The main purpose of this study is to explore the dynamic association between financial development, tourism, primary and renewable energy utilization, urbanization, and carbon emission by employing the longitudinal data of 52 countries from 1995 to 2017. Empirical results of panel pooled mean group-autoregressive distributive lag (PMG-ARDL) model reveal that financial development significantly improves the environmental quality in developed countries. However, it has a detrimental but insignificant effect on the environment in developing countries. In the case of developed countries, the profound tourism sector is more harmful to the environment due to a large number of tourist arrivals in contrast to the developing countries. There is a wide difference between developed and developing countries concerning industrial, regional, and economic structure, in the effect of financial and tourism development on carbon emission, but both urbanization and primary energy utilization promote carbon emissions. The utilization of renewable energy sources improves the environmental quality in both regions. Generally, it is suggested that investment in renewable energy resources in both regions affects pollution differently and still has the potential to accelerate environmental quality. Moreover, the panel causality test explores that there exists bidirectional causality between financial development, primary energy, and carbon emission in both regions, while a unidirectional causality is observed from urbanization to carbon emission in developed countries. In developing countries, it exists from tourism to carbon emission and carbon emission to renewable energy. Finally, from policy perspectives, the results of this research recommend developing the financial system, and more funds should be allocated in modern and eco-friendly energy projects and utilized energy-efficient technologies.

In the present paper, province-level variations of novel coronavirus (COVID-19) disease incidence across Iran were investigated. To this end, a geo-database from infected cases, deaths, total population, death-to-population ratio, and infected case-to-death ratio for 31 provinces of Iran and during seven successive periods of February 18–March 19 (P1), March 20–April 8 (P2), April 9–April 28 (P3), April 29–May 20 (P4), May 21–June 20 (P5), June 21–September 21 (P6), and September 22–October 21 (P7) of 2020 was built. Based on the last reports of the population and housing census (2018), Iran is home to 81.8 million people. Nationwide case series of 536,181 and 29,403 infected cases and deaths respectively with COVID-19 were reported to Iran’s Minister of Health from February 18 to October 21, 2020. Of the infected cases, 5.48% have died. The spatiotemporal patterns of COVID-19 were different throughout the 31 study provinces. Firstly, the central, north, and northwest of Iran were the main hosts of this virus. Shortly after, other parts of Iran, most notably the west and southwest regions, experienced a momentous rise in the numeral of infected cases and deaths. In the first study period, Tehran, West Azerbaijan, Mazandaran, Qom, and Gilan had the most infected cases (> 1000). In the second to fourth periods, the number of provinces with higher than 1000 infected cases, respectively, reached 12, 10, and 17. For the last three periods (P5–P7), 31 provinces were assigned higher than 1000 infected cases. Tehran had the most deaths with an increasing trend for all study periods among other provinces. The areas around Kohgiluyeh and Boyer-Ahmad, Bushehr, Chaharmahal and Bakhtiari, South Khorasan, and Ilam had the least death cases. The numbers of infected (death) cases in Iran for the first to seventh periods (P1–P7) respectively were 16,730 (1208), 41,285 (1595), 28,530 (1876), 16,366 (1856), 80,694 (6588), 201,585 (6232), and 128,336 (6953). The location quotient (LQ) index showed that most provinces of Iran have the LQ > 1 indicating a high degree of COVID-19 concentration in most of the province’s area in comparison with the nation, especially in the last study period (P7).

We aimed to review the literature to find the specific effect of opioids on the activity of cholinesterase (ChE) enzyme which plays a substantial role in the functioning of cholinergic system. Literature search was performed by two independent reviewers in order to find relevant articles about the changes in the activity of ChE in mice or rat following opioid administration. Based on findings from literature review, opioid administration is able to induce cholinergic modulation via decreasing or increasing the activity of ChE enzyme. However, the degree of variation of ChE in various brain regions is different. No gender differences was reported in the effect of opioids on ChE activity. Although chronic opioid administration may decrease enzyme function, ChE activity might be unchanged following opioid withdrawal using naloxone or the development of tolerance. Opioid type affects whether or not naloxone can reverse the changes of ChE. Direct inhibitory action of morphine and the other opioid ligands believed responsible for the decrease in the ChE activity. Moreover, the potency of codeine to induce allosteric enhancement of acetylcholine receptor signaling might be involved in the cholinergic modulation of codeine and other opioids. Animal studies on rat and mice showed that opioids may change the activity of ChE. These changes can pertain an increase or decrease in enzyme activity; as there might be no change. The type of opioid used may have an effect on the cholinergic modulation. It is beneficial to conduct cross-sectional and cohort studies on addicted individuals, especially opium abusers, to find the precise association of opioids with alterations in human acetyl cholinesterase or butyrylcholinesterase. Simulation studies can also examine the structure-function relationships and provide important details to better understand the mechanism of action of opioid compounds on ChE activity. In addition, understanding how opioids impact ChE activity may help perform proper interventions for drug abstinence.

