蘇泓瑋

台灣各產業物質足跡分析與資源效率指標評估

Material Footprints of Taiwan’s Economy: Analyses by Industries and Comparison between Domestic Consumption, Import, and Export Contribution

SUMMARY

With the development of world economy and technology, the global demand for resources is increasing, which is a considerable burden on limited natural resources. Taiwan is a country with scarce natural resources. According to the data of the general database, the dependence on foreign trade in 2022 will be 118.5%, and the dependence on imports will be 55.9%, showing that Taiwan is a country highly dependent on imports. Therefore, in order to avoid resource shortages caused by international situations or prices, how to allocate resources has become an important issue.

This study mainly uses the domestically published industry association table, and refers to the data of the Exiobase 3 database to sort out the interdependence relationship among various domestic industries. Then, according to the material footprint (MF) calculation formula announced by the European Union, calculate the raw materials equivalent (RME) of imported and exported, and analyze the distribution of materials in various industries. The current results show that high-tech industries such as the metal industry and the electronics industry, as well as processing industries, mainly export, while relatively basic industries mainly imports.

Through the analysis of material footprint, this research hopes to analyze the general situation of material use in domestic industries, so as to understand the flow and quantity of material use. It is hoped that relevant enterprises or governments can find potential sources of pollution based on these data, so as to make corresponding material input planning or improvement plans.

凃欣宇

利用機器學習開發空氣污染排放設施未妥善控制而排放之預警模型

Developing prediction models for factories’ illegal air pollution emissions using the machine learning techniques

SUMMARY

When inspecting illegal discharges of air pollution, how to improve inspection efficiency is an important issue for inspection units. Machine learning analysis helps to find hidden correlations between data and output prediction results, and formulate control strategies based on the prediction results, which is also the development direction of environmental law enforcement in recent years.

Therefore, this study will establish a predictive model for inspection of non-compliance cases, and predict the daily behavior of illegal air pollutant emissions without proper control of polluting equipment. The research focuses on fixed pollution sources. The predicted labels are from Environmental Inspection and Punishment Control System. Additionally, raw materials, waste declarations, meteorological data, air quality index, IoT-based microsensors data, CEMS monitoring data are used as predictive data. The study analyzes the associations between different environmental factors and factories’ non-compliance behavior.

Regarding model training, various feature selection methods, and data pre-processing methods such as PCA and Positive-Unlabeled (PU) learning algorithms are explored to investigate their impact on the dataset.

The results of the correlation analysis indicate that on days when factory violations occur, the air quality in the vicinity of the factories is generally poorer, and higher past violation frequencies increase the likelihood of subsequent non-compliance.

The model predictions reveal that the best-performing pipeline, involves no feature selection, PU learning with re-labeling, PCA dimensionality reduction, and training a Multilayer Perceptron (MLP) classifier after applying SMOTE for class balancing. The achieved F1-score reaches a maximum of 0.508.

黃沛靜

整合投入產出分析開發產業供應鏈空污與碳排放資訊工具

Development of an integrated input-output analysis tool for assessing air pollution and carbon emissions across industries' supply chains

SUMMARY

In the global drive for decarbonization, businesses are compelled to conduct carbon audits and devise decarbonization strategies to stay competitive in the sustainable performance market. However, the main challenge they face in their low-carbon transition is a lack of funds and technology. They need to seek transformation loans or financing from banks. Hence, they may struggle to provide comprehensive decarbonization plans for bank review.

This study aims to develop a simplified information tool that can rapidly assess the environmental and social impact hotspots of the industrial supply chain and provide investment risk assessment. The tool will employ environmental input-output analysis and emission coefficient methods to estimate the environmental impact hotspots of supply chain activities. The resulting environmental damages will be quantified in monetary terms. Additionally, the tool will utilize a trend extrapolation method to establish practical decarbonization targets for businesses. It will also consolidate publicly available data from government agencies to facilitate easy access to relevant information for businesses and the financial sector.

After validating the research model, the study identified several significant findings. (1) the model estimates higher emissions than the reported carbon emissions data by companies, revealing previously unrecognized emissions, including Scope 3 emissions. (2) in manufacturing industries, the estimated environmental impact closely corresponds to the expected impact. (3) the screening tool provides results that closely approximate actual emissions, considering industry characteristics and the dependence on imports and exports.

