Afforestation is one potential action for improving the environment from local to global scales. Deforestation plagues many regions of the world and in recent times, there are ongoing efforts by some countries to expand afforestation programs. One key decision in the design of afforestation programs is species selection. Here, we demonstrate species selection for afforestation using two different multi-criteria decision-making (MCDM) techniques. The study covers two regions within the Khyber Pakhtunkhwa province of Pakistan and is based on their ongoing project, the Billion Tree Tsunami. We considered six criteria for decision making. These criteria included cost, reproducibility, growth rate, environmental compatibility (including soil compatibility, temperature, rainfall requirements), environmental effects (including transpiration rate, evergreen or not, soil erosion control) and uses (medical, constructional and fodder). The results of both MCDM methods were comparable, suggesting that our findings are acceptable and consistent. The study is useful for the forestry department at local and international levels. Additionally, it is informative for researchers and readers with an interest in the application of MCDM in forestry.

In this study, climate change and human impacts on water quality in five major urban areas of Pakistan, including Karachi, Lahore, Peshawar, Abbottabad, and Gilgit, were determined. Secondary data on various physical, chemical, and bacteriological water quality parameters were taken from published papers, reports, and theses. Surface and groundwater were the major sources of drinking water in these cities. The physicochemical parameters were total turbidity, pH, dissolved solids (TDS), sulphates, chlorides, calcium, sodium, HCO₃, potassium, magnesium, nitrates, fluorides, arsenic, and hardness. The bacteriological parameters were total coliform, total faecal coliform, and total plate counts. The data revealed that pH, TDS, fluoride, chloride, HCO₃, sodium, and hardness were above the limits in Karachi. MCB Market, Goth Ibrahim, and Malir Town were the main contaminated areas in Karachi. In Lahore, arsenic was found above the limits in all sampling locations. Turbidity, pH, HCO₃, calcium, magnesium, and hardness were found above the limits in Peshawar. In Gilgit city, all physicochemical parameters were found within the limits except turbidity, which was 10 NTU in Nomal valley. Nitrates were higher in the water sources in Abbottabad. Bacterial contamination was found in the water of all five cities. Most of the studies revealed that this contamination could be human-induced. The improper disposal of solid waste, sewage, and animal waste and the excessive use of fertilisers deteriorate the quality of the water. Precipitation, a rise in temperature, and seasonal variation are climate variables that affect water quality and are responsible for major outbreaks of waterborne diseases. There is an urgent need for regular analysis, proper management, and proper treatment of drinking water before it is supplied to the local community in these cities.

Improved plant nutrition to get high productivity is under severe influence of human activities drastically impacting the soil-plant ecosystem. In the scenario of increased global socio-economic demand for food, the changes in land use systems to gain higher agricultural productivity are disrupting the soil properties as well as the associated soil services. This work investigated the impact of different land use systems on phosphorus (P) and associated soil nutrients including K, Ca and Mg across six different land use systems in Abbottabad, Pakistan. Phosphorous fractions were determined by the modified sequential extraction procedures and the concentration of nutrients was measured by double acid digestion. Results revealed the significant variations across different land use systems for P where different P fractions were found considerably varying in order of HCL>NaOH>NaHCO₃>H₂O extractable phosphorus. Interestingly, nutrients were found to be varying from thick forest to cultivated lands. Results demonstrate that the shift from the thick forests to thin forests or arable lands may increase the P losses and ultimately disturb the associated soil-plant nutrient status thus should remain intact to promote the plant productivity in a sustainable way.

This study investigates the impact of globalization, energy consumption, economic growth, urbanization, and trade openness on environmental degradation in case of Pakistan. The dynamic autoregressive distributed lag (DARDL) technique was applied to measure the short- and long-term estimates, which are robust and have higher predictive power compared to the conventional ARDL technique with a dataset that spans from 1980 to 2023 for Pakistan. The empirical findings confirm a significant long-run cointegrating relationship among the variables under investigation. Specifically, globalization and trade openness are found to exert a significant negative impact on CO₂ emissions, suggesting their potential role in fostering environmental amelioration. Conversely, energy consumption and economic growth demonstrate a significant positive impact on CO₂ emissions, indicating their contribution to increased environmental degradation. Notably, urbanization does not show a significant relationship with CO₂ emissions, a finding attributed to Pakistan’s inefficient and environmentally unfriendly urban infrastructure, despite a substantial 2.93 percent annual rate of urbanization. Furthermore, the widely posited Environmental Kuznets Curve (EKC) hypothesis is not supported by the data; instead, economic growth appears to be associated with an exponential increase in CO₂ emissions. The findings offer crucial policy insights for sustainable development initiatives for Pakistan and generally for developing nations.