Global Air Pollution Research Articles

Cluster‐Enhanced Ensemble Learning for Mapping Global Monthly Surface Ozone From 2003 to 2019

AbstractSurface ozone is damaging to human health and crop yields. When evaluating global air pollution risk, gridded datasets with high accuracy are desired to reflect the local variations in air pollution concentrations. Here, a cluster‐enhanced ensemble machine learning method was used to develop a new 0.5‐degree monthly surface ozone data set during 2003–2019 by combining numerous informative variables. The overall accuracy of our data set is 91.5% (90.8% for space and 92.3% for time). Historically, populations in South Asia, North Africa and Middle‐East, and High‐income North America are exposed to the highest ozone concentrations. Globally, the population weighted ozone concentration in the peak season is 47.07 ppbv. Our results highlight that ozone pollution is intensifying in some regions, and implicate air quality management is crucial to secure human health from air pollution.

IoT Based Air Quality Prediction using SVM and Random Forest

Internet of Things (IoT) may be a worldwide System of “smart devices” which will sense and connect with their surroundings and interact with users and other systems. Global air pollution is one of the major concerns of our era. The level of pollution has increased with time by a lot of things like the increase in population, increased vehicle use, industrialization, and urbanization which ends up in harmful effects on human wellbeing by directly affecting the health of the population exposed to it. Air quality goes down when enough amount of harmful gases are present in the air like carbon dioxide, smoke, alcohol, benzene, NH3, and NO2. To analyses, we are developing an IoT Based pollution Monitoring System which we'll monitor the Air Quality over an internet server. Existing monitoring systems have inferior precision, low sensitivity, and need laboratory analysis. Therefore, improved monitoring systems are needed.

Black carbon aerosol number and mass concentration measurements by picosecond short-range elastic backscatter lidar

Black carbon aerosol emissions are recognized as contributors to global warming and air pollution. There remains, however, a lack of techniques to remotely measure black carbon aerosol particles with high range and time resolution. This article presents a direct and contact-free remote technique to estimate the black carbon aerosol number and mass concentration at a few meters from the emission source. This is done using the Colibri instrument based on a novel technique, referred to here as Picosecond Short-Range Elastic Backscatter Lidar (PSR-EBL). To address the complexity of retrieving lidar products at short measurement ranges, we apply a forward inversion method featuring radiometric lidar calibration. Our method is based on an extension of a well-established light-scattering model, the Rayleigh–Debye–Gans for Fractal-Aggregates (RDG-FA) theory, which computes an analytical expression of lidar parameters. These parameters are the backscattering cross-sections and the lidar ratio for black carbon fractal aggregates. Using a small-scale Jet A-1 kerosene pool fire, we demonstrate the ability of the technique to quantify the aerosol number and mass concentration with centimetre range-resolution and millisecond time-resolution.

Toxicity assessment and heavy metal components of inhalable particulate matters (PM2.5 & PM10) during a dust storm invading the city

Dust storm (DS) represent global air pollution and health issues considering the high morbidity and premature death rate every year. This study explores the characteristics, composition, and variations in inhalable particulate matters (PMs) as well as their corresponding in vitro toxicity to human lung epithelial cells (A549) during DS and normal days (ND) in the downtown (DT) and the north suburban (NS) of Nanjing city, eastern China. Results showed that compared to ND, concentrations of heavy metals (i.e., Cr, Cu, Ni, and Pb) bound in PMs were lower during the DS. Furthermore, the relationship of cytotoxicity with Ni and Pb levels in PMs was significant. However, the cytotoxicity difference was insignificant between NS and DT. This may be due to the long-range transport of components from natural sources mixed with local pollutants emitted from anthropogenic sources, offsetting the pollution difference between urban and suburban areas. During both periods, PM2.5 toxicity was greater than PM10, while the potential of PM10 to induce proinflammatory cytokines was comparable to PM2.5. Results suggested that inflammation risk will increase significantly during DS due to a substantial increase in ambient air PM10 concentration.

Advances in catalysts for hydrogen production by methanolysis of sodium borohydride

Fossil energy is a major contributor to global greenhouse gases and air pollutants, causing serious environmental and health issues. In order to develop clean new energy as a substitute, catalytic methanolysis of sodium borohydride (NaBH4) has become a hot topic in hydrogen energy field. In this work, the latest research development of hydrogen production by NaBH4 methanolysis is comprehensively reviewed from the perspective of different types of catalysts, furthermore, the merits and demerits of these studies are analyzed, the comparison between various catalysts is also completed from the dimensions of hydrogen generation rate, apparent activation energy as well as durability, and the technical challenges the hydrogen production process may face and the corresponding recommendations are proposed. This review can provide enlightenment for the research and application of novel catalysts for the methanolysis of NaBH4 and the development of efficient hydrogen production technology.