柯威廷

整合排除屋頂特定結構及裝置之方法於屋頂太陽光電潛力評估:以南科台南園區為例

Rooftop photovoltaic potential evaluation by integrating the method to exclude the roof area occupied by structures and devices: A study on Tainan Science Park

SUMMARY

In recent years, the Taiwanese government has been actively promoting energy transition. Due to Taiwan's abundant solar energy resources, its high concentration of buildings, and urbanized land use patterns, the government has identified rooftop photovoltaic (PV) as a key focus for renewable energy development. Evaluating rooftop PV potential is crucial in promoting the deployment of rooftop PV systems. In previous research, the GIS-based modeling methods have been considered practical and effective for estimating the available area for rooftop PV. However, the GIS-based modeling methods often require manual inspection to assist in analyzing the influence of roof objects on the available roof area. Alternatively, high-resolution Digital Surface Model (DSM) data with a spatial resolution of ≤ 0.25m is necessary to accurately identify roof objects. However, acquiring DSM data with such high precision is a challenging task. Therefore, our study attempts to improve the limitations of rooftop object identification in the GIS-based modeling methods by integrating the Mask R-CNN instance segmentation model. We consider the Tainan Science Park as the research area and aim to analyze the rooftop photovoltaic potential in this region while considering multiple roof suitability factors.

梁芳綺

整合臺灣廢棄物數據估算建築都市礦及

預測二次建材資源產量－

以臺北市與高雄市為例

Analysis of Building Material Stocks Using Demolition Waste Data and Secondary Resources Prediction: Cases of Taipei City and Kaohsiung City

SUMMARY

When the circular economy has attracted much attention in recent years, urban mine has become one popular research topic. However, the most used inventory approaches are demanding for data. Therefore, many studies are hard to juggle the discussion over spatial analysis of urban mines and accurate inventory calculation. In our case, we collected the government datasets that had been well-archived and preserved electronically. So, we can combine two common inventory approaches.

This study used Building Use Permit data and Waste Disposal Plans data. After data processing and spatial data integration, 2,630 demolition cases were finally obtained, mostly located in Taipei City and Kaohsiung City. By analyzing these demolition cases, we conducted a building lifetime analysis and calculated the building material intensities. According to the above results, the material intensities and lifetimes of real buildings are predicted by Monte Carlo simulations, and then future urban mineral outflows can be estimated. 

According to the results, we obtained more kinds of material intensities data than in previous studies in Taiwan. In addition, we examined the lifetime distribution for different types of buildings in the municipality of Taiwan. Based on this detailed data preparation and modeling, the spatiotemporal analysis of building materials in cities and the time for exploitation are presented. 

周芳汝

印刷電路板製造成本診斷與降低策略

—銅循環導向物質流成本會計工具開發

與分析應用

Diagnosis of Cost Reduction Potential for Printed Circuit Board Manufacturers by Recycling Copper

－Tool Development and Analysis with Material Flow Cost Accounting

SUMMARY

With the rapid development of a low-carbon economy, the copper resources demand is increasing. Taiwan, highly dependent on imports, may face a shortage of copper resources in the future. Taiwan's government has been promoting circular economy in recent years and hopes to sustainably manage copper resources and reduce the potential risks of copper resource. However, there is still a problem of losing copper resources through the flows of industrial wastes in Taiwan. Therefore, this study intends to take the printed circuit board manufacturing industry as the research object, and adopt the circular economy strategy of in-plant copper recycling.

This study conducted a Material Flow Analysis (MFA) to analyze the utilization of copper resources and potential recycling sites in the printed circuit board manufacturing industry. Then, we select four plants as sample to analyzed the impact of implementing copper recycling in-plant by a Material Flow Cost Accounting (MFCA)-based model. In process, we implement two recycling programs and eight recycling rate scenarios to discuss the impact on plant’s economics and waste management benefits.

The results show that after each plant implements in-plant copper recycling, both recycling programs can contribute to significant waste management benefit. Regarding economic benefit, the material loss costs mainly affected the waste hidden costs. Additionally, the copper weight of waste influenced the input cost of the recycling process and the value of recycled products. Finally, both benefits results showed that process-by-process copper recycling program is a better solution for most plants.

