PM2.5 Concentration Exposure over the Belt and Road Region from 2000 to 2020

Global economic structure transition boosts PM2.5-related human health impact in Belt and Road Initiative

The Belt and Road Initiative (BRI) is an open platform for international cooperation proposed by China to promote common global development and prosperity. The BRI can promote the optimal allocation of resources and promote in-depth cooperation in international trade. Meanwhile, it can establish a green supply chain cooperation network to help BRI countries achieve green transformation. BRI has made a notable contribution to the rapid growth of cross-border trade. However, it has also brought environmental impacts. Given that little attention has been paid to the trade-embodied particulate matter 2.5 related human health impacts (PM2.5-HHI) throughout the BRI, this study accounts for and traces the embodied PM2.5-HHI flows between the BRI countries and non-Belt and Road Initiative (non-BRI) countries. Moreover, this study also uncovers the critical socioeconomic drivers of PM2.5-HHI changes in BRI countries during 1990-2015, based on the multi-regional input-output based structural decomposition analysis (MRIO-SDA). Results show that, firstly, BRI countries had significantly increased their economic added value by exporting products to the non-BRI countries. They also have brought PM2.5-HHI to themselves. Secondly, the final demand of BRI countries was the largest potential driving force of PM2.5-HHI of BRI countries. Thirdly, the emission intensity change of BRI is the key socioeconomic factor for reducing PM2.5-HHI. While per capita final demand level change of BRI and production structure change of non-BRI are the key socioeconomic factors for increasing PM2.5-HHI. The study's findings on the one hand can help reduce the PM2.5-HHI and impacts of environmental pollution of BRI countries from a global perspective by providing scientific support. On the other hand, they can help provide relevant policy recommendations for the green transformation of BRI and the construction of green BRI.

The cellular consequences of particulate matter pollutants in plants: Safeguarding the harmonious integration of structure and function

Particulate matter (PM) pollution is one of the pressing environmental concerns confronting human civilization in the face of the Anthropocene era. Plants are continuously exposed to an accelerating PM, threatening their growth and productivity. Although plants and plant-based infrastructures can potentially reduce ambient air pollutants, PM still affects them morphologically, anatomically, and physiologically. This review comprehensively summarizes an up-to-date review of plant-PM interaction among different functional plant groups, PM deposition and penetration through aboveground and belowground plant parts, and plants' cellular strategies. Upon exposure, PM represses lipid desaturases, eventually leading to modification of cell wall and membrane and altering cell fluidity; consequently, plants can sense the pollutants and, thus, adapt different cellular strategies. The PM also causes a reduction in the photosynthetically active radiation. The study demonstrated that plants reduce stomatal density to avoid PM uptake and increase stomatal index to compensate for decreased gaseous exchange efficiency and transpiration rates. Furthermore, genes and gene sets associated with photosynthesis, glycolysis, gluconeogenesis, and the TCA cycle were dramatically lowered by PM stress. Several transcription factors, including MYB, C2H2, C3H, G2-like, and WRKY were induced, and metabolites such as proline and soluble sugar were accumulated to increase resistance against stressors. In addition, enzymatic and non-enzymatic antioxidants were also accumulated to scavenge the PM-induced reactive oxygen species (ROS). Taken together, this review provides an insight into plants' underlying cellular mechanisms and gene regulatory networks in response to the PM to determine strategies to preserve their structural and functional blend in the face of particulate pollution. The study concludes by recommending that future research should precisely focus on plants' response to short- and long-term PM exposure.

Modeling spatial-temporal variability of PM2.5 concentrations in Belt and Road Initiative (BRI) region via functional adaptive density approach

