Climate change and air pollution are arguably two most pressing environmental issues facing the world today. This talk gives an overview of recent studies relating the two at the decadal to multi-decadal time scale. The first part focusing on interactions will review recent works on how global warming affects aerosol distribution (Banks et al., 2021; Fiore et al., 2022), and in turn, how aerosols affect mean and extreme precipitation (Xu et al., 2022) and circulation changes (Diao and Xu, 2022), which could consequently impact air pollution itself (Wang et al., 2021), completing an intrinsic two-way feedback loop.

The second part will address the joint occurrence of heat extremes and air pollution, including haze (Xu et al., 2020) and ozone (Xiao et al., 2022), raising awareness of their broader impact on human health and crop yield. Some concluding thoughts are given on how to mitigate the near-term warming rates by achieving co-benefits of air quality improvement (Ocko et al., 2021), while avoiding the temporary shock of aerosol unmasking (Dreyfus et al., 2022). A novel yet simple integrated human-Earth modeling framework is introduced to further demonstrate the importance of cutting non-CO2 pollutants to stabilize global warming (Xu and Ramanathan, in review).

How to cite: Xu, Y.: Decadal trends of global climate and air pollution: two-way interactions, joint impacts and synergistic mitigation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4129, https://doi.org/10.5194/egusphere-egu24-4129, 2024.

Fine particulate matter (PM_2.5) pollution threatens human lives and wellbeing worldwide. Agricultural ammonia (NH₃) is a key precursor of PM_2.5. To examine how food consumption, production, and trade in different countries and regions affect global air quality, we derived a half-century (1962–2018) crop- and livestock-specific agricultural NH₃ emission inventory and used it to conduct numerical experiments with the GEOS-Chem chemical transport model to estimate the impacts of food production, consumption, and trade in nine major food-importing and food-exporting countries or regions (China, India, Japan, Russia, Argentina, Brazil, Canada, European Union, USA) on PM_2.5 pollution in themselves and in other countries via both atmospheric transport and food trade. We further performed sensitivity experiments by deducting NH₃ emissions related to different food items that are consumed domestically vs. exported for each major country or region. We found that the rise in domestic food and feed crop consumption contribute significantly to PM_2.5 pollution in China and India (up to ~40% of the total PM_2.5 increase from all sources), among which ~40% is driven by meat production and consumption, highlighting the environmental impacts of dietary changes. We also found that even though China and India consume substantial amount of food imported from other countries, it is not a major contributor to PM_2.5pollution in the exporting countries (e.g., ~1% of total PM_2.5 in the food trading partners), mostly because the majority of domestic food demand is still satisfied by domestic production, and food import is diversified among a basket of exporting countries. Furthermore, agricultural NH₃ is found to have a crucial modulating influence on PM_2.5; e.g., the increase in PM_2.5 due to agricultural NH₃ could partly offset the decrease in PM_2.5 induced by other anthropogenic emissions in North America after 1990, and such a phenomenon is expected for China as significant controls of non-agricultural emissions are underway. Our study highlights the significance of food consumption, production and trade in shaping PM_2.5 worldwide, and it is important to incorporate sustainable food-system and agricultural strategies to simultaneously safeguard food security as well as the health of citizens and our planet.

How to cite: Tai, A. and Wong, A.: Effects of historical food production, consumption and trade on agricultural ammonia emissions and fine particulate matter (PM2.5) pollution worldwide: Implications for food-system mitigation strategies for a sustainable future, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14068, https://doi.org/10.5194/egusphere-egu24-14068, 2024.

