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Urban sustainability can be considered as a part of sustainable development, which emphasizes the balance between three dimensions of environmental, economic, and social sustainability to improve human well-being and the quality of life. In this study, it was attempted to assess urban sustainability in the most critical, populous, and expanded district of Tehran (district 4) using sustainability assessment by fuzzy evaluation. For this purpose, 52 primary indices which were divided into 8 secondary components were employed. Among them, 18 indices for environmental issues were grouped into three secondary indices as E1, to E3, and 34 indices for economic–social and cultural issues were classified into five secondary indices as H1 to H5. The results revealed that 56% of the study area was potentially unsustainable and 44% of it had a medium sustainability in terms of environmental aspects. Furthermore, 65% of the study area had a medium human well-being sustainability and 35% of it was potentially unsustainable in terms of economic–social and cultural aspects. Finally, 45% of the study area was found unsuitable in terms of overall urban sustainability. The functional sample proposed in the present study can provide the directors and planners with the required information about the condition of sustainability in the most important district of Tehran.

Groundwater remains the primary source of freshwater for essential agricultural practice. Two billion people depend on groundwater as their essential source of water. Thus, fifty percent of the groundwater is used to produce food for the globe. Groundwater serves as the main strategic asset in periods of drought. Determining the groundwater potential zones highly facilitates the effective management of available water resources. The current study attempts to find out the potential zones for groundwater using remote sensing and geographical information system. This tool has become deliberate for groundwater potentiality modeling and mapping as it is highly efficient, accurate, and cost-effective. Satellite and conventional data sources include a total of nine parameters, such as rainfall, geology, geomorphology, lineament density, drainage density, soil, land use, slope, and topographic wetness index, which are considered for the identification of groundwater potential by using multicriteria decision-making approaches such as analytical hierarchy process (AHP), frequency ratio (FR), and multi-influencing factor (MIF). The study is applied to Tanjore District where the proposed methodology has not been attempted in earlier studies. The potential groundwater zones obtained were categorized into five classes: very low, low, moderate, high, and very high. The receiver operating characteristic curve was plotted, and the area under the curve was estimated for results, and the precision showed FR 88%, AHP 75%, and MIF 71%. The results will be valuable for controlling water supplies, land-use planning, and environmental management purposes for planners and engineers.

Plastic pollution is one of the major problems being faced by the world today. The lack of proper recycling and insufficient waste management practices; leaves more than 55% of plastic waste unattended resulting in open dumping of plastic waste. Microplastic pollution is one of the niche areas of study addressed by a few researchers and inventors. Researchers are working on various aspects concerned with the microplastic impact on marine, freshwater, and soil environment. The paper covers a detailed patent landscape for analysis, extraction, identification, and separation techniques for microplastics in marine, freshwater, and soil ecosystem. The patent analysis is performed through the IP classification, applicants, and inventor’s details, citation analysis, patent grant, kind codes, country codes, document types, and jurisdictions. The paper also includes relevant bibliometric analysis of the research publications in the area of microplastics identification, separation, and analysis techniques supporting the patent landscape to understand the overall research scenario in the area of microplastic pollution. The patent landscape is done by using the Lens patent database, Espacenet, and applications such as MS excel and origin. The objective of this study is to provide an overview of the research trends and the need for research and innovation in the field of microplastics pollution, considering the patenting activity and publications as an indicator of innovation.

With the development of 3D printing technology, there will be a lot of changes in manufacturing. Recently, research on 3D pen using 3D printing technology is increasing. Unlike 3D printing, 3D pen can print products instantly. So, 3D pen will be applied in various fields. In this study, the design education method using 3D pen was studied. The results of this study are as follows. First of all, design education using 3D pen can develop students’ creativity and problem-solving skills. In particular, this curriculum can be used in making education. The results of studies are expected to be important data for future education. Moreover, these results could be the basis for making textbooks for future schools. In the future, 3D pen should also be developed for students to use in practice.

Most of the world’s major cities currently face the risk of flooding, which is becoming more frequent. Floods often leave behind enormous material damage and, worse still, loss of human life. With this in mind, this paper proposes a conceptual approach to modeling flood risk-sensitive areas in the Mfoundi watershed (95.6 km2) that drains Yaounde town, the political capital located in the humid tropical zone of the southern plateau of Cameroon. The multi-criteria decision analysis (MCDA) approach coupled with the analytical hierarchy process (AHP) and the geographical information system (GIS) environment was employed in this study. The method was applied to ten parameters to calculate the flood risk index and hence to generate the flood susceptibility map. The results show five main classes of susceptibility to flooding: very low (9.27 km2), low (24.63 km2), moderate (22.04 km2), high (21.01 km2) and very high (19.50 km2). Two methods were adopted to validate the flood susceptibility map, which was produced by overlaying 50 regularly flooded points identified in the Mfoundi watershed. The so-called visual method shows that 36 of these points (72%) are found in environments with very high susceptibility and 11 points (22%) are located in areas with high susceptibility, proving that the results reflect reality. The presence of flood points in areas of low and moderate susceptibility could be linked to both human activities and climatic disruption, which sometimes triggers high rainfall. The statistical method (AUC) presents a very good accuracy (0.84 or 84%) of the map produced. This study is important for several reasons: (1) it is carried out in an area with potential for environmental accidents but where very few studies were carried out to delineate these hazards; (2) it provides a basic tool for making decisions about environmental issues for more efficient management of the Mfoundi Watershed; (3) it is also an experimental study representative of the humid tropical forest zone subject to forcings that should be extended to larger scales by covering several climate units in Cameroon.

Air pollution is one of the main environmental problems in the metropolitan area of Sao Paulo (MASP) in Brazil, with frequent exceedances of air quality standards. Occasionally, the exceedance events last many days, resulting in continuous exposure to concentrations above the standards, with impacts to human health. In this air pollution long-term study, a method was developed to identify persistent exceedance events (PEE) of particulate matter (PM10) and ozone (O3) and associated surface weather patterns. Between 2005 and 2017, 119 PEE were identified, with exceedances occurring simultaneously in at least 50% of monitoring stations along 3 to 14 consecutive days. Median PM10 and O3 concentrations increased by 60% during the events. Mean fields of sea level pressure from global reanalysis data revealed the influence of high-pressure systems and pre-frontal conditions. PM10 events were frequent in austral winter and mostly driven by anomalous atmospheric circulation with a wind change to northwest. On the other hand, O3 events were common in the spring, associated with higher positive anomalies of temperature and solar radiation. Overall, results show that PEE span a regional scale, differing from ordinary exceedance events that can be driven by local conditions. Policy makers should be aware of the frequency of PEE in the development of mitigation measures against the exposure to harmful levels of air pollutants. The concept of PEE can be applied to other metropolitan areas and may support the development of data-driven air quality predictive models based on current or forecasted weather conditions.