The rapid development of the Belt and Road Initiative (BRI) has led to severe air pollution dominated by PM2.5 concentrations which can cause a profound negative impact on human health and economic activity. This problem poses a critical environmental challenge to efficiently handling large-scale spatial-temporal PM2.5 data in this extended region. Functional data analysis (FDA) technique offers powerful tools that have the potential to enhance the analysis of spatial distributions and temporal dynamic changes in high-dimensional pollution data. However, modeling the spatial-temporal variability of PM2.5 concentrations by FDA remains unrevealed in the BRI region. To address this research gap, our study aimed to achieve two main objectives: first, to model the spatial-temporal dynamic variability of PM2.5 in 125 BRI nations (1998-2021), and second, to identify the underlying clusters behind the variations. We employed the recently developed functional adaptive density peak (FADP) clustering approach to solve the current problem. The proposed method is based on the joint use of functional principal components (FPCs) and functional cluster analyses. The main results are as follows: (i) The first three FPCs almost captured 99% of the total variations involving all valuable information on PM2.5 concentrations. (ii) PM2.5 pollution was highly concentrated in the developing countries (Pakistan, Bangladesh, and Nigeria) and the developed countries (Arabian Gulf countries: Qatar, United Arab Emirates, Bahrain, Saudi Arabia, Oman), and the least developed countries (Yemen and Chad). (iii) Three optimal clusters were identified and thus classified the PM2.5 into three distinct degrees of pollution: severe, moderate, and light. (iv) Cluster 1 had a severe pollution effect degree with a high rate of change, and it covered the Arabian Peninsula countries, African countries (Cameroon, Egypt, Gambia, Mali, Mauritania, Nigeria, Sudan, Senegal, Chad), Bangladesh, and Pakistan. (v) About 62 BRI countries belonged to cluster 2 showing a light pollution degree with annul average of less than 20 [Formula: see text]; this pointed out that the PM2.5 concentration remains stable in the cluster 2-related countries. The findings of this research would benefit governments and policymakers in preventing and controlling PM2.5 pollution exposure in BRI. Furthermore, this research could pay attention to sustainable development goals and the vision of the Green BRI policy.

Particulate Matter Pollution Remains a Threat for Cardiovascular Health: Findings From the Global Burden of Disease 2019

Background Particulate matter (PM) pollution is a significant risk factor for cardiovascular diseases, causing substantial disease burden and deaths worldwide. This study aimed to investigate the global burden of cardiovascular diseases attributed to PM from 1990 to 2019. Methods and Results We used the GBD (Global Burden of Disease) study 2019 to investigate disability-adjusted life-years (DALYs), years of life lost (YLLs), years lived with disability (YLDs), and deaths attributed to PM as well as its subgroups. It was shown that all burden measures' age-standardized rates for PM were in the same decreasing trend, with the highest decline recorded for deaths (-36.7%). However, the all-age DALYs increased by 31%, reaching 8.9 million in 2019, to which YLLs contributed the most (8.2 million [95% uncertainty interval, 7.3 million-9.2 million]). Men had higher deaths, DALYs, and YLLs despite lower years lived with disability in 2019 compared with women. There was an 8.1% increase in the age-standardized rate of DALYs for ambient PM; however, household air pollution from solid fuels decreased by 65.4% in the assessed period. Although higher in men, the low and high sociodemographic index regions had the highest and lowest attributed YLLs/YLDs ratio for PM pollution in 2019, respectively. Conclusions Although the total age-standardized rate of DALYs for PM-attributed cardiovascular diseases diminished from 1990 to 2019, the global burden of PM on cardiovascular diseases has increased. The differences between men and women and between regions have clinical and policy implications in global health planning toward more exact funding and resource allocation, in addition to addressing inequity in health care access.

Unveiling air pollution patterns in Yemen: a spatial-temporal functional data analysis

The application of spatiotemporal functional analysis techniques in environmental pollution research remains limited. As a result, this paper suggests spatiotemporal functional data clustering and visualization tools for identifying temporal dynamic patterns and spatial dependence of multiple air pollutants. The study uses concentrations of four major pollutants, named particulate matter (PM2.5), ground-level ozone (O3), carbon monoxide (CO), and sulfur oxides (SO2), measured over 37 cities in Yemen from 1980 to 2022. The proposed tools include Fourier transformation, B-spline functions, and generalized-cross validation for data smoothing, as well as static and dynamic visualization methods. Innovatively, a functional mixture model was used to capture/identify the underlying/hidden dynamic patterns of spatiotemporal air pollutants concentration. According to the results, CO levels increased 25% from 1990 to 1996, peaking in the cities of Taiz, Sana'a, and Ibb before decreasing. Also, PM2.5 pollution reached a peak in 2018, increasing 30% with severe concentrations in Hodeidah, Marib, and Mocha. Moreover, O3 pollution fluctuated with peaks in 2014-2015, 2% increase and pollution rate of 265 Dobson. Besides, SO2 pollution rose from 1997 to 2010, reaching a peak before stabilizing. Thus, these findings provide insights into the structure of the spatiotemporal air pollutants cycle and can assist policymakers in identifying sources and suggesting measures to reduce them. As a result, the study's findings are promising and may guide future research on predicting multivariate air pollution statistics over the analyzed area.

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 (PM_2.5), 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 PM_2.5 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 PM_2.5 concentration. Similarly, NRE and POP contribute significantly to increasing the PM_2.5 concentration in SA. However, RE and GLO play an important role to decrease the PM_2.5 concentration in SA.