Characteristics of typical intermediate and semi volatile organic compounds in Shanghai during China International Import Expo event.

To ensure good air quality during the China International Import Expo (CIIE) event, stringent emission-reduction measures were implemented in Shanghai. To assess the efficacy of these measures, this study measured typical categories of intermediate/semi volatile organic compounds (I/SVOCs), including alkanes (C10-C26 n-alkanes and pristane), EPA-priority polycyclic aromatic hydrocarbons (PAHs), alkylnaphthalenes, benzothiazole (BTH) and chlorobenzenes (CBs), at an urban site of Shanghai before and during two CIIE events (2019 and 2020; non-CIIE versus CIIE). The average concentrations of alkanes and PAHs during both 2019 and 2020 CIIE events decreased by approximately 41% and 17%, respectively, compared to non-CIIE periods. However, the decline in BTH and CBs was only observed during CIIE-2019. Secondary organic aerosol (SOA) formation from alkanes, PAHs and BTH was evaluated under atmospheric conditions, revealing considerable SOA contributions from dimethylnaphthalenes and BTH. Positive matrix factorization (PMF) analysis further revealed that life-related sources, such as cooking and residential emissions, make a noticeable contribution (21.6%) in addition to the commonly concerned gasoline-vehicle sources (31.5%), diesel-related emissions (20.8%), industrial emissions (18.6%) and ship emissions (7.5%). These findings provide valuable insights into the efficacy of the implemented measures in reducing atmospheric I/SVOCs levels. Moreover, our results highlight the significance of exploring additional individual species of I/SVOCs and life-related sources for further research and policy development.

Characterization of organic vapors by a Vocus proton-transfer-reaction mass spectrometry at a mountain site in southeastern China.

Biogenic and anthropogenic organic vapors are crucial precursors of ozone and secondary organic aerosol (SOA) in the atmosphere. Here we conducted real-time measurements of gaseous organic compounds using a Vocus proton-transfer-reaction mass spectrometer (Vocus PTR-MS) at the Shanghuang mountain site (1128 m a.s.l.) in southeastern China during November 2022. Our results revealed a substantial impact of mixed biogenic and anthropogenic compounds at the mountain site, with oxygenated volatile organic compounds (OVOCs) comprising 74 % of the organic vapors. Two distinct periods, characterized by sunny days (P1) and persistent cloud events (P2), were observed. P1 exhibited higher concentrations of biogenic-related emissions compared to P2. For instance, isoprene, monoterpenes, and sesquiterpenes during P1 were 2.4-2.9 times higher than those during P2. OVOCs such as acetaldehyde, MVK + MACR, acetone, and MEK also showed higher concentrations during P1, indicating a dominant source from the photochemical oxidation of biogenic VOCs. Anthropogenic-related VOCs like benzene and toluene had higher concentrations during P2, displaying different diurnal cycles compared to P1. Our analysis identified four biogenic-related factors dominated by isoprene and sesquiterpene oxidation products, and two anthropogenic-related factors. During P1, biogenic sources contributed approximately 80 % to total organic compounds, while during P2, anthropogenic sources, particularly the aromatic-related factor, increased from 16 % to 35 %. Furthermore, a unique factor characterized by C2 amines and C3 amides and periodic plumes indicated the influence of industrial emissions from regional transport. The study highlights the significant variations in sources and compositions of gaseous organic compounds at regional mountain sites due to changes in meteorology and photochemical processing, potentially impacting regional ozone and SOA formation.

High organic aerosol in the low layer over a rural site in the North China Plain (NCP): Observations based on large tethered balloon.

