Aerobic granular sludge for swine wastewater treatment: Implications for antibiotic and antibiotic resistance gene elimination.

Swine wastewater (SW) contains high levels of traditional pollutants, antibiotics, and antibiotic resistance genes (ARGs), necessitating effective elimination. Two parallel aerobic granular sludge (AGS) reactors, R1 and R2, were constructed and optimized for treating SW from two pig farms, identified as SW1 and SW2. R2 showed higher antibiotic removal efficiency, particularly in the removal of sulfonamides, while fluoroquinolones tended to adsorb onto the sludge. Process optimization by introducing an additional anoxic phase enhanced denitrification and reduced effluent ARG levels, also aiding in the improved removal of fluoroquinolones. The nitrite-oxidizing bacteria (NOB) Nitrospira accumulated after the treatment process, reaching 12.8 % in R1 and 14.1 % in R2, respectively. Mantel's test revealed that pH, NH4+-N, and Mg significantly affected ARGs and microbial community. Sulfadiazine and sulfamethazine were found to significantly impact ARGs and the microbial communities. This study provides innovative insights into the application of AGS for the treatment of real SW.

Tower-based profiles of wintertime secondary organic aerosols in the urban boundary layer over Guangzhou.

Secondary organic aerosol (SOA) accounts for a large fraction of fine particulate matter (PM2.5), but the lack of vertical observations of SOA in the urban boundary layer (UBL) limits a comprehensive understanding of its sources and formation mechanisms. In this study, PM2.5 samples were simultaneously collected at 3 m, 118 m, and 488 m on the Canton Tower in Guangzhou during winter. Typical SOA tracers, including oxidation products of isoprene (SOAI), monoterpene (SOAM), sesquiterpene (SOAS), and toluene (ASOA), were investigated alongside meteorological parameters and gaseous/particulate pollutants. Total concentrations of SOA tracers showed an increasing trend with height, with daytime levels exceeding nighttime levels. C5-alkene triols and 2-methylglyceric acid displayed a significant increase with height, potentially affected by nighttime chemistry in the residual layer, determining the overall vertical trend of SOAI tracers. Concentrations of later-generation SOAM (SOAM_S) tracers also increased with height, while those of first-generation SOAM (SOAM_F) tracers decreased, indicating relatively aged SOAM in the upper layers. SOAS and ASOA tracers exhibited higher enhancement under polluted conditions, likely impacted by biomass burning and anthropogenic emissions. The yields of SOAI tracers varied with temperature in the vertical profile. The formation of SOAM_F tracers was negatively correlated with relative humidity, liquid water content, and pH, affecting their vertical distributions. The effect of O3 on SOA formation enhanced significantly with height, influenced by air mass transport, and likely contributed to the higher yields of SOA in the upper layer. However, at ground level, SOA formation was primarily driven by high local emissions of both NOx and volatile organic compounds. We also observed the roles of SO2 in SOA generation, particularly at 118 m. This study demonstrates the vertical diurnal characteristics of SOA tracers in the UBL, highlighting the varying effects of meteorological conditions and anthropogenic pollutants on SOA formation at different heights.

Sources and formation characteristics of particulate nitrate in the Pearl River Delta region of China: Insights from three-year online observations.

Nitrate (NO3-) has been identified as a key component of particulate matter (PM2.5) in China. However, there is still a lack of understanding regarding its sources and how it forms, especially in the context of high-frequency and long-term data. In this study, NO3- levels were observed on an hourly basis over an almost three-year period at an urban site in the Pearl River Delta (PRD) region, China, from January 2019 to December 2021. The results reveal an average daily NO3- concentration ranging from 0.08 µg m-3 to 61.69 µg m-3, constituting 11.9 ± 12.5 % of PM2.5. This percentage rose to as high as 57 % during pollution episodes, highlighting NO3-'s significant role in pollution formation. The ammonia-rich environment was found to be the most important factor in promoting NO3- formation. Positive Matrix Factorization (PMF) analysis indicates that the primary sources of NO3- in the PRD region were vehicle emissions (43.8 ± 21.2 %) and coal combustion (39.1 ± 21.5 %), with shipping emissions, sea salt, soil dust and industrial emissions + biomass burning following in importance. Regarding source areas, the primary contributor of vehicle emissions was predominantly from the PRD region, whereas the coal combustion, aside from local contributions, also originates from the northern region. From a long-term perspective, NO3- pollution has remained relatively stable since the summer of 2020. Concurrently, coal combustion source has shown a localization trend. These insights derived from the extensive, high-frequency observation presented in this study serve as a valuable reference for devising strategies to control NO3- and PM2.5 in the PRD region and China.

Evaluation of laboratory and environmental exposure systems for protein modification upon gas pollutants and environmental factors.

