[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.

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.

[Source Profiles and Impact of Volatile Organic Compounds in the Coating Manufacturing Industry].

SUMMA canisters were used to collect the exhaust gas from eight coating manufacturers in East China. A total of 106 VOCs was determined by gas chromatography-mass spectrometry (GC-MS) method to identify the emission characteristics of volatile organic compounds (VOCs) and the contribution of VOCs emitted by various companies to ozone generation, and the source profiles of solvent-based and water-based coatings were established. The results show that the characteristic components of VOCs in the coating manufacturing industry are mainly aromatic hydrocarbons and oxygenated hydrocarbons. The concentration ranges from 65.5% to 99.9%. The VOC emissions of solvent-based coatings were mainly aromatic hydrocarbons, accounting for 63.0%-94.0% of total VOCs; VOC emissions from waterborne coatings were mainly composed of oxygenated hydrocarbons, accounting for 54.5% to 99.9% of the total VOCs. m,p-xylene (32.4%), ethylbenzene (19.0%), and ethyl acetate (12.1%) were solvent-based coating sources, and ethyl acetate (83.7%) and 2-butyl ketone (8.0%) were the sources of waterborne coating emissions. Aromatic hydrocarbons and oxygenated hydrocarbons are the main active components in the coating manufacturing industry, with a total contribution to the ozone generation potential (OFP) ranging from 92.9% to 99.9%. Source reactivity (SR) analysis showed that the VOCs per unit mass of water-based coatings contributed much less to the formation of ozone than solvent-based coatings, so water-based coatings significantly reduced the potential for ozone generation. Studies have shown that for VOC pollution control in the coating manufacturing industry, attention should be paid to the VOCs that contribute more to the ozone-forming potential of aromatic hydrocarbons and oxygenated hydrocarbons, and VOC emissions should be controlled from the source.

[First Long-Term Study of Atmospheric New Particle Formation in the Suburb of Shanghai from 2015 to 2017].

In this study, long-term continuous monitoring of atmospheric new particle formation was conducted from 2015 to 2017 in the Shanghai suburbs using a scanning mobility particle sizer (SMPS). Combined with meteorological parameters, gaseous pollutants, and PM2.5 chemical composition data, the characterization of new particle formation was analyzed. The results of data analysis showed there were 172 new particle formation (NPF) days in the Shanghai suburbs, accounting for 18.3% of the total effective days (942 d). Typical new particle formation days (Event) and new particle growth-shrinkage (Shrinkage) days were 150 d and 32 d, respectively. The frequency of NPF occurrence was the highest in spring and summer, followed by autumn and winter. Compared with non-new particle formation (Non-NPF) days, Event and Shrinkage days had higher temperature and wind speed, lower humidity, less rainfall, and stronger solar radiation. The ratio of Event days was the highest when the prevailing wind was southerly, southwesterly, or westerly, and when the air masses were mainly from the vegetation cover and agricultural planting areas in the Taihu Lake Basin. The prevailing wind directions for Non-NPF and Shrinkage days were northeasterly and easterly to southeasterly. On the Event days, SO2 and O3 were higher than that on the Non-NPF days, indicating gaseous sulfuric acid and photochemical reactions were key contributors to new particle formation. Higher PM10 concentration was detected on the Event days than on the Non-NPF days, which may be attributed to the photocatalytic reaction. All the pollutant concentrations were the lowest on Shrinkage days, except that of O3. The average concentrations of inorganic components of PM2.5, such as NH4+, SO42-, and NO3- were higher on Event than on Non-NPF days in fall, whereas the opposite results were observed in other seasons. The average concentration of organic carbon on Event days was higher than that on Non-NPF days in each season. The concentrations of PM2.5 components on Shrinkage days were the lowest. However, the ratio of organic carbon on Shrinkage days was higher than that on Non-NPF days in spring, summer, and winter. The higher ratio of organic carbon on the NPF days than on the Non-NPF days suggested an important role of organic matter in the formation and growth of new particles in the suburbs of Shanghai.

[Pollution Characteristics and Health Risk Assessment of VOCs in Areas Surrounding a Petrochemical Park in Shanghai].