The purpose of this study is to determine energy use patterns, evaluating the environmental impacts and economic evaluation of smoked fish production in the Guilan Province. The initial data were collected from seven smokehouses in the north of Iran through face-to-face questionnaire method, while the required data related to the background system were extracted from the Ecoinvent 2.2 database. The total input and output energy result showed the use is examined to be 98,143.29 and 60,048 MJ ton⁻¹, respectively. About 79.31% of this was generated by fish, 7.7% from electricity, and 6.7% from wood chip. Life cycle assessment results showed that fish and salt emissions have the most notable effects. Among damage categories, the largest emissions were related to human health (37.77%). Climate change (30.35%), resource (28.78%), and ecosystem quality (0.92%) are next phases. The rates of nonrenewable, fossil in CExD method calculated 35,426.61 MJ ton⁻¹. Economic analysis of production was carried out. Some economic indicators have been calculated, and the benefit to cost ratio was obtained as 3.09. Due to the justification of fisheries management, these issues merit further exploration.

Currently, there is a major problem of water contaminations, especially of dyes, all over the world. A new technique is being developed daily for the treatment of contaminated water. In many ways, a photocatalytic degradation of a dye by a mixed metal oxide photocatalyst is counted as the best technique for water treatment. This paper also addresses the preparation and photocatalytic application of newly developed mixed metal oxide nanocomposite, CuO-ZnO-CdWO₄. A novel mixed metal oxide CuO-ZnO-CdWO₄ nanocomposite has been synthesized by a green route using Brassica Rapa leaves extract. The application of CuO-ZnO-CdWO₄ as a photocatalyst in wastewater treatment has been thoroughly discussed. Several spectroscopic and microscopic techniques were used to characterize the prepared nanocomposite. The photocatalytic activity of CuO-ZnO-CdWO₄ nanocomposite with a band gap of 3.13 eV was observed under the artificial visible light and sunlight for the degradation of Congo red dye. The results under sunlight show the 1.45 times greater removal efficiency than under the artificial visible light. Pseudo-first-order, diffusion, and Singh kinetics models were used to describe the kinetics of dye degradation. Pseudo-first-order model was found to be best fitted model for present study. The performance of CuO-ZnO-CdWO₄ was estimated by significant parameters such as quantum yield, figure of merit, turnover number, and mean turnover frequency. The value these parameters were calculated as 1.70 × 10⁻⁸ molecules photon⁻¹, 1.77 × 10⁻⁴, 2.98 × 10⁸ s⁻¹, and 3.31 × 10⁻⁴ s⁻¹, respectively. These parameters revealed high potential of CuO-ZnO-CdWO₄ for Congo red dye degradation.

Monitoring the concentration of particle pollutants is very important for industrial production control and workers’ health protection. Low-cost sensors are widely used to reduce deployment costs. The outliers in the observed data of pollutant concentration can be eliminated by outlier detection algorithms. However, it is difficult to meet the actual needs of changing working conditions or scene migration in factories by building a single algorithm for specific scenarios. It is a feasible scheme to identify the changing characteristics of data and adaptively adjust the outlier detection algorithm. From the point of view of data characteristics, we creatively match typical data types with high-performance algorithms. The framework proposed in this paper provides a general process including five basic tasks and uses a modular structure to complete the outlier detection target. The actual pollutant data of the workshops are used to evaluate the performance of our framework. At last, we compare eight different strategies under this framework and analyze the contribution of each step to outlier detection from the perspective of algorithm principle. The results show that low-cost sensors following the framework can meet the outlier detection requirements in the field of pollutant monitoring, thus greatly reducing the cost of algorithm selection and data adaptation.