High mass concentration of organic aerosol (OA) and its fraction in PM2.5 (particle matter with radius <2.5 µm) were observed in the low layer over a rural site of the North China Plain (NCP) in winter 2018. The mass fraction of OA in PM2.5 was 65.5 % at ground level (5 m above ground), and decreased to 37.1 % in layer of 200-1000 m. In addition, there was a sharp decrease of OA at around the top of planetary boundary layer (PBL), which was distinctly different from the vertical distributions of secondary inorganic aerosols (SIA, e.g., nitrate (NO3-), ammonium (NH4+), and sulfate (SO42-)). The altitude with sharp decrease of OA was very low in the morning and evening, e.g., the sharp decrease of OA occurred at a height <50 m at nighttime on Dec. 19, while was elevated in the noon with the PBL development. Furthermore, OA at ground level exhibited a distinct diurnal variation with a night-to-day ratio of 2.3, which was much larger than those of SIA and inactive CO. All the above results indicated the extremely high OA concentration at the rural site was mainly attributed to direct emission from local sources, such as the combustion of coal and biomass for heating. The extremely high OA could be expected in vest rural areas of the NCP in winter because the farmer activities are very similar to the investigated rural site, underscoring the urgency to mitigate OA emission in rural area for improving the local as well as the regional air quality.

Associations between ultrafine particle pollution and daily outpatient visits for respiratory diseases in Shanghai, China: a time-series analysis.

Previous epidemiological studies have linked short-term exposure to particulate matter with outpatient visits for respiratory diseases. However, evidence on ultrafine particle (UFP) is still scarce in China. To investigate the association between short-term UFP exposure and outpatient visits for respiratory diseases as well as the corresponding lag patterns, information on outpatient visits for main respiratory diseases during January 1, 2017, to December 31, 2019 was collected from electronic medical records of two large tertiary hospitals in Shanghai, China. Generalized additive models employing a Quasi-Poisson distribution were employed to investigate the relationships between UFP and respiratory diseases. We computed the percentage change and its corresponding 95% confidence interval (CI) for outpatient visits related to respiratory diseases per interquartile range (IQR) increase in UFP concentrations. Based on a total of 1,034,394 hospital visits for respiratory diseases in Shanghai, China, we found that the strongest associations of total UFP with acute upper respiratory tract infection (AURTI), bronchitis, chronic obstructive pulmonary disease (COPD), and pneumonia occurred at lag 03, 03, 0, and 03 days, respectively. Each IQR increase in the total UFP concentrations was associated with increments of 9.02% (95% CI: 8.64-9.40%), 3.94% (95% CI: 2.84-5.06%), 4.10% (95% CI: 3.01-5.20%), and 10.15% (95% CI: 9.32-10.99%) for AURTI, bronchitis, COPD, and pneumonia, respectively. Almost linear concentration-response relationship curves without apparent thresholds were observed between total UFP and outpatient-department visits for four respiratory diseases. Stratified analyses illustrated significantly stronger associations of total UFP with AURTI, bronchitis, and pneumonia among female patients, while that with COPD was stronger among male patients. After adjustment of criteria air pollutants, these associations all remained robust. This time-series study indicates that short-term exposure to UFP was associated with increased risk of hospital visits for respiratory diseases, underscoring the importance of reducing ambient UFP concentrations for respiratory diseases control and prevention.

Knockdown of BUB1B Inhibits the Proliferation, Migration, and Invasion of Colorectal Cancer by Regulating the JNK/c-Jun Signaling Pathway.

Background: Colorectal cancer (CRC) ranks as the third most common cancer, accounting for a significant number of cancer-related deaths worldwide every year. Yet, the molecular mechanisms responsible for the progression of this malignancy are not fully understood. Numerous studies indicate that BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) plays a role in the progression of various malignant tumors. However, the specific biological functions and the detailed mechanisms of how BUB1B influences CRC are still not completely known. This study aimed to explore the expression and role of BUB1B in CRC. Materials and Methods: To achieve this, the expression levels of BUB1B in human CRC tissues and cell lines were examined using real-time polymerase chain reaction and Western blotting. The role and associated mechanisms of BUB1B in CRC cell progression were assessed both in vitro and in vivo using RNA interference. Results: The findings of this study revealed an elevated expression of BUB1B in both CRC tissues and cell lines. The silencing of BUB1B in CRC cell lines notably inhibited cell proliferation, migration, and invasion, leading to cell cycle arrest and apoptosis. In addition, the knockdown of BUB1B inhibited the JNK/c-Jun signaling pathway, increased the expression of proapoptotic proteins, and decreased the expression of antiapoptotic proteins. The effects of BUB1B knockdown on CRC cell progression were reversed by the JNK activator PAF(C-16). Conclusions: In summary, the suppression of BUB1B hindered malignant tumor progression and heightened apoptosis and cell cycle arrest in CRC cells via the JNK/c-Jun pathway. Importantly, the removal of BUB1B expression curtailed tumor growth in human CRC xenografts in nude mice, suggesting its potential as a promising therapeutic target for CRC patients. ClinicalTrials.gov ID: No.2019 K-C086.