Sum up, this research institute established a Material Flow Cost Accounting (MFCA)-based model for copper recycling in printed circuit board manufacturing plants, which can assist plants in benefits analysis and provide suggestions for better copper recycling programs in-plant, and can also be used as a reference for the government or industry to promote copper resources for circulation in Taiwan in the future.

李冠緯

運用廢棄物產出投入分析工業區產業共生現況及與其他區域資源整合機會 

Analysis of waste inputs and outputs for by-product synergies in an industrial park and the potential to improve industrial symbiosis by regional resources integration

SUMMARY

Industrial Symbiosis (IS) is an ecosystem-like industrial cooperation model. Waste produced by an industry can be used as material in another industry. The lack of information between operators limits the identification of symbiosis opportunities. Many studies have found that information tools have great potential in solving information barriers and promoting industrial symbiosis. Based on Taiwan's waste input and output database, this study developed an IS information system, which includes five application functions designed for different query needs. 

To verify that this IS tools developed in this study can effectively find IS potential, Tainan Guantian is selected as the object of the regional case study. Use the regional matching function to query the IS potential of Guantian District, the wastes that have not been properly reused are inorganic sludge, lead and its compounds. According to the function of waste matching results, it is found that the pre-mixed concrete manufacturing industry has good reusing potential. There are ready-mixed concrete manufacturing industries in the Guantian, Shanhua, Madou, Xinying and Shanshang districts. The cross-regional matching of industrial parks has increased the overall waste recycling rate from 60.9% to 73.6%. In terms of the amount of reuse, through cross-regional symbiosis, many wastes in Guantian District that could not be reused, such as D-0902 and D-1199, are reused. The waste cost saved by increasing the amount of reuse is nearly 40 million NTD. It can be seen that cross-regional matching can bring economic benefits.

張簡睿豪

運用WIO表的架構為基礎發展循環減碳評估模式與塑膠循環多情境分析

Waste input-output model for Taiwan’s carbon reduction potential of the policy goals for plastic circulation and multi-scenario analysis

SUMMARY

As the impacts of global warming have become obvious, countries worldwide have begun to mitigate greenhouse gas (GHG) emissions, hoping to slow down the speed of climate change. Many think tanks have recognized the transition toward circular economies with significant GHGs reduction potential in many countries. The closed supply chains and maximized resource efficiency can reduce the energy requirements in raw material extraction, processing, and manufacturing. In a circular economy, the recycling system can also reuse the materials at the end of the product life cycle. Thus, the carbon footprint of the second life cycle might be significantly reduced. To assess the reduction potential for a circular economic system, a comprehensive analysis should consider the relationship between the industrial and waste management systems. This study evaluated the carbon reduction potential for different plastic circulation policy goals with scenario analyses from the waste input-output perspective. First, we integrated various industrial and waste stream datasets to establish a waste input-output model. Then, we combined GHG emissions data to evaluate the GHG emissions for each sector. The scenarios being analyzed include the plastic packaging reduction goals proposed by the Taiwan EPA and the four circular patterns mentioned in an article of the Journal of Economic Structures. The results show that improvement in plastic recycling has a more carbon reduction on other upstream industrial sectors than the “plastic products” sector. Looking at the inter-industrial linkages, the reduced demand for plastic could effectively reduce the GHG emissions from the petrochemical and chemical material industries.

卓冠廷

以機器學習開發事業廢水未妥善處理排放潛勢之預測模型

Potential prediction models for the discharge of industrial wastewater without normal treatment based on machine learning

