Carbonaceous aerosols pose significant climatic impact, however, their sources and respective contribution to light absorption vary and remain poorly understood. In this work, filter-based PM₂.₅ samples were collected in winter of 2021 at three urban sites in Yibin, a fast-growing city in the south of Sichuan Basin, China. The composition characteristics of PM₂.₅, light absorption and source of carbonaceous aerosol were analyzed. The city-wide average concentration of PM₂.₅ was 87.4 ± 31.0 μg/m³ in winter. Carbonaceous aerosol was the most abundant species, accounting for 42.5% of the total PM₂.₅. Source apportionment results showed that vehicular emission was the main source of PM₂.₅ during winter, contributing 34.6% to PM₂.₅. The light absorption of black carbon (BC) and brown carbon (BrC) were derived from a simplified two-component model. We apportioned the light absorption of carbonaceous aerosols to BC and BrC using the Least Squares Linear Regression with optimal angstrom absorption exponent of BC (AAEBC). The average absorption of BC and BrC at 405 nm were 51.6 ± 21.5 Mm⁻¹ and 17.7 ± 8.0 Mm⁻¹, respectively, with mean AAEBC = 0.82 ± 0.02. The contribution of BrC to the absorption of carbonaceous reached 26.1% at 405 nm. Based on the PM₂.₅ source apportionment and the mass absorption cross-section (MAC) value of BrC at 405 nm, vehicle emission was found to be the dominant source of BrC in winter, contributing up to 56.4%. Therefore, vehicle emissions mitigation should be the primary and an effective way to improve atmospheric visibility in this fast-developing city.

Surface water is one of the primary sources of irrigation water for produce production; therefore, its contamination by foodborne pathogens, such as Salmonella, may substantially impact public health. In this study, we determined the presence of Salmonella in surface water and characterized the relationship between Salmonella detection and environmental and anthropogenic factors. From April 2019 to February 2020, 120 samples from 30 sites were collected monthly in four watersheds located in two different central Chile agricultural regions (N = 1080). Water samples from rivers, canals, streams, and ponds linked to each watershed were obtained. Surface water (10 L) was filtrated in situ, and samples were analyzed for the presence of Salmonella. Salmonella was detected every month in all watersheds, with a mean detection percentage of 28% (0%–90%) across sampling sites, regardless of the season. Overall, similar detection percentages were observed for both regions: 29.1% for Metropolitan and 27.0% for Maule. Salmonella was most often detected in summer (39.8% of all summer samples tested positive) and least often in winter (14.4% of winter samples). Random forest analysis showed that season, water source, and month, followed by latitude and river, were the most influential factors associated with Salmonella detection. The influences of water pH and temperature (categorized as environmental factors) and factors associated with human activity (categorized as anthropogenic factors) registered at the sampling site were weakly or not associated with Salmonella detection. In conclusion, Salmonella was detected in surface water potentially used for irrigation, and its presence was linked to season and water source factors. Interventions are necessary to prevent contamination of produce, such as water treatment before irrigation.

Human exposure to organic contaminants is widespread. Many of these contaminants show adverse health effects on human population. Human biomonitoring (HBM) follows the levels and the distribution of biomarkers of exposure (BoE), but it is usually done in a targeted manner. Suspect and non-targeted screening (SS/NTS) tend to find BoE in an agnostic way, without preselection of compounds, and include finding evidence of exposure to predicted, unpredicted known and unknown chemicals. This study describes the application of high-resolution mass spectrometry (HRMS)-based SS/NTS workflow for revealing organic contaminants in urine of a cohort of 200 children from Slovenia, aged 6–9 years. The children originated from two regions, urban and rural, and the latter were sampled in two time periods, summer and winter. We tentatively identified 74 BoE at the confidence levels of 2 and 3. These BoE belong to several classes of pharmaceuticals, personal care products, plasticizers and plastic related products, volatile organic compounds, nicotine, caffeine and pesticides. The risk of three pesticides, atrazine, amitraz and diazinon is of particular concern since their use was limited in the EU. Among BoE we tentatively identified compounds that have not yet been monitored in HBM schemes and demonstrate limited exposure data, such as bisphenol G, polyethylene glycols and their ethers. Furthermore, 7 compounds with unknown use and sources of exposure were tentatively identified, either indicating the entry of new chemicals into the market, or their metabolites and transformation products. Interestingly, several BoE showed location and time dependency. Globally, this study presents high-throughput approach to SS/NTS for HBM. The results shed a light on the exposure of Slovenian children and raise questions on potential adverse health effects of such mixtures on this vulnerable population.