Shoreline changes have been a major environmental concern to coastal geomorphologists, engineers’ as well coastal ecologists as a result increased alteration in the ecological system of many coasts of the world. It is causing major coastal structure damage and requires harbour dredging. The current study aimed at integrating remote sensing, geographical information system, and statistical methods to monitor and quantify spatio-temporal shoreline dynamics along Ilaje Local Government, Ondo State, Nigeria over 31 years (1986–2017). Four multi-temporal and spectral Landsat satellite images were used to examine the shoreline changes for a long-term period (1986–2017), besides three short-term time intervals. Images were classified using supervised classification to map the land use land cover changes in the study area. Integrating the Digital Shoreline Analysis System version 4.3 tool within ArcGIS facilitated the quantification of shoreline changes via the End-Point Rate and Net Shoreline Movement statistical techniques. The study revealed a coastal length of about 80 km with both accretion and erosion processes actively shown along the coastline. About 40 km of the coastline was found to be accreting with an average of + 1.08 m/year followed by 35.4 km of coastal erosion with an average of − 1.40 m/year and 4.6 km of the coast more or less appears stable. The overall shoreline changes fall within high accretion (> + 1 to ≤ + 2) to high erosion (

Coronavirus disease 2019 brings about the economic damage and loss of life. Thus, demand of personal protective equipment continues to increase, consequently an increase in infectious equipment pollution. Most of these wastes threaten the environment and increase the spread of diseases. This paper provides a research hypothesis whether effective medical waste management would prevent the possible impacts of coronavirus disease 2019-related waste issues on environment at the city level. To confirm this hypothesis, installation of waste treatment centre is addressed. Then, by incorporating uncertain waste generation amounts utilizing Jimenez method, a pickup routing is addressed to decide the pickup routes between the waste treatment centre and residential area. This study is first to assign the optimistic, realistic and pessimistic scenarios of the uncertain waste generation using time series analysis method and waste generation formulation. Also, L-type matrix is used to define, assess and prioritize the environmental and operational risks on waste generation formulation and to provide risk reaction strategies. Practicality of these approaches is illustrated in the case of Turkey. The computational results reveal the effectiveness of the integrated method, which ensures practical and theoretical insights controlling the waste generation to prevent virus propagation for health authorities.

The realization of the goals of sustainable development (SDGs) presupposes administrative policy capacity. The NPM implementation is related to that capacity. Empirical research on this relationship has been conducted rarely in developing countries. To fill this gap, this research aims to study the impact of the policy capacity on the implementation of one of the NMP themes as well as a method to achieve SDGs, namely, performance-based budgeting (PBB) and the impact of PBB on increasing the policy capacity. Iran has been selected for a case study and the data from interviews as well as documents, news, and related scientific papers have been analyzed by a qualitative method. The results showed that 1) one of the requirements for realizing the SDGs is administrative policy capacity. 2) the lack of that capacity caused many problems for the implementation of the PBB by preventing the formulation of the budgeting system change plan and the appropriate annual plan. And, 3) the implementation of PBB did not increase the policy capacity.

Emission control strategies, meteorological factors, and interregional atmospheric transport of pollutants are considered significant factors that affect PM2.5 concentrations in a city. In this research, two multiple linear regression models are proposed to achieve an accurate estimation of PM2.5 concentrations in Zibo City, Shandong Province of China. The influence of policy was considered as dummy variables in the models. First, a PM2.5–meteorological–policy–interregional model was constructed to explore the diversity of influences from all the parameters mentioned above. Second, for easy predictions of PM2.5 concentrations in the future, a PM2.5–meteorological–policy model was constructed considering meteorological factors from ground monitoring and pertinent air control policies. Data needed to construct the models were obtained from the monthly statistical data from Zibo and surrounding cities from January 2014 to September 2019. Then, the model predictions were extended to July 2021 and compared with the actual series. Model verification was revealed using goodness-of-fit and significant testing statistics. In specific, temperature, wind velocity, and the implementation of relative policies had clear effects on the PM2.5 concentrations in Zibo. Furthermore, Jinan, the provincial capital bordering Zibo to the west, made the largest contribution to fluctuations in PM2.5 concentrations in Zibo. Accordingly, the implementation of strict policies and regulations was undoubtedly a better measure to reduce PM2.5 concentrations in a city under certain topographic and climatic conditions.

One of the ways to implement practical plans in planning and protecting them is to be aware of the ecological potential of these resources and to investigate the factors affecting their degradation. In this Hyrcanian forest study in northern Iran, a study was conducted to determine the ecological capability of the forest based on three methods: AHP, fuzzy gamma and regression based on GIS and weighting of factors with AHP model. Then, using field data and stepwise regression model, a region decline map was constructed. The validation results of the three methods using the ROC model showed that the fuzzy gamma estimates the region capability with the highest accuracy and only 27% of the region has high and very high capability. Livestock grazing, climate change, land use change and diseases have played the most important role in the decline. The decline map developed along with the capability map can be helpful to any management of oak forests in the area to reduce decline factors and prioritize areas for conservation and support programs.

Due to increased awareness of the current and future issues with the environment, sustainable development has become a well-known concept and goal in the last decades. Based on this idea, organic agriculture is now fairly generalized in many farms and grape processing factories. Life cycle assessment (LCA) represents a valuable and standardized technique to evaluate how sustainable a crop can become, determining the potential impacts that the complete-life product causes on the environment and on the management/conservation of resources. Although LCA can be applied to any product, this work focusses on organic grapevine crops as the subject of study, in order to improve energy and water efficiency and minimizing issues such as the use of pesticides. This paper, collecting primary data from three Spanish grape processing factories, quantifies the reduction of the overall impact related to the avoidance of artificial irrigation, amounting to 10%, and the saving of resources (− 4.3 kg oil eq. per ha) due to the replacement of chemical fertilisers with animal manure. On the other hand, the use of manure has shown some controversy from an environmental point of view as it contributes to global warming, resulting in an increase in the total impact of the organic vineyard. As predictable, the application of conventional practices as well as the use of water for irrigation could both result in a higher overall yield, and in a contemporary growth of environmental impacts; a discussion about the quantification of this aspect is also inserted.

