The presence of hydrogen sulfide (H2S) gas in the muddy ecosystems is consequence of anthropogenic interference. To understand ecosystem health present study was intended to gauge H2S concentrations involved in annihilation of meiofauna and associated aquatic life from four hotspots including Manora channel, Korangi creeks, Sonmiani, and Bhambhore along the Pakistan coastal belt. Using a handheld gas detector device, it was observed that Bhambhore exhibited lower levels of H2S therefore embraces numerous benthic organisms whereas Manora channel (backwater) and Korangi creek area showed elevated level that does not allow macro-organisms to stay around. The diversity varied across locations, with Bhambhore collecting the most species of mudskippers and Manora creeks collecting the rarest. Overall result of this study reveals that H2S 5~274 ppm is alarming. The data of crabs, mudskippers, fishes, mantis shrimps, shells in relation to the environmental variables of temperature, salinity, conductivity dissolved oxygen and H2S were used to develop canonical correspondence analysis. The variability among first two components was 64.47 and 28.44%, eigenvalue (0.154, 0.068 and trace 0.239) respectively. Considering baseline findings of this study, greater efforts are required for ecosystem resilience for the sake of human health concerns.

Most pollutants found in rivers come from the discharge of raw sewage from both point and nonpoint sources. So, monitoring the pollution levels in surface water sources is essential. River pollution monitoring is a real challenge. Using remote sensing, precise outcomes can be achieved with the help of the selection of the right combination of satellite images and algorithms. Generally, established available algorithms are site-specific, indicating that they may not work at all areas on Earth's surface due to differences in altitude, cloud cover, and sun glint. The present work determined Chlorophyll-a concentrations in the Tapi River at various locations using Landsat-8 satellite images and Acolite software from 2017 to 2021 Period. The outcomes reveal that applying the dark spectrum fitting with sun glint correction when processing Landsat-8 satellite images is needed. In the present study, water quality results were obtained very precisely for the months of January, February, November, and December after processing and analysing satellite images. Due to factors such as sun glare, cloud cover, cloud shadow, and haze, the desired effect could not be achieved in the remaining months of the study period. This research provides a solid foundation for estimating the impact of eutrophication in the water body by estimating chlorophyll-a concentration from satellite images.

Thermochemical conversion of biomass and petrochemical wastes blend is an excellent method to produce valuable fuels and reduce environmental pollution. Bio-oil production via blending of paulownia wood and polypropylene plastic was investigated in a fixed bed horizontal reactor at different reaction temperatures and different Polymer/ Biomass weight ratios. Biomass showed the highest amount of bio-oil production (52.8 wt.%) at 500°C. The results show that with increase in temperature, the production of lighter products (with lower carbon number) has increased. Co-pyrolysis on a horizontal reactor showed positive synergy for the production of liquid and gaseous products. Bio-oil production increased to 61.03 wt.% and the relative oxygen content of the liquid products decreased. In co-pyrolysis with the ratio of 60:40 of PAW: PP, aromatic compounds with 35% by weight constitute the highest amount of liquid product and production of furans and aldehyde/ketones reduced. While this number is equal to 8% for blend of 5% PP and 95% PAW.

Carbon dioxide, as a great part of greenhouse gases, stands as a major contributor to climate change; hence, various techniques have been presented for controlling and decreasing CO2 emissions. The studies show that the adsorption and conversion into environmentally benign substances are the most practical and efficient strategies for this purpose. As amines are active in CO2 adsorption, N-(2-aminoethyl)-3-aminopropyltrimethoxysilane was chosen as an amine group to functionalize MCM-41 mesoporous in order to hydrate CO2 and convert to calcium carbonate in this study. The synthesis of the mesoporous materials and amine functionalization were carried out using the wet impregnation method, and the materials were characterized by XRD, FT-IR, SEM, and BET analysis. The results demonstrated a high adsorption capacity (165 mg CaCO3) due to the presence of the -NH2 group in the catalysts. Moreover, the results have been compared with similar mesoporous materials functionalized with metals for CO2 capture and hydration. The adsorption-desorption isotherm corresponded to type IV, as defined in the IUPAC classification.

Municipal Solid Waste (MSW) dumpsites are one of the major source of methane (CH4) emissions due anaerobic degradation of organic matter content in the waste. Control technologies are available to reduce these emissions, but they are costly and their application on existing sites is complex. Moreover, tropical climate is responsible for rapid degradation of organic matter in open dumps leading to substantial CH4 emissions mainly due to hot and humid conditions amongst other factors. Methanotrophs are bacteria capable of oxidizing CH4 into carbon dioxide (CO2) by virtue of methane monooxygenase enzyme. Various cover materials can be utilized to enhance methane oxidation (MO) ability of these organisms by providing favorable conditions thus converting methane from unmanaged dumpsites into CO2 which has lower global warming potential. Hence their application shows great potential for contributing towards meeting the greenhouse gas (GHG) reduction goals. This review focuses on the attempts to attenuate CH4 emissions by different biocover systems and the current scenario while giving special emphasis to tropical conditions.

