Analysis of PM2.5 inorganic and organic constituents to resolve contributing sources in Seoul, South Korea and Beijing, China and their possible associations with cytokine IL-8.

China and South Korea are the most polluted countries in East Asia due to significant urbanization and extensive industrial activities. As neighboring countries, collaborative management plans to maximize public health in both countries can be helpful in reducing transboundary air pollution. To support such planning, PM2.5 inorganic and organic species were determined in simultaneously collected PM2.5 integrated filters. The resulting data were used as inputs to positive matrix factorization, which identified nine sources at the ambient air monitoring sites in both sites. Secondary nitrate, secondary sulfate/oil combustion, soil, mobile, incinerator, biomass burning, and secondary organic carbon (SOC) were found to be sources at both sampling sites. Industry I and II were only identified in Seoul, whereas combustion and road dust sources were only identified in Beijing. A subset of samples was selected for exposure assessment. The expression levels of IL-8 were significantly higher in Beijing (167.7 pg/mL) than in Seoul (72.7 pg/mL). The associations between the PM2.5 chemical constituents and its contributing sources with PM2.5-induced inflammatory cytokine (interleukin-8, IL-8) levels in human bronchial epithelial cells were investigated. For Seoul, the soil followed by the secondary nitrate and the biomass burning showed increase with IL-8 production. However, for the Beijing, the secondary nitrate exhibited the highest association with IL-8 production and SOC and biomass burning showed modest increase with IL-8. As one of the highest contributing sources in both cities, secondary nitrate showed an association with IL-8 production. The soil source having the strongest association with IL-8 production was found only for Seoul, whereas SOC showed a modest association only for Beijing. This study can provide the scientific basis for identifying the sources to be prioritized for control to provide effective mitigation of particulate air pollution in each city and thereby improve public health.

Reduction of ovarian reserves and activation of necroptosis to in vivo air pollution exposures.

We investigated the association between air pollution and changes in ovarian follicles, anti-mullerian hormone (AMH) levels, the occurrence of necroptosis cell death by activation of receptor-interacting protein kinase 3 (RIPK3) and, the activation of mixed lineage kinase domain-like (MLKL) proteins. Forty-two female Wistar rats were divided into three groups of 14 each, which were exposed to real-ambient air, filtered air and purified air (control) in two periods of 3 and 5 months. The results showed that the number of ovarian follicles decreased in the group exposed to real-ambient air versus the control group (P < 0.0001). The trend of age-related AMH changes with respect to exposure to air pollutants was affected and its levels decreased after 3 months of exposure. The MLKL increased in the group exposed to the real-ambient air compared to the control group (P = 0.033). Apparently long-term exposure to air pollution can reduce ovarian reserves.

Dynamic Changes of Composition of Particulate Matter Emissions during Residential Biomass Combustion.

Residential biomass combustion in developing countries produces significant primary particulate matter (PM) emissions. Highly time-resolved aerosol mass spectrometry and aethalometer measurements were used to investigate the dynamic changes of emitted PM chemical composition from a typical improved stove burning with wood and crop straw in China. Combustion temperature and organic aerosol (OA) concentration increased quickly during the ignition stage. The flaming stage was characterized by high combustion temperature and high pollutant [including OA, black carbon (BC), inorganic salts, and polycyclic aromatic hydrocarbons (PAHs)] emissions, while the burnout stage is characterized by low combustion temperature and lower pollutant emissions. OA was the primary emitted species; emission factors of OA in the flaming stage were generally higher (24.5-792%) than those in the burnout stage. Mass spectral signatures of OA were obtained. The ratio of Cl-/OA for wood combustion (0.05 ± 0.01) is much lower than that from burning crop straw (0.32 ± 0.19). Hydrocarbon OA emissions dominated during the ignition and flaming stages. A high percentage of oxidized OA was emitted during the burnout stage. The relationship between PAHs and BC/OA emissions under different burning conditions was investigated, and PAHs may act as intermediate products in the conversion of OA to BC.

Triggering of ST-elevation myocardial infarction by ultrafine particles in New York: Changes following Tier 3 vehicle introduction.

