Temporal evolution of speciated volatile organic compound (VOC) emissions from solvent use sources in the Pearl River Delta Region, China (2006-2019).

Volatile organic compounds (VOCs) emitted from solvent use sources constitute an important part of ozone (O3) and secondary organic aerosols (SOA) in the Pearl River Delta (PRD) region, China. While stringent control measures targeting VOCs have been implemented in recent years, an assessment of historical trends is imperative to evaluate their effectiveness. In this study, trends of VOC emissions, compositions, and reactivity from solvent use sources in the PRD region from 2006 to 2019 were estimated using a developed methodology, which considered the improvement of manufacturing equipment and removal efficiency. Results showed that total VOC emissions from solvent use sources displayed an overall increase from 277 kt in 2006 to 400 kt in 2019 despites some fluctuations, with metal products contributing more than 20 % each year. Aromatics and oxygenated VOCs (OVOCs) accounted for over 70 % of total VOC emissions, increasing by 21 kt and 52 kt respectively. OFP and SOAFP increased by 40 % and 23 % respectively from 2006 to 2019. Specific aromatic species, including m/p-xylene, toluene, 1,2,3,5-tetramethylbenzene, o-xylene and ethylbenzene were identified as key species in both VOC emission amount and reactivity. This study aims to facilitate the understanding of VOC emission evolution from solvent use sources in the region and provide insights into the impact of enacted measures, aiding in the future development of more targeted and efficient strategies in the PRD region.

Quantifying the contributions of meteorology, emissions, and transport to ground-level ozone in the Pearl River Delta, China.

Ozone pollution presents a growing air quality threat in urban agglomerations in China. It remains challenge to distinguish the roles of emissions of precursors, chemical production and transportations in shaping the ground-level ozone trends, largely due to complicated interactions among these 3 major processes. This study elucidates the formation factors of ozone pollution and categorizes them into local emissions (anthropogenic and biogenic emissions), transport (precursor transport and direct transport from various regions), and meteorology. Particularly, we attribute meteorology, which affects biogenic emissions and chemical formation as well as transportation, to a perturbation term with fluctuating ranges. The Community Multiscale Air Quality (CMAQ) model was utilized to implement this framework, using the Pearl River Delta region as a case study, to simulate a severe ozone pollution episode in autumn 2019 that affected the entire country. Our findings demonstrate that the average impact of meteorological conditions changed consistently with the variation of ozone pollution levels, indicating that meteorological conditions can exert significant control over the degree of ozone pollution. As the maximum daily 8-hour average (MDA8) ozone concentrations increased from 20 % below to 30 % above the National Ambient Air Quality Standard II, contributions from emissions and precursor transport were enhanced. Concurrently, direct transport within Guangdong province rose from 13.8 % to 22.7 %, underscoring the importance of regional joint prevention and control measures under adverse weather conditions. Regarding biogenic emissions and precursor transport that cannot be directly controlled, we found that their contributions were generally greater in urban areas with high nitrogen oxides (NOx) levels, primarily due to the stronger atmospheric oxidation capacity facilitating ozone formation. Our results indicate that not only local anthropogenic emissions can be controlled in urban areas, but also the impacts of local biogenic emissions and precursor transport can be potentially regulated through reducing atmospheric oxidation capacity.

piR-1919609 Is an Ideal Potential Target for Reversing Platinum Resistance in Ovarian Cancer.

