Dataset Information

A modified approach to Industrial Pollution Projection System for the assessment of sectoral pollution loads in Bangladesh.

ABSTRACT: Industrial pollution in Bangladesh has posed a serious threat to human health, economic activity, and the environment. By emphasizing industries that produce major pollutants, substantial improvements can be made to pollution mitigation measures. In countries where primary pollution data is not readily available, the Industrial Pollution Projection System (IPPS) could be used to calculate the pollution load utilizing total industrial output or employment data. IPPS data, which was designed for developed countries like the USA, had been used directly for other countries without any normalization in previously reported studies. The main purpose of this study is to modify the current IPPS approach for any other country by incorporating specific correction factor for a specific country. In this study, a specific correction factor for Bangladesh was determined, taking into account the country's major polluting industries, and used to estimate the pollution scenario for the year 2020. The accuracy of the specific pollution intensities was also evaluated by comparing the data obtained using both gross output and employee number. According to this study, the top three air-polluting industries are structural clay products, cement-lime-plaster industry, and iron and steel industry. Similarly, for water pollution, the food industry, paper and paper product industry, and textile industry are the largest pollutant contributors. The detailed pollution load matrix in terms of air and water pollution is also developed, and can be used to predict both short-term and long-term scenarios of industrial pollution in Bangladesh, which eventually will assist the policy makers to adopt appropriate pollution management approach. Moreover, the methods developed in this study will help to tailor the IPPS data for any country and increase the accuracy of the pollution load.

SUBMITTER: Karmaker A

PROVIDER: S-EPMC9073829 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Background:Exposure to cadmium (Cd) is a global public health concern. The primary Cd exposure pathways are inhalation and ingestion. Globally, Cd production and consumption has increased, along with nickel-cadmium battery production, alloys, anticorrosive coatings, pigments, polyvinyl chloride stabilizers, semiconductors for solar cells, etc. After the end use of these elements, improper management may cause Cd pollution in different spheres of the environment and living organisms that eventually lead to adverse effects on human health. Objectives:The aim of the present study is to demonstrate the sources and routes of Cd that enter different environmental spheres, their concentrations, and describe associated human health impacts in Bangladesh. Methods:The present study searched a total of 304 peer-reviewed articles in the National Center for Biotechnology Information database, Science Direct, Web of Science, Springer Link, BanglaJOL, and university libraries and ultimately selected 71 articles. Afterwards, the relevant findings on Cd exposure through inhalation and diet and age-based impacts (i.e., adults, women, children and infants) in Bangladesh were combined. Finally, the results were processed with a cross-tabulation technique. Results:The present study found that Cd concentration in the local diet and river water is within the World Health Organization and Bangladesh Standard Testing Institute guidelines. Discussion:The concentration of Cd in sediments is comparatively higher than in river water in Bangladesh. Cadmium has been found in samples of foods, including leafy and non-leafy vegetables collected from different places in Bangladesh and may ultimately enter the human body via dietary intake of these foods. Consequently, individuals may be exposed to Cd and may be suffering from long-term adverse health effects. Conclusions:The comparison of concentrations in this study with national and international standards will assist with the formulation of effective pollution mitigation measures in Bangladesh. Competing Interests:The authors declare no competing financial interests.

Project description:Mining activities are one of the main contamination sources of Cd in soil. However, the information about the influence of silver mining on Cd pollution in soil in mining-affected areas is limited. In the present study, sixteen paired soil and rice grain samples were collected from the farmland along the Luxi River nearby a silver mine in Yingtan City, Jiangxi Province, China. The total, bioavailable, and fraction of Cd in soil and Cd content in rice grain were determined by inductively coupled plasma mass spectrometry. The transformation of Cd in the soil-rice system and potential health risk via consumption of these rice grains were also estimated. The results showed that Cd concentration in these paddy soils ranged from 0.21 to 0.48 mg/kg, with the mean Cd concentration (0.36 mg/kg) exceeded the national limitation of China (0.3 mg/kg, GB 15618-2018). Fortunately, all these contaminated paddy soils were just slightly polluted, with the highest single-factor pollution index value of 1.59. The DTPA- and CaCl2-extractable Cd in these paddy soils ranged from 0.16 to 0.22 mg/kg and 0.06 to 0.11 mg/kg, respectively, and the acid-soluble Cd occupied 40.40% to 52.04% of the total Cd, which was the highest among different fractions. The concentration of Cd in rice grain ranged from 0.03 to 0.39 mg/kg, and the mean Cd concentration in rice grain (0.16 mg/kg) was within the national limitation of China (0.2 mg/kg, GB 2762-2017). The bioaccumulation factor of Cd in rice grain ranged from 0.09 to 1.18, and its correlation with various indicators was nonsignificant (p < 0.05). Health risk assessment indicated that the noncarcinogenic risk for local rice consumers was within the acceptable range, but the carcinogenic risk (CR) was ranging from 1.24 × 10-2 to 1.09 × 10-3 and higher than the acceptable range (1.0 × 10-4), indicating that the local rice consumers suffered serious risk for carcinogenic diseases. The results of the present study can provide reference for safety production of rice in silver mining-affected areas.

