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Di Maio M, Valachovic E. Temporal modeling of nitrogen dioxide levels on Main Street, East Los Angeles: Estimating annual periodic components using the Variable Bandpass Periodic Block Bootstrap. PLoS One 2024; 19:e0309790. [PMID: 39240936 PMCID: PMC11379299 DOI: 10.1371/journal.pone.0309790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2024] [Accepted: 08/19/2024] [Indexed: 09/08/2024] Open
Abstract
In this study we assess periodicities in nitrogen dioxide levels at a location in Los Angeles using a novel Variable Bandpass Periodic Block Bootstrap (VBPBB) method resulting in confidence interval bands for the periodic mean. Nitrogen dioxide (NO2) is an air pollutant primarily produced by the combustion of fossil fuels by power plants and vehicles with internal combustion engines which has been linked with a variety of adverse health outcomes including dementia, breast cancer, decreased cognitive function, increased susceptibility to Covid-19, cardiovascular and respiratory mortality. Previous analysis methods such as block bootstrapping can obscure periodically correlated patterns in time series. The sampling destroys the correlation observed in the data for patterns of different periods, such as the daily, weekly and yearly patterns of nitrogen dioxide levels we wish to investigate. We use the VBPBB method to isolate significant periodicities using a band pass filter before bootstrapping so that the correlations between the data are preserved. Confidence interval bands for VBPBB are compared against existing block bootstrapping. The resulting narrower confidence interval bands created by VBPBB show a significant annual fluctuation in nitrogen dioxide levels while the existing methods do not show it as clearly. Better characterization of pollution patterns will aid in pollution reduction efforts by allowing us to pinpoint times of highest risk and direct mitigation efforts where they will have the greatest impact. This technique exhibits potential for future applications to other areas of environmental and health interest and concern.
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Affiliation(s)
- Megan Di Maio
- Department of Epidemiology and Biostatistics, School of Public Health, University at Albany, State University of New York, Albany, New York, United States of America
| | - Edward Valachovic
- Department of Epidemiology and Biostatistics, School of Public Health, University at Albany, State University of New York, Albany, New York, United States of America
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Musonye HA, He YS, Bekele MB, Jiang LQ, Fan Cao, Xu YQ, Gao ZX, Ge M, He T, Zhang P, Zhao CN, Chen C, Wang P, Pan HF. Exploring the association between ambient air pollution and COVID-19 risk: A comprehensive meta-analysis with meta-regression modelling. Heliyon 2024; 10:e32385. [PMID: 39183866 PMCID: PMC11341291 DOI: 10.1016/j.heliyon.2024.e32385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 05/07/2024] [Accepted: 06/03/2024] [Indexed: 08/27/2024] Open
Abstract
Introduction Air pollution is speculated to increase the risk of Coronavirus disease-2019 (COVID-19). Nevertheless, the results remain inconsistent and inconclusive. This study aimed to explore the association between ambient air pollution (AAP) and COVID-19 risks using a meta-analysis with meta-regression modelling. Methods The inclusion criteria were: original studies quantifying the association using effect sizes and 95 % confidence intervals (CIs); time-series, cohort, ecological or case-crossover peer-reviewed studies in English. Exclusion criteria encompassed non-original studies, animal studies, and data with common errors. PubMed, Web of Science, Embase and Google Scholar electronic databases were systemically searched for eligible literature, up to 31, March 2023. The risk of bias (ROB) was assessed following the Agency for Healthcare Research and Quality parameters. A random-effects model was used to calculate pooled risk ratios (RRs) and their 95 % CIs. Results A total of 58 studies, between 2020 and 2023, met the inclusion criteria. The global representation was skewed, with major contributions from the USA (24.1 %) and China (22.4 %). The distribution included studies on short-term (43.1 %) and long-term (56.9 %) air pollution exposure. Ecological studies constituted 51.7 %, time-series-27.6 %, cohorts-17.2 %, and case crossover-3.4 %. ROB assessment showed low (86.2 %) and moderate (13.8 %) risk. The COVID-19 incidences increased with a 10 μg/m3 increase in PM2.5 [RR = 4.9045; 95 % CI (4.1548-5.7895)], PM10 [RR = 2.9427: (2.2290-3.8850)], NO2 [RR = 3.2750: (3.1420-3.4136)], SO2 [RR = 3.3400: (2.7931-3.9940)], CO [RR = 2.6244: (2.5208-2.7322)] and O3 [RR = 2.4008: (2.1859-2.6368)] concentrations. A 10 μg/m3 increase in concentrations of PM2.5 [RR = 3.0418: (2.7344-3.3838)], PM10 [RR = 2.6202: (2.1602-3.1781)], NO2 [RR = 3.2226: (2.1411-4.8504)], CO [RR = 1.8021 (0.8045-4.0370)] and O3 [RR = 2.3270 (1.5906-3.4045)] was significantly associated with COVID-19 mortality. Stratified analysis showed that study design, exposure period, and country influenced exposure-response associations. Meta-regression model indicated significant predictors for air pollution-COVID-19 incidence associations. Conclusion The study, while robust, lacks causality demonstration and focuses only on the USA and China, limiting its generalizability. Regardless, the study provides a strong evidence base for air pollution-COVID-19-risks associations, offering valuable insights for intervention measures for COVID-19.
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Affiliation(s)
- Harry Asena Musonye
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University 678 Furong Road, Hefei, 230601, Anhui, China
- Anhui Provincial Institute of Translational Medicine, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Yi-Sheng He
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University 678 Furong Road, Hefei, 230601, Anhui, China
- Anhui Provincial Institute of Translational Medicine, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Merga Bayou Bekele
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University 678 Furong Road, Hefei, 230601, Anhui, China
- Anhui Provincial Institute of Translational Medicine, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Ling-Qiong Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University 678 Furong Road, Hefei, 230601, Anhui, China
- Anhui Provincial Institute of Translational Medicine, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Fan Cao
- Department of Ophthalmology, The Second Affiliated Hospital of Anhui Medical University, 678 Furong Road, Hefei, 230601, Anhui, China
- Department of Clinical Medicine, The Second School of Clinical Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Yi-Qing Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University 678 Furong Road, Hefei, 230601, Anhui, China
- Anhui Provincial Institute of Translational Medicine, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Zhao-Xing Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University 678 Furong Road, Hefei, 230601, Anhui, China
- Anhui Provincial Institute of Translational Medicine, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Man Ge
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University 678 Furong Road, Hefei, 230601, Anhui, China
- Anhui Provincial Institute of Translational Medicine, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Tian He
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University 678 Furong Road, Hefei, 230601, Anhui, China
- Anhui Provincial Institute of Translational Medicine, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Peng Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University 678 Furong Road, Hefei, 230601, Anhui, China
- Anhui Provincial Institute of Translational Medicine, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Chan-Na Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University 678 Furong Road, Hefei, 230601, Anhui, China
- Anhui Provincial Institute of Translational Medicine, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Cong Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University 678 Furong Road, Hefei, 230601, Anhui, China
- Anhui Provincial Institute of Translational Medicine, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Peng Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Teaching Center for Preventive Medicine, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Hai-Feng Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University 678 Furong Road, Hefei, 230601, Anhui, China
- Anhui Provincial Institute of Translational Medicine, No. 81 Meishan Road, Hefei, 230032, Anhui, China
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Xia C, Delei W. Urban resilience governance mechanism: Insights from COVID-19 prevention and control in 30 Chinese cities. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2024. [PMID: 38922992 DOI: 10.1111/risa.14615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 06/02/2024] [Accepted: 06/13/2024] [Indexed: 06/28/2024]
Abstract
Due to the pervasive uncertainty in human society, super large and megacities are increasingly prone to becoming high-risk areas. However, the construction of urban resilience in this new era lacks sufficient research on the core conditions and complex interactive mechanisms governing it. Hence, this study proposes a specialized event-oriented framework for governing urban resilience in China based on the pressure-state-response (PSR) theory. We examined COVID-19 cases in 30 cities across China and analyzed the distribution of prevention and control achievements between high-level and non-high-level conditions. Our findings reveal the following key points: (1) High-level achievements in COVID-19 prevention and control rely on three condition configurations: non-pressure-responsive type, pressure-state type, and pressure-responsive type. (2) High economic resilience may indicate a robust state of urban systems amid demographic pressures. In cities experiencing fewer event pressure factors, the application of digital technology plays a crucial role in daily urban management. (3) The implementation of flexible policies proves beneficial in mitigating the impact of objective pressure conditions, such as environmental factors, on urban resilience.
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Affiliation(s)
- Cao Xia
- School of Economics and Management, Harbin Engineering University, Harbin, China
| | - Wang Delei
- School of Economics and Management, Harbin Engineering University, Harbin, China
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Norkaew S, Narikawa S, Nagashima U, Uemura R, Noda J. Efficacy of treating bacterial bioaerosols with weakly acidic hypochlorous water: A simulation chamber study. Heliyon 2024; 10:e26574. [PMID: 38434335 PMCID: PMC10907660 DOI: 10.1016/j.heliyon.2024.e26574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 01/25/2024] [Accepted: 02/15/2024] [Indexed: 03/05/2024] Open
Abstract
The COVID-19 pandemic highlighted the dangers of airborne transmission and the risks of pathogen-containing small airborne droplet inhalation as an infection route. As a pathogen control, Weakly Acidic Hypochlorous Water (WAHW) is used for surface disinfection. However, there are limited assessments of air disinfection by WAHW against airborne pathogens like bioaerosols. This was an empirical study evaluating the disinfection efficacy of WAHW in an atmospheric simulation chamber system against four selected model bacteria. The strains tested included Staphylococcus aureus (SA), Escherichia coli (EC), Pseudomonas aeruginosa (PA), and Pseudomonas aeruginosa (PAO1). Each bacterial solution was nebulized into the chamber system as the initial step, and bioaerosol was collected into the liquid medium by a bio-sampler for colony forming units (CFU) determination. Secondly, the nebulized bacterial bioaerosol was exposed to nebulized double distilled water (DDW) as the control and nebulized 150 ppm of WAHW as the experimental groups. After the 3 and 30-min reaction periods, the aerosol mixture inside the chamber was sampled in liquid media and then cultured on agar plates with different dilution factors to determine the CFU. Survival rates were calculated by a pre-exposed CFU value as a reference point. The use of WAHW decreased bacterial survival rates to 1.65-30.15% compared to the DDW control. PAO1 showed the highest survival rates and stability at 3 min was higher than 30 min in all experiments. Statistical analysis indicated that bacteria survival rates were significantly reduced compared to the controls. This work verifies the bactericidal effects against Gram-positive/negative bioaerosols of WAHW treatment. As WAHW contains chlorine in the acid solution, residual chlorine air concentration is a concern and the disinfection effect at different concentrations also requires investigation. Future studies should identify optimal times to minimize the treated time range and require measurements in a real environment.
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Affiliation(s)
- Saowanee Norkaew
- Faculty of Public Health, Thammasat University, Khlong Nueng, Klong Luang, Pathum Thani, 12121, Thailand
- Research Unit in Occupational Ergonomics, Thammasat University, Khlong Nueng, Klong Luang, Pathum Thani, 12121, Thailand
| | - Sumiyo Narikawa
- School of Veterinary Medicine, Rakuno Gakuen University, Bunkyodai-Midorimachi, Ebetsu, Hokkaido, 069-8501, Japan
| | - Ukyo Nagashima
- School of Veterinary Medicine, Rakuno Gakuen University, Bunkyodai-Midorimachi, Ebetsu, Hokkaido, 069-8501, Japan
| | - Ryoko Uemura
- Department of Veterinary Sciences, Faculty of Agriculture, University of Miyazaki, GakuenKibanadai-Nishi, Miyazaki, 889-2192, Japan
| | - Jun Noda
- School of Veterinary Medicine, Rakuno Gakuen University, Bunkyodai-Midorimachi, Ebetsu, Hokkaido, 069-8501, Japan
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Rybarczyk Y, Zalakeviciute R, Ortiz-Prado E. Causal effect of air pollution and meteorology on the COVID-19 pandemic: A convergent cross mapping approach. Heliyon 2024; 10:e25134. [PMID: 38322928 PMCID: PMC10844283 DOI: 10.1016/j.heliyon.2024.e25134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 01/15/2024] [Accepted: 01/22/2024] [Indexed: 02/08/2024] Open
Abstract
Environmental factors have been suspected to influence the propagation and lethality of COVID-19 in the global population. However, most of the studies have been limited to correlation analyses and did not use specific methods to address the dynamic of the causal relationship between the virus and its external drivers. This work focuses on inferring and understanding the causal effect of critical air pollutants and meteorological parameters on COVID-19 by using an Empirical Dynamic Modeling approach called Convergent Cross Mapping. This technique allowed us to identify the time-delayed causation and the sign of interactions. Considering its remarkable urban environment and mortality rate during the pandemic, Quito, Ecuador, was chosen as a case study. Our results show that both urban air pollution and meteorology have a causal impact on COVID-19. Even if the strength and the sign of the causality vary over time, a general trend can be drawn. NO2, SO2, CO and PM2.5 have a positive causation for COVID-19 infections (ρ > 0.35 and ∂ > 9.1). Contrary to current knowledge, this study shows a rapid effect of pollution on COVID-19 cases (1 < lag days <24) and a negative impact of O3 on COVID-19-related deaths (ρ = 0.53 and ∂ = -0.3). Regarding the meteorology, temperature (ρ = 0.24 and ∂ = -0.4) and wind speed (ρ = 0.34 and ∂ = -3.9) tend to mitigate the epidemiological consequences of SARS-CoV-2, whereas relative humidity seems to increase the excess deaths (ρ = 0.4 and ∂ = 0.05). A causal network is proposed to synthesize the interactions between the studied variables and to provide a simple model to support the management of coronavirus outbreaks.
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Affiliation(s)
- Yves Rybarczyk
- School of Information and Engineering, Dalarna University, Falun, Sweden
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Wang J, Wei JL, Cao Q, Cheng XF, Chen ZK, He JH. Chemresistive Detection of NO 2 of ppb Level in Humid Air at 350 K Using Azo-Spaced Polycroconamide. ACS Sens 2024; 9:236-243. [PMID: 38123468 DOI: 10.1021/acssensors.3c01869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
Organic molecules are of great interest for gas sensing applications. However, achieving high-performance gas sensors with high sensitivity, fast response, low consumption, and workability in humid conditions is still challenging. Herein, we report the rational design and synthesis of an ion-in-conjugation polymer, PADC (poly-4,4'-azodianiline-croconamide), obtained by the condensation of croconic acid with 4-4'diaminoazobenzene for gas sensing under humid conditions. The as-fabricated PADC-based gas sensor exhibits ultrahigh sensitivity (802.7 ppm-1 at 1 ppm), subppb detection limit, and high selectivity under humid air with an 80% humidity effect at a temperature down to 350 K. PADC shows good planarity, excellent thermostability, and a narrow band gap of 1.2 eV because of azobenzene fragments spacing previously repulsed biphenyl rings. Compared to previous humidity immunity works, PADC-based sensors realized humidity immunity at a relatively lower temperature, resulting in lower energy consumption.