PURPOSE: PIWI-interacting RNAs (piRNAs) are a type of noncoding small RNA that can interact with PIWI-like RNA-mediated gene silencing (PIWIL) proteins to affect biological processes such as transposon silencing through epigenetic effects. Recent studies have found that piRNAs are widely dysregulated in tumors and associated with tumor progression and a poor prognosis. Therefore, this study aimed to investigate the effect of piR-1919609 on the proliferation, apoptosis, and drug resistance of ovarian cancer cells. METHODS: In this study, we used small RNA sequencing to screen and identify differentially expressed piRNAs in primary ovarian cancer, recurrent ovarian cancer, and normal ovaries. A large-scale verification study was performed to verify the expression of piR-1919609 in different types of ovarian tissue, including ovarian cancer tissue and normal ovaries, by RT-PCR and to analyze its association with the clinical prognosis of ovarian cancer. The expression of PIWILs in ovarian cancer was verified by RT-PCR, Western blotting and immunofluorescence. The effects of piR-1919609 on ovarian cancer cell proliferation, apoptosis and drug resistance were studied through in vitro and in vivo models. RESULTS: (1) piR-1919609 was highly expressed in platinum-resistant ovarian cancer tissues (p < 0.05), and this upregulation was significantly associated with a poor prognosis and a shorter recurrence time in ovarian cancer patients (p < 0.05). (2) PIWIL2 was strongly expressed in ovarian cancer tissues (p < 0.05). It was expressed both in the cytoplasm and nucleus of ovarian cancer cells. (3) Overexpression of piR-1919609 promoted ovarian cancer cell proliferation, inhibited apoptosis, and promoted tumor growth in nude mice. (4) Inhibition of piR-1919609 effectively reversed ovarian cancer drug resistance. CONCLUSION: In summary, we showed that piR-1919609 is involved in the regulation of drug resistance in ovarian cancer cells and might be an ideal potential target for reversing platinum resistance in ovarian cancer.

Temperature-Dependent Evaporative Anthropogenic VOC Emissions Significantly Exacerbate Regional Ozone Pollution.

The evaporative emissions of anthropogenic volatile organic compounds (AVOCs) are sensitive to ambient temperature. This sensitivity forms an air pollution-meteorology connection that has not been assessed on a regional scale. We parametrized the temperature dependence of evaporative AVOC fluxes in a regional air quality model and evaluated the impacts on surface ozone in the Beijing-Tianjin-Hebei (BTH) area of China during the summer of 2017. The temperature dependency of AVOC emissions drove an enhanced simulated ozone-temperature sensitivity of 1.0 to 1.8 µg m-3 K-1, comparable to the simulated ozone-temperature sensitivity driven by the temperature dependency of biogenic VOC emissions (1.7 to 2.4 µg m-3 K-1). Ozone enhancements driven by temperature-induced AVOC increases were localized to their point of emission and were relatively more important in urban areas than in rural regions. The inclusion of the temperature-dependent AVOC emissions in our model improved the simulated ozone-temperature sensitivities on days of ozone exceedance. Our results demonstrated the importance of temperature-dependent AVOC emissions on surface ozone pollution and its heretofore unrepresented role in air pollution-meteorology interactions.

[High Resolution Emission Inventory of Greenhouse Gas and Its Characteristics in Guangdong，China].

Based on the typical city survey data and statistics of Guangdong Province， a 2018-based 3 km×3 km gridded greenhouse gas emissions inventory was developed for Guangdong Province using the combination of top-down and bottom-up emission factor methods. The inventory covered the CO2， CH4， and N2O emissions from energy， industrial processes， agriculture， land use change and forest， waste management， and indirect sources. The results showed that estimates for CO2， CH4， and N2O in Guangdong Province for the year 2018 were 8.5×108， 1.9×106， and 1.1×105 t， respectively， and 8.5×108， 4.0×107， and 3.4×107 t by equivalent carbon dioxide， totaling 9.2×108 t. CO2 was the main greenhouse gas in Guangdong Province， accounting for 92.0% of the total emissions. Energy and indirect sources were the main emission sources， accounting for 77.9% and 7.6%， respectively， totaling 85.5%. Spatial distributions illustrated that most grids were greenhouse gas emissions， whereas some others were greenhouse gas sinks； the greenhouse gas emissions were distributed mainly in the Pearl River Delta region and had certain characteristics of distribution along the road network and channels. The greenhouse gas grids of high emission were mainly the locations of high energy-consuming enterprises such as large power plants， steel mills， and cement plants.