In recent decades, growing urbanization and rapid land use changes have been important components of current development, affecting environmental dynamics, particularly air quality. Over 80% of city people may be exposed to levels of pollution that exceed WHO standards (WHO 2016). Previous research focused solely on the relationship between built-up space and particulate matter (PM), with no concern for future scenarios. This study explores the potential impact of land use change on air quality using a detailed scenario-based technique. The air pollutant data for 2022 was principally gathered from five distinct land uses, whereas previous years (2010 to 2021) were received from the Central Pollution Control Board. In a supervised classification technique, a Maximum Likelihood Classifier is utilized to analyze the LULC of 2010, 2016, and 2022 in Kharagpur, a rising industrial town and the fourth-largest city in West Bengal. The analysis shows a strong 20.62 percent rise in urban areas, particularly in the eastern region, from 2010 to 2022, comprising residential, commercial, and industrial zones. Between 2010 and 2022, there is an 11.23 percent loss in vegetative areas, a 9.29 percent decrease in agricultural land, and a 0.10 percent decrease in aquatic bodies. Further spatiotemporal analysis reveals that areas with low urban density had the lowest amounts of air pollution, with an overall Air Quality Index (AQI) in the "excellent" range (0-50). Industrial land use contributes 74.37 percent to air pollution, followed by densely populated urban regions, which have a 47.62 percent higher AQI than low-density zones. Furthermore, the vehicular corridor has a 33.49 percent higher AQI than low-density places. According to the data, the most significant pollutants leading to AQI variance are PM2.5 and PM10. A correlation study emphasizes the effect of land use changes on air quality since PM10 was followed by overall AQI is positively related to built-up areas and negatively related to vegetation and water bodies. It suggests that fast urbanization may damage air quality, but vegetation and waterbodies might improve air quality and lower AQI. Polluted air has a negative impact on human health, agricultural production, and numerous ecosystems, putting future urban growth at risk. It is therefore critical to assess future land use changes in order to predict future air quality settings and take preventive efforts to mitigate air pollution. To compare future air quality settings to a baseline, two scenarios for LULC prediction are examined: business as usual (BUA) and sustainable development (SD). These scenarios can help determine future urban development paths, as well as land use planning and policy-level action to improve air quality.

Keywords: Land Use change, Air quality, Time series forecasting, CA-ANN, Scenario-based Analysis, Kharagpur.

How to cite: Sarkar, T., Gautam, A., Behera, M. D., and Aithal, B. H.: Scenario-based Assessment of Land Use Change on Air Quality, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1386, https://doi.org/10.5194/egusphere-egu24-1386, 2024.

As greenhouse gases and air pollutants are often co-emitted, the co-benefits on air quality improvement arising from implementing low-carbon policies are drawing much attention. Here we focus our research on the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in south-eastern China, the demonstration zone for air pollution prevention and control initiatives of China, while still contending with severe ozone pollution, particularly in autumn. This study assesses whether China’s ‘Dual-Carbon’ targets contribute to the GBA achieving the national ozone control goals and offers corresponding mitigation strategies. We developed an external module to softly couple an integrated assessment model IMEDCGE (Integrated Model of Energy, Environment, and Economy for Sustainable Development, Computable General Equilibrium) with the WRF-Chem atmospheric chemistry transport model. The fusion allows us to project the regional ozone pollution evolutions from the base year (2015) to 2050 under various future scenarios. We explore three anthropogenic emission reduction pathways, each reflecting different levels in climate change mitigation targets and end-of-pipe control policies, resulting in varied ozone precursor reduction patterns. The results show that implementing China’s ‘Dual-Carbon’ policies, combined with stringent end-of-pipe control measures, will substantially decrease the averaged MDA8 surface ozone across the GBA to below 90 μg m^-3 by 2050. However, different ozone concentration trends emerge between the southern and northern regions due to spatial variations in ozone chemical regimes, as indicated by H₂O₂/HNO₃ ratios. Overall, NO_x emission reduction will become increasingly effective in curbing ozone pollution till 2050, while NMVOCs emission reduction, driven by strict end-of-pipe control policies, plays a pivotal role in the short term (before 2030). Even under the most ideal scenario, where more than 90% of local anthropogenic NO_x and 85% of NMVOCs emissions are eliminated, our findings underscore the imperative of coordinated efforts across all sectors and collaborative emission reduction beyond the GBA to mitigate ozone pollution effectively.

How to cite: Li, D., Ye, X., Zhang, L., Liu, X., Guo, C., Wu, K., and Dai, H.: Ozone pollution mitigation under China’s ‘Dual-Carbon’ scenario over the Guangdong-Hong Kong-Macao Greater Bay Area, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14477, https://doi.org/10.5194/egusphere-egu24-14477, 2024.

