P1126

107

45,000 千元

2018/12/26

2020/03/26

郭崇義

臺中市政府環境保護局

盧宜含

中山醫學大學、景丰科技股份有限公司

大氣空氣

細懸浮微粒、環境汚染物、健康風險評估、三維網格空品模式

fine particulate matter, PM2.5, air pollutants, health risk assessment, 3-dimension grid model in air quality modeling

張鈺鋒

劉遵賢

蔡徵霖

06-2098539#22

jltsai0408@gmail.com

本計畫主要目的在經由大氣環境調查及模式模擬分析臺中地區大氣有害空氣污染物之相關資訊，以研議後續減量策略之訂定。工作內容包含四大重點：(1)執行空氣污染物之採樣與分析。(2)評析各地區及季節空氣污染物濃度變化之現象。(3)由實測資料進行臺中市各地區污染物之健康風險評估。(4)利用模式模擬結果評估本市重大污染源之貢獻情況，並研議風險管理計畫。 在九區中各污染物之濃度大致以市區為最高，而以非工業區為最低，但各區差異之幅度並不大，在三階段(105年期~107年期)數據中，並未發現有那一測站其污染物之濃度有明顯長期偏高之現象。在季節變化上，PM2.5質量濃度、PM2.5中之金屬及PAHs濃度均以夏季為最低，而PAHs濃度明顯以冬季為最高；另VOCs濃在季節之變化趁勢較不明顯。與國內外文獻比較，本計畫各污染物之濃度大都落在相關文獻濃度範圍之內，但與部份針對排放源附近環境之調查報告相比較，本計畫針對大環境空品之調查結果，其濃度明顯較低。配合風向及排放源特徵元素之特性，研判部份採樣點有遭受鋼鐵工業排放之影響。 彙整三年期之現址調查結果，計算大氣中揮發性有機物、PM2.5中所含重金屬、多環芳香烴化合物其終生每日暴露劑量(LADD)，並推估及討論各區之致癌及非致癌風險。臺中市全區致癌風險中數值為7.61E-06，而其致癌風險上限值為1.39E-05；分析影響臺中市全區前5大致癌污染物分別為無機砷、苯、六價鉻、鎘、鎳。在非致癌風險之影響上，發現后里區之生長發育、生殖系統及呼吸系統之非致癌風險危害指數上限值>1，其主要影響因素是鎳；港區、后里區及工業區C之神經系統非致癌風險危害指數上限值>1，主要影響因素是錳。 經由收集本市各污染源現場檢測資料、國內外相關行業科研計畫文獻資料及美國環保署SPECIATE圖譜資料，搭配點、線及面源粒狀物及揮發性有機物排放量完成本市有害空氣污染物排放量資料建置，物種包含砷、苯、鎳、六價鉻、鎘、多環芳香烴化合物（PAHs）、二氯甲烷、鉛、錳、汞、甲苯及戴奧辛共12個物種。 建置完成三維網格模式模擬之環境相關設定，於基準年（105年）不同季節之5月、7月、10月及12月進行氣象及空品模擬，與觀測數據比較的結果皆符合環保署公告「空氣品質模式模擬規範」之規定。解析本市7個重大污染源排放的12個物種於本市之濃度分布及貢獻比例，模擬結果顯示各重大污染源較明顯影響區域為其所在及下風鄰近區域，而其中排放管道較高及排放量較大者於全市各區較其他重大點源有較為明顯之影響。 彙整分析國內外都會區健康風險管理策略，並依據環境調查成果、有害物質排放量資料及不同減量情境之模擬結果，研擬短、中及長期風險管理計畫，首先改善方案應針對本市鋼鐵相關產業及電力及燃氣供應業加以管制其有害物質之排放量，後續則可參考參照美國TCEQ及MATES有害空氣污染物管制策略之研擬以持續有效降低本市大氣環境有害污染物之危害。

細懸浮微粒、環境汚染物、健康風險評估、三維網格空品模式

107年臺中市后里區、西屯區、大雅區及港區空氣污染物健康風險調查計畫_成果報告.pdf

74MB

2021/6/23 上午 12:00:00

The main purpose of this project is to investigate air pollutants (PM2.5, metals, PAHs, VOCs, and acidic gas) in Taichung City by field campaigns and model simulations for further evaluations of health risk assessment and regulations of emission reduction plans. The project was conducted in four parts, as follows: (I) to collect and analyze ambient air pollutants in Taichung City; (II) to explore the concentration variations of air pollutants among different sampling sites and seasons; (III) to assess health risks based on the measurement of pollutant concentrations in situ; and (IV) to evaluate the contribution from the major pollution sources in Taichung and to investigate the draft for risk management. Among the nine sampling districts, the highest mean concentrations of pollutants were found in the center district of Taichung City, while the lowest concentrations were found in the non-industry district. However, the concentrations among the nine sampling districts did not show a large amplitude of differences. The three-years sampling data also showed that in none of sampling stations had high concentrations of pollutants occurred obviously and consistently. For seasonal variations, mass concentrations of PM2.5, and concentrations of metal and PAHs in PM2.5 all had the lowest values in the summer season. Furthermore, PAHs showed the highest value in the winter season, while the seasonal variations were not obvious for VOCs. Compared with other investigation data from numerous studies, the pollutant concentrations of this project were within the range of previous studies. However, compared to the studies focusing on the effects of pollution sources at nearby sites, this study focusing on the air quality of the living environment for residents of Taichung City showed obviously lower values. Associated with wind direction and characteristic elements of pollution sources, a sampling site suggests that it was polluted by a steel plant. This study calculated, evaluated, and thoroughly discussed the life-time average daily dose (LADD) and health risk assessments based on the measurement of pollutant concentrations in situ. The 50% percentile and 95% percentile of cancer risk in Taichung City were 7.61E-06 and 1.39E-05, respectively. The five top pollutants of cancer risk contributors in Taichung City were: As, benzene, Cr6+, Cd , and Ni. The results of the hazard indices of non-carcinogenic risk showed that the developmental system, reproductive system, and respiratory system were all higher than the minimum target risk level of 1 in Houli district, where the dominant pollutant was Ni. The hazard indices of non-carcinogenic risk for the nervous system was higher than 1 for Harbor district , Houli district ,and Industry-C district, where the dominant pollutant was Mn. Based on the data on stack samples analysis in Taichung, the results of peer-reviewed scientific papers related to the industries in Taichung and the profiles in the USEPA Speciate database in conjunction with the emission dataset of TEDS 10, an emission dataset of 12 hazardous air pollutants: As, Benzene, Ni, Cr6+, Cd, PAHs, Dichloromethane, Pb, Mn, Hg, Toluene, Dioxin, was constructed. The environmental variables for the modelling system were set up and the evaluations of the mesoscale meteorological modeling and regional air quality modeling for the base year conducted; the comparisons with observation were in good agreement. In addition, simulations of the 7 major emission sources were conducted and the results showed that the areas affected by these sources were always where they were located and the surrounding areas. In addition, the major sources with higher stack height and larger emission have more obvious impact in the whole city, compared to other major sources. The risk management plans were suggested based on the results of environmental pollution surveys, the emission dataset of hazardous air pollutants and the simulation results of different emission reduction scenarios. It showed that steel industries and power plants are the major sources that need to reduce the hazardous air pollutants emission in the beginning. A long-term air pollutant control strategy can be developed by referring to the TCEQ and MATES in the States, in order to effectively reduce the environmental hazardous air pollutants.

fine particulate matter, PM2.5, air pollutants, health risk assessment, 3-dimension grid model in air quality modeling