Prognostic significance of TM4SF1 and DDR1 expression in epithelial ovarian cancer.

Transmembrane 4 L6 family member 1 (TM4SF1) and discoidin domain receptor 1 (DDR1) are expressed in numerous types of cancer, but their expression in epithelial ovarian cancer and the association between their expression and patient prognosis are unclear. The present study aimed to explore the expression of TM4SF1 and DDR1 and their relationship with prognosis in epithelial ovarian cancer. Firstly, the Oncomine and Gene Expression Profiling Interactive Analysis (GEPIA) platforms were used to compare the expression levels of TM4SF1 and DDR1 in ovarian cancer and normal ovarian tissue, and Kaplan-Meier plotter was used to analyze the association between gene expression and patient prognosis. The proteins interacting with TM4SF1 and DDR1 were analyzed using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and enrichment analysis of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways was conducted for the interacting proteins. Furthermore, immunohistochemical staining was performed to detect the expression of TM4SF1 and DDR1 protein in epithelial ovarian cancer tissue and to analyze the association between expression and prognosis. The Oncomine and GEPIA analyses showed that the expression levels of TM4SF1 and DDR1 were significantly higher in epithelial ovarian cancer than in normal ovarian tissue, and the analysis of clinical samples revealed that TM4SF1 and DDR1 were coexpressed in some cases. STRING analysis indicated that the TM4SF1 and DDR1 proteins interact with each other. The overall survival and progression-free survival of patients whose epithelial ovarian cancer coexpressed TM4SF1 and DDR1 were significantly shorter than those of patients lacking TM4SF1 and DDR1 coexpression. Multivariate analysis indicated that TM4SF1 and DDR1 protein coexpression was an independent prognostic factor. In summary, TM4SF1 and DDR1 proteins were coexpressed in some epithelial ovarian cancer tissues and appear to be adverse prognostic factors for epithelial ovarian cancer. In addition, TM4SF1 and DDR1 may have an interactive or mutual regulatory mechanism.

Hourly emissions of air pollutants and greenhouse gases from open biomass burning in China during 2016-2020.

Open biomass burning (OBB) is a significant source of air pollutants and greenhouse gases that have contributed to air pollution episodes in China in recent years. An accurate emission inventory is critical for the precise control of OBB. Existing OBB emission datasets are commonly based on MODIS observations, and most only have a daily-scale temporal resolution. Daily OBB emissions, however, might not accurately represent diurnal variations, peak hours, or any open burning processes. The China Hourly Open Biomass Burning Emissions (CHOBE) dataset for mainland China from 2016 to 2020 was developed in this study using the spatiotemporal fusion of multiple active fires from MODIS, VIIRS S-NPP and Himawari-8 AHI detections. At a spatial resolution of 2 km, CHOBE provided gridded CO, NOx, SO2, NH3, VOCs, PM2.5, CO2, CH4 and N2O emissions from OBB. CHOBE will enhance insight into OBB spatiotemporal variability, improves air quality and climate modelling and forecasting, and aids in the formulation of precise OBB preventive and control measures.

Developing a model-ready highly resolved HONO emission inventory in Guangdong using domestic measured emission factors.

Nitrous acid (HONO) plays an important role in the budget of hydroxyl radical (OH) in the atmosphere. However, current chemical transport models (CTMs) typically underestimate ambient concentrations of HONO due to a dearth of high resolution primary HONO emission inventories. To address this issue, we have established a highly resolved bottom-up HONO emission inventory for CTMs in Guangdong province, utilizing the best available domestic measured emission factors and newly obtained activity data. Our results indicate that emissions from various sources in 2020, including soil, on-road traffic, non-road traffic, biomass burning, and stationary combustion, were estimated at 21.5, 10.0, 8.2, 2.5, and 0.7 kt, respectively. Notably, the HONO emissions structure differed between the Pearl River Delta (PRD) and the non-PRD regions. Specifically, traffic sources were the dominant contributors (62 %) to HONO emissions in the PRD, whereas soil sources accounted for the majority (65 %) of those in the non-PRD. Among on-road traffic sources, diesel vehicles played a significant role, contributing 99.7 %. Comparisons with previous methods suggest that HONO emissions from diesel vehicles are underestimated by approximately 2.5 times. Higher HONO emissions, dominated by soil emissions, were observed in summer months, particularly in August. Furthermore, diesel vehicle emissions were pronounced at night, likely contributing to the nighttime accumulation of HONO and the morning peak of OH. The emission inventories developed in this study can be directly applied to widely used CTMs, such as CMAQ, CAMx, WRF-Chem, and NAQPMS, to support the simulation of OH formation and secondary air pollution.

