Industrial Odour and Psychosocial Wellbeing: A Systematic Review

Abstract

Industrial odour is a common pollution concern raised with local regulatory authorities, with communities citing impacts to their mental health and wellbeing. We performed a systematic review to determine if industrial odours are associated with psychosocial wellbeing in nearby communities. PubMed, Medline, PsycINFO, and Web of Science were searched for peer-reviewed articles published between 2003 and 2023, assessing associations between industrial odour and psychosocial wellbeing (mental health or quality of life). Critical appraisal of the studies was conducted using JBI’s assessment tools. We undertook a narrative synthesis of results. After screening, 13 articles met the inclusion criteria: 11 cross-sectional and 2 longitudinal studies. Sample sizes ranged from 23 to 25,236 participants. Odour exposure was assessed through self-reported measures (intensity, annoyance) and objective measures (proximity to source, odorous chemical concentration). Psychosocial health outcomes included stress, psychological distress, quality of life, depression and anxiety. Of the 13 studies, 11 identified an association between odour exposure and poorer psychosocial wellbeing, with the strongest evidence relating to quality of life. However, the critical appraisal identified quality issues with most studies. The findings suggest that industrial odours may be associated with poorer psychosocial wellbeing for nearby residents, particularly in terms of quality of life. Future research using consistent objective and subjective measures of odour exposure, and prospective data collection, would strengthen the quality of the evidence.

1. Introduction

The detrimental impact of industrial odour in residential areas is a common complaint received by regulatory agencies [1,2]. Some industries are known to emit volatile chemical species including sulphur, nitrogen, and volatile organic compounds, which can smell unpleasant [3,4,5]. Odour pollution has been associated with a range of physical health symptoms, including headaches, nausea and vomiting [6,7,8]. Reported effects of industrial odour can also include issues related to psychological health, such as stress and mood disturbances [7,9,10]; however, studies considering these symptoms are limited [6].

While odour is considered a pollutant in many jurisdictions, the way it is regulated varies worldwide [4]. Guidelines surrounding odour regulation can vary at the national, state, or municipal level depending on the country [4,6]. Often these guidelines are framed qualitatively around reducing nuisance and quality of life impacts (particularly from odour and noise) to surrounding communities [4,11,12]. However, there remains a need to understand this linkage in a more consistent and quantitative manner to better equip regulatory and preventive approaches towards this issue.

There are a few hypothesised mechanisms through which offensive odour could lead to adverse psychological health outcomes [13]. One suggestion is that persistent stimulation of the olfactory sensors from unpleasant odours directly triggers the release of stress hormones within the nervous system [14]. The individuals’ perception of odour may also influence the extent of their psychological response. This has been explained using the transactional model of stress and coping, proposed by Lazarus and Folkman [15]. This model suggests that responses to a stressor (e.g., odour pollution) are determined by perception of the source, a person’s appraisal and reappraisal of that stressor (i.e., whether it is perceived to be a threat or harmful and whether people believe they have the capacity to deal with the stressor), and the types of coping strategies that are employed. It is proposed that stress can be experienced if a stressor (e.g., odour pollution) is perceived as harmful and a person’s coping resources are not considered to be sufficient to resolve the issue [16]. Coping strategies to avoid exposure to unpleasant odours can also lead to reduced health-promoting behaviours [17]. For example, people may act to reduce certain outdoor activities, such as gardening [11], if there is an offensive odour, which may then have subsequent impacts on both their physical and psychological health.

Despite the potential biological interaction between industrial odour and psychological mechanisms, and reports in grey literature [12,18,19] and anecdotally from communities of psychological health impacts from industrial odour, there is limited robust evidence from epidemiological research literature to support a link between emissions and psychological health outcomes. Only one systematic review and meta-analysis has been conducted relating to industrial odour pollution and health in general [6]. However, the review primarily focused on physical health and included both residential and workplace exposure [6]. The review highlighted that high-quality evidence is largely limited by a lack of standardised methods for assessing odour exposure.

In summary, evidence from previous studies indicates that industrial odour pollution can influence an emotional response, supporting anecdotal evidence from the community. It is therefore plausible that odour pollution can negatively impact people’s psychosocial wellbeing; however, the scientific evidence remains unclear. With increasing research interest into the psychological impacts of environmental exposures [20], we conducted a systematic review to determine the current state of knowledge of whether residential exposure to industrial odours is associated with negative psychosocial health outcomes. Our underlying research question was: Is residential exposure to industrial odour associated with poorer psychosocial wellbeing?

