Environment Development and Sustainability

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It is expected that diseases are likely to spread to newer areas, and high-income countries may experience some illnesses that may have been restricted to low or middle-income countries. In addition, following the Intergovernmental Panel on Climate Change, the present study noted that climate change is likely to have many effects on the spatial and temporal distribution of malaria in many Sub-Saharan African countries. This study examines climate change effects on the geographical distribution of malaria occurrence and how extreme climatic events may perhaps be determining factors in the range of vectors for human diseases in SSA in the nearest future. Here, the study appraisals the symbiotic connection of (1) malaria transmission and association with the changes in temperature, rainfall, and humidity as well as their extremes in SSA and (2) the relationship between climate and malaria with the role of climate change in determining upsurge in malaria and meningitis occurrences in the SSA. The study concludes that major drivers of malaria occurrence are climatic elements such as precipitation and temperature. Therefore, we call for a better early Warning System on a proposed roadmap solution for Sub-Saharan Africa.
Geographical location of the study area
Partition line chart of U1 for the DWCC in the study area from 1996 to 2015
Partition line chart of U2 for the PSA in the study area from 1996 to 2015
The degree of coupling coordination between Drinking Water Carrying Capacity (DWCC) and Population Spatial Agglomeration (PSA) is a primary indicator for assessing the sustainable development of society. However, current research using quantitative model methods to explore relationships between the DWCC and the PSA is extremely rare. In order to provide theoretical and methodological support for research of regional population control or water resource allocation, based on the idea of coupling and coordination in physics, this paper constructs a Comprehensive Evaluation Model of Drinking Water Carrying Capacity (CEMDWCC), a Population Spatial Aggregation Index Model (PSAIM) and a Coupling Coordination Model of Human Water Relationship (CCM-HWR). Then, we use of the output results of the CEMDWCC and the PSAIM as the input parameters for the CCM-HWR to integrate these three models together. Through the above processing, we deduce a quantitative analysis method for the degree of coupling and coordination between the DWCC and the PSA. On this basis, we further use Kunming, a region of the water-deficient severely as a research area to discuss the coupling coordination relationships of the DWCC and the PSA during 20 years from 1996 to 2015. The results demonstrate that, on the one hand, in the time dimensions, the coupling degree of the DWCC and the PSA fluctuates little, and it is basically in a straight development state during the 20-year study period. Moreover, the degree of coordination between them is moderately unbalanced and has not fluctuated much for many years in this period. This shows that the DWCC and the PSA have not yet reached a positive interaction state, which is not conducive to sustainable development in the future. On the other hand, in the spatial dimensions, there are certain spatial differences in different regions. These differences are explicitly manifested in the degree of coupling and coordination, which is the better in regions with more developed economies. On the whole, the results of the study are more consistent with the actual situation in the study area. In other words, the economically developed regions have relatively high population spatial concentration, and the DWCC has also reached a relatively high state. Moreover, in these areas, the coupling relationship between the DWCC and the PSA remains relatively stable, and the coordination relationship between them is more harmonious and orderly. As can be seen from the above research results, the research method in this paper can quantitatively analyze the coupling and coordination relationships between the DWCC and the PSA. Therefore, this method is of great importance for promoting research for the sustainable development of population, resources, environment, economy, and society in arid regions of the world.
Rapid urbanization has led to a sharp increase in municipal waste generation, which has resulted in significant environmental problems. However, the existing efficiency assessment models can neither well consider environmental sustainability nor provide empirical research. This paper constructed a municipal waste treatment efficiency index system from an ecological perspective and used the three-stage Bootstrap-DEA model to measure the efficiency of the OECD countries from 2008 to 2017. Kruskal–Wallis rank-sum tests are adopted to figure out factors. It was found that the overall municipal waste treatment efficiencies in the 29 OECD countries were relatively high. There was a slight downward trend from 2007 to 2010 and a steadily rising trend from 2010 to 2018. The average municipal waste treatment efficiencies were significant in the Slovak Republic, Slovenia, and Hungary but were relatively low in Turkey, Poland, and Italy. Then factors like the amount of municipal waste generated and the number of waste management employees can significantly affect efficiency performance. Combined with the empirical results, the article proposed targeted measures to promote waste treatment efficiency for policymakers in OECD countries.
Spatio-temporal variability of extreme precipitation characteristics (EPCs) were analyzed using clustering techniques to establish homogeneous sub-regions (clusters), the nonparametric Mann–Kendall (M–K) test to detect significant monotonic temporal trend and the nonparametric Lepage (LP) test to detect change-points (jumps) representing significant short-term temporal trend. The study area is Fars province (southern Iran), exhibiting diverse climatic conditions within relatively small area. Detailed clustering analysis involved utilization of eight algorithms and four validation indices. Consequently, one algorithm was selected, suggesting seven clusters (C1 to C7) for the study area. EPCs were identified by eight variables, which were used for temporal analysis. The M–K test utilizing within cluster EPC data did not detect any significant trend (5% or 1% levels), for the study period (1976–2013). However, the LP test conducted at 10- and 5-year time-steps showed significant change-points (5% level) in temporal behavior of EPCs in every cluster. Furthermore, “between-cluster variability” was strong as shown in the number of EPCs with significant change-point. For 10-year time-step, C1 and C2, respectively, had two and eight EPCs with significant change-points, representing minimum and maximum number of EPCs. Remaining clusters had between three and seven EPCs with significant change-point. The 5-year time-step also showed strong EPC variability (within and between clusters). According to results for regions with diverse climatic conditions, detailed spatio-temporal analyses of EPCs should include proper identification of homogenous sub-regions (clusters) and also detection of both long-term and short-term (change-point) temporal trends by tests such as the M–K and LP. Results from this type of research can be used as part of the information, which is necessary for flood mitigation/prevention planning at the regional scale.
Global climate change due to greenhouse gas emissions has observable impacts on environment. Among the GHG emissions, carbon dioxide is the primary source of global climate change. In order to provide appropriate measures to control carbon emissions, it appears that there is an urgent need to address how such factors such as economic growth, exports, imports, and technology innovation affect carbon emissions in world’s top carbon emitter countries. We thus employed an extended Environmental Kuznets Curve, Population, Affluence and Technology (STIRPAT) model combined with panel quantile regression to analyze the driving factors of carbon emissions across top 10 countries from 2000 to 2014. We also conducted the panel quantile regression to ascertain the relationship between variables and examine the EKC. The results obtained show that firstly, the main results are that income per capita significantly increases environmental pollution across top 10 carbon emissions countries; this study also supported the EKC hypothesis in the top 10 countries in China, USA, India, Russia, Japan, Germany, South Korea, Canada, Mexico, and South Africain China, USA, India, Russia, Japan, Germany, South Korea, Canada, Mexico, and South Africa. Second, with the top 10 countries, the STIRPAT model is verified using the panel quantile regression approach, and population, energy use, exports, and imports of information communication technology are found to be the key impact factors of higher level of carbon emissions. However, technology innovation is conducive to the carbon emissions reduction. The results obtained show that the EKC hypothesis holds across top 10 carbon emissions countries. The governments of these countries should institute policies for promoting environmental technology innovation and energy efficiency in order to achieve sustainable development of population, resources, and the environment.
Distribution of publication on climate change in Indian Himalayan region
Distribution of publications over the years in the IHR
Distribution of climate change publications under different thematic study group in the IHR
There are a few regions in the world, where climate change impacts are more intense than other regions of the world, and Himalaya is the case. The Himalaya, one of the biodiversity hotspot regions and provider of ecosystem services to billion of people all across the world. Present study reviewed and synthesized climate change studies in the Himalayan region in general and Indian Himalayan region (IHR) in particular. Analysis of the literature indicates exponentially increase in climate change studies 2005 onward in the IHR, and maximum are from Jammu and Kashmir (105) followed by Uttarakhand (100) and Himachal Pradesh (77). Among the subject types, maximum climate change impact was studied on water resources/glacier retreat (141 studies) followed by agriculture (113) and forests/biodiversity (86). Increasing temperature, frequent drought spells, erratic rainfall and declining snowfall are commonly reported indicators of climate change. For instance, temperature is reported to increase by 1.5 °C in the Himalaya than an average increase of 0.74 °C globally in last century; however, it varied in eastern (0.1 °C per decade and western Himalayas (0.09 °C per decade. An increase in temperature between 0.28 and 0.80 °C per decade was reported for North-western Himalaya and 0.20–1.00 °C per decade for Eastern Himalaya. The higher altitude of Himalayan and Trans-Himalayan zone are reported to be warming at higher rates. Many of the glaciers were reported to be retreating in both eastern and western Himalaya. Heavy rainfall is becoming very common in the region often accompanied by cloudbursts that aggravate flood situation many times. Perception-based studies of the region reported to provide firsthand and detailed descriptions of climate change indicators and impacts from rural and remote areas, where no instrumental data are available.