To investigate the pollution characteristics of volatile organic compounds (VOCs) in the vicinity of a petrochemical park, the composition and concentration of VOCs was successively monitored by application of a gas chromatography-flame ionization detector in the residential area surrounding a petrochemical park in Shanghai in October 2017. Moreover, the maximum incremental reactive method was employed to estimate the O3-formation potential contributed by VOCs, and health risks were assessed. Results showed that during the observation period, TVOCs concentrations ranged from 16.4 µg·m-3 to 1947.8 µg·m-3 with an average concentration of 40.7 µg·m-3, whereas the average proportions of alkanes, alkene/alkynes, and aromatic hydrocarbons were 66.2%, 25.9%, and 7.9%, respectively. The diurnal variation of total VOCs concentration showed a monomodal change, with a peak concentration of 127.9 µg·m-3 at 07:00, whereas the TVOCs had an average ozone formation potential (OFP) of 249.7 µg·m-3. Analysis of OFP indicated that trans-2-butene and ethylene were the most important species in ozone production with accountabilities for total OFP of 153.4 µg·m-3. Propylene, trans-2-butene, and ethylene were the key active species. Furthermore, health risk assessments revealed that no significant health risks had been caused by hexane, benzene, toluene, ethylbenzene, o-xylene, and m-xylene.

Relevant risk factors for positive lateral margin after en bloc endoscopic submucosal dissection for early gastric adenocarcinoma.

OBJECTIVE: This study aimed to systematically assess the relevant risk factors of positive lateral margin (LM) after en bloc resection of early gastric adenocarcinoma. METHODS: A total of 242 patients who had undergone endoscopic submucosal dissection (ESD) due to early gastric lesions from January 2009 to March 2015 were included in the study. Clinicopathological features of the lesions and the risk factors related to positive LM were analyzed. RESULTS: The curative rate was 82.2% and positive LM was found in 12.4% of the lesions. Univariate analysis showed that positive LM was significantly associated with the tumor location (at the upper third of the stomach), size (>3 cm), histological findings, the presence of lymphovascular invasion and deeper invasion depth. Moreover, positive LM had a higher incidence of recurrent or residual tumors. A multivariate analysis showed that the location, tumor size and histological classification of tumors were independent risk factors for positive LM. CONCLUSIONS: Positive LM is closely related to the upper third of stomach, a tumor larger than 3 cm and a mixed-type carcinoma. Additionally, positive LM has a predilection for recurrent or residual tumors.

[Characteristics and Source Apportionment of VOCs of High Pollution Process at Chemical Industrial Area in Winter of China].

Online GC was adopted to monitor VOCs of high pollution process near a chemical industrial area in winter. PMF model was used to identify the major sources of VOCs and evaluate their contributions. The result showed that the main components during the period of observation were toluene, xylene, C3-C4 hydrocarbon and chloroform, etc. Organic sulfur compounds were the major odor pollutants at the chemical industrial area. The compounds including isobutane, n-butane, propane and acrylonitrile were enriched during two pollution periods. VOCs and NOx had the diurnal features of high concentration in the evening versus lower concentration during daytime, indicating the main influence from chemical industrial sources. While O3 had the diurnal features reflecting the photochemical reaction at chemical industrial area in winter. The PMF result showed that 48.0% of the total VOCs concentrations were attributed to synthetic materials industry, 24.0% to industrial organic sulfur process and wastewater treatment (including three sources), 14.7% to industrial organic solvent usage, and 13.3% to petrochemical process. So the wastewater treatment unit was a major source of odor pollution at chemical industrial area.

Positive relationship between p42.3 gene and inflammation in chronic non-atrophic gastritis.