VOC emission caps constrained by air quality targets based on response surface model: A case study in the Pearl River Delta Region, China.

Because of the recent growth in ground-level ozone and increased emission of volatile organic compounds (VOCs), VOC emission control has become a major concern in China. In response, emission caps to control VOC have been stipulated in recent policies, but few of them were constrained by the co-control target of PM2.5 and ozone, and discussed the factor that influence the emission cap formulation. Herein, we proposed a framework for quantification of VOC emission caps constrained by targets for PM2.5 and ozone via a new response surface modeling (RSM) technique, achieving 50% computational cost savings of the quantification. In the Pearl River Delta (PRD) region, the VOC emission caps constrained by air quality targets varied greatly with the NOx emission reduction level. If control measures in the surrounding areas of the PRD region were not considered, there could be two feasible strategies for VOC emission caps to meet air quality targets (160 µg/m3 for the maximum 8-hr-average 90th-percentile (MDA8-90%) ozone and 25 µg/m3 for the annual average of PM2.5): a moderate VOC emission cap with <20% NOx emission reductions or a notable VOC emission cap with >60% NOx emission reductions. If the ozone concentration target were reduced to 155 µg/m3, deep NOx emission reductions is the only feasible ozone control measure in PRD. Optimization of seasonal VOC emission caps based on the Monte Carlo simulation could allow us to gain higher ozone benefits or greater VOC emission reductions. If VOC emissions were further reduced in autumn, MDA8-90% ozone could be lowered by 0.3-1.5 µg/m3, equaling the ozone benefits of 10% VOC emission reduction measures. The method for VOC emission cap quantification and optimization proposed in this study could provide scientific guidance for coordinated control of regional PM2.5 and O3 pollution in China.

A meteorologically adjusted ensemble Kalman filter approach for inversing daily emissions: A case study in the Pearl River Delta, China.

The conventional Ensemble Kalman filter (EnKF), which is now widely used to calibrate emission inventories and to improve air quality simulations, is susceptible to simulation errors of meteorological inputs, making accurate updates of high temporal-resolution emission inventories challenging. In this study, we developed a novel meteorologically adjusted inversion method (MAEInv) based on the EnKF to improve daily emission estimations. The new method combines sensitivity analysis and bias correction to alleviate the inversion biases caused by errors of meteorological inputs. For demonstration, we used the MAEInv to inverse daily carbon monoxide (CO) emissions in the Pearl River Delta (PRD) region, China. In the case study, 60% of the total CO simulation biases were associated with sensitive meteorological inputs, which would lead to the overestimation of daily variations of posterior emissions. Using the new inversion method, daily variations of emissions shrank dramatically, with the percentage change decreased by 30%. Also, the total amount of posterior CO emissions estimated by the MAEInv decreased by 14%, indicating that posterior CO emissions might be overestimated using the conventional EnKF. Model evaluations using independent observations revealed that daily CO emissions estimated by MAEInv better reproduce the magnitude and temporal patterns of ambient CO concentration, with a higher correlation coefficient (R, +37.0%) and lower normalized mean bias (NMB, -17.9%). Since errors of meteorological inputs are major sources of simulation biases for both low-reactive and reactive pollutants, the MAEInv is also applicable to improve the daily emission inversions of reactive pollutants.

