Mitigated PM2.5 Changes by the Regional Transport During the COVID-19 Lockdown in Shanghai, China.
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ABSTRACT:
SUBMITTER: Gu Y
PROVIDER: S-EPMC8250290 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:During the Covid-19 outbreak, strict lockdown measures led to notable reductions in transportation-related emissions and significantly altered atmospheric pollution characteristics in urban and suburban areas. In this work, we compare comprehensive online measurements of PM2.5 major components and organic molecular markers in a suburban location in Shanghai, China before lockdown (Dec. 28, 2019 to Jan. 23, 2020) and during lockdown (Jan. 24 to Feb. 9, 2020). The NOx levels declined sharply by 59% from 44 to 18 ppb during the lockdown, while O3 rose two times higher to 42 ppb. The PM2.5 level dropped from 64 to 49 μg m-3 (-24%). The major components all showed reductions, with the reduction of nitrate most prominent at -58%, followed by organics at -19%, and sulfate at -17%. Positive matrix factorization analysis identifies fourteen source factors, including nine primary sources and five secondary sources. The secondary sources consist of sulfate-rich factor, nitrate-rich factor, and three secondary organic aerosol (SOA) factors, with SOA_I being anthropogenic SOA, SOA_II associated with later generation products of organic oxidation, and SOA_III being biogenic SOA. The combined secondary sources contributed to 69% and 63% (40 and 22 μg m-3) of PM2.5 before and during lockdown, respectively, among which the reductions in the nitrate-rich (-55%) factor was the most prominent. Among primary sources, large reductions (>80%) were observed in contributions from industrial, cooking, and vehicle emissions. Unlike some studies reporting that the restriction during the Covid-19 resulted in enhanced secondary sulfate and SOA formation, we observed decreases in both secondary inorganic and SOA formation despite the overall elevated oxidizing capacity in the suburban site. Our results indicate that the formation change in secondary inorganic and organic compounds in response to substantial reductions in urban primary precursors are different for urban and suburban environments.
| S-EPMC9359772 | biostudies-literature
Project description:To analyse the cause of the atmospheric PM2.5 pollution that occurred during the COVID-19 lockdown in Nanning, Guangxi, China, a single particulate aerosol mass spectrometer, aethalometer, and particulate Lidar coupled with monitoring near-surface gaseous pollutants, meteorological conditions, remote fire spot sensing by satellite and backward trajectory models were utilized during 18-24 February 2020. Three haze stages were identified: the pre-pollution period (PPP), pollution accumulation period (PAP) and pollution dissipation period (PDP). The dominant source of PM2.5 in the PPP was biomass burning (BB) (40.4%), followed by secondary inorganic sources (28.1%) and motor vehicle exhaust (11.7%). The PAP was characterized by a large abundance of secondary inorganic sources, which contributed 56.1% of the total PM2.5 concentration, followed by BB (17.4%). The absorption Ångström exponent (2.2) in the PPP was higher than that in the other two periods. Analysis of fire spots monitored by remote satellite sensing indicated that open BB in regions around Nanning City could be one of the main factors. A planetary boundary layer-relative humidity-secondary particle matter-particulate matter positive feedback mechanism was employed to elucidate the atmospheric processes in this study. This study highlights the importance of understanding the role of BB, secondary inorganic sources and meteorology in air pollution formation and calls for policies for emission control strategies.
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Project description:The COVID-19 epidemic broke out in Wuhan, Hubei in December 2019 and in January 2020 and was later transmitted to the entire country. Quarantine measures during Chinese New Year effectively alleviated the spread of the epidemic, but they simultaneously resulted in a decline in anthropogenic emissions from industry, transportation, and import and export of goods. Herein, we present the major chemical composition of non-refractory PM2.5 (NR-PM2.5) and the concentrations of gaseous pollutants in an urban site in Shanghai before and during the quarantine period of the COVID-19 epidemic, which was Jan. 8-23 and Jan. 24-Feb. 8, respectively. The observed results show that the reduction in PM2.5 can be mainly attributed to decreasing concentrations of nitrate and primary aerosols. Nitrate accounted for 37% of NR-PM2.5 before the quarantine period when there was no emission reduction. During the quarantine period, the nitrate concentration decreased by approximately 60%, which is attributed to a reduction in the NOx concentration. Ammonium, as the main balancing cation, showed an approximately 45% simultaneous decrease in concentration. The concentrations of chloride and hydrocarbon-like organic aerosols from primary emissions also declined due to limited human activities. By contrast, sulphate and oxygenated organic aerosols showed a slight decrease in concentration, with their contributions increasing to 27% and 18%, respectively, during the quarantine period, which resulted in two pollution episodes with PM2.5 exceeding 100 μg/m3. This study provides a better understanding of the impact of quarantine measures on variations of the PM2.5 concentration and chemical compositions. Atmospheric oxidation capacities based on the oxidant (Ox = O3 + NO2) and oxidation ratios have been discussed for elucidating the source and formation of haze in an environment with lower anthropogenic emissions. With increasing contribution of secondary aerosols, lower NOx and nitrate concentrations did not completely avoid haze in Shanghai during the epidemic.
