The influences of Yellow River input and nutrient dynamics on colloidal Fe migration in the Bohai Sea, China

The coupling relationship between the <1 kDa, 1-3 kDa, 3-10 kDa, 10-100 kDa, and 100 kDa-0.45 μm Fe fractions and the environmental factors in the Bohai Sea (BS) was investigated. The 1-100 kDa Fe in the surface water exhibited a non-conservative phenomenon during the river-sea mixing process, which was related to the removal of colloidal Fe via flocculation during this process. For the bottom water, the ligands released by the sediments may form additions to the <100 kDa Fe. The COC and DOC were mainly closely related to the behavior of the Fe in the bottom water. The <1 and 3-10 kDa Fe was mainly significantly positively correlated with the DOC, while the <100 kDa-0.45 μm Fe was significantly negatively correlated with the DOC. <100 kDa LMW colloidal Fe exhibited more synergistic behavior with easily absorbed ammonium salts.

Spatial distribution, compositional pattern, and source apportionment of colloidal trace metals in the coastal water of Shandong Peninsula, northeastern China

The Shandong Peninsula (SP) is the largest peninsula in China hosting rich economic and agricultural activities. In this study, we investigated the behavior of dissolved Mn, Fe, Cu, Zn, Cd, and Pb and their colloidal phases in the coastal and estuarine areas of SP. Pb and Zn had the highest contamination factors of 0.22-10.15 and 0.90-4.41, respectively. The <1 kDa accounted for 23-57 % of the total dissolved phase. Mn, Fe, Cu, Zn, Cd, and Pb were more likely to bind to 100 kDa-0.45 μm colloids (21-57 %). For colloidal Fe and Cu, the adsorption-release behavior had more significant effects on their dynamics. In contrast, the changes in colloidal Mn, Cd, and Pb were mainly controlled by the combined influence of temperature, dissolved oxygen, and microbial activity. However, the 1-3 kDa Zn exhibited a greater pH-dependent dispersion and was significantly positively correlated with it.

Estimation of pan-European, daily total, fine-mode and coarse-mode Aerosol Optical Depth at 0.1° resolution to facilitate air quality assessments

Aerosol Optical Depth (AOD) data derived from satellites is crucial for estimating spatially-resolved PM concentrations, but existing AOD data over land remain affected by several limitations (e.g., data gaps, coarser resolution, higher uncertainty or lack of size fraction data), which weakens the AOD-PM relationship. We developed a 0.1° resolution daily AOD data set over Europe over the period 2003-2020, based on two-stage Quantile Machine Learning (QML) frameworks. Our approach first fills gaps in satellite AOD data and then constructs three components' models to obtain reliable full-coverage AOD along with Fine-mode AOD (fAOD) and Coarse-mode AOD (cAOD). These models are based on AERONET (AErosol RObotic NETwork) observations, Gap-filled satellite AOD, climate and atmospheric composition reanalyses. Our QML AOD products exhibit better quality with an out-of-sample R2 equal to 0.68 for AOD, 0.66 for fAOD and 0.65 for cAOD, which is 23-92 %, 11-13 % and 115-132 % higher than the corresponding satellite or reanalysis products, respectively. Over 91.6 %, 81.6 %, and 88.9 % of QML AOD, fAOD and cAOD predictions fall within ±20 % Expected Error (EE) envelopes, respectively. Previous studies reported that a weak satellite AOD-PM correlation across Europe (Pearson correlation coefficient (PCC) around 0.1). Our QML products exhibit higher correlations with ground-level PMs, particularly when broadly matched by size: AOD with PM10, fAOD with PM2.5, cAOD with PM coarse (R = 0.41, 0.45 and 0.26, respectively). Different AOD fractions more effectively distinct PM size fractions, than total AOD. Our QML aerosol dataset and models pioneer full-coverage, daily high-resolution monitoring of fine-mode and coarse-mode aerosols, effectively addressing existing AOD challenges for further PMs exposures' estimations. This dataset opens avenues for more in-depth exploration of the impacts of aerosols on human health, climate, visibility, and biogeochemical processes, offering valuable insights for air quality management and environmental health risk assessment.

Major ions in Central European precipitation - Insight into changes in NO3-/SO42-, NH4+/NO3- and NH4+/SO42- ratios over the last four decades

