Sectoral price stabilization is critical in the pressing context of de-globalization and the climate crisis. Strategic price controls may be effective in reducing economic volatility, but fail to curb emissions, unlike quantity controls such as rationing consumption. In contrast, carbon pricing may accelerate decarbonization, but generate inflationary pressures. In order to evaluate the effectiveness of sector-oriented policies in stabilizing sectoral prices and accelerating the low-carbon transition at the same time, this paper employs a novel environmentally-extended, data-driven dynamic model of multi-sector growth based on the Bielefeld disequilibrium approach to the microeconomic stability of competitive economies. The general composite model allows to empirically characterize the network structure and intensity of dynamic price-quantity interactions at the sector level, which capture heterogeneous firm behavior by integrating long-run Walrasian price and classical quantity dynamics coupled with short-run Keynesian features in the form of target rate of return pricing and demand-led investment. A Bayesian hierarchical model on US BEA data empirically estimates the linear adjustment coefficients and stable combinations are computed. The US economy is shown to feature a highly hierarchical network structure of intermediate production that is particularly vulnerable to micro-economic shocks driven by wars and climate change. Tax-subsidy schemes are shown to be the most effective in stabilizing sectoral prices and economy-environment interactions.