[A Comparison Study on Multiple Modeling Approaches for Air Pollutant Geographic Model Development in Shanghai].

Geostatistical models have been widely used in the exposure assessment of ambient air pollutants. However, few studies have focused on comparisons of modeling approaches and their prediction results. Here, we collected the NO2 and PM2.5 monitoring data from 55 sites in Shanghai from 2016 to 2019 and the geographic variables, such as road network, points of interest of emission locations, and satellite data were included. We used partial least squares regression (PLS), supervised linear regression (SLR), and random forest (RF) algorithms to develop spatial models and used ordinary kriging (OK) to develop a two-step model. We evaluated the models using a 5-fold cross validation method and selected the best model structure for each modeling approach between one-or two-step models that had been developed with or without OK. The results revealed that the best NO2 models were the RF-OK (Rmse2 was 0.70-0.82) and PLS-OK (Rmse2 was 0.78-0.84) models; the PLS model for PM2.5(Rmse2 was 0.62-0.71) outperformed the other PM2.5 models. We used the best models to predict annual exposures in Shanghai at a 1 km spatial scale and conducted the correlation analysis among the predictions of the best models. The results demonstrated that the NO2 predictions had higher correlation coefficients (r was 0.82-0.91) compared with those of the PM2.5 models (r was 0.66-0.96). Based on the exposure results predicted using the three models in 2019, we evaluated the cumulative population exposure concentrations for NO2 and PM2.5 in Shanghai.

Atmospheric mercury in a developed region of eastern China: Interannual variation and gas-particle partitioning.

Atmospheric mercury plays a crucial role in the biogeochemical cycle of mercury. This study conducted an intensive measurement of atmospheric mercury from 2015 to 2018 at a regional site in eastern China. During this period, the concentration of particle-bound mercury (PBM) decreased by 13%, which was much lower than those of gaseous elemenral mercury (GEM, 30%) and reactive gaseous mercury (GOM, 62%). The gradual decrease in the correlation between PBM and CO, K, and Pb indicates that the influence of primary emissions on PBM concentration was weakening. Moreover, the value of the partitioning coefficient (Kp) increased gradually from 0.05 ± 0.076 m3/µg in 2015 to 0.16 ± 0.37 m3/µg in 2018, indicating that GOM was increasingly inclined to adsorb onto particulate matter. Excluding the influence of meteorological conditions and the primary emissions, the change in aerosol composition is designated as the main trigger factor for the increasing gas-particle partitioning of reactive mercury (RM). The increasing ratio of Cl-, NO3-, and organics (Org) in the chemical composition of particle matters (PM2.5), as well as the decrease in the proportion of SO42-, NH4+, and K+, are conducive to the adsorption of GOM onto particles, forming PBM, which led to an increase of Kp and a lag of PBM reduction compared to GEM and GOM under the continuous control measures of anthropogenic mercury emissions. The evolution of aerosol compositions in recent years affects the migration and transformation of atmospheric mercury, which in turn can affect the biogeochemical cycle of mercury.

Comprehensive Assessment of Pollution Sources and Health Impacts in Suburban Area of Shanghai.

Shanghai, one of China's largest metropolises, faces significant environmental pollution challenges due to rapid economic development. Suburban areas of Shanghai are affected by both long-distance transport and local sources of pollutants. This study conducted an integrated analysis that links health-risk assessment of heavy metals and source apportionment of atmospheric constituents to distinguish the contributions of emission sources and the major sources of health risks. Source-apportionment analysis revealed that secondary sources had the greatest contribution to the local pollutants, indicating the significant influence of peripheral and long-distance transport. Health-risk assessment of Cr, Ni, As, and Cd revealed that local residents were exposed to respiratory health risks, in which Cr is the major contributor. This health risk was primarily associated with emissions from nearby industry-related sources. Our study highlights the significant effects of both long-distance transport and local source emissions on atmospheric composition and human health in large urban agglomerations. The findings can inform future efforts to develop more precise emission-reduction strategies and policy improvements to mitigate environmental pollution and protect public health.

