Polycyclic aromatic compounds (PACs) in industrial soils from northwestern of China: occurrence, distribution, exposure risk, and implications on risk-based controls.

Some Polycyclic Aromatic Compounds (PACs) such as nitrated-PAHs (NPAHs), oxygenated-PAHs (OPAHs) and methyl-PAHs (MPAHs) have attracted significant concern due to derivatives have greater potential to be more toxic at low environmental concentrations compared to their PPAHs, particularly in petrochemical industrial region and its surrounding areas surface soils in China. Hence, this article provides an insight into the fate, sources, impacts, and relevance to the external environment of PAH-derivatives based on important emissions source. Moreover, prospective health risk due to their exposure has also been discussed. In this study, the concentration (10-3 ng/g) of Æ©18PPAHs, Æ©11MPAHs, Æ©12NPAHs, and Æ©4OPAHs in the park were 9.67 ± 1.40, 3.24 ± 0.54, 0.03 ± 0.02 and 0.19 ± 0.65, respectively, which were 4.47, 3.89, 2.04 and 1.17 times than of them surrounding the region. A decreasing trend of the low molecular weight (2-4Rings) contribution to the total amount of PAHs, while the fraction of high molecular weight (5-6Rings) species showed the opposite trend. According to the principal component analysis (PCA) and diagnostic ratios indicated PAHs in the soil samples have mixed sources from industrial activities, solid fuel combustion, and heavy traffic. Despite the high concentrations of MPAHs and OPAHs, the toxicity equivalency quotients (TEQs) of them were not calculated due to the lack of toxic equivalent factors (TEF), thus current studies on PAH and derivatives could have underestimated their exposure risks. The quality and sustainable management of soils are crucial for human health and sustainable development, while there is lack of public awareness of the severe issue of soil pollution. It is recommended to conduct more intensive monitoring and regional assessments in the future.

Response of Arctic Black Carbon Contamination and Climate Forcing to Global Supply Chain Relocation.

Black carbon (BC) plays a vital role in Arctic warming. Extensive investigations have been conducted to elucidate the source-receptor relationships of BC between the Arctic and mid-/high-latitude sources. However, it is unclear to what extent source relocation under globalization could disturb Arctic BC contamination and climate forcing from anthropogenic BC emissions. Here, we show that the global supply chain (GSC) relocation featured by the southward shift of industries from high-latitude developed countries to low-latitude developing countries markedly reduces the BC burden in the Arctic using a global chemical transport model (GEOS-Chem) and a multiregional input-output analysis (MRIO). We find that Arctic annual mean BC concentration associated with the GSC relocation drops by ∼15% from the case without the GSC relocation. The total net BC level declines 7% over the entire Arctic and 16% in the European Arctic. We also observed markedly declining BC deposition as well as direct and snow albedo radiative forcing in the Arctic. We show that the Arctic BC burden would be further reduced by decreasing BC emissions in China, attributable to its emission reduction and ongoing shift of the GSC from China to southern and southeastern Asia.

Deep Learning Prediction of Polycyclic Aromatic Hydrocarbons in the High Arctic.

Given the lack of understanding of the complex physiochemical and environmental processes of persistent organic pollutants (POPs) in the Arctic and around the globe, atmospheric models often yield large errors in the predicted atmospheric concentrations of POPs. Here, we developed a recurrent neural network (RNN) method based on nonparametric deep learning algorithms. The RNN model was implemented to predict monthly air concentrations of polycyclic aromatic hydrocarbons (PAHs) at the high Arctic monitoring station Alert. To train the RNN system, we used MODIS satellite remotely sensed forest fire data, air emissions, meteorological data, sea ice cover area, and sampled PAH concentration data from 1996 to 2012. The system was applied to forecast monthly PAH concentrations from 2012 to 2014 at the Alert station. The results were compared with monitored PAHs and an atmospheric transport model (CanMETOP) for POPs. We show that the RNN significantly improved PHE and BaP predictions from 2012 to 2014 by 62.5 and 91.1%, respectively, compared to CanMETOP predictions. The sensitivity analysis using the Shapley value reveals that air emissions determined the magnitude of PAH levels in the high Arctic, whereas forest fires played a significant role in the changes in PAH concentrations in the high Arctic, followed by air temperature and meridional wind fields.

Pollution Characteristics and Health Risks of Polycyclic Aromatic Compounds (PACs) in Soils of a Coking Plant.