Model used for this study
This study examines the sustainability and green banking performance of Indonesian banking sectors from their disclosures in sustainability reports covering a period of nine consecutive years. The findings elucidate that sustainability and green-banking disclosures are still dynamic year to year. Economic disclosures are the most widely disclosed information, while environmental disclosures are the lowest. Applying a content analysis method, this study uses the sustainability disclosure guidelines from the global reporting initiatives (GRI) and Measuring Green Banking Practices guidelines developed by Shaumya and Arulrajah (2016). Combining these two measurements provided a more comprehensive disclosure list as guidance. This study is important, as it will contribute to the literature on green banking, which is scarce in the extant literature. Given the lack of standardization in sustainability, this study develops an indicator database to advance research on sustainability measurement and reporting in relation to green banking. The managerial implications for banks implementing sustainability they require sustainability governance as a platform to evaluate and monitor the sustainable finance action plan and build a sustainability strategy. This will enable banks to manage not only economic, but also environmental, social, and governance (ESG) risk.
This research consists in diagnosing the hygrothermal imbalance problem inside tourism buildings located at the edge of the Mediterranean Sea. In particular, we study the case of Ben M’Hidi tourism development area in Skikda coastline in Algeria. The southern room of "Royal Tulip" hotel was chosen as object of this study in order to investigate its internal hygrothermal behavior. Our study uses the problem-based approach for generating biomimetic architectural concepts that help to develop a meteorosensitive room’s envelope depending on hygrothermic local conditions. Our proposed biomimetic design was inspired by the hygro-adaptive mechanism of the so-called endemic plant "Silene Amphorina". The focus of this paper is to compare the hygrothermal efficiency of the biomimetic envelope versus the real room’s envelope. For this purpose, hygrothermal simulations were performed using the WUFI Plus® software. Our results show that the biomimetic hygrothermal behavior is more adapted than the real one. It has regulated the ambient temperature and it has reduced the internal humidity rate by around 20% in summer, 23% in mid-season and 35% in winter, which will enhance the internal hygrothermal comfort and ensuring the sustainability of the tourism building. In future works, we will be able to propose meteorosensitive envelope responses based on these results.
The objective of this work was to analyse the relations between innovation management and organisational sustainability in a Brazilian higher education institution. This work used a qualitative research approach through a case study. The data were collected using documents, direct observation and interviews. The chosen data analysis technique was relation-type content analysis. The 31 relationships identified were considered at the level of technological activities and sustainable activities of higher education institutions, with an emphasis on technological activities of curricular structure and sustainable activities of relationships with stakeholders, where one of the 21 activities in the study presented relations with other activities. This work denotes the importance of investigations that, in addition to technological capabilities, promote the analysis of sustainable capabilities, based on the analysis of relationships among the phenomena, for the improvement and development of technological capabilities in this context of convergence between innovation management and organisational sustainability.
The extant literature reveals that scholars and policy makers are highly concerned about exploring the validity of the environmental Kuznets curve (EKC) hypothesis using a different set of variables with the prime objective of exploring environmental degradation issues related to sustainable economic development for different countries. We examine the validity of the EKC hypothesis for the five most influenced economies of the G-20 from 1993 to 2017 using GDP per capita and CO 2 emissions, along with some other variables, namely technological development, financial development (FD), energy use, and social globalization to avoid any misspecification in the empirical model. The LM bootstrap approach confirms the co-integration in the series, and the panel Driscoll-Kraay standard error method confirms that veto-power economies have an N-shaped relationship between CO 2 emissions and GDP per capita. Furthermore, empirical findings exhibit that technological advancement and energy consumption positively correlate with CO 2 emissions, whereas FD and social globalization attenuate environmental degradation. These empirical findings suggest that appropriate policies need to be designed for these sample countries, depending on their GDP per capita and CO 2 emissions levels. An environmentally friendly policy may be adopted to achieve sustainable development goals. Policymakers also need to implement a policy that encourages financial development and boosts technologies with fewer polluting characteristics.
Dynamic decision matrix effects
Results of sensitivity analysis
Disposal of healthcare waste is a key issue of environmental sustainability in the world. The amount of healthcare waste is increasing every day, and it is necessary to adequately dispose of this kind of waste. There are various treatments for healthcare waste disposal, of which incineration of healthcare waste is one of the solutions. This paper suggests a model for selection of the type of incinerators that best solve the problem of healthcare waste in secondary healthcare institutions in Bosnia and Herzegovina. In the selection of incinerators, extended sustainability criteria were applied. Basic sustainability criteria: environmental, economic, and social criteria, were extended with the technical criterion. To assess which of the incinerators best meets the needs for healthcare waste collection, multi-criteria decision-making was used. For this purpose, a combination of two MCDA methods was applied in this paper, namely full consistency method (FUCOM) and compromise ranking of alternatives from distance to ideal solution (CRADIS). The FUCOM method was applied to determine the weights of the criteria, while the CRADIS method was applied to rank the alternatives. The best alternative of the six alternatives used is A2 (I8-M50), followed by alternative A1 (I8-M40), while the worst ranked alternative is A5 (I8-M100). These results were confirmed by applying the other six methods of multi-criteria analysis and the performed sensitivity analysis. The contribution of this paper is reflected through a new method of multi-criteria analysis that was used to solve decision-making problems. This method has shown simplicity and flexibility in operation and can be used in all problems when it is necessary to make a multi-criteria selection of alternatives.
Conservation of greenbelts is the most enduringly successful and popular basic need for today to protect green land, preserve ecological landscape and open green spaces or gardens in urban fringes. Developing countries like Pakistan need to generate a wide range of strategic policies for the limitation of urban sprawl and construction of green structures to achieve sustainable green development. The research method was focused on a survey study regarding conservation of greenbelts with their significant impacts on environment , commercial market and the business community itself in the City of Peshawar, Pakistan. The study was projected mainly through an adapted questionnaire (n = 200) and then analyzed through Statistical Package for Social Sciences applying chi-square test and cross-tables, graphs, frequencies and percentages. The study highlighted the deterioration of greenbelts' infrastructure system smashed possibly with improper developmental plans inside the urban fringes and inadequate maintenance of green structures. Opinion measures reported improved environmental and psychological paybacks, i.e., development of strong human senses to release stress and purify air, and several other benefits (a healthy, green, noise and pollution-free environment). The percentage swift urban sprawl and commer-cialization are the main causes of greenbelt deterioration and uplift of urban property costs. On the other hand, lack of spaces for greenbelts is a major cause for non-availability of facilities like sitting areas, walking track, trees, streetlights and car parking area. Qualitative surveillance based on conservation of greenbelts in an urban area revealed significant impacts on the environment, commercial marketing and the business community itself.
Stages of the research design used in this study
Outcomes of the various stages involved in the PRISMA literature selection and identification process
Top 10 most frequently reported benefits of implementing environmental management systems in the Architecture, Engineering and Construction sectors
Top 10 most frequently reported barriers to implementing environmental management systems in the Architecture, Engineering and Construction sectors
Roadmap of how EMS benefits link to the SDGs (✓ Green block = short-term achievement; ✓ blue block = medium-term achievement; ✓ grey block = long-term achievement) resources
Realisation of the sustainable development goals (SDGs) will provide improvements to people's lives and longevity of the planet. The architectural, engineering and construction (AEC) sectors have a potentially huge role in aiding the delivery of many SDGs; however, there appears to be a lack of research into the engagement within this sector. The leading environmental management system (EMS), ISO 14001, can enable organisations in the AEC sectors to improve their business operations, whilst minimising their impacts on the environment and improving society. Therefore, the study sets out to use institutional theory to determine the usefulness of ISO 14001 as a tool within the AEC sector and to demonstrate how the organisational benefits could facilitate the delivery of the SDGs. A stepwise PRISMA review process facilitated the compiling of academic articles and professional reports (n = 44), which enabled the creation of an inventory of the perceived benefits (n = 85) and the recognised barriers (n = 63) to implementing ISO 14001 across the AEC sectors. These barriers and benefits were confirmed by environmental practitioners as being relevant to the incorporation of an EMS. The most widely reported benefits within the AEC sectors were improving environmental performance and compliance with legislation. Lack of government pressure and lack of expertise were the most widely reported barriers, followed by cost to AEC organisations utilising an EMS. Following on from this inventory of benefits, it was possible to develop of a conceptual roadmap, which illustrates where linkages exist with the SDGs. SDG 4, 8, 12 and 13 are shown as exhibiting the most associations with the benefits. This roadmap was reviewed by AEC sector professionals who confirmed its usefulness. Therefore, it is surmised that the roadmap could aid strategic organisational sustainable planning or for organisations to demonstrate the delivery of their corporate social responsibilities.
