Plastic waste accumulation has been recognized as one of the most critical challenges of modern societies worldwide. Traditional waste management practices include open burning, landfilling, and incineration, resulting in greenhouse gas emissions and economic loss. In contrast, emerging techniques for plastic waste management include microwave-assisted conversion, plasma-assisted conversion, supercritical water conversion, and photo reforming to obtain high-value products. Problems with poorly managed plastic waste are particularly serious in developing countries. This review article examines the emerging strategies and production of various high-value-added products from plastic waste. Additionally, the uses of plastic waste in different sectors, such as construction, fuel production, wastewater treatment, electrode materials, carbonaceous nanomaterials, and other high-value-added products are reviewed. It has been observed that there is a pressing need to utilize plastic waste for a circular economy and recycling for different value-added products. More specifically, there is limited knowledge on emerging plastic waste conversion mechanisms and efficiency. Therefore, this review will help to highlight the negative environmental impacts of plastic waste accumulation and the importance of modern techniques for waste management.

Brick kilns add enormous quantities of organic pollutants to the air that can cause serious health issues, especially in developing countries; poor air quality is associated with community health problems, yet receives no attention in Northern Pakistan. The present study, therefore, assessed the chemical composition and investigated the impacts of air pollution from brick kilns on public health. A field-based investigation of air pollutants, i.e., PM₁, PM_2.5 and PM₁₀, CO₂, CO, NO, NO₂, H₂S, and NH₃ using mobile scientific instruments was conducted in selected study area locations. Social surveys were conducted to investigate the impacts of air pollution on community health. The results reveal the highest concentrations of PM1, PM2.5, and PM10, i.e., 3377, 2305, and 3567.67 µg/m3, respectively, in specific locations. Particulate matter concentrations in sampling points exceeded the permissible limits of the Pakistan National Environmental Quality Standard and, therefore, may risk the local population’s health. The highest mean value of CO₂ was 529 mg/L, and other parameters, such as CO, NO, NO₂, H₂S, and NH₃ were within the normal range. The social survey’s findings reveal that particulate matter was directly associated with respiratory diseases such as asthma, which was reported in all age groups selected for sampling. The study concluded by implementing air pollution reduction measures in brick kiln industries to protect the environment and community health. In addition, the region’s environmental protection agency needs to play an active role in proper checking and integrated management to improve air quality and protect the community from air hazards.

In this paper, new models were investigated and developed for landslide hazards in Muzaffarabad District, located in the Azad Jammu and Kashmir region of Pakistan. The influential factors used in the landslide modelling were land use/landcover (LULC), elevation, slope, slope aspect, rainfall, drainage, road, surface roughness, and topographic index. The GIS-based Analytic Hierarchy Process (AHP) model was applied by utilizing the database of 35 active landslides and their pixels present in classes of all influential factors. The mean landslide hazard values, obtained from the mean landslide hazard analysis, were used as hazard weightages in the AHP model for development of a landslide hazard zone map. The highest mean hazard values for: (i) bare soil in LULC was 14.6%; (ii) 600–800 m in elevation was 6.89%; (iii) 30°–35° in slope was 6%; (iv) S and SW in slope aspect was 9.01%; (v) 1350–1405 mm/yr in rainfall was 9.03%; (vi) 40–80 m in buffered drainage was 12.83%; (vii) 40–80 m in buffered road was 12.48%; (viii) 60–138 in surface roughness index was 10.99%; (ix) −1.74–−1.25 in topographic position index was 13.07%. The percentages of very low, low, moderate, high, and very high landslide hazard zones were 1.48%, 11.80%, 39.36%, 37.36%, and 9.57% respectively. The co-efficient of the determination (r²) value of 0.96 indicated a strong relationship between the model development and validation. Thus, landslide hazard zone map models and methodology indicated a very high accuracy. This landslide hazard zone map could be utilized for the landslide damages’ reduction and the planning and development of road and building infrastructures in the study area. Additionally, this research could be replicated in other landslide prone areas of Pakistan for the minimizing the damages of landslides.

Human activities are altering the existing patterns of Land Use Land Cover (LULC) and Land Surface Temperature (LST) on a global scale. However, long-term trends of LULC and LST are largely unknown in many remote mountain areas such as the Karakorum. . The objective of our study therefore was to evaluate the historical changes in land use and land cover (LULC) in an alpine environment located in Islamabad Capital Territory, Pakistan. We used Landsat satellite pictures (namely Landsat 5 TM and Landsat 8 OLI) from the years 1988, 2002, and 2016 and applied the Maximum Likelihood Classification (MLC) approach to categorize land use classes. Land Surface Temperatures (LST) were calculated using the thermal bands (6, 10, and 11) of Landsat series data. The correlation between the Human Modification Index (HMI) and LULC as well as LST was evaluated by utilizing data from Google Earth Engine (GEE). Over the study period, the urbanized area increased by 9.94%, whilst the agricultural and bare soil areas decreased by 3.81% and 3.94%, respectively. The findings revealed a significant change in the LULC with a decrease of 1.99% in vegetation. The highest LST class exhibited a progressive trend, with an increase from 12.27% to 48.48%. Based on the LST analysis, the built-up area shows the highest temperature, followed by the barren, agricultural, and vegetation categories. Similarly, the HMI for different LST categories indicates that higher LST categories have higher levels of human alteration compared to lower LST categories, with a strong correlation (R-value = 0.61) between HMI and LST. The findings can be utilized to promote sustainable urban management and for biodiversity conservation efforts. The work also has the potential of utilizing it to protect delicate ecosystems from human interference and to formulate strategies and regulations for sustainable urban growth, including aspects of land utilization and zoning, reduction of urban heat stress, and urban infrastructure.