Role of rumours and locals’ perceptions on the level of environmental impacts of Lynas Advanced Material Plant, Kuantan, Malaysia
Husna Jamaludin *, Arianto Patunru, Kuntala Lahiri-Dutt Crawford School of Public Policy, ANU College of Asia and the Pacific, The Australian National University Canberra, ACT, 0200, Australia
A number of factors influence how people perceive environmental impacts of an industrial or a development project. This paper examines the role that rumours play in shaping public perceptions. It reports a study carried out in 2015 among residents living around a rare earth processing plant, the Lynas Advanced Material Plant (LAMP), in Kuantan, Malaysia. Primary data, derived from a semi-structured questionnaire-based survey of 570 respondents and interviews with experts, collated with secondary data from various sources, show that re-spondents generally perceived LAMP to be dangerous. However, such perception is only evident in the long-term. Estimation results reveal that those who received information from rumours perceived LAMP to be dangerous. Other variables, such as education, gender, race and socio-cultural factors, also play vital roles in influencing people’s perceptions. The links between public perceptions, experts’ views and data disclosure, once revealed, may inform best practice and help to better understand how the public gauge risk.
1. Introduction
The impact of a rare earth processing plant, the Lynas Advanced Material Plant (LAMP), in Pahang, Malaysia remains in dispute. Despite that LAMP has support from the previous Malaysian government, local communities consider it harmful to the environment, human health and the livelihoods of local people (Jamaludin and Lahiri-Dutt, 2017). Their views could be based on the news raised by the Lynas engineers, about poor structural integrity of waste storage that may contribute to high sulfuric acid emissions into the air (Bradsher, 2011); and/or based on a scientific study conducted by an appointed expert1 who warned the possibility of environmental problems arising from the improper waste management of LAMP. For instance, toxic wastewater discharged in an open-channel can seep into the groundwater and flow into the Balok River and the South China Sea (Schmidt, 2013). This two information
were described in mass media2 (Phua, 2016; Waste Management World, 2013; Save Malaysia Stop Lynas, 2011).
If the above information are accurate, the quality of local production, such as of plants, aquatic flora and fauna, may be affected, and poten-tially no longer safe for consumption, as they absorb rare earth elements (REE) during their growth (Hongyan et al., 2002; Mayfield and Fair-brother, 2015; Zhang et al., 2000a). Air pollution due to rare earth dust exposure is also associated with lung cancer (Chen et al., 2004), pneu-moconiosis (Yoon et al., 2005; Sabbioni et al., 1982) and interstitial lung fibrosis (Porru et al., 2001). If local production is contaminated, eating local goods may be harmful for locals’ health, because even food con-taining low-dose REEs has detrimental effects on human health in the long-term (Li et al., 2013; Zhang et al., 2000a, 2000b).
This paper has four objectives. The first objective is to uncover locals’ perceptions about LAMP. People’s perceptions are categorised into two:
1 Gerhard Schmidt was appointed by the local NGOs to conduct a study on environmental impacts of LAMP (see 3.3.4 for the details). 2 It should be noted that although the issue was raised by the Lynas engineers and a scientific study has confirmed the possibility of environmental problems of
LAMP operation, the explanation given by the mass media and those who read the news are different when the information was transferred to the third party. For example, it was stated that LAMP causes environmental hazard (McCoy, 2013) and subsequently affects humans’ health (Idris, 2012). However, the word “possi-bility” used by the experts is to show that there is a chance of environmental problem to occur, and it does not mean that LAMP has caused environmental problems, and thus will affect humans’ health. This mismatch gets even worse when the third party transfers the unconfirmed information to a larger group based on their own understanding. This is the case when the locals believed LAMP is a nuclear reactor (Misa, 2012), which is not true.
general and specific perceived LAMP impact. The specific perceived impacts of LAMP are classified into short-term (1 ¼ less than five years from 2015) and long-term (2 ¼ more than ten years from 2015).3 The impacts are further classified into four main areas of enquiry4: i) How do people perceive the LAMP’s impacts on environmental quality? ii) What are the perceived impacts of changes in the environmental quality on local production? iii) What are the perceived impacts of changes in the environmental quality on human health? and iv) What are the perceived impacts of changes in local production on human health? The second objective is to investigate the consistency of public perceptions with the experts’ views. The third objective is to examine the results from the scientific data and the last objective is to examine the roles of rumours, if any, in influencing communities’ perceptions.
Understanding perception is important because perception affects people’s behaviour (e.g. Shi and He, 2012). When people perceive that there is a risk or negative effect associated with some activities, in normal circumstances they will respond so as to mitigate the risks perceived (Brewer et al., 2004; Sj€oberg, 1999; Slovic et al., 1981). The actions taken in response to public perceptions will have consequences in terms of costs borne by the public per se, the industry and the policy makers. This study will contribute to the literature of rare earth elements (REEs) in terms of perceived or subjective assessment.
This paper is structured as follows: it presents the methods used, and then discusses the results and findings. The conclusion provides a summary and recommendations.