Distribution of sample villages
Statistics on average scores of farmers’ environmental awareness in sample counties
While most studies focus on the impact characteristics of farmers and family economic traits have on participation in rural environmental improvement, few studies focus on the relationship between farmers’ environmental awareness and rural residential environment improvement. Based on the survey data of 200 farmers in Sichuan Province, this paper divides farmers’ environmental awareness into three dimensions: environmental problem cognition, environmental pollution tolerance, and environmental protection attitude and constructs a binary logistic regression model to explore the relationship between farmers’ environmental awareness and the improvement of rural residential environment. The results show that the rural residential environment in Sichuan Province still faces some challenges, and farmers’ environmental awareness significantly influences their improvement behaviors. Higher levels of environmental problem cognition can promote farmers’ participation in environmental improvement, but sensitive environmental pollution tolerance does not promote environmental improvement behavior. Positive environmental attitudes have both positive and negative effects on improving behavior. In addition, individual characteristics of farmers, household economic aspects, and nonpoint source pollution status of their residence also affect their participation in rural environmental improvement to varying degrees. This study can help us better understand the explanatory role of farmers’ subjective consciousness in their environmental behavior decision-making and thus provide support for the formulation and implementation of policies of human settlements improvement.
a Silicon carbide balls. b Shredded rice straw .c Rice straw biochar
Process flow for predictive modelling and experimental validation
Predicted versus experimental biochar yield for validation with test data
Heating rate for different microwave absorbers at 800 W
Predicted versus experimental biochar yield for validation with experimental data
A machine learning model for microwave-assisted pyrolysis technology was developed in this study. The data set of 112 unique experiments was created by analysing the published literature based on biochar. The linear, interactive and quadratic regression models were trained with the selected data set. Out of three regressions models, the quadratic model Biochar Yield=-601.78+17.336×VM+25.338×AC-0.26367×T-0.293×VM×AC-0.10305×VM2-0.1893×AC2+1.59×10-3×T2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{Biochar Yield}} = - 601.78 + 17.336 \times {\text{VM}} + 25.338 \times {\text{AC}} - 0.26367 \times T - 0.293 \times {\text{VM}} \times {\text{AC}} - 0.10305 \times {\text{VM}}^{2} - 0.1893 \times {\text{AC}}^{2} + 1.59 \times 10^{ - 3} \times T^{2}$$\end{document} was found to have highest R² value of 0.894. The predicted model developed based on the data from literature was validated with laboratory experimental results. Prediction and validation results showed that data prediction can be a useful tool for the preview of selected feedstock and process parameters. Volatile matter, ash content and temperature were found to be the prominent factors in the trained model. Biochar yield was predicted with a minimum root mean square error of 7 when validated with experimental results. Thus, the predicted model can be used as empirical equation for future experiments to predict biochar yield.
Forest cover change is having an enduring link with climatic factors. This study was designed to study the impact of forest cover change in the Western Ghats on meteorological parameters like rainfall and land surface temperature (LST) between 2000 and 2019 using Landsat images. Land use land cover (LULC) data were extracted from Landsat images, and rainfall data of 53 stations were obtained from tropical rainfall measuring mission (TRMM) data. Mann–Kendall trend test, a nonparametric test, was adopted to evaluate the long-run trends in rainfall for North East (NE) and South West (SW) monsoon during the selected time period. The test results indicate that 19 stations in the North of Kerala show a positive trend in SW monsoon and 3 stations show a negative trend in NE monsoon. The breakpoint analysis of the rainfall dataset with time and with the elevation from mean sea level (MSL) is performed and the results show a breakpoint in the rainfall for the year 2008 and at 47 m elevation (MSL) from the coast of the Arabian Sea. Forest cover data show that there is a loss of 12.65% in the region for two decades span and also a significant increase in minimum LST from 8.308 to 9.208 °C and increase in maximum LST from 41.51 to 46.29 °C during the selected time period. Forest cover loss could be an important factor responsible for the increase in LST. The research outcomes would help the policymakers in improvising the measures for land management policies including plantation and urbanization.
Study districts of Punjab province of Pakistan
Pastoralism is mostly related to specific ethnic group or group of people whose livelihoods generally depend on production of livestock in the rangelands. Pastoralists’ livelihood regarding livestock is hastily becoming indefensible due to mounting pressure of population growth on rangelands and desertification of vast rangeland, the reason for severe climate change. This study attempted to investigate the impact of violent conflicts and environmental hazards on sustainability of pastoral in Punjab, Pakistan. Muzaffargarh, Rahim Yar Khan and Bahawalpur districts of southern Punjab due to significant contribution in livestock and grazing rangeland locations were purposively selected for this study. This research work used the data of 840 pastoralists’ and employed instrumental variable regression model for empirical estimation of the study. Estimates of the study indicated livestock holding negatively influenced from violent conflicts and environmental hazards as this effect can initiate without any exception of livestock holding size. Finding also highlighted pastoralists significant welfare indicators such as income and expenses were negatively influenced due to livestock losses. Pastoralist’s livelihood sustainability is feasible by overcoming such negative impacts of violent conflicts and environmental hazards. There is need to sure pastoralists’ community sustainability by priority focusing on environment sustainable agenda not only internationally but also on national and regional levels. More particularly, implementation proper policy measures regarding climate change coping strategies, controlling violent conflicts, land management and managing programs for reducing poverty more specifically for pastoralist’s rangeland households is needed.
Space representation of different membership grades (Peng & Dai, 2019)
Flow diagram of Methodology
Graphical representations of attribute weights given by decision makers
Environmental deterioration and global warming has created a substantial impact on international companies to incorporate eco-friendly, green supply chain practices and remain competitive in the market. In food supply chain, the selection of the best supply chain management (SCM) strategy can improve the overall performance and can be crucial in managing the food supply chain challenges and achieving sustainable food supply chain. In this paper, different green SCM strategies were explored and evaluated for food supply chain using combinative distance-based assessment method under interval-valued q-rung orthopair fuzzy information as interval extension of q-rung orthopair fuzzy can effectively handle the ambiguity and uncertainty of preference given by experts in decision making. A generalized p-distance between two interval-valued q-rung orthopair fuzzy numbers is proposed in the current study and is used to formulate interval-valued q-rung orthopair fuzzy Hamming distance and interval-valued q-rung orthopair fuzzy Euclid distance. Five supply chain strategies, namely risk-based, efficiency-based, resource-based, innovation-based, and closed-loop strategy, are evaluated to select best strategy for food supply chain based on different attributes such as green manufacturing, green design and development, green management system, green procurement, and green marketing which contribute toward sustainability. It is found that closed-loop supply chain strategy is the best strategy for food supply chain to attain sustainability. A comparative analysis and sensitivity analysis are done to examine the reliability of results obtained from the proposed framework.
