syN-BEATS for Robust Pollutant Forecasting in Data-Limited Context

Author:

Berman Josef1,Pinhasov Ben1,Tshuva Moshe1,Aperstein Yehudit1

Affiliation:

1. Afeka College of Engineering

Abstract

Abstract

This research introduces syN-BEATS, a novel ensemble deep learning model tailored for effective pollutant forecasting under conditions of limited data availability. Based on the N-BEATS architecture, syN-BEATS integrates various configurations with differing numbers of stacks and blocks, effectively combining weak and strong learning approaches. Our experiments show that syN-BEATS outperforms standard models, especially when using Bayesian optimization to fine-tune ensemble weights. The model consistently achieves low relative root mean square errors, proving its capacity for precise pollutant forecasting despite data constraints. A key aspect of this study is the use of data from only one meteorological and one air quality monitoring station per region, simulating environments with restricted monitoring capabilities. By applying this approach in regions with diverse climates and air quality levels, we thoroughly assess the model's flexibility and resilience under different environmental conditions. The results highlight syN-BEATS' ability to support the development of effective health alert systems that can detect specific airborne pollutants, even in areas with limited monitoring infrastructure. This advancement is crucial for enhancing environmental monitoring and public health management in under-resourced areas.

Publisher

Springer Science and Business Media LLC

Reference28 articles.

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3. Kumari, Shweta and Jain, Manish Kumar (2018) A Critical Review on Air Quality Index. Springer Singapore, Singapore, 978-981-10-5792-2, Air quality index (AQI) is used worldwide to inform the public about levels of air pollution (degradation or improvement) and associated to different biological effects. Different types of anthropogenic activity mainly transportation have an enormous impact on the ambient air quality in several ways. The transportation dependence continues to grow; it is adversely affecting the quality of human life. Due to pollution, the ambient air quality in major cities (Delhi, Agra, Kanpur, Lucknow, Varanasi, Faridabad, Ahmedabad, Chennai, Bangalore and Hyderabad) in India is very poor. According to WHO surveys, India is one of the most polluted countries in the world. Concentrations of air pollutants affect Air Quality Index. Air Quality scenario in most of the Indian cities presents a harsh picture, the majority of national monitoring stations have recorded particulate concentrations exceeding the WHO recommended guideline. The higher the AQI value, the greater the level of air pollution and greater the health concern. This review paper is helpful to understand the development of Air quality Index in India with the experience of the world., 87--102, Singh, Vijay P and Yadav, Shalini and Yadava, Ram Narayan, Environmental Pollution

4. Mariantonietta Ruggieri and Antonella Plaia (2012) An aggregate AQI: Comparing different standardizations and introducing a variability index. Science of The Total Environment 420: 263-272 https://doi.org/https://doi.org/10.1016/j.scitotenv.2011.09.019, https://www.sciencedirect.com/science/article/pii/S0048969711010199, Aggregate AQI, Standardization, Air quality categories, Variability index, Many studies demonstrate a strong relationship between air pollution and respiratory and cardiovascular diseases. For this reason, assessing air pollution, and conveying information about its possible adverse health effects, may encourage population and policy makers to reduce those activities increasing pollution levels. In this paper a relative index of variability, to be associated with the aggregate Air Quality Index (AQI) among pollutants proposed by Ruggieri and Plaia (2011), is developed in order to better investigate air pollution conditions for the whole area of a city/region. The most widely-used and up to date pollution indices, based mainly on AQI computed by the US Environmental Protection Agency (EPA) and often defined by the value of the pollutant with the highest (opportunely standardized) concentration on a given day, aim at warning the people for short term health impact. An aggregate AQI, taking into account the combined effects of all the considered pollutants, gives emphasis to possible chronic health effects and long term damages on environment caused by air pollution. The proposed index of variability adds precious information to the aggregate AQI, as it allows one to know whether the value assumed by the AQI is influenced by one or more pollutants. The two indices are jointly used on simulated data, considering different possible scenarios. Applications to real air pollution data are also reported. Before applying the two indices, the effects of different standardizations on data are evaluated from a theoretical point of view., 0048-9697

5. Monteiro, A. and Vieira, M. and Gama, C. and Miranda, A. I. (2017) Towards an improved air quality index. Air Quality, Atmosphere and Health 10(4): 447--455 https://doi.org/10.1007/s11869-016-0435-y, https://doi.org/10.1007/s11869-016-0435-y, Monteiro2017, Air quality indices (AQI) are commonly used to indicate the level of severity of air pollution to the public. A number of methods were developed in the past by various researchers/environmental agencies for the calculation of AQI, but there is no universally accepted method, appropriate for all situations. An updated review of the major air quality indices developed worldwide is presented in this paper. These methods differentiate mainly in the number of pollutants included, its sampling period and air quality classes and breakpoints. When applying different AQI to a common case study, important differences are found in terms of the classification of the quality of the air. The purposes of this research are to identify weaknesses of the current AQI and to discuss possible changes and updates with Portugal as case study. A survey, with 10 questions about the calculation and use of the AQI and its dissemination to public, was delivered to the five regional environmental agencies in Portugal and, based on results, modifications to the current AQI are proposed. Two main changes--inclusion of PM2.5 and specific urban/industrial AQI--were tested, comparing the current and the proposed AQI along the 2014 year. It is observed that a significant difference exists when specific urban and industrial sites are considered when calculating the AQI. On the other hand, and contrarily to other regional studies, the results show that the inclusion of fine suspended particulate (PM2.5) does not impact the final AQI value., 1873-9326

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