2. Data & methods
This paper employs primary and secondary datasets. Primary data were collected via a semi-structured questionnaire distributed to 570 respondents located in five areas (Beserah, Semambu, Tanjung Lumpur, Teruntum, and Inderapura). Fifty-eight per cent of respondents were Malay ethnic and were surveyed on a home-to-home basis. They were selected randomly (via random number generator,5 available online) based on data6 requested from the election commission of Malaysia (see appendix – Map 1). Due to a lower rate of response among non-Malay respondents, the remaining 42% were surveyed using an online survey method via Facebook and website links. 7 Assistants and/or represen-tatives of the State Assembly, the Vice-President of Pan-Malaysian Is-lamic Party, and Member of Parliament of Kuantan were contacted to distribute the links. The links were also shared on the Facebook pages of Kuantan and respective areas.
Two pilot tests were conducted to test the clarity and validity of the questionnaire. The first pilot test was conducted with 32 people for four different groups (fishermen, sellers and buyers, local residents and anti-
Lynas group); and close-ended perception questions were changed into open-ended questions as people had lot to say. The sample area also had to be expanded because those who live in the city area are more con-cerned with the LAMP issue and the Malay group (mostly located in Paya Besar) was claimed to have been enjoying the benefit of being employed by LAMP. The second pilot test was conducted with 90 people to check the relevance of new areas and it is found that Paya Besar is not relevant for further analysis because most of them had no idea about LAMP.8
The questionnaire was designed in three different languages: En-glish, Bahasa and Mandarin (based on the advised given by one of the representatives of State Assembly in the study area). The Mandarin version was designed by a Chinese research assistant and the questions were asked by a hired group of local Chinese. The responses received were then translated into English.9 The interviewers were given a detail briefing before data collection to ensure all of them have understood the items in the questionnaire. Some further questions were asked to the interviewers to ensure they could deliver the message as intended.
Interviews with relevant experts from four sources – the Department of Environment (DOE), the Atomic Energy Licencing Board (AELB), the LAMP and an external institute – have been conducted in person or via email correspondence. Secondary data were collected from various sources, such as reports on the LAMP prepared by the €Oko-Institut e.V.10
in Germany, published articles, the websites of Lynas Corporation and civil society groups such as ‘Save Malaysia, Stop Lynas’, media reports, and printed materials provided by the DOE, Lynas Corporation and groups opposing LAMP. Data on air and river quality in the area were obtained from the DOE.
The data were analysed in four distinct ways. First, questionnaire data on public perceptions are analysed using a descriptive analysis and cross tabulation. Second, a descriptive method is used to address data from interviews with the experts. The scientific data concerning air and river water quality being incomplete, in the third section, an interpo-lation technique using cubic spline is used to estimate the missing values. Air quality data are then compared with the DOE and the World Health Organisation (WHO) standards, while river water data are compared with the Water Quality Index (WQI), to determine the relative pollution levels in the area of LAMP. Last, an ordered logit estimation is used to examine the role of rumours on public perceptions.
3. Results & findings
3.1. General perception of LAMP
In general, majority of the respondents (72%) believed that the plant was dangerous (Table 1 – see ‘total’ column). Of this number (not in the Table), 83% perceived LAMP to be more dangerous than other chemical factories in the area because it may cause either severe health defects like cancer (51%), or minor health problems such as headaches or irri-tation to the eyes, throat and nose (32%). A small percentage of the sample (12%) believed that LAMP was not dangerous at all, and approximately 16% declined to offer a judgement, citing a lack of knowledge.
3 This distinction was made because people may not worry about the short- term effects due to their low-level impacts, but may be concerned with the long-term cumulative effects as some studies showed that they could be detri-mental (Wei et al., 2013; Chen et al., 2004; Zhang et al., 2000b).
4 The four categories are formed based on the problem raised by the Lynas engineers (Bradsher, 2011) and the study conducted on LAMP case by Schmidt (2013). Literature on rare earth mining is also referred (Mayfield and Fair-brother, 2015; Li et al., 2013; Yoon et al., 2005; Chen et al., 2004; Hongyan et al., 2002; Zhang et al., 2000a, 2000b; Porru et al., 2001; Sabbioni et al., 1982).
5 http://stattrek.com/statistics/random-number-generator.aspx. 6 The data is in the PDF file which consists of 122,000 people and their de-
tails. Their addresses were used to survey the respondents at their home. 7 An independent sample t-test was conducted on 245 non-Malay respondents
to determine if there are differences in their perceptions about LAMP’s impacts based on sampling methods: random and non-random. The results showed that the perceived impacts of respondents in random sampling method has no sta-tistically significant differences (M¼1.06, SD ¼ 0.02) compared to respondents in non-random sampling method (M¼1.12, SD ¼ 0.12), t (7.4) ¼ � 0.52, p ¼0.62.
8 Before conducting the pilot tests, an officer in the Department of Environ-ment (DOE), who monitored LAMP project was consulted to determine the internal validity of the survey questions. A few items designed were not appropriate in the current context. For instance, ‘air pollution from LAMP’s operation contaminates local crops’, and affects local livestock’. According to the officer, local crops and livestock are not affected. The word used for ‘fish’ was also not appropriate and it was suggested to change it to ‘aquatic’, which has a broader meaning.
9 Interview bias may arise from the re—translation procedure because back- translation method was not used. 10 A non-profit environmental research and consultancy institute in Germany
which provides advice to policymakers, NGOs, institutions and companies.