Budget of atmospheric nitrous acid (HONO) during the haze and clean periods in Shanghai: Importance of heterogeneous reactions.

Nitrous acid (HONO) plays a significant role in radical cycling and atmospheric oxidative chemistry. While the source and evolution of HONO in the Yangtze River Delta (YRD) region of China after 2018 remains largely unknown, this work monitored HONO and other air pollutants throughout 2019 at an urban site (Pudong, PD) and a suburban site (Qingpu, QP) in Shanghai. Episodes with high HONO mixing ratios but different PM2.5 levels, namely haze and clean episodes, were chosen for HONO budget analysis. Using an observation-based photochemical box model, relative importance of different sources and sinks of HONO were evaluated. Gas-phase reaction of NO with OH was found to be one of the most important daytime HONO formation sources, especially during the QPhaze period (accounting for 40.3 % of daytime HONO formation). In particular, heterogeneous conversion of NO2 on ground and aerosol surface was found to be the dominant source for nocturnal HONO. Photo-enhanced NO2 conversion on ground surface plays an important role in daytime HONO production (19.4 % in PDhaze vs. 27.6 % in PDclean, and 19.8 % in QPhaze vs. 25.9 % in QPclean). In addition, photo-enhanced NO2 conversion at the aerosol surface during haze episodes made more significant contributions to HONO formation compared to the clean periods (20.9 % in PDhaze vs. 17.1 % in PDclean, and 19.7 % in QPhaze vs. 11.2 % in QPclean). The role of multiphase reactions was found to be increasingly important in HONO generation with enhanced relative humidity (RH) during daytime. Significant unknown HONO source was further analyzed and found to be positively related with photolytic as well as multiphase pathways. Overall, our study sheds light on the budget of HONO in one of the biggest megacities in east China, which would help developing future mitigation strategies for urban HONO and atmospheric oxidation capacity.

Relationship between light absorption properties of black carbon and aerosol origin at a background coastal site.

As a potent climate forcer, black carbon (BC) optical properties can have significant impacts on the regional meteorology and climate. To unveil the seasonal differences of BC and its contribution by various emission sources, a one-year continuous monitoring of atmospheric aerosols was conducted at a background coastal site in Eastern China. By comparing the seasonal and diurnal patterns between BC and elemental carbon, we observed that BC were evidently aged with varying extents among all four seasons. The light absorption enhancement of BC (Eabs) was calculated as 1.89 ± 0.46, 2.40 ± 0.69, 1.91 ± 0.60, and 1.34 ± 0.28, from spring to winter, respectively, indicating that BC was more aged in summer. Contrary to the negligible impact of pollution levels on Eabs, the patterns of air masses arriving to the sampling site had a significant impact on the seasonal optical characteristics of BC. Sea breezes evidently exhibited higher Eabs than land-sourced breezes, and BC was more aged and light-absorbing with an increased contribution of marine airflows. By applying a receptor model, we resolved six emission sources as ship emission, traffic emission, secondary pollution, coal combustion, sea salt, and mineral dust. The mass absorption efficiency of BC for each source was estimated, showing the highest from the ship emission sector. This explained the highest Eabs observed in summer and sea breezes. Our study highlights that curbing emission from shipping activities is beneficial for reducing the warming effect of BC in coastal areas, particularly in the context of future rapid development of international shipping.

A satellite-driven model to estimate long-term particulate sulfate levels and attributable mortality burden in China.

