Application of WASP model and Gini coefficient in total mass control of water pollutants: a case study in Xicheng Canal, China

Abstract

A B S T R A C TThe main objective of this study was to apply the water quality analysis simulation programme to develop total mass control of pollutant (TMCP) programmes by calculating the water assimilative capacities for chemical oxygen demand (COD) and ammonia nitrogen (NH 3 -N) of a river that connects the Taihu Lake and the Yangtze River. Based on the distribution of water assimilative capacities, the geographical distribution of the pollutant permitted discharge load was validated by calculating the Gini coefficients for the economic, social and environmental efficiencies. According to the validation results, pollutant permitted discharge load was reallocated between townships and the rates of the reductions in pollutants for each township in the watershed were calculated. The water assimilative capacities of COD and NH 3 -N of Xicheng Canal watershed were calculated as 4803 ton/yr and 186 ton/yr, respectively. The results for the reallocation of pollutant permitted discharge load between townships indicated that the reduction in COD was small, with only 11.2% reduction for Qingyang Town and 33.6% for Chengjiang Town. In contrast, the NH 3 -N reductions of Yuecheng Town, Nanzha Town, Qingyang Town and Chengjiang Town were 52.9, 40.0, 61.4 and 54.5%, respectively, while the total reduction for Xicheng Canal watershed reached 53.5%. Based on the case, a new TMCP framework for allocating the pollutant permitted discharge loads in rivers was established, which not only combined the total mass of pollutant with the water quality but also took account for equity and efficiency in the allocation of pollutant permitted discharge loads.

Nutrients and pesticides in Chinese waters : Future pollution and solutions

“…Existing studies used mainly the Gini optimization approach for local analysis. Gini was used to allocate pollution permits on pollutants for provincial or central government (Wang et al 2016;Yuan et al 2017). This was done for different pollutants.…”

“…This was done for different pollutants. For example, the Gini approach was applied to allocate rights for the carbon and SO2 emissions from industries, discharge permits for chemical oxygen demand (COD) and Ammonia Nitrogen (NH3-N) in wastewater among cities (Li et al 2016;Shen et al 2018;Sun et al 2010;Wang et al 2016;Zhou et al 2015). These studies allocated the pollution permit at an administrative scale (e.g., cities).…”

“…Our study selected GDP, population, agricultural land area and sub-basin areas as four indexes to represent the socio-economic development of GDP, population, basin area, and agricultural area are often selected as the indexes to reflect the socio-economic development in similar studies (Wang et al 2016;Yuan et al 2017). Wang et al (2016) selected population, GDP and river length to reflect the social, economic and environmental efficiency. In Yuan et al (2017), GDP, population and environmental receiving capacity of pollutants are selected as indexes to reflect socio-economic and environmental aspects of the region.…”

“…Other studies allocated nutrient pollution permits using, so called, the grandfathering approach (Wang et al 2016). Equality in pollution reduction has been considered in P a g e | 67 economic studies (Biancotti 2006;Lambert 1985;Rahman et al 2009), but hardly for large Chinese rivers.…”

“…The Gini coefficient is a widely used measure of social inequality in a region (see Section 4.2). Gini optimization was done for some individual, small watersheds or cities (Sun et al 2010;Wang et al 2016;Yuan et al 2017). For example, Yuan et al (2017) applied Gini optimization to equally allocate discharge permits of waste water among cities in Jiangsu province in China.…”