With the improvement of people's living standards, the number of automobiles has increased rapidly, and the problem of exhaust pollution has become more and more serious. Automobile exhaust emits a large amount of nitrogen oxides, hydrocarbons and fine particle pollutants, resulting in enhanced atmospheric oxidation and hazy weather in cities. The purpose of this paper is to study the hazards and countermeasures of automobile exhaust pollution based on deep reinforcement learning. Combining the perception ability of deep learning and the decision-making ability of reinforcement learning, it has the ability to solve complex control problems, and tries to apply it to the energy management problem of hybrid electric vehicles. Compared with the total average emission factors of various pollutants of traditional gasoline cars, the average emission factors of CO, HC and NOX of clean cars based on deep reinforcement learning have obvious advantages compared with traditional gasoline cars, indicating that the deep reinforcement learning of clean cars Has good emission reduction performance.

Rajite Ragab. The Harm and Countermeasures of Automobile Exhaust Pollution Based on Deep Reinforcement Learning. Academic Journal of Environmental Biology (2021), Vol. 2, Issue 4: 36-43. https://doi.org/10.38007/AJEB.2021.020405.

[1] Esme F T, Munro A P. Lead Exposure as a Confounding Factor in the Association of Air Pollution Exposure and Psychotic Experiences. JAMA Psychiatry, 2019, 76(10):1095-1096.

[2] Mukhitdinov, O. Pollution of Air with Exhaust Gases of Internal Combustion Engine (Ice) Vehicles and Actions to Reduce Their Toxicity. Acta of Turin Polytechnic University in Tashkent, 2018, 8(4):6-6.

[3] Achmad, Rizki, Pratama, et al. Analysis of Air Pollution due to Vehicle Exhaust Emissions on The Road Networks of Beringin Janggut Area. Journal of Physics: Conference Series, 2019, 1198(8):82030-82030.

[4] Lozoya-Santos D J, Torres J R, Herrera A S, et al. Study of an Electric Energy Generation System from Exhaust Waste Recovery from an Internal Combustion Engine. International Journal of Thermal and Environmental Engineering, 2018, 16(1):51-58. https://doi.org/10.5383/ijtee.16.01.007

[5] M D’Angelo, AE González, Tizze N R. First approach to exhaust emissions characterization of light vehicles in Montevideo, Uruguay. Science of the Total Environment, 2018, 618(MAR.15):1071-1078.

[6] Celiktas V, Otu H, Duzenli S, et al. Traffic-Induced Air Pollution Effects On Physio-Biochemical Activities Of The Plant Eucalyptus Camuldensis. Fresenius Environmental Bulletin, 2019, 28(12):9373-9378.

[7] Kweon B S, Mohai P, Lee S, et al. Proximity of public schools to major highways and industrial facilities, and students' school performance and health hazards. Environment and Planning, 2018, 45(2):312-329.

[8] Urme S A, Radia M A, Alam R, et al. Dhaka landfill waste practices: addressing urban pollution and health hazards. Buildings and Cities, 2021, 2(1):700-716. https://doi.org/10.5334/bc.108

[9] Guleria R, Tiwari P. Air Pollution: Health Hazards and Prevention. Journal of Cardiac Critical Care TSS, 2019, 03(01):01-04.

[10] Ibrahim S A, Abed M F, Al-Tawash S. Calculation of Pollution Indicators and Health Hazards of Heavy Elements in Surface Soils in Samarra City. Iraqi Journal of Science, 2018, 59(No. 3B):1419-1429. https://doi.org/10.24996/ijs.2018.59.3B.9

[11] Ilankoon I M S K, Ghorbani Y, Meng N C, et al. E-waste in the international context - A review of trade flows, regulations, hazards, waste management strategies and technologies for value recovery. Waste Management, 2018, 82(DEC.):258-275.

[12] Udiba U U, Udofia U U, Akpan E R. Concentration and Potential Human Health Hazards of Heavy Metals in Periwinkle (Tympanotonus fuscatus) Purchased from Major Markets in Calabar, Nigeria. Journal of Health and Pollution, 2020, 10(28):1-28.

[13] Mishra S, Rath C C, Das A P. Marine microfiber pollution: A review on present status and future challenges. Marine Pollution Bulletin, 2019, 140(MAR.):188-197.

[14] Balaji K, Selvam M. Investigation Of Secure Vekit Web Interface For Preventing Environment Pollution. Transport, 2020, 35(5):1-12. https://doi.org/10.3846/transport.2020.13038

[15] Iderawumi A M. Sources of Environmental Hazards Effects and Control. Asia Pacific Journal of Energy and Environment, 2019, 6(2):77-82. https://doi.org/10.18034/apjee.v6i2.268

[16] Rajpoot S, Singh D P. Emerging Public Health Concern and Air Pollution: A Case Study of Delhi's Air Pollution Governance. International Journal for Modern Trends in Science and Technology, 2020, 6(5):196-201. https://doi.org/10.46501/IJMTST060530

[17] Shokry M, Elhattab M, Assi C, et al. Optimizing Age of Information Through Aerial Reconfigurable Intelligent Surfaces: A Deep Reinforcement Learning Approach. IEEE Transactions on Vehicular Technology, 2021, PP(99):1-1.

[18] Seo G, Yoon S, Kim M, et al. Deep Reinforcement Learning-Based Smart Joint Control Scheme for On/Off Pumping Systems in Wastewater Treatment Plants. IEEE Access, 2021, PP(99):1-1. https://doi.org/10.1109/ACCESS.2021.3094466