Issue 10

Every year, the number of people who die because of pollution rises, with air pollution being the major cause. Air pollution is generated by a variety of factors, one of which is pollution caused by automobiles. Technological improvements make great efforts to detect accidents and monitor the increasing pollution. In this paper, a novel Internet of Things-based Vehicle Gas Emission Monitoring System (IoT-VGEMS) to monitor and control the reduction of gas emissions. The overall work is categorized into two sections: One is Transmission Part, and the other is receiving part. The Transmitting Part consists of Arduino UNO, MQ-135 Sensor, and nRF24L01 transmitter. The Receiving Part consists of Arduino UNO, LCD Display, GSM, and nRF24L01 receiver. Initially, creating code to sense the data from the MQ-135 sensor to the Arduino UNO and store the data in Arduino 1 is fetched to transfer with the help of the nRF24L01 module. Using an Arduino UNO to interface with a GSM module. GSM module that would deliver the warning and intimation messages to the vehicle owner and display them on LCD. Finally, GSM can able to send a message to the respective user if the pollution level exceeds the threshold. Hence the message from our device will give information about the emission and the user could rectify it. Few people will not take any action even if they receive a warning from transport officials, they will be penalized further.

Air pollution monitoring is becoming increasingly important, with an emphasis on the effects on human health. Because nitrogen dioxide (NO2) and sulphur dioxide (SO2) are the principal pollutants, many models for forecasting their potential harm have been created. Nonetheless, making precise predictions is nearly impossible. The prediction of air pollution enables researchers to understand how pollution affects human health. Deteriorating air quality can lead to respiratory diseases such as lung cancer and asthma. The effect of pollution on environmental degradation can also be predicted and reductions can be detected in the ozone layer. This study also focuses on and promotes the development of smart city environments by obtaining influential pollutants that affect the air, thereby reducing the source of specific pollutants An Artificial Neural Network (ANN) model is used as a forecast the pollution and the starling murmuration optimization (SMO) procedure is used to optimise the Artificial Neural Network strictures to achieve a lower forecasting error. Furthermore, in this research work, we used real time dataset as we have used Winsen ZPHS01B sensor module to collect the data, which is stored in cloud platform. After the composed data is used to train and test, after this process we will evaluate the results. To assess the performance of the suggested model. Furthermore, the perfect has been tested using two alternative kinds of input parameters: type as, which contains various lagged values of variables (NO2 and SO2), and type as, which only includes lagged values of the yield variables. The collected findings suggest that the projected model is more precise than existing joint forecasting benchmark models when different network input variables are considered.

The goal of this work is to evaluate generation estimation and metals recycling potential of retired mobile phones in Philippines. The generation estimation is conducted with the sales&new method and statistic data, such as sales of mobile phones and amount of the subscribers. The result shows that there are 18.11 million of mobile phones retired in 2021, compared 6.31 million in 2010. Accordingly, the deduced lifetime have minimum and maximum value in 2016 and 2011, which is 4.24 and 27.22 years, compared with 9.02 years in 2021. The crosscheck testifies to the veracity of the result in comparison with the actual condition. The metals recycling potentials and dynamic are also calculated with the content and amount of retired mobile phones. The result shows that the metals recycling potentials and dynamic increase with the increasing amount of retired mobile phones in Philippines.

Methyldimethylhydrazine and its by-products cause serious damage to human health. In this paper, Re3+-doped mesoporous TiO2 were synthesized for the photodegradation of UDMH. The structure, morphology and optical properties of photocatalyst were extensively characterized. The photocatalytic degradation was significantly enhanced, and 2%Nd-TiO2 showed the most excellent photocatalytic degradation performance with 93.3% degradation rate of UDMH. NDMA and FDMH were gradually and completely degraded. .O2- and·OH played an important role in the photocatalytic degradation of UDMH. The possible degradation pathways of UDMH analyzed by GC-MS. The work provided an effective method for the degradation of UDMH wastewater.