Theoretical framework of research (integrating TPB and TAM models)
The geographical position of Marivan and Sarvabad towns in Kurdistan province of Iran
The structural model with standardized estimates
Good agricultural practices (GAPs) include conscious agricultural techniques that are not harmful to human health and the environment, with the goal of protecting natural resources, as well as ensuring health and food security. The use of these practices may be influenced by various psychological and social factors. Thus, the main purpose of this study was to design an integrated model for strawberry growers’ behavior toward implementation of good agricultural practices (GAPs) in Iran. The research framework was developed by integrating the theory of planned behavior (TPB) and technology acceptance model (TAM). The integrated model was empirically tested using data collected from a survey of 200 strawberry growers. The findings of structural equation modeling showed that perceived ease of use (PEU), perceived behavior control (PBC), and behavioral intention (BI) of strawberry growers significantly influenced the behavior of growers toward using GAPs (BGAPs). These factors explained 30% of the variance in behavior of growers to use GAPs. The study also supported the significant indirect effect of perceived usefulness (PU), PEU, subjective norms, PBC, and attitudes on BGAPs. Overall, the calculated total effects of factors on BGAPs indicated that PBC, PEU, and behavioral intention were the three important determinants of growers’ behavior to use GAPs, respectively. The findings of this study show integrating of TAM plus TPB and particularly considering a direct relationship between PEU and BGAPs in this model influenced the predictive power significantly. It can be a comprehensive, complete, and understandable framework for explaining clienteles' behavior to apply good agricultural practices and be used by other researchers for developing future research and policy makers to make the right and suitable decisions to develop GAPs in farmlands.
As per the objective of the present experimental investigation, influence of various configurations of manifolds for optimum flow distribution in concentric glass tube solar air collector (CGTSAC) has been analyzed for transient conditions. Based on the previous studies it was found that the performance of solar air collector is robustly dependent on the flow distribution and decreases with non-uniform flow distribution. For evaluating four different flow distribution arrangements, the experimental setup of CGTSAC is installed at N.I.T., Kurukshetra (29°58′ (latitude) North and 76°53′ (longitude) East), India, and tested with various configurations of manifolds at different operating conditions. The experimental data have been recorded and found that the maximum exit air temperature is 53.1 and 52.9 °C, and the average values of COPt are 0.2731 and 0.2943 at air mass flow rate of 26.6 and 34.2 kg/h respectively with series flow arrangement. Also, the circular fin is introduced in CGTSAC to enhance the performance of the series flow arrangement by increasing the heat transfer.
Classification of supply chain design models based on network configuration
Suggested closed-loop supply chain
Parameters’ impact on the objective functions
Values of Z1, Z2, and Z3 for four multi-objective decision making (MODM) methods
Values of Z1, Z2, and Z3 in eight problems
Forward and reverse supply chains are one of the most important issues in supply chain management. These kinds of supply chain networks include a direct and reverse supply chain. In this paper, a multi-objective closed-loop supply chain network consisting of multi-level, multi-period, and multi-products is proposed under the set of parameter uncertainties. We formulate the problem as a mixed-integer linear programming model. The model assumes a shortage and a remaining inventory at the end of each period. The first objective function is to minimize the total costs of the network. The second one is to maximize the on-time delivery of the products purchased from suppliers to factories. The third objective is to maximize the quality according to the quality of the products produced in the forward supply chain and those that can be recovered in the reverse supply chain. Another point worth noting in this manuscript is selecting the best supplier. Because choosing the best supplier is one of the most critical decisions that purchasing managers have to make in a supply chain. It is based on different criteria, such as price, quality, customer service, and delivery, discussed in this article. Uncertainty is also considered in the model, and a scenario-based robust optimization approach is used to cope with it. Due to the problem’s multi-objective nature, four exact methods, namely LP-metric, sequential linear goal programming (SLGP), TH approach, and simple additive weighting are used to solve the objective functions. Finally, the most effective method for solving various numerical examples is selected as the best method by the least deviations compared to the other methods; in this paper, the SLGP method is chosen. To illustrate the response to a problem in more detail, some of the SLGP method outputs are presented. The results show the efficiency of the proposed model. Thus, it can be used in a variety of industries whose products are recycled and where the quality of products and the choice of appropriate suppliers are of great importance.
Location of Yulin in Shaanxi Province
Collection and sorting process of livable environment assessment indicators in Yulin City
Schematic diagram of livability evaluation of 11 districts (counties) in Yulin city in 2018
Schematic result of 2010–2018 livable environment evaluation in Yulin
Deficiency of livable environment construction and resource development in Yulin City
Rural areas in Northwest China have always been the main concentration of poverty-stricken people in China. In 1986, China listed 665 poor counties (mostly in the northwest), and successively launched the actions of “Volunteer Teaching in Western China” and “Great Development of Western China” to help underdeveloped areas get rid of poverty. At present, the number of poor counties has been reduced to 52. In 2014, the Chinese government proposed to comprehensively improve the rural living environment by 2020. Through in-depth investigation and visit to 11 districts (counties) of Yulin City, Shaanxi Province, China, this study puts forward a set of index system suitable for evaluating the human settlements in underdeveloped rural areas and constructs a comprehensive evaluation model by using a variety of mathematical methods. Using the combination of accurate evaluation and fuzzy comprehensive evaluation, this paper makes a horizontal evaluation on the residential environment of each district (county) in Yulin City, and a dynamic evaluation on the overall development level of livable environment in Yulin City in recent 9 years. Finally, using qualitative and quantitative analysis methods, this paper discusses the shortcomings, available advantages and development prospects in the construction of human settlements in Yulin City, and concludes that the key to improving rural human settlements is to develop township enterprises. This study is an empirical analysis of the government’s long-term poverty alleviation effect, summarizes experience and finds out existing problems, so as to provide basis and reference for the government’s poverty alleviation in future.
In dry-hot areas, such as southern Tunisia, the availability of good water is very limited by the low scanty rainfall, the long dry periods and the high evaporation rate. Thus, to deal with these issues, information concerning the quality of irrigation water and the variability of groundwater quality across the oasis system from water well to the final runoff released into the natural environment, is required to evaluate the potential impacts on agricultural soil fertility and to assess the effects of land-use and agricultural practices in environmental conservation and natural resources exploitation. In the current study, 28 water samples have been collected from public wells along the irrigation scheme and drainage canals and have been analyzed. The obtained data prove that groundwater has large spatial variability (EC between 2.93 and 10.05 ms/cm and TDS between 1.95 and 8.15 g/L) caused by different influencing factors such as aquifer water quality, overexploitation, distribution system and evaporation processes. According to the used ionic ratios (SAR, KR, PI, MH, TH, SSP, ESP, etc..), the used waters are locally of permissible quality, while the majority fall unsuitable class to be used in irrigation with a maximum SAR of 18 at El Hamma region. The findings indicate that, besides the severe restrictions required for the use of these high mineralized resources, CI water quality shows a slight variability along irrigation scheme, which may provide additive water resources that may be reused in agriculture, the runoff released into the environment and the excess of irrigation water lost to evaporation process. The evaluation of chemical quality of drainage water may provide a scientific basis for the reuse of these waters to more efficient land management aiming to the sustainable development of oasis agriculture and the prevention of land degradation.
The essence of megacity ecosystem problems is the unbalanced relationship between humans and their living environment. The most notable features of this imbalance are the environmental quality decline and resource shortages, which cause human survival crises. This paper combines the drivers, pressures, state, impact, and response (DPSIR) framework to explore a new system dynamics (SD) model to achieve megacity ecosystems’ sustainability. First, indicator selection is conducted using the DPSIR framework model. Second, causal loop diagrams and stock-flow charts of systems are generated with the SD model to simulate the change tendency inside the megacity ecosystem. Finally, to validate the applicability of the proposed method, we select the urban ecosystem of Beijing as the case study. This study utilizes the proposed research framework to analyze the effect of the main driving factors among five development strategies and current trends. The results show that the combination of population, environmental protection policies and technical means had the greatest sustainability potential. This study reveals a dynamic relationship between the main influencing factors within megacity ecosystems and offers suggestions to the sustainability of the environment, resources and social economy of megacities.
