Characteristics of mulching film residue pollution in farmland and its influencing factors in Xinjiang region
In order to investigate the intensity and distribution of plastic film residue pollution in the Xinjiang region,625 valid locations in Xinjiang were selected for questionnaire surveys and on-site sampling.The entropy weight method and analytic hierarchy process were employed to combine weights for the influencing factors of plastic film residue,including plot area,distance from the village,years of film coverage,and proportion of film coverage.The weight coefficients were calculated as 0.200,0.315,0.265,and 0.220,respectively.Based on the optimized clustering indicators,a cluster analysis was conducted on the plastic film residue pollution data for the year 2021.The results showed that there were highly significant differences in plastic film residue amounts under the influence of different factors,including plot area,distance from the village,years of film coverage,and proportion of film coverage(P<0.01).The weight coefficients played a crucial role,with the plastic film residue quantities ranking as follows:Class Ⅰ<Class Ⅱ<Class Ⅲ<Class Ⅳ.The corresponding average residue amounts were 63,100,110 kg·hm-2,and 135 kg·hm-2,respectively.The clustering analysis results were consistent with objective reality and were influenced by the factors affecting plastic film residue.Based on the clustering results of plastic film residue levels,we divided them into three intensity levels:low pollution,moderate pollution,and high pollution,exhibiting distinct distribution differences among the levels.The study indicated that the overall pollution intensity in the Xinjiang region followed a"higher in central areas,lower in northern and southern areas"distribution pattern.It is important to pay attention to locations and regions with high pollution levels and implement targeted management measures to accelerate the plastic film residue pollution control process,thereby safeguarding the sustainable development of agriculture.
国家科技期刊平台
NSTL
万方数据
维普