High number of response (79%) saying LAMP is dangerous were found in Teruntum area (31 km from LAMP), among non-Malay ethnics (88%), and among male respondents (73%). There seemed to be no significant difference in perceptions of LAMP across age categories or across reported incomes, but the percentage of those who believed that LAMP was dangerous was higher among recipients reporting tertiary education (84%). Mann-Whitney U test and Kruskall-Wallis H test are used to compare respondents’ general perceived impact of LAMP based on districts, race, gender, age, education, and income (see Appendix – Fig. 1). The distributions of perceptions with regards to districts, races (Malays or non-Malays), education and income level are statistically different at the 1% level; but there is no significant difference between male and female, and between age groups.11
3.2. Specific perception of LAMP
The specific perceived impacts of LAMP are classified into short- and long-term. These impacts can be broken down into four main areas: environmental quality; environmental quality and local production; environmental quality and human health; and local production and human health. A Likert scale is used to rate the perceived impacts of LAMP in the four aforementioned areas between 1 and 6 (where 1 ¼absent, 2 ¼marginal, 3 ¼moderate, 4 ¼ serious, 5 ¼ very serious, 6 ¼ I don’t know).12 We first compared these responses based on the short- or long-run perceived impacts, using Wilcoxon signed-rank test. We found that people’s responses to 14 perception questions about LAMP impacts were statistically different at 1% between short-term and the long-term impacts (see Appendix – Fig. 2).
To simplify the analysis, the impacts were classified into three cat-egories: ‘1’ or ‘low’ comprises ‘absent’, ‘marginal’ and ‘moderate’ im-pacts, ‘2’ or ‘high’ comprises ‘serious’ and ‘very serious’ effects, while ‘3’ is ‘I don’t know’.13 The result is presented in Table 2.
3.2.1. Environmental quality In the short-term, about half of respondents saw the impacts of LAMP
are low on the air quality (59% of respondents) and water quality (57%). People were not very concerned with air quality because some of them believed that smoke released by LAMP is similar to that released by other factories, while some others believed that sources of pollution like bauxite industry and trucks passing on the road had more severe im-pacts. With regard to river water pollution, respondents perceived that as long as no dead fish were floating on the surface of the water, the river are in good condition. For both soil (57%) and groundwater (49%) is-sues, the short-term impacts were also seen by the respondents to be low. In the long-term, however, about half of the respondents anticipated that the effects of air (60%), river (64%), soil (50%) and groundwater pollution (55%) may have high level of impacts.
3.2.2. Environmental quality and local production Approximately half of the respondents perceived the short-term
impacts of LAMP’s air pollution and river pollution on local food sold in stalls (55%) and aquatic life (51%) to be low level of impacts. Due to LAMP’s location approximately 5 km from the South China Sea, some respondents believed that the wind from the sea would blow smoke somewhere else, or that it might be absorbed by nearby trees and plants. Meanwhile, they believed that fish and other aquatic fauna in the river could swim away from pollution to safer and cleaner waters. Asked about the impacts to downstream beach aquatic life, more than one fifth (27%) of respondents perceived the impacts to be unknown because they could not imagine that LAMP’s treated wastewater impact could reach that far. In the long-term, however, more than half of the respondents believed that air and river pollution from LAMP may have high impacts on food (57%) and river aquatics (66%), and 46% believed the impact on beach aquatic life may also be high.
Table 1 General perception & characteristics of respondents.
Source: Authors’ calculation based on the field survey. Note: EQ (environmental quality), LP (local production), and HH (human health).
11 Given than the variables are categorical, we also run chi square test of in-dependence. The results are similar with those above. 12 For the detail’s definition of the Likert scale, see Questionnaire (under the
Definition of outcome) in the Appendix.
13 Wilcoxon signed-rank test found similar results for both six likert scale and the simplified likert scale in terms of their significance level.
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3.2.3. Environmental quality & human health A large number of respondents answered that they did not know
about the perceived short-term impacts of the LAMP’s air (28%), river (29%), soil (36%) and groundwater (36%) pollution on human health because they have no medical expertise. Half of them, however, ex-pected that the effects of air (54%) and river pollution (51%) on human health may be high level of impacts in the long-term, while for soil and groundwater pollution, about 43 percent of them perceived the long- term impacts may be serious or very serious.
3.2.4. Local production & human health The effects of LAMP’s perceived environmental impact on human
health via the consumption of local produce were believed, at least in the short-term, to be unknown (27–29%) and low impacts (38–41%). However, approximately two fifths of respondents (42–48%) believing that the long-term impacts may be high level of impacts due to the accumulated effects.
3.2.5. Summary There is a marked inconsistency in people’s perceptions of LAMP’s
environmental impacts. In general, majority of them (72%) expressed a belief that the plant was dangerous. Nevertheless, the short-term im-pacts of the LAMP were mostly seen as being low impacts, rated as ab-sent, marginal, moderate or unknown. The long-term impacts, meanwhile, were consistently perceived to be serious or very serious (42–66%); and as noted, the people’s responses to 14 perception ques-tions about LAMP impacts were statistically different at 1% between short-term and the long-term impacts. However, the percentage of re-spondents expressing serious long-term of LAMP was still lower than the 72% who expressed a general belief that the plant may pose a danger. This inconsistency may be due to the influence of rumour-spreading. A point to which we will return.