BACKGROUND: Previously, we found increased rates of ST-elevation myocardial infarction (STEMI) associated with increased ultrafine particle (UFP; <100 nm) concentrations in the previous few hours in Rochester, New York. Relative rates were higher after air quality policies and a recession reduced pollutant concentrations (2014-2016 versus 2005-2013), suggesting PM composition had changed and the same PM mass concentration had become more toxic. Tier 3 light duty vehicles, which should produce less primary organic aerosols and oxidizable gaseous compounds, likely making PM less toxic, were introduced in 2017. Thus, we hypothesized we would observe a lower relative STEMI rate in 2017-2019 than 2014-2016. METHODS: Using STEMI events treated at the University of Rochester Medical Center (2014-2019), UFP and other pollutants measured in Rochester, a case-crossover design, and conditional logistic regression models, we estimated the rate of STEMI associated with increased UFP and other pollutants in the previous hours and days in the 2014-2016 and 2017-2019 periods. RESULTS: An increased rate of STEMI was associated with each 3111 particles/cm3 increase in UFP concentration in the previous hour in 2014-2016 (lag hour 0: OR = 1.22; 95% CI = 1.06, 1.39), but not in 2017-2019 (OR = 0.94; 95% CI = 0.80, 1.10). There were similar patterns for black carbon, UFP11-50nm, and UFP51-100nm. In contrast, increased rates of STEMI were associated with each 0.6 ppb increase in SO2 concentration in the previous 120 h in both periods (2014-2016: OR = 1.26, 95% CI = 1.03, 1.55; 2017-2019: OR = 1.21, 95% CI = 0.87, 1.68). CONCLUSIONS: Greater rates of STEMI were associated with short term increases in concentrations of UFP and other motor vehicle related pollutants before Tier 3 introduction (2014-2016), but not afterwards (2017-2019). This change may be due to changes in PM composition after Tier 3 introduction, as well as to increased exposure misclassification and greater underestimation of effects from 2017 to 2019.

Generating High Spatial Resolution Exposure Estimates from Sparse Regulatory Monitoring Data.

Random Forest algorithms have extensively been used to estimate ambient air pollutant concentrations. However, the accuracy of model-predicted estimates can suffer from extrapolation problems associated with limited measurement data to train the machine learning algorithms. In this study, we developed and evaluated two approaches, incorporating low-cost sensor data, that enhanced the extrapolating ability of random-forest models in areas with sparse monitoring data. Rochester, NY is the area of a pregnancy-cohort study. Daily PM2.5 concentrations from the NAMS/SLAMS sites were obtained and used as the response variable in the model, with satellite data, meteorological, and land-use variables included as predictors. To improve the base random-forest models, we used PM2.5 measurements from a pre-existing low-cost sensors network, and then conducted a two-step backward selection to gradually eliminate variables with potential emission heterogeneity from the base models. We then introduced the regression-enhanced random forest method into the model development. Finally, contemporaneous urinary 1-hydroxypyrene was used to evaluate the PM2.5 predictions generated from the two approaches. The two-step approach increased the average external validation R2 from 0.49 to 0.65, and decreased the RMSE from 3.56 µg/m3 to 2.96 µg/m3. For the regression-enhanced random forest models, the average R2 of the external validation was 0.54, and the RMSE was 3.40 µg/m3. We also observed significant and comparable relationships between urinary 1-hydroxypyrene levels and PM2.5 predictions from both improved models. This PM2.5 model estimation strategy could improve the extrapolating ability of random forest models in areas with sparse monitoring data.

N,Zn-Doped Fluorescent Sensor Based on Carbon Dots for the Subnanomolar Detection of Soluble Cr(VI) Ions.

The development of a fluorescent sensor has attracted much attention for the detection of various toxic pollutants in the environment. In this work, fluorescent carbon dots (N,Zn-CDs) doped with nitrogen and zinc were synthesized using citric acid monohydrate and 4-pyridinecarboxyaldehyde as carbon and nitrogen sources, respectively. The synthesized N,Zn-CDs served as an "off" fluorescence detector for the rapid and sensitive detection of hexavalent chromium ions (Cr(VI)). The zinc metal integrated into the heteroatomic fluorescent carbon dot played a functional role by creating a coordination site for the hydrogen ions that were displaced after the addition of Cr to the solution matrix. The stepwise addition of Cr(VI) effectively quenched the fluorescence intensity of the N,Zn-CDs, and this phenomenon was attributed to the internal filter effect. A low detection limit of 0.47 nmol/L for Cr(VI) was achieved in the fluorescence experiments. Real water samples were used to evaluate the practical application of N,Zn-CDs for the quantification of Cr(VI). The results show acceptable recoveries and agreement with ion chromatography-ultraviolet spectrometry results. These good recoveries indicate that the fluorescence probe is very well suited for environmental measurements.