Ambient fine particulate matter (PM2.5) pollution is a major environmental and public health challenge in China. In the recent decade, the PM2.5 level has decreased mainly driven by reductions in particulate sulfate as a result of large-scale desulfurization efforts in coal-fired power plants and industrial facilities. Emerging evidence also points to the differential toxicity of particulate sulfate affecting human health. However, estimating the long-term spatiotemporal trend of sulfate is difficult because a ground monitoring network of PM2.5 constituents has not been established in China. Spaceborne sensors such as the Multi-angle Imaging SpectroRadiometer (MISR) instrument can provide complementary information on aerosol size and type. With the help of state-of-the-art machine learning techniques, we developed a sulfate prediction model under support from available ground measurements, MISR-retrieved aerosol microphysical properties, and atmospheric reanalysis data at a spatial resolution of 0.1°. Our sulfate model performed well with an out-of-bag cross-validationR2 of 0.68 at the daily level and 0.93 at the monthly level. We found that the national mean population-weighted sulfate concentration was relatively stable before the Air Pollution Prevention and Control Action Plan was enforced in 2013, ranging from 10.4 to 11.5 µg m-3. But the sulfate level dramatically decreased to 7.7 µg m-3 in 2018, with a change rate of -28.7 % from 2013 to 2018. Correspondingly, the annual mean total non-accidental and cardiopulmonary deaths attributed to sulfate decreased by 40.7 % and 42.3 %, respectively. The long-term, full-coverage sulfate level estimates will support future studies on evaluating air quality policies and understanding the adverse health effect of particulate sulfate.

A hybrid deep learning model for regional O3 and NO2 concentrations prediction based on spatiotemporal dependencies in air quality monitoring network.

Short-term prediction of urban air quality is critical to pollution management and public health. However, existing studies have failed to make full use of the spatiotemporal correlations or topological relationships among air quality monitoring networks (AQMN), and hence exhibit low precision in regional prediction tasks. With this consideration, we proposed a novel deep learning-based hybrid model of Res-GCN-BiLSTM combining the residual neural network (ResNet), graph convolutional network (GCN), and bidirectional long short-term memory (BiLSTM), for predicting short-term regional NO2 and O3 concentrations. Auto-correlation analysis and cluster analysis were first utilized to reveal the inherent temporal and spatial properties respectively. They demonstrated that there existed temporal daily periodicity and spatial similarity in AQMN. Then the identified spatiotemporal properties were sufficiently leveraged, and monitoring network topological information, as well as auxiliary pollutants and meteorology were also adaptively integrated into the model. The hourly observed data from 51 air quality monitoring stations and meteorological data in Shanghai were employed to evaluate it. Results show that the Res-GCN-BiLSTM model was better adapted to the pollutant characteristics and improved the prediction accuracy, with nearly 11% and 17% improvements in mean absolute error for NO2 and O3, respectively compared to the best performing baseline model. Among the three types of monitoring stations, traffic monitoring stations performed the best for O3, but the worst for NO2, mainly due to the impacts of intensive traffic emissions and the titration reaction. These findings illustrate that the hybrid architecture is more suitable for regional pollutant concentration.

Hourly Ultrafine Particle Exposure and Acute Myocardial Infarction Onset: An Individual-Level Case-Crossover Study in Shanghai, China, 2015-2020.

Associations between ultrafine particles (UFPs) and hourly onset of acute myocardial infarction (AMI) have rarely been investigated. We aimed to evaluate the impacts of UFPs on AMI onset and the lag patterns. A time-stratified case-crossover study was performed among 20,867 AMI patients from 46 hospitals in Shanghai, China, between January 2015 and December 2020. Hourly data of AMI onset and number concentrations of nanoparticles of multiple size ranges below 0.10 µm (0.01-0.10, UFP/PNC0.01-0.10; 0.01-0.03, PNC0.01-0.03; 0.03-0.05, PNC0.03-0.05; and 0.05-0.10 µm, PNC0.05-0.10) were collected. Conditional logistic regressions were applied. Transient exposures to these nanoparticles were significantly associated with AMI onset, with almost linear exposure-response curves. These associations occurred immediately after exposure, lasted for approximately 6 h, and attenuated to be null thereafter. Each interquartile range increase in concentrations of total UFPs, PNC0.01-0.03, PNC0.03-0.05, and PNC0.05-0.10 during the preceding 0-6 h was associated with increments of 3.29, 2.08, 2.47, and 2.93% in AMI onset risk, respectively. The associations were stronger during warm season and at high temperatures and were robust after adjusting for criteria air pollutants. Our findings provide novel evidence that hourly UFP exposure is associated with immediate increase in AMI onset risk.

Evidence of aircraft activity impact on local air quality: A study in the context of uncommon airport operation.

