Investigating the nitrogen dioxide concentrations in the boundary layer by using multi-axis spectroscopic measurements and comparison with satellite observations

The relationship between political instability and stock market performance: An analysis of the MSCI index in the case of Pakistan

The stock market is the barometer of the economy that reflects the overall health and direction of the economic development and is affected by different factors including social, environmental and political. It is important to investigate the effect of the political instability on the stock market performance, especially on emerging economies. Therefore, we aim to study the relationship between political instability and stock market performance in Pakistan. To meet our objectives, we used past data from 1996 to 2021. Data are collected from the DataStream data base. MSCI indices are used as the proxy for the Stock market performance of the selected country. World governance six indicators are used in the study as the explanatory variable concentrating the political instability index as the main explanatory variable. Regression analysis is used but two-way robustness analysis was done for the accuracy of the findings through GMM methods and taking GDP as another endogenous variable. Our findings shows that the political stability has significant positive impact on the stock market performance while, political instability has negative impact on stock market performance. Moreover, other governance indicators has a significant positive impact on performance. However, political instability disrupts the operations and economical activities that leads to decrease the investor confidence and also decrease the foreign investment with the increment of the risk in the country. Moreover, our study has some implications for investors to develop the diversified portfolio to minimize the risk and policy makers can increase their foreign direct investment within the economy by controlling the political instability.

Inorganic-organic nanofiber networks with antibacteria properties for enhanced particulate filtration: The critical role of amorphous titania

The demand for air filter media at indoor and outdoor is increasing tremendously due to air pollution and especially for problems related to airborne particulate matter (PM). To realize that, here a class nanofiber air filter media with strong antibacterial activity, hydrophobic nature, high filtration efficiency with low pressure drop is prepared. Novel organic-inorganic nanocomposite nanofibers used in this work benefited for the multifunctional performance. Amorphous titanium dioxide (mTiO₂) is utilized for air filtration application which exhibits excellent enhancement of PM_2.5 filtration properties and antibacterial activity. The unique Poly (vinylpyrrolidone) (PVP)-mTiO₂ nanofiber air filter media acquired hydrophobic nature with a large increase in water contact angle of 127° from 36°. The resulting free-standing nanofiber filters exhibit high PM_2.5 filtration efficiency of >99.9% and low pressure drop of 39 Pa. Antibacterial activity of nanofibrous membrane has been rationally engineered by titanium oxide as the barrier to bacterial ingression. A long term of 160 h filtration test has proved PVP-mTiO₂ nanofibers air filter media holds outstanding 99% filtration efficiency for PM_2.5. This work takes forward a significant lead in design and production of high performance and very low pressure drop air filter media with a wide range of functional properties.

The COVID-19 pandemic and its impact on environment: the case of the major cities in Pakistan

In Wuhan city, China, a pneumonia-like disease of unknown origin triggered a catastrophe. This disease has spread to 215 nations, affecting a diverse variety of persons. It was formally called extreme acute respiratory syndrome coronavirus 2 (SARS CoV-2), also known as coronavirus disease, by the World Health Organization as a pandemic. This pandemic forced countries to enforce a socio-economic lockdown to avoid its widespread presence. This study focuses on how the pollution of particulate matter during the coronavirus pandemic in the period from 23 March 2020 to 31 December 2020 was reduced compared to the pre-pandemic situation in the country. The improvement in air quality and atmosphere due to the coronavirus pandemic in Pakistan was identified by both ground-based and satellite observations with a primary focus on the four provincial capitals and country capitals, namely, Peshawar, Karachi, Quetta, Lahore, and Islamabad, and statistically verified through paired Student's t test. Both datasets have shown a significant decrease in the levels of PM2.5 pollutions across Pakistan (ranging from 15 to 35% for satellite observations, while 27 to 61% for ground-based observations). The result shows that poor air quality is one of the key factors for a higher COVID-19 spread rate in major Pakistani cities. By extending the same investigation across the nation, there is a greater need to investigate the connections between COVID-19 spread and air pollution. However, both higher population density rates and frequent population exposure can be partially attributed to increased levels of PM2.5 concentrations before the pandemic of the coronavirus.

