This study combines air pollution tolerance index (APTI) and anticipated performance index (API) in order to determine the potential of trees and ornamental shrubs that are frequently growing on the roads of Quetta, Pakistan, and the campus of the University of Balochistan, in Quetta, for green belt development. Our investigation exposed that not only APTI is suitable for the fitness of trees for building green belts. It is used to categorize vulnerable plant species for only bio-monitoring. The grouping of APTI and API in the present study is a practical technique for decreasing air pollution control. Laboratory analysis for APTI was carry out by the four physico-biological factors such as leaf extract pH, total chlorophyll content, ascorbic acid content, and relative water content. API for different plant species (trees and ornamental shrubs) was determined depending upon the characteristic grading by allotted + or-to the plants. The standard for determining API is given in Table 2. For examining the relationships among these factors statistics were utilized. This study indicated that the APTI is used as an instrument for choosing suitable plants to reduce environmental urban heat. API designated that Morus alba L., Pinus halepensis Miller, Ficus carica L., and Pistacia vera L. with API = 6 are excellent performers for green belt development. Morus nigra L. and Malus pumila Miller had API 5 and are considered very good performers, and Fraxinus angustifolia Vahl., Prunus armeniaca L., and Platycladus orientalis L. showed 4 API values with good performance for green belt formation. All the other remaining investigated trees and ornamental shrubs demonstrated poor values of API

Due to the COVID-19 pandemic, all countries around the world have imposed nationwide lockdowns to control the spreading of the virus. During the lockdown period, many countries saw a drastic drop in air pollution. In Bangladesh, there were two nationwide lockdowns. The first lockdown was imposed on 26 March–30 May in 2020 and the second lockdown was imposed on 3 April until the study period of 31 May in 2021. This study aimed to analyze the NO2 pollution over Bangladesh during the two periods of lockdown. Tropospheric NO2 column spatial configuration was measured over Bangladesh using Sentinel-5P data. A map of the monthly average concentration of tropospheric NO2 in 2020 and 2021 over Bangladesh was produced using the HARP toolkit and Python. Then, the map was compared with same period Sentinel-5P product’s map for the same period in 2019. It was found that during the first lockdown in Bangladesh between 26 March and 30 May 2020, NO2 concentration drastically decreased in April but increased in May. However, during the second lockdown from 3 April to 31 May in 2021, the NO2 concentration was found to be much higher. Most of the pollution occurred in the Dhaka district. During the second lockdown, the restrictions were much lighter than those during the first one, which impacted the NO2 concentration. This kind of study can be essential for the authorities to look closely at air quality and use sentinel data to improve air quality monitoring in the future.

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