Overall framework of mapping conservation priorities and actions for rural landscape under land-use changes: conservation priorities and actions were set based on the framework of vulnerability assessment. Landscape vulnerability was calculated through the combination of exposure, sensitivity and resilience indicators. The final conservation actions would have feedbacks on improving current rural landscape
Analysis framework of mapping conservation priorities and actions for rural landscape
Overall exposure, sensitivity, resilience and vulnerability of rural China to land-use changes
Conservation priorities and their responding conservation actions across rural China: there are four categories of priority set, which are first priority (1st P), second priority (2nd P), third priority (3rd P) and fourth priority (4th P) and four types of conservation actions summarized for national plan, namely protection (Pt), restoration (Rs), management (Mg) and maintenance (Mt)
Integration of agricultural, cultural and natural conservation to address land-use change risk has become a crucial issue for rural sustainability, especially for China with dense population and undergoing hyper-urbanization. There is not yet a specific study going with conservation of the whole rural landscape at national level. In this paper, a multi-scale approach is presented as a first proxy to meet this challenge through synthetically combining agricultural, cultural and natural conservation concerns of rural landscape within a spatially analytical framework of landscape vulnerability assessment. This framework consists of three main indicators (exposure, sensitivity and resilience), aiming to identify vulnerable rural areas under land-use changes based on the assumption that more vulnerable areas should receive higher priorities in conservation. Conservation actions were also derived and mapped with conservation priorities. The results show this approach can well-address integrated conservation issue within rural areas. The top conservation priorities in rural China were identified in areas with diverse bio-culture and those significantly suffered from urbanization and rapid agriculture-nature transition. Protection actions were assigned to areas with high exposure risk, while restoration actions were set for areas with low sensitivity. Besides, management actions aimed at areas with low resilience, and maintenance actions covered areas with low exposure, high sensitivity and high resilience. Though this approach was detailed in rural China, it is applicable to any large-scale rural regions under land-use change risk. We conclude that this approach promotes integrated conservation within rural landscape and facilitate real-world implementation of its conservation actions, and suggest that further detailed examinations at refined scale will also be needed to efficiently guild local conservation practices.
The present study was conducted to analyze cropping intensity of four blocks (Mogra-Chinsurah, Polba-Dadpur, Singur and Haripal) of the Gangetic alluvial zone of India using multi-dated Sentinel-2 data in 2018–19 cropping year. It was observed that during peak growing stage all crops ascribed higher Normalized Difference Vegetation Index NDVI values (0.4 to 0.73) and NDVI became as low as 0.06 when the fields were vacant. Sentinel-2 data acquired in the peak crop growing period during each cropping season were carefully selected, and NDVI was computed over the whole study area. Rule-based classification was applied for cropping sequence and cropping intensity classification based on the occurrence and non-occurrence of crops using NDVI threshold (0.4). Sentinel-2 images acquired on 22/10/2018, 6/12/2018, 30/1/2019 and 30/4/2019 were used for masking of trees and non-agricultural area. October 22, January 30 and April 30 imageries demonstrated peak crop growing period during kharif, rabi and pre-kharif seasons whereas December 6 image represented occurrence of no or little crop in the study area. Crop acreage was the highest in Polba-Dadpur block during all the three seasons. The crop–fallow—crop sequence occupied the highest areas (43%) followed by crop–crop–crop sequence (39%). 50% and 39% of the total cultivated land was under 200% and 300% cropping intensities. Overall, accuracies of cropping system and cropping intensity classification were 88.54% and 87.85%, respectively. Sentinel-2 data can be successfully used for cropping system analysis which helps in crop planning and management.
Drying of fish at the Sagar Island (21.7269° N, 88.1096° E) is generally carried out in open sun on the seashore on plastic sheets or mat of palm leaves. This is not an environment-friendly and healthy practice. To alleviate the limitations of open sun drying, 600 kg (300 kg × 2) walk-in solar thermal dryer was installed at a fishing cooperative. The dryer consequently augmented the income of the fisher folk by enhancing throughput and refining the quality of dried fish. The design incorporated, (a) 80% UV cut-off film to take care of appearance of the dried fish; (b) facilitating proper air flow pattern for uniform both side drying; (c) completely dismantlable system to take care of incoming storms/cyclones in advance; (d) solar photovoltaic powered dehumidifiers to control the relative humidity at night and achieve a dried batch in less than 24 h. The fabricated solar thermal dryer had drying temperature in the range of 36.9–53.1 °C throughout the day. Due to the use of the dehumidifiers, an entire batch of fish could be dried from an initial 80% to final 10% moisture content (wet basis) in less than 24 h compared to 38 h in open sun drying. The solar thermal drying efficiency was 30.24% and specific energy consumption was found to be 2.35 kg/kWh. The embodied energy was 10,756 kWh and CO2 emission was calculated to be 422 kg per year, which was lower than other fossil-driven drying systems.
Heavy metal pollution has attracted more attention due to the toxicity and migration characteristics, which has close relationship with soil environment and food safety. Typical heavy metal pollutants, copper, lead, zinc, cadmium, chromium, nickel, arsenic and mercury, have been investigated in Jinan Steel Plant located in Jinan, Shandong Province, People’s Republic of China. The indexes of Nemerow, geo-accumulation, and potential ecological risk were applied to evaluate the soil pollution. Spatial distribution and vertical migration characteristics were also detected and analyzed. The pollution is mainly concentrated in (1) coke processing plant, (2) blast furnace and (3) stock area. According to the concentration index, Zn and Cr were selected as main pollutants; however, Hg and Pb play directly and indirectly roles in soil pollution based on evaluation system. The analysis in vertical direction indicated that heavy metals showed a certain migration and transformation ability. Moreover, heavy metals predominately existed in the residual fraction on the surface and the middle profile. The bioavailable fraction of Pb and Hg accounts relatively higher proportion, which could threaten human health along the food chain. In the process of heavy metal pollution evaluation and analysis, we should not only pay attention to high concentrations of heavy metals, but also focus on heavy metals with high toxicity and strong migration-transformation capability, which need real-time monitoring and assessment.
This paper examines higher education efforts linking United Nations Sustainable Development Goals (UNSDGs) and agri-food system sustainability given reports of stagnant movement for SDG2 in Southeast Asia and lack of data for effective monitoring or evaluation to realize the 2030 Agenda. It discusses Thai contexts amid a growing global movement in academic theory, policy and practice to mainstream SDG knowledge and implementation across campuses presenting one case to illustrate broader concerns. Chulalongkorn University policies, faculty awareness, curricula, research, sustainability reporting and partnerships about SDGs have contributed to SDG2 objectives from different disciplines and academic units. However, some faculty still lack understanding of SDGs generally while SDG2 has not been an institutional priority. The university has made welcome progress since a 2017 policy promoting SDGs but still needs to strengthen SDG2 data collection, teaching, research and community outreach capacities including links to government and international reporting to address complex agri-food system sustainability challenges. Comparative studies could also help while critically debating SDG deficiencies and promoting socioeconomic, ecological, agri-food system, community and campus sustainability.
Trends of energy consumption, FDI and GDP
Influencing mechanisms
Spatial distribution of GTFEP, FDI and TP in 2017
This paper uses the slack-based measure-Malmquist–Luenberger (SBM-ML) method to calculate green total factor energy productivity (GTFEP), constructs a dynamic panel data model to analyse the impact of foreign direct investment (FDI) and technological progress (TP) on GTFEP, and further verifies robustness through heterogeneity tests, quantile regression and a dynamic spatial Durbin model. The main results of this study show that from a national perspective, GTFEP has the characteristics of accumulation and sustainability, and the GTFEP value is positively affected by the value in the previous period. FDI, TP and their interaction term can all contribute significantly to GTFEP, and the effect of FDI in promoting GTFEP through TP is very obvious. The regional heterogeneity test shows that FDI can play a significant role only in the central region, and resource-based city policy can improve GTFEP to a certain extent. The results of quantile regression show that there is a dynamic process of the marginal effects of FDI and TP on GTFEP. The empirical results of the dynamic spatial Durbin model show that the results are still robust after considering spatial factors. Finally, corresponding policy implications are proposed based on the empirical conclusions.
COD and NH4 intensity over 1998–2016
Yearly abatement cost of a COD and b NH4
Spatial distribution of abatement cost for a COD and b NH4
Industrial water pollution has become one of the largest threats to China's sustainable development and human welfare. Although China has implemented numerous policies in the past decades that have achieved remarkable success, there has been little analysis of the costs of mitigating industrial water pollutants. Understanding the heterogeneity and convergence patterns of abatement costs among Chinese provinces is crucial for cost-effective policies, such as a national trading system. We use a directional distance function model to estimate the abatement cost of chemical oxygen demand (COD) and NH 4 , and then conduct a convergence analysis of abatement cost to check the patterns of mitigation and convergence. We show that the mean industrial abatement cost across Chinese provinces is 610 Yuan/kg for COD and 4614 Yuan/kg for NH 4. At the steady state, the abatement cost is about 786 Yuan/kg for COD and 2235 Yuan/kg for NH 4. As theory suggests, a β-convergence pattern is observed for the abatement cost across Chinese provinces. In other words, it is theoretically feasible for China to build up an integrated national trading system for water pollution. We conclude that a pollutant-based trading system is needed and should be updated year by year.
