Environmental Development最新文献

Achieving a blue economy will require reconciling the value of emerging ocean uses with their impacts on the seascape and sectors with historical access to marine resources and areas. To meet this challenge, we developed an analytical framework for conducting marine spatial planning through tradeoff analysis, and applied it to prospective offshore wind energy development in the ∼974 km² Morro Bay, California, USA Wind Energy Area (WEA). We generated spatial data layers estimating MW power production and impacts on fisheries value and marine wildlife conservation (seabird and cetacean populations) from wind farm development. We then quantified each sector's response to plans of development across the WEA and inside three leases recently acquired by the energy industry for prospective development. Finally, we integrated the sector response data into an analytical framework for mitigating sector tradeoffs with novel spatial planning solutions (maps of wind farm size, location, and configuration) that optimally maximize value to the emergent energy sector (MW power) while minimizing impacts to historical (fisheries and wildlife) sectors. We found that western sites in the WEA had the highest potential power production concurrent with the lowest impact on the historical sectors, revealing the eastern lease to be less efficient at optimally balancing the sector's objectives relative to the development of the central or western leases or the optimal spatial plans identified in the tradeoff analysis. Within a lease, tradeoff analysis found spatial planning able to generate out-sized savings in fisheries value with only modest losses in MW power – for example, by avoiding development in just 5% of the eastern lease to preserve nearly half its fisheries value and still generate 95% its total power potential. Small-scale development opportunities (e.g., a pilot project) with significant power potential and no fisheries impact were also identified, in this case by placing turbines in an area in the western lease with no fisheries value and high power production potential. These plans would also have a relatively low impact on the wildlife conservation sectors, due to decreases in vulnerability levels of both seabird and cetacean populations to turbines going from east to west across the WEA. Our results can inform site evaluation and permitting processes for wind energy development in the Morro Bay WEA. We also expect the tradeoff analysis framework we developed to provide a simple and actionable analytical tool for supporting marine spatial planning of offshore wind energy and other emerging blue economy activities from a balanced perspective that values emerging uses of marine resources alongside existing socio-economic and conservation interests.

The current Ukraine War underlines the importance of grain self-sufficiency. After the adoption of the Paris Agreement, two major challenges developing countries are facing in the coming decades are increasing agricultural production to ensure food security and reducing carbon emissions (CE). The key to such an “environment-development dilemma” is to improve agricultural carbon emission efficiency (CEE). Using China as the study site, we systematically analyze the impacts of agricultural management activities on agricultural CEE from 1997 to 2019. Global and local Moran's I index tests provide evidence of a positive spatial dependence of agricultural CEE. Using the LISA cluster map, we observe that high CEE regions tend to be distributed together, dominated by environmental conditions. However, with the promotion of agricultural management activities, such a clustering pattern vanished. Our spatial Durbin model (SDM) estimation results indicate that there are significant nonlinear relationships between agricultural practices and agricultural CEE. While the consumption of fertilizers and pesticides has economies of scale effects, the deployment of agricultural machinery and irrigation have diseconomies of scale effects on local CEE. Based on the SDM results, the direct and indirect effect estimation results suggest that the significant direct and spillover effects of many practices on agricultural CEE have opposite nonlinear shapes, implying a more complicated situation in promoting these activities, as the positive regional effect of an agricultural activity might have a negative impact on adjacent regions. All the results indicate that local policymakers should carefully tailor agricultural development policies based on local environmental conditions.

New policy solutions are necessary to make cities more liveable in a future that will be hampered by climate change, urbanization, landscape fragmentation and overall overexploitation of limited resources and space. There is an aspiration to continue to integrate Nature-Based Solutions (NBS) into global agendas to cope with climate change and urbanization due to their multiple benefits and co-benefits. Nevertheless, socio-economic and especially negative impacts of NBS are rarely considered and integrated into policy literature. Hence, the objective of this study is to address this gap by simulating three different policy instruments to mitigate green gentrification and enhance the impact of co-designed NBS in Genova. For that purpose, the spatially explicit hedonic pricing simulation model SULD (Sustainable Urbanizing Landscape Development) was used to simulate a linearly decreasing property tax to high-income households, a property tax subsidy provided to low and middle-income households and a zoning buffer policy around the NBS implementation area. Results show that all policy instruments have the ability to curb green gentrification, however the property tax subsidy led to added urban expansion, fostering urban sprawl. Both the zoning buffer and the property tax had better overall socio-economic and land use impacts by curbing green gentrification, posing little impact on low-income households and maintaining urban contraction, even though this contraction was smaller for the property tax instrument. Hence, it can be concluded that a policy mix including information, planning and economic instruments may be most effective to enhance the impact and mitigate green gentrification of NBS.