Suspect Screening and Nontargeted Analysis of Per- and Polyfluoroalkyl Substances in a Lake Ontario Food Web.

Per- and polyfluoroalkyl substances (PFAS) are globally distributed in the natural environment, and their persistent and bioaccumulative potential illicit public concern. The production of certain PFAS has been halted or controlled by regulation due to their adverse effect on the health of humans and wildlife. However, new PFAS are continuously developed as alternatives to legacy PFAS. Additionally, many precursors are unknown, and their metabolites have not been assessed. To better understand the PFAS profiles in the Lake Ontario (LO) aquatic food web, a quadrupole time-of-flight mass spectrometer (QToF) coupled to ultrahigh-performance liquid chromatography (UPLC) was used to generate high-resolution mass spectra (HRMS) from sample extracts. The HRMS data files were analyzed using an isotopic profile deconvoluted chromatogram (IPDC) algorithm to isolate PFAS profiles in aquatic organisms. Fourteen legacy PFAAs (C5-C14) and 15 known precursors were detected in the LO food web. In addition, over 400 unknown PFAS features that appear to biomagnify in the LO food web were found. Profundal benthic organisms, deepwater sculpin(Myoxocephalus thompsonii), and Mysis were found to have more known precursors than other species in the food web, suggesting that there is a large reservoir of fluorinated substances in the benthic zone.

Evaluation of impact of "2+26″ regional strategies on air quality improvement of different functional districts in Beijing based on a long-term field campaign.

Consecutive measurements of ambient fine particulate matter (PM2.5) from February 2016 to April 2018 have been performed at four representative sites of Beijing to evaluate the impact of "2 + 26" regional strategies implemented in 2017 for air quality improvement in non-heating period (2017NH) and heating period (2017H). The decrease of PM2.5 were significant both in 2017NH (20.2% on average) and 2017H (43.7% on average) compared to 2016NH and 2016H, respectively. Eight sources were resolved at each site from the PMF source apportionment including secondary nitrate, traffic, coal combustion, soil dust, road dust, sulfate, biomass/waste burning and industrial process. The results show that the reductions of industrial process, soil dust, and coal combustion were most effective among all sources at each site after the regional strategies implementation with the large reductions in potential source areas. The decrease of coal combustion in 2017NH were larger than 2017H at all sites while that of soil dust and industrial sources were the opposite. Insignificant reduction of coal combustion contribution at the suburban site in the heating period indicated that rural residential coal burning need further control. The industrial source control in the suburbs were least effective compared with other districts. Traffic was the largest contributer at each site and control of traffic emissions were more effective in 2017H than 2017NH. The local nature and increase of biomass/waste burning contributions emphasized the effect of fireworks and bio-fuel use in rural areas and incinerator emissions in urban districts. Secondary nitrate and sulfate were mainly impacted by the regional transport from southern adjacent areas and favorable meteorological conditions played an important part in the PM2.5 abatements of 2017H. Secondary nitrate became a more major role in the air pollution process because of the larger decrease of sulfate. Finally suggestions for future control are made in this study.

Human exposure to aerosol from indoor gas stove cooking and the resulting nervous system responses.

