*3.2. Economic Barriers*

The main economic barrier for PV integration has been the high upfront cost and an unwillingness of banks to fund such investments [35]. The higher construction costs have previously made financial institutions more likely to perceive renewables as risky, lending money at higher rates and making it harder for utilities or developers to justify the investment. Perceptions of the (high) costs associated with solar PV can still be a barrier even if prices have come down considerably in recent years.

There have been efforts towards establishing the economic viability of solar PV in different regions of the world. A study focusing on the Middle East and North Africa regions concluded that rooftop PV systems were competitive with other energy producing plants in the region [33], however development has not followed suit. Nevertheless, a study in the Kenyan context confirms this. In [36] the authors used a levelised cost of energy evaluation and established that solar power in combination with other renewable energy generation technologies is competitive in relation to non-renewable energy. In spite of the high insolation levels, solar PV has mainly been used for off-grid application such as solar lanterns because of the high upfront investment costs of grid-connected solar PV systems [37]. However, currently, solar PV has been highly incentivized and prices have dropped significantly thus making it a viable option compared to diesel-fuel generators that are expensive to run [38].

Cost comparisons and competitiveness of solar PV with the conventional fossil fuels to electricity production are among the most significant barriers for adoption of solar PV in Kenya both for the utility company and for individual investors [17]. From the perspective of both the national utility company Kenya Power and Lighting Company (Nairobi, Kenya) and independent power producers, large-scale PV electricity generation without a well-functioning energy storage system maybe too expensive considering the fact these companies are also required to maintain the grid infrastructure and manage other running costs [31].

To mitigate these challenges, the incumbent could consider selling or leasing out PV energy storage systems, provide financing and grid connections or build a service relationship with individual investors. Once the domestic market grows, the installation costs will become cheaper; this could further be facilitated by training and certification of solar PV installers at the national level [39].


**Impact Analysis of Air Pollutant Emission Policies on Thermal Coal Supply Chain Enterprises in China**

#### **Xiaopeng Guo, Xiaodan Guo and Jiahai Yuan**

**Abstract:** Spurred by the increasingly serious air pollution problem, the Chinese government has launched a series of policies to put forward specific measures of power structure adjustment and the control objectives of air pollution and coal consumption. Other policies pointed out that the coal resources regional blockades will be broken by improving transportation networks and constructing new logistics nodes. Thermal power takes the largest part of China's total installed power generation capacity, so these policies will undoubtedly impact thermal coal supply chain member enterprises. Based on the actual situation in China, this paper figures out how the member enterprises adjust their business decisions to satisfy the requirements of air pollution prevention and control policies by establishing system dynamic models of policy impact transfer. These dynamic analyses can help coal enterprises and thermal power enterprises do strategic environmental assessments and find directions of sustainable development. Furthermore, the policy simulated results of this paper provide the Chinese government with suggestions for policy-making to make sure that the energy conservation and emission reduction policies and sustainable energy policies can work more efficiently.

Reprinted from *Sustainability*. Cite as: Guo, X.; Guo, X.; Yuan, J. Impact Analysis of Air Pollutant Emission Policies on Thermal Coal Supply Chain Enterprises in China. *Sustainability* **2015**, *7*, 75-95.

#### **1. Introduction**

According to the Air Quality Report issued by the Chinese Environmental Protection Ministry, in 2013 China's annual haze days reached the highest level on record (19.5 days) owing to unsustainable development and an unreasonable energy structure. In addition, the national annual concentration of PM2.5 has reached 72 micrograms per cubic meter. Only three cities reached the standard, which accounts for 4.1 percent of all 74 cities. The Intergovernmental Panel on Climate Change (IPCC) found that coal combustion is the main source of air pollutants. In addition, the research done by the Chinese Academy of Sciences (CAS) showed that: the sources of Beijing's particulate matter (PM10) emission are secondary inorganic aerosols (26%), industrial pollution (25%), coal consumption (18%), soil dust (15%), biomass burning (12%), and automobile exhaust gas and waste incineration (4%). The secondary inorganic aerosols, industrial pollution, and coal consumption are all caused by the burning of fossil fuels. Therefore, China's worsening air quality is probably caused by extensive coal consumption and a high energy consumption development pattern.

Coal consumption is considered to be the second most important anthropogenic contributor to global air pollution [1,2]. From the perspective of coal consumption structure, the electric power industry is the biggest contributor to the coal resources consumption. The power generation industry produces more than 40 percent of total air pollution emissions in China [3]. China's past electricity development policies have led the power industry to make excessive investment in thermal power installed capacity and low operational efficiency [4]. If a long-term transition towards a low carbon economy is not carried out, China's CO2 emissions could rise by 160%–250% from 2010 to 2050 [5]. By the year 2020, China's thermal power generation may reach over 7 trillion kilowatt-hours, and air-pollution intensity will be nearly twice the 2005 level [6].

