Explaining Patterns through Dimensions of Structural Complexity

Structure is mostly invisible. Structure is the result of formal and informal ways of ‘how the world works’ that have been tacitly accepted, such as power structures or the distribution of resources or explicitly institutionalised rules, norms and policies.

Understanding structure underlying a system helps explain why event patterns occur.

System structure itself is shaped by complex system traits such as the lack of central control, co-evolutionary and path-dependent processes. As explained in the introduction of the theoretical framework awareness of these processes is a prerequisite for effective intervention design. Interventions purposely disrupt the status quo; they are deliberate attempts to end or alter current patterns of events or to create new ones. Interventions need to consider and address events, even seemingly unrelated ones, in an interconnected way to avoid a ‘silo effect’. A silo effect occurs when each intervention sees and treats a situation as separate (Scharmer, 2008). Diagram 5.7 illustrates how system structure influences patterns of events. The diagram also highlights how the analysis of problem drivers at structural level links to Systems Thinking, the overarching analytical framework of the study. The discussion in Chapter 3 explained in detail how Systems Thinking can help to elucidate issues caused by the structural make-up of a system.

Diagram 5.7 System Structure Driving Patterns of Events

5.4.1 Co-Evolutionary Processes

Co-evolutionary processes are frequently the by-product of transitions occurring in other parts of the system. Co-evolutionary processes can give rise to patterns, which generate new events or have an impact on existing ones. The structure of the system is the

145 relationship between patterns. Co-evolutionary processes can exert a reinforcing or a balancing force on the process, which gave rise to it in the first place.

Increasing household consumption is a co-evolutionary process. It is occurring alongside the decline of traditional industries. The relationship between increasing consumption, energy demand and pollution has been emerging as a new pattern. This pattern has been created by deliberate government policy to shift away from traditional industries to a less energy intensive economy. The strategy of changing economic drivers has borne fruit in controlling electricity demand in the early years of the economic restructuring policy.

Over the years 2013 to 2015 electricity consumption remained stable (NSBC, 2016; WSJ, 2016). Across the country, industrial output grew at less than 6% in December 2015 according to data from the National Bureau of Statistics (2017). More recent electricity consumption figures published by the NDRC suggest that electricity usage has shifted from deceleration back to acceleration. The first quarter data of 2016 indicates an annual

increase in consumption by 3.2 % for the period. As noted in the in the introductory section household electricity use and consumption by the service sector each rose by almost 11%

year on year, while industry use almost stagnated at a growth rate of only 0.2% (Lockett, 2016; NSBC, 2016). Long-term impact of domestic consumption threatens to offset environmental gains achieved through scaling back combustion of coal for electricity generation. This finding is supported by other studies, which confirm that consumption from an emerging urban middle class has appeared as a main driver of energy demand as well as pollution (Miao, 2017; Huo et al., 2013; Peters et al., 2007).

Co-evolutionary processes are counter-productive to the government’s efforts to reform the electricity sector, unless adequate measures are taken to control rising electricity usage from consumers. The cause and effect relationship between rising affluence, electricity consumption and people’s material standard of living is illustrated in Problem Tree 3 (Diagram 5.6). The transition from heavy manufacturing to less pollution intensive forms of economic growth has unexpected side effects on the environment. The link between improving living standards and deteriorating environmental quality connects Problem Trees 2 and 3.

In addition to increasing household affluence, other co-evolutionary processes are

expected to lead to a future rise in consumption and residential electricity usage. One such factor is falling saving rates. China has one of the world’s highest household saving rates, which has depressed consumption in the past. The household saving rate surged from 5 % in the mid-1970s to almost 40 % in recent years⁴⁶. The introduction of the one child family policy brought with it lower household expenditure and the requirement to save for old age (Modigliani and Cao, 2004; Choukhmane, 2013; Curtis, Lugauer and Mark, 2012). The reduction of social services such as healthcare and lower job security following the

abandonment of guaranteed lifetime employment in state-owned enterprises contributed to the precautionary motive of saving a large part of the household income (Zhang, 2016).

46According to data gathered by the OECD (2017b) Chinese households saved 37.88% of their disposable income in 2014. Household savings rates recorded for Germany and the U.S. were 9.67% and 6.0% respectively in 2015. In the UK households saved on average 0.16% of their income in the same year.

