The GHG Intensities of Wind Power Plants in China from a Life-Cycle Perspective: The Impacts of Geographical Location, Turbine Technology and Management Level

Abstract

Presented in this study is a comparative life cycle assessment of 60 wind plant systems’ GHG intensities (49 of onshore and 11 of offshore) in China with regard to different geographical location, turbine technology and management level. As expected, geographical location and turbine technology affect the results marginally. The result shows that the life-cycle GHG intensities of onshore and offshore cases are 5.84–16.71 g CO₂eq/kWh and 13.30–29.45 g CO₂eq/kWh, respectively, which could be decreased by 36.41% and 41.30% when recycling materials are considered. With wind power density increasing, the GHG intensities of onshore cases tend to decline, but for offshore cases, the larger GHG intensity is as the offshore distance increases. The GHG intensities of onshore cases present a decreasing trend along with the technical advancement, and offshore counterparts is around 65% higher than the onshore cases in terms of wind turbines rated at more than 3 MW. The enlarging of offshore turbine size does not necessarily bring marginal benefit as onshore counterparts due to the increasing cost from construction and maintenance. After changing the functional unit to 1 kWh on-grid electricity (practical), the highest GHG intensities of Gansu province increase to 17.94 g CO₂eq/kWh, same as other wind resource rich provinces, which significantly offsets their wind resource endowment. The results obtained in this study also highlight the necessity for policy interventions in China to enhance resource exploration efficiency and promote robust and sustainable development of the wind power industry.

1. Introduction

There is a broad consensus that renewable energy as wind power is increasingly playing a crucial role in achieving China’s ambitious goal of peaking carbon dioxide emissions before 2030 and achieving carbon neutrality before 2060. It is also a fact that China’s wind power has achieved soaring development since the release of the Renewable Energy Law in 2005, and has the world’s largest installed capacity of 328 GW in 2021 [1], representing 41% of global build, which is projected to reach at least 800 GW and 3000 GW in 2030 and 2060 under the ambitious carbon neutral goal, respectively [2]. At the same time, this process has been accompanied with an enlarging trend of wind turbines with higher energy efficiency but also higher material consumption, illustrated by the fact that the mean capacity of newly installed wind turbines in China increased from 1.47 MW in 2010 to 2.7 MW per turbine in 2020.

Despite the renewable nature of wind energy conversion, non-renewable resource inputs and the related environmental impacts occur during the whole life-cycle of wind power plants, which can be quantified and assessed by life cycle assessment (LCA) method [3]. As such, there is an increasing number of studies conducted to quantify GHG intensities from a life-cycle perspective in the last decade, one of the most representative indicators for assessing the environmental impacts of wind power plants both in China and other countries (see

Table 1. Reviews on previous LCA studies of wind power plants in China and other countries.

Reference	Country	Turbine Type	Methods	GHG Intensity g CO2eq/kWh
[10]	France	250 kW-onshore	Process-based LCA	46.40
		4.5 MW-onshore		15.80
[11]	China	1.25 MW-onshore	Process-based LCA	7.20
[12]	Germany	5 MW-offshore	Process-based LCA	32.00
[13]	Britain	2 MW-offshore	Process-based LCA	13.40
			Hybrid LCA	28.70
			IO-LCA	29.70
[14]	Norway	5 MW-offshore	Hybrid LCA	35.10
[15]	Brazil	1.5 MW-onshore	Process-based LCA	7.10
[16]	China	1.5 MW-onshore	Process-based LCA	7.20
[17]	Britain	5 MW-offshore	Process-based LCA	18.00–31.40
[18]	Germany	5 MW-offshore	Process-based LCA	16.80
[19]	America	2 MW, 3 MW-onshore	Hybrid LCA	17.30
[20]	Europe	2.3 MW, 3.2 MW-onshore	Process-based LCA	7.00
		4.0 MW, 6.0 MW-offshore	Process-based LCA	11.00
[21]	Turkey	2 MW-onshore	Process-based LCA	7.30
[22]	China	2 MW-onshore	IO-LCA	7.55
[23]	America	1.5 MW-onshore	IO-LCA	14.50–28.50
[24]	Japan	1.65 MW-onshore	IO-LCA	22.77
[25]	China	3.6 MW, 5 MW-offshore	Process-based LCA	25.50
[26]	China	850 kW-onshore	Process-based LCA	86.50
[27]	Germany	2 MW, 3 MW-onshore	Process-based LCA	11.70–18.30
[28]	China	600 kW-onshore	Process-based LCA	2.02
[29]	China	2 MW-onshore	Process-based LCA	16.40–28.20
[30]	Colombia	1.3 MW-onshore	Hybrid LCA	12.93
[31]	Europe	2 MW-offshore	Process-based LCA	9.49–18.60
		2 MW-onshore	Process-based LCA	7.09
		5 MW-offshore	Process-based LCA	11.52

). This indicator can be used to depict the static spatial distribution of wind power plants’ GHG emissions. For example, Bi et al. explores the spatial distribution of carbon emissions of 378 wind power plants in China that were still in operation in 2015, considering the detailed information of location, installed capacity, turbine size, construction year [4]. Xu et al. further estimates China’s national and regional GHG emissions in 2019 under different scenarios [5]. From this, it may infer the emission reduction effect of wind power deployed in the past and the emission reduction potential in the future [6], which can provide reference for future wind power deployment. In other words, the greatly increased proportion of wind power for the energy transition means that conventional power generation is being replaced on a large-scale, and there are some studies investigating GHG emission reduction from wind power replacing coal-fired power. For example, Liao et al. analyses the GHG emission reduction potential by 2020 of eight types of emission-reducing power generation technologies in China’s power generation sector, including wind power, and calculates their emission reduction costs and unit emission reduction costs based on the result [7]. Li et al. compares the life-cycle environmental emissions from wind and coal-fired systems in China, suggesting that around 500 million tons of CO₂ emissions will be mitigated in 2020 [8]. Zhao et al. assesses that China has great potential to realize this substitution effect, and further concludes that wind power should be developed faster than the 12th Five Year Renewable Energy Development Plan to meet the established carbon reduction targets [9]. These studies provide a good reference for the calculation of GHG emission reduction under the policy using the result of GHG intensities from the limited wind power plants. However, determining what extent of GHG intensities from a life-cycle perspective with comparable criteria for different wind power plants becomes vital to decision makers.

Shown in Table 1, it can be found that there are large variations in the reported results due to different system boundary definitions and model assumptions, as well as inconsistent case-specific data inputs, which present an existing limitation for the wind power development policy-making decisions. For instance, the life-cycle GHG intensities of wind energy can be 86.50 g CO₂eq/kWh for a wind power plant in Inner Mongolia (V52-850 kW by Vestas) [26] and 2.02 g CO₂eq/kWh for an onshore wind power plant in Taiwan (V47-600 kW by Vestas) of China [28]. To have a more comprehensive understanding of a wind plant system, several comparative studies have been conducted in consideration of different capacities of wind power plants. Xie et al. calculates the average carbon emissions of three wind power plants, comparing the occupied shares of each primary energy input in manufacturing, construction, operation, and disposal phases [28]. Similar work has been conducted by Wang and Sun for four typical wind power plants, which provided a narrow range of life-cycle GHG intensity from 5.00 to 8.20 g CO₂eq/kWh [32]. More importantly, Kaldellis and Apostolou presents a literature review on the life-cycle carbon and energy footprint, especially focusing on offshore wind power plants, which concludes that offshore wind plants can be counterbalanced from the better wind resource, resulting in an increased renewable electricity generation, although it exhibits larger carbon footprints compared to onshore counterparts [33]. To have a more holistic view of environmental profiles of wind power, simplified LCA models have been developed to harmonize the LCA results with estimations and approximations for wind turbines and wind power plants in Europe [34] and China [5]. It is worthwhile to note that these studies are basically based on disparate, sometimes invalid literature data, and mainly focus on wind turbines and foundations with less information of other ancillary facilities.

It is plainly evident that the life-cycle GHG intensity of the wind plant system is affected by the three types of factors of geographical location (e.g., wind power density), turbine technology (e.g., rated power and turbine size) and management level (e.g., wind curtailment) [35]. These factors are very significant for China with rapid development, vast territory, and interest confliction between local governments, wind power plants and the State Grid. Harmonization of LCA results with simplified models addresses some of these challenges; however, to be truly consistent, a comparison of different wind power plants should be conducted within a single analytical structure using detailed inventory data of practical running cases [36]. As such, it is still very necessary to conduct multiple cases research with a consistent LCA method framework and detailed inventory data to obtain a relatively generalized profile of GHG intensity of wind plant systems in China with regard to these three different factors.

Generally, LCA methods consist of process-based LCA, IO-LCA and Hybrid LCA, the advantages and shortcomings of which has been extensively discussed [37], which are beyond the scope of this study. Due to much data efficiency and well-defined frameworks by ISO 14040/44, the bottom-up process-based LCA method prevails in assessment of renewable energy technologies. In the present study, we estimate the different life-cycle GHG intensity and analyze its changes in reference to different geographical location, turbine technology and management level by applying the process-based LCA method to multiply case plants. Multi-perspective life-cycle assessment of multiple cases helps to paint a more complete picture that is essential for technology innovation and roadmap development associated with the wind power industry under the carbon neutrality target in China, as well as other developing countries.

The remaining part of this paper is organized as follows. Section 2 introduces the case wind power plants and provides an overview of the LCA method framework, followed by the goal and definition, a description of assumption for calculation as well as data sources. The results of assessing the life-cycle GHG intensity of the studied wind power plants are demonstrated in Section 3, and Section 4 proposes a further discussion from the perspectives of multi-dimensions. Finally, we conclude and shed light on directions for future studies and policy makers in Section 5.

2. Material and Methods

In this study, altogether 60 utility running wind power plants, including 49 of onshore and 11 of offshore, are sampled with geographical and technical considerations (see Figure 1). In China, the onshore wind resources mainly distribute in the Northeast, Northwest and North China (Three North Regions). The National Development and Reform Commission (NDRC) has divided onshore land into four classes of wind resource zones to benchmark feed-in tariffs with regard to wind power density (see Figure 1). To have broad representation, at least 6 plants are sampled for each onshore wind resource zone, and the offshore plants are distributed geographically from north to south along the coastal water. To be specific, there are 11, 6, 8 and 24 onshore plants that are sampled from class Ⅰ to class Ⅳ, respectively. The offshore plant cases are located in the sea with a distance of 4–62 km offshore, and wind turbine foundation includes three types, i.e., monopile, elevated pile-cap and four-pile jacket. The annual average operating time of the onshore plants in four classes of wind resource zones vary between 2809 h and 2280 h. On average, the running time of the offshore plants (2837 h) is higher than that of the onshore plants, ranging from 2499 h to 3357 h.

We take rated power, hub height and blade diameter as the basic indicators for the technical advance of wind turbines. In the last decade, the mainstream rated power of newly installed onshore wind turbines in China has transitioned from 1.5 MW in 2008 to 2.0 MW and 2.5 MW in 2018 [38], while the average rated power of offshore wind turbines is mostly above 3 MW at present, and the latest installed one has reached 6.8 MW. In this study, the onshore plants equipped with 1.5 MW, 2.0 MW, 2.5 MW and more than 3.0 MW wind turbines account for 28.57%, 28.57%, 24.49% and 18.37% of the total selected cases, respectively. Generally, wind turbines with larger rated power tend to have larger hub height and blade diameter. In this study, the average hub height and blade diameter of wind turbines with a rated power of 1.5 MW are 75 m and 87 m, while that of more than 3.0 MW are 104 m and 145 m.

Wind curtailment is a severe problem for China in the development and operation of the wind power industry. The national average curtailment rate amounts to 17%, and in certain provinces, this number exceeded 40% in the year of 2016 [39]. This problem is a joint result from volatility of technology, planning, networking management as well energy policies, which not only cause serious energy waste and thus impact the economic benefits of wind power plants [40], but also affect the overall life-cycle GHG intensity of wind power plants.

The general information on the model and number of wind turbines, type of foundations, power yield, service time and offshore distance for offshore plants is obtained from the related design reports from the electricity companies. In addition, the detailed technical parameters associated with wind power equipment including component weight, hub height and rotor diameter are extracted from the Chinese Wind Turbine Generator System Selection Manual (2017). The GHG emission factors are derived from the previous literature for China’s practice [38] and China Products Carbon Footprint Factors Database (2022). For key materials and equipment, GHG emissions during their sea transportation is estimated from the transportation load and shipping activities, while the facility installation is calculated based on the project construction planning.

2.1. Goal and Scope Definition

As mentioned above, process-based LCA is a bottom-up approach based on production system processes, and if inputting detailed process data into a model, results can potentially be generated with a great deal of detail and accuracy. The life-cycle study for different wind power plants contains various components, including wind turbine (rotors and nacelle), tower, transformer, collection, and transmission cable and foundation. The disassembled components are used as primary data inputs for LCA. The whole system boundary of this study is the cradle-to-gate process of a wind power plant, including Manufacturing, Transportation, Construction & Installation (C&I), Operation & Maintenance (O&M) and End-of-Life (EoL) phases (see Figure 2). Meanwhile, parts of wind power components are recycled after the EoL phase and offset the demand for an equivalent quantity of raw material, i.e., Recycle phase, referring to the GHG intensity of raw material production that is avoided by the use of recycled material [41]. The functional unit is set as 1 kWh electricity production, which is based on the design lifetime of wind plants (of 20 years), and the unit of GHG intensity is g CO₂-eq/kWh. In this study, the GHG intensity highlights their breakdown at each phase of LCA, and the total and net GHG intensities are calculated under the system boundary which is cut off by the EoL and Recycle phases, respectively. Some assumptions on the life-cycle phases are made during calculations to ensure that the subsequent analyses can be achieved.

2.2. Assumptions for Calculation

2.2.1. Manufacturing Phase

This phase involves six wind power components, i.e., wind turbine, tower, transformer, cable, cable tower and foundations. For offshore wind turbines, the distance to coastline and water depth affects the selection and design of foundation type [42]. When compared to onshore wind plant systems, offshore facilities require a more stable foundation. The foundation types of offshore wind turbines in this study involve monopile, elevated pile-cap, four-pile jacket based on their structural configuration. Each wind turbine is equipped with a box transformer, and after the electricity (0.69 kV) generated by the wind turbines is boosted to 35 kV by the box transformer, the cables are collected to the 110/220 kV substation and incorporated into the regional power grid. The transmission and distribution activities within the wind power plant that feeds into the regional power grid are not included in the system boundary, and the grid losses in transformers and cables are also ignored. Onshore wind power plants construct a mixed combination of buried cable and overhead wire, while offshore wind power plants adopt submarine cable. The types of buried cable, submarine cable and overhead wire are ZR-YJV22-26/35 kV − 3 × 70 (high voltage) and ZC-YJV22-0.6/1 kV − 1 × 240 (low voltage), ZS-YJQF41 + OFC1-26/35 kV, and LGJ-240/30, respectively. Data on the material composition of transformers and cables are obtained from literatures [11,43].

2.2.2. Transportation Phase

In this study, it is assumed that wind turbine tower and building materials are transported from the production plants to the assembling site/wind power plant. In most of the designing reports, there is information about the production brand and factories of wind turbines, and based on that, the transportation distance can be estimated. For those lacking such information, proximity assumption is made, i.e., the nearest distance from the possible manufacturers for wind turbine or tower to wind power plants [44], and building materials are assumed to be purchased at the local city. It is worthwhile to note that the offshore wind power generator is first assembled on the shore before they are shipped to the installation sites, the transportation of which consists of two parts, i.e., the land and sea transportation. Trucks with diesel are adopted for transport on land, while transportation at sea is assumed to be carried out by a sea tanker with residual oil. Fuel consumption intensity depends on travel distances and loading weights [45]. The consumption intensity of the diesel is estimated as 41.5 g/(t·km) [11], while that of the residual oil is 3.54 g/(t·km) [46,47].

2.2.3. C&I Phase

The construction phase of the wind power plant is composed of building works and installing equipment. Building works for onshore wind power plants further include wind turbine foundation and road. All onshore wind turbines are designed with circular extended independent gravity foundations, which require a substantial amount of steel reinforcement and concrete. Road as an important and indispensable auxiliary engineering construction of onshore wind power plants, is rarely involved in the system boundary of life cycle assessment. We assume that the fuel consumption coefficient per kilometer of road construction is 21.6 t/km. At the same time, for offshore wind power plants, assumptions on marine vessel activities have referred to the literature [14], including the installation of wind turbine and foundation, and we use conversion factors 0.83 kg/L (residual oil) as conversion of units of sea tanker.

2.2.4. O&M Phase

It is usually assumed that the GHG intensity for onshore wind power plants’ operation is equal to 1.5% of manufacturing phase [28]. Similarly, within the life span of a typical wind generator, it is supposed to substitute one blade and 15% of the nacelle’s component [10]. For each offshore wind turbine, the maintenance phase typically involves regular maintenance 1–2 times and unregular maintenance 1–4 times every year [14,48,49]. The activities of marine vessel operations during the O&M phase of wind turbine are considered. According to the O&M experience of offshore wind power plants, a moderately sized offshore wind power plant usually needs to have its own O&M center, which is generally set up in the surrounding areas, such as ports and docks, close to the wind power plants. Therefore, we consider the offshore distance at this phase as a function of work days. The work days are first calculated for the wind power plant located 36 km from the shore, and every 5 km closer to the shore will result in 17% less transport time compared to the 36 km wind power plant [42].

2.2.5. EoL Phase

Ideally, after the wind power plant’s life-cycle reaches an end, it is performed to be decommissioned and returned to a site close to its original state [50]. However, there is no unified plan for wind power plants’ decommissioning at present, so assumptions have to be made for this phase based on other types of wind power or renewable energy projects. Parts of wind power components are decommissioned, some of which are recycled (Section 2.2.6), while others are buried on site. GHG emitted during the whole decommissioning phase is assumed to be equal to the construction and installation phase [28,51].

2.2.6. Recycle Phase

During the EoL phase, it is estimated that 85–90% of a wind turbine can be reused [52]. We assume that 98% of the rotor, 90% of the tower, 100% of the generator would be recycled, and for the other parts of nacelle, about 95% of the composition is recycled and the remaining is disposed in a landfill [10,53]. For offshore wind power plants, 100% of the foundation structure primarily fabricated in steel is recycled [54]. Due to the recycled material being used as a replacement for raw materials, the associated GHG intensity is regarded [45]. Furthermore, since the recycled wind power components can be beneficial to reduce the demand for raw materials, they are treated as resource benefits and the associated environmental benefit is deducted when calculating the life-cycle GHG intensity of the wind power plants presented in this study.

3. Results

3.1. The Life-Cycle GHG Intensities of Wind Power Plants

Figure 3 shows that the average life-cycle GHG intensities of case plants are 13.03 g CO₂eq/kWh. It is plainly evident that the manufacturing phase is a main contributor of GHG intensities in most of the cases, accounting for 30.45–68.35%, another important contributor of which is the C&I phase for onshore wind power plants, and the O&M phase for offshore wind power plants. The percentage of GHG intensities is 27.78–45.35% in the C&I phase of onshore wind power plants, while it is 18.02–55.98% in the O&M phase of offshore wind power plants. Moreover, the Recycling phase accounts for 25.07–56.46% of life-cycle GHG intensities. During the manufacturing phase, the largest contributors of GHG intensities are successively tower (30.86–61.65%), rotor blade (11.46–23.79%) and electronic components (1.10–14.34%) for onshore wind power plants. However, for offshore wind power plants, the largest contributors of GHG intensities are foundation (39.40–64.71%), tower (11.93–26.26%) and rotor blade (4.76–10.26%), respectively.

3.2. The First Dimension: Geographical Location

3.2.1. Onshore Versus Offshore Wind Power Plants

Shown as Figure 4 (left), the result illustrates that the total GHG intensities of onshore (red-colored circles) and offshore (blue-colored circles) wind power plants are 5.84–16.71 g CO₂eq/kWh and 13.30–29.45 g CO₂eq/kWh, while the net GHG intensities are 3.55–10.74 g CO₂eq/kWh and 6.78–22.07 g CO₂eq/kWh. As mentioned above, offshore wind power plants have longer average annual operating times and larger rated power of wind turbines than onshore wind power plants have, which means that they have a higher annual amount of electricity output. It has been reported that about 50% more electricity of offshore wind power plants would be generated if the same wind turbines were installed as its onshore counterparts [42,55].

Besides, shown as Figure 4 (right), there is a slight difference embedded in onshore and offshore wind power plants in terms of GHG intensities’ contribution at each phase from a life-cycle perspective. For onshore wind plants, manufacturing and C&I phases contribute the largest of GHG intensities, while manufacturing and O&M phases are the largest contributors for offshore wind plants to GHG intensities. Since equipped with material intensive facilities especially in foundation construction, offshore wind plants have a larger recycling potential with recycling environmental benefits compared to onshore counterparts. When recycling materials are considered, the average total GHG intensities emitted from onshore and offshore wind plants could be decreased by 36.41% and 41.30%, respectively.

3.2.2. Four Classes of Wind Resource Zones of Onshore Wind Power Plants

As mentioned above, the local wind resource has also played a very important factor that affects GHG intensities from a life-cycle perspective. The zone with better wind resources has been installed with low power rating turbines but with higher production efficiency. As expected, the wind power plants in the class Ⅰ zone with the best wind resource has the lowest average GHG intensity of 9.71 g CO₂eq/kWh. The similar average values of plants in the class Ⅱ, Ⅲ and Ⅳ wind resource zones show the balance between wind resource and technological advances in wind turbines. Comparison among the wind power plants installed with 1.5 MW wind turbines across the four classes of zones (shown as red-colored points in Figure 5) further illustrate the critical role of wind resource plays in alleviating GHG intensities. The average GHG intensities present an increasing trend from class Ⅰ to class Ⅳ, which is 11.04, 12.05, 13.12 and 14.15 g CO₂eq/kWh, respectively. In other words, for the wind power plants equipped with the same rated power of onshore wind turbines, those in the zones with better wind resources have lower GHG intensities.

3.2.3. Different Offshore Distance of Offshore Wind Power Plants

The distance to shore and foundation type of offshore wind power plants are relevant to their GHG intensities with regard to the transportation cost and large quantity consumption of iron and steel materials. In this study, the case operating offshore wind power plants are distributed in the sea with a distance from 4 to 62 km to the shore, and wind turbine foundations include three types: monopile, elevated pile-cap and four-pile jacket. Figure 6 shows the total GHG intensities of offshore cases with regard to different offshore distance and foundations. Overall, the longer the distance, the larger the GHG intensity. In the case of the same offshore distance (12 km) and the same wind turbine foundation (monopile), the wind power plant with larger wind turbines (6 MW) produces 15.8% lower GHG intensity (13.30 g CO₂eq/kWh). In the case of same rated power of wind turbine (3 MW), the wind power plant with elevated pile-cap foundation has higher GHG intensity (21.26 g CO₂eq/kWh) than that with monopile foundation. Similarly, the case plant No. 4 and No. 6 are equipped with the same rated power of wind turbines (6 MW), due to the lower usages of steel, concrete and reinforcement, and the higher annual operating time; GHG intensity of the former is significantly lower than the latter. For the case plants rated at 5 MW wind turbines, GHG intensity of the case plant No. 5 is larger than No. 7 because the annual operating time of the former is lower than the latter, although the usages of wind turbine foundation of these are similar. In addition, as the offshore distance increases, the percentage of the total GHG intensity in the O&M phase also increases, ranging from 23.98% to 55.98%.

3.3. The Second Dimension: Wind Turbine Technology

3.3.1. Different Rated Power of Per Wind Turbine

It is undoubted that the development of turbine technology helps to promote the exploration efficiency of wind resources; however, the enlarging of wind generators also requires more resource inputs. As shown in Figure 7, the average GHG intensities of the onshore wind plants present the evidence of decreasing trends along with the increase of the rated power of wind turbines, which decreases from 12.75 g CO₂eq/kWh (1.5 MW) to 7.39 g CO₂eq/kWh (≥3.0 MW), and offshore counterparts is around 65% higher than the onshore cases in terms of wind turbines rated at more than 3 MW. To have a further comparison by excluding the impact from difference of wind resource, we selected 21 onshore wind power plants from the class Ⅰ wind resource zone with regard to different rated power of wind turbines (red-colored circles in the figure); the same trend can be found that the enlarging of wind turbines helps to reduce GHG intensity. Such a trend is not evident for the offshore wind plants mainly due to the insufficient case number and complex coupled influence from technological advances and wind resource.

3.3.2. Different Rotor Diameter and Hub Height

In addition, a Pearson correlation analysis between the total GHG intensities and other two technical parameters, rotor diameter and hub height, is conducted to further investigate the impacts of technological advances. The red-colored circles in Figure 8 show GHG intensities of onshore wind plants, and the blue-colored circles represent GHG intensities of offshore wind plants. Similar to the impacts of rated power of wind turbines, the total GHG intensities of onshore wind plants have a significant negative correlation (level p < 0.01) with rotor diameter and hub height of wind turbines, while a weak positive correlation is found for offshore cases. It is at least prudent to argue that the enlarging of rotor diameter and hub height of offshore wind turbines does not necessarily bring marginal benefit, due to the increasing cost from construction and maintenance in the current situation of China.

3.4. The Third Dimension: Management Level

The result in Section 3.2.2. shows a trend that GHG intensities increase from class Ⅰ to class Ⅳ. The average GHG intensity of onshore plants rated at 1.5 MW turbines in the class Ⅰ wind resource zone is 11.04 g CO₂ eq/kWh, while that in the class Ⅳ wind resource zone is 14.15 g CO₂ eq/kWh. Therefore, it is obvious that GHG intensity of onshore cases rated at 1.5 MW turbines in the class Ⅰ wind resource zone is 21.98% lower than those in the class Ⅳ wind resource zone. This means that, compared to the wind plants in the class Ⅳ wind resource zone, those in the class Ⅰ zone, assuming 21.98% of wind curtailment rate, will offset the GHG reduction potential caused by geographical location. To reflect the impacts of wind curtailment, we change the functional unit from 1 kWh electricity production (designed) to 1 kWh on-grid electricity (practical) with regard to different provinces faced with the curtailment problem, and assume the average availability of unit wind turbine is 95%. The error bars for 1 kWh on-grid electricity (practical) illustrate the differences in GHG intensities under the highest and lowest curtailment rates recorded during 2013–2020, based on the average GHG intensity per province. It can be found from Figure 9 that wind curtailment has a great impact on the total GHG intensity, especially for the provinces of Gansu, Xinjiang, Jilin and Inner Mongolia.

4. Further Discussions

The result in this study firstly explores the relationship between GHG intensities of onshore wind plants and wind power density of its location, indicating that there exists a negative trend. For offshore counterparts, the result shows that the total GHG intensities tend to increase with offshore distance in a life-cycle perspective, but can be affected by the difference in rated power and foundation types of wind turbines. Similarly, Tsai et al. uses the unified Vestas V112-3.0 MW wind turbines to evaluate the environmental impacts for 20 offshore wind power plants’ siting scenarios, showing that the GHG intensities of wind turbines with tripod and floating foundation increase with the increase of offshore distance [42]. The result of this study also shows that the total average GHG intensity of the wind turbines with monopile foundation offshore distance between 0–15 km is 26.73 g CO₂eq/kWh higher than in this study (14.53 g CO₂eq/kWh). The total average GHG intensities of the wind turbines with tripod and floating foundation offshore distance between 10–30 km are 42.83 g CO₂eq/kWh and 34.44 g CO₂eq/kWh, respectively, but the results are not comparable with this study because of the different foundation and rated power of wind turbines. Raadal et al. analyses the GHG intensities of six same offshore rated power of wind turbine foundation concepts (5 MW) assumed to be located 200 km offshore, comprising five floating and one bottom-fixed, which allows comparisons to be made [17]. The result shows that it is varying from 18.00 to 31.40 g CO₂eq/kWh for floating foundation, and thus compared to the novel foundations, conventional bottom-fixed foundations show the same or higher environmental impacts.

From the perspective of technological dimension, the result in this study shows that the average total GHG intensities of wind power plants decrease as rated power of wind turbines increases. Hub height and blade diameter have positive correlation with GHG intensities of wind power plants. Moreover, some previous studies illustrate wind turbine size is closely related to environmental impacts. For example, Lozano-Minguez et al. demonstrates wind power will become environmentally friendly as the size of wind turbines increases [56], and Caduff et al. calculates GHG payback time for 4161 wind turbine locations determined as the function of hub height and blade diameter of the wind turbine [57]. Nugent and Sovacool explores the relationship between GHG intensity and hub height, showing that GHG intensity of wind turbines with 30 m of rotor diameter is around 200 g CO₂eq/kWh, but those with 124 m of rotor diameter tend to be zero [58], similar to the wind turbines with rotor diameters of 120–130 m in this study (8.40–15.26 g CO₂eq/kWh).

In previous LCA studies of China, wind curtailment has been considered an important factor through setting scenarios, and thus some interesting results have been obtained. For example, Li et al. sets wind curtailment rate as a main variable in order to compare the carbon emission intensity and emission reduction potential of the wind power plant under different scenarios [59]. This research puts wind curtailment as an indicator into one specific case’s life cycle assessment, but it is also applied in the national and provincial aspects. For example, Xu et al. finds that the reduced curtailment can lead to further GHG intensity mitigation of wind power at the national level by 5.4% [5], and Bi et al. thinks high wind curtailment rate leads to large carbon emissions per unit of wind power generation in the northwest provinces of China (Gansu, Xinjiang, Ningxia, etc.) [4].

