INDUSTRIAL POLLUTION AND ENVIRONMENT
Author : Srushti Mahajan
Roll no. 0225026
Review of Literature :
1 . The impact of intermediate product imports on industrial pollution emissions
This study investigates how intermediate product imports affect industrial pollution, and lightly polluting industries experience different degrees of emission reduction. emissions in China, using panel data from 30 industries between 2003 and 2015. Employing GMM regression and mediation effect tests, the authors find that imports of intermediate goods significantly reduce emissions of wastewater, waste gas, and solid waste. The impact, however, is heterogeneous: heavily, moderately The mechanisms identified include the import competition effect (forcing domestic firms to improve efficiency and reduce waste), the variety effect (exposure to a wider range of imported inputs that enhance innovation and production quality), and the technology spillover effect (transfer of advanced processes and knowledge embedded in imported goods). Each of these channels plays a partial mediating role in reducing pollution. The study concludes that intermediate product imports not only improve productivity and competitiveness but also contribute to green development by lowering industrial emissions. This provides empirical evidence that trade liberalization, particularly in intermediate goods, can be an effective pathway for pollution reduction in developing countries like China.
Citation : Wan, L., Mao, Y., Fu, Y., & Wan, X. (2023)
2 . Industrial pollution in Jilin Restricted development zone A spatial Economic analysis
This article evaluates industrial pollution in Jilin’s Restricted Development Zone (JRDZ) between 2006 and 2015, focusing on its spatial-temporal evolution and influencing factors. Using the entropy weight method, the authors construct a comprehensive industrial pollution index that integrates six pollutants: wastewater, COD, waste gas, SO₂, NOₓ, and solid waste. The results show that pollution levels first declined and then rose again, reflecting uneven progress in control efforts. Spatial analysis reveals significant geographical disparities, with counties showing polarized pollution characteristics and clustering patterns. The Moran index confirms strong spatial autocorrelation, meaning pollution levels in one county are closely related to those in neighboring counties. The spatial econometric analysis identifies key drivers: economic development, technological progress, and industrialization are negatively correlated with pollution, suggesting that modernization and innovation help reduce emissions. Conversely, population density and industrial production capacity are positively correlated, indicating that concentrated populations and high-output industries intensify pollution.
Citation : Guo, Y., Tong, L., & Mei, L. (2021).
3. The Effect of goverance on industrial waterwaste pollution
This article analyzes the relationship between governance and industrial wastewater pollution in China using panel data from 30 provinces between 2005 and 2020. The authors employ fixed-effect and system generalized moment estimation (SYS-GMM) models to assess whether investment in wastewater governance reduces pollution. Interestingly, the findings reveal a positive correlation: higher per capita investment in industrial wastewater governance is associated with increased emissions of both inorganic pollutants (e.g., mercury, cadmium, lead, arsenic) and organic pollutants (e.g., volatile phenol, chloride, petroleum, ammonia nitrogen). This suggests that while investment is rising, it may not be effectively structured or targeted, leading to inefficiencies and even worsening pollution levels. The study also identifies an inverted U-shaped relationship between per capita GDP and pollutant emissions, indicating that pollution initially rises with economic growth but declines after reaching a certain development threshold. Moreover, when considering the proportion of wastewater governance investment relative to total environmental governance investment, the results show a negative correlation with pollutant emissions, implying that a balanced investment structure can improve outcomes. The authors conclude that China must not only increase investment in wastewater treatment but also optimize the allocation of funds and technologies to achieve meaningful reductions in industrial wastewater pollution.
Citation: Li, L., Shi, Y., Huang, Y., Xing, A., & Xue, H. (2022).
4. Influencing factors of industrial pollution control Efficency
This article investigates the spatial-temporal evolution and influencing factors of industrial pollution control efficiency in China between 2012 and 2018. Using DEA window analysis with panel data from 30 provinces, the study measures how human, financial, and material inputs in pollution control relate to outputs such as wastewater, sulfur dioxide emissions, and solid waste utilization. The findings reveal that overall industrial pollution control efficiency declined during the study period, though regional differences were significant. Eastern and central provinces generally aligned with the national average, while western and northeastern regions showed fluctuating efficiency levels. The study highlights that provinces such as Shandong, Jiangsu, and Hebei maintained relatively high efficiency, while others like Shanxi, Liaoning, and Henan experienced sharp declines. The results underscore that regional disparities stem from differences in industrial structure, resource allocation, and governance intensity.
Citation: Zou, W., Zhang, L., Xu, J., Xie, Y., & Chen, H. (2022).
5. Exploring the effect of producer services and manufacturing industrial coagglomeration on the ecological environment pollution control in China.
