Environmental and Sustainability Indicators最新文献

Global greenhouse gases and carbon dioxide emissions have escalated to concerning levels. Given the growing urbanization, industrialization, and energy consumption, it is crucial to understand how carbon dioxide emissions from various sectors influence environmental sustainability in Pakistan. The prime objective of this study is to examine the nexus between sectoral carbon dioxide emissions and environmental sustainability in Pakistan, analyzing data from 1971 to 2014. The study employs the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) method and the Autoregressive Distributive Lag (ARDL) model to analyze patterns and relationships, providing insights into how each sector's emissions contribute to the overall environmental impact. The results highlight that the independent variables – economic growth, population growth, and energy consumption - are the most significant contributors to overall carbon dioxide emissions, driven by the high consumption of fossil fuels. At an aggregate/disaggregate level, various models show mixed associations between dependent variables such as overall carbon dioxide emissions, carbon dioxide emissions from gaseous fuel consumption, carbon dioxide emissions from liquid fuel consumption, carbon dioxide emissions from solid fuel consumption, carbon dioxide emissions from residential buildings, commercial and public services, and carbon dioxide emissions from the transportation sector with the independent variables. Pairwise Granger causality confirms a unidirectional causality among various pairs of relationships. The study suggests that policymakers in Pakistan adopt a multi-sectoral approach to achieve environmental sustainability. It also recommends accelerating the transition to renewable energy sources such as solar, wind, and hydropower to reduce dependence on fossil fuels.

The world has witnessed serious climate-related problems. Even though there are various effective factors in this point, sustainable resource consumption takes place among critical factors that have been deeply affecting climate change. Accordingly, Sustainable Development Goals (SDGs) 8–12 have come to the fore for all related parties due to the directly affecting resource use. Among all, Gulf Cooperation Council (GCC) countries have a special position in terms of global climate change-related goals because they have high oil and resource consumption. Hence, this study firstly attempts to investigate the validity of the environmental Kuznets curve (EKC) hypothesis for material footprint (MAF) in GCC countries by analyzing the impact of income, energy consumption, financial institution development, and technological development, performing augmented mean group model, and using data for the period 2000–2019. The findings show that (i) the EKC hypothesis is valid for the GCC panel, whereas it is the case for only Oman on a country basis; (ii) energy consumption increases (decreases) MAF at GCC panel (Qatar); (iii) financial institution development does not affect MAF in the GCC panel, while it causes an increase in Saudi Arabia; (iv) technological development reduces MAF at GCC panel and in Bahrain, Kuwait, and Saudi Arabia on a country basis. Thus, the results highlight the need for GCC countries to focus on both income level and technological development to achieve climate-related targets and SDGs by decreasing resource-based consumption.

The Low-Carbon City Pilot (LCCP) program in China is a climate policy implemented at the city level, and its impact on the development of corporate artificial intelligence (AI) remains to be studied. The LCCP program aims to promote low-carbon transformation in multiple Chinese cities and serves as a quasi-natural experiment to determine whether similar city-level climate policies can foster the development of corporate AI. This study employs a multi-period differences-in-differences (DID) approach to evaluate the impact of China’s LCCP program on the development of corporate AI. By redirecting attention from national-level policies to city-level initiatives, this study provides unique insights into the localized effects of climate policies on technological innovation within firms. The research findings indicate that the LCCP program has a significant promoting effect on the development of corporate AI. These results underscore the potential of city-level climate policies, such as the LCCP program, to drive advancements in corporate AI technologies. By demonstrating a positive correlation between the implementation of the LCCP program and increased levels of AI development within companies, the study provides valuable insights into the intersection of environmental policies and technological innovation. Policymakers and businesses can use these findings to guide the design and implementation of initiatives aimed at promoting sustainable economic growth through enhanced AI adoption. This study not only contributes to the academic discourse on environmental policy and technological innovation but also offers practical recommendations for achieving a balance between environmental sustainability and technological advancement.