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Affiliation(s)
- Jia Wang
- College of Chemistry Chemical Engineering and Materials Science, Soochow University, Suzhou 215123, China
| | | | - Qiang Cao
- College of Chemistry Chemical Engineering and Materials Science, Soochow University, Suzhou 215123, China
| | - Xue-Feng Cheng
- College of Chemistry Chemical Engineering and Materials Science, Soochow University, Suzhou 215123, China
| | - Ze-Kun Chen
- College of Chemistry Chemical Engineering and Materials Science, Soochow University, Suzhou 215123, China
| | - Jing-Hui He
- College of Chemistry Chemical Engineering and Materials Science, Soochow University, Suzhou 215123, China
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Feng B, Lian J, Yu F, Zhang D, Chen W, Wang Q, Shen Y, Xie G, Wang R, Teng Y, Lou B, Zheng S, Yang Y, Chen Y. Impact of short-term ambient air pollution exposure on the risk of severe COVID-19. J Environ Sci (China) 2024; 135:610-618. [PMID: 37778832 PMCID: PMC9550293 DOI: 10.1016/j.jes.2022.09.040] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 09/26/2022] [Accepted: 09/27/2022] [Indexed: 08/01/2023]
Abstract
Ecological studies suggested a link between air pollution and severe COVID-19 outcomes, while studies accounting for individual-level characteristics are limited. In the present study, we aimed to investigate the impact of short-term ambient air pollution exposure on disease severity among a cohort of 569 laboratory confirmed COVID-19 patients admitted to designated hospitals in Zhejiang province, China, from January 17 to March 3, 2020, and elucidate the possible biological processes involved using transcriptomics. Compared with mild cases, severe cases had higher proportion of medical conditions as well as unfavorable results in most of the laboratory tests, and manifested higher air pollution exposure levels. Higher exposure to air pollutants was associated with increased risk of severe COVID-19 with odds ratio (OR) of 1.89 (95% confidence interval (CI): 1.01, 3.53), 2.35 (95% CI: 1.20, 4.61), 2.87 (95% CI: 1.68, 4.91), and 2.01 (95% CI: 1.10, 3.69) for PM2.5, PM10, NO2 and CO, respectively. OR for NO2 remained significant in two-pollutant models after adjusting for other pollutants. Transcriptional analysis showed 884 differentially expressed genes which mainly were enriched in virus clearance related biological processes between patients with high and low NO2 exposure levels, indicating that compromised immune response might be a potential underlying mechanistic pathway. These findings highlight the impact of short-term air pollution exposure, particularly for NO2, on COVID-19 severity, and emphasize the significance in mitigating the COVID-19 burden of commitments to improve air quality.
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Affiliation(s)
- Baihuan Feng
- Department of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China; Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou 310000, China; Institute of Laboratory Medicine, Zhejiang University, Hangzhou 310000, China
| | - Jiangshan Lian
- Department of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China
| | - Fei Yu
- Department of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China; Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou 310000, China; Institute of Laboratory Medicine, Zhejiang University, Hangzhou 310000, China
| | - Dan Zhang
- Department of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China; Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou 310000, China; Institute of Laboratory Medicine, Zhejiang University, Hangzhou 310000, China
| | - Weizhen Chen
- Department of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China; Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou 310000, China; Institute of Laboratory Medicine, Zhejiang University, Hangzhou 310000, China
| | - Qi Wang
- Department of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China; Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou 310000, China; Institute of Laboratory Medicine, Zhejiang University, Hangzhou 310000, China
| | - Yifei Shen
- Department of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China; Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou 310000, China; Institute of Laboratory Medicine, Zhejiang University, Hangzhou 310000, China
| | - Guoliang Xie
- Department of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China; Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou 310000, China; Institute of Laboratory Medicine, Zhejiang University, Hangzhou 310000, China
| | - Ruonan Wang
- Department of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China; Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou 310000, China; Institute of Laboratory Medicine, Zhejiang University, Hangzhou 310000, China
| | - Yun Teng
- Department of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China; Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou 310000, China; Institute of Laboratory Medicine, Zhejiang University, Hangzhou 310000, China
| | - Bin Lou
- Department of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China; Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou 310000, China; Institute of Laboratory Medicine, Zhejiang University, Hangzhou 310000, China
| | - Shufa Zheng
- Department of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China; Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou 310000, China; Institute of Laboratory Medicine, Zhejiang University, Hangzhou 310000, China.
| | - Yida Yang
- Department of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China.
| | - Yu Chen
- Department of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China; Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou 310000, China; Institute of Laboratory Medicine, Zhejiang University, Hangzhou 310000, China; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China.
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8
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Shousha HI, Ayman H, Hashem MB. Climate Changes and COVID-19. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1458:217-231. [PMID: 39102199 DOI: 10.1007/978-3-031-61943-4_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/06/2024]
Abstract
Climatic change, which influences population growth and land usage, has been theorized to be linked to the emergence and spread of new viruses like the currently unfolding COVID-19 pandemic. In this chapter, we explain how climate change may have altered the beginning, transmission, and maybe even the sickness consequences of the COVID-19 pandemic. Where possible, we also provide mechanistic explanations for how this may have occurred. We have presented evidence that suggests climate change may have had a role in the establishment and transmission of SARS-CoV-2 infection, and most possibly even in some of its clinical effects. Human activities bringing people into closer contact with bats and animals like pangolins that potentially represent the intermediate hosts, and evidence that climate-induced changes in vegetation are the main reservoir source of coronaviruses for human infection, are among the explanations. Although there are still unsubstantiated indications that the first viral pathogen may have escaped from a laboratory, it is possible that this encounter took place in the field or in marketplaces in the instance of COVID-19. We also present the argument that climate change is working to enhance transmission between diseased and uninfected humans, and this is true regardless of the source of the original development of the disease. Changes in temperature and humidity make it easier for viruses to survive, and the impacts of industrial pollution induce people to cough and sneeze, which releases highly infectious aerosols into the air. These three factors combine to make this a more likely scenario than it would otherwise be. We suggest that changes in climate are contributing to create conditions that are favorable for the development of more severe symptoms of illness. It is more difficult to build the argument for this circumstance, and much of it is indirect. However, climate change has caused some communities to adjust their nutritional habits, both in terms of the quantity of food they eat and the quality of the foods they consume. The effects frequently become apparent as a result of alterations that are imposed on the microbiome of the gut, which, in turn, influence the types of immune responses that are produced. The incidence of comorbidities like diabetes and animal vectors like bats that transmit other illnesses that modify vulnerability to SARS-CoV-2 are also two examples of the factors that have been affected by climate change. In order to curb the development of infectious illnesses caused by new viruses, it is necessary to understand the connection between environmental dynamics and the emergence of new coronaviruses. This knowledge should lead to initiatives aimed at reducing global greenhouse gas emissions.
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Affiliation(s)
- Hend Ibrahim Shousha
- Faculty of Medicine, Endemic Medicine and Hepatogastroenterology, Cairo University, Giza, Egypt.
| | - Hedy Ayman
- Faculty of Medicine, Endemic Medicine and Hepatogastroenterology, Cairo University, Giza, Egypt
| | - Mohamed B Hashem
- Faculty of Medicine, Endemic Medicine and Hepatogastroenterology, Cairo University, Giza, Egypt
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Houweling L, Maitland-Van der Zee AH, Holtjer JCS, Bazdar S, Vermeulen RCH, Downward GS, Bloemsma LD. The effect of the urban exposome on COVID-19 health outcomes: A systematic review and meta-analysis. ENVIRONMENTAL RESEARCH 2024; 240:117351. [PMID: 37852458 DOI: 10.1016/j.envres.2023.117351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 10/06/2023] [Accepted: 10/07/2023] [Indexed: 10/20/2023]
Abstract
BACKGROUND The global severity of SARS-CoV-2 illness has been associated with various urban characteristics, including exposure to ambient air pollutants. This systematic review and meta-analysis aims to synthesize findings from ecological and non-ecological studies to investigate the impact of multiple urban-related features on a variety of COVID-19 health outcomes. METHODS On December 5, 2022, PubMed was searched to identify all types of observational studies that examined one or more urban exposome characteristics in relation to various COVID-19 health outcomes such as infection severity, the need for hospitalization, ICU admission, COVID pneumonia, and mortality. RESULTS A total of 38 non-ecological and 241 ecological studies were included in this review. Non-ecological studies highlighted the significant effects of population density, urbanization, and exposure to ambient air pollutants, particularly PM2.5. The meta-analyses revealed that a 1 μg/m3 increase in PM2.5 was associated with a higher likelihood of COVID-19 hospitalization (pooled OR 1.08 (95% CI:1.02-1.14)) and death (pooled OR 1.06 (95% CI:1.03-1.09)). Ecological studies, in addition to confirming the findings of non-ecological studies, also indicated that higher exposure to nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2), and carbon monoxide (CO), as well as lower ambient temperature, humidity, ultraviolet (UV) radiation, and less green and blue space exposure, were associated with increased COVID-19 morbidity and mortality. CONCLUSION This systematic review has identified several key vulnerability features related to urban areas in the context of the recent COVID-19 pandemic. The findings underscore the importance of improving policies related to urban exposures and implementing measures to protect individuals from these harmful environmental stressors.
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Affiliation(s)
- Laura Houweling
- Department of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands; Dept. of Pulmonary Medicine, Amsterdam UMC, Amsterdam, the Netherlands.
| | - Anke-Hilse Maitland-Van der Zee
- Dept. of Pulmonary Medicine, Amsterdam UMC, Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands; Amsterdam Public Health, Amsterdam, the Netherlands
| | - Judith C S Holtjer
- Department of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands
| | - Somayeh Bazdar
- Dept. of Pulmonary Medicine, Amsterdam UMC, Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands; Amsterdam Public Health, Amsterdam, the Netherlands
| | - Roel C H Vermeulen
- Department of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - George S Downward
- Department of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Lizan D Bloemsma
- Dept. of Pulmonary Medicine, Amsterdam UMC, Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands; Amsterdam Public Health, Amsterdam, the Netherlands
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10
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Fedrizzi L, Carugno M, Consonni D, Lombardi A, Bandera A, Bono P, Ceriotti F, Gori A, Pesatori AC. Air pollution exposure, SARS-CoV-2 infection, and immune response in a cohort of healthcare workers of a large university hospital in Milan, Italy. ENVIRONMENTAL RESEARCH 2023; 236:116755. [PMID: 37517490 DOI: 10.1016/j.envres.2023.116755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 07/24/2023] [Accepted: 07/25/2023] [Indexed: 08/01/2023]
Abstract
Several studies have examined the possible relationship between air pollutants and the risk of COVID-19 but most returned controversial findings. We tried to assess the association between (short- and long-term) exposure to particulate and gaseous pollutants, SARS-CoV-2 infections, and immune response in a population of healthcare workers (HCWs) with well-characterized individual data. We collected occupational and clinical characteristics of all HCWs who performed a nasopharyngeal swab (NPS) for detecting SARS-CoV-2 at the Policlinico Hospital in Milan (Lombardy, Italy) between February 24, 2020 (day after first documented case of COVID-19 in our hospital) and December 26, 2020 (day before start of the vaccination campaign). Each subject was assigned daily average levels of particulate matter ≤10 μm (PM10), nitrogen dioxide (NO2), and ozone (O3) retrieved from the air quality monitoring station closest to his/her residential address. Air pollution data were treated as time-dependent variables, generating person-days at risk. Multivariate Poisson regression models were fit to evaluate the rate of positive NPS and to assess the association between air pollution and antibody titer among NPS-positive HCWs. Among 3712 included HCWs, 635 (17.1%) had at least one positive NPS. A 10 μg/m3 increase in NO2 average concentration in the four days preceding NPS was associated with a higher risk of testing positive [Incidence Rate Ratio (IRR) = 1.08, 95% confidence interval (CI): 1.01; 1.16)]. When considering a 1 μg/m3 increase in 2019 annual NO2 average, we observed a higher risk of infection (IRR: 1.02, 95%CI: 1.00; 1.03) and an increased antibody titer (+2.4%, 95%CI: 1.1; 3.6%). Findings on PM10 and O3 were less consistent and, differently from NO2, were not confirmed in multipollutant models. Our study increases the body of evidence suggesting an active role of air pollution exposure on SARS-CoV-2 infection and confirms the importance of implementing pollution reduction policies to improve public health.
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Affiliation(s)
- Luca Fedrizzi
- Epidemiology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Michele Carugno
- Epidemiology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy.
| | - Dario Consonni
- Epidemiology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Andrea Lombardi
- Infectious Diseases Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Alessandra Bandera
- Infectious Diseases Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Patrizia Bono
- Clinical Laboratory, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Ferruccio Ceriotti
- Clinical Laboratory, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Andrea Gori
- Infectious Diseases Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Angela Cecilia Pesatori
- Epidemiology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
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11
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Hooshmand S, Kassanos P, Keshavarz M, Duru P, Kayalan CI, Kale İ, Bayazit MK. Wearable Nano-Based Gas Sensors for Environmental Monitoring and Encountered Challenges in Optimization. SENSORS (BASEL, SWITZERLAND) 2023; 23:8648. [PMID: 37896744 PMCID: PMC10611361 DOI: 10.3390/s23208648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 10/04/2023] [Accepted: 10/09/2023] [Indexed: 10/29/2023]
Abstract
With a rising emphasis on public safety and quality of life, there is an urgent need to ensure optimal air quality, both indoors and outdoors. Detecting toxic gaseous compounds plays a pivotal role in shaping our sustainable future. This review aims to elucidate the advancements in smart wearable (nano)sensors for monitoring harmful gaseous pollutants, such as ammonia (NH3), nitric oxide (NO), nitrous oxide (N2O), nitrogen dioxide (NO2), carbon monoxide (CO), carbon dioxide (CO2), hydrogen sulfide (H2S), sulfur dioxide (SO2), ozone (O3), hydrocarbons (CxHy), and hydrogen fluoride (HF). Differentiating this review from its predecessors, we shed light on the challenges faced in enhancing sensor performance and offer a deep dive into the evolution of sensing materials, wearable substrates, electrodes, and types of sensors. Noteworthy materials for robust detection systems encompass 2D nanostructures, carbon nanomaterials, conducting polymers, nanohybrids, and metal oxide semiconductors. A dedicated section dissects the significance of circuit integration, miniaturization, real-time sensing, repeatability, reusability, power efficiency, gas-sensitive material deposition, selectivity, sensitivity, stability, and response/recovery time, pinpointing gaps in the current knowledge and offering avenues for further research. To conclude, we provide insights and suggestions for the prospective trajectory of smart wearable nanosensors in addressing the extant challenges.
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Affiliation(s)
- Sara Hooshmand
- Sabanci University Nanotechnology Research and Application Center (SUNUM), Tuzla, Istanbul 34956, Turkey
| | - Panagiotis Kassanos
- The Hamlyn Centre, Institute of Global Health Innovation, Imperial College London, South Kensington, London SW7 2AZ, UK;
- Department of Electrical and Electronic Engineering, Imperial College London, South Kensington, London SW7 2AZ, UK
| | - Meysam Keshavarz
- The Hamlyn Centre, Institute of Global Health Innovation, Imperial College London, South Kensington, London SW7 2AZ, UK;
- Department of Electrical and Electronic Engineering, Imperial College London, South Kensington, London SW7 2AZ, UK
| | - Pelin Duru
- Faculty of Engineering and Natural Science, Sabanci University, Istanbul 34956, Turkey; (P.D.); (C.I.K.)
| | - Cemre Irmak Kayalan
- Faculty of Engineering and Natural Science, Sabanci University, Istanbul 34956, Turkey; (P.D.); (C.I.K.)
| | - İzzet Kale
- Applied DSP and VLSI Research Group, Department of Computer Science and Engineering, University of Westminster, London W1W 6UW, UK;
| | - Mustafa Kemal Bayazit
- Sabanci University Nanotechnology Research and Application Center (SUNUM), Tuzla, Istanbul 34956, Turkey
- Faculty of Engineering and Natural Science, Sabanci University, Istanbul 34956, Turkey; (P.D.); (C.I.K.)