This article examines how producer services and manufacturing industrial co-agglomeration affect ecological environment pollution control in China, using a spatial Durbin model and testing the mediating role of technological innovation. The study distinguishes between government-dominated and market-driven co-agglomeration modes. At the national level, government-led co-agglomeration significantly improves local pollution control, while market-driven co-agglomeration not only enhances local outcomes but also generates positive spatial spillover effects in surrounding regions. The analysis also identifies an inverted “U-shaped” relationship between economic development and ecological pollution, meaning that pollution initially worsens with growth but improves after reaching a certain development threshold. Environmental regulation is found to support pollution control, whereas industrial structure and foreign direct investment tend to exacerbate pollution. Regionally, the eastern provinces benefit most, with both government and market-driven co-agglomeration promoting pollution control locally and regionally, though the spillover effect of market-driven co-agglomeration is stronger. In contrast, central and western regions only experience local improvements, without significant spillover
Citation: Yang, H., Zhang, F., & He, Y. (2021).
6. The impact of Air pollution on morbidity in the industrial Areas of the east kazzakhstan region
This systematic review explores the impact of air pollution and smog on human health in Pakistan, focusing on major urban centers such as Lahore, Karachi, Faisalabad, Islamabad, and Rawalpindi. The study identifies key pollution drivers including industrial activities, vehicular emissions, brick kilns, crop burning, and rapid urbanization. Using the PRISMA methodology, 45 peer-reviewed studies were analyzed to assess pollutant sources (PM2.5, PM10, CO, SO₂, NO₂, O₃, VOCs) and their health consequences.The findings reveal that Karachi and Lahore experience the highest pollution levels, with Lahore particularly affected by winter smog events. PM2.5 concentrations in Lahore often exceed WHO guidelines by more than 60 times, leading to severe respiratory and cardiovascular risks. Brick kilns, especially traditional ones using rubber as fuel, contribute significantly to particulate matter emissions, causing lung impairment among workers.
Citation: Iram, S., Qaisar, I., Shabbir, R., Pomee, M. S., Schmidt, M., & Hertig, E. (2025).
7. Ecology of Industrial pollution in china
This article provides a comprehensive overview of the ecology of industrial pollution in China, tracing its evolution over the past four decades and examining its impacts on aquatic and soil ecosystems, as well as the development of monitoring and risk management systems. Since China’s reform and opening up in 1978, rapid industrialization has driven economic growth but also led to severe pollution, particularly in eastern coastal regions. Industrial solid waste, wastewater, and gas emissions grew exponentially until around 2011, with provinces such as Hebei, Jiangsu, and Liaoning among the largest contributors. The study highlights that pollution has caused widespread degradation of aquatic and soil ecosystems, with effects observable at species, population, community, and ecosystem levels. Aquatic ecosystems have been heavily impacted by pollutants such as heavy metals, persistent organic pollutants (POPs), and excess nutrients (TN, TP), leading to eutrophication, biodiversity loss, and disruption of food webs.
Citation: Yuan, J., Lu, Y., Wang, C., Cao, X., Chen, C., Cui, H., Zhang, M., Wang, C., Li, X., Johnson, A. C., Sweetman, A. J., & Du, D. (2020).
8. Impact of Foreign Direct Investment and Industrial structure transformation on Haze pollution across china
This article investigates how foreign direct investment (FDI) and industrial structure transformation influence haze pollution across China, using provincial data from 2000 to 2017. Employing exploratory spatial data analysis (ESDA) and spatial econometric models, the study reveals that haze pollution exhibits strong spatial agglomeration, shifting from central and western regions toward the eastern coastal provinces. The findings show that a 1% increase in FDI reduces haze pollution locally by 0.066% and in neighboring provinces by 0.3538%, highlighting significant spatial spillover effects. However, the impact of FDI is heterogeneous across different stages of economic development: in the early stages, FDI tends to aggravate pollution by flowing into resource-intensive industries, while in transitional stages, it curbs pollution through ecological innovation spillovers.
Citation : Li, C., Lin, T., Xu, Z., & Chen, Y. (2021)
9. Pollution Mechanism and driving factors of groundwater quality in typical industrial areas
This article examines the mechanisms and driving factors behind groundwater pollution in industrial areas of China, focusing on Zibo City, Shandong Province. Groundwater samples were collected from two aquifer types—pore phreatic water and karst confined water—during both dry and flood seasons in 2022. The study used hydrochemical analyses, including Piper trilinear diagrams, Gibbs diagrams, ion ratio diagrams, and principal component analysis (PCA), to identify pollution sources and controlling factors. Results showed that pore phreatic water had higher concentrations and exceedance rates of ions such as Na⁺, Cl⁻, and NO₃⁻ compared to karst confined water, indicating stronger human influence. Seasonal variations were evident: in the flood season, pore phreatic water was affected by evaporite dissolution, industrial activities, and domestic sewage, while in the dry season, halite and carbonate weathering dissolution combined with sewage were dominant. Karst confined water, on the other hand, was consistently controlled by water-rock interactions and industrial activities across both seasons.
