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In recent decades, the world's population is progressively shifting towards coastal areas, and it is estimated that it could reach 1 billion by 2050. On the other hand, meteocean forcings show increasing modification in terms of the occurrence and frequency of energetic events related to climate change trends. Then, the definition of adaptation strategies is crucial to managing coastal areas, especially in the most densely populated or highly valued tourist and environmental areas. Meaningful long-term strategies should then be based on quantitative estimation of future scenarios in a changing climate. Although most of the studies in the literature focus on extreme events, this paper aims to assess, through synthetic indicators, whether and how average and mild energy conditions related to wave climate will vary considering the current situation compared to future projections. The study is based on the analysis of wave data. The projection of average and mild energy conditions can indeed influence, just for example, the long-term morphodynamics of sandy beaches and the quality of bathing waters. Data extracted from the Copernicus database are considered. The methodology has been applied to the case of Sardinia island at a regional scale. Then, the aim of this paper is twofold: on the one hand, a method is proposed to evaluate the variation of average and mild wave conditions; on the other hand, it aims to apply the method to the case study of the Sardinia coastal area to highlight its feasibility. Results confirm that variations are expected. In the analyzed case study, it emerges that, on average, the long-term evolution of the wave climate shows a tendency toward intensification, while a decrease in the frequency of calm conditions is estimated. The average annual number of events undergoes an increase. Moreover, changes in wave directional sectors are observed, which, from being unimodal, are estimated to exhibit bimodal characteristics in particular on the west coast of the island. [ABSTRACT FROM AUTHOR]

The climate change process is leading to an increase in the sea level and the storm intensity. The associated shoreline recession can damage coastal facilities and also beaches protected by submerged/emerged breakwaters whose defense action can become ineffective. The application of cross-shore numerical models does not allow the performance of long-term analyses. In this paper, a semi-analytical model for the evaluation of shoreline recession due to waves and sea-level rise for free and protected beaches is proposed. The model is an extension of the Dean's approach in which some limitations on the beach profile are overcome and the effects of breakwaters on the wave height (wave transmission) and on the water level (piling-up) are considered. The model takes into account a wide range of parameters for wave, sea level, beach profile, and breakwater characteristics. Among the breakwater parameters, the freeboard and the berm width are found to mainly affect the shoreline recession. For submerged breakwaters, an optimal value of the freeboard can be computed depending on the sea level and the offshore wave characteristics. The results of the model are then used to find prediction relations of the shoreline recession, with r2 > 0.99, for both free and protected beaches, depending on the main hydrodynamic/geometrical characteristics. [ABSTRACT FROM AUTHOR]

In the face of geopolitical challenges and climate change, economic progress, safe production, and environmental protection have emerged as important directions for chemical industry development. However, the rational optimization of the chemical industry layout under the backdrop of ecological environmental protection necessitates further exploration. This study explores the evolution and future development direction of the chemical industry layout within the coastal region of Jiangsu Province, China, using the CA–Markov model. The findings reveal a trend of spatial agglomeration growth among coastal chemical enterprises, with Moran's Index increasing from 0.109 in 2007 to 0.206 in 2017. The petrochemical industry, in particular, demonstrated the most significant agglomeration effect, with approximately 52.10% being concentrated in 14 coastal industrial parks in 2017. Under the constraints of the ecological environment and policy guidance, the land area allocated for the chemical industry experienced a reduction of over 10%, further strengthening the emphasis on spatial agglomeration. Chemical industries along Jiangsu's coast have become agglomerated and concentrated near industrial parks and ports. Their spatial distribution and connectivity were mainly influenced by factors such as convenient transportation, the ecological environment, local policies, the distance from residential areas, and industrial agglomeration. Under different scenarios—including natural growth, ecological environment constraints, and policy guidance—chemical industries show diverse spatial patterns. Ecological environmental constraints and policy guidance can provide various intervention methods for the government to promote the optimization direction and focus of the chemical industry layout while minimizing its impact on the ecological environment. [ABSTRACT FROM AUTHOR]

In the face of environmental change, high-quality and fine-scale information is essential in order to monitor the highly dynamic environments on land and sea. While traditional approaches to data collection face a number of practical limitations, advanced technologies could supplement and further improve our efforts. Taking sea turtles as a modeling organism, we present a novel methodological framework for monitoring species by means of advanced technologies, including Unmanned Aerial Vehicles coupled with image and temperature sensors. Diverse monitoring protocols were refined through pilot studies conducted in both terrestrial and nearshore sea turtle habitats. Our approach focuses on the collection of information for critical biological parameters concerning species reproduction and habitat use, following the complex life cycle of the species. Apart from biological information, our framework encompasses also the collection of information on crucial environmental factors that might be changing due to current and future human-derived pressures, such as beach erosion and temperature profile, as well as highly important human activities such as recreational use within nesting beaches that could undermine habitat quality for the species. This holistic and standardized approach to monitoring using advanced technologies could foster our capacity for conservation, resolving difficulties previously addressed and improving the collection of biological and environmental data in the frame of an adaptive management scheme. [ABSTRACT FROM AUTHOR]