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12
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Popescu IM, Baditoiu LM, Reddy SR, Nalla A, Popovici ED, Margan MM, Anghel M, Laitin SMD, Toma AO, Herlo A, Fericean RM, Baghina N, Anghel A. Environmental Factors Influencing the Dynamics and Evolution of COVID-19: A Systematic Review on the Study of Short-Term Ozone Exposure. Healthcare (Basel) 2023; 11:2670. [PMID: 37830707 PMCID: PMC10572520 DOI: 10.3390/healthcare11192670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 09/25/2023] [Accepted: 09/30/2023] [Indexed: 10/14/2023] Open
Abstract
The potential influence of environmental factors, particularly air pollutants such as ozone (O3), on the dynamics and progression of COVID-19 remains a significant concern. This study aimed to systematically review and analyze the current body of literature to assess the impact of short-term ozone exposure on COVID-19 transmission dynamics and disease evolution. A rigorous systematic review was conducted in March 2023, covering studies from January 2020 to January 2023 found in PubMed, Web of Science, and Scopus. We followed the PRISMA guidelines and PROSPERO criteria, focusing exclusively on the effects of short-term ozone exposure on COVID-19. The literature search was restricted to English-language journal articles, with the inclusion and exclusion criteria strictly adhered to. Out of 4674 identified studies, 18 fulfilled the inclusion criteria, conducted across eight countries. The findings showed a varied association between short-term ozone exposure and COVID-19 incidence, severity, and mortality. Some studies reported a higher association between ozone exposure and incidence in institutional settings (OR: 1.06, 95% CI: 1.00-1.13) compared to the general population (OR: 1.00, 95% CI: 0.98-1.03). The present research identified a positive association between ozone exposure and both total and active COVID-19 cases as well as related deaths (coefficient for cases: 0.214; for recoveries: 0.216; for active cases: 0.467; for deaths: 0.215). Other studies also found positive associations between ozone levels and COVID-19 cases and deaths, while fewer reports identified a negative association between ozone exposure and COVID-19 incidence (coefficient: -0.187) and mortality (coefficient: -0.215). Conversely, some studies found no significant association between ozone exposure and COVID-19, suggesting a complex and potentially region-specific relationship. The relationship between short-term ozone exposure and COVID-19 dynamics is complex and multifaceted, indicating both positive and negative associations. These variations are possibly due to demographic and regional factors. Further research is necessary to bridge current knowledge gaps, especially considering the potential influence of short-term O3 exposure on COVID-19 outcomes and the broader implications on public health policy and preventive strategies during pandemics.
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Affiliation(s)
- Irina-Maria Popescu
- Department of Infectious Diseases, Discipline of Epidemiology, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania; (I.-M.P.); (L.M.B.); (E.D.P.); (M.A.); (S.M.D.L.)
- Doctoral School, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania;
| | - Luminita Mirela Baditoiu
- Department of Infectious Diseases, Discipline of Epidemiology, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania; (I.-M.P.); (L.M.B.); (E.D.P.); (M.A.); (S.M.D.L.)
| | - Sandhya Rani Reddy
- Department of General Medicine, Prathima Institute of Medical Sciences, Nagunur 505417, Telangana, India;
| | - Akhila Nalla
- Department of General Medicine, MNR Medical College, Sangareddy 502294, Telangana, India;
| | - Emilian Damian Popovici
- Department of Infectious Diseases, Discipline of Epidemiology, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania; (I.-M.P.); (L.M.B.); (E.D.P.); (M.A.); (S.M.D.L.)
| | - Madalin-Marius Margan
- Department of Functional Sciences, Discipline of Public Health, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania;
| | - Mariana Anghel
- Department of Infectious Diseases, Discipline of Epidemiology, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania; (I.-M.P.); (L.M.B.); (E.D.P.); (M.A.); (S.M.D.L.)
| | - Sorina Maria Denisa Laitin
- Department of Infectious Diseases, Discipline of Epidemiology, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania; (I.-M.P.); (L.M.B.); (E.D.P.); (M.A.); (S.M.D.L.)
| | - Ana-Olivia Toma
- Department of Dermatology, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania
| | - Alexandra Herlo
- Department of Infectious Diseases, Discipline of Infectious Diseases, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania;
| | - Roxana Manuela Fericean
- Doctoral School, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania;
| | - Nina Baghina
- National Meteorological Administration of Romania, Soseaua Bucuresti-Ploiesti 97, 013686 Bucuresti, Romania;
| | - Andrei Anghel
- Department of Biochemistry and Pharmacology, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania;
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13
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da Silveira LHM, Cataldi M, de Farias WCM. Development of multi-scale indices of human mobility restriction during the COVID-19 based on air quality from local and global NO 2 concentration. iScience 2023; 26:107599. [PMID: 37664602 PMCID: PMC10470316 DOI: 10.1016/j.isci.2023.107599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 02/22/2023] [Accepted: 08/08/2023] [Indexed: 09/05/2023] Open
Abstract
This study investigated whether variability in air quality, especially related to vehicular emissions, during the COVID-19 pandemic could indicate social distancing. Data from in situ measurements and satellite estimates were used. The study areas were São Paulo, Brazil, and Bologna, Italy. We focused our analysis on NO2, a combustion-derived pollutant, because of its availability in surface stations and satellite tracking, and because it has a short atmospheric lifetime. The analyses included graphical, statistical, and wavelet transform-based approaches to understand NO2 concentrations before and during the pandemic. After confirming the reduction in vehicular emissions during the pandemic, we created normalized indices to assess the social remoteness in 2020 in different locations, with a focus on São Paulo and Bologna. These indices were compared to existing indices based on cell phone mobility. The indices proposed in this study suffered high sensitivity to social distance compared to existing ones and helped to understand the actual application of social distance and contamination rates, considering the various dimensions of the problem.
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Affiliation(s)
- Larissa Haringer Martins da Silveira
- LAMMOC Group, Department of Agricultural and Environmental Engineering, Biosystems Engineering Graduate Program, Universidade Federal Fluminense, Niterói 24210-240, Brazil
| | - Marcio Cataldi
- LAMMOC Group, Department of Agricultural and Environmental Engineering, Biosystems Engineering Graduate Program, Universidade Federal Fluminense, Niterói 24210-240, Brazil
- MAR Group, Department of Physics. School of Chemistry. University of Murcia, 30100 Murcia, Spain
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14
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Razzaq A, Cui Y, Irfan M, Maneengam A, Acevedo-Duque Á. Asymmetric effects of fine particulate matter and stringency policy on COVID-19 intensity. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2023; 33:837-849. [PMID: 35361029 DOI: 10.1080/09603123.2022.2059452] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 03/24/2022] [Indexed: 06/14/2023]
Abstract
This study aims to examine the influence of environmental performance (PM2.5) on COVID-19 intensity . For this purpose, we employ the newly introduced Hidden Panel Cointegration test and Nonlinear Panel Autoregressive Distributed Lag model. Results indicate the asymmetric linkages between PM2.5 and COVID-19 intensity, as the positive shock in PM2.5 raises the COVID-19 intensity by 21%, whereas the negative shock in PM2.5 decreases COVID-19 intensity by 12% in long-run. On the contrary, the positive shock in stringency measures decreases COVID-19 intensity by 42.8%, while the negative shock in stringency policy increases COVID-19 intensity by 66.7%. These findings imply that higher pollution increases the COVID-19 severity while higher stringency measures slow down people's movement and reduce COVID-19 intensity. However, a sudden negative shock in lockdown increases people's interaction, leading to a higher spread of the virus. These results suggest that governments should adopt stringent action plans to contain the transmissibility of COVID-19.
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Affiliation(s)
- Asif Razzaq
- School of Economics and Management, Dalian University of Technology, Dalian, PR China
| | - Yiniu Cui
- School of Finance, Shanxi University of Finance and Economics, Taiyuan, Shanxi, China
| | - Muhammad Irfan
- School of Management and Economics, Beijing Institute of Technology, Beijing, China
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, China
- Department of Business Administration, Ilma University, Karachi, Pakistan
| | - Apichit Maneengam
- Department of Mechanical Engineering Technology, College of Industrial Technology, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand
| | - Ángel Acevedo-Duque
- Public Policy Observatory Faculty of Business and Administration, Universidad Autónoma de Chile, Santiago, Chile
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15
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Shezad N, D'Agostini M, Ezzine A, Franchin G, Colombo P, Akhtar F. 3D-printed zeolite 13X-Strontium chloride units as ammonia carriers. Heliyon 2023; 9:e19376. [PMID: 37810019 PMCID: PMC10558346 DOI: 10.1016/j.heliyon.2023.e19376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 08/21/2023] [Accepted: 08/21/2023] [Indexed: 10/10/2023] Open
Abstract
The selective catalytic reduction (SCR) system in automobiles using urea solution as a source of NH3 suffers from solid deposit problems in pipelines and poor efficiency during engine startup. Although direct use of high pressure NH3 is restricted due to safety concerns, which can be overcome by using solid sorbents as NH3 carrier. Strontium chloride (SrCl2) is considered the best sorbent due to its high sorption capacity; however, challenges are associated with the processing of stable engineering structures due to extraordinary volume expansion during the NH3 sorption. This study reports the fabrication of a novel structure consisting of a zeolite cage enclosing the SrCl2 pellet (SPZC) through extrusion-based 3D printing (Direct Ink Writing). The printed SPZC structure demonstrated steady sorption of NH3 for 10 consecutive cycles without significant uptake capacity and structural integrity loss. Furthermore, the structure exhibited improved sorption and desorption kinetics than pure SrCl2. The synergistic effect of zeolite as physisorbent and SrCl2 as chemisorbent in the novel composite structure enabled the low-pressure (<0.4 bar) and high-pressure (>0.4 bar) NH3 sorption, compared to pure SrCl2, which absorbed NH3 at pressures above 0.4 bar. Regeneration of SPZC composite sorbent under evacuation showed that 87.5% percent of NH3 was desorbed at 20 °C. Thus, the results demonstrate that the rationally designed novel SPZC structure offers safe and efficient storage of NH3 in the SCR system and other applications.
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Affiliation(s)
- Nasir Shezad
- Division of Materials Science, Department of Engineering Sciences and Mathematics, Luleå University of Technology, Luleå, SE-971 87, Sweden
| | - Marco D'Agostini
- Department of Industrial Engineering, University of Padova, Via Marzolo, 9, Padova, 35131, Italy
| | - Ali Ezzine
- Department of Industrial Engineering, University of Padova, Via Marzolo, 9, Padova, 35131, Italy
| | - Giorgia Franchin
- Department of Industrial Engineering, University of Padova, Via Marzolo, 9, Padova, 35131, Italy
| | - Paolo Colombo
- Department of Industrial Engineering, University of Padova, Via Marzolo, 9, Padova, 35131, Italy
- Department of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, USA
| | - Farid Akhtar
- Division of Materials Science, Department of Engineering Sciences and Mathematics, Luleå University of Technology, Luleå, SE-971 87, Sweden
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16
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Solarin SA, Sahu PK. Sectoral foreign direct investment and environmental degradation: new insights from diversification of energy mix containing fossil fuels and renewable energy. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:91853-91873. [PMID: 37480530 DOI: 10.1007/s11356-023-28741-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 07/06/2023] [Indexed: 07/24/2023]
Abstract
The objective of the study is to extend the existing literature by investigating the effects of foreign direct investment, gross domestic products and per capita and energy diversification on the nitrogen oxide emissions in Brazil, Russia, India, China and South Africa (BRICS) by using annual data during the period 1992-2019. As per our knowledge, the present study is a first of its kind to examine the impact of a new energy diversification index, based on Herfindahl-Hirschman framework on pollution. This study has adopted a new quantile regression augmented method of moments, which is capable of producing the total impacts of the independent variables across the entire distribution of nitrogen oxides emissions. The findings suggest that an increase in foreign direct investment leads to a decrease in nitrogen oxides emissions at the aggregate level and in both manufacturing and service sectors. We observe that foreign direct investment leads to an increase in nitrogen oxides emissions in the agricultural sector in most of the quantiles. Diversification towards renewable energy causes a decrease in nitrogen oxides emissions in most quantiles at aggregate level, agricultural and manufacturing sectors, whilst diversification leads to an increase in nitrogen oxides emissions in the service sector. The findings also suggest that GDP per capita leads to an increase in NOx emissions in all the quantiles. The study suggests the policy to use and attract more clean energy through foreign direct investment for towards the achievement of sustainable development.
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17
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Jenkins GS, Freire SM, Ogunro T, Niang D, Andrade M, Drame MS, Huvi JB, Pires EES, Toure EN, Camara M. COVID-19 New Cases and Environmental Factors During Wet and Dry Seasons in West and Southern Africa. GEOHEALTH 2023; 7:e2022GH000765. [PMID: 37519911 PMCID: PMC10383768 DOI: 10.1029/2022gh000765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 05/08/2023] [Accepted: 06/20/2023] [Indexed: 08/01/2023]
Abstract
Sub-Saharan Africa has been the last continent to experience a significant number of cases in the novel Coronavirus (COVID-19). Studies suggest that air pollution is related to COVID-19 mortality; poor air quality has been linked to cardiovascular, cerebrovascular, and respiratory diseases, which are considered co-morbidities linked to COVID-19 deaths. We examine potential connections between country-wide COVID-19 cases and environmental conditions in Senegal, Cabo Verde, Nigeria, Cote D'Ivorie, and Angola. We analyze PM2.5 concentrations, temperatures from cost-effective in situ measurements, aerosol optical depth (AOD), and fire count and NO2 column values from space-borne platforms from 1 January 2020 through 31 March 2021. Our results show that the first COVID-19 wave in West Africa began during the wet season of 2020, followed by a second during the dry season of 2020. In Angola, the first wave starts during the biomass burning season but does not peak until November of 2020. Overall PM2.5 concentrations are the highest in Ibadan, Nigeria, and coincided with the second wave of COVID-19 in late 2021 and early 2022. The COVID-19 waves in Cabo Verde are not in phase with those in Senegal, Nigeria, and Cote, lagging by several months in general. Overall, the highest correlations occurred between weekly new COVID-19 cases meteorological and air quality variables occurred in the dry season.
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Affiliation(s)
- G. S. Jenkins
- Alliance for Education, Science, Engineering and Design with Africa (AESEDA)Pennsylvania State UniversityUniversity ParkPAUSA
| | | | | | - D. Niang
- Cheikh Anta Diop UniversityDakarSenegal
| | | | | | - J. B. Huvi
- Instituto Superior de Ciências da Educação de Benguela ‐ AngolaBenguelaAngola
| | - E. E. S. Pires
- Centro de Estudos e Pesquisa do TundavalaEngineering DepartmentISPTundavalaLubangoAngola
| | - E. N. Toure
- University Felix Houphouet BiognyAbidjanCote D'Ivorie
| | - M. Camara
- University of Assane SeckZiguinchorSenegal
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Akuno AO, Ramírez-Ramírez LL, Espinoza JF. Inference on a Multi-Patch Epidemic Model with Partial Mobility, Residency, and Demography: Case of the 2020 COVID-19 Outbreak in Hermosillo, Mexico. ENTROPY (BASEL, SWITZERLAND) 2023; 25:968. [PMID: 37509915 PMCID: PMC10378648 DOI: 10.3390/e25070968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 06/02/2023] [Accepted: 06/14/2023] [Indexed: 07/30/2023]
Abstract
Most studies modeling population mobility and the spread of infectious diseases, particularly those using meta-population multi-patch models, tend to focus on the theoretical properties and numerical simulation of such models. As such, there is relatively scant literature focused on numerical fit, inference, and uncertainty quantification of epidemic models with population mobility. In this research, we use three estimation techniques to solve an inverse problem and quantify its uncertainty for a human-mobility-based multi-patch epidemic model using mobile phone sensing data and confirmed COVID-19-positive cases in Hermosillo, Mexico. First, we utilize a Brownian bridge model using mobile phone GPS data to estimate the residence and mobility parameters of the epidemic model. In the second step, we estimate the optimal model epidemiological parameters by deterministically inverting the model using a Darwinian-inspired evolutionary algorithm (EA)-that is, a genetic algorithm (GA). The third part of the analysis involves performing inference and uncertainty quantification in the epidemic model using two Bayesian Monte Carlo sampling methods: t-walk and Hamiltonian Monte Carlo (HMC). The results demonstrate that the estimated model parameters and incidence adequately fit the observed daily COVID-19 incidence in Hermosillo. Moreover, the estimated parameters from the HMC method yield large credible intervals, improving their coverage for the observed and predicted daily incidences. Furthermore, we observe that the use of a multi-patch model with mobility yields improved predictions when compared to a single-patch model.
