Uncovering the characteristics of air pollutants emission in industrial parks and analyzing emission reduction potential: case studies in Henan, China

Abstract

Industrial parks contribute greatly to China’s economic development while emitting huge air pollutants. It is necessary to study the characteristics of air pollutant emissions in industrial parks. In this study, emission inventories for 11 industrial parks were established. Meanwhile, the source emission and spatial distribution characteristics of the industrial park were analyzed. The cluster analysis was used to classify these parks into “4Hs”, “Mixed” and “4Ls” parks. “4Hs”, “Mixed” and “4Ls” represent that the levels of energy intensity, economic proportion of energy-intensive industries, coal proportion and pollution performance value are high, medium and low in turn. Then three emission reduction measures were set up to estimate the emission reduction potential and environmental impacts. The results show that: (1) the emissions of SO2, NOx, CO, PM10, PM2.5, VOCs and NH3 of 11 industrial parks in 2017 were 11.2, 23.1, 30.8, 8.3, 3.5, 5.1, and 1.1 kt, respectively. (2) Power plants were the largest source of SO2 and NOx emissions, and industrial processes were the largest emission source of CO, PM10, PM2.5, VOCs and NH3. (3) “4Hs” parks with traditional energy-intensive industries as the leading industries should be the emphasis of air pollutant emission reduction. (4) Through the optimal emission reduction measures, SO2, NOx, PM10, PM2.5 and VOCs were reduced by 81, 46, 51, 46 and 77%, respectively. Environmental impact reductions include 1.6 kt SO2eq acidified gas emissions, 1.4 kt PO43−eq eutrophication substances, 4.2 kt PM10eq atmospheric particulate emissions, 7.0 kt 1,4-DCEeq human toxic substances, and 5.2 kt PM2.5 eq breathing Inorganic. This study is helpful to understand the characteristics of air pollutants emissions in industrial parks and promotes the proposal and implementation of air pollutant emissions reduction strategies.

Integration of Data and Predictive Models for the Evaluation of Air Quality and Noise in Urban Environments

“…In the context of urban planning, the findings of this study have significant implications [ 26 ]. Identifying critical areas affected by urban sources, such as industrial zones and traffic routes, provides essential information for making informed decisions [ 51 ].…”

“…Unlike previous studies that might have focused on specific aspects of environmental monitoring, this proposal aims to provide a holistic and systematic approach [ 24 ]. This includes not only the collection of environmental data but also its detailed analysis to inform urban management policies and strategies better [ 25 , 26 ].…”