Emissions and Marine Boundary Layer Concentrations of Unregulated Chlorocarbons Measured at Cape Point, South Africa

Abstract

Unregulated chlorocarbons, here defined as dichloromethane (CH 2 Cl 2 ), perchloroethene (C 2 Cl 4 ), chloroform (CHCl 3 ), and methyl chloride (CH 3 Cl), are gases not regulated by the Montreal Protocol. While CH 3 Cl is the largest contributor of atmospheric chlorine, recent studies have shown that growth in emissions of the less abundant chlorocarbons could pose a significant threat to the recovery of the ozone layer. Despite this, there remain many regions for which no atmospheric monitoring exists, leaving gaps in our understanding of global emissions. Here, we report on a new time series of chlorocarbon measurements from Cape Point, South Africa for 2017, which represent the first published high-frequency measurements of these gases from Africa. For CH 2 Cl 2 and C 2 Cl 4 , the majority of mole fraction enhancements were observed from the north, consistent with anthropogenically modified air from Cape Town, while for CHCl 3 and CH 3 Cl, we found evidence for both oceanic and terrestrial sources. Using an inverse method, we estimated emissions for south-western South Africa (SWSA). For each chlorocarbon, SWSA accounted for less than 1% of global emissions. For CH 2 Cl 2 and C 2 Cl 4 , we extrapolated using population statistics and found South African emissions of 8.9 (7.4−10.4) Gg yr −1 and 0.80 (0.64−1.04) Gg yr −1 , respectively.

Large Methane Emission Fluxes Observed From Tropical Wetlands in Zambia

“…Model errors were sampled from a uniform distribution of 0–30 ppb. The inversion was solved using Markov Chain Monte Carlo simulations with a No‐U‐Turn sampler for emissions and boundary conditions, and a slice sampler for the model error hyperparameter (Say et al., 2020).…”

Rapid increase in dichloromethane emissions from China inferred through atmospheric observations

“…Nightlights (i.e. anthropogenic lighting observable from space during darkness) constitute an approximate representation of population and industrialization density and are therefore assumed to be a reasonable proxy for CH 2 Cl 2 emissions 55 . The underlying grid was aggregated into 150 basis functions using a quadtree algorithm 56 , determined by the a priori contribution of each region to the mole fraction enhancement.…”

“…To solve for the a posteriori parameters, a Markov Chain Monte-Carlo (MCMC) method was employed, following the approach of Say et al 55 . Each output parameter and hyperparameter was sampled from Markov chains of 2.5 × 10 5 steps, which were constructed by a two-step sampler, using a No-U-Turn sampler (NUTS) 59 for the emissions and boundary conditions, and a slice sampler 60 for the hyperparameters.…”

Estimates of North African Methane Emissions from 2010 to 2017 Using GOSAT Observations

“…The elements of the latent field containing emissions are a basis function representation of the NAME domain. We follow the approach of Say et al 29 and optimize 100 basis functions based on the a priori above-background mole fraction contribution in space using a quadtree algorithm. 34 The algorithm recursively divides the basis function into four new basis functions until the desired number of basis functions is achieved, giving a higher spatial resolution where there is a greater above-background a priori mole fraction contribution and lower elsewhere (Figure S6).…”

“…We infer the emissions and influence from the boundary conditions using hierarchical Bayesian inference . Sampling uses a two-stage sampler as in Say et al First, a No-U-Turn (NUTS) sampler samples the latent field x . A NUTS sampler is an extension to the Hamiltonian Monte Carlo, which has previously been used for inference of trace-gas emissions. , A slice sampler, which is computationally faster per iteration, samples the hyperparameter σ mod as a second step in the sampling process.…”