Standard assessment analyses of the three scenarios with well-defined economic instruments and focus on NA-P H-CB are reported in Section 5.1, while breakeven assessments of the two investment-based scenarios are reported in Section 5.2. Health-related shock values are given in Table 1 and imposed on the CGE model (together with efficiency gains, investment costs, and required demand constraints, see the Box above) to derive results for our analyses.
The economic impact of NA-P H-CB is analysed in the first sub-section, while wider macroeconomic impacts are analysed in the second sub-section. Results are presented in Table 2.
Economic impact of non-air pollution health co-benefits
NA-P H-CB effects, additional to those from air pollution, are particularly important for the active travel scenario. Increased physical activity, associated with increased walking and cycling, leads to significant estimated reductions in disease burdens for chronic diseases such as diabetes, Alzheimer’s disease, and depression with other notable contributions from ischaemic heart disease, cerebrovascular disease, and breast and bowel cancer. Among the health-related shocks (Table 1), the potential UK public sector deficit reduction (£15.0bn) is the net result of reduced health-system costs (£15.9bn) and higher social security transfers (£0.9bn) (increased pensions slightly outweigh reduced benefit payments to working age people). Combined with a larger effective labour force due to increased physical activity (95,000 person-years or 4,750 workers per year), this leads to an £18.9bn increase in GDP during 2011–30 (Table 2). These macroeconomic gains from NA-P H-CB are, together with efficiency gains from the internalized congestion externality, large enough to cover the gross GDP loss of the active travel scenario (See Fig. 1 below).
NA-P H-CB are less important for the two remaining healthy diet and household energy scenarios. The largest health co-benefits come with the introduction of healthy diets, where reduced animal source saturated fat intake (with substitution by plant source polyunsaturated fatty acids) may significantly lower the disease burden of ischaemic heart disease and lead to an estimated £4.7bn increase in GDP (Table 2). The household energy scenario has smaller health co-benefits, and results in a combined £450 m GDP gain. The latter estimate is on the low side as, for example, common mental disorder (depression) attributable to alleviation of winter indoor cold, was assumed to apply for only the first season. In general, our co-benefits estimates are conservative since benefits will continue to accumulate beyond our 20 year time horizon (due to the time lag between exposure change and health impact, which may be as much as 30–40 years for lung cancer risk).
Apart from the variation in economic impacts, there are wide differences in morbidity (YLDs) and mortality (YLLs) health co-benefits across scenarios (Table 1). These alternative welfare indicators show that morbidity effects are particularly important for the active travel scenario (30 % of total Disability Adjusted Life Years (DALYs), where DALYs = YLDs + YLLs), while mortality-effects are particularly important for the healthy diet scenario (>90 % of total DALYs). This is due to differences in modelled diseases. The active travel scenario (with a focus on increased physical activity) has a particularly strong impact on chronic diseases such as diabetes, Alzheimer’s disease, and depression, while the healthy diet scenario (with a focus on reduced intakes of saturated fat and cholesterol) mainly affects diseases for which periods of disability may be relatively short lived (e.g. a myocardial infarction in the case of ischaemic heart disease).
The relatively large numbers of DALYs saved in the healthy diet (and household energy) scenarios show that macroeconomic indicators cannot stand alone. This is further underlined by the impact of health co-benefits on GDP per capita which is (1) negative in the short and medium term for healthy diet, (2) negative in the medium and long term for household energy, and (3) positive for active travel (Table 2; lower part). The negative results for the former scenarios are not surprising since they reflect substantial increases in life expectancy. The highly welfare improving survival of large groups of people into old age turns into a welfare reduction measured by GDP per capita (since it increases the denominator in the GDP per capita calculation). Hence, this points to the need for a broader and more holistic assessment approach, which properly values welfare-improving health co-benefits with potentially negative economic repercussions (such as increased longevity).
Macroeconomic impact of UK GHG scenarios
Having detailed the positive macroeconomic impacts of NA-P H-CB, we now consider the wider macroeconomic effects of our three scenarios with well-defined economic instruments. Table 2 and Fig. 1 indicate that the healthy diet scenario is likely to be the most costly to implement. The scenario relies on demand-constraining mitigation and tax distortions which raise gross UK costs above £100bn over our 20 year time horizon, or £96bn net of health co-benefits. Technological mitigation in the household energy scenario is less costly with an estimated net welfare loss of around £25bn, while the active travel scenario (with internalization of a congestion externality and substantial health co-benefits) is close to being cost-neutral. In general, we find that mitigation scenarios will probably need to include efficiency-enhancing elements (either through internalisation of externalities or through introduction of new technologies) and significant health co-benefits in order to reduce societal costs and approach cost-effectiveness.
For the healthy diet scenario, a high food tax on animal products (26 % in 2030) is required to achieve the desired reduction in consumption of meat and dairy products (Table 2).Footnote 5 The large tax distortions and increasing survival of the population leads to substantial GDP per capita reductions: £77, £79 and £69 in the short, medium and long terms (Table 2). NA-P H-CB only cover 5 % of gross GDP losses (Fig. 1). The implementation of a food tax on animal products may allow the government to reduce household income tax rates by >0.6 %-points in the long term, but real household incomes are likely to be substantially reduced by lower factor returns (due to food tax distortions). National production of processed meat and dairy industries is reduced by >17 %, and lay-offs are likely to spill over into livestock and other processed food sectors (Fig. 2). At the same time, less closely related sectors such as extraction industries may benefit from reduced wages and increase production. This ‘leakage’ of carbon emissions emphasizes the need for economy-wide strategies to reduce total GHG emissions.