Knowledge of precipitation composition is important, among other things, to reveal changes in atmospheric chemistry. Here we present the long-term time trends in ratios of major ions in precipitation, namely nitrate to sulphate (NO3-/SO42-), ammonium to sulphate (NH4+/SO42-) and ammonium to nitrate (NH4+/NO3-). For this we explore the long-term time series recorded by the Czech Hydrometeorological Institute at eight monitoring sites situated in urban, rural and mountain regions of the Czech Republic between 1980 and 2020. To that end, we use innovative Bayesian inference with the Integrated Nested Laplace Approximation (INLA) computational method appropriate for investigating complicated large-scale data. Our results indicated: (i) increasing NO3-/SO42- ratio in precipitation over time and distinct seasonal behaviour with higher values in winter and lower values in summer, (ii) increasing NH4+/SO42- ratio in precipitation and distinct seasonal behaviour with higher values in summer and lower values in winter and (iii) relatively stable NH4+/NO3- ratio in precipitation with a mild recent increase and distinct seasonal behaviour with higher values in summer and lower values in winter. This behaviour pattern holds true for all the sites analysed, irrespective of their geographical position, altitude or environment. Though explored in detail rarely, the ion ratios are important to study as they reflect changes in atmospheric chemistry, mirroring changes in emissions and meteorology and suggesting changing impacts on ecosystems and the environment.

Effects of Anthropogenic and Natural Forcings on the Summer Temperature Variations in East Asia during the 20th Century

The effects of the emissions of anthropogenic greenhouse gases (GHGs), aerosols, and natural forcing on the summer-mean surface air temperature (TAS) in the East Asia (EA) land surface in the 20th century are analyzed using six-member coupled model inter-comparison project 5 (CMIP5) general circulation model (GCM) ensembles from five single-forcing simulations. The simulation with the observed GHG concentrations and aerosol emissions reproduces well the land-mean EA TAS trend characterized by warming periods in the early (1911–1940; P1) and late (1971–2000; P3) 20th century separated by a cooling period (1941–1970; P2). The warming in P1 is mainly due to the natural variability related to GHG increases and the long-term recovery from volcanic activities in late-19th/early-20th century. The cooling in P2 occurs as the combined cooling by anthropogenic aerosols and increased volcanic eruptions in the 1960s exceeds the warming by the GHG increases and the nonlinear interaction term. In P3, the combined warming by GHGs and the interaction term exceeds the cooling by anthropogenic aerosols to result in the warming. The SW forcing is not driving the TAS increase in P1/P3 as the shortwave (SW) forcing is heavily affected by the increased cloudiness and the longwave (LW) forcing dominates the SW forcing. The LW forcing to TAS cannot be separated from the LW response to TAS, preventing further analyses. The interaction among these forcing affects TAS via largely modifying the atmospheric water cycle, especially in P2 and P3. Key forcing terms on TAS such as the temperature advection related to large-scale circulation changes cannot be analyzed due to the lack of model data.

Comparison of aerosol and cloud condensation nuclei between wet and dry seasons in Guangzhou, southern China

Cloud condensation nuclei (CCN), condensation nuclei (CN) and aerosol chemical composition were measured simultaneously at an urban site of Guangzhou from July to August 2015 and in January 2016, and the seasonal variations of aerosol activated fractions (N_CCN/N_CN) as well as their relevant influence factors were further studied accordingly. N_CN is generally higher in winter (dry season), whereas N_CCN and N_CCN/N_CN are mostly higher in summer (wet season) instead. In particular, N_CCN and N_CCN/N_CN are much lower at smaller supersaturation levels (SS<0.2) in winter. In spite of similar diurnal variations for N_CCN and N_CN, N_CCN/N_CN indicates an opposite tendency, relatively lower at midday, dusk and before midnight. Other than the size of particles as well as their chemical composition, some other factors, such as mass, gas precursors, pollutant transportation, meteorological conditions, etc., also contribute to the variations of N_CCN and N_CCN/N_CN. Particles from the local source or local-oceanic combination source cast influence on CN and CCN significantly, while the pollutants originating from and crossing over distant polluted areas contribute largely to CCN/CN. N_CN and N_CCN are relatively higher under pollution-free conditions in summertime and polluted conditions in wintertime, but N_CCN/N_CN is just the opposite. On various polluted conditions, aerosol CCN activities are greatly discrepant between summer and winter, especially during mist or heavy haze periods. The results imply that anthropogenic pollutants exert critical impacts on aerosol CCN activation.

Long-range and regional transported size-resolved atmospheric aerosols during summertime in urban Shanghai

In this study, the concentrations of water soluble ions (WSI), organic carbon (OC), and elemental carbon (EC) of size-resolved (0.056-18μm) atmospheric aerosols were measured in July and August 2015 in Shanghai, China. Backward trajectory model and potential source contribution function (PSCF) model were used to identify the potential source distributions of size-resolved particles and PM_1.8-associated atmospheric inorganic and carbonaceous aerosols. The results showed that the average mass concentrations of PM_0.1, PM₁, and PM_1.8 were 21.21, 82.90, and 100.1μgm^-3 in July and 7.00, 29.21, and 35.10μgm^-3 in August, respectively, indicating that the particulate matter pollution was more serious in July than in August in this study due to the strong dependence of the aerosol species on the air mass origins. The trajectory cluster analysis revealed that the air masses originated from heavily industrialized areas including the Pearl River Delta (PRD) region, the Yangtze River Delta (YRD) region and the Beijing-Tianjin region were characterised with high OC and SO₄^2- loadings. The results of PSCF showed that the pollution in July was mainly influenced by long-range transport while it was mainly associated to local and intra-regional transport in August. Besides the contributions of anthropogenic sources from YRD and PRD region, ship emissions from the East China Sea also made a great contribution to the high loadings of PM_1.8 and PM_1.8-associated NO₃^-, NH₄⁺, and EC in July. SO₄^2- in Shanghai was dominantly ascribed to anthropogenic sources and the high PSCF values for PM_1.8-associated SO₄^2- observed in August was mainly due to the ship emissions of Shanghai port, such as Wusong port and Yangshan deep-water port. These results indicated that the particulate pollutants from long-range transported air masses and shipping made a significant contribution to Shanghai's air pollution.