Exploring the linkage between PM2.5 levels and COVID-19 spread and its implications for socio-economic circles

A pneumonia-like disease of unknown origin caused a catastrophe in Wuhan city, China. This disease spread to 215 countries affecting a wide range of people. World health organization (WHO) called it a pandemic and it was officially named as Severe Acute Respiratory Syndrome Corona virus 2 (SARS CoV-2), also known as Corona virus disease (COVID-19). This pandemic compelled countries to enforce a socio-economic lockdown to prevent its widespread. This paper focuses on how the particulate matter pollution was reduced during the lockdown period (23 March to April 15, 2020) as compared to before lockdown. Both ground-based and satellite observations were used to identify the improvement in air quality of Pakistan with primary focus on four major cities of Lahore, Islamabad, Karachi and Peshawar. Both datasets have shown a substantial reduction in PM_2.5 pollution levels (ranging from 13% to 33% in case of satellite observations, while 23%-58% in ground-based observations) across Pakistan. Result shows a higher rate of COVID-19 spread in major cities of Pakistan with poor air quality conditions. Yet more research is needed in order to establish linkage between COVID-19 spread and air pollution. However, it can be partially attributed to both higher rate of population density and frequent exposure of population to enhanced levels of PM_2.5 concentrations before lockdown period.

An Emerged Challenge of Air Pollution and Ever-Increasing Particulate Matter in Pakistan; A Critical Review

This study, for the first time, aims to evaluate the situation of air quality in Pakistan critically; through a detailed assessment of sources, policies, and key challenges to identify the plausible way forward. Air pollution and particulate matter have merged as a global challenge in recent years because of its growing health and socio-economic risks. The intensity and impacts of these risks have become more pronounced, especially in developing countries like Pakistan that lack adequate warning, protection, and management systems. Various epidemiological studies have linked poor air quality with different health disorders and increasing death rates. In Pakistan, mortality rates as a result of exposure to increased levels of air pollutants, especially particulate matter, are alarming. According to the World Bank's estimates, Pakistan's annual burden of disease from outdoor air pollution is responsible for around 22,000 premature adult deaths and 163,432 DALYs (disability-adjusted life years) lost. The concentration of major air pollutants in Pakistan, such as NOx, O_3, and SO₂ have also been increasing significantly over the last two decades. Several studies are also reporting multiple instances of air quality around the major cities of Pakistan being consistently exceeding the national guidelines. During teh year 2019 PM_2.5 cocnentrations in the city of Lahore revealed that almost every single day was in exceedance of the WHO and national air quality standards. Although the substantial effects of these rising pollutant concentrations in Pakistan have been stated in a few studies, however, the total extent, nature of contributing factors, and consequences remain inadequately understood. This study aims to use data available from monitoring stations, satellites, and literature to highlight the gaps in our understanding and emphasize the critical challenges associated with poor air quality faced in Pakistan. Topmost is the lack of air quality monitoring systems followed by poor initiatives by policymakers and enforcement agencies. A way forward while addressing these key challenges is also discussed, which focuses on the development of flexible monitoring, new technologies, and monitoring approaches in addition to communications among the various public, private agencies, and all relevant stakeholders.