Enhancing the construction of transportation infrastructure is considered one of the viable pathways to ease traffic congestion and air pollution problems. To investigate whether increasing the level of transportation infrastructure construction can help reduce haze problem, a random-effects model is used to test the effects of haze reduction, based on inter-provincial panel data of 31 Chinese provinces from 2013 to 2017. The empirical results deliver several interesting findings. Firstly, enhancing transportation infrastructure construction has a statistically significant and positive impact on haze emission reduction; secondly, upgrading the industrial structure enhances this optimistic effect. Finally, improving transportation infrastructure construction shows more significant effects in haze reduction within highly polluted areas than lightly polluted cities. Therefore, to reduce haze pollution more effectively, China needs to improve the level of transportation infrastructure construction further and adopt a differentiated haze management strategy for high and low pollution areas.

Drainage basins act as indicators of geomorphic information for hydrogeological and sustainable natural resources development. Concerning the impacts of short-duration excessive downpour and flash floods worldwide, management strategies for such analysis accordingly assume a paramount importance. Understanding drainage characteristics of watersheds for stability and gradual release of waters downstream is imperative to recognize their linkage to erosion and flash flood processes. This study proposed an empirical and semiquantitative method for determining an index referred herein as erosion and flash flood susceptibility index for 18 major stream drainage areas of the Jhelum River Basin (JRB) of Kashmir Himalaya, India. The index was employed to assess and prioritize stream watersheds, considering statistically driven weightage-based influence of 23 morphometric attributes and 10 slope categories which govern the erosion and flash floods of these watersheds. Results demonstrated that about 83% of the JRB, encompassing 12 stream watersheds, fall under high- to moderate-priority classes and thereby contribute to frequent flooding and erosion in the eventuality of heavy downpours. The new index provided in this research would help in better understanding stream watershed conditions and deliver recommendations for watershed management authorities in regions deficient in hydrometric and erosion yield datasets. The present work further would support the regions to accomplish various sustainable development goals after implementing the management procedures. The findings arising out of this study will provide tangible inputs for watershed management authorities in the region typically characterized as deficient in hydrometric and erosion yield datasets.

Hydroelectric generation is a potential flexible electricity source that can ease the transition to a decarbonized energy economy. As such, using scarce hydroelectric generating resources efficiently is important. We examine approaches to represent the operating characteristics of hydroelectric resources. Many hydroelectric-plant owners use water tables or generic unit characteristics for operational planning. Such practice may be inefficient, as it does not account for unit-specific operating-characteristic changes or time-related impacts, e.g., plant degradation. We demonstrate a data-driven approach to modeling plant operations that is unit-specific and depends solely on observable and controllable variables. Numerical results using historical data for four hydroelectric units illustrate the proposed methodology.

Air pollution from cars, vans and other different motor cars had observed in higher concentrations at public transportation stations. Now a day’s air pollutants from public transportation, industry, cooking from firewood and dust production alongside main roads in Addis Ababa is increasing and affecting human health. Individuals who live and work close to streets seem to have an expanded occurrence and openness to medical issues related to transportation air contamination. Appropriately, the Addis Ababa Light Rail Transit was the main current mass transit framework in Ethiopia just as in Sub Saharan Africa launched in 2015. Thus, this study aimed to know the air quality at LRT, bus, taxi and mixed stations through an air tracking device, and health effect at sampled public transportation stations. Air quality data include particulate matter (PM2.5, PM10), air quality index (AQI), carbon dioxide (CO2), humidity and temperature with a half-hour observation through Air-Visual pro for every 24 purposively sampled stations from North to South LRT line. The average measured air quality indicated that higher than 35 μg/m3 PM2.5 and 100 AQI, which is unhealthy. Regards to this, 30 persons were questioned at all stations. Seven hundred twenty (720) persons in total to know the health effect of those living/working in and around the stations. The findings indicated that out of 720 respondents, 324 (45%) have experienced to air quality-related diseases residing and working proximity to the stations. These suggested that the aged vehicles, land-use, dust and design of bus-stop shelter for waiting passengers have increased exposure to vehicles air pollution. Consequently, peoples are exposing to air quality-related respiratory diseases particularly unhealthy for sensitive groups.

Urban air pollution and exposure-related health impacts are being noticed and discussed very intensely in India. On the other hand, source-specific control is the primary focus for policymakers; however, diverse and complex sources make it difficult to immediately see the action and consequent impacts on better air quality. Many cities across the world have witnessed high air pollution levels at traffic junctions, more so in all Indian cities. Site-specific air pollution reduction can be a promising solution for managing the pollution level at highly polluted locations. CSIR-National Environmental Engineering Research Institute, India, has designed and developed Wind Augmentation and purifYing Unit (WAYU) to remove particulate and gaseous pollutants from urban hot spots such as traffic locations. In the present study, the authors attempted to evaluate the performance of two different designs of WAYU for the removal of particulate matters from polluted air at different traffic locations in Delhi City, the national capital territory of India. The performance analyses show that the current design of WAYU removes PM10 and PM2.5 concentrations in the range of 34–49% and 19–25%, respectively from the inlet air. The total PM collected from all WAYU devices was 34.19 kg from 120,557 operating hours’ at all the sampling sites. The PM removal rate depends on the size-segregated particulate matter pollution load in the ambient air. Supplementary Information The online version contains supplementary material available at 10.1007/s13762-021-03641-3.

The prime purpose of this study is to explore the use of RS and GIS for flood risk mapping in the Patna district in conjunction with the frequency ratio and entropy model. The variables such as elevation, LULC, rainfall, slope, distance from the river, TWI, and drainage density have played significant roles in causing floods in the study area. The flood vulnerability map has been generated and categorized as very high, high, moderate, low, and very low vulnerable flood areas. The validation of the results outcomes was conducted using the ROC curve, which indicates that the frequency ratio model for flood vulnerability mapping is more authentic, reliable and can assist in demarcating flood vulnerable areas and potential flood risk sites. The results show that about 16.35% (FR model) and 9.98% (SEI model) of the study area have come under very high risk of flooding, especially located in the southeast and northwestern sites of the district. The blockwise flood risk assessment shows that 13 out of 23 blocks recorded over 25% of their total area under very high flood risk. The present study reveals the usefulness of RS and GIS techniques along with bivariate models for the investigation and evaluation of flood vulnerabilities as they provide a wide range of data and reliable platforms. The results of this report will assist planners in developing flood prevention plans as part of regional flood risk management initiatives and will serve as a foundation for future studies in the study region.

