Near-surface ozone pollution, associated with complex responses to changing precursor emissions and meteorological conditions, has become one of the biggest challenges in China’s air quality management. Here, we present the spatiotemporal evolution of ozone concentrations from 2010 to 2021 using measurements of the national air quality monitoring network. We evaluate the effectiveness of the national air pollution control programme, including Phase 1 (2013–2017) and Phase 2 (2018–2021), in reducing the ozone level over China, using an optimized machine learning approach, high-resolution emission estimates and an improved air quality model. We find that while emission changes in Phase 1 increased the ozone level over the five highly developed regions, further reductions of nitrogen oxide emissions in Phase 2 have generally constrained the ozone pollution. The changing effect of emission controls on ozone pollution is due to the shift in the prevailing regime for ozone formation and the weakened effects of aerosol declines, as emission reductions continue. We further find that current emission controls have been more effective in rural locales in four of the five regions, and more effective in summer than winter. Therefore, further control of ozone pollution should consider these regional and seasonal variations to identify the most important precursors for the pollution.

Fossil fuel and aerosol emissions have played important roles on climate over the Indian subcontinent over the last century. As the world transitions toward decarbonization in the next few decades, emissions pathways could have major impacts on India's climate and people. Pathways for future emissions are highly uncertain, particularly at present as countries recover from COVID-19. This paper explores a multimodel ensemble of Earth system models leveraging potential global emissions pathways following COVID-19 and the consequences for India's summertime (June-July-August-September) climate in the near- and long-term. We investigate specifically scenarios which envisage a fossil-based recovery, a strong renewable-based recovery and a moderate scenario in between the two. We find that near-term climate changes are dominated by natural climate variability, and thus likely independent of the emissions pathway. By 2050, pathway-induced spatial patterns in the seasonally-aggregated precipitation become clearer with a drying in the fossil-based scenario and wetting in the strong renewable scenario. Additionally, extreme temperature and precipitation events in India are expected to increase in magnitude and frequency regardless of the emissions scenario, though the spatial patterns of these changes as well as the extent of the change are pathway dependent. This study provides an important discussion on the impacts of emissions recover pathways following COVID-19 on India, a nation which is likely to be particularly susceptible to climate change over the coming decades.

China, the largest global CO2 emitter, recently announced ambitious targets for carbon neutrality by 2060. Its technical and economic feasibility is unclear given severe renewable integration barriers. Here, we developed a cross-sector, high-resolution assessment model to quantify optimal energy structures on provincial bases for different years. Hourly power system simulations for all provinces for a full year are incorporated on the basis of comprehensive grid data to quantify the renewable balancing costs. Results indicate that the conventional strategy of employing local wind, solar, and storage to realize 80% renewable penetration by 2050 would incur a formidable decarbonization cost of $27/ton despite lower levelized costs for renewables. Coordinated deployment of renewables, ultra-high-voltage transmissions, storages, Power-to-gas and slow-charging electric vehicles can reduce this carbon abatement cost to as low as $−25/ton. Were remaining emissions removed by carbon capture and sequestration technologies, achieving carbon neutrality could be not only feasible but also cost-competitive post 2050.

As the world’s largest CO₂ emitter, China’s ability to decarbonize its energy system strongly affects the prospect of achieving the 1.5 °C limit in global, average surface-temperature rise. Understanding technically feasible, cost-competitive, and grid-compatible solar photovoltaic (PV) power potentials spatiotemporally is critical for China’s future energy pathway. This study develops an integrated model to evaluate the spatiotemporal evolution of the technology-economic-grid PV potentials in China during 2020 to 2060 under the assumption of continued cost degression in line with the trends of the past decade. The model considers the spatialized technical constraints, up-to-date economic parameters, and dynamic hourly interactions with the power grid. In contrast to the PV production of 0.26 PWh in 2020, results suggest that China’s technical potential will increase from 99.2 PWh in 2020 to 146.1 PWh in 2060 along with technical advances, and the national average power price could decrease from 4.9 to 0.4 US cents/kWh during the same period. About 78.6% (79.7 PWh) of China’s technical potential will realize price parity to coal-fired power in 2021, with price parity achieved nationwide by 2023. The cost advantage of solar PV allows for coupling with storage to generate cost-competitive and grid-compatible electricity. The combined systems potentially could supply 7.2 PWh of grid-compatible electricity in 2060 to meet 43.2% of the country’s electricity demand at a price below 2.5 US cents/kWh. The findings highlight a crucial energy transition point, not only for China but for other countries, at which combined solar power and storage systems become a cheaper alternative to coal-fired electricity and a more grid-compatible option.