climate burdens must be allocated across two co-product stages. The first is in the swine slaughtering stage, where climate burdens are divided between the dressed carcass and the small intestine. The second is in the casing-processing stage, with climate burdens further divided between casings and intestinal mucosa. Here, we develop a cradle-to-gate life-cycle model for crude heparin sodium. Results show that choices of mass (M) and economic (E) allocations strongly influence the carbon footprint. M-M allocation produces the highest carbon footprint, followed by M-E, E-M, and E-E, in all time horizons of 20, 100, and 500 years. Heparin sodium has a carbon footprint of 819 tCO2e t−1 at a 100-year horizon with M-M allocation, and 74% of emissions are sourced from the swine feeding stage. The net footprint is 732 tCO2e t−1 calculated by subtracting the carbon credits from intestinal residue as a substitute for soybean meal (87 tCO2e). Swine feeding improvement can reduce the carbon footprint by 18% under mass allocation. Such upstream reduction slightly exceeds that of full use of green electricity by downstream producers (15%). However, both reduction potentials are below the apparent decrease that is generated by the method switch from mass allocation to economic allocation (30%). The slaughtering stage has a stronger influence than allocation in the casing-processing stage, thus representing the leverage point in the heparin sodium production. Our findings highlight the importance of improving the transparency in reporting the allocation choice in carbon-footprint assessments.
With ongoing climate change, the projected rise in temperature-related mortality has become a critical public health concern. Beyond climate change, intensifying urban heat island (UHI) effects and rapid population aging are key drivers shaping future exposure to extreme temperatures. However, most previous studies have examined these drivers in isolation, leaving their combined influence on future temperature-related mortality poorly understood. This study assesses the compound effects of UHI and population aging on future temperature-related mortality across more than 2300 European cities. The results reveal clear asymmetric impacts of this compound factor. In summer, it increases heat-related deaths by 19% (2030) to 58% (2100) beyond the sum of their individual effects, demonstrating a synergistic “1 + 1 > 2” relationship. In winter, UHI offsets 46% (2030) to 10% (2100) of the additional cold-related deaths from aging, resulting in lower mortality than aging alone (“1 + 1 < 1”). These results demonstrate that compound interactions between urban environmental change and demographic aging can substantially reshape future temperature-related mortality patterns. Accounting for such asymmetric interactions is therefore essential for accurately projecting climate-related health risks and for designing effective urban climate adaptation strategies.
Accelerating the transition to low-carbon urbanisation was critical for climate change mitigation. The delineation of local carbon emission zones (LCEZs) offers a promising approach for integrating urban morphology with CO2 emissions patterns for targeted planning. However, existing LCEZs frameworks are affected by scale dependence and often provided limited, context-insensitive explanations of emission heterogeneity. This study developed a cross-scale LCEZs framework and applied it to London, New York, Paris, and Sydney. First, the collapse method, grounded in finite-size scaling, was used to identify morphology factors exhibiting cross-scale statistical regularity, thereby mitigating the scale effect of the modifiable areal unit problem. Second, an optimal parameter-based geographical detector (OPGD) model was used to identify city-specific combinations of morphology factors associated with heterogeneity in CO2 emissions to construct LCEZs. Eleven factors passed the collapse screening, including transport, building, and landscape factors. In the constructed LCEZs results of the four cities, at least one transportation-related variable was retained in every combination, while mean building volume (MBV) emerged as a core factor in three of the four metropolises, demonstrating high universality and influence. The resulting LCEZs were statistically validated by Kruskal-Wallis tests, with effect sizes ranging from 0.143 to 0.233, and intra-zone coefficients of variation were reduced by over 80% relative to the global baseline in each metropolis, confirming strong internal homogeneity. This framework provided an basis for comparing morphology–emission associations and informing low-carbon interventions. It offered a repeatable diagnostic procedure to quantify trade-offs and tailor measures to local contexts, bridging computational urban science with planning practice.
Livestock production supplies dietary protein and supports agricultural development, but it also contributes substantially to nitrogen pollution and non-CO2 greenhouse gas (GHG) emissions. Amid growing pressures related to climate change, resource scarcity, and environmental protection, enhancing nitrogen use efficiency and curbing pollution have emerged as important objectives for the green transformation of the livestock sector. This study combined a livestock-centred coupled human and natural systems (CHANS) accounting framework, the IPCC emission-factor approach, and a spatial-equilibrium trade model to quantify provincial nitrogen budgets, non-CO2 GHG emissions, and trade-induced virtual transfers of environmental pressures in China's livestock sector from 2000 to 2024. A business-as-usual (BAU) baseline and four mitigation scenarios were developed to assess dietary adjustment, improved feed conversion efficiency, enhanced manure recycling, and their combined implementation through 2050. The results showed that total livestock-sector non-CO2 GHG emissions peaked at 546.98 Mt. CO2-eq in 2005 and subsequently declined with fluctuations to 415.59 Mt. CO2-eq in 2024. CH4 from enteric fermentation was the main non-CO2 GHG source. The livestock sector maintained a persistent nitrogen surplus, and NH3 volatilization remained the dominant nitrogen-loss pathway. Relative to BAU in 2050, dietary adjustment was projected to reduce non-CO2 GHG emissions by approximately 42%, whereas improved feed conversion efficiency and enhanced manure recycling were projected to reduce nitrogen losses by approximately 28% and 31%, respectively. The combined mitigation scenario was projected to achieve the strongest co-mitigation effect, reducing non-CO2 GHG emissions and nitrogen losses by approximately 45% and 50%, respectively. These findings suggest that coordinated dietary adjustment, feed-efficiency improvement, and manure-management optimization may offer considerable potential for synergistically reducing nitrogen losses and non-CO2 GHG emissions, providing a scientific basis for regionally differentiated, whole-chain mitigation strategies and the green transformation of China's livestock sector.