Rethinking our chemical legacy and reclaiming our planet

Rethinking our chemical legacy and reclaiming our planet

Shengmai Yin alleviated plaque vulnerability and ischemic myocardial damage in diesel exhaust particle-aggravated atherosclerosis with myocardial ischemia

Exposure to diesel exhaust particles (DEP) increases the risk of ischemic heart disease, especially heart attacks and ischemic/thrombotic strokes. Shengmai Yin (SMY) is a traditional Chinese medicine used to treat coronary heart disease. The aim of this study was to determine the protective role of SMY and the mechanism by which SMY affects DEP-induced cardiovascular injury. This study is expected to provide the basis for the development of an adaptive signature of SMY in the prevention of atherosclerotic cardiovascular disease and premature death from global air pollution exposure. We developed animal models of myocardial ischemia and atherosclerosis (AS) in response to DEP exposure. After SMY treatment, serum lipids returned to normal. Aortic plaque area and MMP9 expression were significantly reduced and collagen fiber expression increased after SMY treatment compared to DEP exposure alone. Thus, the risk of plaque formation and vulnerability is reduced. In addition, SMY improved left ventricular structure, morphology, function, blood flow, infarct area, myocardial damage, and ROS accumulation to varying degrees in ApoE-/- mice. These results indicate that the use of SMY is effective, to varying degrees, for the treatment of dyslipidemia, atherosclerosis, myocardial ischemia, and oxidative stress in ApoE-/- mice. SMY has a potential protective effect in DEP-aggravated AS in people with myocardial ischemia.

Emissions impacts of electrifying motorcycle taxis in Kampala, Uganda

Large fleets of motorcycle taxis in Kampala, Uganda, and other cities in low and middle-income countries (LMICs) emit significant local and global air pollutants . To reduce emissions, companies have started selling electric motorcycles. We quantify the use-phase emissions impact of electrifying motorcycle taxis by processing real-world trip and charging data from Kampala, then estimating charging-caused emissions with an economic dispatch model of the Ugandan power system. We then compare these emissions to tank-to-wheels estimates of conventional motorcycles over the same trips. We find that electrifying gas-powered motorcycle taxis would reduce carbon dioxide (CO 2 ), carbon monoxide (CO), nitrogen oxide (NO x ), and hydrocarbon emissions by 36%, 90%, 58%, and 99%, respectively, but increase sulfur oxide (SO x ), particulate matter 10 μm or less (PM 10 ), and particulate matter 2.5 μm or less (PM 2.5 ) emissions by 870%, 109%, and 97%, respectively. PM and SO x emission increases stem from generation at bagasse and heavy fuel oil (HFO) point sources far from load centers. Additionally, we find seasonality of the charging associated emissions due to dominance of hydropower in the Ugandan grid. Overall, we find clear and potential local air pollution benefits of electrifying motorcycle taxis in Kampala.

교육시설 옥상 녹화시스템에 대한 환경성 평가

In addition to the excellence of the functional aspect of green roof, the impact of green roof on the environment in the process of disposal before and after construction as life cycle assessment was evaluated.BR In order to alleviate climate change, we paid attention to energy consumed by buildings, the main source and cause of greenhouse gases, chose green roof as a method to reduce energy use, and evaluated the environmental impact of the green roof. In this study, basic data on measures to reduce greenhouse gas emissions were presented by evaluating the environmental impact of the entire process from manufacturing to disposal of global warming and air pollution according to the green roof method. As a result of the analysis of environmental impact, it was calculated as 21,540kg CO₂e of greenhouse gas, which is the cause of global warming, accounting for 51%, the highest ratio of 11,646kg CO₂e in the installation stage including the manufacturing process, 31% in the use stage of artificial soil. In the case of environmental impact from urban air pollution, 57% of the environmental load was found in the installation process including the manufacturing process, 36% in the use stage, and 7% in the disposal stage.

