Taiwan EPA Research Articles

Removal of toxic arsenic(iii) from an old endemic black-foot disease groundwater by oxidative electrosorption

Environmental context Naturally occurring arsenic was the likely cause of endemic black foot disease in groundwaters in Taiwan, and levels still exceed Taiwan EPA water quality standards. A method for the clean-up of these groundwaters that is both feasible and environmentally friendly is urgently needed. Oxidation of As(III) as H3AsO3 to the less toxic As(V)− and removal of As in groundwater was performed quantitatively by electrosorption using materials derived from agricultural wastes; this shows that this method has the potential to be a novel, green remediation method. Rationale Naturally occurring arsenic in the groundwater caused black-foot disease (BFD) in the 1950s on the southwest seashore of Taiwan. Recently, we found that the concentration of arsenic in groundwater taken from currently sealed wells in areas previously affected by BFD remained higher than the Taiwan (EPA) water quality standard. Although clean tap water is available in that area, removal of arsenic from the groundwater is of great importance to expand possible utilisation. Methodology Removal of arsenic from two old endemic BFD groundwaters with activated carbon (AC) electrodes recycled from agricultural wastes by electrosorption using capacitive deionisation (CDI) processes was studied. A better understanding of arsenic electrochemistry involved in electrosorption was investigated by in situ X-ray absorption near-edge structure spectroscopy. Results Arsenic removal efficiencies (61–93%) remained high across concentrations (5 and 196 mg/L). A high oxidation rate constant (0.93 h−1) for As(III)0 to As(V)− was found, allowing the electrosorption of As(V)− onto the meso- and micro-pores of the AC CDI electrodes with rate constants of 0.021 and 0.0013 h−1, respectively. Removal of arsenic from contaminated groundwater for drinking water was achieved with six CDI reactors in series. Moreover, in the presence of other ions (such as Na+, Mg2+ and Ca2+), 60–73% of As(III)0 and As(V)− ions were removed from the groundwaters by electrosorption. Discussion We have developed an engineering-feasible method for converting As(III)0 to less toxic As(V)−, enabling its removal by electrosorption, which demonstrates the feasibility for green remediation of BFD waters as well as other arsenic-contaminated groundwaters.

Influence of point-of-use dispensers on lead level assessment in drinking water of a lead pipe-free campus

Point-of-use (POU) dispensers, referring to those directly connected to the water supply lines, are widely used in public facilities such as schools and universities in Taiwan. These dispensers are equipped with filters that can remove contaminants, including heavy metals in drinking water. Assessment of water lead (Pb) levels rely heavily on sampling surveys that involve various sampling protocols. This study evaluated the effects of using first draw (FD), flush (FL) incorporating at least 20 s of flushing, and random daytime (RDT) sampling protocols on Pb level assessment in water samples collected from faucets and POU dispensers of a Pb pipe-free campus between March 2017 and July 2020. This was the first study to examine the influence of POU dispensers on different sampling protocols and their survey results. Pb levels in 19% of faucet and 11% of dispenser samples exceeded the Taiwan EPA standard of 10 μg/L. FL sampling produced the lowest Pb levels, followed by RDT and FD in the samples collected from faucets. Interestingly, all three sampling protocols exhibited similar Pb levels in samples collected from dispensers. Thus, any of the three sampling protocols can be employed to monitor Pb levels in water samples collected from dispensers.

Qualifying and Quantifying the Emissions of Volatile Organic Compounds from the Coking Process in a Steel Plant Using an Innovative Sampling Technique

The aim of this paper is to quantify the amounts of volatile organic compounds (VOCs) emitted from a coke oven in a steel plant in Taiwan and estimate the emission factors of VOCs using an innovative sampling technique. The identification of VOCs emissions was referred to in the AP-42 report issued by the USEPA and the field measurement data of fugitive emissions. VOCs were sampled using a self-designed closed sampling system. A total of six emission points, including quenching emissions, charge lid emissions, combustion stack emissions, door emissions, charging emissions, and coke pushing emissions, were identified in the coking process after comparing with the report of AP-42, and the emission factor of VOCs was 0.030 kg/ton-coke. It showed that the emission factor of VOCs via field measurement was approximately 56% of that reported by Taiwan EPA. Therefore, VOCs emissions estimated by the Taiwan EPA would be highly overestimated than those from the coke oven in the site.