SUMMARY

Discharging wastewater without treatment causes environmental pollution. Industrial wastewater contains pollutants that could be hazardous to human health. In order to reduce the cost of water treatment, factories illegally discharge the industrial wastewater directly or with an underground pipeline. Environmental inspection is a method to prevent illicit wastewater discharge. However, the low efficiency results in the short-staffed problem. Therefore, building a crime forecasting system to be a decision-making supporting tool can predict the illegal event to help environmental agencies have appropriate staffing deployment. Since crime is a complex social problem, developing a crime forecasting system with machine learning can overcome non-linear, heterogeneous, and unknown feature importance problems. Observing the changes in waste sludge amount, we transform the data into binary format to indicate the probability of illegal discharges. The research is divided into two experiments due to the drastic decrease of waste sludge during the lunar New Year. Scenario.1 remains original data, and scenario.2 excludes February data. We selected precipitation, river quality, city, and population density to be the predicting features, and used Synthetic Minority Oversampling Technique (SMOTE) and Random Undersampling to solve imbalance data problem, and performed machine learning with Random Forest (RF), K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and Multilayer Perceptron (MLP). The best result is scenario.2, which excluding February data with SMOTE and RF algorithm. Three industries applicable for building prediction models were Printed Circuit Boards with AUC 0.83, surface treatments with AUC 0.765, and IC manufacturing with AUC 0.75. Validating models with wastewater punishments records, the rates for all industries were above 15%, which were higher than the efficiency of environmental inspection.

李婕瑜

以個體行為導向模型模擬自行車路網對公共自行車系統使用之影響與環境效益-以臺北市為例

Agent-based modeling for bike-lane network’s influence on a bike-sharing system and environmental benefits with a case study of Taipei

SUMMARY

The rapid expansion of the Bike Sharing Systems (BSS) in recent years has not only complemented the first or last mile of the public transportation system, but also replaced some short-distance trips by private vehicles. Previous studies have analyzed the travel behaviors of BSS users and the factors that affect their willingness to use them. However, few studies have done quantitative analysis on riding environment factors. Therefore, using the YouBike system in Taipei City as the subject, this research analyzed the impacts of Taipei City’s three horizontal and three vertical bikeway networks. The trip data of the YouBike system were analyzed with tailor-made data mining for building a model with a bikeway network that allows the public to choose travel modes and times. The agent-based model was developed to simulate the decision-making behaviors of trips in Taipei. This study presents the simulation results of the scenarios with and without bike lanes and the scenario with improved bicycle lanes. The changes in people’s choice of their travel modes vehicles generate environmental benefits of reduced air pollution and environmental impacts. The results show that when a bike-lane network becomes accessible, the mobile air pollutant emissions can be 12.7% less than the situation without a bike-lane network. And the reduced environmental impact proportions are 10.8%, 11.5%, and 12.2% than the scenario without a bike-lane network at human health, ecosystem, and resource. In addition, the improvement on bike lane road conditions (including width and continuity) has a slightly higher effect on reducing air pollutants and environmental impacts by about 0.2%. The simulation model built in this study can display the distribution of the trips hiring public bikes and show the dynamic change in the calculated environmental benefits (air pollutant emissions and environmental impact), which can be used as a reference for policymakers in the future.

林姿蓉

臺灣短期細懸浮微粒與氣喘之關聯性分析—

健保資料庫與政府民間空品資料之整合應用

Relationships between asthma and short-term exposure to fine particulate matter in Taiwanintegrated application of a national health data and the air quality data 

SUMMARY

Asthma is a recurrent attack of airflow obstruction. Once the patient is exposed to risk factors, it may cause symptoms of acute asthma. Many studies have pointed out that asthma can be divided into early-onset asthma and late-onset asthma according to the age. The mechanism of the attack between the two is completely different. Also, in terms of air pollutant exposure, it’s limited by the number and distribution of air quality monitoring stations. This study used a case-crossover study design to select asthma patients from National Health Insurance Research Database of Health and Welfare Data Science Center from 2008 to 2015, according to the disease diagnosis code of the International Classification of Diseases-9 code. The environmental monitoring data used in this study was taken from the air quality monitoring data of the Environmental Protection Administration and the observation data of the Central Weather Bureau automatic weather station. This study found that acute asthma attacks were positively correlated with PM2.5, O3, NOx, but only patients in early-onset asthma negatively correlated with SO2. Among all, NOx has the most significant impact on the risk of acute attacks, the higher the NOx concentration, the greater the impact on the risk of acute asthma attacks. When PM2.5 and O3 is below a certain concentration, the risk of an acute asthma attack is small. However, once the concentration exceeds this concentration range, the risk of the acute attack of asthma will increase significantly. 