2. Methods

This review followed the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) reporting guidelines [21] and was retrospectively registered with Open Science Framework (https://osf.io/76ymg/, accessed on 31 August 2025).

2.1. Eligibility Criteria

We included peer-reviewed studies that assessed an association between an odour-emitting industry and psychosocial wellbeing (cross-sectional or longitudinal). Odour-emitting industries identified for inclusion in the review were: manufacturing, fishing, mining and extraction, chemical processing, food processing, energy production, construction, textile and apparel production, automotive production, paper and printing, husbandry, electronics and technology, landfill, and wastewater. These were based on a previous systematic review [6]. We focused on odours arising from persistent, localized, and anthropogenic sources that are amenable to monitoring and mitigation. Therefore, naturally occurring odour nuisances (e.g., fire and wild animal activity), domestic odours (e.g., mould and mildew), one-off disasters (e.g., oil spills), and traffic and airline odours were excluded. Included methods to measure odour exposure were: distance from the source, self-reported odour intensity or annoyance, and measurement of odorous chemical compounds.

Studies were included if they reported at least one outcome related to psychosocial wellbeing, such as depression, anxiety, stress, psychological distress, quality of life, or life satisfaction. Studies were excluded if odour annoyance was the sole outcome, as annoyance may also serve as a proxy for exposure rather than wellbeing. Both clinically assessed and self-reported outcomes were eligible for inclusion.

Quality of life and life satisfaction are integral components of psychosocial wellbeing and also serve as indicators of it. Quality of life, defined as an individual’s perception of their life [22], encompasses multiple dimensions, including emotional and social functioning. Life satisfaction, by contrast, reflects a person’s subjective evaluation of their overall life experience.

The population of interest was people living near an odour-emitting industry. Studies that related to occupational and institutional facilities, such as nursing homes, hospitals, and schools, were excluded from the review, as these settings involve distinct exposure pathways and indoor air environments that differ from residential contexts.

2.2. Information Source and Search

Combinations of search terms and Medical Subject Headings (MeSH) were tailored to capture the relevant literature for the research question. The full list of search terms is available in Supplementary Table S1.

Systematic searches were performed by the first author (JM) on 25 September 2023 using four databases: PubMed, Medline (via Ovid), PsycINFO (via Ovid), and Web of Science. The search was limited to English language primary literature published from 2003–2023 in academic journals, that only included human participants. On 19 September 2025 we scanned the literature for recent relevant publications and did not identify any that met our inclusion criteria.

2.3. Study Selection and Data Collection

For screening, search results were uploaded to Covidence, an online systematic review software package. Each article was reviewed independently by two of three independent reviewers (JM, KF or SM) based on the inclusion and exclusion criteria for titles, abstract and full-text screening. When discrepancies arose between the two reviewers, they first discussed the article to reach consensus. If consensus could not be achieved, the third reviewer adjudicated the decision. This process was applied across both study selection and data extraction phases.

Data was extracted by the first author (JM) and checked by a second author (NH). Extracted data were: first author, publication year, location of study, study design, sample characteristics (number of participants, sex ratio, age range), industry odour source, exposure variable type, health outcome assessment (type of health outcome, whether health symptoms were clinical examined, type of questionnaire used), analytical methods (statistical approach, confounders/covariates), effect measure, results (effect estimate and 95% confidence interval (CI), p-value, where relevant). Outcomes were summarised into five categories: quality of life (which also included subjective wellbeing and life satisfaction), stress, psychological distress, depression (which included depression, sadness, gloomy, blue, unhappy or negative mood states), and anxiety (which included anxiousness, anxiety or nervousness).

2.4. Critical Appraisal

The JBI Critical Appraisal Checklist for Cross-sectional Studies was used to critically appraise the methodological aspects of all included studies [22]. Although some included studies employed longitudinal designs, these studies were structured as panel designs, with exposure and outcome measured concurrently at each time point. As such, we applied the JBI checklist for analytical cross-sectional studies, as it was more appropriate than the JBI cohort checklist for assessing methodological quality. Two reviewers (JM and NH) independently assessed the quality of the studies. Any differences were resolved through discussion with a third reviewer (SM). To meet question five of the appraisal, a minimum set of confounders was needed to have been adjusted for or considered in the analysis. The confounders were: age, gender or sex, and individual-level socioeconomic status (SES) (e.g., education, employment status, income).

2.5. Data Synthesis

A narrative synthesis was conducted to summarise and interpret the findings of the included studies. We assessed which studies reported evidence that supported the association of interest. Evidence was defined as a statistically significant result, typically indicated by a p-value less than 0.05 and/or a confidence interval that did not cross the null value (e.g., 0 for mean differences or regression coefficients, 1 for odds ratios or relative risks).