The Stabilization of Waste Funnel Glass of CRT by SiO2 Film Coating Technique

The funnel glass of the CRT monitor contains about 22–28% of lead oxide, of which lead is a highly toxic species and hazardous to the environment. This study proposes a process to form a protective layer of SiO2 film coating on the funnel glass to reduce the hazardous effect of lead leaching to the environment. The film coating benefits from the advantages of the sol–gel method. There are two key procedures of the stabilization technique, including the alkaline treatment and the formation of SiO2 coating from TEOS. The results show that the funnel glass powder treated with 10 M NaOH can produce a mushy layer on the surface. The mushy layer, which comprises OH− and water, can promote the formation of the SiO2 film layer on the surface of funnel glass powder. The conditions of the SiO2 film coating proposed in this study are: alkaline treatment by 10 M NaOH, the addition ratio of TEOS and funnel glass powder 2: 1, reaction temperature 40 °C, and reaction time 1.3 h. The EDS and ESCA results show that the Pb peak intensity on the surface of funnel glass decreases with the film coating. In the TCLP test, the leaching amount for Pb of the SiO2 film coated funnel glass powders is 0.7 mg/L, which is far lower than the standard in Taiwan EPA. Based on the experimental results, the formation mechanism of the SiO2 film layer on the surface of waste funnel glass powder is proposed. This study demonstrates that the SiO2 film coating is a potentially effective method to solve the problem of the waste funnel glass.

Using a land use regression model with machine learning to estimate ground level PM2.5.

Ambient fine particulate matter (PM2.5) has been ranked as the sixth leading risk factor globally for death and disability. Modelling methods based on having access to a limited number of monitor stations are required for capturing PM2.5 spatial and temporal continuous variations with a sufficient resolution. This study utilized a land use regression (LUR) model with machine learning to assess the spatial-temporal variability of PM2.5. Daily average PM2.5 data was collected from 73 fixed air quality monitoring stations that belonged to the Taiwan EPA on the main island of Taiwan. Nearly 280,000 observations from 2006 to 2016 were used for the analysis. Several datasets were collected to determine spatial predictor variables, including the EPA environmental resources dataset, a meteorological dataset, a land-use inventory, a landmark dataset, a digital road network map, a digital terrain model, MODIS Normalized Difference Vegetation Index (NDVI) database, and a power plant distribution dataset. First, conventional LUR and Hybrid Kriging-LUR were utilized to identify the important predictor variables. Then, deep neural network, random forest, and XGBoost algorithms were used to fit the prediction model based on the variables selected by the LUR models. Data splitting, 10-fold cross validation, external data verification, and seasonal-based and county-based validation methods were used to verify the robustness of the developed models. The results demonstrated that the proposed conventional LUR and Hybrid Kriging-LUR models captured 58% and 89% of PM2.5 variations, respectively. When XGBoost algorithm was incorporated, the explanatory power of the models increased to 73% and 94%, respectively. The Hybrid Kriging-LUR with XGBoost algorithm outperformed the other integrated methods. This study demonstrates the value of combining Hybrid Kriging-LUR model and an XGBoost algorithm for estimating the spatial-temporal variability of PM2.5 exposures.