In this study we investigated the persistent problem of modern slave labor (MSL) in the cattle industry in the state of Pará, Brazil. We identified key characteristics of cattle ranches implicated in MSL and evaluated the efficacy of Zero-Deforestation Agreements in preventing MSL in supply chains. We found properties on the “Dirty List” for MSL tend to be larger, more forested, and faster at deforesting than other ranches. Additionally, we discovered degrading conditions and debt bondage are the predominant MSL types in the cattle sector. Our results show slaughterhouses avoid buying directly from properties with MSL. However, cattle from Dirty List properties continue to enter slaughterhouse supply chains through indirect suppliers, even those committed to Zero-Deforestation Agreements. Overall, our findings reveal the complexity of addressing labor exploitation in opaque cattle supply chains. Expanding monitoring and traceability systems, improving transparency, and providing alternative livelihoods for at-risk workers are urgently needed. Public-private collaborations show promise for strengthening enforcement and improving working conditions in the cattle industry.

This study highlights the significance of comprehending the region's caste system and cultural norms and their influence on implementing compensation and resettlement programs in hydropower projects to gain social sustainability. By leveraging Social Justice Theory, we examine how systemic inequalities affect tribal women, particularly in the context of large-scale hydropower projects. Tribal women's social and cultural identities expose them to vulnerabilities, leading to negative consequences concerning large-scale hydropower projects. The lack of access to justice and limited participation in decision-making poses social justice challenges, undermining their fundamental rights, such as basic needs, healthcare, and education. Consequently, their well-being and quality of life suffer, impeding support for such projects. The extent of these adverse effects may vary depending on whether women belong to local (Indigenous) or non-local tribes (non-Indigenous). Our analysis reveals the critical role of tribal affiliation in moderating the relationship between social justice dimensions—such as distributive, procedural, substantive, and recognition justice—and social sustainability, offering new insights into Social Justice Theory. This study explores the potential of careful planning that prioritises the needs of tribal women regardless of tribal affiliation to mitigate these negative social consequences. The study employs a social justice framework to address these challenges. Through the analysis of 511 questionnaires using PLS-SEM, the study revealed that tribal affiliation moderates the relationship between social justice and sustainability. This contribution enriches Social Justice Theory by providing empirical evidence of the intersectionality of social justice issues in the context of development projects. The study further identified that social sustainability and community satisfaction mediate the relationship between social justice and support for hydropower projects, while tribal affiliation moderates this relationship.

Even though the UN's Sustainable Development Goals emphasize improving dietary diversity and overall nutritional status globally by promoting sustainable agriculture, inadequately diversified dietary intake remains a public health problem in many low-income countries, including in Sub-Saharan Africa. The main objective of this study was to gather relevant information to gain an improved understanding of household dietary diversity and explore the role that production diversification could play within household diets and nutrition so that appropriate interventions could be implemented with the goal of enhancing nutrition-sensitive agriculture while also considering the varied features across the agroecosystems. Agroecosystem-based cross-sectional study design was employed. Data were collected predominantly through semi-structured questionnaires and analyzed by descriptive and inferential statistics, and a multilevel mixed-effect model. Results showed that the usual dietary intake of households has a monotonous pattern dominated by starchy staple foods, and consumption of fruits, vegetables, and animal-sourced foods was very limited. One out of five households had inadequate dietary diversity but varied significantly across agroecosystems. About 26% of the heterogeneity in dietary diversity was attributed due to agroecosystem level factors. In the fixed-effect part of the model, production diversification, wealth status, number of meals per day, market access, and annual mean rainfall were significantly associated with household dietary diversity status. The findings of our research contribute to give insights on the linkage between dietary diversity and production diversification among subsistence rural farmers across contrasting agroecosystem zones. Therefore, understanding agroecosystem variations and local context in the rural subsistence farming setup is a key point in designing nutrition-sensitive agriculture.

Drought is a common feature of all rangelands, which directly affects biotic life including local dwellers by various means. These drought-prone dwellers have adopted various strategies to survive in severe weather conditions. These strategies vary according to locality and depend on multiple socioeconomic factors. It is crucial to record different coping mechanisms at the local level to reduce the risks associated with recurring droughts given the forecasts of increased drought impacts in pastoral regions and other social pressures. The objective of this study is to estimate the severity of drought and look at short-term drought coping mechanisms in the Cholistan rangeland and characterize its characteristics. 320 respondents were selected from different areas of the Cholistan rangeland by using a random sampling technique. The Standardized Precipitation Index was used to estimate the severity of drought through rainfall data from 1987 to 2017, obtained from the Pakistan Council for Research in Water Resources. The results revealed that severe droughts occurred in Cholistan during the years 1999 (−10), 2002 (−11.6), 2014 (−2.69), 2015 (−2.93), and 2017 (−0.53). Migration, livestock sales, herd splitting, and destocking are the four important short-term coping strategies adopted by pastoralists before and during droughts in Cholistan rangeland with 50.4%, 27.4%, 10.3%, and 11.97% respectively. The chi-square result showed that there is a significant difference (p ≤ 0.05) in strategies adopted by pastoralists in different localities, as well as residence and herd size, and also significantly affect (p ≤ 0.05) the strategies adopted by pastoralists from the Cholistan rangelands. Drought in Cholistan is evident through various ecological and socioeconomic effects and pastoralists adopt different measures against drought by mostly relying on existing resources.

