Megacities frequently suffer from poor air quality, with PM2.5 concentrations routinely exceeding WHO guidelines and elevating the risk of cardiovascular and respiratory disease. Air quality legislation typically targets primary emissions from traffic, a dominant urban source of PM₂.₅. Here, we present direct, chemically resolved quantification of PM₁ emissions from three contrasting megacity neighbourhoods—London, Beijing and Delhi—revealing the magnitude and diversity of urban sources by applying a novel source attribution approach to eddy-covariance flux measurements using aerosol mass spectrometry. In Delhi, traffic and combustion dominate primary PM₁ emissions. In contrast, cooking is the largest source during mealtimes in London and Beijing, contributing up to 83% of midday emissions and 87% in the early evening in London, and up to 61% and 76%, respectively, in Beijing. These findings suggest that air quality legislation in London and Beijing has effectively reduced non-refractory transport and combustion emissions, allowing cooking to emerge as the largest local source of primary non-refractory PM₁. Although cooking is not included in national, European or global emission inventories, recent estimates from the London Atmospheric Emissions Inventory align well with our observations. Together, these results show that the sources dominating primary non-refractory PM₁ emissions differ from those controlling ambient PM1 mass. Although cooking is now the leading primary source in London and Beijing, further reductions in urban PM₁ will depend on mitigating secondary formation processes.
Accurate greenhouse gas (GHG) inventories are essential for tracking climate mitigation. While many developed countries now publish comprehensive and timely emission inventories, developing countries still face data, time and resource constraints that hinder inventory development. This paper reviews the status of national and city-level GHG inventories in developing countries. We outline the main GHG accounting methods and examine their application in developing countries. We then assess the uneven geographic coverage of inventories at national and city scales and analyze the challenges faced in these contexts. Sparse city-level coverage across developing countries reflects gaps in basic activity data, a lack of locally specific emission factors and inconsistent accounting boundaries that limit comparability. Additionally, many existing inventories are outdated and insufficiently transparent, limiting their usefulness for policy design and evaluation. Emerging techniques such as machine-learning and atmospheric-science based approaches remain constrained by data limitations, observation coverage and limited knowhow. Inventory improvement in developing countries should prioritize routine core data collection, transparent documentation, targeted sectoral and facility-level detail, careful evaluation of non-state data products and task-specific use of advanced methods. Sustained institutional capacity and long-term data stewardship are therefore central to closing the inventory gaps.
The Afro-Asian summer monsoon precipitation sustains billions of people across the two continents, and its variability strongly affects water supply, irrigation, and drought-flood risks. While this variability has been linked to air-sea interactions, its connection with land-surface signals remains unclear. Using large-ensemble snow perturbation experiments and information flow causal analysis, we show that reduced Tibetan Plateau snow cover (TPS) contributes to a dipole pattern in Afro-Asian summer monsoon precipitation: positive anomalies over tropical Africa and negative anomalies over South Asia. This relationship is modulated by an accelerated tropical easterly jet (TEJ). Reduced TPS enhances thermal heating, exciting an upper-level anticyclonic anomaly. The easterly flow along its southern flank intensifies the TEJ, enhancing moisture transport toward tropical Africa and reinforcing the low-level anticyclonic anomaly over South Asia, resulting in a dipole precipitation pattern. Since 2006, TPS extent has stayed below 9% (a transition after which the TPS-TEJ coupling substantially weakens), raising uncertainty in future projections of Afro-Asian monsoon under continued warming and TPS loss.
Dimethyl sulfide (DMS) is a major natural source of marine cloud condensation nuclei (CCN), yet whether its variability leaves a detectable imprint on precipitation remains unclear. Using a new dataset of two decades of daily global DMS fields reconstructed from satellite observations, we found DMS–precipitation co-variability across extensive but regionally patchy ocean sectors. The dominance of the annual cycle indicates that much of the observed DMS–precipitation co-variability is embedded within large-scale climatic forcing common to both fields. While the sub-seasonal signal carries negligible power at these scales, interannual coherence is regionally confined. Removing the seasonal cycle makes this explicit: once field significance is enforced, annual coherence survives in key parts of the ocean. Those are the regions where DMS and precipitation seem to co-vary beyond their common seasonality. By identifying where and when coherence actually emerges, this study provides a quantifiable scale-resolved candidate diagnostic for evaluating marine aerosol–cloud interactions in Earth System Models, which we argue is the way forward to elucidate the physics of the problem.