Recurrent Learning on PM2.5 Prediction Based on Clustered Airbox Dataset

The progress of industrial development naturally leads to the demand for more electrical power. Unfortunately, due to the fear of the safety of nuclear power plants, many countries have relied on thermal power plants, which will cause more air pollutants during the process of coal burning. This phenomenon as well as increased vehicle emissions around us, have constituted the primary factors of serious air pollution. Inhaling too much particulate air pollution may lead to respiratory diseases and even death, especially PM <inline-formula><tex-math notation="LaTeX">$_{2.5}$</tex-math></inline-formula> . By predicting the air pollutant concentration, people can take precautions to avoid overexposure to air pollutants. Consequently, accurate PM <inline-formula><tex-math notation="LaTeX">$_{2.5}$</tex-math></inline-formula> prediction becomes more important. In this study, we propose a PM <inline-formula><tex-math notation="LaTeX">$_{2.5}$</tex-math></inline-formula> prediction system, which utilizes the dataset from EdiGreen Airbox and Taiwan EPA. Autoencoder and Linear interpolation are adopted for solving the missing value problem. Spearman’s correlation coefficient is used to identify the most relevant features for PM <inline-formula><tex-math notation="LaTeX">$_{2.5}$</tex-math></inline-formula> . Two prediction models (i.e., LSTM and LSTM based on K-means) are implemented which predict PM <inline-formula><tex-math notation="LaTeX">$_{2.5}$</tex-math></inline-formula> value for each Airbox device. To assess the performance of the model prediction, the daily average error and the hourly average accuracy for the duration of a week are calculated. The experimental results show that LSTM based on K-means has the best performance among all methods. Therefore, LSTM based on K-means is chosen to provide real-time PM <inline-formula><tex-math notation="LaTeX">$_{2.5}$</tex-math></inline-formula> prediction through the Linebot.

Disinfection efficiency of hospital infectious disease wards with chlorine dioxide and hypochlorous acid.

The disinfection efficiencies of two chemical disinfectants, chlorine dioxide and weak acid hypochlorous water (WAHW), were examined in the soiled room and dishwashing room of a hospital infectious disease ward in Taiwan. The investigations were conducted in two seasons, namely winter and summer, in order to examine the correlation between the bioaerosol concentration and the environmental factors. In addition, a single-daily disinfection mode (SM) and a twice-daily disinfection mode (TM) were applied in this study. The results showed that the bacteria and fungi colony counts were strongly correlated with the temperature. Both disinfectants reduced the bacteria and fungi concentrations in the considered rooms. However, of the two disinfectants, the ClO2 showed a stronger disinfection effect than the WAHW. It means that when using ClO2 as the disinfectant, the disinfection efficiency of the TM treatment mode is significantly better than that of the SM treatment mode. But, when using WAHW as the disinfectant, no significant difference is found between the disinfection efficiencies of the two methods. Overall, the results showed that the application of ClO2 twice daily provided the most effective means of satisfying the Taiwan EPA guidelines for the indoor air quality of hospital medical wards.

Emission characteristics of dl-PCNs, PCDD/Fs, and dl-PCBs from secondary copper metallurgical plants: Control technology and policy

This study investigated the characteristics of dl-PCNs, PCDD/Fs and dl-PCBs emitted from two typical secondary copper metallurgical plants processing copper sludge equipped with different sets of air pollution control devices (APCDs). Results indicated that the emission factors of dl-PCNs and PCDD/Fs of plant A are 0.00775 and 1.09 μg TEQ/ton, respectively, which are remarkably lower than those of plant B (3.12, 181 and 25.5 μg TEQ/ton for dl-PCNs, PCDD/Fs and dl-PCBs, respectively). Dl-PCNs contributed 0.7–2.7% of total TEQ for flue gases and up to 2.6% of TEQ for ash samples. The TEQ concentration of dl-PCNs in fly ash individually exceeds the regulated level of 1 ng TEQ/g regulated by Taiwan EPA, indicating that emission and discharge of dl-PCNs should be regulated. The combination of semidry scrubber and activated carbon injection (ACI) + baghouse (BH) is effective for simultaneous removals of dl-PCNs and PCDD/Fs in plant A; while the combination of cyclone, secondary combustion chamber, ACI + BH and wet scrubber (WS) is not optimal for removing dl-PCNs, PCDD/Fs and dl-PCBs. Memory effect occurring within BH and WS is responsible for low removal efficiencies of these POPs in plant B. This study suggests appropriate APCDs for simultaneous removal of three POP groups and recommends the inclusion of dl-PCNs in emission standard.