Coke production is an important source of environmental polycyclic aromatic compounds (PACs), including parent polycyclic aromatic hydrocarbons (PAHs) and their derivatives. The focus near coking plants has primarily been on parent-PAH contamination, with less attention given to highly toxic derivatives. In this study, soil samples were collected from both within and outside of a coking plant. The concentrations of parent-PAHs and their derivatives, including methylated-PAHs, oxygenated-PAHs, and nitrated-PAHs, were examined. Spatial interpolation was employed to determine their spatial distribution patterns. Methods for identifying potential sources and conducting incremental lifetime cancer risk analysis were used. This could achieve a comprehensive understanding of the status of PAC pollution and the associated health risks caused by coke production. The concentrations of total PACs inside the plant ranged from 7.4 to 115.8 mg/kg, higher than those outside (in the range of 0.2 to 65.7 mg/kg). The spatial distribution of parent-PAH concentration and their derivatives consistently decreased with increasing distance from the plant. A significant positive correlation (p < 0.05) among parent-PAHs and their derivatives was observed, indicating relatively consistent sources. Based on diagnostic ratios, the potential emission sources of soil PACs could be attributed to coal combustion and vehicle emissions, while principal component analysis-multiple linear regression further indicated that primary emissions and secondary formation jointly influenced the PAC content, accounting for 60.4% and 39.6%, respectively. The exposure risk of soil PACs was dominated by 16 priority control PAHs; the non-priority PAHs' contribution to the exposure risk was only 6.4%.

Assessing the contribution of global wildfire biomass burning to BaP contamination in the Arctic.

Polycyclic aromatic hydrocarbons (PAHs) have become cause for growing concern in the Arctic ecosystems, partly due to their stable levels despite global emission reduction. Wildfire is considered one of the primary sources that influence PAH levels and trends in the Arctic, but quantitative investigations of this influence are still lacking. This study estimates the global emissions of benzo[a]pyrene (BaP), a congener of PAHs with high carcinogenicity, from forest and grassland fires from 2001 to 2020 and simulates the contributions of wildfire-induced BaP emissions from different source regions to BaP contamination in the Arctic. We find that global wildfires contributed 29.3% to annual averaging BaP concentrations in the Arctic from 2001 to 2020. Additionally, we show that wildfires contributed significantly to BaP concentrations in the Arctic after 2011, enhancing it from 10.1% in 2011 to 83.9% in 2020. Our results reveal that wildfires accounted for 94.2% and 50.8% of BaP levels in the Asian Arctic during boreal summer and autumn, respectively, and 74.2% and 14.5% in the North American Arctic for the same seasons. The source-tagging approach identified that local wildfire biomass emissions were the largest source of BaP in the Arctic, accounting for 65.7% of its concentration, followed by those of Northern Asia (17.8%) and Northern North America (13.7%). Our findings anticipate wildfires to play a larger role in Arctic PAH contaminations alongside continually decreasing anthropogenic emissions and climate warming in the future.

Effects of African BaP emission from wildfire biomass burning on regional and global environment and human health.

The vegetation burning caused by wildfires can release significant quantities of aerosols and toxic chemicals into the atmosphere and result in health risk. Among these emitted pollutants, Benzo(a)pyrene (BaP), the most toxic congener of 16 parent PAHs (polycyclic aromatic hydrocarbons), has received widespread concerns because of its carcinogenicity to human health. Efforts have been made to investigate the environmental and health consequences of wildfire-induced BaP emissions in Africa. Still, uncertainties remain due to knowledge and data gaps in wildfire incidences and biomass burning emissions. Based on a newly-developed BaP emission inventory, the present study assesses quantitatively the BaP environment cycling in Africa and its effects on other continents from 2001 to 2014. The new inventory reveals the increasing contribution of BaP emission from African wildfires to the global total primarily from anthropogenic sources, accounting for 48% since the 2000 s. We identify significantly higher BaP emissions and concentrations across sub-Saharan Africa, where the annual averaged BaP concentrations were as high as 5-8 ng/m3. The modeled BaP concentrations were implemented to estimate the lifetime cancer risk (LCR) from the inhalation exposure to BaP concentrations. The results reveal that the LCR values in many African countries exceeded the acceptable risk level at 1 × 10-6, some of which suffer from very high exposure risk with the LCR>1 × 10-4. We show that the African BaP emission from wildfires contributed, to some extent, BaP contamination to Europe as well as other regions, depending on source proximity and atmospheric pathways under favorable atmospheric circulation patterns.

