In the current context of rapid development and urbanization, land use and land cover (LULC) types have undergone unprecedented changes, globally and nationally, leading to significant effects on the surrounding ecological environment quality (EEQ). The urban agglomeration in North Slope of Tianshan (UANST) is in the core area of the Silk Road Economic Belt of China. This area has experienced rapid development and urbanization with equally rapid LULC changes which affect the EEQ. Hence, this study quantified and assessed the spatial-temporal changes of LULC on the UANST from 2001 to 2018 based on remote sensing analysis. Combining five remote sensing ecological factors (WET, NDVI, IBI, TVDI, LST) that met the pressure-state-response(PSR) framework, the spatial-temporal distribution characteristics of EEQ were evaluated by synthesizing a new Remote Sensing Ecological Index (RSEI), with the interaction between land use change and EEQ subsequently analyzed. The results showed that LULC change dominated EEQ change on the UANST: (1) From 2001 to 2018, the temporal and spatial pattern of the landscape on the UANST has undergone tremendous changes. The main types of LULC in the UANST are Barren land and Grassland. (2) During the study period, RSEI values in the study area were all lower than 0.5 and were at the [good] levels, reaching 0.31, 0.213, 0.362, and 0346, respectively. In terms of time and space, the overall EEQ on the UANST experienced three stages of decline-rise-decrease. (3) The estimated changes in RSEI were highly related to the changes of LULC. During the period 2001 to 2018, the RSEI value of cropland showed a trend of gradual increase. However, the rest of the LULC type's RSEI values behave differently at different times. As the UANST is the core area of Xinjiang's urbanization and economic development, understanding and balancing the relationship between LULC and EEQ in the context of urbanization is of practical application in the planning and realization of sustainable ecological, environmental, urban, and social development in the UANST.
Solar cells are considered one of the most important and widespread solar applications in the world. However, the performance of the PV modules is significantly affected by the dust in the air. This paper, therefore, presents a comparison of an outdoor experimental study of dust effect on monocrystalline, and polycrystalline photovoltaic (PV) modules. For analysis, four 100 W PVs were installed horizontally in Sohar, Oman. For each pair of PV modules, one was left dusty due to environmental impact, and the second was cleaned daily. PV performance and environmental parameter measurements were conducted every 30 min for 35 days. The effects of dust on current, voltage, power, and energy were discussed in terms of time and normalized values. Also, cleaning methods were tested to determine the optimum one. It is found that power degradation of monocrystalline (20%) is higher compared with polycrystalline (12%) due to dust accumulation. For monocrystalline, the current, voltage, and power losses ranged between 10.0-24.0%, 2.0-3.5%, and 14.0-31.0%, respectively. However, for polycrystalline, the degradation rates were 16.88-27.92%, 0.455-0.455%, and 17.14-28.1% for current, voltage, and power losses after exposure to outdoor conditions for the same period, respectively. The dust accumulation on the PV surface found after 5 weeks is 0.493 mg/cm2, which can be considered the lowest accumulation rate compared to other Gulf countries, but which, however, leads to less energy degradation as well. It is found that water is sufficient to clean PV in the study area. However, sodium detergent as a cleaner introduced better results compared to water, especially when there is high pollution in the location.
For the purpose of this study, the role of technological innovation is examined. Few studies have examined empirically and theoretically the relationship between technological innovation and ecological footprint in conjunction with other factors, such as the human capital index and renewable energy sources, such as biofuels and nuclear power. This study examines the impact of technological innovation on G-7 countries' ecological footprints from 1990 to 2020. A cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model is used in the study. The results of the study show that technological innovation minimizes the ecological footprint. A lower ecological footprint is also associated with increased usage of human capital and renewable energy. Depletion of the natural environment is a short-term and long-term consequence of increased GDP growth. Our results confirm that ecologically sustainable technology enhances the quality of the environment. Consistent panel causality results were achieved. In the context of the G-7 countries, our study's results could support the idea that there are new policy ideas that could help achieve the Sustainable Development Goals (SDG 3, 4, 7, 8, 9, and 13).