Project description:BackgroundRecords kept as a result of the implementation of Integrated Pollution Prevention and Control (IPPC) and the European Pollutant Release and Transfer Register (E-PRTR) constitute a public inventory of industries, created by the European Commission, which is a valuable resource for monitoring industrial pollution. Our objective is to ascertain whether there might be excess colorectal cancer mortality among populations residing in the vicinity of Spanish industrial installations that are governed by the IPPC Directive and E-PRTR Regulation and report their emissions to air.MethodsAn ecological study was designed to examine colorectal cancer mortality at a municipal level (8098 Spanish towns), over the period 1997-2006. We conducted an exploratory "near vs. far" analysis to estimate the relative risks (RR) of towns situated at a distance of less than 2 km from industrial installations. The analysis was repeated for each of the 24 industrial groups. RR and their 95% credible/confidence intervals (95%CI) were estimated on the basis of Poisson regression models, using two types of modelling: a) the conditional autoregressive Bayesian model proposed by Besag, York and Mollié, with explanatory variables; and b) a mixed regression model. Integrated nested Laplace approximations were used as a Bayesian inference tool.ResultsStatistically significant RRs were detected in the vicinity of mining industry (RR 1.258; 95%CI 1.082 - 1.463), paper and wood production (RR 1.071; 95%CI 1.007 - 1.140), food and beverage sector (RR 1.069; 95%CI 1.029 - 1.111), metal production and processing installations (RR 1.065; 95% CI 1.011 - 1.123) and ceramics (RR 1.050 ; 95%CI 1.004 - 1.099).ConclusionsGiven the exploratory nature of this study, it would seem advisable to check in other countries or with other designs, if the proximity of industries that emit pollutants into the air could be an added risk factor for colorectal cancer mortality. Nevertheless, some of the differences between men and women observed in the analyses of the industrial groups suggest that there may be a component of occupational exposure, little-studied in the case of cancers of the digestive system.

Project description:BackgroundComputed tomography (CT) is an advanced medical imaging technology. The images obtained by CT are helpful for improving diagnostic accuracy. Currently, CT is widely used in clinical settings for diagnosis and health examinations. However, full angle CT scanning has the disadvantage of causing radiation damage to the human body. Sparse angle projection CT scanning is the most effective way to minimize this damage, but the quality of the reconstructed image is reduced. Therefore, it is important to improve the reconstructed image quality produced by sparse angle projection.MethodsIn this paper, we focused on the algebraic reconstruction algorithm. To reduce the accumulation of random noise, we formulated a modified algebraic reconstruction algorithm. Firstly, the algebraic reconstruction algorithm was used to compute two consecutive results, and then the weighted sum of these two results was used to correct the reconstructed image, and an iterative result was obtained. Using this method, we aimed to reduce the noise accumulation caused by iteration.ResultsIn this study, 20 angle projections were used for the reconstruction. The experimental object was the Shepp-Logan phantom test image. The experiments were implemented under two conditions: without noise and with noise. The peak signal to noise ratio (PSNR) and the mean squared error (MSE) of the reconstructed image from projections without noise were 76.0896 and 0.0016, respectively. The PSNR and MSE of the reconstructed image from projections with noise were 75.8263 and 0.0017, respectively. The reconstructed performance was superior to the previous algebraic reconstruction algorithm.ConclusionsThe performance of the proposed method was superior to other algorithms, which confirms that noise accumulation caused by iteration can be effectively reduced by the weighted summation of two consecutive reconstruction results. Moreover, the reconstruction performance under noisy projection is superior to other algorithms, which demonstrates that the proposed method improves anti-noise performance.

Dataset Information

A modified approach to Industrial Pollution Projection System for the assessment of sectoral pollution loads in Bangladesh.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets