Understanding environmental impacts on initial atmospheric corrosion based on corrosion monitoring sensors

Journal Pre-proof Understanding environmental impacts on initial atmospheric corrosion based on corrosion monitoring sensors Zibo Pei, Xuequn Cheng, Xiaojia Yang, Qing Li, Chenhan Xia, Dawei Zhang, Xiaogang Li

PII:

S1005-0302(20)30023-2

DOI:

https://doi.org/10.1016/j.jmst.2020.01.023

Reference:

JMST 1890

To appear in:

Journal of Materials Science & Technology

Received Date:

12 June 2019

Revised Date:

2 August 2019

Accepted Date:

19 August 2019

Please cite this article as: Pei Z, Cheng X, Yang X, Li Q, Xia C, Zhang D, Li X, Understanding environmental impacts on initial atmospheric corrosion based on corrosion monitoring sensors, Journal of Materials Science and amp; Technology (2020), doi: https://doi.org/10.1016/j.jmst.2020.01.023

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Research Article

Understanding environmental impacts on initial atmospheric corrosion based on corrosion monitoring sensors Zibo Peia, Xuequn Chenga,*, Xiaojia Yanga, Qing Lib, Chenhan Xiab, Dawei Zhanga,*,

a

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Xiaogang Lia,*

Beijing Advanced Innovation Center for Materials Genome Engineering, Key

Laboratory for Corrosion and Protection (MOE), Institute for Advanced Materials and Technology, University of Science and Technology Beijing, Beijing 100083,

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China

School of Material Science and Engineering, Nanchang Hangkong University,

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*Corresponding authors.

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Nanchang 330063, China

E-mail addresses: [email protected] (X. Cheng); [email protected] (D.

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Zhang); [email protected] (X. Li).

[Received 12 June 2019; Received in revised form 2 August 2019; Accepted 19

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August 2019]

Atmospheric corrosion monitoring (ACM) sensors were employed to study the initial atmospheric corrosion of carbon steels over a one-month period in six outdoor dynamic atmospheric environments in China. Based on the ~250000 corrosion data sets collected, the environmental impacts of relative humidity, temperature and rainfall on the initial corrosion behavior of carbon steels were investigated. The results showed that rainfall was the strongest environmental factor influencing the

initial atmospheric corrosion rate. Relative humidity significantly influenced the corrosion of carbon steels in low-precipitation environments and non-rainfall period.

Keywords: Atmospheric corrosion, Corrosion monitoring, Sensors, Carbon steels

1. Introduction As one of the most common form of corrosion, atmospheric corrosion is affected by a variety of environmental factors and is found to widely impact infrastructure,

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transportation, energy and other industries[1]. It is generally believed that the main environmental factors affecting the outdoor atmospheric corrosion rate include

temperature, relative humidity (RH), dew, fog, and atmospheric pollutants[2-4]. The

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mass loss due to corrosion with time generally conforms to the power law[5-8].

RH is considered to be a main environmental factor, and can be reflected by the

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time of wetness (TOW) according to ISO9223 by the International Standardization Organization (ISO)[9, 10]. However, an increasing number of studies have shown that

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TOW cannot be simply represented by RH[11-13] as the relationship between the humidity and the acceleration of the corrosion rate shows remarkably nonlinear characteristics[14, 15]. Moreover, TOW is also affected by the sample thickness,

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roughness, heat transfer, and atmospheric deposition[16, 17]. Environmental temperature is another main environmental factor affecting the atmospheric corrosion rates[18].

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Some studies showed that the influence of temperature on atmospheric corrosion in outdoor environments is considered to be secondary and is only effective with a

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continuous high humidity[12, 19]. Rainfall can also affect the atmospheric corrosion behavior of metallic

materials[20, 21]. Unlike dew and a thin liquid film formed at RH > 80%, rainwater could provide more sufficient and dynamic electrolyte environment for corrosion electrochemical reactions. The effect of rainfall on the corrosion mechanism is complex. On one hand, acidic rainwater can dissolve corrosion products which protect metal surface from further corrosion[22-24]. On the other hand, it can inhibit

atmospheric corrosion by cleaning the surface from corrosive deposits and contaminants. These two mechanisms have opposite effects on the corrosion rates. The corrosion products of different materials may have different solubility in rainwater, and the cleaning effect depends not only on the environment but also on the material surface properties[23, 25]. Therefore, the dominating mechanism in the effect of rainwater is often unpredictable. Previous studies claimed that the cleaning mechanism is dominant so the effect of rainwater on corrosion rates was secondary to other factors such as dews and wet-dry cycles with increased and decreased RH[25, 26].

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Only very few studies have shown that rainfall was the most impactful climatic parameter on atmospheric corrosion[27, 28].

Unlike RH or temperature, the instantaneous and accumulative impacts of

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rainwater on the corrosion processes could only be accurately elucidated based on

corrosion tests taking place in real atmospheric environments. In this view, the use of

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corrosion (and environmental) monitoring techniques is highly desirable. Many types of atmospheric corrosion monitoring (ACM) sensors have been developed for

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applications in transportation and infrastructures. The most common ones are those based on galvanic corrosion cell, electrical resistance and electrochemical impedance. In galvanic-cell type ACM, galvanic couples are assembled based on active metals

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and noble metals or carbon electrodes that are electrically connected. When electrochemical corrosion occurs on the active metal, electrons are transferred from

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the anode to the cathode through wires connected in series of a micro-galvanometer, which can directly capture the magnitude of the current. As a result, the corrosivity of

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the atmosphere is determined by monitoring the magnitude of the galvanic current[2932]

. Unlike the impedance-based sensors, galvanic-cell type ACM sensors can be used

for non-equilibrated electrochemical systems and do not require external polarization disturbed current which is needed to measure impedance information[15, 33]. And compared to resistance-based corrosion sensors, galvanic-cell type ACM exhibited higher sensitivity and better tolerance to temperature variation[15, 34, 35]. In this work, the atmospheric corrosion of carbon steels was continuous

monitored for one month at six different typical atmospheric environments in China by using galvanic ACM sensors. ~250000 corrosion data sets were collected by the ACM sensors and were correlated with the corrosion mass loss obtained by standard coupon exposure tests. Climatic factors including temperature, RH and rainfall were recorded in the meantime. The main environmental factors affecting corrosion of carbon steels in the dynamic outdoor atmospheric environments were studied.

2. Experimental

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2.1 ACM sensor preparation Fig. 1 is a schematic diagram showing the design of the ACM sensor. A 45 steel (carbon steel) anode and a pure copper (>99.5%) cathode were used to assemble the

galvanic corrosion couples. The chemical composition of the 45 steel is given in Table

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1. The electrodes were separated by glass fiber-reinforced epoxy composite boards

(FR4) for electrical insulation. Each sensor consists of a total of seven pairs of metal

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couples. The exposed area of each piece of carbon steel and copper electrodes is 21 mm × 1 mm. The spacing between the metal sheets is controlled by the thickness of

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the epoxy composite (0.1 mm). The electrode assembly was sealed in epoxy and abraded by #1200 sandpaper prior to use. When an electrolyte film is formed on the

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sensor surface, the steel and copper electrodes are connected to generate a galvanic corrosion current.

2.2 Field exposure test

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The atmospheric corrosion monitoring tests were conducted at six standard exposure test sites of National Environmental Corrosion Platform in China. The

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climate types and the classification of atmospheric corrosivity by ISO9223[10] of the six sites were summarized in Table 2. At each site, the ACM sensors and five parallel 45 steel coupons (100 mm × 50 mm × 5 mm) were installed at a distance of more than 1 m above ground and 45° to the south. The humidity and temperature sensors were placed next to the ACM sensor and were exposed to the same corrosive environment (Fig. 2).The exposure tests started in August 2018 and ended in September 2018, lasting for ~30 d. The galvanic current of the ACM sensor was obtained using the

model Qianlang CM-200 as the micro-galvanometer during the test at an acquisition frequency of once per minute. The resolution of the obtained current was 0.1 nA, zero drift of current measurement is no more than 0.3 nA per year, and the current value ranged from 0.1 nA to 50 mA, beyond which the current could not be determined. The mass loss was obtained based on the total area of the six parallel standardized coupons. The corrosion products of the carbon steel were removed by scrubbing with a wire brush in 18wt.% hydrochloric acid solution as specified in ISO8407 C.3.5[36]. After removing the corrosion product, the average mass loss was calculated as the

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difference in the weight of the specimens before and after the exposure tests.

3. Results and discussion 3.1 ACM data validation

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Fig. 3 are the complete data sets of the instantaneous galvanic current on ACM sensors (IACM-instant) obtained over the entire one-month test duration. The

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instantaneous current values obtained at all six test sites were highly fluctuated, reflecting the dynamic nature of atmospheric corrosion. In general, a higher current

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value reflects a stronger environmental corrosivity[30]. In order to better reflect the differences between the corrosivity of the six different environments, the values of

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galvanic current output IACM-instant were integrated over the test time to obtain the electric quantity output (QACM-instant) according to Eq. (1), (1)

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𝑄ACM-instant = ∑ 𝐼ACM-instant × 1 min

where IACM-instant represents the real-time galvanic corrosion current obtained on the

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ACM sensor, and 1 min is data acquisition interval. As clearly presented in Fig. 3(b), the integral electric quantities were different among the six locations, following the trend of Qingdao >> Sanya > Hangzhou > Beijing > Wuhan > Tulufan. According to Table 2, Qingdao has an industrial and coastal atmospheric environment, which is known for a high corrosivity (C5-CX according to ISO9223). Among the six sites, Tulufan exhibits a lowest environmental corrosivity. As an arid area, the average temperature and RH were 36.3°C and 22.1%, respectively. The rainfall time

accounted for only 2.3% of the total exposure test duration. After the exposure tests, the ACM sensors and the standardized coupons were retrieved. The surface appearances of the ACM sensors and the steel coupons after the outdoor exposure were shown in Fig. 4. Both ACM sensors and steel coupons presented uniform corrosion morphologies. The relationship between the average galvanic current for carbon steel on ACM sensors and the corrosion rate of the standardized coupons (rsteel), obtained over the one-month period, are established in Fig. 5, which suggests that the output of ACM sensors could reflect the corrosion

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status of the corrosion coupons.

The carbon steel electrodes and copper electrodes in our sensors formed galvanic couples which accelerated the corrosion process on the carbon steel electrodes. Thus,

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the effect of such galvanic corrosion must be evaluated in order to confirm that the

corrosion kinetics on the steel electrode on the ACM sensors can accurately represent

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that on the standardized steel coupon. The galvanic current density generated between the steel and the copper electrodes ig(A) (mA m-2), averaged over the one-month test

𝑄

ACM 𝑖𝑔(𝐴) = 𝑡×𝐴×10 6

(2)

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duration, can be calculated based on Eq. (2):

where QACM represents the total electric quantity output from the ACM sensor,

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integrated over one-month test duration; t is the duration of test time ( ~ 30 d in this case); A is the total exposure area (7 × 21 mm × 1 mm) of the carbon steel electrodes

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on the sensor surface. It is also reasonable to assume that the galvanic current was entirely generated because of the oxidation of Fe in the steel anodes to form Fe2+ and

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Fe3+ corrosion products. Therefore, rsteel can then be converted into the natural corrosion current density, icorr (mA m-2), of carbon steel without galvanized. icorr was determined using Eq. (3): 𝑖corr =

𝑟steel × 𝑛 × 𝐷Fe 3.27 × 𝐴Fe

(3)

where DFe is the density of iron metal materials (7.86 g cm-3); AFe is the atomic weight of iron (55.845). The value of n is between 2 and 3 considering that the corrosion products contains both Fe2+ and Fe3+. When a galvanic corrosion occurs, the

relationships in Eqs. (4) and (5) are established[37]. 𝑖corr(𝐴) ＜𝑖corr ＜𝑖corr(𝐴) + 𝑖𝑔(𝐴) (4) ratio𝑔 =

𝑖corr(𝐴) +𝑖𝑔(𝐴) −𝑖corr 𝑖corr

＜

𝑖𝑔(𝐴) 𝑖corr

(5)

where icorr(A) represents the natural current density of anodic metal galvanized (carbon steel galvanized on ACM sensors). ratiog represents the ratio of the accelerated corrosion to the natural corrosion of the carbon steel on ACM sensors due to the galvanic corrosion. Table 3 summarizes the values of ig(A), icorr, and ratiog obtained

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from Eqs. (2)-(5). The values of ratiog show that the acceleration effect of the galvanic couple relative to the natural corrosion rates were all less than 10%. Based on these

results, it can be considered that the corrosion status of the carbon steel on the ACM sensor surface was basically the same as that of the corrosion coupon surface.

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Therefore, the instantaneous current from the ACM sensor can be used to reflect the actual corrosion status of the steel in the atmospheric environment.

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The relationship between the average galvanic current of ACM sensors (IACM) and rsteel as shown in Fig. 5 can be fitted using Eq. (6):

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𝑟steel = 60.28±40.97 + 0.1915±0.03 × 𝐼ACM1.2746±0.08 (6) According to Eq. (6), when IACM is 0 nA, the value of rsteel is 60.28 g m-2 a-1, which

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suggests that the ACM sensor cannot show a current response if the natural corrosion rate is lower than 60.28 g m-2 a-1 for any atmospheric environment (corresponding to

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C1~C2 by ISO9223:2012). This phenomenon is attributed to the difficulty in forming a continuous electrolyte film that connects the carbon steel anode and copper cathode

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on the ACM sensor in an environment with low corrosivity. Instantaneous galvanic current can be approximately converted into instantaneous natural corrosion rate by Eq. (6).

3.2 Effect of temperature and RH Figs. 6 and 7 present the variation of temperature and RH during the entire onemonth exposure at the six test sites, respectively. For each site, the plot contains about 30 concentric rings; each ring contains the data collected from 0:00 to 23:59 during

one entire day. A redder color corresponds to a higher value. The empty rings indicate missing data due to power outages. By comparing the results for each location in Figs. 6 and 7, it can be seen that the intensities of temperature and RH distributions were generally opposite. The RH values at higher temperatures were lower. According to Table 2, the coastal areas such as Sanya, Qingdao, and Hangzhou clearly demonstrated high RH values. The humidity distributions were different among the inland areas such as Beijing and Tulufan. Although Wuhan is relatively far from the coastline compared to Beijing, it is known for the high humidity owing to its low

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latitude and sub-tropical humid monsoon climate especially in summer.The full data sets of the galvanic current on ACM sensors are shown in Fig. 8. Compared with Figs. 6 and 7, it is clear that the intensities of the galvanic current at all locations were

highly similar to those of the RH values. From these intuitive presentations, corrosion

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was found to occur mostly at night. In general, the RH is inversely proportional to temperature. Therefore, because of the increase and decrease of the surface

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temperature from sunrise and sunset, respectively, wet-dry cycles are generated on the metal surface. As the temperature decreases at night, the RH increases, promoting the

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condensation of a thicker and more continuous thin electrolyte film on the ACM sensor surface, activating the galvanic corrosion between the steel and the copper

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electrodes. After sunrise, the RH decreases as the temperature rises; and the electrolyte film evaporated and become discontinuous. The intensities of the galvanic currents in Tulufan were mostly below the detectable limit (1 nA) since the local

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atmosphere was too dry to form a continuous electrolyte film on the sensor electrodes.

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3.3 Effect of rainfall

In order to directly observe the dynamic influence of rainfall on the initial corrosion of carbon steels, the rainfall duration in the six regions was recorded. It should be noted that after rainfall the rainwater stays on the metal surface and provides electrolytes for continuous corrosion reactions. This influence is over only after the rainwater completely evaporates. To ensure that the influence of the rainwater was taken fully into account, the rainfall duration noted in this study was from ~10 min

before and ~2 h after the raining process stops. Fig. 9 presents the detailed ACM sensor data obtained over 5 d from Qingdao. The current obtained by the ACM sensor sharply increased when it rained, and rapidly decreased after the rainfall. Typically, the peak of the current occurred when the rainfall begins, and then a relatively high current value was maintained for a period of time. When the rainfall was over, the wet-to-dry process took place, and the galvanic corrosion reaction stopped when the thin electrolyte film evaporated and became highly discontinuous. Laboratory measurement results from previous studies generally showed that during the wet-dry

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cycles, a thick electrolyte film could hinder the oxygen transport, lowering the cathodic corrosion rates; yet when the electrolyte film was too thin, it can hardly form

an effective and continuous electrolyte for corrosion reactions[38]. However, during the dynamic rainfall process, it is speculated that the transport of the oxygen is always

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sufficient because of the continual disturbance of the electrolyte film, which resulted in the highest corrosion currents as detected by the ACM sensor. The non-rainfall

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period in Fig. 9 also presents three current peaks as identified. The three peak values, from high to low, are referring to dewing environment (100% RH), nearly dewing

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environment (97% RH) and general atmospheric environment (90% RH), respectively. The peak values show that, for non-rainfall period the intensity of the

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atmospheric corrosion increases with the environmental RH and dewy atmosphere was more corrosive.

To quantify the influence of rainfall on corrosion, the values of instantaneous

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corrosion rate during rainfall was estimated based on Eq. (6). The contribution of rainfall to corrosion at the initial corrosion stage ratiorainfall is determined using Eq.

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(7).

ratiorainfall =

∑ 𝑟steel-instant-rainfall ×1min 𝑟steel ×𝑡

× 100%

(7)

where rsteel-instant-rainfall represents instantaneous natural corrosion rate when it is raining. Fig. 10(a) and (b) summarized the cumulative rainfall duration and the contribution of rainfall to corrosion mass loss at the six sites, respectively, and the calculation error ranges were also shown according to the fitting error of Eq. (6).

Since Eq. (6) is in exponential form, the calculation error would increase with the increasing value of corrosion mass loss. For Tulufan, most of the test time (97.7%) were sunny and cloudy, and 90.4% of the total mass loss occurred during this period. This result suggests that the main cause of corrosion in arid areas like Tulufan is the changes in the humidity and temperature. For the other five areas, rainfall accounted for 16.3%-29.7% of the total test time but contributed to 64.6%-89.0% of the corrosion mass loss. The opposite effects of rainfall on metal corrosion has been recognized. The corrosive deposits and contaminants on the ACM sensors surface

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were repeatedly washed by rain, which would inhibit corrosion. In terms of direct observation, corrosion increased significantly during rainfall, corresponding to the

promoting effect. Therefore, it can be concluded that during the initial corrosion stage of the carbon steels, although the influence of moist atmosphere cannot be ignored,

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rainfall has a greater effect than the RH. In the initial stage of atmospheric corrosion, fewer corrosion products were formed, making it difficult for the steel surface to

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absorb water from the atmosphere to effectively form an electrolyte film. As the corrosion stage moved into the middle and later stages and the rust layers became

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stable, the promotion effect of rainfall may be diminished. 3.4 Effect of atmospheric deposition

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Limited by the immaturity technology for real-time monitoring pollutant deposition, the chloride deposition level was measured in Qingdao and Wuhan sties following the ISO 9225[39] norm (also called the wet candle method) during the test

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time, respectively were 71.03 mg m-2 d-1 and 0.44 mg m-2 d-1. The chloride deposition levels were much different due to the geographical location. Meanwhile the average

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temperature and relative humidity data collected in Qingdao and Wuhan were close during the test time, respectively were 28.6 °C and 30.8 °C, 79.2% and 73.3%. Consequently, the final electricity output values of the ACM sensors were 5.62 C in Qingdao and 0.54 C in Wuhan. Different chlorine deposition would lead to different corrosion rate of carbon steel[9], which is also reflected in the difference of electricity output of the sensor. In addition to the recognized corrosive factor, the instantaneous current of ACM sensor was also increased by the aerosol deposition[40] which had

been proved. As a result, atmospheric deposition has a big influence on the monitoring results of ACM.

4. Conclusion Atmospheric corrosion in six typical outdoor atmospheric environments was monitored using galvanic-cell type ACM sensors consisting of 45 steel anodes and pure copper cathodes. The impacts of climatic factors including RH, temperature and rainfall on the initial stage of atmospheric corrosion were studied. The results showed

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that the atmospheric corrosivity can be quantitatively evaluated by the ACM sensor for C2 or more corrosive environments (according to ISO9223). The results from the ACM sensors demonstrated a good correlation with those obtained from corrosion

mass loss on standardized steel coupons. During the initial atmospheric corrosion of

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the carbon steels, the effect of RH was stronger than that of the temperature. The most impactful climatic factor for the initial atmospheric corrosion was rainfall except for

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an arid environment (e.g. Tulufan). Our future work will focus on quantitatively modelling the influence of the variation of the dynamic electrolyte film on the ACM

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current response and also on assessing the ACM corrosion data during longer-term

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corrosion tests.

Acknowledgments

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This work was supported by the National Key Research and Development Program of China (Nos. 2017YFB0702100 and 2016YFB0300604) and the National

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Environmental Corrosion Platform.

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Program: Summary of Results: Developed by ISO/TC 156/WG 4, Atmospheric Corrosion Testing and Classification of Corrosivity of Atmosphere, ASTM International, 2010, pp. 10-65. [10] B. ISO, The British Standard Institute, 2012.

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[27] S.L. Zelinka, D. Derome, S.V. Glass, Build. Environ. 46 (2011) 2060-2068. [28] S.L. Zelinka, S.V. Glass, C.R. Boardman, D. Derome, Corros. Sci. 102 (2016) 178-185. [29] D. To, T. Shinohara, O. Umezawa, ECS Transactions, 75 (2017) 1-10. [30] D. Mizuno, S. Suzuki, S. Fujita, N. Hara, Corros. Sci. 83 (2014) 217-225. [31] F. Mansfeld, J. Kenkel, Corros. Sci. 16 (1976) 111-122. [32] F. Mansfeld, S. Tsai, Corros. Sci. 20 (1980) 853-872. [33] A.P. Yadav, F. Suzuki, A. Nishikata, T. Tsuru, Electrochim. Acta 49 (2004) 2725-2729. [34] B. Kamsu-Foguem, Adv. Eng. Inform. 26 (2012) 859-869. [35] Z. Li, D. Fu, Y. Li, G. Wang, J. Meng, D. Zhang, Z. Yang, G. Ding, J. Zhao, Materials 12 (2019) 1065.

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450.

Table list Table 1 Chemical composition of 45 steel (mass%).

C

Si

Mn

S

P

Ni

Cr

Cu

0.47

0.18

0.59

0.010

0.014

0.015

0.016

≤0.01

Table 2 Location and climate information of six standard exposure test sites.

Location

Longitude and

Climate type

latitude

corrosivity by ISO Rural dry-hot

Tulufan temperate 114.26, 30.58

Urban humid

Wuhan subtropical 116.35, 39.99

Urban warm

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Beijing

C1-C2

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89.22, 42.92

Atmospheric

C3-C4

C3-C4

temperate

Coastal humid

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109.36, 18.29 Sanya

C4

tropical

Industrial humid

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120.51, 30.37 Hangzhou

C4

subtropical

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120.44, 36.07 Qingdao

Coastal, Industrial humid temperate

C5-CX

Table 3 Effect of galvanic corrosion on corrosion rate of carbon steel on ACM sensors.

Exposure

ig(A) (mA m-

site

2

Tulufan

icorr (mA m-2)

ratiog

0.09

6.35-9.52

＜1.4%

Wuhan

1.22

17.27-25.91

＜7.1%

Beijing

2.09

22.03-33.04

＜9.5%

Sanya

3.15

44.38-66.57

＜7.1%

Hangzhou

3.38

43.68-65.52

＜7.7%

Qingdao

13.11

219.60-329.40

＜6.0%

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Figure list

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Fig. 1. Fe-Cu galvanic atmospheric corrosion monitor (ACM) sensor.

Fig. 2. Setup of ACM sensors and standardized coupons exposed at Sanya site.

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current, (b) electric quantity.

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Fig. 3. Real-time data of ACM sensors during one-month exposure test at 6 sites: (a) galvanic

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Fig. 4. Surfaces of ACM sensors and steel coupons after one-month exposure tests at different

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sites.

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Fig. 5. The relationship between the one-month average corrosion rate of the carbon steel and the one-month average galvanic current from the ACM sensor.

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Fig. 6. Temporal distribution of environmental temperature for 6 exposure test stations: (a)

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Hangzhou, (b) Sanya, (c) Beijing, (d) Qingdao, (e) Wuhan, (f) Tulufan.

Fig. 7. Temporal distribution of environmental RH for 6 exposure test stations: (a) Hangzhou, (b) Sanya, (c) Beijing, (d) Qingdao, (e) Wuhan, (f) Tulufan.

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Fig. 8. Temporal distribution of ACM sensors galvanic current for6 exposure test stations: (a)

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Hangzhou, (b) Sanya, (c) Beijing, (d) Qingdao, (e) Wuhan, (f) Tulufan.

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Fig. 9. Variation of 45 steel ACM sensor current during raining time in Qingdao.

Fig.10. (a) Cumulative rainfall/non-rainfall duration during one-month exposure test; (b)

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contribution of rainfall/non-rainfall period to corrosion mass loss.