Iran law makes municipalities responsible for recycling or disposing of household waste. Therefore, municipalities can use the geographical and cultural potential of each area as an opportunity to improve the situation. However, waste management would be impossible without people's participation. In Iran, neither has much effort been made to increase people's participation, nor have appropriate policies been implemented to increase the amount of recycling at source. In this study, an attempt was made to get citizens to participate voluntarily in household waste management for six months. They were encouraged to dry their food waste. The results of this study showed that due to the hot and arid climate of Iran and the pattern of Iranian food consumption, dehydration of food waste at the source of production can reduce their mass by a maximum of 80%, and as a result, the cost and frequency of collecting them will drop drastically. Moreover, implementing this method not only removed leachate but also increased people's responsibility for the produced waste. Therefore, one can conclude if people participated, Iran's geographical and climatic circumstances would allow food waste to dry at the source by imposing the lowest cost and energy consumption on households. In that case, the costs of collecting, disposing, managing of waste and leachate, as well as the environmental damage will reduce significantly. Also, waste separation will be done better because households have to separate their food waste from dry and recyclable waste.

Surface Urban Heat Islands significantly deteriorate urban sustainability and livability. Effective ways to monitor and mitigate this phenomenon are gaining importance among environment researchers. In order to lessen the extreme heat waves of tropical cities, an understanding of the spatial features affecting urban micro-climate is needed. Local climate zones can provide the much needed framework for city level climate studies. This paper presented satellite imagery-based workflow to identify critical zones within a city, using the spatial thermal characteristics. The results brought out the critical thermal scenario in summer, for two mega cities of India. Prolonged heat trapping resulted in 13.99% nocturnal heat island cover in the New Delhi region and 22.26% in the Kolkata City region. Moderate to strong heat stress was observed for central city areas, even at night time. Surface temperature variation within local climate zones of a city reflected significant rise in temperature over certain urban pockets due to building morphology. Over a distance of 12 km from vegetated land to low-rise dense built-up, a drastic 8.76 °C temperature rise was noted on a summer night. The temperature patterns were further verified with seasonal surface albedo mapping. Based on areal distribution, location, thermal range and contribution in heat island formation, sustainable planning strategies for each local climate zone were laid out. The study aimed to achieve an optimum cooling level for given urban structures and also highlighted the potential thermal environment changes faced by suburban regions.

The advent of new data acquisition and handling techniques has opened the door to alternative and more comprehensive approaches to environmental monitoring that will improve our capacity to understand and manage environmental systems. Researchers have recently begun using machine learning (ML) techniques to analyze complex environmental systems and their associated data. Herein, we provide an overview of data analytics frameworks suitable for various Environmental Science and Engineering (ESE) research applications. We present current applications of ML algorithms within the ESE domain using three representative case studies: (1) Metagenomic data analysis for characterizing and tracking antimicrobial resistance in the environment; (2) Nontarget analysis for environmental pollutant profiling; and (3) Detection of anomalies in continuous data generated by engineered water systems. We conclude by proposing a path to advance incorporation of data analytics approaches in ESE research and application.

This study aims to analyze the pattern of bank erosion and simulate the physical aspects of vulnerability in the lower Meghna River, Bangladesh using remote sensing (RS) and geographic information systems (GIS). The physical factors of vulnerability were analyzed using GIS-based Structured Query Language (SQL). A questionnaire survey, GPS survey and field observation survey were conducted for collecting the primary data in the study area. The secondary data were mainly satellite image collected from the United States Geological Survey (USGS) website. Using time series Landsat images (MSS, TM and OLI-TIRS), this study analyzed 36 years of erosion and accretion process in the Mehendiganj Upazila region from 1980 to 2016. The result indicates that an enormous amount of land (4470.47 ha) was submerged by the river and average land loss rate was 124.18 ha/year. The study quantifies the number of vulnerable households beneath the present condition and how much it will be altered after a positive/negative change with the factors of vulnerability related to the households. Simulation data reveals that under the present physical condition, 43.88% of households were identified as severely vulnerable. The output of this study can be used in the classification of vulnerable households and for the improvement of the physical infrastructure development process near the erosion prone areas, also helps to mitigate environmental disaster in the developing countries.

The goal of this study was to assess the impact of the introduction of various waste management methods on the amount of greenhouse gas emissions from these activities. The assessment was carried out on the example of the Russian waste management sector. For this purpose, three scenarios had been elaborated for the development of the Russian waste management sector: Basic scenario, Reactive scenario and Innovative scenario. For each of the scenarios, the amount of greenhouse gas emissions generated during waste management was calculated. The calculation was based on the 2006 Intergovernmental Panel on Climate Change Guidelines for National Greenhouse Gas Inventories. The results of the greenhouse gas net emissions calculation are as follows: 64 Mt CO2-eq./a for the basic scenario, 12.8 Mt CO2-eq./a for the reactive scenario, and 3.7 Mt CO2-eq./a for the innovative scenario. An assessment was made of the impact of the introduction of various waste treatment technologies on the amounts of greenhouse gas emissions generated in the waste management sector. An important factor influencing the reduction in greenhouse gas emissions from landfills is the recovery and thermal utilization of 60% of the generated landfill gas. The introduction of a separate collection system that allows to separately collect 20% of the total amount of generated municipal solid waste along with twofold increase in the share of incinerated waste leads to a more than threefold reduction in total greenhouse gas emissions from the waste management sector.

Rapid urbanization and poor management of solid waste in cities have escalated to unfavorable environmental impacts. This paper uses blockchain technology to propose a smart waste management system for mitigating the damaging impacts of traditional waste management services. This contributes to a healthy environment by optimizing the storage, collection, and disposal of solid waste. Blockchain, though in its budding stage, is believed to have a transformative impact on the world economy by enabling near real-time agreement of any transactions in a peer-to-peer and distributed manner. The growth of smart waste management systems using the Internet of Things (IoT) has been prevalent, but the use of blockchain in this application area is almost negligible. This paper identifies the problems associated with the traditional waste management system, defines algorithms that underpin the proposed smart waste management system, and compares the two systems by discussing how the latter alleviates the problems of the traditional waste management system. This paper utilizes smart contracts on the Ethereum blockchain to design a proof of concept of the proposed smart waste management system, and hence, the system can be measured at Technology Readiness Level 4 (TRL 4). This paper also calculates the cost of deploying the smart contracts onto the Ethereum private test net.

