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Beijing suffers from poor air quality, particularly during wintertime haze episodes when concentrations of PM2.5 (particulate matter with a diameter 400 µg m−3. Black carbon (BC), an aerosol which strongly absorbs solar radiation, can make up to 10 % of PM2.5 in Beijing. BC is of interest due to its climatic and health impacts. BC has also been found to impact planetary boundary layer (PBL) meteorology. Through interacting with radiation and altering the thermal profile of the lower atmosphere, BC can either suppress or enhance PBL development depending on the properties and altitude of the BC layer. Previous research assessing the impact of BC on PBL meteorology has been investigated through the use of regional models, which are limited both by resolution and the chosen boundary layer schemes. In this work, we apply a high-resolution model (UCLALES-SALSA) that couples an aerosol and radiative transfer model with large-eddy simulation (LES) to quantify the impact of BC at different altitudes on PBL dynamics using conditions from a specific haze episode which occurred from 1–4 December 2016 in Beijing. Results presented in this paper quantify the heating rate of BC at various altitudes to be between 0.01 and 0.016 K/h per µg/m3 of BC, increasing with altitude but decreasing around PBL top. Through utilising a high-resolution model which explicitly calculates turbulent dynamics, this paper showcases the impact of BC on PBL dynamics both within and above the PBL. These results show that BC within the PBL increases maximum PBL height by 0.4 % but that the same loading of BC above the PBL can suppress PBL height by 6.5 %. Furthermore, when BC is present throughout the column, the impact of BC suppressing PBL development is further maximised, with BC causing a 17 % decrease in maximum PBL height compared to only scattering aerosols. Assessing the impact of these opposite effects, in this paper, we present a mechanism through which BC may play a prominent role in the intensity and longevity of Beijing's pollution episodes.

This review presents how the boreal and the tropical forests affect the atmosphere, its chemical composition, its function, and further how that affects the climate and, in return, the ecosystems through feedback processes. Observations from key tower sites standing out due to their long-term comprehensive observations: The Amazon Tall Tower Observatory in Central Amazonia, the Zotino Tall Tower Observatory in Siberia, and the Station to Measure Ecosystem-Atmosphere Relations at Hyytiala in Finland. The review is complemented by short-term observations from networks and large experiments. The review discusses atmospheric chemistry observations, aerosol formation and processing, physiochemical aerosol, and cloud condensation nuclei properties and finds surprising similarities and important differences in the two ecosystems. The aerosol concentrations and chemistry are similar, particularly concerning the main chemical components, both dominated by an organic fraction, while the boreal ecosystem has generally higher concentrations of inorganics, due to higher influence of long-range transported air pollution. The emissions of biogenic volatile organic compounds are dominated by isoprene and monoterpene in the tropical and boreal regions, respectively, being the main precursors of the organic aerosol fraction. Observations and modeling studies show that climate change and deforestation affect the ecosystems such that the carbon and hydrological cycles in Amazonia are changing to carbon neutrality and affect precipitation downwind. In Africa, the tropical forests are so far maintaining their carbon sink. It is urgent to better understand the interaction between these major ecosystems, the atmosphere, and climate, which calls for more observation sites, providing long-term data on water, carbon, and other biogeochemical cycles. This is essential in finding a sustainable balance between forest preservation and reforestation versus a potential increase in food production and biofuels, which are critical in maintaining ecosystem services and global climate stability. Reducing global warming and deforestation is vital for tropical forests.