The embodied carbon of building materials and the energy consumed during construction have a significant impact on the environmental credentials of buildings. The structural systems of a building present opportunities to reduce environmental emissions and energy. In this regard, mass timber materials have considerable potential as sustainable materials over other alternatives such as steel and concrete. The aim of this investigation was to compare the environment impact, energy consumption, and life cycle cost (LCC) of different wood-based materials in identical single-story residential buildings. The materials compared are laminated veneer lumber (LVL) and glued laminated timber (GLT). GLT has less global warming potential (GWP), ozone layer depletion (OLD), and land use (LU), respectively, by 29%, 37%, and 35% than LVL. Conversely, LVL generally has lower terrestrial acidification potential (TAP), human toxicity potential (HTP), and fossil depletion potential (FDP), respectively, by 30%, 17%, and 27%. The comparative outcomes revealed that using LVL reduces embodied energy by 41%. To identify which of these materials is the best alternative, various environmental categories, embodied energy, and cost criteria require further analysis. Therefore, the multi-criteria decision-making (MCDM) method has been applied to enable robust decision-making. The outcome showed that LVL manufacturing using softwood presents the most sustainable choice. These research findings contribute to the body of knowledge about the use of mass timber in construction.
Rapid increases in energy consumption and economic growth over the past three decades are considered the driving force behind rising environmental degradation, which remain a threat to people and healthy environment. This study investigates the impact of energy consumption on environmental quality in the MINT countries using a panel PMG/ARDL modelling technique, and the Granger causality test spanning from 1971 to 2017. The empirical results confirm the existence of long-run nexus among the variables employed. The results also reveal that economic growth, energy consumption and bio-capacity have a positive and statistically significant effect on environmental degradation during the long run period. We find that a 1% increase in primary energy consumption leads to 0.4172% increase in environmental deterioration in the long-run period, but it is insignificant in the short run. This implies that energy consumption deteriorates environmental quality through a negative effect of ecological footprint. The result also suggests that as MINT countries increase the use of energy to accelerate pace of economic growth, environmental quality would deteriorate through increased ecological footprints. The coefficient of the error correction term (ect) is negative and significant (- 0.2306), suggesting that ecological footprint, a measure of environmental degradation would converge to its long-run equilibrium in the MINT region by 23.06% speed of adjustment every year due to contribution of economic growth, energy consumption, urbanization and biocapacity. The Granger non-causality test results reveal a unidirectional causal relationship from economic growth, energy consumption, and urbanization to ecological footprint and from economic growth to biocapacity. The results further show bi-directional causality between biocapacity and ecological footprint as well as between biocapacity and economic growth. Moreover, urbanization causes economic growth and biocapacity Granger-causes urbanization. Based on these findings, policy implications are adequately discussed.
Green finance can promote economic transformation and technological innovation and play a key role in solving the ecological environment and energy crisis. This paper constructs a comprehensive ecological livable environment evaluation system based on the provincial panel data in China from 2011 to 2019. At the same time, the panel mediation effect and spatial econometric model are used to test the impact of green finance on the ecological and livable environment. The main research conclusions include the following: (1) green finance has significantly improved China's ecological and livable environment; (2) green finance improves the ecological and livable environment by improving the level of technological innovation; (3) the impact of green finance on the ecological livable environment has regional heterogeneity, and green finance in the central provinces has a better effect on the improvement of the ecological livable environment; and (4) the ecological livable environment among Chinese provinces has a significant positive spatial correlation. Among them, green finance has significantly improved the local ecological livable environment but reduced the ecological livable environment of surrounding provinces. Based on the above conclusions, this paper suggests that the government should pay more attention to green finance and technological innovation and coordinate the development of the ecological livable environment among provinces. The research results provide empirical evidence for better developing green finance and improving the ecological livable environment and also provide certain theoretical guidance for China's coordinated regional development and high-quality economic development.