The purpose of this study was to determine possible damage created by recreational activities in Yedigoller (Seven Lakes) National Park and to recommend recreational impact management decisions in order to ensure its sustainable use. Four picnic and camping areas and one control area in the National Park were selected as sampling areas. In order to determine the ecological effects of recreational activities and the pressures on the plant life and the soil, an observation form was used. The study also addressed the stress on the Fagus orientalis trees in all recreation areas near Nazli Lake, Buyuk Lake, and Derin Lake. Findings from the soil analysis indicated that in general, intense human activities in the area had negatively affected both the physical and chemical properties of the soil. As a result of the evaluation of the observation forms, all of the sampling areas in the park were determined to be in poor condition. project titled Research on Possible Damage of Recreational Activities in Yedigoller National Park This study was supported by the project titled Research on Possible Damage of Recreational Activities in Yedigoller National Park upon the request of the Nature Conservation and National Parks 9th Regional Directorate of the Bolu National Parks Branch Directorate. We also thank Assoc. Prof. Dr. Hulya Torun for contributing to the measurement of the physiological parameters in the study. WOS:000674564600002 2-s2.0-85110806711

The design of an optimum hydrometeorological and hydrometric station network constitutes a key factor for the collection of comprehensive and reliable hydrometeorological and flow data that are necessary both for decision making in water resources policy and management, and for the hydrometeorological risk assessment. This article describes a methodology developed in a geographic information system (GIS) using a multicriteria decision making (MCDM) approach, which combines several spatial criteria to propose suitable locations for installation of such a station network in the Sarantapotamos River Basin in the western part of the Attica Region, Greece. Through the design of two networks that meet different requirements, various aspects concerning this methodology are illustrated, such as criteria weights determination, which is a problem that arises frequently in many MCDM techniques. The criteria weights for the hydrometric station network design are estimated using both the Analytic Hierarchy Process (AHP) and the Fuzzy Analytic Hierarchy Process (FAHP), while, for hydrometeorological station network design, all weights are equal. Hydrometeorological station final position selection is achieved by introducing the criteria of density and spatial distribution to the suitable locations. For hydrometric station network design, the analysis indicates that the criterion of slope mainly controls the MCDM outputs. According to station density thresholds proposed by the World Meteorological Organization (WMO), an optimum hydrometeorological and hydrometric station network for the region should comprise three and two stations, respectively.

Nitrate is a common pollutant in most of Asian countries, notably in underdeveloped countries like Afghanistan. From the very first hydrochemical studies, high nitrate level was of great concern. Also, multiple investigations have approved the concern as they showed dangerous content of nitrate in water resources in Afghanistan. Water projects have so far focused mainly on Kabul and then its chemical composition more defined rather than other main cities. The major source of nitrate in Kabul city is domestic sewage, including cesspits and latrines. Moreover, growing population is another major concern because more than 5 million live in the city, while the city’s potential is less than 2 million. Kabul city has suffered from an ineffective sewage network, and this imposed a high load of nitrate into the Kabul’s groundwater system. Studies showed that high percentage of samples—on average approx. 30%—had nitrate concentrations exceeding World Health Organization and Afghanistan National Drinking Water Standard limits, which is 50 mg/L. Then, this leads to a set of public health problems in Kabul’s residents. Hydrogeochemically, NO3 formation processes and following hydrogeochemical reactions are completely explained. In terms of denitrification, based on Kabul city condition and comprehensive assessments, permeable reactive barrier technique is highly recommended. The review provides a solid and knowledge-based framework for further projects and researchers. It increases public and global awareness concerning the extent of nitrate pollution in Kabul city and can serve as valuable reference for similar areas around the globe.

Soil erosion is a danger that threatens the world today and the basis of the fight against erosion must be sought in the role human. The aim of this study is determine a logical relationship between natural and planted forests conditions with soil erosion risk classes in the kasilian watershed. This basin is located in the Hyrcanian vegetation area on the northern slopes of the Alborz Mountains in northern Iran. In this research, the erosion risk map was prepared using the ICONA model and RS/GIS techniques and it was adapted to the physical realities of the area. The results showed that human interventions and pressures have reduced habitat good species percentage in the downstream areas in the northern part and upstream areas near the forest-rangeland boundary in the southern part. Also, the choice of species was incorrect in some planted forest. Therefore, high erosion risk class is clearly seen in these areas. There is a low erosion risk class (19.3%) in natural forest and a very low erosion risk class (2.73%) in plantation forest. The main reason for the high percentage of very low erosion risk class in planted forests can be due to the presence of 70–80% of canopy, which is a combination of 90% of broadleaf plants with 10% of conifers. These results are consistent with the realities in the study area. The ICONA model and RS/GIS techniques can be used as a reliable framework for erosion risk assessment.

Droughts can cause devastating impacts on water and land resources and therefore monitoring these events forms an integral part of planning. The most common approach for detecting drought events and assessing their intensity is use of the Standardized Precipitation Index (SPI), which requires abundant precipitation records at good spatial distribution. This may restrict SPI usage in many regions around the world, particularly in areas with limited numbers of ground meteorological stations. Therefore, the use of remotely sensed derived data of precipitation can contribute to drought monitoring. In this study, remotely sensed precipitation estimates from the POWER/Agroclimatology archive of NASA and their derived SPI for different time intervals were evaluated against gauged observations of precipitation from 13 different stations in arid and semiarid locations in Jordan. Results showed significant correlations between remotely sensed and ground data with relatively high R values (0.67–0.91), particularly where seasonal precipitation exceeded 50 mm/year. For evaluation of remotely sensed data in SPI calculation, several objective functions were used; the results showed that SPI based on satellite estimates (SAT-SPI) showed good performance in detecting extreme droughts and indicating wet/dry conditions. However, SAT-SPI showed high tendency to overestimate drought intensity. Based on these findings, remotely sensed precipitation from the POWER/Agroclimatology archive showed good potential for use in detecting extreme meteorological drought with the provision of careful interpretation of the data. These types of studies are essential for evaluating the applicability of new drought monitoring information and tools to support decision-making at relevant scales.

Anthropogenically influenced transboundary catchment areas require an appropriately adapted exposure modelling. In such catchments, water management decisions strongly influence and override natural river hydrology. We adapted the existing exposure assessment model GREAT-ER to better represent artificially overprinted hydrological conditions in the simulations. Changes in flow directions and emission routes depending on boundary conditions can be taken into account by the adopted approach. The approach was applied in a case study for the drug metformin in the cross-border catchment of Vecht (Germany/Netherlands). In the Dutch part, pumps to maintain necessary water levels and minimum flow rates during dry periods lead to a reversal of the (natural) flow directions and as a consequence to additional pollutant input from the Lower Rhine/Ijssel along with a spatial redistribution of emissions in the catchment area. The model results for the pharmaceutical product metformin show plausible concentration patterns that are consistent with both monitoring results and literature findings at mean discharges and the effects of the changed hydrology in times of low natural discharges, namely an increase in polluted river sections under dry conditions due to the pumping activities. The adapted methodology allows for realistic application of the GREAT-ER model in anthropogenically modified catchments. The approach can be used in similar catchments worldwide for more realistic aquatic exposure assessment.