Digital and smart technologies (DSTs¹) for agriculture are currently widely discussed in the literature and increasingly included in common farming practices. However, the main agricultural use of DSTs remains yield-increasing and effort-reducing applications focused on the economic advantages of precision. The potential of DSTs to enhance biodiversity in agricultural landscapes has rarely been examined, especially from the stakeholder perspective. In this study, we examined the barriers to and potential for using DSTs to promote biodiversity in agricultural areas in Germany. For this purpose, we conducted a nationwide stakeholder acceptance analysis based on an online survey and an expert discussion. Our analysis revealed the notable potential of DSTs to strengthen biodiversity in agricultural landscapes, which is, however, accompanied by critical barriers to the broad acceptance and regular use of such technologies by farmers. Only if based on adequate legal and financial political framework, which create incentives for solution-focused cooperation among all relevant stakeholders and allow a user-orientated technology development, can DSTs develop their underlying potential and gain acceptance among farmers.

The present study attempted to quantify and value of supporting services of India's forest ecosystem. The supporting services comprises by habitat and biodiversity services across India's sixteen forest types was estimated using data for various factors through Remote Sensing and secondary sources as per the proposed model. Indicators were combined using an Analytical Hierarchical Process, and various class of each service was also estimated using the equal interval method in QGIS. Hotspot analysis was used to identify key areas for forest conservation. The results suggest that littoral and swamp forest had maximum habitat services and tropical semi-evergreen forest had maximum biodiversity service and tropical wet evergreen forest had maximum supporting services. Out of total forest of country, 11.52%, 17.48% and 10.34% forest area was having high value for habitat, biodiversity and supporting service, respectively. Hotspot analysis revealed that 22.93%, 23.61% and 26.44% Indian forest had high habitat, biodiversity and supporting service, respectively. The annual per hectare economic value using Benefit Transfer method for habitat, biodiversity and supporting services of forests was US$ 4330.71, US$ 5987.38 and US$ 10,624.23, respectively. The annual economic value of habitat, biodiversity and supporting services from Indian forests was US$ 303,506.09 million, US$ 419,609.45 million and US$ 744,570.85 million, respectively. In totality, tropical dry deciduous forest, tropical moist deciduous and tropical semi-deciduous forest had high economic value for supporting service. Monetary valuation of forest ecosystem services assists to determine the net present value and costs for conservation interventions. Biodiversity hotspots as the Western Ghats, Indo-Burma region, and Eastern Himalayas offer high ecosystem service and thus attach prime importance for conservation, while the Western Himalayas, with lower ecosystem service, requires customized ecosystem management strategies.

Ecosystem services are crucial for human survival and development. Changes in land use can lead to alterations in ecosystem service functions. However, the mechanism of how land use changes resulting from underground coal mining affect ecosystem service remains unclear, especially in areas with high groundwater levels. To address this issue, we studied the spatiotemporal in land use change in Jining City from 2000 to 2020 and employed Markov-PIM (probability integration method)-PLUS (Patch-generate Land Use Simulation) model to simulate land use change and ecosystem service values (ESV) in Jining City by 2030 under four different scenarios. The results indicate that from 2000 to 2020, the area of ecological space increased by 169.99 km², and the area of living space expanded by 775.28 km², while the area of production space decreased by 945.27 km², conversely. These changes led to a 3 million yuan increase in total ESV. From 2020 to 2030, there was a marked decline in ESV under both natural development (ND) and living space preference (LSP) scenarios, with decreases of 0.59 billion yuan and 1.38 billion yuan, respectively. In contrast, in production space preference (PSP) and ecological space preference (ESP) scenarios, ESV increase by 0.22 billion yuan and 0.34 billion yuan. The ESP scenario is an effective strategy to strengthen environmental protection, significantly improve the ESV level of Jining City and meet the development goals of Jining City. Finally, the study concludes with recommendations like comprehensive management, industrial upgrading, and collaborative development for optimizing Jining City's future land use and enhance ESV for urban development.