Unsupervised PM2.5 anomalies in China induced by the COVID-19 epidemic.

To stop the spread of COVID-19 (2019 novel coronavirus), China placed lockdown on social activities across China since mid-January 2020. The government actions significantly affected emissions of atmospheric pollutants and unintentionally created a nationwide emission reduction scenario. In order to assess the impacts of COVID-19 on fine particular matter (PM2.5) levels, we developed a "conditional variational autoencoder" (CVAE) algorithm based on the deep learning to discern unsupervised PM2.5 anomalies in Chines cities during the COVID-19 epidemic. We show that the timeline of changes in number of cities with unsupervised PM2.5 anomalies is consistent with the timeline of WHO's response to COVID-19. Using unsupervised PM2.5 anomaly as a time node, we examine changes in PM2.5 before and after the time node to assess the response of PM2.5 to the COVID-19 lockdown. The rate of decrease of PM2.5 around the time node in northern China is 3.5 times faster than southern China, and decreasing PM2.5 levels in southern China is 3.5 times of that in northern China. Results were also compared with anomalous PM2.5 occurring in Chinese's Spring Festival from 2017 to 2019, PM2.5 anomalies during around Chinese New Year in 2020 differ significantly from 2017 to 2019. We demonstrate that this method could be used to detect the response of air quality to sudden changes in social activities.

An inter-comparative evaluation of PKU-FUEL global SO2 emission inventory.

PKU-FUEL is a recently developed gridded global emission inventory for multiple air pollutants that uses a bottom-up approach. The inventory includes data collected monthly for the period of 1960 to 2014 and at a 0.1° × 0.1° latitude/longitude resolution. In an effort to evaluate and improve this emission inventory, the PKU-FUEL Sulfur Dioxide (SO2) emission inventory was compared to other currently available and widely used global SO2 emission inventories constructed based on bottom-up and top-down approaches, including CEDS and OMI-HTAP. While PKU-FUEL is capable of capturing SO2 emissions across the globe and particularly in Asia, it misses 41 industrial point sources globally, accounting for 9.3% of Ozone Monitoring Instrument (OMI) remote sensing-measured industrial point sources. Most of these missing point sources are identified in Latin America, the Middle East (~60%), and some remote places. To improve the PKU-FUEL SO2 inventory, we applied OMI-measured emissions to sources missing from PKU-FUEL. GEOS-Chem model simulations were performed to evaluate original and improved PKU-FUEL SO2 inventories against measured SO2 concentrations across the world. Results were further compared to GEOS-Chem modeled SO2 concentrations using the CEDS inventory. We show that the modeled SO2 concentrations determined using both CEDS and improved PKU-FUEL inventories to a large extent corroborate sampled data and that the improved PKU-FUEL performs better for those regions lacking monitoring data.

Effect of northern boreal forest fires on PAH fluctuations across the arctic.

Polycyclic aromatic hydrocarbons (PAHs) are formed by the incomplete combustion of fossil fuels and forest or biomass burning. PAHs undergo long-range atmospheric transport, as evidenced by in situ observations across the Arctic. However, monitored atmospheric concentrations of PAHs indicate that ambient PAH levels in the Arctic do not follow the declining trend of worldwide anthropogenic PAH emissions since the 2000s, suggesting missing sources of PAHs in the Arctic or other places across the Northern Hemisphere. To trace origins and causes for the increasing trend of PAHs in the Arctic, the present study reconstructed PAH emissions from forest fires in the northern boreal forest derived by combining forest carbon stocks and MODIS burned area. We examined the statistical relationships of forest biomass, MODIS burned area, emission factors, and combustion efficiency with different PAH congeners. These relationships were then employed to construct PAH emission inventories from forest biomass burning. We show that for some PAH congeners, for example, benzo[a]pyrene (BaP)-the forest-fire-induced air emissions are almost one order of magnitude higher than previous emission inventories in the Arctic. A global-scale atmospheric chemistry model, GEOS-Chem, was used to simulate air concentrations of BaP, a representative PAH congener primarily emitted from biomass burning, and to quantify the response of BaP to wildfires in the northern boreal forest. The results showed that BaP emissions from wildfires across the northern boreal forest region played a significant role in the contamination and interannual fluctuations of BaP in Arctic air. A source-tagging technique was applied in tracking the origins of BaP pollution from different northern boreal forest regions. We also show that the response of BaP pollution at different Arctic monitoring sites depends on the intensity of human activities.