We did not perform meta-analysis due to heterogeneity in study designs, measurement approaches, and reported outcomes. Instead, our synthesis focused on identifying patterns of consistency across studies and highlighting areas of agreement or divergence in the evidence.

3. Results

3.1. Study Characteristics

A total of 3428 articles were captured in the initial search after removing 908 duplicates. After title and abstract screening, 75 articles were identified for full text screening, of which 13 articles were included in the review (Figure 1).

Descriptive characteristics of the studies are outlined in

Table 1. Descriptive characteristics of studies included in the review.

	First Author (Year), Location, Study Design	Sample Characteristics	Industry	Exposure Measure	Outcome Measure
1	Berkers (2021), Netherlands, Cross-Sectional [14]	N = 25,236; 55% female; age: 19–64 years	Agriculture, other industry	Odour annoyance (Self-report [SR]; 11-point scale)	Psychological distress (SR; Kessler-10 scale)
2	Eltarkawe (2018), USA, Cross-Sectional [34]	N = 326; 25% male; age: 18–85 years	Mixed	(i) Perceived odour (SR; 5-point scale) (ii) Odour acceptability (SR; 3-point scale)	Subjective well-being (SR; Industrial Odors and Wellbeing Questionnaire)
3	Heaney (2011), USA, Longitudinal [33]	N = 23, 48% women, 52% men; age: 18+ years	Landfill	Odour intensity (SR; 5-point scale)	(i) Stressed (ii) Gloomy, blue, unhappy (iii) nervous or anxious Any negative mood states (SR; Profile of Mood States instrument)
4	Hooiveld (2015), Netherlands, Cross-Sectional [23]	N = 753, 63% female; age: 18+ years	Animal feeding operation	Odour annoyance (SR; yes/no)	Anxiousness, sadness, stress (SR; questionnaire)
5	Horton (2009), USA, Longitudinal [32]	N = 101, 66% female, 35% male; age range: 19.2 to 89.5 years	Industrial hog operations	(i) Odour intensity (SR; 9-point scale) (ii) H2S concentration (O)	Stressed/annoyed; nervous/anxious; gloomy/blue/unhappy (SR; Profile of Mood States instrument)
6	Μichalopoulos (2016), Greece, Cross-Sectional [24]	Exposed group: n = 209, 70% men, 30% women; mean (sd) age: 49.1 (18) years Control group: n = 168, 60% men, 40% women; mean (sd) age: 43.8 (17.9) years	Intensive hog farming operation	Living within 3 km of hog farm (relative to control group—>3–<5 km away) (O)	Quality of life (SR; questionnaire not stated)
7	Njoku (2019), South Africa, Cross-Sectional [25]	Exposed group: n = 50, 58% female, 42% male; 64% aged 21–40 years Control group: n = 50, 54% female, 46% male; 84% aged 21–40 years	Landfill	Living within 100–500 m of landfill (relative to control group—1–2 km away) (O)	Life satisfaction (SR; questionnaire not stated)
8	Pedersen (2015), Sweden, Cross-Sectional [26]	Exposed group: n = 83, 51% female, mean (sd) age: 51 (15) years. Control group: n = 61, 49% female, mean (sd) age: 53 (14) years.	Sewage treatment plant and harbour	Odour annoyance (SR; 5-point scale)	Life satisfaction (SR; questionnaire) Stress (SR; 2 questions)
9	Phan (2021), Vietnam, Cross-Sectional [27]	Exposed group: n = 405 Control group: n = 396 Overall: 53% women, 46% men; 78% aged less than 60.	Landfill	Living within 2 km of solid waste management facility (relative to control community) (O)	Quality of life (SR; WHO QoL assessment scale)
10	Radon (2004), Germany, Cross-Sectional [28]	N = 2745; 49% male; age: 18–44 years	Intensive animal production	Odour annoyance (SR; 4-point scale)	Quality of life (SR; SF-12 questionnaire)
11	Sopsuk, (2013), Thailand, Cross-Sectional [29]	(i) n = 120; 61% female, 34% male; mean (sd) age: 38.8 (12.5) years (ii) n = 121; 60% female, 40% male; mean age: 41.3 (13.2) years (iii) n = 106; 66% female, 34% male; mean (sd) 44 (13.5) years Control: n = 113 75% female; mean (sd) age: 43 (11.8) years	(i) gas refinery, (ii) electricity power plant (iii) two organic industries	Living near a gas refinery, power plant or organic industry (relative to control community) (O)	Quality of life (SR; WHO QOL-BREF-THAI scale)
12	Villeneuve (2009), Canada, Cross-Sectional [30]	N = 723, 51% men, 49% women; age: 18+ years.	Intensive animal operation (hog farm)	Distance to hog farm (O; <3, 3–<9, and ≥9 km)	Quality of life (SR; SF-36) Anxiety (SR; diagnosed condition) Depression (SR; diagnosed condition)
13	Wojnarowska (2020), Poland, Cross-Sectional [31]	N = 1992, 59% women, 41% men; average age: 39 years.	Sewage treatment plant, waste processing, other industry	Odour intensity (SR; 7-point scale)	Quality of life indicators (SR) E.g. Disturbed relaxation; I did not like returning home; I could not open the window