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Affiliation(s)
- Albert Orwa Akuno
- Departamento de Probabilidad y Estadística, Centro de Investigación en Matemáticas A.C., Jalisco s/n, Colonia Valenciana, Guanajuato C.P. 36023, Gto, Mexico
| | - L Leticia Ramírez-Ramírez
- Departamento de Probabilidad y Estadística, Centro de Investigación en Matemáticas A.C., Jalisco s/n, Colonia Valenciana, Guanajuato C.P. 36023, Gto, Mexico
| | - Jesús F Espinoza
- Departamento de Matemáticas, Universidad de Sonora, Rosales y Boulevard Luis Encinas, Hermosillo C.P. 83000, Sonora, Mexico
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19
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Alaniz AJ, Vergara PM, Carvajal JG, Carvajal MA. Unraveling the socio-environmental drivers during the early COVID-19 pandemic in China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023:10.1007/s11356-023-27969-0. [PMID: 37310602 DOI: 10.1007/s11356-023-27969-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 05/24/2023] [Indexed: 06/14/2023]
Abstract
The effect of environmental and socioeconomic conditions on the global pandemic of COVID-19 had been widely studied, yet their influence during the early outbreak remains less explored. Unraveling these relationships represents a key knowledge to prevent potential outbreaks of similar pathogens in the future. This study aims to determine the influence of socioeconomic, infrastructure, air pollution, and weather variables on the relative risk of infection in the initial phase of the COVID-19 pandemic in China. A spatio-temporal Bayesian zero-inflated Poisson model is used to test for the effect of 13 socioeconomic, urban infrastructure, air pollution, and weather variables on the relative risk of COVID-19 disease in 122 cities of China. The results show that socioeconomic and urban infrastructure variables did not have a significant effect on the relative risk of COVID-19. Meanwhile, COVID-19 relative risk was negatively associated with temperature, wind speed, and carbon monoxide, while nitrous dioxide and the human modification index presented a positive effect. Pollution gases presented a marked variability during the study period, showing a decrease of CO. These findings suggest that controlling and monitoring urban emissions of pollutant gases is a key factor for the reduction of risk derived from COVID-19.
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Affiliation(s)
- Alberto J Alaniz
- Departamento de Ingeniería Geoespacial y Ambiental, Universidad de Santiago de Chile, Santiago, Chile.
- Centro de Formación Técnica del Medio ambiente, IDMA, Santiago, Chile.
- Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago, Chile.
- Departamento de Gestión Agraria, Facultad Tecnolִógica, Universidad de Santiago de Chile, Santiago, Chile.
| | - Pablo M Vergara
- Departamento de Gestión Agraria, Facultad Tecnolִógica, Universidad de Santiago de Chile, Santiago, Chile
| | - Jorge G Carvajal
- Departamento de Gestión Agraria, Facultad Tecnolִógica, Universidad de Santiago de Chile, Santiago, Chile
| | - Mario A Carvajal
- Departamento de Gestión Agraria, Facultad Tecnolִógica, Universidad de Santiago de Chile, Santiago, Chile
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20
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AlShehhi A, Welsch R. Artificial intelligence for improving Nitrogen Dioxide forecasting of Abu Dhabi environment agency ground-based stations. JOURNAL OF BIG DATA 2023; 10:92. [PMID: 37303479 PMCID: PMC10236404 DOI: 10.1186/s40537-023-00754-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 05/08/2023] [Indexed: 06/13/2023]
Abstract
Nitrogen Dioxide (NO2 ) is a common air pollutant associated with several adverse health problems such as pediatric asthma, cardiovascular mortality,and respiratory mortality. Due to the urgent society's need to reduce pollutant concentration, several scientific efforts have been allocated to understand pollutant patterns and predict pollutants' future concentrations using machine learning and deep learning techniques. The latter techniques have recently gained much attention due it's capability to tackle complex and challenging problems in computer vision, natural language processing, etc. In the NO2 context, there is still a research gap in adopting those advanced methods to predict the concentration of pollutants. This study fills in the gap by comparing the performance of several state-of-the-art artificial intelligence models that haven't been adopted in this context yet. The models were trained using time series cross-validation on a rolling base and tested across different periods using NO2 data from 20 monitoring ground-based stations collected by Environment Agency- Abu Dhabi, United Arab Emirates. Using the seasonal Mann-Kendall trend test and Sen's slope estimator, we further explored and investigated the pollutants trends across the different stations. This study is the first comprehensive study that reported the temporal characteristic of NO2 across seven environmental assessment points and compared the performance of the state-of-the-art deep learning models for predicting the pollutants' future concentration. Our results reveal a difference in the pollutants concentrations level due to the geographic location of the different stations, with a statistically significant decrease in the NO2 annual trend for the majority of the stations. Overall, NO2 concentrations exhibit a similar daily and weekly pattern across the different stations, with an increase in the pollutants level during the early morning and the first working day. Comparing the state-of-the-art model performance transformer model demonstrate the superiority of ( MAE:0.04 (± 0.04),MSE:0.06 (± 0.04), RMSE:0.001 (± 0.01), R2 : 0.98 (± 0.05)), compared with LSTM (MAE:0.26 (± 0.19), MSE:0.31 (± 0.21), RMSE:0.14 (± 0.17), R2 : 0.56 (± 0.33)), InceptionTime (MAE: 0.19 (± 0.18), MSE: 0.22 (± 0.18), RMSE:0.08 (± 0.13), R2 :0.38 (± 1.35) ), ResNet (MAE:0.24 (± 0.16), MSE:0.28 (± 0.16), RMSE:0.11 (± 0.12), R2 :0.35 (± 1.19) ), XceptionTime (MAE:0.7 (± 0.55), MSE:0.79 (± 0.54), RMSE:0.91 (± 1.06), R2 : - 4.83 (± 9.38) ), and MiniRocket (MAE:0.21 (± 0.07), MSE:0.26 (± 0.08), RMSE:0.07 (± 0.04), R2 : 0.65 (± 0.28) ) to tackle this challenge. The transformer model is a powerful model for improving the accurate forecast of the NO2 levels and could strengthen the current monitoring system to control and manage the air quality in the region. Supplementary Information The online version contains supplementary material available at 10.1186/s40537-023-00754-z.
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Affiliation(s)
- Aamna AlShehhi
- Biomedical Engineering, Khalifa University, Abu Dhabi, United Arab Emirates
| | - Roy Welsch
- Sloan School of Management and Statistics, Massachusetts Institute of Technology, Cambridge, Massachusetts USA
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21
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Spatio-temporal analysis of nitrogen dioxide (NO 2) from Sentinel-5P imageries using Google Earth Engine changes during the COVID-19 social restriction policy in jakarta. NATURAL HAZARDS RESEARCH 2023; 3:344-352. [PMCID: PMC10166263 DOI: 10.1016/j.nhres.2023.02.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 02/07/2023] [Accepted: 02/22/2023] [Indexed: 08/26/2024]
Abstract
The number of cases due to COVID-19 is increasing, especially in Jakarta, requiring the government to establish a policy of social restrictions. The policy impacting the mobility of people using motor vehicles becomes limited, affecting air quality such as Nitrogen Dioxide (NO2). NO2 concentrations can be determined using the Sentinel-5P satellite using Google Earth Engine. This study analyzed NO2 changes and people's mobility in residential and workplace categories through google mobility data in Jakarta spatially and temporally for January 2020 to December 2021. The Pearson's correlation (R) between NO2 from Sentinel-5P imageries and air quality monitoring stations was 0.426–0.736, indicating a moderate to strong correlation with a p-value <0.05. The decrease in NO2 occurred at the beginning of the Large-Scale Social Restriction (PSBB) from April 2020 to May 2020 and the Implementation of Restrictions on Social Activities (PPKM) policy from July 2021 to August 2021; it was −11.381 μmol/m2 and -23.195 μmol/m2, with very low and low mobility in the residential and workplace categories. The area that experienced a change in NO2 increase of 1 μmol/m2, the highest occurred from May 2021 to June 2021 at 641.571 km2. Meanwhile, from November 2020 to December 2020, no area experienced an increase of 1 μmol/m2. We discovered that there were a number of anomalies when people's mobility in the residential and workplace category was very high, NO2 actually decreased. This anomaly shows that the decrease in NO2 is influenced by decreased mobility and other factors such as precipitation.
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Atiaga O, Guerrero F, Páez F, Castro R, Collahuazo E, Nunes LM, Grijalva M, Grijalva I, Otero XL. Assessment of variations in air quality in cities of Ecuador in relation to the lockdown due to the COVID-19 pandemic. Heliyon 2023; 9:e17033. [PMID: 37484275 PMCID: PMC10361106 DOI: 10.1016/j.heliyon.2023.e17033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 06/05/2023] [Accepted: 06/05/2023] [Indexed: 07/25/2023] Open
Abstract
This study analyzes the effect of lockdown due to COVID-19 on the spatiotemporal variability of ozone (O3), sulfur dioxide (SO2), and nitrogen dioxide (NO2) concentrations in different provinces of continental Ecuador using satellite information from Sentinel - 5P. The statistical analysis includes data from 2018 to March 2021 and was performed based on three periods defined a priori: before, during, and after lockdown due to COVID-19, focusing on the provinces with the highest concentrations of the studied gases (hotspots). The results showed a significant decrease in NO2 concentrations during the COVID-19 lockdown period in all the study areas: the Metropolitan District of Quito (DMQ) and the provinces of Guayas and Santo Domingo de los Tsáchilas. In the period after lockdown, NO2 concentrations increased by over 20% when compared to the pre-lockdown period, which may be attributable to a shift towards private transportation due to health concerns. On the other hand, SO2 concentrations during the lockdown period showed irregular, non-significant variations; however, increases were observed in the provinces of Chimborazo, Guayas, Santa Elena, and Morona Santiago, which could be partly attributed to the eruptive activity of the Sangay volcano during 2019-2020. Conversely, O3 concentrations increased by 2-3% in the study areas; this anomalous behavior could be attributed to decreased levels of NOx, which react with ozone, reducing its concentration. Finally, satellite data validation using the corresponding data from monitoring stations in the DMQ showed correlation values of 0.9 for O3 data and 0.7 for NO2 data, while no significant correlation was found for SO2.
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Affiliation(s)
- Oliva Atiaga
- Departamento de Ciencias de la Tierra y la Construcción, Universidad de las Fuerzas Armadas ESPE, Av. General Rumiñahui s/n, Sangolquí, P.O. Box 171-5-231B, Ecuador
- CRETUS. Departamento de Edafoloxía e Química Agrícola, Facultade de Bioloxía, Universidade de Santiago de Compostela, Campus Sur, 15782 Santiago de Compostela, Spain
| | - Fernanda Guerrero
- Departamento de Ciencias de la Tierra y la Construcción, Universidad de las Fuerzas Armadas ESPE, Av. General Rumiñahui s/n, Sangolquí, P.O. Box 171-5-231B, Ecuador
| | - Fernando Páez
- Departamento de Ciencias de la Tierra y la Construcción, Universidad de las Fuerzas Armadas ESPE, Av. General Rumiñahui s/n, Sangolquí, P.O. Box 171-5-231B, Ecuador
| | - Rafael Castro
- Geospace Solutions, Av. Manuel Córdova Galarza km 4.5, P.O. Box 170177, Ecuador
| | - Edison Collahuazo
- Geospace Solutions, Av. Manuel Córdova Galarza km 4.5, P.O. Box 170177, Ecuador
| | - Luís Miguel Nunes
- Faculdade de Ciências e Tecnologia, Universidade do Algarve, Campus de Gambelas, Faro, Portugal
- CERIS, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001, Lisboa, Portugal
| | - Marcelo Grijalva
- Departamento de Ciencias de la Vida, Universidad de las Fuerzas Armadas ESPE, Av. General Rumiñahui s/n, Sangolquí, P.O. Box 171-5-231B, Ecuador
| | - Iván Grijalva
- Independent consultant. Avenida Amazonas N22-62 y Ramirez Dávalos, PO BOX 170526, Quito, Ecuador
| | - Xosé Luis Otero
- CRETUS. Departamento de Edafoloxía e Química Agrícola, Facultade de Bioloxía, Universidade de Santiago de Compostela, Campus Sur, 15782 Santiago de Compostela, Spain
- REBUSC Network of Biological Field Stations of the University of Santiago de Compostela, Marine Biology Stations of A Graña and Ferrol, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain
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23
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Ghobakhloo S, Khoshakhlagh AH, Mostafaii GR, Chuang KJ, Gruszecka-Kosowska A, Hosseinnia P. Critical air pollutant assessments and health effects attributed to PM 2.5 during and after COVID-19 lockdowns in Iran: application of AirQ + models. Front Public Health 2023; 11:1120694. [PMID: 37304093 PMCID: PMC10249069 DOI: 10.3389/fpubh.2023.1120694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Accepted: 04/28/2023] [Indexed: 06/13/2023] Open
Abstract
Objectives The aim of this study was to evaluate changes in air quality index (AQI) values before, during, and after lockdown, as well as to evaluate the number of hospitalizations due to respiratory and cardiovascular diseases attributed to atmospheric PM2.5 pollution in Semnan, Iran in the period from 2019 to 2021 during the COVID-19 pandemic. Methods Daily air quality records were obtained from the global air quality index project and the US Environmental Protection Administration (EPA). In this research, the AirQ+ model was used to quantify health consequences attributed to particulate matter with an aerodynamic diameter of <2.5 μm (PM2.5). Results The results of this study showed positive correlations between air pollution levels and reductions in pollutant levels during and after the lockdown. PM2.5 was the critical pollutant for most days of the year, as its AQI was the highest among the four investigated pollutants on most days. Mortality rates from chronic obstructive pulmonary disease (COPD) attributed to PM2.5 in 2019-2021 were 25.18% in 2019, 22.55% in 2020, and 22.12% in 2021. Mortality rates and hospital admissions due to cardiovascular and respiratory diseases decreased during the lockdown. The results showed a significant decrease in the percentage of days with unhealthy air quality in short-term lockdowns in Semnan, Iran with moderate air pollution. Natural mortality (due to all-natural causes) and other mortalities related to COPD, ischemic heart disease (IHD), lung cancer (LC), and stroke attributed to PM2.5 in 2019-2021 decreased. Conclusion Our results support the general finding that anthropogenic activities cause significant health threats, which were paradoxically revealed during a global health crisis/challenge.
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Affiliation(s)
- Safiye Ghobakhloo
- Department of Environmental Health Engineering, School of Health, Kashan University of Medical Sciences, Kashan, Iran
| | - Amir Hossein Khoshakhlagh
- Department of Occupational Health Engineering, School of Health, Kashan University of Medical Sciences, Kashan, Iran
| | - Gholam Reza Mostafaii
- Department of Environmental Health Engineering, School of Health, Kashan University of Medical Sciences, Kashan, Iran
| | - Kai-Jen Chuang
- School of Public Health, College of Public Health, Taipei Medical University, Taipei, Taiwan
| | - Agnieszka Gruszecka-Kosowska
- Faculty of Geology, Geophysics, and Environmental Protection, Department of Environmental Protection, AGH University of Science and Technology, Krakow, Poland
| | - Pariya Hosseinnia
- Department of Public Health, Garmsar Branch, Islamic Azad University, Garmsar, Iran
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24
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Hu H, Laden F, Hart J, James P, Fishe J, Hogan W, Shenkman E, Bian J. A spatial and contextual exposome-wide association study and polyexposomic score of COVID-19 hospitalization. EXPOSOME 2023; 3:osad005. [PMID: 37089437 PMCID: PMC10118922 DOI: 10.1093/exposome/osad005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 03/22/2023] [Accepted: 04/06/2023] [Indexed: 04/25/2023]
Abstract
Environmental exposures have been linked to COVID-19 severity. Previous studies examined very few environmental factors, and often only separately without considering the totality of the environment, or the exposome. In addition, existing risk prediction models of severe COVID-19 predominantly rely on demographic and clinical factors. To address these gaps, we conducted a spatial and contextual exposome-wide association study (ExWAS) and developed polyexposomic scores (PES) of COVID-19 hospitalization leveraging rich information from individuals' spatial and contextual exposome. Individual-level electronic health records of 50 368 patients aged 18 years and older with a positive SARS-CoV-2 PCR/Antigen lab test or a COVID-19 diagnosis between March 2020 and October 2021 were obtained from the OneFlorida+ Clinical Research Network. A total of 194 spatial and contextual exposome factors from 10 data sources were spatiotemporally linked to each patient based on geocoded residential histories. We used a standard two-phase procedure in the ExWAS and developed and validated PES using gradient boosting decision trees models. Four exposome measures significantly associated with COVID-19 hospitalization were identified, including 2-chloroacetophenone, low food access, neighborhood deprivation, and reduced access to fitness centers. The initial prediction model in all patients without considering exposome factors had a testing-area under the curve (AUC) of 0.778. Incorporation of exposome data increased the testing-AUC to 0.787. Similar findings were observed in subgroup analyses focusing on populations without comorbidities and aged 18-24 years old. This spatial and contextual exposome study of COVID-19 hospitalization confirmed previously reported risk factor but also generated novel predictors that warrant more focused evaluation.