To accelerate the control of air pollution, the Chinese government has introduced many policies managing the air quality and adjusting the energy structure since 2009. These air pollution emission policies will surely change the operating environment of coal supply chain enterprises. So it is urgent to analyze the policy impact and optimize the development patterns for coal and power industries under new policy restraints [7]. From the perspective of the power industry, coal-fired power will translate into clean and efficient energy power after the implementation of sustainable development policies [5,8]. China's hydropower, wind power, and nuclear power industry will meet a tremendous need in the following decades under the encouragement of energy structure adjustment and an emission reduction policy [9,10]. Nuclear and hydropower may play a dominant role in contributing to China's air pollution reduction in the long term [11]. Also, the promotion of renewable energy utilization will surely have a great effect on China's coal and power industry [12]. Further, the air pollution emission reduction policies can also accelerate the technological advancement and clean coal utilization of thermal coal supply chain enterprises [13,14].

The thermal coal supply chain system is the whole system of coal enterprises, power enterprises, and coal transportation enterprises, which guide the process from coal production to coal consumption. In addition, air pollutant emission reduction policies' impact on the thermal coal supply chain is a complex, dynamic evolution process concerning many fields such as policies related to energy conservation and emission reduction, economic development, power production and consumption, resource exploitation and utilization, and energy price. So it is obvious that the power structure adjustment has nonlinear characteristics. The system dynamics (SD) method not only models the market's real behavior but also properly explains the relationship between the main variables of the system [15]. Considering the advantages of integrity and dynamics that system dynamics has in analyzing complex dynamic problems, this paper set up a complete system dynamics model by analyzing: the air pollution emitted during coal combustion, coal washing technology, installed capacity, unit transform, and new energy power generation, under the constraint of the new atmospheric pollutant emission policy, to seek a development pattern for the thermal coal supply chain.

The SD approach has been applied in investigating the sustainable management of electric power systems. Some scholars have set up an SD-based model to investigate the distributed energy resource expansion planning [15–17] and energy efficiency improvement [18], considering both energy states and production constraints. Other scholars use SD methodology to simulate the behavior of the renewable energy sectors such as nuclear [19] and photovoltaic energy [20]. SD models are also widely built to explore the effects of energy consumption and CO2 emission reduction policies [21–24]. Previous models have structured the investment, dispatch, pricing heuristics, and electricity generation resource factors with common emission reduction policies such as feed-in-tariffs, investment subsidies, and carbon taxes. In order to deeply investigate the new development pattern of the power and energy industry, some scholars have qualitative explored the link between transportation systems and air pollution reduction policies using the SD approach [25,26]. However, the dynamic behavior of the thermal power system and the complicated feedback of a coal system under pollution reduction policies were not taken into account in previous studies.

As policy refinement increases, China's air pollutant emission reduction policies select the specific goals of pollution emission, coal cleaning proportion, and desulfurated capacity proportion. Under the new policy situation, the former system dynamic model is not suitable to measure the effect on China's thermal coal supply chain member enterprises.

The objectives of this paper are as follows:

The simulated results are significant in predicting energy proportion, power proportion, and development routes of thermal coal supply chain member enterprises. In addition, the simulations of China's air pollution emission reductions have meaning for policy-making institutions.

#### **2. China's Air Pollution Emission Reduction Policies**

China is the world's biggest energy consumer [27,28]. According to the information distributing platform of National Statistics, China's coal consumption accounts for about 70% of the total energy consumption in 2013. The thermal coal consumption of China's electric industry is 1967 million tons, accounting for 64.29% of the total coal consumption. China's growing atmospheric pollution problem is caused by the long-term accumulation of multiple factors such as unsustainable development patterns and unreasonable energy electric power industry structures. In order to better reduce air pollution, the Chinese government has introduced many laws involving concrete measures since 2009.

In 2009, after realizing the importance of sustainable development the Chinese government first proposed to reduce carbon dioxide emissions per unit of GDP by 40%–45% in 2020, as of the 2005 level. This restrictive goal has also been included in the medium and long term planning of China's national economic and social development.

In 2010, the fifth plenary session of the 17th CPC Central Committee emphasized that China should make the construction of a resource-saving and environment-friendly society an important focus despite the acceleration of economic growth and the readjustment of the economic structure. Prime Minister Wen Jiabao promised that China would energetically promote energy conservation and raise the efficiency of energy consumption, especially in industry and transportation. Wen also said that China would add 80 million tons of standard coal energy saving ability annually, and that all additional and reconstructive coal-fired units must build and run flue gas desulfurization facilities synchronously.

Since 2012, hazy weather in the Beijing-Tianjin-Hebei and Yangtze River Delta areas is becoming more and more frequent, so the importance of air pollutant prevention is becoming more and more noticeable. In October 2012, the Chinese National Development and Reform Commission, the Ministry of Environmental Protection, and the Ministry of Finance jointly issued The 12th Five-Year Plan for the prevention and control of atmospheric pollution in key areas. The 12th Five-Year Plan pointed out that we should focus on the optimization of industrial layout and energy structure and the enhancement of clean energy under the current serious situation of air pollution. China should adhere to a diversified energy development strategy, strive to improve the proportion of clean low-carbon fossil energy and non-fossil energy, promote the efficient utilization of clean coal, implement the alternatives of traditional energy, and speed up the optimization of energy production and consumption structure. By the end of the 12th period, the proportion of non-fossil energy consumption should increase to 11.4% and the proportion of coal consumption should decrease to 65%. The proportion of non-fossil energy generation installed capacity should reach 30%.

