In this study, the stratigraphic and sedimentological data have been utilized to decipher the tectonostratigraphic evolution of the Kalat and Mach area of the northern Kirthar Range, Balochistan Basin, Pakistan. Three (3) stratigraphic sections are measured, and the Jurassic-Paleogene facies variation with their depositional environments is documented in the study area. Based on the biostratigraphic and facies augmented information, four tectonostratigraphic evolution stages are described which include a) The late early Jurassic (Toarcian)-mid Jurassic (Callovian-Aalenian) around 180 Ma-159.4 Ma; the deposition of Anjira-Chiltan Formation, and a late Jurassic thermal uplift; preceding the Indo-Madagascar separation from the Afro-Arbian Plate may have caused the shallowing and ultimately the exposure of mid Jurassic carbonate platform forming an erosional unconformity, b) early Cretaceous (Berreiasian) black clays and the interbedded clastics of the Parh Limestone (equivalent to the Sembar Formation) relates to the thermal uplift of the eastern margin of the Indo-Pak Plate and reworking of the late Jurassic paleosoles of the Chiltan Formation in the deep marine settings. c) The constituent facies of the Accretionary Prism Sediments (APS) and its stratigraphic relationship within the study area confirms that its obduction is related to the middle Cretaceous (late Coniacian-early Santonian) around 84-86 Ma during passive margin phase of the Indian Plate d) The uplift of the middle Eocene (Lutetian) carbonate platform is evident from the deposition of the fluvial reddish clays which are sandwiched between the foraminiferal limestone of the Kirthar Formation. The study area has promising reservoir rock potential, with multiple horizons present. Notable candidates include the Chiltan limestone, Parh Limestone, and various dolomite and sandstone horizons. The Ghazij Formation, rich in shale, is an ideal seal. However, an angular unconformity at the base of the Kirthar Formation suggests Eocene deformation, raising uncertainties about its presence. Despite these uncertainties, the study area has favorable geological characteristics for a viable petroleum system.
Soil moisture scarcity is a major constraint to achieving potential soil productivity in arid and semi-arid regions. Hydrogel application has shown promise in addressing this issue, but its benefits for crop improvement and soil moisture retention require further exploration. This study evaluated the impact of hydrogel on soil moisture retention, soil characteristics, and wheat yield in a rainfed agricultural system in Jand, Attock. A randomized complete block design (RCBD) experiment with four replications was conducted from 2018 to 2021, comprising three treatments: control (no hydrogel), hydrogel application via seed drill, and hydrogel application via broadcast. Results revealed significant enhancements in relative soil moisture contents (up to 33.25%) and wheat yield (3960 kg ha(-1)) with hydrogel application. Increase in nutrient availability (2.57 to 3.43 mg kg(-1) of P2O5, 51.26 to 76 K2O) and soil organic matter contents (0.62 to 0.77) were also observed. This study demonstrated the potential of hydrogel as a strategy to improve crop productivity in rainfed regions.
The detrimental effects of droughts on water resources and agriculture can lead to significant economic losses and risk to lives. Using key climatic factors to analyze changes in a relevant index, this study aims to forecast droughts. The study is structured into three distinct phases. First, the computation of the Standardized Precipitation Evapotranspiration Index (SPEI) for the Chitral and Swat River basins was carried out using data from 1981 to 2022. This index is designed to predict both short-term and long-term droughts. Second, the dataset was split into training and testing sets, with 80% designated for training and 20% for testing the models, employing algorithms such as XGBoost, Decision Tree, AdaBoost, and Linear Regression, along with various climate variables. Finally, the models were evaluated using statistical metrics like R-2 (Coefficient of Determination), RMSE (Root Mean Square Error), MAE (Mean Absolute Error), and MSE (Mean Squared Error), and future predictions from 2023 to 2045 were made based on the well-trained and tested models. The results demonstrate promising performance, with R-2 values of 0.968, 0.906, 0.901, and 0.287, and RMSE values of 0.265, 0.291, 0.302, and 0.837 for XGBoost, AdaBoost, Decision Tree, and Linear Regression, respectively. The SPEI shows potential as a useful tool for drought prediction, and spatial distribution mapping in ArcMap using the Inverse Distance Weighting method reveals persistent moderate droughts in both basins. Additional research using a larger dataset or combining data from different areas could enhance the applicability of the findings and lead to a deeper understanding.
Indoor air pollution in rural and resource-constrained households is primarily caused by the use of biomass fuel in cookstoves, a significant risk factor for morbidity and mortality throughout the world. This study uniquely investigates indoor microplastic pollution from cookstove emissions in Pakistani slums, as plastic has been identified as one of the major tertiary fuels used to start cookstoves, addressing a major research gap. Unlike previous local studies focused on outdoor air, this study identifies and characterizes polymeric particles in PM10 and PM2.5 from 2 different cookstoves, using FTIR and Raman spectroscopy, offering first-time molecular evidence in this context. Particulate matter (PM) samples were collected both from the traditional and the locally manufactured rocket biomass cookstove kitchens, within H-11 and F-11 slums in Islamabad, Pakistan. Two analytical techniques, Raman and Fourier Transform Infrared Spectroscopy (FTIR), were employed to identify and characterize microplastics in PM10 and PM2.5 samples. The detected polymers included polypropylene, polyvinyl chloride, polystyrene, polyolefins, and polyurethanes. At Site 2, LDPE, polyolefins, and polypropylene were identified. Results from the comparative analysis of traditional and rocket stoves in PM10 and PM2.5 samples revealed a significant difference in the concentration of particulate matter contamination at both sites. The findings from this study indicate that the rocket stove had a lower concentration of particulate matter in PM10 and PM2.5 samples as compared to the traditional stove, which may suggest that microplastic concentration was also lower, thereby offering enhanced potential health benefits for users, as inhalation and continuous exposure to microplastics are associated with adverse health effects. Overall, ICS reduced PM10 concentrations by 38.73% and PM2.5 concentrations by 34.75% across both monitored sites. This study emphasizes the importance of using rocket stoves as they offer a superior alternative to traditional stoves by reducing particulate matter and microplastic exposure, making them a cleaner and safer cooking option in slum areas.
There is an increasing global concern about the potential environmental impacts of the continuous expansion of highways and transportation infrastructure, particularly regarding air quality. This research provides a comprehensive analysis of the effects of highway development, specifically the M3 Motorway, on air quality in the Punjab region by integrating innovative air impact prediction models and spatial analysis techniques. This research uses ground-based data from 2006 to 2022 and Remote Sensing data (Sentinel-5P and MODIS) from 2018 to 2022. The analysis is focused on the concentrations of key air pollutants, including sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), methane (CH4), aerosol optical depth (AOD), formaldehyde (HCHO), and ozone (O-3). The results revealed that SO2 concentrations fluctuated noticeably, ranging from 0.08 to 0.26 mu mol/m(2). Higher amounts were regularly noted in the Renala Khurd and Kabir Wala regions. Similarly, NO2 values ranged from 78.65 to 97.54 mu mol/m(2) in the Renala Khurd and Sahiwal regions. The concentrations of CO varied between 36.30 and 40.30 mu mol/m2, with higher values found in urban areas. The concentration of CH4 was noted from 188058 to 1920961.12 mu mol/m(2), reflecting the effects of industry and agricultural pollutants. Predictive modelling coupled with spatial analysis provides a thorough framework for evaluating the complex links between highway construction and air quality. This study helps to balance contemporary transportation networks and environmental stewardship by advancing a more nuanced knowledge of the environmental impact of highway developments in Punjab.