146

Continuing urbanisation, the relaxation of the one child policy, the growth of e-commerce, the emergence of a new generation of sophisticated consumers, who unlike their frugal parents were raised in a period of relative abundance, are expected to become the main factors driving the expansion of China’s consumer economy (Barton et al., 2013; Cheng, 2016). Research by the Boston Consulting Group (Kuo et al., 2015) forecasts that household consumption will grow by 50% from 2015 levels to 6.5 trillion US $ in 2020, even if GDP growth stays suppressed at under 6%. The estimated incremental growth over the next five years alone is equivalent to 1.3 times that of today’s UK consumer market.

As illustrated in Diagram 5.6, household income is the main factor that influences the usage of electricity. A more complex picture of consumption patterns emerges in light of distinct regional economic structures. People are affected by the country’s transition in different ways. Given distinct regional differences in household affluence in terms of income, consumption levels across regions are rising at a different pace. With the government promoting household consumption as new economic driver, the gap between regions in terms of local pollution and the population’s standard of living is set to widen. Regional consumption patterns have far wider implications for equity than differences in the material standard of living. The high standard of living enjoyed by people in the richest provinces comes at the expense of energy related local pollution in less affluent regions.

Feng et al. (2013) find that up to 80% of emissions embedded in goods consumed in the East are imported. This observation extends to electricity consumption. Electricity used by households in the East, as explained earlier, is to a varying degree imported from the inner provinces, where generation takes place in mostly obsolete coal fired plants.

5.4.2 Path Dependency of the Energy System

As explained previously, energy systems are subject to strong and long-lived path dependence, owing to technological, infrastructural, institutional and behavioural lock-ins (Simmie, 2012). Experts interviewed pointed out that innovation is required to transform China’s coal based energy system into a clean, low-carbon system. The dominance of coal based power generation is the legacy of past investment decisions.

Given their long life span, the large sums invested in coal-based generation threaten to crowd out the deployment of cleaner generation technology for many years to come.

The idea of a path dependent process as a self-reinforcing cycle has been employed in the analysis of the persisting regional disparities in economic development and the ‘lock-in’ of regions to a particular economic structure. Unlike the metropolitan areas on the coast that rely on innovative industries and services for economic growth the inner regions are locked into a coal-dependent energy infrastructure based on inferior technology. The retirement of power plants, as they approach the end of their life, could be an opportunity to end the lock-in effect of a coal based energy system. However, plans to construct more coal based power stations, most of them in the inner provinces, could start a new cycle of path dependence. In 2015 China’s provincial governments issued environmental approvals for 155 new coal-fired power plants (Boren, 2015). Following an intervention of the central government, some of the planned projects appear to have been put on hold. The

147 implications of devolution of power from national authorities to regional governments are discussed in the next section.

Path dependence is more than a lock-in to an emission intensive capital and physical infrastructure of the energy system. Along the establishment of an unsustainable energy sector, social and political processes have increasingly become locked-in. A shift away from a coal-based energy infrastructure, for example, requires a structural shift providing access to technology, finance and a labour force with a suitable skillset (Green and Stern, 2014).

The consultation of stakeholders brought to light that potential social impacts of the reform have not been given much consideration. The topic remained absent from most of the discussions unless brought onto the agenda by myself, the researcher. Further

questioning revealed that effects of de-carbonising the energy sector on employment opportunities were not thought to be relevant. A very insightful interview with the founder of a Beijing based ENGO was an exception (Interview 24). The discussion highlighted the challenge for provinces locked into a coal-based economic structure to facilitate the transition for its work force. A report by the Chinese Academy of Social Sciences (CASS, 2017) confirmed that the continuing decline of the coal sector will cause a range of social problems. The authors estimate that by 2020 approximately 2.3 million miners alone will require re-employment. Considering that the study does not consider employment in the coal power sector, the scale of the problem could be much wider.

What is encouraging for the mining regions is that the main sites for the generation of renewable energy, wind power in particular, are also concentrated in the Northern and Western part of China. According to the International Renewable Energy Agency (IRENA, 2017) currently 3.65 million people are employed by the renewable sector in China. It is widely accepted that renewable technology development, the production and deployment of equipment, creates more jobs per kWh generated than fossil fuel power generation. It is estimated that wind power creates almost a third more jobs than the same amount of energy generated by a coal fired plant (EWEA, 2009; Lewis, 2013). Less clear, however, is to which extent new jobs in the renewables sector⁴⁷ could replace employment in the traditional industries. The employment of the local workforce would require large-scale re-education initiatives (Joint, 2011). In the aforementioned interview, it was pointed out that there are plenty of obstacles to the re-employment of miners in the light of uncertainties over future funding and market prospects.