Treatment of biodegradable waste using the black soldier fly larvae (BSFL) is an emerging waste treatment technology attracting entrepreneurial activities around the globe, mainly because the larvae grown on the waste have the potential to become starting material for several commercial products such as animal feed, biodiesel, chitin as a biopolymer, and soil fertilizer. Insect-based waste treatment technology offers a financially viable solution for the solid waste problem mitigation, which otherwise has been an arduous task for many parts of the globe, especially for the developing nations. Although considered a better alternative than other well-established technologies such as composting or anaerobic digestion, the technology is still in its infancy. The researchers and entrepreneurs who wish to gain an insight into and develop the BSFL-based waste processing technology further, require to have a holistic understanding of the various ways in which the performance of BSFL technology can be enhanced and its scaling-up can be formulated to solve the waste management problems in community- and city-level. This review article is a collection of state-of-the-art knowledge on various aspects related to the technology development for full-scale utilization for commercialization purposes, such as the artificial rearing techniques of BSF, waste stabilization performances of the BSFL at different environmental conditions, and the effects of micronutrients and associated microorganism communities.

E-waste is the globally mounting solid waste stream which is increasing due to domestic as well as a result of transboundary exportation. This solid waste stream is considered as an amalgam of valuable and toxic material which is concern of environmental and human health risks. To accomplish successful management of electronic equipment after post-consumer stage, numerous lucid initiatives have been offered globally. The ever-increasing quantum of e-waste has enforced environmental organizations of many developing world such as India and China to invent, and implement environmentally favorable opportunities and strategies for mitigation and control of environmental and human threat. Many developed countries have given topmost priorities for e-waste management, so setup appropriate facilities to treat maximum of the generated e-waste, but in low economic nation like India, economic conditions, infrastructure scarcity, and inappropriate legislations are some of the problematic issues which dodge complete replication of the WEEEs management system. Our study represents an evaluation and valuation, of e-waste generation and cross-border movement to the management strategies followed in highly industrialized as well as developing nations. These findings would expand into regulated and non-regulated countries to put more emphasize on e-waste management.

The role of technological innovation in lowering the pollution is motivated by the rise of global emissions. Technological innovation for carbon dioxide mitigation mainly focuses on the role of patents ignoring trademarks. This study tests the role of eco-patents and trademarks for carbon dioxide alleviation using data from 2000 to 2018. This study introduces a new interaction term by combining trademarks and eco-patents and examining the role of environmental policy, energy consumption, environmental taxes, urbanization, and economic growth on the environment. The panel effect is tested using the Nonlinear ARDL and OLS methods, whereas country-specific results are estimated using the Granger causality approach. The outcomes reveal that trademarks and eco-patents decrease carbon dioxide emission; however, energy consumption, urbanization and economic growth are the main polluters in both regions. Environmental policies and taxes have a significant impact on the western region’s mitigation efforts, while insignificant evidence is found for the southern region. Unidirectional and bidirectional causal relationships are observed among the variables; still, the outcomes are country-specific. The study also provides policy implications based on the results.

Soil is a living heterogeneous body mass consists of solid, water, gases, organic, inorganic matters and organisms and acts upon as a source and sink of any contaminant. Nanotechnology is a diversified, dynamic and transformative technology, which stimulates the scientific innovation for the betterment of different sectors of the society which produces large number of nanocontaminants. Nanocontaminants in the soil are a major concern because of their toxicities with subsequent threat to soil, environment and human community. These contaminants may badly influence soil ecology, crop production, or product quality, ground water purity and human health. Moreover, the safety protocol for the specific nanocontaminants is yet to be developed to protect our environment and ecology. Of late many research experiments were conducted to investigate and comprehend the outcome, lethal dose and behaviour of nanocontaminants and consequently to extend this knowledge for development of bio-safety protocol to handle the nanocontaminants in the coming decade. Research initiatives are focused on to understand the impacts of manufactured nanoparticles on human being, soil and formulate combat mechanisms to mitigate the adverse consequences of nanocontaminants on human health and soil quality. While this attempt signifies an exclusive chance for soil scientists to investigate these highly potential technologies, it also emphasizes on foremost challenges to a field of research that has great scope to predict the consequences of nanocontaminants on the soil ecology and animal health. Currently nanocontaminants draw the major world research attention and need more endeavours to entirely assess their impacts. This review documented an outline of impacts of nanocontaminants in soil, which highlights the understanding of major interactive effects of nanocontaminants on soil organisms, plants, and human. This article also provides highlights of the challenges that soil researchers and policy makers face when developing risk assessment tool for nanocontaminants in soil and subsequently for human being.

Flood hazard zoning is an important problem that has received much attention from environmental researchers. This problem requires complex spatial analysis; hence, numerous criteria have to be assessed. Factors contributing to the flood formation includes both natural and socioeconomic ones. However, the central question is what factors are important in creating a flood and how to quantify these factors. To answer this question, one of the popular approaches is the analytical hierarchy process (AHP) developed by Saaty. The usage of the AHP algorithm to calculate the weight of each factor is one of the main steps in the process of creating a flood hazard map. This paper will provide an overview of the factors that affect flood formation and analyze their weight by selecting and evaluating the degree of effect of factors in various research using the AHP algorithm. The results can be used as a reference for studies on flood risk zoning in different basins when selecting the impact criteria.

Aviation has the most intense impact on air quality during the landing and takeoff cycles (LTO) of aircraft operations, which are defined as being equivalent by aircraft manufacturers, airport managers and regulators. In this study, an environmental impact assessment and cost analysis study was conducted, taking into consideration airline traffic data from 2018 of Turkey's biggest commercial airline company. Calculations are based on the LTO cycle. Emissions evaluated in the study are CO, CO2, HC and NOx. In order to assess the emissions, the aircraft types in which the airline forms the fleet, tail numbers, engine types, number of seats, passenger-carrying capacity, emission indices at different power settings of the engines and annual passenger traffic of the aircraft have been employed. In addition, two approaches are employed to explain the meaning of emissions: the amount of environmental impact and the environmental damage cost. In the light of data generated by calculating the annual environmental costs of the fleets, fleet renewal or employment of new engine technologies can be caused to low-emission tariffs that achieve more efficient combustion. As a result, changing the engine combinations of aircraft in the Turkish Airlines fleet will result in fewer emissions and therefore less cost. The important thing is the optimization of the ratio of the cost of environmental impact on the cost of changes in the combination of aircraft engines.

