High concentrations of particulate matter (PM) could significantly reduce the quality of useful life and human life expectancy. The origin, control, and management of the problem has made great steps in recent decades. However, the problem is still prominent in developing countries. In fact, often the number and spatial distribution of the air quality monitoring stations does not have an appropriate design, misleading decision makers. In the present research, an innovative assessment is proposed of the environmental, health and economic benefits corresponding to a 20% reduction in the PM2.5 concentration in the urban area of Cartagena de Indias, Colombia. Cases of mortality and morbidity attributable to fine particles (PM2.5) were estimated, with particular emphasis on mortality, emergency room visits and hospitalizations from respiratory diseases, in addition to their economic assessment using BenMAP-CE®. The novelty of using BenMAP-CE® in studying respiratory diseases and PM2.5 exposure in developing countries lies in its ability to provide a comprehensive assessment of the health impacts of air pollution in these regions. This approach can aid in the development of evidence-based policy and intervention strategies to mitigate the impact of air pollution on respiratory health. Several concentration-response (C-R) functions were implemented to find PM2.5 attributable mortality cases of ischemic heart and cardiopulmonary disease, lung cancer, respiratory and cardiovascular disease, as well as cases of morbidity episodes related to asthma exacerbation and emergency room/hospitalization care for respiratory disease. A 20% reduction would have avoided 104 cases of premature death among the population older than 30 in Cartagena, and around 65 cases of premature mortality without external causes.
In most of the cities of the Colombian Caribbean, the emission factors associated to road traffic have not yet been estimated, due to the shortage of technical and economic resources. The authorities of some municipalities across Colombia have developed emission inventories adopting emission factors from other countries and, although these inventories are theoretically approximate, results indicate that road traffic is a source of emission of significant amounts of pollutants into the atmosphere. Studies conducted in 2013 by the Institute of Immunological Research (IIR), associated with the University of Cartagena, determined that the concentrations of CO and PM2.5 which were recorded throughout the city generally increased in the vicinity of the main roads. The present study aims to estimate the concentration of air pollutants generated by road traffic on the main roads of the city of Cartagena de Indias, Colombia, taking into account the critical points of increased vehicular flow. The upper limits of the emission factors values applying the inverse modeling technique were estimated for CO and PM2.5 considering average concentrations obtained for 24 hours of the pollutants that represent a greater threat to public health, as well as effects of weather conditions and urban morphology. This study is a starting point to determine the magnitude of the emission associated with road traffic in Cartagena and also provides technical support to be able to identify approximately the impact of different vehicle sources in the city. Finally, this article aims to propitiate applicable tools for the authorities to develop effective mitigation and/or control strategies pointed at minimizing the impact of vehicle emissions on the Cartagena inhabitants’ health.
The dispersion of air pollutants and the spatial representation of meteorological variables are subject to complex atmospheric local parameters. To reduce the impact of particulate matter (PM2.5) on human health, it is of great significance to know its concentration at high spatial resolution. In order to monitor its effects on an exposed population, geostatistical analysis offers great potential to obtain high-quality spatial representation mapping of PM2.5 and meteorological variables. The purpose of this study was to define the optimal spatial representation of PM2.5, relative humidity, temperature and wind speed in the urban district in Cartagena, Colombia. The lack of data due to the scarcity of stations called for an ad hoc methodology, which included the interpolation implementing an ordinary kriging (OK) model, which was fed by data obtained through the inverse distance weighting (IDW) model. To consider wind effects, empirical Bayesian kriging regression prediction (EBK) was implemented. The application of these interpolation methods clarified the areas across the city that exceed the recommended limits of PM2.5 concentrations (Zona Franca, Base Naval and Centro district), and described in a continuous way, on the surface, three main weather variables. Positive correlations were obtained for relative humidity (R2 of 0.47), wind speed (R2 of 0.59) and temperature (R2 of 0.64).
The increase in airborne pollution in large cities since the mid-20th century has had a physiologically proven impact on respiratory health, resulting in the irritation and corrosion of the alveolar wall. One of the demographics of the population most affected by this problem is children. This study focuses on the relationship between particulate matter of 2.5 µm (PM2.5) and childhood asthma, which is one of the main respiratory diseases identified in developing countries. The city of Cartagena de Indias, Colombia, is taken as a case study. A relevant correlation between childhood asthma and PM2.5 is found. Incidence series of paediatric asthma on a monthly scale and PM2.5 records in the city of Cartagena are considered. As is common in developing countries, the series was incomplete due to a lack of experts and insufficient economical resources. Therefore, several statistical and analytical processes were applied to provide sufficient quality to the series. An improvement of the time scale of the records was carried out, as well as the completion (statistical imputation) of missing data due to low statistical significance, by applying Rstudio®, PAST® and SPSS®. The last phases consisted of the determination of the main factors that cause childhood asthma incidence, the estimation of the correlation between asthma incidence and PM2.5, as well as the estimation of health impact. A reduction in PM2.5 concentration was simulated using BenMap-CE software to reach safe levels according to the WHO guidelines on air quality to identify preventable cases of childhood asthma, as air pollution has been found to be related to this disease. In addition, a log-linear model was applied to determine the number of hospital visits avoided after reducing the levels of PM2.5 concentration to the maximum levels recommended by WHO. The results showed a good agreement between childhood asthma incidence and PM2.5 pollutants in the spectral analysis (75% coincidence) and Chi2 (85.5% of coincidence) assessments, while visual correlation, mean and linear regression showed lower relations (61.0%, 55.5% and 0.48%, respectively). A reduction to a safe level of 5 µg/m3 would lead to a reduction of 240 annual cases of childhood asthma (95% CI: 137–330).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.