Citation : Wang, L., Wang, Q., & Zheng, D. (2025)
10. Growth with pollution research on economic growth patterns of industrial enterprise based on industry attributes
The study explores the dual economic growth patterns of Chinese industrial enterprises “sustainable growth” versus “growth with pollution” by analyzing micro-level data from 24,386 listed firms between 2011 and 2018. It highlights the role of pollution fees as both a regulatory mechanism and a determinant of enterprise growth. Firms not levied pollution fees generally show higher sales growth, particularly in high-pollution industries such as mining, smelting, and chemical production, suggesting that cleaner production technologies are rewarded by the market. Conversely, firms that pay pollution fees often achieve higher sales growth as well, indicating that some enterprises rely on paying fees to legally discharge pollutants rather than adopting environmentally friendly practices. The regression analysis confirms that pollution fees negatively affect sales growth when considered as a binary variable (whether fees are levied), but positively affect growth when measured by the proportion of fees relative to operating income.
Citation: Yue, Q., & Chen, J. (2020).
11. Conclusion
The ten studies collectively conclude that industrial pollution remains a major challenge alongside economic growth. While industrialization has boosted development, it has also caused serious air, water, and soil pollution, leading to environmental degradation and health risks. The research shows that economic growth can both increase and reduce pollution depending on regulatory strength, technological innovation, industrial structure, and governance efficiency. Spatial Spillover effects and regional differences highlight the need for coordinated policies. Overall, sustainable development requires stricter environmental regulations, cleaner technologies, industrial upgrading, and well-structured governance to balance economic progress with ecological protection.
Refernces
Wan, Lu, Mao, Yuling, Fu, Yizhong, & Wan, Xiya. (2023). The impact of intermediate product imports on industrial pollution emissions: Evidence from 30 industries in China. PLOS ONE, 18(10), e0292347. Public Library of Science. https://doi.org/10.1371/journal.pone.0292347 (doi.org in Bing)
Guo, Yanhua, Tong, Lianjun, & Mei, Lin. (2021). Evaluation and influencing factors of industrial pollution in Jilin restricted development zone: A spatial econometric analysis. Sustainability, 13(8), 4194. MDPI. https://doi.org/10.3390/su13084194
Li, Lili, Shi, Yaobo, Huang, Yun, Xing, Anlu, & Xue, Hao. (2022). The effect of governance on industrial wastewater pollution in China. International Journal of Environmental Research and Public Health, 19(15), 9316. MDPI. https://doi.org/10.3390/ijerph19159316
Zou, Wenjie, Zhang, Liqin, Xu, Jieying, Xie, Yufeng, & Chen, Huangxin. (2022). Spatial-temporal evolution characteristics and influencing factors of industrial pollution control efficiency in China. Sustainability, 14(9), 5152. MDPI. https://doi.org/10.3390/su14095152
Yang, Haochang, Zhang, Faming, & He, Yixin. (2021). Exploring the effect of producer services and manufacturing industrial co-agglomeration on the ecological environment pollution control in China. Environment, Development & Sustainability, 23(11), 16119–16144. Springer Nature. https://doi.org/10.1007/s10668-021-01339-7 (doi.org in Bing)
Iram, Shazia, Qaisar, Iqra, Shabbir, Rabia, Pomee, Muhammad Saleem, Schmidt, Matthias, & Hertig, Elke. (2025). Impact of air pollution and smog on human health in Pakistan: A systematic review. Environments, 12(2), 46. MDPI. https://doi.org/10.3390/environments12020046
Yuan, Jingjing, Lu, Yonglong, Wang, Chenchen, Cao, Xianghui, Chen, Chunci, Cui, Haotian, Zhang, Meng, Wang, Cong, Li, Xiaoqian, Johnson, Andrew C., Sweetman, Andrew J., & Du, Di. (2020). Ecology of industrial pollution in China. Ecosystem Health and Sustainability, 6(1), 1779010. Taylor & Francis. https://doi.org/10.1080/20964129.2020.1779010
Li, Chenggang, Lin, Tao, Xu, Zhenci, & Chen, Yuzhu. (2021). Impacts of foreign direct investment and industrial structure transformation on haze pollution across China. Sustainability, 13(10), 5439. MDPI. https://doi.org/10.3390/su13105439
Wang, Li, Wang, Qi, & Zheng, Dechao. (2025). Study on the pollution mechanism and driving factors of groundwater quality in typical industrial areas of China. Water, 17(10), 1420. MDPI. https://doi.org/10.3390/w17101420Y
ue, Qin, & Chen, Jiameng. (2020). “Sustainable growth” or “growth with pollution”: Research on economic growth patterns of industrial enterprise based on industry attributes. IOP Conference Series: Earth and Environmental Science, 571(1), 012089. IOP Publishing. https://doi.org/10.1088/1755-1315/571/1/012089