Like other large-scale development projects, the design, construction, and utilization of subway projects have several positive and negative environmental consequences. In this study, geological hazards in the construction phase of Ahvaz Subway Line 1identified and localized. The environmental impacts also were assessed in the surface and subsurface sections. During the surface evaluation, after providing and preparing the required information layers, AHP and TOPSIS methods were used to model the environmental effects in the subway route. During the subsurface evaluation, the subsidence, liquefaction, soil corrosion, and RQD characteristics were examined separately in a vertical section. The results showed that Stations 1, 2, 11, and 12 had the most significant potential for environmental hazards at the surface section. Assessing the subsurface conditions showed that due to the type of alluvial material and lithology and water table, subsidence was possible in a subway route. Due to the region's seismic conditions, seismic stresses can cause soil displacement and tunnel collapse along the subway route, especially during the construction phase. The soil chemical test results showed that soils in the subway route had moderate to severe corrosion potential.

Climate change is strongly affecting the Himalayas. Geologically young and fragile, the Himalayas are sensitive to even minor changes in the climate. Regional warming in Himalayas has been observed between 0.15 and 0.60°C per decade, which is higher than the mean global warming rate of 0.74°C per 100years. Consequent to this warming trend, the glaciological changes in Himalayas are obvious, which has resulted in the formation, expansion and disappearance of various types of glacial lakes. The dangerous lakes among these pose threat to downstream community and infrastructure. In this study, an attempt has been made to critically analyze the progress in Glacier Lake Outburst Floods (GLOF) research and understand its dynamism from multiple approaches through a meta-analysis of peer-reviewed scholarly literature for a period of 2001–2020. The study has found that the glacial lakes in the study region are increasing in number and expanding rapidly owing to the climate change and anthropogenic causes as the Glacier Lake Outburst Floods (GLOFs) are becoming common. The expansion rates of pro-glacial lakes connected to glaciers and moraine-dammed lakes are faster than other type of lakes. Findings from the studies on area change analysis in the region reveal that a number of expanding glacial lakes can emerge as potential sites for future GLOFs, hence need immediate monitoring and observation. Geospatial tools and techniques coupled with field investigations have been found as a potent tool for mapping the evolution and propagation of GLOF hazards resulting from accelerated shrinking and thinning of glaciers and continued lake expansion. Further, the satellite-based remote sensing and modeling has been found as an excellent tool for GLOF management as well as reconstruction of previous GLOF events and prediction of future outburst potential. The idea of this study is linked to the increased incidence of GLOF events in the Himalayan region. This study will help in better understanding of glacial lake expansion and provide scope for future research in devising risk management action plans of potential GLOFs by selecting expanding glacial lakes as case studies.

Flood-control infrastructures—channelization, levees, and dams—are considered as the flood mitigation which can control flood disturbances of rivers. However, the flood mitigation, which is deemed as a rigid and one-dimensional approach, not only increases the frequency and severity of floods but also destroys the ecological and societal aspects of rivers. The Kan River, in Tehran, is one of the rivers which is equipped by channels, but it is still considered as one of the chaotic rivers in Tehran. Therefore, an alternative plan instead of channelization is required in order to mitigate the floods of the river. In this regard, we seek to propose an indigenous and flood-friendly plan for the river against flood disturbances. To this purpose, the theoretical foundation of social-ecological resilience is considered as an appropriate approach; thus, the theory of social-ecological resilience is reviewed, and its indicators are extracted. Then, based on the inherent characteristics and landscape of the river, a resilient plan in the face of floods is proposed. We argue that the river should be considered as a dynamic and social-ecological phenomenon. Such a view would help to overcome the disturbances of the river and avoid the one-dimensional planning and approaches. In addition, we suggest that the indicators of social-ecological resilience can be utilized to provide and suggest large-scale, middle-scale, and micro-scale strategies in order to improve the resiliency of the river against floods. The findings of this paper can be applied to the rehabilitation of chaotic urban rivers globally.

Purpose of ReviewAs the application space for energy storage systems (ESS) grows, it is crucial to valuate the technical and economic benefits of ESS deployments. Since there are many analytical tools in this space, this paper provides a review of these tools to help the audience find the proper tools for their energy storage analyses.Recent FindingsThere are many software tools for valuating ESS. These tools can be classified into two groups: (1) power system simulation and planning tools for analyzing the technical contributions of ESSs, and (2) techno-economic analysis tools for valuating the economic benefits of ESS deployment and specifying the optimal design of energy systems that include ESSs. While many of the tools, developed by the national laboratories, are free to use, the commercial tools are also of great importance in meeting the customers’ specific needs.SummaryThis paper provides a review of software tools for ESS valuation and design. A review of analysis tools for evaluating the technical impacts of energy storage deployments is also provided, as well as a discussion of development trends for valuation and design tools.

Variability in precipitation results flooding and drought worldwide. The climate change has a close relationship with the precipitation and temperature pattern as well as river discharge. In this research, spatial and temporal rainfall variability have been analyzed. The rainfall data of seventeen meteorological stations for the period of 1980–2018 was acquired from China Meteorological Administration. To assess drought in the study area, the standardized precipitation index (SPI) was applied and to check the temporal drought trend the Mann–Kendall test was applied, while the data normality was checked through skewness, kurtosis, and standard deviation. The Mann–Kendall results shows decreasing rainfall and increasing drought trend in the study area. The study area southwest Xinjiang is an arid region and the decreasing rainfall trend will further aggravate the conditions of already endangered flora and fauna in the region. This study will provide a platform for decision makers to take proactive actions to mitigate the risk of increasing drought in the study area.

First of all, this paper which is based on the panel data of 30 provinces, 27 manufacturing industries, and 1164 listed manufacturing companies in China measures the technological innovation efficiency of the manufacturing industry and then establishes the dynamic system generalized method of moments model and panel threshold model from the regional, industrial and enterprise levels to analyze the impact of environmental regulations on the technological innovation efficiency of China’s manufacturing industry empirically. The results indicate: three kinds of environmental regulation tools have different influences on the technological innovation efficiency of the manufacturing industry and have a certain time lag effect. Overall, environmental regulation has an inhibitory effect on the technological innovation efficiency of the China’s manufacturing industry in the same period. Still, it has a promoting effect on the lag stage. Threshold regression results show that the market incentive environmental regulation tools have a threshold effect on technological innovation efficiency, and there is an inverted "U" type relationship between them. Therefore, China should propose regulation methods according to the environmental pollution situation in different regions, promote enterprises to carry out technological reform, and improve the efficiency of technological innovation.