In June 2013, the premier, Li Keqiang, introduced ten measures for the control of air pollution in the state council executive meeting. The main content of these measures is the reduction of air pollutant emission, the control of high energy-consuming enterprises, the adjustment of energy structures, and the new energy conservation and emissions reduction mechanisms of incentive and constraint. We should speed up the adjustment of energy structure by implementing the interregional transmission project, controlling coal consumption reasonably, and promoting the use of clean coal. By the end of 2014, China should complete the elimination of backward installed capacity ahead of time. The Chinese government should follow the guiding and incentive rule of taxes and subsidies, in order to push for sustainable development.

In September 2013, The Action Plan for the Control of Air Pollution, issued by the state council, clearly pointed out that in 2017 the inspirable particle concentrations of China's prefecture-level cities should be reduced by 10% from 2012 levels and the inspirable particle concentrations of Beijing-Tianjin-Hebei, the Yangtze River Delta area, and the Pearl River Delta area should be reduced by about 25%, 20%, and 15%, and the PM10 concentrations of Beijing especially should be reduced to under 60 micrograms per cubic meter. The Action Plan for the Control of Air Pollution also mentioned the adjustment of energy structure, the optimization of industrial layout, the improvement of environmental economic policies, and some other measures. Measures optimizing the industrial layout covered the capacity limitation of energy-intensive and highly polluting industries, the acceleration of backward capacity elimination, and the compression of excessive capacity. China should take a sustainable development pattern by controlling coal consumption, increasing the proportion of washed coal, accelerating the use of clean energy, and raising the energy usage effectiveness. An energy conservation and emissions reduction mechanism of incentive and constraint should be promoted actively in order to improve sustainable environmental economic policies.

In addition, some local governments introduced policies to cooperate with the implementation of The Action Plan for the Control of Air Pollution, such as an action plan implementing rules for the control of air pollution in Beijing-Tianjin-Hebei and surrounding areas. These rules made more detailed targets for the provinces and cities of the Beijing-Tianjin-Hebei region. The plan pointed out that by the end of 2017 the proportion of Beijing's coal consumption will drop below 10% and high-quality energy such as electricity and natural gas will account for more than 90%. Beijing will cut 13 million tons of raw coal by using many comprehensive measures such as eliminating backward production capacity, clear violations capacity, strengthening energy conservation and emissions reduction, implementing clean energy replacement, safe development of nuclear power, and strengthening the new energy-efficient utilization.

Overall, these air-pollution reduction policies focused on optimizing the industrial structure and energy structure, and giving impetus to industrial transformation and upgrading. Along with the restriction of coal consumption and the development of clean energy generation, the business environment and development modes of coal enterprises and power generation enterprises must change significantly. It is a big challenge for thermal coal supply chain member enterprises, including coal enterprises, power generation enterprises, and thermal coal transportation enterprises, to make the right decisions in response to the policy influence [29]. Completing the analysis of policy implications will be of great significance in researching the policy mechanism and predicting the developing direction for thermal coal supply chain node enterprises under the policy background. The policy implications are complex and dynamic, so it is difficult for a general model to simulate the changing process of each factor in the thermal coal supply chain under the influence of air pollutant emission reduction policies. Considering the advantages of the SD model on integrity and dynamics during complex analysis, this paper plans to establish a system dynamics model of thermal coal supply chain member enterprises' development processes under the impact of air pollutant emission reduction policies to figure out the policy mechanism and assist decision-making in node enterprises.


**Advanced Coatings for Buildings**

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**Anibal C. Maury-Ramirez In ˆes Flores-Colen Hideyuki Kanematsu**

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*Editors* Anibal C. Maury-Ramirez Universidad El Bosque, Decanatura Facultad de Ingenier´ıa Colombia

Inesˆ Flores-Colen CERIS (Civil Engineering Research and Innovation for Sustainability), DECivil (Department of Civil Engineering, Architecture and Georesources), IST (Instituto Superior Tecnico), ´ University of Lisbon Portugal

Hideyuki Kanematsu National Institute of Technology, Suzuka College Japan

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**Author details**

Kavita Chahal1 \*, Vaishali Gupta1 , Naveen Kumar Verma1 , Anand Chaurasia2 and Babita Rana3

1 Department of Botany, Government College, Bichhua, Chhindwara, Madhya Pradesh, India

2 Department of Botany, Government College, Pawai, Panna, Madhya Pradesh, India

3 Department of Botany, Guru Nanak Khalsa College of Arts, Science and Commerce, Matunga, Mumbai, India

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© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.