Energy Production from Biodegradable Waste as an Example of the Circular Economy

A growing population, technological progress and economic development result in a constant increase in energy demand. Energy is mostly obtained from fossil energy resources such as coal, natural gas, and crude oil. Burning them leads to air pollution with greenhouse gases (CO2, CH4, NH3 and N2O) and dust (PM2.5 and PM10). They are recognized as the cause of global warming and air pollution. Wind, water, solar and biomass energy are used to eliminate harmful emissions. The latter may come from special plant crops or from biodegradable waste from farming, animal husbandry, the agrifood industry and households. These wastes are transformed into biogas in biogas plants, the basic ingredient of which is methane. Most often, biogas is burned in a cogeneration process, providing electricity and heat. After purification of admixtures, it can be injected into the high-methane gas network or converted into hydrogen in the steam reforming process. In this way, environmentally harmful waste becomes a raw material for energy production, which is an example of a circular economy. The article discusses the functioning of biogas plants in selected EU countries. The current biogas production in Poland was assessed and compared with the production potential of dairy farms. The aim of this article was to show that the production of biogas reduces the emission of greenhouse gases into the atmosphere and the electricity produced from it is not burdened with the cost of purchasing CO2 emission allowances applicable in the EU.

Global validation and hybrid calibration of CAMS and MERRA-2 PM2.5 reanalysis products based on OpenAQ platform

It is highly valuable to obtain high-quality PM2.5 concentration worldwide for continuous monitoring of global air pollution. Recently, global reanalysis products of PM2.5 have come into the view. However, most studies focus on the validation and calibration of a single product regionally, few studies expand to a global scale and integrate multiple products. With the help of global open-source data provided by the OpenAQ platform, we propose a hybrid calibration method aimed to improve the accuracy of CAMSRA and the MERRA-2 PM2.5 products. In the study, the accuracy of the two datasets are assessed on multi-time scales at first. Secondly, we try to use some machine learning models to correct the deviation of the original products alone and then further explore the possibility of the hybrid calibration. Global-scale validation results show that CAMSRA products are generally overestimated (daily R = 0.6), and MERRA-2 products are underestimated (daily R = 0.3), which supports our hybrid calibration method to an extent. Using the Extremely Randomized Tree (ERT) to implement the separate calibration scheme, two products show different degrees of accuracy improvement, to be specific, R increases by 0.19 and 0.43 for daily CAMSRA and MERRA-2 products, respectively. Compared with the separate calibration modeling, the hybrid method performs better, with R reaching up to 0.81. RMSE is only 14.94 μg/m³, which has a decrease of 60.99% and 64.42% to two abovementioned original products. The obtained daily PM2.5 maps have higher quality with no data gaps, which can be a promising data source of air pollution monitoring and health research. This dataset is published in GeoTIFF format at https://doi.org/10.5281/zenodo.5168102.

MRS-STFF: Evaluation of biomass energy combustion and associated pollutants

The seasonal open burning of straw around the world has become one of the sources of high global air pollutant emissions. Suspended particles, gaseous pollutants, photochemical oxidants, and other substances produced during straw incineration have greatly catalyzed the deterioration trend of the surrounding environment. The current study explores the spatio-temporal distribution characteristics of straw burning and associated pollution in agricultural areas, proposes suggest on effective governance of straw burning behavior to promote the global carbon neutralization process. This study is based on the method of Multi-source Remote Sensing Spatio-temporal Feature Fusion (MRS-STFF), which combines the change in incineration area, the spatial distribution characteristics of aerosol and the monthly average concentration of pollutants, and studies the driving relationship between burning biomass energy and its associated pollutants utilizing management and control. The results demonstrate that the interannual change of straw incineration area in the experimental area showed a U-shaped trend of decreasing first and then increasing, and the periodical duration decreases, while the change of accompanying pollutants showed a U-shaped trend of first being reduced and then increase, and the periodical duration changeful. This method of combining multi-source data not only provides a reliable decision-making basis for management and control, but also helps to promote the reuse of biomass resources.

Short communication The Outbreak of the COVID-19 Pandemic and its Healing Effects on the Environment

COVID 19, the virus which originated from a wet market in Wuhan, China. Since its exposure in December, 2019, the virus has spread to almost all the countries in the world, thus turning an epidemic into a pandemic. Although COVID 19 has taken a massive toll on the Human health and global economy, its outbreak has shown positive impacts on the environmental air quality. As the majority of the world is under lock down, the global air pollution has reduced by 40 percent during April 2020. This was identified with the assistance of the data collected from European and American Atmospheric monitoring sites. This article thus summarizes the positive effects of lock down and reduced human mobility, towards the improvement of environmental air quality.

