• Washed MSWI fly ash was used as partial cement or sand substitute.• Sand replacing is beneficial for strength, while cement replacement reduces strength.• Cementing efficiency factor and mortar pore structure explain the strength results.• Health risk assessment was conducted for MSWI fly ash blended cement mortar.• CR and HI contributed by different exposures and heavy metals were analyzed. The strength of cement substituted mortar decreases with the increase in fly ash amount, whereas the strength increases when the fly ash is blended as sand substitute. A mortar with highest strength (compressive strength= 30.2 Mpa; flexural strength= 7.0 Mpa) was obtained when the sand replacement ratio was 0.75%. The k value (cementing efficiency) of fly ash varied between 0.36 and 0.15 for the fly ash fraction in binder between 5% and 25%. The k values of fly ash used for sand replacement were all significantly above that used for cement substitution. The macropores assigned to the gaps between particles decreased when the fly ash was used as sand replacement, providing an explanation for the strength enhancement. The waste-extraction procedure (toxicity-sulphuric acid and nitric acid method (HJ/T 299-2007)) was used to evaluate metal leaching, indicating the reuse possibility of fly ash blended mortar. For the mortar with the mass ratio of fly ash to binder of 0.5%, the carcinogenic risks (CR) and non-carcinogenic hazard quotient (HQ) in sensitive scenario for blended mortar utilization were 9.66 × 10-7 and 0.06, respectively; these results were both lower than the threshold values, showing an acceptable health risk. The CR (9.89 × 10-5) and HQ (3.89) of the non-sensitive scenario for fly ash treatment exceeded the acceptable threshold values, indicating health risks to onsite workers. The main contributor to the carcinogenic and non-carcinogenic risk is Cr and Cd, respectively. The CR and HQ from inhalation was the main route of heavy metal exposure. 相似文献
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In recent 2 years, the incidence of influenza showed a slight upward trend in Guangxi; therefore, some joint actions should be done to help preventing and controlling this disease. The factors analysis of affecting influenza and early prediction of influenza incidence may help policy-making so as to take effective measures to prevent and control influenza. In this study, we used the cross correlation function (CCF) to analyze the effect of climate indicators on influenza incidence, ARIMA and ARIMAX (autoregressive integrated moving average model with exogenous input variables) model methods to do predictive analysis of influenza incidence. The results of CCF analysis showed that climate indicators (PM2.5, PM10, SO2, CO, NO2, O3, average temperature, maximum temperature, minimum temperature, average relative humidity, and sunshine duration) had significant effects on the incidence of influenza. People need to take good precautions in the days of severe air pollution and keep warm in cold weather to prevent influenza. We found that the ARIMAX (1,0,1)(0,0,1)12 with NO2 model has good predictive performance, which can be used to predict the influenza incidence in Guangxi, and the predicted incidence may be useful in developing early warning systems and providing important evidence for influenza control policy-making and public health intervention.