Allocating provincial CO2 quotas for the Chinese national carbon program

In order to improve the efficiency of climate change initiatives China launched its national carbon market in December 2017. Initial CO2 quota allocations are a matter of significant concern. How should we allocate CO₂ emissions reduction responsibilities among Chinese provinces, assuming that provinces will not or cannot trade these responsibilities among themselves? In this paper, we allocate CO₂ quota from the perspective of cost minimisation. First, we estimate the national CO₂ marginal abatement cost (MAC) function and deduce the interprovincial MAC functions. Second, we build an allocation model with nonlinear programming for cost minimisation. Finally, we obtain the allocation results under the emissions reduction target by 2030. The results are as follows. (i) The national MAC was 134.3 Yuan/t (at the constant price of 1978) in 2011, with an overall upward trend from 1990 to 2011. (ii) The interprovincial MACs differ significantly and decline gradually from east to west. Hebei has the largest emissions reduction quota, and Shandong has the largest emissions quota by 2030. (iii) Compared with other criteria of per capita, gross domestic product (GDP), grandfathering and carbon intensity, the proposed approach is the most cost‐effective in achieving the reduction target, with cost savings of 37.7, 34.5, 47.9 and 33.87 per cent, respectively.     

Mathematical formulation and exact solution for landing location problem in tropical forest selective logging,a case study in Southeast Cameroon

In Central Africa, creating forest roads and skid trails is one of the most costly and environmentally damaging operations for the forest's ecosystem. An optimized road network is essential for reducing construction costs and improving the sustainable management of timber resources. The location of landings is vital in the development of a future forest road network. In this study, a binary integer programming model similar to the uncapacitated facility location problem is formulated to optimize the locations of the landings. The model is applied to selective logging in Central Africa and tested on an annual logging zone in Southeast Cameroon. The results are compared to that of manual road planning, the currently used method.     

Macroeconomics,finance, commodities: Interactions with carbon markets in a data-rich model

This article assesses the transmission of international shocks to EUA spot, EUA futures, and CER futures carbon prices using a broad dataset that includes 115 macroeconomic, financial and commodities indicators with daily frequency from April 4, 2008 to January 25, 2010 totalling 463 observations. The framework adopted is a Factor-Augmented Vector Autoregression model with latent factors extracted from the dataset, as proposed by Bernanke et al. (2005). The main results can be summarized as follows. First, based on impulse responses, we show that carbon prices tend to respond negatively (between ? 0.2 and ? 1.2 standard deviation) to an exogenous shock that reduces global economic indicators by one standard deviation. Second, we find evidence that the responses are heterogeneous among the different kinds of carbon prices: CER futures prices tend to react much more significantly than EUA spot and futures prices. Third, the factors explain about 50% of the total variance of all variables in the dataset. The largest contribution is accounted for by the factor correlated with commodities markets, which explains about 28% of the total variability.