You have bigger problems than heteroskedasticity here
Based on the straight diagonal line forming the lower bound of the residuals on the lower-left side of the plot, it appears that you are using a linear regression to deal with a non-negative response variable (possibly a count variable?). If this is the case then it would be usual to either use a count regression model or at least use a logarithmic transformation on your response variable in the model. This would usually give you a more appropriate model for this kind of data and would typically deal with the heteroskedasticity at issue.
Before worrying about heteroskedasticity, I recommend that you reconsider whether you are using the correct model. If your response is a count variable then I would recommend starting with a negative-binomial count regression. If your response is not a count variable, but is some other non-negative variable, I would recommend that you consider a log-linear regression (with an adjustment for response values of zero). You can also consider variations on these models, but that is where I would start.