Chemical modifications of proteins induced by ambient ozone (O3) and nitrogen oxides (NOx) are of public health concerns due to their potential to trigger respiratory diseases. The laboratory and environmental exposure systems have been widely used to investigate their relevant mechanism in the atmosphere. Using bovine serum albumin (BSA) as a model protein, we evaluated the two systems and aimed to reduce the uncertainties of both the reactants and products in the corresponding kinetic study. In the laboratory simulation system, the generated gaseous pollutants showed negligible losses. Ten layers of BSA were coated on the flow tube with protein extraction recovery of 87.4%. For environmental exposure experiment, quartz fiber filter was selected as the upper filter with low gaseous O3 (8.0%) and NO2 (1.7%) losses, and cellulose acetate filter was appropriate for the lower filter with protein extraction efficiency of 95.2%. The protein degradation process was observed without the exposure to atmospheric oxidants and contributed to the loss of protein monomer mass fractions, while environmental factors (e.g., molecular oxygen and ultraviolet) may cause greater protein monomer losses. Based on the evaluation, the study exemplarily applied the two systems to protein modification and both showed that O3 promotes the protein oligomerization and nitration, while increased temperature can accelerate the oligomerization and increased relative humidity can inhibit the nitration in the environmental exposure samples. The developed laboratory and environmental systems are suitable for studying protein modifications formed under different atmospheric conditions. A combination of the two will further reveal the actual mechanism of protein modifications.

Single particle mass spectral signatures from on-road and non-road vehicle exhaust particles and their application in refined source apportionment using deep learning.

With advances in vehicle emission control technology, updating source profiles to meet the current requirements of source apportionment has become increasingly crucial. In this study, on-road and non-road vehicle particles were collected, and then the chemical compositions of individual particles were analyzed using single particle aerosol mass spectrometry. The data were grouped using an adaptive resonance theory neural network to identify signatures and establish a mass spectral database of mobile sources. In addition, a deep learning-based model (DeepAerosolClassifier) for classifying aerosol particles was established. The objective of this model was to accomplish source apportionment. During the training process, the model achieved an accuracy of 98.49 % for the validation set and an accuracy of 93.36 % for the testing set. Regarding the model interpretation, ideal spectra were generated using the model, verifying its accurate recognition of the characteristic patterns in the mass spectra. In a practical application, the model performed hourly source apportionment at three specific field monitoring sites. The effectiveness of the model in field measurement was validated by combining traffic flow and spatial information with the model results. Compared with other machine learning methods, our model achieved highly automated source apportionment while eliminating the need for feature selection, and it enables end-to-end operation. Thus, in the future, it can be applied in refined and online source apportionment of particulate matter.

Multiphase reactions of proteins in the air: Oligomerization, nitration and degradation of bovine serum albumin upon ambient exposure.

Proteins in atmospheric aerosol can react with atmospheric pollutants such as ozone (O3) and nitrogen dioxide (NO2) in the atmosphere via the reactions of oxidation, nitration, and cross-linking etc. Currently, the reactions have been more thoroughly studied in the laboratory but rarely investigated in the ambient environment. In this study, we used bovine serum albumin (BSA) as the model protein to conduct the exposure experiment in the ambient environment in southern China, an area with increasing oxidative capacity, to investigate the reactions of proteins in the atmosphere. We observed the occurrence of oligomerization, nitration and degradation of BSA upon exposure. The mass fraction of BSA monomer decreased by 5.86 ± 1.61% after exposure and those of dimers, trimers and higher oligomers increased by 1.04 ± 0.49%, 1.37 ± 0.74% and 3.40 ± 1.06%, respectively. Simultaneously, the nitration degrees of monomers, dimers, trimers and higher oligomers increased by 0.42 ± 0.15%, 0.53 ± 0.15%, 0.55 ± 0.28% and 2.15 ± 1.01%, respectively. The results show that oligomerization was significantly affected by O3 and temperature and nitration was jointly affected by O3, temperature and relative humidity, indicating the important role of atmospheric oxidants in the atmospheric reactions of protein. Atmospheric degradation of BSA was observed with the release of free amino acids (FAAs) such as glycine, alanine, serine and methionine. Glycine was the dominant FAA with a molar yield ranging from ∼8% to 33% for BSA. The estimated stoichiometric coefficient (α) of glycine is 10-7-10-6 for the degradation of BSA upon O3. Our observation suggests the occurrence of protein reactions in the oxidative ambient environment, leading to the production of nitrated products, oligomers and low molecular weight products such as peptides and FAAs. This study may deepen the current understanding of the atmospheric reaction mechanisms and reveal the influence of environmental factors in the atmosphere.

Influence of ozone pollution on the mixing state and formation of oxygenated organics containing single particles.

The formation and aging processes of oxygenated organic molecules (OOMs) are important for understanding the formation mechanisms of secondary organic aerosols (SOAs) in the field. In this study, we investigated the mixing states of OOM particles by identifying several oxygenated species along with the distributions of secondary organic carbon (SOC) during both clean and ozone (O3)-polluted periods in July and September of 2022 in Guangzhou, China. OOM-containing particles accounted for 57 % and 49 % of the total detected single particles in July and September, respectively. Most of the OOM particles were internally mixed with sulfate and nitrate, while elemental carbon and hydrocarbon species were absent. Despite the higher SOC/OC ratio in September (81 %) than it in July (72 %), comparative investigations of the mass spectra, diurnal patterns, and distributions of OOM particles revealed the same composition and aging states of OOMs in two O3 pollution periods. As the O3 concentration increased from the clean to the polluted periods, the ratio of SOC to OC increased along with the relative abundance of secondary OOM particles among total OOM particles. In contrast, the relative abundance of OC-type OOM particles gradually decreased, indicating the conversion of hydrocarbon species into OOMs as the SOC/OC ratio increased. Both the bulk analysis of SOC from filter measurement and the mixing states of OOM particles suggested that OOM production and degree of oxidation were higher in the O3-polluted periods than in the clean periods. These results elucidate the effects of O3 pollution on the OOM formation process and offer new perspectives for the joint investigation of SOA production based on filter sampling and single-particle measurements.