Note: SR: Self-report; O: Objective.

. Most studies were cross-sectional (n = 11) [14,16,23,24,25,26,27,28,29,30,31], with longitudinal study design being less common (n = 2) [32,33]. The longitudinal studies both involved twice daily data collection for two weeks.

Study sample sizes ranged between 23 and 25,236 participants. Two studies [25,30] included child participants, while the other studies only included adult participants starting at 18 (n = 9) [16,23,26,27,28,29,31,33,34] or 19 years of age (n = 3) [14,25,32]. Geographically, seven studies were from Europe [14,16,23,24,26,28,31], four studies from North America [30,32,33,34], two studies from Asia [27,29] and one study from Africa [25]. For gender/sex distribution, eight studies [14,16,25,26,27,28,30,33] had a similar male-to-female ratio, four studies [23,24,29,32] had a higher female ratio, and one had a higher male ratio [31] (Table 1).

In terms of exposure assessment, six studies used self-reported odour intensity or odour annoyance [14,23,26,28,31,33,34]; five studies used an objective measure of proximity to an odour source [24,25,26,27,29,30]; and one study used both self-report (odour presence) and objective measurement (H₂S concentration) [32].

Intensive animal operations were the most frequently studied industry (n = 6) [14,23,24,28,30,32], followed by landfills or waste processing facilities (n = 4) [25,27,31,33], and sewage treatment plants (n = 2) [26,31]. Five studies assessed odour associated with multiple industries [14,26,29,31,34], while the others focused on a single source.

For assessment of psychosocial health outcomes, all studies assessed self-reported symptoms via questionnaires. Two studies [23,31] attempted to validate self-reported symptoms with clinical presentations, however this data was not used in analyses with odour exposure. Outcomes were assessed through a variety of questionnaires or single-item questions as outlined in

Table 2. JBI critical appraisal for included studies measuring the association between industrial odours and psychosocial wellbeing.

	Q1	Q2	Q3	Q4	Q5	Q6	Q7	Q8
	Sample Inclusion	Subjects and Settings	Exposure Measurement	Measurement of Condition	Confounders Identified	Confounding Addressed	Measurement of Outcome	Statistical Analysis	Overall
Berkers (2021) [14]	Y	Y	N	N/A	Y	Y	Y	Y	86%
Eltarkawe (2018) [34]	Y	N	N	N/A	Y	Y	Y	Y	71%
Heaney (2011) [33]	Y	N	N	N/A	N	Y	Y	Y	57%
Hooiveld (2015) [23]	Y	Y	N	N/A	Y	Y	N	N	57%
Horton (2009) [32]	Y	Y	Y	N/A	N	N	Y	Y	71%
Μichalopoulos (2016) [24]	N	Y	N	N/A	Y	Y	U	Y	57%
Njoku (2019) [25]	Y	Y	N	N/A	N	N	N	Y	43%
Pedersen (2015) [26]	Y	N	N	N/A	N	N	Y	Y	43%
Phan (2021) [27]	Y	Y	N	N/A	Y	N	Y	N	57%
Radon (2004) [28]	Y	Y	N	N/A	Y	Y	Y	Y	86%
Sopsuk (2013) [29]	Y	Y	N	N/A	Y	N	Y	Y	71%
Villeneuve (2009) [30]	Y	Y	N	N/A	Y	Y	Y	Y	86%
Wojnarowska (2020) [31]	Y	Y	N	N/A	N	N	N	N	29%
Total across all included studies	92%	77%	8%	N/A	62%	54%	69%	77%

Y: Yes, N: No, N/A: not applicable; U: unclear, JBI Critical Appraisal Checklist; Q1. Were the criteria for inclusion in the sample clearly defined? Q2. Were the study subjects and the setting described in detail? Q3. Was the exposure measured in a valid and reliable way? Q4. Were objective, standard criteria used for measurement of the condition? Q5. Were confounding factors identified? Q6. Were strategies to deal with confounding factors stated? Q7. Were the outcomes measured in a valid and reliable way? Q8. Was appropriate statistical analysis used?