[Analysis of Ozone Pollution Spatio-temporal Evolution Characteristics and Identification of Its Long-term Variation Driving Factor over Hunan Province].

Despite the alleviation of particulate matter (PM), the ambient ozone (O3) concentration is continuously increasing in Hunan province where the investigation of O3 pollution has been rarely reported. Accordingly, the spatio-temporal evolution of O3 pollution was first analyzed based on hourly air quality data observed by national monitoring stations from 2015 to 2020 over 14 cities in Hunan province. Afterwards, the combination of meteorological data from the European Center for Medium-range Weather Forecast (ECMWF) and the generalized additive model (GAM) was applied to investigate the driving factors of the O3 long-term trend during this period. The results presented obvious diurnal, monthly, and seasonal characteristics of O3 variations. High O3 concentrations occurred in May and September monthly, and the peak O3 season was autumn. Furthermore, the 90th percentile O3 increased at a rate of 4.7 µg·(m3·a)-1 temporally, and high O3 values mainly occurred in the north-eastern region spatially, in contrast to the low O3 values in the western region. The modeling results indicated that the increase in O3 was mainly ascribed to precursor emissions. Furthermore, meteorology promoted a rise in O3 with the impact magnitude of 1 µg·(m3·a)-1. Remarkably, meteorology accelerated the O3 increases in spring, summer, and the eastern region, whereas it restrained increases in autumn, winter, and the northwest. The effect of meteorology on PM10 was different from O3 during this period. Overall, this study highlighted the importance of meteorological impacts when regulating emission reduction measures for O3 abatement. It required greater effort regarding O3 mitigation to offset the side-effect from meteorology in meteorology-sensitive seasons and regions. Additionally, the regional corporation is indispensable to reduce O3 transportation from upwind.

Near-real-time estimation of hourly open biomass burning emissions in China using multiple satellite retrievals.

Open biomass burning (OBB) is an important source of air pollutants and greenhouse gases, but its dynamic emission estimation remains challenging. Existing OBB emission datasets normally provide daily estimates based upon Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals but tend to underestimate the emissions due to the coarse spatial resolution and sparse observation frequency. In this study, we proposed a novel approach to improve OBB emission estimations by fusing multiple active fires detected by MODIS, Visible Infrared Imaging Radiometer onboard the Suomi National Polar-orbiting Partnership (VIIRS S-NPP) and Himawari-8. The fusion of multiple active fires can capture the missing small fires and the large fires take place during the non-overpass time of MODIS observations. Also, regional-based fire radiative power (FRP) cycle reconstruction models and OBB emission coefficients were developed to address the large spatial discrepancies of OBB emission estimations across China and to promote the estimate to an hourly resolution. Using the new approach, hourly gridded OBB emissions in China were developed and can be updated with a lag of 1-day, or even near-real-time when real-time multiple active fires are available. OBB emissions in China based on this approach were more than 3 times of those in previous datasets. Evaluations revealed that the spatial distribution of the estimated PM2.5 emissions from this study was more consistent with the ambient PM2.5 concentrations during several episodes than existing datasets. The hourly OBB emissions provide new insight into its spatiotemporal variations, enhance timely and reliable air quality modeling and forecast, and support the formulation of accurate prevention and control policies of OBB.

Emission source-based ozone isopleth and isosurface diagrams and their significance in ozone pollution control strategies.

In the past decade, ozone (O3) pollution has been continuously worsening in most developing countries. The accurate identification of the nonlinear relationship between O3 and its precursors is a prerequisite for formulating effective O3 control measures. At present, precursor-based O3 isopleth diagrams are widely used to infer O3 control strategy at a particular location. However, there is frequently a large gap between the O3-precursor nonlinearity delineated by the O3 isopleths and the emission source control measures to reduce O3 levels. Consequently, we developed an emission source-based O3 isopleth diagram that directly illustrates the O3 level changes in response to synergistic control on two types of emission sources using a validated numerical modeling system and the latest regional emission inventory. Isopleths can be further upgraded to isosurfaces when co-control on three types of emission sources is investigated. Using Guangzhou and Foshan as examples, we demonstrate that similar precursor-based O3 isopleths can be associated with significantly different emission source co-control strategies. In Guangzhou, controlling solvent use emissions was the most effective approach to reduce peak O3 levels. In Foshan, co-control of on-road mobile, solvent use, and fixed combustion sources with a ratio of 3:1:2 or 3:1:3 was best to effectively reduce the peak O3 levels below 145 ppbv. This study underscores the importance of using emission source-based O3 isopleths and isosurface diagrams to guide a precursor emission control strategy that can effectively reduce the peak O3 levels in a particular area.

