Waste to energy: air pollutant emissions from the steam boilers using recycled waste wood

In Taiwan, combustible wood mostly comes from waste pallets and scrap packaging materials discarded by factories, which produced a total of 278,067 tons of waste wood in 2019. In this study, the heat value of waste wood was 18.3 ± 1.07 MJ kg–1. The measured volatile fraction was 76.5 ± 7.34%, the fixed carbon was 15.7 ± 3.19%, the ash content was 2.96 ± 2.45%, and the moisture content was 21.6 ± 10.2%. The proportions of the elemental constituents in the waste wood were 45.3 ± 4.95%, 46.9 ± 3.94%, 5.9 ± 0.44%, 0.21 ± 0.17%, 0.29 ± 0.26%, and 0.02 ± 0.02% for carbon, oxygen, hydrogen, sulfur, nitrogen, and chlorine, respectively. The average boiler capacity was 11.5 ± 6.84 ton hr–1, the average fuel consumption of the boilers was 1.47 ± 1.81 ton hr–1, the average operating temperature of the boilers was 853 ± 228°C, the average steam generation of the boilers was 7.63 ± 5.97 ton hr–1, and the average exhaust flow rate was 246.6 ± 200.9 m3 min–1. The main air pollution control systems used in the waste wood combustion boilers were systems combining a cyclone, a baghouse and a scrubber (37.8%), a cyclone and a baghouse (28.4%), a cyclone and a scrubber (10.2%), and systems using a baghouse only (9.8%). Based on our fuel consumption data, the air pollutant emission factors were 0.71 ± 1.44 kg per ton of wood for PM, 0.86 ± 1.47 kg per ton of wood for SOx, and 5.24 ± 9.56 kg per ton of wood for NOx. In July 2022, new emission standards for boilers will be implemented, and emission reductions of at least 30% for PM, 35% for NOx and 7% for SO2 will be required

Mass-Size Distributions of Particulate Sulfate, Nitrate, and Ammonium in a Particulate Matter Nonattainment Region in Southern Taiwan

[[abstract]]Concentrations and distributions of three major water-soluble ion species (sulfate, nitrate, and ammonium) contained in ambient particles were measured at three sampling sites in the Kao-ping ambient air quality basin, Taiwan. Ambient particulate matter (PM) samples were collected in a Micro-orifice Uniform Deposit Impactor from February to July 2003 and were analyzed for water-soluble ion species with an ion chromatograph. The PM1/PM2.5 and PM1/PM10 concentration ratios at the emission source site were 0.73 and 0.53 and were higher than those (0.68 and 0.48) at the background site because there are more combustion sources (i.e., industrial boilers and traffic) around the emission source site. Mass-size distributions of PM NO3 − were found in both the fine and coarse modes. SO4 2− and NH4 + were found in the fine particle mode (PM2.5), with significant fractions of submicron particles (PM1). The source site had higher PM1/PM10 (79, 42, and 90%) and PM1/PM2.5 concentration ratios (90, 58, and 93%) for the three major inorganic secondary aerosol components (SO4 2−, NO3 −, and NH4 +) than the receptor site (65, 27, and 65% for PM1/PM10; 69, 51, and 70% for PM1/PM2.5). Results obtained in this study indicate that the PM1 (submicron aerosol particles) fraction plays an important role in the ambient atmosphere at both emission source and receptor sites. Further studies regarding the origin and formation of ambient secondary aerosols are planned

Airborne Air Pollutant Emission Characteristics of Mobile Vehicles in Taiwan

This study examines the air pollutant emission characteristics, activity intensity, and trends of mobile sources from 2013 to 2021. The target pollutants include criteria pollutants (fine particulate matters, nitrogen oxides, and hydrocarbons) and hazardous air pollutants (benzene, formaldehyde, and BaP). The results indicated that the activity intensity levels of road mobile sources in Taiwan were148 × 109, 156 × 109, 159 × 109, and 155 × 109 km/year in 2013, 2016, 2019, and 2021, respectively, with the largest proportion attributed to gasoline passenger cars (42.6%), followed by four-stroke motorcycles (32.6%). An emission factor of PM2.5 was estimated by EPA’s MOVES (Motor Vehicle Emission Simulator) model, and the results showed that the emission sequence was diesel > gasoline > motorcycle; the NOx emission factor was estimated using the MOBILE6.2 model, and the results showed that the order was diesel > gasoline > motorcycle; the HC emission factor was compiled with the use of gasoline vehicle dynamometer data, and the results showed that motorcycle > gasoline vehicles. Further results showed that the emission sequence for benzene was motorcycle > gasoline ≥ diesel; the formaldehyde emission sequence was diesel > motorcycle ≥ gasoline. The BaP emission factors of different vehicle types were estimated using MOVES, and the emission factors of old heavy-duty diesel vehicles were the highest