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Project description:We apply an online-coupled meteorology-chemistry model (WRF-Chem) embedded with an improved process analysis to examine aerosol-radiation feedback (ARF) impacts on effectiveness of emission control due to Coronavirus Disease 2019 (COVID-19) lockdown over North China Plain. Emission reduction alone induces PM2.5 decrease by 16.3 μg m-3 and O3 increase by 10.2 ppbv during COVID-19 lockdown. The ARF enhances PM2.5 decrease by 2.7 μg m-3 (16.6%) and O3 increase by 0.8 ppbv (7.8%). The ARF-induced enhancement of PM2.5 decline is mostly attributed to aerosol chemistry process, while enhancement of O3 rise is ascribed to physical advection and vertical mixing processes. A set of sensitivity experiments with emission reductions in different degrees indicate that the ARF-induced enhancements of PM2.5 declines (O3 rises) follow a robust linear relationship with the emission-reduction-induced PM2.5 decreases. The fitted relationship has an important implication for assessing the effectiveness of emission abatement at any extent.
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Project description:Estimating the impacts on PM2.5 pollution and CO2 emissions by human activities in different urban regions is important for developing efficient policies. In early 2020, China implemented a lockdown policy to contain the spread of COVID-19, resulting in a significant reduction of human activities. This event presents a convenient opportunity to study the impact of human activities in the transportation and industrial sectors on air pollution. Here, we investigate the variations in air quality attributed to the COVID-19 lockdown policy in the megacities of China by combining in-situ environmental and meteorological datasets, the Suomi-NPP/VIIRS and the CO2 emissions from the Carbon Monitor project. Our study shows that PM2.5 concentrations in the spring of 2020 decreased by 41.87% in the Yangtze River Delta (YRD) and 43.30% in the Pearl River Delta (PRD), respectively, owing to the significant shutdown of traffic and manufacturing industries. However, PM2.5 concentrations in the Beijing-Tianjin-Hebei (BTH) region only decreased by 2.01% because the energy and steel industries were not fully paused. In addition, unfavorable weather conditions contributed to further increases in the PM2.5 concentration. Furthermore, CO2 concentrations were not significantly affected in China during the short-term emission reduction, despite a 19.52% reduction in CO2 emissions compared to the same period in 2019. Our results suggest that concerted efforts from different emission sectors and effective long-term emission reduction strategies are necessary to control air pollution and CO2 emissions.
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Project description:Specification of PM 2.5 transmission characteristics is important for pollution control and policymaking. We apply higher-order organization of complex networks to identify major potential PM 2.5 contributors and PM 2.5 transport pathways of a network of 189 cities in China. The network we create in this paper consists of major cities in China and contains information on meteorological conditions of wind speed and wind direction, data on geographic distance, mountains, and PM 2.5 concentrations. We aim to reveal PM 2.5 mobility between cities in China. Two major conclusions are revealed through motif analysis of complex networks. First, major potential PM 2.5 pollution contributors are identified for each cluster by one motif, which reflects movements from source to target. Second, transport pathways of PM 2.5 are revealed by another motif, which reflects transmission routes. To our knowledge, this is the first work to apply higher-order network analysis to study PM 2.5 transport.