Wuhan Tianhe International Airport (WUH) was suspended to contain the spread of COVID-19, while Shanghai Hongqiao International Airport (SHA) saw a tremendous flight reduction. Closure of a major international airport is extremely rare and thus represents a unique opportunity to straightforwardly observe the impact of airport emissions on local air quality. In this study, a series of statistical tools were applied to analyze the variations in air pollutant levels in the vicinity of WUH and SHA. The results of bivariate polar plots show that airport SHA and WUH are a major source of nitrogen oxides. NOx, NO2 and NO diminished by 55.8%, 44.1%, 76.9%, and 40.4%, 33.3% and 59.4% during the COVID-19 lockdown compared to those in the same period of 2018 and 2019, under a reduction in aircraft activities by 58.6% and 61.4%. The concentration of NO2, SO2 and PM2.5 decreased by 77.3%, 8.2%, 29.5%, right after the closure of airport WUH on 23 January 2020. The average concentrations of NO, NO2 and NOx scatter plots at downwind of SHA after the lockdown were 78.0%, 47.9%, 57.4% and 62.3%, 34.8%, 41.8% lower than those during the same period in 2018 and 2019. However, a significant increase in O3 levels by 50.0% and 25.9% at WUH and SHA was observed, respectively. These results evidently show decreased nitrogen oxides concentrations in the airport vicinity due to reduced aircraft activities, while amplified O3 pollution due to a lower titration by NO under strong reduction in NOx emissions.

Application of multi-angle spaceborne observations in characterizing the long-term particulate organic carbon pollution in China.

Ambient PM2.5 pollution is recognized as a leading environmental risk factor, causing significant mortality and morbidity in China. However, the specific contributions of individual PM2.5 constituents remain unclear, primarily due to the lack of a comprehensive ground monitoring network for constituents. This issue is particularly critical for carbonaceous species such as organic carbon (OC) and elemental carbon (EC), which are known for their significant health impacts, and understanding the OC/EC ratio is crucial for identifying pollution sources. To address this, we developed a Super Learner model integrating Multi-angle Imaging SpectroRadiometer (MISR) retrievals to predict daily OC concentrations across China from 2003 to 2019 at a 10-km spatial resolution. Our model demonstrates robust predictive accuracy, as evidenced by a random cross-validation R2 of 0.84 and an RMSE of 4.9 µg/m3, at the daily level. Although MISR is a polar-orbiting instrument, its fractional aerosol data make a significant contribution to the OC exposure model. We then use the model to explore the spatiotemporal distributions of OC and further calculate the EC/OC ratio in China. We compared regional pollution discrepancies and source contributions of carbonaceous pollution over three selected regions: Beijing-Tianjin-Hebei, Fenwei Plain, and Yunnan Province. Our model observes that OC levels are elevated in Northern China due to industrial operations and central heating during the heating season, while in Yunnan, OC pollution is mainly contributed by local forest fires during fire seasons. Additionally, we found that OC pollution in China is likely influenced by climate phenomena such as the El Niño-Southern Oscillation. Considering that climate change is increasing the severity of OC concentrations with more frequent fire events, and its influence on OC formation and dispersion, we suggest emphasizing the role of climate change in future OC pollution control policies. We believe this study will contribute to future epidemiological studies on OC, aiding in refining public health guidelines and enhancing air quality management in China.

Short-Term Associations between Size-Fractioned Particles and Cardiopulmonary Function in COPD Patients: A Panel Study in Shanghai, China, during 2014-2021.

It remains unknown which size fractions dominate the adverse cardiopulmonary effects of particulate matter (PM). Therefore, this study aimed to explore the differential associations between size-fractioned particle number concentrations (PNCs) and cardiopulmonary function measures, including the forced expiratory volume in one second (FEV1), the forced vital capacity (FVC), and the left ventricular ejection fraction (LVEF). We conducted a panel study among 211 patients with chronic obstructive pulmonary disease (COPD) in Shanghai, China, between January 2014 and December 2021. We applied linear mixed-effect models to determine the associations between cardiopulmonary function measures and PNCs ranging from 0.01 to 10 µm in diameter. Generally, only particles <1 µm showed significant associations, i.e., ultrafine particles (UFPs, <0.1 µm) for FVC and particles ranging from 0.1 to 1 µm for FEV1 and LVEF. An interquartile range (IQR) increment in UFP was associated with decreases of 78.4 mL in FVC. PNC0.1-0.3 and PNC0.3-1 corresponded to the strongest effects on FEV1 (119.5 mL) and LVEF (1.5%) per IQR increment. Particles <1 µm might dominate the cardiopulmonary toxicity of PM, but UFPs might not always have the strongest effect. Tailored regulations towards particles <1 µm should be intensified to reduce PM pollution and protect vulnerable populations.

