Climate and price shocks can reshape smallholders’ incentives to adopt agroecological practices, yet limited evidence exists on whether such responses persist over time. Drawing on the Protective Action Decision Model and expected utility theory, this study examines how climate and price shocks influence initial and consistent adoption of agroecological practices among smallholders in northern Ghana. Three-wave household panel data (2014, 2020 and 2023) were combined with 41 years of climate records. Panel Multivariate Probit and Fixed-effects Poisson models were used to estimate adoption decisions and intensity, respectively, complemented by focus group discussions. Results reveal that adoption responses are both shock- and practice-specific. Flood shocks stimulate initial adoption across agroecological domains and consistent adoption of crop- and land-specific practices, whereas drought and heat stress primarily influence land- and crop-specific adoption, respectively. Food price shocks predominantly stimulate initial adoption, while input price shocks encourage more sustained adoption, particularly of land-specific practices. Flood exposure increases the intensity of initial and consistent adoption by 0.49 and 0.30 units respectively, while food and input price shocks increase initial adoption intensity by 0.82 and 0.45 units. Positive correlations across adoption decisions further indicate complementarities among agroecological practices. The findings demonstrate that shocks can induce agroecological practices adoption, although the persistence of responses varies by shock type. Policies should therefore promote complementary bundles of agroecological practices while strengthening institutional and resource support for sustained adoption.
Communities in the United States increasingly undertake distinct planning processes to build resilience to reduce natural hazard impacts, adapt to changing conditions, enhance sustainability to reduce energy and resource use and consumption, and promote economic prosperity. Planning efforts addressing these multifaceted goals result in community-based resilience, adaptation, and sustainability plans. Given the time- and resource-intensive nature of community planning, this study identifies shared processes, goals, and information requirements that could be standardized across these distinct planning objectives and identifies further guidance development needs to improve plan quality. A content analysis of resilience, adaptation, and sustainability planning guidance documents reveals structural similarities across plan goals, indicating that common standardized processes for goal setting, stakeholder engagement, and standard solution sets to mitigate natural hazard risk would be suitable for all three planning types. Conversely, unique technical requirements for analyzing natural hazard exposure and vulnerability in adaptation and resilience planning are not present in sustainability planning. These requirements are not suitable for common standard methods and necessitate unique planning workforce training. Comparing the assessment of plan guidance results with prior plan quality evaluations highlights a continued need for standard methods and metrics to improve plan evaluation and monitoring.
With the deepening of industrial integration and the refined division of labor, the structure of carbon emission linkages between different industrial sectors is constantly evolving and becoming increasingly complex. Interdependencies among sectors have amplified the potential for synergistic emission reductions. Therefore, analyzing the dynamic evolution of embodied carbon transfer at the sectoral level from a network perspective forms the basis for formulating policies for collaborative carbon reduction across multiple industrial sectors. To investigate the evolutionary mechanisms and synergistic emission reduction pathways of embodied carbon transmission among industrial sectors, this study combines input–output analysis with social network analysis to characterize the evolution of sectoral carbon linkage networks. A temporal exponential random graph model is constructed to examine the impact mechanisms of dynamic changes. The findings reveal that: (1) The scale of embodied carbon transfers continues to expand, and the network structure is characterized by localized clustering and asymmetry. (2) The evolution of cross-sectoral carbon linkage networks is driven jointly by endogenous network structure, time dependence and exogenous factors, with endogenous structural effects weakening over time. (3) Carbon linkages between industrial sectors exhibit distinct evolutionary patterns within the high-carbon sub-network, low-carbon sub-network, and hybrid network. (4) Green technological innovations in any sector can generate synergistic emission reduction effects at the network level through technology diffusion, while the impact of adjustments to production and consumption structures on embodied carbon flows exhibits heterogeneity. Therefore, carbon reduction policies should shift from sector-specific emission controls to network-oriented collaborative governance. By implementing differentiated strategies for different types of industrial sectors and promoting the diffusion of green technologies, we can leverage the advantages of network structures to achieve efficient multi-sectoral emission reductions.
As the world's leading CO2 emitter, China faces significant air quality challenges, particularly from the road transportation sector. Concerns over severe air pollution have driven the adoption of pollution control measures to reconcile economic growth with climate neutrality goals. We investigate the synergistic effects of PM2.5 and CO2 emission reductions in road transportation, focusing on the impact of the "Action Plan for Air Pollution Prevention and Control" (APAPPC). The APAPPC proposed control measures targeting pollution from mobile sources and designated key cities for prioritized regulation, yet existing studies provide limited city-level evidence on how such policies influence PM2.5 reduction and synergistic emission mitigation within the road transportation sector at the prefecture-level city scale. We seek to answer how various factors contribute to emission reductions, and how the effectiveness of the APAPPC operates through specific policy mechanisms in advancing climate-neutral mobility via pollution control. Employing empirical models and emissions data from 276 prefecture-level cities in China during 2005-2018, we identify systemic decarbonization enablers across the road transportation sector and measure the impacts of policy interventions. The findings reveal that a 1-million-ton reduction in transport-related CO2 emissions is associated with an approximately 84.75-ton decline in PM2.5 emissions, indicating significant synergistic relationships, although the magnitude of this relationship varies across cities. Moreover, the APAPPC has been effective in achieving a 2.53% reduction in PM2.5 emissions, largely through increased public transportation usage, decreased road freight, and reduced vehicle numbers. Therefore, future efforts to reduce road transportation emissions should adopt differentiated strategies, with policies designed for individual cities based on their transport profiles and major emission sources.
Existing studies lack an integrated analysis of energy enterprises’ market competition, abatement cooperation, and technological signaling under different information structures. This study examines competition and cooperation between new energy enterprises and traditional energy enterprises. It develops an integrated biform game and signaling game model to analyze carbon risk management strategies for the low-carbon transition under symmetric and asymmetric information. The findings are as follows. (1) Technological progress by traditional energy enterprises reduces carbon risk but increases total carbon emissions. The profit of new energy enterprises follows an inverted-U relationship with carbon abatement investment cost. (2) A moderate increase in consumers’ price sensitivity raises energy demand. Greater product substitutability intensifies competition, expands market size, increases energy prices, and significantly raises the profits of new energy enterprises. (3) Under asymmetric information, signaling reduces the sensitivity of profits to carbon abatement costs and weakens the benefits of cost sharing. As the prior probability of the high-efficiency type increases, the separating equilibrium reduces decision-making uncertainty while simultaneously improving the profits and technological capabilities of traditional energy enterprises. Under the baseline parameters, social welfare declines under both equilibria and remains higher under the pooling equilibrium than under the separating equilibrium. These findings support differentiated carbon-abatement incentives and transparent information disclosure by policymakers, while guiding enterprises in selecting cost-sharing, signaling, technology-investment, and pricing strategies according to the prevailing information structure and market conditions.
