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The intensive search of new and cleaner energy catches interest in recent years due to huge consumption of fossil fuels coupled with the challenge of energy and environmental sustainability. Production of renewable and environmentally benign energy from locally available raw materials is coming in the frontline. In this work, conversion of the combined biomass (cotton gin trash, cow manure, and Microalgae [Nannochloropsis oculata]) through batch pyrolysis has been investigated. The effect of temperature to the production of energy fuels such as bio-oil, char, and biogas have been simulated considering the yield and energy content as responses. Result of the investigation generally revealed that the proportions of the different biomass did not significantly affect the product yield and energy recovery. Significant effect of temperature is evident in the simulation result of energy recovery whereby maximum conversion was achieved at 400°C for char (91 wt%), 600°C for syngas (22 wt%), and 551°C for bio-oil (48 wt%). Overall energy conversion efficiency of 75.5% was obtained at 589°C in which 15.6 MJ/kg of mixed biomass will be elevated to pyrolysis products.

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Early summer (May–June) is the season where the surface air temperature (SAT) variability is largest and may result in extreme temperature conditions over Pakistan. Therefore, we analysed the early summer interannual SAT variability over Pakistan for the period 1981–2018 using observational dataset and model simulations. We noted that upper‐level anticyclonic circulation anomalies over Pakistan, which are associated with upper to the middle tropospheric descending motion, favour clear skies with an increase in net shortwave radiation that leads to extreme surface warming over the region. Moreover, the El Niño–Southern Oscillation (ENSO) based on Niño3.4 SST index is negatively associated with SAT anomalies over Pakistan. The cold ENSO phase favours the positive geopotential height anomalies due to the strengthening of the Walker circulation that enhance the sinking motion and result in less cloudiness leading to the extreme higher surface temperature conditions over Pakistan, while the opposite happens in the warm ENSO phase. Moreover, the Saudi‐KAU Atmospheric Global Climate Model (AGCM) simulated large‐scale patterns that are in good agreement with the observations. Sensitivity experiments with the AGCM confirm that cold SST anomalies in the ENSO region significantly favour above‐normal SAT anomalies over Pakistan, while the opposite happens in the warm ENSO phase. These results are important to understand and potentially predict regional heatwaves over the South Asian region, particularly over Pakistan.