3.3. Experts’ views
Experts’ views were sought to understand if there is a mismatch between public perceptions and experts’ opinions. We consulted four experts: an official from DOE, another official from AELB, a radiological safety advisor from Lynas Corporation, and a former specialist from the €Oko-Institute who was appointed by a local environmental group to analyse the Environmental Impact Assessment (EIA) document prepared by Lynas Corporation.
3.3.1. The Department of Environment (DOE) The officer stated that LAMP has no significant impacts on the
quality of air, river water, soil and groundwater in the area. This, ac-cording to the officer, is because Lynas Corporation complies with Malaysia’s environmental regulations and requirements, and applies technologies, such as a waste gas treatment system and a chemical and biological treatment system, to reduce the effects of air emissions and its effluents. The DOE representative went on to note that the LAMP also monitors air, river water and groundwater in the area to ensure no issues arise from their operation.
3.3.2. The atomic Energy Licensing Board (AELB) Dr. Teng Iyu Lin, an expert with 15 years’ experience in radioactive
waste management who has been working for the AELB, declared that the LAMP is safe, and will not affect the environment in either the short- or long-term. The interviewee gave two reasons for this conclusion: first, the naturally occurring radioactive materials (NORM) with which the LAMP deals are within a safe background level, and second, a
Radiological Impact Assessment (RIA) showed that the LAMP’s radia-tion is within permissible dose limits.14 The interviewee also noted that all LAMP effluents are checked and are only released into the environ-ment if they are below permissible limits, thereby mitigating any negative effects.
3.3.3. Lynas Corporation Dr. Ismail Bahari is a radiological safety advisor for Lynas Corpora-
tion. He argued that LAMP does not have any impact on the local environment, local production or human health. This, he claimed, is because LAMP complies with national emission standards. Specifically, LAMP would not pollute the air because it uses a five-stage Waste Gas Treatment Plant (WGTP), which filters out dust, sulphur dioxide, sulphur trioxide and toxic gas, ensuring only clean air meeting standards set by the DOE is released. Two monitoring systems, a Continuous Emission Monitoring System (CEMS) and Aerosol Monitoring System (AMS), are also installed.15
He also noted that LAMP has no impact on river water because no wastewater that has come into contact with radioactive material is released. All such water is fully recycled, and the wastewater that does not come in contact with radioactive material is treated in a Waste Water Treatment Plant (WWTP). Only water that complies with a standard set by the DOE is discharged, and Lynas and the DOE monitor this water’s quality. Further, all processing areas are built on a bunded secondary containment concrete structure, thereby protecting soil quality. Any acid spills will be contained in the bund, and residue is stored in an engineered Residue Storage Facility (RSF) to prevent contamination of underground soil. This residue is also kept wet to prevent airborne dust from contaminating surface soil.
3.3.4. Gerhard Schmidt, a former researcher in the €Oko-Institute He is a specialist of 26 years in chemical technology, radioactive
waste management and final storage, environmental and radiological impact assessment and remediation of radioactive sites. According to Schmidt, Lynas Corporation has not applied the current Best Available Technology (BAT)16 to reduce the LAMP’s impacts. With regard to air pollution, the treatment systems for abating emissions of acidic gases and dusts are below BAT standard, and thus may cause sulfuric acid emissions. In addition, Schmidt noted that elsewhere in the LAMP, separated rare earth oxalate is roasted in a furnace oven and the waste gas is discharged directly into the air, contributing to air pollution.
Schmidt also noted that in the preliminary EIA and other documents, Lynas did not provide information about the by-products of its ore concentrate and the specific constituents of its wastewater, meaning calculations cannot be made about the environmental consequences. Nevertheless, the LAMP’s liquid emission reduction is below BAT stan-dards, meaning the already high Chemical Oxygen Demand (COD) concentration in the Balok River will increase further, affecting river water quality. Lynas, Schmidt found, did not even identify the reasons for the high COD of 2000 mg per litre in LAMP’s waste water. If the reason is sulphite, no microbes will be able to survive until the sulphite is finally oxidised, which will consume a large amount of the dissolved oxygen (DO) in the river.
Schmidt also noted that without the use of a pipeline, toxic waste
14 The national and international Annual Dose Limit for the public is 1mSv/ year. The LAMP’s radiation exposure to the public is about 0.002mSv/year, although for some workers at the LAMP their exposure is about 2mSv/year. 15 The CEMS was installed to monitor the quality of air released at the stack,
and the AMS was installed on site and at IPD Kuantan to monitor radiation levels in the air. 16 BAT, based on the precautionary principle, requires that a company should
not produce any impacts on the environment, but if this requirement cannot be fulfilled, they have to reduce environmental impacts to the smallest technically possible or to at least as low as what others have demonstrated is possible.
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elements might leach into groundwater. The design of the RSF is not state-of-the-art, and should use 2.5 mm HDPE and at least two 25 cm layers of clay, instead of 1 mm HDPE and only a single 30 cm layer of clay. This inappropriate layout, Schmidt claimed, will result in leakage even under normal operating conditions and will affect soil composition and groundwater. Schmidt, therefore, concluded that the negative im-pacts on the environmental quality as a result of LAMP’s activity may have negative repercussions on the river aquatic, but unknown effects on other subsequent impacts. Extensive monitoring has to be undertaken to evaluate the results.
