Brand imitation (referring to the strategic imitation of mature and sustainable brands by enterprises through innovative technology adaptation or repetitive visual replication) can reduce the risk of enterprises entering the green market, expand brand awareness, but to a certain extent, it will reduce consumers' perception of the green quality of the brand, thereby affecting the effectiveness of marketing strategies. To explore the degree of consumer preference for green brand information, this study designed a discrete choice experiment and constructed a brand combination that includes attributes such as brand imitation degree, environmental information tendency, green attribute centrality, sales channels, and promotion intensity. A mixed Logit model and latent category model were used to investigate consumers' independent preferences and cumulative effects on different attribute information, revealing the differences in consumer preferences in the shopping cart (intention) and payment (behavior) stages. Above all, the following conclusions are drawn: After the above analysis, the following conclusions were drawn: (1) The mixed Logit model shows that both green and traditional attributes significantly affect consumer brand choice. During the purchase stage, there is a preference for green attributes, while during the payment stage, there is a preference for traditional attributes. Consumers are more sensitive to information on innovation, self-benefit tips, green core attributes, direct sales, and high promotional efforts. (2) The latent category model indicates that consumers with different psychological processing modes have different dependencies on brand attributes. Value-oriented, interest-oriented, identity-oriented, and trust-oriented consumers have opposite choices in brand imitation, environmental information inclination, and channel preference. (3) Unlike trust testing, interest identification, and trust, endogenous consumers are willing to pay higher costs for green attributes. (4) The value of a product has the most significant impact on sales channel preferences, followed by environmental information preferences. (5) Consumers of different genders have consistent preferences for brand information, but high-income groups show more significant differences. The results of this study will contribute to the development of green marketing strategies for enterprises. In the shopping cart stage, companies can emphasize green technology; in the payment stage, they should strengthen cost-effectiveness. Providing authoritative authentication is an effective strategy for trusting consumers. For value-conscious users, product co-creation opportunities can be opened, while limitedtime promotions can be implemented for price-sensitive groups. In addition, high-value products should prioritize technological innovation based on imitation to avoid simple appearance replication.
Current restoration practices apply uniform management thresholds across entire regions, overlooking spatial heterogeneity and limiting efficiency. We tested whether distinct spatial clustering patterns in China’s Yellow River Basin require different ecological thresholds. Integrating 20-year land use data (2000 ~ 2020) with spatial clustering and machine learning, we quantified driver thresholds for five ecosystem services across four spatial patterns: High-High (HH) synergy, Low-Low (LL) weak synergy, and High-Low (HL) / Low-High (LH) trade-off zones. Vegetation thresholds (NDVI) differed by 33% between HH zones (0.5 ~ 0.7) and LL zones (0.4 ~ 0.5), while driver contributions varied 1.9-fold across patterns. Dominant drivers shifted from population density (2000) to temperature (2020), indicating a transition from anthropogenic to climate-driven dynamics. These findings demonstrate that uniform thresholds misallocate resources—over-investing in resilient HH zones while under-investing in vulnerable LL zones. We propose pattern-specific strategies: maintaining NDVI > 0.5 in synergy zones, surpassing NDVI > 0.4 breakpoints in transitional zones, and implementing dual climate-population controls in degraded areas. This framework advances restoration from uniform prescriptions toward spatially targeted approaches, providing actionable guidance for precision management in degraded drylands globally.
Decoupling economic growth from water use is essential for achieving sustainable development in the Belt and Road Initiative (BRI) countries. However, previous studies have primarily focused on decoupling analysis from the production perspective, failing to capture the complex relationship between water use and value added across supply chains. This study integrates the Environmentally Extended Multi-Regional Input-Output (EE-MRIO) model with the Tapio decoupling model to investigate the decoupling status of BRI countries from the consumption and income perspectives during 2004 ~ 2021. We find that 55% of BRI countries exhibit discrepancies in decoupling status when comparing the consumption or income perspectives with the production perspective. For instance, Qatar demonstrates strong decoupling from the production perspective. However, it shows weak decoupling from the consumption perspective and expansive negative decoupling from the income perspective. Temporally, 30 countries shifted from strong to weak or negative decoupling from the production perspective. Similar deteriorations were observed from the consumption and income perspectives, where decoupling statuses worsened in 28 and 30 countries. Extending the analysis to trading pairs reveals that more than 75% of trading pairs have not achieved strong decoupling from either the consumption or income perspective. International collaboration plays a vital role in decoupling economic growth in BRI countries from water use along their supply chains. This study provides insights into the decoupling between water use and value added from the consumption and income perspectives, thereby informing existing water-saving policies.
Satellite-based techniques are increasingly used to monitor gas flaring (GF) and assess its environmental impacts. This study applies the Reed-Xiaoli Detector (RXD) algorithm to identify GF locations in the Pars Special Economic Energy Zone (PSEEZ) in Iran, one of the world’s largest gas reserves. RXD was first implemented on shortwave infrared (SWIR) images from the OLI sensor on Landsat 8/9, and its performance was then evaluated using MSI data from Sentinel-2A/B. All available cloud-free OLI and MSI SWIR reflectance data from 2016 to 2022 were processed. To improve detection robustness, a new step based on the annual persistence of the RXD metric was introduced, ensuring an optimal balance between sensitivity and accuracy. Ground-truth GF locations from field surveys and very high-resolution satellite imagery were used to assess RXD performance. Results show that RXD, on both OLI and MSI, enhances the identification, mapping and monitoring of gas flaring sites compared with existing satellite GF products using similar spectral bands. The demonstrated reliability of RXD outputs highlights the algorithm as a valuable component of a multi-source GF monitoring framework, supporting decision-making for the sustainable management of industrial activities.
Population aging is reshaping the structure and distribution of household carbon footprints, presenting new sustainability challenges. We clarify the mechanisms through which aging impacts carbon footprint formation at individual, household, and societal levels. We use a multi-regional input-output (MRIO) model, household survey data, and Gini coefficient decomposition to conduct our analysis. This approach allows us to systematically examine the age-related evolution, provincial heterogeneity, and urban-rural disparities of household carbon footprints in China. We also forecast future changes in these footprints and assess the associated inequality. Our results show that: (1) The carbon footprint of households of older adults (60+) follows a “low base, high growth” trend, increasing by 139.6% from 2012 to 2017 — the fastest of any age group — and is projected to make this cohort the second-largest emitter by 2030. (2) This age-related heterogeneity is driven by four mechanisms: life-cycle effects, household expenditure structure, income elasticity, and intergenerational stratification. (3) Urban households of older adults have higher total footprints and faster per capita growth than their rural counterparts, indicating a more pronounced aging impact in urban areas. (4) The impact of aging on carbon inequality follows an inverted U-shaped curve with regional variations. Aging exacerbates inequality in industrial and resource-based provinces, driven by high-carbon subsistence consumption and youth out-migration. Conversely, it reduces inequality in developed coastal regions through technological substitution and pension-supported green consumption. We elucidate the complex relationship between aging and carbon footprints, advancing climate justice research. It also provides targeted policy recommendations for aligning climate goals with social equity.