A newly integrated dataset of volatile organic compounds (VOCs) source profiles and implications for the future development of VOCs profiles in China.

Volatile organic compounds (VOCs) source profiles can be used for a number of purposes, such as creating speciated air pollutant emission inventories and providing inputs to receptor and air quality models. In this study, we first collected and schematically evaluated more than 500 Chinese domestic source profiles from literature and field measurements, and then established a most up-to-date dataset of VOCs source profiles in China by integrating 363 selective VOCs profiles into 101 sector-based source profiles. The profile dataset covers eight major source categories and contains 447 VOCs species including non-methane hydrocarbons (NMHCs) species and oxygenated VOCs (OVOCs) species. The results shown that (1) VOCs composition characteristics exhibit variations for most Level-II source sectors and Level-III sub-sectors even under the same Level-I source category; (2) OVOCs, which were significantly missing in previous profiles, account for more than 95% in cooking and 20- 40% in non-road mobile, biomass burning and solvent use sources; (3) aromatics account for 20%-40% in most emission sources except cooking source, alkenes and alkynes account for ~20% in combustion sources (stationary combustion, mobile source and biomass burning), alkanes are abundant in gasoline-related emission sources(on-road mobile source and fuel oil storage and transportation); (4) missing OVOCs species could bring 30%-50% to ozone formation potentials in most emission sources; and (5) there are considerable differences in VOCs chemical groups and individual species for most emission sources between this dataset and the widely used U.S. SPECIATE database, indicating the importance of developing domestic VOCs source profiles. The dataset developed in this study can help support reactive VOCs species-based ozone control strategy and provide domestic profile data for source apportionment and air quality modeling in China and other countries or regions with similar emission source characteristics.

Insight into the characteristics of carbonaceous aerosols at urban and regional sites in the downwind area of Pearl River Delta region, China.

Carbonaceous aerosols (CAs) take up a substantial fraction of fine particle (PM2.5) in the atmosphere, yet high temporal resolution and seasonal variations of their emission sources and formation mechanisms are still poorly characterized in the regions with strong anthropogenic activities. In this study, the spatiotemporal characteristics of CAs and their subfractions, i.e., organic carbon (OC) and elemental carbon (EC), were studied in one of China's key city clusters, the Pearl River Delta (PRD) region. Results show that the annual mean OC and EC concentrations are 5.89 ± 3.32 µg/m3 and 1.60 ± 1.00 µg/m3 at the urban site, respectively. Such levels are consistently higher than those at the regional site (4.94 ± 3.34 µg/m3 of OC and 1.45 ± 0.82 µg/m3 of EC), suggesting the strong impact of human activities on OC and EC concentration. Moreover, the OC concentration peak sharply appears at 19:00 across all seasons at the urban site due to the direct influence of traffic exhaust and cooking activities. At regional site, OC peaks in fall afternoon due to intensive photochemical reactions derived combustion-related secondary organic carbon (SOCcom) contributions to the downwind PRD region. Correlations between SOCcom and influence factors were found at both regional and urban sites, suggesting that SOCcom formation is more regionally homogenous and mainly originates from the Zhaoqing-Foshan-Jiangmen belt. In addition, there are significantly different formation mechanisms of non-combustion-related secondary organic carbon (SOCnon-com) in the downwind PRD region. This study provides a solid evidence for collaborative efforts in the mitigation of secondary aerosols in the PRD region.

