N = 78) and one main study (N = 215), we confirmed that anger toward the system of racial inequalities mediated between injustice and collective action intentions, and that kama muta toward the movement mediated between collective efficacy and collective action intentions. Both mediations were found for both Black and White participants. We also observed additional unpredicted paths from anger to kama muta and from efficacy to anger. Together, this provides evidence for the pivotal role of emotions in collective action intentions, but also points out that appraisals need to be better understood.Participation in collective action is known to be driven by two appraisals of a social situation: Beliefs that the situation is unfair  and beliefs that a group can change the situation . Anger has been repeatedly found to mediate the relationship between injustice appraisals and collective action. Recent work suggests that the emotion of being moved mediates the relationship between efficacy appraisals and collective action. Building on this prior work, the present research applies kama muta theory to further investigate the relationship between efficacy appraisals and collective action. Kama muta is a positive emotion that is evoked by a sudden intensification of communal sharing, and largely overlaps with the English concept being moved. We investigated its relationship with collective action in both advantaged and disadvantaged racial groups in the context of the Black Lives Matter Movement (BLM) in Spring of 2020. In one pilot study ( The Black Lives Matter movement (BLM) has become the largest social movement in the history of the United States . In 2020Emotions play a pivotal role to motivate or undermining collective action efforts because they sit at the intersection of multiple determining processes: They influence decision-making and action . When shBuilding on these contributions, in the current research, we study intentions to participate in collective action toward racial equality of both Black and White US Americans. To follow up on the role of being moved in collective action, we use kama muta theory . Kama muCollective action is defined as an action taken by a group of individuals to achieve a common goal . DiffereTheoretical and empirical work has clarified that collective action often involves a change in social identification and the content of identity , 2018. PCollective action typically plays out among groups (here we use the terms advantaged and disadvantaged groups). Members of disadvantaged groups are usually more inclined than advantaged groups to challenge injustice through collective action . ConsequActions by members of advantaged groups may result from them adopting the aforementioned politicized identities as new social identities that cross the original group boundaries. As a result of shared beliefs and emotions, it is possible to create connections among people and to create new groups . These sCollective actions depend on at least three different variables: identity, perceived unfairness, and perceived efficacy. Theorizing of such processes is grounded in classic theories of social identity and relative deprivation . AccordiA later model distinguishes two different paths for collective action and includes an emotional component explicitly. The dynamic dual-path model  suggestsRecent contributions elaborate this approach by suggesting that emotions can be mediators in both paths. For instance, the Social Identity Model of Pro-Environmental Action (SIMPEA) acknowledges that various emotions may determine goals and actions . Furtherstatus quo, identity and perception of justice are important predictors of collective action , “überwältigt” (“overwhelmed”), and “ergriffen” (“stirred”). Being moved was distinguishable from sadness, which was measured separately.Being moved has received increased attention in recent years. The literature is not without its controversies . Some aukama muta (being moved by love)  , 2019. Iby love) ; that itby love) .being moved. Kama muta theory proposes intensifications of communal sharing as the primary appraisal, and argues that appraisals of exceeded morality or achievement should only lead to kama muta if they themselves affirm a communal sharing relation. For instance, athletes might be crying after victory because they see the victory as an affirmation of the communal relation to their family that sacrificed a lot for enabling them to train, or as an affirmation of the inclusion of the disadvantaged group they are a member of. However, this claim of kama muta theory has never been thoroughly tested. Also, neither Note that there are a few differences between kama muta theory and how Landmann and Rohmann use their concept We nevertheless prefer to use the concept of kama muta over the term being moved in the current paper for two reasons: (1) We want to avoid using a vernacular concept from one specific language that may or may not be the language that is actually used in the measure . (2) We Landmann and Rohmann formulated and tested their being-moved explanation of collective efficacy with groups that presumably consider themselves as the disadvantaged groups opposing powerful others (a mining company and the authorities). If correct, the model should generalize to other situations of social movements, including the BLM movement. However, does it also hold for advantaged groups?We argue here that the model should apply to members of both advantaged and disadvantaged groups. As explained above, members of an advantaged group who perceive the situation to be unjust or as violating moral standards and are thereby motivated to change the situation, can identify with the disadvantaged group and/or adopt a politicized identity with a movement, which can cross the original intergroup divide. In both cases, perceiving that the group one identifies with is unified and has the potential to change the situation through joint action  should lead to kama muta.Regarding social movements, our assumption is that they are understood as relationships on a foundation of a perceived shared essence of having the same beliefs, values and goals. Such relations are conceptualized as communal sharing relations by relational models theory  . Some evSocial movements and social activists seem to successfully evoke kama muta to motivate people to participate and act through messages of communal identity and justice . In poliThe process is nicely illustrated by a the following quote from the (White) host of a widely distributed podcast published in June 2020, days after the murder of George Floyd:“My kids really wanted to protest. […] I live in an overwhelmingly White town. […] It was important to them, […] it was important to me. […] We went as a family down to the town hall […] and stood on a corner […] with signs saying: “Enough is enough,” “Black Lives Matter.” […] I had one of the four or five most moving […] experiences of my life. […] I went down there thinking that we would have trouble. […] I would say the positive response to our protest on this busy intersection ran about six, seven or eight to one from the most unexpected places. […] We had guys on […] Harleys […] putting their thumbs up, […] guys in […] huge pickup trucks […] cheering us on, […] two sheriff’s cars … give us this very subtle thumbs up. […] So my plea to you [listeners] is: … Get on the right side of history. […] Make a sign and protest.” Here, protest for the cause of a disadvantaged group after a moral norm violation resulted in an experience of support by other members of the advantaged group labeled as moving, and included the belief that there is large support (efficacy), and further support (plea for others to join). As noted above, kama muta theory specifically predicts that intensifications of communal sharing relations lead to the emotion. The theory has yet to spell out in detail what such intensifications can be, but common examples include reunions, altruistic help, selfless acts of compassion, expressions of love and closeness, and manifestations or affirmations of social inclusion. Subjectively, such events appear to be experienced as increases in social closeness. Affirmation of moral values of the communal relation seems to be an additional route . ExperieIt is also possible that when perceiving injustice and moral norm violations, members of advantaged groups identify with the disadvantaged group. The same processes of experiencing collective efficacy should apply, possible through vicarious or third-person kama muta, and perhaps enhanced by compassion and empathic concern .Communal sharing relations largely neglect to keep track of contributions, but rather follow the principle of distributing resources according to need and ability. Once experienced, kama muta is theorized to result in increased motivation to affirm and engage in the same relation and to relate based on communal sharing principles. Extant studies on kama muta have found support for these ideas using self-reported general motivations  for a measure designed based on kama muta theory that also includes feeling labels, and references to appraisals, physiological reactions, valence, and motivation .Fourth, we collected data on multiple targets of those emotions, both concrete in- and outgroups and more politically defined social entities . In line with the findings by As a fifth goal, we use measures of identification with various groups and identities to understand the nature of the kama muta experiences that we observe. Landmann and Rohmann found the higher politicized identification  was, the more participants reported participating in effortful and non-normative collective actions. Here, we use the identification measures in exploratory analyses to understand how politicized identity relates to kama muta in disadvantaged and advantaged groups.In the pilot study, we piloted a comprehensive measure of emotions and obtained the first exploratory data of the emotions and their association to collective action in the BLM movement. We targeted the measure of emotions toward the BLM movement, the system of racial inequalities, and Black and White people. We selected these targets because they represented the involved ethnic categories, the most active social movement, and the antagonist that this movement identified. We explored the associations between the emotions toward each target and their relationship with collective action.N = 100 participants from Academic Prolific1 requesting US Americans. Participants were compensated with 1.25 GBP for approximately 10 min of their time. We excluded participants who failed 1 or both of the included attention checks and those who did not complete the survey (n = 22). The remaining 78 participants were 19–69 years old ; 32 reported being female, 45 male, and one third gender. Regarding ethnicity, 64.1% reported being White and the 35.9% remaining mentioned being members of ethnic minorities . Participants indicated their political ideology on a scale from 1 (“left”) to 10 (“right”); the average value was M = 4.60, SD = 2.73, 64.1% reported values between 1 and 5. Thus, the sample was skewed toward leaning politically left, and there were few Black participants.We recruited Qualtrics.com. First, participants read an information sheet and signed a consent form. Then, participants were asked to respond to the measures in the same order described below. Data analysis was performed using SPSS statistics version 26.Each participant was presented with a survey delivered online through The emotional experience in the past year was assessed through a new measure designed for this research. We presented participants with the descriptions of three emotions: sadness, anger, and kama muta. Descriptions contained detailed information about the valence, appraisals, physical reactions, and labels that characterize each one of those emotions. Here is an example of the description that was used to measure kama muta. Note that it starts off without naming any label. Because it is only our theoretical term, the term kama muta was never mentioned:“This emotion gives you a positive feeling, and it makes you feel connected to others. Perhaps you have felt this emotion after experiencing a sudden sense of closeness to somebody else or an incredibly strong bond with another person or a group of people. When this emotion is mild, it feels a little warm and fuzzy. When it is more intense, you may notice warmth or a stirring in the center of the chest; your eyes may tear up, or you actually weep. Some