5.4.3 Lack of Central Control

Not all system aspects can be externally controlled. Most complex systems are to an extent self-organising, even in the presence of an authority with central control. Pattern formation

47 It is not quite clear how much new employment will be created in the renewables sector. In January 2017 The National Energy Agency (NEA) of China forecast 13 million new jobs from 2016 to 2020. In an announcement made one month earlier the NDRC put forward a more cautious estimate of an additional 3 million jobs by 2020 (Reuters, 2015b).

148

occurs through interactions internal to the system, frequently without intervention by external directing influences (Yates, 2012).

Despite the powerful position of the central government, China's political system is de-facto functioning more like federalism (Zheng, 2006). Chinese regional decentralisation evolved during the post-Mao reform. Provincial governments were given control over a significant amount of resources including energy (Xu, 2006). The surge of plans for the construction of 155 new coal-based power plants appears to be the outcome of the central government’s decision to decentralise authority to approve coal-fired power plant projects to the province level in March 2015. Within a year provincial governments approved the construction of new coal-fired units with a total capacity of 169 GW. This is over three times more than the year before. As noted in the earlier discussion on regional differences that exist within the energy sector, the construction of new coal capacity is concentrated in a few central provinces. Permits for 55 of the plants with over 40% of the total capacity were issued in Shanxi, Inner Mongolia and Xinjiang. In these three provinces coal-related sectors such as mining and energy generation have the biggest share in GDP (Myllyvirta et al. 2016; Jakobowski, 2016).

The rationale behind the political decentralisation process was based on the idea that local knowledge and resources would respond more effectively and efficiently to local needs than interventions initiated by central authorities in Beijing (Landry, 2008). One of the consequences of delegating competences to provincial governments involves the central state losing control of the energy sector reform. Paradoxically, in the parts of the country which are the main target of reform the provincial governments were undermining national reform efforts the most. New investment in coal-fired energy generation was seen as a way to stimulate local economies and to fight rising unemployment by supporting coal related sectors (Jakobowski, 2016).

In light of the existing overcapacities in the region of 100 GW (estimated by Kahrl (2016) for the year 2014) and the environmental impact of the new plants, central government brought the approval process of new power plants back under its control. If constructed, the additional generation capacity could jeopardise carbon and air pollution targets⁴⁸. In March 2016, the National Development and Reform Council announced its intention to end the construction of coal-fired units (NDRC, 2016b). The key element of the plan is to suspend the process of issuing permits for the construction of new power plants until the end of 2017, and to put all approved projects, whose construction has not yet been

48 In line with emission limits given in the approval decisions or environmental impact assessments, air

pollutants from the 155 power plants are estimated at 96,000 tonnes of SO2, 124,000 tonnes of NOx and 29,000 tonnes of particulate matter emitted in one year. The yearly CO2 emissions from the 155 projects would be equal to 6% of China’s current emissions, or to the total energy-related emissions of Brazil (Myllyvirta et al., 2016).

149 launched, on hold. The restrictions cover 15 provinces⁴⁹, in which an oversupply of

electricity has been observed.

Despite the benefits of local decision making, a lack of central control could be counter-productive in facilitating a major reform of the energy sector. Other conflicts of interest which have been documented are the reluctance of local officials to carry out orders by the central government (Kostka and Mol, 2013; Kostka and Hobbs, 2012),such as the

shutdown of heavily polluting factories or power plants (Zhu, 2016; Interview 6). The example of the coal sector shows that the success of China’s transition, including the market-led reform of the energy sector, depends on the central government’s ability to control groups that seek to maintain the status quo, i.e. existing patterns of

unsustainability.

This section illustrated how socio-economic and political structures of a country shapes current unsustainable and inequitable patterns of electricity generation and consumption.

The discussion highlighted the importance of structural reform either facilitated by a market-based intervention or supplementary measures. Once linkages and

interdependences between different system components are known, the effect of a deliberate change in the system structure, through an intervention, such as a carbon market, can be better understood. The first step is to construct a causal model of the Chinese energy sector.