OBJECTIVE: Gastric cancer (GC) is a typical type of inflammation-related tumor. The p42.3 gene is shown to be highly expressed in GC, but its association with gastritis remains unknown. We aimed to explore the relationship between gastric inflammation and p42.3 gene in vitro and in vivo. METHODS: Normal gastric epithelial cells (GES-1) were treated with Helicobacter pylori (H. pylori) and tumor necrosis factor (TNF)-α. Total cell mRNA and protein were extracted and collected, and polymerase chain reaction and Western blot were performed to determine the relative expression of p42.3 gene. In total, 291 biopsy samples from patients with chronic non-atrophic gastritis were collected and immunohistochemistry was used to measure the p42.3 protein expression. The association between p42.3 protein expression and the clinicopathological characteristics of these patients were analyzed. RESULTS: Both H. pylori and TNF-α significantly enhanced the p42.3 protein expression in GES-1 cells in a time and dose-dependent manner. In addition, p42.3 gene expression was positively associated with the severity of gastric mucosal inflammation and H. pylori infection (P = 0.000). Its expression was significantly more common in severe gastric inflammation and in H. pylori-infected cases. CONCLUSION: p42.3 gene expression is associated with gastric mucosal inflammation that can be upregulated by TNF-α and H. pylori infection.

[Characteristics and sources of organic carbon and elemental carbon in PM2.5 in Shanghai urban area].

Organic carbon (OC) and elemental carbon (EC) in PM2.5 samples collected in Shanghai urban area during June 2010 to May 2011 were analyzed with IMPROVE-TOR protocol. The results showed that the annual average concentrations of OC and EC in PM2.5 were 8.6 µg.m-3 ± 6.2 µg.m-3 and 2.4 µg.m-3 ± 1.3 µg.m-3 respectively, accounting for 20% of PM2.5 mass concentration. The seasonal average concentrations of OC and EC were highest in winter and lowest in summer. And the percentages of OC and EC in PM2.5 were highest in autumn. The annual average OC/EC ratio was 3. 54 ± 1. 14. The concentrations of secondary organic carbon (SOC) were evaluated by the minimum OC/EC ratio method and the annual average concentration of SOC was 3.9 µg.m(-3) ±4.2 µg.m(-3), accounting for 38.9% of OC. In summer, the concentrations of SOC were relatively low and were correlated well with the maximum hourly concentrations of ozone, which indicated that the photochemical reaction was an important way of SOC formation. In autumn and winter when the west wind direction was predominant, the concentrations of SOC were higher than that in windless condition, which meant the transportation of SOC. The carbonaceous components were associated with source contributions using the principal component analysis (PCA) with eight thermally-derived carbon fractions, OC1, OC2, OC3, OC4, EC1, EC2, EC3 and OPC. Motor vehicle, coal-fired units, biomass burning and road dust were four main sources of OC and EC in PM2.5 in Shanghai urban area, which contributing 69. 8% - 81. 4% of carbonaceous aerosols. The contribution of motor vehicle was high throughout the year. Biomass burning contributed about 15% -20% of OC and EC. The influence of road dust was relatively obvious in spring and autumn. And the contribution of coal-fired units was higher in winter than those in other seasons.

[Secondary aerosol formation through photochemical reactions estimated by using air quality monitoring data in the downtown of Pudong, Shanghai].

Analyses of diurnal patterns of PM10 in the downtown of Pudong, Shanghai have been performed in this study at different daily ozone maximum concentrations (O(3,max)) from May to October, 2010. In order to evaluate secondary aerosol formation at different ozone levels, CO was used as a tracer for primary aerosol, and 0(3, max) was used as an index for photochemical activity. Results show that along with increasing of O3 concentration, the concentration of primary and secondary aerosol was increased respectively from 0. 036 to 0.044 mg x m(-3) and from 0.018 to 0.055 mg x m(-3). The ratio of secondary to primary aerosol was increased from 49.8% to 124.5%. Furthermore, along with the increase of O(3, max) the forming time of O(3,max) and secondary aerosol was changed respectively from 13:00 to 14:00 and from 11:00-20:00 to 09:00-20:00. At the same time, the chemical composition of PM2.5 was different at different photochemical levels. PM(2.5) was composed of 12.0% organic carbon (OC), 18.7% sulfate (SO4(2-1)), 13.1% nitrate (NO3-) and 4.5% element carbon (EC) when O(3, max) was < 0.10 mg x m(-3) and PM2.5 was composed of 20.0% organic carbon (OC), 22.9% sulfate, 23.1% nitrate and 4.7% element carbon (EC) with O(3, max) > 0. 20 mg x m(-3). These results approved that the photochemical reactivity promoted the production of SO4(2-), NO3- and OC.

[Characteristics of ambient VOCs and their role in O3 formation: a typical air pollution episode in Shanghai urban area].