Perceived behavioral control moderates the relationship between video exposure and attitude
This study examines the effectiveness of a public service announcement (PSA) video designed based on the theory of planned behavior (TPB) in motivating people to engage in proper recycling. Based on a representative sample of New York State residents (N = 707), survey results show that all three TPB variables are significant predictors of recycling intention. The PSA video increases recycling intention through attitude, but this mediated relationship is only significant among individuals with low perceived behavioral control. In terms of practical implication, these results suggest that environmental campaigns using a video format may be particularly effective among audiences who perceive low self-efficacy in recycling. Theoretically, this moderated mediation effect suggests that future research based on the theory of planned behavior should not only examine the main effect of each predicting variable, but also assess the role of perceived behavior control as a moderating factor.
Energy security is a multi-dimensional concept that is gaining a growing interest worldwide for studying the sustainability of a given energy sector. The level of energy security has been always quantified and evaluated by focusing on economic and technical dimensions, and modest importance was attributed to social and environmental aspects. Moreover, countries of the Middle East and North Africa (MENA) region were always under-reported in the literature pertaining to energy security issues. This study strives to evaluate energy security in this region through the establishment of an original Environmental Energy Security Index (EESI) in order to cover different dimensions of security of energy supply within these counties. A total of nine sub-indicators were selected based on the current policies and orientations in the region. These indicators were normalized, weighted, and aggregated for each country of the MENA region between 2008 and 2017. According to the assessment objectives, results showed that on average Yemen holds the highest EESI score of 5.319 followed by Morocco 4.304 and Algeria 4.087. On the other hands, Bahrain is ranked last 1.610 preceded by UAE 2.249 and Qatar 2.461. Some key proposals were suggested including investment in local resources, diversification of the energy mix, reduction of energy imports, and use of energy-efficient technologies.
Interaction mechanisms of education with environmental degradation
Education index as a major component of the human development index.
Source: UNDP (2020)
Bivariate relationships between the model series
Evolution of CO2 and EDU variables by countries
Environmental degradation, which became evident after the Industrial Revolution, is one of the most important problems to be solved in the twenty-first century. The need for energy in the production process has caused the rapid use of carbon stores, and global warming has been experienced with the increase in carbon emissions. Due to the fact that global warming has reached a level that threatens human life and negatively affects the quality of life, many studies have been carried out to find ways of preventing the decrease in the life quality caused by environmental degradation. The policies developed by politicians to reduce this degradation have been insufficient, and the increase in environmental degradation has continued. The increase in needs with the increasing population, more consume more happiness and costly access to clean energy sources are the reasons for the failure of these policies. Failures of policies implemented on a macro-scale have led to searches for different policies. In this process, education-oriented policies came to the fore. Education has an important role in production, technological progress, and awareness about the environment, which are determinants of environmental degradation. Although the education is an important policy tool to be used against environmental degradation in the future, studies on the effects of education on the environment are limited and theoretical. Hence, the purpose of this research was to investigate empirically whether education is an important policy tool for addressing environmental quality in developing countries. To this end, the causal relationship between education and CO2 emissions for 14 developing countries from 1990 to 2017 was explored using the de Kónya method (Econ Modell 23(6):978–992, 2006. https://doi.org/10.1016/j.econmod.2006.04.008). This method uses an augmented panel non-causality procedure that controls cross-sectional dependence and heterogeneity. The results showed that there is a causality relation of education to CO2 emissions in Chile and Poland, countries with the highest education and income levels among the emerging nations. Also, the corrective effect of income level expressed in EKC on the environment can be realized at lower income levels thanks to education. In this respect, education policy can be seen as an important tool in preventing environmental degradation, particularly in developing countries.
In medical imaging applications, the accurate diagnosis of brain tumors from magnetic resonance imaging (MRI) at an early stage is a challenging task to researchers nowadays. The early detection of the tumor reduces the mortality rate from brain cancer-related deaths. Among various medical imaging techniques, the MRI is utilized due to low ionization and radiation, but manual inspection takes a lot of time. This proposed work introduces a machine learning technique (MLT) to recognize and classify the tumorous or non-tumorous regions based on the brain MRI dataset. There are four steps to carry out the MLT such as preprocessing, segmentation, feature extraction, and classification procedures. In the first stage, the skull is removed manually to reduce the time complexity by avoiding the process of the unwanted area of the brain image, and median filtering is utilized to filter the noise factor. Next, Chan-Vese (C-V) technique is used to segment the active tumor by selecting the exact initial point. In the very next step, the features of the tumor area are extracted using the gray level co-occurrence matrix (GLCM), and then important statistical features were chosen. Finally, a two-class classifier is implemented using the support vector machine (SVM) and its performance is then validated with k nearest neighbor (KNN). The accomplishment of the proposed flow work was evaluated in terms of accuracy, sensitivity, specificity, and precision by performing on the BRATS 2017 benchmark dataset. The simulation results reveal that the proposed system outer performs over existing methods with high accuracy.
The low water storage capacity caused water crisis in Pakistan; therefore, the country needs both small- and large-scale reservoirs to store surplus water resources. The construction of large dams in Pakistan could not be materialized due to financial and political constraints. However, the construction of multi-purpose small dams is the next best option to store water. To this end, there is a need to identify the best feasible sites in the country. The selection of feasible sites for multi-purpose dams must take into account multiple criteria, including engineering, socioeconomic and environmental. The current study utilizes the coupled Remote Sensing and Geographical Information System techniques to identify the feasible sites for multi-purpose small dams, considering the socioeconomic and environmental criteria in addition to the established engineering criteria in district Swat, Khyber Pakhtunkhwa. The suitability map considered nine engineering criteria, including rainfall distribution, slope, land use, curve number, runoff depth, soil, alluvial depth, closeness to streams, and drainage density, using the weights calculated from priority indices. The suitability map is divided into four classes, i.e., excellent, good, moderate, and unsuitable with the excellent and good classes area of 66.78 km2, and 195.75 km2. Twenty sites (based on accessibility and closeness to Swat River) from each class are selected that are situated in Kalam, Babozai, Bahrain, Madyan, Khwazakhela, Matta, Kabal, and Barikot areas of district Swat and evaluated using socioeconomic and environmental criteria, i.e., community well and no displacement cost, management ownership–private or public, biodiversity protection services, instrumental in groundwater recharge for the community, electricity generation for the local community, low maintenance cost, flood friendly, appropriate distribution of water resources, political well, and irrigation and drinking water potential. The top priority for these areas is electricity generation, flood protection, irrigation and drinking water capability, sustainable operation, low maintenance cost and political well. The current study demonstrated that socioeconomic and environmental criteria augment the engineering approach in identifying the best feasible site for multi-purpose small dams. These sites would not only store the water but would also provide important services (electricity generation, irrigation water, etc.) to the local community and economy.
The increasing mortality of COVID-19 can aggravate soil contamination by metals, harmful to the health of the population, requiring new projects for future cemeteries capable of mitigating these impacts to the environment, justifying the importance of studying the concentrations of metals in the soil of urban cemeteries. The paper analyzed the levels of metals in the soil of urban cemeteries in the City of Carazinho, in the state of Rio Grande do Sul, located in southern Brazil, considering the increase in deaths by COVID-19, for the purpose of future projects for cemeteries aimed at mitigating the impacts generated on the environment. The soils of the three urban cemeteries in Carazinho were sampled, with 5 internal and external points, with 3 repetitions at depths of 0–20 and 20–40 cm, adding 180 samples to measure the concentrations of Fe, Mn, Cu, Zn, Cr and Pb (g kg−1), considering the analytical sequence: (1) analysis in triplicate with mean deviation (RDS); (2) R2 of the analytical curve; (3) traceability of the pattern of each metal; (4) quantification limit of each metal (QL), with the performance of nitroperchloric digestion of the samples and the determinations of metals by flame modality atomic absorption spectrometry. Quantitative data on deaths by COVID-19 were analyzed by univariate modeling of time series, in the integrated autoregressive moving averages model. The results of this study were made available to fifteen architects, who attributed future solutions for environmentally sustainable cemeteries. The results showed high levels of copper (Cu) and iron (Fe) in the soil of the cemeteries studied. Considering the increase in deaths and subsequent burials per COVID-19 revealed a prediction for the death toll of 6,082,306 for June 9, 2022, it is assumed that metal contamination can reach even higher levels. To mitigate these levels of contamination by metals, 80% of the architect respondents expressed their preference for a vertical cemetery, with treatment of gases and effluents to mitigate environmental impacts.
