住民の旅行行動に顕著な変動が見られる場合の大気汚染の時間的分布特性と健康への影響に関する分析．中国広州市の事例

Analysis on the Temporal Distribution Characteristics of Air Pollution and Its Impact on Human Health under the Noticeable Variation of Residents' Travel Behavior: A Case of Guangzhou, China.

• Xiaoxia Wang
• Chao Zou
• Luqi Wang

抄録

中国でCOVID-19が大規模に発生した際、中国政府は複数の対策を講じた。その結果、住民の旅行行動に急激な変化が生じた。本研究では、大気汚染の時間的分布をより良く評価し、特に特殊な状況下での人間活動が大気質に及ぼす影響を効果的に探るために、このような新たな視点から中国の事例都市の実データに基づいて研究を行った。住民の移動行動が変化する前の研究をケース1、移動行動が変化した後の研究をケース2とし、2つのケースシナリオを構築した。データソースとしては、拡張ディッキーフラー（ADF）試験に合格したPM、PM、SO、NO、CO、Oの1時間ごとのリアルタイム濃度を採用した。相関法、エントロピーウェイト法、大気質指数(AQI)計算法を用いて、一連の詳細な研究を行った。その結果、NO濃度の減少率は61.05％、PM濃度の減少率は53.68％であることがわかった。逆にO濃度の平均値は大幅に上昇しており、その上昇率は9.82％に達している。交通量の少ない最初の週の大気の質は優秀なカテゴリーにあり、主な汚染物質(CP)や過剰汚染物質(EP)は見られなかったが、交通量の増加に伴い、2週目、3週目には悪化した。また、Oの1時間当たりの平均濃度が上昇していることから、今後もOの発生傾向には注意が必要である。本研究の知見は、大気汚染防止、クリーン生産、室内環境安全問題の研究、特に住民の移動行動が大きく変化した異常な交通環境の研究に何らかの指針的意義を持つものと考えられる。

During the large-scale outbreak of COVID-19 in China, the Chinese government adopted multiple measures to prevent the epidemic. The consequence was that a sudden variation in residents' travel behavior took place. In order to better evaluate the temporal distribution of air pollution, and to effectively explore the influence of human activities on air quality, especially under the special situation, this study was conducted based on the real data from a case city in China from this new perspective. Two case scenarios were constructed, in which the research before the changes of residents' travel behavior was taken as case one, and the research after the changes in residents' travel behavior as case two. The hourly real-time concentrations of PM, PM, SO, NO, CO and O that have passed the augmented Dickey-Fuller (ADF) test were employed as a data source. A series of detailed studies have been carried out using the correlation method, entropy weight method and the Air Quality Index (AQI) calculation method. Additionally, the research found that the decrease rate of NO concentration is 61.05%, and the decrease rate of PM concentration is 53.68%. On the contrary, the average concentration of O has increased significantly, and its growth rate has reached to 9.82%. Although the air quality in the first week with fewer travels was in the excellent category, and chief pollutant (CP), as well as excessive pollutant (EP), were not found, as traffic volume increased, it became worse in the second and third weeks. In addition to that, special attention should still be paid to the development trend of O, as its average hourly concentration has increased. The findings of this study will have some guiding significance for the study of air pollution prevention, cleaner production, and indoor environmental safety issues, especially for the study of abnormal traffic environments where residents' travel behaviors have changed significantly.