people experience chills or goosebumps. You would probably call this as being touched or moved, and you would perhaps call the situation heart-warming.”After each description, participants indicated their emotional experiences on four items measuring the frequency [“How often did you feel this emotion toward the (target) during the past year?”], intensity , salience , and ease of retrieval [“How easily do situations from the last year come to your mind where you felt this emotion toward the (target)?”] of the respective emotion experienced.not at all/never to 5 = very much/always. In total, we assessed each target with four items for each one of the three emotions in a 4 (targets) × 3 (emotions) design  toward each of the four targets: the system of racial inequalities, the BLM, and White and Black people. Items were answered on 5-point Likert scales ranging from 1 = strongly disagree to 5 = strongly agree. The seven items were adapted from Participants reported their intentions to participate in collective action toward racial equality on a 5-point Likert scale ranging from 1 = We calculated Chronbach’s alpha for the four items for each emotion and target separately. Analyses demonstrated high internal consistency for all 12 scales. Subsequently, we averaged all items for each emotion and target and created composite variables. Reliability values and descriptive information for the scales are presented in 2 (20) = 117.92, p < 0.001. Since sphericity was violated (ε = 0.660), Greenhouse–Geisser-corrected results are reported. Results indicate that there was no overall difference between emotions F = 2.367, p = 0.101, η2 = 0.03. However, there were differences between targets irrespective of the emotions F = 6.500, p = 0.001, η2 = 0.07. Finally, the emotions and target factors interacted significantly F = 29.79, p < 0.001, η2 = 0.28. The system of racial inequalities elicited the highest levels of anger and sadness, while Black and White people elicited the highest levels of kama muta  and emotion (anger vs. kama muta vs. sadness) as within-participant factors. Mauchly’s test indicated a violation of sphericity assumption χmuta see .p < 0.05 and excludes them with p > 0.10 iteratively. We included the 12 composite variables as potential predictors. Additionally, we examined whether ethnicity could have an impact on the model and split the sample into White and non-White participants based on their reported ethnic identity. In order to explore the association between the emotions, kama muta, sadness, anger, and collective action, we calculated a multiple linear regression. The model was run as a stepwise regression with the default settings in SPSS, which includes predictors with This study aimed to pilot a new measure of emotions and carry out exploratory analysis of the association of those emotions and collective action intentions. These findings indicate that the measure designed for the current research context satisfactorily differentiated the emotions for each target. The results of exploratory regression analysis revealed that kama muta toward the movement was positively associated with collective actions toward racial equity, followed by sadness toward the system of racial inequalities in the total sample and for each sub-group. Neither anger toward the movement nor anger toward the system of racial inequalities was significantly associated with collective action. Notably, while kama muta toward Black people was high overall, it correlated much less with collective action than kama muta toward the BLM movement did. In the stepwise regression, it even ended up with a negative sign (likely the outcome of a suppression effect).These initial findings mainly supported our initial theorizing on the positive relationship between kama muta and collective action and sadness and collective action. Different from our theorizing, the relationship between anger and collective action was not statistically significant in the present sample. However, the pattern of results points to the expected direction. Notably, the sample size was small. Given the partial preliminary support for the hypothesized association of emotions and collective action, we set up the main study as a confirmatory test of our full theoretical model see .https://aspredicted.org/pd2w3.pdf.The main study tested a mediation model to explain the relations between appraisals and collective action intention toward racial equity through the three emotions. To test this model, we surveyed only White and Black Americans. Specifically, we hypothesized that (H1) Kama muta toward the BLM movement mediates the relationship between collective efficacy and collective action; (H2) Anger toward the system of racial inequalities mediates the relationship between injustice appraisals and collective action intentions and (H3) Sadness toward the system of racial inequalities mediates the relationship between unfairness appraisal and collective action see . In addiN = 306 participants from Academic Prolific with an equal sampling of US Black and White Americans. We aimed to collect data for 300 participants, 150 participants in each group, given that correlations are more stable around this sample size (SD (n = 7) and if they failed any of the included attention checks (n = 83). The analyzed sample included N = 215 participants.We recruited ple size . Particin = 107) were 18–70 years old ; 41 reported being male, 62 female and 4 third gender. Participants indicated their political ideology on a scale from 1 (“left”) to 10 (“right”); the average value was M = 3.40 (SD = 2.60). 84.1% reported at least some college education. Black participants (N = 108) reported age varying from 18 to 68 , 57 reported being male and 51 female. The average value of ideology was 4.31 (SD = 2.49), and 84.3% reported some college education.White participants  = 134.64, p < 0.001. Since sphericity was violated (ε = 0.69), Huynh-Feldt results are reported. We found main effects of emotion, ethnicity, and targets. More importantly, emotions differed depending on the target, as indexed by an emotion by target interaction, F = 153.33, p < 0.001, ηp2 = 0.42. However, there was no three-way interaction between emotion, target and ethnicity, F = 1.726, p = 0.189, ηp2 = 0.01. Finally, the test of between-subjects effects indicated that across emotions both groups differed in their overall emotion levels, F = 12.73 p < 0.001, ηp2 = 0.06. Black participants reported higher levels of emotional reactions across targets. The system of racial inequalities elicited a higher level of anger and sadness. The BLM movement elicited higher levels of kama muta, especially in Black participants  Collective efficacy appraisals are positively associated with collective action intentions and (H2.a) Injustice appraisals are positively associated with collective action. We ran a multiple regression on the complete sample while including ethnicity as a moderator. As pre-registered, we regressed collective action on ethnicity (contrast-coded as –1/2 for White participants and +1/2 for Black participants), injustice appraisal (centered), collective efficacy (centered), and the interaction terms of both injustice and efficacy with ethnicity. Note that we did not include the three-way interaction. Also, note that centering was done on the complete sample.R2 = 0.27, F = 15.80, p < 0.001. The intercept was B = 5.25, and represents the average of collective action scores. The main effect of ethnicity was not significant, B = –0.03, p = 0.885. Both appraisals explained a significant amount of variance. Injustice appraisals were positively associated with collective action, B = 0.57 , β = 0.26, p < 0.001. Collective efficacy appraisals were also positively associated with collective action, B = 0.63 , β = 0.37, p < 0.001. Ethnicity did not moderate the effect of injustice, B = –0.34 , β = –0.08, p = 0.212 and neither the effect of collective efficacy, B = –0.29 , β = –0.09, p = 0.171. Analysis run separately in each group can be found in the The model explained 27.4% of variance of collective action, F = 35.36, p < 0.001. The intercept was B = 5.23. The main effect of ethnicity was marginally significant, indicating slightly higher values for white B = –0.32  compared to black participants, B = –0.11, p = 0.030. In line with hypotheses, the three emotions were positively associated with collective action intentions: Anger, B = 0.67 , β = 0.46, p < 0.001, kama muta, B = 0.32 , β = 0.25, p < 0.001, and sadness B = 0.10 , β = 0.15, p = 0.023. Ethnicity did not moderate the effect of anger, B = 0.12 , β = 0.52, p = 0.523, and neither kama muta, B = 0.17, β = 0.07, p = 0.245   = 54.50, p < 0.001 and 46.2% of the variance for Black participants, F = 29.82, p < 0.001. For White participants, anger, B = 0.61 , β = 0.41, p < 0.001, sadness B = 0.48 , β = 0.32, p = 0.001, and kama muta, B = 0.24 , β = 0.16, p < 0.001, were positively associated to collective action. For Black participants, anger B = 0.73 , β = 0.50, p < 0.001 and kama muta B = 0.41 , β = 0.34, p < 0.001, but not sadness, B = –0.07 , β = –0.74, p = 0.460, were positively associated to collective action intentions. For both groups anger explained most of the variance of collective action. Kama muta descriptively explained more variance in the Black participants than in White participants, but this was not statistically significant, as noted above. Sadness significantly explained variance in White participants but not in Black participants.We proceeded to analyze the model in each group separately without centering variables. The model explained 61.4% of the variance of collective action for White participants We performed a Structural equation modeling (SEM) to test the mediation model, using SPSS Amos version 27. The model combined the analyses above. It featured two independent variables , the three emotions as mediators, and collective action as the dependent variable. The complete model is depicted in 2(6) = 110.29, p < 0.001. These parameters were thus allowed to differ from 0 in all following models. This indicates that, unsurprisingly, the correlations among the three emotions cannot be fully explained by the two appraisals.A preliminary model (1) tested whether the covariances among the residuals of the emotion terms  could be set to zero while allowing all other parameters to differ between the groups. This model did not fit the data well, RMSEA = 0.286 , χ2(15) = 49,51 p = 0.003. We inspected all modification indices > 2 . This tested the hypothesis that the two groups do not differ regarding the relationship between the variables. Overall fit was not good, RMSEA = 0.104 , χ > 2 see . The mod2(12) = 16.86, p = 0.540 , but not for Black participants . The standardized total effect of collective efficacy on collective action, which includes both mediated and direct effects, was significant, for both White, β = 0.38, p < 0.001, and Black, β = 0.37, p < 0.001, participants. The standardized total effect of injustice on collective action, which includes both mediated and direct effects, was significant for both White, β = 0.31, p < 0.001, and Black participants, β = 0.26, p < 0.001. The standardized indirect effect of collective efficacy through emotions on collective action is β = 0.22 for White and β = 0.18 for Black participants. The mediated effect of injustice through emotions on collective action is β = 0.25 for White and β = 0.20 for Black participants. This indicates that more than half of the total effect of collective efficacy and two-thirds of the effect of injustice on collective action is mediated through emotions.Injustice and collective efficacy appraisals covaried for White participants , the BLM (r = 0.59), and Black people in general (r = 0.48). The other possible identifications play no role. Kama muta toward the movement was associated most with identification with the movement (r = 0.60), somewhat less with identification with racial justice activists (r = 0.53), and still less with identification with Black people (r = 0.27). Collective efficacy is linked to identification with racial justice activists (r = 0.37) and BLM (r = 0.32), and surprisingly also somewhat with identification with White people (r = 0.23). .We assessed the association between the main variables of the study (kama muta toward the movement and collective action) and the social identification options for each group separately see . For Blar = 0.73) and the BLM (r = 0.72), and less but still significantly with Black people in general (r = 0.32). The other possible