The study is aimed at investigating the impact of waste management in the context of Industry 4.0 and sustainable development. Data were collected from 257 production managers in the industrial sector using a survey questionnaire and analyzed using SPSS and PLS-SEM. The findings indicated that Industry 4.0 and waste management significantly contribute to achieving sustainable development. The integration of Industry 4.0 technologies and effective waste management practices can help organizations implement sustainable development goals. Practical implications include assisting organizations in implementing Industry 4.0 technologies and waste management strategies based on the 3Rs principle. This can lead to reduced environmental impacts and improved resource efficiency, contributing to sustainable development. Policymakers can also benefit from the study's insights to address waste management challenges and promote sustainable development. The study's originality lies in its incorporation of the cyber-physical system and niche theory to explore how Industry 4.0 can facilitate sustainable waste management. It highlights the transformative potential of Industry 4.0 in the industrial sector, particularly in developing countries. Overall, this research offers a unique contribution to understanding waste management within the context of Industry 4.0 and sustainable development.
The connection between ecological footprint and economic complexity has significant implications for environmental sustainability regarding the policy. Additionally, institutional quality is crucial in ensuring environmental sustainability and moderating the link between economic complexity and ecological footprint. The task of achieving sustainable environmental development and preventing further degradation of the environment poses a formidable challenge to policymakers. This study delves into the significance of technology innovation and renewable energy in creating a more sustainable environment. Recognizing the need for a more critical review, this research establishes the dynamic linkage between ecological footprint, renewable energy consumption, and technological innovation, especially in conjunction with a moderating component, particularly institutional quality, in G20 countries from 1990 to 2021. We employ advanced panel approaches to address panel data analysis concerns, such as cross-sectional dependence, slope heterogeneity, unit root, cointegration test and CS-ARDL. The long-term estimator indicates that renewable energy and technological innovation negatively but significantly impact the ecological footprint. Whilst economic growth, FDI, and urbanization have shown a positive and significant impact on ecological footprint; institutional quality negatively moderates the relationship between ecological footprint, renewable energy, and technological innovation in the G20 countries. Further evidence from the Dumitrescu-Hurlin Granger causality test shows that efforts to expand access to renewable energy, technological advancements, and economic growth will significantly affect environmental impacts. Based on our results, it is imperative to introduce more favorable legislation and encourage technological advancements in the field of renewable energy if we want to achieve our sustainable development objectives.
Estimating the asymmetrical influence of foreign direct investment is the primary goal of the current study. In addition, further controlled variables affect environmental degradation in OIC nations. Due to this, current research employs the asymmetric (NPARDL) approach and the data period from 1980 to 2021 to estimate about viability of the EKC (environmental Kuznets curve) theory. The study utilized greenhouse gas (GHG) including emissions of carbon dioxide (CO2), nitrous oxide (N2O), methane (CH4), and ecological footprint as substantial parameters of environmental quality. A nonlinear link between foreign direct investments, trade openness, economic growth, urbanization, energy consumption, and environmental pollution with CO2, N2O, CH4, and ecological footprint in the OIC nations is confirmed by the study's outcomes, which however reveals inconsistent results. Furthermore, the results also show that wrong conclusions might result from disregarding intrinsic nonlinearities. The study's conclusions provide the most important recommendations for decision-makers.
