Ho-Wen Chen is currently a professor with Environmental Science and Engineering in Tunghai University of Taiwan. He received a B.S. degree in Environmental Science from Tunghai University in Taiwan in 1993, and M.S. and Ph.D. degrees in Environmental Engineering from National Cheng Kung University (NCKU) in 1995 and 1999, respectively. Since 2000, Dr. Chang has been directing academic research in the field of“Environmental Sustainability and Systems Analysis”. His areas of research include sustainable systems engineering, sustainability science, environmental and hydrological informatics and remote sensing, computational intelligence and soft computing, industrial ecology, ecological engineering, green infrastructure system planning, environmental and ecological systems modeling, and system control/engineering optimization.
Ho-Wen has received widespread recognition for his interdisciplinary research. As of Dec. 2013, Ho-Wen is the author or co-author of over 43 peer-reviewed journal papers. Articles published have been cited worldwide by over 449 cites as of Dec. 2012. He is the current associate editor of International Journal of Environmental Science and Technology and Journal Stochastic Environmental Research and Risk Assessment in addition to being an editorial board member of British Journal of Environment and Climate Change, international fellow of the UCF Stormwater Management Academy. Supervisors: Ni-Bin Chang
International Journal of Environmental Science & Technology, 2010
ABSTRACT Rapid development of information technology has changed people’s attitudes towards infor... more ABSTRACT Rapid development of information technology has changed people’s attitudes towards information usage. To tender to the public’s expectation, information system must feature facilities to increase the efficiency of information usage using modern information technology. Facing this challenge, it is necessary to establish a sustainable information environment, including information policy, data quality regulations and information management framework to deal with the rapidly increasing environmental data and changing behavior related to data/information usage except upgrading the hardware and software devices. Taking the uniqueness and complexity of environmental data into account, this study proposes a systematic framework based on the principle of life cycle assessment to outline the elements and its associated guidance required for a sustainable information environment. Simultaneously, the concept of information ecology is also embedded into such a planning for the purpose of establishing a self-evolutional information environment. Finally, the environmental protection administration of Taiwan is used as a case study to explain the practice of proposed framework.
Groundwater is indispensable water resource in coastal areas of Taiwan and is typically used foll... more Groundwater is indispensable water resource in coastal areas of Taiwan and is typically used following simple disinfection. Disinfection by-products (DBP), which are hazardous materials that are biologically toxic, are commonly produced. To elucidate the effect of environmental factors on the formulation of DBPs and arsenic species, and the effect of these factors on the bio-toxicity, data from a one-year monitoring program that was performed in a coastal area of central Taiwan were analyzed using the multivariate statistical method of redundancy analysis (RDA). The results reveal that the dominant DBP for trihalomethanes (THMs) was CHCl3 and for haloacetic acids (HAAs) was CHClBr2COOH (BDCAA). The formation of these compounds was most affected by the concentrations of humic substances and Br(-). As(5+) ions are abundant in the area close to the seashore and are the main source of biological toxicity. Cl(-), Br(-) and As(5+) concentrations were strongly correlated with biological to...
This paper presents a neural-fuzzy inference approach to identify the land use and land cover (LU... more This paper presents a neural-fuzzy inference approach to identify the land use and land cover (LULC) patterns in large urban areas with the 8-meter resolution of multi-spectral images collected by Formosat-2 satellite. Texture and feature analyses support the retrieval of fuzzy rules in the context of data mining to discern the embedded LULC patterns via a neural-fuzzy inference approach. The case study for Taichung City in central Taiwan shows the application potential based on five LULC classes. With the aid of integrated fuzzy rules and a neural network model, the optimal weights associated with these achievable rules can be determined with phenomenological and theoretical implications. Through appropriate model training and validation stages with respect to a groundtruth data set, research findings clearly indicate that the proposed remote sensing technique can structure an improved screening and sequencing procedure when selecting rules for LULC classification. There is no limitation of using broad spectral bands for category separation by this method, such as the ability to reliably separate only a few (4-5) classes. This normalized difference vegetation index (NDVI)-based data mining technique has shown potential for LULC pattern recognition in different regions, and is not restricted to this sensor, location or date.