Impact assessment of meteorological and environmental parameters on PM2.5 concentrations using remote sensing data and GWR analysis (case study of Tehran)

The PM_2.5 as one of the main pollutants in Tehran city has a devastating effect on human health. Knowing the key parameters associated with PM_2.5 concentration is essential to take effective actions to reduce the concentration of these particles. This study assesses the relationship between meteorological (humidity, pressure, temperature, precipitation, and wind speed) and environmental parameters (normalize difference vegetation index and land surface temperature of MODIS satellite data) on PM_2.5 concentration in Tehran city. The Geographically Weighted Regression (GWR) was employed to assess the impact of key parameters on PM_2.5 concentrations in winter and summer. For this purpose, first the seasonal average of meteorological data were extracted and synchronized to satellite data. Then, using the ordinary least square model, the important parameters related to PM_2.5 concentration were determined and evaluated. Finally, using the GWR model, the relationships between parameters related to PM_2.5 concentration were analyzed. The results of this study indicate that meteorological and environmental parameters in winter season (71%) have a much higher ability to explain PM_2.5 concentration than summer season (40%). In winter, PM_2.5 concentration has a negative correlation with vegetation at most parts of the study area, a negative correlation with LST in the western and a positive correlation in the eastern part of the study area, a positive correlation with temperature, and a negative correlation with wind speed in the northeastern part of the study area. Precipitation has a positive correlation with PM_2.5 concentration in most parts of the study area in both seasons. But, it was investigated in case of higher precipitation (more than 2 mm), PM_2.5 concentration decreases. But, there is no negative relationship in any of the dependent parameters with PM_2.5 concentration in summer. In this season, the air temperature parameter showed a high correlation with PM_2.5 concentration. Also, spatial variations of the local coefficients for all parameters are higher in winter than in summer.

Multi-sensor temporal assessment of tropospheric nitrogen dioxide column densities over Pakistan

Spatial and temporal distributions of tropospheric NO₂ vertical column densities over Pakistan during the period 2002-2014 are discussed. Data products from three satellite instruments SCIAMACHY, OMI, and GOME-2 are used to prepare a database of tropospheric NO₂ column densities over Pakistan and temporal evolution is also determined. Plausible NO₂ sources in Pakistan are also discussed. The results show a large NO₂ growth over all provinces and the major cities of Pakistan except the megacity of Karachi. Decline in industrial activities due to energy crises, worsening law and order situation, terrorist attacks, and political instability was explored as the main factor for lower NO₂ VCDs over Karachi City. The overall increase can be attributed to the anthropogenic emissions over the areas with high population, traffic density, and industrial activities. Source identification revealed that use of fossil fuels by various sectors including power generation, vehicles, and residential sectors along with agriculture fires are among significant sources of NO₂ emissions in Pakistan. Existing emission inventories such as EDGARv4.2 and MACCity largely underestimate the true anthropogenic NO_x emissions in Pakistan. This study may provide vital information to policy makers and regulatory authorities in developing countries, including Pakistan, in order to devise effective air pollution abatement policies.

Identification and future description of warming signatures over Pakistan with special emphasis on evolution of CO2 levels and temperature during the first decade of the twenty-first century

Like other developing countries, Pakistan is also facing changes in temperature per decade and other climatic abnormalities like droughts and torrential rains. In order to assess and identify the extent of temperature change over Pakistan, the whole Pakistan was divided into five climatic zones ranging from very cold to hot and dry climates. Similarly, seasons in Pakistan are defined on the basis of monsoon variability as winter, pre-monsoon, monsoon, and post-monsoon. This study primarily focuses on the comparison of surface temperature observations from Pakistan Meteorological Department (PMD) network with PRECIS (Providing Regional Climates for Impacts Studies) model simulations. Results indicate that PRECIS underestimates the temperature in Northern Pakistan and during the winter season. However, there exists a fair agreement between PRECIS output and observed datasets in the lower plain and hot areas of the country. An absolute increase of 0.07 °C is observed in the mean temperature over Pakistan during the time period of 1951-2010. Especially, the increase is more significant (0.7 °C) during the last 14 years (1997-2010). Moreover, SCIAMACHY observations were used to explore the evolution of atmospheric CO₂ levels in comparison to temperature over Pakistan. CO₂ levels have shown an increasing trend during the first decade of the twenty-first century.