identifications played no role. Kama muta toward the movement in White participants was associated with identification with both racial justice activists specifically (r = 0.43) and the BLM in general (r = 0.41), and less but still significantly with identification with Black people (r = 0.21). Collective efficacy is again linked to identification with racial justice activists (r = 0.45) and BLM (r = 0.41), and this time also with identification with Black people (r = 0.32). .For White participants, collective action motivation was most strongly associated with identification with both Racial Justice activists  strongly with collective action, (b) solidly with kama muta with the BLM movement, and (c) also solidly with collective efficacy in both Black and White participants. Kama muta with the movement was correlated more clearly with identification with the movement in Black participants than in White participants.Thus, the results confirmed the mediating role of kama muta on the relationship between collective efficacy and collective action. Nonetheless, it also indicates a mediator role of kama muta for the effect of injustice. In addition, the model held for both White and Black participants, meaning that there was no difference between both groups in the pathways to collective action. It is notable that injustice appraisals and collective efficacy were correlated for White but not Black participants.The findings on kama muta conceptually replicate and extend the findings that being moved construct, but we reiterate here that this distinction is largely theoretical for the present results. The two theories differ mainly in an area that was included in neither study, namely their conjectures about why situations that cause the constellation of kama muta or being moved do that. While there is an overlap in the causes assumed by both theories , there are also diverging ideas . This would clearly be a fruitful area for further work.Any research on emotions, especially when it uses self-report on longer periods of time, is limited by participants’ ability to remember, and verbally report the emotions. Discussing these measures critically is thus crucial. The current work based the design of the emotions measure and the general theoretical argument on the kama muta construct rather than on Landmann and Rohmann’s The kama muta measure designed and used in the current studies was piloted but otherwise not validated. It includes a more complete description of emotional experiences that can be directed to different targets. We are confident that is an appropriate measure because (a) it was based on a well-researched theoretical background, and (b) because the equivalent  measure of anger replicated the classic mediation between injustice and collective action. Nevertheless, future research should validate this measure of kama muta and adapt it to other intergroup contexts. Note that the design of the measure presented a conundrum. We opted for giving a rich description of the kama muta prototype that included an abstract description of the appraisal and the resulting motivation. The prompt was written in a way that asked participants to compare emotional experiences in the last year to this abstract description. Nevertheless, there is a potential downside to this richness, namely that the kama muta measure captures variance that actually belongs to predictor (collective efficacy) and outcome (motivation). We acknowledge this as a shortcoming of the study, but are confident that it does not compromise the results given that many other studies with separate measures of the kama muta components typically find parallel predictions by all components . The fact that our results closely parallel those of It is important to mention that the sample in this study is not representative. Larger and more representative samples could provide further evidence of the stability of these results. In addition, the results surely capture a transient moment in the life of a social movement. The items asked participants to reflect on their last year, which included massive protests, a polarizing presidential election with campaigns that often referenced the movement, and a pandemic that highlighted tragic vulnerabilities caused by the same social inequalities.In general, more evidence is needed to test the causality of the association between emotions and appraisals, therefore experimental research could provide insights in this direction. Note, however, that the kama muta model to some extent predicts reciprocal effects, especially over time in a dynamic social relation. If people experience kama muta from seeing joint demonstrations of advantaged and disadvantaged groups for values that they support and then join a demonstration themselves, this will give them another boost of experiencing collective efficacy and encourage further kama muta experiences.The current data do not yet identify what elements of experiencing collective action lead to kama muta experiences and what role morality plays. Qualitative data could add more depth to understanding the context in which this emotion arises in a movement like Black Lives Matter. The idea that experiencing collective efficacy is equivalent to a communal sharing intensification and thus leads to kama muta experiences may be surprising at first. However, imagine situations like joining together to help a child that got lost, pushing a car out of mud, or defeating an opposing team in a tug-of-war. The experience of jointly having the potential and indeed power to enact collective action might act as a manifestation and confirmation of the communal sharing relation and thereby cause an experience of oneness and togetherness , which cIn addition to the mediator role of kama muta through the path of collective efficacy, the results showed that kama muta also mediated the association between injustice and collective action. This relation was not predicted, but strong enough to survive the correction for multiple comparisons for the unpredicted mediations, and it deserves to be taken seriously while being interpreted with caution. Similar to our results, one emotional path to collective action. There might in fact be other emotions that play a role. Nevertheless, these results contrast with most collective action models that emphasize the tight association between injustice appraisal and anger, indicating only Being moved and kama muta are conceptualized as social-relational emotions that are influenced by, and themselves result in, relational processes. The current work focused on the larger picture, from judgments of the social situation  to collective action. Disentangling the more minute details, including tracing how social identification with the various identities involved change throughout these emotional experiences, remains a task for future work. However, the current research offers some insights in how kama muta  and different social identities interact in the context of collective action.We started our exploration in the pilot study by focusing on both politicized identities  and ethnically defined identities (Black and White people). The former outperformed in the prediction of collective action, and thus, we focused on politicized entities. This is in line with longstanding arguments and findings that politicized identities play a major role in social change . In the Second, the correlations that we observe tentatively suggest a more central, or perhaps more uniform, role for kama muta toward the movement for Black participants than for White participants. It is possible that there is more diversity in what moved White participants about the BLM movement, and what identifications are at play. Some may see BLM as a movement that bridges the disadvantaged and advantaged group and be moved by the collective efficacy of this new joint social group that they identify with. A politicized collective identity based on shared values and beliefs about fairness and equity seems promising to integrate advantaged and disadvantaged groups . Others It is noteworthy that we found no association between US American identity to kama muta toward the movement or to intentions to participate in collective action. Previous work has shown that kama muta can reduce affective polarization and increase the salience of a common in-group in the context of US politics . Common Based on the context of the BLM, we have mainly focused on collective action that is aimed at increasing equality and intergroup relations. Note, however, that the exact same emotional processes should propel collective movements aimed at other goals. collective in collective efficacy.The present research extends the role of being moved for collective action, suggesting an application of kama muta theory to intergroup relations that can lead to collective actions aimed to foster equality among groups. We replicate earlier work showing that the impact of collective efficacy on collective action is partly mediated by the emotional experience of the togetherness, which is typically labeled being moved, and what we conceptualize as kama muta. Simply put, this emphasizes the https://osf.io/aqmxh.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: The studies involving human participants were reviewed and approved by the internal review board at the Department of Psychology, University of Oslo. The patients/participants provided their written informed consent to participate in this study.DLP conceptualized the research, created the materials, carried out the investigation, and wrote the first draft of the manuscript. DLP and TS conducted the all statistical analyses. TS and JR edited and reviewed the manuscript. All authors planned the research.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Excessive use of pesticides and fertilisers has been a key issue limiting sustainable agricultural development. China is a typical pesticide- and chemical-fertiliser-dependent agricultural production area. We have matched the target indicators related to sustainable agricultural development (SDG1 and SDG2) and analysed the gap between China and four developed countries in terms of fertiliser and pesticide use intensity and efficiency from 2002 to 2016. We have used an improved Logarithmic Mean Divisia Index model and cluster analysis to identify the factors and effects driving increased pesticide and fertiliser inputs in China, and we discuss the exploratory effects of different provinces in reducing pesticide and fertiliser application and increasing efficiency. The findings reveal that (1) China is a typical pesticide- and fertiliser-dependent agricultural production area. The average combined fertiliser application efficiency in China from 2002 to 2016 was only 28% of that of the Netherlands, and the country’s average combined pesticide application efficiency was only 35% of that of the USA. (2) The most important of the three main drivers of the increase in pesticide and fertiliser inputs in China is the value added of the primary industry, contributing 56% for the period 2007–2016. (3) Further analysis at the provincial level according to four types—high-intensity high-yield type, high-intensity low-yield type, low-intensity high-yield type, and low-intensity low-yield type—clarified the provinces that should be focused on at the national level in terms of pesticide and fertiliser application reduction and efficiency increase in the future. Population growth and increasing socio-economic development are driving the increasing demand for food. The issue of food is related directly to the livelihood of farmers and the subsistence of the population. Of the 17 sustainable development goals in the United Nations 2030 Agenda for Sustainable Development, “No poverty” and “Zero hunger” have been set to address persistent and emerging challenges facing humanity and the planet. China achieved a great victory of poverty eradication in 2020, and the next key challenges to be addressed are consolidating the results of poverty eradication and coordinating the mechanism of poverty eradication and rural revitalisation. Construction of the rural ecological environment is vital for the sustainable development of the countryside.2, and the annual loss of phosphorus fertiliser is 38.8 kg/hm2. The excessive application of nitrogen and phosphorus nutrients causes serious eutrophication of water bodies and nitrate and nitrite pollution of groundwater through surface runoff and infiltration into rivers, lakes, and groundwater, and these can endanger human