3.3.5. Summary The authorities and the company shared the same views, supporting
that the LAMP’s operation would not cause detrimental effects to the environment and human beings. The external expert, on the other hand, believed the opposite. Despite their inconsistency in perceiving the general and specific impacts of LAMP, local perceptions overlapped with the views of these experts. In the short-term, some of them (10–13%) perceived that LAMP may have no effect on the environmental quality. This is in line with the company’s and the authorities’ views, which believed the impacts are absent. About 72–83% of the respondents, nevertheless, believed that there were some impacts on the environ-mental quality, ranging from marginal to very serious. Their perceptions were in line with Schmidt, who believed that without applying the Best Available Technology (BAT) technique, LAMP may produce some negative impacts to the surroundings.
With the exception of perceived air pollution on food and perceived river pollution on river aquatic, as people imagine the impacts, rated as marginal to very serious (80–83%), the subsequent impacts were mostly (27–36%) rated by the locals to have unknown impacts in the short- term. These perceived impacts were parallel with Schmidt’s views. However, Schmidt also viewed the impact to be unknown for perceived effect of air pollution on food. This view is contradictory to the company and the authorities as they believed there are no subsequent effects because the environmental quality is not being polluted.
However, in the long-term, about 69–79% people expected that there may be some impacts, ranging from moderate to very serious due to their accumulated effects. This view was contradicted with the company and the authorities, who maintain that there is no long-term impact arising from LAMP. For the subsequent long-term impacts, except for the food (76%) and river aquatic (79%)—rated to be moderate to very serious—more than one-fifth of the sample (25–35%) rated the subse-quent impacts to be unknown. This view was supported by Schmidt with the exception of food impact. Nevertheless, more than half of them (53–62%) perceived that the long-term impacts may be serious or very serious and Schmidt advised a detailed monitoring activity should be conducted to determine the impacts.
3.4. Monitoring data on air and river water quality
Data collected from monitoring systems reveals the current quality of the environment around LAMP, thereby proving whether the experts’ views are representative of the facts and providing a basis to compare with the public perceptions.
3.4.1. Data on air quality To measure air quality in Malaysia, the DOE use the Air Pollution
Index (API) (Asian Development Bank, 2006). The API includes all major pollutants, namely ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2) and suspended particulate matter of less than 10 μm in size (PM10). Prolonged exposure to CO could cause people to lose consciousness and suffocate because it displaces oxygen in the blood and deprives the heart, brain and other vital organs of oxygen (U.S Department of Labour Occupational Safety and Health Administration, 2002). NO2 is a reactive gas which can irritate the lungs and weaken resistance to respiratory infections (Niedell, 2004). Exposure to SO2
could affect breathing, causing respiratory problems, alterations in pulmonary defenses and aggravation of existing cardiovascular diseases (Australian Government Department of Environment, n.d). And the major concerns around PM10 exposure are breathing and respiratory problems, premature death, lung tissue damage and cancer (Nargesh, 2015). The DOE did not require Lynas to report ozone because ozone measures are affected by factors like smoke produced by other factories. It is for this reason that the data were disaggregated only on CO, NO2, SO2 and PM10.
The monitoring data were collected at four open spaces: A1, A2, A3 and A4.17 Table 3 below presents the amounts of each pollutant detected in five separate years, alongside their means, the limits set by the DOE and the WHO’s recommended guidelines (2005). The monthly data were collected from the DOE with some missing values. Thus, the numbers provided in Table 3 are generated through interpolation technique where known data points from the original function were used to esti-mate a new data. Cubic spline method using Maple 10 was employed to interpolate the data because the available data were non-linear and fluctuated.18
The result shows that LAMP pollution levels were below the re-quirements set by the DOE. Nevertheless, based on the WHO standards, LAMP has exceeded advisable limits of PM10 three times in five years, especially at site A3. Exceeding the limit of PM10 standard would most likely to affect the elderly, children and those who have respiratory problems (USEPA, 2018).
3.4.2. Data on river water quality To measure water quality, the DOE uses six parameters to calculate
Water Quality Index (WQI): dissolved oxygen, biological oxygen de-mand, chemical oxygen demand, suspended solids, pH and ammoniacal nitrogen.
Dissolved oxygen (DO) is free oxygen (O2) in the water (Fondriest Environmental, 2013b); a high level of DO indicates better water qual-ity. Biochemical oxygen demand (BOD) is the amount of oxygen consumed by bacteria and microorganisms in water (USEPA, 2012). Discharge of effluent with high BOD will accelerate bacterial growth which consumes DO, which can be lethal for fish and aquatic insects (Northeast Georgia Regional Development Center, n.d). Chemical oxy-gen demand (COD) also measures organic compounds in water, but COD coverage is wider as it predicts oxygen requirement during the decom-position of organic matter and the oxidation of inorganic chemicals (Amneera et al., 2013). Power of hydrogen (pH), on a scale of 0–14, reflects how acidic or basic a body of water is, with lower numbers being more acidic and higher numbers more basic (Fondriest Environmental, 2013a). Suspended solids (SS) are made up of organic and/or inorganic materials. Higher degrees of SS reduce water clarity and pollute water, increasing water temperatures because they absorb heat, reducing DO (Fondriest Environmental, 2013b). Finally, ammoniacal nitrogen (NH3–N) indicates nutrient status, organic enrichment and the health of a water body (Amneera et al., 2013). High concentrations of AN cause alga problems which increase the demand for oxygen (USEPA, 2016). The formula used to calculate the WQI is shown in the Appendix (Table 1).