ARRDC3 as a Diagnostic and Prognostic Biomarker for Epithelial Ovarian Cancer Based on Data Mining.

PURPOSE: The dysregulation of arrestin domain containing 3 (ARRDC3) has an important effect on oncogenesis and tumor progression in many cancers, including renal cell carcinoma and breast cancer. However, the role of ARRDC3 in ovarian cancer (OC) has not been reported. METHODS: The present study explored the diagnostic and prognostic roles of ARRDC3 in ovarian cancer using GEPIA, ONCOMINE, GEO, and Kaplan-Meier Plotter databases for training and validation. Then, we conducted a stratified analysis for clinicopathological factors using Kaplan-Meier Plotter and GEPIA databases. To further explore the mechanisms, we also used the MIST database to visualize the protein-protein interaction network of ARRDC3 associated with OC. The gene-gene interaction network was visualized by GeneMANIA plugin in Cytoscape 3.8.0 software, and the associated co-expression genes of ARRDC3 were analyzed by the cBioPortal database. The 100 top co-expression genes chosen for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used by the DAVID website. RESULTS: A significant difference in ARRDC3 mRNA expression was found between OC and normal ovary tissues. ARRDC3 could potentially be implicated in the diagnosis of OC. A high ARRDC3 mRNA expression level was associated with poor overall survival and progression-free survival. However, no significance was reported in respect to post progression survival. Except for histology, which had no prognostic value for PPS in stratified analysis, stratified analysis of other factors had prognostic value for OS, PFS, and PPS. Interestingly, we found a positive correlation between ARRDC3 expression and CD8+ T cells, macrophages, neutrophils, and dendritic cells, indicating that ARRDC3 might be associated with immune infiltration of these immune cells. Co-expression genes enrichment analysis found that they were involved in the Renin-angiotensin system pathway. CONCLUSION: Differentially expressed ARRDC3 might be a potential prognostic and diagnostic marker in Ovarian Cancer.

An updated model-ready emission inventory for Guangdong Province by incorporating big data and mapping onto multiple chemical mechanisms.

An accurate characterization of spatial-temporal emission patterns and speciation of volatile organic compounds (VOCs) for multiple chemical mechanisms is important to improving the air quality ensemble modeling. In this study, we developed a 2017-based high-resolution (3 km × 3 km) model-ready emission inventory for Guangdong Province (GD) by updating estimation methods, emission factors, activity data, and allocation profiles. In particular, a full-localized speciation profile dataset mapped to five chemical mechanisms was developed to promote the determination of VOC speciation, and two dynamic approaches based on big data were used to improve the estimation of ship emissions and open fire biomass burning (OFBB). Compared with previous emissions, more VOC emissions were classified as oxygenated volatile organic compound (OVOC) species, and their contributions to the total ozone formation potential (OFP) in the Pearl River Delta (PRD) region increased by 17%. Formaldehyde became the largest OFP species in GD, accounting for 11.6% of the total OFP, indicating that the model-ready emission inventory developed in this study is more reactive. The high spatial-temporal variability of ship sources and OFBB, which were previously underestimated, was also captured by using big data. Ship emissions during typhoon days and holidays decreased by 23-55%. 95% of OFBB emissions were concentrated in 9% of the GD area and 31% of the days in 2017, demonstrating their strong spatial-temporal variability. In addition, this study revealed that GD emissions have changed rapidly in recent years due to the leap-forward control measures implemented, and thus, they needed to be updated regularly. All of these updates led to a 5-17% decrease in the emission uncertainty for most pollutants. The results of this study provide a reference for how to reduce uncertainties in developing model-ready emission inventories.

Role of export industries on ozone pollution and its precursors in China.