health through certain exposure pathways [Fertilisers promote crop growth by artificially supplementing nutrients, such as nitrogen, phosphorus, and potassium, essential for plant growth to achieve stable and increased agricultural production. Pesticides both prevent and kill crop pests and diseases to effectively reduce agricultural losses and ensure the yield and quality of agricultural products. Agricultural production has become increasingly dependent on chemical fertilisers and pesticides to ensure sustainable and stable crop yields, and the phenomenon of excessive application of chemical fertilisers and pesticides has become increasingly serious and harmful. Long-term excessive application of chemical fertilisers tends to cause soil consolidation and acidification, in addition to nutrient structure disorders, reducing the fertility of the soil and causing a decline in crop yield and quality ; the propathways .In 2015, as a response to the problem of pesticide and fertiliser pollution, the Ministry of Agriculture proposed a “zero-growth action on the use of pesticides and fertilisers by 2020”, requiring an increase in the rate of utilisation of pesticides and fertilisers, reducing the amount of pesticides and fertilisers applied. As of the end of 2020, after five years of implementation of this strategy, China has achieved its desired goal with respect to fertiliser and pesticide reduction and efficiency; fertiliser and pesticide use has been reduced significantly, the rate of utilisation of fertilisers and pesticides has been improved significantly, and high-quality development of the planting industry has been promoted. Although there have been remarkable achievements in China’s rural green development in recent years, the long-term extensive growth also makes China a typical global agricultural production area dependent on pesticides and fertilisers, and there is still a huge gap between China and developed countries in the control of pesticides and fertilisers.This paper presents a comparative study on the intensity and efficiency of fertiliser and pesticide application in China, the United Kingdom (UK), France, the United States (USA), and the Netherlands based on data provided by the Food and Agriculture Organisation of the United Nations (FAO) on fertiliser application and grain production in each of these countries from 2002 to 2016. In addition, it explores the changing patterns of fertiliser and pesticide application intensity (PI) and efficiency in China. We analyse their effects on total fertiliser and pesticide application in China of three influencing factors: the value added of primary industry, the scale of rural operation, and the producer price of agricultural products. Furthermore, based on China’s rural statistics, we apply cluster analysis to pesticide and fertiliser application intensity (FI) and the value added of primary industry in 31 provinces in China  and combine international experience to promote the high-quality development of agriculture in each part of China according to local conditions ,6. ThrouIn the context of the national advocacy of zero-growth and reduction in fertiliser and pesticide use, it has become vital to improve the efficiency of farmers’ use of fertilisers and pesticides. In studying spatial and temporal differences in pesticide and fertiliser application, Pingping Wang et al.  applied To analyse factors influencing pesticide application efficiency, Wang Yijie and Yang Zonghui et al. used comparative study analysis, the SDM model, the Tobit model, the C-D production function, and the grey correlation model to measure the influence of the value added of primary industry on utilisation of fertilisers and pesticides ,19,20,21To summarise, scholars have conducted much research into pesticide and fertiliser application in rural China, with most of the study areas being provincial or prefecture-level cities; however, there has been relatively insufficient analysis of the temporal trends and influencing factors of fertiliser and pesticide inputs and outputs at the national level. To provide a basis for promoting high-quality agricultural development in various parts of China, this study utilises data from 2002 to 2016 to examine the changing trends of fertiliser and pesticide input intensity and efficiency in China, applies a comprehensive fertiliser and pesticide utilisation efficiency calculation model to comparison with some developed countries, and uses an improved Logarithmic Mean Divisia Index (LMDI) model and cluster analysis to identify the driving factors and driving effects of increased pesticide and fertiliser inputs in China.Total pesticide use, pesticide use intensity, pesticide output rate (PO), and grain production per unit area in China and typical developed countries come from the FAO database; total fertiliser use in China and typical developed countries comes from the IFA database; and FI in typical countries is based on the fertiliser output rate (FO) from the World Bank statistics database and the FAO database. The data on the intensity of fertiliser use and the intensity of pesticide use in China’s provinces come from the National Bureau of Statistics; the overall producer price index for agricultural products is taken from the China Agricultural Product Price Survey Yearbook; and the value added of primary industry is taken from the Statistical Bulletin of the People’s Republic of China on National Economic and Social Development. The data on average sown area per household come primarily from the China Rural Statistical Yearbook and the China Population and Employment Statistical Yearbook. The domestic data in this paper are based on the provincial administrative regions of China. The agricultural land systems in Hong Kong, Macau, and Taiwan are not included because of certain differences from the mainland. The data cover the period of 1997–2016 for all 31 provinces  in China.Despite remarkable achievements in China’s rural green development in recent years, the long-term crude growth has made China a typical agricultural production area dependent on pesticides and chemical fertilisers, and there is still a huge gap between China and developed counties in the control of pesticides and chemical fertilisers. This paper applies the calculation model of relative output rate and comprehensive efficiency of fertiliser proposed by Liu Qinpu et al.  to data (1) Fertiliser and pesticide application intensityFI refers to the amount of fertiliser applied per unit of crop sown area, and it is an important indicator in measuring the efficiency of fertiliser utilisation in a country. The calculation equation isFI denotes fertiliser application intensity, kg/hm2; M denotes total fertiliser application, kg; and A denotes crop sown area, hm2.PI refers to the amount of pesticides applied per unit of crop sown area, and it is an important indicator in measuring the efficiency of pesticide use in a country. The calculation equation isPI indicates the intensity of pesticide application, kg/hm2; N indicates the total amount of pesticide application, kg; A indicates the crop sown area, hm2.(2) Relative output rate of fertiliser and pesticide applicationFO refers to the yield of agricultural products per unit of fertiliser input and is computationally equal to the grain yield divided by the FI. As FO is a relative measure of intensity with a quantitative scale, it has no maximum upper limit, and it is inconvenient to make a typology of either high or low efficiency. To facilitate comparison of fertiliser application efficiency in different countries, with reference to the DEA method for measuring relative efficiency [FRO), which is the ratio of a given FO to the maximum FO, has been proposed. The calculation equation is as follows:FRO denotes the relative output rate or net efficiency of fertiliser application; FO denotes the fertiliser application output rate, MAXFO denotes the maximum fertiliser application output rate, kg/kg; and Y denotes the crop yield, kg/hm2.The ficiency , the conPO refers to the yield of agricultural products corresponding to each unit of pesticide input, and the concept of relative output rate of pesticide application (PRO) is proposed in the same way, that is, the ratio of the output rate of a certain pesticide application to the maximum PO. The calculation equation is as follows:The (3) Yield scale factorPOs, we propose the concept of yield scale coefficient (YS), which is the ratio of the yield of a certain unit of sown area of a crop to the yield of the highest unit of sown area, reflecting the scale effect of crop production. The larger the YS, the higher the crop yield indicated. The calculation equation isYS denotes the yield scale factor, and MAXY denotes the maximum yield, kg/hm2.To reflect the crop yield scale of fertiliser and (4) Efficiency of integrated application of fertilisers and pesticidesFIE) is proposed as the open square of the product of the crop yield scale factor and the relative output rate of fertiliser application, calculated asFIE indicates the integrated relative output rate of fertiliser application, i.e., the integrated efficiency, and the larger the integrated efficiency, the better the combined effect of the FRO and crop yield.To reflect the scale effect of fertiliser application, the concept of Fertilisation Integrated Efficiency (This paper adopts the LMDI method  to facto(i) Influence of primary industry value added on total fertiliser and pesticide use.The application of pesticides and chemical fertilisers can boost crop yields and reduce farmers’ agricultural capital investment. In most provincial areas of China, there is a correlation between grain production and fertiliser application. Grain production is very highly dependent on fertiliser application, which is increasing year by year, and the phenomenon of random and additive fertiliser application is widespread in China . The app(ii) Impact of the scale of rural operations on total fertiliser and pesticide use.Research shows that the coexistence of different farming operation scales is a long-standing social phenomenon in China, and different scales of farming operation affect farming behaviour, such as production inputs, labour allocation, technology adoption, and planting motivation of farming households. The scale of rural operations plays a key role in the sustainable development of agriculture, and it has a profound impact on the economic and environmental performance of agricultural production . In gene(iii) Influence of total agricultural producer price index on total fertiliser and pesticide use.Agricultural product prices are an important component of the agricultural market. Price fluctuations of agricultural product affect not only the overall operation of the agricultural economy but also all aspects of agricultural production. Food output is directly related to farmers’ production investment. Farmers play a pivotal role in production investment. Price fluctuations of agricultural products as a signal of market changes influence farmers’ production investment decisions. According to the rational man assumption, farmers are profit maximisers in an ideal market model. When the prices of production factors remain constant, an increase in the price of agricultural products will cause an increase in expected returns, and farmers will tend to increase factor inputs to the point where marginal cost equals marginal return. Fertilisers and pesticides are important factors of production, and when the price of agricultural products falls, farmers may reduce fertiliser and pesticide inputs to obtain a relatively high net profit. The increase in agricultural product prices may also cause an increase in inputs of materials such as fertilisers and pesticides for farmers. In the current context of steadily increasing agricultural product prices, China’s agricultural policy orientation has shifted from increasing production to focusing on greenness and quality, and reduction in fertiliser use is an inevitable requirement for green, healthy, and sustainable agricultural development . Consequt and F0 denote the total fertiliser–pesticide use in period t and the base period, respectively; ΔFGDP-pi represents the change in total fertiliser and pesticide use due to value added in the primary sector; ΔFTPPPI-ap represents the change in total fertiliser and pesticide use due to agricultural producer prices; and ΔFFLCI represents the change in total fertiliser and pesticide use due to the scale of rural operations. We used the LMDI model to process