Increased contribution to PM2.5 from traffic-influenced road dust in Shanghai over recent years and predictable future.

Traffic contributes to fine particulate matter (PM2.5) in the atmosphere through engine exhaust emissions and road dust generation. However, the evolution of traffic related PM2.5 emission over recent years remains unclear, especially when various efforts to reduce emission e.g., aftertreatment technologies and high emission standards from China IV to China V, have been implemented. In this study, hourly elemental carbon (EC), a marker of primary engine exhaust emissions, and trace element of calcium (Ca), a marker of road dust, were measured at a nearby highway sampling site in Shanghai from 2016 to 2019. A random forest-based machine learning algorithm was applied to decouple the influences of meteorological variables on the measured EC and Ca, revealing the deweathered trend in exhaust emissions and road dust. After meteorological normalization, we showed that non-exhaust emissions, i.e., road dust from traffic, increased their fractional contribution to PM2.5 over recent years. In particular, road dust was found to be more important, as revealed by the deweathered trend of Ca fraction in PM2.5, increasing at 6.1% year-1, more than twice that of EC (2.9% year-1). This study suggests that while various efforts have been successful in reducing vehicular exhaust emissions, road dust will not abate at a similar rate. The results of this study provide insights into the trend of traffic-related emissions over recent years based on high temporal resolution monitoring data, with important implications for policymaking.

Hourly organic tracers-based source apportionment of PM2.5 before and during the Covid-19 lockdown in suburban Shanghai, China: Insights into regional transport influences and response to urban emission reductions.

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.

Assessment of long-term particulate nitrate air pollution and its health risk in China.

Air pollution is a major environmental and public health challenge in China and the Chinese government has implemented a series of strict air quality policies. However, particulate nitrate (NO3 -) concentration remains high or even increases at monitoring sites despite the total PM2.5 concentration has decreased. Unfortunately, it has been difficult to estimate NO3 - concentration across China due to the lack of a PM2.5 speciation monitoring network. Here, we use a machine learning model incorporating ground measurements and satellite data to characterize the spatiotemporal patterns of NO3 -, thereby understanding the disease burden associated with long-term NO3 - exposure in China. Our results show that existing air pollution control policies are effective, but increased NO3 - of traffic emissions offset reduced NO3 - of industrial emissions. In 2018, the national mean mortality burden attributable to NO3 - was as high as 0.68 million, indicating that targeted regulations are needed to control NO3 - pollution in China.

High Resolution On-Road Air Pollution Using a Large Taxi-Based Mobile Sensor Network.

Traffic-related air pollution (TRAP) was monitored using a mobile sensor network on 125 urban taxis in Shanghai (November 2019/December 2020), which provide real-time patterns of air pollution at high spatial resolution. Each device determined concentrations of carbon monoxide (CO), nitrogen dioxide (NO2), and PM2.5, which characterised spatial and temporal patterns of on-road pollutants. A total of 80% road coverage (motorways, trunk, primary, and secondary roads) required 80-100 taxis, but only 25 on trunk roads. Higher CO concentrations were observed in the urban centre, NO2 higher in motorway concentrations, and PM2.5 lower in the west away from the city centre. During the COVID-19 lockdown, concentrations of CO, NO2, and PM2.5 in Shanghai decreased by 32, 31 and 41%, compared with the previous period. Local contribution related to traffic emissions changed slightly before and after COVID-19 restrictions, while changing background contributions relate to seasonal variation. Mobile networks are a real-time tool for air quality monitoring, with high spatial resolution (~200 m) and robust against the loss of individual devices.