Traditional communication channels and new “human-computer interaction” spread channels are intertwined, facilitating the promote of the concept of “green for all”. This paper integrates the influence of virtual channel and physical channel attributes into the Motivation-Opportunity-Ability theory (MOA) and Theory of Planned Behavior (TPB) to explore the spread process of public green behaviors. The results show that: (1) In the composite effect, environmental responsibility (ER) and external objective factors (EOF) have no significant impact on the propagation of green behavior among the public. Both virtual channel attributes (VCA) and physical channel attributes (PCA) can accelerate the spread process of public green behavior, with PCA having the greatest impact on the propagation of public green behavior. (2) ER, VCA, PCA, EOF, and external subjective factors (ESF) can all promote the spread of public green behavior through the intermediary chain of spread motivation and spread intention. Among them, channel attributes more directly influence the spread of green behavior, and the chain mediating effect of ER through the chain was the most significant. At the same time, ESF plays a significant moderating role between the intention to spread and propagation behavior (PB), effectively bridging the gap between behavior and intention. (3) Further heterogeneity analysis shows that, compared with males, PCA has a greater promoting effect on the green behavior propagation of females, while VCA has a more significant positive effect on the green behavior propagation of the more educated public. Finally, this article examines the presence of intermediary and regulatory mechanisms among various income groups. Research has found that promoting the creation of conducive conditions for comprehensive green behavior propagation and developing targeted and mass-oriented green behavior propagation strategies by all societal stakeholders are crucial for enhancing public engagement in green practices.

The importance of global climate models (GCMs) is increasingly recognized due to their excellent ability to accurately predict climatic factors. These capabilities prove invaluable to water resources engineers as they facilitate effective planning and strategic decision-making. Finally, evaluating the performance of GCMs is very important because it allows us to simulate and predict different climate scenarios, empowering us to make informed choices. Therefore, the purpose of this study is to determine the degree of discordance between historical simulated data produced by the CMIP6 models and historical observational data over different climate zones of India. The ability of 24 different GCMs to reproduce the geographical and seasonal distribution of Indian precipitation has been tested by analyzing the daily historical precipitation forecasts from these models. These models have been used to estimate the degree of uncertainty associated with the spatiotemporal variability of precipitation forecasts. More than 20% percent bias (PBIAS) is observed to occur predominantly in four climate classifications: polar tundra, temperate, cold, and tropical monsoon. In some regions of India, the CMIP6 models produce overestimated or underestimated results. The locations identified indicate that there have been changes of more than 20% PBIAS near Sivalik Range, Naga Hills, and Western Ghats. The precipitations of those regions that have been underestimated also imply that those locations have different climatic conditions. This study also highlights that CMIP6 GCMs are yet to produce better results near several Indian mountainous regions depending upon climates. The outcomes of this study will be very useful for reconstructing modeled data for that specific regions.

Readiness is critical to adaptation to climate change and includes how organizations adjust their structures, processes, and policies for both mitigation and adaptation. Organizational learning regarding climate change is the process by which organizations and institutions acquire the knowledge, skills, and capabilities necessary to understand, manage, and adapt to the impacts of climate change. This process emphasizes continuous learning, innovation, and collaboration as key strategies for effectively responding to the ongoing climate crisis. The aim of this study was to investigate the current state of organizational learning related to climate change among the General Directorates of Natural Resources and Watershed Management in Golestan and North Khorasan provinces of Iran. The research was conducted using a survey method, through which 80 experts from two organizations were randomly selected to complete a structured questionnaire. The findings revealed that although employees have a strong attitude towards climate change, organizational learning related to climate change is weak. The five dimensions of organizational learning (knowledge acquisition, information distribution, information interpretation, organizational memory, information application) were assessed. Information interpretation had the most weight, while organizational memory had the least. Positive attitudes toward climate change were associated with increased engagement in climate change-related organizational learning. The study recommends implementing training and awareness initiatives, fostering knowledge sharing and retention, encouraging positive attitudes towards climate change, and promoting collaboration to enhance organizational learning as a prerequisite for organizational readiness to climate change.