Harmful algal blooms (HABs) are recurrent in the NW Patagonia fjords system and their frequency has increased over the last few decades. Outbreaks of HAB species such as Alexandrium catenella, a causal agent of paralytic shellfish poisoning, and Protoceratium reticulatum, a yessotoxins producer, have raised considerable concern due to their adverse socioeconomic consequences. Monitoring programs have mainly focused on their planktonic stages, but since these species produce benthic resting cysts, the factors influencing cyst distributions are increasingly gaining recognition as potentially important to HAB recurrence in some regions. Still, a holistic understanding of the physico-chemical conditions influencing cyst distribution in this region is lacking, especially as it relates to seasonal changes in drivers of cyst distributions, as the characteristics that favor cyst preservation in the sediment may change through the seasons. In this study, we analyzed the physico–chemical properties of the sediment (temperature, pH, redox potential) and measured the bottom dissolved oxygen levels in a “hotspot” area of southern Chile, sampling during the spring and summer as well as the fall and winter, to determine the role these factors may play as modulators of dinoflagellate cyst distribution, and specifically for the cysts of A. catenella and P. reticulatum. A permutational analysis of variance (PERMANOVA) showed the significant effect of sediment redox conditions in explaining the differences in the cyst assemblages between spring-summer and fall-winter periods (seasonality). In a generalized linear model (GLM), sediment redox potential and pH were associated with the highest abundances of A. catenella resting cysts in the spring-summer, however it was sediment temperature that most explained the distribution of A. catenella in the fall-winter. For P. reticulatum, only spring-summer sediment redox potential and temperature explained the variation in cyst abundances. The implications of environmental (physico-chemical) seasonality for the resting cysts dynamics of both species are discussed.

Effects of human activities on atmospheric nitrate (NO₃⁻) formation remain unclear, though the knowledge is critical for improving atmospheric chemistry models and nitrogen deposition reduction strategies. A potentially useful way to explore this is to compare NO₃⁻ oxidation processes in urban and rural atmospheres based upon the oxygen stable isotope composition of NO₃⁻ (Δ¹⁷O–NO₃⁻). Here we compared the Δ¹⁷O–NO₃⁻ from three-years of daily-based bulk deposition in urban (Shenyang) and forested rural sites (Qingyuan) in northeast China and quantified the relative contributions of different formation pathways based on the SIAR model. Our results showed that the Δ¹⁷O in Qiangyuan (26.2 ± 3.3‰) is significantly higher (p < 0.001) than in Shenyang (24.0 ± 4.0‰), and significantly higher in winter (Shenyang: 26.1 ± 6.7‰, Qingyuan: 29.6 ± 2.5‰) than in summer (Shenyang: 22.7 ± 2.9‰, Qingyuan: 23.8 ± 2.4‰) in both sites. The lower values in the urban site are linked with conditions that favored a higher relative contribution of nitrogen dioxide reaction with OH pathway (0.76-0.91) than in rural site (0.47-0.62), which should be induced by different levels of human activities in the two sites. The seasonal variations of Δ¹⁷O–NO₃⁻ in both sites are explained by a higher relative contribution of ozone-mediated oxidation chemistry and unfavorable conditions for the OH pathway during winter relative to summer, which is affected by human activities and seasonal meteorological condition change. Based on Δ¹⁷O, wintertime conditions led to a contribution of O₃ related pathways (NO₃ + DMS/HC and N₂O₅ hydrolysis) of 0.63 in Qingyuan and 0.42 in Shenyang, while summertime conditions led to 0.15 in Qingyuan and 0.05 in Shenyang. Our comparative study on Δ¹⁷O–NO₃⁻ between urban and rural sites reveals different anthropogenic effects on nitrate formation processes on spatial and temporal scales, illustrating different responses of reactive nitrogen chemistry to changes in human activities.

The prevalence and transmission of antibiotic resistance genes (ARGs) and opportunistic pathogens in water environments can pose great threat to public health. However, the dissemination of ARGs and opportunistic pathogens from water environments to humans has been poorly explored. Here, we employed 16S rRNA gene sequencing and high-throughput quantitative PCR techniques to explore the seasonal distribution of ARGs and opportunistic pathogens in the Yellow River water (source water) and tap water, as well as their relationships with healthy humans at Lanzhou, China. Physiochemical analysis was applied to detect water quality parameters and heavy metal contents. The absolute abundance and diversity of ARGs in the Yellow River and tap water demonstrated distinct seasonal patterns. In winter, the Yellow river water had the highest ARG abundance and diversity, while tap water owned the lowest. Mobile genetic elements (MGEs) were the predominant driver of ARG profiles in both the Yellow river and tap water. Null model analysis showed that ARG assembly in the Yellow River was more influenced by stochastic processes than tap water and this was independent of seasons. Total organic carbon and arsenic contents exhibited positive correlations with many ARGs. Opportunistic pathogens Aeromonas and Pseudomonas may be potential hosts for ARGs. Approximately 80% of detected ARGs were shared between water samples and the human gut. These persistent ARGs could not be entirely eliminated through drinking water treatment processes. Thus, it is crucial to protect sources of tap water from anthropogenic pollution and improve water treatment technologies to reduce the dissemination of ARGs and ensure drinking-water biosafety for human health.