Development of a Face Prediction System for Missing Children in a Smart City Safety Network

Cases of missing children not being found are rare, but they continue to occur. If the child is not found immediately, the parents may not be able to identify the child’s appearance because they have not seen their child for a long time. Therefore, our purpose is to predict children’s faces when they grow up and help parents search for missing children. DNA paternity testing is the most accurate way to detect whether two people have a blood relation. However, DNA paternity testing for every unidentified child would be costly. Therefore, we propose the development of the Face Prediction System for Missing Children in a Smart City Safety Network. It can predict the faces of missing children at their current age, and parents can quickly confirm the possibility of blood relations with any unidentified child. The advantage is that it can eliminate incorrect matches and narrow down the search at a low cost. Our system combines StyleGAN2 and FaceNet methods to achieve prediction. StyleGAN2 is used to style mix two face images. FaceNet is used to compare the similarity of two face images. Experiments show that the similarity between predicted and expected results is more than 75%. This means that the system can well predict children’s faces when they grow up. Our system has more natural and higher similarity comparison results than Conditional Adversarial Autoencoder (CAAE), High Resolution Face Age Editing (HRFAE) and Identity-Preserved Conditional Generative Adversarial Networks (IPCGAN)

Traffic-Related Airborne VOC Profiles Variation on Road Sites and Residential Area within a Microscale in Urban Area in Southern Taiwan

The sampling sites, including roadsides and residential areas, were set up to collect ambient air and determine the volatile organic species it contained. For the roadside air, the average VOCs (volatile organic compounds) abundant at rush hour periods was two times that at non-rush hour periods. In the residential area, the VOC concentrationswere106 and 129 ppb during rush hour periods. The VOC concentration ratios of roadside and residential areas were in the range of 1.08–1.75 and the traffic emissions were related to the VOCs abundant in air. The highest VOC concentration was 168 ppb at midnight at residential sites and the VOC abundance could be two times that of roadside sites. This level of concentration could be attributed to the application of solvents and to human activity in a nearby motorcycle/vehicle maintenance plant, laundry rooms, etc. High abundant species were similar in both the roadside and residential air samples. These highly abundant species included toluene, acetone, acetonitrile, m,p-xylene and n-pentane, all of which can be emitted from traffic exhaust. Benzene, acrolein, formaldehyde, vinyl chloride and 1,3-butadiene were the main species with health impacts collected at both sites. In the micro-scale environment, the residential ambient air was affected by traffic flow from morning to night. In the midnight period, some local activities (a motorcycle/vehicle maintenance shop and laundry shops) affected the concentrations of certain VOCs (acetonitrile, toluene, hexane, 2-methylpentane, methyl cyclopentane and 3-methylpentane). The traffic and motor vehicles’ effects were determined, which could be useful for air quality management and strategy development in an urban area

Product Characteristics of Sludge Pyrolysis and Adsorption Performance of Metals by Char

The microwave heating system was used for sludge pyrolysis. The raw sludge and KOH-immersed sludge were pyrolyzed and their product characteristics were determined. The research results are advantageous to understand the influence of KOH activation on characteristics of pyrolysis products and the adsorption performance of metals in char. In the case of a high temperature and high KOH dose, most of the lost mass from sludge pyrolysis was converted into gaseous products instead of oil. The heat values of liquid oils were 40.86–41.39 MJ kg−1, which has the potential for use as fuels. The use of a higher KOH dose for sludge pyrolysis is beneficial to the porosity development and generates a mesopore structure. The results from adsorption tests indicate that precipitation could be the dominant adsorption mechanism due to the binding between alkaline anion and carbonate and metal ions with a strong chemical affinity. The high KOH dose sludge adsorbent has a remarkable adsorption performance and can be used as adsorbent for the removal of the studied metals