. Four studies [23,24,25,31] did not state the name of the questionnaire used, but one [24] noted that it had been previously validated. Four studies assessed psychosocial health outcomes across multiple categories, while the other nine assessed only one psychosocial health outcome.

3.2. Critical Appraisal

The studies’ scores on the critical appraisal tool are outlined in Table 2 and ranged from 29% [31] to 86% [14,28]. No study was able to completely satisfy the critical appraisal indicating that each contained a level of bias or quality issues. Seven studies [14,24,25,26,31,32,33] scored under 80%, indicating issues with at least three areas of the appraisal. Most of the included studies scored poorly on the item relating to exposure assessment, with only one study assessed as meeting this criterion. This study used a combination of objective and self-reported measures [32]. Other items that were met by less than 70% of studies related to identifying and addressing possible confounders and measurement of the outcome. Studies were assessed as not measuring the outcome in a reliable or valid way if they did not use a validated questionnaire to measure psychosocial outcomes.

3.3. Qualitative Review

A summary of the associations between odour pollution and psychosocial health outcomes for each study is included in Table 2. A detailed results table is provided in Supplementary Table S2.

3.3.1. Quality of Life

Quality of life related outcomes were assessed in nine studies [24,25,26,27,28,29,30,31,34] and was the most common outcome category measured (

Table 3. Summary of the association between exposure to industrial odours and psychosocial wellbeing for included studies.

				Evidence of Odour and Psychosocial Wellbeing Association
First Author (Year)	Location	Predominant Industry	Objective/SR Exposure	Quality of Life	Stress	Psychological Distress	Anxiety	Depression
Berkers (2021) [14]	Netherlands	Agriculture, other industry	SR			+
Hooiveld (2015) [23]	Netherland	Intensive animal operations	SR		+		+	+ a
Horton (2009) [32]	USA	Intensive animal operations	SR/O		+ b		+ b	+ c
Μichalopoulos (2016) [24]	Greece	Intensive animal operations	O	+
Radon (2004) [28]	Germany	Intensive animal operations	SR	+
Villeneuve (2009) [30]	Canada	Intensive animal operations	O	+			Null	+
Heaney (2011) [33]	USA	Landfill	SR					+
Njoku (2019) [25]	South Africa	Landfill	O	+
Sopsuk (2013) [29]	Thailand	Gas refinery; power plant; organic industries		+
Eltarkawe (2018) [34]	USA	Mixed	O	+
Pedersen (2015) [26]	Sweden	Sewage treatment plant and harbour	SR	Null	Null
Phan (2021) [27]	Vietnam	Landfill	O	Null
Wojnarowska (2020) [31]	Poland	Sewage treatment, waste processing	SR	+

+: Evidence that higher odour exposure is associated with higher levels of negative psychosocial wellbeing. This was determined by a p-value < 0.05 and a 95% confidence interval that did not include the null value. Null: No evidence of an association between odour and psychosocial wellbeing. ^a Outcome only for people with lower back pain, ^b Outcome for odour exposure that was measured via H₂S and self-reported, ^c Outcome only for odour exposure that was self-reported.

). Six of these studies assessed quality of life [24,27,28,29,30,31], while two assessed life satisfaction [25,26] and one subjective wellbeing [34].

Seven of the nine studies [16,24,25,27,28,29,34] found evidence that higher exposure to odour pollution from an industrial source was associated with lower self-reported quality of life, life satisfaction or subjective wellbeing. These studies were conducted across a range of industries, including intensive animal operations, landfill, gas refinery and sewage treatment. Four of these studies assessed odour pollution by comparing a community proximal to an industrial source with a control community further away (assessed using varying distances). The other three studies used self-reported odour [31,34] and/or odour annoyance [28,34]. One study in the United States [30] that assessed quality of life in relation to proximity to a hog farm also found differences in quality of life scores among people who reported having had a concern related to the hog farm (e.g., outdoor smells or air pollution).

Two studies [26,27] did not find an association between odour and quality of life. These studies assessed odour pollution through proximity to a landfill [27] and odour annoyance in an area close to a sewage treatment plant and harbour [26].

