The “cost of carbon” is a political regulatory construct. It is not something that can be measured. It is not a metric. Arbitrarily manipulating prices by instituting a carbon tax to raise the cost of carbon sounds like a good idea at first. But upon closer examination such a decision based on a singular focus (carbon tax) has not yielded expected results.
Some advocacy groups go further and say supporting a “carbon tax” is leadership. But as in this case it would “leadership” in the wrong direction. A different approach is needed to achieve sustainable communities and cities.
“For some time now, a small but vocal group of writers have tried to convince the base of libertarians and conservatives that a carbon tax is actually consistent with their principles. Although I disagree with their arguments, I’m happy to have such a debate, as I think the case against a carbon tax is very strong. ” click here
Posted in Economics
“Climate policies will continue to shape the global energy system,” the national security strategy states. “U.S. leadership is indispensable to countering an anti-growth, energy agenda that is detrimental to U.S. economic and energy security interests. Given future global energy demand, much of the developing world will require fossil fuels, as well as other forms of energy, to power their economies and lift their people out of poverty.” click here
This threat by Moody’s (here) is nonsense. It’s time to move on and rely on a different agency that can demonstrate integrity and honesty.
This study is an exercise in statistical manipulation that distorts reality. Many factors affect productivity such that any correlation between TFP and atmospheric temperature is inconclusive. A correlation even if present is not indicative of causation or even that one is the “primary driver” of the other.
Peng Zhang, Olivier Deschenes, Kyle Meng, Junjie Zhang. Temperature effects on productivity and factor reallocation: Evidence from a half million chinese manufacturing plants. Journal of Environmental Economics and Management Volume 88, March 2018, Pages 1-17
This paper uses detailed production data from a half million Chinese manufacturing plants over 1998–2007 to estimate the effects of temperature on firm-level total factor productivity (TFP), factor inputs, and output. We detect an inverted U-shaped relationship between temperature and TFP and show that it primarily drives the temperature-output effect. Both labor- and capital- intensive firms exhibit sensitivity to high temperatures. By mid 21st century, if no additional adaptation were to occur, we project that climate change will reduce Chinese manufacturing output annually by 12%, equivalent to a loss of $39.5 billion in 2007 dollars. This implies substantial local and global economic consequences as the Chinese manufacturing sector produces 32% of national GDP and supplies 12% of global exports.
California’s cap and trade approach is simply not sustainable. It’s like shooting yourself in the foot.
“A small group of California Republican legislators are reversing their opposition to AB 32 — the “Global Warming Solutions Act” — and embracing California’s controversial climate change policies.” click here
Capitanescu F, Rege S, Marvuglia A, Benetto E, Ahmadi A, Gutiérrez TN, Tiruta-Barna L. Cost versus life cycle assessment-based environmental impact optimization of drinking water production plants. Journal of environmental management 2016 Apr 21;177:278-287. doi: 10.1016/j.jenvman.2016.04.027.
Empowering decision makers with cost-effective solutions for reducing industrial processes environmental burden, at both design and operation stages, is nowadays a major worldwide concern. The paper addresses this issue for the sector of drinking water production plants (DWPPs), seeking for optimal solutions trading-off operation cost and life cycle assessment (LCA)-based environmental impact while satisfying outlet water quality criteria. This leads to a challenging bi-objective constrained optimization problem, which relies on a computationally expensive intricate process-modelling simulator of the DWPP and has to be solved with limited computational budget. Since mathematical programming methods are unusable in this case, the paper examines the performances in tackling these challenges of six off-the-shelf state-of-the-art global meta-heuristic optimization algorithms, suitable for such simulation-based optimization, namely Strength Pareto Evolutionary Algorithm (SPEA2), Non-dominated Sorting Genetic Algorithm (NSGA-II), Indicator-based Evolutionary Algorithm (IBEA), Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), Differential Evolution (DE), and Particle Swarm Optimization (PSO). The results of optimization reveal that good reduction in both operating cost and environmental impact of the DWPP can be obtained. Furthermore, NSGA-II outperforms the other competing algorithms while MOEA/D and DE perform unexpectedly poorly.