Pakistan has been facing energy crises for more than a decade as a result of its reliance on imported fossil fuels, circular debt, political instability, and absurd energy policies. However, the country has abundant renewable energy resources which, if harnessed, may help to effectively cope with ever-increasing energy demand. This review study investigates the country’s economic and energy situations, energy crises, and energy sector performance. A critical analysis of studies conducted on Pakistan’s energy planning since its independence in 1947 is, and policies announced to date are assessed. This review reveals that the economic situation of the country has remained severely stressed, and energy sector performance has been compromised over the years for various underlying reasons. The energy policy narrative in the early decades of the post-independence period focused on water resource management, whereas energy concerns were only realized in the late 1960s as demand grew. The first-ever energy and power planning study in Pakistan was conducted in 1967, and since then, various studies have been conducted to support the medium-term development plans of the government. These planning studies inspired further development, and in 1994, the first-ever electricity-focused power policy was announced by the government in response to industrial growth and subsequent electricity demand. However, this and subsequent policies were fossil-fuel-centric until 2006, when the government announced the first-ever renewable energy policy. This 2006 policy focused on increasing renewable energy penetration in the overall energy mix by setting specific targets. However, these targets have rarely been accomplished as a result of a lack of an effective planning paradigm, as most of studies have been conducted without sound demand forecasting and without considering renewable energy’s potential to meet growing demand. As such, planning efforts based on proven methodologies/modeling tools and the undertaking of demand forecasts and renewable energy assessments are inevitable for countries such as Pakistan. Therefore, we suggest that sectoral energy demand forecasting, estimation of renewable energy potential with end use, and modeling of optimal penetration of renewable energy using energy modeling tools will be helpful to develop sustainable energy policies in Pakistan to eradicate the energy crisis.

Demand for water resources has increased dramatically due to the global increase in consumption of water, which has resulted in water depletion. Additionally, global climate change has further resulted as an impediment to human survival. Moreover, Pakistan is among the countries that have already crossed the water scarcity line, experiencing drought in the water-stressed Thar desert. Drought mitigation actions can be effectively achieved by forecasting techniques. This research describes the application of a linear stochastic model, i.e., Autoregressive Integrated Moving Average (ARIMA), to predict the drought pattern. The Standardized Precipitation Evapotranspiration Index (SPEI) is calculated to develop ARIMA models to forecast drought in a hyper-arid environment. In this study, drought forecast is demonstrated by results achieved from ARIMA models for various time periods. Result shows that the values of p, d, and q (non-seasonal model parameter) and P, D, and Q (seasonal model parameter) for the same SPEI period in the proposed models are analogous where “p” is the order of autoregressive lags, q is the order of moving average lags and d is the order of integration. Additionally, these parameters show the strong likeness for Moving Average (M.A) and Autoregressive (A.R) parameter values. From the various developed models for the Thar region, it has been concluded that the model (0,1,0)(1,0,2) is the best ARIMA model at 24 SPEI and could be considered as a generalized model. In the (0,1,0) model, the A.R term is 0, the difference/order of integration is 1 and the moving average is 0, and in the model (1,0,2) whose A.R has the 1st lag, the difference/order of integration is 0 and the moving average has 2 lags. Larger values for R² greater than 0.9 and smaller values of Mean Error (ME), Mean Absolute Error (MAE), Mean Percentile Error (MPE), Mean Absolute Percentile Error (MAPE), and Mean Absolute Square Error (MASE) provide the acceptance of the generalized model. Consequently, this research suggests that drought forecasting can be effectively fulfilled by using ARIMA models, which can be assist policy planners of water resources to place safeguards keeping in view the future severity of the drought.

Solid fuel combustion in a chamber does not necessarily occur at a constant rate and may show fluctuations due to variables such as varying burning rates, chamber pressure, and residual combustion. These variables can cause the fuel to burn disproportionately. The acoustic environment of obstacle vortex-driven flow due to transient combustion with pressure oscillations in a solid fuel chamber is numerically investigated in the present study. Solid fuel combustion is considered transient, and flow characteristics of the present problem are governed by large eddies shed from an obstacle. Since unsteady Reynolds-averaged Navier-Stokes (URANS) simulations are not appropriate to compute the present flow phenomenon, therefore, a detached eddy simulation (DES) is performed to precisely predict the flow behavior. Simulation of steady-state combustion is carried out to validate the numerical results with available experimental data from the literature. The simulation of transient combustion shows that if the combustion frequency is close to the chamber’s modal frequency of the chamber, its amplitude increases greatly and creates an acute acoustic environment. This will result in fuel savings. The amplitude of pressure oscillation up to 18% and 5% of mean pressure are evident at the first and second mode of forced oscillation frequencies respectively. Interestingly, it is also found that pressure oscillation always occurs at inlet mass flux disturbance frequency and not between the disturbance and natural frequency of the chamber. As a result, it is evident that the combustion process or chamber configuration could be modified to ensure that both frequencies are far away enough to interact and create both a harsh acoustic environment and sufficient fuel to burn disproportionately.

Pakistan is not merely confronting the energy crisis but also dealing with the scarcity of economical technologies for the utilization of energy resources. From the basic resources, renewable energy is one of the considerable resources. Due to environmental issues related to greenhouse gases (GHGs) and air pollution in Pakistan, the other energy resources are constricted. In rural areas, biomass resources are a fundamental need for domestic purposes. The prominent reason for environmental degradation and deforestation is due to ineffective use of such resources. Biomass resources for heating and cooking purposes are abundantly available in rural areas of Pakistan. In this context, this study helps us select the applicable cookstove technologies for the Sindh province for the proper utilization of biomass resources. The AHP (analytical hierarchy process) was used as the central methodology for the cookstove ranking. Concerning its improvement, four main criteria corresponding to 12 sub-criteria were considered for the selection of three cookstove technologies, i.e., traditional cookstoves (TCS), efficient cookstoves (ECS), and biogas cookstoves (BCS). The final decision of the AHP framework exposed the ECS technology as the advantageous technology, followed by the BCS and TCS, respectively. To analyze the results, a sensitivity analysis of the major results has also been carried out, and under the final ranking matrix, the ECS alternative got the highest weightage, nearly 36.56%, based on the developed model.

Regression is a statistical method that is generally used for forecasting and prediction. It helps us to estimate the relationship between a dependent variable and one or more independent variables. This is the most widely used technique that best approximates the individual data points. It has found numerous successful applications in Engineering, Science, business and other fields. Getting average removal % of Biological Oxygen Demand (BOD5) from greywater through Rotating Biological Contactor (RBC), following experiment was conducted in Sindh University hostels using different parameters such as Hydraulic Retention Time (HRT) i.e. 2 hours (0.42 liter per min), 2.5 hours (0.33 l/min) and 3 hours (0.28 l/min) and multiple number of discs i.e. 40, 42, 44, 46, 48, 50 and 52. Consequences reveal that linear estimate of HRTs and numbers of disc are considerable whereas linear and quadratic estimates of number of discs are highly significant, which evidence the significance of time and discs. However, as p-value is greater than 0.05, hence quadratic estimate of HRT is not significant. By using coefficients of the table the regression equation is Removal = - 79.995 + 6.88 time + 2.90 disc, where the sample standard deviation is 7.151, coefficient of correlation is 0.86 and coefficient of determination is 0.742. Distributions of errors are approximately normal as probability plot of the residuals is approximately linear. Residual analysis shows that against each predicted variable, residuals plot falls approximately in a horizontal band symmetric and centered about the horizontal axis and against predicted y-values. Moreover, Residual plot shows the constant standard deviations and linearity assumptions appear to be met.