Our knowledge of the effects of exposure to indoor ultrafine particles (sub-100 nm, #/cm3 ) on human brain activity is very limited. The effects of cooking ultrafine particles (UFP) on healthy adults were assessed using an electroencephalograph (EEGs) for brain response. Peak ultrafine particle concentrations were approximately 3 × 105 particle/cm3, and the average level was 1.64 × 105 particle/cm3 . The average particle number emission rate (S) and the average number decay rate (a+k) for chicken frying in brain experiments were calculated to be 2.82 × 1012 (SD = 1.83 × 1012 , R2  = 0.91, p = 0.0013) particles/min, 0.47 (SD = 0.30, R2  = 0.90, p < 0.0001) min-1 , respectively. EEGs were recorded before and during cooking (14 min) and 30 min after the cooking sessions. The brain fast-wave band (beta) decreased during exposure, similar to people with neurodegenerative diseases. It subsequently increased to its pre-exposure condition for 70% of the study participants after 30 min. The brain slow-wave band to fast-wave band ratio (theta/beta ratio) increased during and after exposure, similar to observed behavior in early-stage Alzheimer's disease (AD) patients. The brain then tended to return to its normal condition within 30 min following the exposure. This study suggests that chronically exposed people to high concentrations of cooking aerosol might progress toward AD.

Nontargeted Discovery of Novel Contaminants in the Great Lakes Region: A Comparison of Fish Fillets and Fish Consumers.

Sport fish fillets and human sera (fish consumers) were collected in the Lake Superior and Lake Michigan basin and screened for novel contaminants using the isotopic profile deconvoluted chromatogram (IPDC) algorithm. The IPDC algorithm was extended beyond traditional Cl/Br filters to detect additional potential bioaccumulative and toxic (PBT) such as perfluoroalkyl substances (PFAS). The IPDC algorithm screened for approximately 13.5 million theoretical molecular formulas. Additional algorithm modules were developed to detect data independent MS/MS fragmentation products and a retention time index calculator using a series of 13C-labeled perfluoroalkyl carboxylic acids (13C-PFCAs). Ten potential compound classes were isolated including six untargeted PFAS, six homologue groups of polyfluorinated carboxylic acids, polyfluorinated telomer alcohols (PoFTOHs), two hydroxylated polychlorobiphenyls, pesticides, herbicides, antifungals, pharmaceuticals, artificial sweeteners, and personal care products with minimal postprocessing efforts. The algorithm isolated 48 ubiquitous PoFTOHs in both fish fillet and serum of fish consumers suggesting a region wide distribution of this class of compounds. The 3, 4, and 7 fluorine substituted PoFTOH were the most abundant congeners in both biological matrices.

Characterization of Halogenated Organic Compounds in Pelagic Sharks and Sea Turtles Using a Nontargeted Approach.

Halogenated organic compounds (HOCs) in marine species collected from the Atlantic Ocean [3 shortfin mako (Isurus oxyrinchus) and 1 porbeagle (Lamna nasus)], and 12 sea turtles collected from the Pacific Ocean [3 loggerhead (Caretta caretta), 3 green (Chelonia mydas), 3 olive ridley (Lepidochelys olivacea), and 3 hawksbill (Eretmochelys imbricata)] were analyzed with a nontargeted analytical method using two-dimensional gas chromatography coupled to high-resolution time-of-flight mass spectrometry. Sharks and sea turtles had distinct HOC profiles. Halogenated methoxyphenols (halo-MeOPs) were the most abundant compound class identified in sea turtle livers, while polychlorinated biphenyls (PCBs) were the most abundant in shark livers. In addition to legacy contaminants and halo-MeOPs, a total of 110 nontargeted/novel HOCs (NHOCs) were observed in the shark livers. Shortfin mako collected from the northern Gulf of Mexico contained the largest number (89) and most diverse structural classes of NHOCs. Among all NHOCs, a group of compounds with the elemental composition C14H12-nCln (n = 5-8) exhibited the highest concentrations, followed by chlorocarbazoles and tris(chlorophenyl) methanes (TCPMs). Using nontargeted workflows, a variety of known and unknown HOCs were observed, which demonstrate the need to develop more complete chemical profiles in the marine environment.

Assessing Human Exposure to SVOCs in Materials, Products, and Articles: A Modular Mechanistic Framework.