There is a belief that ambient air pollution  is accountable for degrading the air quality indoors. Although in principle the indoor air quality should be better than that of outdoor air quality given the shielding effect of a house structure. However, ambient air quality can infiltrate and influence indoor air pollution concentrations in low-income urban informal settlements due to rudimentary designed household structures. Given this phenomenon, the current study endeavoured to explore the influence of outdoor exposure concentration on indoor air quality within the informal settlements of urban neighbourhoods. The exposure concentrations of indoor and outdoor particulate matter and nitrogen dioxide pollutants were simultaneously measured during summer and winter seasons. The GilAir Plus air sample pump was used to acquire measurements of particulate matter collected over 48 hours. While nitrogen dioxide gases were measured using passive diffusive samplers. All statistical analyses were performed using Python (version 3.8) Spyder. The current study has discovered that in many instances the results were comparable indoors and outdoors. For instance, this has been corroborated by the nitrogen dioxide discoveries where the current results were slightly comparable as indoor exposure concentrations values were recorded to be between (4 µg/m3 and 13 µg/m3), whilst the outdoor concentration ranged between (6 µg/m3 and 11 µg/m3). Likewise, a similar trend was observed for particulate matter exposure concentrations indoors (14 µg/m3 ) and (12 µg/m3) outdoors. The statistical inferences futher confirmed that the exposure values of indoor and outdoor were not significant (p>0.05) within the study areas of concern.

Cedrus deodara is a coniferous tree native to Himalayan region. Its wood is a valuable resource for the timber industry; however, its bark is typically discarded as a waste material. The present study examines the performance of Cedrus deodara bark powder (CD) as an inexpensive adsorbent for elimination of Pb (II) ions. In addition to this multiple linear regression (MLR) and artificial neural network (ANN) models were developed for modelling the adsorption process and prediction of Pb (II) removal efficiency. The structural and chemical properties of CD were explored using Field Emission Scanning Electron Microscope (FE-SEM), Energy Dispersive Spectrometer (EDS), X-Ray Diffractometer (XRD) and Fourier Transform Infrared Spectroscopy (FTIR). Batch experiments were conducted to investigate the influence of factors including pH, contact time, initial Pb (II) concentration and temperature on Pb (II) adsorption. The adsorption followed pseudo-second-order kinetic and Langmuir isotherm models with maximum monolayer uptake capacity 77.52 mg/g. Based on the thermodynamic criteria, the process was endothermic and spontaneous with enthalpy change (ΔH = 8.08 kJ/mol), free energy change (ΔG = -2.44 kJ/mol) and entropy change (ΔS = 0.03 kJ/K/mol). Statistical comparison of MLR model (R2 = 0.817, RMSE = 8.954, MAPE = 17.379 %) and ANN model (R2 = 0.993, RMSE = 1.777, MAPE = 2.054 %) confirmed that ANN model was far more accurate in predicting removal efficiency.

Today, the problem of air pollution has been highlighted by rapid population growth and urbanisation, along with the development of industry. Over the last fifty years, much attention has been paid to the relationship between lichens and airborne particulate matter (especially heavy metals). The use of living organisms in air pollution studies is now widely accepted in many countries and the results of these biomonitoring studies are very important for future action. The goal of this study was to determine heavy metals in Kırşehir province using the bag technique, a biomonitoring approach, with Pseudevernia furfuracea (L.) Zopf lichen and to develop a pollution map of the city. In November 2002, lichen specimens were obtained from an unpolluted region in the Yapraklı Mountains, Çankırı, and transplanted to 4 distinct places in Kırşehir. After 3 and 6 months of exposure, they were collected in order to analyse heavy metals (Cu, Cd, Mn, Ni, Pb and Zn) with Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). In addition, chlorophyll-a and chlorophyll-b contents were determined by Dimethyl sulfoxide (DMSO) method. The findings revealed that the heavy metal contents in various stations are the result of industrial, traffic, and heating activities. As a result, P. furfuracea showed excellent bioindicator ability for detecting air pollution.

Today, world pollution is increasing, and many pollutants such as radioactive elements enter to environment through human activity contaminants play an essential role in human life and health. Therefore, the examination of models for dispersion caused by radioactive substances is an important issue. This article is a simulation study of the hypothetical scenario of the Zaporizhzhia Nuclear Power Plant (ZNPP) in Ukraine, which is one of the NPPs in Europe. This scenario includes the occurrence of an accident in the power plant that entry of pollutants to environment and creates an environmental disaster. The simulation of this scenario was done using the Hyspli4 )Hybrid Single-Particle Lagrangian Integrated Trajectory) model and NOAA website data of ZNPP (include the wind information, temperature, humidity, and atmospheric pressure in different spatial and temporal scales) to predict and deal with pollutants. The simulation was conducted in the first week of April 2023 for 131 I and 137Cs elements, which are important elements that come out of the power plant and cause many problems. The results show the highest annual dose and concentration are 4.6 mSv/year and 2.7E+06 Bq.s/m3 respectively. It also shows that in the event of pollution, the entry of contaminated materials into the Dnieper River and the western edge of the blackened sea will bring a great disaster. Also, the eastern and northeastern regions of Ukraine, especially Kharkiv and the western borders of Russia, lead to pollution that causes radiation hazard, so the news should be shared with everyone before an actual incident occurs.

In the face of emerging and re-emerging diseases, novel and innovative approaches to population scale surveillance are necessary for the early detection and quantification of pathogens. The last decade has seen the rapid development of wastewater and environmental surveillance (WES) to address public health challenges, which has led to establishment of wastewater-based epidemiology (WBE) approaches being deployed to monitor a range of health hazards. WBE exploits the fact that excretions and secretions from urine, and from the gut are discharged in wastewater, particularly sewage, such that sampling sewage systems provides an early warning system for disease outbreaks by providing an early indication of pathogen circulation. While WBE has been mainly used in locations with networked wastewater systems, here we consider its value for less connected populations typical of lower-income settings, and assess the opportunity afforded by pit latrines to sample communities and localities. We propose that where populations struggle to access health and diagnostic facilities, and despite several additional challenges, sampling unconnected wastewater systems remains an important means to monitor the health of large populations in a relatively cost-effective manner.