For this study, water sampling data collected by Lynas consultant in the Balok River was used, paying particular attention to two of the eleven locations in which they sampled: W10 (100 m downstream from the LAMP final discharge point) and W11 (750 m upstream from the LAMP final discharge point).
17 A1 is located at the south east corner of LAMP’s site, A2 in the north east portion of the site, A3 at the south west corner of the site, and A4 in the west quadrant of the site. 18 The available data on each of the air quality component were put in a
formatted equation and the missing period/value was generated using the cubicspline command.
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Based on the DOE’s classification of WQI (see Appendix - Table 2), the overall river water quality across the five years at both sites can be categorised as either slightly polluted or polluted.
W10’s readings were more polluted compared to W11’s readings, shown in Table 4, probably due to its proximity to LAMP (100 m, compared to 750 m for W11). Based on this result, LAMP operation may have an impact on river water. However, this finding should be explained carefully as pollution in both locations was technically ‘non- point source pollution’, meaning that many other factories contribute to the deterioration of the water quality.
3.5. Role of rumours in influencing perception
Rumours are unconfirmed messages passed from one person to another (Buckner, 1965); and they are socially infectious because they originate in legitimate social networks and play on feelings of uncer-tainty and anxiety, offering people information from familiar sources in ways that inform belief and action (DiFonzo and Bordia, 2007; Rosnow, 1991). In this study, rumours are defined as any negative and uncon-firmed news about LAMP received by respondents which come from
various sources such as family members, friends, politicians and the mass media. For example, rumours about the plant as a nuclear reactor (Misa, 2012), causes health problems (Idris, 2012) and environmental hazard (McCoy, 2013). These sources become rumours when people believe in it without any investigation or detailed reference to relevant sources, for instance, the authority.
Exposure to rumours can therefore influence the way people perceive environmental impacts (Bradsher, 2011). According to Brody et al. (2004), when information regarding environmental pollution was received via television, people were more likely to continue to perceive their environment to be clean, while when information was received via friends, people were more likely to perceive their environment to be polluted. Other variables such as education, income, gender, age, health status, race, pollution exposure and having trust on the company are argued to have some impacts in influencing people’s perceptions.
Liao et al. (2015) found that educated people were more sensitive to environmental degradation because they have a better understanding of environmental problems (Dogaru et al., 2009), and thus perceive envi-ronmental impacts to be serious. Other studies found the opposite, noting that educated people tend to be the ones benefiting from polluting industries (Shi and He, 2012), meaning they are less concerned about the impacts, and less educated people are likely to care because they receive none of the benefits of such industries (Obiri et al., 2016). Several studies found income has no impact on perception (Liao et al., 2015; Dogaru et al., 2009; Brody et al., 2004; Elliott et al., 1999); however, some found it to have both positive (Afroz et al., 2016) and negative significance (Obiri et al., 2016; Liao et al., 2015). Further, Afroz et al. (2016) found that males are likely to see water pollution as a danger, but Melo et al. (2015) found the same relationship between females and environmental pollution.
Age has an effect on perceived impacts of pollution (Melo et al., 2015; Afroz et al., 2016; Brody et al., 2004; Um et al., 2002), arguably because as persons’ physical health declines they become more sensitive to pollution (Shi and He, 2012). Elliott et al. (1999) included health status in their model because they found that having asthmatic (un-healthy) persons in a household, significantly affected people’s per-ceptions; and some studies (Brody et al., 2004; Um et al., 2002) found that race also plays a role in influencing perception. Pollution emission from industries is expected to have an impact on people’s perception. For instance, Jakus et al. (2009) found that having arsenic exposure had
Table 3 Air quality components.
Parameter Year A1 A2 A3 A4 Mean DOE Limit WHO Limit
a significant effect on perceived risk. Finally, having trust in a company (or lack thereof) will affect the way people contextualise that company’s actions or act to ensure their own safety (Smith and Desvousges 1986).
Better education, male, non-Malay and high level of air pollution are expected to have a positive impact on the dependent variable. Scientific information about rare earth elements (REEs) are available in English and require more than a basic level of education to understand. Thus, those who have higher levels of education can read information about REEs and risks associated with them. Male respondents are more likely to have had exposure to information compared to women in the work-place. Women who are not working (41%) may not have this exposure, and those who are working but married are expected to focus more on family matters. Non-Malay respondents are expected to perceive LAMP
impacts to be serious because they have a recent history of demonstra-tion and protest in these areas. High level of air pollution is expected to have a positive effect on people’s perceptions. Although data on river water quality is available, the water quality data contain pollution produced by all industries and could not segregate the pollution pro-duced by LAMP and other industries. Therefore, this paper focuses merely on air pollution data.