| S-EPMC5643331 | biostudies-literature
Project description:A comprehensive investigation using the air quality network and meteorological data of China in 2015 showed that PM2.5 driven by cold surges from the ground level could travel up to 2000 km from northern to southern China within two days. Air pollution is more severe and prominent during the winter in north China due to seasonal variations in energy usage, trade wind movements, and industrial emissions. In February 2015, two cold surges traveling from north China caused a temporary increase in the concentration of PM2.5 in Shanghai. Subsequently, the concentration of PM2.5 in Xiamen increased to a high of 80 µg/m3, which is double the average PM2.5 concentration in Xiamen during the winter. This finding is a new long-range transport mechanism comparing to the well-established mechanism, with long-range transport more likely to occur in the upper troposphere than at lower levels. These observations were validated by results from the back trajectory analysis and the RAMS- CMAQ model. While wind speed was found to be a major facilitator in transporting PM2.5 from Beijing to Xiamen, more investigation is required to understand the complex relationship between wind speed and PM2.5 and how it moderates air quality in Beijing, Shanghai, and Xiamen.
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Project description:The spatial disparity of air pollutants is one of the key influential factors for environmental inequality. We quantitatively evaluated the evolution of PM2.5 spatial disparity in China during 2013-2020, and investigated the associations between PM2.5 spatial disparity and economic indicators. Differences in PM2.5 between more- and less-polluted cities declined over time, suggesting decreased absolute disparity. However, the more polluted cities in 2013 remained so in 2017 and 2020, and vice versa, indicating persistent relative disparity. PM2.5 pollution levels increased with higher GDP per capita in less-developed areas of China, but such negative effects weakened over time, while economic development tended to promote cleaner air in developed areas of China. Therefore, policies to improve air quality and promote economic development simultaneously are needed in China to reduce the disparity of air pollution and promote all people to enjoy environmental equality.
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Project description:Fine particulate matter (PM2.5) has been reported to be an important risk factor for asthma. This study was designed to evaluate the relationship between PM2.5 and lung function among children with asthma in Shanghai, China. From 2016 to 2019, a total of 70 Chinese children aged 4 to 14 in Shanghai were recruited for this panel study. The questionnaire was used to collect baseline information, and the lung function covering forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1) and peak expiratory flow (PEF) were carried out for each child more than twice during follow-up. Meanwhile, the simultaneous daily air atmospheric pollutants and meteorological data were collected. The linear mixed effect (LME) model was used to assess the relationship between air pollutants and lung function. A significantly negative association was found between PM2.5 and lung function in children with asthma. In the single-pollutant model, the largest effects of PM2.5 on lung function were found for lag 0-2, with FVC and FEV1 decreasing by 0.91% [95% confidence interval (CI): -1.75, -0.07] and 1.05% (95% CI: -2.09, 0.00), respectively, for each 10 μg/m3 increase in PM2.5. In the multi-pollution model (adjusted PM2.5 + SO2 + O3), the maximum effects of PM2.5 on FVC and FEV1 also appeared for lag 0-2, with FVC and FEV1 decreasing by 1.57% (95% CI: -2.69, -0.44) and 1.67% (95% CI: -3.05, -0.26), respectively, for each 10 μg/m3 increase in PM2.5. In the subgroup analysis, boys, preschoolers (<6 years old) and hot seasons (May to September) were more sensitive to changes. Our findings may contribute to a better understanding of the short-term exposure effects of PM2.5 on lung function in children with asthma.
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Project description:Aerosol-cloud interactions (aerosol indirect effects) play an important role in regional meteorological variations, which could further induce feedback on regional air quality. While the impact of aerosol-cloud interactions on meteorology and climate has been extensively studied, their feedback on air quality remains unclear. Using a fully coupled meteorology-chemistry model, we find that increased aerosol loading due to anthropogenic activities in China substantially increases column cloud droplet number concentration and liquid water path (LWP), which further leads to a reduction in the downward shortwave radiation at surface, surface air temperature and planetary boundary layer (PBL) height. The shallower PBL and accelerated cloud chemistry due to larger LWP in turn enhance the concentrations of particulate matter with diameter less than 2.5 μm (PM2.5) by up to 33.2 μg m-3 (25.1%) and 11.0 μg m-3 (12.5%) in January and July, respectively. Such a positive feedback amplifies the changes in PM2.5 concentrations, indicating an additional air quality benefit under effective pollution control policies but a penalty for a region with a deterioration in PM2.5 pollution. Additionally, we show that the cloud processing of aerosols, including wet scavenging and cloud chemistry, could also have substantial effects on PM2.5 concentrations.
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