Wind erosion is recognized as one of the main environmental issues and seriously threatens ecosystem services in the Yarlung Zangbo River basin (YZRB), southern Tibetan Plateau. Exploring the spatiotemporal dynamics and drivers of wind erosion is crucial for improving regional ecosystem services and sustainable development. This study was conducted to examine the spatiotemporal patterns of soil wind erosion modulus (SWEM) in YZRB from 1990 to 2020 by using the revised wind erosion equation (RWEQ) and to identify the influence of climate change and anthropogenic activities on wind erosion dynamics. The results showed that temporally, the overall SWEM presented a significant downward trend (−0.912 t·hm−2·a−1) and a continuous downward trend in the key implementation areas of ecological engineering. Spatially, the severe area of wind erosion is mainly concentrated in the flat and broad river valley, where sand sources are widely distributed. Significant SWEM differences were found among various land use/cover (LULC) types. Exceeding 90% reduction rates in SWEM occurred in forests, grasslands, and cultivated land. Additionally, the influence analysis showed that climate change was the dominant factor driving the variations in wind erosion due to the reduction of wind speed. By contrast, the contribution of anthropogenic activities is relatively less, accounting for 43.50% of wind erosion change, which closely matches the transfer of LULC to grassland and forest land with the implementation area of ecological engineering projects. This study provides useful information on the driving mechanism of wind erosion, prevention service changes, and determining priority zones for desertification prevention in YZRB. We suggest that eco-restoration activities should be endorsed in the future, as well as the adaptive management that is required to control wind erosion and improve ecosystem services and human well-being for people in the YZRB region. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is one of the most important areas for the study of the carbon budgets of terrestrial ecosystems. However, the estimation of the net ecosystem productivity (NEP) remains uncertain in this region due to its complex topographic properties and climatic conditions. Using CO2-eddy-covariance-flux data from 1982 to 2018 at 18 sites distributed around the TP grassland, we analyzed the spatial–temporal patterns of the grassland NEP and its driving factors from 1982 to 2018 using a random forest (RF) model. Our results showed that the RF model captured the size of the carbon sink (R2 = 0.65, p < 0.05) between the observed and simulated values for the validation samples. During the observation period, the grassland acted as a carbon sink of 26.2 Tg C yr−1 and increased significantly, by 0.4 g C m−2 yr−1. On a regional scale, the annual NEP gradually increased from the northwest to the southeast, and a similar pattern was also observed in the long-term trends. Furthermore, the moisture conditions, such as the specific humidity and precipitation, were proven to be the main driving factors of the carbon flux in the southeastern areas, while the temperature predominantly controlled the carbon flux in the northwest. Our results emphasize the net carbon sink of the TP and provide a reliable way to upscale NEP from sites. [ABSTRACT FROM AUTHOR]

Climate change has had a significant impact on the tourism industry in many countries, leading to changes in policies and adaptations to attract more visitors. However, there are few studies on the effects of climate change on Sri Lanka's tourism industry and income, despite its importance as a destination for tourists. A study was conducted to analyze the holiday climate index (HCI) for Sri Lanka's urban and beach destinations to address this gap. The analysis covered historical years (2010–2018) and forecasted climatic scenarios (2021–2050 and 2071–2100), and the results were presented as colored maps to highlight the importance of HCI scores. Visual analysis showed some correlation between HCI scores and tourist arrivals, but the result of the overall correlation analysis was not significant. However, a country-specific correlation analysis revealed interesting findings, indicating that the changing climate can be considered among other factors that impact tourist arrivals. The research proposes that authorities assess the outcomes of the study and conduct further research to develop adaptive plans for Sri Lanka's future tourism industry. The study also investigated potential scenarios for beach and urban destinations under two climate scenarios (RCP 4.5 and RCP 8.5) for the near and far future, presenting the findings to tourism industry stakeholders for any necessary policy changes. As Sri Lanka expects more Chinese visitors in the future due to ongoing development projects, this study could be valuable for policymakers and industry stakeholders when adapting to changing climate and future tourist behavior. While more research is needed to fully understand the effects of climate change on Sri Lanka's tourism industry, this study serves as a starting point for future investigations. [ABSTRACT FROM AUTHOR]

This article provides a general methodology for calculating the retreat of the coastline and the volume of sand necessary to renourish a beach due to sea level rise (SLR) in the medium-long term. An example is presented, Victoria Beach, and a projection is made for the years 2030, 2040, 2050, and 2100. The results obtained take into account global sea level rise (GSLR), which is worldwide, and local sea level rise (LSLR), which considers climate variability and vertical land movements. Regarding GSLR, data were provided by the projections from IPCC (Intergovernmental Panel on Climate Change) scenarios and empirical models, such as Rahmstorf and Pfeffer. The LSLR data came from the tide gauge station located in Cadiz. Finally, the results obtained showed that global warming impacts erosive effects and the subsequent volume of sand required to renourish beaches. The total sea level rise (TSLR) projections indicated for Victoria Beach are relatively higher than the GSLR projections. Even in the best IPCC scenario (RCP 2.6), Victoria Beach presents a significant erosion of 52 m, requiring a volume of sand of 1.0 Mm3 to supply renourishment. [ABSTRACT FROM AUTHOR]