Many studies revealed the rapid decline of atmospheric PM₂.₅ in Beijing due to the emission control measures. The variation of particle number concentration (PN) which has important influences on regional climate and human health, however, was rarely reported. This study measured the particle number size distributions (PNSD) in 3–700 nm in winter of Beijing during 2013–2019. It was found that PN decreased by 58% from 2013 to 2017, but increased by 29% from 2017 to 2019. By Positive matrix factorization (PMF) analysis, five source factors of PNSD were identified as Nucleation, Fresh traffic, Aged traffic + Diesel, Coal + biomass burning and Secondary. Overall, factors associated with primary emissions were found to decrease continuously. Coal + biomass burning dominated the reduction (65%) among the three primary sources during 2013–2017, which resulted from the great efforts on emission control of coal combustion and biomass burning. Fresh traffic and Aged traffic + Diesel decreased by 43% and 66%, respectively, from 2013 to 2019, as a result of the upgrade of the vehicle emission standards in Beijing-Tianjin-Hebei area. On the other hand, the contribution from Nucleation and Secondary decreased with the reduction of gaseous precursors in 2013–2017, but due to the increased intensity of new particle formation (NPF) and secondary oxidation, they increased by 56% and 70%, respectively, from 2017 to 2019, which led to the simultaneously increase of PN and particle volume concentration. This study indicated that NPF may play an important role in urban atmosphere under continuous air quality improvement.

The diurnal variation, gas-particle partitioning, health risks, and sources of polycyclic aromatic hydrocarbons (PAHs) were investigated in a northern basin city of China in winter, 2020. The mean concentrations of particulate and gaseous PAHs were 87.90 ng m⁻³ and 69.65 ng m⁻³, respectively, and their concentrations were considerably enhanced during the domestic heating period. The relationship between the gas-particle partitioning coefficient of PAHs (KP) and subcooled liquid vapor pressure of PAHs (PL⁰) indicated organic absorption as the mechanism for this partitioning. However, the dual sorption model confirmed adsorption onto elemental carbon (EC). The health risks indicated by several equivalent parameters showed an important health effect of PAHs, especially of particulate PAHs bound onto PM₂.₅ during the heating period. Environmentally persistent free radicals (EPFRs) were also studied as an auxiliary parameter to evaluate the health impact of PAHs. According to the diagnostic ratios of PAHs and PMF model results, petroleum volatilization and coal combustion were the dominant sources of particulate PAHs during the non-heating and heating periods, respectively. The source apportionment results can help efficiently control PAHs and their health risks.

PM₂.₅ (fine particulate matter with aerodynamics diameter <2.5 μm) is the most important component of air pollutants, and has a significant impact on the atmospheric environment and human health. Using satellite remote sensing aerosol optical depth (AOD) to explore the hourly ground PM₂.₅ distribution is very helpful for PM₂.₅ pollution control. In this study, Himawari-8 AOD, meteorological factors, geographic information, and a new deep forest model were used to construct an AOD-PM₂.₅ estimation model in China. Hourly cross-validation results indicated that estimated PM₂.₅ values were consistent with the site observation values, with an R² range of 0.82–0.91 and root mean square error (RMSE) of 8.79–14.72 μg/m³, among which the model performance reached the optimum value between 13:00 and 15:00 Beijing time (R² > 0.9). Analysis of the correlation coefficient between important features and PM₂.₅ showed that the model performance was related to AOD and affected by meteorological factors, particularly the boundary layer height. Deep forest can detect diurnal variations in pollutant concentrations, which were higher in the morning, peaked at 10:00–11:00, and then began to decline. High-resolution PM₂.₅ concentrations derived from the deep forest model revealed that some cities in China are seriously polluted, such as Xi ‘an, Wuhan, and Chengdu. Our model can also capture the direction of PM₂.₅, which conforms to the wind field. The results indicated that due to the combined effect of wind and mountains, some areas in China experience PM₂.₅ pollution accumulation during spring and winter. We need to be vigilant because these areas with high PM₂.₅ concentrations typically occur near cities.