Integrated assessment of health risk and climate effects of black carbon in the Pearl River Delta region, China

Lin, Weiwei; Dai, Jiajia; Liu, Run; Zhai, Yueyang; Yue, Dingli; Hu, Qiansheng

doi:10.1016/j.envres.2019.06.003

Cited by 54 publications

(21 citation statements)

References 66 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Various toxic and harmful substances are easily absorbed onto the surface of black carbon due to its loose and porous structure. These harmful substances would affect human health when they are sucked into the respiratory tract and reach the lung together with BC [15][16][17]. Therefore, it is also imperative to reduce black carbon in the atmosphere.…”

Section: Introductionmentioning

confidence: 99%

Impact of Black Carbon on Surface Ozone in the Yangtze River Delta from 2015 to 2018

et al. 2021

View full text Add to dashboard Cite

Despite the yearly decline in PM2.5 in China, surface ozone has been rapidly increasing recently, which makes it imperative to coordinate and control both PM2.5 and ozone in the atmosphere. This study utilized the data of pollutant concentrations and meteorological elements during 2015 to 2018 in Nanjing, China to analyze the daily correlation between black carbon and ozone (CBO), and the distribution of the pollutant concentrations under different levels of CBO. Besides, the diurnal variations of pollutant concentrations and meteorological elements under high positive and negative CBO were discussed and compared. The results show that the percentage of positive CBO had been increasing at the average rate of 7.1%/year, and it was 38.7% in summer on average, nearly twice of that in other seasons (19.2%). The average black carbon (BC), PM2.5 and NO2 under positive CBO was lower than those under negative CBO. It is noticeable that the surface ozone began to ascend when CBO was up to 0.2, with PM2.5 and NO2 decreasing and BC remaining steady. Under negative CBO, pollutant concentrations and meteorological elements showed obvious diurnal variations: BC showed a double-peak pattern and surface ozone, PM2.5, SO2 and CO showed single-peak patterns and NO2 showed a trough from 10:00 to 19:00. Wind speed and visibility showed a single-peak pattern with little seasonal difference. Relative humidity rose first, then it lowered and then it rose. Under positive CBO, the patterns of diurnal variations became less obvious, and some of them even showed no patterns, but just fluctuated at a certain level.

show abstract

Section: Introductionmentioning

confidence: 99%

Impact of Black Carbon on Surface Ozone in the Yangtze River Delta from 2015 to 2018

et al. 2021

View full text Add to dashboard Cite

show abstract

“…The two nonlinear ensemble models (BPNN-E and HW-E) were modelled using a similar method to that of the respective single models. For the two linear ensembles (SAE and WAE), the modeling was carried out using Equations (1) and (2). The performance results of the ensemble techniques are presented in Table 4.…”

Section: Results Of the Ensemble Modelingmentioning

confidence: 99%

Hybrid Machine Learning Ensemble Techniques for Modeling Dissolved Oxygen Concentration

et al. 2020

View full text Add to dashboard Cite

The reliable prediction of dissolved oxygen concentration (DO) is significantly crucial for protecting the health of the aquatic ecosystem. The current research employed four different single AI-based models, namely long short-term memory neural network (LSTM), extreme learning machine (ELM), Hammerstein-Weiner (HW) and general regression neural network (GRNN) for modeling the DO concentration of Kinta River, Malaysia using available water quality (WQ) parameters. Afterwards, the first scenario used four different ensemble techniques (ET). Two linear, i.e. simple averaging ensemble (SAE) and weighted averaging ensemble (WAE) and two nonlinear namely; backpropagation neural network ensemble (BPNN-E) and HW ensemble (HW-E). The second scenario employed a hybrid random forest (RF) ensemble in order to enhance the prediction accuracy of the single models. The WQ parameters were subjected to a different pre-analysis test to ascertain their stability. The four-model combinations are generated using the nonlinear sensitivity input selection approach. The modeling performance was assessed using the statistical measures of Nash-Sutcliffe coefficient efficiency (NSE), Willmott's index of agreement (WI), root mean square error (RMSE), mean absolute error (MAE) and mean square error (MSE) and correlation coefficient (CC). The results of the single AI-based models demonstrated that HW (M3) served as the best model for predicting DO concentration. For ensemble results, BPNN-E (WI=0.9764) was superior to the other three ET with average decreased of more than 2% with regards to MAE. Investigation on the hybrid RF ensemble demonstrated the reliable accuracy for all the hybrid models with better predictive skill shown by the HW-RF (CC=0.981) ensemble. The overall results verified the promising impact of HW-M3, ET and hybrid RF ensemble for the prediction of the DO concentration in the Kinta River, Malaysia.

show abstract

“…BC has been associated with various health effects, such as cardiovascular disease, ischemic heart disease, asthma, and lung cancer [35]. A study in the Pearl River Delta region (China) had confirmed the possibility of carcinogenicity in children caused by BC exposure, by estimating an excess of 1.97 cancer cases per 10,000 children [36]. Meanwhile, a study in Chiang Mai (Thailand) had reported the health risks posed by BC was found comparable to a high number of passively smoked cigarettes, regarding the risk of percentage of lung function reduction of school-aged children [37].…”

Section: Concentrations Of Air Pollutants In Schoolsmentioning

confidence: 99%

The Influence of Traffic-Related Air Pollution (TRAP) in Primary Schools and Residential Proximity to Traffic Sources on Histone H3 Level in Selected Malaysian Children

Suhaimi

Jalaludin

Bakar

2021

IJERPH

View full text Add to dashboard Cite

This study aimed to investigate the association between traffic-related air pollution (TRAP) exposure and histone H3 modification among school children in high-traffic (HT) and low-traffic (LT) areas in Malaysia. Respondents’ background information and personal exposure to traffic sources were obtained from questionnaires distributed to randomly selected school children. Real-time monitoring instruments were used for 6-h measurements of PM10, PM2.5, PM1, NO2, SO2, O3, CO, and total volatile organic compounds (TVOC). Meanwhile, 24-h measurements of PM2.5-bound black carbon (BC) were performed using air sampling pumps. The salivary histone H3 level was captured using an enzyme-linked immunosorbent assay (ELISA). HT schools had significantly higher PM10, PM2.5, PM1, BC, NO2, SO2, O3, CO, and TVOC than LT schools, all at p < 0.001. Children in the HT area were more likely to get higher histone H3 levels (z= -5.13). There were positive weak correlations between histone H3 level and concentrations of NO2 (r = 0.37), CO (r = 0.36), PM1 (r = 0.35), PM2.5 (r = 0.34), SO2 (r = 0.34), PM10 (r = 0.33), O3 (r = 0.33), TVOC (r = 0.25), and BC (r = 0.19). Overall, this study proposes the possible role of histone H3 modification in interpreting the effects of TRAP exposure via non-genotoxic mechanisms.

show abstract

Integrated assessment of health risk and climate effects of black carbon in the Pearl River Delta region, China

Cited by 54 publications

References 66 publications

Impact of Black Carbon on Surface Ozone in the Yangtze River Delta from 2015 to 2018

Impact of Black Carbon on Surface Ozone in the Yangtze River Delta from 2015 to 2018

Hybrid Machine Learning Ensemble Techniques for Modeling Dissolved Oxygen Concentration

The Influence of Traffic-Related Air Pollution (TRAP) in Primary Schools and Residential Proximity to Traffic Sources on Histone H3 Level in Selected Malaysian Children

Contact Info

Product

Resources

About