Classification of aerosols using particle linear depolarization ratio (PLDR) over seven urban locations of Asia.

Active lidar remote sensing has been used to obtain detailed and quantitative information about the properties of aerosols. We have analyzed the spatio-temporal classification of aerosols using the parameters of particle linear depolarization ratio and single scattering albedo from Aerosol Robotic Network (AERONET) over seven megacities of Asia namely; Lahore, Karachi, Kanpur, Pune, Beijing, Osaka, and Bandung. We find that pollution aerosols dominate during the winter season in all the megacities. The concentrations, however, vary concerning the locations, i.e., 70-80% pollution aerosols are present over Lahore, 40-50% over Karachi, 90-95% over Kanpur and Pune, 60-70% and over Beijing and Osaka. Pure Dust (PD), Pollution Dominated Mixture (PDM), and Dust Dominated Mixture (DDM) are found to be dominant during spring and summer seasons.This proposes that dust over Asia normally exists as a mixture with pollution aerosols instead of pure form. We also find that black carbon (BC) dominated pollution aerosols.

Assessment of variability in PM2.5 and its impact on human health in a West African country.

PM2.5 has become a global challenge threatening human health, climate, and the environment. PM2.5 is ranked as the most common cause of premature mortality and morbidity. Therefore, the current study endeavors to probe the spatiodynamic characteristics of PM2.5 in the Republic of Niger and its impacts on human health from 1998 to 2019. Based on remotely sensed satellite datasets, the study found that the concentration of PM2.5 continued to rise in Niger from 68.85 µg/m3 in 1998 to 70.47 µg/m3 in 2019. During the study period, the annual average PM2.5 concentration is far above the WHO guidelines and the interim target-1 (35 µg/m3). The overall annual growth rate of PM2.5 concentration in Niger is 0.02 µg/m3/year. The health risk (HR) due to PM2.5 exposure is also escalated in Niger, particularly, in Southern Niger. The extent of the extremely high-risk areas corresponding to 1 × 104-9.4 × 105 µg.persons/m3 is increased from 0.9% (2000) to 2.8% (2019). Niamey, southern Dakoro, Mayahi, Tessaoua, Mirriah, Magaria, Matameye, Aguié, Madarounfa, Groumdji, Madaoua, Bouza, Keita, eastern Tahoua, eastern Illéla, Bkomnni, southern Dogon-Doutchi, Gaya, eastern Boboye, central Kollo, and western Tillabéry are experienced high HR due to long-term exposure to PM2.5. These findings indicate that PM2.5 causes a serious health risk across Niger. There is an immediate need to carry out its regional control. Therefore, policymakers and the Nigerien government should make conscious efforts to identify the priority target areas with radically innovative appropriate mitigation interventions.

Long term spatiotemporal trends and health risk assessment of remotely sensed PM2.5 concentrations in Nigeria.

PM2.5 is an important indicator reflecting air quality variations. Currently, environmental pollution related issues have become more severe that significantly threaten human health. The current study is an attempt to analyze the spatio-dynamic characteristics of PM2.5 in Nigeria based on the directional distribution and trend clustering analysis from 2001 to 2019. The results indicated that PM2.5 concentration increased in most of the Nigerian states, particularly in mid-northern and southern states. The lowest PM2.5 concentration in Nigeria is even beyond the interim target-1 (35 µg/m3) of the WHO. During the study period, the average PM2.5 concentration increased at a growth rate of 0.2 µg/m3/yr from 69 µg/m3 to 81 µg/m3. The growth rate varied from region to region. Kano, Jigawa, Katsina, Bauchi, Yobe, and Zamfara experienced the fastest growth rate of 0.9 µg/m3/yr with 77.9 µg/m3 mean concentration. The median center of the national average PM2.5 moved toward the north indicating the highest PM2.5 concentration in northern states. The Saharan desert dust is the dominant source of PM2.5 in northern areas. Moreover, agricultural practices and deforestation activities along with low rainfall increase desertification and air pollution in these regions. Health risks increased in most of the mid-northern and southern states. The extent of ultra-high health risk (UHR) areas corresponding to the 8×104-7.3×106 µg⋅person/m3 increased from 1.5% to 2.8%. Mainly Kano, Lagos, Oyo, Edo, Osun, Ekiti, southeastern Kwara, Kogi, Enugu, Anambra, Northeastern Imo, Abia, River, Delta, northeastern Bayelsa, Akwa Ibom, Ebonyi, Abuja, Northern Kaduna, Katsina, Jigawa, central Sokoto, northeastern Zamfara, central Borno, central Adamawa, and northwestern Plateau are under UHR areas.

Defining the role of renewable energy, economic growth, globalization, energy consumption, and population growth on PM2.5 concentration: evidence from South Asian countries.

Rapid industrialization and economic development in South Asia (SA) caused serious air pollution-related issues. Air pollutants, particularly fine particulate matter (PM2.5), have negative effects on health, instigating widespread concern. The current study is an attempt to analyze the impact of non-renewable energy (NRE), globalization (GLO), GDP, renewable energy (RE), and population (POP) on PM2.5 concentration in SA from 1998 to 2020. In doing so, this study incorporated advanced and robust econometric techniques, i.e., Pesaran (Economet Rev 34(6-10), 1089-1117, 2015), to check the cross-sectional dependency, and the unit root presence checked through Cross-sectional Im, Pesaran, and Shin (CIPS) and Cross-sectionally Augmented Dickey-Fuller (CADF) unit root tests. Moreover, the long and short-run association among the selected variables was analyzed through Westerlund and Edgerton (Econ Lett 97(3), 185-190, 2007), cointegration test, and cross-sectional augmented ARDL (CS-ARDL). The empirical results indicate that the panel was cross-sectionally correlated, stationary at the first difference, and co-integrated in the long run. Moreover, the CS-ARDL model indicates a positive association between GDP and PM2.5 concentration. Similarly, NRE and POP contribute significantly to increasing the PM2.5 concentration in SA. However, RE and GLO play an important role to decrease the PM2.5 concentration in SA.

Spatial and temporal variations in PM2.5 and associated health risk assessment in Saudi Arabia using remote sensing.

Air pollutants, especially ambient particulate matter (PM2.5), detrimentally impact human health and cause premature deaths. The dynamic characteristics and associated health risks of PM2.5 are analyzed based on the standard deviational ellipse (SDE) and trend analysis in Saudi Arabia (SAU) from 1998 to 2018 by utilizing recently updated satellite-derived PM2.5 concentrations (V4.GL.03). The outcomes show that the national average PM2.5 concentration increased from 28 µg/m3 to 45 µg/m3 with a growth rate of 2.3 µg/m3/year. The center of median PM2.5 concentrations moved to the southeast over the years studied due to the presence of vast sandy deserts, sand dunes, a busy port, and coastal and industrial areas in this region. The areas of SAU that experienced PM2.5 concentrations above 35 µg/m3 increased from 20% to 70%. The rapid-fast growth (RFG) class acquired from the unsupervised classification has the fastest growth rate of 2.5 µg/m3/yr, occurring in southeastern SAU, namely Ash-Sharqiyah, Ar-Riyad, and Najran. It covered ∼27% of the total area of SAU over the study period. Whereas, the slow growth (SG) class with a less than 0.2 µg/m3/yr growth rate covered 12% of the total area of SAU, distributed in northwestern regions. The extent of extremely-high risk areas corresponding to greater than 1 × 103 µg·person/m3 increased from 4% to 11%, particularly in Makkah, Central Al-Madinah, and western Asir, Jizan, mid-eastern Najran, Al-Quassim, and mid-eastern Ar-Riyad and Ash Sharqiyah.

Evaluating the Influences of Natural Resources and Ageing People on CO2 Emissions in G-11 Nations: Application of CS-ARDL Approach.

Globalization as well as the ratio of ageing people in the group of 11 (G-11) countries has seen a rapid increase in recent years. Therefore, this study aims to provide effective policy recommendations for sustainable development goals 13, 8, and 7, for the G-11 countries. This work estimates the impact of natural resources and the ageing population on the emission of carbon dioxide (CO2) in G-11 countries using panel data from 1990-2020. For empirical results, second-generation methods were applied. The Westerlund co-integration test that assesses co-integration confirms the firm association among the parameters, and the values of coefficient of the cross-sectional autoregressive distributed lag (CS-ARDL) approach show that a 1% increase in the ageing population will lower the emissions of CO2 by 13.41% among G-11 countries. Moreover, the findings show that there exists an environmental Kuznets curve (EKC) among natural resources, globalization, economic growth, ageing people, and the emission of CO2. Based on the findings, this work presents some important policy implications for achieving sustainable growth in the G-11 countries. These countries need to lower the amount of energy obtained from fossil fuels to improve air quality.

Exploring the existence of environmental Phillips curve in South Asian countries.

Considering the economic activities that trigger alarming situations for the global atmosphere and ecology, this work probes the associations of unemployment (UNE), GDP, population growth (POP), renewable (REN), non-renewable energy use (ENE), and ecological footprints (EF) for South Asian countries. The annual data of 1991-2019 is analyzed for empirical results. This is the first study that employs panel as well as country-specific estimations for South Asian countries by utilizing the Pool mean group (PMG) and autoregressive distributed lag (ARDL) methods, respectively. The study also validates the environmental Phillips curve (EPC) for selected counties. The empirical evidence in all models confirms the positive effects of GDP, ENE, and POP on environmental dilapidation whereas REN and UNE reduce environmental deprivation. The findings confirm the presence of the EPC in South Asian countries. This work presents some important policy instruments for south Asian countries to reduce environmental pollution. In the efforts to improve air quality, these countries have increased unemployment. These nations have to raise the share of renewable energy to the total energy consumption. This will sustain their economies with an increasing employment ratio. At the same time, there is a need to revise the urban policies because the increasing population is also a contributing factor towards environmental degradation.

Spatio-temporal variations in fine particulate matter and evaluation of associated health risk over Pakistan.

Human health and the environment are adversely affected by fine particulate matter. By utilizing standard deviation ellipse and trend analyses, we studied the spatial patterns and temporal trends of PM2.5 over Pakistan from 1998 to 2016. The outcomes of these analyses indicated that PM2.5 concentrations were considerably amplified in Pakistan, particularly in the provinces of Punjab and Sindh. The areal extent of PM2.5 concentrations below 15 µg/m3 declined constantly, and the area with PM2.5 concentrations above 35 µg/m3 increased significantly. The highly affected cities were Lahore, Faisalabad, Multan, Southern Gujranwala, Dera Ghazi Khan, Bahawalpur, Sukkur, and Larkana. Overall, the northwest-southeast axis experienced more rapid variations in the spatial pattern of PM2.5 than the northeast-southwest axis; similarly, the east-north axis also experienced faster changes in the spatial distribution of this crucial pollutant than the west-south axis. To support nationwide air pollution control, a two-tier level was recommended for allocated regions in Pakistan depending on their PM2.5 concentrations. From 1998 to 2016, health risks expanded and increased in Pakistan, particularly in Lahore, Karachi, Multan, Gujranwala, Faisalabad, and Hyderabad; these are Pakistan's most populated cities. The outcomes of this study suggest that human health is continuously affected by PM2.5 in Pakistan, and that a plan of action to combat air pollution is immediately needed. Integr Environ Assess Manag 2021;17:1243-1254. © 2021 SETAC.