the data and decompose the total fertiliser and pesticide use into three factors: the value added of primary industry, the scale of rural operation, and the total producer price index of agricultural products. The LMDI calculates the specific influence and contribution of each factor to either the increase or the decrease in use of fertilisers and pesticides, and the results can then be analysed to identify the main factors influencing the total fertiliser and pesticide use. The additive equation of LMDI is expressed as follows:The results of the factor decomposition analysis reveal that the value added of the primary industry has the most significant impact on fertiliser and pesticide use. To understand the characteristics of the relationship between the intensity of fertiliser and pesticide application and crop yield in each province, this paper presents the intensity of fertiliser and pesticide use and the value added of primary industry in each province in recent years. First, the 31 provinces have been classified into the following four categories: high-intensity, high-yield (HS–HY); high-intensity, low-yield (HS–LY); low-intensity, high-yield (LS–HY); and low-intensity, low-yield (LS–LY), using the intensity of pesticide use as the intensity indicator and the value added of primary industry as the yield indicator.Then, the intensity of fertiliser and pesticide application in each province was equated to a horizontal coordinate, the value added of primary industry in each province was equated to a vertical coordinate, and the results were arranged in descending order. The distance between each point and the top of the histogram shows the combination of intensity–yield characteristics. Lastly, we used the four provinces closest to the fixed points of the histogram as the initial clustering centres and the Euclidean distance for clustering analysis. The different provinces have been classified within the four different intensity–yield categories .2, which was three times that of France, two times that of the Netherlands, two times that of the UK, and 3.7 times that of the US, respectively, and far greater than the global average fertiliser use of 138.9 kg/hm2.2 lower than that in China by 2016. To reduce the impact of pesticide use on the ecological environment, France implemented a pesticide reduction plan in 2008, with the goal of reducing pesticide use by 50% over 10 years. The main types of pesticides used in the UK are herbicides; before 2005, the annual use of herbicides in the UK was approximately 20–25 thousand tonnes, whereas, after 2005, the use of herbicides decreased significantly due to the use of alternative herbicides with higher activity at lower dosage. FAO data show that the intensity of pesticide use in China in 2016 reached 13.06 kg/hm2, ranking 15th in the world and higher than in developed countries such as the US, the UK, France, and The Netherlands.Based on Equations (2) and (3), we have calculated the relative output rates of fertiliser application, i.e., net efficiency, for China and four other countries from 2002 to 2016. China’s total fertiliser use and intensity of use were both at a high international level, but the relative FO was low, even far below those of the developed countries and the world average.The relative output rate of fertiliser application only reflects the net rate of fertiliser utilisation of a country. However, agricultural production that aspires to a high yield per unit area requires a high rate of fertiliser utilisation, i.e., high efficiency and high output, which better reflects the meaning and role of fertiliser inputs. Therefore, considering the combined effects of relative FO and grain yield, we used Equations (4) and (5) to calculate the combined efficiency of fertiliser application in each country for each year . The larFrom 1997 to 2016, the PO in China fell from 525.3 kg/kg to 461.7 kg/kg, a reduction of 63.6 kg/kg, whereas the POs of developed countries such as France, the UK, the US, and the Netherlands increased by 309.2 kg/kg, 1002.3 kg/kg, and 907.3 kg/kg, respectively. Overall, the POs of China and the Netherlands were significantly lower than those of other countries, mainly due to the higher intensity of pesticide use in both countries . The larWe used the LMDI model to process the data and decompose the total fertiliser and pesticide use into three factors: the value added of the primary industry, the scale of rural operations, and the total producer price index of agricultural products. In addition, we calculated the specific impact and rate of contribution each factor to either the increase or the decrease in fertiliser and pesticide use , and theWe divided the 1997–2016 time series into two phases: 1997–2006 and 2007–2016. We used the equations to calculate the contribution value and contribution rate  of the following three factors: primary industry value added, rural operation scale, and the total agricultural producer price index for the total fertiliser and pesticide use.As the factors are in a state of fluctuation, the contribution of each effect to the total pesticide use is expressed more visually through horizontal bar charts, and the contribution of each factor is shown in The histogram of the contribution of the factors plotted reveals that the contribution of the value added of the primary industry to the total fertiliser and pesticide use from 1997 to 2006 was more than 100%. There was a significant downward trend in the degree of scale of arable land during this period, and the total agricultural producer price index first declined and then showed a significant upward trend after 2002. There was a significant upward trend in both the degree of scale of arable land and the total agricultural producer price index from 2007 to 2016. The degree of influence of two factors—the degree of scale of arable land and the total price index of agricultural products—on the total use of fertilisers and pesticides increased significantly from 2007 to 2016. The influence rate of the added value of primary industry on the total fertiliser and pesticide use exceeded 50%. As a developing country, China possesses huge potential for economic development; between 1997 and 2016, the growth rate of the value added of primary industry in China reached 75.99%. The contribution of the value added of the primary industry to the total fertiliser and pesticide use is anticipated to increase further. Though scale of operation of arable land facilitates the management of fertiliser and pesticide use, the current rural land transfer is still fragmented, the land transfer rate is still low, and the scale development trend has not yet been formed. Consequently, the impact of the scale level on the intensity of fertiliser and pesticide use is limited.The LMDI model analysis shows that the value added of primary industry in China had the greatest impact on the total use of fertilisers and pesticides. There was an increase in the degree of impact of the scale of rural operations and producer prices of agricultural products on the total amount of use. The above three influencing factors play a crucial role in promoting both reduction and efficiency of chemical fertiliser, pesticide reduction, and pest control in China, thereby determining whether China can achieve transformational development and high-quality development and follow a modern agricultural development path with high output efficiency, product safety, resource conservation, and environmental friendliness. However, China’s regional development is uneven, with large disparities between provinces and regions with respect to natural geographic conditions, and the performance characteristics and influence effects of the three influencing factors of value added of primary industries, rural business scale, and producer prices of agricultural products differ. Therefore, based on China’s rural statistics, we used the cluster analysis method to analyse the intensity of pesticide and fertiliser use and the value added of the primary industry in 31 Chinese provinces , and we combined international experience to promote the high-quality development of agriculture in various parts of China according to local conditions.Using the intensity of pesticide use as an indicator of intensity and the value added of primary industry as an indicator of production, we classified the 31 provinces into the four categories of HI–HY, HI–LY, LI–HY, and LI–LY. The horizontal coordinate is the intensity of pesticide use in each province, and the vertical coordinate is the value added of primary industry in each province, with the coordinates arranged in descending order to form the histogram in We used the provinces of Henan, Guangdong, Ningxia, and Hainan, those with the shortest distance from the histogram’s vertices, as the initial clustering centres and then standardised the data and clustered them by Euclidean distance .Using the fertiliser use intensity as an indicator of intensity and the value added of primary industry as an indicator of production, we classified the 31 provinces into the four categories of HI–HY, HI–LY, LI–HY, and LI–LY. The horizontal coordinate is the intensity of fertiliser use in each province, and the vertical coordinate is the value added of primary industry in each province, with the coordinates arranged in descending order to form the histogram in We used the provinces of Shandong, Beijing, Sichuan, and Qinghai, those with the shortest distance from the histogram vertices, as the initial clustering centres, and then we standardised the data and clustered them by Euclidean distance .The results of the cluster analysis of FI and the value added of primary industry against the results of the cluster analysis of pesticide application intensity and value added of primary industry in 2016 revealed that 16 of the 31 provinces had the same type of “intensity–yield” of fertilisers and pesticides. In this paper, we focus on two core tasks. The first task is a comparative study of the trends in fertiliser and pesticide use intensity and integrated application efficiency in China and four developed countries ; the second task involves using an improved LMDI model and cluster analysis to identify the driving factors and driving effects of increased pesticide and chemical fertiliser inputs in China and to discuss the exploratory effects of different provinces in reducing the use of chemical fertilisers and pesticides and in increasing efficiency based on the results of the impact factor analysis.China’s consumption of pesticides and fertilisers ranks highest in the world, and the country shows an overall trend of rapid growth until 2012, after which the rate of growth tends to level off. Compared with other countries, China’s total use and intensity of use of pesticides and fertilisers are both high, and its comprehensive efficiency of utilisation of pesticides and fertilisers is not high and is far below the world average. Overall, the gap between grain crop yields per unit area of grain in China and those in typical developed countries is narrowing gradually; however, there is significant variation in the quality of major grain varieties, and greater efforts are needed to close the gap.Application efficiency is measured mainly by the relative output ratio of grain crop yield to application of fertilisers and pesticides. Cereal yields in the five countries studied exhibit a fluctuating upward trend, and the gap between China’s grain crop yields and those of typical developed countries per unit area of grain is narrowing gradually. However, in recent years, China’s grain production efforts and scientific research have focused mainly on increasing grain quantity, neglecting improvement in grain quality, which, in turn, has resulted in significant variation in the quality of major grain varieties. The world’s major developed countries and agricultural countries attach considerable importance to cultivating and promoting good crop varieties , and theChina’s total fertiliser and pesticide use and intensity of use are at a high international level; however, the country’s relative output rate is low, even far below those of the developed countries and the world average. In recent years, due to the implementation of measures to reduce and increase the efficiency of chemical fertilisers and pesticides in China, the country’s grain production has continued to increase, and there has been slight improvement in the relative output rate of application. Since 2015, the Ministry of Agriculture and Rural Affairs has