Insights into tropical cloud chemistry in Réunion (Indian Ocean): results from the BIO-MAÏDO campaign

We present here the results obtained during an intensive field campaign conducted in the framework of the French “BIO-MAÏDO” (Bio-physico-chemistry of tropical clouds at Maïdo (Réunion Island): processes and impacts on secondary organic aerosols' formation) project. This study integrates an exhaustive chemical and microphysical characterization of cloud water obtained in March–April 2019 in Réunion (Indian Ocean). Fourteen cloud samples have been collected along the slope of this mountainous island. Comprehensive chemical characterization of these samples is performed, including inorganic ions, metals, oxidants, and organic matter (organic acids, sugars, amino acids, carbonyls, and low-solubility volatile organic compounds, VOCs). Cloud water presents high molecular complexity with elevated water-soluble organic matter content partly modulated by microphysical cloud properties. As expected, our findings show the presence of compounds of marine origin in cloud water samples (e.g. chloride, sodium) demonstrating ocean–cloud exchanges. Indeed, Na+ and Cl− dominate the inorganic composition contributing to 30 % and 27 %, respectively, to the average total ion content. The strong correlations between these species (r2 = 0.87, p value: < 0.0001) suggest similar air mass origins. However, the average molar Cl-/Na+ ratio (0.85) is lower than the sea-salt one, reflecting a chloride depletion possibly associated with strong acids such as HNO3 and H2SO4. Additionally, the non-sea-salt fraction of sulfate varies between 38 % and 91 %, indicating the presence of other sources. Also, the presence of amino acids and for the first time in cloud waters of sugars clearly indicates that biological activities contribute to the cloud water chemical composition. A significant variability between events is observed in the dissolved organic content (25.5 ± 18.4 mg C L−1), with levels reaching up to 62 mg C L−1. This variability was not similar for all the measured compounds, suggesting the presence of dissimilar emission sources or production mechanisms. For that, a statistical analysis is performed based on back-trajectory calculations using the CAT (Computing Atmospheric Trajectory Tool) model associated with the land cover registry. These investigations reveal that air mass origins and microphysical variables do not fully explain the variability observed in cloud chemical composition, highlighting the complexity of emission sources, multiphasic transfer, and chemical processing in clouds. Even though a minor contribution of VOCs (oxygenated and low-solubility VOCs) to the total dissolved organic carbon (DOC) (0.62 % and 0.06 %, respectively) has been observed, significant levels of biogenic VOC (20 to 180 nmol L−1) were detected in the aqueous phase, indicating the cloud-terrestrial vegetation exchange. Cloud scavenging of VOCs is assessed by measurements obtained in both the gas and aqueous phases and deduced experimental gas-/aqueous-phase partitioning was compared with Henry's law equilibrium to evaluate potential supersaturation or unsaturation conditions. The evaluation reveals the supersaturation of low-solubility VOCs from both natural and anthropogenic sources. Our results depict even higher supersaturation of terpenoids, evidencing a deviation from thermodynamically expected partitioning in the aqueous-phase chemistry in this highly impacted tropical area.