Public acceptance of treated sewage (TS) reuse in agriculture is a key element in successful implementation of TS reuse projects, but relevant research on the topic is limited. This study examined public willingness to accept (WTA) and willingness to pay (WTP) for agricultural products derived by irrigation with TS in Lorestan province, Iran, applying the contingent valuation (CV) method. The agricultural products determined for the study included corn, peaches, apricots, and plums, while TS was introduced in three qualities [Q1, complete TS treatment (i.e., physical treatment, aeration, and chemical treatment); Q2, partial TS treatment (i.e., physical treatment and aeration); and Q3, no TS treatment]. With reference to WTA, products irrigated with Q1 TS received 62.7% positive responses, while products irrigated with Q2 TS and Q3 TS received 21.3% and 17.0% positive responses, respectively. With reference to WTP, data showed that if the price of products derived by irrigation with TS was less than that of products irrigated with fresh water, some people would be willing to pay for these products (52.0% positive responses versus 48.0% negative responses). Awareness had a significantly positive impact on WTA1 and WTA2 (products irrigated with Q1 TS and Q2 TS, respectively) as well as on WTP1, WTP2, and WTP3 (products irrigated with Q1 TS, Q2 TS, and Q3 TS, respectively). Similarly, information sources had a significantly positive effect on WTP1, WTP2, and WTP3. Overall, individuals with high levels of health risk perception and high awareness showed high WTA, while non-processed corn and men were associated with low WTA. Concerning WTP, individuals with high awareness and those who had access to information sources showed high WTP, while men were associated with low WTP. Information about the importance of TS reuse, reduction of prices of products derived by irrigation with TS, and promotion of public confidence in TS are essential to increase public WTA and WTP.

Vegetation-growing Concrete (VC), as a new type of cemented soil, is usually used for plants growing on the surface of high and steep rocky slopes. With the widespread application of VC substrate, a pressing problem arises to ensure its durability under wetting and drying conditions. To explore the greatest possible impact on the mechanical properties and microstructure features of VC substrate, an experimental program including triaxial test, SEM analysis, and ultrasonic testing was implemented. The results showed that wetting and drying cycles can significantly decrease more than 40-percent of peak strength, 60-percent of residual strength, and 50-percent of cohesion for VC substrate under ultimate conditions. The fundamental cause of reduction in mechanical performance was found to be the weakening of the bond between soil particles. And it was discovered that structural damage increased as the number of wetting and drying cycles increased but at a slower rate. Based on the tested results, linear functions between the loss extent parameters of mechanical performance and the structural damage variable were established for the VC substrate. Finally, the action mechanisms of wetting and drying cycles for VC substrate were discussed, and the main influential factors were proposed.

The exponentially multiplying population of the world demands increasing freshwater resources. Thelimited resources comprising less than 3% of the earth’s water resources are getting polluted at an alarming rate. To deal with this situation, seawater reverse osmosis is being carried out at large scales across the globe. The concentrate generated in return is two times more concentrated in terms of total dissolved solids when compared to the feed. The adverse effects of the concentrate stream on the marine ecosystem and further pollution of water cause an immediate need to treat the concentrate. In this review, the harm caused by the direct discharge of concentrate stream has been discussed and therefore volume minimization using treatment methods has been addressed. The treatment methods are mainly classified into four types; membrane-based, thermal-based, electricity-based, and chemical-based methods. Integrated methods, which have been mainly tested on a pilot scale for zero liquid discharge, have also been discussed. The treatment methods that are probable for seawater concentrate treatment falling under the above categories for other concentrate sources have also been attended to. Finally, the disposal methods employed for the discharge of the leftover concentrate have been addressed. Thermal methods are well established but require a lot of energy compared to other methods whereas chemical methods can be economic due to the profit obtained from recovered chemicals, but they are mostly employed for pretreatment. Electricity-based and membrane-based methods are emerging technologies. It was also found that seawater reverse osmosis concentrate is usually discharged directly and therefore integrated methods based on zero liquid discharge are to be implemented. To compensate for the intensive research required for zero liquid discharge to become a reality, innovative and environmentally-friendly disposal methods are available to cut the resultant footprint.

In today’s world, with ever-changing pollutants and their concentrations, the designing of low-cost meteorological systems is unavoidable for assessing environmental parameters. Wireless instrumentation is an effective way of measuring the physical quantities as it can measure and transmit the data to the targeted location at high speed. In the present work, an IoT-enabled embedded system was developed to measure the concentration of carbon dioxide, ozone, and the presence of smoke. The ARM microcontroller reads the sensor data and processes the information to calculate the pollutant parameters. The measured data is displayed on the LCD, mobile phone, and a computer simultaneously using wireless technology. With Embedded C, the Keil compiler was used to develop the interfacing software for the designed system. Portability, user-friendliness, and reliability are the significant advantages of the device compared with the conventional systems, and it can be widely used as an inexpensive solution for the monitoring of environmental conditions.