deployed an in-depth zero-growth action of chemical fertilisers and pesticides to reduce their use and increase their efficiency to achieve significant results. Grain crops make up the largest proportion of the total sown area of crops. Between 2015 and 2019, there has been a fluctuating upward trend of China’s total sown area of crops. In 2019, the total sown area of crops China was 165,931 thousand hectares, an increase of 29 thousand hectares from the previous year, at a rate of increase of 0.02% year-on-year. The use of agricultural fertilisers is continuing to decline. In 2018, 565.342 million tonnes of agricultural fertilisers were applied in China, which was down by 2.0599 million tonnes from the previous year, at a rate of decrease of 3.52% year-on-year. In 2019, 54.0359 million tonnes of agricultural fertiliser were applied in China, which was down by 2.4983 million tonnes from the previous year, with a rate of decrease of 4.42% year-on-year. The use of pesticides has also shown a continuous downward trend, with 1.5 million tonnes of pesticides applied in 2018, down 9.64% year-on-year, and 1.39 million tonnes applied in 2019, down 7.33% year-on-year. Scientific calculations show that, in 2019, the fertiliser utilisation rate for the three major food crops of rice, corn, and wheat in China was 39.2%, 1.4 percentage points higher than in 2017, and 4.0 percentage points higher than in 2015. Meanwhile, the pesticide utilisation rate was 39.8%, 1.0 percentage points higher than in 2017, and 3.2 percentage points higher than in 2015 .Analysis of the contributions of the three factors of the value added of the primary industry, the scale of rural operations, and the total producer price index of agricultural products has shown that the value added of the primary industry has a more significant impact on the use of fertilizers and pesticides . The valThe provinces of Hainan and Shanghai are in the HI–LY category. Hainan is located in the agricultural and forestry area of Qionglei and the islands of the South China Sea. According to the 2019 National Arable Land Quality Grade Status Bulletin, Hainan is dominated by purple, limestone (rock), and sandy soils of relatively low basic strength, and it lacks farmland infrastructure . MoreoveShanghai is located on the plains of the lower reaches of the Yangtze River, and it is a hilly agricultural and fishery area, with mainly yellowish-brown and brown soil, poor standing conditions, large topographic fluctuations, poor levels of soil nutrients, low basic strength, backward water conservancy facilities, inadequate irrigation conditions, and obstacles in some of the arable land . FarmersThe results of the cluster analysis show that the intensity of fertiliser application is high in Beijing, Tianjin, Jilin, Shanghai, Fujian, Hainan, Shaanxi, and Xinjiang, though the added value of primary industry is relatively low. Beijing and Tianjin both face the problem of unbalanced fertiliser application structure, and over-fertilisation by farmers is the main cause of surface pollution by fertilisers.A comparison of the total area planted with crops and the intensity of fertiliser application in Beijing and Tianjin over the past 20 years reveals a downward trend in the two regions; however, there has been an increase in the area planted with cash crops and vegetables. The intensity of fertiliser application is exhibiting a trend of continuous growth . AdditioAlthough Jilin province is an important grain production base in China, the analysis reveals it to be in a low-yield region. The factors affecting grain production in Jilin include the following: first, Jilin’s farmland infrastructure is backward, with a large area of low- and medium-yielding fields and declining soil fertility; second, drought has become an important factor restricting agricultural development in this province; and third, with the shift of the agricultural labour force, there has been a decline in the quality of the labour force engaged in agricultural production. These problems have had a severe impact on food production in Jilin . In 2007Fujian province is located in the middle and lower reaches of the Yangtze River, in hilly and mountainous areas of low-quality arable land with poor standing conditions, large topographic fluctuations, poor soil nutrients, low basic strength, and poor field infrastructure. These limitations of the land affect the province’s food production. Nevertheless, Fujian is a large agricultural province. Since the start of the new millennium, agriculture in Fujian province has continued to develop rapidly; however, there has been no significant change in the extensive agricultural development pattern of “high input, high output, high emissions”, and the change in planting structure has exacerbated agricultural surface pollution. Although grain production in Fujian province has declined, there has been a rapid increase in the production of cash crops. Cash crops have a higher demand for chemicals such as fertilisers than do food crops . MoreoveShaanxi province is located in China’s inland hinterland. Though there are many people there, the little available arable land is of poor quality, reserve resources are inadequate, and the situation with regard to the protection of arable land is very serious. In recent years, conditions of Shaanxi agricultural production have improved significantly; however, neither the scale nor the intensification are high, the gap in food production has widened, the level of livestock production has lingered, the process of development of modern agriculture is slow, agricultural production generally has low yields, and labour efficiency is not high, all of which negatively affect agricultural production in Shaanxi province. As a traditional agricultural province in the west of China, the production and operational behaviour and the organisational system of farm households in Shaanxi province are typical of traditional farm households in China, combining traditional agriculture with a high degree of fertilisation, leading to excessive use of chemical fertilisers .As a large agricultural province (region), Xinjiang’s food production occupies an important place in its economic structure. However, Xinjiang’s location in the southwestern part of China, deep inland, where it is hot all year round and there is little rainfall, has led to a shortage of surface water and poor agricultural irrigation conditions, which poses enormous challenges for food production in the province.Agricultural development in Xinjiang is currently facing the problem of agricultural surface pollution, which restricts the sustainable development of agriculture. Fertiliser input source pollution is one of the main types of agricultural source pollution in Xinjiang, where the intensity of fertiliser application is far above safe standards for fertiliser use. The main focus is on application of nitrogen and phosphorus fertilisers . MeanwhiChina is a vast country, with huge differences between provinces in terms of natural geographic conditions and agricultural development, and the amount of chemical fertilisers and pesticides applied also differs between provinces. The results of the cluster analysis of the intensity of pesticide and fertiliser use and the value added of primary industries in each province of China in 2016 show that the provinces of Guangdong and Hubei are in the HI–HY category. As part of China’s main food supply area, they need to maintain production of agricultural products in accordance with an optimal pesticide and fertiliser reduction and efficiency technology model. Both Hainan and Shanghai are in the HI–LY group. Although the region has high intensity of application of chemical fertilisers and pesticides, the crop yield is low, and there is need to reduce the pressure on agricultural production, through the use of soil testing and fertilisation, planting structure adjustment, and other measures to reduce agricultural input. The five provinces of Hebei, Anhui, Hunan, Guangxi, and Sichuan are in the LI–HY category; they have low intensity of fertiliser and pesticide, coupled with high yield. The level of agricultural development is relatively high, the future offers good potential for agricultural development, and there is a need to improve the quality and efficiency of agriculture without increasing the inputs of pesticides and fertilisers. The four provinces of Yunnan, Tibet, Gansu, and Qinghai are in the LI–LY category and are key to improving the sustainable development of China’s agriculture. Aside from the above provinces, Fujian Province has a relatively high level of intensity of fertiliser and pesticide application, which should be adapted to the local conditions, and a pesticide and fertiliser reduction and efficiency improvement technology model suitable for the local geographic and cultural conditions should be sought.In recent successive years, chemical fertilisers and pesticides have played a key role in China’s grain harvests; however, they have had certain impacts on the environment . Before Since the promotion of the “double reduction” programme for application of fertilisers and pesticides, both the total amount and the intensity of the fertilisers and pesticides used in agricultural have declined greatly throughout China; however, as total amount of agricultural fertilisers and pesticides used in China is so high, the intensity of use is still too high, and there is still enormous room for improvement in reducing fertiliser and pesticide use, particularly in areas with high pesticide and fertiliser input intensity and low value added in primary industries, strengthening the policy of double reduction of chemical fertilizers and pesticides is particularly critical .The intensity of pesticide and fertiliser application in China is high and has been increasing steadily. However, the comprehensive efficiency of utilisation of pesticides and fertilisers in China is not high and is far below the world average. The average comprehensive efficiency of application of fertilisers in China from 2002 to 2016 was 0.27, which was only 28% of the comprehensive efficiency of application in the Netherlands and 41% of that in the US. The average comprehensive efficiency of application pesticides in China was 0.28, which is only 35% of that of the USA and 40% of that of the UK. Of the three factors of value added of primary industry, scale of rural operation, and producer price of agricultural products, value added of primary industry has the greatest influence on total fertiliser and pesticide application. The degree of influence of the scale of rural operations and producer prices of agricultural products on the total use has increased. The value added of the primary industry contributed 56% from 2007 to 2016, and the total agricultural producer price index and the scale of rural operations contributed 35.51% and 8.49%, respectively. The results of cluster analysis of the intensity of pesticide and fertiliser use and the value added of the primary industry in 2016 in 31 provinces showed that Hainan and Shanghai had high intensity of pesticide application but low value added of the primary industry, and Beijing, Tianjin, Jilin, Shanghai, Fujian, Hainan, Shaanxi, and Xinjiang had high intensity of fertiliser application but relatively low value added of the primary industry. There is huge and imperative pressure to reduce the application of fertilisers and pesticides.As of the end of 2020, China has successfully achieved the expected goals in fertiliser and pesticide reduction and efficiency, with a significant reduction in the application of fertilisers and pesticides and a significant increase in the efficiency of fertilisers and pesticides, thereby promoting the high-quality development of the plantation industry, with obvious results. However, the agricultural surface pollution resulting from the excessive use of pesticides and chemical fertilisers has become a bottleneck for the sustainable development of China’s agriculture. In the future, we will conduct further research work through questionnaires and field interviews to guide, in a more scientific and effective manner, the actions toward pesticide and chemical fertiliser reduction and increased efficiency for different crops, in addition to farming methods and planting structures in various regions, promote agricultural transformation and upgrading, follow the route of socialist rural revitalisation with Chinese characteristics, and accelerate the modernisation of both agriculture and rural areas.