Journal of the Taiwan Institute of Chemical Engineers, 2014
ABSTRACT The nanoscale zero valent iron-Fenton (nZVI-Fenton) process combines the advantages of n... more ABSTRACT The nanoscale zero valent iron-Fenton (nZVI-Fenton) process combines the advantages of nZVI reduction and Fenton oxidation, was regarded as a very effective process for the treatment of azo-dye/textile wastewater. In this paper, we present the results of the investigation of the on-line monitoring of oxidation–reduction potential (ORP), pH, and dissolved oxygen (DO) to evaluate the effectiveness of the nZVI-Fenton process for the removal of color and chemical oxygen demand (COD) from azo-dyes textile wastewater. The experimental results indicated that the optimal doses of nZVI and H2O2 for color removal were 60–80 mg/L and 300–400 mg/L, respectively. The nZVI reduction removed around 80–90% of the color; however, less than 15% of the COD was removed. To attain the desired removal of COD, much higher doses of nZVI and H2O2 were required, i.e., 200–225 mg/L and 1000–1125 mg/L, respectively. ORP, pH, and DO had direct and meaningful correlations with the removal efficiencies of both color and COD. Thus, regression models and artificial neural networks (ANN) models were used to predict the color and COD removal efficiencies using the monitoring data acquired for ORP, pH, and DO. The ANN model provided very precise prediction results with R2 values in the range of 0.96–0.99. The predictions provided by the regression model had R2 values in the range of 0.92–0.95. These results indicated that on-line ORP, DO, and pH monitoring data can be used as input to either model to obtain a reliable evaluation of the effectiveness of the nZVI-Fenton process for the removal of color and COD from azo-dyes textile wastewater.
In this study, a Cummins B5 diesel engine was set up to operate on a dynamometer under the US tra... more In this study, a Cummins B5 diesel engine was set up to operate on a dynamometer under the US transient cycle. Twenty-four diesel fuels were tested. Regulated air pollutants (HC, CO, NOx, particulate matter) and polycyclic aromatic hydrocarbon (PAH) emissions were meas- ured. PAH was analyzed by gas chromatography/mass spectrometer detector (GC/MS). The av- erage emission factors were 0.32, 2.1,
... GICS Level 10 by the staff in the Center for Space and Remote Sensing Re-search ... Instead o... more ... GICS Level 10 by the staff in the Center for Space and Remote Sensing Re-search ... Instead of using advanced direct matching algorithms, this study applied a different method in which ... due to the measurement error of the study area, the discrepancy among integration of three ...
Limited to insufficient land resources, incinerators are considered in many countries such as Jap... more Limited to insufficient land resources, incinerators are considered in many countries such as Japan and Germany as the major technology for a waste management scheme capable of dealing with the increasing demand for municipal and industrial solid waste treatment in urban regions. The evaluation of these municipal incinerators in terms of secondary pollution potential, cost-effectiveness, and operational efficiency has become a new focus in the highly interdisciplinary area of production economics, systems analysis, and waste management. This paper aims to demonstrate the application of data envelopment analysis (DEA)--a production economics tool--to evaluate performance-based efficiencies of 19 large-scale municipal incinerators in Taiwan with different operational conditions. A 4-year operational data set from 2002 to 2005 was collected in support of DEA modeling using Monte Carlo simulation to outline the possibility distributions of operational efficiency of these incinerators. Uncertainty analysis using the Monte Carlo simulation provides a balance between simplifications of our analysis and the soundness of capturing the essential random features that complicate solid waste management systems. To cope with future challenges, efforts in the DEA modeling, systems analysis, and prediction of the performance of large-scale municipal solid waste incinerators under normal operation and special conditions were directed toward generating a compromised assessment procedure. Our research findings will eventually lead to the identification of the optimal management strategies for promoting the quality of solid waste incineration, not only in Taiwan, but also elsewhere in the world.