Toxic metal concentrations and Cu–Zn–Pb isotopic compositions in tires

Background Particles from non-exhaust emissions derived from traffic activities are a dominant cause of toxic metal pollution in urban environments. Recently, studies applying multiple isotope values using the Iso-source and positive matrix factorization (PMF) models have begun to be used as useful tools to evaluate the contribution of each pollution source in urban environments. However, data on the metal concentrations and isotopic compositions of each potential source are lacking. Therefore, this study presents data on toxic metals and Cu, Zn, and Pb isotopic compositions in tires, which are one of the important non-exhaust emission sources. Findings Among the toxic metals, Zn had the highest concentration in all tire samples, and the mean concentrations were in the order of Zn > Cu > Pb > Sn > Sb > Ni > Cr > As > Cd. Ni, Zn, Sn, and Sb had higher concentrations in domestic tires (South Korea), and the Cu, Cd, and Pb concentrations were relatively higher in imported tires. The mean values of δ65CuAE647, δ66ZnIRMM3702, and 206Pb/207Pb ranged from − 1.04 to − 0.22‰, − 0.09 to − 0.03‰, and 1.1242 to 1.1747, respectively. The concentrations and isotopic compositions of Cu and Pb in the tires showed large differences depending on the product and manufacturer. However, the differences in Zn concentration and δ66ZnIRMM3702 values were very small compared with those of Cu and Pb. The relationships of the Zn concentration and isotopic composition showed that domestic tires are clearly distinguishable from imported tires. Bi-plots of Cu, Zn, and Pb isotopic compositions indicated that tires can be clearly discriminated from natural-origin and other non-exhaust traffic emission sources. Conclusions The multi-isotope signatures of Cu, Zn, and Pb exhibited different isotopic values for other non-exhaust traffic emission sources than for tires, and application of the multi-isotope technique may be a powerful method for distinguishing and managing non-exhaust sources of metal contamination in urban environments.

Climate Changes and Atmospheric Pollution

The objective of this chapter is to present the central concepts, parameters, and methods for the monitoring of climate changes, with a focus on air pollution, and the possible global and regional impacts of climate changes as well. There are plant species used as bioindicators that have a high sensitivity or ability to accumulate environmental pollutants. Another method that this chapter will present is the use of receiver models that employ both mathematical and statistical approaches to quantify the individual contribution of a given number of emission sources in the composition of a sample. The data presented in this chapter will provide reliable bases and methodologies for environmental control, supporting the adoption of more restrictive policies.

Using satellites to uncover large methane emissions from landfills

As atmospheric methane concentrations increase at record pace, it is critical to identify individual emission sources with high potential for mitigation. Landfills are responsible for large methane emissions that can be readily abated but have been sparsely observed. Here we leverage the synergy between satellite instruments with different spatiotemporal coverage and resolution to detect and quantify emissions from individual landfill facilities. We use the global surveying Tropospheric Monitoring Instrument (TROPOMI) to identify large emission hot spots, and then zoom in with high-resolution target-mode observations from the GHGSat instrument suite to identify the responsible facilities and characterize their emissions. Using this ‘tip and cue’ approach, we detect and analyze strongly emitting landfills (3-29 t hr−1) in Buenos Aires (Argentina), Delhi (India), Lahore (Pakistan), and Mumbai (India). We find that city-level emissions are 1.6-2.8 times larger than reported in commonly used emission inventories and that the landfills contribute 5-47% of those emissions. Our work demonstrates how complementary satellites enable global detection, identification, and monitoring of methane super-emitters at the facility-level.

Long-Range Transport of Sulfur Dioxide Emissions From External Sources to Tehran

Large-scale emissions of sulfur dioxide (SO2) from the combustion of heavy fuel oils are deteriorating the air quality in Tehran and regularly causing complex atmospheric pollution situations and human health concerns. Our analysis of the long-term SO2 emission data in Tehran confirmed that the magnitude of local SO2 emission sources is not adequate to reach SO2 concentrations to their present levels. Tehran is predominantly affected by regional transport of SO2 from exterior sources further away located in Iraq, Saudi Arabia, and adjacent provinces neighboring Tehran. Approximately 80% of total SO2 emissions in Tehran were observed to have impacts from the external hotspots outside of Tehran. While local emission sources only contribute around 20% of the total SO2 emissions. Bivariate polar plots, k-mean cluster, pairwise polar correlation, and PSCF analysis provided evidence for the impact of large-scale transport of SO2 emissions from external locations from the west/northwest, north/northeast, and south/southwestern areas of the region. Further observations of these hotspot areas observed in our analysis with TROPOMI satellite data confirmed significant SO2 emissions resulting from the consumption of heavy fuel oils in thermal power plants and oil/gas refineries. Overall, the results suggested that the regulatory strategies for controlling local traffic emissions of SO2 in Tehran would not be beneficial for reducing public health exposures to SO2 in Tehran. Such improvements can be attained mainly by diminishing the emission sources located further away from Tehran.