5. Conclusions and Policy Implications

5.1. Conclusions

The above analysis reveals the GHG intensities from different factors on wind power plants from a life-cycle perspective with the aid of multiple real running cases in China. As an infrastructure intensive industry, the total GHG intensities of wind power plants in China deserve much attention paid to them, with regard to soaring development trends, ambitious goals as well as diversified multi-dimensional differences. Despite the considerable variability in the results, this study provides a fairly holistic understanding of life-cycle environmental impacts of wind power development in terms of GHG intensities. In addition, the impacts from both technical and non-technical factors as geographical location, turbine technology and management level are investigated.

The results highlight the importance of wind resource and technological advances in levelling the GHG intensities, which has different contributions for different wind resource zones as well as onshore and offshore wind power plants. Technological innovations are needed to design and manufacture larger wind power converters with evident marginal environmental benefits before the threshold appears. The results of this study also highlight the necessity for policy interventions in China. For example, to better accommodate renewables and lessen the wind curtailment in consideration of the foreseeable massive installation, China’s future electricity market planning should emphasize flexibility by diversifying generation sources, coordinating renewable energy locations, and optimizing generation and transmission resources across the grid.

5.2. Policy Implications

With regard to the impacts from different influencing factors, wind resource plays a central role in alleviating the overall GHG intensities by providing higher electricity generated with certain input. As a result, manufacturing and C&I being the largest contributors to entire life-cycle phases, the average GHG intensities of offshore wind power plants are significantly higher than those of onshore wind power plants. More explicitly, for onshore wind power plants, wind resource as an important influencing factor is typically evident for the cases in the class I wind resource zone. Offshore distance and the related foundation types determine the GHG intensity in terms of offshore wind power. However, with the expansion of wind power development across China, the marginal difference of wind resource can be offset by technological advances. In other words, enlarging wind turbine size has an obvious marginal utility, i.e., GHG intensities increase with the enlargement in rated power, rotor diameter and hub height. As such, the design and manufacturing of larger wind power converters is the pursuit of technology development. It is worthwhile to note that although achieving rapid development, China is still lagging one generation behind in equipment technology compared to those in Europe. Therefore, technological introduction and innovation are critical for the upgrade of installed equipment quality, which will substantially promote wind resource exploration efficiency and decrease the overall GHG intensities.

As mentioned above, wind curtailment is a typical and severe non-technical problem in China, which has arisen great attention both from the scientific community and policy makers. Obviously, provinces in northern China with rich wind resources suffer from more severe wind curtailment, such as Gansu, Inner Mongolia, Xinjiang and Jilin provinces, which leads to great waste and causes overall environmental impacts. The fundamental reason for wind curtailment in China may be a lack of coordination between wind power plants and electric transmission lines. In such a case, a reasonable development rate should be set and blind rush installation should be avoided in consideration of grid capacity. Special focus should be paid on spatially balancing power generation with demand with regard to wind resource availability, transmission capacity of the power grid, and considering variations in end-user demands [60]. In fact, ultra-high voltage transmission lines are being constructed and policies have been adjusted to reduce the curtailment problem in China. Moreover, joint efforts of multi-stakeholders, such as wind power plants developers, local governments and the central government, should be involved to figure out robust wind power development planning. In this study, the system boundary of wind power transmission only includes the cable to the local 220 kV voltage station, i.e., the power transmission to other regions is not considered. Limited research has been carried out using LCA for wind power transmission systems, but only for offshore, indicating that the total GHG intensity of the North Sea power transmission for GDv05 scenarios is 2.49 g CO₂eq/kWh [61]. At the same time, for avoiding transmission costs and curtailment losses outweighing the higher wind production costs, encouraging wind development in eastern low wind speed regions should be focused on. Combined with reducing wind curtailment and accelerating grid connection, these ways require reform efforts in China’s electric power system to make both the generation and transmission systems more renewable-friendly.

It must be admitted that some limitations inevitably exist in this research. With regard to case collection, this research collected 60 representative running wind power plants. These cases can reflect the condition of the wind power industry in China in certain content, but there is still deviation from the reality. In subsequent research, work with more cases for various wind power plants can be collected to have a better holistic view on GHG intensity evaluation. Besides, some assumptions have to be made due to the lack of detailed data, for instance, proximity production center and average provincial wind curtailment rate, which also might bring together uncertainty to the results. Nevertheless, this study provides well compatible results with the available knowledge, and new insights as well as evidence-based policy implications for the health and development of the wind power industry under the carbon neutrality target in China.