Ozone control strategies for local formation- and regional transport-dominant scenarios in a manufacturing city in southern China

Mao, Jingying; Yan, Fenghua; Zheng, Lianming; You, Yingchang; Wang, Weiwen; Jia, Shiguo; Liao, Wenhui; Wang, Xuemei

doi:10.1016/j.scitotenv.2021.151883

Cited by 21 publications

(7 citation statements)

References 51 publications

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“…The PRD region is the first urban agglomeration in China to change its main pollutant from particulate matter with an aerodynamic diameter of less than or equal to 2.5 mm (PM 2.5 ) to O 3 . Numerous studies in the PRD region have investigated the daytime O 3 characteristics, such as the long-term trends (Xue et al, 2014;Li et al, 2022), the nonlinear response of O 3 to precursor emissions (Lu et al, 2010;Mao et al, 2022), the source apportionment of O 3 (Shen et al, 2015;Liu et al, 2020), and the relative contributions of precursor emissions and meteorology to O 3 (L. Chen et al, 2020). In terms of nighttime O 3 , Tong and Leung (2012) observed a double-peak pattern of diurnal O 3 variation in Hong Kong during 1990-2005 and found that nocturnal O 3 peaks are sometimes higher than daytime maxima.…”

Section: Introductionmentioning

confidence: 99%

Quantitative impacts of vertical transport on the long-term trend of nocturnal ozone increase over the Pearl River Delta region during 2006–2019

You

Jia

et al. 2023

Atmos. Chem. Phys.

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Abstract. The Pearl River Delta (PRD) region in southern China has been subject to severe ozone (O3) pollution during daytime and anomalous nocturnal O3 increase (NOI) during nighttime. In this study, the spatiotemporal variation of NOI events in the PRD region from 2006 to 2019 is comprehensively analysed, and the role of vertical transport in the occurrence of NOI events is quantified based on observed surface and vertical O3 and the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5) dataset. The results show that the average annual frequency of NOI events in the whole PRD region during the 14 year period is estimated to be 53 ± 16 d yr−1, with an average of 58 ± 11 µg m−3 for the nocturnal O3 peak (NOP) concentration. Low-level jets (LLJs) are the main meteorological processes triggering NOI events, explaining on average 61 % of NOI events. Annual NOI events exhibit an upward trend before 2011 (4.70 d yr−1) and a downward trend thereafter (−0.72 d yr−1), which is consistent with the annual variation of LLJs (r=0.88, p<0.01). Although the contribution of convective storms (Conv) to NOI events is relatively small with an average value of 11 %, Conv-induced NOI events steadily increased at a rate of 0.26 d yr−1 during this 14 year period due to the impact of urbanisation. Seasonally, a relatively higher frequency of NOI events is observed in spring and autumn, which is consistent with the seasonal pattern of LLJs and maximum daily 8 h average (MDA8) O3. Spatially, NOI events are frequent in the eastern PRD, which agrees well with the spatial distribution of the frequency of LLJs and partially overlaps with the distribution of MDA8 O3 concentration, suggesting that vertical transport plays a more important role in NOI events than daytime O3 concentration. The Weather Research and Forecasting (WRF) model coupled with the Community Multiscale Air Quality (CMAQ) model and the observed vertical O3 profiles are further applied to illustrate the mechanisms of NOI formation caused by LLJs and Conv. The results confirm that both LLJs and Conv trigger NOI events by inducing downdrafts with the difference being that LLJs induce downdrafts by wind shear, while Conv by compensating downdrafts. Through observational and modelling analysis, this study presents the long-term (2006–2019) trends of NOI events in the PRD region and quantifies the contribution of meteorological processes for the first time, emphasising the importance of vertical transport, as well as daytime O3 concentration for the occurrence of NOI events.

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Section: Introductionmentioning

confidence: 99%

Quantitative impacts of vertical transport on the long-term trend of nocturnal ozone increase over the Pearl River Delta region during 2006–2019

You

Jia

et al. 2023

Atmos. Chem. Phys.