Mercury isotopic compositions in fine particles and offshore surface seawater in a coastal area of East China: implications for Hg sources and atmospheric transformations

Isotopic compositions of Mercury (Hg) in atmospheric particles (HgPM) are probably the mixed results of emission sources and atmospheric processes. Here, we present Hg isotopic compositions in daily fine particles (PM2.5) collected from an industrial site (Chunxiao – CX) and a nearby mountain site (Daimeishan – DMS) in a coastal area of East China, and in surface seawater close to the industrial area, to reveal the influence of anthropogenic emission sources and atmospheric transformations on Hg isotopes. The PM2.5 samples displayed a significant spatial difference in δ202Hg. For the CX site, the negative δ202Hg values are similar to those of source materials, and the HgPM contents were well correlated with chemical tracers, indicating the dominant contributions of local industrial activities to HgPM2.5, whereas the observed positive δ202Hg at the DMS site was likely associated with regional emissions and extended atmospheric processes during transport. The Δ199Hg values in PM2.5 from the CX and DMS sites were comparably positive. The unity slope of Δ199Hg versus Δ201Hg over all data suggests that the odd mass independent fractionation (MIF) of HgPM2.5 was primarily induced by the photoreduction of Hg2+ in aerosols. The positive Δ200Hg values with a minor spatial difference were probably associated with the photooxidation of Hg0, which is generally enhanced in the coastal environment. Total Hg in offshore surface seawater was characterized by negative δ202Hg and near-zero Δ199Hg and Δ200Hg values, which are indistinguishable from Hg isotopes of source materials. Overall, the PM2.5 collected from industrial areas had comparable δ202Hg values but more positive Δ199Hg and Δ200Hg as compared to surface seawater. The results indicate that atmospheric transformations would induce the significant fractionation of Hg isotopes and obscure the Hg isotopic signatures of anthropogenic emissions.

Reduced-complexity air quality intervention modeling over China: the development of InMAPv1.6.1-China and a comparison with CMAQv5.2

This paper presents the first development and evaluation of a reduced-complexity air quality model for China. In this study, the reduced-complexity Intervention Model for Air Pollution over China (InMAP-China) is developed by linking a regional air quality model, a reduced-complexity air quality model, an emission inventory database for China, and a health impact assessment model to rapidly estimate the air quality and health impacts of emission sources in China. The modeling system is applied over mainland China for 2017 under various emission scenarios. A comprehensive model evaluation is conducted by comparison against conventional Community Multiscale Air Quality (CMAQ) modeling system simulations and ground-based observations. We found that InMAP-China satisfactorily predicted total PM2.5 concentrations in terms of statistical performance. Compared with the observed PM2.5 concentrations, the mean bias (MB), normalized mean bias (NMB) and correlations of the total PM2.5 concentrations are −8.1 µg m−3, −18 % and 0.6, respectively. The statistical performance is considered to be satisfactory for a reduced-complexity air quality model and remains consistent with that evaluated in the USA. The underestimation of total PM2.5 concentrations was mainly caused by its composition, primary PM2.5. In terms of the ability to quantify source contributions of PM2.5 concentrations, InMAP-China presents similar results to those based on the CMAQ model, with variation mainly caused by the different treatment of secondary inorganic aerosols in the two models. Focusing on the health impacts, the annual PM2.5-related premature mortality estimated using InMAP-China in 2017 was 1.92 million, which was 250 000 deaths lower than estimated based on CMAQ simulations as a result of the underestimation of PM2.5 concentrations. This work presents a version of the reduced-complexity air quality model over China that provides a powerful tool to rapidly assess the air quality and health impacts associated with control policy and to quantify the source contribution attributable to many emission sources.