A critical review of the current state of knowledge of chemical emissions from indoor sources, partitioning among indoor compartments, and the ensuing indoor exposure leads to a proposal for a modular mechanistic framework for predicting human exposure to semivolatile organic compounds (SVOCs). Mechanistically consistent source emission categories include solid, soft, frequent contact, applied, sprayed, and high temperature sources. Environmental compartments are the gas phase, airborne particles, settled dust, indoor surfaces, and clothing. Identified research needs are the development of dynamic emission models for several of the source emission categories and of estimation strategies for critical model parameters. The modular structure of the framework facilitates subsequent inclusion of new knowledge, other chemical classes of indoor pollutants, and additional mechanistic processes relevant to human exposure indoors. The framework may serve as the foundation for developing an open-source community model to better support collaborative research and improve access for application by stakeholders. Combining exposure estimates derived using this framework with toxicity data for different end points and toxicokinetic mechanisms will accelerate chemical risk prioritization, advance effective chemical management decisions, and protect public health.

Spring Festival and COVID-19 Lockdown: Disentangling PM Sources in Major Chinese Cities.

Responding to the 2020 COVID-19 outbreak, China imposed an unprecedented lockdown producing reductions in air pollutant emissions. However, the lockdown driven air pollution changes have not been fully quantified. We applied machine learning to quantify the effects of meteorology on surface air quality data in 31 major Chinese cities. The meteorologically normalized NO2, O3, and PM2.5 concentrations changed by -29.5%, +31.2%, and -7.0%, respectively, after the lockdown began. However, part of this effect was also associated with emission changes due to the Chinese Spring Festival, which led to ∼14.1% decrease in NO2, ∼6.6% increase in O3 and a mixed effect on PM2.5 in the studied cities that largely resulted from festival associated fireworks. After decoupling the weather and Spring Festival effects, changes in air quality attributable to the lockdown were much smaller: -15.4%, +24.6%, and -9.7% for NO2, O3, and PM2.5, respectively.

An updated systematic review on the association between atmospheric particulate matter pollution and prevalence of SARS-CoV-2.

On December 31, 2019, the novel human coronavirus (COVID-19) was emerged in Wuhan city, China, which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). There is a much controversial debate about the major pathways of transmission of the virus including airborne route. The present work is a systematic literature review (SR) aimed to assess the association of air pollution especially particulate matter pollution in the transmission and acceleration of the spread of SARS-CoV-2. The systematic literature search was performed to identify the available studies published through October 31, 2020 concerning the transmission of the disease and particulate matter air pollution in four international electronic databases. From the results of the included studies, there are suggestions that atmospheric particulate matter pollution plays a role in the SARS-CoV-2 spread, but the literature has not confirmed that it enhances the transmission although some studies have proposed that atmospheric particulate matter can operate as a virus carrier, promoting its spread. Therefore, although PM concentration alone cannot be effective in spreading the COVID-19 disease, other meteorological and environmental parameters including size of particles in ambient air, weather conditions, wind speed, relative humidity (RH) and temperature are involved. Therefore, it is necessary to consider all influencing parameters to prevent the spreading of COVID-19 disease. More studies are required to strengthen the scientific evidence and support more definitive conclusions.

Persistent high PM2.5 pollution driven by unfavorable meteorological conditions during the COVID-19 lockdown period in the Beijing-Tianjin-Hebei region, China.

Lockdown measures to curtail the COVID-19 pandemic in China halted most non-essential activities on January 23, 2020. Despite significant reductions in anthropogenic emissions, the Beijing-Tianjin-Hebei (BTH) region still experienced high air pollution concentrations. Employing two emissions reduction scenarios, the Community Multiscale Air Quality (CMAQ) model was used to investigate the PM2.5 concentrations change in this region. The model using the scenario (C3) with greater traffic reductions performed better compared to the observed PM2.5. Compared with the no reductions base-case (scenario C1), PM2.5 reductions with scenario C3 were 2.70, 2.53, 2.90, 2.98, 3.30, 2.81, 2.82, 2.98, 2.68, and 2.83 µg/m3 in Beijing, Tianjin, Shijiazhuang, Baoding, Cangzhou, Chengde, Handan, Hengshui, Tangshan, and Xingtai, respectively. During high-pollution days in scenario C3, the percentage reductions in PM2.5 concentrations in Beijing, Tianjin, Shijiazhuang, Baoding, Cangzhou, Chengde, Handan, Hengshui, Tangshan, and Xingtai were 3.76, 3.54, 3.28, 3.22, 3.57, 3.56, 3.47, 6.10, 3.61, and 3.67%, respectively. However, significant increases caused by unfavorable meteorological conditions counteracted the emissions reduction effects resulting in high air pollution in BTH region during the lockdown period. This study shows that effective air pollution control strategies incorporating these results are urgently required in BTH to avoid severe pollution.