Evolution of CO2 emission, economic growth, COVID-19 infections, and oil prices
Methodology strategy
CUSUM representation model 1
CUSUM representation model 2
This study explores the interdependence among a sanitary crisis, environmental degradation, oil prices, and economic activity in the USA based on weekly data over the period from January 03, 2020, to October 02, 2020, through VECM and Granger causality methods. The study period is characterized by lockdowns and mobility restrictions due to COVID-19 pandemic that may affect the economic and energy sector in the USA. Thus, a meticulous analysis of the impact of a sanitary crisis on economic and energy sectors seems to be crucial. Findings are very interesting and confirm the existence of a significant impact of a COVID-19 pandemic on WTI oil price. More importantly, bidirectional causal relations between the three couples: COVID-19 infections–carbon emission, COVID-19 infections–economic growth, and COVID-19 infections–oil price are also discovered. Taken together, our empirical findings are effective for the relevant authorities and policymakers in the USA to develop an appropriate financial and fiscal policy such as reducing interest rates, subsidizing, promoting sustainable industrialization, and carbon taxation to boost investment and to recover the economic growth without harming the environment and complicating the sanitary situation.
Purulia is a hard rock terrain where water scarcity as well as water quality degradation has been a major threat for the past few decades. The prolong use of fluoride contaminated groundwater causes serious health issues in human. The study was performed during the post-monsoon period for better understanding of the general geochemistry along with the fluoride contamination of groundwater and analysis of the health risk factor for the local dwellers. The physico-chemical parameters were analysed during the field work and rest in the laboratory using the standard procedures. The statistical mean values of the cations Ca+2; Na+; Mg+2; K+; Fe+2 are 91.53 mg/l, 42.3 mg/l, 31.76 mg/l, 3.58 mg/l and 0.93 mg/l and for anions HCO3 -, Cl- , SO4 - , NO3 - , F – are 231.67 mg/l, 106.81 mg/l, 82.83 mg/l, 31.52 mg/l and 4.06 mg/l, respectively. Fluoride is one of the important trace element in groundwater, the value ranges from 1.30 mg/l to 7 mg/l with an average of 4.06 mg/l in the study region. According to the piper plot the water type are 80% Ca-HCO3, 19% mixed CaMgCl and 1% CaCl type. Gibbs diagram indicates that the rock-water interaction is the most dominating mechanism prevailing in this region. The health risk assessment are revealed based upon the values of hazard quotient for ingestion (HQin) and dermal pathway (HQde) for the different age groups. The results from the research shows that 6-12 month babies are more exposed to health risk through direct consumption of contaminated water in the study region.
Rotating process of PM
Flowchart of the proposed intelligent performance analysis system
Initial path analysis model
Final model from path analysis
Financial weights of the subject
In this research, a new method to determine the supply chain performance based on its sustainable strategies is proposed. This method consists of a balanced scorecard, path analysis, and hybrid Shapley value and Multimoora method. The main contribution of this research is to design an intelligent performance evaluation system for different supply chains. In this intelligent performance evaluation method, first, a set of strategies are determined through the balanced scorecard, next, by applying the path analysis method, the best strategic paths are specified, and then the Shapely value of the listed paths is calculated. Among these, five with the highest Shapley value are selected through the hybrid Dematel-based analytical network process and Multimoora method. This method is implemented in the petrochemical supply chain in Iran, and the results are analyzed. This application revealed that the best policy in organizational–operational management optimization is subject to applying this up-to-date technological apparatus at its best. In this approach, the production and delivery time cycle would be reduced. This intelligent system reduces production costs as well. The findings here can be applied in any industry of concern as to improve operations.
The present study tends to close this gap of knowledge by introducing new data based on cross-sectional surveys operated through two steps, a specifc questionnaire at local hospitals involving mainly cancer patients (n=315) and a general households questionnaire concerning frstly the population of Gafsa region and secondly its surroundings (n=103). Results showed that most subjects are females sufering from breast cancer attaining 67.74% of the respondents. About 17.46% of the male subjects sufer from prostate cancer which is the second most frequent type among both sexes. Our fndings concerning breast cancer are in consistency with the data of the Tunisian cancer centers and the worldwide data confrm that it is the most frequent type of cancer with the highest rates of annual new incidences. Approximately half of Gafsa residents declared to have at least one family member working in the mining industry which is in consistency with the percentage of respondents with dental fuorosis and/or kidney dysfunction. Proximity of mine areas, also, has been identifed as an exacerbating factor of cancer morbidity in the studied area.
  • Fateme MalekiFateme Maleki
  • Saeed YaghoubiSaeed Yaghoubi
  • Atieh FanderAtieh Fander
Current research concentrates primarily on the effect of the organic level on the deterioration rate of products over a two-echelon food supply chain with two manufacturers and a retailer. One of the manufacturers produces organic products (OP), which is called the organic manufacturer (OM), and the other one produces non-organic products (NOP) with sales effort, which is called the non-organic manufacturer (NOM). Indeed, the NOM compensates for the organic advantage of OM by sales effort. The deterioration rate is assumed to be an ascending function of the organic level, and the products start to deteriorate at a specific rate that depends on the type of that product. In this study, the green supply chain based on the organic level is firstly examined in decentralized and centralized conditions, and then coordination between the retailer and the OM with the contract mechanisms is investigated. To demonstrate the performance of mathematical models, a real-world example and sensitivity analysis of crucial factors are presented. Thus, the chain profit increases, but one of the member’s profits will decrease.
Variation of COVID-19 daily confirmed cases, particulate matter (both PM2.5\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_{2.5}$$\end{document} and PM10\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_{10}$$\end{document}) and Air Quality Index (AQI) with 3 days rolling mean for five different metropolitan cities of India
Variation of COVID-19 confirmed C(t) cases with particulate matter (both PM2.5\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_{2.5}$$\end{document} and PM10\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_{10}$$\end{document}) and air quality index (AQI) for five different metropolitan cities of India. The first column shows the correlation between confirmed cases and PM10\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_{10}$$\end{document} for five different metropolitan cities and the second column represent the correlation between confirmed cases and PM2.5\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_{2.5}$$\end{document}. The third column shows the correlation between the AQI and confirmed cases of COVID-19
India is affected strongly by the Coronavirus and within a short period, it becomes the second-highest country based on the infected case. Earlier, there was an indication of the impact of pollution on COVID-19 transmission from a few studies with early COVID-19 data. The study of the effect of pollution on COVID-19 in Indian metropolitan cities is ideal due to the high level of pollution and COVID-19 transmission in these cities. We study the impact of different air pollutants on the spread of coronavirus in different cities in India. A correlation is studied with daily confirmed COVID-19 cases with a daily mean of ozone, particle matter (PM) in size ≤\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\le$$\end{document} 10 μ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu$$\end{document}m, carbon monoxide, sulfur dioxide, and nitrogen dioxide of different cities. It is found that particulate matter concentration decreases during the nationwide lockdown period and the air quality index improves for different Indian regions. A correlation between the daily confirmed cases with particulate matter (PM2.5\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_{2.5}$$\end{document} and PM10\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_{10}$$\end{document} both) is observed. The air quality index also shows a positive correlation with the daily confirmed cases for most of the metropolitan Indian cities. The correlation study also indicates that different air pollutants may have a role in the spread of the virus.
Percent share of inputs in total energy for okra and tomato production in Chotanagpur plateau region
Source wise distribution of direct, indirect, renewable and non-renewableinput energy for okra and tomato production in Chotanagpur plateau region
Greenhouse gas (GHG) emissions (kg CO2eq ha⁻¹) from different inputs used in okra and tomato production in Chotanagpur plateau region
  • B. SarkarB. Sarkar
  • B. DasB. Das
  • P. K. SundaramP. K. Sundaram
  • [...]