In 2021, the World Health Organization (WHO) introduced for the first time the standard for the peak season ozone (six-month mean MDA8 ozone) of no more than 60 μg m^-3. Typically, the warm season from April to October is often considered as the peak ozone season. However, the highly polluted North China saw the prolonged ozone pollution season based the national surface network measurement, which is threatening public health and the mitigation of PM2.5 pollution. In order to accurately quantify the risk of this ozone season exposure, here this study proposes some methods to quantitatively characterize the active ozone photochemistry season based on the Ox (NO2+O3) and ozone-temperature relationship. Firstly, we found that the active ozone photochemistry season has extended by about four weeks in the course of fast emission reductions from 2014-2022. Then, combined with atmospheric chemical modeling and future SSP scenarios, it is found that deep emission reductions and climate warming will significantly increase the length of peak ozone season over the North China Plain.

How to cite: Li, K. and Liao, H.: Future prolonged ozone pollution season over the North China Plain driven by emission reductions and climate change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5923, https://doi.org/10.5194/egusphere-egu24-5923, 2024.

Natural wetlands account for one-third of global methane (CH₄) emissions and so profoundly influence climate. However, existing estimates of future changes in CH₄ usually neglect feedbacks associated with global biogeochemical cycles. Here, we employ data-driven approaches to estimate both current and future wetland emissions that consider the effects of changing meteorology and biogeochemical feedbacks arising from sulfate deposition and CO₂ fertilization. We report intensified wetland emissions from 2000-2100, with biogeochemical effects explaining 30% of emissions growth by 2100. Our results suggest that 8-15% more aggressive cuts to anthropogenic methane emissions are needed if we are to stay within the Paris Agreement guardrails of 1.5°C warming.

How to cite: Shen, L., Peng, S., Zhang, Z., Tong, C., Lin, J., Li, Y., Zhong, H., Ma, S., Zhuang, M., and Gauci, V.: Biogeochemical feedback effects on future wetland methane emissions and implications for global mitigation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4267, https://doi.org/10.5194/egusphere-egu24-4267, 2024.

Biomass burning is an important source of aerosol emissions that greatly deteriorates air quality near the source and downwind regions. More importantly, large amounts of greenhouse gases (GHGs) such as carbon dioxide (CO2) and methane (CH4) are emitted from wildfires. A quantitative estimate of emissions from biomass burning is vital to understand the fire impacts on climate, weather, environment and public health because wildfires are projected to increase in frequency, severity, and extent in the warming climate. As one of the major climate drivers but with relatively short lifetime in the atmosphere, CH4 is an attractive mitigation target to restrict the pace of global warming. The estimation of spatially and temporally resolved CH4 emissions from the biomass burning sector provides critical information in developing measurement-informed CH4 inventories and assessing mitigation strategies and policy decision making. Satellite observations of fire radiative power is one pathway to investigate wildfires around the world. The Global Biomass Burning Emissions Product (GBBEPx) algorithm is employed to estimate long-term temporal variation and geographic distribution of CH4 emissions using satellite observations from Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Suomi NPP and NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS). Globally, about 23 teragrams of CH4 are emitted from biomass burning every year, with nearly 49% of it released from Africa alone. We will present inter-annual variability of CH4 emissions and describe the magnitude of emissions from notable big fires such as the 2020 gigafire in California and 2023 Canadian fires, to compare and contrast emissions from biomass burning source sector versus various anthropogenic sources.

How to cite: Kondragunta, S. and Zhu, A.: Methane Emissions from Wildfires: Trends and Anomalies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20492, https://doi.org/10.5194/egusphere-egu24-20492, 2024.

Accurate quantification of methane emissions is critical for setting and tracking the mitigation goals. However, previously estimated anthropogenic methane emissions in China differ by up to 50% among different studies. Satellite observations are expected to reduce the uncertainty, but large discrepancies still exist in earlier quantifications. Here, using satellite observations from the blended TROPOMI+GOSAT product, we conducted an ensemble of high-resolution (~50 km) inversions to assess the sources of uncertainty in the quantification. Overall, satellite observations can provide robust constraints on China’s total emissions but are less effective in quantifying individual sources with lower emission magnitudes. Of all sectors, emissions from coal mines and livestock can be well constrained due to frequent satellite observations, higher emission magnitudes, and lower prior uncertainty. Furthermore, we constructed marginal cost curves for emission reductions from each source to better inform future mitigation measures.

How to cite: Zhong, H., Shen, L., and Qu, M.: Unraveling the sources of uncertainty in China's top-down methane emission estimates, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4953, https://doi.org/10.5194/egusphere-egu24-4953, 2024.