The concentration, speciation and chemical reactivity of ambient volatile organic compounds (VOCs) in shanghai city were analyzed and measured by using online gas chromatography with flame ionization detection systems (GC-FID) during a typical air pollution episode (from Oct. 30th to Nov. 2nd, 2010) and 55 kinds of VOCs were detected. The results show that averaged concentrations of VOCs was 27 x 10(-9) before the episode, and then dramatically increased by 3 times (87 x 10(-9)) in the episode than the former, the main components were alkanes (35.2 x 10(-9)), aromatics (30.0 x 10(-9)), alkenes (21.6 x 10(-9)). Furthermore, the maximum ozone formation potential (PhiOFP) is analyzed and showed that PhiOFP (in the episode) > PhiOFP (after the episode) PhiOFP (before the episode). Before the episode, the percent of PhiOFP for aromatics 53.0% , alkenes 36. 1% and alkanes 11.7%; in the episode, the percent of PhiOFP for aromatics 54.7%, alkenes 36.7% and alkanes 9.8%; after the episode, the percent of PhiOFP for alkenes 52.7%, aromatics 36.0% and alkanes 13.2%. Alkenes (C2-C4) and aromatics (C6-C8) are the main components for the ozone formation, namely toluene, m,p-xylene, 1,3-butadiene, propene, ethene et al. In addition, the relationship is negative and nonlinear between the O3 and PhiOFP. And efficiencies of PhiOFP formed into O3 are below 20. 0% in different stage of episode. This is very important and meaningful for the quantitative evaluate the influence of VOCs towards O3.

An emission inventory of marine vessels in Shanghai in 2003.

We developed an air pollutant emission inventory for marine vessels in the Shanghai Port in 2003. We estimated emissions under cruising and maneuvering conditions based on two categories of vessels: (1) vessels in the Outer Port, which enter the area following notification of the Shanghai Maritime Safety Administration, a division of the Ministry of Communications of P.R. China; and (2) vessels in internal waterways, which enter those waters following notification of the local Port Administration Centers. Vessels in the Outer Port consist of three subcategories: (1) international vessels that are engaged in foreign commerce; (2) domestic vessels traveling along the downstream portion of the Huangpu River; and (3) domestic vessels traveling along the coast. We also estimate emissions from vessels over 1000 DWT operating under hotelling conditions in the Outer Port. In 2003, the total number of calls was approximately 1.3 million, of which 57% is attributed to vessels in internal waterways and 43% to vessels in the Outer Port. Total marine emissions for NOx, SO2, PM, HC, and CO2 in 2003 are estimated to be 58,160, 51,180, 6960, 4560, and 3,012,800 tons, respectively. Emissions are allocated to 1 km x 1 km grid cells for the 129 km x 102 km Shanghai Port study domain.

Application of DALYs in measuring health effect of ambient air pollution: a case study in Shanghai, China.

OBJECTIVE: To investigate the effect of ambient air pollution on human health and the subsequent disability-adjusted life years (DALYs) lost in Shanghai. METHODS: We used epidemiology-based exposure-response functions to calculate the attributable number of cases due to air pollution in Shanghai in 2000, and then we estimated the corresponding DALYs lost in Shanghai based on unit DALYs values of the health consequences. RESULTS: Ambient air pollution caused 103,064 DALYs lost in Shanghai in 2000. Among all the health endpoints, premature deaths and chronic bronchitis predominated in the value of total DALYs lost. CONCLUSION: The air pollution levels have an adverse effect on the general population health and strengthen the rationale for limiting the levels of air pollution in outdoor air in Shanghai.

Establishment of exposure-response functions of air particulate matter and adverse health outcomes in China and worldwide.

OBJECTIVE: To obtain the exposure-response functions that could be used in health-based risk assessment of particulate air pollution in China. METHODS: Meta analysis was conducted on the literatures on air particulate matter and its adverse health outcomes in China and worldwide. RESULTS: For each health outcome from morbidity to mortality changes, the relative risks were estimated when the concentration of air particulate matter increased to some certain units. CONCLUSION: The exposure-response functions recommended here can be further applied to health risk assessment of air particulate matter in China.