Spatio-Temporal Pattern Estimation of PM2.5 in Beijing-Tianjin-Hebei Region Based on MODIS AOD and Meteorological Data Using the Back Propagation Neural Network

Ni, Xiliang; Cao, Chunxiang; Zhou, Yuke; Cui, Xianghui; Singh, Ramesh P.

doi:10.3390/atmos9030105

Cited by 40 publications

(24 citation statements)

References 42 publications

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“…1) available in the study area. The annual average MODIS and ground measured PM 2.5 data were used in a statistical correlation (Ni et al 2018). The Correlation Coe cient (R 2 ) and the Adjusted Correlation Coe cient were estimated (Fig.…”

Section: Pm 25 Data Validationmentioning

confidence: 99%

Assessment of Health Impacts of Particulate Matter (PM2.5) on the Vulnerable Groups in the Central part of Bangladesh

Islam

Bhuiyan

2022

Preprint

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Particulate matter (PM2.5) is one of the critical sources for outdoor air pollution and poses the most significant public health threat. In Bangladesh, particularly in the major urban cities, PM2.5 has been identified as a significant public health hazard. This research aims to perform a spatiotemporal mapping of PM2.5 from 2002–2019 to identify the hotspots in central Bangladesh and to estimate the health impacts on pregnant women and population aged 60+. A time-series of remotely sensed PM2.5 is used in hotspot analysis, applying Geographic Information Systems (GIS). To explore the health impacts due to PM2.5, a questionnaire survey is conducted on pregnant women and population aged 60 + in both high- and low-spots zones. A Mann-Whitney U test of non-parametric statistical analysis is conducted to understand the mean impacts. The findings of this research reveal that the annual concentration of PM2.5 is increased by 47% during 2002–2019. Most of the high hotspot zones are identified in the middle of the study areas; the core urban areas of Dhaka, Narayanganj, and Gazipur Districts. The traffic vehicles, urbanization, construction and brickfield activities, and industrial emissions are the main controlling factors for increasing PM2.5. Further, the health impacts of both pregnant and population 60+ are higher in the high-spot zone than in the low-spot area. Note that pregnant women have less PM2.5 related information than 60+ population in both high- and low-spot zones. On the policy applications, the relevant departments may utilize these findings for health hazard risk reduction and local and regional air pollution mitigation.

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Section: Pm 25 Data Validationmentioning

confidence: 99%

Assessment of Health Impacts of Particulate Matter (PM2.5) on the Vulnerable Groups in the Central part of Bangladesh

Islam

Bhuiyan

2022

Preprint

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“…Anthropogenic emission is the main cause of pollution in Beijing Tianjin Hebei area (Miao et al 2015). From 2014 to 2016, the concentration of PM2.5 in most cities of Beijing, Tianjin and Hebei decreased (Ni et al 2018).…”

Section: Air Pollution Risk In the Development Of Beijing-tianjin-hebei Urban Agglomerationmentioning

confidence: 99%

Climatic risks of Beijing–Tianjin–Hebei urban agglomeration and their changes

Chen

Guo

2021

Geomatics, Natural Hazards and Risk

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Aiming at building an international urban agglomeration, Beijing-Tianjin-Hebei urban agglomeration takes an active part in international cooperation and competition in a greater depth, and plays a crucial role in supporting and guiding the national economic and social prosperity. In the passing years, Beijing-Tianjin-Hebei urban agglomeration has been severely subjected to extreme weather-climate events, which has aroused tremendous response and enormous concern among all social strata. This thesis sums up the impact of building the Beijing-Tianjin-Hebei urban agglomeration on extreme events such as rainstorm, high temperature and heavy haze, and the meteorological disaster risks faced by Beijing-Tianjin-Hebei urban agglomeration in the context of climate change, and comes up with corresponding countermeasures and suggestions for planning and building Beijing-Tianjin-Hebei urban agglomeration and Xiong'an New Area in the context of climate change.

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“…However, using the Life Cycle Assessment Method to analyze environmental problems produced in the process of integrated exploitation of tailings, can calculate their environmental pollution values in advance from the beginning of technology designing and achieve the goal of green production from the origin. There are a lot of assessment methods at present (Ni et al, 2018;Zhai et al, 2018;Zhao et al, 2018;Zhou et al, 2018;Li et al, 2017;Yang et al, 2017;Jin et al, 2015;Li et al, 2015b;Song et al, 2015;Yan et al, 2014). Most of the methods are based on the current situation, and only the Life Cycle Assessment (LCA) starts from the source.…”

Section: Introductionmentioning

confidence: 99%

Life Cycle Assessment of Integrated Exploitation Technology for Tailings in Bayan Obo Mine, China

Wang¹,

Jiao²,

Lu³

et al. 2019

Appl. Ecol. Env. Res.

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Bayan Obo mine in China is the largest iron-niobium-rare-earth symbiotic and associated mine in the world. Its exploitation has brought great economic benefit over the years. At the same time, many environmental problems arise. One of the most serious problems is tailings. Based on the theory and method of life cycle assessment, the environmental problems caused by integrated exploitation technology for tailings in Bayan Obo mine have been studied. Environmental impact assessment method TRACI 2.1 developed by Environmental Protection Agency of the United States has been chosen in this study. Through the study of resource consumption, energy consumption, pollution input by raw materials, pollution from industrial emissions etc. of each process, 10 types of environmental impacts have been studied and their values have been calculated. Results show that the main environmental impact types are Human toxicity non-cancer, Human toxicity cancer, Ecotoxicity, Global warming air, Human health particulate air, respectively. And the pollution input by raw materials is much greater than that from industrial emission, which provides a typical case and support for green purchasing, green manufacturing, process improving etc.

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Spatio-Temporal Pattern Estimation of PM2.5 in Beijing-Tianjin-Hebei Region Based on MODIS AOD and Meteorological Data Using the Back Propagation Neural Network

Cited by 40 publications

References 42 publications

Assessment of Health Impacts of Particulate Matter (PM2.5) on the Vulnerable Groups in the Central part of Bangladesh

Assessment of Health Impacts of Particulate Matter (PM2.5) on the Vulnerable Groups in the Central part of Bangladesh

Climatic risks of Beijing–Tianjin–Hebei urban agglomeration and their changes

Life Cycle Assessment of Integrated Exploitation Technology for Tailings in Bayan Obo Mine, China

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