Description: National commitments under the Paris Agreement on climate change interact with other global environmental objectives, such as those of the Minamata Convention on Mercury. We assess how mercury emissions and deposition reductions from national climate policy in China under the Paris Agreement could contribute to the country's commitments under the Minamata Convention. We examine emissions under climate policy scenarios developed using a computable general equilibrium model of China's economy, end-of-pipe control scenarios that meet China's commitments under the Minamata Convention, and these policies in combination, and evaluate deposition using a global atmospheric transport model. We find climate policy in China can provide mercury benefits when implemented with Minamata policy, achieving in the year 2030 approximately 5\% additional reduction in mercury emissions and deposition in China when climate policy achieves a 5% reduction per year in carbon intensity (CO2 emissions 9.7 Gt in 2030). This corresponds to 63 Mg additional mercury emissions reductions in 2030 when implemented with Minamata Convention policy, compared to Minamata policy implemented alone. Climate policy provides emissions reductions in sectors not considered under the Minamata Convention, such as residential combustion. This changes the combination of sectors that contribute to emissions reductions. This data submission includes scripts to project China's 2012 mercury emissions from the Emissions Database for Global Atmospheric Research (EDGAR) and prepare them for input to the global chemical transport model, GEOS-Chem. It also includes scripts to plot projected emissions and plot deposition results (with required raw results from GEOS-Chem) for the figures included in the Environmental Science and Technology article.

Description: This dataset contains a pollution flag in 1 min time resolution. It is derived by the pollution detection algorithm (PDA) based on the corrected particle number concentration data (doi:10.1594/PANGAEA.941886) measured during the year long MOSAiC expedition from October 2019 to September 2020. With pollution, we refer to emission from the exhaust of the ship stack, snow groomers, diesel generators, ship vents, helicopters and other. Pollution hence reflects locally emitted particles and trace gases, which are not representative of the central Arctic ambient concentrations. The PDA identifies and flags periods of polluted data in the particle number concentration dataset five steps. The first and most important step identifies polluted periods based on the gradient (time-derivative) of a concentration over time. If this gradient exceeds a given threshold, data are flagged as polluted. Further pollution identification steps are a simple concentration threshold filter, a neighboring points filter (optional), a median and a sparse data filter (optional). The detailed methodology of the derivation of the pollution flag is described in Beck et al. (2022). A description and download link to the used particle number concentration dataset can be found here: doi:10.1594/PANGAEA.941886. The code of the PDA can be found on Zenodo (Beck et al., 2021; doi:10.5281/zenodo.5761101). Participation of the Swiss Container was co-financed by the Swiss Polar Institute and University of Helsinki.