Mangroves provide essential ecosystem services including coastal protection by acting as coastal greenbelts; however, human-driven anthropogenic activities altered their existence and ecosystem functions worldwide. In this study, the successive degradation of the second largest mangrove forest, Chakaria Sundarbans situated at the northern Bay of Bengal part of Bangladesh was assessed using remote sensing approaches. A total of five multi-temporal Landsat satellite imageries were collected and used to observe the land use land cover (LULC) changes over the time periods for the years 1972, 1990, 2000, 2010, and 2020. Further, the supervised classification technique with the help of support vector machine (SVM) algorithm in ArcGIS 10.8 was used to process images. Our results revealed a drastic change of Chakaria Sundarbans mangrove forest, that the images of 1972 were comprised of mudflat, waterbody, and mangroves, while the images of 1990, 2000, 2010, and 2020 were classified as waterbody, mangrove, saltpan, and shrimp farm. Most importantly, mangrove forest was the largest covering area a total of 64.2% in 1972, but gradually decreased to 12.7%, 6.4%, 1.9%, and 4.6% for the years 1990, 2000, 2010, and 2020, respectively. Interestingly, the rate of mangrove forest area degradation was similar to the net increase of saltpan and shrimp farms. The kappa coefficients of classified images were 0.83, 0.87, 0.80, 0.87, and 0.91 with the overall accuracy of 88.9%, 90%, 85%, 90%, and 93.3% for the years 1972, 1990, 2000, 2010, and 2020, respectively. By analyzing normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), and transformed difference vegetation index (TDVI), our results validated that green vegetated area was decreased alarmingly with time in this study area. This destruction was mainly related to active human-driven anthropogenic activities, particularly creating embankments for fish farms or salt productions, and cutting for collection of wood as well. Together all, our results provide clear evidence of active anthropogenic stress on coastal ecosystem health by altering mangrove forest to saltpan and shrimp farm saying goodbye to the second largest mangrove forest in one of the coastal areas of the Bay of Bengal, Bangladesh.
Environmental sustainability is a key target to achieve sustainable development goals (SDGs). However, achieving these targets needs tools to pave the way for achieving SDGs and COP28 targets. Therefore, the primary objective of the present study is to examine the significance of clean energy, research and development spending, technological innovation, income, and human capital in achieving environmental sustainability in the USA from 1990 to 2022. The study employed time series econometric methods to estimate the empirical results. The study confirmed the long-run cointegrating relationship among CO2 emissions, human capital, income, R&D, technological innovation, and clean energy. The results are statistically significant in the short run except for R&D expenditures. In the long run, the study found that income and human capital contribute to further aggravating the environment via increasing CO2 emissions. However, R&D expenditures, technological innovation, and clean energy help to promote environmental sustainability by limiting carbon emissions. The study recommends investment in technological innovation, clean energy, and increasing R&D expenditures to achieve environmental sustainability in the USA.
The present study aimed to examine whether physical and environment elements of PETTLEP imagery relate to the ability to image five types of sport imagery (i.e. skill, strategy, goal, affect and mastery). Two hundred and ninety participants (152 males, 148 females; Mage = 20.24 years, SD = 4.36) from various sports completed the Sport Imagery Ability Questionnaire (SIAQ), and a set of items designed specifically for the study to assess how frequently participants incorporate physical (e.g. 'I make small movements or gestures during the imagery') and environment (e.g. 'I image in the real training/competition environment') elements of PETTLEP imagery. Structural equation modelling tested a hypothesised model in which imagery priming (i.e. the best fitting physical and environment elements) significantly and positively predicted imagery ability of the different imagery types (skill, β = 0.38; strategy, β = 0.23; goal, β = 0.21; affect, β = 0.25; mastery, β = 0.22). The model was a good fit to the data: χ2(174) = 263.87, p
This study was designed to optimize the culture conditions of juvenile Epinephelus fuscoguttatus (Forsskål, 1775) under laboratory conditions. To this effect, the rate of oxygen consumption was monitored as an index of stress under different temperature, salinity, pH, photoperiod, and urea concentrations. The result obtained after 12 h of exposure suggests the preference of the juvenile E. fuscoguttatus to a temperature range of 15-25 °C and salinity of 30 ppt. Based on this study, temperature was found to be the most lethal as 100% mortality was observed after 6 h in fish exposure to temperatures above the optimal (≥ 30 °C). However, the oxygen consumption rate was similar under the different pH, photoperiod, and urea concentration tested. It was concluded that water temperature was most critical in terms of respiration physiology of the juvenile E. fuscoguttatus given the range and levels of environmental factors tested in this study.
Data are presented from a long-term study of banded langurs in three contrasting rain forest habitats in Peninsular Malaysia. Results from different sites and months are used to correlate ranging patterns with food availability and other environmental variables. Day range lengths are correlated with availability of preferred foods; the degree of territoriality is related to the distribution and size of food sources and length of time for which any one of these produces favoured food items.