Association between Global Air Pollution and COVID-19 Mortality: A Study of Forty-Six Cities in the World

Ambient air pollution plays a significant role in an increased risk of incidence and mortality of COVID-19 on a global scale. This study aims to understand the multiscale spatial effect of global air pollution on COVID-19 mortality. Based on forty-six cities from six countries worldwide between 1 April 2020 and 31 December 2020, a Bayesian space–time hierarchical model was used based on the lag effects of seven, fourteen, and twenty-one days to quantify the relative risks of NO2 and PM2.5 on the daily death rates of COVID-19, accounting for the effect of meteorological and human mobility variability based on global and city level. Results show that positive correlations between air pollution and COVID-19 mortality are observed, with the relative risks of NO2 and PM2.5 ranging from 1.006 to 1.014 and from 1.002 to 1.004 with the lag effects of seven, fourteen, and twenty-one days. For the individual city analysis, however, both positive and negative associations are found between air pollution and daily mortality, showing that the relative risks of NO2 and PM2.5 are between 0.754 and 1.245 and between 0.888 and 1.032, respectively. The discrepancies in air pollution risks among cities were demonstrated in this study and further allude to the necessity to explore the uncertainty in the multiscale air pollution–mortality relationship.

Numerical Optimization and Energetic Advantages of an Innovative Solar Power System Based on Scheffler Receiver Coupled with Volumetric Expanders

In the current context of increasing public awareness of the externalities of fossil fuel-based energy consumption, improvement in new technologies for energy-saving systems has become a crucial target to reduce both global warming and air pollution. Being motivated by such a critical matter, this study presents an innovative solar thermal plant based on volumetric expanders as work-producing devices coupled with Scheffler solar receivers as a thermal source. Nowadays, Scheffler receivers are well performing owing to high efficiency of the focal receiver which reduce heat losses. Simultaneously, screw expanders are volumetric machines which are able to convert thermal to mechanical power with acceptable efficiency also by expanding vapor-liquid blends at low operating pressures. The numerical model presented in this study evaluates the energetic benefits of the proposed solar power system for various operating situations. Parametric optimization of this solar power plant is then performed in a broad range of operating conditions: the optimum evaporation temperatures, together with the corresponding maximum global efficiencies, were so defined under various solar radiation intensities. The numerical results attained in this research prove that solar electricity generation systems based on screw expanders coupled with the Scheffler receivers are a promising technology.

Potential for future reductions of global GHG and air pollutants from circular waste management systems

The rapidly rising generation of municipal solid waste jeopardizes the environment and contributes to climate heating. Based on the Shared Socioeconomic Pathways, we here develop a global systematic approach for evaluating the potentials to reduce emissions of greenhouse gases and air pollutants from the implementation of circular municipal waste management systems. We contrast two sets of global scenarios until 2050, namely baseline and mitigation scenarios, and show that mitigation strategies in the sustainability-oriented scenario yields earlier, and major, co-benefits compared to scenarios in which inequalities are reduced but that are focused solely on technical solutions. The sustainability-oriented scenario leaves 386 Tg CO2eq/yr of GHG (CH4 and CO2) to be released while air pollutants from open burning can be eliminated, indicating that this source of ambient air pollution can be entirely eradicated before 2050.

Global urban temporal trends in fine particulate matter (PM2·5) and attributable health burdens: estimates from global datasets

SummaryBackgroundWith much of the world's population residing in urban areas, an understanding of air pollution exposures at the city level can inform mitigation approaches. Previous studies of global urban air pollution have not considered trends in air pollutant concentrations nor corresponding attributable mortality burdens. We aimed to estimate trends in fine particulate matter (PM2·5) concentrations and associated mortality for cities globally.MethodsWe use high-resolution annual average PM2·5 concentrations, epidemiologically derived concentration response functions, and country-level baseline disease rates to estimate population-weighted PM2·5 concentrations and attributable cause-specific mortality in 13 160 urban centres between the years 2000 and 2019.FindingsAlthough regional averages of urban PM2·5 concentrations decreased between the years 2000 and 2019, we found considerable heterogeneity in trends of PM2·5 concentrations between urban areas. Approximately 86% (2·5 billion inhabitants) of urban inhabitants lived in urban areas that exceeded WHO's 2005 guideline annual average PM2·5 (10 μg/m3), resulting in an excess of 1·8 million (95% CI 1·34 million–2·3 million) deaths in 2019. Regional averages of PM2·5-attributable deaths increased in all regions except for Europe and the Americas, driven by changes in population numbers, age structures, and disease rates. In some cities, PM2·5-attributable mortality increased despite decreases in PM2·5 concentrations, resulting from shifting age distributions and rates of non-communicable disease.InterpretationOur study showed that, between the years 2000 and 2019, most of the world's urban population lived in areas with unhealthy levels of PM2·5, leading to substantial contributions to non-communicable disease burdens. Our results highlight that avoiding the large public health burden from urban PM2·5 will require strategies that reduce exposure through emissions mitigation, as well as strategies that reduce vulnerability to PM2·5 by improving overall public health.FundingNASA, Wellcome Trust.