Air pollution in urban environments has been shown to have a negative impact on air quality and human health, particularly in megacities. Over recent decades, Delhi, India, has suffered high atmospheric pollution, with significant particulate matter (PM) concentrations as a result of anthropogenic activities. Organic aerosols (OAs) are composed of thousands of different chemical species and are one of the main constituents of submicron particles. However, quantitative knowledge of OA composition, their sources and their processes in urban environments is still limited. This is important particularly in India, as Delhi is a massive, inhomogeneous conurbation, where we would expect the apportionment and concentrations to vary depending on where in Delhi the measurements/source apportionment is performed, indicating the need for multisite measurements. This study presents the first multisite analysis carried out in India over different seasons, with a focus on identifying OA sources. The measurements were taken during 2018 at two sites in Delhi, India. One site was located at the India Meteorological Department, New Delhi (ND). The other site was located at the Indira Gandhi Delhi Technical University for Women, Old Delhi (OD). Non-refractory submicron aerosol (NR-PM1) concentrations (ammonium, nitrate, sulfate, chloride and organic aerosols) of four aerosol mass spectrometers were analysed. Collocated measurements of volatile organic compounds, black carbon, NOx and CO were performed. Positive matrix factorisation (PMF) analysis was performed to separate the organic fraction, identifying a number of conventional factors: hydrocarbon-like OAs (HOAs) related to traffic emissions, biomass burning OAs (BBOAs), cooking OAs (COAs) and secondary OAs (SOAs). A composition-based estimate of PM1 is defined by combining black carbon (BC) and NR-PM1 (C-PM1= BC + NR-PM1). No significant difference was observed in C-PM1 concentrations between sites, OD (142 ± 117 µg m−3) compared to ND (123 ± 71 µg m3), from post-monsoon measurements. A wider variability was observed between seasons, where pre-monsoon and monsoon showed C-PM1 concentrations lower than 60 µg m−3. A seasonal variation in C-PM1 composition was observed; SO42- showed a high contribution over pre-monsoon and monsoon seasons, while NO3- and Cl− had a higher contribution in winter and post-monsoon. The main primary aerosol source was from traffic, which is consistent with the PMF analysis and Aethalometer model analysis. Thus, in order to reduce PM1 concentrations in Delhi through local emission controls, traffic emission control offers the greatest opportunity. PMF–aerosol mass spectrometer (AMS) mass spectra will help to improve future aerosol source apportionment studies. The information generated in this study increases our understanding of PM1 composition and OA sources in Delhi, India. Furthermore, the scientific findings provide significant information to strengthen legislation that aims to improve air quality in India.

Aromatic hydrocarbons are a class of volatile organic compounds associated with anthropogenic activity and make up a significant fraction of urban volatile organic compound (VOC) emissions that contribute to the formation of secondary organic aerosol (SOA). Benzene is one of the most abundant species emitted from vehicles, biomass burning and industry. An iodide time-of-flight chemical ionisation mass spectrometer (ToF-CIMS) and nitrate ToF-CIMS were deployed at the Jülich Plant Atmosphere Chamber as part of a series of experiments examining benzene oxidation by OH under high- and low-NOx conditions, where a range of organic oxidation products were detected. The nitrate scheme detects many oxidation products with high masses, ranging from intermediate volatile organic compounds (IVOCs) to extremely low volatile organic compounds (ELVOCs), including C12 dimers. In comparison, very few species with C≥6 and O≥8 were detected with the iodide scheme, which detected many more IVOCs and semi-volatile organic compounds (SVOCs) but very few ELVOCs and low volatile organic compounds (LVOCs). A total of 132 and 195 CHO and CHON oxidation products are detected by the iodide ToF-CIMS in the low- and high-NOx experiments respectively. Ring-breaking products make up the dominant fraction of detected signal and 21 and 26 of the products listed in the Master Chemical Mechanism (MCM) were detected. The time series of highly oxidised (O≥6) and ring-retaining oxidation products (C6 and double-bond equivalent = 4) equilibrate quickly, characterised by a square form profile, compared to MCM and ring-breaking products which increase throughout oxidation, exhibiting sawtooth profiles. Under low-NOx conditions, all CHO formulae attributed to radical termination reactions of first-generation benzene products, and first-generation auto-oxidation products are observed. Several N-containing species that are either first-generation benzene products or first-generation auto-oxidation products are also observed under high-NOx conditions. Hierarchical cluster analysis finds four clusters, of which two describe photo-oxidation. Cluster 2 shows a negative dependency on the NO2/NOx ratio, indicating it is sensitive to NO concentration and thus likely to contain NO addition products and alkoxy-derived termination products. This cluster has the highest average carbon oxidation state (OSC‾) and the lowest average carbon number. Where nitrogen is present in a cluster member of cluster 2, the oxygen number is even, as expected for alkoxy-derived products. In contrast, cluster 1 shows no dependency on the NO2/NOx ratio and so is likely to contain more NO2 addition and peroxy-derived termination products. This cluster contains fewer fragmented species, as the average carbon number is higher and OSC‾ lower than cluster 2, and more species with an odd number of oxygen atoms. This suggests that clustering of time series which have features pertaining to distinct chemical regimes, for example, NO2/NOx perturbations, coupled with a priori knowledge, can provide insight into identification of potential functionality.