The growing Urbanization, Industrialization, Institutional, and IT sector development contribute to the exponential growth of motorized road transportation increasing the composition of harmful gaseous pollutants in ambient air. So, it is necessary to analyze and quantify the concentration of pollutants such as CO, NOx, SOx, and PM10 (for calculating the Air Quality Index) in ambient air at traffic signal zones in National Highway 948 across Coimbatore city and to model its dispersion using Quantum GIS. Using a Respirable Dust Sampler, the ambient air samples are collected at various locations based on heavy traffic signals zones during the month of December 2022 – March 2023.Quantified data are compared with National Ambient Air Quality Standards (NAAQS) to know about air quality, i.e., Air Quality Index. The dispersion rate in terms of concentration of CO, NOx, and SOx in the sampling locations of National Highway 948 revealed that; In comparison to other sampling months, the mean NOx concentration was higher in December at SL1 (78 µg/m³).The mean concentration value of SOx was high at SL2 (57 µg/m³) in the month of February 2023, and the mean concentration of CO is relatively high at SL1 (1.93 mg/m3) in NH 948.Sampling Locations such as SL1, SL5, SL7, and SL11 fall under the category of Poor compared to other sampling locations because of improper alignment of roadway, Traffic congestion, Liberty, and Violation of Traffic rules, Lack of vehicular maintenance, and End life vehicles. The lack of implementation of environmental regulations contributes to the bad air quality in most Indian cities.

From this study, green seaweed Caulerpa Scalpelliformis is utilized as a sorbent for the removal of three metals such as lead (Pb), nickel (Ni) and zinc (Zn). Adsorption tests showed that maximum removal efficiency of 75.02% for Pb, 80% for Ni and 91.11% for Zn was obtained at an optimal equilibrium pH of 7 for Pb and 6 for Ni, Zn, 2g/L sorbent at an ionic strength of 100 mg/L of 30°C. Four isotherm models, such as Langmuir, Freundlich, Toth, and Sips used in this study to determine the correct fit model from test results. The toth model (R2=0.999) was well fit compared to other isotherms models based on correlation coefficients. Kinetic model results obtained at initial Pb, Ni and Zn concentrations revealed a high biosorption rate. In contrast, the results have been modelled effectively with the pseudo-first and second orders. As a result, tests with elutants found that 0.1M HCl is the perfect desorption elutant for three metal ions.

The total nitrogen (TN) is the key indicator for the eutrophication of Miyun Reservoir. Base on the long-term series of remote sensing, hydrological and water quality observation data, this paper comprehensively analyzed the trend of water quality especially the TN concentration and its influencing factors over 30 years in Miyun reservoir. The development trends of the TN concentration during the 14th Five Year Plan Period were predicate with the designed water quality scenarios simulations. The results showed that the water covered area of Miyun reservoir was reduced from 1986 to 2004 and enlarged from 2004 to 2020, and the smallest water covered area was about 56.4km2 in 2004 while the largest was about 170.7km2 in 2020. For the regional rainfall and artificial water storage, the inflow of Miyun reservoir is much greater than the water intake, and this is the main reason for the water covered area increased. From 1988 to 2020, TN contents in the inflow water of Chaohe river and Baihe river were generally in upward trends, with annual upward rates of 0.16 mg/L and 0.05 mg/L at the 99% confidence levels separately. However, the TN concentrations from Chaohe river and Baihe river presented downward trends for the recent 5 years. And this is own to the emission control and river ecological control measures in the upstream basin of Miyun reservoir. From 1988 to 2020, the annual averaged TN concentration of the main dams in Chaohe and Baihe (BHZB and CHZB) was 1.10±0.32 mg/L and 1.17±0.31 mg/L respectively and in recent 5 years, and significant positive trends were also identified at both two stations with the steadily rising the water level and volume in Miyun reservoir. The lightly increase of TN concentration in recent years in Miyun reservoir was the comprehensive results of external input and self purification capacity. Based on the MIKE21 model of four scenario simulations, the TN concentration of Miyun reservoir will meet the class Ⅱ water quality level (China’s Environmental Quality Standards for Surface Waters, GB3838-2002) under the comprehensive implementation of rural domestic source control and agricultural non-point emission control measures in the upstream basin of Miyun reservoir during the 14th Five Year Plan period.