Sympatric gibbon species Hylobates lar and H. syndactylus were censused on a mountain in Malaya (West Malaysia). Habitat quality was assessed between 380- and 1,525-m altitudes. H. syndactylus was found to occur up to altitudes higher than does H. lar, and this is discussed with reference to the two species' divergent foraging strategies indicated by previous research. It is suggested that gibbons are restricted in their altitudinal range by an increasingly unfavourable ratio of food consumed to energy expended in its location, caused by a reduced food-source density and more difficult terrain at higher elevations.
The extent to which genetic gain achieved from selection programs under strictly controlled environments in the nucleus that can be expressed in commercial production systems is not well-documented in aquaculture species. The main aim of this paper was to assess the effects of genotype by environment interaction on genetic response and genetic parameters for four body traits (harvest weight, standard length, body depth, body width) and survival in Red tilapia (Oreochromis spp.). The growth and survival data were recorded on 19,916 individual fish from a pedigreed population undergoing three generations of selection for increased harvest weight in earthen ponds from 2010 to 2012 at the Aquaculture Extension Center, Department of Fisheries, Jitra in Kedah, Malaysia. The pedigree comprised a total of 224 sires and 262 dams, tracing back to the base population in 2009. A multivariate animal model was used to measure genetic response and estimate variance and covariance components. When the homologous body traits in freshwater pond and cage were treated as genetically distinct traits, the genetic correlations between the two environments were high (0.85-0.90) for harvest weight and square root of harvest weight but the estimates were of lower magnitudes for length, width and depth (0.63-0.79). The heritabilities estimated for the five traits studied differed between pond (0.02 to 0.22) and cage (0.07 to 0.68). The common full-sib effects were large, ranging from 0.23 to 0.59 in pond and 0.11 to 0.31 in cage across all traits. The direct and correlated responses for four body traits were generally greater in pond than in cage environments (0.011-1.561 vs. -0.033-0.567 genetic standard deviation units, respectively). Selection for increased harvest body weight resulted in positive genetic changes in survival rate in both pond and cage culture. In conclusion, the reduced selection response and the magnitude of the genetic parameter estimates in the production environment (i.e., cage) relative to those achieved in the nucleus (pond) were a result of the genotype by environment interaction and this effect should be taken into consideration in the future breeding program for Red tilapia.
The industrialized world has entered a new era of widespread automation, and although this may create long-term gains in economic productivity and wealth accumulation, many professions are expected to disappear during the ensuing shift, leading to potentially significant disruptions in labor markets and associated socioeconomic difficulties. Food production, like many other industrial sectors, has also undergone a century of mechanization, having moved toward increasingly large-scale monoculture production-especially in developed economies-with higher yields but detrimental environmental impacts on a global scale. Certain characteristics of the food sector and its products cast doubts on whether future automation will influence it in the same ways as in other sectors. We conceptualize a model of future food production within the socioeconomic conditions created by widespread automation. We ideate that despite immediate shocks to the economy, in the long run higher productivity can free up human activity to be channeled toward more interactive, skill-intensive food production systems, where communal efforts can reduce industrial reliance, diversify farming, and reconnect people to the biosphere-a realization of human well-being that resembles the classical philosophical ideal of Eudaimonia. We explore food production concepts, such as communal gardens and polyculture, and the economic conditions and institutions needed to underwrite them [e.g., a universal basic income (UBI)]. However, arguments can be raised as to why social-ecological systems would benefit from more labor-intensive food production. In this paper we: (1) discuss the current state of the food system and the need to reform it in light of its environmental and social impacts; (2) present automation as a lever that could move society toward more sustainable food production; (3) highlight the beneficial attributes of a Eudaimonian model; and (4) discuss the potential challenges to its implementation. Our purpose is to highlight a possible outcome that future research will need to refine and expand based on evidence and successful case studies. The ultimate aim is to promote a food system that can provide food security while staying within the safe operating space of planetary boundaries, produce more nutritious diets, enhance social capital, and reconnect communities with the biosphere.