A systematic review and meta-analysis of human biomonitoring studies on exposure to environmental pollutants in Iran.

Population exposure to environmental contaminants can be precisely observed through human biomonitoring studies. The present study aimed to systematically review all the biomonitoring studies conducted in Iran on some selected carcinogen environmental pollutants. In this systematic review study, 11 carcinogen agents were selected including arsenic, cadmium, chromium, nickel, lindane, benzene, trichloroethylene (TCE), pentachlorophenol (PCP), radon-222, radium-224, - 226, - 228, and tobacco smoke. The Web of Science, PubMed, and Scopus databases were searched for peer-reviewed articles published in English. After several screening steps, data were extracted from the studies. Meta-analyses (a random-effect model using the DerSimonian-Laired method) were performed only for the biomarkers with more than three eligible articles, including cadmium in blood and breast milk, and arsenic in breast milk. Methodological quality of the studies was assessed using the Newcastle-Ottawa Quality Assessment Scale adapted for cross-sectional studies. Of the 610 articles found in the database search, 30 studies were eligible for qualitative review, and 13 were included in the meta-analysis (cadmium in blood (n = 3), cadmium in breast milk (n = 6), and arsenic in breast milk (n = 4)). The overall pooled average concentrations (95% CI) of cadmium in blood, cadmium in breast milk, and arsenic in breast milk were 0.11 (95% CI: 0.08, 0.14), 5.38 (95% CI: 3.60, 6.96), and 1.42 (95% CI: 1.02, 1.81) µg/L, respectively. These values were compared with the biomarker concentrations in other countries and health-based guideline values. This study showed that there is a need for comprehensive action plans to reduce the exposure of general population to these environmental contaminants.

COVID-19 pandemic in Wuhan: Ambient air quality and the relationships between criteria air pollutants and meteorological variables before, during, and after lockdown.

As a result of the lockdown (LD) control measures enacted to curtail the COVID-19 pandemic in Wuhan, almost all non-essential human activities were halted beginning on January 23, 2020 when the total lockdown was implemented. In this study, changes in the concentrations of the six criteria air pollutants (PM2.5, PM10, SO2, NO2, CO, and O3) in Wuhan were investigated before (January 1 to 23, 2020), during (January 24 to April 5, 2020), and after the COVID-19 lockdown (April 6 to June 20, 2020) periods. Also, the relationships between the air pollutants and meteorological variables during the three periods were investigated. The results showed that there was significant improvement in air quality during the lockdown. Compared to the pre-lockdown period, the concentrations of NO2, PM2.5, PM10, and CO decreased by 50.6, 41.2, 33.1, and 16.6%, respectively, while O3 increased by 149% during the lockdown. After the lockdown, the concentrations of PM2.5, CO and SO2 declined by an additional 19.6, 15.6, and 2.1%, respectively. However, NO2, O3, and PM10 increased by 55.5, 25.3, and 5.9%, respectively, compared to the lockdown period. Except for CO and SO2, WS had negative correlations with the other pollutants during the three periods. RH was inversely related with all pollutants. Positive correlations were observed between temperature and the pollutants during the lockdown. Easterly winds were associated with peak PM2.5 concentrations prior to the lockdown. The highest PM2.5 concentrations were associated with southwesterly wind during the lockdown, and northwesterly winds coincided with the peak PM2.5 concentrations after the lockdown. Although, COVID-19 pandemic had numerous negative effects on human health and the global economy, the reductions in air pollution and significant improvement in ambient air quality likely had substantial short-term health benefits. This study improves the understanding of the mechanisms that lead to air pollution under diverse meteorological conditions and suggest effective ways of reducing air pollution in Wuhan.

Evaluation of regional transport of PM2.5 during severe atmospheric pollution episodes in the western Yangtze River Delta, China.