Trust and good health are expected to have a negative relationship with perception variable. Someone with a poor health status might perceive negative impacts because they are easily affected by pollution exposure, and healthy people are expected to be less concerned. No priory expectations on variables such as source of information received, income and age.
PerceptA1 1 ¼ Perceived high level of impacts on air quality 0 ¼ Perceived low level of impacts on air quality
Info 1 ¼ Received information from more than one sources þ/�0 ¼ Received information from one source, either pro/anti- Lynas group
Edu Education þ
Secondary ¼ 1 if secondary and 0 otherwise Tertiary ¼ 1 if tertiary and 0 otherwise Base: Primary
Y Income in Ringgit Malaysia (RM) per month: þ/�Lower middle (1501–3500) ¼ 1 if lower middle and 0 otherwise Upper middle (3501–10,000) ¼ 1 if upper middle and 0 otherwise High (10,001þ) ¼ 1 if high and 0 otherwise Base: low (Below 1500)
Gender 1 ¼ Male, 0 ¼ Female þ
Age Given in years þ/�Health2 Health status: –
Fair ¼ 1 if fair and 0 otherwise Good ¼ 1 if good and 0 otherwise Base: Poor
Race 1 ¼ Non-Malay, 0 ¼ Malay þ
Trust 1 ¼ Trusts LAMP’s waste management, 0 ¼ Does not trust – NO2 Nitrogen dioxide in μg/m3 þ
CO Carbon monoxide in μg/m3 þ
PM10 Particulate matter 10 in μg/m3 þ
Dummy3 Random sampling ¼ 1, 0 ¼ Otherwise
1 Perceived impact on river quality is not discussed in this paper because data on river water quality could not differentiate the pollution produced by LAMP and other industries. 2 The five categories of heath condition in the questionnaire were reduced to three. ‘1’ or ‘Poor’ consists of ‘Very poor’ and ‘Poor’; ‘2’ or ‘Fair’ only has one component, ‘Fair’; ‘3’ or ‘Good’ comprises of ‘Good’ and ‘Very good’. See Ap-pendix – Questionnaire for a detail definition. 3 The dummy is created to check whether there is a difference response between random and non-random sampling respondents.
Table 5 presents the marginal effect of each independent variable on perceived air pollution as a result of LAMP’s operation. The table shows that in the short-term, source of information plays an important role in affecting people’s perceptions on air pollution. Other variables such as education, income, gender, race, and trust also have significant effects. Specifically, it shows that those who received information about LAMP
Table 5 Public Perceptions of Air Pollution (Marginal effects).a,b
Note: *p < 0.1; **p < 0.05; ***p < 0.01. Standard errors are in parentheses. a Since LAMP is located in the industrial area, people’s perceptions of local air
quality might be influenced by pollution emission produced by other industries. Therefore, Air Pollution Index (API) was used to capture the overall impact of industrial pollution on people’s perceptions. However, the estimation result (regressed separately) found it to be insignificant in affecting people’s perceptions.
b The present study has classified the impact of LAMP into two: direct and indirect impacts. The estimated results for both direct and indirect perceived impacts are similar to the result shown in Table 5, thus, they are not discussed in the text.
c Dummy variable is not significant showing there is no significant difference between respondents collected through random and non-random sampling method, and this result is consistent with the result given by independent sample t-test.
19 Correlation matrix among the independent variables was conducted to check the correlation among the variables to avoid a multicollinearity problem. All variables have low correlation except for CO and NO2 (.-88); and CO and SO2 (0.98), thus SO2 (VIF¼39.62) was omitted to avoid multicollinearity problem.
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from multiple sources are 13% more likely to believe that LAMP may cause high level of air pollution in the short-term compared to those who received information only from one source. The reason is that many of the respondents received information from mass media (77%); and anti- Lynas group, families and friends (52%) (Jamaludin, 2017) and chan-nels that are not controlled by the government are widely discussed about the health and environmental problems associated with LAMP0
operation (Idris, 2012; McCoy, 2013). Mazur (1990, p.295), “extensive reporting of a controversial technological or environmental project not only arouses public attention, but also pushes it towards opposition.”
Those who attained the highest level of education are 17% more likely to perceive high level of environmental impacts as compared to those who have the lowest education level. The same goes for non- Malays, with this group being 12% more likely to perceive the level of environmental impact to be high compared to Malay ethnic group. However, the upper and highest income groups are 10% and 30% less likely to perceive the level of environmental impact to be high in the short-run, as compared to the lowest income group. Male, in contrast to the priory expectation, is found to be 8% less likely to perceive LAMP’s impacts on air quality to be high level. One of the possible reasons is that they already get used to work and live in a poor air quality condition due to smoke/dust from their working place and the nearby industries. Furthermore, those who trust Lynas are 65% less likely to see high level of impacts in the short-term.
None of the data on pollution emissions are significant in influencing people’s perceptions on LAMP. This is possibly because most of the pollution variables (see Table 3) are below than the limit set by the authority, thus it may not be detectable by the locals.
Similar results are found with regard to perceived long-term effects of LAMP with the exception of gender and pollution emissions of PM10. In the short-run, gender is important determinant, however, in the long- run, PM10 is found to be significant. The scientific data on air quality components presented in Table 3 show that LAMP (especially PM10) has three times exceeded the limit set by the authority. Therefore, in the long-run, the perceived impact might be serious.
