The marble industry is growing in Pakistan, and Khyber Pakhtunkhwa province is the largest producer of marble tiles in Pakistan. Marble production consumes a considerable amount of water during its life cycle stages and impacts various environmental compartments, such as air, water, and soil; therefore, this study aimed to quantify the environmental impacts, water footprint, and cumulative energy demand of one-tonne marble tile manufactured in a small industrial estate Mardan (SIEM), Pakistan, and provide recommendations to improve its environmental impact profile. The study covers water consumption, energy use, and associated environmental impacts of raw materials and processes through different stages of the marble life-cycle during 2017–2018. The cradle-to-gate (extraction to factory gate or store house) life cycle assessment approach was followed in this study. The functional unit for the current study was one tonne of finished marble tile produced. Primary data from the field surveys and secondary data were modeled using the water scarcity index (WSI), CML 2000 v.2.05 methodology, and the cumulative energy demand indicator present by default in SimaPro v.8.3 software. The total water footprint required for one tonne of finished marble tile was 3.62 cubic meters per tonne (m³/t), with electricity consumed at processing units contributing to environmental burdens the most. Similarly, electricity consumed (at processing units and during polishing) and transportation of finished marble tile to the local market were responsible for global warming potential (388 kg CO₂ eq/tonne tile), human toxicity (84.34 kg 1,4-DB-eq/tonne), freshwater aquatic ecotoxicity (94.97kg 1,4-DB eq/tonne) and abiotic depletion (7.1 × 10⁻⁵ kg Sb eq/tonne). The results of our study follow other marble tile LCA studies conducted globally (such as in Turkey and Italy), which also reported a high contribution to GWP, AP, EP, and HT due to electricity and fossil fuels consumption. The total cumulative energy demand (CED) was calculated as 5863.40 MJ (Mega Joule), with most energy usage associated with non-renewable fossil fuel sources. The results indicated that reducing electricity (using standard automatic machinery) and waste materials, especially paper and plastic wastes, can reduce environmental impacts. Most of the surveyed industrial units did not have wastewater treatment and recycling plants, and wastewater directly flows to nearby freshwater bodies and terrestrial ecosystems. These wastewaters should be adequately treated before being discharged into freshwater aquatic bodies. Environmental impacts must be improved by using the latest automatic machinery, reducing waste materials generation, reducing the distance between processing units and the market, and installing wastewater recycling plants.

A thorough life cycle assessment (LCA) was conducted to determine whether wood pellets were a viable substitute for non-renewable fuels like oil and gas, especially for heating. To evaluate the properties of wood pellets and their effects on the environment, the study was conducted in the Hazara division of Khyber Pakhtunkhwa, Pakistan. A few factors were investigated, including the carbon and water footprints and the identification of potential growth opportunities in the production of wood pellets. One kilogram of wood pellets served as the analysis reference unit. Raw materials were obtained from sawmills and furniture stores to make the wood pellets. Sawdust, a bio binder, and lubricating oil were used in the production process along with the pelletizer machine. SimaPro 9.2 software was used in the environmental footprint assessment to evaluate several environmental effects, including eutrophication, ozone depletion, abiotic depletion, rusting, human toxicity, and aquatic ecotoxicity. The highest contribution was shown by the wood pellets produced from the softwood sawdust as 149.8558 in marine aquatic ecotoxicity. The study’s findings showed that using lubricating oil during the production of wood pellets significantly affected the overall environmental results. The characterization of wood pellets showed that the Higher heating Values (HHV) resulted from burning wood pellets made from sawdust of Melia azedarach as 24.79 MJ/kg. Softwood mixed species recorded the highest water footprint and damage assessment impact and the highest carbon footprint of 0.186 CO₂ e. With a 3.84 × 10⁻⁷ DALY (disability-adjusted life years) measurement, softwood mixed species showed the highest contribution to human health damage among the damage categories. In terms of cost, producing one kilogram of wood pellets from softwood mixed species was priced at 22 PKR, the lowest among the assessed species. The highest cost of 26 PKR was associated with producing wood pellets from Parthenium hysterophorus and Diospyros lotus.

Life cycle assessment was carried out for a conventional wooden furniture set produced in Mardan division of the Khyber Pakhtunkhwa province of Pakistan during 2018-19. Primary data regarding inputs and outputs were collected through questionnaire surveys from 100 conventional wooden furniture set manufacturers, 50 in district Mardan and 50 in district Swabi. In the present study, cradle-to-gate life cycle assessment approach was applied for a functional unit of one conventional wooden furniture set. Production weighted average data were modelled in the environmental impacts modelling software i.e., SimaPro v.8.5. The results showed that textile used in sofa set, wood preservative for polishing and preventing insects attack and petrol used in generator had the highest contribution to all the environmental impact categories evaluated. Total cumulative energy demand for wooden furniture set manufactured was 30,005 MJ with most of the energy acquired from non-renewable fossil fuel resources.