One of the costs of Taiwan&am... more One of the costs of Taiwan's massive economic development has been severe air pollution problems in many parts of the island. Since vehicle emissions are the major source of air pollution in most of Taiwan's urban areas, Taiwan's government has implemented policies to rectify the degrading air quality, especially in areas with high population density. To reduce vehicle pollution emissions an on-road remote sensing and monitoring system is used to check the exhaust emissions from gasoline engine automobiles. By identifying individual vehicles with excessive emissions for follow-up inspection and testing, air quality in the urban environment is expected to improve greatly. Because remote sensing is capable of measuring a large number of moving vehicles in a short period, it has been considered as an assessment technique in place of the stationary emission-sampling techniques. However, inherent measurement uncertainty of remote sensing instrumentation, compounded by the indeterminacy of monitoring site selection, plus the vagaries of weather, causes large errors in pollution discrimination and limits the application of the remote sensing. Many governments are still waiting for a novel data analysis methodology to clamp down on heavily emitting vehicles by using remote sensing data. This paper proposes an artificial neural network (ANN), with vehicle attributes embedded, that can be trained by genetic algorithm (GA) based on different strategies to predict vehicle emission violation. Results show that the accuracy of predicting emission violation is as high as 92%. False determinations tend to occur for vehicles aged 7-13 years, peaking at 10 years of age.
This study applies on-line pH and oxidation-reduction potential (ORP) monitoring and artificial n... more This study applies on-line pH and oxidation-reduction potential (ORP) monitoring and artificial neural network models to dynamically control the wastewater chlorination and dechlorination dosage for reuse purposes. A series of wastewater chlorination and dechlorination experiments were conducted in a continuous laboratory-scale reactor. The ORP and pH variations in raw wastewater, and chlorination and dechlorination reactors were monitored on-line. Artificial neural networks (ANNs) were used to build control models using the monitored ORP and pH data. Another series of continuous experiments were conducted to evaluate the proposed control strategy for meeting different requirements for total coliform counts and residual chlorine concentrations for different wastewater reclamation purposes. The dynamical controlled experimental results show that chlorination and dechlorination were effectively controlled, and that appropriate disinfection efficiencies were achieved and remaining chlorine residuals in effluent were controlled simultaneously for different treatment targets. This ANN control method is simple and has potential benefits in reducing chemical costs for wastewater chlorination and dechlorination.
This study assessed the concentrations of five volatile organic compounds (VOCs), including BTEX ... more This study assessed the concentrations of five volatile organic compounds (VOCs), including BTEX (the acronym for benzene, toluene, ethylbenzene, and xylene) and methyl tertiary-butyl ether (MTBE), in six different industrial park neighborhoods in southern Taiwan, including the Nei-Pu, Ping-Tung, Ping-Nan, Ren-Wu, Lin-Yuan and Nan-Zi industrial parks. The concentrations of MTBE and BTEX ranged from undetectable to 145.6 microg/m3. Average MTBE-BTEX ratios of Nei-Pu, Ping-Tung, Ping-Nan, Ren-Wu, Lin-Yuan and Nan-Zi were (13.4:3.6:4.7:1.0:7.4), (2.9:1.0:1.7:1.3:2.9), (3.0:1.0:2.7:1.0:2.7), (5.2:1.0:8.6:1.7:4.9), (3.1:3.1:2.8:1.0:3.3) and (4.3:1.2:3.6:1.0:3.8), respectively. Moreover, average T/B ratios in Nei-Pu, Ping-Tung, Ping-Nan, Ren-Wu, Lin-Yuan and Nan-Zi were 1.3, 1.7, 2.6, 8.6, 0.9 and 2.9, respectively. High T/B ratio (8.6) in the neighborhood of the Ren-Wu industrial park suggested that the emission of large additional sources of toluene from this industrial park, or the existence of major differences in the auxiliary fuels used. Average X/E ratios in Nei-Pu, Ping-Tung, Ping-Nan, Ren-Wu, Lin-Yuan and Nan-Zi were 7.4, 2.2, 2.7, 2.9, 3.3 and 3.8, respectively. The lower X/E ratio (2.2) in the Ping-Tung neighborhood compared to elsewhere indicates an aged air parcel. Furthermore, principal component analysis also confirmed that the dominant influences in the six different industrial park neighborhoods were related to the emissions of MTBE, benzene and toluene.
