Search

The current study was carried out to analyze the role of religiosity, family integration, and social capital as predictors of post-incarceration reintegration in Punjab, Pakistan. The current study was carried out using quantitative research methods with the implication of cross-sectional, explanatory, and survey research approaches. Data were collected by using interview schedules by visiting ex-inmates at their community settings and by telephonic interviews. The research instrument was developed by using preexisting scales pertaining to the variables of the study. To obtain the study results, descriptive analysis, KMO factor analysis, reliability analysis, and regression analysis were applied to test the study model using SPSS and Smart PLS SEM (structural equation modelling). The findings of the study showed that all the predictor variables in the model (religiosity, family integration, and social capital) showed a positive and statistically significant effect on the reintegration of ex-prisoners following their release from prison. However, in comparison to all predictor variables, family integration has a strong effect (0.568) on post-incarceration reintegration. [ABSTRACT FROM AUTHOR]

Several agroforestry systems prevail in different agro-ecological zones of Pakistan, and cover a remarkable area of 19.3 million hectares. They not only play an important role in slowing down CO2 emissions, but also contribute to mitigating climate change. However, in many regions, the relevant effect of agroforestry systems on overall carbon (C) stock and their reliance on various factors are quite unidentified. This study was planned to assess the biomass accumulation and C stocks of different commonly practiced agroforestry systems (boundary, bund, scattered, agri-horticulture) and their constituent land use types (tree + cropland) through a non-destructive approach (allometric equations) in a semi-arid region of Punjab, Pakistan. The results showed that the highest plant biomass (87.12 t ha−1) increased by 46%, 17%, 78%, and 339%, and C stock (42.77 t ha−1) increased by 49.51%, 20%, 82%, and 361% in the boundary planting system compared to the bund, scattered, agri-horti and sole cropland, respectively. The soil organic carbon (SOC) stock at all three depths, 0–15 cm, 15–30 cm & 30–45 cm, was found in the following order: boundary planting system > bund planting system > agri-horti system > scattered planting system > agricultural system, with a maximum in the boundary planting system and minimum in the sole cropping system at all three depths. Overall, the total C stock of the ecosystem's vegetation + soil C (0–30 cm) in the forested area was 275 t ha−1, equating to 37 t ha−1 in the agricultural system alone. Our results highlighted that agroforestry systems have the highest potential for C sequestration. We suggest that research and investment in agroforestry systems can be a successful way for Pakistan to achieve some of its climate change mitigation goals. [ABSTRACT FROM AUTHOR]

Industries have been a major culprit in increasing carbonaceous emissions and major contributors to global warming over the past decades. Factories in the urban periphery tend to warm cities more as compared with rural surroundings. Recently, nature-based solutions have been promoted to provide solutions related to climate adaptations and mitigation issues and challenges. Among these solutions, urban trees have proven to be an effective solution to remove air pollutants and mitigate air pollution specifically caused by carbon emissions. This work was designed to assess the role of tree species in mitigating air emissions of carbon around the vicinity of various industrial sites. For this purpose, three different industrial sites (weaving, brick kiln, and cosmetic) were selected to collect data. Selected industrial sites were divided into two areas, i.e., (a) area inside the industry and (b) area outside the industry. The samples were collected from 100 square meters inside the industries and 100 square meters outside the industries. Five different trees species comprised of four replications were selected for sampling. About twenty trees species from inside and outside of the industries were measured, making it 120 trees from all three selected industries for estimating aboveground and belowground biomass, showing their carbon estimation. The results showed that Moringa oleifera depicted overall higher total biomass from both inside (2.58, 0.56, and 4.57 Mg ha−1) and outside sites from all three selected industries. In terms of total carbon stock and carbon sequestration inside the industry sites, Syzygium cumini had the most dominant values in the weaving industry (2.82 and 10.32 Mg ha−1) and brick kiln (3.78 and 13.5 Mg ha−1), while in the cosmetic industry sites, Eucalyptus camaldulensis depicted higher carbon, stock, and sequestration values (7.83 and 28.70 Mg ha−1). In comparison, the sites outside the industries' vicinity depicted overall lower carbon, stock, and sequestration values. The most dominant tree inside came out to be Dalbergia sisso (0.97 and 3.54 Mg ha−1) in the weaving industry sites, having higher values of carbon stock and carbon sequestration. Moringa oliefra (1.26 and 4.63) depicted dominant values in brick kiln sites, while in the cosmetic industry, Vachellia nilotica (2.51 and 9.19 Mg ha−1) displayed maximum values as compared with other species. The findings regarding belowground biomass and carbon storage indicate that the amount of soil carbon decreased with the increase in depth; higher soil carbon stock values were depicted at a 0–20 cm depth inside and outside the industries. The study concludes that forest tree species present inside and outside the vicinity of various industries have strong potential in mitigating air emissions. [ABSTRACT FROM AUTHOR]

The current study was conducted to estimate the carbon (C) storage status of agroforestry systems, via a non-destructive strategy. A total of 75 plots (0.405 ha each) were selected by adopting a lottery method of random sampling for C stock estimations for soil, trees and crops in the Mandi-Bahauddin district, Punjab, Pakistan. Results revealed that the existing number of trees in selected farm plots varied from 25 to 30 trees/ha. Total mean tree carbon stock ranged from 9.97 to 133 Mg C ha−1, between 5–10 km away from the brick kilns in the study area. The decreasing order in terms of carbon storage potential of trees was Eucalyptus camaldulensis > Syzygium cumin > Popolus ciliata > Acacia nilotica > Ziziphus manritiana > Citrus sinensis > Azadirachtta Indica > Delbergia sisso > Bambusa vulgaris > Melia azadarach > Morus alba. Average soil carbon pools ranged from 10.3–12.5 Mg C ha−1 in the study area. Meanwhile, maximum C stock for wheat (2.08 × 106 Mg C) and rice (1.97 × 106 Mg C) was recorded in the cultivated area of Tehsil Mandi-Bahauddin. The entire ecosystem of the study area had an estimated woody vegetation carbon stock of 68.5 Mg C ha−1 and a soil carbon stock of 10.7 Mg C ha−1. These results highlight that climate-smart agriculture has great potential to lock up more carbon and help in the reduction of CO2 emissions to the atmosphere, and can be further used in planning policies for executing tree planting agendas on cultivated lands and for planning future carbon sequestration ventures in Pakistan. [ABSTRACT FROM AUTHOR]