3.3.2. Stress-Related Symptoms

Three studies [23,26,32] reported stress-related outcomes associated with industrial odour exposure. One study found that higher self-reported odour from intensive animal operations and objectively measured H₂S concentrations were associated with stress symptoms [32]. Another study, also in intensive animal operations, found that the association with odour annoyance and stress was only significant for those with lower back pain [23]. One study [26] did not find an association between proximity to odour sources and stress. However, in that study, odour exposure was assessed indirectly by comparing neighbourhoods with different industries and stress was assessed as a potential mediator rather than a primary outcome.

3.3.3. Psychological Distress

The single study that examined psychological distress, using the Kessler Psychological Distress Scale (K10) [14], found that odour annoyance from agricultural and “other” industrial sources was significantly associated with higher levels of psychological distress. This association remained after noise annoyance was controlled for [14].

3.3.4. Depression-Related Symptoms

Four studies [23,30,32,33] assessed depression, and all found an association between industrial odour and higher depression-related symptoms. Two studies from the United States found that higher self-reported odour was associated with more gloomy/blue/unhappy symptoms, near a landfill [33] and near intensive animal operations [32]. For one of these studies, when odour was objectively measured using concentrations of H₂S an association was not observed [32]. One study that assessed odour annoyance relating to intensive animal operations reported that this was only significantly associated with sadness in a sub-group with lower back pain [23]. Another study that assessed odour with distance found that adults who lived within 3 km of an industrial hog farm were twice as likely to self-report being diagnosed with depression compared to those who lived at least 9 km away [30].

3.3.5. Anxiety-Related Symptoms

Three of the studies assessing depression-related symptoms also measured anxiety-related symptoms [23,30,32]. The two United States studies [23,32] found evidence of an association between self-reported odour annoyance, or presence of odour, and symptoms of anxiousness among residents. However, in one study, this association was attenuated after adjusting for other environmental annoyances (noise, air pollution, traffic). The other study [32], however, established an association using an objective measure—concentration of H₂S. The third study from Canada did not find a statistically significant association between distance to a hog farm and self-reported previous diagnosis of anxiety [30]. The different methods used to assess the exposure and outcome in these studies may explain the differential findings.

4. Discussion

This systematic review provides evidence on the potential link between industrial odour and psychosocial wellbeing. Eleven of the thirteen studies reviewed (85%) reported an association between odour exposure and at least one indicator of quality of life, stress, psychological distress, anxiety, or depression-related symptoms. One of these studies did not find a statistically significant association with anxiety, but found evidence that odour was associated with both depression and quality of life [30]. Two studies did not identify an association between proximity to an odorous industry or odour annoyance with quality of life or stress [26,27]. Overall, these findings align with the previous systematic review [6] and provide further detail on the aspects of psychosocial health that appear to be associated with industrial odour.

We did not conduct a meta-analysis due to the diversity of exposure assessment methods and psychosocial wellbeing outcomes. However, based on the number of studies conducted, the psychosocial wellbeing outcome for which there was the strongest evidence of odour impacts was quality of life. This evidence was drawn from studies exploring a variety of industries—intensive animal operations, landfills, sewage treatment plant, gas refinery, and other industries. This review also identified suggestive evidence for detrimental impacts of odour on depressive symptoms, while there is limited or mixed evidence for stress, psychological distress or anxiety-related outcomes. Further research on these outcomes would provide greater certainty about their association with odour exposure.

A challenge with synthesising the evidence on the psychosocial health impacts of odour is the limited number of studies and diversity in self-reported and objective methods used to assess and measure the experience of industrial odour. Through the critical appraisal process we identified that most studies included did not measure the exposure in a valid or reliable way. For the studies using self-reported methods to assess odour, various measures were used to assess odour intensity, odour acceptability and odour annoyance. Odour intensity reflects how strong a smell is, odour acceptability indicates how tolerable or agreeable it is, and odour annoyance measures how bothersome or disturbing it is to the individual. Although these are similar concepts, they measure different aspects of perception, which makes direct comparison across studies difficult. We included studies that used any of these constructs as exposures to increase the comprehensiveness of our review. However, acceptability and annoyance are generally considered to be different concepts to odour intensity. For example, while odour annoyance and odour intensity might be correlated for acute events (i.e., higher intensity leads to greater annoyance), chronic exposure at low intensity may also lead to odour annoyance [35]. Another consideration is that odour annoyance may act as a mediator between odour exposure (i.e., intensity) and health outcomes [6]. This should be considered when comparing the findings of papers included in this review that differed in their exposure assessment method.

