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Wastewater from textile industry is considered one of the major environmental challenges due to the large volume of highly colored, polluted and toxic effluent. This study investigated the treatability of real textile wastewater by pilot-scale anoxic-aerobic Membrane Bioreactor (MBR) system without sludge wasting for operation period of 100 days. The proposed system was investigated under different Internal Recycle (IR) ratios and the impact of IR ratio on Total Organic Carbon (TOC), Total Nitrogen (TN) and Color removals were examined. Under IR ratios between anoxic and aerobic tanks of 0.0, 0.5 and 2.0, the respective average removal efficiency of TN was 20.9%,53.4% and 71.7%, whereas average color removal of 81%, 85% and 88%, respectively was noted. The results indicated that increase of recycle ratio from 0.5 to 2.0 enhanced TN removal to about 71% and color removal to above 85%. The IR between anoxic and aerobic tanks has a significant role in TN and color removal due its effect on the development of bacterial communities. On the other hand, the results indicate over 93% TOC removal, which was independent of IR ratio.

Transportation driven by fossil fuels increases air pollution induced by urbanisation. Heavy metals such as Cadmium (Cd), Chromium (Cr), Copper (Cu), Iron (Fe), Lead (Pb), and Zinc (Zn) are life-threatening elements and their concentration is increasing alarmingly in soil in various countries. Air pollution and associated metals contaminate the environment and affect nature's abiotic and biotic components. The significance of tree species originates from their connection to the effects of pollution and the solution approach to their biological cycle. Nineteen distinct tree species dominate the region, with heavy metals sinking in the range of Cd<0.4, Cr<1, Cu<15, Fe<2, Pb<5, and Zn<2 mg/kg or parts per million. According to the findings of this study, tree species can sink heavy metals. The different trees have distinct metals-sink ratios. The competence results showed the order of heavy metal sink as Delonix Regia-red (4) > Delonix Regia-yellow (4) > Syzygium Cumini (3) > Muntingic Calabura (3) of the trees with the highest sink rates and nine species had absorbed lead metal. The nine tree species were unsuitable for heavy metal absorption or deposition. There, Albizia Lebbeck (T02), Biancaca Decapetela (T05), Brucea Javanica (T06), Ficus Elastica (T09), Ficus Religiosa (T10), Pithecellobium Dulce (T13), Tamarind (T17), Terminalia Catappa (T18), and Thespesia Populnea (T19) were very low, less than 10% of other dominant tree species. Syzygium cumini (T16) is a high-yielding tree species that absorb significant quantities of Lead (Pb) and Copper (Cu). These studies confirm that, tree species can capture several heavy metals simultaneously from the polluted environment.

Dimethoate is an organophosphate (OP) insecticide used in agriculture to kill insects. However, information on the effect of the insecticide on non-target organisms like phytoplankton is sparse. When dimethoate enters water ecosystems, it affects the photosynthesis of the phytoplankton cells. The effect of dimethoate on the photosynthesis mechanism of three Chlorophyceaen and two Bacillariophyceaen species was studied measuring oxygen production, chlorophyll fluorescence and xanthophyll pigments. Oxygen evolution rates of the five phytoplankton species decreased with increasing dimethoate concentrations. OJIP fluorescence characteristics in presence of dimethoate was similar to those of DCMU inhibition. DCMU is a PSII inhibitor used as a positive control. Non-photochemical quenching (NPQ) development and the concentration of specific xanthophyll pigments decreased with increasing insecticide concentration, giving another evidence for the target of dimethoate in the selected phytoplankton species. Dark relaxation kinetics did not show a photoinhibition of the cells in presence of dimethoate. Perfekthion, the commercial formulation of dimethoate, inhibited the photosynthesis of the tested phytoplankton species stronger than dimethoate, leading probably to photoinhibition.

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.