Economic TEHES-Tube Material Evaluation by Absorbability Index under O-S-Dimensions for Minimizing Global Warming and Air Pollution by Exploring Dominance Theory: Green Management Initiative

It is investigated that the Global Warming and Air Pollution (GWAP) issues are highly prioritized around the world. There is a high magnitude of contaminated hot heat (CHH) from hot fluids such as contaminated water, oils, and mixed oils; toxic oils increase the GWAP ON emission. Such GWAP can be controlled by applying the methods-techniques for optimizing the energy processes, evaluating the high energy absorption material among available materials and technological advancement in energy flow devices, optimizing design of energy systems and low heat emission strategy, etc. It is observed that nowadays, Thermal Energy Heat Exchanger Systems (TEHESs) are utilized in many industries for transferring the energy between two mineral or contaminated liquids, separated by walls. It is found that TEHESs are constructed by tube materials, might be contributed to control the GWAP if TEHESs are fabricated with composite material, and have a high absorbability index. The evaluation of the Energy Absorbability Index (EAI) of TEHES composite tube materials provides the two innovative solutions to TEHES designers such as choose the economic/cost TEHESs and initiate to green management (reducing minimizing the GWAP). On literature survey, a few research documents are found by authors, which focused on mathematical modelling of either O- (objective-) or S- (subjective-) dimensions of composite TEHES tube material evaluation models for computing EAI. It is also probed that those models are simulated by single or nondynamic material evaluation methods. Therefore, it is summarized that there are no still research document pertaining to integrated/mixed mathematical modelling of O-S- (objective-subjective-) dimensions of composite TEHES tube materials with dominance theory for computing EAI of composite TEHES tube materials. Said research gaps are respected as major research defies (help to minimize the GWAP or green management). To fulfil the said research defies, the authors developed and proposed the TEHES-O-S-composite tube material evaluation model by conducting literature and real industrial survey, consisting of seven TEHES-O and four TEHES-S tube material dimensions. The O-dimensions are framed by available O-rating/data, while S-dimension is framed S-rating. The TFNs (triangular fuzzy numbers) are used by a team of experts for assigning the appropriateness ratings vs. four TEHES-S composite tube material dimension, and priority weights are assigned vs. entire TEHES-O-S tube material dimensions. After data modelling of the TEHES-O-S-composite tube material evaluation model, defuzzification is carried out to normalize O-S-data. Later, the authors’ implemented integrated optimization technique “crisp VIKOR combined FMF technique” to evaluate the EAI of composite TEHES tube materials. As the reliability of results is an enormous concern, dominance theory is applied by conducting the comparative analysis among evaluated results and delivering the accurate and reliable results. The evaluated beast composite TEHES tube materials based on EAI linked to green management and economic concern of material. The research can be used by TEHES designers to minimize the GWAP across the universe.

Low-cost solutions to global warming, air pollution, and energy insecurity for 145 countries

Timeline to transition 145 countries to 100% wind-water-solar by 2035, with 80% by 2030.

Selection of Some Plant Species Suitable for Green Belt Expansion in Mumbai Industrial Area - A Baseline to Alleviate Global Air Pollution

The air quality and global environment is immensely affected due to the industrial as well as urban expansion. The present study aims to identify the natural tolerance of six plant species towards the air pollution, which are growing along the Chembur industrial area of Mumbai. The plant’s air pollution tolerance level was identified by evaluating Air Pollution Tolerance Index (APTI) and Anticipated Performance Index (API). The estimation of APTI was done based on the measurement of physico-chemical parameters like pH, ascorbic acid, total chlorophyll content and the relative leaf water content of the fresh leaves of plant species grown along the industrial and non-industrial areas. The higher API values obtained for the Thespesia populnea (L.) Sol. excorrea, Polyalthia longifolia and Albizia saman (Jacq.) Merr plant species growing in the industrial zone indicate a good tolerance towards polluted air and hence are suggested for green zone development in the Chembur industrial area. The present work can be extended for the selection of the most air pollution tolerant plant species for the development of green zone along the industrial belt across the world. It will facilitate healthy atmosphere for the nearby population.