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Affiliation(s)
- Hui Hu
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Francine Laden
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jaime Hart
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Peter James
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Population Medicine, Harvard Pilgrim Healthcare, Boston, MA, USA
| | - Jennifer Fishe
- Department of Emergency Medicine, University of Florida College of Medicine—Jacksonville, Jacksonville, FL, USA
| | - William Hogan
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Elizabeth Shenkman
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Jiang Bian
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA
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25
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Guo K, Yan L, He Y, Li H, Lam SS, Peng W, Sonne C. Phytoremediation as a potential technique for vehicle hazardous pollutants around highways. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 322:121130. [PMID: 36693585 DOI: 10.1016/j.envpol.2023.121130] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 01/14/2023] [Accepted: 01/19/2023] [Indexed: 06/17/2023]
Abstract
With the synchronous development of highway construction and the urban economy, automobiles have entered thousands of households as essential means of transportation. This paper reviews the latest research progress in using phytoremediation technology to remediate the environmental pollution caused by automobile exhaust in recent years, including the prospects for stereoscopic forestry. Currently, most automobiles on the global market are internal combustion vehicles using fossil energy sources as the primary fuel, such as gasoline, diesel, and liquid or compressed natural gas. The composition of vehicle exhaust is relatively complex. When it enters the atmosphere, it is prone to a series of chemical reactions to generate various secondary pollutants, which are very harmful to human beings, plants, animals, and the eco-environment. Despite improving the automobile fuel quality and installing exhaust gas purification devices, helping to reduce air pollution, the treatment costs of these approaches are expensive and cannot achieve zero emissions of automobile exhaust pollutants. The purification of vehicle exhaust by plants is a crucial way to remediate the environmental pollution caused by automobile exhaust and improve the environment along the highway by utilizing the ecosystem's self-regulating ability. Therefore, it has become a global trend to use phytoremediation technology to restore the automobile exhaust pollution. Now, there is no scientific report or systematic review about how plants absorb vehicle pollutants. The screening and configuration of suitable plant species is the most crucial aspect of successful phytoremediation. The mechanisms of plant adsorption, metabolism, and detoxification are reviewed in this paper to address the problem of automobile exhaust pollution.
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Affiliation(s)
- Kang Guo
- Henan Province Engineering Research Center for Biomass Value-added Products, School of Forestry, Henan Agricultural University, Zhengzhou, 450002, China
| | - Lijun Yan
- Henan Province Engineering Research Center for Biomass Value-added Products, School of Forestry, Henan Agricultural University, Zhengzhou, 450002, China
| | - Yifeng He
- Henan Province Engineering Research Center for Biomass Value-added Products, School of Forestry, Henan Agricultural University, Zhengzhou, 450002, China
| | - Hanyin Li
- Henan Province Engineering Research Center for Biomass Value-added Products, School of Forestry, Henan Agricultural University, Zhengzhou, 450002, China
| | - Su Shiung Lam
- Higher Institution Centre of Excellence (HICoE), Institute of Tropical Aquaculture and Fisheries (AKUATROP), Universiti Malaysia Terengganu, 21030, Kuala Nerus, Terengganu, Malaysia; Center for Transdisciplinary Research, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India
| | - Wanxi Peng
- Henan Province Engineering Research Center for Biomass Value-added Products, School of Forestry, Henan Agricultural University, Zhengzhou, 450002, China.
| | - Christian Sonne
- Aarhus University, Department of Bioscience, Arctic Research Centre (ARC), Frederiksborgvej 399, PO Box 358, DK-4000 Roskilde, Denmark; Sustainability Cluster, School of Engineering, University of Petroleum & Energy Studies, Dehradun, Uttarakhand 248007, India
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26
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Huang J, Kwan MP. Associations between COVID-19 risk, multiple environmental exposures, and housing conditions: A study using individual-level GPS-based real-time sensing data. APPLIED GEOGRAPHY (SEVENOAKS, ENGLAND) 2023; 153:102904. [PMID: 36816398 PMCID: PMC9928735 DOI: 10.1016/j.apgeog.2023.102904] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 02/11/2023] [Accepted: 02/13/2023] [Indexed: 06/18/2023]
Abstract
Few studies have used individual-level data to explore the association between COVID-19 risk with multiple environmental exposures and housing conditions. Using individual-level data collected with GPS-tracking smartphones, mobile air-pollutant and noise sensors, an activity-travel diary, and a questionnaire from two typical neighborhoods in a dense and well-developed city (i.e., Hong Kong), this study seeks to examine 1) the associations between multiple environmental exposures (i.e., different types of greenspace, PM2.5, and noise) and housing conditions (i.e., housing types, ownership, and overcrowding) with individuals' COVID-19 risk both in residential neighborhoods and along daily mobility trajectories; 2) which social groups are disadvantaged in COVID-19 risk through the perspective of the neighborhood effect averaging problem (NEAP). Using separate multiple linear regression and logistical regression models, we found a significant negative association between COVID-19 risk with greenspace (i.e., NDVI) both in residential areas and along people's daily mobility trajectories. Meanwhile, we also found that high open space and recreational land exposure and poor housing conditions were positively associated with COVID-19 risk in high-risk neighborhoods, and noise exposure was positively associated with COVID-19 risk in low-risk neighborhoods. Further, people with work places in high-risk areas and poor housing conditions were disadvantaged in COVID-19 risk.
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Affiliation(s)
- Jianwei Huang
- Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Mei-Po Kwan
- Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin, Hong Kong, China
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, Hong Kong, China
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27
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Monoson A, Schott E, Ard K, Kilburg-Basnyat B, Tighe RM, Pannu S, Gowdy KM. Air pollution and respiratory infections: the past, present, and future. Toxicol Sci 2023; 192:3-14. [PMID: 36622042 PMCID: PMC10025881 DOI: 10.1093/toxsci/kfad003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Air pollution levels across the globe continue to rise despite government regulations. The increase in global air pollution levels drives detrimental human health effects, including 7 million premature deaths every year. Many of these deaths are attributable to increased incidence of respiratory infections. Considering the COVID-19 pandemic, an unprecedented public health crisis that has claimed the lives of over 6.5 million people globally, respiratory infections as a driver of human mortality is a pressing concern. Therefore, it is more important than ever to understand the relationship between air pollution and respiratory infections so that public health measures can be implemented to ameliorate further morbidity and mortality. This article aims to review the current epidemiologic and basic science research on interactions between air pollution exposure and respiratory infections. The first section will present epidemiologic studies organized by pathogen, followed by a review of basic science research investigating the mechanisms of infection, and then conclude with a discussion of areas that require future investigation.
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Affiliation(s)
- Alexys Monoson
- Department of Pulmonary, Critical Care and Sleep Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio 43210, USA
| | - Evangeline Schott
- Department of Pulmonary, Critical Care and Sleep Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio 43210, USA
| | - Kerry Ard
- School of Environment and Natural Resources, The Ohio State University, Columbus, Ohio 43210, USA
| | - Brita Kilburg-Basnyat
- Department of Pharmacology and Toxicology, East Carolina University, Greenville, North Carolina 27834, USA
| | - Robert M Tighe
- Department of Medicine, Duke University Medical Center, Durham, North Carolina 27710, USA
| | - Sonal Pannu
- Department of Pulmonary, Critical Care and Sleep Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio 43210, USA
| | - Kymberly M Gowdy
- Department of Pulmonary, Critical Care and Sleep Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio 43210, USA
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Shrivastav LK, Kumar R. Empirical Analysis of Impact of Weather and Air Pollution Parameters on COVID-19 Spread and Control in India Using Machine Learning Algorithm. WIRELESS PERSONAL COMMUNICATIONS 2023; 130:1963-1991. [PMID: 37206636 PMCID: PMC10019423 DOI: 10.1007/s11277-023-10367-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 03/06/2023] [Indexed: 05/21/2023]
Abstract
The COVID-19 has affected and threatened the world health system very critically throughout the globe. In order to take preventive actions by the agencies in dealing with such a pandemic situation, it becomes very necessary to develop a system to analyze the impact of environmental parameters on the spread of this virus. Machine learning algorithms and artificial Intelligence may play an important role in the detection and analysis of the spread of COVID-19. This paper proposed a twinned gradient boosting machine (GBM) to analyze the impact of environmental parameters on the spread, recovery, and mortality rate of this virus in India. The proposed paper exploited the four weather parameters (temperature, humidity, atmospheric pressure, and wind speed) and two air pollution parameters (PM2.5 and PM10) as input to predict the infection, recovery, and mortality rate of its spread. The algorithm of the GBM model has been optimized in its four distributions for best performance by tuning its parameters. The performance of the GBM is reported as excellent (where R2 = 0.99) in training for the combined dataset comprises all three outcomes i.e. infection, recovery and mortality rates. The proposed approach achieved the best prediction results for the state, which is worst affected and highest variation in the atmospheric factors and air pollution level.
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Affiliation(s)
| | - Ravinder Kumar
- SFET, Shri Vishwakarma Skill University, Gurugram, India
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Joshua BW, Fuwape I, Rabiu B, Pires EES, Sa'id RS, Ogunro TT, Awe OF, Osunmakinwa OO, Ogunjo S. The Impact of the First and Second Waves of COVID-19 Pandemic in Nigeria. GEOHEALTH 2023; 7:e2022GH000722. [PMID: 36968154 PMCID: PMC10030272 DOI: 10.1029/2022gh000722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 02/08/2023] [Accepted: 02/09/2023] [Indexed: 06/18/2023]
Abstract
In recent times, the COVID-19 pandemic has been the subject of global concern. It has so far claimed over 5.4 million lives globally, with over 291 million cases recorded worldwide as of 5 January 2022. It is known to have different waves and variants, thus making it difficult to handle/manage. This study investigates the impact of the first and second waves of COVID-19 in Nigeria, West Africa. The data used is for the 36 states of Nigeria archived at the National Centre for Disease Control from February 2020 to April 2021. Results from the study reveal that the highest number of COVID-19 cases during the first/second wave was recorded at Lagos (23,238/34,616), followed by the Federal Capital Territory (FCT) (6,770/12,911) and alternates between Plateau (3,858/5,170) and Kaduna (3,064/5,908). Similarly, the highest number of deaths (during the first/second wave) was also recorded in Lagos (220/219), followed by Edo (112/73), and then FCT (83/81). The Case Fatality Ratio (CFR) was observed to be higher mostly in northern Nigeria during the first wave and the southeast during the second wave of the pandemic. On the average, the number of cases/deaths recorded during the second wave was higher than those of the first wave, but a decrease in the CFR values was observed during the second wave. Higher values of COVID-19 cases/death were mostly recorded in Nigeria during; maximum relative humidity (RH) (>70%) with minimum Temperatures (<25°C), Low temperatures, and low RH which is mostly observed during the cold/dusty periods.
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Affiliation(s)
- Benjamin Wisdom Joshua
- Department of PhysicsKebbi State University of Science and Technology AlieroKauraNigeria
- Physics UnitDepartment of Physical and Natural SciencesUniversity of the GambiaSerrekundaNigeria
| | - Ibiyinka Fuwape
- Department of PhysicsMichael and Cecilia Ibru UniversityEriem FieldsNigeria
- Department of PhysicsFederal University of Technology AkureGagaNigeria
| | - Babatunde Rabiu
- African Regional Centre for Space Science and Technology Education ‐ EnglishIle‐IfeNigeria
- Atmospheric & Space Weather Research LaboratoryARCSSTE‐ENASRDAOsun State UniversityOsogboNigeria
| | - Evanilton E. S. Pires
- Centro de Estudos e Pesquisa do TundavalaEngineering DepartmentISPTundavalaLubangoAngola
| | | | | | - Oluwayomi Funmilola Awe
- Atmospheric & Space Weather Research LaboratoryARCSSTE‐ENASRDAOsun State UniversityOsogboNigeria
| | | | - Samuel Ogunjo
- Department of PhysicsFederal University of Technology AkureGagaNigeria
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Singh BP, Sohrab SS, Athar M, Alandijany TA, Kumari S, Nair A, Kumari S, Mehra K, Chowdhary K, Rahman S, Azhar EI. Substantial Changes in Selected Volatile Organic Compounds (VOCs) and Associations with Health Risk Assessments in Industrial Areas during the COVID-19 Pandemic. TOXICS 2023; 11:165. [PMID: 36851040 PMCID: PMC9963041 DOI: 10.3390/toxics11020165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 02/01/2023] [Accepted: 02/06/2023] [Indexed: 06/18/2023]
Abstract
During the COVID-19 pandemic, governments in many countries worldwide, including India, imposed several restriction measures, including lockdowns, to prevent the spread of the infection. COVID-19 lockdowns led to a reduction in gaseous and particulate pollutants in ambient air. In the present study, we investigated the substantial changes in selected volatile organic compounds (VOCs) after the outbreak of the coronavirus pandemic and associations with health risk assessments in industrial areas. VOC data from 1 January 2019 to 31 December 2021 were collected from the Central Pollution Control Board (CPCB) website, to identify percentage changes in VOC levels before, during, and after COVID-19. The mean TVOC levels at all monitoring stations were 47.22 ± 30.15, 37.19 ± 37.19, and 32.81 ± 32.81 µg/m3 for 2019, 2020, and 2021, respectively. As a result, the TVOC levels gradually declined in consecutive years due to the pandemic in India. The mean TVOC levels at all monitoring stations declined from 9 to 61% during the pandemic period as compared with the pre-pandemic period. In the current study, the T/B ratio values ranged from 2.16 (PG) to 26.38 (NL), which indicated that the major pollutant contributors were traffic and non-traffic sources during the pre-pandemic period. The present findings indicated that TVOC levels had positive but low correlations with SR, BP, RF, and WD, with correlation coefficients (r) of 0.034, 0.118, 0.012, and 0.007, respectively, whereas negative correlations were observed with AT and WS, with correlation coefficients (r) of -0.168 and -0.150, respectively. The lifetime cancer risk (LCR) value for benzene was reported to be higher in children, followed by females and males, for the pre-pandemic, pandemic, and post-pandemic periods. A nationwide scale-up of this study's findings might be useful in formulating future air pollution reduction policies associated with a reduction in health risk factors. Furthermore, the present study provides baseline data for future studies on the impacts of anthropogenic activities on the air quality of a region.