In short, sources of information, education, income, gender, race, trust and/or pollution emission were found to be important de-terminants of perception. These results are consistent with the previous research (Afroz et al., 2016; Liao et al., 2015; Lanz and Provins, 2014; Shi and He, 2012; Dogaru et al., 2009; Brody et al., 2004; Um et al., 2002; Elliott et al., 1999).
4. Conclusion & recommendations
Most people perceived the rare earth processing plant, Lynas Advance Material Plant (LAMP), to be more dangerous than other chemical plants in the Gebeng Industrial Estate, Malaysia. However, a close examination of the data reveals that respondents perceived LAMP’s impacts to be low level in the short-term (48–57%) and un-known for most of the subsequent effects (27–36%). The high level of impacts are only perceived in the long-term (42–66%). Despite their inconsistencies, such perceptions overlapped with some of the experts’
views and the interpolation data. Logit results reveal that rumours play a role in shaping public perceptions. That is, those who received infor-mation from rumours are more likely to perceive LAMP to have high level of impacts compared to those who did not. Other variables such as education, income, gender, age, race, and trust in the LAMP’s waste management processes may also affect public perception.
But many other chemical plants are operating in the area long before the establishment of the LAMP, so why is the LAMP subjected to such scrutiny and blame? The role of rumours spread by family, friends and mass media, may create fear among the locals and influence their per-ceptions. It is difficult to control rumours spreading around, but data availability, which is currently incomplete and inaccessible, can serve as sources of clarifications.
Specifically, environmental data such as the Air Pollution Index (API) and Water Quality Index (WQI) are important to indicate which companies produce high levels of pollution. Making this data publicly accessible will encourage Lynas and other similar companies to reduce their pollution emissions and adopt state-of-the-art technologies to create better environments for living things and thus, also avoiding public ire. Currently, the responsibility to ensure the health of the environment rests with the DOE, but the engagement of the public may help to increase oversight and reduce the likelihood of issues being overlooked. Data disclosure is also essential to inform the public about the current state of their environment, which can guide them to interact with it in the safest and most rational ways. As it is, relying on percep-tions that are subject to error, the public may incur costs to avoid non- existent impacts, or fail to take action where action is wise because they do not perceive impacts.
Furthermore, results of our logit estimation revealed that, other than rumours, education, race and trust in LAMP’s waste management are important variables affecting people’s perceptions. Therefore, special attention has to be given to residents who obtained secondary level of education and belonged to the non-Malay group, as they were found to be dissatisfied with LAMP’s operations. Thus, the company was accused by the environmental group, trying to avoid and delay meeting the group, and some concerned issues raised were not addressed properly and logically and consequently, develops suspicions and distrust among them and influenced their perceptions. The company should take ini-tiatives to get along and gain people’s trust because it is found that trust has a positive impact on perception. Therefore, Lynas should address people’s concern to reduce their fear.
Declaration of competing interest
None.
Acknowledgement:
We thank the late David William for his constructive comments in this paper.This work was supported by the International Mining Development Centre, Australia [C096].
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Appendix
Map 1. Studied Area – Kuantan.
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Fig. 1. Distribution of General Perceptions on LAMP Note: *p < 0.1; **p < 0.05; ***p < 0.01.
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Fig. 2. Distribution of Responses to Specific Perception Questions – Short- and Long-term.
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Table 1 Calculation of Water Quality Index (WQI)
WQI ¼ 0.22 SIDO þ 0.19 SIBOD þ 0.16 SICOD þ 0.16 SISS þ 0.15 SIAN þ 0.12 SIpH (1)
Sub-index for DO (in saturation)
SIDO ¼ 0 for DO < 8 (2a) ¼100 for DO > 92 (2b) ¼ � 0.395 þ 0.030DO2-0.0002DO3 for 8 < DO < 92 (2c) Sub-index for BOD SIBOD ¼ 100.4-4.23BOD for BOD < 5 (3a) ¼108e-0.055BOD for BOD > 5 (3b) Sub-index for COD SICOD ¼ -1.33CODþ99.1 for COD < 20 (4a) ¼103e-0.0157COD-0.04COD for COD > 20 (4b) Sub-index for AN SIAN ¼ 100.5-105AN for AN < 0.3 (5a) ¼94e-0.573AN-5 | AN-2| for 0.3 < AN < 4 (5b) ¼0 for AN > 4 (5c) Sub-index for SS SISS ¼ 97.5e-0.00676SSþ0.05SS for SS < 100 (6a) ¼71e-0.0016SS-0.015SS for 100 < SS < 1000 (6b) ¼0 for SS > 1000 (6c) Sub-index for pH SIpH ¼ 17.2-17.2pH þ 5.02pH2 for pH < 5.5 (7a) ¼-242 þ 95.5pH–6.67pH2 for 5.5 < pH < 7 (7b) ¼-181 þ 82.4pH–6.05pH2 for 7 < pH < 8.75 (7c) ¼536-77.0pH þ 2.76pH2 for pH > 8.75 (7d)
Source: Zainudin (2010).
Table 2 DOE Water Quality Classification Based on WQI
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