Thermal conductivity of polymer-based (nano)composites is typically limited by thermal resistances occurring at the interfaces between the polymer matrix and the conductive particles as well as between particles themselves. In this work, the adoption of molecular junctions between thermally conductive graphene foils is addressed, aiming at the reduction of the thermal boundary resistance and eventually lead to an efficient percolation network within the polymer nanocomposite. This system was computationally investigated at the atomistic scale, using classical Molecular Dynamics, applied the first time to the investigation of heat transfer trough molecular junctions within a realistic environment for a polymer nanocomposite. A series of Molecular Dynamics simulations were conducted to investigate the thermal transport efficiency of molecular junctions in polymer tight contact, to quantify the contribution of molecular junctions when graphene and the molecular junctions are surrounded by polydimethylsiloxane (PDMS) molecules. A strong dependence of the thermal conductance was found in PDMS/graphene model, with best performances obtained with short and conformationally rigid molecular junctions. Furthermore, the adoption of the molecular linkers was found to contribute additionally to the thermal transport provided by the surrounding polymer matrix, demonstrating the possibility of exploiting molecular junctions in composite materials. Thermally conductive polymer-based materials are of interest in several thermal management applications, owing to the unique set of properties of polymeric materials, coupling excellent chemical resistance in harsh environment, mechanical flexibility, and ease of processing into complex shapes ,2. As poThermal Boundary Conductance (TBC) at particle–particle contacts was numerically studied with different computational tools by various authors, either between carbon nanotubes and graphene platelets, functionalized with small bridging groups ,13,14,15Classical Molecular Dynamics (MD) has become a popular method to investigate dynamic properties of materials at the atomistic scale . It is biT is the temperature of ith slab portion, iN is the number of atoms in Ith group, kB is the Boltzmann’s constant, jm and jp are atomic mass and momentum of atom j, respectively. Within this method, longer simulation time assures higher accuracy of the temperature calculation thanks to the longer sampling time. From the plot of the average temperature of the slabs, as a function of the coordinate displacement, it is possible to evaluate the thermal jump across the junction. As a consequence, the thermal conductance can be computed through Equation (2),cG is the thermal boundary conductivity, T the temperature across the interface.After the transitory thermostated pre-heating stage, the system runs flawlessly in steady-state, and for the following 2.5 ns the information of the thermal energy exchanged trough the thermostats and temperature of the slabs ,31 was cThe largest subset of the atoms constituting the simulation belongs to the Polydimethylsiloxane (PDMS) polymer which surrounds the junction between two graphene foils. The design of the PDMS mass, made up of 2 blocks of 34 molecules , initiated by the creation of a 49-monomer single chain, Si-methyl terminated of 507 atoms each .−3, a typical literature value [2 graphene platelets jointed by three molecular junctions covalently bound, plus an unjointed one for comparison. Overall, about 36,500 atoms were computed in each simulation. As a common assumption, the van der Waals cut-off was set to 10 Å.To create a bulky mass, an NPT stage was carried by rising the pressure up to 1.5 GPa for 500 ps to set the density of the polymer to about 0.97 g cmre value . All there value . COMPASSre value . The COMre value ,22. The Three different molecular structures were selected in this work as junctions between the graphene foils and compared with the unjointed graphene. We choose the three molecules based on the results from our previous studies where we screened some chemically feasible  thermal −1 with an average improvement of about 4%. For the aromatic biphenyl, the heat flux rises up to 1.65 eV ps−1 and for the anthracene, a value of 1.78 eV ps−1 was calculated, with a gain of about 12% and 21%, respectively.For each of the molecular junction described above, the energy transferred from the hot thermostat region to the cold thermostat region is reported in The temperatures of the graphene thermal layers for PDMS-embedded junctions investigated are reported in −2 K−1. As a general physical concept, with longer or more complex paths for the phonons to transport, the phonon scattering increases and thus the lower is expected to be the thermal conductance. Such a basic concept is in agreement with our findings as summarized in 2), thus representing the conductance of the whole system between the two thermostats as a contribution of ITC between graphene and PDMS and TBC trough edges. Adopting the same methodology for the other models where linkers were employed, the C5OP temperature jump  the thermal conductance of the linkerless junction. Given the small thermal jump observed in the acene-bound interface, the ACN junction could be considered the equivalent of a continuous defective material. With this latter model, a continuous fit of the temperature may be applied, as depicted in −1 K−1. This value may be considered representative of a network of graphene flakes fully joined by acene junctions within a PDMS matrix and represents a theoretical upper value for molecularly joined graphene-based nanocomposites.The model without molecular junctions between the graphene foils a reporteure jump  was calcjunction c shows ajunction . The temion 67%,  than incion 67%, . The antWhile the thermal conductance calculated for the different PDMS embedded molecular junctions suggest large differences in their effectiveness, the conductance trend appears coherent with conductance values reported for self-standing junctions . HoweverThe thermal conductance between graphene platelets surrounded by a PDMS polymer matrix has been evaluated trough NEMD simulations. We observed that even in presence of a tight contact with the polymer, the linker type influenced the overall conductance value by reducing the thermal drop. The hybrid aliphatic and aromatic C5OP junction yields to a thermal conductance improvement of about 20% compared to the unbound sheets, while aromatic structures provided higher enhancements, confirming the previously reported trends for self-standing junctions. In particular, biphenyl junctions enhanced thermal conductance by about 68% while anthracene linkers, considered as a sort of upper bound theoretical case study, yielded to a five-times reduction of thermal resistance. We also observed that the presence of the molecular junctions contributes to the total heat flux, adding on the heat flow exchanged via the surrounding polymer, embedding the junctions. The strong dependence of the thermal conductance in PDMS and graphene model is attributed to both the length and the chemical structure of the linker. On one hand, short linkers force the flakes to keep a smaller gap between the platelets than longer ones; consequently, the volume of interposed polymer is smaller. On the other hand, the length of the linker is not sufficient to justify the observations and it is therefore suggested that the conformational stiffness of the linker strongly affects the efficiency of the junction, in agreement with previous findings for self-standing junctions. The findings reported in this paper are therefore opening the way for the engineering of thermal contacts between conductive nanoparticles, within the next generation of advanced polymer based materials for heat management applications.