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Affiliation(s)
- Bhupendra Pratap Singh
- Department of Environmental Studies, Deshbadhu College, University of Delhi, New Delhi 110019, India
- Delhi School of Climate Change and Sustainability (Institute of Eminence), University of Delhi, New Delhi 110007, India
| | - Sayed Sartaj Sohrab
- Special Infectious Agents Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Mohammad Athar
- Science and Technology Unit, Umm Al-Qura University, Makkah 21955, Saudi Arabia
- Department of Medical Genetics, Faculty of Medicine, Umm Al-Qura University, Makkah 21955, Saudi Arabia
| | - Thamir A. Alandijany
- Special Infectious Agents Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Saumya Kumari
- Department of Zoology, Deshbandhu College, University of Delhi, New Delhi 110019, India
| | - Arathi Nair
- Department of Zoology, Deshbandhu College, University of Delhi, New Delhi 110019, India
| | - Sweety Kumari
- Department of Zoology, Deshbandhu College, University of Delhi, New Delhi 110019, India
| | - Kriti Mehra
- Department of Life Science, Deshbadhu College, University of Delhi, New Delhi 110019, India
| | - Khyati Chowdhary
- Department of Life Science, Deshbadhu College, University of Delhi, New Delhi 110019, India
| | - Shakilur Rahman
- Department of Medical Elementology and Toxicology, School of Chemical and Life Sciences, Jamia Hamdard, New Delhi 110019, India
| | - Esam Ibraheem Azhar
- Special Infectious Agents Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia
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Kumar P, Aishwarya, Srivastava PK, Pandey MK, Anand A, Biswas JK, Drews M, Dobriyal M, Singh RK, De la Sen M, Singh SS, Pandey AK, Kumar M, Rani M. Nitrogen dioxide as proxy indicator of air pollution from fossil fuel burning in New Delhi during lockdown phases of COVID-19 pandemic period: impact on weather as revealed by Sentinel-5 precursor (5p) spectrometer sensor. ENVIRONMENT, DEVELOPMENT AND SUSTAINABILITY 2023:1-12. [PMID: 36785714 PMCID: PMC9907871 DOI: 10.1007/s10668-023-02977-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 01/22/2023] [Indexed: 06/18/2023]
Abstract
There has been a long-lasting impact of the lockdown imposed due to COVID-19 on several fronts. One such front is climate which has seen several implications. The consequences of climate change owing to this lockdown need to be explored taking into consideration various climatic indicators. Further impact on a local and global level would help the policymakers in drafting effective rules for handling challenges of climate change. For in-depth understanding, a temporal study is being conducted in a phased manner in the New Delhi region taking NO2 concentration and utilizing statistical methods to elaborate the quality of air during the lockdown and compared with a pre-lockdown period. In situ mean values of the NO2 concentration were taken for four different dates, viz. 4th February, 4th March, 4th April, and 25th April 2020. These concentrations were then compared with the Sentinel (5p) data across 36 locations in New Delhi which are found to be promising. The results indicated that the air quality has been improved maximum in Eastern Delhi and the NO2 concentrations were reduced by one-fourth than the pre-lockdown period, and thus, reduced activities due to lockdown have had a significant impact. The result also indicates the preciseness of Sentinel (5p) for NO2 concentrations.
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Affiliation(s)
- Pavan Kumar
- College of Horticulture and Forestry, Rani Lakshmi Bai Central Agricultural University, Jhansi, 284003 India
| | - Aishwarya
- College of Agriculture, Rani Lakshmi Bai Central Agricultural University, Jhansi, 284003 India
| | - Prashant Kumar Srivastava
- Remote Sensing Laboratory, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, Uttar Pradesh 221005 India
| | - Manish Kumar Pandey
- Remote Sensing Laboratory, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, Uttar Pradesh 221005 India
- Centre for Quantitative Economics and Data Science, Birla Institute of Technology, Mesra, Jharkhand Ranchi, India
| | - Akash Anand
- Remote Sensing Laboratory, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, Uttar Pradesh 221005 India
| | - Jayanta Kumar Biswas
- Department of Ecological Studies, International Centre for Ecological Engineering, University of Kalyani West Bengal, Kalyani, India
| | - Martin Drews
- Department of Technology, Management and Economics, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
| | - Manmohan Dobriyal
- College of Horticulture and Forestry, Rani Lakshmi Bai Central Agricultural University, Jhansi, 284003 India
| | - Ram Kumar Singh
- Department of Natural Resources, TERI School of Advanced Studies, New Delhi, 110070 India
| | - Manuel De la Sen
- Department of Electricity and Electronics, Institute of Research and Development of Processes IIDP, University of the Basque Country, Campus of Leioa, PO Box 48940, Leioa, Bizkaia Spain
| | - Sati Shankar Singh
- Extension Education, Rani Lakshmi Bai Central Agricultural University, Jhansi, 284003 India
| | - Ajai Kumar Pandey
- College of Horticulture and Forestry, Rani Lakshmi Bai Central Agricultural University, Jhansi, 284003 India
| | - Manoj Kumar
- GIS Centre, Forest Research Institute (FRI), PO: New Forest, Dehradun, 248006 India
| | - Meenu Rani
- Department of Geography, Kumaun University, Nainital, Uttarakhand India
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Jeyananthan P. Role of different types of RNA molecules in the severity prediction of SARS-CoV-2 patients. Pathol Res Pract 2023; 242:154311. [PMID: 36657221 PMCID: PMC9840815 DOI: 10.1016/j.prp.2023.154311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 01/11/2023] [Accepted: 01/14/2023] [Indexed: 01/16/2023]
Abstract
SARS-CoV-2 pandemic is the current threat of the world with enormous number of deceases. As most of the countries have constraints on resources, particularly for intensive care and oxygen, severity prediction with high accuracy is crucial. This prediction will help the medical society in the selection of patients with the need for these constrained resources. Literature shows that using clinical data in this study is the common trend and molecular data is rarely utilized in this prediction. As molecular data carry more disease related information, in this study, three different types of RNA molecules ( lncRNA, miRNA and mRNA) of SARS-COV-2 patients are used to predict the severity stage and treatment stage of those patients. Using seven different machine learning algorithms along with several feature selection techniques shows that in both phenotypes, feature importance selected features provides the best accuracy along with random forest classifier. Further to this, it shows that in the severity stage prediction miRNA and lncRNA give the best performance, and lncRNA data gives the best in treatment stage prediction. As most of the studies related to molecular data uses mRNA data, this is an interesting finding.
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РОЗРОБКА ОБЛАДНАННЯ ДЛЯ ЗНЕЗАРАЖЕННЯ ПОВІТРЯ В СИСТЕМАХ ВЕНТИЛЯЦІЇ ТА КОНДИЦІОНУВАННЯ ГРОМАДСЬКИХ БУДІВЕЛЬ МЕТОДАМИ ФОТОКАТАЛІЗУ Й ПЛАЗМОХІМІЇ. SCIENCE AND INNOVATION 2023. [DOI: 10.15407/scine19.01.071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Вступ. Сезонні хвилі спалаху ГРВІ, зокрема й COVID-19, спричиняють потребу розробки комплексу заходів щодостворення безпечних для здоров’я умов перебування в місцях скупчення людей.Проблематика. Наявні припливно-витяжні системи централізованого опалення, вентиляції і кондиціювання повітря (ОВіК) не лише не захищають від зараження, а й слугують джерелом накопичення та поширення патогенних мікроорганізмів. Пошук ефективних способів очищення повітря у місцях масового скупчення людей як складової протиепідемічних заходів є актуальним завданням.Мета. Розробка та створення обладнання для очищення і знезаражування повітря від аеродисперсної патогенноїмікрофлори в системах ОВіК, яке може вмонтовуватися в централізовані системи вентиляції будівель без їхньої реконструкції та зміни технологічних параметрів.Матеріали й методи. Комплекс фізико-хімічних методів, які охоплюють аналітичне та експериментальне дослідження з використанням теорії електрогазодинаміки дисперсних систем та залученням методів растрової скануючої мікроскопії, методів порівняння однотипних якісних показників проб і вихідних зразків.Результати. Для дослідження ефективності як окремих плазмохімічних і фотокаталітичних модулів, так і установки вцілому при режимах роботи, що моделюють умови експлуатації систем централізованої вентиляції, створено експериментальний стенд. Визначено оптимальні технологічні параметри процесів для підвищення ефективності знезараження й очищення повітря в ОВіК системах методами плазмофотокаталізу. Запропоновано технічні рішення для підвищення енергоефективності дослідно-експериментальної установки комплексного очищення і знезараження повітря від широкого класу забруднювачів повітря в системах припливно-витяжної вентиляції будівель.Висновки. Знезаражування повітря методом комбінованого плазмофотокаталітичного впливу на повітряний потік із системою каталітично-термічного розкладання надлишкового озону забезпечує ефективне очищення від забруднювачів та дозволяє знизити ступінь мікробіологічної контамінації повітря до безпечного рівня.
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Burbank AJ. Risk Factors for Respiratory Viral Infections: A Spotlight on Climate Change and Air Pollution. J Asthma Allergy 2023; 16:183-194. [PMID: 36721739 PMCID: PMC9884560 DOI: 10.2147/jaa.s364845] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 01/20/2023] [Indexed: 01/26/2023] Open
Abstract
Climate change has both direct and indirect effects on human health, and some populations are more vulnerable to these effects than others. Viral respiratory infections are most common illnesses in humans, with estimated 17 billion incident infections globally in 2019. Anthropogenic drivers of climate change, chiefly the emission of greenhouse gases and toxic pollutants from burning of fossil fuels, and the consequential changes in temperature, precipitation, and frequency of extreme weather events have been linked with increased susceptibility to viral respiratory infections. Air pollutants like nitrogen dioxide, particulate matter, diesel exhaust particles, and ozone have been shown to impact susceptibility and immune responses to viral infections through various mechanisms, including exaggerated or impaired innate and adaptive immune responses, disruption of the airway epithelial barrier, altered cell surface receptor expression, and impaired cytotoxic function. An estimated 90% of the world's population is exposed to air pollution, making this a topic with high relevance to human health. This review summarizes the available epidemiologic and experimental evidence for an association between climate change, air pollution, and viral respiratory infection.
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Affiliation(s)
- Allison J Burbank
- Division of Pediatric Allergy and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA,Correspondence: Allison J Burbank, 5008B Mary Ellen Jones Building, 116 Manning Dr, CB#7231, Chapel Hill, NC, 27599, USA, Tel +1 919 962 5136, Fax +1 919 962 4421, Email
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Bonilla JA, Lopez-Feldman A, Pereda PC, Rivera NM, Ruiz-Tagle JC. Association between long-term air pollution exposure and COVID-19 mortality in Latin America. PLoS One 2023; 18:e0280355. [PMID: 36649353 PMCID: PMC9844883 DOI: 10.1371/journal.pone.0280355] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 12/27/2022] [Indexed: 01/18/2023] Open
Abstract
Recent studies have shown a relationship between air pollution and increased vulnerability and mortality due to COVID-19. Most of these studies have looked at developed countries. This study examines the relationship between long-term exposure to air pollution and COVID-19-related deaths in four countries of Latin America that have been highly affected by the pandemic: Brazil, Chile, Colombia, and Mexico. Our results suggest that an increase in long-term exposure of 1 μg/m3 of fine particles is associated with a 2.7 percent increase in the COVID-19 mortality rate. This relationship is found primarily in municipalities of metropolitan areas, where urban air pollution sources dominate, and air quality guidelines are usually exceeded. By focusing the analysis on Latin America, we provide a first glimpse on the role of air pollution as a risk factor for COVID-19 mortality within a context characterized by weak environmental institutions, limited health care capacity and high levels of inequality.
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Affiliation(s)
- Jorge A. Bonilla
- Department of Economics, Universidad de Los Andes, Bogota, Colombia
| | - Alejandro Lopez-Feldman
- Environment for Development, University of Gothenburg, Göteborg, Sweden
- Department of Economics, Centro de Investigacion y Docencia Economicas, Mexico City, Mexico
| | - Paula C. Pereda
- Department of Economics, University of São Paulo, São Paulo, Brazil
| | | | - J. Cristobal Ruiz-Tagle
- Department of Geography & Environment, London School of Economics and Political Science, London, United Kingdom
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Gu Z, Han J, Zhang L, Wang H, Luo X, Meng X, Zhang Y, Niu X, Lan Y, Wu S, Cao J, Lichtfouse E. Unanswered questions on the airborne transmission of COVID-19. ENVIRONMENTAL CHEMISTRY LETTERS 2023; 21:725-739. [PMID: 36628267 PMCID: PMC9816530 DOI: 10.1007/s10311-022-01557-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 12/20/2022] [Indexed: 06/17/2023]
Abstract
Policies and measures to control pandemics are often failing. While biological factors controlling transmission are usually well explored, little is known about the environmental drivers of transmission and infection. For instance, respiratory droplets and aerosol particles are crucial vectors for the airborne transmission of the severe acute respiratory syndrome coronavirus 2, the causation agent of the coronavirus 2019 pandemic (COVID-19). Once expectorated, respiratory droplets interact with atmospheric particulates that influence the viability and transmission of the novel coronavirus, yet there is little knowledge on this process or its consequences on virus transmission and infection. Here we review the effects of atmospheric particulate properties, vortex zones, and air pollution on virus survivability and transmission. We found that particle size, chemical constituents, electrostatic charges, and the moisture content of airborne particles can have notable effects on virus transmission, with higher survival generally associated with larger particles, yet some viruses are better preserved on small particles. Some chemical constituents and surface-adsorbed chemical species may damage peptide bonds in viral proteins and impair virus stability. Electrostatic charges and water content of atmospheric particulates may affect the adherence of virion particles and possibly their viability. In addition, vortex zones and human thermal plumes are major environmental factors altering the aerodynamics of buoyant particles in air, which can strongly influence the transport of airborne particles and the transmission of associated viruses. Insights into these factors may provide explanations for the widely observed positive correlations between COVID-19 infection and mortality with air pollution, of which particulate matter is a common constituent that may have a central role in the airborne transmission of the novel coronavirus. Supplementary Information The online version contains supplementary material available at 10.1007/s10311-022-01557-z.
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Affiliation(s)
- Zhaolin Gu
- School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an, 710049 People’s Republic of China
| | - Jie Han
- School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an, 710049 People’s Republic of China
| | - Liyuan Zhang
- School of Water and Environment, Chang’an University, Xi’an, 710064 People’s Republic of China
| | - Hongliang Wang
- Health Science Center, Xi’an Jiaotong University, Xi’an, 710049 People’s Republic of China
| | - Xilian Luo
- School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an, 710049 People’s Republic of China
| | - Xiangzhao Meng
- School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an, 710049 People’s Republic of China
| | - Yue Zhang
- School of Architecture, Chang’an University, Xi’an, 710064 People’s Republic of China
| | - Xinyi Niu
- School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an, 710049 People’s Republic of China
| | - Yang Lan
- School of Public Health, Xi’an Jiaotong University, Xi’an, 710049 People’s Republic of China
| | - Shaowei Wu
- School of Public Health, Xi’an Jiaotong University, Xi’an, 710049 People’s Republic of China
| | - Junji Cao
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029 People’s Republic of China
| | - Eric Lichtfouse
- State Key Laboratory of Multiphase Flow in Power Engineering, Xi’an Jiaotong University, Xi’an, 710049 Shaanxi People’s Republic of China
- CNRS, IRD, INRAE, CEREGE, Aix-Marseille University, 13100, Aix-en-Provence, France
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Liu Z, Liang Q, Liao H, Yang W, Lu C. Effects of short-term and long-term exposure to ambient air pollution and temperature on long recovery duration in COVID-19 patients. ENVIRONMENTAL RESEARCH 2023; 216:114781. [PMID: 36375498 PMCID: PMC9650677 DOI: 10.1016/j.envres.2022.114781] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 10/24/2022] [Accepted: 11/08/2022] [Indexed: 05/06/2023]
Abstract
BACKGROUND The novel coronavirus disease 2019 (COVID-19) has spread rapidly around the world since December 8, 2019. However, the key factors affecting the duration of recovery from COVID-19 remain unclear. OBJECTIVE To investigate the associations of long recovery duration of COVID-19 patients with ambient air pollution, temperature, and diurnal temperature range (DTR) exposure. METHODS A total of 427 confirmed cases in Changsha during the first wave of the epidemic in January 2020 were selected. We used inverse distance weighting (IDW) method to estimate personal exposure to seven ambient air pollutants (PM2.5, PM2.5-10, PM10, SO2, NO2, CO, and O3) at each subject's home address. Meteorological conditions included temperature and DTR. Multiple logistic regression model was used to investigate the relationship of air pollution exposure during short-term (past week and past month) and long-term (past three months) with recovery duration among COVID-19 patients. RESULTS We found that long recovery duration among COVID-19 patients was positively associated with short-term exposure to CO during past week with OR (95% CI) = 1.42 (1.01-2.00) and PM2.5, NO2, and CO during past month with ORs (95% CI) = 2.00 (1.30-3.07) and 1.95 (1.30-2.93), and was negatively related with short-term exposure to O3 during past week and past month with ORs (95% CI) = 0.68 (0.46-0.99) and 0.41 (0.27-0.62), respectively. No association was observed for long-term exposure to air pollution during past three months. Furthermore, increased temperature during past three months elevated risk of long recovery duration in VOCID-19 patients, while DTR exposure during past week and past month decreased the risk. Male and younger patients were more susceptible to the effect of air pollution on long recovery duration, while female and older patients were more affected by exposure to temperature and DTR. CONCLUSION Our findings suggest that both TRAP exposure and temperature indicators play important roles in prolonged recovery among COVID-19 patients, especially for the sensitive populations, which provide potential strategies for effective reduction and early prevention of long recovery duration of COVID-19.
