Buyers and regulators increasingly expect suppliers to demonstrate environmental management, yet the export value of such practices may depend on the complementary capabilities a firm holds and vary across practices. Drawing on resource-based and complementarity theories, this study examines whether digital adoption helps firms convert environmental management routines into export-relevant capabilities. Using survey data on Pakistani manufacturing firms, we estimate recursive mixed-process systems that jointly model digital adoption, green management practices, export propensity, and export intensity. Our results show three patterns. First, green management practices yield no export premium on their own; however, when combined with basic digital technologies, they are positively associated with export performance, consistent with complementarity, with digital adoption strengthening the export payoff of green practices. Second, this complementarity operates on how much firms export (the intensive margin) but is not statistically significant for whether firms export at all (the extensive margin). Third, the moderating effect is not uniform across digital–green combinations. Digital visibility interacts positively and significantly with both green components, whereas transaction-oriented coordination does so only for renewable energy adoption, and the profile does not vary appreciably by firm size. An exploratory analysis pooling nine economies in the Middle East, North Africa, Afghanistan and Pakistan (MENAAP) suggests a similar pattern. The study adds to the environmental management and digital-sustainable business model literature by showing that green practices operate as conditional economic capabilities. For practice, the findings suggest that firms and policymakers should combine green-practice adoption with digital tools that support information exchange, documentation, coordination, and standards-oriented communication.
Nature-based stormwater solutions (NBSS) support urban stormwater management while providing additional ecosystem services. Their hybrid grey–green design sets them apart from conventional drainage systems requiring specific maintenance to ensure long-term performance. This study combines a global practitioner survey and a review of maintenance guidelines aiming to characterize shortcomings in NBSS management, focusing on failure mechanisms and maintenance practices. Based on 22 responses, survey results show that, in the absence of maintenance, systems are mainly affected by sediment buildup, litter, and green waste accumulation, as well as excessive vegetation growth, and invasive species. Maintenance (e.g., visual inspections, litter removal) is performed regularly, from monthly to annually, consistent with guidelines. Vegetation management typically follows a seasonal frequency (∼three months). Our review of 35 guidelines indicates that maintenance practices are very diverse and context-dependent, depending on the type of NBSS and socio-ecological-technological context, reflecting a potential barrier to mainstreaming of best practices. No universal maintenance frequency can be established as it strongly depends on NBBS and local context (e.g., climate, available resources). Systematic data collection on failures, their occurrence, and impacts is however essential to support predictive local maintenance strategy.
Wetland restoration is increasingly recognized as a nature-based climate solution, but effective planning requires balancing nonlinear ecological responses with economic and implementation constraints. We propose a conceptual and computational framework for climate-oriented coastal wetland restoration that embeds process-based ecosystem modeling within restoration optimization. Restoration strategies are represented as portfolios combining discrete choices among restoration measures with continuous decisions on implementation intensity and area allocation. A vertically resolved ecohydrological model simulates soil organic carbon dynamics and decomposition-driven CO2 and CH4 emissions, allowing environmental outcomes to arise from the interaction between restoration decisions and ecosystem processes. These emissions represent decomposition-driven source fluxes and do not constitute a complete net ecosystem greenhouse-gas balance. The optimization is performed using a genetic algorithm with multiple independent runs and provides approximate solutions without a formal guarantee of global optimality. The framework is illustrated through a benchmark analysis and an application to the Ebro Delta. The benchmark shows that alternative objective specifications select distinct interior and corner solutions from the same ecological trade-off. In the Ebro Delta application, imposing a budget constraint reallocates restored area from the deep-rooted vegetation type toward the less expensive shallow-rooted type, while maintaining high vegetation densities and compliance with the methane target, although the CO2 target is exceeded. Global sensitivity analysis identifies the density and area allocation of the deep-rooted vegetation type as the main drivers of restoration performance. The results show that restoration outcomes depend not only on total vegetation cover but also on portfolio composition and implementation intensity. The proposed framework provides a flexible methodology for integrating process-based ecological models into restoration planning under alternative environmental objectives and resource constraints.
The rapid increase in environmental pollution and global energy demand has intensified the search for sustainable technologies capable of simultaneously addressing wastewater contamination and clean fuel generation. Photocatalysis has emerged as a promising strategy because it utilizes solar energy to drive redox reactions under mild operating conditions. Among various photocatalytic materials, bismuth-based photocatalysts have attracted significant attention due to their narrow band gaps, excellent visible-light absorption, layered crystal structures, chemical stability, and tuneable electronic properties. The review discusses the structural and functional characteristics of major bismuth-based systems. Emphasis is placed on advanced modification strategies such as heterojunction construction, metal/non-metal doping, and oxygen-vacancy defect regulation, all of which significantly improve charge separation efficiency, light harvesting and surface reaction kinetics. Recent ternary and Z-scheme systems have demonstrated excellent capability for degrading organic pollutants while concurrently enhancing hydrogen production rates under visible-light irradiation. The review further analyzes the photocatalytic mechanisms governing reactive oxygen species generation, interfacial charge migration and proton reduction pathways. Despite major progress, several limitations remain, including photo-corrosion, charge recombination, low quantum efficiency and challenges in scaling laboratory results to practical reactors. Future perspectives highlight defect-controlled nanostructures, noble-metal-free cocatalysts, real wastewater applications and pilot-scale solar reactor development. Overall, bismuth-based photocatalysts offer strong potential as multifunctional materials for integrating environmental remediation with renewable hydrogen production, supporting the transition toward sustainable energy and water treatment technologies.