International Journal of Environmental Science & Technology, 2010
ABSTRACT Rapid development of information technology has changed people’s attitudes towards infor... more ABSTRACT Rapid development of information technology has changed people’s attitudes towards information usage. To tender to the public’s expectation, information system must feature facilities to increase the efficiency of information usage using modern information technology. Facing this challenge, it is necessary to establish a sustainable information environment, including information policy, data quality regulations and information management framework to deal with the rapidly increasing environmental data and changing behavior related to data/information usage except upgrading the hardware and software devices. Taking the uniqueness and complexity of environmental data into account, this study proposes a systematic framework based on the principle of life cycle assessment to outline the elements and its associated guidance required for a sustainable information environment. Simultaneously, the concept of information ecology is also embedded into such a planning for the purpose of establishing a self-evolutional information environment. Finally, the environmental protection administration of Taiwan is used as a case study to explain the practice of proposed framework.
Groundwater is indispensable water resource in coastal areas of Taiwan and is typically used foll... more Groundwater is indispensable water resource in coastal areas of Taiwan and is typically used following simple disinfection. Disinfection by-products (DBP), which are hazardous materials that are biologically toxic, are commonly produced. To elucidate the effect of environmental factors on the formulation of DBPs and arsenic species, and the effect of these factors on the bio-toxicity, data from a one-year monitoring program that was performed in a coastal area of central Taiwan were analyzed using the multivariate statistical method of redundancy analysis (RDA). The results reveal that the dominant DBP for trihalomethanes (THMs) was CHCl3 and for haloacetic acids (HAAs) was CHClBr2COOH (BDCAA). The formation of these compounds was most affected by the concentrations of humic substances and Br(-). As(5+) ions are abundant in the area close to the seashore and are the main source of biological toxicity. Cl(-), Br(-) and As(5+) concentrations were strongly correlated with biological to...
This paper presents a neural-fuzzy inference approach to identify the land use and land cover (LU... more This paper presents a neural-fuzzy inference approach to identify the land use and land cover (LULC) patterns in large urban areas with the 8-meter resolution of multi-spectral images collected by Formosat-2 satellite. Texture and feature analyses support the retrieval of fuzzy rules in the context of data mining to discern the embedded LULC patterns via a neural-fuzzy inference approach. The case study for Taichung City in central Taiwan shows the application potential based on five LULC classes. With the aid of integrated fuzzy rules and a neural network model, the optimal weights associated with these achievable rules can be determined with phenomenological and theoretical implications. Through appropriate model training and validation stages with respect to a groundtruth data set, research findings clearly indicate that the proposed remote sensing technique can structure an improved screening and sequencing procedure when selecting rules for LULC classification. There is no limitation of using broad spectral bands for category separation by this method, such as the ability to reliably separate only a few (4-5) classes. This normalized difference vegetation index (NDVI)-based data mining technique has shown potential for LULC pattern recognition in different regions, and is not restricted to this sensor, location or date.