RECYCLING OF LIGHT-EMITTING DIODE WASTE QUARTZ SAND ACTING AS A POZZOLANIC MATERIAL FOR PORTLAND CEMENT

LED waste quartz sand (LEDWS), which is a prominent by product of the LED manufacturing process, may contaminate the environment because it comprises specific heavy metals (e.g., As and Cu), which are hazardous ingredients to the environment when disposed of improperly. Therefore, this study investigated the use of light-emitting diode (LED) waste quartz sand to partially replace Portland Type I cement (OPC) to evaluate the feasibility of reusing it as a pozzolanic material. The SiO2, Na2O, and CaO contents in the LED waste quartz sand were 70.37, 16.52, and 9.19%, respectively. The results showed that the LED waste quartz sand met the Taiwan EPA regulatory thresholds. Microstructure analysis techniques, such as mercury intrusion porosimetry (MIP), X-ray diffraction (XRD) and scanning electron microscopy (SEM), were used to measure the LED waste quartz sand-blended cement paste (LEDBCP) samples. Compressive strength analysis of the pastes containing 10 wt.% LED waste quartz sand showed that the LED waste quartz sand not only acts as a pozzolanic material to increase the density of the microstructure but also improves the compressive strength of the pastes. LEDBCP with LED waste quartz sand exhibited higher intensity diffraction peaks corresponding to calcium silicate hydrate and lower intensity diffraction peaks corresponding to portlandite (CH) compared with ordinary Portland cement samples at an early age. The gel porosity and pore sizes of the LEDBCP increased with increases in the proportion of LED waste quartz sand. LEDBCP with 10-20 wt.% LED waste quartz sand provides a paste with good pozzolanic characteristics.

The improvement of spatial-temporal resolution of PM2.5 estimation based on micro-air quality sensors by using data fusion technique

With the rapid development of the Internet of things (IoTs) and modern industrial society, forecasting air pollution concentration, e.g., the concentration of PM2.5, is of great significance to protect human health and the environment. Accurate prediction of PM2.5 concentrations is limited by the number and the data quality of air quality monitoring stations. In Taiwan, the spatial and temporal data of PM2.5 concentrations are measured by 77 national air quality monitoring stations (built by Taiwan EPA). However, the national stations are costly and scarce because of the highly precise instrument and their size. Therefore, many places are still out of coverage of the monitoring network. Recently, under the framework of IoTs, there are hundreds of portable air quality sensors called “AirBox” developed jointly by the Taiwan local government and a private company. By virtue of its low price and portability, the AirBox can provide a higher resolution of space-time PM2.5 measurement. However, the spatiotemporal distribution is different between AirBox and EPA stations, and data quality and accuracy of AirBox is poorer than national air quality monitoring stations. Thus, to integrate the heterogeneous PM2.5 data, the data fusion technique should be used before further analysis.In this study, we propose a new data fusion method called multi-sensor space-time data fusion framework. It is based on the Optimum Linear Data Fusion theory and integrating with a multi-time step Kriging method for spatial-temporal estimation. The method is used to do heterogeneous data fusion from different sources and data qualities. It is able to improve the estimation of PM2.5 concentration in space and time. Results have shown that by combining PM2.5 concentration data from 1176 low-cost AirBoxes as additional information in our model, the estimation of spatial-temporal PM2.5 concentration becomes better and more reasonable. The r2 of the validation regression model is 0.89. Under the approach proposed in this study, we made the information of the micro-sensors more reliable and improved the higher spatial-temporal resolution of air quality monitoring. It could provide very useful information for better spatial-temporal data analysis and further environmental management, such as air pollution source localization, health risk assessment, and micro-scale air pollution analysis.

