摘要
传统的空气污染监测通常以人类健康为中心，而忽略了可持续发展方面的考虑。为此，本研究采用基于传感器的设备和建模技术，通过调查城市空气质量及其对健康的影响，扩大了研究范围。本研究特别深入研究了印度印度洋-甘地平原城市（阿格拉、德里、法里达巴德、加齐阿巴德、坎普尔、勒克瑙和诺伊达）从 "正常值"（2019 年）到 "新正常值"（2021 年）的转变。德里、法里达巴德、加齐亚巴德、坎普尔、勒克瑙和诺伊达等城市的 PM2.5 年平均浓度分别下降了 11%、7%、14%、7%、4% 和 17%，但阿格拉的 PM2.5 年平均浓度在 2020 年上升了 9%，而在 2021 年，德里、法里达巴德和加齐亚巴德的 PM2.5 年平均浓度分别上升了 7%、11%、7% 和 2%，而阿格拉、坎普尔和勒克瑙的 PM2.5 年平均浓度分别下降了 2%、7% 和 11%。2020 年的气态污染物较高，但二氧化氮除外，原因是人口流动受到限制。大多数城市的温度、湿度和太阳辐射都有所上升，而除加济阿巴德和勒克瑙外，所有城市的风速都有所下降。风速上升图和污染上升图显示了来自多个方向的长程污染传输。2020-2021 年期间，阿格拉、德里、加齐阿巴德和坎普尔的风速（WS）与 PM2.5 之间呈负相关（r = -0.5 至 -0.6）。同样，坎普尔的风速与二氧化氮呈负相关（r = -0.6），阿格拉和加济阿巴德的风速与一氧化碳呈负相关（r = -0.5至-0.6）。这些相关性表明，较高的风速有助于分散和输送这些污染物。AirQ + 健康评估显示，2019 年死亡人数显著增加，2020 年有所减少，而 2021 年则有所增加，这突出表明 PM2.5 水平与死亡率之间存在很强的相关性。通过创新技术和分析方法获得的这一洞察力为政策制定者、环保人士和公共卫生官员在 "新常态 "下管理长期空气质量提供了指导。Traditional air pollution monitoring has often centered on human health, sidelining sustainable development considerations. In response, the present study expands the scope by investigating urban air quality and its effect on health, employing sensor-based devices and modeling techniques. The investigation specifically delves into the shift from the "Normal" (2019) to the "New Normal" (2021) in the urban cities of Indo-Gangetic Plain (Agra, Delhi, Faridabad, Ghaziabad, Kanpur, Lucknow, and Noida), India. The cities like Delhi, Faridabad, Ghaziabad, Kanpur, Lucknow, and Noida and experienced a decrease in annual average PM2.5 concentration by 11, 7, 14, 7, 4, and 17%, respectively, however, Agra experienced 9% increase in year 2020, while in year 2021, Delhi, Faridabad, and Ghaziabad had an increase of 7, 11, 7, and 2% respectively, whereas Agra, Kanpur, and Lucknow experienced decreases of 2, 7, and 11%. Gaseous pollutants were higher in 2020, except for NO2 due to restrict movement. Temperature, humidity, and solar radiation increased in most cities, while wind speed decreased in all cities except Ghaziabad and Lucknow. The wind rose and pollution rose plots indicated long-range pollution transport from multiple directions. Negative correlations between wind speed (WS) and PM2.5 were observed in Agra, Delhi, Ghaziabad, and Kanpur (r = -0.5 to -0.6) during 2020–2021. Similarly, WS showed negative correlations with NO2 in Kanpur (r = -0.6) and with CO in Agra and Ghaziabad (r = -0.5 to -0.6). These correlations indicate that higher wind speeds aid in dispersing and transporting these pollutants. The AirQ + health assessment revealed a significant number of fatalities in 2019, a reduction in 2020, and an increase in 2021, highlighting a strong correlation between PM2.5 levels and mortality. This insight, gained through innovative technologies and analytical methods, guides policymakers, environmentalists, and public health officials in managing long-term air quality in the "New Normal".
Graphical Abstract
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