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Affiliation(s)
- Zijing Liu
- XiangYa School of Public Health, Central South University, Changsha, 410078, Hunan, China
| | - Qi Liang
- Department of Radiology, The Third XiangYa Hospital, Central South University, Changsha, 410083, China
| | - Hongsen Liao
- XiangYa School of Public Health, Central South University, Changsha, 410078, Hunan, China
| | - Wenhui Yang
- XiangYa School of Public Health, Central South University, Changsha, 410078, Hunan, China
| | - Chan Lu
- XiangYa School of Public Health, Central South University, Changsha, 410078, Hunan, China.
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Kumar S, Singh NA, Jain V, Subramaneyaan M, Kumar P. Coronavirus Disease (COVID-19) Possible Transmission Routes and Alleviation Strategies. INTERNATIONAL JOURNAL OF PHARMACEUTICAL RESEARCH AND ALLIED SCIENCES 2023. [DOI: 10.51847/7owk1mtle1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/08/2023]
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Tumbas M, Markovic S, Salom I, Djordjevic M. A large-scale machine learning study of sociodemographic factors contributing to COVID-19 severity. Front Big Data 2023; 6:1038283. [PMID: 37034433 PMCID: PMC10080051 DOI: 10.3389/fdata.2023.1038283] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 02/27/2023] [Indexed: 04/11/2023] Open
Abstract
Understanding sociodemographic factors behind COVID-19 severity relates to significant methodological difficulties, such as differences in testing policies and epidemics phase, as well as a large number of predictors that can potentially contribute to severity. To account for these difficulties, we assemble 115 predictors for more than 3,000 US counties and employ a well-defined COVID-19 severity measure derived from epidemiological dynamics modeling. We then use a number of advanced feature selection techniques from machine learning to determine which of these predictors significantly impact the disease severity. We obtain a surprisingly simple result, where only two variables are clearly and robustly selected-population density and proportion of African Americans. Possible causes behind this result are discussed. We argue that the approach may be useful whenever significant determinants of disease progression over diverse geographic regions should be selected from a large number of potentially important factors.
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Affiliation(s)
- Marko Tumbas
- Quantitative Biology Group, Faculty of Biology, University of Belgrade, Belgrade, Serbia
| | - Sofija Markovic
- Quantitative Biology Group, Faculty of Biology, University of Belgrade, Belgrade, Serbia
| | - Igor Salom
- Institute of Physics Belgrade, National Institute of the Republic of Serbia, University of Belgrade, Belgrade, Serbia
| | - Marko Djordjevic
- Quantitative Biology Group, Faculty of Biology, University of Belgrade, Belgrade, Serbia
- *Correspondence: Marko Djordjevic
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Antonietti R, Falbo P, Fontini F. The Wealth of Nations and the First Wave of COVID-19 Diffusion. ITALIAN ECONOMIC JOURNAL 2023; 9. [PMCID: PMC8591320 DOI: 10.1007/s40797-021-00174-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
A large debate has risen about the hypothesis that “COVID-19 is a disease for the rich ones” suggesting that both its diffusion and mortality rates are somehow linked with economic wealth. In this study we observe a sample of 138 countries during the first wave contagion period, namely the 5 weeks between 24 March and 21 April 2020. Using different data sources, our estimates show that both the early infection and the mortality rates of COVID-19 are higher in wealthier countries, more precisely in countries with a higher GDP per capita. As an explanation of this finding, we also find that both mortality and infection rates increase with a higher share of elderly population and with the international flows of imported goods or tourists. However, the death rate decreases in countries with higher endowments of health facilities. We also demonstrate that these results are robust to simultaneity, unobserved heterogeneity, the possible poor quality of the data on COVID-19 deaths, and the extension of the time frame.
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Affiliation(s)
- Roberto Antonietti
- Marco Fanno” Department of Economics and Management, University of Padova, Padua, Italy
| | - Paolo Falbo
- Department of Economics and Management, University of Brescia, Brescia, Italy
| | - Fulvio Fontini
- Marco Fanno” Department of Economics and Management, University of Padova, Padua, Italy
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Kostoff RN, Briggs MB, Kanduc D, Dewanjee S, Kandimalla R, Shoenfeld Y, Porter AL, Tsatsakis A. Modifiable contributing factors to COVID-19: A comprehensive review. Food Chem Toxicol 2023; 171:113511. [PMID: 36450305 PMCID: PMC9701571 DOI: 10.1016/j.fct.2022.113511] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 11/01/2022] [Accepted: 11/03/2022] [Indexed: 11/29/2022]
Abstract
The devastating complications of coronavirus disease 2019 (COVID-19) result from an individual's dysfunctional immune response following the initial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Multiple toxic stressors and behaviors contribute to underlying immune system dysfunction. SARS-CoV-2 exploits the dysfunctional immune system to trigger a chain of events ultimately leading to COVID-19. The current study identifies eighty immune system dysfunction-enabling toxic stressors and behaviors (hereafter called modifiable contributing factors (CFs)) that also link directly to COVID-19. Each CF is assigned to one of the five categories in the CF taxonomy shown in Section 3.3.: Lifestyle (e.g., diet, substance abuse); Iatrogenic (e.g., drugs, surgery); Biotoxins (e.g., micro-organisms, mycotoxins); Occupational/Environmental (e.g., heavy metals, pesticides); Psychosocial/Socioeconomic (e.g., chronic stress, lower education). The current study shows how each modifiable factor contributes to decreased immune system capability, increased inflammation and coagulation, and increased neural damage and neurodegeneration. It is unclear how real progress can be made in combatting COVID-19 and other similar diseases caused by viral variants without addressing and eliminating these modifiable CFs.
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Affiliation(s)
- Ronald Neil Kostoff
- Independent Consultant, Gainesville, VA, 20155, USA,Corresponding author. Independent Consultant, 13500 Tallyrand Way, Gainesville, VA, 20155, USA
| | | | - Darja Kanduc
- Dept. of Biosciences, Biotechnologies, and Biopharmaceutics, University of Bari, Via Orabona 4, Bari, 70125, Italy
| | - Saikat Dewanjee
- Advanced Pharmacognosy Research Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700032, India
| | - Ramesh Kandimalla
- Applied Biology, CSIR-Indian Institute of Chemical Technology, Uppal Road, Tarnaka, Hyderabad, 500007, Telangana, India
| | - Yehuda Shoenfeld
- Zabludowicz Center for Autoimmune Diseases, Sheba Medical Center, Tel-Hashomer, 5265601, Israel
| | - Alan L. Porter
- School of Public Policy, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Aristidis Tsatsakis
- Department of Forensic Sciences and Toxicology, Faculty of Medicine, University of Crete, 71003, Heraklion, Greece
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Alaniz AJ, Carvajal MA, Carvajal JG, Vergara PM. Effects of air pollution and weather on the initial COVID-19 outbreaks in United States, Italy, Spain, and China: A comparative study. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2023; 43:8-18. [PMID: 36509703 PMCID: PMC9877606 DOI: 10.1111/risa.14080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 08/03/2022] [Accepted: 11/05/2022] [Indexed: 06/17/2023]
Abstract
Contrasting effects have been identified in association of weather (temperature and humidity) and pollutant gases with COVID-19 infection, which could be derived from the influence of lockdowns and season change. The influence of pollutant gases and climate during the initial phases of the pandemic, before the closures and the change of season in the northern hemisphere, is unknown. Here, we used a spatial-temporal Bayesian zero-inflated-Poisson model to test for short-term associations of weather and pollutant gases with the relative risk of COVID-19 disease in China (first outbreak) and the countries with more cases during the initial pandemic (the United States, Spain and Italy), considering also the effects of season and lockdown. We found contrasting association between pollutant gases and COVID-19 risk in the United States, Italy, and Spain, while in China it was negatively associated (except for SO2 ). COVID-19 risk was positively associated with specific humidity in all countries, while temperature presented a negative effect. Our findings showed that short-term associations of air pollutants with COVID-19 infection vary strongly between countries, while generalized effects of temperature (negative) and humidity (positive) with COVID-19 was found. Our results show novel information about the influence of pollution and weather on the initial outbreaks, which contribute to unravel the mechanisms during the beginning of the pandemic.
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Affiliation(s)
- Alberto J. Alaniz
- Departamento de Ingeniería Geoespacial y Ambiental, Facultad de IngenieríaUniversidad de Santiago de ChileSantiagoChile
- Facultad de Ciencias BiológicasPontificia Universidad Católica de ChileSantiagoChile
- Departamento de Gestión Agraria, Facultad TecnológicaUniversidad de Santiago de ChileSantiagoChile
- Centro de Estudios en Ecología Espacial y Medio AmbienteEcogeografíaSantiagoChile
| | - Mario A. Carvajal
- Facultad de Ciencias BiológicasPontificia Universidad Católica de ChileSantiagoChile
- Departamento de Gestión Agraria, Facultad TecnológicaUniversidad de Santiago de ChileSantiagoChile
| | - Jorge G. Carvajal
- Departamento de Gestión Agraria, Facultad TecnológicaUniversidad de Santiago de ChileSantiagoChile
- Centro de Estudios en Ecología Espacial y Medio AmbienteEcogeografíaSantiagoChile
| | - Pablo M. Vergara
- Departamento de Gestión Agraria, Facultad TecnológicaUniversidad de Santiago de ChileSantiagoChile
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Rittweger J, Gilardi L, Baltruweit M, Dally S, Erbertseder T, Mittag U, Naeem M, Schmid M, Schmitz MT, Wüst S, Dech S, Jordan J, Antoni T, Bittner M. Temperature and particulate matter as environmental factors associated with seasonality of influenza incidence - an approach using Earth observation-based modeling in a health insurance cohort study from Baden-Württemberg (Germany). Environ Health 2022; 21:131. [PMID: 36527040 PMCID: PMC9755806 DOI: 10.1186/s12940-022-00927-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 10/21/2022] [Indexed: 05/04/2023]
Abstract
BACKGROUND Influenza seasonality has been frequently studied, but its mechanisms are not clear. Urban in-situ studies have linked influenza to meteorological or pollutant stressors. Few studies have investigated rural and less polluted areas in temperate climate zones. OBJECTIVES We examined influences of medium-term residential exposure to fine particulate matter (PM2.5), NO2, SO2, air temperature and precipitation on influenza incidence. METHODS To obtain complete spatial coverage of Baden-Württemberg, we modeled environmental exposure from data of the Copernicus Atmosphere Monitoring Service and of the Copernicus Climate Change Service. We computed spatiotemporal aggregates to reflect quarterly mean values at post-code level. Moreover, we prepared health insurance data to yield influenza incidence between January 2010 and December 2018. We used generalized additive models, with Gaussian Markov random field smoothers for spatial input, whilst using or not using quarter as temporal input. RESULTS In the 3.85 million cohort, 513,404 influenza cases occurred over the 9-year period, with 53.6% occurring in quarter 1 (January to March), and 10.2%, 9.4% and 26.8% in quarters 2, 3 and 4, respectively. Statistical modeling yielded highly significant effects of air temperature, precipitation, PM2.5 and NO2. Computation of stressor-specific gains revealed up to 3499 infections per 100,000 AOK clients per year that are attributable to lowering ambient mean air temperature from 18.71 °C to 2.01 °C. Stressor specific gains were also substantial for fine particulate matter, yielding up to 502 attributable infections per 100,000 clients per year for an increase from 7.49 μg/m3 to 15.98 μg/m3. CONCLUSIONS Whilst strong statistical association of temperature with other stressors makes it difficult to distinguish between direct and mediated temperature effects, results confirm genuine effects by fine particulate matter on influenza infections for both rural and urban areas in a temperate climate. Future studies should attempt to further establish the mediating mechanisms to inform public health policies.
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Affiliation(s)
- Jörn Rittweger
- Institute of Aerospace Medicine, German Aerospace Center (DLR), 51147, Cologne, Germany.
- Department of Pediatrics and Adolescent Medicine, University Hospital Cologne, Cologne, Germany.
| | - Lorenza Gilardi
- German Remote Sensing Data Center, German Aerospace Center (DLR), Oberpfaffenhofen, Germany
| | - Maxana Baltruweit
- Allgemeine Ortskrankenkasse Baden-Württemberg (AOK-BW), Stuttgart, Germany
| | - Simon Dally
- Allgemeine Ortskrankenkasse Baden-Württemberg (AOK-BW), Stuttgart, Germany
| | - Thilo Erbertseder
- German Remote Sensing Data Center, German Aerospace Center (DLR), Oberpfaffenhofen, Germany
| | - Uwe Mittag
- Institute of Aerospace Medicine, German Aerospace Center (DLR), 51147, Cologne, Germany
| | - Muhammad Naeem
- Kohat University of Science and Technology, Kohat, Pakistan
| | - Matthias Schmid
- Institute of Medical Biometry, Informatics and Epidemiology, University Hospital Bonn, Bonn, Germany
| | - Marie-Therese Schmitz
- Institute of Aerospace Medicine, German Aerospace Center (DLR), 51147, Cologne, Germany
- Institute of Medical Biometry, Informatics and Epidemiology, University Hospital Bonn, Bonn, Germany
| | - Sabine Wüst
- German Remote Sensing Data Center, German Aerospace Center (DLR), Oberpfaffenhofen, Germany
| | - Stefan Dech
- German Remote Sensing Data Center, German Aerospace Center (DLR), Oberpfaffenhofen, Germany
| | - Jens Jordan
- Institute of Aerospace Medicine, German Aerospace Center (DLR), 51147, Cologne, Germany
- Medical Faculty, University of Cologne, Cologne, Germany
| | - Tobias Antoni
- Allgemeine Ortskrankenkasse Baden-Württemberg (AOK-BW), Stuttgart, Germany
| | - Michael Bittner
- German Remote Sensing Data Center, German Aerospace Center (DLR), Oberpfaffenhofen, Germany
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Cao Z, Cai X, Feltrin AC, Feng P, Kaiser A, Akhtar F. Calcium/strontium chloride impregnated zeolite A and X granules as optimized ammonia sorbents. RSC Adv 2022; 12:34910-34917. [PMID: 36540240 PMCID: PMC9727750 DOI: 10.1039/d2ra02981b] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 11/19/2022] [Indexed: 08/15/2023] Open
Abstract
Calcium chloride (CaCl2) impregnated zeolite A and strontium chloride (SrCl2) impregnated zeolite A and X composite granules were evaluated as ammonia sorbents for automotive selective catalytic reduction systems. The SrCl2-impregnated zeolite A granules showed a 14% increase in ammonia uptake capacity (8.39 mmol g-1) compared to zeolite A granules (7.38 mmol g-1). Furthermore, composite granules showed 243% faster kinetics of ammonia sorption (0.24 mmol g-1 min-1) compared to SrCl2 (0.07 mmol g-1 min-1) in the first 20 min. The composite CaCl2/SrCl2 impregnated zeolite A granules combined the advantages of the zeolites and CaCl2/SrCl2, where the rapid physisorption from zeolites can reduce the ammonia loading and release time, and chemisorption from the CaCl2/SrCl2 offers abundant ammonia capacity. Moreover, by optimizing the content of SrCl2 loading, the composite granules maintained the granular form with a crushing load of 17 N per granule after ammonia sorption-desorption cycles. Such structurally stable composite sorbents offer an opportunity for fast ammonia loading/release in automotive selective catalytic reduction systems.