This study was carried out with the aim of using three processes of soil washing, electrofenton and biological leaching method in order to rehabilitate the soil contaminated with lead and phenanthrene around the south Tehran oil refinery. The variables examined in this study are the amount of soil (500, 1000, 1500, 2000 mg), the ratio of surfactant to soil (7.50, 15, 22.50, 30, 37.50 L/Kg), time (6, 12, 18, 24, 30 hours), lead concentration (25, 50, 37.50, 62.50 mg/kg) and phenanthrene concentration (50, 100, 15, 200 mg/kg). In the washing process, the highest percentage of lead removal is 78.23% at the contact surface of 2000 mg, the surfactant-to-soil ratio is 30 ml/kg, the time is 24 hours, the concentration of lead and phenanthrene is 50 and 100 mg/kg and the highest removal percentage of phenanthrene (73.4%) in the soil amount of 1000 mg, the ratio of soil to surfactant equal to 30 liters/kg, in 12 hours, the amount of lead and phenanthrene were obtained equal to 25 and 100 mg/kg. Next, the soil was placed in a discontinuous reactor with graphene electrode as cathode and iron electrode as anode to conduct electrofenton. The investigated variables are solution pH (2, 4, 6, 8, 10), reaction time (12.5, 25, 37.5, 50, 62.5 minutes), hydrogen peroxide concentration (0.5, 1, 1.5, 2, 2.5 w/w) and direct electric current (0.75, 1.5, 2.25, 3, 3.75 A). The results indicated that in the electrofenton pH process, hydrogen peroxide concentration and then voltage had the greatest effect and time had the least effect on the removal of lead and phenanthrene. In this way, the highest percentage of lead removal was 85.4% at pH equal to 8, hydrogen peroxide concentration equal to 2 W/W, current equal to 1.5 A and 50 minutes and the highest percentage of phenanthrene removal (85.9%) at pH equal to 6, hydrogen peroxide concentration equal to 1.5W/W, current equal to 2.25 A and 37.5 minutes were obtained. In the biological leaching method, the purified strain (Pseudomonas aeruginosa) was isolated from the soils around the refinery. Environmental pH (3, 5, 7, 9, 11), pollutant to biomass ratio (7.50, 15, 22.50, 30, 37.5 mg/g) and retention time (1, 2, 3, 4, 5 hour) were considered as main variables. pH was the most important parameter influencing the removal of lead and phenanthrene from soil in biological method. The highest percentage of lead removal with 85.4% was obtained at pH equal to 8, hydrogen peroxide concentration equal to 2W/W, current 1.5 A and 50 minutes time. In the case of phenanthrene, the highest removal percentage of phenanthrene (85.9%) was measured at pH equal to 6, hydrogen peroxide concentration of 1.5 W/W, current of 2.25 A and in 37.5 minutes. Comparing the results of the third stage of soil cleaning with the control sample without preparation steps with the removal percentage of 0.67 and 0.42 for lead and phenanthrene, shows the effect of the soil preparation process in order to improve the ability of bacteria to function and shows that by combining three methods of washing, electrofenton and biologic, it is possible to rehabilitate contaminated soils resistant to biological decomposition.

Toxic algal blooms have become a major environmental problem over the last few decades because of their impact on fisheries, leisure activities, national income and human health. It is known that Harmful Algal Blooms (HABs) can occur naturally but the frequency of occurrence as well as their geographical distribution are alarming. HABs, beyond the scientific interest, have been an issue of concern for policy makers due to the high cost for implementing management practices. Unlike other marine environmental problems, the causes of HAB formation are not known so far with certainty and a high degree of uncertainty remains, regarding possible triggering mechanisms. Various factors, apart from nutrient concentrations, seem to be connected with this phenomenon: abundance, presence and absence of phytoplankton species, presence of grazers, weather conditions, seawater temperature and water mass circulation patterns, have already been reported in the scientific literature as potential factors. However, there are strong indications that eutrophic conditions play a paramount role in HABs formation. Machine learning methods, applied over the last few years to predict HAB’s occurrences, have also confirmed the role of nutrients. In the present work, toxic algal blooms in regional seas characterized by eutrophic conditions that is the Mediterranean Sea, the Black Sea, the Baltic Sea, the North Sea, Wider Caribbean Region and the South China Sea are reviewed. Relevant issues including the drivers of eutrophication triggering HAB’s events as well as effects on ecosystem services and socio-economic consequences are also considered.