林昱廷

結合環保署與空氣盒子數據開發智慧空污暴露

推估模式

Exposure Assessment of Fine Particulate Matters with Smart Spatial Interpolation Based on Low-Cost Sensors

SUMMARY

Spatial data has spatial heterogeneity, when assessing site-specific concentrations, the temporal and spatial variations in air pollutant concentrations may be higher in different weather conditions and areas where the land surface is uneven. Since the existing spatial interpolation methods still have uncertainties, the estimated concentrations are biased. The purpose of this study is to reduce the uncertainty of previous estimates. Combined with EPA and Airbox data, an smart air pollution exposure estimation model was established to estimate exposure to PM2.5 concentrations using a representative EPA monitoring station. The Modeling of site-specific exposures uses inverse distance weighted interpolation between data from a set of representative air quality stations, which are generated through spatial clustering analysis by large amounts of data from low-cost sensors.This study uses leave-one-out cross-validation to verify the feasibility of the model. And compared with Kriging method and inverse distance weighting method. We found that the developed method can generate a better exposure database by selecting suitable sites for spatial interpolation smartly, with considering clustering of air quality regions that are differentiated by local weather and terrain conditions, compared with traditional spatial interpolation methods, kriging and inverse distance weighting. The developed exposure database will support further analysis of the air pollutants on related health effects.

莊純柔

跨事業產業共生資源鏈結機會鑑定與循環效益

分析-台灣糖業公司為例

Identification of Opportunities and Benefits from the Industrial symbiosis in a Multi-Business Firm-Study of Taiwan Sugar Corporation

SUMMARY

In Taiwan, Taiwan Sugar company has multi-business including sugar refinery, livestock, agriculture and, biotechnology, etc., There are opportunities to develop by-product Industrial symbiosis among the business. This study is to change the current state of the Taiwan Sugar Company by recycling and recycling the by-products of the business. Materials, energy, water and resources that are no longer needed in one process can be used as a raw material in another process, to improve the efficiency of resource use to enhance environmental and economic benefits. The environmental and economic benefits of the new resource chain model will be assessed, using eco-efficiency and Cost- Benefit Analysis, respectively. The eco-efficiency calculations show the new circular of the sugar industry and the livestock industry, the ratio between total product volume and waste volume increased by 24.8% and 61.5%, respectively; the ratio between total revenue and waste volume increased by 23.3% and 79.5%, respectively. The cost-benefit analysis of the manufacture of by-products into new products shows that the sugar industry by-product soot is made into the red brick of the construction industry with a profit of 5,302,330 NTD; the sugar industry ash replaces the cement component in the concrete hollow brick, and the profit is as high as 291,700,005 NTD. The sugar industry by-product bagasse was used for pulping and papermaking, and the profit was 19,411,770NTD. The sugar industry by-product molasses extracted ethylene oxide as a natural surfactant, with a profit of 35,301,000 NTD.

蔡宗延

銅循環於臺灣產業鏈之潛力與價值-銅之物質流

及成本效益整合性分析

Assessing the Potential Value of Circular Practice in Taiwan’s Industrial Chains of Copper with Material Flow and Cost Analyses

SUMMARY

The study shows the material flow and cost analyses for copper in Taiwan’s industrial chains. Then, the principle of circular economy is applied in this study to create or find the value of copper circulation. To illustrate current situation of copper consumption and quantify the cost and benefit for analyzing the value chain of copper, the material flow analysis and material flow cost accounting are implemented respectively. According to the results of material flow analysis show that the great amount of the cathode is imported, and the copper recycle is not complete in Taiwan. Furthermore, from the results of five hotspots that we screen out show that the amount of waste wire and cable can reach the profit standard for the copper smelting, but the vehicle can’t be reached. And the results of material flow cost accounting show that the main loss part of printed circuit board process is caused by etching and detection, the vehicle process is caused by the consumption of raw material and crushing/sorting. Finally, in conclusion, the study knows the current situation of copper are imported from the global supply chain, and the amount of waste wire and cable can be used as the raw material of the copper smelting plant. Considering the circular-economy scenario benefit, the printed circuit board industry and the vehicle industry are positive value of circular economy, but the heat-exchange equipment is negative value of circular economy.