Estimation of PM2.5 concentration considering meteorological factors, policy, and interregional atmospheric transport

Yang, Jin; Liu, S.; Geng, Qijin; Chen, G.; Wang, Yeqing

doi:10.1007/s13762-021-03717-0

Cited by 3 publications

(19 citation statements)

References 39 publications

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“…6 Similar results were found in Licheng Zhang's research for the same parameters. 10 However, PM 2.5 concentrations had clear negative correlations with precipitation in Zibo city in the research, 6 which differed from the result in Licheng Zhang's research. 10 Therefore, it is still necessary to conduct further in-depth analysis on the influence of meteorological factors in different cities.…”

Section: Introductionsupporting

confidence: 85%

“…The maximum concentration in a year usually occurred in December and January, in agreement with the previous studies. 6 In winter in northern cities, the increased emission of pollutants from coal combustion and the weakened diffusion of pollutants caused serious PM 2.5 pollution. 20 (2) From 2014 to 2021, a time series analysis illustrated that the annual PM 2.5 concentrations in each city gradually Urban emissions in the target cities were significantly alleviated, and levels in Yantai, Qingdao, and Weihai had reached the grade II standard (CAAQS).…”

Section: Resultsmentioning

confidence: 99%

“…The detailed mapping method can be found in the previous research. 6 In the figure, the closer the color of the layer to dark purple, the higher the PM 2.5 concentration.…”

Section: Spatial Distribution Analysismentioning

confidence: 97%

“…During the research, four seasons were classified as winter (December−February of the following year), spring (March−May), summer (June−August), and autumn (September−November), as in the previous research. 6 Relative air emission policies were discussed separately in Section 2. 3.…”

mentioning

confidence: 99%

“…The detailed process of model construction and statistical testing can be found in the previous research. 6 2.3. Emission Control Policies.…”

mentioning

confidence: 99%

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Effect of Evaluation of Various Emission Control Policies on PM_2.5 Reduction

Yang,

Liu,

Geng

et al. 2023

ACS Omega

Self Cite

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In previous work, a methodology was developed to discuss the influence of meteorological factors, policies, and surrounding cities on PM2.5 concentrations in a city. Two models were constructed using Zibo City, Shandong Province, as the target city. Initially, we improved the established PM2.5-Meteorological-Policy (PMP) model and applied it to six other target cities in Shandong Province. Concurrently, a novel model named the PM2.5-Interregional (PI) model was further developed in each city to directly express the influence of surrounding cities on the target cities. The model construction period was from January 2014 to August 2022, with the extended prediction period until November 2022. The results confirmed that disparities in the spatial distribution in seasons became smaller after the implementation of environmental policies. Moreover, two models in each city revealed good interpretation with high adjusted R 2 values (>0.7) and lower MAPE and RMSE values (the lowest was 5.53% and 2.57), suggesting reasonable short-term prediction. Additionally, meteorological factors and the combined implementation of different policy types played crucial roles in reducing PM2.5 concentrations in all cities. Specifically, the temperature and wind speed were negatively correlated with PM2.5 concentrations in all models, with temperature having a stronger influence. The Law of the People’s Republic of China on the Prevention and Control of Atmospheric Pollution (LAPAP), implemented in 2016, had a clear influence on reducing PM2.5 concentrations, with the highest absolute fitted coefficient in most cities (−0.166 to −0.344). On the contrary, the influence of temperature seemed to be more significant compared to policies, due to the larger standardized coefficient in each city (−0.606 to −0.864).

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Section: Introductionsupporting

confidence: 85%

Section: Resultsmentioning

confidence: 99%

“…The detailed mapping method can be found in the previous research. 6 In the figure, the closer the color of the layer to dark purple, the higher the PM 2.5 concentration.…”

Section: Spatial Distribution Analysismentioning

confidence: 97%

mentioning

confidence: 99%

“…The detailed process of model construction and statistical testing can be found in the previous research. 6 2.3. Emission Control Policies.…”

mentioning

confidence: 99%

See 3 more Smart Citations

Effect of Evaluation of Various Emission Control Policies on PM_2.5 Reduction

Yang,

Liu,

Geng

et al. 2023

ACS Omega

Self Cite

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Multi-source observations on the effect of atmospheric blocking on air quality in İstanbul: a study case

Özdemir,

Birinci,

Deniz

2024

Environ Monit Assess

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Simulation and Forecasting Study on the Influential Factors of PM2.5 Related to Energy Consumption in the Beijing–Tianjin–Hebei Region

Li,

Shi,

Sun

et al. 2024

Sustainability

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It is still necessary to regularly investigate the breakdown of socio-economic elements as a starting point for analyzing the effects of diverse human production activities on PM2.5 intensity from industrial and regional viewpoints. In this paper, the emission factor model was adopted to measure PM2.5 emissions in the Beijing–Tianjin–Hebei (BTH) region at the regional and industrial levels. The logarithmic mean Divisia index (LMDI) decomposition model was employed to analyze the factors affecting PM2.5 emissions related to energy consumption in the BTH region at the regional and sectoral levels. Building on this foundation, a system dynamics (SD) model was established to make a prediction regarding PM2.5 pollution in the BTH region in 2025. This study found that secondary industry was a major source of PM2.5 emissions in the BTH region. Coal remained the main form of energy consumption in the BTH region. Secondly, the effect size of the factors affecting PM2.5 intensity ranked in the order of energy intensity, energy structure, and industrial structure. Thirdly, in 2025, PM2.5 emissions in the BTH region will decline appreciably, but there is still a certain gap in terms of meeting the targets of “the 14th Five-Year Plan” between the three provinces and cities. These results indicate that the BTH region should achieve the effective management of PM2.5 pollution at the source through the following initiatives: it is necessary to carry out the continuous adjustment of energy structures to gradually increase the proportion of clean energy; we must steadily promote the decline in energy intensity reduction, and gradually strengthen scientific and technological innovation; and we must continue to promote the optimization of the industrial structure and increase the proportion of tertiary industry every year.

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Estimation of PM2.5 concentration considering meteorological factors, policy, and interregional atmospheric transport

Cited by 3 publications

References 39 publications

Effect of Evaluation of Various Emission Control Policies on PM_2.5 Reduction

Effect of Evaluation of Various Emission Control Policies on PM_2.5 Reduction

Multi-source observations on the effect of atmospheric blocking on air quality in İstanbul: a study case

Simulation and Forecasting Study on the Influential Factors of PM2.5 Related to Energy Consumption in the Beijing–Tianjin–Hebei Region

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Estimation of PM2.5 concentration considering meteorological factors, policy, and interregional atmospheric transport

Cited by 3 publications

References 39 publications

Effect of Evaluation of Various Emission Control Policies on PM2.5 Reduction

Effect of Evaluation of Various Emission Control Policies on PM2.5 Reduction

Multi-source observations on the effect of atmospheric blocking on air quality in İstanbul: a study case

Simulation and Forecasting Study on the Influential Factors of PM2.5 Related to Energy Consumption in the Beijing–Tianjin–Hebei Region

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Product

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Effect of Evaluation of Various Emission Control Policies on PM_2.5 Reduction

Effect of Evaluation of Various Emission Control Policies on PM_2.5 Reduction