Investigation of biosolid-compost produced by high-temperature fermentation process

Disposal of biosolids has been paid a due attention in Taiwan owing to their increasing amounts in the recent years. As there is no special landfill for biosolids dumping in Taiwan, transformation of biosolids to compost could be one of the suitable means of disposal. The study aimed to investigate the use of high-temperature fermentation technique to produce biosolid compost and examine the quality of bio-solid compost produced. Biosolids collected from a municipal wastewater treatment plant were treated by electro-kinetics to remove heavy metals and mixed with some agricultural wastes (mushroom waste and chicken excreta) to transform into the compost by a high-temperature (130°C) fermentation process. Prior and post to fermentation, the concentration of heavy metals and pathogenic bacteria in the biosolid-compost were determined. Results indicated that concentration of Cd, Cr, Cu, Ni and Pb in the compost after fermentation was within the soil control standard of Taiwan EPA. The pathogenic bacteria such as Escherichia coli, Salmonella, and parasitic ova in the final compost were within the government criteria. Biosolid compost was then applied as a soil improvement material to compare the relative growth (with a control) of red leaf shovel within the campus premises. The plants in the plot with biosolid compost demonstrated a better growth than the same plants in the control.

The relationship between air pollution exposure and the risk of diabetic retinopathy

PDS 67: Outdoor air pollution cardiometabolic effects, Exhibition Hall (PDS), Ground floor, August 27, 2019, 4:30 PM - 5:30 PM Background/Aim: Exposure to air pollution has been linked to adverse effects on vascular diseases. However, the effects of air pollution exposure on diabetic retinopathy (DR), a form of vascular disease, have not been studied. The aim of this study was to determine the association between ambient air pollution exposure and diabetic retinopathy occurrence. Material and Methods Retrospective cohort study design was applied for investigating the long-term effect of ambient air pollution on DR occurrence among diabetics. Newly diagnosed diabetes mellitus (DM) cases during 2003-2012 from the National Health Insurance Research Database (NHIRD) – Longitudinal Health Insurance Database 2005 (LHID2005) were included in the study cohort. Yearly air exposure levels were obtained from the Taiwan EPA air monitoring station. Kriging method was used to interpolate concentrations of air pollutants in township levels. We linked yearly townships exposure levels with townships of residence in each year, and calculated the average concentrations of follow-up period as personal exposure. The Cox proportional hazard models were performed adjusting for sex, age of DM onset and comorbidities. Results: A total of 17,403 subjects with newly diagnosed DM were included in the study. Among them, 585 newly diagnosed DR cases were found during the follow-up periods (mean: 5.6 years). The hazard ratio (HR) of DR occurrence associated with per 10 μg/m3 increase in PM2.5, PM2.5-10, 1 ppb in nitrogen dioxide (NO2) and sulfur dioxide (SO2), were 2.06 (95% confidence interval, CI: 1.60-2.66), 1.71 (95%CI: 1.39-2.10), 1.05 (95%CI: 1.03-1.08), and 1.23 (95%CI: 1.13-1.34), respectively. In two-pollutant models, the effects of PM2.5, PM2.5-10, NO2 and SO2 remained robust after adjusting for other air pollutants. Conclusion: Exposure to higher levels of air pollution was associated with increased risk of DR occurrence in diabetic patients.