While the healthy diet scenario is likely to be quite costly by itself, it only represents one element of our food and agriculture strategy; the other element being the introduction of new abatement technologies such as improved efficiency of livestock farming, improved land use and manure management, and decreased dependence on fossil-fuel inputs (see annex B). Since these technological elements are not modelled, our overall GHG strategy for food and agriculture is likely to be much less costly. This is further supported by the fact that policy-induced shifts in preferences may substantially reduce societal costs by switching demand away from animal products towards consumption of high-yielding fruit and vegetable products.
In the active travel scenario, the demand-constraining intervention also creates distortions (due to the introduction of a road pricing tax). The resulting welfare loss is however balanced by the internalization of a congestion externality and by strong NA-P H-CB from increased walking and cycling. The analysis underscores that internalization of externalities and health co-benefits have the potential to balance significant societal costs of demand-constraining mitigation interventions. Overall, NA-P H-CB cover 38 % of gross GDP losses (£49bn) for the active travel scenario (Table 2; Fig. 1). NA-P H-CB therefore play a major part in eliminating net costs for the active travel scenario, and ensuring cost-effectiveness for our overall urban transport strategy (see discussion in Section 5.2).
A high road pricing tax (29 % in 2030) is required to achieve the desired reduction in urban motor vehicle transportation (Table 3). This may allow the government to reduce household income tax rates by >0.5 %-points in the long term, but tax distortions are likely to reduce factor returns and lower household income levels (similar to the food tax). The negative factor returns are reflected in declining GDP per capita over the short and medium terms: −£13 and −£8 (Table 2; upper part). However, GDP per capita becomes positive in the long term (+£10) due to rising health co-benefits (from reduced disease burdens of chronic diseases, mainly). At the sector level, reduced private transportation lowers domestic production of transport equipment and fossil fuels (Fig. 2), but re-allocation of demand again leads to leakages of GHG emissions to other production sectors.
The household energy scenario requires significant reallocation of investment to the construction sector and thereby crowds out investment which could be used productively elsewhere. By itself, crowding-out of productive investment leads to a £49bn GDP loss (Table 2). However, health co-benefits (£450 m) and energy efficiency gains (£24.4bn) cover around 50 % of gross society costs (Fig. 1). The recovery rate is expected to be much higher if account is taken of health and energy efficiency gains over the lifetime of the housing improvements, beyond 2030. Hence, the initial net costs of the UK household energy efficiency strategy will, in all likelihood, be eliminated over the very long term.Footnote 6
The GDP per capita effects of the household energy scenario are initially positive (£2) as relatively cheap insulation and ventilation investment in the initial phases yields proportionally high gains in efficiency (Table 2). In addition the mental health impacts of this scenario brings immediate gains to those affected, increasing healthcare savings and productive labour supply (but by relatively small amounts). In the medium and long terms, GDP per capita effects, however, become negative (−£20 and −£47 respectively) as efficiency measures with longer repayment periods are introduced (including solid wall insulation and glazing replacement).
We undertook multiple sensitivity analyses: instantaneous vs. staggered implementation, variation in discount rates, and variation in demand elasticities. The analyses indicate that GDP losses for the healthy diet scenario vary substantially with staggered policy implementation (−55 %), discount rates (up to −28 %), and demand elasticities (up to +38 %). Similarly, GDP losses for the household energy scenario vary substantially with discount rates (up to −42 %), and demand elasticities (up to +79 %). However, the qualitative nature of our results is unchanged. For the active travel scenario, NA-P H-CB continue to account for a major share of gross GDP losses, and the net GDP impact remains close to zero under all circumstances except for one specific sensitivity analysis: When UK urban fossil fuel-based private transportation is a luxury good, the active travel scenario becomes cost-effective (up to +4.1bn £). Hence, our sensitivity analyses confirms that NA-P H-CB play a key role in reducing net costs and ensuring cost-effectiveness for the active travel scenario.
The breakeven simulations of the two investment-based technological cleaner cars and household energy scenarios indicate that the introduction of efficiency-enhancing new technologies allows for substantial investment outlays. The household energy scenario remains cost-effective as long as investment costs are kept below £26bn; £142bn for the cleaner cars scenario. The results also suggest that NA-P H-CB account for £250–£500 m; less than one per cent of gross co-benefits in the cleaner cars scenario. Hence, our technological mitigation interventions generally result in small NA-P H-CB, while the recovery of potential investment outlays mainly stems from efficiency improvements.
As demonstrated in the previous section, the cleaner cars scenario is likely to be cost-effective within our 20 year time horizon, while the household energy scenario only becomes cost-effective in the very long term. A UK network for electric cars is yet to be developed and hybrid cars remain comparatively costly. Nevertheless, the implementation of the cleaner cars scenario may well be attained through a general change in attitudes towards hybrid and smaller fossil fuel-based vehicles at little additional or possibly even at lower (investment and maintenance) costs to car owners. This is all the more likely as the hybrid car technology is likely to become cheaper and more accessible for the average car buyer over time. Cheaper cars also come with the risk of creating rebound effects which may lower GHG emissions impact. Alternative (and potentially more costly) ways to implement the scenario includes graduated car taxation or outright regulation of car standards. In any case, with an overall breakeven investment cost estimated at £142bn, the UK cleaner cars scenario—and by the same token, the overall UK urban transport strategy with the cost-neutral active travel scenario—is very likely to be cost-effective.