Bera Om Prakash, Venkatesh U, Pal Gopal Krushna, Shastri Siddhant, Chakraborty Sayantan, Grover Ashoo, Joshi Hari Shanker
Global Health Advocacy Incubator (GHAI), Washington, DC, 20005, USA.
Centre for Policy Research & Data Analytics in Health and Environment (CePRAHE), All India Institute of Medical Sciences, Gorakhpur, Uttar Pradesh, 273008, India.
Lancet Reg Health Southeast Asia. 2024 Oct 7;30:100486. doi: 10.1016/j.lansea.2024.100486. eCollection 2024 Nov.
Uttar Pradesh, India's largest state, faces critical pollution levels, necessitating urgent action. The National Clean Air Programme (NCAP) targets a 40% reduction in particulate pollution by 2026. This study assesses the impact of NCAP on 15 non-attainment cities in Uttar Pradesh using the Prophet forecasting model.
Monthly data on AQI and concentrations from 2016 to 2023 were sourced from the Uttar Pradesh Pollution Control Board. Significant changes in mean AQI and levels from 2017 to 2023 were evaluated using the Friedman test. Prophet models forecast concentrations for 2025-26, with relative percentage changes calculated and model evaluation metrics assessed.
Most cities exhibited unhealthy air quality. Jhansi had the lowest AQI (72.73) in 2023, classified as 'moderate' by WHO standards. Gorakhpur consistently showed 'poor' AQI levels, peaking at 249.31 in 2019. Western Uttar Pradesh cities such as Ghaziabad, Noida, and Moradabad had significant pollution burdens. Predictions showed Bareilly with over a 70% reduction in levels, Raebareli 58%, Moradabad 55%, Ghaziabad 48%, Agra around 41%, and Varanasi 40%, meeting NCAP targets. However, Gorakhpur and Prayagraj predicted increases in levels by 50% and 32%, respectively. Moradabad's model showed the best performance with an of 0.81, MAE of 17.27 , and MAPE of 0.10.
Forecasting concentrations in Uttar Pradesh's non-attainment cities offers policymakers substantial evidence to enhance current efforts. While existing measures are in place, our findings suggest that intensified provisions may be necessary for cities predicted to fall short of meeting program targets. The Prophet model's forecasts can pinpoint these at-risk areas, allowing for targeted interventions and regional adjustments to strategies. This approach will help promote sustainable development customized to each city's specific needs.
No funding was issued for this research.
印度最大的邦北方邦面临着严重的污染水平，需要立即采取行动。国家清洁空气计划（NCAP）的目标是到2026年将颗粒物污染减少40%。本研究使用先知预测模型评估NCAP对北方邦15个未达标的城市的影响。
2016年至2023年的空气质量指数（AQI）和[具体污染物名称]浓度的月度数据来自北方邦污染控制委员会。使用弗里德曼检验评估2017年至2023年平均AQI和[具体污染物名称]水平的显著变化。先知模型预测了2025 - 2026年的[具体污染物名称]浓度，计算了相对百分比变化并评估了模型评估指标。
大多数城市的空气质量不健康。占西2023年的AQI最低（72.73），根据世界卫生组织标准被归类为“中等”。戈勒克布尔的AQI水平一直显示为“差”，2019年达到峰值249.31。北方邦西部的城市如加济阿巴德、诺伊达和莫拉达巴德有严重的污染负担。预测显示，巴雷利的[具体污染物名称]水平降低超过70%，勒克瑙降低58%，莫拉达巴德降低55%，加济阿巴德降低48%，阿格拉约降低41%，瓦拉纳西降低40%，达到了NCAP的目标。然而，戈勒克布尔和普拉亚格拉杰预测[具体污染物名称]水平将分别增加50%和32%。莫拉达巴德的模型表现最佳，决定系数为0.81，平均绝对误差为17.27[单位]，平均绝对百分比误差为0.10。
预测北方邦未达标的城市中的[具体污染物名称]浓度为政策制定者加强当前的努力提供了大量证据。虽然现有措施已经到位，但我们的研究结果表明，对于预计无法达到计划目标的城市，可能需要加强措施。先知模型的预测可以确定这些风险区域，从而进行有针对性的干预和对战略的区域调整。这种方法将有助于促进根据每个城市的具体需求定制的可持续发展。
本研究未获得资金。
