Application of air quality combination forecasting to Bogota

The bulk of existing work on the statistical forecasting of air quality is based on either neural networks or linear regressions, which are both subject to important drawbacks. In particular, while neural networks are complicated and prone to in-sample overfitting, linear regressions are highly dependent on the specification of the regression function. The present paper shows how combining linear regression forecasts can be used to circumvent all of these problems. The usefulness of the proposed combination approach is verified using both Monte Carlo simulation and an extensive application to air quality in Bogota, one of the largest and most polluted cities in Latin America. © 2014 Elsevier Ltd.

Methods to prioritise adaptation options for iconic seabirds and marine mammals impacted by climate change

Climate change is already impacting a wide range of marine species around Australia. Australia has a large number of marine mammals and seabirds, particularly when Australian Antarctic and Southern Ocean species are included: 110 species of seabird and 52 species of marine mammal. These iconic species are protected throughout Australia and in some cases are recovering from previous anthropogenic impacts including harvest. The first tool we developed is a simple 'cost-benefit- risk' (CBR) screening tool to evaluate each scenario-specific adaptation option against a number of semi-quantitative attributes. Awareness and identification of potentially contested options would be useful to managers charged with implementing adaptation options. Following on from specific application, testing some of the adaptation options in limited field trials would be a useful next step, further building the experience of researchers and managers charged with securing the status of these iconic species in the future.

Designer policy for carbon and biodiversity co-benefits under global change

Carbon payments can help mitigate both climate change and biodiversity decline through the reforestation of agricultural land. However, to achieve biodiversity co-benefits, carbon payments often require support from other policy mechanisms such as regulation, targeting, and complementary incentives. We evaluated 14 policy mechanisms for supplying carbon and biodiversity co-benefits through reforestation of carbon plantings (CP) and environmental plantings (EP) in Australia's 85.3 Mha agricultural land under global change. The reference policy - uniform payments (bidders are paid the same price) with land-use competition (both CP and EP eligible for payments), targeting carbon - achieved significant carbon sequestration but negligible biodiversity co-benefits. Land-use regulation (only EP eligible) and two additional incentives complementing the reference policy (biodiversity premium, carbon levy) increased biodiversity co-benefits, but mostly inefficiently. Discriminatory payments (bidders are paid their bid price) with land-use competition were efficient, and with multifunctional targeting of both carbon and biodiversity co-benefits increased the biodiversity co-benefits almost 100-fold. Our findings were robust to uncertainty in global outlook, and to key agricultural productivity and land-use adoption assumptions. The results suggest clear policy directions, but careful mechanism design will be key to realising these efficiencies in practice. Choices remain for society about the amount of carbon and biodiversity co-benefits desired, and the price it is prepared to pay for them.