ABSTRACT
Background A number of studies have shown that heavy metals in atmospheric PM2.5 have impacts on human health, while studies on the impact of long-term and low-concentration exposure to lead in PM2.5 on human health are limited. Objective To investigate the pollution characteristics of lead in ambient PM2.5 and assess its chronic health risks. Methods Daily PM2.5 concentration data in Jinan from 2014 to 2019 were collected, and the year-by-year trend of PM2.5 concentration was analyzed. Licheng District (an industrial area) and Shizhong District (a residential area) were elected to install an ambient PM2.5 monitoring stationrespectively. The sampling instrument was a 100 L·min−1 high-flow PM2.5 sampler, with a cumulative sampling time of 20-24 h per day, using a quartz fiber filter membrane for lead detection and a glass fiber filter membrane for PM2.5 determination. The sampling frequency was 7 consecutive days per month from the 10th to the 16th (A total of 493 d were sampled and some were missing; 172 d during the heating period and 321 d during the non-heating period). Two PM2.5 samples were collected in one monitoring site each day. A total of 986 samples were collected in one monitoring site. The lead content in PM2.5 samples was detected by inductively coupled plasma mass spectrometry. The concentration of PM2.5 was measured by weighing method. The annual average concentration and enrichment factor of lead in PM2.5, the change trend of lead content per unit mass of PM2.5, and the difference between heating period and non-heating period from 2014 to 2019 were estimated. Technical guide for environment health risk assessment of chemical exposure (WS/T 777-2021) was used to assess the health risks of exposure to lead in PM2.5. Results The average annual concentration of lead in PM2.5 ranged from 23.2 ng·m−3 to 154.7 ng·m−3. The average concentration in heating period from 2015 to 2019 was higher than that in non-heating period, and the differences in 2015, 2017, and 2019 were statistically significant (P < 0.01 or 0.001). The enrichment factors ranged from 200 to 1342 in 2014 to 2019. The average enrichment factors in heating period in 2015, 2017, and 2018 was higher than those in non-heating period, and the difference was statistically significant (P < 0.05 or 0.001). The lead contents per unit mass of PM2.5 ranged from 493 ng·mg−1 to 1944 ng·mg−1, and the differences between heating period and non-heating period in 2014, 2017, and 2018 were statistically significant (P < 0.05 or 0.001). The average annual concentration and enrichment factor of lead in PM2.5 showed a downward trend, and thus the lead content per unit mass of PM2.5 also decreased. From 2014 to 2019, the carcinogenic risk of lead in PM2.5 in Jinan ranged from 1.69×10−8 to 2.45×10−6, showing a significant downward trend year by year, and the 95th percentile decreased by 3%-46% from the previous year. The carcinogenic risk level of lead was reduced to an acceptable level (<1×10−6) after 2017. Conclusion From 2015 to 2019, lead concentration and enrichment factor in PM2.5 increase during heating period compared with non-heating period, but it is not completely consistent of lead content in PM2.5 per unit mass. From 2014 to 2016, exposure to lead in PM2.5 may elevate carcinogenic risk to human. After 2017, the carcinogenic risks of exposure to lead in PM2.5 are at an acceptable level.
ABSTRACT
Objective To explore PM2.5 concentration modeling and prediction based on the monthly average concentrations of PM2.5 in Shanghai since 2015, and to provide new ideas about PM2.5 prediction methods. Methods The seasonal factors were introduced into the Grey Model (GM). GM(1,1) model modified with seasonal factors was established and compared with seasonal autoregressive integrated moving average model (ARIMA) model. The data of 2015-2021 was used for modeling and prediction, and the data from January to October in 2022 was used as a validation set to evaluate the prediction effectiveness. The monthly average PM2.5 concentrations in Shanghai from November to December in 2022 were predicted. Results Seasonal ARIMA model showed RMSE=4.02 and MAPE=15.50% in the validation set, while GM(1,1) model modified with seasonal factors showed RMSE=3.30 and MAPE=11.59%. GM(1,1) model modified with seasonal factors predicted the monthly average PM2.5 concentrations in Shanghai from November to December in 2022 to be 24.99 and 34.83μg/m3, respectively. Conclusion The prediction effect of GM(1,1) model modified with seasonal factors has better predictive performance than seasonal ARIMA model. The grey prediction model modified with seasonal factors can be considered when predicting seasonal time series such as the concentration of PM2.5.
ABSTRACT
<p><b>OBJECTIVE</b>Risk assessment and risk control for occupational exposure to chemical toxicants were performed on an isophorone nitrile device with an annual production of 5,000 tons, based on improved Singaporean semi-quantitative risk assessment method, with consideration of actual situation in China and in the present project.</p><p><b>METHODS</b>With the use of engineering analysis and identification of occupational hazards in the improved Singaporean semi-quantitative risk assessment method, hazard rating (HR) and risk assessment were performed on chemical toxicants from an isophorone nitrile device with an annual production of 5,000 tons.</p><p><b>RESULTS</b>The chemical toxicants in the isophorone nitrile device were mainly isophorone, hydrocyanic acid, methanol, phosphoric acid, sodium hydroxide, and sodium cyanide; the HR values were mild hazard (2), extreme hazard (5), mild hazard (2), mild hazard (2), moderate hazard (3), and extreme hazard (5), respectively, and the corresponding exposure rating (ER) values were 2.09, 2.72, 2.76, 1.68, 2.0, and 1.59, respectively. The risk of chemical toxicants in this project was assessed according to the formula Risk = [HR×ER](1/2). Hydrocyanic acid was determined as high risk, sodium hydroxide and sodium cyanide as medium risk, and isophorone, methanol, and phosphoric acid as low risk. Priority in handling of risks was determined by risk rating. The table of risk control measure was established for pre-assessment of occupational hazards.</p><p><b>CONCLUSION</b>With risk assessment in this study, we concluded that the isophorone nitrile device with 5,000 ton annual production was a high-occupational hazard device. This device is a project of extreme occupational hazard. The improved Singaporean semi-quantitative risk assessment method is a scientific and applicable method, and is especially suitable for pre-evaluation of on-site project with no analogy.</p>
Subject(s)
Humans , Cyclohexanones , Nitriles , Occupational Exposure , Risk AssessmentABSTRACT
Cyanobacterial toxins may pose a threat to human health through drinking water and recreational water exposure. The official guideline limits of cyanobacterial toxins have not been established. The human health effects, exposure routes, possible guideline limits and calculation method were introduced in the present paper. The knowledge will provide a base to undertake risk management for the toxins and will also contribute to establishing official guideline limits of cyanobacterial toxins in water and will be benefit for ensuring the safety of drinking water.