Dynamic nowcast of the New Zealand greenhouse gas inventory
Malcolm Jones Hannah Chorley Flynn Owen Tamsyn Hilder Holly Trowland Paul Bracewell
As efforts to mitigate the effects of climate change grow, reliable and
thorough reporting of greenhouse gas emissions are essential for measuring
progress towards international and domestic emissions reductions targets. New
Zealand's national emissions inventories are currently reported between 15 to
27 months out-of-date. We present a machine learning approach to nowcast
(dynamically estimate) national greenhouse gas emissions in New Zealand in
advance of the national emissions inventory's release, with just a two month
latency due to current data availability. Key findings include an estimated
0.2% decrease in national gross emissions since 2020 (as at July 2022). Our
study highlights the predictive power of a dynamic view of emissions intensive
activities. This methodology is a proof of concept that a machine learning
approach can make sub-annual estimates of national greenhouse gas emissions by
sector with a relatively low error that could be of value for policy makers.