Sustainable development of countries necessitates parallel enhancements of societal wellbeing and reductions of environmental impacts. To track how countries perform to achieve these twin objectives, we introduce and calculate a novel metric called the Just Transition Score (JTS) that aims to assess countries' relative sustainability of social progress. Based on the content of environmental impacts per unit of progress, we calculate the JTS for 161 countries from 2011 to 2019. Additionally, we break down the aggregate indicator into two main components, namely the Carbon Just Transition Score, and the Material Just Transition Score. The results show significant disparities across countries both in terms of the overall JTS and its components. Countries with the best JTS performance, such as Portugal, Spain, and Costa Rica achieve the most sustainable social progress, while countries with the lowest JTS scores either fall short on social progress (the poorest countries) or create high environmental damage (such as the Gulf countries). The relative sustainability of social progress of poorer countries can be improved by increasing societal wellbeing while limiting growth of their environmental impacts. In richer countries, improvements would require more aggressive measures aimed at reducing the extent of environmental damage.

Place-based socio-economic and biophysical context has been viewed as an essential driver in shaping perceptions of forest risks and land management. Growing evidence of the importance of diverse community context in forested landscapes sets the stage to further consider how people's understandings of their local environment influence natural resource management preferences. However, research to date largely lacks considerations of how community context informs social responses to long-term environmental change over time. Using the mountain pine beetle (MPB) outbreak in Colorado, we analyze and compare longitudinal interview and survey data collected from nine north-central Colorado communities to understand the relationships between community context and changing perceptions of forest disturbance and engagement with land management. Both qualitative and quantitative findings show that community context framed and continues to inform variations in local perceptions of the MPB outbreak and forest management. Interviews with key informants provided rich narratives on different context-based trajectories in local residents' perceptional responses, while survey data allowed for general patterns of evolving community variations (e.g., stable or clearer community clustering, reduced community differences) to be uncovered. We explore methodological implications for community indication and future directions for understanding differing community responses to slow-moving environmental change. Incorporating knowledge of changing local contexts and variations can also help practitioners advance toward more dynamic and effective management strategies.

The Sustainable Development Goal (SDG) seven highlights the need to ensure access to affordable, reliable, sustainable, and modern energy for all. Improving access to reliable and affordable modern energy for cooking have far-reaching benefits on human health and the environment. In most developing countries, the use of solid biomass fuel (SBF) for cooking is widespread. Using a nationally representative household-level data from Ghana and the biprobit model, this paper examines the relationship between SBF and ill-health. The first stage results show that the adoption of SBF is significantly influenced by socio-economic factors, rental and dwelling status, food hardship, information about SBF, and geographical controls. The adoption of SBF for cooking increases the probability of a household reporting ill-health and frequently reporting ill-health by 25% each, respectively. The differential analysis indicates that charcoal has a moderate effect on ill-health relative to using wood as fuel for cooking. The findings of the study imply that households are more likely to improve their health with increasing affordability and use of clean cooking fuels. Government programs on the promotion of clean energy fuels must be intensified and make more accessible and affordable to households.

Enhancing environmental quality has become one of the most commonly discussed topics in the modern world, particularly in response to the challenges posed by the increasing threats to climate change. The financial system is acknowledged as a crucial factor in achieving environmental quality by facilitating the flow of financial resources. This study aims to examine the impact of a unique aspect of the financial system—financial market development—on environmental quality in Australia. What sets this study apart from existing works is its comprehensive approach, capturing broader measures of financial market development, including financial market depth, access, efficiency, and stability. By employing the Autoregressive Distributive Lag (ARDL) model over the period from 1983 to 2021, our research demonstrates a positive impact of market-based financial development on Australia's environmental quality by reducing greenhouse gas emissions in the long run. Specifically, an opposing impact of financial market development on environmental quality is evident in the short run. Our findings highlight that financial market development degrades environmental quality in the short run by contributing to increased greenhouse gas emissions, which further emphasizes the importance of integrating both the positive and negative effects of financial market development in policymaking, particularly in the context of achieving Australia's environmental targets.