Personal feelings towards the odour source may also bias results when using self-reported measures of exposure. Three studies [23,24,30] concealed the purpose of their questionnaire and another two studies asked participants about their personal views about the industry and odour [27,34]. However, most studies did not acknowledge this potential source of bias. For studies where the purpose of the survey was not concealed, it is possible that included participants may have been more health conscious, annoyed by the malodour or had a negative feeling towards the industry responsible for the odour. Many studies also did not report enough detail to allow an assessment of whether the sample included was representative of the target population. This may result in an overestimate of the psychosocial impact from industrial odour.

While self-report measures of exposure are generally considered to be susceptible to information bias due to their subjective nature, there were also validity issues with the objective measures used to assess exposure in the included studies. Only one study [32] objectively assessed odour concentration through H₂S monitors. This study also assessed whether wind speed was an effect modifier, finding no evidence that it modified associations between H₂S and stress or negative mood. A strength of this study was that they combined this objective measure with self-reported odour intensity, finding that associations with psychosocial outcomes were stronger for self-reported odour than for odour concentration. However, measuring a single gas (H₂S) may not be a reliable marker for odour given that there may be other odorous compounds contributing to the experience of odour [10].

Most studies assessed exposure using proxy measures, such as distance to the site or comparisons between exposed and more distant control communities. The distances used to determine exposure varied across studies, making comparability difficult. For example, distances used to classify participants as exposed ranged from 100 m through to 3 km, while distances for control communities ranged from 1 km to 9 km. A key limitation of distance measures is the assumption that all participants in the assigned area experience equal odour exposure. This may not be the case for several reasons, including wind direction or topography of the area. Dispersion models are often used to account for these factors when modelling potential odour exposure [5,36]. However, these do not necessarily accurately reflect community experience of odour and can have high levels of uncertainty [37]. The approach recommended by environmental regulators for obtaining reproducible measurements of odour is to use trained assessors using field odour surveillance using the European Standard Methods [38,39,40]. The assessors are also screened for their sense of smell using the dynamic olfactometry method, which uses an olfactometer combined with a human panel [41]. This way, community reports can be validated with a systematic odour surveillance campaign run in parallel with community surveys. Use of this method in future research would improve the quality of the evidence base by providing a more accurate assessment of community odour exposure.

Only one of the studies assessed potential mediators of the association between odour exposure and psychosocial wellbeing; an opportunity to understand potential mechanisms. Pedersen [26] found that odour annoyance contributed to reduced residential satisfaction, which in turn led to lower quality of life. Previous research has found that differential health risk perceptions of odour may be a mechanism through which odour annoyance and physical health symptoms may occur [42]. Studies that include both self-reported (e.g., perceived intensity) and objective measures (e.g., distance from the odour source, modelled data) alongside potential mediators (e.g., odour annoyance, health risk perception) may provide a more complete understanding of how odour is experienced by target communities and the mechanisms through which adverse psychosocial outcomes may occur. Additionally, many studies had issues with adjusting adequately for standard confounders (age, gender, education/income/SES), with some adjusting for reduced factors with limited justification while others did not account for any, further contributing comparability issues.

4.1. Recommendations for Future Research

While there has been a rapid expansion of evidence in the past decade into the psychological health effects of environmental exposures more generally [20], the state of knowledge specific to industrial odour remains relatively small. The majority of studies in this review examined quality of life, with fewer studies assessing associations between odour exposure and mental health conditions, such as depression and anxiety. Additional studies assessing similar exposure–outcome relationships would make it more feasible to conduct a meta-analysis in the future, which would provide stronger evidence of the strength and consistency of these associations.

Several studies relied on non-validated or single-item psychosocial measures, which may compromise reliability and limit comparability. These simplified tools risk misrepresenting complex constructs and reduce confidence in reported associations. Future research should prioritise validated instruments to improve measurement quality and synthesis potential.

The critical appraisal process also identified areas for study improvement. These included identifying and adjusting for potential confounding factors (using appropriate statistical methods) and using valid and reliable methods for assessing exposures and outcomes. Most of the studies included in the review assessed the exposure at a single point in time only, which may not capture odour characteristics such as frequency and duration [11]. Prospective studies could help address this gap and assess whether exposure to odour pollution causes adverse psychosocial outcomes. While two longitudinal studies were included in this review, these were panel studies with data collection limited to a two-week period. Industrial odour can have both acute and chronic impacts [35]. Longer-term studies with multiple collection time points may help clarify the relationship between odour characteristics (i.e., frequency, intensity, duration, offensiveness and location [43]) and the development and duration of mental health conditions. Ideally, such studies would span a sufficient duration to capture seasonal variation. Environmental factors like temperature and wind influence odour dispersion from sources such as landfills and agricultural operations. While extended follow-up would be valuable, practical constraints such as cost and participant retention must be considered. Including a comparison group or using individuals as their own control—particularly if relocation occurs during the study—could enhance causal inference, though each approach has methodological trade-offs.