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Affiliation(s)
- Zhejian Cao
- Division of Materials Science, Luleå University of Technology 971 87 Luleå Sweden
| | - Xiaoping Cai
- School of Materials Science and Physics, China University of Mining and Technology 221116 Xuzhou People's Republic of China
| | - Ana Carolina Feltrin
- Division of Materials Science, Luleå University of Technology 971 87 Luleå Sweden
| | - Peizhong Feng
- School of Materials Science and Physics, China University of Mining and Technology 221116 Xuzhou People's Republic of China
| | - Andreas Kaiser
- Department of Energy Conversion, Technical University of Denmark 2800 Kgs. Lyngby Denmark
| | - Farid Akhtar
- Division of Materials Science, Luleå University of Technology 971 87 Luleå Sweden
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STOIAN IM, PARVU S, NEAMTU A, CALOTA V, VOINOIU A, PISTOL A, CUCUIU R, MINCA DG. PM10 and NO2 Air Pollution and Evolution of COVID-19 Cases in Romania. MAEDICA 2022; 17:777-784. [PMID: 36818269 PMCID: PMC9923075 DOI: 10.26574/maedica.2022.17.4.777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Abstract
Objectives:Based on the correlation between air pollution and COVID-19 incidence/mortality already existing in the literature, we aimed to develop a study to investigate the link between the average level of PM10 (particulate matter 10 - particulate matter 10 microns in diameter) and NO2 (nitrogen dioxide) concentration over five years and the cumulative incidence of COVID-19 cases per 1000 people in Romania. Methods: To assess PM10 and NO2 exposure, we determined the average value of annual PM10 and NO2 concentration for each city over five years (2015-2019). For this purpose, the average of annual PM10 and NO2 concentrations collected from monitoring stations in selected cities was calculated. Then, the annual values over five years were averaged to finally obtain the average PM10 and NO2 concentration for each city. Data on the cumulative number of confirmed cases of COVID-19 up to the 28th of September 2020 were provided by the National Centre for Surveillance and Control of Communicable Diseases (CNSCBT) of the National Institute of Public Health (INSP). The study used the cumulative incidence/hour per 1000 population on 28.09.2020. Results:According to Law no. 104/2011, the annual permissible limit value of PM10 concentration of 40 μg/m³ was not exceeded in any of the 43 cities in our study. The average for all cities was 24.0±4.8 ìg/m³, with a minimum value of average PM10 concentration of 13.9 μg/m3 measured in Alba Iulia and a maximum value of 39.1 μg/m³ in Iasi. The regression model shows that, in Bucharest, 77.9% of the variation in case incidence is explained by the variation in PM10 concentration. In order to find the number of new cases that would correspond to a cumulative incidence of 0.166, taking as an example one of the districts with a population of 259,084, the above regression model shows that an increase in the average PM10 concentration by one unit is associated with 43 new cases. Conclusion:The study demonstrates that an exposure of the population to particulate matter in atmospheric air, at low values, below the permissible limit values but for a long time (the follow-up period in our study was five years, between 2015 and 2019), can have effects on the health status of the population, which becomes much more vulnerable to external agents, in our case pathogenic microorganisms (viruses).
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Affiliation(s)
- Irina Mihaela STOIAN
- “Carol Davila” University of Medicine and Pharmacy, Bucharest, Romania,National Institute of Public Health, Bucharest, Romania
| | - Simona PARVU
- “Carol Davila” University of Medicine and Pharmacy, Bucharest, Romania,National Institute of Public Health, Bucharest, Romania
| | - Andra NEAMTU
- National Institute of Public Health, Bucharest, Romania
| | | | | | - Adriana PISTOL
- “Carol Davila” University of Medicine and Pharmacy, Bucharest, Romania,National Institute of Public Health, Bucharest, Romania
| | - Radu CUCUIU
- National Institute of Public Health, Bucharest, Romania
| | - Dana Galieta MINCA
- “Carol Davila” University of Medicine and Pharmacy, Bucharest, Romania,National Institute of Public Health, Bucharest, Romania
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Paital B, Das K. Spike in pollution to ignite the bursting of COVID-19 second wave is more dangerous than spike of SAR-CoV-2 under environmental ignorance in long term: a review. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:85595-85611. [PMID: 34390474 PMCID: PMC8363867 DOI: 10.1007/s11356-021-15915-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 08/07/2021] [Indexed: 04/15/2023]
Abstract
Specific areas in many countries such as Italy, India, China, Brazil, Germany and the USA have witnessed that air pollution increases the risk of COVID-19 severity as particulate matters transmit the virus SARS-CoV-2 and causes high expression of ACE2, the receptor for spike protein of the virus, especially under exposure to NO2, SO2 and NOx emissions. Wastewater-based epidemiology of COVID-19 is also noticed in many countries such as the Netherlands, the USA, Paris, France, Australia, Spain, Italy, Switzerland China, India and Hungary. Soil is also found to be contaminated by the RNA of SARS-CoV-2. Activities including defecation and urination by infected people contribute to the source for soil contamination, while release of wastewater containing cough, urine and stool of infected people from hospitals and home isolation contributes to the source of SARS-CoV-2 RNA in both water and soil. Detection of the virus early before the outbreak of the disease supports this fact. Based on this information, spike in pollution is found to be more dangerous in long-term than the spike protein of SARS-CoV-2. It is because the later one may be controlled in future within months or few years by vaccination and with specific drugs, but the former one provides base for many diseases including the current and any future pandemics. Although such predictions and the positive effects of SARS-CoV-2 on environment was already forecasted after the first wave of COVID-19, the learnt lesson as spotlight was not considered as one of the measures for which 2nd wave has quickly hit the world.
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Grants
- ECR/2016/001984 Science and Engineering Research Board
- 1188/ST, Bhubaneswar, dated 01.03.17, ST- (Bio)-02/2017 Department of Biotechnology, DST, Govt. of Odisha, IN
- 36 Seed/2019/Philosophy-1, letter number 941/69/OSHEC/2019, dt 22.11.19 Department of Higher Education, Govt. of Odisha, IN
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Affiliation(s)
- Biswaranjan Paital
- Redox Regulation Laboratory, Department of Zoology, College of Basic Science and Humanities, Odisha University of Agriculture and Technology, Bhubaneswar, 751003, India.
| | - Kabita Das
- Department of Philosophy, Utkal University, Bhubaneswar, India
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Sharifi A. An overview and thematic analysis of research on cities and the COVID-19 pandemic: Toward just, resilient, and sustainable urban planning and design. iScience 2022; 25:105297. [PMID: 36246575 PMCID: PMC9540689 DOI: 10.1016/j.isci.2022.105297] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Revised: 07/11/2022] [Accepted: 09/28/2022] [Indexed: 12/14/2022] Open
Abstract
Since early 2020, researchers have made efforts to study various issues related to cities and the pandemic. Despite the wealth of research on this topic, there are only a few review articles that explore multiple issues related to it. This is partly because of the rapid pace of publications that makes systematic literature review challenging. To address this issue, in the present study, we rely on bibliometric analysis techniques to gain an overview of the knowledge structure and map key themes and trends of research on cities and the pandemic. Results of the analysis of 2,799 articles show that research mainly focuses on six broad themes: air quality, meteorological factors, built environment factors, transportation, socio-economic disparities, and smart cities, with the first three being dominant. Based on the findings, we discuss major lessons that can be learned from the pandemic and highlight key areas that need further research.
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Affiliation(s)
- Ayyoob Sharifi
- Hiroshima University, Graduate School of Humanities and Social Science, Higashi-Hiroshima, Hiroshima, Japan
- Network for Education and Research on Peace and Sustainability (NERPS)
- Center for Peaceful and Sustainable Futures (CEPEAS), The IDEC Institute, Hiroshima University
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48
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Santos A, Lucarevschi B, Cunha C, Ribeiro P, Cesar A, Nascimento L. Exposure to air pollution and hospitalization due to COVID-19 in São José dos Campos, Brazil. Braz J Med Biol Res 2022; 55:e12273. [PMID: 36383802 PMCID: PMC9668087 DOI: 10.1590/1414-431x2021e12273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 10/10/2022] [Indexed: 12/23/2022] Open
Abstract
The association between exposure to air pollutants and respiratory diseases is well known. This study aimed to identify the association between this exposure and hospitalizations for COVID-19 in São José dos Campos, SP, a medium-sized city, between April 2020 and April 2021. Hospitalization data, concerning code B34.2, was supplied by DATASUS, and data concerning pollutants and climate variables were supplied by CETESB. Cases were quantified by sex, age, length of hospital stay in days, and type of discharge, whether hospital discharge or death. The negative binomial regression model was chosen. Estimates were produced for the relative risk (RR) of significant exposure to pollutants (P≤0.05) with a 10 µg/m3 increase of pollutant, as well as for excess hospitalizations. There were 1873 hospitalizations, with a daily average of 4.7 (±3.8), ranging from zero to 21: 716 deaths (38.2%) were recorded, 1065 admissions were men, and women were less susceptible (OR=0.82). The average age of women was higher than that of men; in cases of death, men were older than women; discharged patients were younger. All the above variables were significant. The risk of ozone exposure was higher and more significant in Lag 2, and the risk of nitrogen dioxide exposure was high in Lag 3, which was the period of the highest increase in hospitalizations, at 11.3%. The findings of this study, the first conducted in Brazil, corroborate the results of studies conducted in other centers.
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Affiliation(s)
- A.O.R. Santos
- Departamento de Medicina, Universidade de Taubaté, Taubaté, SP, Brasil
| | - B.R. Lucarevschi
- Departamento de Medicina, Universidade de Taubaté, Taubaté, SP, Brasil
| | - C.J.D. Cunha
- Faculdade de Engenharia de Guaratinguetá, Universidade Estadual Paulista Júlio de Mesquita Filho, Guaratinguetá, SP, Brasil
| | - P.C. Ribeiro
- Faculdade de Engenharia de Guaratinguetá, Universidade Estadual Paulista Júlio de Mesquita Filho, Guaratinguetá, SP, Brasil
| | - A.C.G. Cesar
- Instituto Federal de Educação, Ciência e Tecnologia de São Paulo, Bragança Paulista, SP, Brasil
| | - L.F. Nascimento
- Faculdade de Engenharia de Guaratinguetá, Universidade Estadual Paulista Júlio de Mesquita Filho, Guaratinguetá, SP, Brasil,Programa de Pós-graduação em Ciências Ambientais, Universidade de Taubaté, Taubaté, SP, Brasil
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Haque MN, Sharif MS, Rudra RR, Mahi MM, Uddin MJ, Ellah RG. Analyzing the spatio-temporal directions of air pollutants for the initial wave of Covid-19 epidemic over Bangladesh: Application of satellite imageries and Google Earth Engine. REMOTE SENSING APPLICATIONS 2022; 28:100862. [PMID: 36349349 PMCID: PMC9633110 DOI: 10.1016/j.rsase.2022.100862] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 10/16/2022] [Accepted: 10/26/2022] [Indexed: 11/06/2022]
Abstract
One of the most critical issues for city viability and global health is air quality. The shutdown interval for the COVID-19 outbreaks has turned into an ecological experiment, allowing researchers to explore the influence of human/industrial operations on air quality. In this study, we have observed and examined the spatial pattern of air pollutants, specifically CO, NO2, SO2, O3 as well as AOD Over Bangladesh. For that reason, the timeline was chosen from March 2019 to October 2020 (before and during the first surge of COVID-19). The full analysis has been performed in Google Earth Engine (GEE). The findings showed that, CO, SO2, and AOD levels dropped significantly, but SO2 dropped slowly and O3 levels were similar, with marginally greater quantities in some areas during the lockdown than in 2019. During the shutdown, the association involving airborne pollutants and weather parameters (temperature and rainfall) revealed that rainfall and temperature were directly associated with air pollutants. COVID-19 mortality had a high positive connection with NO2 (R2 = 0.145; r = 0.38) and AOD (R2 = 0.17; r = 0.412). It is also found that various air impurities concentration has a strong relationship with Covid death. It would help the policymakers and officials to gain a better understanding of the sources of atmospheric emissions to develop a substantial proof of short- and long-term mitigation ways to enhance air quality and reduce the associated disease and disability burden.
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Affiliation(s)
- Md. Nazmul Haque
- School of Humanities and Social Sciences, Hiroshima University, Hiroshima, Japan,Department of Urban and Regional Planning, Khulna University Engineering & Technology, Khulna, 9203, Bangladesh,Corresponding author. School of Humanities and Social Sciences, Hiroshima University, Hiroshima, Japan Department of Urban and Regional Planning, Khulna University of Engineering and Technology, Room # 208, URP Building, KUET, Khulna, 9203, Bangladesh
| | - Md. Shahriar Sharif
- Department of Urban and Regional Planning, Khulna University Engineering & Technology, Khulna, 9203, Bangladesh
| | - Rhyme Rubayet Rudra
- Department of Urban and Regional Planning, Khulna University Engineering & Technology, Khulna, 9203, Bangladesh
| | - Mahdi Mansur Mahi
- Department of Urban and Regional Planning, Khulna University Engineering & Technology, Khulna, 9203, Bangladesh
| | - Md. Jahir Uddin
- Department of Civil Engineering, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh
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Singh D, Kumar K, Mishra P. Holiday for nature: a way forward in sustainability of the planet. GEOJOURNAL 2022; 88:2865-2887. [PMID: 36345555 PMCID: PMC9631588 DOI: 10.1007/s10708-022-10779-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 10/14/2022] [Indexed: 06/02/2023]
Abstract
This paper proposes to observe a day's break as the Planet Day (While the proposed day can also be named as the Gaia Day (after James Lovelock), Planet Day seems to be simpler and easier name for better understanding by the masses and greater connect of the issues with them. Hence, here the proposed day is termed as the Planet Day) every month to allow the nature to heal and ensure sustainability of the planet in the long run. Based on the concept of sustainable degrowth, the paper carries out benefit-cost analysis of the proposed Planet Day and presents a framework based on extensive literature review, secondary data analysis and stakeholders' (Here, participants are referred to as one of the "stakeholders" in the sense that every human being who lives on this planet is accountable for the harm done to it and is impacted by ecological degradation. Hence, they are supposed to contribute to healing of the nature through appropriate initiatives both individually and collectively. In addition to the common residents, there are other stakeholders of the ecology as well such as the government, the business enterprises, and manufacturing firms, etc.) perceptions through a non-random convenience sample survey. The paper finds that the net benefit from the Planet Day amounts to be USD 9002.37 billion across the world and USD 102.48 billion for India per annum. The respondents also perceive the proposed Planet Day as ecologically and economically beneficial and thus support the idea of healing time for the planet. However, a critical challenge is to take different stakeholders on board, ensure their active participation, and design appropriate institutional mechanisms for its successful implementation.
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Affiliation(s)
- Daisy Singh
- Department of Humanities and Social Science, Indian Institute of Technology (IIT), Kharagpur, West Bengal India
| | - Kishan Kumar
- Department of Humanities and Social Science, Indian Institute of Technology (IIT), Kharagpur, West Bengal India
| | - Pulak Mishra
- Department of Humanities and Social Science, Indian Institute of Technology (IIT), Kharagpur, West Bengal India
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