Comparisons of ambient air particulates concentrations (TSP, PM2.5) and dry depositions during smog and non-smog periods at Luliao, Shalu District sampling site

The concentrations of ambient total suspended particulates (TSP) and PM2.5, and the dry depositions at a sample site at Luliao Junior High School (Luliao) in central Taiwan were measured during smog and non-smog days between December 2017 and July 2018. The results are compared to those obtained during non-smog periods in the years 2015–2017. The mean TSP and PM2.5 concentrations and dry deposition flux were 72.41 ± 26.40, 41.88 ± 23.51 μg/m3, and 797.57 ± 731.46 μg/m2 min, respectively, on the smog days. The mean TSP and PM2.5 concentrations and dry deposition flux on the non-smog days were 56.39 ± 18.08, 34.81 ± 12.59 μg/m3 and 468.93 ± 600.57 μg/m2 min, respectively. The mean TSP concentration in the smog period was 28% greater than that in the non-smog period, and the mean PM2.5 concentration was 20% higher. The mean dry deposition flux in the smog period was 70% higher than that in the non-smog period at Luliao. The PM2.5 concentrations exceeded the standards set by the Taiwan EPA (35 μg/m3 daily, and 15 μg/m3 annually). Therefore, the TSP and PM2.5 concentrations and dry deposition must be reduced in central Taiwan on smog days. In addition, atmospheric TSP and PM2.5 concentrations at various sampling sites were compared, and those herein were not higher than those measured in other countries. Finally, apart from the local traffic emissions, during smog periods, the other pollution source originated from the transportation process of traffic pollutants emitted in the northwest side of Taiwan.

Challenges for Integrating Strategic Environmental Assessment to Enhance Environmental Thinking: A Case Study of Taiwan Energy Policy

There is an increasing need to evaluate environmental impacts at higher policy planning levels, especially after the European Union (EU) strategic environmental assessment (SEA) directive proposed in 2001. However, integrating SEA and policy planning processes is challenging owing to institutional challenges and/or political problems. We aimed to explore the challenges of this integration process through in-depth interviews with core stakeholders in Taiwan energy policy making. Our results reveal three main types of challenge related to policy planning, SEA implementation, and difficulties in dealing with environmental issues. The first includes the policy planning model, transparency in the policy planning process, and controversial issues clarification; the second includes the different types of SEA purposes, unclear feedback on policy planning, and public participation limitation; the third includes a lack of knowledge of brokerage processes, scientific uncertainty, the role of the Taiwan EPA (TEPA) for environmental thinking, and the influence of local information in policy planning. The results of this study can be applied to countries that use impact-oriented SEA (currently the most common type of SEA) and consider environmental issues during the energy policy planning process.

Integrated electrokinetic processes for the remediation of phthalate esters in river sediments: A mini-review

Concerning the contamination of phthalate esters (PAEs) in river sediments, this mini-review introduces four recently reported novel “integrated electrokinetic (EK) processes” for the remediation purpose, namely two combined technologies of the EK process and advanced oxidation process (EK-AOP Processes) and two combined technologies of the EK process and biological process (EK-BIO Processes). The following is a comprehensive summary for these remediation processes: (1) the EK process coupled with nano-Fe3O4/S2O82− oxidation process – Test results have shown that nanoscale Fe3O4 played a significant role in activating persulfate oxidation. Even a recalcitrant compound like di(2‑ethylhexyl)phthalate (DEHP), its concentration in test sediment was reduced to 1.97 mg kg−1, far below the regulatory levels set by Taiwan EPA; (2) the EK process integrated with a novel Fenton-like process catalyzed by nanoscale schwertmannite (nano-SHM) – Test results have revealed that simultaneous injection of nano-SHM slurry and H2O2 into the anode reservoir and sediment compartment is a good practice. 70–99% in removal efficiency was obtained for various target PAEs; (3) enhanced in situ bioremediation coupled with the EK process for promoting the growth of intrinsic microorganisms by adding H2O2 as an oxygen release compound (ORC) – Test results have demonstrated that an intermittent mode of injecting lab-prepared ORC directly into the contaminant zone would be beneficial to the growth of intrinsic microorganisms in test sediment for in situ bioremediation of target PAEs; and (4) coupling of a second-generation ORC (designated 2G-ORC) with the EK-biological process – Test results have proved that 2G-ORC is long-lasting and can be directly utilized as the carbon source and oxygen source for microbial growth resulting in an enhanced biodegradation of PAEs. Except DEHP having a residual concentration of 4 μg kg−1, all other target PAEs in test sediment were totally removed by this novel combined remediation process.