Previous studies have reported that poly(vinylidene fluoride-hexafluoropropylene) (P(VDF-HFP)) copolymers can exhibit large electrostrictive strains depending on the filler. This work examines the electrostrictive and structural properties of P(VDF-HFP) nanofibers modified with conductive polymer polyaniline (PANI). The P(VDF-HFP)/PANI composite nanofibers were prepared by an electrospinning method with different PANI concentrations . The average diameter, water contact angle and element were analyzed by SEM, WCA and EDX, respectively. The crystalline, phase structure and mechanical properties were investigated by XRD, FTIR and DMA, respectively. The dielectric properties and electrostrictive behavior were also studied. The results demonstrated that the composite nanofibers exhibited uniform fibers without any bead formation, and the WCA decreased with increasing amount of PANI. However, a high dielectric constant and electromechanical response were obtained. The electrostrictive coefficient, crystalline, phase structure, dielectric properties and interfacial charge distributions increased in relation to the PANI content. Moreover, this study indicates that P(VDF-HFP)/PANI composite nanofibers may represent a promising route for obtaining electrostrictive composite nanofibers for actuation applications, microelectromechanical systems and sensors based on electrostrictive phenomena. The SEM images were also used to analyze the average fiber diameter using the ImageJ program. As demonstrated in cX) of pure P(VDF-HFP) nanofibers is 48.40%, and it increases upon the addition of PANI filler. The composite fibers are molecularly oriented during the electrospinning. −1. The vibrational bands at 534, 617, 765 and 976 cm−1 are determined to the characteristic peaks of the α-phase observed in the pure P(VDF-HFP) nanofiber web [−1 are increased. It can be inferred that with PANI loaded in P(VDF-HFP), not only is the α-phase reduced but also the β-phase is also induced in the composite nanofibers. In F(β)) with various concentrations of PANI filler is shown. It is found that the F(β) values increase from 73.53% to 85.79% when the minimum amount of PANI (0.5 wt.%) is added to P(VDF-HFP). The F(β) values slightly increase with the increasing amount of PANI filler. Furthermore, the absolute β fraction (%β), evaluated by Equation (3) using the XRD and FTIR results, gives information about the overall β-phase within the as-prepared nanofibers. It is evident that the %β values increase rapidly upon adding only 0.5 wt.% of PANI and then increase gradually with the PANI content. These observations denote the effect of varying PANI filler loaded into P(VDF-HFP) nanofibers prepared by electrospinning techniques, which can affect the orientation of the dipoles to promote β-phase formation [The electroactive β-phase in the nanofiber samples was further examined via FTIR spectra. iber web , indicatormation . E′ is observed from −40 °C to 0 °C, which is ascribed to the glass transition of P(VDF-HFP) [tanδ as a function of temperature for pure and composite nanofibers at varying concentrations of PANI filler. The first peak damping of the relaxation process provided the α-relaxation, which was related to the motion in a crystalline fraction, while the second peak relaxation process depicted the melting temperature [tanδ curve [terfaces . A slow VDF-HFP) . This efperature . Normallnδ curve . The β-rnδ curve . The You2 Hz), a high dielectric constant is observed and it decreases with increasing frequency. The dielectric constant is associated with free dipole vibration in an alternating field at low frequency. The dielectric constant increases with the PANI concentration, as listed in 2 Hz increases from 1.48 to 2.58 for the 5 wt.% P(VDF-HFP)/PANI composite nanofibers, which is around 1.74 times that of the pure P(VDF-HFP) nanofibers. Clearly, the PANI reduces air gaps and induces surface charges, causing strong Maxwell–Wagner interfacial polarization. Furthermore, the dielectric loss tangent increases with the PANI concentration from 0.00071 to 0.02403 at 102 Hz. It is recommended for use in ferroelectric and dielectric applications.Y is the Young’s modulus. According to a prior publication, the strain from Maxwell stress is minimal compared to the measured strain, and therefore the Maxwell stress effect can be neglected [σ) at 102 Hz. The Young’s modulus (Y) and electrostrictive coefficients  composite nanofibers can be performed successfully by electrospinning techniques. The P(VDF-HFP)/PANI composite nanofibers exhibit uniform fibers without any bead formation, with a high dielectric constant and electromechanical response. The water contact angle of the nanofibers is found to be in the range of 126 ± 2.8° to 139.2 ± 3.2°, indicating a hydrophobic surface. The synergistic effect of electrospinning and the addition of PANI to the P(VDF-HFP) composite nanofibers can enhance the crystallinity, β-phase content and absolute β fraction by approximately 55.49%, 89.22% and 49.51% for a 5.0% PANI concentration, respectively. The elastic modulus and dielectric constant also increase after PANI filling. Furthermore, the P(VDF-HFP)/PANI 5 wt.% composite nanofibers display the largest electrostrictive coefficient The results indicate that PANI addition in P(VDF-HFP) nanofibers can improve the electrostriction behavior attributed to the crystalline, phase structure, dielectric properties and interfacial charge distributions. The electrostrictive coefficient increases related to the PANI contents. Moreover, the electrostrictive strain response improves under low electric fields. This study indicates that P(VDF-HFP)/PANI composite nanofibers may represent a promising route for obtaining electrostrictive composite nanofibers for actuation applications that are poor wettability.


In this research, five kinds of PLLA with different molecular weights were prepared by ring-opening polymerization with strict dehydration operations and multistep purification treatments. Then, thin film isothermal crystallization experiments were carried out to obtain crystallized samples. Previous research has proven that the PLLA α crystal form is usually formed at a temperature above 120 °C and the PLLA δ (or α’) crystal form is usually formed at a temperature below 120 °C. However, in this research, the characterization results indicated that the PLLA crystal changed from δ form to α form with the decrease of molecular weight at a temperature of 80 °C. Considering the molecular weight effect, the paper argued that the transitions of the α/δ crystal form are not only associated with temperature, but also related to entanglement state before crystallization. The small-angle X-ray scattering of the PLLA crystal and rheology analysis of the PLLA melt before crystallization further proved the significant role of entanglement. Finally, we tentatively proposed the entanglement effect mechanism on the transitions of the α/δ crystal form.Poly( Please see The number-average molecular weight Confocal Laser Scanning Microscopy (CLSM). The altitude and morphology of the polymer film were measured by CLSM on a Zeiss LSM 700  at atmospheric condition, which can take the place of AFM when the size of the observed object is bigger than 50 μm.Atomic Force Microscopy (AFM). AFM  was used to measure the thickness and morphology of the crystals at atmospheric conditions, operating with silicon cantilevers in the PeakForce Tapping mode. The peak force error image was obtained to reflect the phase morphology of polymer samples.Wide-Angle X-ray Diffraction (WAXD). WAXD measurement was performed by using a DMAX-2500PC  with a Cu Kα source, operating at 40 kV and 150 mA. The scanning range was from 5° to 35° and the rotate rate was 2°/min.Differential Scanning Calorimeter (DSC). The melting processes of the crystallized PLLA samples were measured by using a NETZSCH STA 4495F5 apparatus . The crystallized samples with an average weight of 5 mg were reheated to 200 °C at a rate of 10 °C/min under a nitrogen atmosphere.2, AntonPaar, Graz, Austria) was used to measure the long periods, thickness of crystal layers, and thickness of amorphous layers of the lamellar stacks of PLLA samples with different molecular weights. The PLLA samples were stripped from the Si wafer after crystallization treatments. The operation voltage was 40 kV, and the operation current was 50 mA. The wavelength of X-ray radiation was 0.1542 nm, and the distance from sample to detector was 264.5 mm. The raw SAXS data were then background corrected according to a standard procedure.Small-Angle X-ray Scattering (SAXS). SAXS  was used to characterize the rheological properties of the PLLA samples. The testing samples for rheology characterization had a circle shape with a diameter of 20 mm and a thickness of 1.2 mm. The frequency sweep tests in a constant strain mode were performed at a strain of 0.1% over a frequency range of 0.1–10 Hz.It is well known that molecular weight has significant influence on polymer crystallization. Five kinds of PLLA with different molecular weights were made into thin films, and then isothermal crystallization experiments were carried out. Please refer to This section will further investigate the crystal structure differences of the five PLLA samples. In The DSC curve of PLLA3 shows two melting peaks at 154.0 °C and 161.6 °C, respectively. This kind of double melting peak of PLLA was also found in other research ,19. AccoFurthermore, there is significant difference among the peak positions of the same crystal form, e.g., the melting peaks of PLLA1 and PLLA2. According to the Gibbs–Thomson equation for melting point, the deviation of melting point temperature Tm from the thermodynamic equilibrium melting point rived by :(1)Tm−Tm−1  of PLLA is near 4000 g/mol.  . In thisBased on intramolecular nucleation theory ,40 and mThe molecular weight of PLLA1 is much smaller than Me, and the PLLA1 melt has no shear thinning phenomenon. So, PLLA1 molecular chains can be assembled into crystals in the form of extended chains or integral folding chains. The molecular weight of PLLA2 is slightly larger than Me, and the slight entanglements are easily untied under the driven force of crystallization kinetics. PLLA2 molecular chains can also be assembled into crystals by integral folding chains. From this point, the formation process of α crystals in the PLLA1 and PLLA2 sample is almost unaffected by entanglement.By comparison, the entanglement effect is more remarkable in the PLLA3, PLLA4 and PLLA5 samples. With the driving force of crystallization, it is difficult to extract the molecular chain from the entangled network in time. The molecular chain cannot form extended chain and integer-folded chain, but forms non-integer folding chain in the crystal. According to the WAXD results shown in As mentioned in Based on the research of Fritzsching et al. , entanglFurthermore, considering the molecular weight dependence of the transition between δ and α form, the crowded amorphous region may be what hinders the ordering process of the δ molecular helix chain with low mobility under low temperature. When the molecular weight is smaller than the critical entanglement molecular weight, there is little or no crowding on the end surface of the lamella. As a result, the PLLA molecular chains can be assembled in an ordered α system, even though the temperature is below 120 °C. When the molecular weight is significantly larger than the critical entanglement molecular weight, the crowding effect will squeeze the helix chain in the crystal region and the helix chain tends to form disordered δ crystals.Based on the above results and discussions, l-lactide-co-d-lactide) [l-lactic acid-co-l-2-hydroxybutanoic acid) [l-lactic acid-alt-glycolic acid) [l-lactic acid-co-l-alanine) [l-lactic acid-co-l-alanine) copolymers with wide alanine unit content ranges for melt-crystallization, and the molecular weight of this copolymer is in the range of 10,000~17,000 g/mol. They found that the transition crystallization temperature of copolymer samples from α form to δ form decreases with an increase of alanine unit content [Furthermore, during the crystallization of lactic acid-based copolymers, including Poly(lactide) ,54, Polyic acid) ,56, Polyic acid)  and polyalanine) ,59, therl-lactic acid and small polydispersity of PLLA provided us basic conditions to tailor the crystal structure to. The characterization results of WAXD indicated that the PLLA crystal is changed from the δ form to the α form with the decrease of molecular weight at a temperature of 80 °C. Considering the molecular weight effect and rheology feature of PLLA melt, this paper argued that the transition of the crystal form is related to molecular entanglements. The ordering of the δ crystal form may be hindered by crowding on the end surface of the lamella, which is caused by entanglements and other amorphous chain segments at low temperatures. Hence, the transition of the α/δ crystal form is not only associated with temperature, but also related to entanglement state before crystallization. The findings of this research again enhance the significant role of entanglement in polymer crystallization. With significant entanglement effect or molecular weight effect, long-chain molecules of polymer tend to form metastable crystal structures during the ordering process at low temperatures.In this research, five kinds of PLLA with different molecular weights were prepared by ring-opening polymerization with strict dehydration operations and multistep purification treatments. The high purity of