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“…Therefore, controlling traffic emissions is the key to improving air pollution in this region. In addition, a large number of studies have shown that the evolution of O 3 , NOx, and VOCs has characteristics such as nonlinearity, non-stationary, and complexity (Han et al, 2020 ; Hao et al, 2018 ; Jiang et al, 2018 ; Liu et al, 2022a , 2022b , 2022c ; Mao et al, 2022 ; Tan et al, 2018 ; Zhou et al, 2022 ). Therefore, to reduce the concentration of O 3 pollution, the precursors VOCs and NOx cannot be controlled simply.…”

Section: Resultsmentioning

confidence: 99%

Long-Term Air Pollution Characteristics and Multi-scale Meteorological Factor Variability Analysis of Mega-mountain Cities in the Chengdu-Chongqing Economic Circle

Abdullah

Sobri

et al. 2023

Water Air Soil Pollut

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Currently, air quality has become central to global environmental policymaking. As a typical mountain megacity in the Cheng-Yu region, the air pollution in Chongqing is unique and sensitive. This study aims to comprehensively investigate the long-term annual, seasonal, and monthly variation characteristics of six major pollutants and seven meteorological parameters. The emission distribution of major pollutants is also discussed. The relationship between pollutants and the multi-scale meteorological conditions was explored. The results indicate that particulate matter (PM), SO 2 and NO 2 showed a “U-shaped” variation, while O 3 showed an “inverted U-shaped” seasonal variation. Industrial emissions accounted for 81.84%, 58% and 80.10% of the total SO 2 , NOx and dust pollution emissions, respectively. The correlation between PM2.5 and PM10 was strong ( R = 0.98). In addition, PM only showed a significant negative correlation with O 3 . On the contrary, PM showed a significant positive correlation with other gaseous pollutants (SO 2 , NO 2 , CO). O 3 is only negatively correlated with relative humidity and atmospheric pressure. These findings provide an accurate and effective countermeasure for the coordinated management of air pollution in Cheng-Yu region and the formulation of the regional carbon peaking roadmap. Furthermore, it can improve the prediction accuracy of air pollution under multi-scale meteorological factors, promote effective emission reduction paths and policies in the region, and provide references for related epidemiological research. Graphical abstract Supplementary Information The online version contains supplementary material available at 10.1007/s11270-023-06279-8.

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“…This work uses the appropriate technology to measure and record these data continuously. This includes air quality sensors that monitor PM2.5, VOCs, and NOx, as well as noise sensors that record noise levels at different locations in the city [ 14 , 15 ]. Vehicle traffic is one of the primary sources of air and noise pollution in cities.…”

Section: Introductionmentioning

confidence: 99%

Integration of Data and Predictive Models for the Evaluation of Air Quality and Noise in Urban Environments

Govea,

Gaibor-Naranjo,

Sanchez-Viteri

et al. 2024

Sensors

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This work addresses assessing air quality and noise in urban environments by integrating predictive models and Internet of Things technologies. For this, a model generated heat maps for PM2.5 and noise levels, incorporating traffic data from open sources for precise contextualization. This approach reveals significant correlations between high pollutant/noise concentrations and their proximity to industrial zones and traffic routes. The predictive models, including convolutional neural networks and decision trees, demonstrated high accuracy in predicting pollution and noise levels, with correlation values such as R2 of 0.93 for PM2.5 and 0.90 for noise. These findings highlight the need to address environmental issues in urban planning comprehensively. Furthermore, the study suggests policies based on the quantitative results, such as implementing low-emission zones and promoting green spaces, to improve urban environmental management. This analysis offers a significant contribution to scientific understanding and practical applicability in the planning and management of urban environments, emphasizing the relevance of an integrated and data-driven approach to inform effective policy decisions in urban environmental management.

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Ozone control strategies for local formation- and regional transport-dominant scenarios in a manufacturing city in southern China

Cited by 21 publications

References 51 publications

Quantitative impacts of vertical transport on the long-term trend of nocturnal ozone increase over the Pearl River Delta region during 2006–2019

Quantitative impacts of vertical transport on the long-term trend of nocturnal ozone increase over the Pearl River Delta region during 2006–2019

Long-Term Air Pollution Characteristics and Multi-scale Meteorological Factor Variability Analysis of Mega-mountain Cities in the Chengdu-Chongqing Economic Circle

Integration of Data and Predictive Models for the Evaluation of Air Quality and Noise in Urban Environments

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