Remediation of highly fuel oil-contaminated soil by food waste composting and its volatile organic compound (VOC) emission

Food waste composting was used to treat highly fuel oil-contaminated soil (two particle size fractions - fine < 0.3 cm and coarse > 1.3 cm). The initial fuel oil concentrations in the fine and coarse piles were 12,000 and 11,850 mg/kg, respectively. After 45-day incubation, the removal efficiencies of the fine and coarse piles were 82% and 93%, respectively. Residual fuel oil concentration (847 mg/kg) in the coarse pile met the Taiwan EPA standard limit (1000 mg/kg). The results indicated that the soil particle size fraction affected the efficiency of the composting treatment. Besides, emissions of oxygenated volatile organic compounds (OVOCs) and BTEXs from the food waste composting treatment were investigated. Ketones and toluene were the most abundant species of OVOCs and BTEXs, respectively. This study demonstrated that food waste composting would be a promising treatment technology for highly fuel oil-contaminated soil.

Characterization of PCDD/Fs and dioxin-like PCBs emitted from two woodchip boilers in Taiwan

This study investigates the formation and removal of PCDD/Fs and dl-PCBs in two woodchips boilers during different operating periods. Results indicate that combustion condition affects PCDD/F and dl-PCB formation within the woodchip combustion process. PCDD/F and dl-PCB concentrations during the start-up period are much higher than those measured during normal operation and shut-down periods due to unstable combustion. PCDD/F and dl-PCB concentrations at APCDs inlet of Plant A are significantly higher than that of Plant B due to the lower combustion temperature (500–850 °C) compared with Plant B (850–925 °C). Major PCDD/F congeners at APCDs inlet of both plants during normal operation are O8CDD, 1,2,3,4,6,7,8-H7CDD and 1,2,3,4,6,7,8-H7CDF, while major dl-PCBs are TeCB-77, PeCB-118 and PeCB-126. The removal efficiencies of PCDD/F and PCBs achieved with the APCDs of Plant A are 95.6% and 88.6%, respectively, while those of Plant B are 99.3% and 94.9%. Possibly, the AC concentration of Plant A exceeds the optimal AC concentration and, PCDD/Fs and dl-PCBs might be formed because the AC injected can supply additional reaction area and carbon source. Also, this may be due to different operating temperatures of APCDs, which affects removal efficiency of PCDD/F and dl-PCB congeners. The emission factors (PCDD/Fs + dl-PCBs) of Plants A and B are calculated as 17.86 and 1.25 μg I-TEQ/ton, respectively. Concentrations of PCDD/Fs in the BF ash of Plants A and B during normal operation are measured as 98.57 and 38.06 ng I-TEQ/g, which are significantly higher than the standard limit (1.0 ng I-TEQ/g) promulgated by Taiwan EPA.

Assessment of different route choice on commuters' exposure to air pollution in Taipei, Taiwan.