  • A. KumarA. Kumar
The information on greenhouse gas (GHG) emission and energy use patterns from vegetable production in the Chotanagpur plateau region of Jharkhand state is minimal. The current study analyzed the energy input–output and GHG emission and their relationship with the productivity of two critical vegetables grown in the region, viz. summer season okra and tomato. In this regard, data were collected from 30 vegetable farmers of the region in a pretested questionnaire through personal interviews. The results show that the overall energy input used in the okra production was 8828.71 MJ ha⁻¹ of which human energy (27.62%), petrol (27.31%), farmyard manure (13.59%), and animal energy (13.22%) contributed the primary inputs. The total energy required for tomato production was 4798.66 MJ ha⁻¹, where petrol (25.13%) contributed the highest, followed by fertilizer (16.94%), diesel (14.67%), electricity (12.06%), farmyard manure (12.03%), and human energy (11.65%), respectively. The energy ratio (energy output to energy input) for okra and tomato was estimated at 2.85 and 7.58, respectively. The benefit cost ratios for tomato and okra production were 7.87 and 1.71, respectively, showing that the cultivation of both the vegetables is remunerative in the region, with tomato being more remunerative than okra. The total GHG emission was 875.41 and 322.75 kg CO2eq ha⁻¹ for okra and tomato, respectively. The economical use of inputs could help reduce GHG emissions in vegetable production.
Outlines of the cumulative sum
Outlines of the cumulative sum of squares
Charts of Scatter matrix of variables
Environmental degradation has become a serious concern of the government of Bangladesh especially due to the limited scope of the nation in transforming its energy systems in an environmentally sustainable manner. Against this backdrop, this study investigates the impacts of financial sector growth, energy consumption, and economic growth on carbon dioxide emissions in Bangladesh over the period from 1980 to 2019. Besides, the possible moderation impacts of financial sector growth are also explored. Accordingly, the analysis is categorized into two segments in which the former does not consider the moderation effect, while the latter takes the moderation effects into account. Overall, the findings show that the environmental Kuznets curve hypothesis holds for Bangladesh. Besides, the growth of the financial sector is witnessed to improve ecological excellence by reducing carbon dioxide emissions in the country. In contrast, higher consumption of energy is seen to stimulate higher emissions of carbon dioxide in the long run. However, when the moderation effects are considered, the environmental Kuznets curve hypothesis no longer holds valid. This indicates that the development of the financial sector alongside directly reducing the emissions also influences the validity of the environmental Kuznets curve hypothesis in Bangladesh. Hence, in light of these findings, this study recommends the Bangladesh government to strategize its financial development policies by taking the environmental objectives into cognizance. Moreover, to tackle the rise in energy use-related emissions, the government should also use the financial sector to catalyze investments in green projects while inhibiting unclean investments in the country.
Environmental development in Indonesia refers to long-term sustainable challenges in which the environment is continually preserved for the benefit of current and future generations. However, the economic growth, which is supposed to benefit citizens, has an influence on environmental degradation because it affects changes in natural and environmental situations. Changes in natural conditions and the environment must be regulated by law so that they may be used for the benefit of citizens without harming the environment and can be enjoyed and handed on to future generations. This article used normative legal research on Environmental Protection and Management Law No. 32/2009. It relates to legal guarantees from the government for environmental protection, especially the prevention of environmental damage due to massive exploitation of natural resources in Indonesia. The research method used a descriptive approach by analyzing and explaining what is inside the books, journals, or the opinions of environmental experts. The results showed that excessive use of natural resources to pursue development for the welfare of society may damage the environment and the efforts made by the government in handling the environmental damage with sustainable development policies are the best solution in managing the environment in Indonesia.
Assessment of anthropogenic pressure on natural ecosystems is crucial for the formulation of appropriate policy measures for their conservation, sustainable utilization, and management. However, methodological and analytical issues arising due to the use of multiple variables with different frames of reference and units of measurement during such assessment may impede decision-making. We demonstrate a simple yet effective frequency-based protocol to assess anthropogenic pressure on natural ecosystems using the case study of a seasonal wetland in northeast India. For this purpose, we collected household and village-level data on the extraction of natural resources from 26 riparian villages of the wetland following standard survey and sampling methods. Using this protocol, we identified the wetland resources vulnerable to over-extraction by the riparian communities and prioritized them for adopting appropriate management actions. The proposed protocol would be useful for the researchers, stakeholders, and policymakers to assess and compare anthropogenic pressure on any natural ecosystems.
Petroleum is an important strategic material connected with the national economy's safety. Sustainable supplier performance evaluation plays a considerable role in establishing an effective, sustainable supply chain management (SSCM) and is related to the safety of petroleum production and supply. Social responsibility, governmental regulations, and public consciousness of environmental aspects are enforcing the companies to make their supply chains more sustainable. This paper presents a method for sustainable supplier selection problems by combining fuzzy decision-making trial and evaluation laboratory (DEMATEL), analytic network process (ANP), data envelopment analysis (DEA) methods, and Anderson-Peterson rating model. This method proposes a novel procedure for solving the sustainable supplier selection problem. It allows decision-makers to minimize the negative environmental effects and maximize the social impact of the supply chain while maximizing its business performance. At first, the effects between selection criteria are computed by Fuzzy DEMATEL. Then the weights of each criterion-related with to the petroleum supplier selection are derived by the ANP method. Results of this stage are inputs for the next stage, where DEA is applied to select the best suppliers. Finally, 15 petroleum supplier companies in Iran are evaluated and prioritized as a case study to show the capabilities of the proposed model.
With the tremendous rise of aged offshore oil and gas (O&G) facilities, the world is on the horizon of a decommissioning dilemma. In addition to higher cost consumption, decommissioning offshore O&G platforms is an energy-intensive process and results in the production of huge waste on dry land. Few studies have been undertaken to assess and compare the environmental impacts of various decommissioning options, but economic barriers and data gaps have confronted the virtue of these studies. A holistic framework to assess the environmental and economic implications and identify the best decommissioning option is the need of the hour which can give clarity of selection to stakeholders of the offshore O&G decommissioning industry. This study aims to develop an eco-efficiency framework, by integrating environmental life cycle assessment and life cycle costing, to assess the environmental and economic impacts of the decommissioning process of offshore O&G platforms. A comparative study of four decommissioning options is carried out to determine the best decommissioning option for a specific offshore O&G platform. The study indicated that the use of vessels in the decommissioning process is the major contributor to the environmental impacts and costs. This framework helps the decision-makers to select cost-effective options which can reduce the environmental impacts and result in the reduction in resource exploitation.
Waste management is a crucial issue for maintaining the environment and caring for people’s health. Since a wide array of people and communities are exposed to dangers from exceeding the production and growth rate of waste, the efficiency of waste management benefits everyone. This measure requires logical and precise planning. The primary aim of this paper is to categorize waste generation management to preserve the well-being of public health, the environment, and environmental resources. Waste management with the cooperation and collective efforts of citizens, businesses, industries, and government, can continue to enhance materials’ reuse, recycling the whole solid wastes resources. Reducing the excess production of materials is the primary goal of this project. It has been proved that prevention is better than remedy in most cases, thereby proposing green production as an answer. Green production, alongside cleaner production, is seeking prevention innovations, protecting the environment by analysing the flow of materials and energy throughout the manufacturing process. In this regard, this study reviews and summarizes the related research to identify proper options for minimizing the waste materials, energy, and emissions from industrial processes, through strategies for the optimal utilization and application of resources. The reviewed papers are classified into oversees the prerequisite steps for management strategies before and after waste generation. Finally, research gaps have been reported to identify areas for future study. The obtained results showed that in approaching waste, more studied materials are dedicated to waste management but not to prevention or waste minimization before its inception. Furthermore, the best manners in waste management to protect the environment are prioritized, respectively, at first prevention, secondly waste minimization, thereafter recycling the manufactured wastes to hasten the delivery to the landfills and lessen the amount of transportation.
Top-cited authors
Hussein A Kazem
  • Sohar University
Arthur P.j. Mol
  • Wageningen University & Research
Abu Reza Md Towfiqul Islam
  • Begum Rokeya University, Rangpur
Miqdam Tariq Chaichan
  • University of Technology- Iraq
Samuel Asumadu Sarkodie