This study seeks to estimate how global supply chain relocates emissions of tropospheric ozone precursors and its impacts in shaping ozone formation. Here we show that goods produced in China for foreign markets lead to an increase of domestic non-methane volatile organic compounds (NMVOCs) emissions by 3.5 million tons in 2013; about 13% of the national total or, equivalent to half of emissions from European Union. Production for export increases concentration of NMVOCs (including some carcinogenic species) and peak ozone levels by 20-30% and 6-15% respectively, in the coastal areas. It contributes to an estimated 16,889 (3,839-30,663, 95% CI) premature deaths annually combining the effects of NMVOCs and ozone, but could be reduced by nearly 40% by closing the technology gap between China and EU. Export demand also alters the emission ratios between NMVOCs and nitrogen oxides and hence the ozone chemistry in the east and south coast.

Characterization of VOC emissions from construction machinery and river ships in the Pearl River Delta of China.

Speciated characterization of Volatile Organic Compounds (VOCs), including oxygenated VOCs (OVOCs), from construction machinery and river ships in China is currently lacking. In this regard, we conducted field measurement on speciated VOC (including OVOC) emissions from six construction machinery and five river ships in the Pearl River Delta (PRD) region to identify VOC emission characteristics. We noticed that OVOC emissions from construction machinery and ships accounted for more than 50% of the total VOC emissions, followed by alkenes, aromatics and alkanes. Formaldehyde and acetaldehyde were the most emission species, accounting for 61.8%-83.2% of OVOCs. For construction machinery, the fuel-based emission factors of roller, grader and pile driver were 3.12, 3.12 and 7.36 g/kg, respectively. With the rigorous restraint by the national emission standards, VOC emissions of construction machinery had decreased considerably, especially during stage Ⅲ. Ozone formation potential was also significantly reduced due to the significant decrease in emissions of OVOCs and alkenes with higher reactivity. For river ships, the fuel-based emission factors of cargo ships and speedboat were 1.46 and 0.44 g/kg, respectively. VOC emissions from construction machinery and river ships in Guangdong Province in 2017 were 8851.0 and 4361.0 ton, respectively. This study filled the knowledge gaps of reactive gas emissions from different kinds of non-road mobile sources over the PRD, and more importantly, highlighted the necessity in adding OVOC measurement to give a complete and accurate depiction of reactive gas emissions from non-road mobile sources.

Quantifying the impact of daily mobility on errors in air pollution exposure estimation using mobile phone location data.

One major source of uncertainty in accurately estimating human exposure to air pollution is that human subjects move spatiotemporally, and such mobility is usually not considered in exposure estimation. How such mobility impacts exposure estimates at the population and individual level, particularly for subjects with different levels of mobility, remains under-investigated. In addition, a wide range of methods have been used in the past to develop air pollutant concentration fields for related health studies. How the choices of methods impact results of exposure estimation, especially when detailed mobility information is considered, is still largely unknown. In this study, by using a publicly available large cell phone location dataset containing over 35 million location records collected from 310,989 subjects, we investigated the impact of individual subjects' mobility on their estimated exposures for five chosen ambient pollutants (CO, NO2, SO2, O3 and PM2.5). We also estimated exposures separately for 10 groups of subjects with different levels of mobility to explore how increased mobility impacted their exposure estimates. Further, we applied and compared two methods to develop concentration fields for exposure estimation, including one based on Community Multiscale Air Quality (CMAQ) model outputs, and the other based on the interpolated observed pollutant concentrations using the inverse distance weighting (IDW) method. Our results suggest that detailed mobility information does not have a significant influence on mean population exposure estimate in our sample population, although impacts can be substantial at the individual level. Additionally, exposure classification error due to the use of home-location data increased for subjects that exhibited higher levels of mobility. Omitting mobility could result in underestimation of exposures to traffic-related pollutants particularly during afternoon rush-hour, and overestimate exposures to ozone especially during mid-afternoon. Between CMAQ and IDW, we found that the IDW method generates smooth concentration fields that were not suitable for exposure estimation with detailed mobility data. Therefore, the method for developing air pollution concentration fields when detailed mobility data were to be applied should be chosen carefully. Our findings have important implications for future air pollution health studies.