An overview on the assessment of wind energy technology adoption and the extent of penetration of wind energy as an alternative energy source in different regions of the world is presented. A global scenario of Asia, Americas, Europe and Gulf States were reviewed and particular attention was centred on the successes of wind energy in Africa. The four major drivers—global warming, natural disasters, crisis and agreements—that have affected growth of wind energy technology were discussed. The economics of wind energy technology particularly as a grid connected solution was reviewed, challenges in the roll-out of wind energy technology were also highlighted. Finally, the prospects and future of wind energy as part of the overall energy mix was reviewed.

Globally, the rising level of air pollution is becoming a cause of serious concern. The situation has reached such an alarming situation that knowing the extent of air pollution well in advance has become an absolute necessity before we step out of our home. An advance prediction can help the urban travellers to know the possibility of enhanced pollution ahead of time at strategic locations of a city and thereby be useful in planning a less polluted route. Different cities of the world have pollutants levels with varied dispersion pattern. As a result, a generic prediction model is needed that can cater to all types of pollutants and which can offer better forecasts of pollution data irrespective of their dispersion levels. In this paper, the authors modelled recurrent neural network (RNN)-based bidirectional long short-term memory (Bi-LSTM) that forecasts pollutants concentration with least RMSE. The model is trained and tested on the pollution data of Delhi, the most polluted capital city in the world for the second consecutive year in 2019. Air pollutants like PM10, PM2.5, NO2, O3, and CO are considered that have a varied dispersion pattern. To test the efficacy of our predictions, the model is tested on real data obtained from the Central Pollution Control Board (CPCB) of India. The performance metrics are also generated to evaluate the performance of the proposed model.

Presently, the progressive concern for the adverse effect of mining has emphasized the significance of reclamation in derelict mine site. The manuscript aims to present a scientometric analysis followed by a review on eco-restoration of heavy metal polluted mine spoil, tailing and to develop a timeline analysis done in the last 10 years (2010–2020). Web of Science (WoS) database was used to obtain the desired data set, and these are analysed based on WoS categories, leading journals and contributing countries. According to these databases, research progress was delineated to draw a clear picture of the scientific status and progress and to develop knowledge gap in this area. China is the leading country in eco-restoration-based study for heavy metal remediation in mines. Among the categories, “Environmental Science” has the highest number of publications in this domain. After reviewing various literature, it is evident that vegetation cover has the ability to remediate mine derelict sites. Most of the studies reported that woody, fast growing, native vegetation cover suit best for heavy metal remediation. The use of vegetation cover native to the mining sites should be prioritized as they are better indicator of reclamation success due to their high biomass, fast growing, ability to acclimatize in adverse environmental condition in nature. Lastly, as most studies focused on the recuperating soil properties, the application of innovative genomic approaches (recognising genetic markers for abatement of contaminants) to heavy metal remediation practice should also be amplified to develop new concepts of land reclamation in mining area.

Due to its sensitive geopolitical situation as well as giant oil and gas fields, the Persian Gulf has exceptional environmental conditions. However, it is one of the most polluted maritime zones because of strategic sensitivities that have consistently led to political and military tensions, enormous economic resources and marine structures for natural resource extraction. Given the importance of the marine environment, the lack of comprehensive resource monitoring and management and pollution control plan results in environmental degradation. Oil and gas piers are one of the most common offshore structures that may be deteriorated and lead to human and financial losses as well as irreparable environmental impacts. Therefore, damage detection in the early stages of marine structure development is of great importance. The modal strain energy is a non-destructive damage detection method for concrete structures that estimates the damage localization or severity by changing the dynamic properties of the structure. Making some corrections to the previous versions of the modal strain energy method, this study aims to estimate the damage location and severity of a real sample of pile-deck LPG pier in the South Pars Gas Field (Assaluyeh) of Persian Gulf numerically and experimentally. Results showed that the present method has higher accuracy in locating damages than the other methods. Also, single and multiple damages of low and high severity were estimated by this method with good accuracy.

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The low-cost sensors and IoT have come to the rescue due to the high cost and operational complexity of equipment and methodologies in environmental monitoring. They are relatively inexpensive and reliable. It is on this assumption that we have decided to use the World Air Quality satellite data supplied by air matters.com. This study is a 40-day preliminary work in which air quality (Air Quality Index (AQI), PM2.5, PM10, NO2, CO, SO2, and O3) and meteorological (temperature, humidity, and wind speed) parameters were monitored. The data collected was for five locations in Lagos State, Nigeria (Ojodu, Opebi, Ikeja, Maryland, and Eti-Osa). The data obtained were subjected to basic statistical analyses. The findings showed that the Opebi had the highest mean value of PM2.5 (69.28 µg/m3), PM10 (107.38 µg/m3), and CO (1392 µg/m3). The mean values of O3 are as follows: 32.52, 38.7, 36.2, 37.85, and 36.13µg/m3 for Ikeja, Maryland, Opebi, Ojodu, and Eti-Osa respectively. Opebi had the highest value (3179µg/m3), followed by Eti-Osa (2978µg/m3), and the lowest value in Maryland (1943µg/m3) among the CO reference locations. AQI of all locations presented the levels of contamination as 'Unhealthy for Vulnerable Groups'. The pollutants were much higher than the World Health Organization (WHO) guidelines. There were relationships between the parameters monitored and meteorological influences, and the effects of natural and man-made activities may be the sources of the elevated pollutants throughout the locations.

This paper studies the shoreline alterations occurring along the Al Batinah region in the Sultanate of Oman and the impacts of Cyclone Kyarr on its shoreline. The methods used in this research employed Sentinel images and the Digital Shoreline Analysis System within the GIS environment to measure changes of the shoreline and explore Kyarr’s impacts from 2017 to 2020. The results showed that from 2017 to 2020, the Al Batinah coast experienced erosion at a rate of 9 m/year. In addition, the Shoreline Change Envelop showed that the maximum shoreline change was reported from 2018 to 2019, with a 1145 m advancement that coincided with Kyarr in 2019. Further, data from the period between 2017 and 2018 showed that 73 % of the coastline was dominated by soil deposition at an average rate of 10 m/year, while the period between 2018 and 2019 showed erosion at an average rate of -40 m/year. The results of this study will be of interest to decision-makers involved in monitoring shoreline changes and would also be of immence importance in ensuring sustainable coastal zone management and development, especially in areas prone to extreme events such as tropical cyclones.