Future studies assessing the impact of industrial odours on psychosocial wellbeing should consider focusing on several key areas to gain deeper insights into how industrial odour exposure specifically affects individuals and communities. These areas include the impact on social life, particularly how odours impact family dynamics; for example, discouraging visits from friends and relatives, or prompting children and parents to seek social connections outside the home, potentially causing fractured familial relationships. Additionally, the effects on sleep quality, concentration, and productivity, could further provide insight, especially in relation to children’s education and social development. Researchers should also explore how odours limit engagement in outdoor activities and weaken broader community connections. Finally, it is important to investigate the coping strategies people adopt, such as avoiding exercise or spending excessive time indoors, to fully understand the psychosocial well-being impact of living with persistent industrial odours.

Further research should also explore potential effect modifiers of the relationship between odour exposure and psychosocial wellbeing, to improve understanding of whether certain characteristics may make people more predisposed to experiencing psychosocial symptoms following odour exposure—for example, demographic characteristics, odour annoyance or perceived health risk [8,42]. These recommendations could assist with producing more reliable evidence and guidance to inform government strategies in odour regulation, particularly for lower-level persistent odour generation issues where there may be low visibility of community experiences.

4.2. Implications for Regulators

Although the research evidence base on odour and psychosocial health is still limited, anecdotal reports and the findings of this review suggest that health risk assessments of odorous industries should include psychosocial health outcomes for the surrounding community.

This is particularly important in communities that may already experience cumulative environmental burdens, where odour impacts can exacerbate existing health and social inequities. Recognising odour as an environmental justice issue may help prioritise responses in disproportionately affected areas.

A key challenge that remains is collecting consistent data to understand when an odour source could lead to adverse psychosocial health outcomes in the community [20]. This is particularly a challenge for regulators, as community can report concerns to a range of stakeholders (e.g., state government, local government, independent lobby groups, industry). Reporting trends to each stakeholder can fluctuate over time due to odour characteristics (e.g., frequency, intensity or duration of odour events), and broader social and political factors (e.g., level of community advocacy, reporting fatigue, accessibility barriers, policy decisions). These dynamics limit the breadth and consistency of data available to any single regulator to inform their response. Given the limited scientific research in this area, regulators and local government could collaborate to enhance existing odour pollution data. This could involve field assessments with surveys capturing self-reported odour intensity, odour annoyance and psychosocial health, enabling deeper analysis of this association. This may offer opportunities for longitudinal studies if designed appropriately and may also improve responses to community concerns about chronic odour pollution issues.

Collaborations between regulators, local government and researchers could be beneficial in progressing this field. Regulators and local government could inform the research direction by providing guidance on industry sectors that that are the subject of a disproportionate amount of odour complaints from local communities. This research may also provide evidence on characteristics linked to higher risk of psychosocial health outcomes (e.g., type of industry, odour character, intensity or frequency). Advice from odour scientists on the most valid and sensitive methods to assess odour exposure in the community, such as systematic field odour assessment [44], would also improve study quality and validity of the findings.

4.3. Strengths and Limitations

To our knowledge, this is the first systematic review focusing on the relationship between odour pollution and psychosocial wellbeing. While an emerging field of research, this provides an important contribution to the state of knowledge, particularly for environmental regulators. Our review highlights areas for further research, including opportunities for improvement in research methodology, and potential implications for regulating odour pollution. A limitation of this review is that we could not perform a meta-analysis due to methodological heterogeneity. Other limitations include that this review was limited to papers published in English and we cannot rule out the possibility of publication bias whereby the under-reporting of null results may exaggerate negative impacts and overstate the overall effect.

5. Conclusions

In summary, there is evidence suggesting that industrial odour may have a negative impact on the psychosocial well-being of residents in nearby communities, particularly in terms of quality of life. To improve the quality of evidence, future studies should employ standardised measures of odour assessment, assess prevalence of mental health conditions (such as depression and anxiety), and use longitudinal study designs to capture frequency and duration of odour exposure. Exploring mediating pathways and potential effect modifiers of the odour-psychosocial wellbeing association will also assist regulators to understand potential mechanisms and identify areas that may be of higher risk of potential harm. With continuing urbanisation and convergence of residential and industrial activities, odour pollution and its potential effect on psychosocial health and is an issue that will require ongoing attention from government agencies.