During winter 2018, the 16 prefecture-level cities in Anhui Province, Western Yangtze River Delta region, China had very high PM2.5 concentrations and prolonged pollution days. The impact of regional transport in the formation, accumulation, as well as dispersion of fine particulate matter (PM2.5) in Anhui Province was very significant. This study quantified and analyzed the vertical transport of PM2.5 in three major cities (Hefei, Fuyang, and Suzhou) of Anhui Province in January and July 2018 using the Weather Research and Forecasting (WRF) model coupled with the Community Multiscale Air Quality (CMAQ) model. The results of the inter-regional transport of PM2.5 revealed the dominant transport pathways for the three cities. The flux mainly flowed into Fuyang from Henan (2.23 and 1.42 kt/day in January and July, respectively) and Bozhou (1.96 and 1.21 kt/day in January and July, respectively), while the main flux from Fuyang flowed into Henan (-2.15 kt/day) and Lu'an (-1.91 kt/day) in January and Henan (-0.34 kt/day) and Bozhou (-0.29 kt/day) in July. In addition, the dominant transport pathways and the heights at which they occurred were identified: the northwest-southeast and northeast-south pathways in both winter and summer at both lower (˂300 m) and higher (≥300 m) levels for Fuyang; the northwest-south and northeast-southwest pathways in winter (at both lower and upper levels) and northwest-east and northeast-southwest pathways in summer at lower and upper levels for Hefei; and the northwest-southeast and northeast-south pathways in both winter (from 50 m up to the top level) and summer (between 100 and 300 m) for Suzhou. Furthermore, the intensities of daily PM2.5 transport fluxes in Fuyang during the atmospheric pollution episode (APE1) were stronger than the monthly average. These results show that joint emission controls across multiple cities along the identified pathways are urgently needed to reduce winter episodes.

Ambient ozone over mid-Brahmaputra Valley, India: effects of local emissions and atmospheric transport on the photostationary state.

This study presents the characteristics of ground level atmospheric ozone (O3) over the rural mid-Brahmaputra Valley region of the northeastern India. Ozone and oxides of nitrogen (NOx = NO + NO2) concentration data were obtained from continuous measurement of O3 and NOx housed at the MAPAN-AQM station at Tezpur University. The meteorological parameters were obtained from the same station. The diel, monthly, and seasonal variations of O3 were studied. The O3-NOx photostationary state (PS) was carefully examined and it was found that the net O3 concertation deviated substantially from the PS during the winter season. The deviation could be attributed to local biomass burning, biogenic VOC emission from forest and agriculture, and long-range transport of peroxyacyl nitrate (PAN). The long-range transport has been ascertained by examining the ventilation coefficients (VC), which correlated with the steep growth of net O3 concentrations in the morning hours. The HYSPLIT air mass back trajectories were used in concentration-weighted trajectory (CWT) analyses of O3 to assess the long-range regional transport of O3 precursors, which positively influenced local O3 concentrations.

Decadal Differences in Emerging Halogenated Contaminant Profiles in Great Lakes Top Predator Fish.

Legacy halogenated contaminants have been monitored in the Great Lakes for decades, but there are many additional unknown halogenated contaminants potentially affecting the Great Lakes ecosystem. To address this concern, lake trout (Salvelinus namaycush) were collected in 2005/2006 and 2015/2016 from each lake and screened for previously unidentified compounds. The isotopic profile deconvoluted chromatogram algorithm was used to isolate unknown halogenated components using high-resolution mass spectrometry data files generated by an atmospheric pressure gas chromatography-quadrupole time-of-flight mass spectrometer operated in positive and negative modes. The temporal and spatial differences in the newly detected features were used to isolate new potential contaminants. Decadal differences in the unknown halogenated compounds (or features) were compared with the total polychlorinated biphenyl concentration trends. Greater than 2000 unknown halogenated features were detected. As expected, Lake Superior contained the lowest number of unknown halogenated features, whereas Lake Ontario contained the highest. Unknown features tended to have fewer Cl and/or Br atoms compared to traditional legacy contaminant features typically monitored. Diverse patterns of unknown halogenated compounds between lakes suggested that there continues to be unidentified sources of halogenated contaminants in the Great Lakes missed by current monitoring programs.