The purposes of this study are to develop a healthy commute map indicating cleanest route in Taipei metropolitan area for any given journey and to evaluate the pollutant doses exposed in different commuting modes. In Taiwan, there are more than 13.6 million motorcycles and 7.7 million vehicles among the 23 million people. Exposure to traffic-related air pollutants can thus cause adverse health effects. Moreover, increasing the level of physical activity during commuting and longer distances will result in inhalation of more polluted air. In this study, we utilized air pollution monitoring data (CO, SO2, NO2, PM10, and PM2.5) from Taiwan EPA's air quality monitoring stations in Taipei metropolitan area to estimate each pollutant exposure while commuting by different modes (motorcycling, bicycling, and walking). Spatial interpolation methods such as inverse distance weighting (IDW) were used to estimate each pollutant's distribution in Taipei metropolitan area. Three routes were selected to represent the variety of different daily commuting pathways. The cleanest route choice was based upon Dijkstra's algorithm to find the lowest cumulative pollutant exposure. The IDW interpolated values of CO, SO2, NO2, PM10, and PM2.5 ranged from 0.42-2.2 (ppm), 2.6-4.8 (ppb), 17.8-42.9 (ppb), 32.4-65.6 (μg/m3), and 14.2-38.9 (μg/m3), respectively. To compare with the IDW results, concentration of particulate matter (PM10, PM2.5, and PM1) along the motorcycle route was measured in real time. In conclusion, the results showed that the shortest commuting route for motorcyclists resulted in a much higher cumulative dose (PM2.5 3340.8μg/m3) than the cleanest route (PM2.5 912.5μg/m3). The mobile personal monitoring indicated that the motorcyclists inhaled significant high pollutants during commuting as a result of high-concentration exposure and short-duration peaks. The study could effectively present less polluted commuting routes for citizen health benefits.

Cellular Mutagenicity and Heavy Metal Concentrations of Leachates Extracted from the Fly and Bottom Ash Derived from Municipal Solid Waste Incineration.

Two incinerators in Taiwan have recently attempted to reuse the fly and bottom ash that they produce, but the mutagenicity of these types of ash has not yet been assessed. Therefore, we evaluated the mutagenicity of the ash with the Ames mutagenicity assay using the TA98, TA100, and TA1535 bacterial strains. We obtained three leachates from three leachants of varying pH values using the toxicity characteristic leaching procedure test recommended by the Taiwan Environmental Protection Agency (Taiwan EPA). We then performed the Ames assay on the harvested leachates. To evaluate the possible relationship between the presence of heavy metals and mutagenicity, the concentrations of five heavy metals (Cd, Cr, Cu, Pb, and Zn) in the leachates were also determined. The concentrations of Cd and Cr in the most acidic leachate from the precipitator fly ash and the Cd concentration in the most acidic leachate from the boiler fly ash exceeded the recommended limits. Notably, none of the nine leachates extracted from the boiler, precipitator, or bottom ashes displayed mutagenic activity. This data partially affirms the safety of the fly and bottom ash produced by certain incinerators. Therefore, the biotoxicity of leachates from recycled ash should be routinely monitored before reusing the ash.

Continuous sampling of MSWI dioxins.

Municipal solid waste incineration (MSWI) is generally considered as a well-controlled source of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), in brief dioxins. Start-up conditions continue, however, to be problematic. A self-developed continuous sampler was specially designed and built to fulfill the various sampling criteria of U.S. EPA Method 23 and monitor the trends of dioxins emissions during diverse operating conditions. In the MSWI plant investigated, a 98.1% TEQ PCDD/F removal efficiency was achieved in normal operation using activated carbon injection + bag filtration (ACI + BF) and the corresponding PCDD/F emission remains well below the standard set by Taiwan EPA (0.1 ng I-TEQ/Nm(3) @ 11% O2). During start-up, however, continuous sampling indicates that this limit value is reached only after 12 and 9 days, respectively for the 1st (2011) and 2nd test campaign (2012). Only 15 days after start-up the PCDD/F emissions shrunk to the levels typically measured during normal operation. The PCDD/F emissions from the 1st and 2nd continuous sampling campaigns were 5.4 and 5.5 mg I-TEQ, respectively. Short-term PCDD/F sampling such as the U.S. EPA Method 23 is less adapted to monitor these transient PCDD/F emissions representatively and accurately, due to a steady decrease of PCDD/F emissions after start-up. This self-developed continuous sampler effectively enhances the ease and reliability of emission data collecting during transient conditions of MSWI.