Journal of the Taiwan Institute of Chemical Engineers, 2014
ABSTRACT The nanoscale zero valent iron-Fenton (nZVI-Fenton) process combines the advantages of n... more ABSTRACT The nanoscale zero valent iron-Fenton (nZVI-Fenton) process combines the advantages of nZVI reduction and Fenton oxidation, was regarded as a very effective process for the treatment of azo-dye/textile wastewater. In this paper, we present the results of the investigation of the on-line monitoring of oxidation–reduction potential (ORP), pH, and dissolved oxygen (DO) to evaluate the effectiveness of the nZVI-Fenton process for the removal of color and chemical oxygen demand (COD) from azo-dyes textile wastewater. The experimental results indicated that the optimal doses of nZVI and H2O2 for color removal were 60–80 mg/L and 300–400 mg/L, respectively. The nZVI reduction removed around 80–90% of the color; however, less than 15% of the COD was removed. To attain the desired removal of COD, much higher doses of nZVI and H2O2 were required, i.e., 200–225 mg/L and 1000–1125 mg/L, respectively. ORP, pH, and DO had direct and meaningful correlations with the removal efficiencies of both color and COD. Thus, regression models and artificial neural networks (ANN) models were used to predict the color and COD removal efficiencies using the monitoring data acquired for ORP, pH, and DO. The ANN model provided very precise prediction results with R2 values in the range of 0.96–0.99. The predictions provided by the regression model had R2 values in the range of 0.92–0.95. These results indicated that on-line ORP, DO, and pH monitoring data can be used as input to either model to obtain a reliable evaluation of the effectiveness of the nZVI-Fenton process for the removal of color and COD from azo-dyes textile wastewater.
In this study, a Cummins B5 diesel engine was set up to operate on a dynamometer under the US tra... more In this study, a Cummins B5 diesel engine was set up to operate on a dynamometer under the US transient cycle. Twenty-four diesel fuels were tested. Regulated air pollutants (HC, CO, NOx, particulate matter) and polycyclic aromatic hydrocarbon (PAH) emissions were meas- ured. PAH was analyzed by gas chromatography/mass spectrometer detector (GC/MS). The av- erage emission factors were 0.32, 2.1,
... GICS Level 10 by the staff in the Center for Space and Remote Sensing Re-search ... Instead o... more ... GICS Level 10 by the staff in the Center for Space and Remote Sensing Re-search ... Instead of using advanced direct matching algorithms, this study applied a different method in which ... due to the measurement error of the study area, the discrepancy among integration of three ...
Limited to insufficient land resources, incinerators are considered in many countries such as Jap... more Limited to insufficient land resources, incinerators are considered in many countries such as Japan and Germany as the major technology for a waste management scheme capable of dealing with the increasing demand for municipal and industrial solid waste treatment in urban regions. The evaluation of these municipal incinerators in terms of secondary pollution potential, cost-effectiveness, and operational efficiency has become a new focus in the highly interdisciplinary area of production economics, systems analysis, and waste management. This paper aims to demonstrate the application of data envelopment analysis (DEA)--a production economics tool--to evaluate performance-based efficiencies of 19 large-scale municipal incinerators in Taiwan with different operational conditions. A 4-year operational data set from 2002 to 2005 was collected in support of DEA modeling using Monte Carlo simulation to outline the possibility distributions of operational efficiency of these incinerators. Uncertainty analysis using the Monte Carlo simulation provides a balance between simplifications of our analysis and the soundness of capturing the essential random features that complicate solid waste management systems. To cope with future challenges, efforts in the DEA modeling, systems analysis, and prediction of the performance of large-scale municipal solid waste incinerators under normal operation and special conditions were directed toward generating a compromised assessment procedure. Our research findings will eventually lead to the identification of the optimal management strategies for promoting the quality of solid waste incineration, not only in Taiwan, but also elsewhere in the world.