Payment for ecosystem services (PES) is a mechanism where a consumer is able and ready to pay for the protection of the precise ecosystem service and there must be a provider such as local societies receiving an economic resource, who in return, must have the ability to maintain that ecosystem service. Economic valuation provides basis for payment for ecosystem services. Therefore, objective of this study was to evaluate tourism and carbon stock services of the Islamabad Capital Territory (ICT), Pakistan. Two forest zones (Chirpine and Scrub) of Islamabad capital territory (ICT) were selected for estimation of carbon stock and their carbon credits and carbon worth, a questionnaire-based survey was conducted for tourism as a payment for ecosystem services. The method for carbon stock assessment was systematic sampling for Chirpine forest whereas random sampling was done for scrub forest. The size of sampling plot was 17.84 m radius, and a total of 93 plots (49 Scrub zone and 44 Chirpine zone) was taken in the study area. The carbon stock of both zones (Chirpine and Scrub zone) is 22556.75 ton/ha (Chirpine 20105.79, Scrub 2450.96) and total carbon dioxide sequestered by both zone is 82557.72 ton/ha (Chirpine 73587.2, Scrub 8970.52), total carbon credits of both zone is 302160.87 (Chirpine 269328.97, Scrub 32831.9) and the carbon worth of both Chirpine and scrub zone is 4532418.92 $ (Chirpine 4039937.09$, Scrub 492481.83$). Similarly, from tourism point of view, in Shakar Parian, 94% tourists were agreed for PES whereas 6% were disagreed for the PES (the 6% tourist were disagreed to contribute for PES, 40% were agreed for Rs.5 contribution and 54% for Rs.10.). moreover, in Lake view Park, 97% tourists were agreed and 3% are disagreed (In Lake View Park 5% tourists were disagreed for the PES contribution whereas 32% were agreed for Rs.5 and 63% were for Rs.10). In Damen e Koh, around 87% tourist were agreed and 13% were disagreed, (24% were agreed for the contribution of Rs.5 and 63% tourists were agreed for the contribution of Rs.10). In Marghazar Zoo, 93% tourists were agreed (22% were agreed for contribution of Rs.5 and 71% tourist were agreed for contribution of Rs.10) and 7% are disagreed for PES whereas 7% tourists were not agreed for contribution. PES may implement to compensate forest and parks manager to ensure better management of the forests and parks. Due to prime location and scenic beauty of the ICT, it has huge potential for implementation of PES mechanism for sustainable forest management and conservation. Therefore, it is recommended that Capital Development Authority (CDA) Islamabad should devise a plan for implementation of PES in forests and parks of ICT for its sustainable management of recreational and forest resources.

A socio-economic study was conducted in district Mardan of the Khyber Pakhtunkhwa (KP) province of Pakistan to get a comprehensive knowledge of the agroforestry tree species grown on the farmlands, their yield, and carbon stock. For yield and carbon stock estimation, data were collected from 59 sample plots by measuring the diameter, height, volume, and biomass of selected agroforestry tree species through D-tape and Haga altimeter. A total of 59 sample plots were inventoried using 2.5 percent sampling intensity. Each sample plot has an area of 0.5 ha, where each tree with a Diameter at Breast Height (DBH) ≥ 5 cm was inventoried. The calculated amount of volume of each tree species was then converted to biomass by multiplying it by the density of wood and the Biomass Expansion Factor (BEF). Total yield and C stock for the selected agroforestry tree species were 11535.2 metric tons and 2102.2 metric tons, respectively. Populus euroamericana is classified as the main tree with 28% growing stock prior to Morus alba by 21%, while Melia azedarach, Eucalyptus camaldulensis, Dalbergia sissoo, Acacia nilotica, Salix tetrasperma, and Bombax ceiba consist of 15%, 12%, 8%, 6%,7% and 3% growing stock respectively. Among the species found in different sampling plots the yield of Populus euroamericana was found to be 4747.5 metric tons and it was followed by the species Morus alba found at 2027.3 metric tons. Similarly, the volume for Melia azedarach, Eucalyptus camaldulensis, Dalbergia sissoo, Salix spp, Boombox ceiba, and Acacia nilotica was 1532.2 tons,1503 ton,745.7,203.5ton, 555.4ton and 220.5ton, respectively. The carbon stock for Populus euroamericana was calculated as 777.8 ton/ha, while for Eucalyptus camaldulensis, Melia azedarach, Morus alba, Dalbergia sissoo, Acacia nilotica, Salix species, and Bombax ceiba it was calculated as 312.3ton/ha, 272.1ton/ha, 363ton/ha, 245.1ton/ha, 51.4ton/ha, 27.3ton/ha and 53.2ton/ha, respectively. The questionnaire survey conducted for price dynamics showed that the majority of respondents purchase timber from the market for construction. But they use farm trees with low-quality city construction. They dislike using local timber in the conventional building as timber from farm trees is liable to insect attack. Rs. 50,000-100000, (33.33%) of daily sales was concluded from 50% of the trader while (16.7%) of the traders have their sales between Rs.150,000-200,000. Therefore, it is concluded by the authors that both provincial and federal government should promote agroforestry in Pakistan through different incentives because it has the potential to cope with dilemma of deforestation of natural forests and improve the livelihood of local peoples. It is strongly recommended that special projects just like the Ten Billion Tree Afforestation Project (T-BTTP) should be launched for agroforestry plantation and promotion in the country to sustain the ecological harmony and uplift the socio-economic condition of the peoples of Pakistan.

This study aimed to develop and evaluate data driven models for prediction of forest yield under different climate change scenarios in the Gallies forest division of district Abbottabad, Pakistan. The Random Forest (RF) and Kernel Ridge Regression (KRR) models were developed and evaluated using yield data of two species (Blue pine and Silver fir) as an objective variable and climate data (temperature, humidity, rainfall and wind speed) as predictive variables. Prediction accuracy of both the models were assessed by means of root mean squared error (RMSE), mean absolute error (MAE), correlation coefficient (r), relative root mean squared error (RRMSE), Legates-McCabe’s (LM), Willmott’s index (WI) and Nash-Sutcliffe (NS_E) metrics. Overall, the RF model outperformed the KRR model due to its higher accuracy in forecasting of forest yield. The study strongly recommends that RF model should be applied in other regions of the country for prediction of forest growth and yield, which may help in the management and future planning of forest productivity in Pakistan.