Dust events and their influence on aerosol optical properties over Jaipur in Northwestern India

In this study, we systematically document the link between dust episodes and local scale regional aerosol optical properties over Jaipur located in the vicinity of Thar Desert in the northwestern state of Rajasthan. The seasonal variation of AOT(500 nm) (aerosol optical thickness) shows high values (0.51 ± 0.18) during pre-monsoon (dust dominant) season while low values (0.36 ± 0.14) are exhibited during winter. The Ångström wavelength exponent has been found to exhibit low value (<0.25) indicating relative dominance of coarse-mode particles during pre-monsoon season. The AOT increased from 0.36 (Aprilmean) to 0.575 (May-June(mean)). Consequently, volume concentration range increases from April through May-June followed by a sharp decline in July during the first active phase of the monsoon. Significantly high dust storms were observed over Jaipur as indicated by high values of single scattering albedo (SSA(440 nm) = 0.89, SSA(675 nm) = 0.95, SSA870 nm = 0.97, SSA(1,020 nm) = 0.976) than the previously reported values over IGP region sites. The larger SSA values (more scattering aerosol), especially at longer wavelengths, is due to the abundant dust loading, and is attributed to the measurement site's proximity to the Thar Desert. The mean and standard deviation in SSA and asymmetry parameter during pre-monsoon season over Jaipur is 0.938 ± 0.023 and 0.712 ± 0.017 at 675 nm wavelength, respectively. Back-trajectory air mass simulations suggest Thar Desert in northwestern India as the primary source of high aerosols dust loading over Jaipur region as well as contribution by long-range transport from the Arabian Peninsula and Middle East gulf regions, during pre-monsoon season.

Global air quality and climate

Emissions of air pollutants and their precursors determine regional air quality and can alter climate. Climate change can perturb the long-range transport, chemical processing, and local meteorology that influence air pollution. We review the implications of projected changes in methane (CH(4)), ozone precursors (O(3)), and aerosols for climate (expressed in terms of the radiative forcing metric or changes in global surface temperature) and hemispheric-to-continental scale air quality. Reducing the O(3) precursor CH(4) would slow near-term warming by decreasing both CH(4) and tropospheric O(3). Uncertainty remains as to the net climate forcing from anthropogenic nitrogen oxide (NO(x)) emissions, which increase tropospheric O(3) (warming) but also increase aerosols and decrease CH(4) (both cooling). Anthropogenic emissions of carbon monoxide (CO) and non-CH(4) volatile organic compounds (NMVOC) warm by increasing both O(3) and CH(4). Radiative impacts from secondary organic aerosols (SOA) are poorly understood. Black carbon emission controls, by reducing the absorption of sunlight in the atmosphere and on snow and ice, have the potential to slow near-term warming, but uncertainties in coincident emissions of reflective (cooling) aerosols and poorly constrained cloud indirect effects confound robust estimates of net climate impacts. Reducing sulfate and nitrate aerosols would improve air quality and lessen interference with the hydrologic cycle, but lead to warming. A holistic and balanced view is thus needed to assess how air pollution controls influence climate; a first step towards this goal involves estimating net climate impacts from individual emission sectors. Modeling and observational analyses suggest a warming climate degrades air quality (increasing surface O(3) and particulate matter) in many populated regions, including during pollution episodes. Prior Intergovernmental Panel on Climate Change (IPCC) scenarios (SRES) allowed unconstrained growth, whereas the Representative Concentration Pathway (RCP) scenarios assume uniformly an aggressive reduction, of air pollutant emissions. New estimates from the current generation of chemistry-climate models with RCP emissions thus project improved air quality over the next century relative to those using the IPCC SRES scenarios. These two sets of projections likely bracket possible futures. We find that uncertainty in emission-driven changes in air quality is generally greater than uncertainty in climate-driven changes. Confidence in air quality projections is limited by the reliability of anthropogenic emission trajectories and the uncertainties in regional climate responses, feedbacks with the terrestrial biosphere, and oxidation pathways affecting O(3) and SOA.