Earth Systems

A renewed rise in global HCFC-141b emissions between 2017–2021

Authors' Summary: The production of ozone-destroying gases is being phased out. Even though production of one of the main ozone-depleting gases, called HCFC-141b, has been declining for many years, the amount that is being released to the atmosphere has been increasing since 2017. We do not know for sure why this is. A possible explanation is that HCFC-141b that was used to make insulating foams many years ago is only now escaping to the atmosphere, or a large part of its production is not being reported.

Abstract: Global emissions of the ozone-depleting gas HCFC-141b (1,1-dichloro-1-fluoroethane, CH3CCl2F) derived from measurements of atmospheric mole fractions increased between 2017 and 2021 despite a fall in reported production and consumption of HCFC-141b for dispersive uses. HCFC-141b is a controlled substance under the Montreal Protocol, and its phase-out is currently underway, after a peak in reported consumption and production in developing (Article 5) countries in 2013.

If reported production and consumption are correct, our study suggests that the 2017–2021 rise is due to an increase in emissions from the bank when appliances containing HCFC-141b reach the end of their life, or from production of HCFC-141b not reported for dispersive uses. Regional emissions have been estimated between 2017–2020 for all regions where measurements have sufficient sensitivity to emissions. This includes the regions of northwestern Europe, east Asia, the United States and Australia, where emissions decreased by a total of 2.3 ± 4.6 Gg yr−1, compared to a mean global increase of 3.0 ± 1.2 Gg yr−1 over the same period. Collectively these regions only account for around 30 % of global emissions in 2020. We are not able to pinpoint the source regions or specific activities responsible for the recent global emission rise.

Large mitigation potential of smoke PM2.5 in the US from human-initiated fires

Abstract: Increasing fire activity and the associated degradation in air quality in the United States has been indirectly linked to human activity via climate change. In addition, direct attribution of fires to human activities may provide opportunities for near term smoke mitigation by focusing policy, management, and funding efforts on particular ignition sources.

We analyze how fires associated with human ignitions (agricultural fires and human-initiated wildfires) impact fire particulate matter under 2.5 microns (PM2.5) concentrations in the contiguous United States (CONUS) from 2003 to 2018. We find that these agricultural and human-initiated wildfires dominate fire PM2.5 in both a high fire and human ignition year (2018) and low fire and human ignition year (2003). Smoke from these human levers also makes meaningful contributions to total PM2.5 (~5-10% in 2003 and 2018). Across CONUS, these two human ignition processes account for more than 80% of the population-weighted exposure and premature deaths associated with fire PM2.5.

These findings indicate that a large portion of the smoke exposure and impacts in CONUS are from fires ignited by human activities with large mitigation potential that could be the focus of future management choices and policymaking.

Assessing the role of top-down techniques for improving regional estimates of artisanal and small-scale gold mining mercury emissions

Abstract: ASGM is the world’s largest source of anthropogenic Hg emissions and is common in Latin America, Sub-Saharan Africa, South Asia, and East Asia. However, the amount of mercury emitted from ASGM and contributing to global mercury emissions is subject to substantial uncertainty. Bottom-up studies have quantified sources of Hg, including ASGM, using data on underlying activities to estimate regional and global totals. In contrast, top-down studies have used atmospheric concentration measurements and models to constrain Hg emissions. However, no top-down estimates have yet been calculated for ASGM emissions.

With GEOS-Chem’s global-scale chemical transport model for Hg, we investigate whether and how ASGM-related Hg emissions can be quantified from existing regional measurement sites for gaseous elemental mercury (GEM). By combining our top-down method with existing bottom-up data, we improve estimates of Hg emissions from ASGM activities, using Peru and the Madre de Dios region of South America as case studies.

We find that quantitative constraints on ASGM emissions are better provided by information on the shape of the probability distribution of GEM concentrations, such as the interquartile range and the 95% range, suggesting possible design guidelines for monitoring networks. The model-based analysis offers insights into improving regional estimates of ASGM emissions.

When private governance impedes multilateralism: The case of international pesticide governance

Abstract: Private standards play an increasingly important governance role, yet their effects on state-led policymaking remain understudied.

We examine how the operation of private agricultural standards influences multilateral pesticide governance with a particular focus on the listing of substances under the Rotterdam Convention on the Prior Informed Consent Procedure for Certain Hazardous Chemicals and Pesticides in International Trade, a treaty-based information-sharing mechanism that allows countries to refuse hazardous chemical imports.

We find that private agricultural standard-setting bodies use the Rotterdam Convention's pesticide list to develop their own lists of banned substances. This alters the Rotterdam Convention's intended role, impeding efforts to add substances to the treaty, as attempts by private actors to impose stricter governance than state actors can undermine the potential for international state-based governance to become more stringent. We characterize this as a “confounding interaction” whereby institutional linkages between actions by public and private actors with broadly aligned goals results in unexpected negative consequences for governance.

Statistical and machine learning methods for evaluating trends in air quality under changing meteorological conditions

Abstract: Evaluating the influence of anthropogenic-emission changes on air quality requires accounting for the influence of meteorological variability. Statistical methods such as multiple linear regression (MLR) models with basic meteorological variables are often used to remove meteorological variability and estimate trends in measured pollutant concentrations attributable to emission changes. However, the ability of these widely used statistical approaches to correct for meteorological variability remains unknown, limiting their usefulness in the real-world policy evaluations.

Here, we quantify the performance of MLR and other quantitative methods using simulations from a chemical transport model, GEOS-Chem, as a synthetic dataset. Focusing on the impacts of anthropogenic-emission changes in the US (2011 to 2017) and China (2013 to 2017) on PM2.5 and O3, we show that widely used regression methods do not perform well in correcting for meteorological variability and identifying long-term trends in ambient pollution related to changes in emissions.

The estimation errors, characterized as the differences between meteorology-corrected trends and emission-driven trends under constant meteorology scenarios, can be reduced by 30 %–42 % using a random forest model that incorporates both local- and regional-scale meteorological features. We further design a correction method based on GEOS-Chem simulations with constant-emission input and quantify the degree to which anthropogenic emissions and meteorological influences are inseparable, due to their process-based interactions. We conclude by providing recommendations for evaluating the impacts of anthropogenic-emission changes on air quality using statistical approaches.

What are the likely changes in mercury concentration in the Arctic atmosphere and ocean under future emissions scenarios?

Authors' Highlights: 

• Arctic mercury concentrations respond to changes in emissions and environmental change.

• Modeling shows rapid mercury deposition decline with aggressive reduction measures.

• Delaying action will limit the impact of mercury emission reduction measures.
 
• Until 2050, mercury emissions influence ocean mercury concentrations more than environmental change scenarios.
 
• There is a need for prompt and ambitious action to reduce mercury concentrations in the Arctic.

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