One of the costs of Taiwan&am... more One of the costs of Taiwan's massive economic development has been severe air pollution problems in many parts of the island. Since vehicle emissions are the major source of air pollution in most of Taiwan's urban areas, Taiwan's government has implemented policies to rectify the degrading air quality, especially in areas with high population density. To reduce vehicle pollution emissions an on-road remote sensing and monitoring system is used to check the exhaust emissions from gasoline engine automobiles. By identifying individual vehicles with excessive emissions for follow-up inspection and testing, air quality in the urban environment is expected to improve greatly. Because remote sensing is capable of measuring a large number of moving vehicles in a short period, it has been considered as an assessment technique in place of the stationary emission-sampling techniques. However, inherent measurement uncertainty of remote sensing instrumentation, compounded by the indeterminacy of monitoring site selection, plus the vagaries of weather, causes large errors in pollution discrimination and limits the application of the remote sensing. Many governments are still waiting for a novel data analysis methodology to clamp down on heavily emitting vehicles by using remote sensing data. This paper proposes an artificial neural network (ANN), with vehicle attributes embedded, that can be trained by genetic algorithm (GA) based on different strategies to predict vehicle emission violation. Results show that the accuracy of predicting emission violation is as high as 92%. False determinations tend to occur for vehicles aged 7-13 years, peaking at 10 years of age.
This study applies on-line pH and oxidation-reduction potential (ORP) monitoring and artificial n... more This study applies on-line pH and oxidation-reduction potential (ORP) monitoring and artificial neural network models to dynamically control the wastewater chlorination and dechlorination dosage for reuse purposes. A series of wastewater chlorination and dechlorination experiments were conducted in a continuous laboratory-scale reactor. The ORP and pH variations in raw wastewater, and chlorination and dechlorination reactors were monitored on-line. Artificial neural networks (ANNs) were used to build control models using the monitored ORP and pH data. Another series of continuous experiments were conducted to evaluate the proposed control strategy for meeting different requirements for total coliform counts and residual chlorine concentrations for different wastewater reclamation purposes. The dynamical controlled experimental results show that chlorination and dechlorination were effectively controlled, and that appropriate disinfection efficiencies were achieved and remaining chlorine residuals in effluent were controlled simultaneously for different treatment targets. This ANN control method is simple and has potential benefits in reducing chemical costs for wastewater chlorination and dechlorination.
This study assessed the concentrations of five volatile organic compounds (VOCs), including BTEX ... more This study assessed the concentrations of five volatile organic compounds (VOCs), including BTEX (the acronym for benzene, toluene, ethylbenzene, and xylene) and methyl tertiary-butyl ether (MTBE), in six different industrial park neighborhoods in southern Taiwan, including the Nei-Pu, Ping-Tung, Ping-Nan, Ren-Wu, Lin-Yuan and Nan-Zi industrial parks. The concentrations of MTBE and BTEX ranged from undetectable to 145.6 microg/m3. Average MTBE-BTEX ratios of Nei-Pu, Ping-Tung, Ping-Nan, Ren-Wu, Lin-Yuan and Nan-Zi were (13.4:3.6:4.7:1.0:7.4), (2.9:1.0:1.7:1.3:2.9), (3.0:1.0:2.7:1.0:2.7), (5.2:1.0:8.6:1.7:4.9), (3.1:3.1:2.8:1.0:3.3) and (4.3:1.2:3.6:1.0:3.8), respectively. Moreover, average T/B ratios in Nei-Pu, Ping-Tung, Ping-Nan, Ren-Wu, Lin-Yuan and Nan-Zi were 1.3, 1.7, 2.6, 8.6, 0.9 and 2.9, respectively. High T/B ratio (8.6) in the neighborhood of the Ren-Wu industrial park suggested that the emission of large additional sources of toluene from this industrial park, or the existence of major differences in the auxiliary fuels used. Average X/E ratios in Nei-Pu, Ping-Tung, Ping-Nan, Ren-Wu, Lin-Yuan and Nan-Zi were 7.4, 2.2, 2.7, 2.9, 3.3 and 3.8, respectively. The lower X/E ratio (2.2) in the Ping-Tung neighborhood compared to elsewhere indicates an aged air parcel. Furthermore, principal component analysis also confirmed that the dominant influences in the six different industrial park neighborhoods were related to the emissions of MTBE, benzene and toluene.
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Papers by Ho-Wen Chen